diff --git a/code/estimark/agents.py b/code/estimark/agents.py index 4bb19d2..e874bd8 100644 --- a/code/estimark/agents.py +++ b/code/estimark/agents.py @@ -16,6 +16,7 @@ from HARK.ConsumptionSaving.ConsPortfolioModel import PortfolioConsumerType from HARK.ConsumptionSaving.ConsWealthPortfolioModel import WealthPortfolioConsumerType from HARK.core import AgentType +import numpy as np # ===================================================== # Define objects and functions used for the estimation @@ -26,7 +27,7 @@ class TempConsumerType(AgentType): def check_restrictions(self): return None - def simBirth(self, which_agents): + def sim_birth(self, which_agents): """Alternate method for simulating initial states for simulated agents, drawing from a finite distribution. Used to overwrite IndShockConsumerType.simBirth, which uses lognormal distributions. @@ -49,6 +50,9 @@ def simBirth(self, which_agents): self.t_age[which_agents] = 0 # Which period of the cycle each agents is currently in self.t_cycle[which_agents] = 0 + + def sim_death(self): + return np.zeros(self.AgentCount, dtype=bool) ### Overwrite sim_one_period to not have death or look up of agent ages diff --git a/code/estimark/content/tables/min/PortfolioDiscFac_estimate_results.csv b/code/estimark/content/tables/min/PortfolioDiscFac_estimate_results.csv new file mode 100644 index 0000000..8c6bf4f --- /dev/null +++ b/code/estimark/content/tables/min/PortfolioDiscFac_estimate_results.csv @@ -0,0 +1,15400 @@ +CRRA,6.614528749695077 +DiscFac,1.0357967813213964 +time_to_estimate,207.89406180381775 +params,"{'CRRA': 6.614528749695077, 'DiscFac': 1.0357967813213964}" +criterion,0.5414098309112865 +start_criterion,0.6339659358362199 +start_params,"{'CRRA': 9.252106996349742, 'DiscFac': 1.0}" +algorithm,multistart_tranquilo_ls +direction,minimize +n_free,2 +message,Absolute criterion change smaller than tolerance. +success, +n_criterion_evaluations, +n_derivative_evaluations, +n_iterations, +history,"{'params': [{'CRRA': 9.474902352534894, 'DiscFac': 0.9999364724331312}, {'CRRA': 8.635210994449684, 'DiscFac': 0.5395034896195957}, {'CRRA': 10.314593710620104, 'DiscFac': 0.839446855669377}, {'CRRA': 8.635210994449684, 'DiscFac': 0.8283678716666038}, {'CRRA': 10.314593710620104, 'DiscFac': 1.0999999747595868}, {'CRRA': 10.314593710620104, 'DiscFac': 0.5389047702194539}, {'CRRA': 10.099775031645393, 'DiscFac': 0.5}, {'CRRA': 8.635210994449684, 'DiscFac': 1.0754042612834813}, {'CRRA': 10.314593710620104, 'DiscFac': 0.8992682338268907}, {'CRRA': 10.02804372855336, 'DiscFac': 1.1}, {'CRRA': 8.635210994449684, 'DiscFac': 1.0126290881448918}, {'CRRA': 9.383098701781327, 'DiscFac': 0.5}, {'CRRA': 9.565093432029592, 'DiscFac': 1.1}, {'CRRA': 8.784457936968376, 'DiscFac': 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58.93786389986053, 60.09956929972395, 61.246673699934036, 62.39065769966692, 63.537203199695796, 64.6880405000411, 65.84563069976866, 67.12054200004786, 68.2633369998075, 69.40824959985912, 70.57097999984398, 71.71744199981913, 72.86136729968712, 74.00794119993225, 75.30863319989294, 76.46647779969499, 77.64264229964465, 78.78975840006024, 79.93701329967007, 81.08435950009152, 82.23052149964496, 83.39726469991729, 84.69916970003396, 85.85893659992144], 'batches': [0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71]}" +convergence_report,"{'one_step': {'relative_criterion_change': 1.525257377346415e-05, 'relative_params_change': 0.004758913549058271, 'absolute_criterion_change': 8.257893387653148e-06, 'absolute_params_change': 0.031397306790084616}, 'five_steps': {'relative_criterion_change': 1.525257377346415e-05, 'relative_params_change': 0.004758913549058271, 'absolute_criterion_change': 8.257893387653148e-06, 'absolute_params_change': 0.031397306790084616}}" +multistart_info,"{'start_parameters': [{'CRRA': 9.252106996349742, 'DiscFac': 1.0}, {'CRRA': 9.474902352534894, 'DiscFac': 0.9999364724331312}], 'local_optima': [Minimize with 2 free parameters terminated. + +The tranquilo_ls algorithm reported: Absolute criterion change smaller than tolerance. + +Independent of the convergence criteria used by tranquilo_ls, the strength of convergence can be assessed by the following criteria: + + one_step five_steps +relative_criterion_change 1.183e-07* 3.672e-05 +relative_params_change 8.471e-07* 0.001055 +absolute_criterion_change 6.406e-08* 1.988e-05 +absolute_params_change 1e-06* 0.006933 + +(***: change <= 1e-10, **: change <= 1e-8, *: change <= 1e-5. Change refers to a change between accepted steps. The first column only considers the last step. The second column considers the last five steps.), Minimize with 2 free parameters terminated. + +The tranquilo_ls algorithm reported: Absolute criterion change smaller than tolerance. + +Independent of the convergence criteria used by tranquilo_ls, the strength of convergence can be assessed by the following criteria: + + one_step five_steps +relative_criterion_change 6.004e-07* 0.03035 +relative_params_change 4.702e-06* 0.1395 +absolute_criterion_change 3.251e-07* 0.01643 +absolute_params_change 2.892e-05 0.9212 + +(***: change <= 1e-10, **: change <= 1e-8, *: change <= 1e-5. Change refers to a change between accepted steps. The first column only considers the last step. The second column considers the last five steps.)], 'exploration_sample': [{'CRRA': 9.252106996349742, 'DiscFac': 1.0}, {'CRRA': 16.45625, 'DiscFac': 0.9125000000000001}, {'CRRA': 14.093749999999998, 'DiscFac': 0.9875}, {'CRRA': 17.046875, 'DiscFac': 0.6312500000000001}, {'CRRA': 7.596874999999999, 'DiscFac': 0.9312500000000001}, {'CRRA': 18.81875, 'DiscFac': 0.5375}, {'CRRA': 15.274999999999999, 'DiscFac': 0.65}, {'CRRA': 11.73125, 'DiscFac': 0.7625000000000001}, {'CRRA': 10.549999999999999, 'DiscFac': 0.8}, {'CRRA': 9.368749999999999, 'DiscFac': 0.8375}, {'CRRA': 5.824999999999999, 'DiscFac': 0.9500000000000001}, {'CRRA': 12.9125, 'DiscFac': 0.575}, {'CRRA': 17.6375, 'DiscFac': 1.0250000000000001}, {'CRRA': 8.1875, 'DiscFac': 0.7250000000000001}, {'CRRA': 12.321874999999999, 'DiscFac': 1.08125}, {'CRRA': 7.00625, 'DiscFac': 0.6125}, {'CRRA': 4.64375, 'DiscFac': 0.6875}, {'CRRA': 3.4625, 'DiscFac': 0.875}, {'CRRA': 2.871875, 'DiscFac': 0.78125}, {'CRRA': 2.28125, 'DiscFac': 1.0625}], 'exploration_results': array([0.64235819, 0.99955613, 1.1121001 , 1.75705837, 1.77123339, + 1.82132756, 1.94396028, 2.07018913, 2.11467658, 2.15218408, + 2.24402179, 2.54668134, 2.78807842, 2.90740886, 3.01539999, + 3.32546076, 3.5830362 , 4.07905962, 4.08578359, 6.94508729])}" +algorithm_output,"{'states': [State(trustregion=Region(center=array([9.47490235, 0.99993647]), radius=0.9474902352534894, bounds=Bounds(lower=array([1.1, 0.5]), upper=array([20. , 1.1]))), model_indices=[0], model=ScalarModel(intercept=0.6448272261874601, linear_terms=array([0., 0.]), square_terms=array([[0., 0.], + [0., 0.]]), scale=0.9474902352534894, shift=array([9.47490235, 0.99993647])), vector_model=VectorModel(intercepts=array([ 0.0503911 , 0.12838033, 0.15541499, 0.20185793, 0.22718579, + 0.24311703, 0.24583074, 0.08262932, -0.06406015, -0.05102962, + -0.39325651, -0.40243304, -0.13275181, -0.10596104, -0.09671903, + -0.10022582, -0.10660703]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + 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n_evals_per_point=None, n_evals_acceptance=None), State(trustregion=Region(center=array([9.47490235, 0.99993647]), radius=0.9474902352534894, bounds=Bounds(lower=array([1.1, 0.5]), upper=array([20. , 1.1]))), model_indices=array([ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12]), model=ScalarModel(intercept=0.7324177488592093, linear_terms=array([-0.1604269 , -1.70678719]), square_terms=array([[0.05311507, 0.46725062], + [0.46725062, 4.78691623]]), scale=array([0.83969136, 0.3 ]), shift=array([9.47490235, 0.8 ])), vector_model=VectorModel(intercepts=array([ 0.0503911 , 0.12838033, 0.15541499, 0.20185793, 0.22718579, + 0.24311703, 0.24583074, 0.08262932, -0.06406015, -0.05102962, + -0.39325651, -0.40243304, -0.13275181, -0.10596104, -0.09671903, + -0.10022582, -0.10660703]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 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State(trustregion=Region(center=array([9.47490235, 0.99993647]), radius=0.4737451176267447, bounds=Bounds(lower=array([1.1, 0.5]), upper=array([20. , 1.1]))), model_indices=array([ 0, 4, 6, 7, 9, 10, 11, 12, 13]), model=ScalarModel(intercept=0.4596011524812236, linear_terms=array([-0.15193583, -0.53365863]), square_terms=array([[0.20583856, 0.85488875], + [0.85488875, 3.85975947]]), scale=array([0.41984568, 0.2599546 ]), shift=array([9.47490235, 0.8400454 ])), vector_model=VectorModel(intercepts=array([ 0.0503911 , 0.12838033, 0.15541499, 0.20185793, 0.22718579, + 0.24311703, 0.24583074, 0.08262932, -0.06406015, -0.05102962, + -0.39325651, -0.40243304, -0.13275181, -0.10596104, -0.09671903, + -0.10022582, -0.10660703]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + 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radius=0.23687255881337235, bounds=Bounds(lower=array([1.1, 0.5]), upper=array([20. , 1.1]))), model_indices=array([ 0, 6, 7, 9, 10, 11, 12, 13, 14]), model=ScalarModel(intercept=0.47748362589833987, linear_terms=array([0.03029103, 0.35911003]), square_terms=array([[0.02625602, 0.18108694], + [0.18108694, 1.39847469]]), scale=array([0.20992284, 0.15499318]), shift=array([9.47490235, 0.94500682])), vector_model=VectorModel(intercepts=array([ 0.0503911 , 0.12838033, 0.15541499, 0.20185793, 0.22718579, + 0.24311703, 0.24583074, 0.08262932, -0.06406015, -0.05102962, + -0.39325651, -0.40243304, -0.13275181, -0.10596104, -0.09671903, + -0.10022582, -0.10660703]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=0.9474902352534894, shift=array([9.47490235, 0.99993647])), candidate_index=15, candidate_x=array([9.68482519, 0.8851367 ]), index=0, x=array([9.47490235, 0.99993647]), fval=0.6448272261874602, rho=-3.7543621103084996, accepted=False, new_indices=array([], dtype=int32), old_indices_used=array([ 0, 6, 7, 9, 10, 11, 12, 13, 14]), old_indices_discarded=array([1, 2, 3, 4, 5, 8]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([9.47490235, 0.99993647]), radius=0.11843627940668618, bounds=Bounds(lower=array([1.1, 0.5]), upper=array([20. , 1.1]))), model_indices=array([ 0, 9, 11, 12, 14, 15]), model=ScalarModel(intercept=0.781511080377176, linear_terms=array([-0.06570334, 0.6958516 ]), square_terms=array([[ 0.00455801, -0.05593978], + [-0.05593978, 0.75231219]]), scale=array([0.10496142, 0.10251247]), shift=array([9.47490235, 0.99748753])), vector_model=VectorModel(intercepts=array([ 0.0503911 , 0.12838033, 0.15541499, 0.20185793, 0.22718579, + 0.24311703, 0.24583074, 0.08262932, -0.06406015, -0.05102962, + -0.39325651, -0.40243304, -0.13275181, -0.10596104, -0.09671903, + -0.10022582, -0.10660703]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + 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model=ScalarModel(intercept=0.6108530298545867, linear_terms=array([-0.10139668, -0.14696738]), square_terms=array([[0.07792252, 0.32866092], + [0.32866092, 1.49842941]]), scale=0.05921813970334309, shift=array([9.47490235, 0.99993647])), vector_model=VectorModel(intercepts=array([ 0.0503911 , 0.12838033, 0.15541499, 0.20185793, 0.22718579, + 0.24311703, 0.24583074, 0.08262932, -0.06406015, -0.05102962, + -0.39325651, -0.40243304, -0.13275181, -0.10596104, -0.09671903, + -0.10022582, -0.10660703]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + 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square_terms=array([[0.03333137, 0.10554599], + [0.10554599, 0.37011472]]), scale=0.029609069851671544, shift=array([9.47490235, 0.99993647])), vector_model=VectorModel(intercepts=array([ 0.0503911 , 0.12838033, 0.15541499, 0.20185793, 0.22718579, + 0.24311703, 0.24583074, 0.08262932, -0.06406015, -0.05102962, + -0.39325651, -0.40243304, -0.13275181, -0.10596104, -0.09671903, + -0.10022582, -0.10660703]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], 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scale=0.014804534925835772, shift=array([9.50661188, 1.0031676 ])), vector_model=VectorModel(intercepts=array([ 0.0503911 , 0.12838033, 0.15541499, 0.20185793, 0.22718579, + 0.24311703, 0.24583074, 0.08262932, -0.06406015, -0.05102962, + -0.39325651, -0.40243304, -0.13275181, -0.10596104, -0.09671903, + -0.10022582, -0.10660703]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=0.9474902352534894, shift=array([9.47490235, 0.99993647])), candidate_index=19, candidate_x=array([9.49185035, 1.0059291 ]), index=19, x=array([9.49185035, 1.0059291 ]), fval=0.6370780738825652, rho=1.4693827516516844, accepted=True, new_indices=array([], dtype=int32), old_indices_used=array([ 0, 17, 18]), old_indices_discarded=array([], dtype=int32), step_length=0.015017609941676606, relative_step_length=1.0143925504521585, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([9.49185035, 1.0059291 ]), radius=0.029609069851671544, bounds=Bounds(lower=array([1.1, 0.5]), upper=array([20. , 1.1]))), model_indices=array([ 0, 12, 16, 17, 18, 19]), model=ScalarModel(intercept=0.6412257536348447, linear_terms=array([-0.06905576, -0.03758833]), square_terms=array([[0.03588925, 0.1094543 ], + [0.1094543 , 0.37040144]]), scale=0.029609069851671544, shift=array([9.49185035, 1.0059291 ])), vector_model=VectorModel(intercepts=array([ 0.0503911 , 0.12838033, 0.15541499, 0.20185793, 0.22718579, + 0.24311703, 0.24583074, 0.08262932, -0.06406015, -0.05102962, + -0.39325651, -0.40243304, -0.13275181, -0.10596104, -0.09671903, + -0.10022582, -0.10660703]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=0.9474902352534894, shift=array([9.47490235, 0.99993647])), candidate_index=20, candidate_x=array([9.52125862, 1.00094573]), index=19, x=array([9.49185035, 1.0059291 ]), fval=0.6370780738825652, rho=-0.11096998055275568, accepted=False, new_indices=array([], dtype=int32), old_indices_used=array([ 0, 12, 16, 17, 18, 19]), old_indices_discarded=array([], dtype=int32), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([9.49185035, 1.0059291 ]), radius=0.014804534925835772, bounds=Bounds(lower=array([1.1, 0.5]), upper=array([20. , 1.1]))), model_indices=array([ 0, 17, 18, 19, 20]), model=ScalarModel(intercept=0.6375966987395302, linear_terms=array([ 0.00059101, -0.00033053]), square_terms=array([[2.18308578e-05, 1.28615347e-03], + [1.28615347e-03, 8.40653356e-02]]), scale=0.014804534925835772, shift=array([9.49185035, 1.0059291 ])), vector_model=VectorModel(intercepts=array([ 0.0503911 , 0.12838033, 0.15541499, 0.20185793, 0.22718579, + 0.24311703, 0.24583074, 0.08262932, -0.06406015, -0.05102962, + -0.39325651, -0.40243304, -0.13275181, -0.10596104, -0.09671903, + -0.10022582, -0.10660703]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=0.9474902352534894, shift=array([9.47490235, 0.99993647])), candidate_index=21, candidate_x=array([9.47704841, 1.00621177]), index=21, x=array([9.47704841, 1.00621177]), fval=0.6363070785814076, rho=1.2946325204884988, accepted=True, new_indices=array([], dtype=int32), old_indices_used=array([ 0, 17, 18, 19, 20]), old_indices_discarded=array([], dtype=int32), step_length=0.01480464158988585, relative_step_length=1.0000072048227528, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([9.47704841, 1.00621177]), radius=0.029609069851671544, bounds=Bounds(lower=array([1.1, 0.5]), upper=array([20. , 1.1]))), model_indices=array([ 0, 12, 16, 17, 18, 19, 20, 21]), model=ScalarModel(intercept=0.6740948994884155, linear_terms=array([-0.0775299 , -0.08137508]), square_terms=array([[0.03091198, 0.10157856], + [0.10157856, 0.37039842]]), scale=0.029609069851671544, shift=array([9.47704841, 1.00621177])), vector_model=VectorModel(intercepts=array([ 0.0503911 , 0.12838033, 0.15541499, 0.20185793, 0.22718579, + 0.24311703, 0.24583074, 0.08262932, -0.06406015, -0.05102962, + -0.39325651, -0.40243304, -0.13275181, -0.10596104, -0.09671903, + -0.10022582, -0.10660703]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=0.9474902352534894, shift=array([9.47490235, 0.99993647])), candidate_index=22, candidate_x=array([9.50732214, 1.00462907]), index=21, x=array([9.47704841, 1.00621177]), fval=0.6363070785814076, rho=-0.029474268266789803, accepted=False, new_indices=array([], dtype=int32), old_indices_used=array([ 0, 12, 16, 17, 18, 19, 20, 21]), old_indices_discarded=array([], dtype=int32), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([9.47704841, 1.00621177]), radius=0.014804534925835772, bounds=Bounds(lower=array([1.1, 0.5]), upper=array([20. , 1.1]))), model_indices=array([ 0, 17, 18, 19, 20, 21, 22]), model=ScalarModel(intercept=0.6367076097989959, linear_terms=array([ 6.38911855e-04, -5.64861763e-05]), square_terms=array([[1.99591697e-05, 1.23030124e-03], + [1.23030124e-03, 8.44345370e-02]]), scale=0.014804534925835772, shift=array([9.47704841, 1.00621177])), vector_model=VectorModel(intercepts=array([ 0.0503911 , 0.12838033, 0.15541499, 0.20185793, 0.22718579, + 0.24311703, 0.24583074, 0.08262932, -0.06406015, -0.05102962, + -0.39325651, -0.40243304, -0.13275181, -0.10596104, -0.09671903, + -0.10022582, -0.10660703]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=0.9474902352534894, shift=array([9.47490235, 0.99993647])), candidate_index=23, candidate_x=array([9.46224557, 1.00643568]), index=23, x=array([9.46224557, 1.00643568]), fval=0.6355934835508369, rho=1.1173242341721383, accepted=True, new_indices=array([], dtype=int32), old_indices_used=array([ 0, 17, 18, 19, 20, 21, 22]), old_indices_discarded=array([], dtype=int32), step_length=0.014804537200668226, relative_step_length=1.0000001536578127, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([9.46224557, 1.00643568]), radius=0.029609069851671544, bounds=Bounds(lower=array([1.1, 0.5]), upper=array([20. , 1.1]))), model_indices=array([ 0, 12, 17, 18, 19, 20, 21, 22, 23]), model=ScalarModel(intercept=0.6376967017750665, linear_terms=array([-0.00887642, -0.07715602]), square_terms=array([[0.00091426, 0.02162778], + [0.02162778, 0.54194842]]), scale=0.029609069851671544, shift=array([9.46224557, 1.00643568])), vector_model=VectorModel(intercepts=array([ 0.0503911 , 0.12838033, 0.15541499, 0.20185793, 0.22718579, + 0.24311703, 0.24583074, 0.08262932, -0.06406015, -0.05102962, + -0.39325651, -0.40243304, -0.13275181, -0.10596104, -0.09671903, + -0.10022582, -0.10660703]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=0.9474902352534894, shift=array([9.47490235, 0.99993647])), candidate_index=24, candidate_x=array([9.49199772, 1.00943198]), index=23, x=array([9.46224557, 1.00643568]), fval=0.6355934835508369, rho=-0.23439049876600507, accepted=False, new_indices=array([], dtype=int32), old_indices_used=array([ 0, 12, 17, 18, 19, 20, 21, 22, 23]), old_indices_discarded=array([], dtype=int32), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([9.46224557, 1.00643568]), radius=0.014804534925835772, bounds=Bounds(lower=array([1.1, 0.5]), upper=array([20. , 1.1]))), model_indices=array([ 0, 17, 18, 19, 20, 21, 22, 23, 24]), model=ScalarModel(intercept=0.6357439312845821, linear_terms=array([ 0.00057539, -0.00082847]), square_terms=array([[2.06319310e-05, 1.26644672e-03], + [1.26644672e-03, 8.60694145e-02]]), scale=0.014804534925835772, shift=array([9.46224557, 1.00643568])), vector_model=VectorModel(intercepts=array([ 0.0503911 , 0.12838033, 0.15541499, 0.20185793, 0.22718579, + 0.24311703, 0.24583074, 0.08262932, -0.06406015, -0.05102962, + -0.39325651, -0.40243304, -0.13275181, -0.10596104, -0.09671903, + -0.10022582, -0.10660703]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=0.9474902352534894, shift=array([9.47490235, 0.99993647])), candidate_index=25, candidate_x=array([9.44744469, 1.00679353]), index=25, x=array([9.44744469, 1.00679353]), fval=0.6347642471305107, rho=1.4044689675006616, accepted=True, new_indices=array([], dtype=int32), old_indices_used=array([ 0, 17, 18, 19, 20, 21, 22, 23, 24]), old_indices_discarded=array([], dtype=int32), step_length=0.014805197302692493, relative_step_length=1.000044741483609, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([9.44744469, 1.00679353]), radius=0.029609069851671544, bounds=Bounds(lower=array([1.1, 0.5]), upper=array([20. , 1.1]))), model_indices=array([ 0, 18, 19, 20, 21, 22, 23, 24, 25]), model=ScalarModel(intercept=0.6347153364849043, linear_terms=array([ 0.00136442, -0.00288838]), square_terms=array([[7.21853077e-05, 4.81168593e-03], + [4.81168593e-03, 3.57552054e-01]]), scale=0.029609069851671544, shift=array([9.44744469, 1.00679353])), vector_model=VectorModel(intercepts=array([ 0.0503911 , 0.12838033, 0.15541499, 0.20185793, 0.22718579, + 0.24311703, 0.24583074, 0.08262932, -0.06406015, -0.05102962, + -0.39325651, -0.40243304, -0.13275181, -0.10596104, -0.09671903, + -0.10022582, -0.10660703]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], 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old_indices_discarded=array([17]), step_length=0.02961001570090617, relative_step_length=1.0000319445777717, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([9.41784149, 1.00742862]), radius=0.05921813970334309, bounds=Bounds(lower=array([1.1, 0.5]), upper=array([20. , 1.1]))), model_indices=array([ 0, 18, 19, 21, 22, 23, 24, 25, 26]), model=ScalarModel(intercept=0.6332385782456339, linear_terms=array([0.0028514 , 0.00022792]), square_terms=array([[2.79552380e-04, 1.89198753e-02], + [1.89198753e-02, 1.43266898e+00]]), scale=0.05921813970334309, shift=array([9.41784149, 1.00742862])), vector_model=VectorModel(intercepts=array([ 0.0503911 , 0.12838033, 0.15541499, 0.20185793, 0.22718579, + 0.24311703, 0.24583074, 0.08262932, -0.06406015, -0.05102962, + -0.39325651, -0.40243304, -0.13275181, -0.10596104, -0.09671903, + -0.10022582, -0.10660703]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=0.9474902352534894, shift=array([9.47490235, 0.99993647])), candidate_index=27, candidate_x=array([9.35862837, 1.00819965]), index=27, x=array([9.35862837, 1.00819965]), fval=0.6303511715372276, rho=1.0071263421242136, accepted=True, new_indices=array([], dtype=int32), old_indices_used=array([ 0, 18, 19, 21, 22, 23, 24, 25, 26]), old_indices_discarded=array([12, 15, 16, 17, 20]), step_length=0.0592181407159667, relative_step_length=1.0000000170998888, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([9.35862837, 1.00819965]), radius=0.11843627940668618, bounds=Bounds(lower=array([1.1, 0.5]), upper=array([20. , 1.1]))), model_indices=array([ 0, 18, 19, 21, 23, 24, 25, 26, 27]), model=ScalarModel(intercept=0.639178807035496, linear_terms=array([ 0.00132575, -0.26376211]), square_terms=array([[8.65219778e-04, 5.51863712e-02], + [5.51863712e-02, 3.95321986e+00]]), scale=array([0.10496142, 0.09838088]), shift=array([9.35862837, 1.00161912])), vector_model=VectorModel(intercepts=array([ 0.0503911 , 0.12838033, 0.15541499, 0.20185793, 0.22718579, + 0.24311703, 0.24583074, 0.08262932, -0.06406015, -0.05102962, + -0.39325651, -0.40243304, -0.13275181, -0.10596104, -0.09671903, + -0.10022582, -0.10660703]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=0.9474902352534894, shift=array([9.47490235, 0.99993647])), candidate_index=28, candidate_x=array([9.25366695, 1.00955655]), index=28, x=array([9.25366695, 1.00955655]), fval=0.6252147257628975, rho=1.035476052619481, accepted=True, new_indices=array([], dtype=int32), old_indices_used=array([ 0, 18, 19, 21, 23, 24, 25, 26, 27]), old_indices_discarded=array([11, 12, 13, 14, 15, 16, 17, 20, 22]), step_length=0.10497019014652463, relative_step_length=0.8863009769673553, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([9.25366695, 1.00955655]), radius=0.23687255881337235, bounds=Bounds(lower=array([1.1, 0.5]), upper=array([20. , 1.1]))), model_indices=array([ 0, 19, 21, 23, 24, 25, 26, 27, 28]), model=ScalarModel(intercept=1.3525263472005808, linear_terms=array([-0.05604803, -3.65995549]), square_terms=array([[3.37929225e-03, 1.66025609e-01], + [1.66025609e-01, 9.20973251e+00]]), scale=array([0.20992284, 0.15018314]), shift=array([9.25366695, 0.94981686])), vector_model=VectorModel(intercepts=array([ 0.0503911 , 0.12838033, 0.15541499, 0.20185793, 0.22718579, + 0.24311703, 0.24583074, 0.08262932, -0.06406015, -0.05102962, + -0.39325651, -0.40243304, -0.13275181, -0.10596104, -0.09671903, + -0.10022582, -0.10660703]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + 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14, 15, 16, 17, + 18, 20, 22]), step_length=0.20993957271621416, relative_step_length=0.8862975676368734, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([9.04374411, 1.01220715]), radius=0.4737451176267447, bounds=Bounds(lower=array([1.1, 0.5]), upper=array([20. , 1.1]))), model_indices=array([ 3, 7, 10, 13, 22, 25, 27, 28, 29]), model=ScalarModel(intercept=2.887557528467335, linear_terms=array([ 0.32145309, -7.82327945]), square_terms=array([[ 0.01909841, -0.39706853], + [-0.39706853, 13.16541827]]), scale=array([0.41984568, 0.25381927]), shift=array([9.04374411, 0.84618073])), vector_model=VectorModel(intercepts=array([ 0.0503911 , 0.12838033, 0.15541499, 0.20185793, 0.22718579, + 0.24311703, 0.24583074, 0.08262932, -0.06406015, -0.05102962, + -0.39325651, -0.40243304, -0.13275181, -0.10596104, -0.09671903, + -0.10022582, -0.10660703]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=0.9474902352534894, shift=array([9.47490235, 0.99993647])), candidate_index=30, candidate_x=array([8.62389843, 0.98935244]), index=29, x=array([9.04374411, 1.01220715]), fval=0.6151402665456015, rho=-1.1829304881995348, accepted=False, new_indices=array([], dtype=int32), old_indices_used=array([ 3, 7, 10, 13, 22, 25, 27, 28, 29]), old_indices_discarded=array([ 0, 1, 2, 4, 5, 6, 8, 9, 11, 12, 14, 15, 16, 17, 18, 19, 20, + 21, 23, 24, 26]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([9.04374411, 1.01220715]), radius=0.23687255881337235, bounds=Bounds(lower=array([1.1, 0.5]), upper=array([20. , 1.1]))), model_indices=array([ 7, 10, 13, 23, 25, 26, 27, 28, 29]), model=ScalarModel(intercept=1.1785163391833393, linear_terms=array([ 0.04245163, -3.2666068 ]), square_terms=array([[ 1.11423119e-03, -2.87009785e-02], + [-2.87009785e-02, 8.89866124e+00]]), scale=array([0.20992284, 0.14885785]), shift=array([9.04374411, 0.95114215])), vector_model=VectorModel(intercepts=array([ 0.0503911 , 0.12838033, 0.15541499, 0.20185793, 0.22718579, + 0.24311703, 0.24583074, 0.08262932, -0.06406015, -0.05102962, + -0.39325651, -0.40243304, -0.13275181, -0.10596104, -0.09671903, + -0.10022582, -0.10660703]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=0.9474902352534894, shift=array([9.47490235, 0.99993647])), candidate_index=31, candidate_x=array([8.83382127, 1.00530622]), index=29, x=array([9.04374411, 1.01220715]), fval=0.6151402665456015, rho=-0.21904622845287416, accepted=False, new_indices=array([], dtype=int32), old_indices_used=array([ 7, 10, 13, 23, 25, 26, 27, 28, 29]), old_indices_discarded=array([ 0, 1, 3, 6, 9, 11, 12, 14, 15, 16, 17, 18, 19, 20, 21, 22, 24, + 30]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([9.04374411, 1.01220715]), radius=0.11843627940668618, bounds=Bounds(lower=array([1.1, 0.5]), upper=array([20. , 1.1]))), model_indices=array([ 7, 10, 13, 25, 26, 27, 28, 29, 31]), model=ScalarModel(intercept=0.588971346798013, linear_terms=array([ 0.01505103, -0.13000888]), square_terms=array([[ 2.31746838e-04, -3.20175653e-03], + [-3.20175653e-03, 3.75543886e+00]]), scale=array([0.10496142, 0.09637714]), shift=array([9.04374411, 1.00362286])), vector_model=VectorModel(intercepts=array([ 0.0503911 , 0.12838033, 0.15541499, 0.20185793, 0.22718579, + 0.24311703, 0.24583074, 0.08262932, -0.06406015, -0.05102962, + -0.39325651, -0.40243304, -0.13275181, -0.10596104, -0.09671903, + -0.10022582, -0.10660703]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + 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17, 18, 19, 20, 21, 22, 23, 24, 30]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([9.04374411, 1.01220715]), radius=0.05921813970334309, bounds=Bounds(lower=array([1.1, 0.5]), upper=array([20. , 1.1]))), model_indices=array([13, 28, 29, 31, 32]), model=ScalarModel(intercept=0.6214336044267341, linear_terms=array([0.00147887, 0.10259686]), square_terms=array([[4.10977860e-04, 1.78962346e-02], + [1.78962346e-02, 8.79816604e-01]]), scale=0.05921813970334309, shift=array([9.04374411, 1.01220715])), vector_model=VectorModel(intercepts=array([ 0.0503911 , 0.12838033, 0.15541499, 0.20185793, 0.22718579, + 0.24311703, 0.24583074, 0.08262932, -0.06406015, -0.05102962, + -0.39325651, -0.40243304, -0.13275181, -0.10596104, -0.09671903, + -0.10022582, -0.10660703]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + 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n_evals_acceptance=1), State(trustregion=Region(center=array([9.04374411, 1.01220715]), radius=0.029609069851671544, bounds=Bounds(lower=array([1.1, 0.5]), upper=array([20. , 1.1]))), model_indices=array([29, 32, 33]), model=ScalarModel(intercept=0.6151402665456009, linear_terms=array([0.00149709, 0.00482735]), square_terms=array([[7.65543339e-05, 5.14393571e-03], + [5.14393571e-03, 3.91745261e-01]]), scale=0.029609069851671544, shift=array([9.04374411, 1.01220715])), vector_model=VectorModel(intercepts=array([ 0.0503911 , 0.12838033, 0.15541499, 0.20185793, 0.22718579, + 0.24311703, 0.24583074, 0.08262932, -0.06406015, -0.05102962, + -0.39325651, -0.40243304, -0.13275181, -0.10596104, -0.09671903, + -0.10022582, -0.10660703]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=0.9474902352534894, shift=array([9.47490235, 0.99993647])), candidate_index=34, candidate_x=array([9.0141328 , 1.01223102]), index=34, x=array([9.0141328 , 1.01223102]), fval=0.6138905842835336, rho=0.8565054081815938, accepted=True, new_indices=array([], dtype=int32), old_indices_used=array([29, 32, 33]), old_indices_discarded=array([], dtype=int32), step_length=0.02961131833730782, relative_step_length=1.0000759390837854, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([9.0141328 , 1.01223102]), radius=0.05921813970334309, bounds=Bounds(lower=array([1.1, 0.5]), upper=array([20. , 1.1]))), model_indices=array([13, 28, 29, 31, 32, 33, 34]), model=ScalarModel(intercept=0.620881773286023, linear_terms=array([0.00197631, 0.09173778]), square_terms=array([[3.44046695e-04, 1.64408522e-02], + [1.64408522e-02, 8.92929811e-01]]), scale=0.05921813970334309, shift=array([9.0141328 , 1.01223102])), vector_model=VectorModel(intercepts=array([ 0.0503911 , 0.12838033, 0.15541499, 0.20185793, 0.22718579, + 0.24311703, 0.24583074, 0.08262932, -0.06406015, -0.05102962, + -0.39325651, -0.40243304, -0.13275181, -0.10596104, -0.09671903, + -0.10022582, -0.10660703]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=0.9474902352534894, shift=array([9.47490235, 0.99993647])), candidate_index=35, candidate_x=array([8.95483028, 1.00724033]), index=34, x=array([9.0141328 , 1.01223102]), fval=0.6138905842835336, rho=-0.906107936879546, accepted=False, new_indices=array([], dtype=int32), old_indices_used=array([13, 28, 29, 31, 32, 33, 34]), old_indices_discarded=array([], dtype=int32), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([9.0141328 , 1.01223102]), radius=0.029609069851671544, bounds=Bounds(lower=array([1.1, 0.5]), upper=array([20. , 1.1]))), model_indices=array([29, 32, 33, 34, 35]), model=ScalarModel(intercept=0.6137867229839677, linear_terms=array([0.00142032, 0.00043433]), square_terms=array([[7.69832064e-05, 5.16913372e-03], + [5.16913372e-03, 3.92730596e-01]]), scale=0.029609069851671544, shift=array([9.0141328 , 1.01223102])), vector_model=VectorModel(intercepts=array([ 0.0503911 , 0.12838033, 0.15541499, 0.20185793, 0.22718579, + 0.24311703, 0.24583074, 0.08262932, -0.06406015, -0.05102962, + -0.39325651, -0.40243304, -0.13275181, -0.10596104, -0.09671903, + -0.10022582, -0.10660703]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 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model=ScalarModel(intercept=0.619467823965291, linear_terms=array([0.00209097, 0.09020298]), square_terms=array([[3.29303090e-04, 1.61351934e-02], + [1.61351934e-02, 9.00329160e-01]]), scale=0.05921813970334309, shift=array([8.98452585, 1.01258669])), vector_model=VectorModel(intercepts=array([ 0.0503911 , 0.12838033, 0.15541499, 0.20185793, 0.22718579, + 0.24311703, 0.24583074, 0.08262932, -0.06406015, -0.05102962, + -0.39325651, -0.40243304, -0.13275181, -0.10596104, -0.09671903, + -0.10022582, -0.10660703]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + 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linear_terms=array([0.00140759, 0.00037964]), square_terms=array([[7.68743253e-05, 5.17639009e-03], + [5.17639009e-03, 3.94127433e-01]]), scale=0.029609069851671544, shift=array([8.98452585, 1.01258669])), vector_model=VectorModel(intercepts=array([ 0.0503911 , 0.12838033, 0.15541499, 0.20185793, 0.22718579, + 0.24311703, 0.24583074, 0.08262932, -0.06406015, -0.05102962, + -0.39325651, -0.40243304, -0.13275181, -0.10596104, -0.09671903, + -0.10022582, -0.10660703]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 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square_terms=array([[3.04730334e-04, 2.06301143e-02], + [2.06301143e-02, 1.58200616e+00]]), scale=0.05921813970334309, shift=array([8.95491894, 1.01294575])), vector_model=VectorModel(intercepts=array([ 0.0503911 , 0.12838033, 0.15541499, 0.20185793, 0.22718579, + 0.24311703, 0.24583074, 0.08262932, -0.06406015, -0.05102962, + -0.39325651, -0.40243304, -0.13275181, -0.10596104, -0.09671903, + -0.10022582, -0.10660703]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], 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+ [6.38199381e-02, 2.30738160e+00]]), scale=array([0.10496142, 0.09565189]), shift=array([8.89570505, 1.00434811])), vector_model=VectorModel(intercepts=array([ 0.0503911 , 0.12838033, 0.15541499, 0.20185793, 0.22718579, + 0.24311703, 0.24583074, 0.08262932, -0.06406015, -0.05102962, + -0.39325651, -0.40243304, -0.13275181, -0.10596104, -0.09671903, + -0.10022582, -0.10660703]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], 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1.60156668e+00]]), scale=0.05921813970334309, shift=array([8.89570505, 1.01365764])), vector_model=VectorModel(intercepts=array([ 0.0503911 , 0.12838033, 0.15541499, 0.20185793, 0.22718579, + 0.24311703, 0.24583074, 0.08262932, -0.06406015, -0.05102962, + -0.39325651, -0.40243304, -0.13275181, -0.10596104, -0.09671903, + -0.10022582, -0.10660703]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + 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scale=array([0.10496142, 0.09531582]), shift=array([8.83649067, 1.00468418])), vector_model=VectorModel(intercepts=array([ 0.0503911 , 0.12838033, 0.15541499, 0.20185793, 0.22718579, + 0.24311703, 0.24583074, 0.08262932, -0.06406015, -0.05102962, + -0.39325651, -0.40243304, -0.13275181, -0.10596104, -0.09671903, + -0.10022582, -0.10660703]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=0.9474902352534894, shift=array([9.47490235, 0.99993647])), candidate_index=42, candidate_x=array([8.73152925, 1.01043262]), index=41, x=array([8.83649067, 1.01432978]), fval=0.6057905110013826, rho=-0.2539961161624663, accepted=False, new_indices=array([], dtype=int32), old_indices_used=array([13, 31, 32, 35, 36, 37, 38, 39, 41]), old_indices_discarded=array([ 1, 3, 7, 10, 26, 27, 28, 29, 30, 33, 34, 40]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([8.83649067, 1.01432978]), radius=0.05921813970334309, bounds=Bounds(lower=array([1.1, 0.5]), upper=array([20. , 1.1]))), model_indices=array([13, 31, 32, 35, 37, 38, 39, 41, 42]), model=ScalarModel(intercept=0.6128960194558581, linear_terms=array([0.00323829, 0.08375858]), square_terms=array([[2.19797272e-04, 1.29854569e-02], + [1.29854569e-02, 9.21144727e-01]]), scale=0.05921813970334309, shift=array([8.83649067, 1.01432978])), vector_model=VectorModel(intercepts=array([ 0.0503911 , 0.12838033, 0.15541499, 0.20185793, 0.22718579, + 0.24311703, 0.24583074, 0.08262932, -0.06406015, -0.05102962, + -0.39325651, -0.40243304, -0.13275181, -0.10596104, -0.09671903, + -0.10022582, -0.10660703]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=0.9474902352534894, shift=array([9.47490235, 0.99993647])), candidate_index=43, candidate_x=array([8.77720289, 1.00979089]), index=41, x=array([8.83649067, 1.01432978]), fval=0.6057905110013826, rho=-0.636748464236313, accepted=False, new_indices=array([], dtype=int32), old_indices_used=array([13, 31, 32, 35, 37, 38, 39, 41, 42]), old_indices_discarded=array([ 3, 7, 10, 29, 30, 33, 34, 36, 40]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([8.83649067, 1.01432978]), radius=0.029609069851671544, bounds=Bounds(lower=array([1.1, 0.5]), upper=array([20. , 1.1]))), model_indices=array([13, 31, 32, 37, 38, 39, 41, 42, 43]), model=ScalarModel(intercept=0.6129958444671166, linear_terms=array([0.00125322, 0.0420077 ]), square_terms=array([[7.02244693e-05, 3.72273429e-03], + [3.72273429e-03, 2.29436197e-01]]), scale=0.029609069851671544, shift=array([8.83649067, 1.01432978])), vector_model=VectorModel(intercepts=array([ 0.0503911 , 0.12838033, 0.15541499, 0.20185793, 0.22718579, + 0.24311703, 0.24583074, 0.08262932, -0.06406015, -0.05102962, + -0.39325651, -0.40243304, -0.13275181, -0.10596104, -0.09671903, + -0.10022582, -0.10660703]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=0.9474902352534894, shift=array([9.47490235, 0.99993647])), candidate_index=44, candidate_x=array([8.80679818, 1.00940247]), index=41, x=array([8.83649067, 1.01432978]), fval=0.6057905110013826, rho=-1.1780504359812205, accepted=False, new_indices=array([], dtype=int32), old_indices_used=array([13, 31, 32, 37, 38, 39, 41, 42, 43]), old_indices_discarded=array([35]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([8.83649067, 1.01432978]), radius=0.014804534925835772, bounds=Bounds(lower=array([1.1, 0.5]), upper=array([20. , 1.1]))), model_indices=array([31, 39, 41, 43, 44]), model=ScalarModel(intercept=0.6059146038962105, linear_terms=array([0.00063063, 0.00133693]), square_terms=array([[1.93356047e-05, 1.31514692e-03], + [1.31514692e-03, 1.01583452e-01]]), scale=0.014804534925835772, shift=array([8.83649067, 1.01432978])), vector_model=VectorModel(intercepts=array([ 0.0503911 , 0.12838033, 0.15541499, 0.20185793, 0.22718579, + 0.24311703, 0.24583074, 0.08262932, -0.06406015, -0.05102962, + -0.39325651, -0.40243304, -0.13275181, -0.10596104, -0.09671903, + -0.10022582, -0.10660703]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=0.9474902352534894, shift=array([9.47490235, 0.99993647])), candidate_index=45, candidate_x=array([8.82168485, 1.01432664]), index=45, x=array([8.82168485, 1.01432664]), fval=0.6051564916805549, rho=1.020928649746183, accepted=True, new_indices=array([], dtype=int32), old_indices_used=array([31, 39, 41, 43, 44]), old_indices_discarded=array([], dtype=int32), step_length=0.014805816548052337, relative_step_length=1.0000865695695937, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([8.82168485, 1.01432664]), radius=0.029609069851671544, bounds=Bounds(lower=array([1.1, 0.5]), upper=array([20. , 1.1]))), model_indices=array([13, 31, 37, 39, 41, 42, 43, 44, 45]), model=ScalarModel(intercept=0.6115555266177718, linear_terms=array([0.00124126, 0.04101205]), square_terms=array([[7.04241015e-05, 3.73186729e-03], + [3.73186729e-03, 2.30210452e-01]]), scale=0.029609069851671544, shift=array([8.82168485, 1.01432664])), vector_model=VectorModel(intercepts=array([ 0.0503911 , 0.12838033, 0.15541499, 0.20185793, 0.22718579, + 0.24311703, 0.24583074, 0.08262932, -0.06406015, -0.05102962, + -0.39325651, -0.40243304, -0.13275181, -0.10596104, -0.09671903, + -0.10022582, -0.10660703]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=0.9474902352534894, shift=array([9.47490235, 0.99993647])), candidate_index=46, candidate_x=array([8.79199479, 1.00954484]), index=45, x=array([8.82168485, 1.01432664]), fval=0.6051564916805549, rho=-1.230884779808124, accepted=False, new_indices=array([], dtype=int32), old_indices_used=array([13, 31, 37, 39, 41, 42, 43, 44, 45]), old_indices_discarded=array([32, 35, 38]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([8.82168485, 1.01432664]), radius=0.014804534925835772, bounds=Bounds(lower=array([1.1, 0.5]), upper=array([20. , 1.1]))), model_indices=array([31, 41, 43, 44, 45, 46]), model=ScalarModel(intercept=0.6052045803357664, linear_terms=array([5.75893275e-04, 2.08251016e-05]), square_terms=array([[2.14888603e-05, 1.39552818e-03], + [1.39552818e-03, 1.02157333e-01]]), scale=0.014804534925835772, shift=array([8.82168485, 1.01432664])), vector_model=VectorModel(intercepts=array([ 0.0503911 , 0.12838033, 0.15541499, 0.20185793, 0.22718579, + 0.24311703, 0.24583074, 0.08262932, -0.06406015, -0.05102962, + -0.39325651, -0.40243304, -0.13275181, -0.10596104, -0.09671903, + -0.10022582, -0.10660703]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=0.9474902352534894, shift=array([9.47490235, 0.99993647])), candidate_index=47, candidate_x=array([8.80688164, 1.01452473]), index=47, x=array([8.80688164, 1.01452473]), fval=0.6045010959198394, rho=1.1411150863578703, accepted=True, new_indices=array([], dtype=int32), old_indices_used=array([31, 41, 43, 44, 45, 46]), old_indices_discarded=array([], dtype=int32), step_length=0.014804535502910653, relative_step_length=1.0000000389796022, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([8.80688164, 1.01452473]), radius=0.029609069851671544, bounds=Bounds(lower=array([1.1, 0.5]), upper=array([20. , 1.1]))), model_indices=array([13, 31, 41, 42, 43, 44, 45, 46, 47]), model=ScalarModel(intercept=0.6105358682194937, linear_terms=array([0.00053509, 0.04163391]), square_terms=array([[1.09771507e-04, 4.72352439e-03], + [4.72352439e-03, 2.30297392e-01]]), scale=0.029609069851671544, shift=array([8.80688164, 1.01452473])), vector_model=VectorModel(intercepts=array([ 0.0503911 , 0.12838033, 0.15541499, 0.20185793, 0.22718579, + 0.24311703, 0.24583074, 0.08262932, -0.06406015, -0.05102962, + -0.39325651, -0.40243304, -0.13275181, -0.10596104, -0.09671903, + -0.10022582, -0.10660703]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=0.9474902352534894, shift=array([9.47490235, 0.99993647])), candidate_index=48, candidate_x=array([8.8363726 , 1.00857494]), index=47, x=array([8.80688164, 1.01452473]), fval=0.6045010959198394, rho=-2.17105462493869, accepted=False, new_indices=array([], dtype=int32), old_indices_used=array([13, 31, 41, 42, 43, 44, 45, 46, 47]), old_indices_discarded=array([32, 37, 39]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([8.80688164, 1.01452473]), radius=0.014804534925835772, bounds=Bounds(lower=array([1.1, 0.5]), upper=array([20. , 1.1]))), model_indices=array([31, 41, 43, 44, 45, 46, 47, 48]), model=ScalarModel(intercept=0.6045817009488239, linear_terms=array([ 0.00060537, -0.00012916]), square_terms=array([[2.04142540e-05, 1.36233150e-03], + [1.36233150e-03, 1.02744088e-01]]), scale=0.014804534925835772, shift=array([8.80688164, 1.01452473])), vector_model=VectorModel(intercepts=array([ 0.0503911 , 0.12838033, 0.15541499, 0.20185793, 0.22718579, + 0.24311703, 0.24583074, 0.08262932, -0.06406015, -0.05102962, + -0.39325651, -0.40243304, -0.13275181, -0.10596104, -0.09671903, + -0.10022582, -0.10660703]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=0.9474902352534894, shift=array([9.47490235, 0.99993647])), candidate_index=49, candidate_x=array([8.79207864, 1.01473837]), index=49, x=array([8.79207864, 1.01473837]), fval=0.6038388333603965, rho=1.0929767802825647, accepted=True, new_indices=array([], dtype=int32), old_indices_used=array([31, 41, 43, 44, 45, 46, 47, 48]), old_indices_discarded=array([], dtype=int32), step_length=0.01480454508906136, relative_step_length=1.0000006864940802, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([8.79207864, 1.01473837]), radius=0.029609069851671544, bounds=Bounds(lower=array([1.1, 0.5]), upper=array([20. , 1.1]))), model_indices=array([31, 41, 43, 44, 45, 46, 47, 48, 49]), model=ScalarModel(intercept=0.6039320017441308, linear_terms=array([1.22941931e-03, 2.77206681e-05]), square_terms=array([[7.95912011e-05, 5.38269834e-03], + [5.38269834e-03, 4.12173721e-01]]), scale=0.029609069851671544, shift=array([8.79207864, 1.01473837])), vector_model=VectorModel(intercepts=array([ 0.0503911 , 0.12838033, 0.15541499, 0.20185793, 0.22718579, + 0.24311703, 0.24583074, 0.08262932, -0.06406015, -0.05102962, + -0.39325651, -0.40243304, -0.13275181, -0.10596104, -0.09671903, + -0.10022582, -0.10660703]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=0.9474902352534894, shift=array([9.47490235, 0.99993647])), candidate_index=50, candidate_x=array([8.76247205, 1.01512188]), index=50, x=array([8.76247205, 1.01512188]), fval=0.6024855719631016, rho=1.1053283609927005, accepted=True, new_indices=array([], dtype=int32), old_indices_used=array([31, 41, 43, 44, 45, 46, 47, 48, 49]), old_indices_discarded=array([13, 32, 37, 39, 42]), step_length=0.02960907001757359, relative_step_length=1.000000005603082, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([8.76247205, 1.01512188]), radius=0.05921813970334309, bounds=Bounds(lower=array([1.1, 0.5]), upper=array([20. , 1.1]))), model_indices=array([31, 42, 43, 44, 45, 46, 47, 49, 50]), model=ScalarModel(intercept=0.6026578745853444, linear_terms=array([0.0024301, 0.0002779]), square_terms=array([[3.16909370e-04, 2.15042159e-02], + [2.15042159e-02, 1.65484964e+00]]), scale=0.05921813970334309, shift=array([8.76247205, 1.01512188])), vector_model=VectorModel(intercepts=array([ 0.0503911 , 0.12838033, 0.15541499, 0.20185793, 0.22718579, + 0.24311703, 0.24583074, 0.08262932, -0.06406015, -0.05102962, + -0.39325651, -0.40243304, -0.13275181, -0.10596104, -0.09671903, + -0.10022582, -0.10660703]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=0.9474902352534894, shift=array([9.47490235, 0.99993647])), candidate_index=51, candidate_x=array([8.70325877, 1.0158803 ]), index=51, x=array([8.70325877, 1.0158803 ]), fval=0.5997907962729061, rho=1.1192868878296924, accepted=True, new_indices=array([], dtype=int32), old_indices_used=array([31, 42, 43, 44, 45, 46, 47, 49, 50]), old_indices_discarded=array([ 3, 7, 10, 13, 29, 30, 32, 34, 35, 36, 37, 38, 39, 40, 41, 48]), step_length=0.05921814073463714, relative_step_length=1.0000000174151713, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([8.70325877, 1.0158803 ]), radius=0.11843627940668618, bounds=Bounds(lower=array([1.1, 0.5]), upper=array([20. , 1.1]))), model_indices=array([ 7, 10, 13, 30, 42, 44, 45, 50, 51]), model=ScalarModel(intercept=0.5745601532643059, linear_terms=array([ 0.01933147, -0.20828263]), square_terms=array([[ 3.96552248e-04, -7.70697193e-03], + [-7.70697193e-03, 3.60952666e+00]]), scale=array([0.10496142, 0.09454056]), shift=array([8.70325877, 1.00545944])), vector_model=VectorModel(intercepts=array([ 0.0503911 , 0.12838033, 0.15541499, 0.20185793, 0.22718579, + 0.24311703, 0.24583074, 0.08262932, -0.06406015, -0.05102962, + -0.39325651, -0.40243304, -0.13275181, -0.10596104, -0.09671903, + -0.10022582, -0.10660703]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 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old_indices_discarded=array([ 1, 3, 28, 29, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 43, 46, + 47, 48, 49]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([8.70325877, 1.0158803 ]), radius=0.05921813970334309, bounds=Bounds(lower=array([1.1, 0.5]), upper=array([20. , 1.1]))), model_indices=array([ 7, 10, 30, 42, 43, 46, 49, 50, 51]), model=ScalarModel(intercept=0.5848648139367352, linear_terms=array([ 0.01259792, -0.01987223]), square_terms=array([[ 2.31944576e-04, -1.32546665e-02], + [-1.32546665e-02, 2.24249333e+00]]), scale=0.05921813970334309, shift=array([8.70325877, 1.0158803 ])), vector_model=VectorModel(intercepts=array([ 0.0503911 , 0.12838033, 0.15541499, 0.20185793, 0.22718579, + 0.24311703, 0.24583074, 0.08262932, -0.06406015, -0.05102962, + -0.39325651, -0.40243304, -0.13275181, -0.10596104, -0.09671903, + -0.10022582, -0.10660703]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + 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old_indices_discarded=array([ 3, 13, 31, 32, 35, 36, 37, 38, 39, 41, 44, 45, 47, 48, 52]), step_length=0.05922045545199665, relative_step_length=1.0000391053934683, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([8.64403857, 1.01605409]), radius=0.11843627940668618, bounds=Bounds(lower=array([1.1, 0.5]), upper=array([20. , 1.1]))), model_indices=array([ 7, 10, 30, 42, 43, 50, 51, 52, 53]), model=ScalarModel(intercept=0.6233574060676437, linear_terms=array([ 0.01619734, -0.70631774]), square_terms=array([[2.97413525e-04, 7.75950577e-04], + [7.75950577e-04, 5.79975163e+00]]), scale=array([0.10496142, 0.09445367]), shift=array([8.64403857, 1.00554633])), vector_model=VectorModel(intercepts=array([ 0.0503911 , 0.12838033, 0.15541499, 0.20185793, 0.22718579, + 0.24311703, 0.24583074, 0.08262932, -0.06406015, -0.05102962, + -0.39325651, -0.40243304, -0.13275181, -0.10596104, -0.09671903, + -0.10022582, -0.10660703]), linear_terms=array([[0., 0.], + [0., 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43, 50, 51, 52, 53]), old_indices_discarded=array([ 1, 3, 13, 29, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 44, 45, + 46, 47, 48, 49]), step_length=0.10496625831674383, relative_step_length=0.8862677791178409, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([8.53907715, 1.01706193]), radius=0.23687255881337235, bounds=Bounds(lower=array([1.1, 0.5]), upper=array([20. , 1.1]))), model_indices=array([ 3, 7, 30, 42, 50, 51, 52, 53, 54]), model=ScalarModel(intercept=0.7023662250726452, linear_terms=array([ 0.06492856, -1.1147206 ]), square_terms=array([[ 3.47923203e-03, -8.06332216e-02], + [-8.06332216e-02, 3.61802648e+00]]), scale=array([0.20992284, 0.14643046]), shift=array([8.53907715, 0.95356954])), vector_model=VectorModel(intercepts=array([ 0.0503911 , 0.12838033, 0.15541499, 0.20185793, 0.22718579, + 0.24311703, 0.24583074, 0.08262932, -0.06406015, -0.05102962, + -0.39325651, -0.40243304, -0.13275181, -0.10596104, -0.09671903, + -0.10022582, -0.10660703]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=0.9474902352534894, shift=array([9.47490235, 0.99993647])), candidate_index=55, candidate_x=array([8.32915431, 0.99542161]), index=54, x=array([8.53907715, 1.01706193]), fval=0.5930898839617496, rho=-1.7530958161469754, accepted=False, new_indices=array([], dtype=int32), old_indices_used=array([ 3, 7, 30, 42, 50, 51, 52, 53, 54]), old_indices_discarded=array([ 0, 1, 10, 11, 12, 13, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, + 26, 27, 28, 29, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 43, 44, + 45, 46, 47, 48, 49]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([8.53907715, 1.01706193]), radius=0.11843627940668618, bounds=Bounds(lower=array([1.1, 0.5]), upper=array([20. , 1.1]))), model_indices=array([ 7, 10, 30, 42, 51, 52, 53, 54, 55]), model=ScalarModel(intercept=0.615086708073995, linear_terms=array([ 0.00978289, -0.72244786]), square_terms=array([[4.17284358e-04, 3.04748646e-02], + [3.04748646e-02, 5.74255506e+00]]), scale=array([0.10496142, 0.09394975]), shift=array([8.53907715, 1.00605025])), vector_model=VectorModel(intercepts=array([ 0.0503911 , 0.12838033, 0.15541499, 0.20185793, 0.22718579, + 0.24311703, 0.24583074, 0.08262932, -0.06406015, -0.05102962, + -0.39325651, -0.40243304, -0.13275181, -0.10596104, -0.09671903, + -0.10022582, -0.10660703]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=0.9474902352534894, shift=array([9.47490235, 0.99993647])), candidate_index=56, candidate_x=array([8.43411573, 1.01836827]), index=56, x=array([8.43411573, 1.01836827]), fval=0.5885914443329772, rho=0.3283224223143453, accepted=True, new_indices=array([], dtype=int32), old_indices_used=array([ 7, 10, 30, 42, 51, 52, 53, 54, 55]), old_indices_discarded=array([ 1, 3, 13, 29, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 43, 44, + 45, 46, 47, 48, 49, 50]), step_length=0.10496954879325875, relative_step_length=0.8862955617916246, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([8.43411573, 1.01836827]), radius=0.23687255881337235, bounds=Bounds(lower=array([1.1, 0.5]), upper=array([20. , 1.1]))), model_indices=array([ 7, 10, 30, 51, 52, 53, 54, 55, 56]), model=ScalarModel(intercept=1.9169446392811247, linear_terms=array([-0.05516787, -6.07713486]), square_terms=array([[2.74937852e-03, 1.66261876e-01], + [1.66261876e-01, 1.36583309e+01]]), scale=array([0.20992284, 0.14577728]), shift=array([8.43411573, 0.95422272])), vector_model=VectorModel(intercepts=array([ 0.0503911 , 0.12838033, 0.15541499, 0.20185793, 0.22718579, + 0.24311703, 0.24583074, 0.08262932, -0.06406015, -0.05102962, + -0.39325651, -0.40243304, -0.13275181, -0.10596104, -0.09671903, + -0.10022582, -0.10660703]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=0.9474902352534894, shift=array([9.47490235, 0.99993647])), candidate_index=57, candidate_x=array([8.22419289, 1.02085937]), index=57, x=array([8.22419289, 1.02085937]), fval=0.5799642053547169, rho=0.46355807804061855, accepted=True, new_indices=array([], dtype=int32), old_indices_used=array([ 7, 10, 30, 51, 52, 53, 54, 55, 56]), old_indices_discarded=array([ 0, 1, 3, 11, 12, 13, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, + 27, 28, 29, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, + 45, 46, 47, 48, 49, 50]), step_length=0.2099376195491761, relative_step_length=0.8862893219918404, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([8.22419289, 1.02085937]), radius=0.4737451176267447, bounds=Bounds(lower=array([1.1, 0.5]), upper=array([20. , 1.1]))), model_indices=array([ 3, 7, 30, 52, 53, 54, 55, 56, 57]), model=ScalarModel(intercept=3.341466430284669, linear_terms=array([-1.05103033, -7.77084409]), square_terms=array([[ 0.18279549, 1.34509322], + [ 1.34509322, 11.10009818]]), scale=array([0.41984568, 0.24949316]), shift=array([8.22419289, 0.85050684])), vector_model=VectorModel(intercepts=array([ 0.0503911 , 0.12838033, 0.15541499, 0.20185793, 0.22718579, + 0.24311703, 0.24583074, 0.08262932, -0.06406015, -0.05102962, + -0.39325651, -0.40243304, -0.13275181, -0.10596104, -0.09671903, + -0.10022582, -0.10660703]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=0.9474902352534894, shift=array([9.47490235, 0.99993647])), candidate_index=58, candidate_x=array([8.64403857, 0.99493627]), index=57, x=array([8.22419289, 1.02085937]), fval=0.5799642053547169, rho=-1.0936320536105784, accepted=False, new_indices=array([], dtype=int32), old_indices_used=array([ 3, 7, 30, 52, 53, 54, 55, 56, 57]), old_indices_discarded=array([ 0, 1, 2, 4, 5, 6, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, + 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 31, 32, 33, 34, 35, 36, + 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([8.22419289, 1.02085937]), radius=0.23687255881337235, bounds=Bounds(lower=array([1.1, 0.5]), upper=array([20. , 1.1]))), model_indices=array([ 7, 10, 30, 52, 53, 54, 55, 56, 57]), model=ScalarModel(intercept=1.9832433701127465, linear_terms=array([-0.11608732, -6.1156747 ]), square_terms=array([[5.73554046e-03, 2.62479555e-01], + [2.62479555e-01, 1.32048414e+01]]), scale=array([0.20992284, 0.14453174]), shift=array([8.22419289, 0.95546826])), vector_model=VectorModel(intercepts=array([ 0.0503911 , 0.12838033, 0.15541499, 0.20185793, 0.22718579, + 0.24311703, 0.24583074, 0.08262932, -0.06406015, -0.05102962, + -0.39325651, -0.40243304, -0.13275181, -0.10596104, -0.09671903, + -0.10022582, -0.10660703]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=0.9474902352534894, shift=array([9.47490235, 0.99993647])), candidate_index=59, candidate_x=array([8.01427005, 1.02527945]), index=59, x=array([8.01427005, 1.02527945]), fval=0.5734330166298551, rho=1.093147952169101, accepted=True, new_indices=array([], dtype=int32), old_indices_used=array([ 7, 10, 30, 52, 53, 54, 55, 56, 57]), old_indices_discarded=array([ 1, 3, 13, 27, 28, 29, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, + 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 58]), step_length=0.20996936856056853, relative_step_length=0.8864233561389423, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([8.01427005, 1.02527945]), radius=0.4737451176267447, bounds=Bounds(lower=array([1.1, 0.5]), upper=array([20. , 1.1]))), model_indices=array([ 7, 10, 30, 52, 54, 55, 56, 57, 59]), model=ScalarModel(intercept=9.981376675556422, linear_terms=array([ -0.67948996, -26.92467299]), square_terms=array([[2.66781078e-02, 9.72846991e-01], + [9.72846991e-01, 3.85178573e+01]]), scale=array([0.41984568, 0.24728311]), shift=array([8.01427005, 0.85271689])), vector_model=VectorModel(intercepts=array([ 0.0503911 , 0.12838033, 0.15541499, 0.20185793, 0.22718579, + 0.24311703, 0.24583074, 0.08262932, -0.06406015, -0.05102962, + -0.39325651, -0.40243304, -0.13275181, -0.10596104, -0.09671903, + -0.10022582, -0.10660703]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=0.9474902352534894, shift=array([9.47490235, 0.99993647])), candidate_index=60, candidate_x=array([7.90516021, 1.02719534]), index=60, x=array([7.90516021, 1.02719534]), fval=0.570654333265082, rho=28.312992905781908, accepted=True, new_indices=array([], dtype=int32), old_indices_used=array([ 7, 10, 30, 52, 54, 55, 56, 57, 59]), old_indices_discarded=array([ 0, 1, 2, 3, 4, 5, 6, 8, 9, 11, 12, 13, 14, 15, 16, 17, 18, + 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 31, 32, 33, 34, 35, 36, + 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 53, 58]), step_length=0.1091266633945737, relative_step_length=0.23034889296854485, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([7.90516021, 1.02719534]), radius=0.4737451176267447, bounds=Bounds(lower=array([1.1, 0.5]), upper=array([20. , 1.1]))), model_indices=array([10, 30, 52, 54, 55, 56, 57, 59, 60]), model=ScalarModel(intercept=6.968668322923406, linear_terms=array([ -0.3193095 , -18.62779191]), square_terms=array([[1.10008541e-02, 4.89131866e-01], + [4.89131866e-01, 2.70983093e+01]]), scale=array([0.41984568, 0.24632517]), shift=array([7.90516021, 0.85367483])), vector_model=VectorModel(intercepts=array([ 0.0503911 , 0.12838033, 0.15541499, 0.20185793, 0.22718579, + 0.24311703, 0.24583074, 0.08262932, -0.06406015, -0.05102962, + -0.39325651, -0.40243304, -0.13275181, -0.10596104, -0.09671903, + -0.10022582, -0.10660703]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=0.9474902352534894, shift=array([9.47490235, 0.99993647])), candidate_index=61, candidate_x=array([7.53569564, 1.02680097]), index=61, x=array([7.53569564, 1.02680097]), fval=0.557843378100565, rho=0.7126019978012866, accepted=True, new_indices=array([], dtype=int32), old_indices_used=array([10, 30, 52, 54, 55, 56, 57, 59, 60]), old_indices_discarded=array([ 0, 1, 3, 6, 7, 9, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, + 22, 23, 24, 25, 26, 27, 28, 29, 31, 32, 33, 34, 35, 36, 37, 38, 39, + 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 53, 58]), step_length=0.36946477399899075, relative_step_length=0.7798809111740238, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([7.53569564, 1.02680097]), radius=0.9474902352534894, bounds=Bounds(lower=array([1.1, 0.5]), upper=array([20. , 1.1]))), model_indices=array([30, 52, 54, 55, 56, 57, 59, 60, 61]), model=ScalarModel(intercept=12.13842084066151, linear_terms=array([ -0.90389113, -30.58695776]), square_terms=array([[ 0.04679947, 1.22766505], + [ 1.22766505, 40.38597232]]), scale=array([0.83969136, 0.3 ]), shift=array([7.53569564, 0.8 ])), vector_model=VectorModel(intercepts=array([ 0.0503911 , 0.12838033, 0.15541499, 0.20185793, 0.22718579, + 0.24311703, 0.24583074, 0.08262932, -0.06406015, -0.05102962, + -0.39325651, -0.40243304, -0.13275181, -0.10596104, -0.09671903, + -0.10022582, -0.10660703]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=0.9474902352534894, shift=array([9.47490235, 0.99993647])), candidate_index=62, candidate_x=array([6.69600428, 1.03632926]), index=62, x=array([6.69600428, 1.03632926]), fval=0.5424834330682993, rho=0.7246036090517496, accepted=True, new_indices=array([], dtype=int32), old_indices_used=array([30, 52, 54, 55, 56, 57, 59, 60, 61]), old_indices_discarded=array([ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, + 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 31, 32, 33, 34, + 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, + 53, 58]), step_length=0.8397454168164292, relative_step_length=0.88628398011064, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([6.69600428, 1.03632926]), radius=1.8949804705069788, bounds=Bounds(lower=array([1.1, 0.5]), upper=array([20. , 1.1]))), model_indices=array([52, 54, 55, 56, 57, 59, 60, 61, 62]), model=ScalarModel(intercept=13.436478042611053, linear_terms=array([ -1.77594432, -32.96460288]), square_terms=array([[ 0.1709616 , 2.30049165], + [ 2.30049165, 42.12835475]]), scale=array([1.67938272, 0.3 ]), shift=array([6.69600428, 0.8 ])), vector_model=VectorModel(intercepts=array([ 0.0503911 , 0.12838033, 0.15541499, 0.20185793, 0.22718579, + 0.24311703, 0.24583074, 0.08262932, -0.06406015, -0.05102962, + -0.39325651, -0.40243304, -0.13275181, -0.10596104, -0.09671903, + -0.10022582, -0.10660703]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=0.9474902352534894, shift=array([9.47490235, 0.99993647])), candidate_index=63, candidate_x=array([6.58843012, 1.03594893]), index=63, x=array([6.58843012, 1.03594893]), fval=0.5414632317465802, rho=0.501065213354614, accepted=True, new_indices=array([], dtype=int32), old_indices_used=array([52, 54, 55, 56, 57, 59, 60, 61, 62]), old_indices_discarded=array([ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, + 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, + 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, + 51, 53, 58]), step_length=0.10757483992757301, relative_step_length=0.05676831059836341, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([6.58843012, 1.03594893]), radius=1.8949804705069788, bounds=Bounds(lower=array([1.1, 0.5]), upper=array([20. , 1.1]))), model_indices=array([54, 55, 56, 57, 59, 60, 61, 62, 63]), model=ScalarModel(intercept=13.527389310158597, linear_terms=array([ -1.76412438, -33.07272766]), square_terms=array([[ 0.17044821, 2.26794554], + [ 2.26794554, 42.11033571]]), scale=array([1.67938272, 0.3 ]), shift=array([6.58843012, 0.8 ])), vector_model=VectorModel(intercepts=array([ 0.0503911 , 0.12838033, 0.15541499, 0.20185793, 0.22718579, + 0.24311703, 0.24583074, 0.08262932, -0.06406015, -0.05102962, + -0.39325651, -0.40243304, -0.13275181, -0.10596104, -0.09671903, + -0.10022582, -0.10660703]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=0.9474902352534894, shift=array([9.47490235, 0.99993647])), candidate_index=64, candidate_x=array([5.99457255, 1.04132824]), index=63, x=array([6.58843012, 1.03594893]), fval=0.5414632317465802, rho=-2.858177349740313, accepted=False, new_indices=array([], dtype=int32), old_indices_used=array([54, 55, 56, 57, 59, 60, 61, 62, 63]), old_indices_discarded=array([ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, + 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, + 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, + 51, 52, 53, 58]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([6.58843012, 1.03594893]), radius=0.9474902352534894, bounds=Bounds(lower=array([1.1, 0.5]), upper=array([20. , 1.1]))), model_indices=array([55, 56, 57, 59, 60, 61, 62, 63, 64]), model=ScalarModel(intercept=13.033433276409284, linear_terms=array([ -0.7928235 , -31.91157346]), square_terms=array([[3.91876133e-02, 1.01921230e+00], + [1.01921230e+00, 4.07663306e+01]]), scale=array([0.83969136, 0.3 ]), shift=array([6.58843012, 0.8 ])), vector_model=VectorModel(intercepts=array([ 0.0503911 , 0.12838033, 0.15541499, 0.20185793, 0.22718579, + 0.24311703, 0.24583074, 0.08262932, -0.06406015, -0.05102962, + -0.39325651, -0.40243304, -0.13275181, -0.10596104, -0.09671903, + -0.10022582, -0.10660703]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=0.9474902352534894, shift=array([9.47490235, 0.99993647])), candidate_index=65, candidate_x=array([6.28160798, 1.03757835]), index=63, x=array([6.58843012, 1.03594893]), fval=0.5414632317465802, rho=-1.670491030486846, accepted=False, new_indices=array([], dtype=int32), old_indices_used=array([55, 56, 57, 59, 60, 61, 62, 63, 64]), old_indices_discarded=array([ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, + 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, + 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, + 51, 52, 53, 54, 58]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([6.58843012, 1.03594893]), radius=0.4737451176267447, bounds=Bounds(lower=array([1.1, 0.5]), upper=array([20. , 1.1]))), model_indices=array([55, 57, 59, 60, 61, 62, 63, 64, 65]), model=ScalarModel(intercept=7.57645714444444, linear_terms=array([ -0.29574748, -19.22814953]), square_terms=array([[9.87830891e-03, 4.07101559e-01], + [4.07101559e-01, 2.62853990e+01]]), scale=array([0.41984568, 0.24194837]), shift=array([6.58843012, 0.85805163])), vector_model=VectorModel(intercepts=array([ 0.0503911 , 0.12838033, 0.15541499, 0.20185793, 0.22718579, + 0.24311703, 0.24583074, 0.08262932, -0.06406015, -0.05102962, + -0.39325651, -0.40243304, -0.13275181, -0.10596104, -0.09671903, + -0.10022582, -0.10660703]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=0.9474902352534894, shift=array([9.47490235, 0.99993647])), candidate_index=66, candidate_x=array([6.34718361, 1.03719355]), index=63, x=array([6.58843012, 1.03594893]), fval=0.5414632317465802, rho=-1.608088619606695, accepted=False, new_indices=array([], dtype=int32), old_indices_used=array([55, 57, 59, 60, 61, 62, 63, 64, 65]), old_indices_discarded=array([ 1, 3, 7, 10, 13, 30, 31, 32, 35, 37, 38, 39, 41, 42, 43, 44, 45, + 46, 47, 48, 49, 50, 51, 52, 53, 54, 56, 58]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([6.58843012, 1.03594893]), radius=0.23687255881337235, bounds=Bounds(lower=array([1.1, 0.5]), upper=array([20. , 1.1]))), model_indices=array([61, 62, 63, 64, 65, 66]), model=ScalarModel(intercept=2.51780763816455, linear_terms=array([-0.09621641, -7.35783746]), square_terms=array([[3.42399524e-03, 1.80214137e-01], + [1.80214137e-01, 1.37071817e+01]]), scale=array([0.20992284, 0.13698695]), shift=array([6.58843012, 0.96301305])), vector_model=VectorModel(intercepts=array([ 0.0503911 , 0.12838033, 0.15541499, 0.20185793, 0.22718579, + 0.24311703, 0.24583074, 0.08262932, -0.06406015, -0.05102962, + -0.39325651, -0.40243304, -0.13275181, -0.10596104, -0.09671903, + -0.10022582, -0.10660703]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 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6.45218243e-02], + [6.45218243e-02, 6.96729079e+00]]), scale=array([0.10496142, 0.08450624]), shift=array([6.58843012, 1.01549376])), vector_model=VectorModel(intercepts=array([ 0.0503911 , 0.12838033, 0.15541499, 0.20185793, 0.22718579, + 0.24311703, 0.24583074, 0.08262932, -0.06406015, -0.05102962, + -0.39325651, -0.40243304, -0.13275181, -0.10596104, -0.09671903, + -0.10022582, -0.10660703]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 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6.94910166e+00]]), scale=array([0.10496142, 0.08450474]), shift=array([6.60273304, 1.01549526])), vector_model=VectorModel(intercepts=array([ 0.0503911 , 0.12838033, 0.15541499, 0.20185793, 0.22718579, + 0.24311703, 0.24583074, 0.08262932, -0.06406015, -0.05102962, + -0.39325651, -0.40243304, -0.13275181, -0.10596104, -0.09671903, + -0.10022582, -0.10660703]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + 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0.08458141]), shift=array([6.61449989, 1.01541859])), vector_model=VectorModel(intercepts=array([ 0.0503911 , 0.12838033, 0.15541499, 0.20185793, 0.22718579, + 0.24311703, 0.24583074, 0.08262932, -0.06406015, -0.05102962, + -0.39325651, -0.40243304, -0.13275181, -0.10596104, -0.09671903, + -0.10022582, -0.10660703]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 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vector_model=VectorModel(intercepts=array([ 0.0503911 , 0.12838033, 0.15541499, 0.20185793, 0.22718579, + 0.24311703, 0.24583074, 0.08262932, -0.06406015, -0.05102962, + -0.39325651, -0.40243304, -0.13275181, -0.10596104, -0.09671903, + -0.10022582, -0.10660703]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=0.9474902352534894, shift=array([9.47490235, 0.99993647])), candidate_index=71, candidate_x=array([6.60701913, 1.03578557]), index=69, x=array([6.61449989, 1.0357986 ]), fval=0.5414101559834424, rho=-16.79541545743258, accepted=False, new_indices=array([], dtype=int32), old_indices_used=array([62, 63, 66, 67, 68, 69, 70]), old_indices_discarded=array([], dtype=int32), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([6.61449989, 1.0357986 ]), radius=0.029609069851671544, bounds=Bounds(lower=array([1.1, 0.5]), upper=array([20. , 1.1]))), model_indices=array([62, 63, 67, 68, 69, 70, 71]), model=ScalarModel(intercept=0.5414615742402571, linear_terms=array([8.4752230e-05, 4.0438811e-03]), square_terms=array([[6.98826564e-05, 6.29275999e-03], + [6.29275999e-03, 8.41875305e-01]]), scale=0.029609069851671544, shift=array([6.61449989, 1.0357986 ])), vector_model=VectorModel(intercepts=array([ 0.0503911 , 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x=array([6.61449989, 1.0357986 ]), fval=0.5414101559834424, rho=-10.089924952581605, accepted=False, new_indices=array([], dtype=int32), old_indices_used=array([63, 68, 69, 70, 71, 72]), old_indices_discarded=array([], dtype=int32), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([6.61449989, 1.0357986 ]), radius=0.007402267462917886, bounds=Bounds(lower=array([1.1, 0.5]), upper=array([20. , 1.1]))), model_indices=array([63, 68, 69, 70, 71, 72, 73]), model=ScalarModel(intercept=0.5414619458203902, linear_terms=array([6.9562924e-06, 8.5447900e-04]), square_terms=array([[4.61608585e-06, 4.03102152e-04], + [4.03102152e-04, 5.06614459e-02]]), scale=0.007402267462917886, shift=array([6.61449989, 1.0357986 ])), vector_model=VectorModel(intercepts=array([ 0.0503911 , 0.12838033, 0.15541499, 0.20185793, 0.22718579, + 0.24311703, 0.24583074, 0.08262932, -0.06406015, -0.05102962, + -0.39325651, -0.40243304, -0.13275181, 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69, 70, 71, 73, 74]), old_indices_discarded=array([], dtype=int32), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([6.61449989, 1.0357986 ]), radius=0.0018505668657294715, bounds=Bounds(lower=array([1.1, 0.5]), upper=array([20. , 1.1]))), model_indices=array([69, 70, 71, 74, 75]), model=ScalarModel(intercept=0.5414505447289019, linear_terms=array([-8.39195189e-06, -4.82590678e-04]), square_terms=array([[2.93663647e-07, 2.57520778e-05], + [2.57520778e-05, 3.23949356e-03]]), scale=0.0018505668657294715, shift=array([6.61449989, 1.0357986 ])), vector_model=VectorModel(intercepts=array([ 0.0503911 , 0.12838033, 0.15541499, 0.20185793, 0.22718579, + 0.24311703, 0.24583074, 0.08262932, -0.06406015, -0.05102962, + -0.39325651, -0.40243304, -0.13275181, -0.10596104, -0.09671903, + -0.10022582, -0.10660703]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 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State(trustregion=Region(center=array([6.61449989, 1.0357986 ]), radius=0.0004626417164323679, bounds=Bounds(lower=array([1.1, 0.5]), upper=array([20. , 1.1]))), model_indices=array([69, 76, 77]), model=ScalarModel(intercept=0.5414101559834427, linear_terms=array([ 5.92027706e-05, -8.95483752e-05]), square_terms=array([[1.36984529e-08, 3.03717688e-07], + [3.03717688e-07, 2.08099140e-04]]), scale=0.0004626417164323679, shift=array([6.61449989, 1.0357986 ])), vector_model=VectorModel(intercepts=array([ 0.0503911 , 0.12838033, 0.15541499, 0.20185793, 0.22718579, + 0.24311703, 0.24583074, 0.08262932, -0.06406015, -0.05102962, + -0.39325651, -0.40243304, -0.13275181, -0.10596104, -0.09671903, + -0.10022582, -0.10660703]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + 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bounds=Bounds(lower=array([1.1, 0.5]), upper=array([20. , 1.1]))), model_indices=array([69, 77, 78]), model=ScalarModel(intercept=0.5414101559834427, linear_terms=array([-3.31705191e-05, 8.65285911e-06]), square_terms=array([[2.22032765e-08, 8.67788726e-07], + [8.67788726e-07, 5.06632311e-05]]), scale=0.00023132085821618394, shift=array([6.61449989, 1.0357986 ])), vector_model=VectorModel(intercepts=array([ 0.0503911 , 0.12838033, 0.15541499, 0.20185793, 0.22718579, + 0.24311703, 0.24583074, 0.08262932, -0.06406015, -0.05102962, + -0.39325651, -0.40243304, -0.13275181, -0.10596104, -0.09671903, + -0.10022582, -0.10660703]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + 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square_terms=array([[5.66196704e-10, 3.16088422e-08], + [3.16088422e-08, 3.25790992e-06]]), scale=5.7830214554045985e-05, shift=array([6.61449989, 1.0357986 ])), vector_model=VectorModel(intercepts=array([ 0.0503911 , 0.12838033, 0.15541499, 0.20185793, 0.22718579, + 0.24311703, 0.24583074, 0.08262932, -0.06406015, -0.05102962, + -0.39325651, -0.40243304, -0.13275181, -0.10596104, -0.09671903, + -0.10022582, -0.10660703]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 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n_evals_acceptance=1), State(trustregion=Region(center=array([9.31141951, 1.00056177]), radius=0.028912834363592946, bounds=Bounds(lower=array([1.1, 0.5]), upper=array([20. , 1.1]))), model_indices=array([ 0, 12, 16, 17]), model=ScalarModel(intercept=0.5717127918231406, linear_terms=array([-0.03750891, -0.05450237]), square_terms=array([[0.01170099, 0.06888337], + [0.06888337, 0.44451557]]), scale=0.028912834363592946, shift=array([9.31141951, 1.00056177])), vector_model=VectorModel(intercepts=array([ 0.04871065, 0.12404049, 0.14884012, 0.19380771, 0.21739522, + 0.23240935, 0.23334521, 0.06700373, -0.08020904, -0.06714673, + -0.40907425, -0.41756644, -0.12515654, -0.09879383, -0.08942031, + -0.09320124, -0.09958839]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + 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bounds=Bounds(lower=array([1.1, 0.5]), upper=array([20. , 1.1]))), model_indices=array([ 0, 16, 17, 18]), model=ScalarModel(intercept=0.641670882731942, linear_terms=array([ 0.0001693, -0.0200567]), square_terms=array([[1.68433034e-05, 9.19250943e-04], + [9.19250943e-04, 5.69319975e-02]]), scale=0.014456417181796473, shift=array([9.31141951, 1.00056177])), vector_model=VectorModel(intercepts=array([ 0.04871065, 0.12404049, 0.14884012, 0.19380771, 0.21739522, + 0.23240935, 0.23334521, 0.06700373, -0.08020904, -0.06714673, + -0.40907425, -0.41756644, -0.12515654, -0.09879383, -0.08942031, + -0.09320124, -0.09958839]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 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0, 12, 16, 17, 18, 19]), model=ScalarModel(intercept=0.6012358381863223, linear_terms=array([-0.03042216, -0.04242261]), square_terms=array([[0.0084916 , 0.0594053 ], + [0.0594053 , 0.45360295]]), scale=0.028912834363592946, shift=array([9.2970465 , 1.00584119])), vector_model=VectorModel(intercepts=array([ 0.04871065, 0.12404049, 0.14884012, 0.19380771, 0.21739522, + 0.23240935, 0.23334521, 0.06700373, -0.08020904, -0.06714673, + -0.40907425, -0.41756644, -0.12515654, -0.09879383, -0.08942031, + -0.09320124, -0.09958839]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=0.9252106996349743, shift=array([9.252107, 1. ])), candidate_index=20, candidate_x=array([9.32606997, 1.00479922]), index=19, x=array([9.2970465 , 1.00584119]), fval=0.6292604132865477, rho=-0.08086081452522284, accepted=False, new_indices=array([], dtype=int32), old_indices_used=array([ 0, 12, 16, 17, 18, 19]), old_indices_discarded=array([], dtype=int32), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([9.2970465 , 1.00584119]), radius=0.014456417181796473, bounds=Bounds(lower=array([1.1, 0.5]), upper=array([20. , 1.1]))), model_indices=array([ 0, 17, 18, 19, 20]), model=ScalarModel(intercept=0.6292100231114055, linear_terms=array([ 0.00052506, -0.01570005]), square_terms=array([[1.75334423e-05, 1.15319018e-03], + [1.15319018e-03, 8.52466648e-02]]), scale=0.014456417181796473, shift=array([9.2970465 , 1.00584119])), vector_model=VectorModel(intercepts=array([ 0.04871065, 0.12404049, 0.14884012, 0.19380771, 0.21739522, + 0.23240935, 0.23334521, 0.06700373, -0.08020904, -0.06714673, + -0.40907425, -0.41756644, -0.12515654, -0.09879383, -0.08942031, + -0.09320124, -0.09958839]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 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[0.05731219, 0.45543714]]), scale=0.028912834363592946, shift=array([9.28262709, 1.00867427])), vector_model=VectorModel(intercepts=array([ 0.04871065, 0.12404049, 0.14884012, 0.19380771, 0.21739522, + 0.23240935, 0.23334521, 0.06700373, -0.08020904, -0.06714673, + -0.40907425, -0.41756644, -0.12515654, -0.09879383, -0.08942031, + -0.09320124, -0.09958839]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=0.9252106996349743, shift=array([9.252107, 1. ])), candidate_index=22, candidate_x=array([9.31163449, 1.00761214]), index=21, x=array([9.28262709, 1.00867427]), fval=0.6267379609535012, rho=-0.06817765537610261, accepted=False, new_indices=array([], dtype=int32), old_indices_used=array([ 0, 12, 16, 17, 18, 19, 20, 21]), old_indices_discarded=array([], dtype=int32), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([9.28262709, 1.00867427]), radius=0.014456417181796473, bounds=Bounds(lower=array([1.1, 0.5]), upper=array([20. , 1.1]))), model_indices=array([ 0, 17, 18, 19, 20, 21, 22]), model=ScalarModel(intercept=0.6268638818552913, linear_terms=array([ 7.50654479e-04, -8.32943002e-05]), square_terms=array([[1.70290383e-05, 1.14364707e-03], + [1.14364707e-03, 8.64634329e-02]]), scale=0.014456417181796473, shift=array([9.28262709, 1.00867427])), vector_model=VectorModel(intercepts=array([ 0.04871065, 0.12404049, 0.14884012, 0.19380771, 0.21739522, + 0.23240935, 0.23334521, 0.06700373, -0.08020904, -0.06714673, + -0.40907425, -0.41756644, -0.12515654, -0.09879383, -0.08942031, + -0.09320124, -0.09958839]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=0.9252106996349743, shift=array([9.252107, 1. ])), candidate_index=23, candidate_x=array([9.2681721 , 1.00887763]), index=23, x=array([9.2681721 , 1.00887763]), fval=0.626016100574723, rho=0.9614924551145125, accepted=True, new_indices=array([], dtype=int32), old_indices_used=array([ 0, 17, 18, 19, 20, 21, 22]), old_indices_discarded=array([], dtype=int32), step_length=0.014456422294036085, relative_step_length=1.0000003536311624, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([9.2681721 , 1.00887763]), radius=0.028912834363592946, bounds=Bounds(lower=array([1.1, 0.5]), upper=array([20. , 1.1]))), model_indices=array([ 0, 16, 17, 18, 19, 20, 21, 22, 23]), model=ScalarModel(intercept=0.6302545671695479, linear_terms=array([0.00190945, 0.02595137]), square_terms=array([[4.59886870e-05, 3.02614441e-03], + [3.02614441e-03, 2.38414991e-01]]), scale=0.028912834363592946, shift=array([9.2681721 , 1.00887763])), vector_model=VectorModel(intercepts=array([ 0.04871065, 0.12404049, 0.14884012, 0.19380771, 0.21739522, + 0.23240935, 0.23334521, 0.06700373, -0.08020904, -0.06714673, + -0.40907425, -0.41756644, -0.12515654, -0.09879383, -0.08942031, + -0.09320124, -0.09958839]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=0.9252106996349743, shift=array([9.252107, 1. ])), candidate_index=24, candidate_x=array([9.2392219 , 1.00611615]), index=23, x=array([9.2681721 , 1.00887763]), fval=0.626016100574723, rho=-0.27020250132363843, accepted=False, new_indices=array([], dtype=int32), old_indices_used=array([ 0, 16, 17, 18, 19, 20, 21, 22, 23]), old_indices_discarded=array([12]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([9.2681721 , 1.00887763]), radius=0.014456417181796473, bounds=Bounds(lower=array([1.1, 0.5]), upper=array([20. , 1.1]))), model_indices=array([ 0, 17, 19, 20, 21, 22, 23, 24]), model=ScalarModel(intercept=0.6260945388463117, linear_terms=array([ 7.51624753e-04, -5.54521229e-05]), square_terms=array([[1.66698146e-05, 1.13418053e-03], + [1.13418053e-03, 8.70860695e-02]]), scale=0.014456417181796473, shift=array([9.2681721 , 1.00887763])), vector_model=VectorModel(intercepts=array([ 0.04871065, 0.12404049, 0.14884012, 0.19380771, 0.21739522, + 0.23240935, 0.23334521, 0.06700373, -0.08020904, -0.06714673, + -0.40907425, -0.41756644, -0.12515654, -0.09879383, -0.08942031, + -0.09320124, -0.09958839]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=0.9252106996349743, shift=array([9.252107, 1. ])), candidate_index=25, candidate_x=array([9.25371701, 1.00907341]), index=25, x=array([9.25371701, 1.00907341]), fval=0.6253205234400713, rho=0.9257747492589474, accepted=True, new_indices=array([], dtype=int32), old_indices_used=array([ 0, 17, 19, 20, 21, 22, 23, 24]), old_indices_discarded=array([], dtype=int32), step_length=0.014456419134255051, relative_step_length=1.000000135058262, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([9.25371701, 1.00907341]), radius=0.028912834363592946, bounds=Bounds(lower=array([1.1, 0.5]), upper=array([20. , 1.1]))), model_indices=array([ 0, 17, 19, 20, 21, 22, 23, 24, 25]), model=ScalarModel(intercept=0.6253360883435206, linear_terms=array([1.50448575e-03, 8.41583250e-05]), square_terms=array([[6.56507364e-05, 4.50340306e-03], + [4.50340306e-03, 3.49079339e-01]]), scale=0.028912834363592946, shift=array([9.25371701, 1.00907341])), vector_model=VectorModel(intercepts=array([ 0.04871065, 0.12404049, 0.14884012, 0.19380771, 0.21739522, + 0.23240935, 0.23334521, 0.06700373, -0.08020904, -0.06714673, + -0.40907425, -0.41756644, -0.12515654, -0.09879383, -0.08942031, + -0.09320124, -0.09958839]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=0.9252106996349743, shift=array([9.252107, 1. ])), candidate_index=26, candidate_x=array([9.22480647, 1.00943785]), index=26, x=array([9.22480647, 1.00943785]), fval=0.6238879213243532, rho=0.955377431374471, accepted=True, new_indices=array([], dtype=int32), old_indices_used=array([ 0, 17, 19, 20, 21, 22, 23, 24, 25]), old_indices_discarded=array([12, 16, 18]), step_length=0.028912835624545444, relative_step_length=1.0000000436122063, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([9.22480647, 1.00943785]), radius=0.05782566872718589, bounds=Bounds(lower=array([1.1, 0.5]), upper=array([20. , 1.1]))), model_indices=array([ 0, 17, 19, 21, 22, 23, 24, 25, 26]), model=ScalarModel(intercept=0.6238467663285244, linear_terms=array([0.00300031, 0.00025396]), square_terms=array([[2.60662493e-04, 1.79499400e-02], + [1.79499400e-02, 1.39799232e+00]]), scale=0.05782566872718589, shift=array([9.22480647, 1.00943785])), vector_model=VectorModel(intercepts=array([ 0.04871065, 0.12404049, 0.14884012, 0.19380771, 0.21739522, + 0.23240935, 0.23334521, 0.06700373, -0.08020904, -0.06714673, + -0.40907425, -0.41756644, -0.12515654, -0.09879383, -0.08942031, + -0.09320124, -0.09958839]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=0.9252106996349743, shift=array([9.252107, 1. ])), candidate_index=27, candidate_x=array([9.16698541, 1.0101682 ]), index=27, x=array([9.16698541, 1.0101682 ]), fval=0.6211424674970292, rho=0.9207546180217053, accepted=True, new_indices=array([], dtype=int32), old_indices_used=array([ 0, 17, 19, 21, 22, 23, 24, 25, 26]), old_indices_discarded=array([12, 15, 16, 18, 20]), step_length=0.05782566998640155, relative_step_length=1.0000000217760674, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([9.16698541, 1.0101682 ]), radius=0.11565133745437178, bounds=Bounds(lower=array([1.1, 0.5]), upper=array([20. , 1.1]))), model_indices=array([ 0, 19, 21, 22, 23, 24, 25, 26, 27]), model=ScalarModel(intercept=0.6293604631753875, linear_terms=array([ 0.00168088, -0.25402434]), square_terms=array([[7.94437328e-04, 5.20961396e-02], + [5.20961396e-02, 3.88207149e+00]]), scale=array([0.10249333, 0.09616256]), shift=array([9.16698541, 1.00383744])), vector_model=VectorModel(intercepts=array([ 0.04871065, 0.12404049, 0.14884012, 0.19380771, 0.21739522, + 0.23240935, 0.23334521, 0.06700373, -0.08020904, -0.06714673, + -0.40907425, -0.41756644, -0.12515654, -0.09879383, -0.08942031, + -0.09320124, -0.09958839]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=0.9252106996349743, shift=array([9.252107, 1. ])), candidate_index=28, candidate_x=array([9.06449208, 1.01142033]), index=28, x=array([9.06449208, 1.01142033]), fval=0.6161874288905664, rho=0.9826654333073533, accepted=True, new_indices=array([], dtype=int32), old_indices_used=array([ 0, 19, 21, 22, 23, 24, 25, 26, 27]), old_indices_discarded=array([11, 12, 13, 14, 15, 16, 17, 18, 20]), step_length=0.10250097734076673, relative_step_length=0.8862930563272275, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([9.06449208, 1.01142033]), radius=0.23130267490874357, bounds=Bounds(lower=array([1.1, 0.5]), upper=array([20. , 1.1]))), model_indices=array([ 0, 19, 21, 23, 24, 25, 26, 27, 28]), model=ScalarModel(intercept=1.3269180344206313, linear_terms=array([-0.0530022 , -3.58500408]), square_terms=array([[3.16437378e-03, 1.58383379e-01], + [1.58383379e-01, 9.04125674e+00]]), scale=array([0.20498666, 0.14678316]), shift=array([9.06449208, 0.95321684])), vector_model=VectorModel(intercepts=array([ 0.04871065, 0.12404049, 0.14884012, 0.19380771, 0.21739522, + 0.23240935, 0.23334521, 0.06700373, -0.08020904, -0.06714673, + -0.40907425, -0.41756644, -0.12515654, -0.09879383, -0.08942031, + -0.09320124, -0.09958839]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=0.9252106996349743, shift=array([9.252107, 1. ])), candidate_index=29, candidate_x=array([8.85950542, 1.01399005]), index=29, x=array([8.85950542, 1.01399005]), fval=0.6068057893338722, rho=0.9768016993555535, accepted=True, new_indices=array([], dtype=int32), old_indices_used=array([ 0, 19, 21, 23, 24, 25, 26, 27, 28]), old_indices_discarded=array([ 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, + 18, 20, 22]), step_length=0.20500276489564104, relative_step_length=0.8862965591579142, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([8.85950542, 1.01399005]), radius=0.46260534981748713, bounds=Bounds(lower=array([1.1, 0.5]), upper=array([20. , 1.1]))), model_indices=array([ 7, 10, 13, 21, 22, 24, 27, 28, 29]), model=ScalarModel(intercept=5.056588947128265, linear_terms=array([ 0.12014523, -14.39462599]), square_terms=array([[ 4.11394441e-03, -9.76345780e-02], + [-9.76345780e-02, 2.30839568e+01]]), scale=array([0.40997332, 0.24799163]), shift=array([8.85950542, 0.85200837])), vector_model=VectorModel(intercepts=array([ 0.04871065, 0.12404049, 0.14884012, 0.19380771, 0.21739522, + 0.23240935, 0.23334521, 0.06700373, -0.08020904, -0.06714673, + -0.40907425, -0.41756644, -0.12515654, -0.09879383, -0.08942031, + -0.09320124, -0.09958839]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=0.9252106996349743, shift=array([9.252107, 1. ])), candidate_index=30, candidate_x=array([8.5580007 , 1.00630498]), index=29, x=array([8.85950542, 1.01399005]), fval=0.6068057893338722, rho=-0.3014966051278916, accepted=False, new_indices=array([], dtype=int32), old_indices_used=array([ 7, 10, 13, 21, 22, 24, 27, 28, 29]), old_indices_discarded=array([ 0, 1, 2, 3, 4, 5, 6, 8, 9, 11, 12, 14, 15, 16, 17, 18, 19, + 20, 23, 25, 26]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([8.85950542, 1.01399005]), radius=0.23130267490874357, bounds=Bounds(lower=array([1.1, 0.5]), upper=array([20. , 1.1]))), model_indices=array([ 0, 13, 24, 25, 26, 27, 28, 29, 30]), model=ScalarModel(intercept=0.9805939633807261, linear_terms=array([-0.03836743, -1.98882772]), square_terms=array([[3.07342158e-03, 1.18191343e-01], + [1.18191343e-01, 5.34723779e+00]]), scale=array([0.20498666, 0.1454983 ]), shift=array([8.85950542, 0.9545017 ])), vector_model=VectorModel(intercepts=array([ 0.04871065, 0.12404049, 0.14884012, 0.19380771, 0.21739522, + 0.23240935, 0.23334521, 0.06700373, -0.08020904, -0.06714673, + -0.40907425, -0.41756644, -0.12515654, -0.09879383, -0.08942031, + -0.09320124, -0.09958839]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=0.9252106996349743, shift=array([9.252107, 1. ])), candidate_index=31, candidate_x=array([8.65451876, 1.01183367]), index=31, x=array([8.65451876, 1.01183367]), fval=0.6028983591291701, rho=0.4338323431380853, accepted=True, new_indices=array([], dtype=int32), old_indices_used=array([ 0, 13, 24, 25, 26, 27, 28, 29, 30]), old_indices_discarded=array([ 1, 3, 6, 7, 9, 10, 11, 12, 14, 15, 16, 17, 18, 19, 20, 21, 22, + 23]), step_length=0.20499800027263237, relative_step_length=0.8862759600748705, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([8.65451876, 1.01183367]), radius=0.46260534981748713, bounds=Bounds(lower=array([1.1, 0.5]), upper=array([20. , 1.1]))), model_indices=array([ 3, 7, 10, 13, 27, 28, 29, 30, 31]), model=ScalarModel(intercept=2.6746347212609862, linear_terms=array([ 0.41935614, -7.16647929]), square_terms=array([[ 0.03391117, -0.55595491], + [-0.55595491, 12.02901321]]), scale=array([0.40997332, 0.24906982]), shift=array([8.65451876, 0.85093018])), vector_model=VectorModel(intercepts=array([ 0.04871065, 0.12404049, 0.14884012, 0.19380771, 0.21739522, + 0.23240935, 0.23334521, 0.06700373, -0.08020904, -0.06714673, + -0.40907425, -0.41756644, -0.12515654, -0.09879383, -0.08942031, + -0.09320124, -0.09958839]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=0.9252106996349743, shift=array([9.252107, 1. ])), candidate_index=32, candidate_x=array([8.24454545, 0.98780609]), index=31, x=array([8.65451876, 1.01183367]), fval=0.6028983591291701, rho=-1.992201463503947, accepted=False, new_indices=array([], dtype=int32), old_indices_used=array([ 3, 7, 10, 13, 27, 28, 29, 30, 31]), old_indices_discarded=array([ 0, 1, 2, 4, 5, 6, 8, 9, 11, 12, 14, 15, 16, 17, 18, 19, 20, + 21, 22, 23, 24, 25, 26]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([8.65451876, 1.01183367]), radius=0.23130267490874357, bounds=Bounds(lower=array([1.1, 0.5]), upper=array([20. , 1.1]))), model_indices=array([ 3, 7, 10, 13, 28, 29, 30, 31, 32]), model=ScalarModel(intercept=0.8053556101878039, linear_terms=array([ 0.0500788 , -1.40901645]), square_terms=array([[ 1.81988958e-03, -5.72982752e-02], + [-5.72982752e-02, 4.04450417e+00]]), scale=array([0.20498666, 0.14657649]), shift=array([8.65451876, 0.95342351])), vector_model=VectorModel(intercepts=array([ 0.04871065, 0.12404049, 0.14884012, 0.19380771, 0.21739522, + 0.23240935, 0.23334521, 0.06700373, -0.08020904, -0.06714673, + -0.40907425, -0.41756644, -0.12515654, -0.09879383, -0.08942031, + -0.09320124, -0.09958839]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=0.9252106996349743, shift=array([9.252107, 1. ])), candidate_index=33, candidate_x=array([8.44953211, 1.002411 ]), index=31, x=array([8.65451876, 1.01183367]), fval=0.6028983591291701, rho=-1.2944780565240657, accepted=False, new_indices=array([], dtype=int32), old_indices_used=array([ 3, 7, 10, 13, 28, 29, 30, 31, 32]), old_indices_discarded=array([ 0, 1, 9, 11, 12, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, + 26, 27]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([8.65451876, 1.01183367]), radius=0.11565133745437178, bounds=Bounds(lower=array([1.1, 0.5]), upper=array([20. , 1.1]))), model_indices=array([ 3, 7, 10, 13, 28, 29, 30, 31, 33]), model=ScalarModel(intercept=0.5580455956991042, linear_terms=array([0.02153789, 0.02119119]), square_terms=array([[ 0.0023124 , -0.05543391], + [-0.05543391, 1.707328 ]]), scale=array([0.10249333, 0.09532983]), shift=array([8.65451876, 1.00467017])), vector_model=VectorModel(intercepts=array([ 0.04871065, 0.12404049, 0.14884012, 0.19380771, 0.21739522, + 0.23240935, 0.23334521, 0.06700373, -0.08020904, -0.06714673, + -0.40907425, -0.41756644, -0.12515654, -0.09879383, -0.08942031, + -0.09320124, -0.09958839]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=0.9252106996349743, shift=array([9.252107, 1. ])), candidate_index=34, candidate_x=array([8.55202543, 1.00039176]), index=31, x=array([8.65451876, 1.01183367]), fval=0.6028983591291701, rho=-1.872524866103317, accepted=False, new_indices=array([], dtype=int32), old_indices_used=array([ 3, 7, 10, 13, 28, 29, 30, 31, 33]), old_indices_discarded=array([ 1, 26, 27, 32]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([8.65451876, 1.01183367]), radius=0.05782566872718589, bounds=Bounds(lower=array([1.1, 0.5]), upper=array([20. , 1.1]))), model_indices=array([ 3, 7, 10, 13, 29, 30, 31, 33, 34]), model=ScalarModel(intercept=0.5796812293248299, linear_terms=array([0.01586132, 0.02969879]), square_terms=array([[ 0.00226369, -0.03434719], + [-0.03434719, 0.60957011]]), scale=0.05782566872718589, shift=array([8.65451876, 1.01183367])), vector_model=VectorModel(intercepts=array([ 0.04871065, 0.12404049, 0.14884012, 0.19380771, 0.21739522, + 0.23240935, 0.23334521, 0.06700373, -0.08020904, -0.06714673, + -0.40907425, -0.41756644, -0.12515654, -0.09879383, -0.08942031, + -0.09320124, -0.09958839]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=0.9252106996349743, shift=array([9.252107, 1. ])), candidate_index=35, candidate_x=array([8.59693373, 1.00593781]), index=31, x=array([8.65451876, 1.01183367]), fval=0.6028983591291701, rho=-1.1577436588415695, accepted=False, new_indices=array([], dtype=int32), old_indices_used=array([ 3, 7, 10, 13, 29, 30, 31, 33, 34]), old_indices_discarded=array([], dtype=int32), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([8.65451876, 1.01183367]), radius=0.028912834363592946, bounds=Bounds(lower=array([1.1, 0.5]), upper=array([20. , 1.1]))), model_indices=array([30, 31, 34, 35]), model=ScalarModel(intercept=0.6034966185125235, linear_terms=array([-0.00034619, -0.03914939]), square_terms=array([[9.39236593e-05, 5.48779016e-03], + [5.48779016e-03, 3.65303262e-01]]), scale=0.028912834363592946, shift=array([8.65451876, 1.01183367])), vector_model=VectorModel(intercepts=array([ 0.04871065, 0.12404049, 0.14884012, 0.19380771, 0.21739522, + 0.23240935, 0.23334521, 0.06700373, -0.08020904, -0.06714673, + -0.40907425, -0.41756644, -0.12515654, -0.09879383, -0.08942031, + -0.09320124, -0.09958839]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=0.9252106996349743, shift=array([9.252107, 1. ])), candidate_index=36, candidate_x=array([8.62565678, 1.0153636 ]), index=36, x=array([8.62565678, 1.0153636 ]), fval=0.5971978537018936, rho=2.442794438040451, accepted=True, new_indices=array([], dtype=int32), old_indices_used=array([30, 31, 34, 35]), old_indices_discarded=array([], dtype=int32), step_length=0.02907704145844469, relative_step_length=1.0056793842065692, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([8.62565678, 1.0153636 ]), radius=0.05782566872718589, bounds=Bounds(lower=array([1.1, 0.5]), upper=array([20. , 1.1]))), model_indices=array([ 7, 10, 13, 30, 31, 33, 34, 35, 36]), model=ScalarModel(intercept=0.5603293659645237, linear_terms=array([-0.00236478, 0.12100806]), square_terms=array([[0.00302626, 0.06759657], + [0.06759657, 1.59874941]]), scale=0.05782566872718589, shift=array([8.62565678, 1.0153636 ])), vector_model=VectorModel(intercepts=array([ 0.04871065, 0.12404049, 0.14884012, 0.19380771, 0.21739522, + 0.23240935, 0.23334521, 0.06700373, -0.08020904, -0.06714673, + -0.40907425, -0.41756644, -0.12515654, -0.09879383, -0.08942031, + -0.09320124, -0.09958839]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=0.9252106996349743, shift=array([9.252107, 1. ])), candidate_index=37, candidate_x=array([8.68324715, 1.00858284]), index=36, x=array([8.62565678, 1.0153636 ]), fval=0.5971978537018936, rho=-1.2581050712790383, accepted=False, new_indices=array([], dtype=int32), old_indices_used=array([ 7, 10, 13, 30, 31, 33, 34, 35, 36]), old_indices_discarded=array([ 3, 29]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([8.62565678, 1.0153636 ]), radius=0.028912834363592946, bounds=Bounds(lower=array([1.1, 0.5]), upper=array([20. , 1.1]))), model_indices=array([30, 31, 34, 35, 36, 37]), model=ScalarModel(intercept=0.5981101022806663, linear_terms=array([ 0.00137081, -0.01014437]), square_terms=array([[6.44240543e-05, 4.61221760e-03], + [4.61221760e-03, 3.91431444e-01]]), scale=0.028912834363592946, shift=array([8.62565678, 1.0153636 ])), vector_model=VectorModel(intercepts=array([ 0.04871065, 0.12404049, 0.14884012, 0.19380771, 0.21739522, + 0.23240935, 0.23334521, 0.06700373, -0.08020904, -0.06714673, + -0.40907425, -0.41756644, -0.12515654, -0.09879383, -0.08942031, + -0.09320124, -0.09958839]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=0.9252106996349743, shift=array([9.252107, 1. ])), candidate_index=38, candidate_x=array([8.59675474, 1.01644935]), index=38, x=array([8.59675474, 1.01644935]), fval=0.5956021578624653, rho=0.987318065496306, accepted=True, new_indices=array([], dtype=int32), old_indices_used=array([30, 31, 34, 35, 36, 37]), old_indices_discarded=array([], dtype=int32), step_length=0.02892243332840774, relative_step_length=1.0003319966729682, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([8.59675474, 1.01644935]), radius=0.05782566872718589, bounds=Bounds(lower=array([1.1, 0.5]), upper=array([20. , 1.1]))), model_indices=array([10, 30, 31, 33, 34, 35, 36, 37, 38]), model=ScalarModel(intercept=0.5967490097134395, linear_terms=array([0.00266649, 0.00222244]), square_terms=array([[2.84220825e-04, 1.95806140e-02], + [1.95806140e-02, 1.56758521e+00]]), scale=0.05782566872718589, shift=array([8.59675474, 1.01644935])), vector_model=VectorModel(intercepts=array([ 0.04871065, 0.12404049, 0.14884012, 0.19380771, 0.21739522, + 0.23240935, 0.23334521, 0.06700373, -0.08020904, -0.06714673, + -0.40907425, -0.41756644, -0.12515654, -0.09879383, -0.08942031, + -0.09320124, -0.09958839]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=0.9252106996349743, shift=array([9.252107, 1. ])), candidate_index=39, candidate_x=array([8.53893254, 1.01708857]), index=39, x=array([8.53893254, 1.01708857]), fval=0.5930797801438898, rho=0.9626177327032385, accepted=True, new_indices=array([], dtype=int32), old_indices_used=array([10, 30, 31, 33, 34, 35, 36, 37, 38]), old_indices_discarded=array([ 3, 7, 13, 29]), step_length=0.05782572833136036, relative_step_length=1.0000010307563367, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([8.53893254, 1.01708857]), radius=0.11565133745437178, bounds=Bounds(lower=array([1.1, 0.5]), upper=array([20. , 1.1]))), model_indices=array([10, 30, 31, 33, 34, 35, 36, 38, 39]), model=ScalarModel(intercept=0.6164032682482006, linear_terms=array([-0.0014308, -0.4276386]), square_terms=array([[9.03112375e-04, 5.61729802e-02], + [5.61729802e-02, 4.04976927e+00]]), scale=array([0.10249333, 0.09270238]), shift=array([8.53893254, 1.00729762])), vector_model=VectorModel(intercepts=array([ 0.04871065, 0.12404049, 0.14884012, 0.19380771, 0.21739522, + 0.23240935, 0.23334521, 0.06700373, -0.08020904, -0.06714673, + -0.40907425, -0.41756644, -0.12515654, -0.09879383, -0.08942031, + -0.09320124, -0.09958839]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=0.9252106996349743, shift=array([9.252107, 1. ])), candidate_index=40, candidate_x=array([8.43643921, 1.01837244]), index=40, x=array([8.43643921, 1.01837244]), fval=0.5886586453047548, rho=0.9960093815093017, accepted=True, new_indices=array([], dtype=int32), old_indices_used=array([10, 30, 31, 33, 34, 35, 36, 38, 39]), old_indices_discarded=array([ 1, 3, 7, 13, 28, 29, 32, 37]), step_length=0.10250137012000532, relative_step_length=0.8862964525632524, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([8.43643921, 1.01837244]), radius=0.23130267490874357, bounds=Bounds(lower=array([1.1, 0.5]), upper=array([20. , 1.1]))), model_indices=array([ 3, 7, 30, 31, 32, 35, 36, 39, 40]), model=ScalarModel(intercept=0.724464510197967, linear_terms=array([ 0.0588604 , -1.15277065]), square_terms=array([[ 2.63888902e-03, -4.80501605e-02], + [-4.80501605e-02, 3.54022042e+00]]), scale=array([0.20498666, 0.14330711]), shift=array([8.43643921, 0.95669289])), vector_model=VectorModel(intercepts=array([ 0.04871065, 0.12404049, 0.14884012, 0.19380771, 0.21739522, + 0.23240935, 0.23334521, 0.06700373, -0.08020904, -0.06714673, + -0.40907425, -0.41756644, -0.12515654, -0.09879383, -0.08942031, + -0.09320124, -0.09958839]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=0.9252106996349743, shift=array([9.252107, 1. ])), candidate_index=41, candidate_x=array([8.23145255, 1.00141166]), index=40, x=array([8.43643921, 1.01837244]), fval=0.5886586453047548, rho=-1.288535811487196, accepted=False, new_indices=array([], dtype=int32), old_indices_used=array([ 3, 7, 30, 31, 32, 35, 36, 39, 40]), old_indices_discarded=array([ 0, 1, 10, 11, 12, 13, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, + 26, 27, 28, 29, 33, 34, 37, 38]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([8.43643921, 1.01837244]), radius=0.11565133745437178, bounds=Bounds(lower=array([1.1, 0.5]), upper=array([20. , 1.1]))), model_indices=array([ 7, 10, 30, 33, 34, 35, 38, 39, 40]), model=ScalarModel(intercept=0.6190068223081573, linear_terms=array([-0.00232714, -0.74138835]), square_terms=array([[9.27865058e-04, 6.83995451e-02], + [6.83995451e-02, 5.89689117e+00]]), scale=array([0.10249333, 0.09206044]), shift=array([8.43643921, 1.00793956])), vector_model=VectorModel(intercepts=array([ 0.04871065, 0.12404049, 0.14884012, 0.19380771, 0.21739522, + 0.23240935, 0.23334521, 0.06700373, -0.08020904, -0.06714673, + -0.40907425, -0.41756644, -0.12515654, -0.09879383, -0.08942031, + -0.09320124, -0.09958839]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=0.9252106996349743, shift=array([9.252107, 1. ])), candidate_index=42, candidate_x=array([8.33394588, 1.02058172]), index=42, x=array([8.33394588, 1.02058172]), fval=0.5842263244969528, rho=0.6656700898189453, accepted=True, new_indices=array([], dtype=int32), old_indices_used=array([ 7, 10, 30, 33, 34, 35, 38, 39, 40]), old_indices_discarded=array([ 1, 3, 13, 29, 31, 32, 36, 37, 41]), step_length=0.10251713719284976, relative_step_length=0.8864327853821501, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([8.33394588, 1.02058172]), radius=0.23130267490874357, bounds=Bounds(lower=array([1.1, 0.5]), upper=array([20. , 1.1]))), model_indices=array([ 3, 7, 30, 32, 33, 39, 40, 41, 42]), model=ScalarModel(intercept=0.8040646506922852, linear_terms=array([-0.16272345, -1.28751653]), square_terms=array([[0.03910645, 0.3480799 ], + [0.3480799 , 3.42094897]]), scale=array([0.20498666, 0.14220247]), shift=array([8.33394588, 0.95779753])), vector_model=VectorModel(intercepts=array([ 0.04871065, 0.12404049, 0.14884012, 0.19380771, 0.21739522, + 0.23240935, 0.23334521, 0.06700373, -0.08020904, -0.06714673, + -0.40907425, -0.41756644, -0.12515654, -0.09879383, -0.08942031, + -0.09320124, -0.09958839]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=0.9252106996349743, shift=array([9.252107, 1. ])), candidate_index=43, candidate_x=array([8.53893254, 0.99684816]), index=42, x=array([8.33394588, 1.02058172]), fval=0.5842263244969528, rho=-2.655032004787166, accepted=False, new_indices=array([], dtype=int32), old_indices_used=array([ 3, 7, 30, 32, 33, 39, 40, 41, 42]), old_indices_discarded=array([ 0, 1, 10, 11, 12, 13, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, + 26, 27, 28, 29, 31, 34, 35, 36, 37, 38]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([8.33394588, 1.02058172]), radius=0.11565133745437178, bounds=Bounds(lower=array([1.1, 0.5]), upper=array([20. , 1.1]))), model_indices=array([ 7, 10, 32, 33, 39, 40, 41, 42, 43]), model=ScalarModel(intercept=0.5905582188830226, linear_terms=array([ 0.00921118, -0.6113136 ]), square_terms=array([[4.08156812e-04, 2.99902373e-02], + [2.99902373e-02, 5.44560063e+00]]), scale=array([0.10249333, 0.09095581]), shift=array([8.33394588, 1.00904419])), vector_model=VectorModel(intercepts=array([ 0.04871065, 0.12404049, 0.14884012, 0.19380771, 0.21739522, + 0.23240935, 0.23334521, 0.06700373, -0.08020904, -0.06714673, + -0.40907425, -0.41756644, -0.12515654, -0.09879383, -0.08942031, + -0.09320124, -0.09958839]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=0.9252106996349743, shift=array([9.252107, 1. ])), candidate_index=44, candidate_x=array([8.23145255, 1.01975565]), index=44, x=array([8.23145255, 1.01975565]), fval=0.5809782664932625, rho=0.24916298067878628, accepted=True, new_indices=array([], dtype=int32), old_indices_used=array([ 7, 10, 32, 33, 39, 40, 41, 42, 43]), old_indices_discarded=array([ 1, 3, 13, 29, 30, 31, 34, 35, 36, 37, 38]), step_length=0.10249665809363835, relative_step_length=0.8862557091834465, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([8.23145255, 1.01975565]), radius=0.23130267490874357, bounds=Bounds(lower=array([1.1, 0.5]), upper=array([20. , 1.1]))), model_indices=array([ 3, 7, 10, 32, 33, 40, 41, 42, 44]), model=ScalarModel(intercept=0.9956483394129002, linear_terms=array([-0.42250664, -1.67357518]), square_terms=array([[0.14817312, 0.69125356], + [0.69125356, 3.60029371]]), scale=array([0.20498666, 0.1426155 ]), shift=array([8.23145255, 0.9573845 ])), vector_model=VectorModel(intercepts=array([ 0.04871065, 0.12404049, 0.14884012, 0.19380771, 0.21739522, + 0.23240935, 0.23334521, 0.06700373, -0.08020904, -0.06714673, + -0.40907425, -0.41756644, -0.12515654, -0.09879383, -0.08942031, + -0.09320124, -0.09958839]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=0.9252106996349743, shift=array([9.252107, 1. ])), candidate_index=45, candidate_x=array([8.43643921, 0.9962964 ]), index=44, x=array([8.23145255, 1.01975565]), fval=0.5809782664932625, rho=-1.1980641129471428, accepted=False, new_indices=array([], dtype=int32), old_indices_used=array([ 3, 7, 10, 32, 33, 40, 41, 42, 44]), old_indices_discarded=array([ 0, 1, 11, 12, 13, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, + 28, 29, 30, 31, 34, 35, 36, 37, 38, 39, 43]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([8.23145255, 1.01975565]), radius=0.11565133745437178, bounds=Bounds(lower=array([1.1, 0.5]), upper=array([20. , 1.1]))), model_indices=array([ 7, 10, 32, 33, 40, 41, 42, 44, 45]), model=ScalarModel(intercept=0.600332066842147, linear_terms=array([-0.00086165, -0.70849018]), square_terms=array([[8.18384405e-04, 5.99221947e-02], + [5.99221947e-02, 5.42443420e+00]]), scale=array([0.10249333, 0.09136884]), shift=array([8.23145255, 1.00863116])), vector_model=VectorModel(intercepts=array([ 0.04871065, 0.12404049, 0.14884012, 0.19380771, 0.21739522, + 0.23240935, 0.23334521, 0.06700373, -0.08020904, -0.06714673, + -0.40907425, -0.41756644, -0.12515654, -0.09879383, -0.08942031, + -0.09320124, -0.09958839]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=0.9252106996349743, shift=array([9.252107, 1. ])), candidate_index=46, candidate_x=array([8.12895922, 1.02157425]), index=46, x=array([8.12895922, 1.02157425]), fval=0.5767016574644672, rho=0.6023906618426587, accepted=True, new_indices=array([], dtype=int32), old_indices_used=array([ 7, 10, 32, 33, 40, 41, 42, 44, 45]), old_indices_discarded=array([ 1, 3, 30, 31, 34, 35, 36, 37, 38, 39, 43]), step_length=0.10250946224206313, relative_step_length=0.8863664225457526, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([8.12895922, 1.02157425]), radius=0.23130267490874357, bounds=Bounds(lower=array([1.1, 0.5]), upper=array([20. , 1.1]))), model_indices=array([ 7, 10, 32, 40, 41, 42, 44, 45, 46]), model=ScalarModel(intercept=1.8860503514071725, linear_terms=array([-0.11681592, -5.841289 ]), square_terms=array([[5.93972205e-03, 2.64135430e-01], + [2.64135430e-01, 1.28731339e+01]]), scale=array([0.20498666, 0.1417062 ]), shift=array([8.12895922, 0.9582938 ])), vector_model=VectorModel(intercepts=array([ 0.04871065, 0.12404049, 0.14884012, 0.19380771, 0.21739522, + 0.23240935, 0.23334521, 0.06700373, -0.08020904, -0.06714673, + -0.40907425, -0.41756644, -0.12515654, -0.09879383, -0.08942031, + -0.09320124, -0.09958839]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=0.9252106996349743, shift=array([9.252107, 1. ])), candidate_index=47, candidate_x=array([7.92397257, 1.02550171]), index=47, x=array([7.92397257, 1.02550171]), fval=0.5700309839906248, rho=2.144194285592646, accepted=True, new_indices=array([], dtype=int32), old_indices_used=array([ 7, 10, 32, 40, 41, 42, 44, 45, 46]), old_indices_discarded=array([ 0, 1, 3, 13, 21, 23, 24, 25, 26, 27, 28, 29, 30, 31, 33, 34, 35, + 36, 37, 38, 39, 43]), step_length=0.2050242792857033, relative_step_length=0.8863895731711363, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([7.92397257, 1.02550171]), radius=0.46260534981748713, bounds=Bounds(lower=array([1.1, 0.5]), upper=array([20. , 1.1]))), model_indices=array([ 7, 10, 32, 40, 41, 42, 44, 46, 47]), model=ScalarModel(intercept=9.701952266205492, linear_terms=array([ -0.61691483, -26.37740675]), square_terms=array([[2.29677817e-02, 8.91869339e-01], + [8.91869339e-01, 3.80689975e+01]]), scale=array([0.40997332, 0.2422358 ]), shift=array([7.92397257, 0.8577642 ])), vector_model=VectorModel(intercepts=array([ 0.04871065, 0.12404049, 0.14884012, 0.19380771, 0.21739522, + 0.23240935, 0.23334521, 0.06700373, -0.08020904, -0.06714673, + -0.40907425, -0.41756644, -0.12515654, -0.09879383, -0.08942031, + -0.09320124, -0.09958839]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=0.9252106996349743, shift=array([9.252107, 1. ])), candidate_index=48, candidate_x=array([7.81188801, 1.02714111]), index=48, x=array([7.81188801, 1.02714111]), fval=0.5665120380760114, rho=16.57798751629955, accepted=True, new_indices=array([], dtype=int32), old_indices_used=array([ 7, 10, 32, 40, 41, 42, 44, 46, 47]), old_indices_discarded=array([ 0, 1, 2, 3, 4, 5, 6, 8, 9, 11, 12, 13, 14, 15, 16, 17, 18, + 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 33, 34, 35, 36, + 37, 38, 39, 43, 45]), step_length=0.1120965490592223, relative_step_length=0.24231572138854002, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([7.81188801, 1.02714111]), radius=0.46260534981748713, bounds=Bounds(lower=array([1.1, 0.5]), upper=array([20. , 1.1]))), model_indices=array([ 7, 10, 32, 41, 42, 44, 46, 47, 48]), model=ScalarModel(intercept=9.766219925631294, linear_terms=array([ -0.6871664 , -26.30219402]), square_terms=array([[2.73943250e-02, 9.72602328e-01], + [9.72602328e-01, 3.76072310e+01]]), scale=array([0.40997332, 0.2414161 ]), shift=array([7.81188801, 0.8585839 ])), vector_model=VectorModel(intercepts=array([ 0.04871065, 0.12404049, 0.14884012, 0.19380771, 0.21739522, + 0.23240935, 0.23334521, 0.06700373, -0.08020904, -0.06714673, + -0.40907425, -0.41756644, -0.12515654, -0.09879383, -0.08942031, + -0.09320124, -0.09958839]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=0.9252106996349743, shift=array([9.252107, 1. ])), candidate_index=49, candidate_x=array([8.22186132, 1.02118484]), index=48, x=array([7.81188801, 1.02714111]), fval=0.5665120380760114, rho=-2.3061269690172246, accepted=False, new_indices=array([], dtype=int32), old_indices_used=array([ 7, 10, 32, 41, 42, 44, 46, 47, 48]), old_indices_discarded=array([ 0, 1, 2, 3, 4, 5, 6, 8, 9, 11, 12, 13, 14, 15, 16, 17, 18, + 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 33, 34, 35, 36, + 37, 38, 39, 40, 43, 45]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([7.81188801, 1.02714111]), radius=0.23130267490874357, bounds=Bounds(lower=array([1.1, 0.5]), upper=array([20. , 1.1]))), model_indices=array([10, 32, 41, 42, 44, 46, 47, 48, 49]), model=ScalarModel(intercept=1.4654889570621736, linear_terms=array([-0.05047381, -4.00812911]), square_terms=array([[2.45887025e-03, 1.30332665e-01], + [1.30332665e-01, 8.90254327e+00]]), scale=array([0.20498666, 0.13892277]), shift=array([7.81188801, 0.96107723])), vector_model=VectorModel(intercepts=array([ 0.04871065, 0.12404049, 0.14884012, 0.19380771, 0.21739522, + 0.23240935, 0.23334521, 0.06700373, -0.08020904, -0.06714673, + -0.40907425, -0.41756644, -0.12515654, -0.09879383, -0.08942031, + -0.09320124, -0.09958839]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=0.9252106996349743, shift=array([9.252107, 1. ])), candidate_index=50, candidate_x=array([7.60690135, 1.02565727]), index=50, x=array([7.60690135, 1.02565727]), fval=0.5602123257733056, rho=0.5841994228455609, accepted=True, new_indices=array([], dtype=int32), old_indices_used=array([10, 32, 41, 42, 44, 46, 47, 48, 49]), old_indices_discarded=array([ 1, 3, 7, 13, 29, 30, 31, 33, 34, 35, 36, 37, 38, 39, 40, 43, 45]), step_length=0.20499202897310145, relative_step_length=0.886250144119507, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([7.60690135, 1.02565727]), radius=0.46260534981748713, bounds=Bounds(lower=array([1.1, 0.5]), upper=array([20. , 1.1]))), model_indices=array([32, 41, 42, 44, 46, 47, 48, 49, 50]), model=ScalarModel(intercept=7.123730519114742, linear_terms=array([ -0.32734999, -18.89524377]), square_terms=array([[1.11231711e-02, 4.88743382e-01], + [4.88743382e-01, 2.71922839e+01]]), scale=array([0.40997332, 0.24215803]), shift=array([7.60690135, 0.85784197])), vector_model=VectorModel(intercepts=array([ 0.04871065, 0.12404049, 0.14884012, 0.19380771, 0.21739522, + 0.23240935, 0.23334521, 0.06700373, -0.08020904, -0.06714673, + -0.40907425, -0.41756644, -0.12515654, -0.09879383, -0.08942031, + -0.09320124, -0.09958839]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=0.9252106996349743, shift=array([9.252107, 1. ])), candidate_index=51, candidate_x=array([7.19692803, 1.03046403]), index=51, x=array([7.19692803, 1.03046403]), fval=0.549027411692029, rho=1.0036558314595654, accepted=True, new_indices=array([], dtype=int32), old_indices_used=array([32, 41, 42, 44, 46, 47, 48, 49, 50]), old_indices_discarded=array([ 0, 1, 3, 7, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, + 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 33, 34, 35, 36, 37, 38, 39, + 40, 43, 45]), step_length=0.4100014945883672, relative_step_length=0.8862878363817586, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([7.19692803, 1.03046403]), radius=0.9252106996349743, bounds=Bounds(lower=array([1.1, 0.5]), upper=array([20. , 1.1]))), model_indices=array([32, 41, 44, 46, 47, 48, 49, 50, 51]), model=ScalarModel(intercept=12.73480276563746, linear_terms=array([ -0.87087078, -31.77015852]), square_terms=array([[ 0.042882 , 1.15994563], + [ 1.15994563, 41.41239327]]), scale=array([0.81994663, 0.3 ]), shift=array([7.19692803, 0.8 ])), vector_model=VectorModel(intercepts=array([ 0.04871065, 0.12404049, 0.14884012, 0.19380771, 0.21739522, + 0.23240935, 0.23334521, 0.06700373, -0.08020904, -0.06714673, + -0.40907425, -0.41756644, -0.12515654, -0.09879383, -0.08942031, + -0.09320124, -0.09958839]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=0.9252106996349743, shift=array([9.252107, 1. ])), candidate_index=52, candidate_x=array([6.3769814 , 1.03855253]), index=52, x=array([6.3769814 , 1.03855253]), fval=0.5426853573405204, rho=0.4587040426302159, accepted=True, new_indices=array([], dtype=int32), old_indices_used=array([32, 41, 44, 46, 47, 48, 49, 50, 51]), old_indices_discarded=array([ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, + 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 33, 34, + 35, 36, 37, 38, 39, 40, 42, 43, 45]), step_length=0.8199865279119269, relative_step_length=0.8862700444725059, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([6.3769814 , 1.03855253]), radius=1.8504213992699485, bounds=Bounds(lower=array([1.1, 0.5]), upper=array([20. , 1.1]))), model_indices=array([41, 44, 46, 47, 48, 49, 50, 51, 52]), model=ScalarModel(intercept=14.222023285880177, linear_terms=array([ -1.72856364, -34.55682834]), square_terms=array([[ 0.15979702, 2.19225084], + [ 2.19225084, 43.64084662]]), scale=array([1.63989327, 0.3 ]), shift=array([6.3769814, 0.8 ])), vector_model=VectorModel(intercepts=array([ 0.04871065, 0.12404049, 0.14884012, 0.19380771, 0.21739522, + 0.23240935, 0.23334521, 0.06700373, -0.08020904, -0.06714673, + -0.40907425, -0.41756644, -0.12515654, -0.09879383, -0.08942031, + -0.09320124, -0.09958839]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=0.9252106996349743, shift=array([9.252107, 1. ])), candidate_index=53, candidate_x=array([6.13394911, 1.03978719]), index=52, x=array([6.3769814 , 1.03855253]), fval=0.5426853573405204, rho=-4.2277721907011685, accepted=False, new_indices=array([], dtype=int32), old_indices_used=array([41, 44, 46, 47, 48, 49, 50, 51, 52]), old_indices_discarded=array([ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, + 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, + 34, 35, 36, 37, 38, 39, 40, 42, 43, 45]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([6.3769814 , 1.03855253]), radius=0.9252106996349743, bounds=Bounds(lower=array([1.1, 0.5]), upper=array([20. , 1.1]))), model_indices=array([44, 46, 47, 48, 49, 50, 51, 52, 53]), model=ScalarModel(intercept=15.125592672308542, linear_terms=array([ -0.92742527, -36.66916769]), square_terms=array([[4.28554863e-02, 1.16804426e+00], + [1.16804426e+00, 4.61029190e+01]]), scale=array([0.81994663, 0.3 ]), shift=array([6.3769814, 0.8 ])), vector_model=VectorModel(intercepts=array([ 0.04871065, 0.12404049, 0.14884012, 0.19380771, 0.21739522, + 0.23240935, 0.23334521, 0.06700373, -0.08020904, -0.06714673, + -0.40907425, -0.41756644, -0.12515654, -0.09879383, -0.08942031, + -0.09320124, -0.09958839]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=0.9252106996349743, shift=array([9.252107, 1. ])), candidate_index=54, candidate_x=array([6.27747973, 1.03953523]), index=52, x=array([6.3769814 , 1.03855253]), fval=0.5426853573405204, rho=-13.31771442582917, accepted=False, new_indices=array([], dtype=int32), old_indices_used=array([44, 46, 47, 48, 49, 50, 51, 52, 53]), old_indices_discarded=array([ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, + 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, + 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 45]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([6.3769814 , 1.03855253]), radius=0.46260534981748713, bounds=Bounds(lower=array([1.1, 0.5]), upper=array([20. , 1.1]))), model_indices=array([46, 47, 48, 49, 50, 51, 52, 53, 54]), model=ScalarModel(intercept=10.065029563372587, linear_terms=array([ -0.39719221, -25.86425371]), square_terms=array([[1.16915302e-02, 5.40173955e-01], + [5.40173955e-01, 3.51273033e+01]]), scale=array([0.40997332, 0.23571039]), shift=array([6.3769814 , 0.86428961])), vector_model=VectorModel(intercepts=array([ 0.04871065, 0.12404049, 0.14884012, 0.19380771, 0.21739522, + 0.23240935, 0.23334521, 0.06700373, -0.08020904, -0.06714673, + -0.40907425, -0.41756644, -0.12515654, -0.09879383, -0.08942031, + -0.09320124, -0.09958839]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=0.9252106996349743, shift=array([9.252107, 1. ])), candidate_index=55, candidate_x=array([6.31179845, 1.0384196 ]), index=52, x=array([6.3769814 , 1.03855253]), fval=0.5426853573405204, rho=-0.784363594729585, accepted=False, new_indices=array([], dtype=int32), old_indices_used=array([46, 47, 48, 49, 50, 51, 52, 53, 54]), old_indices_discarded=array([ 1, 3, 7, 10, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, + 43, 44, 45]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([6.3769814 , 1.03855253]), radius=0.23130267490874357, bounds=Bounds(lower=array([1.1, 0.5]), upper=array([20. , 1.1]))), model_indices=array([51, 52, 53, 54, 55]), model=ScalarModel(intercept=2.3920584590081724, linear_terms=array([-0.08950127, -6.81205893]), square_terms=array([[3.19260557e-03, 1.63216758e-01], + [1.63216758e-01, 1.25472782e+01]]), scale=array([0.20498666, 0.13321706]), shift=array([6.3769814 , 0.96678294])), vector_model=VectorModel(intercepts=array([ 0.04871065, 0.12404049, 0.14884012, 0.19380771, 0.21739522, + 0.23240935, 0.23334521, 0.06700373, -0.08020904, -0.06714673, + -0.40907425, -0.41756644, -0.12515654, -0.09879383, -0.08942031, + -0.09320124, -0.09958839]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=0.9252106996349743, shift=array([9.252107, 1. ])), candidate_index=56, candidate_x=array([6.54738856, 1.0376674 ]), index=56, x=array([6.54738856, 1.0376674 ]), fval=0.5422070151116223, rho=0.9994517465051278, accepted=True, new_indices=array([], dtype=int32), old_indices_used=array([51, 52, 53, 54, 55]), old_indices_discarded=array([], dtype=int32), step_length=0.17040945911786537, relative_step_length=0.7367379524905946, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([6.54738856, 1.0376674 ]), radius=0.46260534981748713, bounds=Bounds(lower=array([1.1, 0.5]), upper=array([20. , 1.1]))), model_indices=array([47, 48, 50, 51, 52, 53, 54, 55, 56]), model=ScalarModel(intercept=12.845919206247771, linear_terms=array([ -0.48580072, -33.75567653]), square_terms=array([[1.32030757e-02, 6.68795751e-01], + [6.68795751e-01, 4.63083580e+01]]), scale=array([0.40997332, 0.23615296]), shift=array([6.54738856, 0.86384704])), vector_model=VectorModel(intercepts=array([ 0.04871065, 0.12404049, 0.14884012, 0.19380771, 0.21739522, + 0.23240935, 0.23334521, 0.06700373, -0.08020904, -0.06714673, + -0.40907425, -0.41756644, -0.12515654, -0.09879383, -0.08942031, + -0.09320124, -0.09958839]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 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model=ScalarModel(intercept=2.0362311686925794, linear_terms=array([-0.07626161, -5.56401149]), square_terms=array([[2.97339012e-03, 1.42670586e-01], + [1.42670586e-01, 1.03610380e+01]]), scale=array([0.20498666, 0.13365963]), shift=array([6.54738856, 0.96634037])), vector_model=VectorModel(intercepts=array([ 0.04871065, 0.12404049, 0.14884012, 0.19380771, 0.21739522, + 0.23240935, 0.23334521, 0.06700373, -0.08020904, -0.06714673, + -0.40907425, -0.41756644, -0.12515654, -0.09879383, -0.08942031, + -0.09320124, -0.09958839]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + 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linear_terms=array([-0.01427721, -1.59977577]), square_terms=array([[8.28292861e-04, 6.05950908e-02], + [6.05950908e-02, 7.01428649e+00]]), scale=array([0.10249333, 0.08241296]), shift=array([6.54738856, 1.01758704])), vector_model=VectorModel(intercepts=array([ 0.04871065, 0.12404049, 0.14884012, 0.19380771, 0.21739522, + 0.23240935, 0.23334521, 0.06700373, -0.08020904, -0.06714673, + -0.40907425, -0.41756644, -0.12515654, -0.09879383, -0.08942031, + -0.09320124, -0.09958839]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 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square_terms=array([[3.29232175e-03, 1.89561505e-01], + [1.89561505e-01, 1.70827528e+01]]), scale=array([0.20498666, 0.13397188]), shift=array([6.53909631, 0.96602812])), vector_model=VectorModel(intercepts=array([ 0.04871065, 0.12404049, 0.14884012, 0.19380771, 0.21739522, + 0.23240935, 0.23334521, 0.06700373, -0.08020904, -0.06714673, + -0.40907425, -0.41756644, -0.12515654, -0.09879383, -0.08942031, + -0.09320124, -0.09958839]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + 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6.53773842e+00]]), scale=array([0.10249333, 0.08272521]), shift=array([6.53909631, 1.01727479])), vector_model=VectorModel(intercepts=array([ 0.04871065, 0.12404049, 0.14884012, 0.19380771, 0.21739522, + 0.23240935, 0.23334521, 0.06700373, -0.08020904, -0.06714673, + -0.40907425, -0.41756644, -0.12515654, -0.09879383, -0.08942031, + -0.09320124, -0.09958839]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + 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0.13452982]), shift=array([6.61897887, 0.96547018])), vector_model=VectorModel(intercepts=array([ 0.04871065, 0.12404049, 0.14884012, 0.19380771, 0.21739522, + 0.23240935, 0.23334521, 0.06700373, -0.08020904, -0.06714673, + -0.40907425, -0.41756644, -0.12515654, -0.09879383, -0.08942031, + -0.09320124, -0.09958839]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=0.9252106996349743, shift=array([9.252107, 1. ])), candidate_index=64, candidate_x=array([6.76282269, 1.03712945]), index=62, x=array([6.61897887, 1.03592701]), fval=0.5415174113025932, rho=-0.822486077235511, accepted=False, new_indices=array([63]), old_indices_used=array([52, 56, 57, 58, 59, 60, 61, 62]), old_indices_discarded=array([50, 51, 53, 54, 55]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([6.61897887, 1.03592701]), radius=0.11565133745437178, bounds=Bounds(lower=array([1.1, 0.5]), upper=array([20. , 1.1]))), model_indices=array([52, 56, 58, 59, 60, 61, 62, 63, 64]), model=ScalarModel(intercept=0.8537489797787152, linear_terms=array([-0.02180749, -2.41772558]), square_terms=array([[1.03255446e-03, 8.41806686e-02], + [8.41806686e-02, 9.32527369e+00]]), scale=array([0.10249333, 0.08328316]), shift=array([6.61897887, 1.01671684])), vector_model=VectorModel(intercepts=array([ 0.04871065, 0.12404049, 0.14884012, 0.19380771, 0.21739522, + 0.23240935, 0.23334521, 0.06700373, -0.08020904, -0.06714673, + -0.40907425, -0.41756644, -0.12515654, -0.09879383, -0.08942031, + -0.09320124, -0.09958839]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=0.9252106996349743, shift=array([9.252107, 1. ])), candidate_index=65, candidate_x=array([6.61232843, 1.03835811]), index=62, x=array([6.61897887, 1.03592701]), fval=0.5415174113025932, rho=-0.7324310982234294, accepted=False, new_indices=array([], dtype=int32), old_indices_used=array([52, 56, 58, 59, 60, 61, 62, 63, 64]), old_indices_discarded=array([51, 53, 54, 55, 57]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([6.61897887, 1.03592701]), radius=0.05782566872718589, bounds=Bounds(lower=array([1.1, 0.5]), upper=array([20. , 1.1]))), model_indices=array([56, 58, 59, 60, 61, 62, 63, 64, 65]), model=ScalarModel(intercept=0.5447400521949106, linear_terms=array([-0.00137124, -0.18835934]), square_terms=array([[3.31269825e-04, 3.32990005e-02], + [3.32990005e-02, 4.49770488e+00]]), scale=0.05782566872718589, shift=array([6.61897887, 1.03592701])), vector_model=VectorModel(intercepts=array([ 0.04871065, 0.12404049, 0.14884012, 0.19380771, 0.21739522, + 0.23240935, 0.23334521, 0.06700373, -0.08020904, -0.06714673, + -0.40907425, -0.41756644, -0.12515654, -0.09879383, -0.08942031, + -0.09320124, -0.09958839]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=0.9252106996349743, shift=array([9.252107, 1. ])), candidate_index=66, candidate_x=array([6.56122348, 1.03877707]), index=62, x=array([6.61897887, 1.03592701]), fval=0.5415174113025932, rho=-0.7212604565703155, accepted=False, new_indices=array([], dtype=int32), old_indices_used=array([56, 58, 59, 60, 61, 62, 63, 64, 65]), old_indices_discarded=array([52, 57]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([6.61897887, 1.03592701]), radius=0.028912834363592946, bounds=Bounds(lower=array([1.1, 0.5]), upper=array([20. , 1.1]))), model_indices=array([56, 58, 59, 60, 61, 62, 64, 65, 66]), model=ScalarModel(intercept=0.5416031178062954, linear_terms=array([4.51099211e-05, 1.50726294e-03]), square_terms=array([[6.53193566e-05, 5.88023268e-03], + [5.88023268e-03, 7.83342000e-01]]), scale=0.028912834363592946, shift=array([6.61897887, 1.03592701])), vector_model=VectorModel(intercepts=array([ 0.04871065, 0.12404049, 0.14884012, 0.19380771, 0.21739522, + 0.23240935, 0.23334521, 0.06700373, -0.08020904, -0.06714673, + -0.40907425, -0.41756644, -0.12515654, -0.09879383, -0.08942031, + -0.09320124, -0.09958839]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=0.9252106996349743, shift=array([9.252107, 1. ])), candidate_index=67, candidate_x=array([6.59006647, 1.03608841]), index=67, x=array([6.59006647, 1.03608841]), fval=0.5414379715211688, rho=3.2219246695022767, accepted=True, new_indices=array([], dtype=int32), old_indices_used=array([56, 58, 59, 60, 61, 62, 64, 65, 66]), old_indices_discarded=array([], dtype=int32), step_length=0.028912851176776357, relative_step_length=1.000000581512805, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([6.59006647, 1.03608841]), radius=0.05782566872718589, bounds=Bounds(lower=array([1.1, 0.5]), upper=array([20. , 1.1]))), model_indices=array([56, 58, 59, 60, 61, 62, 65, 66, 67]), model=ScalarModel(intercept=0.5415547803952224, linear_terms=array([ 1.01377641e-05, -3.95364543e-05]), square_terms=array([[2.63397868e-04, 2.35619632e-02], + [2.35619632e-02, 3.13951084e+00]]), scale=0.05782566872718589, shift=array([6.59006647, 1.03608841])), vector_model=VectorModel(intercepts=array([ 0.04871065, 0.12404049, 0.14884012, 0.19380771, 0.21739522, + 0.23240935, 0.23334521, 0.06700373, -0.08020904, -0.06714673, + -0.40907425, -0.41756644, -0.12515654, -0.09879383, -0.08942031, + -0.09320124, -0.09958839]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=0.9252106996349743, shift=array([9.252107, 1. ])), candidate_index=68, candidate_x=array([6.58309627, 1.03614145]), index=68, x=array([6.58309627, 1.03614145]), fval=0.5414293228153648, rho=13.747183659712503, accepted=True, new_indices=array([], dtype=int32), old_indices_used=array([56, 58, 59, 60, 61, 62, 65, 66, 67]), old_indices_discarded=array([52, 55, 57, 63, 64]), step_length=0.0069704007281480235, relative_step_length=0.1205416362936239, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([6.58309627, 1.03614145]), radius=0.05782566872718589, bounds=Bounds(lower=array([1.1, 0.5]), upper=array([20. , 1.1]))), model_indices=array([56, 59, 60, 61, 62, 65, 66, 67, 68]), model=ScalarModel(intercept=0.5414796419298218, linear_terms=array([0.00011312, 0.00042998]), square_terms=array([[2.70149950e-04, 2.41187611e-02], + [2.41187611e-02, 3.15020230e+00]]), scale=0.05782566872718589, shift=array([6.58309627, 1.03614145])), vector_model=VectorModel(intercepts=array([ 0.04871065, 0.12404049, 0.14884012, 0.19380771, 0.21739522, + 0.23240935, 0.23334521, 0.06700373, -0.08020904, -0.06714673, + -0.40907425, -0.41756644, -0.12515654, -0.09879383, -0.08942031, + -0.09320124, -0.09958839]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=0.9252106996349743, shift=array([9.252107, 1. ])), candidate_index=69, candidate_x=array([6.52527224, 1.03657627]), index=68, x=array([6.58309627, 1.03614145]), fval=0.5414293228153648, rho=-2.4940420439925477, accepted=False, new_indices=array([], dtype=int32), old_indices_used=array([56, 59, 60, 61, 62, 65, 66, 67, 68]), old_indices_discarded=array([52, 55, 57, 58, 63, 64]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([6.58309627, 1.03614145]), radius=0.028912834363592946, bounds=Bounds(lower=array([1.1, 0.5]), upper=array([20. , 1.1]))), model_indices=array([56, 59, 60, 62, 65, 66, 67, 68, 69]), model=ScalarModel(intercept=0.5415011318321497, linear_terms=array([ 1.74351890e-05, -2.75129179e-04]), square_terms=array([[6.75592967e-05, 6.01725598e-03], + [6.01725598e-03, 7.88582554e-01]]), scale=0.028912834363592946, shift=array([6.58309627, 1.03614145])), vector_model=VectorModel(intercepts=array([ 0.04871065, 0.12404049, 0.14884012, 0.19380771, 0.21739522, + 0.23240935, 0.23334521, 0.06700373, -0.08020904, -0.06714673, + -0.40907425, -0.41756644, -0.12515654, -0.09879383, -0.08942031, + -0.09320124, -0.09958839]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=0.9252106996349743, shift=array([9.252107, 1. ])), candidate_index=70, candidate_x=array([6.55418436, 1.03637223]), index=68, x=array([6.58309627, 1.03614145]), fval=0.5414293228153648, rho=-11.73867706052995, accepted=False, new_indices=array([], dtype=int32), old_indices_used=array([56, 59, 60, 62, 65, 66, 67, 68, 69]), old_indices_discarded=array([58, 61]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([6.58309627, 1.03614145]), radius=0.014456417181796473, bounds=Bounds(lower=array([1.1, 0.5]), upper=array([20. , 1.1]))), model_indices=array([56, 60, 62, 65, 66, 67, 68, 69, 70]), model=ScalarModel(intercept=0.5414799019531137, linear_terms=array([-3.44991235e-06, -9.05048244e-05]), square_terms=array([[1.67238718e-05, 1.49276761e-03], + [1.49276761e-03, 1.97781855e-01]]), scale=0.014456417181796473, shift=array([6.58309627, 1.03614145])), vector_model=VectorModel(intercepts=array([ 0.04871065, 0.12404049, 0.14884012, 0.19380771, 0.21739522, + 0.23240935, 0.23334521, 0.06700373, -0.08020904, -0.06714673, + -0.40907425, -0.41756644, -0.12515654, -0.09879383, -0.08942031, + -0.09320124, -0.09958839]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=0.9252106996349743, shift=array([9.252107, 1. ])), candidate_index=71, candidate_x=array([6.59042582, 1.03609275]), index=68, x=array([6.58309627, 1.03614145]), fval=0.5414293228153648, rho=-21.95038108304595, accepted=False, new_indices=array([], dtype=int32), old_indices_used=array([56, 60, 62, 65, 66, 67, 68, 69, 70]), old_indices_discarded=array([59]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([6.58309627, 1.03614145]), radius=0.0072282085908982364, bounds=Bounds(lower=array([1.1, 0.5]), upper=array([20. , 1.1]))), model_indices=array([56, 62, 65, 66, 67, 68, 70, 71]), model=ScalarModel(intercept=0.5414632259336039, linear_terms=array([2.83264621e-06, 2.05882321e-05]), square_terms=array([[4.16386161e-06, 3.73300224e-04], + [3.73300224e-04, 4.94351827e-02]]), scale=0.0072282085908982364, shift=array([6.58309627, 1.03614145])), vector_model=VectorModel(intercepts=array([ 0.04871065, 0.12404049, 0.14884012, 0.19380771, 0.21739522, + 0.23240935, 0.23334521, 0.06700373, -0.08020904, -0.06714673, + -0.40907425, -0.41756644, -0.12515654, -0.09879383, -0.08942031, + -0.09320124, -0.09958839]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 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relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([6.58309627, 1.03614145]), radius=0.0036141042954491182, bounds=Bounds(lower=array([1.1, 0.5]), upper=array([20. , 1.1]))), model_indices=array([67, 68, 71, 72]), model=ScalarModel(intercept=0.5414388981465452, linear_terms=array([2.71386294e-05, 3.84330426e-03]), square_terms=array([[1.04795962e-06, 9.32698230e-05], + [9.32698230e-05, 1.23060327e-02]]), scale=0.0036141042954491182, shift=array([6.58309627, 1.03614145])), vector_model=VectorModel(intercepts=array([ 0.04871065, 0.12404049, 0.14884012, 0.19380771, 0.21739522, + 0.23240935, 0.23334521, 0.06700373, -0.08020904, -0.06714673, + -0.40907425, -0.41756644, -0.12515654, -0.09879383, -0.08942031, + -0.09320124, -0.09958839]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + 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State(trustregion=Region(center=array([6.58309627, 1.03614145]), radius=0.0018070521477245591, bounds=Bounds(lower=array([1.1, 0.5]), upper=array([20. , 1.1]))), model_indices=array([67, 68, 71, 72, 73]), model=ScalarModel(intercept=0.5414389397529535, linear_terms=array([3.45115217e-07, 6.30331745e-05]), square_terms=array([[2.70925737e-07, 2.39729562e-05], + [2.39729562e-05, 3.08425190e-03]]), scale=0.0018070521477245591, shift=array([6.58309627, 1.03614145])), vector_model=VectorModel(intercepts=array([ 0.04871065, 0.12404049, 0.14884012, 0.19380771, 0.21739522, + 0.23240935, 0.23334521, 0.06700373, -0.08020904, -0.06714673, + -0.40907425, -0.41756644, -0.12515654, -0.09879383, -0.08942031, + -0.09320124, -0.09958839]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], 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bounds=Bounds(lower=array([1.1, 0.5]), upper=array([20. , 1.1]))), model_indices=array([68, 73, 74]), model=ScalarModel(intercept=0.541429322815365, linear_terms=array([1.41688629e-05, 6.76977808e-05]), square_terms=array([[6.26837304e-08, 5.47876928e-06], + [5.47876928e-06, 7.68259730e-04]]), scale=0.0009035260738622796, shift=array([6.58309627, 1.03614145])), vector_model=VectorModel(intercepts=array([ 0.04871065, 0.12404049, 0.14884012, 0.19380771, 0.21739522, + 0.23240935, 0.23334521, 0.06700373, -0.08020904, -0.06714673, + -0.40907425, -0.41756644, -0.12515654, -0.09879383, -0.08942031, + -0.09320124, -0.09958839]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + 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model=ScalarModel(intercept=0.5414293228153648, linear_terms=array([-2.29729551e-06, -2.98650390e-04]), square_terms=array([[1.73350246e-08, 1.53237458e-06], + [1.53237458e-06, 2.01506003e-04]]), scale=0.0004517630369311398, shift=array([6.58309627, 1.03614145])), vector_model=VectorModel(intercepts=array([ 0.04871065, 0.12404049, 0.14884012, 0.19380771, 0.21739522, + 0.23240935, 0.23334521, 0.06700373, -0.08020904, -0.06714673, + -0.40907425, -0.41756644, -0.12515654, -0.09879383, -0.08942031, + -0.09320124, -0.09958839]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + 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square_terms=array([[5.97250724e-09, 4.20181109e-07], + [4.20181109e-07, 4.91845731e-05]]), scale=0.0002258815184655699, shift=array([6.58309627, 1.03614145])), vector_model=VectorModel(intercepts=array([ 0.04871065, 0.12404049, 0.14884012, 0.19380771, 0.21739522, + 0.23240935, 0.23334521, 0.06700373, -0.08020904, -0.06714673, + -0.40907425, -0.41756644, -0.12515654, -0.09879383, -0.08942031, + -0.09320124, -0.09958839]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 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scale=0.00011294075923278494, shift=array([6.58309627, 1.03614145])), vector_model=VectorModel(intercepts=array([ 0.04871065, 0.12404049, 0.14884012, 0.19380771, 0.21739522, + 0.23240935, 0.23334521, 0.06700373, -0.08020904, -0.06714673, + -0.40907425, -0.41756644, -0.12515654, -0.09879383, -0.08942031, + -0.09320124, -0.09958839]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=0.9252106996349743, shift=array([9.252107, 1. ])), candidate_index=78, candidate_x=array([6.58300196, 1.03607308]), index=68, x=array([6.58309627, 1.03614145]), fval=0.5414293228153648, rho=-0.9288183820802519, accepted=False, new_indices=array([], dtype=int32), old_indices_used=array([68, 76, 77]), old_indices_discarded=array([], dtype=int32), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([6.58309627, 1.03614145]), radius=5.647037961639247e-05, bounds=Bounds(lower=array([1.1, 0.5]), upper=array([20. , 1.1]))), model_indices=array([68, 77, 78]), model=ScalarModel(intercept=0.5414293228153648, linear_terms=array([-1.22674426e-05, -2.40256385e-05]), square_terms=array([[1.26112163e-09, 5.06903136e-08], + [5.06903136e-08, 3.10638384e-06]]), scale=5.647037961639247e-05, shift=array([6.58309627, 1.03614145])), vector_model=VectorModel(intercepts=array([ 0.04871065, 0.12404049, 0.14884012, 0.19380771, 0.21739522, + 0.23240935, 0.23334521, 0.06700373, -0.08020904, -0.06714673, + -0.40907425, -0.41756644, -0.12515654, -0.09879383, -0.08942031, + -0.09320124, -0.09958839]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=0.9252106996349743, shift=array([9.252107, 1. ])), candidate_index=79, candidate_x=array([6.58311861, 1.03619332]), index=68, x=array([6.58309627, 1.03614145]), fval=0.5414293228153648, rho=-0.12812387344724027, accepted=False, new_indices=array([], dtype=int32), old_indices_used=array([68, 77, 78]), old_indices_discarded=array([], dtype=int32), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([6.58309627, 1.03614145]), radius=2.8235189808196236e-05, bounds=Bounds(lower=array([1.1, 0.5]), upper=array([20. , 1.1]))), model_indices=array([68, 78, 79]), model=ScalarModel(intercept=0.541429322815365, linear_terms=array([-2.27116547e-05, 1.08555655e-05]), square_terms=array([[4.35976955e-09, 1.69031789e-08], + [1.69031789e-08, 7.57228023e-07]]), scale=2.8235189808196236e-05, shift=array([6.58309627, 1.03614145])), vector_model=VectorModel(intercepts=array([ 0.04871065, 0.12404049, 0.14884012, 0.19380771, 0.21739522, + 0.23240935, 0.23334521, 0.06700373, -0.08020904, -0.06714673, + -0.40907425, -0.41756644, -0.12515654, -0.09879383, -0.08942031, + -0.09320124, -0.09958839]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=0.9252106996349743, shift=array([9.252107, 1. ])), candidate_index=80, candidate_x=array([6.58312214, 1.03612944]), index=68, x=array([6.58309627, 1.03614145]), fval=0.5414293228153648, rho=-0.35421190384338624, accepted=False, new_indices=array([], dtype=int32), old_indices_used=array([68, 78, 79]), old_indices_discarded=array([], dtype=int32), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([6.58309627, 1.03614145]), radius=1.4117594904098118e-05, bounds=Bounds(lower=array([1.1, 0.5]), upper=array([20. , 1.1]))), model_indices=array([68, 79, 80]), model=ScalarModel(intercept=0.541429322815365, linear_terms=array([ 4.26256780e-06, -1.29794683e-06]), square_terms=array([[1.87697604e-10, 7.48543093e-10], + [7.48543093e-10, 1.92469128e-07]]), scale=1.4117594904098118e-05, shift=array([6.58309627, 1.03614145])), vector_model=VectorModel(intercepts=array([ 0.04871065, 0.12404049, 0.14884012, 0.19380771, 0.21739522, + 0.23240935, 0.23334521, 0.06700373, -0.08020904, -0.06714673, + -0.40907425, -0.41756644, -0.12515654, -0.09879383, -0.08942031, + -0.09320124, -0.09958839]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=0.9252106996349743, shift=array([9.252107, 1. ])), candidate_index=81, candidate_x=array([6.58308246, 1.03614548]), index=81, x=array([6.58308246, 1.03614548]), fval=0.5414254298290705, rho=0.85915882442786, accepted=True, new_indices=array([], dtype=int32), old_indices_used=array([68, 79, 80]), old_indices_discarded=array([], dtype=int32), step_length=1.4381793867319074e-05, relative_step_length=1.018714162363751, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([6.58308246, 1.03614548]), radius=2.8235189808196236e-05, bounds=Bounds(lower=array([1.1, 0.5]), upper=array([20. , 1.1]))), model_indices=array([68, 78, 79, 80, 81]), model=ScalarModel(intercept=0.5414393336189507, linear_terms=array([-6.83138000e-06, -5.43556504e-06]), square_terms=array([[8.38980666e-10, 1.12053013e-08], + [1.12053013e-08, 7.72680051e-07]]), scale=2.8235189808196236e-05, shift=array([6.58308246, 1.03614548])), vector_model=VectorModel(intercepts=array([ 0.04871065, 0.12404049, 0.14884012, 0.19380771, 0.21739522, + 0.23240935, 0.23334521, 0.06700373, -0.08020904, -0.06714673, + -0.40907425, -0.41756644, -0.12515654, -0.09879383, -0.08942031, + -0.09320124, -0.09958839]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + 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old_indices_discarded=array([], dtype=int32), step_length=2.8574644124841038e-05, relative_step_length=1.0120223847953826, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([6.58310557, 1.03616229]), radius=5.647037961639247e-05, bounds=Bounds(lower=array([1.1, 0.5]), upper=array([20. , 1.1]))), model_indices=array([68, 77, 78, 79, 80, 81, 82]), model=ScalarModel(intercept=0.5414289185236869, linear_terms=array([-9.17816477e-06, -1.57462672e-05]), square_terms=array([[1.32415510e-09, 4.69483871e-08], + [4.69483871e-08, 3.08710853e-06]]), scale=5.647037961639247e-05, shift=array([6.58310557, 1.03616229])), vector_model=VectorModel(intercepts=array([ 0.04871065, 0.12404049, 0.14884012, 0.19380771, 0.21739522, + 0.23240935, 0.23334521, 0.06700373, -0.08020904, -0.06714673, + -0.40907425, -0.41756644, -0.12515654, -0.09879383, -0.08942031, + -0.09320124, -0.09958839]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], 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step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([6.58310557, 1.03616229]), radius=2.8235189808196236e-05, bounds=Bounds(lower=array([1.1, 0.5]), upper=array([20. , 1.1]))), model_indices=array([68, 78, 79, 80, 81, 82, 83]), model=ScalarModel(intercept=0.541436888279065, linear_terms=array([-1.16278729e-05, 4.19591953e-06]), square_terms=array([[9.75111772e-10, 1.22776981e-08], + [1.22776981e-08, 7.67636851e-07]]), scale=2.8235189808196236e-05, shift=array([6.58310557, 1.03616229])), vector_model=VectorModel(intercepts=array([ 0.04871065, 0.12404049, 0.14884012, 0.19380771, 0.21739522, + 0.23240935, 0.23334521, 0.06700373, -0.08020904, -0.06714673, + -0.40907425, -0.41756644, -0.12515654, -0.09879383, -0.08942031, + -0.09320124, -0.09958839]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 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n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([6.58313299, 1.03615297]), radius=5.647037961639247e-05, bounds=Bounds(lower=array([1.1, 0.5]), upper=array([20. , 1.1]))), model_indices=array([68, 77, 78, 79, 80, 81, 82, 83, 84]), model=ScalarModel(intercept=0.5414339494417576, linear_terms=array([-6.40143056e-06, -9.29451992e-06]), square_terms=array([[1.23223241e-09, 4.52561651e-08], + [4.52561651e-08, 3.07989367e-06]]), scale=5.647037961639247e-05, shift=array([6.58313299, 1.03615297])), vector_model=VectorModel(intercepts=array([ 0.04871065, 0.12404049, 0.14884012, 0.19380771, 0.21739522, + 0.23240935, 0.23334521, 0.06700373, -0.08020904, -0.06714673, + -0.40907425, -0.41756644, -0.12515654, -0.09879383, -0.08942031, + -0.09320124, -0.09958839]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 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State(trustregion=Region(center=array([6.58313299, 1.03615297]), radius=2.8235189808196236e-05, bounds=Bounds(lower=array([1.1, 0.5]), upper=array([20. , 1.1]))), model_indices=array([68, 79, 80, 81, 82, 83, 84, 85]), model=ScalarModel(intercept=0.5414281500618983, linear_terms=array([-1.16204997e-06, 6.18900498e-06]), square_terms=array([[1.57251918e-10, 5.33198393e-09], + [5.33198393e-09, 7.67778577e-07]]), scale=2.8235189808196236e-05, shift=array([6.58313299, 1.03615297])), vector_model=VectorModel(intercepts=array([ 0.04871065, 0.12404049, 0.14884012, 0.19380771, 0.21739522, + 0.23240935, 0.23334521, 0.06700373, -0.08020904, -0.06714673, + -0.40907425, -0.41756644, -0.12515654, -0.09879383, -0.08942031, + -0.09320124, -0.09958839]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 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radius=1.4117594904098118e-05, bounds=Bounds(lower=array([1.1, 0.5]), upper=array([20. , 1.1]))), model_indices=array([68, 79, 80, 81, 82, 83, 84, 85, 86]), model=ScalarModel(intercept=0.5414321282300018, linear_terms=array([7.70313832e-07, 1.49903860e-06]), square_terms=array([[3.81938577e-11, 1.20494137e-09], + [1.20494137e-09, 1.92248508e-07]]), scale=1.4117594904098118e-05, shift=array([6.58313299, 1.03615297])), vector_model=VectorModel(intercepts=array([ 0.04871065, 0.12404049, 0.14884012, 0.19380771, 0.21739522, + 0.23240935, 0.23334521, 0.06700373, -0.08020904, -0.06714673, + -0.40907425, -0.41756644, -0.12515654, -0.09879383, -0.08942031, + -0.09320124, -0.09958839]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + 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square_terms=array([[0.07792252, 0.32866092], + [0.32866092, 1.49842941]]), scale=0.05921813970334309, shift=array([9.47490235, 0.99993647])), vector_model=VectorModel(intercepts=array([ 0.0503911 , 0.12838033, 0.15541499, 0.20185793, 0.22718579, + 0.24311703, 0.24583074, 0.08262932, -0.06406015, -0.05102962, + -0.39325651, -0.40243304, -0.13275181, -0.10596104, -0.09671903, + -0.10022582, -0.10660703]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + 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[[0., 0.], + [0., 0.]]]), scale=0.9474902352534894, shift=array([9.47490235, 0.99993647])), candidate_index=18, candidate_x=array([9.50661188, 1.0031676 ]), index=18, x=array([9.50661188, 1.0031676 ]), fval=0.6396317123330025, rho=0.05607187891543219, accepted=True, new_indices=array([], dtype=int32), old_indices_used=array([ 0, 12, 16, 17]), old_indices_discarded=array([], dtype=int32), step_length=0.03187372417953975, relative_step_length=1.0764851560421564, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([9.50661188, 1.0031676 ]), radius=0.014804534925835772, bounds=Bounds(lower=array([1.1, 0.5]), upper=array([20. , 1.1]))), model_indices=array([ 0, 17, 18]), model=ScalarModel(intercept=0.6396317123330028, linear_terms=array([ 0.00028177, -0.01430195]), square_terms=array([[2.43882216e-05, 1.35799469e-03], + [1.35799469e-03, 8.34202654e-02]]), scale=0.014804534925835772, shift=array([9.50661188, 1.0031676 ])), vector_model=VectorModel(intercepts=array([ 0.0503911 , 0.12838033, 0.15541499, 0.20185793, 0.22718579, + 0.24311703, 0.24583074, 0.08262932, -0.06406015, -0.05102962, + -0.39325651, -0.40243304, -0.13275181, -0.10596104, -0.09671903, + -0.10022582, -0.10660703]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=0.9474902352534894, shift=array([9.47490235, 0.99993647])), candidate_index=19, candidate_x=array([9.49185035, 1.0059291 ]), index=19, x=array([9.49185035, 1.0059291 ]), fval=0.6370780738825652, rho=1.4693827516516844, accepted=True, new_indices=array([], dtype=int32), old_indices_used=array([ 0, 17, 18]), old_indices_discarded=array([], dtype=int32), step_length=0.015017609941676606, relative_step_length=1.0143925504521585, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([9.49185035, 1.0059291 ]), radius=0.029609069851671544, bounds=Bounds(lower=array([1.1, 0.5]), upper=array([20. , 1.1]))), model_indices=array([ 0, 12, 16, 17, 18, 19]), model=ScalarModel(intercept=0.6412257536348447, linear_terms=array([-0.06905576, -0.03758833]), square_terms=array([[0.03588925, 0.1094543 ], + [0.1094543 , 0.37040144]]), scale=0.029609069851671544, shift=array([9.49185035, 1.0059291 ])), vector_model=VectorModel(intercepts=array([ 0.0503911 , 0.12838033, 0.15541499, 0.20185793, 0.22718579, + 0.24311703, 0.24583074, 0.08262932, -0.06406015, -0.05102962, + -0.39325651, -0.40243304, -0.13275181, -0.10596104, -0.09671903, + -0.10022582, -0.10660703]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=0.9474902352534894, shift=array([9.47490235, 0.99993647])), candidate_index=20, candidate_x=array([9.52125862, 1.00094573]), index=19, x=array([9.49185035, 1.0059291 ]), fval=0.6370780738825652, rho=-0.11096998055275568, accepted=False, new_indices=array([], dtype=int32), old_indices_used=array([ 0, 12, 16, 17, 18, 19]), old_indices_discarded=array([], dtype=int32), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([9.49185035, 1.0059291 ]), radius=0.014804534925835772, bounds=Bounds(lower=array([1.1, 0.5]), upper=array([20. , 1.1]))), model_indices=array([ 0, 17, 18, 19, 20]), model=ScalarModel(intercept=0.6375966987395302, linear_terms=array([ 0.00059101, -0.00033053]), square_terms=array([[2.18308578e-05, 1.28615347e-03], + [1.28615347e-03, 8.40653356e-02]]), scale=0.014804534925835772, shift=array([9.49185035, 1.0059291 ])), vector_model=VectorModel(intercepts=array([ 0.0503911 , 0.12838033, 0.15541499, 0.20185793, 0.22718579, + 0.24311703, 0.24583074, 0.08262932, -0.06406015, -0.05102962, + -0.39325651, -0.40243304, -0.13275181, -0.10596104, -0.09671903, + -0.10022582, -0.10660703]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=0.9474902352534894, shift=array([9.47490235, 0.99993647])), candidate_index=21, candidate_x=array([9.47704841, 1.00621177]), index=21, x=array([9.47704841, 1.00621177]), fval=0.6363070785814076, rho=1.2946325204884988, accepted=True, new_indices=array([], dtype=int32), old_indices_used=array([ 0, 17, 18, 19, 20]), old_indices_discarded=array([], dtype=int32), step_length=0.01480464158988585, relative_step_length=1.0000072048227528, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([9.47704841, 1.00621177]), radius=0.029609069851671544, bounds=Bounds(lower=array([1.1, 0.5]), upper=array([20. , 1.1]))), model_indices=array([ 0, 12, 16, 17, 18, 19, 20, 21]), model=ScalarModel(intercept=0.6740948994884155, linear_terms=array([-0.0775299 , -0.08137508]), square_terms=array([[0.03091198, 0.10157856], + [0.10157856, 0.37039842]]), scale=0.029609069851671544, shift=array([9.47704841, 1.00621177])), vector_model=VectorModel(intercepts=array([ 0.0503911 , 0.12838033, 0.15541499, 0.20185793, 0.22718579, + 0.24311703, 0.24583074, 0.08262932, -0.06406015, -0.05102962, + -0.39325651, -0.40243304, -0.13275181, -0.10596104, -0.09671903, + -0.10022582, -0.10660703]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=0.9474902352534894, shift=array([9.47490235, 0.99993647])), candidate_index=22, candidate_x=array([9.50732214, 1.00462907]), index=21, x=array([9.47704841, 1.00621177]), fval=0.6363070785814076, rho=-0.029474268266789803, accepted=False, new_indices=array([], dtype=int32), old_indices_used=array([ 0, 12, 16, 17, 18, 19, 20, 21]), old_indices_discarded=array([], dtype=int32), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([9.47704841, 1.00621177]), radius=0.014804534925835772, bounds=Bounds(lower=array([1.1, 0.5]), upper=array([20. , 1.1]))), model_indices=array([ 0, 17, 18, 19, 20, 21, 22]), model=ScalarModel(intercept=0.6367076097989959, linear_terms=array([ 6.38911855e-04, -5.64861763e-05]), square_terms=array([[1.99591697e-05, 1.23030124e-03], + [1.23030124e-03, 8.44345370e-02]]), scale=0.014804534925835772, shift=array([9.47704841, 1.00621177])), vector_model=VectorModel(intercepts=array([ 0.0503911 , 0.12838033, 0.15541499, 0.20185793, 0.22718579, + 0.24311703, 0.24583074, 0.08262932, -0.06406015, -0.05102962, + -0.39325651, -0.40243304, -0.13275181, -0.10596104, -0.09671903, + -0.10022582, -0.10660703]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=0.9474902352534894, shift=array([9.47490235, 0.99993647])), candidate_index=23, candidate_x=array([9.46224557, 1.00643568]), index=23, x=array([9.46224557, 1.00643568]), fval=0.6355934835508369, rho=1.1173242341721383, accepted=True, new_indices=array([], dtype=int32), old_indices_used=array([ 0, 17, 18, 19, 20, 21, 22]), old_indices_discarded=array([], dtype=int32), step_length=0.014804537200668226, relative_step_length=1.0000001536578127, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([9.46224557, 1.00643568]), radius=0.029609069851671544, bounds=Bounds(lower=array([1.1, 0.5]), upper=array([20. , 1.1]))), model_indices=array([ 0, 12, 17, 18, 19, 20, 21, 22, 23]), model=ScalarModel(intercept=0.6376967017750665, linear_terms=array([-0.00887642, -0.07715602]), square_terms=array([[0.00091426, 0.02162778], + [0.02162778, 0.54194842]]), scale=0.029609069851671544, shift=array([9.46224557, 1.00643568])), vector_model=VectorModel(intercepts=array([ 0.0503911 , 0.12838033, 0.15541499, 0.20185793, 0.22718579, + 0.24311703, 0.24583074, 0.08262932, -0.06406015, -0.05102962, + -0.39325651, -0.40243304, -0.13275181, -0.10596104, -0.09671903, + -0.10022582, -0.10660703]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=0.9474902352534894, shift=array([9.47490235, 0.99993647])), candidate_index=24, candidate_x=array([9.49199772, 1.00943198]), index=23, x=array([9.46224557, 1.00643568]), fval=0.6355934835508369, rho=-0.23439049876600507, accepted=False, new_indices=array([], dtype=int32), old_indices_used=array([ 0, 12, 17, 18, 19, 20, 21, 22, 23]), old_indices_discarded=array([], dtype=int32), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([9.46224557, 1.00643568]), radius=0.014804534925835772, bounds=Bounds(lower=array([1.1, 0.5]), upper=array([20. , 1.1]))), model_indices=array([ 0, 17, 18, 19, 20, 21, 22, 23, 24]), model=ScalarModel(intercept=0.6357439312845821, linear_terms=array([ 0.00057539, -0.00082847]), square_terms=array([[2.06319310e-05, 1.26644672e-03], + [1.26644672e-03, 8.60694145e-02]]), scale=0.014804534925835772, shift=array([9.46224557, 1.00643568])), vector_model=VectorModel(intercepts=array([ 0.0503911 , 0.12838033, 0.15541499, 0.20185793, 0.22718579, + 0.24311703, 0.24583074, 0.08262932, -0.06406015, -0.05102962, + -0.39325651, -0.40243304, -0.13275181, -0.10596104, -0.09671903, + -0.10022582, -0.10660703]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=0.9474902352534894, shift=array([9.47490235, 0.99993647])), candidate_index=25, candidate_x=array([9.44744469, 1.00679353]), index=25, x=array([9.44744469, 1.00679353]), fval=0.6347642471305107, rho=1.4044689675006616, accepted=True, new_indices=array([], dtype=int32), old_indices_used=array([ 0, 17, 18, 19, 20, 21, 22, 23, 24]), old_indices_discarded=array([], dtype=int32), step_length=0.014805197302692493, relative_step_length=1.000044741483609, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([9.44744469, 1.00679353]), radius=0.029609069851671544, bounds=Bounds(lower=array([1.1, 0.5]), upper=array([20. , 1.1]))), model_indices=array([ 0, 18, 19, 20, 21, 22, 23, 24, 25]), model=ScalarModel(intercept=0.6347153364849043, linear_terms=array([ 0.00136442, -0.00288838]), square_terms=array([[7.21853077e-05, 4.81168593e-03], + [4.81168593e-03, 3.57552054e-01]]), scale=0.029609069851671544, shift=array([9.44744469, 1.00679353])), vector_model=VectorModel(intercepts=array([ 0.0503911 , 0.12838033, 0.15541499, 0.20185793, 0.22718579, + 0.24311703, 0.24583074, 0.08262932, -0.06406015, -0.05102962, + -0.39325651, -0.40243304, -0.13275181, -0.10596104, -0.09671903, + -0.10022582, -0.10660703]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + 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relative_step_length=1.0000319445777717, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([9.41784149, 1.00742862]), radius=0.05921813970334309, bounds=Bounds(lower=array([1.1, 0.5]), upper=array([20. , 1.1]))), model_indices=array([ 0, 18, 19, 21, 22, 23, 24, 25, 26]), model=ScalarModel(intercept=0.6332385782456339, linear_terms=array([0.0028514 , 0.00022792]), square_terms=array([[2.79552380e-04, 1.89198753e-02], + [1.89198753e-02, 1.43266898e+00]]), scale=0.05921813970334309, shift=array([9.41784149, 1.00742862])), vector_model=VectorModel(intercepts=array([ 0.0503911 , 0.12838033, 0.15541499, 0.20185793, 0.22718579, + 0.24311703, 0.24583074, 0.08262932, -0.06406015, -0.05102962, + -0.39325651, -0.40243304, -0.13275181, -0.10596104, -0.09671903, + -0.10022582, -0.10660703]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=0.9474902352534894, shift=array([9.47490235, 0.99993647])), candidate_index=27, candidate_x=array([9.35862837, 1.00819965]), index=27, x=array([9.35862837, 1.00819965]), fval=0.6303511715372276, rho=1.0071263421242136, accepted=True, new_indices=array([], dtype=int32), old_indices_used=array([ 0, 18, 19, 21, 22, 23, 24, 25, 26]), old_indices_discarded=array([12, 15, 16, 17, 20]), step_length=0.0592181407159667, relative_step_length=1.0000000170998888, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([9.35862837, 1.00819965]), radius=0.11843627940668618, bounds=Bounds(lower=array([1.1, 0.5]), upper=array([20. , 1.1]))), model_indices=array([ 0, 18, 19, 21, 23, 24, 25, 26, 27]), model=ScalarModel(intercept=0.639178807035496, linear_terms=array([ 0.00132575, -0.26376211]), square_terms=array([[8.65219778e-04, 5.51863712e-02], + [5.51863712e-02, 3.95321986e+00]]), scale=array([0.10496142, 0.09838088]), shift=array([9.35862837, 1.00161912])), vector_model=VectorModel(intercepts=array([ 0.0503911 , 0.12838033, 0.15541499, 0.20185793, 0.22718579, + 0.24311703, 0.24583074, 0.08262932, -0.06406015, -0.05102962, + -0.39325651, -0.40243304, -0.13275181, -0.10596104, -0.09671903, + -0.10022582, -0.10660703]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=0.9474902352534894, shift=array([9.47490235, 0.99993647])), candidate_index=28, candidate_x=array([9.25366695, 1.00955655]), index=28, x=array([9.25366695, 1.00955655]), fval=0.6252147257628975, rho=1.035476052619481, accepted=True, new_indices=array([], dtype=int32), old_indices_used=array([ 0, 18, 19, 21, 23, 24, 25, 26, 27]), old_indices_discarded=array([11, 12, 13, 14, 15, 16, 17, 20, 22]), step_length=0.10497019014652463, relative_step_length=0.8863009769673553, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([9.25366695, 1.00955655]), radius=0.23687255881337235, bounds=Bounds(lower=array([1.1, 0.5]), upper=array([20. , 1.1]))), model_indices=array([ 0, 19, 21, 23, 24, 25, 26, 27, 28]), model=ScalarModel(intercept=1.3525263472005808, linear_terms=array([-0.05604803, -3.65995549]), square_terms=array([[3.37929225e-03, 1.66025609e-01], + [1.66025609e-01, 9.20973251e+00]]), scale=array([0.20992284, 0.15018314]), shift=array([9.25366695, 0.94981686])), vector_model=VectorModel(intercepts=array([ 0.0503911 , 0.12838033, 0.15541499, 0.20185793, 0.22718579, + 0.24311703, 0.24583074, 0.08262932, -0.06406015, -0.05102962, + -0.39325651, -0.40243304, -0.13275181, -0.10596104, -0.09671903, + -0.10022582, -0.10660703]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + 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step_length=0.20993957271621416, relative_step_length=0.8862975676368734, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([9.04374411, 1.01220715]), radius=0.4737451176267447, bounds=Bounds(lower=array([1.1, 0.5]), upper=array([20. , 1.1]))), model_indices=array([ 3, 7, 10, 13, 22, 25, 27, 28, 29]), model=ScalarModel(intercept=2.887557528467335, linear_terms=array([ 0.32145309, -7.82327945]), square_terms=array([[ 0.01909841, -0.39706853], + [-0.39706853, 13.16541827]]), scale=array([0.41984568, 0.25381927]), shift=array([9.04374411, 0.84618073])), vector_model=VectorModel(intercepts=array([ 0.0503911 , 0.12838033, 0.15541499, 0.20185793, 0.22718579, + 0.24311703, 0.24583074, 0.08262932, -0.06406015, -0.05102962, + -0.39325651, -0.40243304, -0.13275181, -0.10596104, -0.09671903, + -0.10022582, -0.10660703]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=0.9474902352534894, shift=array([9.47490235, 0.99993647])), candidate_index=30, candidate_x=array([8.62389843, 0.98935244]), index=29, x=array([9.04374411, 1.01220715]), fval=0.6151402665456015, rho=-1.1829304881995348, accepted=False, new_indices=array([], dtype=int32), old_indices_used=array([ 3, 7, 10, 13, 22, 25, 27, 28, 29]), old_indices_discarded=array([ 0, 1, 2, 4, 5, 6, 8, 9, 11, 12, 14, 15, 16, 17, 18, 19, 20, + 21, 23, 24, 26]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([9.04374411, 1.01220715]), radius=0.23687255881337235, bounds=Bounds(lower=array([1.1, 0.5]), upper=array([20. , 1.1]))), model_indices=array([ 7, 10, 13, 23, 25, 26, 27, 28, 29]), model=ScalarModel(intercept=1.1785163391833393, linear_terms=array([ 0.04245163, -3.2666068 ]), square_terms=array([[ 1.11423119e-03, -2.87009785e-02], + [-2.87009785e-02, 8.89866124e+00]]), scale=array([0.20992284, 0.14885785]), shift=array([9.04374411, 0.95114215])), vector_model=VectorModel(intercepts=array([ 0.0503911 , 0.12838033, 0.15541499, 0.20185793, 0.22718579, + 0.24311703, 0.24583074, 0.08262932, -0.06406015, -0.05102962, + -0.39325651, -0.40243304, -0.13275181, -0.10596104, -0.09671903, + -0.10022582, -0.10660703]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=0.9474902352534894, shift=array([9.47490235, 0.99993647])), candidate_index=31, candidate_x=array([8.83382127, 1.00530622]), index=29, x=array([9.04374411, 1.01220715]), fval=0.6151402665456015, rho=-0.21904622845287416, accepted=False, new_indices=array([], dtype=int32), old_indices_used=array([ 7, 10, 13, 23, 25, 26, 27, 28, 29]), old_indices_discarded=array([ 0, 1, 3, 6, 9, 11, 12, 14, 15, 16, 17, 18, 19, 20, 21, 22, 24, + 30]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([9.04374411, 1.01220715]), radius=0.11843627940668618, bounds=Bounds(lower=array([1.1, 0.5]), upper=array([20. , 1.1]))), model_indices=array([ 7, 10, 13, 25, 26, 27, 28, 29, 31]), model=ScalarModel(intercept=0.588971346798013, linear_terms=array([ 0.01505103, -0.13000888]), square_terms=array([[ 2.31746838e-04, -3.20175653e-03], + [-3.20175653e-03, 3.75543886e+00]]), scale=array([0.10496142, 0.09637714]), shift=array([9.04374411, 1.00362286])), vector_model=VectorModel(intercepts=array([ 0.0503911 , 0.12838033, 0.15541499, 0.20185793, 0.22718579, + 0.24311703, 0.24583074, 0.08262932, -0.06406015, -0.05102962, + -0.39325651, -0.40243304, -0.13275181, -0.10596104, -0.09671903, + -0.10022582, -0.10660703]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=0.9474902352534894, shift=array([9.47490235, 0.99993647])), candidate_index=32, candidate_x=array([8.93878269, 1.00687716]), index=29, x=array([9.04374411, 1.01220715]), fval=0.6151402665456015, rho=-0.19293832377303985, accepted=False, new_indices=array([], dtype=int32), old_indices_used=array([ 7, 10, 13, 25, 26, 27, 28, 29, 31]), old_indices_discarded=array([ 0, 3, 12, 16, 17, 18, 19, 20, 21, 22, 23, 24, 30]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([9.04374411, 1.01220715]), radius=0.05921813970334309, bounds=Bounds(lower=array([1.1, 0.5]), upper=array([20. , 1.1]))), model_indices=array([13, 28, 29, 31, 32]), model=ScalarModel(intercept=0.6214336044267341, linear_terms=array([0.00147887, 0.10259686]), square_terms=array([[4.10977860e-04, 1.78962346e-02], + [1.78962346e-02, 8.79816604e-01]]), scale=0.05921813970334309, shift=array([9.04374411, 1.01220715])), vector_model=VectorModel(intercepts=array([ 0.0503911 , 0.12838033, 0.15541499, 0.20185793, 0.22718579, + 0.24311703, 0.24583074, 0.08262932, -0.06406015, -0.05102962, + -0.39325651, -0.40243304, -0.13275181, -0.10596104, -0.09671903, + -0.10022582, -0.10660703]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=0.9474902352534894, shift=array([9.47490235, 0.99993647])), candidate_index=33, candidate_x=array([9.10280287, 1.00410548]), index=29, x=array([9.04374411, 1.01220715]), fval=0.6151402665456015, rho=-2.08297420159985, accepted=False, new_indices=array([], dtype=int32), old_indices_used=array([13, 28, 29, 31, 32]), old_indices_discarded=array([], dtype=int32), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([9.04374411, 1.01220715]), radius=0.029609069851671544, bounds=Bounds(lower=array([1.1, 0.5]), upper=array([20. , 1.1]))), model_indices=array([29, 32, 33]), model=ScalarModel(intercept=0.6151402665456009, linear_terms=array([0.00149709, 0.00482735]), square_terms=array([[7.65543339e-05, 5.14393571e-03], + [5.14393571e-03, 3.91745261e-01]]), scale=0.029609069851671544, shift=array([9.04374411, 1.01220715])), vector_model=VectorModel(intercepts=array([ 0.0503911 , 0.12838033, 0.15541499, 0.20185793, 0.22718579, + 0.24311703, 0.24583074, 0.08262932, -0.06406015, -0.05102962, + -0.39325651, -0.40243304, -0.13275181, -0.10596104, -0.09671903, + -0.10022582, -0.10660703]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=0.9474902352534894, shift=array([9.47490235, 0.99993647])), candidate_index=34, candidate_x=array([9.0141328 , 1.01223102]), index=34, x=array([9.0141328 , 1.01223102]), fval=0.6138905842835336, rho=0.8565054081815938, accepted=True, new_indices=array([], dtype=int32), old_indices_used=array([29, 32, 33]), old_indices_discarded=array([], dtype=int32), step_length=0.02961131833730782, relative_step_length=1.0000759390837854, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([9.0141328 , 1.01223102]), radius=0.05921813970334309, bounds=Bounds(lower=array([1.1, 0.5]), upper=array([20. , 1.1]))), model_indices=array([13, 28, 29, 31, 32, 33, 34]), model=ScalarModel(intercept=0.620881773286023, linear_terms=array([0.00197631, 0.09173778]), square_terms=array([[3.44046695e-04, 1.64408522e-02], + [1.64408522e-02, 8.92929811e-01]]), scale=0.05921813970334309, shift=array([9.0141328 , 1.01223102])), vector_model=VectorModel(intercepts=array([ 0.0503911 , 0.12838033, 0.15541499, 0.20185793, 0.22718579, + 0.24311703, 0.24583074, 0.08262932, -0.06406015, -0.05102962, + -0.39325651, -0.40243304, -0.13275181, -0.10596104, -0.09671903, + -0.10022582, -0.10660703]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=0.9474902352534894, shift=array([9.47490235, 0.99993647])), candidate_index=35, candidate_x=array([8.95483028, 1.00724033]), index=34, x=array([9.0141328 , 1.01223102]), fval=0.6138905842835336, rho=-0.906107936879546, accepted=False, new_indices=array([], dtype=int32), old_indices_used=array([13, 28, 29, 31, 32, 33, 34]), old_indices_discarded=array([], dtype=int32), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([9.0141328 , 1.01223102]), radius=0.029609069851671544, bounds=Bounds(lower=array([1.1, 0.5]), upper=array([20. , 1.1]))), model_indices=array([29, 32, 33, 34, 35]), model=ScalarModel(intercept=0.6137867229839677, linear_terms=array([0.00142032, 0.00043433]), square_terms=array([[7.69832064e-05, 5.16913372e-03], + [5.16913372e-03, 3.92730596e-01]]), scale=0.029609069851671544, shift=array([9.0141328 , 1.01223102])), vector_model=VectorModel(intercepts=array([ 0.0503911 , 0.12838033, 0.15541499, 0.20185793, 0.22718579, + 0.24311703, 0.24583074, 0.08262932, -0.06406015, -0.05102962, + -0.39325651, -0.40243304, -0.13275181, -0.10596104, -0.09671903, + -0.10022582, -0.10660703]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=0.9474902352534894, shift=array([9.47490235, 0.99993647])), candidate_index=36, candidate_x=array([8.98452585, 1.01258669]), index=36, x=array([8.98452585, 1.01258669]), fval=0.6125286403569352, rho=0.9657336720601446, accepted=True, new_indices=array([], dtype=int32), old_indices_used=array([29, 32, 33, 34, 35]), old_indices_discarded=array([], dtype=int32), step_length=0.029609089398228004, relative_step_length=1.0000006601543567, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([8.98452585, 1.01258669]), radius=0.05921813970334309, bounds=Bounds(lower=array([1.1, 0.5]), upper=array([20. , 1.1]))), model_indices=array([13, 28, 29, 31, 32, 33, 34, 35, 36]), model=ScalarModel(intercept=0.619467823965291, linear_terms=array([0.00209097, 0.09020298]), square_terms=array([[3.29303090e-04, 1.61351934e-02], + [1.61351934e-02, 9.00329160e-01]]), scale=0.05921813970334309, shift=array([8.98452585, 1.01258669])), vector_model=VectorModel(intercepts=array([ 0.0503911 , 0.12838033, 0.15541499, 0.20185793, 0.22718579, + 0.24311703, 0.24583074, 0.08262932, -0.06406015, -0.05102962, + -0.39325651, -0.40243304, -0.13275181, -0.10596104, -0.09671903, + -0.10022582, -0.10660703]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=0.9474902352534894, shift=array([9.47490235, 0.99993647])), candidate_index=37, candidate_x=array([8.92521698, 1.00771893]), index=36, x=array([8.98452585, 1.01258669]), fval=0.6125286403569352, rho=-0.8416732621911007, accepted=False, new_indices=array([], dtype=int32), old_indices_used=array([13, 28, 29, 31, 32, 33, 34, 35, 36]), old_indices_discarded=array([], dtype=int32), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([8.98452585, 1.01258669]), radius=0.029609069851671544, bounds=Bounds(lower=array([1.1, 0.5]), upper=array([20. , 1.1]))), model_indices=array([29, 32, 33, 34, 35, 36, 37]), model=ScalarModel(intercept=0.6124263604451471, linear_terms=array([0.00140759, 0.00037964]), square_terms=array([[7.68743253e-05, 5.17639009e-03], + [5.17639009e-03, 3.94127433e-01]]), scale=0.029609069851671544, shift=array([8.98452585, 1.01258669])), vector_model=VectorModel(intercepts=array([ 0.0503911 , 0.12838033, 0.15541499, 0.20185793, 0.22718579, + 0.24311703, 0.24583074, 0.08262932, -0.06406015, -0.05102962, + -0.39325651, -0.40243304, -0.13275181, -0.10596104, -0.09671903, + -0.10022582, -0.10660703]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=0.9474902352534894, shift=array([9.47490235, 0.99993647])), candidate_index=38, candidate_x=array([8.95491894, 1.01294575]), index=38, x=array([8.95491894, 1.01294575]), fval=0.6110646963985666, rho=1.04699122192598, accepted=True, new_indices=array([], dtype=int32), old_indices_used=array([29, 32, 33, 34, 35, 36, 37]), old_indices_discarded=array([], dtype=int32), step_length=0.02960908484218274, relative_step_length=1.0000005062810575, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([8.95491894, 1.01294575]), radius=0.05921813970334309, bounds=Bounds(lower=array([1.1, 0.5]), upper=array([20. , 1.1]))), model_indices=array([29, 31, 32, 33, 34, 35, 36, 37, 38]), model=ScalarModel(intercept=0.6110062274424244, linear_terms=array([0.0028986 , 0.00157643]), square_terms=array([[3.04730334e-04, 2.06301143e-02], + [2.06301143e-02, 1.58200616e+00]]), scale=0.05921813970334309, shift=array([8.95491894, 1.01294575])), vector_model=VectorModel(intercepts=array([ 0.0503911 , 0.12838033, 0.15541499, 0.20185793, 0.22718579, + 0.24311703, 0.24583074, 0.08262932, -0.06406015, -0.05102962, + -0.39325651, -0.40243304, -0.13275181, -0.10596104, -0.09671903, + -0.10022582, -0.10660703]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=0.9474902352534894, shift=array([9.47490235, 0.99993647])), candidate_index=39, candidate_x=array([8.89570505, 1.01365764]), index=39, x=array([8.89570505, 1.01365764]), fval=0.608454913769554, rho=0.9122655509396086, accepted=True, new_indices=array([], dtype=int32), old_indices_used=array([29, 31, 32, 33, 34, 35, 36, 37, 38]), old_indices_discarded=array([13]), step_length=0.05921817039076989, relative_step_length=1.0000005182099092, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([8.89570505, 1.01365764]), radius=0.11843627940668618, bounds=Bounds(lower=array([1.1, 0.5]), upper=array([20. , 1.1]))), model_indices=array([13, 31, 32, 34, 35, 36, 37, 38, 39]), model=ScalarModel(intercept=0.614727205905659, linear_terms=array([-0.00711409, -0.08425954]), square_terms=array([[1.97921783e-03, 6.38199381e-02], + [6.38199381e-02, 2.30738160e+00]]), scale=array([0.10496142, 0.09565189]), shift=array([8.89570505, 1.00434811])), vector_model=VectorModel(intercepts=array([ 0.0503911 , 0.12838033, 0.15541499, 0.20185793, 0.22718579, + 0.24311703, 0.24583074, 0.08262932, -0.06406015, -0.05102962, + -0.39325651, -0.40243304, -0.13275181, -0.10596104, -0.09671903, + -0.10022582, -0.10660703]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=0.9474902352534894, shift=array([9.47490235, 0.99993647])), candidate_index=40, candidate_x=array([9.00066647, 1.00519543]), index=39, x=array([8.89570505, 1.01365764]), fval=0.608454913769554, rho=-1.8130574184159354, accepted=False, new_indices=array([], dtype=int32), old_indices_used=array([13, 31, 32, 34, 35, 36, 37, 38, 39]), old_indices_discarded=array([ 0, 1, 3, 7, 10, 21, 23, 25, 26, 27, 28, 29, 30, 33]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([8.89570505, 1.01365764]), radius=0.05921813970334309, bounds=Bounds(lower=array([1.1, 0.5]), upper=array([20. , 1.1]))), model_indices=array([31, 32, 34, 35, 36, 37, 38, 39, 40]), model=ScalarModel(intercept=0.6082515870760768, linear_terms=array([0.00289756, 0.00212777]), square_terms=array([[2.93803015e-04, 2.03395974e-02], + [2.03395974e-02, 1.60156668e+00]]), scale=0.05921813970334309, shift=array([8.89570505, 1.01365764])), vector_model=VectorModel(intercepts=array([ 0.0503911 , 0.12838033, 0.15541499, 0.20185793, 0.22718579, + 0.24311703, 0.24583074, 0.08262932, -0.06406015, -0.05102962, + -0.39325651, -0.40243304, -0.13275181, -0.10596104, -0.09671903, + -0.10022582, -0.10660703]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=0.9474902352534894, shift=array([9.47490235, 0.99993647])), candidate_index=41, candidate_x=array([8.83649067, 1.01432978]), index=41, x=array([8.83649067, 1.01432978]), fval=0.6057905110013826, rho=0.9335608646751216, accepted=True, new_indices=array([], dtype=int32), old_indices_used=array([31, 32, 34, 35, 36, 37, 38, 39, 40]), old_indices_discarded=array([ 7, 10, 13, 29, 30, 33]), step_length=0.05921819354659514, relative_step_length=1.0000009092357902, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([8.83649067, 1.01432978]), radius=0.11843627940668618, bounds=Bounds(lower=array([1.1, 0.5]), upper=array([20. , 1.1]))), model_indices=array([13, 31, 32, 35, 36, 37, 38, 39, 41]), model=ScalarModel(intercept=0.610651531374723, linear_terms=array([ 0.00125715, -0.10509161]), square_terms=array([[7.56634919e-04, 3.91907529e-02], + [3.91907529e-02, 2.39236786e+00]]), scale=array([0.10496142, 0.09531582]), shift=array([8.83649067, 1.00468418])), vector_model=VectorModel(intercepts=array([ 0.0503911 , 0.12838033, 0.15541499, 0.20185793, 0.22718579, + 0.24311703, 0.24583074, 0.08262932, -0.06406015, -0.05102962, + -0.39325651, -0.40243304, -0.13275181, -0.10596104, -0.09671903, + -0.10022582, -0.10660703]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=0.9474902352534894, shift=array([9.47490235, 0.99993647])), candidate_index=42, candidate_x=array([8.73152925, 1.01043262]), index=41, x=array([8.83649067, 1.01432978]), fval=0.6057905110013826, rho=-0.2539961161624663, accepted=False, new_indices=array([], dtype=int32), old_indices_used=array([13, 31, 32, 35, 36, 37, 38, 39, 41]), old_indices_discarded=array([ 1, 3, 7, 10, 26, 27, 28, 29, 30, 33, 34, 40]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([8.83649067, 1.01432978]), radius=0.05921813970334309, bounds=Bounds(lower=array([1.1, 0.5]), upper=array([20. , 1.1]))), model_indices=array([13, 31, 32, 35, 37, 38, 39, 41, 42]), model=ScalarModel(intercept=0.6128960194558581, linear_terms=array([0.00323829, 0.08375858]), square_terms=array([[2.19797272e-04, 1.29854569e-02], + [1.29854569e-02, 9.21144727e-01]]), scale=0.05921813970334309, shift=array([8.83649067, 1.01432978])), vector_model=VectorModel(intercepts=array([ 0.0503911 , 0.12838033, 0.15541499, 0.20185793, 0.22718579, + 0.24311703, 0.24583074, 0.08262932, -0.06406015, -0.05102962, + -0.39325651, -0.40243304, -0.13275181, -0.10596104, -0.09671903, + -0.10022582, -0.10660703]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=0.9474902352534894, shift=array([9.47490235, 0.99993647])), candidate_index=43, candidate_x=array([8.77720289, 1.00979089]), index=41, x=array([8.83649067, 1.01432978]), fval=0.6057905110013826, rho=-0.636748464236313, accepted=False, new_indices=array([], dtype=int32), old_indices_used=array([13, 31, 32, 35, 37, 38, 39, 41, 42]), old_indices_discarded=array([ 3, 7, 10, 29, 30, 33, 34, 36, 40]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([8.83649067, 1.01432978]), radius=0.029609069851671544, bounds=Bounds(lower=array([1.1, 0.5]), upper=array([20. , 1.1]))), model_indices=array([13, 31, 32, 37, 38, 39, 41, 42, 43]), model=ScalarModel(intercept=0.6129958444671166, linear_terms=array([0.00125322, 0.0420077 ]), square_terms=array([[7.02244693e-05, 3.72273429e-03], + [3.72273429e-03, 2.29436197e-01]]), scale=0.029609069851671544, shift=array([8.83649067, 1.01432978])), vector_model=VectorModel(intercepts=array([ 0.0503911 , 0.12838033, 0.15541499, 0.20185793, 0.22718579, + 0.24311703, 0.24583074, 0.08262932, -0.06406015, -0.05102962, + -0.39325651, -0.40243304, -0.13275181, -0.10596104, -0.09671903, + -0.10022582, -0.10660703]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=0.9474902352534894, shift=array([9.47490235, 0.99993647])), candidate_index=44, candidate_x=array([8.80679818, 1.00940247]), index=41, x=array([8.83649067, 1.01432978]), fval=0.6057905110013826, rho=-1.1780504359812205, accepted=False, new_indices=array([], dtype=int32), old_indices_used=array([13, 31, 32, 37, 38, 39, 41, 42, 43]), old_indices_discarded=array([35]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([8.83649067, 1.01432978]), radius=0.014804534925835772, bounds=Bounds(lower=array([1.1, 0.5]), upper=array([20. , 1.1]))), model_indices=array([31, 39, 41, 43, 44]), model=ScalarModel(intercept=0.6059146038962105, linear_terms=array([0.00063063, 0.00133693]), square_terms=array([[1.93356047e-05, 1.31514692e-03], + [1.31514692e-03, 1.01583452e-01]]), scale=0.014804534925835772, shift=array([8.83649067, 1.01432978])), vector_model=VectorModel(intercepts=array([ 0.0503911 , 0.12838033, 0.15541499, 0.20185793, 0.22718579, + 0.24311703, 0.24583074, 0.08262932, -0.06406015, -0.05102962, + -0.39325651, -0.40243304, -0.13275181, -0.10596104, -0.09671903, + -0.10022582, -0.10660703]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=0.9474902352534894, shift=array([9.47490235, 0.99993647])), candidate_index=45, candidate_x=array([8.82168485, 1.01432664]), index=45, x=array([8.82168485, 1.01432664]), fval=0.6051564916805549, rho=1.020928649746183, accepted=True, new_indices=array([], dtype=int32), old_indices_used=array([31, 39, 41, 43, 44]), old_indices_discarded=array([], dtype=int32), step_length=0.014805816548052337, relative_step_length=1.0000865695695937, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([8.82168485, 1.01432664]), radius=0.029609069851671544, bounds=Bounds(lower=array([1.1, 0.5]), upper=array([20. , 1.1]))), model_indices=array([13, 31, 37, 39, 41, 42, 43, 44, 45]), model=ScalarModel(intercept=0.6115555266177718, linear_terms=array([0.00124126, 0.04101205]), square_terms=array([[7.04241015e-05, 3.73186729e-03], + [3.73186729e-03, 2.30210452e-01]]), scale=0.029609069851671544, shift=array([8.82168485, 1.01432664])), vector_model=VectorModel(intercepts=array([ 0.0503911 , 0.12838033, 0.15541499, 0.20185793, 0.22718579, + 0.24311703, 0.24583074, 0.08262932, -0.06406015, -0.05102962, + -0.39325651, -0.40243304, -0.13275181, -0.10596104, -0.09671903, + -0.10022582, -0.10660703]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=0.9474902352534894, shift=array([9.47490235, 0.99993647])), candidate_index=46, candidate_x=array([8.79199479, 1.00954484]), index=45, x=array([8.82168485, 1.01432664]), fval=0.6051564916805549, rho=-1.230884779808124, accepted=False, new_indices=array([], dtype=int32), old_indices_used=array([13, 31, 37, 39, 41, 42, 43, 44, 45]), old_indices_discarded=array([32, 35, 38]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([8.82168485, 1.01432664]), radius=0.014804534925835772, bounds=Bounds(lower=array([1.1, 0.5]), upper=array([20. , 1.1]))), model_indices=array([31, 41, 43, 44, 45, 46]), model=ScalarModel(intercept=0.6052045803357664, linear_terms=array([5.75893275e-04, 2.08251016e-05]), square_terms=array([[2.14888603e-05, 1.39552818e-03], + [1.39552818e-03, 1.02157333e-01]]), scale=0.014804534925835772, shift=array([8.82168485, 1.01432664])), vector_model=VectorModel(intercepts=array([ 0.0503911 , 0.12838033, 0.15541499, 0.20185793, 0.22718579, + 0.24311703, 0.24583074, 0.08262932, -0.06406015, -0.05102962, + -0.39325651, -0.40243304, -0.13275181, -0.10596104, -0.09671903, + -0.10022582, -0.10660703]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=0.9474902352534894, shift=array([9.47490235, 0.99993647])), candidate_index=47, candidate_x=array([8.80688164, 1.01452473]), index=47, x=array([8.80688164, 1.01452473]), fval=0.6045010959198394, rho=1.1411150863578703, accepted=True, new_indices=array([], dtype=int32), old_indices_used=array([31, 41, 43, 44, 45, 46]), old_indices_discarded=array([], dtype=int32), step_length=0.014804535502910653, relative_step_length=1.0000000389796022, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([8.80688164, 1.01452473]), radius=0.029609069851671544, bounds=Bounds(lower=array([1.1, 0.5]), upper=array([20. , 1.1]))), model_indices=array([13, 31, 41, 42, 43, 44, 45, 46, 47]), model=ScalarModel(intercept=0.6105358682194937, linear_terms=array([0.00053509, 0.04163391]), square_terms=array([[1.09771507e-04, 4.72352439e-03], + [4.72352439e-03, 2.30297392e-01]]), scale=0.029609069851671544, shift=array([8.80688164, 1.01452473])), vector_model=VectorModel(intercepts=array([ 0.0503911 , 0.12838033, 0.15541499, 0.20185793, 0.22718579, + 0.24311703, 0.24583074, 0.08262932, -0.06406015, -0.05102962, + -0.39325651, -0.40243304, -0.13275181, -0.10596104, -0.09671903, + -0.10022582, -0.10660703]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=0.9474902352534894, shift=array([9.47490235, 0.99993647])), candidate_index=48, candidate_x=array([8.8363726 , 1.00857494]), index=47, x=array([8.80688164, 1.01452473]), fval=0.6045010959198394, rho=-2.17105462493869, accepted=False, new_indices=array([], dtype=int32), old_indices_used=array([13, 31, 41, 42, 43, 44, 45, 46, 47]), old_indices_discarded=array([32, 37, 39]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([8.80688164, 1.01452473]), radius=0.014804534925835772, bounds=Bounds(lower=array([1.1, 0.5]), upper=array([20. , 1.1]))), model_indices=array([31, 41, 43, 44, 45, 46, 47, 48]), model=ScalarModel(intercept=0.6045817009488239, linear_terms=array([ 0.00060537, -0.00012916]), square_terms=array([[2.04142540e-05, 1.36233150e-03], + [1.36233150e-03, 1.02744088e-01]]), scale=0.014804534925835772, shift=array([8.80688164, 1.01452473])), vector_model=VectorModel(intercepts=array([ 0.0503911 , 0.12838033, 0.15541499, 0.20185793, 0.22718579, + 0.24311703, 0.24583074, 0.08262932, -0.06406015, -0.05102962, + -0.39325651, -0.40243304, -0.13275181, -0.10596104, -0.09671903, + -0.10022582, -0.10660703]), linear_terms=array([[0., 0.], + 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44, 45, 46, 47, 48]), old_indices_discarded=array([], dtype=int32), step_length=0.01480454508906136, relative_step_length=1.0000006864940802, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([8.79207864, 1.01473837]), radius=0.029609069851671544, bounds=Bounds(lower=array([1.1, 0.5]), upper=array([20. , 1.1]))), model_indices=array([31, 41, 43, 44, 45, 46, 47, 48, 49]), model=ScalarModel(intercept=0.6039320017441308, linear_terms=array([1.22941931e-03, 2.77206681e-05]), square_terms=array([[7.95912011e-05, 5.38269834e-03], + [5.38269834e-03, 4.12173721e-01]]), scale=0.029609069851671544, shift=array([8.79207864, 1.01473837])), vector_model=VectorModel(intercepts=array([ 0.0503911 , 0.12838033, 0.15541499, 0.20185793, 0.22718579, + 0.24311703, 0.24583074, 0.08262932, -0.06406015, -0.05102962, + -0.39325651, -0.40243304, -0.13275181, -0.10596104, -0.09671903, + -0.10022582, -0.10660703]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + 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old_indices_discarded=array([13, 32, 37, 39, 42]), step_length=0.02960907001757359, relative_step_length=1.000000005603082, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([8.76247205, 1.01512188]), radius=0.05921813970334309, bounds=Bounds(lower=array([1.1, 0.5]), upper=array([20. , 1.1]))), model_indices=array([31, 42, 43, 44, 45, 46, 47, 49, 50]), model=ScalarModel(intercept=0.6026578745853444, linear_terms=array([0.0024301, 0.0002779]), square_terms=array([[3.16909370e-04, 2.15042159e-02], + [2.15042159e-02, 1.65484964e+00]]), scale=0.05921813970334309, shift=array([8.76247205, 1.01512188])), vector_model=VectorModel(intercepts=array([ 0.0503911 , 0.12838033, 0.15541499, 0.20185793, 0.22718579, + 0.24311703, 0.24583074, 0.08262932, -0.06406015, -0.05102962, + -0.39325651, -0.40243304, -0.13275181, -0.10596104, -0.09671903, + -0.10022582, -0.10660703]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 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13, 29, 30, 32, 34, 35, 36, 37, 38, 39, 40, 41, 48]), step_length=0.05921814073463714, relative_step_length=1.0000000174151713, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([8.70325877, 1.0158803 ]), radius=0.11843627940668618, bounds=Bounds(lower=array([1.1, 0.5]), upper=array([20. , 1.1]))), model_indices=array([ 7, 10, 13, 30, 42, 44, 45, 50, 51]), model=ScalarModel(intercept=0.5745601532643059, linear_terms=array([ 0.01933147, -0.20828263]), square_terms=array([[ 3.96552248e-04, -7.70697193e-03], + [-7.70697193e-03, 3.60952666e+00]]), scale=array([0.10496142, 0.09454056]), shift=array([8.70325877, 1.00545944])), vector_model=VectorModel(intercepts=array([ 0.0503911 , 0.12838033, 0.15541499, 0.20185793, 0.22718579, + 0.24311703, 0.24583074, 0.08262932, -0.06406015, -0.05102962, + -0.39325651, -0.40243304, -0.13275181, -0.10596104, -0.09671903, + -0.10022582, -0.10660703]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 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old_indices_discarded=array([ 1, 3, 28, 29, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 43, 46, + 47, 48, 49]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([8.70325877, 1.0158803 ]), radius=0.05921813970334309, bounds=Bounds(lower=array([1.1, 0.5]), upper=array([20. , 1.1]))), model_indices=array([ 7, 10, 30, 42, 43, 46, 49, 50, 51]), model=ScalarModel(intercept=0.5848648139367352, linear_terms=array([ 0.01259792, -0.01987223]), square_terms=array([[ 2.31944576e-04, -1.32546665e-02], + [-1.32546665e-02, 2.24249333e+00]]), scale=0.05921813970334309, shift=array([8.70325877, 1.0158803 ])), vector_model=VectorModel(intercepts=array([ 0.0503911 , 0.12838033, 0.15541499, 0.20185793, 0.22718579, + 0.24311703, 0.24583074, 0.08262932, -0.06406015, -0.05102962, + -0.39325651, -0.40243304, -0.13275181, -0.10596104, -0.09671903, + -0.10022582, -0.10660703]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + 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old_indices_discarded=array([ 3, 13, 31, 32, 35, 36, 37, 38, 39, 41, 44, 45, 47, 48, 52]), step_length=0.05922045545199665, relative_step_length=1.0000391053934683, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([8.64403857, 1.01605409]), radius=0.11843627940668618, bounds=Bounds(lower=array([1.1, 0.5]), upper=array([20. , 1.1]))), model_indices=array([ 7, 10, 30, 42, 43, 50, 51, 52, 53]), model=ScalarModel(intercept=0.6233574060676437, linear_terms=array([ 0.01619734, -0.70631774]), square_terms=array([[2.97413525e-04, 7.75950577e-04], + [7.75950577e-04, 5.79975163e+00]]), scale=array([0.10496142, 0.09445367]), shift=array([8.64403857, 1.00554633])), vector_model=VectorModel(intercepts=array([ 0.0503911 , 0.12838033, 0.15541499, 0.20185793, 0.22718579, + 0.24311703, 0.24583074, 0.08262932, -0.06406015, -0.05102962, + -0.39325651, -0.40243304, -0.13275181, -0.10596104, -0.09671903, + -0.10022582, -0.10660703]), linear_terms=array([[0., 0.], + [0., 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43, 50, 51, 52, 53]), old_indices_discarded=array([ 1, 3, 13, 29, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 44, 45, + 46, 47, 48, 49]), step_length=0.10496625831674383, relative_step_length=0.8862677791178409, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([8.53907715, 1.01706193]), radius=0.23687255881337235, bounds=Bounds(lower=array([1.1, 0.5]), upper=array([20. , 1.1]))), model_indices=array([ 3, 7, 30, 42, 50, 51, 52, 53, 54]), model=ScalarModel(intercept=0.7023662250726452, linear_terms=array([ 0.06492856, -1.1147206 ]), square_terms=array([[ 3.47923203e-03, -8.06332216e-02], + [-8.06332216e-02, 3.61802648e+00]]), scale=array([0.20992284, 0.14643046]), shift=array([8.53907715, 0.95356954])), vector_model=VectorModel(intercepts=array([ 0.0503911 , 0.12838033, 0.15541499, 0.20185793, 0.22718579, + 0.24311703, 0.24583074, 0.08262932, -0.06406015, -0.05102962, + -0.39325651, -0.40243304, -0.13275181, -0.10596104, -0.09671903, + -0.10022582, 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dtype=int32), old_indices_used=array([ 3, 7, 30, 42, 50, 51, 52, 53, 54]), old_indices_discarded=array([ 0, 1, 10, 11, 12, 13, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, + 26, 27, 28, 29, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 43, 44, + 45, 46, 47, 48, 49]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([8.53907715, 1.01706193]), radius=0.11843627940668618, bounds=Bounds(lower=array([1.1, 0.5]), upper=array([20. , 1.1]))), model_indices=array([ 7, 10, 30, 42, 51, 52, 53, 54, 55]), model=ScalarModel(intercept=0.615086708073995, linear_terms=array([ 0.00978289, -0.72244786]), square_terms=array([[4.17284358e-04, 3.04748646e-02], + [3.04748646e-02, 5.74255506e+00]]), scale=array([0.10496142, 0.09394975]), shift=array([8.53907715, 1.00605025])), vector_model=VectorModel(intercepts=array([ 0.0503911 , 0.12838033, 0.15541499, 0.20185793, 0.22718579, + 0.24311703, 0.24583074, 0.08262932, -0.06406015, -0.05102962, + -0.39325651, -0.40243304, -0.13275181, -0.10596104, -0.09671903, + -0.10022582, -0.10660703]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=0.9474902352534894, shift=array([9.47490235, 0.99993647])), candidate_index=56, candidate_x=array([8.43411573, 1.01836827]), index=56, x=array([8.43411573, 1.01836827]), fval=0.5885914443329772, rho=0.3283224223143453, accepted=True, new_indices=array([], dtype=int32), old_indices_used=array([ 7, 10, 30, 42, 51, 52, 53, 54, 55]), old_indices_discarded=array([ 1, 3, 13, 29, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 43, 44, + 45, 46, 47, 48, 49, 50]), step_length=0.10496954879325875, relative_step_length=0.8862955617916246, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([8.43411573, 1.01836827]), radius=0.23687255881337235, bounds=Bounds(lower=array([1.1, 0.5]), upper=array([20. , 1.1]))), model_indices=array([ 7, 10, 30, 51, 52, 53, 54, 55, 56]), model=ScalarModel(intercept=1.9169446392811247, linear_terms=array([-0.05516787, -6.07713486]), square_terms=array([[2.74937852e-03, 1.66261876e-01], + [1.66261876e-01, 1.36583309e+01]]), scale=array([0.20992284, 0.14577728]), shift=array([8.43411573, 0.95422272])), vector_model=VectorModel(intercepts=array([ 0.0503911 , 0.12838033, 0.15541499, 0.20185793, 0.22718579, + 0.24311703, 0.24583074, 0.08262932, -0.06406015, -0.05102962, + -0.39325651, -0.40243304, -0.13275181, -0.10596104, -0.09671903, + -0.10022582, -0.10660703]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=0.9474902352534894, shift=array([9.47490235, 0.99993647])), candidate_index=57, candidate_x=array([8.22419289, 1.02085937]), index=57, x=array([8.22419289, 1.02085937]), fval=0.5799642053547169, rho=0.46355807804061855, accepted=True, new_indices=array([], dtype=int32), old_indices_used=array([ 7, 10, 30, 51, 52, 53, 54, 55, 56]), old_indices_discarded=array([ 0, 1, 3, 11, 12, 13, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, + 27, 28, 29, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, + 45, 46, 47, 48, 49, 50]), step_length=0.2099376195491761, relative_step_length=0.8862893219918404, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([8.22419289, 1.02085937]), radius=0.4737451176267447, bounds=Bounds(lower=array([1.1, 0.5]), upper=array([20. , 1.1]))), model_indices=array([ 3, 7, 30, 52, 53, 54, 55, 56, 57]), model=ScalarModel(intercept=3.341466430284669, linear_terms=array([-1.05103033, -7.77084409]), square_terms=array([[ 0.18279549, 1.34509322], + [ 1.34509322, 11.10009818]]), scale=array([0.41984568, 0.24949316]), shift=array([8.22419289, 0.85050684])), vector_model=VectorModel(intercepts=array([ 0.0503911 , 0.12838033, 0.15541499, 0.20185793, 0.22718579, + 0.24311703, 0.24583074, 0.08262932, -0.06406015, -0.05102962, + -0.39325651, -0.40243304, -0.13275181, -0.10596104, -0.09671903, + -0.10022582, -0.10660703]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=0.9474902352534894, shift=array([9.47490235, 0.99993647])), candidate_index=58, candidate_x=array([8.64403857, 0.99493627]), index=57, x=array([8.22419289, 1.02085937]), fval=0.5799642053547169, rho=-1.0936320536105784, accepted=False, new_indices=array([], dtype=int32), old_indices_used=array([ 3, 7, 30, 52, 53, 54, 55, 56, 57]), old_indices_discarded=array([ 0, 1, 2, 4, 5, 6, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, + 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 31, 32, 33, 34, 35, 36, + 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([8.22419289, 1.02085937]), radius=0.23687255881337235, bounds=Bounds(lower=array([1.1, 0.5]), upper=array([20. , 1.1]))), model_indices=array([ 7, 10, 30, 52, 53, 54, 55, 56, 57]), model=ScalarModel(intercept=1.9832433701127465, linear_terms=array([-0.11608732, -6.1156747 ]), square_terms=array([[5.73554046e-03, 2.62479555e-01], + [2.62479555e-01, 1.32048414e+01]]), scale=array([0.20992284, 0.14453174]), shift=array([8.22419289, 0.95546826])), vector_model=VectorModel(intercepts=array([ 0.0503911 , 0.12838033, 0.15541499, 0.20185793, 0.22718579, + 0.24311703, 0.24583074, 0.08262932, -0.06406015, -0.05102962, + -0.39325651, -0.40243304, -0.13275181, -0.10596104, -0.09671903, + -0.10022582, -0.10660703]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=0.9474902352534894, shift=array([9.47490235, 0.99993647])), candidate_index=59, candidate_x=array([8.01427005, 1.02527945]), index=59, x=array([8.01427005, 1.02527945]), fval=0.5734330166298551, rho=1.093147952169101, accepted=True, new_indices=array([], dtype=int32), old_indices_used=array([ 7, 10, 30, 52, 53, 54, 55, 56, 57]), old_indices_discarded=array([ 1, 3, 13, 27, 28, 29, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, + 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 58]), step_length=0.20996936856056853, relative_step_length=0.8864233561389423, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([8.01427005, 1.02527945]), radius=0.4737451176267447, bounds=Bounds(lower=array([1.1, 0.5]), upper=array([20. , 1.1]))), model_indices=array([ 7, 10, 30, 52, 54, 55, 56, 57, 59]), model=ScalarModel(intercept=9.981376675556422, linear_terms=array([ -0.67948996, -26.92467299]), square_terms=array([[2.66781078e-02, 9.72846991e-01], + [9.72846991e-01, 3.85178573e+01]]), scale=array([0.41984568, 0.24728311]), shift=array([8.01427005, 0.85271689])), vector_model=VectorModel(intercepts=array([ 0.0503911 , 0.12838033, 0.15541499, 0.20185793, 0.22718579, + 0.24311703, 0.24583074, 0.08262932, -0.06406015, -0.05102962, + -0.39325651, -0.40243304, -0.13275181, -0.10596104, -0.09671903, + -0.10022582, -0.10660703]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=0.9474902352534894, shift=array([9.47490235, 0.99993647])), candidate_index=60, candidate_x=array([7.90516021, 1.02719534]), index=60, x=array([7.90516021, 1.02719534]), fval=0.570654333265082, rho=28.312992905781908, accepted=True, new_indices=array([], dtype=int32), old_indices_used=array([ 7, 10, 30, 52, 54, 55, 56, 57, 59]), old_indices_discarded=array([ 0, 1, 2, 3, 4, 5, 6, 8, 9, 11, 12, 13, 14, 15, 16, 17, 18, + 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 31, 32, 33, 34, 35, 36, + 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 53, 58]), step_length=0.1091266633945737, relative_step_length=0.23034889296854485, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([7.90516021, 1.02719534]), radius=0.4737451176267447, bounds=Bounds(lower=array([1.1, 0.5]), upper=array([20. , 1.1]))), model_indices=array([10, 30, 52, 54, 55, 56, 57, 59, 60]), model=ScalarModel(intercept=6.968668322923406, linear_terms=array([ -0.3193095 , -18.62779191]), square_terms=array([[1.10008541e-02, 4.89131866e-01], + [4.89131866e-01, 2.70983093e+01]]), scale=array([0.41984568, 0.24632517]), shift=array([7.90516021, 0.85367483])), vector_model=VectorModel(intercepts=array([ 0.0503911 , 0.12838033, 0.15541499, 0.20185793, 0.22718579, + 0.24311703, 0.24583074, 0.08262932, -0.06406015, -0.05102962, + -0.39325651, -0.40243304, -0.13275181, -0.10596104, -0.09671903, + -0.10022582, -0.10660703]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=0.9474902352534894, shift=array([9.47490235, 0.99993647])), candidate_index=61, candidate_x=array([7.53569564, 1.02680097]), index=61, x=array([7.53569564, 1.02680097]), fval=0.557843378100565, rho=0.7126019978012866, accepted=True, new_indices=array([], dtype=int32), old_indices_used=array([10, 30, 52, 54, 55, 56, 57, 59, 60]), old_indices_discarded=array([ 0, 1, 3, 6, 7, 9, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, + 22, 23, 24, 25, 26, 27, 28, 29, 31, 32, 33, 34, 35, 36, 37, 38, 39, + 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 53, 58]), step_length=0.36946477399899075, relative_step_length=0.7798809111740238, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([7.53569564, 1.02680097]), radius=0.9474902352534894, bounds=Bounds(lower=array([1.1, 0.5]), upper=array([20. , 1.1]))), model_indices=array([30, 52, 54, 55, 56, 57, 59, 60, 61]), model=ScalarModel(intercept=12.13842084066151, linear_terms=array([ -0.90389113, -30.58695776]), square_terms=array([[ 0.04679947, 1.22766505], + [ 1.22766505, 40.38597232]]), scale=array([0.83969136, 0.3 ]), shift=array([7.53569564, 0.8 ])), vector_model=VectorModel(intercepts=array([ 0.0503911 , 0.12838033, 0.15541499, 0.20185793, 0.22718579, + 0.24311703, 0.24583074, 0.08262932, -0.06406015, -0.05102962, + -0.39325651, -0.40243304, -0.13275181, -0.10596104, -0.09671903, + -0.10022582, -0.10660703]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=0.9474902352534894, shift=array([9.47490235, 0.99993647])), candidate_index=62, candidate_x=array([6.69600428, 1.03632926]), index=62, x=array([6.69600428, 1.03632926]), fval=0.5424834330682993, rho=0.7246036090517496, accepted=True, new_indices=array([], dtype=int32), old_indices_used=array([30, 52, 54, 55, 56, 57, 59, 60, 61]), old_indices_discarded=array([ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, + 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 31, 32, 33, 34, + 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, + 53, 58]), step_length=0.8397454168164292, relative_step_length=0.88628398011064, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([6.69600428, 1.03632926]), radius=1.8949804705069788, bounds=Bounds(lower=array([1.1, 0.5]), upper=array([20. , 1.1]))), model_indices=array([52, 54, 55, 56, 57, 59, 60, 61, 62]), model=ScalarModel(intercept=13.436478042611053, linear_terms=array([ -1.77594432, -32.96460288]), square_terms=array([[ 0.1709616 , 2.30049165], + [ 2.30049165, 42.12835475]]), scale=array([1.67938272, 0.3 ]), shift=array([6.69600428, 0.8 ])), vector_model=VectorModel(intercepts=array([ 0.0503911 , 0.12838033, 0.15541499, 0.20185793, 0.22718579, + 0.24311703, 0.24583074, 0.08262932, -0.06406015, -0.05102962, + -0.39325651, -0.40243304, -0.13275181, -0.10596104, -0.09671903, + -0.10022582, -0.10660703]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=0.9474902352534894, shift=array([9.47490235, 0.99993647])), candidate_index=63, candidate_x=array([6.58843012, 1.03594893]), index=63, x=array([6.58843012, 1.03594893]), fval=0.5414632317465802, rho=0.501065213354614, accepted=True, new_indices=array([], dtype=int32), old_indices_used=array([52, 54, 55, 56, 57, 59, 60, 61, 62]), old_indices_discarded=array([ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, + 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, + 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, + 51, 53, 58]), step_length=0.10757483992757301, relative_step_length=0.05676831059836341, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([6.58843012, 1.03594893]), radius=1.8949804705069788, bounds=Bounds(lower=array([1.1, 0.5]), upper=array([20. , 1.1]))), model_indices=array([54, 55, 56, 57, 59, 60, 61, 62, 63]), model=ScalarModel(intercept=13.527389310158597, linear_terms=array([ -1.76412438, -33.07272766]), square_terms=array([[ 0.17044821, 2.26794554], + [ 2.26794554, 42.11033571]]), scale=array([1.67938272, 0.3 ]), shift=array([6.58843012, 0.8 ])), vector_model=VectorModel(intercepts=array([ 0.0503911 , 0.12838033, 0.15541499, 0.20185793, 0.22718579, + 0.24311703, 0.24583074, 0.08262932, -0.06406015, -0.05102962, + -0.39325651, -0.40243304, -0.13275181, -0.10596104, -0.09671903, + -0.10022582, -0.10660703]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=0.9474902352534894, shift=array([9.47490235, 0.99993647])), candidate_index=64, candidate_x=array([5.99457255, 1.04132824]), index=63, x=array([6.58843012, 1.03594893]), fval=0.5414632317465802, rho=-2.858177349740313, accepted=False, new_indices=array([], dtype=int32), old_indices_used=array([54, 55, 56, 57, 59, 60, 61, 62, 63]), old_indices_discarded=array([ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, + 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, + 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, + 51, 52, 53, 58]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([6.58843012, 1.03594893]), radius=0.9474902352534894, bounds=Bounds(lower=array([1.1, 0.5]), upper=array([20. , 1.1]))), model_indices=array([55, 56, 57, 59, 60, 61, 62, 63, 64]), model=ScalarModel(intercept=13.033433276409284, linear_terms=array([ -0.7928235 , -31.91157346]), square_terms=array([[3.91876133e-02, 1.01921230e+00], + [1.01921230e+00, 4.07663306e+01]]), scale=array([0.83969136, 0.3 ]), shift=array([6.58843012, 0.8 ])), vector_model=VectorModel(intercepts=array([ 0.0503911 , 0.12838033, 0.15541499, 0.20185793, 0.22718579, + 0.24311703, 0.24583074, 0.08262932, -0.06406015, -0.05102962, + -0.39325651, -0.40243304, -0.13275181, -0.10596104, -0.09671903, + -0.10022582, -0.10660703]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=0.9474902352534894, shift=array([9.47490235, 0.99993647])), candidate_index=65, candidate_x=array([6.28160798, 1.03757835]), index=63, x=array([6.58843012, 1.03594893]), fval=0.5414632317465802, rho=-1.670491030486846, accepted=False, new_indices=array([], dtype=int32), old_indices_used=array([55, 56, 57, 59, 60, 61, 62, 63, 64]), old_indices_discarded=array([ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, + 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, + 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, + 51, 52, 53, 54, 58]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([6.58843012, 1.03594893]), radius=0.4737451176267447, bounds=Bounds(lower=array([1.1, 0.5]), upper=array([20. , 1.1]))), model_indices=array([55, 57, 59, 60, 61, 62, 63, 64, 65]), model=ScalarModel(intercept=7.57645714444444, linear_terms=array([ -0.29574748, -19.22814953]), square_terms=array([[9.87830891e-03, 4.07101559e-01], + [4.07101559e-01, 2.62853990e+01]]), scale=array([0.41984568, 0.24194837]), shift=array([6.58843012, 0.85805163])), vector_model=VectorModel(intercepts=array([ 0.0503911 , 0.12838033, 0.15541499, 0.20185793, 0.22718579, + 0.24311703, 0.24583074, 0.08262932, -0.06406015, -0.05102962, + -0.39325651, -0.40243304, -0.13275181, -0.10596104, -0.09671903, + -0.10022582, -0.10660703]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=0.9474902352534894, shift=array([9.47490235, 0.99993647])), candidate_index=66, candidate_x=array([6.34718361, 1.03719355]), index=63, x=array([6.58843012, 1.03594893]), fval=0.5414632317465802, rho=-1.608088619606695, accepted=False, new_indices=array([], dtype=int32), old_indices_used=array([55, 57, 59, 60, 61, 62, 63, 64, 65]), old_indices_discarded=array([ 1, 3, 7, 10, 13, 30, 31, 32, 35, 37, 38, 39, 41, 42, 43, 44, 45, + 46, 47, 48, 49, 50, 51, 52, 53, 54, 56, 58]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([6.58843012, 1.03594893]), radius=0.23687255881337235, bounds=Bounds(lower=array([1.1, 0.5]), upper=array([20. , 1.1]))), model_indices=array([61, 62, 63, 64, 65, 66]), model=ScalarModel(intercept=2.51780763816455, linear_terms=array([-0.09621641, -7.35783746]), square_terms=array([[3.42399524e-03, 1.80214137e-01], + [1.80214137e-01, 1.37071817e+01]]), scale=array([0.20992284, 0.13698695]), shift=array([6.58843012, 0.96301305])), vector_model=VectorModel(intercepts=array([ 0.0503911 , 0.12838033, 0.15541499, 0.20185793, 0.22718579, + 0.24311703, 0.24583074, 0.08262932, -0.06406015, -0.05102962, + -0.39325651, -0.40243304, -0.13275181, -0.10596104, -0.09671903, + -0.10022582, -0.10660703]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=0.9474902352534894, shift=array([9.47490235, 0.99993647])), candidate_index=67, candidate_x=array([6.48488598, 1.03743422]), index=63, x=array([6.58843012, 1.03594893]), fval=0.5414632317465802, rho=-1.0724059676808537, accepted=False, new_indices=array([], dtype=int32), old_indices_used=array([61, 62, 63, 64, 65, 66]), old_indices_discarded=array([], dtype=int32), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([6.58843012, 1.03594893]), radius=0.11843627940668618, bounds=Bounds(lower=array([1.1, 0.5]), upper=array([20. , 1.1]))), model_indices=array([62, 63, 65, 66, 67]), model=ScalarModel(intercept=0.7479032481802277, linear_terms=array([-0.01574272, -1.69550858]), square_terms=array([[8.99601089e-04, 6.45218243e-02], + [6.45218243e-02, 6.96729079e+00]]), scale=array([0.10496142, 0.08450624]), shift=array([6.58843012, 1.01549376])), vector_model=VectorModel(intercepts=array([ 0.0503911 , 0.12838033, 0.15541499, 0.20185793, 0.22718579, + 0.24311703, 0.24583074, 0.08262932, -0.06406015, -0.05102962, + -0.39325651, -0.40243304, -0.13275181, -0.10596104, -0.09671903, + -0.10022582, -0.10660703]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=0.9474902352534894, shift=array([9.47490235, 0.99993647])), candidate_index=68, candidate_x=array([6.60273304, 1.03595193]), index=68, x=array([6.60273304, 1.03595193]), fval=0.5414533040238657, rho=1.1451990693564231, accepted=True, new_indices=array([], dtype=int32), old_indices_used=array([62, 63, 65, 66, 67]), old_indices_discarded=array([], dtype=int32), step_length=0.014302919721513424, relative_step_length=0.12076468285870495, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([6.60273304, 1.03595193]), radius=0.11843627940668618, bounds=Bounds(lower=array([1.1, 0.5]), upper=array([20. , 1.1]))), model_indices=array([62, 63, 65, 66, 67, 68]), model=ScalarModel(intercept=0.7438421645946036, linear_terms=array([-0.01554274, -1.67681543]), square_terms=array([[8.98462125e-04, 6.42713904e-02], + [6.42713904e-02, 6.94910166e+00]]), scale=array([0.10496142, 0.08450474]), shift=array([6.60273304, 1.01549526])), vector_model=VectorModel(intercepts=array([ 0.0503911 , 0.12838033, 0.15541499, 0.20185793, 0.22718579, + 0.24311703, 0.24583074, 0.08262932, -0.06406015, -0.05102962, + -0.39325651, -0.40243304, -0.13275181, -0.10596104, -0.09671903, + -0.10022582, -0.10660703]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=0.9474902352534894, shift=array([9.47490235, 0.99993647])), candidate_index=69, candidate_x=array([6.61449989, 1.0357986 ]), index=69, x=array([6.61449989, 1.0357986 ]), fval=0.5414101559834424, rho=10.755716308584471, accepted=True, new_indices=array([], dtype=int32), old_indices_used=array([62, 63, 65, 66, 67, 68]), old_indices_discarded=array([], dtype=int32), step_length=0.011767854290167887, relative_step_length=0.09936021588249544, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([6.61449989, 1.0357986 ]), radius=0.11843627940668618, bounds=Bounds(lower=array([1.1, 0.5]), upper=array([20. , 1.1]))), model_indices=array([62, 63, 65, 66, 67, 68, 69]), model=ScalarModel(intercept=0.7410229267529151, linear_terms=array([-0.01539784, -1.66026198]), square_terms=array([[8.96829948e-04, 6.39617448e-02], + [6.39617448e-02, 6.90724557e+00]]), scale=array([0.10496142, 0.08458141]), shift=array([6.61449989, 1.01541859])), vector_model=VectorModel(intercepts=array([ 0.0503911 , 0.12838033, 0.15541499, 0.20185793, 0.22718579, + 0.24311703, 0.24583074, 0.08262932, -0.06406015, -0.05102962, + -0.39325651, -0.40243304, -0.13275181, -0.10596104, -0.09671903, + -0.10022582, -0.10660703]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=0.9474902352534894, shift=array([9.47490235, 0.99993647])), candidate_index=70, candidate_x=array([6.62265463, 1.03568817]), index=69, x=array([6.61449989, 1.0357986 ]), fval=0.5414101559834424, rho=-22.25987391656959, accepted=False, new_indices=array([], dtype=int32), old_indices_used=array([62, 63, 65, 66, 67, 68, 69]), old_indices_discarded=array([], dtype=int32), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([6.61449989, 1.0357986 ]), radius=0.05921813970334309, bounds=Bounds(lower=array([1.1, 0.5]), upper=array([20. , 1.1]))), model_indices=array([62, 63, 66, 67, 68, 69, 70]), model=ScalarModel(intercept=0.5414839920684693, linear_terms=array([4.15483856e-05, 3.93468494e-03]), square_terms=array([[2.84874482e-04, 2.52791748e-02], + [2.52791748e-02, 3.36942768e+00]]), scale=0.05921813970334309, shift=array([6.61449989, 1.0357986 ])), vector_model=VectorModel(intercepts=array([ 0.0503911 , 0.12838033, 0.15541499, 0.20185793, 0.22718579, + 0.24311703, 0.24583074, 0.08262932, -0.06406015, -0.05102962, + -0.39325651, -0.40243304, -0.13275181, -0.10596104, -0.09671903, + -0.10022582, -0.10660703]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=0.9474902352534894, shift=array([9.47490235, 0.99993647])), candidate_index=71, candidate_x=array([6.60701913, 1.03578557]), index=69, x=array([6.61449989, 1.0357986 ]), fval=0.5414101559834424, rho=-16.79541545743258, accepted=False, new_indices=array([], dtype=int32), old_indices_used=array([62, 63, 66, 67, 68, 69, 70]), old_indices_discarded=array([], dtype=int32), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([6.61449989, 1.0357986 ]), radius=0.029609069851671544, bounds=Bounds(lower=array([1.1, 0.5]), upper=array([20. , 1.1]))), model_indices=array([62, 63, 67, 68, 69, 70, 71]), model=ScalarModel(intercept=0.5414615742402571, linear_terms=array([8.4752230e-05, 4.0438811e-03]), square_terms=array([[6.98826564e-05, 6.29275999e-03], + [6.29275999e-03, 8.41875305e-01]]), scale=0.029609069851671544, shift=array([6.61449989, 1.0357986 ])), vector_model=VectorModel(intercepts=array([ 0.0503911 , 0.12838033, 0.15541499, 0.20185793, 0.22718579, + 0.24311703, 0.24583074, 0.08262932, -0.06406015, -0.05102962, + -0.39325651, -0.40243304, -0.13275181, -0.10596104, -0.09671903, + -0.10022582, -0.10660703]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=0.9474902352534894, shift=array([9.47490235, 0.99993647])), candidate_index=72, candidate_x=array([6.58489072, 1.03587769]), index=69, x=array([6.61449989, 1.0357986 ]), fval=0.5414101559834424, rho=-1.588880786010452, accepted=False, new_indices=array([], dtype=int32), old_indices_used=array([62, 63, 67, 68, 69, 70, 71]), old_indices_discarded=array([], dtype=int32), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([6.61449989, 1.0357986 ]), radius=0.014804534925835772, bounds=Bounds(lower=array([1.1, 0.5]), upper=array([20. , 1.1]))), model_indices=array([63, 68, 69, 70, 71, 72]), model=ScalarModel(intercept=0.5414393947813702, linear_terms=array([-2.11246402e-05, -1.93873062e-03]), square_terms=array([[1.87338726e-05, 1.64576236e-03], + [1.64576236e-03, 2.06670312e-01]]), scale=0.014804534925835772, shift=array([6.61449989, 1.0357986 ])), vector_model=VectorModel(intercepts=array([ 0.0503911 , 0.12838033, 0.15541499, 0.20185793, 0.22718579, + 0.24311703, 0.24583074, 0.08262932, -0.06406015, -0.05102962, + -0.39325651, -0.40243304, -0.13275181, -0.10596104, -0.09671903, + -0.10022582, -0.10660703]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=0.9474902352534894, shift=array([9.47490235, 0.99993647])), candidate_index=73, candidate_x=array([6.62945645, 1.03581837]), index=69, x=array([6.61449989, 1.0357986 ]), fval=0.5414101559834424, rho=-10.089924952581605, accepted=False, new_indices=array([], dtype=int32), old_indices_used=array([63, 68, 69, 70, 71, 72]), old_indices_discarded=array([], dtype=int32), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([6.61449989, 1.0357986 ]), radius=0.007402267462917886, bounds=Bounds(lower=array([1.1, 0.5]), upper=array([20. , 1.1]))), model_indices=array([63, 68, 69, 70, 71, 72, 73]), model=ScalarModel(intercept=0.5414619458203902, linear_terms=array([6.9562924e-06, 8.5447900e-04]), square_terms=array([[4.61608585e-06, 4.03102152e-04], + [4.03102152e-04, 5.06614459e-02]]), scale=0.007402267462917886, shift=array([6.61449989, 1.0357986 ])), vector_model=VectorModel(intercepts=array([ 0.0503911 , 0.12838033, 0.15541499, 0.20185793, 0.22718579, + 0.24311703, 0.24583074, 0.08262932, -0.06406015, -0.05102962, + -0.39325651, -0.40243304, -0.13275181, -0.10596104, -0.09671903, + -0.10022582, -0.10660703]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=0.9474902352534894, shift=array([9.47490235, 0.99993647])), candidate_index=74, candidate_x=array([6.60709792, 1.03573282]), index=69, x=array([6.61449989, 1.0357986 ]), fval=0.5414101559834424, rho=-19.52833863302675, accepted=False, new_indices=array([], dtype=int32), old_indices_used=array([63, 68, 69, 70, 71, 72, 73]), old_indices_discarded=array([], dtype=int32), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([6.61449989, 1.0357986 ]), radius=0.003701133731458943, bounds=Bounds(lower=array([1.1, 0.5]), upper=array([20. , 1.1]))), model_indices=array([68, 69, 70, 71, 73, 74]), model=ScalarModel(intercept=0.5414709833059852, linear_terms=array([ 2.31365098e-06, -2.97464372e-04]), square_terms=array([[1.14990591e-06, 1.00511445e-04], + [1.00511445e-04, 1.26982949e-02]]), scale=0.003701133731458943, shift=array([6.61449989, 1.0357986 ])), vector_model=VectorModel(intercepts=array([ 0.0503911 , 0.12838033, 0.15541499, 0.20185793, 0.22718579, + 0.24311703, 0.24583074, 0.08262932, -0.06406015, -0.05102962, + -0.39325651, -0.40243304, -0.13275181, -0.10596104, -0.09671903, + -0.10022582, -0.10660703]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=0.9474902352534894, shift=array([9.47490235, 0.99993647])), candidate_index=75, candidate_x=array([6.61079958, 1.03591455]), index=69, x=array([6.61449989, 1.0357986 ]), fval=0.5414101559834424, rho=-7.139306274741185, accepted=False, new_indices=array([], dtype=int32), old_indices_used=array([68, 69, 70, 71, 73, 74]), old_indices_discarded=array([], dtype=int32), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([6.61449989, 1.0357986 ]), radius=0.0018505668657294715, bounds=Bounds(lower=array([1.1, 0.5]), upper=array([20. , 1.1]))), model_indices=array([69, 70, 71, 74, 75]), model=ScalarModel(intercept=0.5414505447289019, linear_terms=array([-8.39195189e-06, -4.82590678e-04]), square_terms=array([[2.93663647e-07, 2.57520778e-05], + [2.57520778e-05, 3.23949356e-03]]), scale=0.0018505668657294715, shift=array([6.61449989, 1.0357986 ])), vector_model=VectorModel(intercepts=array([ 0.0503911 , 0.12838033, 0.15541499, 0.20185793, 0.22718579, + 0.24311703, 0.24583074, 0.08262932, -0.06406015, -0.05102962, + -0.39325651, -0.40243304, -0.13275181, -0.10596104, -0.09671903, + -0.10022582, -0.10660703]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=0.9474902352534894, shift=array([9.47490235, 0.99993647])), candidate_index=76, candidate_x=array([6.61635257, 1.03605919]), index=69, x=array([6.61449989, 1.0357986 ]), fval=0.5414101559834424, rho=-5.448243640313255, accepted=False, new_indices=array([], dtype=int32), old_indices_used=array([69, 70, 71, 74, 75]), old_indices_discarded=array([], dtype=int32), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([6.61449989, 1.0357986 ]), radius=0.0009252834328647358, bounds=Bounds(lower=array([1.1, 0.5]), upper=array([20. , 1.1]))), model_indices=array([69, 75, 76]), model=ScalarModel(intercept=0.5414101559834426, linear_terms=array([6.06884618e-06, 6.19553068e-04]), square_terms=array([[7.09654175e-08, 5.99044034e-06], + [5.99044034e-06, 7.63676033e-04]]), scale=0.0009252834328647358, shift=array([6.61449989, 1.0357986 ])), vector_model=VectorModel(intercepts=array([ 0.0503911 , 0.12838033, 0.15541499, 0.20185793, 0.22718579, + 0.24311703, 0.24583074, 0.08262932, -0.06406015, -0.05102962, + -0.39325651, -0.40243304, -0.13275181, -0.10596104, -0.09671903, + -0.10022582, -0.10660703]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=0.9474902352534894, shift=array([9.47490235, 0.99993647])), candidate_index=77, candidate_x=array([6.61386667, 1.03505462]), index=69, x=array([6.61449989, 1.0357986 ]), fval=0.5414101559834424, rho=-1.3196468367629774, accepted=False, new_indices=array([], dtype=int32), old_indices_used=array([69, 75, 76]), old_indices_discarded=array([], dtype=int32), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([6.61449989, 1.0357986 ]), radius=0.0004626417164323679, bounds=Bounds(lower=array([1.1, 0.5]), upper=array([20. , 1.1]))), model_indices=array([69, 76, 77]), model=ScalarModel(intercept=0.5414101559834427, linear_terms=array([ 5.92027706e-05, -8.95483752e-05]), square_terms=array([[1.36984529e-08, 3.03717688e-07], + [3.03717688e-07, 2.08099140e-04]]), scale=0.0004626417164323679, shift=array([6.61449989, 1.0357986 ])), vector_model=VectorModel(intercepts=array([ 0.0503911 , 0.12838033, 0.15541499, 0.20185793, 0.22718579, + 0.24311703, 0.24583074, 0.08262932, -0.06406015, -0.05102962, + -0.39325651, -0.40243304, -0.13275181, -0.10596104, -0.09671903, + -0.10022582, -0.10660703]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + 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6.94508729])}}" diff --git a/code/estimark/content/tables/min/Portfolio_estimate_results.csv b/code/estimark/content/tables/min/Portfolio_estimate_results.csv new file mode 100644 index 0000000..08b399b --- /dev/null +++ b/code/estimark/content/tables/min/Portfolio_estimate_results.csv @@ -0,0 +1,1067 @@ +CRRA,9.25239894900598 +time_to_estimate,45.062182664871216 +params,{'CRRA': 9.25239894900598} +criterion,0.6423583869781233 +start_criterion,0.9309824869808929 +start_params,{'CRRA': 6.614528749695077} +algorithm,multistart_tranquilo_ls +direction,minimize +n_free,1 +message,Absolute criterion change smaller than tolerance. +success, +n_criterion_evaluations, +n_derivative_evaluations, +n_iterations, +history,"{'params': [{'CRRA': 8.1875}, {'CRRA': 7.36875}, {'CRRA': 9.00625}, {'CRRA': 7.36875}, {'CRRA': 7.36875}, {'CRRA': 9.00625}, {'CRRA': 7.36875}, {'CRRA': 7.36875}, {'CRRA': 9.00625}, {'CRRA': 7.36875}, {'CRRA': 9.00625}, {'CRRA': 7.36875}, {'CRRA': 9.00625}, {'CRRA': 9.00625}, {'CRRA': 7.3687499999999995}, {'CRRA': 9.026168169426626}, {'CRRA': 7.388668169426626}, {'CRRA': 9.038959312915338}, {'CRRA': 10.676459312915338}, {'CRRA': 9.290153724085462}, {'CRRA': 7.652653724085462}, {'CRRA': 9.235117007166322}, {'CRRA': 8.416367007166322}, {'CRRA': 9.1520466847697}, {'CRRA': 9.644492007166322}, {'CRRA': 9.248676532750787}, {'CRRA': 9.658051532750788}, {'CRRA': 9.252525969850202}, {'CRRA': 9.661900969850203}, {'CRRA': 9.25239894900598}], 'criterion': [0.6831279025699917, 0.7818234415442017, 0.6443932011688029, 0.7818234415442017, 0.7818234415442017, 0.6443932011688029, 0.7818234415442017, 0.7818234415442017, 0.6443932011688029, 0.7818234415442017, 0.6443932011688029, 0.7818234415442017, 0.6443932011688029, 0.6443932011688029, 0.7818234415442095, 0.6440402472439135, 0.7787614029619838, 0.6439435808488991, 0.7100198965757869, 0.642415138936857, 0.740451029529312, 0.6424025578938513, 0.6665435566959452, 0.6426661753949429, 0.6484718333650715, 0.6423803321514743, 0.6489393340909813, 0.642358861106374, 0.6490529814080408, 0.6423583869781233], 'runtime': [0.0, 3.074203699827194, 3.283573899883777, 3.498749100137502, 3.7044561998918653, 3.926607399713248, 4.110963100101799, 4.243899200111628, 4.541710100136697, 4.7094960999675095, 4.89852079981938, 5.075110800098628, 5.21526509989053, 12.235306499991566, 15.733508999925107, 16.80475839972496, 17.874723799992353, 18.94831439992413, 20.016572599764913, 21.089213099796325, 22.262267199810594, 23.334850599989295, 24.407207199838012, 25.481976099777967, 26.552139800041914, 27.62647379981354, 28.800836499780416, 29.875069699715823, 30.947488199919462, 32.024298400152475], 'batches': [0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18]}" +convergence_report, +multistart_info,"{'start_parameters': [{'CRRA': 8.1875}], 'local_optima': [Minimize with 1 free parameters terminated. + +The tranquilo_ls algorithm reported: Absolute criterion change smaller than tolerance. + +Independent of the convergence criteria used by tranquilo_ls, the strength of convergence can be assessed by the following criteria: + + one_step five_steps +relative_criterion_change 7.381e-07* 0.002468 +relative_params_change 1.373e-05 0.02307 +absolute_criterion_change 4.741e-07* 0.001585 +absolute_params_change 0.000127 0.2134 + +(***: change <= 1e-10, **: change <= 1e-8, *: change <= 1e-5. Change refers to a change between accepted steps. The first column only considers the last step. The second column considers the last five steps.)], 'exploration_sample': [{'CRRA': 8.1875}, {'CRRA': 10.549999999999999}, {'CRRA': 6.614528749695077}, {'CRRA': 12.9125}, {'CRRA': 5.824999999999999}, {'CRRA': 14.093749999999998}, {'CRRA': 15.274999999999999}, {'CRRA': 4.64375}, {'CRRA': 17.6375}, {'CRRA': 3.4625}], 'exploration_results': array([0.6831279 , 0.69939713, 0.93725113, 1.02360977, 1.18227674, + 1.26376333, 1.54278366, 1.78141341, 2.1808234 , 2.89794431])}" +algorithm_output,"{'states': [State(trustregion=Region(center=array([8.1875]), radius=0.8187500000000001, bounds=Bounds(lower=array([1.1]), upper=array([20.]))), model_indices=[0], model=ScalarModel(intercept=0.6831279025699917, linear_terms=array([0.]), square_terms=array([[0.]]), scale=0.8187500000000001, shift=array([8.1875])), vector_model=VectorModel(intercepts=array([ 0.04052564, 0.1019965 , 0.11618873, 0.15222976, 0.16876834, + 0.17571046, 0.17052397, -0.01190259, -0.1602348 , -0.14801994, + -0.48805873, -0.49085003, -0.08278535, -0.05708457, -0.04823565, + -0.0535541 , -0.06168149]), linear_terms=array([[0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.]]), square_terms=array([[[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]]]), scale=0.8187500000000001, shift=array([8.1875])), candidate_index=0, candidate_x=array([8.1875]), index=0, x=array([8.1875]), fval=0.6831279025699917, rho=nan, accepted=True, new_indices=[0], old_indices_used=[], old_indices_discarded=[], step_length=None, relative_step_length=None, n_evals_per_point=None, n_evals_acceptance=None), State(trustregion=Region(center=array([8.1875]), radius=0.8187500000000001, bounds=Bounds(lower=array([1.1]), upper=array([20.]))), model_indices=array([ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12]), model=ScalarModel(intercept=0.6798922337586231, linear_terms=array([-0.06848896]), square_terms=array([[0.06703103]]), scale=0.8187500000000001, shift=array([8.1875])), vector_model=VectorModel(intercepts=array([ 0.04052564, 0.1019965 , 0.11618873, 0.15222976, 0.16876834, + 0.17571046, 0.17052397, -0.01190259, -0.1602348 , -0.14801994, + -0.48805873, -0.49085003, -0.08278535, -0.05708457, -0.04823565, + -0.0535541 , -0.06168149]), linear_terms=array([[0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.]]), square_terms=array([[[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]]]), scale=0.8187500000000001, shift=array([8.1875])), candidate_index=13, candidate_x=array([9.00625]), index=13, x=array([9.00625]), fval=0.6443932011688028, rho=1.1075462640286373, accepted=True, new_indices=array([ 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12]), old_indices_used=array([0]), old_indices_discarded=array([], dtype=int32), step_length=0.8187499999999996, relative_step_length=0.9999999999999994, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([9.00625]), radius=1.6375000000000002, bounds=Bounds(lower=array([1.1]), upper=array([20.]))), model_indices=array([ 0, 1, 2, 12, 13, 14]), model=ScalarModel(intercept=0.6451809482519073, linear_terms=array([-0.00325077]), square_terms=array([[0.26725027]]), scale=1.6375000000000002, shift=array([9.00625])), vector_model=VectorModel(intercepts=array([ 0.04052564, 0.1019965 , 0.11618873, 0.15222976, 0.16876834, + 0.17571046, 0.17052397, -0.01190259, -0.1602348 , -0.14801994, + -0.48805873, -0.49085003, -0.08278535, -0.05708457, -0.04823565, + -0.0535541 , -0.06168149]), linear_terms=array([[0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.]]), square_terms=array([[[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]]]), scale=0.8187500000000001, shift=array([8.1875])), candidate_index=15, candidate_x=array([9.02616817]), index=15, x=array([9.02616817]), fval=0.6440402472439134, rho=17.852277387983314, accepted=True, new_indices=array([14]), old_indices_used=array([ 0, 1, 2, 12, 13]), old_indices_discarded=array([ 3, 4, 5, 6, 7, 8, 9, 10, 11]), step_length=0.019918169426626164, relative_step_length=0.012163767588779335, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([9.02616817]), radius=1.6375000000000002, bounds=Bounds(lower=array([1.1]), upper=array([20.]))), model_indices=array([ 0, 2, 12, 13, 15, 16]), model=ScalarModel(intercept=0.6447879200688609, linear_terms=array([-0.00206742]), square_terms=array([[0.26466733]]), scale=1.6375000000000002, shift=array([9.02616817])), vector_model=VectorModel(intercepts=array([ 0.04052564, 0.1019965 , 0.11618873, 0.15222976, 0.16876834, + 0.17571046, 0.17052397, -0.01190259, -0.1602348 , -0.14801994, + -0.48805873, -0.49085003, -0.08278535, -0.05708457, -0.04823565, + -0.0535541 , -0.06168149]), linear_terms=array([[0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.]]), square_terms=array([[[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]]]), scale=0.8187500000000001, shift=array([8.1875])), candidate_index=17, candidate_x=array([9.03895931]), index=17, x=array([9.03895931]), fval=0.6439435808488991, rho=11.971513486470478, accepted=True, new_indices=array([16]), old_indices_used=array([ 0, 2, 12, 13, 15]), old_indices_discarded=array([ 1, 3, 4, 5, 6, 7, 8, 9, 10, 11, 14]), step_length=0.012791143488712464, relative_step_length=0.007811385336618298, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([9.03895931]), radius=1.6375000000000002, bounds=Bounds(lower=array([1.1]), upper=array([20.]))), model_indices=array([ 0, 2, 13, 15, 17, 18]), model=ScalarModel(intercept=0.640887156447643, linear_terms=array([-0.03350583]), square_terms=array([[0.21841968]]), scale=1.6375000000000002, shift=array([9.03895931])), vector_model=VectorModel(intercepts=array([ 0.04052564, 0.1019965 , 0.11618873, 0.15222976, 0.16876834, + 0.17571046, 0.17052397, -0.01190259, -0.1602348 , -0.14801994, + -0.48805873, -0.49085003, -0.08278535, -0.05708457, -0.04823565, + -0.0535541 , -0.06168149]), linear_terms=array([[0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.]]), square_terms=array([[[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]]]), scale=0.8187500000000001, shift=array([8.1875])), candidate_index=19, candidate_x=array([9.29015372]), index=19, x=array([9.29015372]), fval=0.6424151389368569, rho=0.5947436919672805, accepted=True, new_indices=array([18]), old_indices_used=array([ 0, 2, 13, 15, 17]), old_indices_discarded=array([ 1, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 14, 16]), step_length=0.25119441117012364, relative_step_length=0.15340116712679305, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([9.29015372]), radius=1.6375000000000002, bounds=Bounds(lower=array([1.1]), upper=array([20.]))), model_indices=array([ 0, 2, 15, 18, 19, 20]), model=ScalarModel(intercept=0.6360123591878122, linear_terms=array([0.0077497]), square_terms=array([[0.23057571]]), scale=1.6375000000000002, shift=array([9.29015372])), vector_model=VectorModel(intercepts=array([ 0.04052564, 0.1019965 , 0.11618873, 0.15222976, 0.16876834, + 0.17571046, 0.17052397, -0.01190259, -0.1602348 , -0.14801994, + -0.48805873, -0.49085003, -0.08278535, -0.05708457, -0.04823565, + -0.0535541 , -0.06168149]), linear_terms=array([[0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.]]), square_terms=array([[[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]]]), scale=0.8187500000000001, shift=array([8.1875])), candidate_index=21, candidate_x=array([9.23511701]), index=21, x=array([9.23511701]), fval=0.6424025578938514, rho=0.09660301085246886, accepted=True, new_indices=array([20]), old_indices_used=array([ 0, 2, 15, 18, 19]), old_indices_discarded=array([ 1, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 16, 17]), step_length=0.05503671691914036, relative_step_length=0.033610208805581895, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([9.23511701]), radius=0.8187500000000001, bounds=Bounds(lower=array([1.1]), upper=array([20.]))), model_indices=array([ 2, 15, 17, 19, 21, 22]), model=ScalarModel(intercept=0.6429673760619858, linear_terms=array([0.0061267]), square_terms=array([[0.06038539]]), scale=0.8187500000000001, shift=array([9.23511701])), vector_model=VectorModel(intercepts=array([ 0.04052564, 0.1019965 , 0.11618873, 0.15222976, 0.16876834, + 0.17571046, 0.17052397, -0.01190259, -0.1602348 , -0.14801994, + -0.48805873, -0.49085003, -0.08278535, -0.05708457, -0.04823565, + -0.0535541 , -0.06168149]), linear_terms=array([[0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.]]), square_terms=array([[[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]]]), scale=0.8187500000000001, shift=array([8.1875])), candidate_index=23, candidate_x=array([9.15204668]), index=21, x=array([9.23511701]), fval=0.6424025578938514, rho=-0.8481705078488714, accepted=False, new_indices=array([22]), old_indices_used=array([ 2, 15, 17, 19, 21]), old_indices_discarded=array([ 0, 1, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 16, 18, 20]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([9.23511701]), radius=0.40937500000000004, bounds=Bounds(lower=array([1.1]), upper=array([20.]))), model_indices=array([ 2, 15, 19, 21, 23, 24]), model=ScalarModel(intercept=0.6421324295697537, linear_terms=array([-0.00046788]), square_terms=array([[0.01412584]]), scale=0.40937500000000004, shift=array([9.23511701])), vector_model=VectorModel(intercepts=array([ 0.04052564, 0.1019965 , 0.11618873, 0.15222976, 0.16876834, + 0.17571046, 0.17052397, -0.01190259, -0.1602348 , -0.14801994, + -0.48805873, -0.49085003, -0.08278535, -0.05708457, -0.04823565, + -0.0535541 , -0.06168149]), linear_terms=array([[0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.]]), square_terms=array([[[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]]]), scale=0.8187500000000001, shift=array([8.1875])), candidate_index=25, candidate_x=array([9.24867653]), index=25, x=array([9.24867653]), fval=0.6423803321514744, rho=2.8683063839230534, accepted=True, new_indices=array([24]), old_indices_used=array([ 2, 15, 19, 21, 23]), old_indices_discarded=array([ 0, 1, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 16, 17, 18, + 20, 22]), step_length=0.013559525584465604, relative_step_length=0.03312250524449613, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([9.24867653]), radius=0.40937500000000004, bounds=Bounds(lower=array([1.1]), upper=array([20.]))), model_indices=array([ 2, 19, 23, 24, 25, 26]), model=ScalarModel(intercept=0.6421484427735298, linear_terms=array([-0.00013227]), square_terms=array([[0.01406608]]), scale=0.40937500000000004, shift=array([9.24867653])), vector_model=VectorModel(intercepts=array([ 0.04052564, 0.1019965 , 0.11618873, 0.15222976, 0.16876834, + 0.17571046, 0.17052397, -0.01190259, -0.1602348 , -0.14801994, + -0.48805873, -0.49085003, -0.08278535, -0.05708457, -0.04823565, + -0.0535541 , -0.06168149]), linear_terms=array([[0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.]]), square_terms=array([[[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]]]), scale=0.8187500000000001, shift=array([8.1875])), candidate_index=27, candidate_x=array([9.25252597]), index=27, x=array([9.25252597]), fval=0.642358861106374, rho=34.526953193374496, accepted=True, new_indices=array([26]), old_indices_used=array([ 2, 19, 23, 24, 25]), old_indices_discarded=array([ 0, 1, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, + 18, 20, 21, 22]), step_length=0.0038494370994150984, relative_step_length=0.009403205128342224, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([9.25252597]), radius=0.40937500000000004, bounds=Bounds(lower=array([1.1]), upper=array([20.]))), model_indices=array([ 2, 19, 23, 26, 27, 28]), model=ScalarModel(intercept=0.64214537534659, linear_terms=array([4.36033832e-06]), square_terms=array([[0.01405292]]), scale=0.40937500000000004, shift=array([9.25252597])), vector_model=VectorModel(intercepts=array([ 0.04052564, 0.1019965 , 0.11618873, 0.15222976, 0.16876834, + 0.17571046, 0.17052397, -0.01190259, -0.1602348 , -0.14801994, + -0.48805873, -0.49085003, -0.08278535, -0.05708457, -0.04823565, + -0.0535541 , -0.06168149]), linear_terms=array([[0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.]]), square_terms=array([[[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]]]), scale=0.8187500000000001, shift=array([8.1875])), candidate_index=29, candidate_x=array([9.25239895]), index=29, x=array([9.25239895]), fval=0.6423583869781233, rho=700.8934507833044, accepted=True, new_indices=array([28]), old_indices_used=array([ 2, 19, 23, 26, 27]), old_indices_discarded=array([ 0, 1, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, + 18, 20, 21, 22, 24, 25]), step_length=0.00012702084422144821, relative_step_length=0.0003102799248157513, n_evals_per_point=1, n_evals_acceptance=1)], 'tranquilo_history': History for least_squares function with 30 entries., 'multistart_info': {'start_parameters': [array([8.1875])], 'local_optima': [{'solution_x': array([9.25239895]), 'solution_criterion': 0.6423583869781233, 'states': [State(trustregion=Region(center=array([8.1875]), radius=0.8187500000000001, bounds=Bounds(lower=array([1.1]), upper=array([20.]))), model_indices=[0], model=ScalarModel(intercept=0.6831279025699917, linear_terms=array([0.]), square_terms=array([[0.]]), scale=0.8187500000000001, shift=array([8.1875])), vector_model=VectorModel(intercepts=array([ 0.04052564, 0.1019965 , 0.11618873, 0.15222976, 0.16876834, + 0.17571046, 0.17052397, -0.01190259, -0.1602348 , -0.14801994, + -0.48805873, -0.49085003, -0.08278535, -0.05708457, -0.04823565, + -0.0535541 , -0.06168149]), linear_terms=array([[0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.]]), square_terms=array([[[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]]]), scale=0.8187500000000001, shift=array([8.1875])), candidate_index=0, candidate_x=array([8.1875]), index=0, x=array([8.1875]), fval=0.6831279025699917, rho=nan, accepted=True, new_indices=[0], old_indices_used=[], old_indices_discarded=[], step_length=None, relative_step_length=None, n_evals_per_point=None, n_evals_acceptance=None), State(trustregion=Region(center=array([8.1875]), radius=0.8187500000000001, bounds=Bounds(lower=array([1.1]), upper=array([20.]))), model_indices=array([ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12]), model=ScalarModel(intercept=0.6798922337586231, linear_terms=array([-0.06848896]), square_terms=array([[0.06703103]]), scale=0.8187500000000001, shift=array([8.1875])), vector_model=VectorModel(intercepts=array([ 0.04052564, 0.1019965 , 0.11618873, 0.15222976, 0.16876834, + 0.17571046, 0.17052397, -0.01190259, -0.1602348 , -0.14801994, + -0.48805873, -0.49085003, -0.08278535, -0.05708457, -0.04823565, + -0.0535541 , -0.06168149]), linear_terms=array([[0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.]]), square_terms=array([[[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]]]), scale=0.8187500000000001, shift=array([8.1875])), candidate_index=13, candidate_x=array([9.00625]), index=13, x=array([9.00625]), fval=0.6443932011688028, rho=1.1075462640286373, accepted=True, new_indices=array([ 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12]), old_indices_used=array([0]), old_indices_discarded=array([], dtype=int32), step_length=0.8187499999999996, relative_step_length=0.9999999999999994, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([9.00625]), radius=1.6375000000000002, bounds=Bounds(lower=array([1.1]), upper=array([20.]))), model_indices=array([ 0, 1, 2, 12, 13, 14]), model=ScalarModel(intercept=0.6451809482519073, linear_terms=array([-0.00325077]), square_terms=array([[0.26725027]]), scale=1.6375000000000002, shift=array([9.00625])), vector_model=VectorModel(intercepts=array([ 0.04052564, 0.1019965 , 0.11618873, 0.15222976, 0.16876834, + 0.17571046, 0.17052397, -0.01190259, -0.1602348 , -0.14801994, + -0.48805873, -0.49085003, -0.08278535, -0.05708457, -0.04823565, + -0.0535541 , -0.06168149]), linear_terms=array([[0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.]]), square_terms=array([[[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]]]), scale=0.8187500000000001, shift=array([8.1875])), candidate_index=15, candidate_x=array([9.02616817]), index=15, x=array([9.02616817]), fval=0.6440402472439134, rho=17.852277387983314, accepted=True, new_indices=array([14]), old_indices_used=array([ 0, 1, 2, 12, 13]), old_indices_discarded=array([ 3, 4, 5, 6, 7, 8, 9, 10, 11]), step_length=0.019918169426626164, relative_step_length=0.012163767588779335, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([9.02616817]), radius=1.6375000000000002, bounds=Bounds(lower=array([1.1]), upper=array([20.]))), model_indices=array([ 0, 2, 12, 13, 15, 16]), model=ScalarModel(intercept=0.6447879200688609, linear_terms=array([-0.00206742]), square_terms=array([[0.26466733]]), scale=1.6375000000000002, shift=array([9.02616817])), vector_model=VectorModel(intercepts=array([ 0.04052564, 0.1019965 , 0.11618873, 0.15222976, 0.16876834, + 0.17571046, 0.17052397, -0.01190259, -0.1602348 , -0.14801994, + -0.48805873, -0.49085003, -0.08278535, -0.05708457, -0.04823565, + -0.0535541 , -0.06168149]), linear_terms=array([[0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.]]), square_terms=array([[[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]]]), scale=0.8187500000000001, shift=array([8.1875])), candidate_index=17, candidate_x=array([9.03895931]), index=17, x=array([9.03895931]), fval=0.6439435808488991, rho=11.971513486470478, accepted=True, new_indices=array([16]), old_indices_used=array([ 0, 2, 12, 13, 15]), old_indices_discarded=array([ 1, 3, 4, 5, 6, 7, 8, 9, 10, 11, 14]), step_length=0.012791143488712464, relative_step_length=0.007811385336618298, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([9.03895931]), radius=1.6375000000000002, bounds=Bounds(lower=array([1.1]), upper=array([20.]))), model_indices=array([ 0, 2, 13, 15, 17, 18]), model=ScalarModel(intercept=0.640887156447643, linear_terms=array([-0.03350583]), square_terms=array([[0.21841968]]), scale=1.6375000000000002, shift=array([9.03895931])), vector_model=VectorModel(intercepts=array([ 0.04052564, 0.1019965 , 0.11618873, 0.15222976, 0.16876834, + 0.17571046, 0.17052397, -0.01190259, -0.1602348 , -0.14801994, + -0.48805873, -0.49085003, -0.08278535, -0.05708457, -0.04823565, + -0.0535541 , -0.06168149]), linear_terms=array([[0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.]]), square_terms=array([[[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]]]), scale=0.8187500000000001, shift=array([8.1875])), candidate_index=19, candidate_x=array([9.29015372]), index=19, x=array([9.29015372]), fval=0.6424151389368569, rho=0.5947436919672805, accepted=True, new_indices=array([18]), old_indices_used=array([ 0, 2, 13, 15, 17]), old_indices_discarded=array([ 1, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 14, 16]), step_length=0.25119441117012364, relative_step_length=0.15340116712679305, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([9.29015372]), radius=1.6375000000000002, bounds=Bounds(lower=array([1.1]), upper=array([20.]))), model_indices=array([ 0, 2, 15, 18, 19, 20]), model=ScalarModel(intercept=0.6360123591878122, linear_terms=array([0.0077497]), square_terms=array([[0.23057571]]), scale=1.6375000000000002, shift=array([9.29015372])), vector_model=VectorModel(intercepts=array([ 0.04052564, 0.1019965 , 0.11618873, 0.15222976, 0.16876834, + 0.17571046, 0.17052397, -0.01190259, -0.1602348 , -0.14801994, + -0.48805873, -0.49085003, -0.08278535, -0.05708457, -0.04823565, + -0.0535541 , -0.06168149]), linear_terms=array([[0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.]]), square_terms=array([[[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]]]), scale=0.8187500000000001, shift=array([8.1875])), candidate_index=21, candidate_x=array([9.23511701]), index=21, x=array([9.23511701]), fval=0.6424025578938514, rho=0.09660301085246886, accepted=True, new_indices=array([20]), old_indices_used=array([ 0, 2, 15, 18, 19]), old_indices_discarded=array([ 1, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 16, 17]), step_length=0.05503671691914036, relative_step_length=0.033610208805581895, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([9.23511701]), radius=0.8187500000000001, bounds=Bounds(lower=array([1.1]), upper=array([20.]))), model_indices=array([ 2, 15, 17, 19, 21, 22]), model=ScalarModel(intercept=0.6429673760619858, linear_terms=array([0.0061267]), square_terms=array([[0.06038539]]), scale=0.8187500000000001, shift=array([9.23511701])), vector_model=VectorModel(intercepts=array([ 0.04052564, 0.1019965 , 0.11618873, 0.15222976, 0.16876834, + 0.17571046, 0.17052397, -0.01190259, -0.1602348 , -0.14801994, + -0.48805873, -0.49085003, -0.08278535, -0.05708457, -0.04823565, + -0.0535541 , -0.06168149]), linear_terms=array([[0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.]]), square_terms=array([[[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]]]), scale=0.8187500000000001, shift=array([8.1875])), candidate_index=23, candidate_x=array([9.15204668]), index=21, x=array([9.23511701]), fval=0.6424025578938514, rho=-0.8481705078488714, accepted=False, new_indices=array([22]), old_indices_used=array([ 2, 15, 17, 19, 21]), old_indices_discarded=array([ 0, 1, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 16, 18, 20]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([9.23511701]), radius=0.40937500000000004, bounds=Bounds(lower=array([1.1]), upper=array([20.]))), model_indices=array([ 2, 15, 19, 21, 23, 24]), model=ScalarModel(intercept=0.6421324295697537, linear_terms=array([-0.00046788]), square_terms=array([[0.01412584]]), scale=0.40937500000000004, shift=array([9.23511701])), vector_model=VectorModel(intercepts=array([ 0.04052564, 0.1019965 , 0.11618873, 0.15222976, 0.16876834, + 0.17571046, 0.17052397, -0.01190259, -0.1602348 , -0.14801994, + -0.48805873, -0.49085003, -0.08278535, -0.05708457, -0.04823565, + -0.0535541 , -0.06168149]), linear_terms=array([[0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.]]), square_terms=array([[[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]]]), scale=0.8187500000000001, shift=array([8.1875])), candidate_index=25, candidate_x=array([9.24867653]), index=25, x=array([9.24867653]), fval=0.6423803321514744, rho=2.8683063839230534, accepted=True, new_indices=array([24]), old_indices_used=array([ 2, 15, 19, 21, 23]), old_indices_discarded=array([ 0, 1, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 16, 17, 18, + 20, 22]), step_length=0.013559525584465604, relative_step_length=0.03312250524449613, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([9.24867653]), radius=0.40937500000000004, bounds=Bounds(lower=array([1.1]), upper=array([20.]))), model_indices=array([ 2, 19, 23, 24, 25, 26]), model=ScalarModel(intercept=0.6421484427735298, linear_terms=array([-0.00013227]), square_terms=array([[0.01406608]]), scale=0.40937500000000004, shift=array([9.24867653])), vector_model=VectorModel(intercepts=array([ 0.04052564, 0.1019965 , 0.11618873, 0.15222976, 0.16876834, + 0.17571046, 0.17052397, -0.01190259, -0.1602348 , -0.14801994, + -0.48805873, -0.49085003, -0.08278535, -0.05708457, -0.04823565, + -0.0535541 , -0.06168149]), linear_terms=array([[0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.]]), square_terms=array([[[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]]]), scale=0.8187500000000001, shift=array([8.1875])), candidate_index=27, candidate_x=array([9.25252597]), index=27, x=array([9.25252597]), fval=0.642358861106374, rho=34.526953193374496, accepted=True, new_indices=array([26]), old_indices_used=array([ 2, 19, 23, 24, 25]), old_indices_discarded=array([ 0, 1, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, + 18, 20, 21, 22]), step_length=0.0038494370994150984, relative_step_length=0.009403205128342224, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([9.25252597]), radius=0.40937500000000004, bounds=Bounds(lower=array([1.1]), upper=array([20.]))), model_indices=array([ 2, 19, 23, 26, 27, 28]), model=ScalarModel(intercept=0.64214537534659, linear_terms=array([4.36033832e-06]), square_terms=array([[0.01405292]]), scale=0.40937500000000004, shift=array([9.25252597])), vector_model=VectorModel(intercepts=array([ 0.04052564, 0.1019965 , 0.11618873, 0.15222976, 0.16876834, + 0.17571046, 0.17052397, -0.01190259, -0.1602348 , -0.14801994, + -0.48805873, -0.49085003, -0.08278535, -0.05708457, -0.04823565, + -0.0535541 , -0.06168149]), linear_terms=array([[0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.], + [0.]]), square_terms=array([[[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]], + + [[0.]]]), scale=0.8187500000000001, shift=array([8.1875])), candidate_index=29, candidate_x=array([9.25239895]), index=29, x=array([9.25239895]), fval=0.6423583869781233, rho=700.8934507833044, accepted=True, new_indices=array([28]), old_indices_used=array([ 2, 19, 23, 26, 27]), old_indices_discarded=array([ 0, 1, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, + 18, 20, 21, 22, 24, 25]), step_length=0.00012702084422144821, relative_step_length=0.0003102799248157513, n_evals_per_point=1, n_evals_acceptance=1)], 'message': 'Absolute criterion change smaller than tolerance.', 'tranquilo_history': History for least_squares function with 30 entries., 'history': {'params': [{'CRRA': 8.1875}, {'CRRA': 7.36875}, {'CRRA': 9.00625}, {'CRRA': 7.36875}, {'CRRA': 7.36875}, {'CRRA': 9.00625}, {'CRRA': 7.36875}, {'CRRA': 7.36875}, {'CRRA': 9.00625}, {'CRRA': 7.36875}, {'CRRA': 9.00625}, {'CRRA': 7.36875}, {'CRRA': 9.00625}, {'CRRA': 9.00625}, {'CRRA': 7.3687499999999995}, {'CRRA': 9.026168169426626}, {'CRRA': 7.388668169426626}, {'CRRA': 9.038959312915338}, {'CRRA': 10.676459312915338}, {'CRRA': 9.290153724085462}, {'CRRA': 7.652653724085462}, {'CRRA': 9.235117007166322}, {'CRRA': 8.416367007166322}, {'CRRA': 9.1520466847697}, {'CRRA': 9.644492007166322}, {'CRRA': 9.248676532750787}, {'CRRA': 9.658051532750788}, {'CRRA': 9.252525969850202}, {'CRRA': 9.661900969850203}, {'CRRA': 9.25239894900598}], 'criterion': [0.6831279025699917, 0.7818234415442017, 0.6443932011688029, 0.7818234415442017, 0.7818234415442017, 0.6443932011688029, 0.7818234415442017, 0.7818234415442017, 0.6443932011688029, 0.7818234415442017, 0.6443932011688029, 0.7818234415442017, 0.6443932011688029, 0.6443932011688029, 0.7818234415442095, 0.6440402472439135, 0.7787614029619838, 0.6439435808488991, 0.7100198965757869, 0.642415138936857, 0.740451029529312, 0.6424025578938513, 0.6665435566959452, 0.6426661753949429, 0.6484718333650715, 0.6423803321514743, 0.6489393340909813, 0.642358861106374, 0.6490529814080408, 0.6423583869781233], 'runtime': [0.0, 3.074203699827194, 3.283573899883777, 3.498749100137502, 3.7044561998918653, 3.926607399713248, 4.110963100101799, 4.243899200111628, 4.541710100136697, 4.7094960999675095, 4.89852079981938, 5.075110800098628, 5.21526509989053, 12.235306499991566, 15.733508999925107, 16.80475839972496, 17.874723799992353, 18.94831439992413, 20.016572599764913, 21.089213099796325, 22.262267199810594, 23.334850599989295, 24.407207199838012, 25.481976099777967, 26.552139800041914, 27.62647379981354, 28.800836499780416, 29.875069699715823, 30.947488199919462, 32.024298400152475], 'batches': [0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18]}, 'multistart_info': {...}}], 'exploration_sample': array([[ 8.1875 ], + [10.55 ], + [ 6.61452875], + [12.9125 ], + [ 5.825 ], + [14.09375 ], + [15.275 ], + [ 4.64375 ], + [17.6375 ], + [ 3.4625 ]]), 'exploration_results': array([0.6831279 , 0.69939713, 0.93725113, 1.02360977, 1.18227674, + 1.26376333, 1.54278366, 1.78141341, 2.1808234 , 2.89794431])}}" diff --git a/code/estimark/content/tables/min/WarmGlowPortfolioBeta_estimate_results.csv b/code/estimark/content/tables/min/WarmGlowPortfolioBeta_estimate_results.csv new file mode 100644 index 0000000..23e13f9 --- /dev/null +++ b/code/estimark/content/tables/min/WarmGlowPortfolioBeta_estimate_results.csv @@ -0,0 +1,13094 @@ +CRRA,4.161270252410767 +BeqFac,3932.5419104702305 +DiscFac,0.9235618590930775 +time_to_estimate,235.31548237800598 +params,"{'CRRA': 4.161270252410767, 'BeqFac': 3932.5419104702305, 'DiscFac': 0.9235618590930775}" +criterion,0.07906739186138749 +start_criterion,0.14974471998399175 +start_params,"{'CRRA': 4.972165469041286, 'BeqFac': 2235.668701887974, 'DiscFac': 1.0}" +algorithm,multistart_tranquilo_ls +direction,minimize +n_free,3 +message,Absolute criterion change smaller than tolerance. +success, +n_criterion_evaluations, +n_derivative_evaluations, +n_iterations, +history,"{'params': [{'CRRA': 4.059438573758104, 'BeqFac': 3932.2768372119126, 'DiscFac': 0.8720884775777547}, {'CRRA': 1.1865624830963672, 'BeqFac': 3618.0088638043917, 'DiscFac': 1.1}, {'CRRA': 18.864750592221043, 'BeqFac': 3615.3369060843656, 'DiscFac': 1.0141895974609063}, {'CRRA': 20.0, 'BeqFac': 4139.2725657346655, 'DiscFac': 0.967186242030893}, {'CRRA': 11.813333909541619, 'BeqFac': 4191.377523809567, 'DiscFac': 0.5}, {'CRRA': 10.612091741842278, 'BeqFac': 4249.216768339459, 'DiscFac': 1.0533987310204382}, {'CRRA': 19.734405812485583, 'BeqFac': 4232.630594232504, 'DiscFac': 1.1}, {'CRRA': 1.193828208860164, 'BeqFac': 4249.216768339459, 'DiscFac': 0.8178772474441116}, {'CRRA': 1.1, 'BeqFac': 3989.879463996817, 'DiscFac': 1.0875233363571497}, {'CRRA': 19.6123309024715, 'BeqFac': 4002.81545313188, 'DiscFac': 0.5}, {'CRRA': 10.53992461925404, 'BeqFac': 3621.516955952882, 'DiscFac': 0.5}, {'CRRA': 1.1, 'BeqFac': 4191.668488920294, 'DiscFac': 0.5012402298207279}, {'CRRA': 17.486517743640487, 'BeqFac': 3633.4669300241812, 'DiscFac': 1.1}, {'CRRA': 12.695956525806718, 'BeqFac': 4249.216768339459, 'DiscFac': 0.5313513765650976}, {'CRRA': 12.977587527627069, 'BeqFac': 4090.746802775686, 'DiscFac': 0.5354925265745473}, {'CRRA': 13.161807680676663, 'BeqFac': 4011.5118199937992, 'DiscFac': 0.5553138137913001}, {'CRRA': 12.198029037880566, 'BeqFac': 3892.659345820969, 'DiscFac': 0.7092685961295264}, 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{'CRRA': 4.1612703469432315, 'BeqFac': 3932.541916014846, 'DiscFac': 0.9235649027864001}, {'CRRA': 4.161274439557252, 'BeqFac': 3932.5419112955856, 'DiscFac': 0.923563562230745}, {'CRRA': 4.161268588061044, 'BeqFac': 3932.5419112935697, 'DiscFac': 0.9235621223236096}, {'CRRA': 4.161264961042685, 'BeqFac': 3932.541912891103, 'DiscFac': 0.923566458371742}, {'CRRA': 4.1612706845073335, 'BeqFac': 3932.54191204673, 'DiscFac': 0.923573432878518}, {'CRRA': 4.161273169417956, 'BeqFac': 3932.5419061378893, 'DiscFac': 0.9235657502956361}, {'CRRA': 4.161267609182726, 'BeqFac': 3932.5419067553134, 'DiscFac': 0.9235645298735619}, {'CRRA': 4.161268346679939, 'BeqFac': 3932.5419060338195, 'DiscFac': 0.9235703644561561}, {'CRRA': 4.161270252410767, 'BeqFac': 3932.5419104702305, 'DiscFac': 0.9235618590930775}], 'criterion': [0.12472562593739224, 1775.1585229804136, 7.528672527611353, 5.000685908221211, 2.607189801137526, 1.7428398529637479, 34.04730103016978, 831.8568092195467, 1794.4913947111004, 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69.41409680014476, 70.62386910011992, 71.77614930039272, 72.92142220027745, 74.430033700075, 74.61684990022331, 74.81267850007862, 75.00723180035129, 75.2044039000757, 75.3887424999848, 75.57385200029239, 75.76805710000917, 75.96694570034742, 76.16238610027358, 76.3546518003568, 76.55501760030165, 77.8122900002636], 'batches': [0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 3, 4, 5, 6, 7, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 9, 10, 11, 12, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 14, 15, 16, 17, 17, 17, 17, 17, 17, 17, 17, 17, 17, 17, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 31, 31, 31, 31, 31, 31, 31, 31, 31, 31, 31, 32, 33, 34, 35, 36, 37, 37, 37, 37, 37, 37, 37, 37, 37, 37, 37, 37, 38, 39, 40, 41, 42, 43, 44, 44, 44, 44, 44, 44, 44, 44, 44, 44, 44, 44, 45, 46, 47, 48, 48, 48, 48, 48, 48, 48, 48, 48, 48, 48, 48, 49]}" +convergence_report,"{'one_step': {'relative_criterion_change': 0.15773345928132843, 'relative_params_change': 0.4431666467150333, 'absolute_criterion_change': 0.015773345928132843, 'absolute_params_change': 1696.956220326838}, 'five_steps': {'relative_criterion_change': 0.15773345928132843, 'relative_params_change': 0.4431666467150333, 'absolute_criterion_change': 0.015773345928132843, 'absolute_params_change': 1696.956220326838}}" +multistart_info,"{'start_parameters': [{'CRRA': 4.972165469041287, 'BeqFac': 2235.668701887974, 'DiscFac': 1.0}, {'CRRA': 4.059438573758104, 'BeqFac': 3932.2768372119126, 'DiscFac': 0.8720884775777547}, {'CRRA': 4.466570349505643, 'BeqFac': 4587.182667295986, 'DiscFac': 0.9284133483434123}], 'local_optima': [Minimize with 3 free parameters terminated. + +The tranquilo_ls algorithm reported: Relative criterion change smaller than tolerance. + +Independent of the convergence criteria used by tranquilo_ls, the strength of convergence can be assessed by the following criteria: + + one_step five_steps +relative_criterion_change 0*** 0.1692 +relative_params_change 0*** 0.05382 +absolute_criterion_change 0*** 0.01692 +absolute_params_change 0*** 0.2525 + +(***: change <= 1e-10, **: change <= 1e-8, *: change <= 1e-5. Change refers to a change between accepted steps. The first column only considers the last step. The second column considers the last five steps.), Minimize with 3 free parameters terminated. + +The tranquilo_ls algorithm reported: Absolute criterion change smaller than tolerance. + +Independent of the convergence criteria used by tranquilo_ls, the strength of convergence can be assessed by the following criteria: + + one_step five_steps +relative_criterion_change 4.245e-07* 5.719e-06* +relative_params_change 4.911e-07* 1.068e-05 +absolute_criterion_change 4.245e-08* 5.719e-07* +absolute_params_change 1.875e-06* 4.663e-05 + +(***: change <= 1e-10, **: change <= 1e-8, *: change <= 1e-5. Change refers to a change between accepted steps. The first column only considers the last step. The second column considers the last five steps.), Minimize with 3 free parameters terminated. + +The tranquilo_ls algorithm reported: Absolute criterion change smaller than tolerance. + +Independent of the convergence criteria used by tranquilo_ls, the strength of convergence can be assessed by the following criteria: + + one_step five_steps +relative_criterion_change 9.277e-06* 0.001793 +relative_params_change 4.611e-05 0.002492 +absolute_criterion_change 9.277e-07* 0.0001793 +absolute_params_change 0.0002187 0.01527 + +(***: change <= 1e-10, **: change <= 1e-8, *: change <= 1e-5. Change refers to a change between accepted steps. The first column only considers the last step. The second column considers the last five steps.)], 'exploration_sample': [{'CRRA': 4.972165469041286, 'BeqFac': 2235.668701887974, 'DiscFac': 1.0}, {'CRRA': 3.4625, 'BeqFac': 6250.0, 'DiscFac': 0.7250000000000001}, {'CRRA': 5.824999999999999, 'BeqFac': 7500.0, 'DiscFac': 0.9500000000000001}, {'CRRA': 4.053125, 'BeqFac': 1562.5, 'DiscFac': 0.8187500000000001}, {'CRRA': 9.959375, 'BeqFac': 937.5, 'DiscFac': 1.00625}, {'CRRA': 7.596874999999999, 'BeqFac': 7187.5, 'DiscFac': 0.9312500000000001}, {'CRRA': 15.865624999999998, 'BeqFac': 7812.5, 'DiscFac': 0.89375}, {'CRRA': 14.684375, 'BeqFac': 3437.5, 'DiscFac': 0.8562500000000001}, {'CRRA': 5.234375, 'BeqFac': 8437.5, 'DiscFac': 0.55625}, {'CRRA': 19.409375, 'BeqFac': 5937.5, 'DiscFac': 0.70625}, {'CRRA': 8.1875, 'BeqFac': 3750.0, 'DiscFac': 0.875}, {'CRRA': 14.093749999999998, 'BeqFac': 8125.0, 'DiscFac': 0.7625000000000001}, {'CRRA': 12.9125, 'BeqFac': 1250.0, 'DiscFac': 1.0250000000000001}, {'CRRA': 18.81875, 'BeqFac': 625.0, 'DiscFac': 0.9125000000000001}, {'CRRA': 17.046875, 'BeqFac': 2187.5, 'DiscFac': 0.6312500000000001}, {'CRRA': 10.549999999999999, 'BeqFac': 5000.0, 'DiscFac': 0.8}, {'CRRA': 17.6375, 'BeqFac': 8750.0, 'DiscFac': 0.575}, {'CRRA': 15.274999999999999, 'BeqFac': 2500.0, 'DiscFac': 0.65}, {'CRRA': 6.415625, 'BeqFac': 2812.5, 'DiscFac': 0.59375}, {'CRRA': 2.871875, 'BeqFac': 4687.5, 'DiscFac': 0.78125}, {'CRRA': 8.778125, 'BeqFac': 9062.5, 'DiscFac': 0.66875}, {'CRRA': 7.00625, 'BeqFac': 1875.0, 'DiscFac': 0.6875}, {'CRRA': 9.368749999999999, 'BeqFac': 5625.0, 'DiscFac': 0.6125}, {'CRRA': 16.45625, 'BeqFac': 6875.0, 'DiscFac': 0.9875}, {'CRRA': 13.503124999999999, 'BeqFac': 6562.5, 'DiscFac': 0.51875}, {'CRRA': 11.73125, 'BeqFac': 4375.0, 'DiscFac': 0.5375}, {'CRRA': 18.228125, 'BeqFac': 4062.5, 'DiscFac': 0.96875}, {'CRRA': 4.64375, 'BeqFac': 3125.0, 'DiscFac': 1.0625}, {'CRRA': 12.321874999999999, 'BeqFac': 9687.5, 'DiscFac': 1.08125}, {'CRRA': 2.28125, 'BeqFac': 9375.0, 'DiscFac': 0.8375}], 'exploration_results': array([ 0.15183336, 0.16963129, 0.3197984 , 0.64023668, 0.65671129, + 0.81183081, 0.97682658, 1.08889746, 1.16160077, 1.27832959, + 1.4056054 , 1.63187357, 1.68853551, 1.72432777, 1.75966476, + 1.80211806, 1.86015904, 1.93985391, 1.96313642, 2.01014295, + 2.05048939, 2.06445231, 2.29147195, 2.43324345, 2.49173392, + 2.54550964, 3.05245049, 4.00840374, 4.33350039, 58.25645251])}" +algorithm_output,"{'states': [State(trustregion=Region(center=array([4.05943857e+00, 3.93227684e+03, 8.72088478e-01]), radius=393.2276837211913, bounds=Bounds(lower=array([1.1, 0. , 0.5]), upper=array([2.0e+01, 1.0e+04, 1.1e+00]))), model_indices=[0], model=ScalarModel(intercept=0.12472562593739224, linear_terms=array([0., 0., 0.]), square_terms=array([[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]]), scale=393.2276837211913, shift=array([4.05943857e+00, 3.93227684e+03, 8.72088478e-01])), vector_model=VectorModel(intercepts=array([ 0.07188797, 0.11842249, 0.08425784, 0.06302381, 0.02761407, + -0.01169908, -0.04725341, -0.13055541, -0.1675786 , -0.01549265, + -0.18310131, -0.00520398, -0.04192809, -0.02779983, -0.03678838, + -0.05747802, -0.07226194]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]]), square_terms=array([[[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 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old_indices_discarded=array([], dtype=int32), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([4.05943857e+00, 3.93227684e+03, 8.72088478e-01]), radius=12.288365116287228, bounds=Bounds(lower=array([1.1, 0. , 0.5]), upper=array([2.0e+01, 1.0e+04, 1.1e+00]))), model_indices=array([ 0, 8, 16, 17]), model=ScalarModel(intercept=675.1794019801806, linear_terms=array([ -2064.6019009 , 718.07582713, -10217.06091518]), square_terms=array([[ 3158.11858269, -1098.22603339, 15626.2724666 ], + [-1098.22603339, 381.93267203, -5434.33216723], + [15626.2724666 , -5434.33216723, 77322.68695368]]), scale=array([6.43190571, 9.90437285, 0.3 ]), shift=array([7.53190571e+00, 3.93227684e+03, 8.00000000e-01])), vector_model=VectorModel(intercepts=array([ 0.07188797, 0.11842249, 0.08425784, 0.06302381, 0.02761407, + -0.01169908, -0.04725341, -0.13055541, -0.1675786 , -0.01549265, + -0.18310131, -0.00520398, -0.04192809, -0.02779983, 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20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30]), model=ScalarModel(intercept=108.75147073194, linear_terms=array([-309.53365492, -36.53619492, 161.80376403]), square_terms=array([[ 441.33077962, 52.10175602, -230.15109169], + [ 52.10175602, 6.15213254, -27.15013825], + [-230.15109169, -27.15013825, 120.92652934]]), scale=array([3.9558125 , 4.95218642, 0.3 ]), shift=array([5.05581250e+00, 3.93227684e+03, 8.00000000e-01])), vector_model=VectorModel(intercepts=array([ 0.07188797, 0.11842249, 0.08425784, 0.06302381, 0.02761407, + -0.01169908, -0.04725341, -0.13055541, -0.1675786 , -0.01549265, + -0.18310131, -0.00520398, -0.04192809, -0.02779983, -0.03678838, + -0.05747802, -0.07226194]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]]), 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candidate_index=31, candidate_x=array([6.44025805e+00, 3.93722902e+03, 6.65771609e-01]), index=0, x=array([4.05943857e+00, 3.93227684e+03, 8.72088478e-01]), fval=0.12472562593739225, rho=-0.00640748988321916, accepted=False, new_indices=array([19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30]), old_indices_used=array([ 0, 17, 18]), old_indices_discarded=array([], dtype=int32), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([4.05943857e+00, 3.93227684e+03, 8.72088478e-01]), radius=3.072091279071807, bounds=Bounds(lower=array([1.1, 0. , 0.5]), upper=array([2.0e+01, 1.0e+04, 1.1e+00]))), model_indices=array([ 0, 20, 21, 22, 23, 25, 26, 27, 28, 29, 30, 31]), model=ScalarModel(intercept=170.59582545012594, linear_terms=array([-277.08221691, 5.5992395 , 233.76105829]), square_terms=array([[ 2.25373873e+02, -4.61116778e+00, -1.89643367e+02], + [-4.61116778e+00, 1.11464760e-01, 3.74415217e+00], + [-1.89643367e+02, 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25, 26, 27, 28, 29, 30, 31]), old_indices_discarded=array([18, 19, 24]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([4.05943857e+00, 3.93227684e+03, 8.72088478e-01]), radius=1.5360456395359035, bounds=Bounds(lower=array([1.1, 0. , 0.5]), upper=array([2.0e+01, 1.0e+04, 1.1e+00]))), model_indices=array([ 0, 20, 21, 22, 23, 26, 27, 28, 29, 30, 31, 32]), model=ScalarModel(intercept=138.3462289851189, linear_terms=array([-147.45463528, -5.65111698, 268.26306503]), square_terms=array([[ 7.86989538e+01, 3.00126776e+00, -1.42903701e+02], + [ 3.00126776e+00, 1.18067220e-01, -5.51395279e+00], + [-1.42903701e+02, -5.51395279e+00, 2.60665493e+02]]), scale=array([1.23804661, 1.23804661, 0.3 ]), shift=array([4.05943857e+00, 3.93227684e+03, 8.00000000e-01])), vector_model=VectorModel(intercepts=array([ 0.07188797, 0.11842249, 0.08425784, 0.06302381, 0.02761407, + -0.01169908, -0.04725341, -0.13055541, -0.1675786 , 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bounds=Bounds(lower=array([1.1, 0. , 0.5]), upper=array([2.0e+01, 1.0e+04, 1.1e+00]))), model_indices=array([ 0, 23, 27, 32, 33]), model=ScalarModel(intercept=1.5830056559661339, linear_terms=array([ 9.99281175, 14.43614264, -39.57256129]), square_terms=array([[ 33.80983754, 48.83787417, -133.54382225], + [ 48.83787417, 70.60333873, -193.11510202], + [-133.54382225, -193.11510202, 528.45490937]]), scale=array([0.6190233, 0.6190233, 0.3 ]), shift=array([4.05943857e+00, 3.93227684e+03, 8.00000000e-01])), vector_model=VectorModel(intercepts=array([ 0.07188797, 0.11842249, 0.08425784, 0.06302381, 0.02761407, + -0.01169908, -0.04725341, -0.13055541, -0.1675786 , -0.01549265, + -0.18310131, -0.00520398, -0.04192809, -0.02779983, -0.03678838, + -0.05747802, -0.07226194]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 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shift=array([4.05943857e+00, 3.93227684e+03, 8.72088478e-01])), candidate_index=34, candidate_x=array([3.77141395e+00, 3.93289586e+03, 8.96820681e-01]), index=0, x=array([4.05943857e+00, 3.93227684e+03, 8.72088478e-01]), fval=0.12472562593739225, rho=-0.0007867459648932072, accepted=False, new_indices=array([], dtype=int32), old_indices_used=array([ 0, 23, 27, 32, 33]), old_indices_discarded=array([], dtype=int32), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([4.05943857e+00, 3.93227684e+03, 8.72088478e-01]), radius=0.38401140988397586, bounds=Bounds(lower=array([1.1, 0. , 0.5]), upper=array([2.0e+01, 1.0e+04, 1.1e+00]))), model_indices=array([ 0, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46]), model=ScalarModel(intercept=0.5847700831496822, linear_terms=array([-0.41675462, -0.44190085, 2.89851388]), square_terms=array([[ 0.18454675, 0.18631726, -1.20807895], + [ 0.18631726, 0.19477978, 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43, 44, 45, 46]), old_indices_used=array([ 0, 33, 34]), old_indices_discarded=array([], dtype=int32), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([4.05943857e+00, 3.93227684e+03, 8.72088478e-01]), radius=0.19200570494198793, bounds=Bounds(lower=array([1.1, 0. , 0.5]), upper=array([2.0e+01, 1.0e+04, 1.1e+00]))), model_indices=array([ 0, 35, 36, 38, 39, 40, 41, 42, 44, 45, 46, 47]), model=ScalarModel(intercept=1.2415835967758433, linear_terms=array([-0.15283733, -0.58871896, 3.13992098]), square_terms=array([[ 0.02040704, 0.03863901, -0.21039381], + [ 0.03863901, 0.14956944, -0.79740606], + [-0.21039381, -0.79740606, 4.2608185 ]]), scale=0.19200570494198793, shift=array([4.05943857e+00, 3.93227684e+03, 8.72088478e-01])), vector_model=VectorModel(intercepts=array([ 0.07188797, 0.11842249, 0.08425784, 0.06302381, 0.02761407, + -0.01169908, -0.04725341, -0.13055541, -0.1675786 , -0.01549265, + -0.18310131, 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upper=array([2.0e+01, 1.0e+04, 1.1e+00]))), model_indices=array([ 0, 35, 36, 39, 40, 41, 42, 44, 45, 46, 47, 48]), model=ScalarModel(intercept=1.0337220474595914, linear_terms=array([-0.20696303, -0.31059194, 1.61730455]), square_terms=array([[ 0.02606724, 0.03394087, -0.17786586], + [ 0.03394087, 0.05073282, -0.26413928], + [-0.17786586, -0.26413928, 1.3775637 ]]), scale=0.09600285247099397, shift=array([4.05943857e+00, 3.93227684e+03, 8.72088478e-01])), vector_model=VectorModel(intercepts=array([ 0.07188797, 0.11842249, 0.08425784, 0.06302381, 0.02761407, + -0.01169908, -0.04725341, -0.13055541, -0.1675786 , -0.01549265, + -0.18310131, -0.00520398, -0.04192809, -0.02779983, -0.03678838, + -0.05747802, -0.07226194]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 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8.72088478e-01])), candidate_index=49, candidate_x=array([4.03665655e+00, 3.93225811e+03, 7.80726618e-01]), index=0, x=array([4.05943857e+00, 3.93227684e+03, 8.72088478e-01]), fval=0.12472562593739225, rho=-0.2193495890214448, accepted=False, new_indices=array([], dtype=int32), old_indices_used=array([ 0, 35, 36, 39, 40, 41, 42, 44, 45, 46, 47, 48]), old_indices_discarded=array([], dtype=int32), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([4.05943857e+00, 3.93227684e+03, 8.72088478e-01]), radius=0.04800142623549698, bounds=Bounds(lower=array([1.1, 0. , 0.5]), upper=array([2.0e+01, 1.0e+04, 1.1e+00]))), model_indices=array([ 0, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61]), model=ScalarModel(intercept=0.11633665599043491, linear_terms=array([ 0.01692106, -0.00599296, -0.07183474]), square_terms=array([[ 0.00430738, -0.00138782, -0.01722234], + [-0.00138782, 0.00047598, 0.00583328], + 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old_indices_used=array([ 0, 48, 49]), old_indices_discarded=array([], dtype=int32), step_length=0.05128066423434844, relative_step_length=1.0683154284367173, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([4.06698105e+00, 3.93229322e+03, 9.20092104e-01]), radius=0.09600285247099397, bounds=Bounds(lower=array([1.1, 0. , 0.5]), upper=array([2.0e+01, 1.0e+04, 1.1e+00]))), model_indices=array([ 0, 50, 51, 54, 55, 56, 57, 58, 59, 60, 61, 62]), model=ScalarModel(intercept=0.08089110047653379, linear_terms=array([-0.00528525, -0.0001229 , 0.02824264]), square_terms=array([[ 1.16009632e-02, 2.30117604e-04, -6.86298394e-02], + [ 2.30117604e-04, 5.27144510e-06, -1.47978107e-03], + [-6.86298394e-02, -1.47978107e-03, 4.37447949e-01]]), scale=0.09600285247099397, shift=array([4.06698105e+00, 3.93229322e+03, 9.20092104e-01])), vector_model=VectorModel(intercepts=array([ 0.07188797, 0.11842249, 0.08425784, 0.06302381, 0.02761407, + -0.01169908, -0.04725341, 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State(trustregion=Region(center=array([4.15738965e+00, 3.93233146e+03, 9.28205841e-01]), radius=0.19200570494198793, bounds=Bounds(lower=array([1.1, 0. , 0.5]), upper=array([2.0e+01, 1.0e+04, 1.1e+00]))), model_indices=array([ 0, 50, 51, 54, 55, 56, 57, 59, 60, 61, 62, 63]), model=ScalarModel(intercept=0.08002590130028917, linear_terms=array([-0.00526566, 0.000661 , 0.04112777]), square_terms=array([[ 2.05912030e-02, -2.69140553e-03, -1.45369821e-01], + [-2.69140553e-03, 4.27142888e-04, 2.22767331e-02], + [-1.45369821e-01, 2.22767331e-02, 1.17421707e+00]]), scale=array([0.15475583, 0.15475583, 0.15475583]), shift=array([4.15738965e+00, 3.93233146e+03, 9.28205841e-01])), vector_model=VectorModel(intercepts=array([ 0.07188797, 0.11842249, 0.08425784, 0.06302381, 0.02761407, + -0.01169908, -0.04725341, -0.13055541, -0.1675786 , -0.01549265, + -0.18310131, -0.00520398, -0.04192809, -0.02779983, -0.03678838, + -0.05747802, -0.07226194]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.], + 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model_indices=array([41, 42, 44, 47, 48, 49, 54, 55, 59, 61, 63, 64]), model=ScalarModel(intercept=0.15326138046317392, linear_terms=array([0.55415723, 0.00612001, 0.65724766]), square_terms=array([[2.16178448e+00, 2.69601220e-02, 2.58028293e+00], + [2.69601220e-02, 3.98421161e-04, 3.15716605e-02], + [2.58028293e+00, 3.15716605e-02, 3.11749315e+00]]), scale=array([0.30951165, 0.30951165, 0.24443416]), shift=array([4.16380226e+00, 3.93248621e+03, 8.55565845e-01])), vector_model=VectorModel(intercepts=array([ 0.07188797, 0.11842249, 0.08425784, 0.06302381, 0.02761407, + -0.01169908, -0.04725341, -0.13055541, -0.1675786 , -0.01549265, + -0.18310131, -0.00520398, -0.04192809, -0.02779983, -0.03678838, + -0.05747802, -0.07226194]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + 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3.93227684e+03, 8.72088478e-01])), candidate_index=65, candidate_x=array([4.03801811e+00, 3.93261118e+03, 8.85249640e-01]), index=64, x=array([4.16380226e+00, 3.93248621e+03, 9.20643341e-01]), fval=0.0797111995279562, rho=-0.04919187191422923, accepted=False, new_indices=array([], dtype=int32), old_indices_used=array([41, 42, 44, 47, 48, 49, 54, 55, 59, 61, 63, 64]), old_indices_discarded=array([ 0, 33, 34, 35, 36, 37, 38, 39, 40, 43, 45, 46, 50, 51, 52, 53, 56, + 57, 58, 60, 62]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([4.16380226e+00, 3.93248621e+03, 9.20643341e-01]), radius=0.19200570494198793, bounds=Bounds(lower=array([1.1, 0. , 0.5]), upper=array([2.0e+01, 1.0e+04, 1.1e+00]))), model_indices=array([ 0, 42, 48, 50, 51, 52, 53, 58, 62, 63, 64, 65]), model=ScalarModel(intercept=0.07981427686533094, linear_terms=array([ 8.23222295e-04, -3.01457336e-06, -1.94680885e-04]), square_terms=array([[ 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fval=0.0797111995279562, rho=-0.4172818202820011, accepted=False, new_indices=array([], dtype=int32), old_indices_used=array([ 0, 42, 48, 50, 51, 52, 53, 58, 62, 63, 64, 65]), old_indices_discarded=array([34, 35, 36, 37, 38, 39, 40, 41, 43, 44, 45, 46, 47, 49, 54, 55, 56, + 57, 59, 60, 61]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([4.16380226e+00, 3.93248621e+03, 9.20643341e-01]), radius=0.09600285247099397, bounds=Bounds(lower=array([1.1, 0. , 0.5]), upper=array([2.0e+01, 1.0e+04, 1.1e+00]))), model_indices=array([42, 48, 50, 51, 52, 53, 58, 62, 63, 64, 65, 66]), model=ScalarModel(intercept=0.0797875761950249, linear_terms=array([ 5.31755989e-04, -2.45518194e-07, -8.66641581e-04]), square_terms=array([[ 1.65529454e-03, -4.13667194e-05, -8.39813544e-03], + [-4.13667194e-05, 8.98752859e-06, 1.51601069e-03], + [-8.39813544e-03, 1.51601069e-03, 2.58158286e-01]]), scale=0.09600285247099397, 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45, 47, 49, 54, 55, 56, 57, 59, 60, 61]), step_length=0.10215613340917244, relative_step_length=1.0640947719760474, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([4.12942468e+00, 3.93239001e+03, 9.20412203e-01]), radius=0.19200570494198793, bounds=Bounds(lower=array([1.1, 0. , 0.5]), upper=array([2.0e+01, 1.0e+04, 1.1e+00]))), model_indices=array([ 0, 50, 51, 54, 55, 56, 57, 59, 60, 63, 64, 67]), model=ScalarModel(intercept=0.0794221211152619, linear_terms=array([-8.78763547e-04, -7.32595189e-05, 1.57498998e-03]), square_terms=array([[ 1.88292059e-02, -8.43669110e-04, -1.35637703e-01], + [-8.43669110e-04, 5.18412063e-05, 7.55602994e-03], + [-1.35637703e-01, 7.55602994e-03, 1.13549976e+00]]), scale=array([0.15475583, 0.15475583, 0.15475583]), shift=array([4.12942468e+00, 3.93239001e+03, 9.20412203e-01])), vector_model=VectorModel(intercepts=array([ 0.07188797, 0.11842249, 0.08425784, 0.06302381, 0.02761407, + -0.01169908, -0.04725341, -0.13055541, 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State(trustregion=Region(center=array([4.16663860e+00, 3.93254477e+03, 9.23613025e-01]), radius=0.38401140988397586, bounds=Bounds(lower=array([1.1, 0. , 0.5]), upper=array([2.0e+01, 1.0e+04, 1.1e+00]))), model_indices=array([41, 42, 44, 47, 48, 49, 55, 63, 65, 66, 67, 68]), model=ScalarModel(intercept=0.11467755048322094, linear_terms=array([ 0.4301884 , -0.10852269, 0.38403869]), square_terms=array([[ 2.8059872 , -0.69595835, 2.53665519], + [-0.69595835, 0.17347376, -0.6322991 ], + [ 2.53665519, -0.6322991 , 2.32273428]]), scale=array([0.30951165, 0.30951165, 0.24294931]), shift=array([4.16663860e+00, 3.93254477e+03, 8.57050687e-01])), vector_model=VectorModel(intercepts=array([ 0.07188797, 0.11842249, 0.08425784, 0.06302381, 0.02761407, + -0.01169908, -0.04725341, -0.13055541, -0.1675786 , -0.01549265, + -0.18310131, -0.00520398, -0.04192809, -0.02779983, -0.03678838, + -0.05747802, -0.07226194]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + 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51, 53, 63, 64, 65, 66, 67, 68]), model=ScalarModel(intercept=0.07972737754656194, linear_terms=array([0.00089106, 0.00026728, 0.00741102]), square_terms=array([[3.83952175e-03, 2.37615327e-04, 1.80862528e-04], + [2.37615327e-04, 1.04844950e-03, 2.29140497e-02], + [1.80862528e-04, 2.29140497e-02, 5.09344565e-01]]), scale=array([0.15475583, 0.15475583, 0.15475583]), shift=array([4.16663860e+00, 3.93254477e+03, 9.23613025e-01])), vector_model=VectorModel(intercepts=array([ 0.07188797, 0.11842249, 0.08425784, 0.06302381, 0.02761407, + -0.01169908, -0.04725341, -0.13055541, -0.1675786 , -0.01549265, + -0.18310131, -0.00520398, -0.04192809, -0.02779983, -0.03678838, + -0.05747802, -0.07226194]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]]), 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candidate_index=70, candidate_x=array([4.12157965e+00, 3.93269953e+03, 9.14415260e-01]), index=68, x=array([4.16663860e+00, 3.93254477e+03, 9.23613025e-01]), fval=0.07908472064494197, rho=-4.697657825504714, accepted=False, new_indices=array([], dtype=int32), old_indices_used=array([42, 47, 48, 50, 51, 53, 63, 64, 65, 66, 67, 68]), old_indices_discarded=array([ 0, 34, 35, 36, 37, 38, 39, 40, 41, 43, 44, 45, 46, 49, 52, 54, 55, + 56, 57, 58, 59, 60, 61, 62, 69]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([4.16663860e+00, 3.93254477e+03, 9.23613025e-01]), radius=0.09600285247099397, bounds=Bounds(lower=array([1.1, 0. , 0.5]), upper=array([2.0e+01, 1.0e+04, 1.1e+00]))), model_indices=array([42, 47, 48, 50, 51, 63, 64, 65, 66, 67, 68, 70]), model=ScalarModel(intercept=0.07970568860996624, linear_terms=array([5.17688765e-04, 7.08684557e-05, 2.23636029e-03]), square_terms=array([[1.54434855e-03, 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accepted=False, new_indices=array([], dtype=int32), old_indices_used=array([42, 47, 48, 50, 51, 63, 64, 65, 66, 67, 68, 70]), old_indices_discarded=array([ 0, 35, 38, 41, 44, 45, 49, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, + 62, 69]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([4.16663860e+00, 3.93254477e+03, 9.23613025e-01]), radius=0.04800142623549698, bounds=Bounds(lower=array([1.1, 0. , 0.5]), upper=array([2.0e+01, 1.0e+04, 1.1e+00]))), model_indices=array([42, 48, 63, 64, 65, 66, 67, 68, 70, 71]), model=ScalarModel(intercept=0.07966045626129445, linear_terms=array([3.20987313e-04, 4.92207090e-05, 2.88283811e-03]), square_terms=array([[ 3.79212673e-04, -2.34327242e-06, -5.41146655e-06], + [-2.34327242e-06, 8.52228643e-06, -6.54738778e-04], + [-5.41146655e-06, -6.54738778e-04, 5.14897659e-02]]), scale=0.04800142623549698, shift=array([4.16663860e+00, 3.93254477e+03, 9.23613025e-01])), vector_model=VectorModel(intercepts=array([ 0.07188797, 0.11842249, 0.08425784, 0.06302381, 0.02761407, + -0.01169908, -0.04725341, -0.13055541, -0.1675786 , -0.01549265, + -0.18310131, -0.00520398, -0.04192809, -0.02779983, -0.03678838, + -0.05747802, -0.07226194]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]]), square_terms=array([[[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + 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n_evals_acceptance=1), State(trustregion=Region(center=array([4.16663860e+00, 3.93254477e+03, 9.23613025e-01]), radius=0.02400071311774849, bounds=Bounds(lower=array([1.1, 0. , 0.5]), upper=array([2.0e+01, 1.0e+04, 1.1e+00]))), model_indices=array([64, 66, 68, 71, 72]), model=ScalarModel(intercept=0.07909174304369689, linear_terms=array([ 9.75729683e-05, -8.37732492e-07, -2.20345183e-03]), square_terms=array([[ 8.71775509e-04, -1.04124643e-06, -6.73499598e-03], + [-1.04124643e-06, 1.31217919e-08, 1.11732679e-05], + [-6.73499598e-03, 1.11732679e-05, 5.71455095e-02]]), scale=0.02400071311774849, shift=array([4.16663860e+00, 3.93254477e+03, 9.23613025e-01])), vector_model=VectorModel(intercepts=array([ 0.07188797, 0.11842249, 0.08425784, 0.06302381, 0.02761407, + -0.01169908, -0.04725341, -0.13055541, -0.1675786 , -0.01549265, + -0.18310131, -0.00520398, -0.04192809, -0.02779983, -0.03678838, + -0.05747802, -0.07226194]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + 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9.23613025e-01]), fval=0.07908472064494197, rho=-0.6896313338426389, accepted=False, new_indices=array([], dtype=int32), old_indices_used=array([64, 68, 72, 73]), old_indices_discarded=array([], dtype=int32), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([4.16663860e+00, 3.93254477e+03, 9.23613025e-01]), radius=0.006000178279437123, bounds=Bounds(lower=array([1.1, 0. , 0.5]), upper=array([2.0e+01, 1.0e+04, 1.1e+00]))), model_indices=array([68, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86]), model=ScalarModel(intercept=0.07925187705246434, linear_terms=array([ 4.83829824e-05, 8.99512457e-06, -1.87907241e-04]), square_terms=array([[ 5.19363336e-05, -4.83339149e-07, -4.29582543e-04], + [-4.83339149e-07, 1.47336322e-08, 3.01353003e-06], + [-4.29582543e-04, 3.01353003e-06, 3.84555377e-03]]), scale=0.006000178279437123, shift=array([4.16663860e+00, 3.93254477e+03, 9.23613025e-01])), vector_model=VectorModel(intercepts=array([ 0.07188797, 0.11842249, 0.08425784, 0.06302381, 0.02761407, + -0.01169908, -0.04725341, -0.13055541, -0.1675786 , -0.01549265, + -0.18310131, -0.00520398, -0.04192809, -0.02779983, -0.03678838, + -0.05747802, -0.07226194]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]]), square_terms=array([[[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + 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relative_step_length=1.0086865448656241, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([4.16101457e+00, 3.93254256e+03, 9.23281861e-01]), radius=0.012000356558874246, bounds=Bounds(lower=array([1.1, 0. , 0.5]), upper=array([2.0e+01, 1.0e+04, 1.1e+00]))), model_indices=array([68, 75, 76, 77, 78, 79, 81, 82, 83, 84, 86, 87]), model=ScalarModel(intercept=0.07914371578873403, linear_terms=array([1.82176925e-04, 7.65262019e-05, 2.45374037e-06]), square_terms=array([[ 1.92862702e-04, -9.93628574e-06, -1.67037516e-03], + [-9.93628574e-06, 7.42657125e-07, 7.94573605e-05], + [-1.67037516e-03, 7.94573605e-05, 1.54724452e-02]]), scale=0.012000356558874246, shift=array([4.16101457e+00, 3.93254256e+03, 9.23281861e-01])), vector_model=VectorModel(intercepts=array([ 0.07188797, 0.11842249, 0.08425784, 0.06302381, 0.02761407, + -0.01169908, -0.04725341, -0.13055541, -0.1675786 , -0.01549265, + -0.18310131, -0.00520398, -0.04192809, -0.02779983, -0.03678838, + 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model_indices=array([68, 75, 76, 77, 78, 79, 80, 81, 83, 84, 86, 87]), model=ScalarModel(intercept=0.07914612489984735, linear_terms=array([ 9.04725864e-05, 3.30565774e-05, -2.19601997e-05]), square_terms=array([[ 4.27792898e-05, -4.53845336e-06, -3.94771372e-04], + [-4.53845336e-06, 5.36493868e-07, 4.14551856e-05], + [-3.94771372e-04, 4.14551856e-05, 3.90706076e-03]]), scale=0.006000178279437123, shift=array([4.16101457e+00, 3.93254256e+03, 9.23281861e-01])), vector_model=VectorModel(intercepts=array([ 0.07188797, 0.11842249, 0.08425784, 0.06302381, 0.02761407, + -0.01169908, -0.04725341, -0.13055541, -0.1675786 , -0.01549265, + -0.18310131, -0.00520398, -0.04192809, -0.02779983, -0.03678838, + -0.05747802, -0.07226194]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 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8.72088478e-01])), candidate_index=89, candidate_x=array([4.15545357e+00, 3.93254035e+03, 9.22788650e-01]), index=87, x=array([4.16101457e+00, 3.93254256e+03, 9.23281861e-01]), fval=0.07907999189313741, rho=-0.3798594883018238, accepted=False, new_indices=array([], dtype=int32), old_indices_used=array([68, 75, 76, 77, 78, 79, 80, 81, 83, 84, 86, 87]), old_indices_discarded=array([74, 82, 85, 88]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([4.16101457e+00, 3.93254256e+03, 9.23281861e-01]), radius=0.0030000891397185614, bounds=Bounds(lower=array([1.1, 0. , 0.5]), upper=array([2.0e+01, 1.0e+04, 1.1e+00]))), model_indices=array([68, 75, 76, 77, 78, 79, 80, 81, 83, 84, 87, 89]), model=ScalarModel(intercept=0.07916583626576876, linear_terms=array([ 3.46835434e-05, 1.37176019e-05, -3.87853430e-06]), square_terms=array([[ 1.16702087e-05, -1.13065279e-06, -1.02787515e-04], + [-1.13065279e-06, 1.19282548e-07, 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old_indices_used=array([68, 75, 76, 77, 78, 79, 80, 81, 83, 84, 87, 89]), old_indices_discarded=array([74, 82, 85, 86, 88]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([4.16101457e+00, 3.93254256e+03, 9.23281861e-01]), radius=0.0015000445698592807, bounds=Bounds(lower=array([1.1, 0. , 0.5]), upper=array([2.0e+01, 1.0e+04, 1.1e+00]))), model_indices=array([68, 77, 83, 87, 89, 90]), model=ScalarModel(intercept=0.07909333025755838, linear_terms=array([-1.15137705e-05, -7.91213109e-07, 9.73368802e-05]), square_terms=array([[ 3.75332861e-06, -1.15364186e-07, -2.97559553e-05], + [-1.15364186e-07, 1.95191461e-08, 8.40989334e-07], + [-2.97559553e-05, 8.40989334e-07, 2.56198599e-04]]), scale=0.0015000445698592807, shift=array([4.16101457e+00, 3.93254256e+03, 9.23281861e-01])), vector_model=VectorModel(intercepts=array([ 0.07188797, 0.11842249, 0.08425784, 0.06302381, 0.02761407, + -0.01169908, -0.04725341, 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x=array([4.16127032e+00, 3.93254191e+03, 9.23567705e-01]), fval=0.07906796375411648, rho=-1.0803986646623365, accepted=False, new_indices=array([], dtype=int32), old_indices_used=array([ 87, 92, 93, 96, 97, 98, 99, 100, 101, 102, 103, 104]), old_indices_discarded=array([68, 77, 83, 89, 90, 91, 94, 95]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([4.16127032e+00, 3.93254191e+03, 9.23567705e-01]), radius=0.0007500222849296404, bounds=Bounds(lower=array([1.1, 0. , 0.5]), upper=array([2.0e+01, 1.0e+04, 1.1e+00]))), model_indices=array([ 87, 92, 93, 94, 95, 96, 97, 98, 99, 101, 102, 104]), model=ScalarModel(intercept=0.07909160054167635, linear_terms=array([-1.29680002e-05, 2.27817382e-06, 1.03758748e-06]), square_terms=array([[ 9.19566779e-07, -3.49328357e-08, -6.93344117e-06], + [-3.49328357e-08, 6.61278422e-09, 2.68258739e-07], + [-6.93344117e-06, 2.68258739e-07, 5.96608551e-05]]), 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bounds=Bounds(lower=array([1.1, 0. , 0.5]), upper=array([2.0e+01, 1.0e+04, 1.1e+00]))), model_indices=array([ 87, 94, 95, 98, 102, 104, 106, 107]), model=ScalarModel(intercept=0.0790879150221595, linear_terms=array([-6.18729811e-06, 2.85069426e-06, 5.24029282e-06]), square_terms=array([[ 6.39029879e-08, -5.52613342e-09, -4.58386220e-07], + [-5.52613342e-09, 1.01866206e-09, 2.93309494e-08], + [-4.58386220e-07, 2.93309494e-08, 3.89516694e-06]]), scale=0.0001875055712324101, shift=array([4.16127032e+00, 3.93254191e+03, 9.23567705e-01])), vector_model=VectorModel(intercepts=array([ 0.07188797, 0.11842249, 0.08425784, 0.06302381, 0.02761407, + -0.01169908, -0.04725341, -0.13055541, -0.1675786 , -0.01549265, + -0.18310131, -0.00520398, -0.04192809, -0.02779983, -0.03678838, + -0.05747802, -0.07226194]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 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0.]]]), scale=393.2276837211913, shift=array([4.05943857e+00, 3.93227684e+03, 8.72088478e-01])), candidate_index=108, candidate_x=array([4.16142287e+00, 3.93254184e+03, 9.23486329e-01]), index=104, x=array([4.16127032e+00, 3.93254191e+03, 9.23567705e-01]), fval=0.07906796375411648, rho=-2.2093933698724797, accepted=False, new_indices=array([], dtype=int32), old_indices_used=array([ 87, 94, 95, 98, 102, 104, 106, 107]), old_indices_discarded=array([], dtype=int32), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([4.16127032e+00, 3.93254191e+03, 9.23567705e-01]), radius=9.375278561620504e-05, bounds=Bounds(lower=array([1.1, 0. , 0.5]), upper=array([2.0e+01, 1.0e+04, 1.1e+00]))), model_indices=array([ 95, 104, 107, 108]), model=ScalarModel(intercept=0.07906796375411641, linear_terms=array([-2.77746966e-05, -3.22673327e-05, -4.25319102e-05]), square_terms=array([[ 5.39542744e-08, 4.53199229e-08, -4.64131654e-08], + [ 4.53199229e-08, 4.98555993e-08, 7.22290924e-08], + [-4.64131654e-08, 7.22290924e-08, 1.14321313e-06]]), scale=9.375278561620504e-05, shift=array([4.16127032e+00, 3.93254191e+03, 9.23567705e-01])), vector_model=VectorModel(intercepts=array([ 0.07188797, 0.11842249, 0.08425784, 0.06302381, 0.02761407, + -0.01169908, -0.04725341, -0.13055541, -0.1675786 , -0.01549265, + -0.18310131, -0.00520398, -0.04192809, -0.02779983, -0.03678838, + -0.05747802, -0.07226194]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]]), square_terms=array([[[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 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new_indices=array([], dtype=int32), old_indices_used=array([ 95, 104, 107, 108]), old_indices_discarded=array([], dtype=int32), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([4.16127032e+00, 3.93254191e+03, 9.23567705e-01]), radius=4.687639280810252e-05, bounds=Bounds(lower=array([1.1, 0. , 0.5]), upper=array([2.0e+01, 1.0e+04, 1.1e+00]))), model_indices=array([104, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, + 120, 121]), model=ScalarModel(intercept=0.07907082869590354, linear_terms=array([ 2.88136945e-06, -3.08394182e-07, -1.07721092e-06]), square_terms=array([[ 4.46329859e-09, -6.05308320e-10, -2.92877945e-08], + [-6.05308320e-10, 1.34067088e-10, 3.43225360e-09], + [-2.92877945e-08, 3.43225360e-09, 2.44027182e-07]]), scale=4.687639280810252e-05, shift=array([4.16127032e+00, 3.93254191e+03, 9.23567705e-01])), vector_model=VectorModel(intercepts=array([ 0.07188797, 0.11842249, 0.08425784, 0.06302381, 0.02761407, + -0.01169908, -0.04725341, -0.13055541, -0.1675786 , -0.01549265, + -0.18310131, -0.00520398, -0.04192809, -0.02779983, -0.03678838, + -0.05747802, -0.07226194]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]]), square_terms=array([[[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + 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State(trustregion=Region(center=array([4.16127032e+00, 3.93254191e+03, 9.23567705e-01]), radius=2.343819640405126e-05, bounds=Bounds(lower=array([1.1, 0. , 0.5]), upper=array([2.0e+01, 1.0e+04, 1.1e+00]))), model_indices=array([104, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 120]), model=ScalarModel(intercept=0.07907053144557313, linear_terms=array([ 1.94854337e-07, -3.55132795e-07, -5.64262326e-07]), square_terms=array([[ 1.08597546e-09, 1.16175887e-10, -7.41141155e-09], + [ 1.16175887e-10, 3.16258142e-11, -6.25413742e-10], + [-7.41141155e-09, -6.25413742e-10, 5.96099329e-08]]), scale=2.343819640405126e-05, shift=array([4.16127032e+00, 3.93254191e+03, 9.23567705e-01])), vector_model=VectorModel(intercepts=array([ 0.07188797, 0.11842249, 0.08425784, 0.06302381, 0.02761407, + -0.01169908, -0.04725341, -0.13055541, -0.1675786 , -0.01549265, + -0.18310131, -0.00520398, -0.04192809, -0.02779983, -0.03678838, + -0.05747802, -0.07226194]), linear_terms=array([[0., 0., 0.], + [0., 0., 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120, 123]), model=ScalarModel(intercept=0.07907067153514401, linear_terms=array([ 2.04407661e-07, -2.51465066e-07, -2.26280892e-07]), square_terms=array([[ 2.06977844e-10, 4.21146920e-11, -1.67593686e-09], + [ 4.21146920e-11, 2.48475075e-11, -3.05589732e-10], + [-1.67593686e-09, -3.05589732e-10, 1.50170769e-08]]), scale=1.171909820202563e-05, shift=array([4.16127032e+00, 3.93254191e+03, 9.23567705e-01])), vector_model=VectorModel(intercepts=array([ 0.07188797, 0.11842249, 0.08425784, 0.06302381, 0.02761407, + -0.01169908, -0.04725341, -0.13055541, -0.1675786 , -0.01549265, + -0.18310131, -0.00520398, -0.04192809, -0.02779983, -0.03678838, + -0.05747802, -0.07226194]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]]), square_terms=array([[[0., 0., 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candidate_x=array([4.16126418e+00, 3.93254192e+03, 9.23574260e-01]), index=104, x=array([4.16127032e+00, 3.93254191e+03, 9.23567705e-01]), fval=0.07906796375411648, rho=-0.2558930827717976, accepted=False, new_indices=array([], dtype=int32), old_indices_used=array([104, 110, 112, 113, 114, 115, 116, 117, 118, 119, 120, 123]), old_indices_discarded=array([111, 121, 122]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([4.16127032e+00, 3.93254191e+03, 9.23567705e-01]), radius=5.859549101012815e-06, bounds=Bounds(lower=array([1.1, 0. , 0.5]), upper=array([2.0e+01, 1.0e+04, 1.1e+00]))), model_indices=array([104, 123, 124, 125, 126, 127, 128, 129, 130, 131, 132, 133, 134, + 135, 136]), model=ScalarModel(intercept=0.07906789905966807, linear_terms=array([2.53618684e-09, 2.53785426e-08, 3.95194505e-07]), square_terms=array([[ 5.35172911e-11, -7.04580653e-12, -3.54919326e-10], + [-7.04580653e-12, 3.06788632e-12, 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square_terms=array([[0.29433574, 0.05189857, 0.69211431], + [0.05189857, 0.01569971, 0.200252 ], + [0.69211431, 0.200252 , 2.57727413]]), scale=array([ 7.56714517, 11.26212487, 0.3 ]), shift=array([8.66714517e+00, 2.23566870e+03, 8.00000000e-01])), vector_model=VectorModel(intercepts=array([ 0.06291566, 0.1164343 , 0.10823532, 0.12189129, 0.12343732, + 0.12357637, 0.12479259, 0.09432371, 0.01973898, 0.10842372, + -0.14822489, -0.07394217, -0.01698702, -0.0183285 , -0.03672195, + -0.06411929, -0.08426122]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]]), square_terms=array([[[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + 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rho=-22860.524324555063, accepted=False, new_indices=array([], dtype=int32), old_indices_used=array([ 0, 9, 15, 16]), old_indices_discarded=array([], dtype=int32), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([4.97216547e+00, 2.23566870e+03, 1.00000000e+00]), radius=6.986464693399919, bounds=Bounds(lower=array([1.1, 0. , 0.5]), upper=array([2.0e+01, 1.0e+04, 1.1e+00]))), model_indices=array([ 0, 9, 16, 17]), model=ScalarModel(intercept=467.19314322074354, linear_terms=array([-1065.72378965, 378.28985285, -1698.61903515]), square_terms=array([[1215.92010216, -431.55891012, 1937.88572934], + [-431.55891012, 153.18465907, -687.77512457], + [1937.88572934, -687.77512457, 3088.84974448]]), scale=array([4.75161395, 5.63106244, 0.3 ]), shift=array([5.85161395e+00, 2.23566870e+03, 8.00000000e-01])), vector_model=VectorModel(intercepts=array([ 0.06291566, 0.1164343 , 0.10823532, 0.12189129, 0.12343732, + 0.12357637, 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bounds=Bounds(lower=array([1.1, 0. , 0.5]), upper=array([2.0e+01, 1.0e+04, 1.1e+00]))), model_indices=array([ 0, 9, 17, 18]), model=ScalarModel(intercept=631.0068374845937, linear_terms=array([ -713.42087297, 227.74637403, -1894.75839998]), square_terms=array([[ 403.38912904, -128.76975477, 1071.25267549], + [-128.76975477, 41.14741941, -341.84595008], + [1071.25267549, -341.84595008, 2845.4276814 ]]), scale=array([2.81553122, 2.81553122, 0.3 ]), shift=array([4.97216547e+00, 2.23566870e+03, 8.00000000e-01])), vector_model=VectorModel(intercepts=array([ 0.06291566, 0.1164343 , 0.10823532, 0.12189129, 0.12343732, + 0.12357637, 0.12479259, 0.09432371, 0.01973898, 0.10842372, + -0.14822489, -0.07394217, -0.01698702, -0.0183285 , -0.03672195, + -0.06411929, -0.08426122]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 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shift=array([4.97216547e+00, 2.23566870e+03, 1.00000000e+00])), candidate_index=19, candidate_x=array([5.22498136e+00, 2.23285317e+03, 9.53585466e-01]), index=0, x=array([4.97216547e+00, 2.23566870e+03, 1.00000000e+00]), fval=0.15183336484019694, rho=-3.163059122264521, accepted=False, new_indices=array([], dtype=int32), old_indices_used=array([ 0, 9, 17, 18]), old_indices_discarded=array([], dtype=int32), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([4.97216547e+00, 2.23566870e+03, 1.00000000e+00]), radius=1.7466161733499797, bounds=Bounds(lower=array([1.1, 0. , 0.5]), upper=array([2.0e+01, 1.0e+04, 1.1e+00]))), model_indices=array([ 0, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31]), model=ScalarModel(intercept=0.14790847307992083, linear_terms=array([-0.33207427, 0.0835986 , 0.80229467]), square_terms=array([[ 1.61949403, -0.29564339, -2.97830876], + [-0.29564339, 0.059162 , 0.58807027], + 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old_indices_used=array([ 0, 18, 19]), old_indices_discarded=array([], dtype=int32), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([4.97216547e+00, 2.23566870e+03, 1.00000000e+00]), radius=0.8733080866749898, bounds=Bounds(lower=array([1.1, 0. , 0.5]), upper=array([2.0e+01, 1.0e+04, 1.1e+00]))), model_indices=array([ 0, 21, 22, 23, 24, 25, 27, 28, 29, 30, 31, 32]), model=ScalarModel(intercept=0.11589494066709435, linear_terms=array([ 0.16454974, 0.04806004, -0.44293767]), square_terms=array([[ 0.76924547, 0.27501651, -2.87758723], + [ 0.27501651, 0.09970594, -1.04942116], + [-2.87758723, -1.04942116, 11.20509916]]), scale=array([0.7038828, 0.7038828, 0.3 ]), shift=array([4.97216547e+00, 2.23566870e+03, 8.00000000e-01])), vector_model=VectorModel(intercepts=array([ 0.06291566, 0.1164343 , 0.10823532, 0.12189129, 0.12343732, + 0.12357637, 0.12479259, 0.09432371, 0.01973898, 0.10842372, + -0.14822489, 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upper=array([2.0e+01, 1.0e+04, 1.1e+00]))), model_indices=array([ 0, 21, 22, 23, 24, 27, 28, 29, 30, 31, 32, 33]), model=ScalarModel(intercept=0.4031517845766621, linear_terms=array([-0.23678438, -0.13921737, 1.90006104]), square_terms=array([[ 0.14109853, 0.0676179 , -0.91471804], + [ 0.0676179 , 0.03464796, -0.47018588], + [-0.91471804, -0.47018588, 6.40611468]]), scale=array([0.3519414, 0.3519414, 0.2259707]), shift=array([4.97216547e+00, 2.23566870e+03, 8.74029299e-01])), vector_model=VectorModel(intercepts=array([ 0.06291566, 0.1164343 , 0.10823532, 0.12189129, 0.12343732, + 0.12357637, 0.12479259, 0.09432371, 0.01973898, 0.10842372, + -0.14822489, -0.07394217, -0.01698702, -0.0183285 , -0.03672195, + -0.06411929, -0.08426122]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 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2.23566870e+03, 1.00000000e+00])), candidate_index=34, candidate_x=array([4.62022407e+00, 2.23602064e+03, 8.03652173e-01]), index=0, x=array([4.97216547e+00, 2.23566870e+03, 1.00000000e+00]), fval=0.15183336484019694, rho=-0.31192568841383445, accepted=False, new_indices=array([], dtype=int32), old_indices_used=array([ 0, 21, 22, 23, 24, 27, 28, 29, 30, 31, 32, 33]), old_indices_discarded=array([20, 25, 26]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([4.97216547e+00, 2.23566870e+03, 1.00000000e+00]), radius=0.21832702166874746, bounds=Bounds(lower=array([1.1, 0. , 0.5]), upper=array([2.0e+01, 1.0e+04, 1.1e+00]))), model_indices=array([ 0, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46]), model=ScalarModel(intercept=0.3311781411225237, linear_terms=array([-0.15829022, -0.12201639, 1.37588212]), square_terms=array([[ 0.07100082, 0.05048831, -0.56524959], + [ 0.05048831, 0.03638561, -0.40733887], + 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old_indices_used=array([ 0, 33, 34]), old_indices_discarded=array([], dtype=int32), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([4.97216547e+00, 2.23566870e+03, 1.00000000e+00]), radius=0.10916351083437373, bounds=Bounds(lower=array([1.1, 0. , 0.5]), upper=array([2.0e+01, 1.0e+04, 1.1e+00]))), model_indices=array([ 0, 35, 36, 38, 39, 40, 41, 42, 44, 45, 46, 47]), model=ScalarModel(intercept=0.7819308994641678, linear_terms=array([ 0.0074579 , -0.0259874 , 1.71946661]), square_terms=array([[ 5.56013887e-04, 1.44714906e-04, -1.22278649e-03], + [ 1.44714906e-04, 6.29275388e-04, -3.58652012e-02], + [-1.22278649e-03, -3.58652012e-02, 2.24563302e+00]]), scale=array([0.08798535, 0.08798535, 0.08798535]), shift=array([4.97216547e+00, 2.23566870e+03, 1.00000000e+00])), vector_model=VectorModel(intercepts=array([ 0.06291566, 0.1164343 , 0.10823532, 0.12189129, 0.12343732, + 0.12357637, 0.12479259, 0.09432371, 0.01973898, 0.10842372, + -0.14822489, -0.07394217, -0.01698702, -0.0183285 , -0.03672195, + -0.06411929, -0.08426122]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]]), square_terms=array([[[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], 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bounds=Bounds(lower=array([1.1, 0. , 0.5]), upper=array([2.0e+01, 1.0e+04, 1.1e+00]))), model_indices=array([ 0, 35, 36, 39, 40, 41, 42, 44, 45, 46, 47, 48]), model=ScalarModel(intercept=0.684129096465268, linear_terms=array([-0.0273062 , -0.01343205, 1.05830747]), square_terms=array([[ 1.32604981e-03, 5.31204096e-04, -3.19319385e-02], + [ 5.31204096e-04, 2.27658842e-04, -1.40325629e-02], + [-3.19319385e-02, -1.40325629e-02, 1.00415127e+00]]), scale=0.054581755417186864, shift=array([4.97216547e+00, 2.23566870e+03, 1.00000000e+00])), vector_model=VectorModel(intercepts=array([ 0.06291566, 0.1164343 , 0.10823532, 0.12189129, 0.12343732, + 0.12357637, 0.12479259, 0.09432371, 0.01973898, 0.10842372, + -0.14822489, -0.07394217, -0.01698702, -0.0183285 , -0.03672195, + -0.06411929, -0.08426122]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + 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scale=223.5668701887974, shift=array([4.97216547e+00, 2.23566870e+03, 1.00000000e+00])), candidate_index=49, candidate_x=array([4.95637410e+00, 2.23565341e+03, 9.50041339e-01]), index=0, x=array([4.97216547e+00, 2.23566870e+03, 1.00000000e+00]), fval=0.15183336484019694, rho=-0.30404049502893676, accepted=False, new_indices=array([], dtype=int32), old_indices_used=array([ 0, 35, 36, 39, 40, 41, 42, 44, 45, 46, 47, 48]), old_indices_discarded=array([], dtype=int32), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([4.97216547e+00, 2.23566870e+03, 1.00000000e+00]), radius=0.027290877708593432, bounds=Bounds(lower=array([1.1, 0. , 0.5]), upper=array([2.0e+01, 1.0e+04, 1.1e+00]))), model_indices=array([ 0, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61]), model=ScalarModel(intercept=0.1606884730144318, linear_terms=array([-0.00451786, -0.00405289, 0.12722605]), square_terms=array([[ 0.00114205, 0.00061019, 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55, 56, 57, 58, 59, 60, 61]), old_indices_used=array([ 0, 49]), old_indices_discarded=array([], dtype=int32), step_length=0.029339079440313165, relative_step_length=1.075050782667748, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([4.94579579e+00, 2.23566755e+03, 9.87190354e-01]), radius=0.054581755417186864, bounds=Bounds(lower=array([1.1, 0. , 0.5]), upper=array([2.0e+01, 1.0e+04, 1.1e+00]))), model_indices=array([ 0, 49, 50, 52, 54, 55, 56, 58, 59, 60, 61, 62]), model=ScalarModel(intercept=0.13142051977624206, linear_terms=array([ 0.00576256, 0.00026056, -0.00133033]), square_terms=array([[ 2.27015032e-03, 1.09767205e-03, -4.97844684e-02], + [ 1.09767205e-03, 5.83638100e-04, -2.63715392e-02], + [-4.97844684e-02, -2.63715392e-02, 1.20784318e+00]]), scale=0.054581755417186864, shift=array([4.94579579e+00, 2.23566755e+03, 9.87190354e-01])), vector_model=VectorModel(intercepts=array([ 0.06291566, 0.1164343 , 0.10823532, 0.12189129, 0.12343732, + 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shift=array([4.97216547e+00, 2.23566870e+03, 1.00000000e+00])), candidate_index=68, candidate_x=array([4.75839345e+00, 2.23564895e+03, 9.94942715e-01]), index=64, x=array([4.77904943e+00, 2.23566008e+03, 9.80374550e-01]), fval=0.11957247313888911, rho=-1.8438302886729045, accepted=False, new_indices=array([], dtype=int32), old_indices_used=array([63, 64, 66, 67]), old_indices_discarded=array([], dtype=int32), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([4.77904943e+00, 2.23566008e+03, 9.80374550e-01]), radius=0.013645438854296716, bounds=Bounds(lower=array([1.1, 0. , 0.5]), upper=array([2.0e+01, 1.0e+04, 1.1e+00]))), model_indices=array([64, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80]), model=ScalarModel(intercept=0.1186316056712768, linear_terms=array([ 0.00347483, 0.00169535, -0.01719098]), square_terms=array([[ 0.00068357, 0.00053277, -0.00534077], + [ 0.00053277, 0.00042502, -0.00424712], + 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67, 68]), old_indices_discarded=array([], dtype=int32), step_length=0.014257763675346667, relative_step_length=1.0448739558755298, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([4.76525937e+00, 2.23565983e+03, 9.83987893e-01]), radius=0.027290877708593432, bounds=Bounds(lower=array([1.1, 0. , 0.5]), upper=array([2.0e+01, 1.0e+04, 1.1e+00]))), model_indices=array([64, 68, 69, 70, 73, 74, 75, 76, 78, 79, 80, 81]), model=ScalarModel(intercept=0.1138846587026767, linear_terms=array([ 0.00286786, 0.0001056 , -0.00362309]), square_terms=array([[ 7.58823322e-04, 1.78136736e-04, -1.27262497e-02], + [ 1.78136736e-04, 4.56758695e-05, -3.21711156e-03], + [-1.27262497e-02, -3.21711156e-03, 2.34475273e-01]]), scale=0.027290877708593432, shift=array([4.76525937e+00, 2.23565983e+03, 9.83987893e-01])), vector_model=VectorModel(intercepts=array([ 0.06291566, 0.1164343 , 0.10823532, 0.12189129, 0.12343732, + 0.12357637, 0.12479259, 0.09432371, 0.01973898, 0.10842372, 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model=ScalarModel(intercept=0.107827872396005, linear_terms=array([0.00271801, 0.00465108, 0.0595416 ]), square_terms=array([[ 0.01913536, -0.00597598, -0.17725347], + [-0.00597598, 0.00225162, 0.06079365], + [-0.17725347, 0.06079365, 1.72780408]]), scale=0.10916351083437373, shift=array([4.68340853e+00, 2.23565787e+03, 9.81541008e-01])), vector_model=VectorModel(intercepts=array([ 0.06291566, 0.1164343 , 0.10823532, 0.12189129, 0.12343732, + 0.12357637, 0.12479259, 0.09432371, 0.01973898, 0.10842372, + -0.14822489, -0.07394217, -0.01698702, -0.0183285 , -0.03672195, + -0.06411929, -0.08426122]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]]), square_terms=array([[[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + 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x=array([4.68340853e+00, 2.23565787e+03, 9.81541008e-01]), fval=0.10637576541348984, rho=-0.4435220960006037, accepted=False, new_indices=array([], dtype=int32), old_indices_used=array([64, 66, 67, 68, 70, 74, 75, 76, 79, 80, 82, 83]), old_indices_discarded=array([ 0, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, + 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 65, 69, 71, + 72, 73, 77, 78, 81]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([4.68340853e+00, 2.23565787e+03, 9.81541008e-01]), radius=0.054581755417186864, bounds=Bounds(lower=array([1.1, 0. , 0.5]), upper=array([2.0e+01, 1.0e+04, 1.1e+00]))), model_indices=array([64, 66, 67, 68, 71, 72, 75, 77, 80, 81, 82, 83]), model=ScalarModel(intercept=0.10753665968218919, linear_terms=array([0.00205224, 0.00035594, 0.02486512]), square_terms=array([[ 4.13042323e-03, 1.27964751e-03, -4.10755431e-02], + [ 1.27964751e-03, 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model=ScalarModel(intercept=102.38671386491994, linear_terms=array([-301.74886293, -7.4096688 , 135.40964517]), square_terms=array([[ 4.49001106e+02, 1.10387141e+01, -1.98898743e+02], + [ 1.10387141e+01, 2.79198932e-01, -4.83711708e+00], + [-1.98898743e+02, -4.83711708e+00, 9.01425346e+01]]), scale=array([ 9.45 , 158.46996556, 0.3 ]), shift=array([1.05500000e+01, 3.93227684e+03, 8.00000000e-01])), vector_model=VectorModel(intercepts=array([ 0.07188797, 0.11842249, 0.08425784, 0.06302381, 0.02761407, + -0.01169908, -0.04725341, -0.13055541, -0.1675786 , -0.01549265, + -0.18310131, -0.00520398, -0.04192809, -0.02779983, -0.03678838, + -0.05747802, -0.07226194]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]]), square_terms=array([[[0., 0., 0.], + 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candidate_x=array([1.29775875e+01, 4.09074680e+03, 5.35492527e-01]), index=0, x=array([4.05943857e+00, 3.93227684e+03, 8.72088478e-01]), fval=0.12472562593739225, rho=-0.00494303523271701, accepted=False, new_indices=array([], dtype=int32), old_indices_used=array([ 0, 1, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12]), old_indices_discarded=array([ 2, 13]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([4.05943857e+00, 3.93227684e+03, 8.72088478e-01]), radius=98.30692093029782, bounds=Bounds(lower=array([1.1, 0. , 0.5]), upper=array([2.0e+01, 1.0e+04, 1.1e+00]))), model_indices=array([ 0, 1, 3, 4, 6, 7, 8, 9, 10, 11, 12, 14]), model=ScalarModel(intercept=116.12151198406633, linear_terms=array([-321.94879911, 8.08795269, 184.9444489 ]), square_terms=array([[ 4.50244477e+02, -1.12411579e+01, -2.55940799e+02], + [-1.12411579e+01, 2.84655841e-01, 6.47245223e+00], + [-2.55940799e+02, 6.47245223e+00, 1.47960373e+02]]), scale=array([ 9.45 , 79.23498278, 0.3 ]), shift=array([1.05500000e+01, 3.93227684e+03, 8.00000000e-01])), vector_model=VectorModel(intercepts=array([ 0.07188797, 0.11842249, 0.08425784, 0.06302381, 0.02761407, + -0.01169908, -0.04725341, -0.13055541, -0.1675786 , -0.01549265, + -0.18310131, -0.00520398, -0.04192809, -0.02779983, -0.03678838, + -0.05747802, -0.07226194]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]]), square_terms=array([[[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + 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16]), model=ScalarModel(intercept=137.95900758299246, linear_terms=array([ 609.72371975, 81.97626858, 1094.06151597]), square_terms=array([[1348.85665695, 181.37053476, 2420.79025551], + [ 181.37053476, 24.39149366, 325.54412825], + [2420.79025551, 325.54412825, 4345.09263337]]), scale=array([ 9.45 , 19.8087457, 0.3 ]), shift=array([1.05500000e+01, 3.93227684e+03, 8.00000000e-01])), vector_model=VectorModel(intercepts=array([ 0.07188797, 0.11842249, 0.08425784, 0.06302381, 0.02761407, + -0.01169908, -0.04725341, -0.13055541, -0.1675786 , -0.01549265, + -0.18310131, -0.00520398, -0.04192809, -0.02779983, -0.03678838, + -0.05747802, -0.07226194]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]]), square_terms=array([[[0., 0., 0.], + [0., 0., 0.], + 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n_evals_acceptance=1), State(trustregion=Region(center=array([4.05943857e+00, 3.93227684e+03, 8.72088478e-01]), radius=6.144182558143614, bounds=Bounds(lower=array([1.1, 0. , 0.5]), upper=array([2.0e+01, 1.0e+04, 1.1e+00]))), model_indices=array([ 0, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30]), model=ScalarModel(intercept=108.75147073194, linear_terms=array([-309.53365492, -36.53619492, 161.80376403]), square_terms=array([[ 441.33077962, 52.10175602, -230.15109169], + [ 52.10175602, 6.15213254, -27.15013825], + [-230.15109169, -27.15013825, 120.92652934]]), scale=array([3.9558125 , 4.95218642, 0.3 ]), shift=array([5.05581250e+00, 3.93227684e+03, 8.00000000e-01])), vector_model=VectorModel(intercepts=array([ 0.07188797, 0.11842249, 0.08425784, 0.06302381, 0.02761407, + -0.01169908, -0.04725341, -0.13055541, -0.1675786 , -0.01549265, + -0.18310131, -0.00520398, -0.04192809, -0.02779983, -0.03678838, + -0.05747802, -0.07226194]), linear_terms=array([[0., 0., 0.], + [0., 0., 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model=ScalarModel(intercept=170.59582545012594, linear_terms=array([-277.08221691, 5.5992395 , 233.76105829]), square_terms=array([[ 2.25373873e+02, -4.61116778e+00, -1.89643367e+02], + [-4.61116778e+00, 1.11464760e-01, 3.74415217e+00], + [-1.89643367e+02, 3.74415217e+00, 1.60694491e+02]]), scale=array([2.47609321, 2.47609321, 0.3 ]), shift=array([4.05943857e+00, 3.93227684e+03, 8.00000000e-01])), vector_model=VectorModel(intercepts=array([ 0.07188797, 0.11842249, 0.08425784, 0.06302381, 0.02761407, + -0.01169908, -0.04725341, -0.13055541, -0.1675786 , -0.01549265, + -0.18310131, -0.00520398, -0.04192809, -0.02779983, -0.03678838, + -0.05747802, -0.07226194]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]]), square_terms=array([[[0., 0., 0.], + 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candidate_x=array([5.66682758e+00, 3.92980074e+03, 6.00414976e-01]), index=0, x=array([4.05943857e+00, 3.93227684e+03, 8.72088478e-01]), fval=0.12472562593739225, rho=-0.006388659400412666, accepted=False, new_indices=array([], dtype=int32), old_indices_used=array([ 0, 20, 21, 22, 23, 25, 26, 27, 28, 29, 30, 31]), old_indices_discarded=array([18, 19, 24]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([4.05943857e+00, 3.93227684e+03, 8.72088478e-01]), radius=1.5360456395359035, bounds=Bounds(lower=array([1.1, 0. , 0.5]), upper=array([2.0e+01, 1.0e+04, 1.1e+00]))), model_indices=array([ 0, 20, 21, 22, 23, 26, 27, 28, 29, 30, 31, 32]), model=ScalarModel(intercept=138.3462289851189, linear_terms=array([-147.45463528, -5.65111698, 268.26306503]), square_terms=array([[ 7.86989538e+01, 3.00126776e+00, -1.42903701e+02], + [ 3.00126776e+00, 1.18067220e-01, -5.51395279e+00], + [-1.42903701e+02, -5.51395279e+00, 2.60665493e+02]]), scale=array([1.23804661, 1.23804661, 0.3 ]), shift=array([4.05943857e+00, 3.93227684e+03, 8.00000000e-01])), vector_model=VectorModel(intercepts=array([ 0.07188797, 0.11842249, 0.08425784, 0.06302381, 0.02761407, + -0.01169908, -0.04725341, -0.13055541, -0.1675786 , -0.01549265, + -0.18310131, -0.00520398, -0.04192809, -0.02779983, -0.03678838, + -0.05747802, -0.07226194]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]]), square_terms=array([[[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + 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30, 31, 32]), old_indices_discarded=array([19, 24, 25]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([4.05943857e+00, 3.93227684e+03, 8.72088478e-01]), radius=0.7680228197679517, bounds=Bounds(lower=array([1.1, 0. , 0.5]), upper=array([2.0e+01, 1.0e+04, 1.1e+00]))), model_indices=array([ 0, 23, 27, 32, 33]), model=ScalarModel(intercept=1.5830056559661339, linear_terms=array([ 9.99281175, 14.43614264, -39.57256129]), square_terms=array([[ 33.80983754, 48.83787417, -133.54382225], + [ 48.83787417, 70.60333873, -193.11510202], + [-133.54382225, -193.11510202, 528.45490937]]), scale=array([0.6190233, 0.6190233, 0.3 ]), shift=array([4.05943857e+00, 3.93227684e+03, 8.00000000e-01])), vector_model=VectorModel(intercepts=array([ 0.07188797, 0.11842249, 0.08425784, 0.06302381, 0.02761407, + -0.01169908, -0.04725341, -0.13055541, -0.1675786 , -0.01549265, + -0.18310131, -0.00520398, -0.04192809, -0.02779983, 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34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46]), model=ScalarModel(intercept=0.5847700831496822, linear_terms=array([-0.41675462, -0.44190085, 2.89851388]), square_terms=array([[ 0.18454675, 0.18631726, -1.20807895], + [ 0.18631726, 0.19477978, -1.27421791], + [-1.20807895, -1.27421791, 8.3918659 ]]), scale=array([0.30951165, 0.30951165, 0.26871159]), shift=array([4.05943857e+00, 3.93227684e+03, 8.31288413e-01])), vector_model=VectorModel(intercepts=array([ 0.07188797, 0.11842249, 0.08425784, 0.06302381, 0.02761407, + -0.01169908, -0.04725341, -0.13055541, -0.1675786 , -0.01549265, + -0.18310131, -0.00520398, -0.04192809, -0.02779983, -0.03678838, + -0.05747802, -0.07226194]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]]), square_terms=array([[[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]]]), scale=393.2276837211913, shift=array([4.05943857e+00, 3.93227684e+03, 8.72088478e-01])), candidate_index=47, candidate_x=array([3.96066338e+00, 3.93258635e+03, 7.66932590e-01]), index=0, x=array([4.05943857e+00, 3.93227684e+03, 8.72088478e-01]), fval=0.12472562593739225, rho=-0.1708886923662552, accepted=False, new_indices=array([35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46]), old_indices_used=array([ 0, 33, 34]), old_indices_discarded=array([], dtype=int32), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([4.05943857e+00, 3.93227684e+03, 8.72088478e-01]), radius=0.19200570494198793, bounds=Bounds(lower=array([1.1, 0. , 0.5]), upper=array([2.0e+01, 1.0e+04, 1.1e+00]))), model_indices=array([ 0, 35, 36, 38, 39, 40, 41, 42, 44, 45, 46, 47]), model=ScalarModel(intercept=1.2415835967758433, linear_terms=array([-0.15283733, -0.58871896, 3.13992098]), square_terms=array([[ 0.02040704, 0.03863901, -0.21039381], + [ 0.03863901, 0.14956944, -0.79740606], + [-0.21039381, -0.79740606, 4.2608185 ]]), scale=0.19200570494198793, shift=array([4.05943857e+00, 3.93227684e+03, 8.72088478e-01])), vector_model=VectorModel(intercepts=array([ 0.07188797, 0.11842249, 0.08425784, 0.06302381, 0.02761407, + -0.01169908, -0.04725341, -0.13055541, -0.1675786 , -0.01549265, + -0.18310131, -0.00520398, -0.04192809, -0.02779983, -0.03678838, + -0.05747802, -0.07226194]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]]), square_terms=array([[[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + 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old_indices_discarded=array([34, 37, 43]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([4.05943857e+00, 3.93227684e+03, 8.72088478e-01]), radius=0.09600285247099397, bounds=Bounds(lower=array([1.1, 0. , 0.5]), upper=array([2.0e+01, 1.0e+04, 1.1e+00]))), model_indices=array([ 0, 35, 36, 39, 40, 41, 42, 44, 45, 46, 47, 48]), model=ScalarModel(intercept=1.0337220474595914, linear_terms=array([-0.20696303, -0.31059194, 1.61730455]), square_terms=array([[ 0.02606724, 0.03394087, -0.17786586], + [ 0.03394087, 0.05073282, -0.26413928], + [-0.17786586, -0.26413928, 1.3775637 ]]), scale=0.09600285247099397, shift=array([4.05943857e+00, 3.93227684e+03, 8.72088478e-01])), vector_model=VectorModel(intercepts=array([ 0.07188797, 0.11842249, 0.08425784, 0.06302381, 0.02761407, + -0.01169908, -0.04725341, -0.13055541, -0.1675786 , -0.01549265, + -0.18310131, -0.00520398, -0.04192809, -0.02779983, -0.03678838, + 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model_indices=array([ 0, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61]), model=ScalarModel(intercept=0.11633665599043491, linear_terms=array([ 0.01692106, -0.00599296, -0.07183474]), square_terms=array([[ 0.00430738, -0.00138782, -0.01722234], + [-0.00138782, 0.00047598, 0.00583328], + [-0.01722234, 0.00583328, 0.07191651]]), scale=0.04800142623549698, shift=array([4.05943857e+00, 3.93227684e+03, 8.72088478e-01])), vector_model=VectorModel(intercepts=array([ 0.07188797, 0.11842249, 0.08425784, 0.06302381, 0.02761407, + -0.01169908, -0.04725341, -0.13055541, -0.1675786 , -0.01549265, + -0.18310131, -0.00520398, -0.04192809, -0.02779983, -0.03678838, + -0.05747802, -0.07226194]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]]), square_terms=array([[[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]]]), scale=393.2276837211913, shift=array([4.05943857e+00, 3.93227684e+03, 8.72088478e-01])), candidate_index=62, candidate_x=array([4.06698105e+00, 3.93229322e+03, 9.20092104e-01]), index=62, x=array([4.06698105e+00, 3.93229322e+03, 9.20092104e-01]), fval=0.08328203055052266, rho=1.1521105575858042, accepted=True, new_indices=array([50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61]), old_indices_used=array([ 0, 48, 49]), old_indices_discarded=array([], dtype=int32), step_length=0.05128066423434844, relative_step_length=1.0683154284367173, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([4.06698105e+00, 3.93229322e+03, 9.20092104e-01]), radius=0.09600285247099397, bounds=Bounds(lower=array([1.1, 0. , 0.5]), upper=array([2.0e+01, 1.0e+04, 1.1e+00]))), model_indices=array([ 0, 50, 51, 54, 55, 56, 57, 58, 59, 60, 61, 62]), model=ScalarModel(intercept=0.08089110047653379, linear_terms=array([-0.00528525, -0.0001229 , 0.02824264]), square_terms=array([[ 1.16009632e-02, 2.30117604e-04, -6.86298394e-02], + [ 2.30117604e-04, 5.27144510e-06, 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+ + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]]]), scale=393.2276837211913, shift=array([4.05943857e+00, 3.93227684e+03, 8.72088478e-01])), candidate_index=63, candidate_x=array([4.15738965e+00, 3.93233146e+03, 9.28205841e-01]), index=63, x=array([4.15738965e+00, 3.93233146e+03, 9.28205841e-01]), fval=0.08098039536167431, rho=1.694664418866965, accepted=True, new_indices=array([], dtype=int32), old_indices_used=array([ 0, 50, 51, 54, 55, 56, 57, 58, 59, 60, 61, 62]), old_indices_discarded=array([35, 36, 39, 40, 41, 42, 44, 45, 46, 47, 48, 49, 52, 53]), step_length=0.09849549625031004, relative_step_length=1.025964267885365, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([4.15738965e+00, 3.93233146e+03, 9.28205841e-01]), radius=0.19200570494198793, bounds=Bounds(lower=array([1.1, 0. , 0.5]), upper=array([2.0e+01, 1.0e+04, 1.1e+00]))), model_indices=array([ 0, 50, 51, 54, 55, 56, 57, 59, 60, 61, 62, 63]), model=ScalarModel(intercept=0.08002590130028917, linear_terms=array([-0.00526566, 0.000661 , 0.04112777]), square_terms=array([[ 2.05912030e-02, -2.69140553e-03, -1.45369821e-01], + [-2.69140553e-03, 4.27142888e-04, 2.22767331e-02], + [-1.45369821e-01, 2.22767331e-02, 1.17421707e+00]]), scale=array([0.15475583, 0.15475583, 0.15475583]), shift=array([4.15738965e+00, 3.93233146e+03, 9.28205841e-01])), vector_model=VectorModel(intercepts=array([ 0.07188797, 0.11842249, 0.08425784, 0.06302381, 0.02761407, + -0.01169908, -0.04725341, -0.13055541, -0.1675786 , -0.01549265, + -0.18310131, -0.00520398, -0.04192809, -0.02779983, -0.03678838, + -0.05747802, -0.07226194]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]]), square_terms=array([[[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + 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n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([4.16380226e+00, 3.93248621e+03, 9.20643341e-01]), radius=0.38401140988397586, bounds=Bounds(lower=array([1.1, 0. , 0.5]), upper=array([2.0e+01, 1.0e+04, 1.1e+00]))), model_indices=array([41, 42, 44, 47, 48, 49, 54, 55, 59, 61, 63, 64]), model=ScalarModel(intercept=0.15326138046317392, linear_terms=array([0.55415723, 0.00612001, 0.65724766]), square_terms=array([[2.16178448e+00, 2.69601220e-02, 2.58028293e+00], + [2.69601220e-02, 3.98421161e-04, 3.15716605e-02], + [2.58028293e+00, 3.15716605e-02, 3.11749315e+00]]), scale=array([0.30951165, 0.30951165, 0.24443416]), shift=array([4.16380226e+00, 3.93248621e+03, 8.55565845e-01])), vector_model=VectorModel(intercepts=array([ 0.07188797, 0.11842249, 0.08425784, 0.06302381, 0.02761407, + -0.01169908, -0.04725341, -0.13055541, -0.1675786 , -0.01549265, + -0.18310131, -0.00520398, -0.04192809, -0.02779983, -0.03678838, + -0.05747802, -0.07226194]), 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upper=array([2.0e+01, 1.0e+04, 1.1e+00]))), model_indices=array([ 0, 42, 48, 50, 51, 52, 53, 58, 62, 63, 64, 65]), model=ScalarModel(intercept=0.07981427686533094, linear_terms=array([ 8.23222295e-04, -3.01457336e-06, -1.94680885e-04]), square_terms=array([[ 4.38349908e-03, -2.78417852e-04, -2.40946662e-02], + [-2.78417852e-04, 1.45680783e-04, 9.88295037e-03], + [-2.40946662e-02, 9.88295037e-03, 6.79192813e-01]]), scale=array([0.15475583, 0.15475583, 0.15475583]), shift=array([4.16380226e+00, 3.93248621e+03, 9.20643341e-01])), vector_model=VectorModel(intercepts=array([ 0.07188797, 0.11842249, 0.08425784, 0.06302381, 0.02761407, + -0.01169908, -0.04725341, -0.13055541, -0.1675786 , -0.01549265, + -0.18310131, -0.00520398, -0.04192809, -0.02779983, -0.03678838, + -0.05747802, -0.07226194]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + 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9.20412203e-01]), fval=0.07939979491586543, rho=3.2737438064381488, accepted=True, new_indices=array([], dtype=int32), old_indices_used=array([42, 48, 50, 51, 52, 53, 58, 62, 63, 64, 65, 66]), old_indices_discarded=array([ 0, 35, 38, 41, 44, 45, 47, 49, 54, 55, 56, 57, 59, 60, 61]), step_length=0.10215613340917244, relative_step_length=1.0640947719760474, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([4.12942468e+00, 3.93239001e+03, 9.20412203e-01]), radius=0.19200570494198793, bounds=Bounds(lower=array([1.1, 0. , 0.5]), upper=array([2.0e+01, 1.0e+04, 1.1e+00]))), model_indices=array([ 0, 50, 51, 54, 55, 56, 57, 59, 60, 63, 64, 67]), model=ScalarModel(intercept=0.0794221211152619, linear_terms=array([-8.78763547e-04, -7.32595189e-05, 1.57498998e-03]), square_terms=array([[ 1.88292059e-02, -8.43669110e-04, -1.35637703e-01], + [-8.43669110e-04, 5.18412063e-05, 7.55602994e-03], + [-1.35637703e-01, 7.55602994e-03, 1.13549976e+00]]), scale=array([0.15475583, 0.15475583, 0.15475583]), shift=array([4.12942468e+00, 3.93239001e+03, 9.20412203e-01])), vector_model=VectorModel(intercepts=array([ 0.07188797, 0.11842249, 0.08425784, 0.06302381, 0.02761407, + -0.01169908, -0.04725341, -0.13055541, -0.1675786 , -0.01549265, + -0.18310131, -0.00520398, -0.04192809, -0.02779983, -0.03678838, + -0.05747802, -0.07226194]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]]), square_terms=array([[[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 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67]), old_indices_discarded=array([34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 52, + 53, 58, 61, 62, 65, 66]), step_length=0.1591995195038744, relative_step_length=0.8291395276612978, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([4.16663860e+00, 3.93254477e+03, 9.23613025e-01]), radius=0.38401140988397586, bounds=Bounds(lower=array([1.1, 0. , 0.5]), upper=array([2.0e+01, 1.0e+04, 1.1e+00]))), model_indices=array([41, 42, 44, 47, 48, 49, 55, 63, 65, 66, 67, 68]), model=ScalarModel(intercept=0.11467755048322094, linear_terms=array([ 0.4301884 , -0.10852269, 0.38403869]), square_terms=array([[ 2.8059872 , -0.69595835, 2.53665519], + [-0.69595835, 0.17347376, -0.6322991 ], + [ 2.53665519, -0.6322991 , 2.32273428]]), scale=array([0.30951165, 0.30951165, 0.24294931]), shift=array([4.16663860e+00, 3.93254477e+03, 8.57050687e-01])), vector_model=VectorModel(intercepts=array([ 0.07188797, 0.11842249, 0.08425784, 0.06302381, 0.02761407, + 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3.93227684e+03, 8.72088478e-01])), candidate_index=71, candidate_x=array([4.13217290e+00, 3.93263940e+03, 9.20311146e-01]), index=68, x=array([4.16663860e+00, 3.93254477e+03, 9.23613025e-01]), fval=0.07908472064494197, rho=-2.866324235420139, accepted=False, new_indices=array([], dtype=int32), old_indices_used=array([42, 47, 48, 50, 51, 63, 64, 65, 66, 67, 68, 70]), old_indices_discarded=array([ 0, 35, 38, 41, 44, 45, 49, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, + 62, 69]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([4.16663860e+00, 3.93254477e+03, 9.23613025e-01]), radius=0.04800142623549698, bounds=Bounds(lower=array([1.1, 0. , 0.5]), upper=array([2.0e+01, 1.0e+04, 1.1e+00]))), model_indices=array([42, 48, 63, 64, 65, 66, 67, 68, 70, 71]), model=ScalarModel(intercept=0.07966045626129445, linear_terms=array([3.20987313e-04, 4.92207090e-05, 2.88283811e-03]), square_terms=array([[ 3.79212673e-04, 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accepted=True, new_indices=array([75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86]), old_indices_used=array([68, 73, 74]), old_indices_discarded=array([], dtype=int32), step_length=0.006052299097263197, relative_step_length=1.0086865448656241, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([4.16101457e+00, 3.93254256e+03, 9.23281861e-01]), radius=0.012000356558874246, bounds=Bounds(lower=array([1.1, 0. , 0.5]), upper=array([2.0e+01, 1.0e+04, 1.1e+00]))), model_indices=array([68, 75, 76, 77, 78, 79, 81, 82, 83, 84, 86, 87]), model=ScalarModel(intercept=0.07914371578873403, linear_terms=array([1.82176925e-04, 7.65262019e-05, 2.45374037e-06]), square_terms=array([[ 1.92862702e-04, -9.93628574e-06, -1.67037516e-03], + [-9.93628574e-06, 7.42657125e-07, 7.94573605e-05], + [-1.67037516e-03, 7.94573605e-05, 1.54724452e-02]]), scale=0.012000356558874246, shift=array([4.16101457e+00, 3.93254256e+03, 9.23281861e-01])), vector_model=VectorModel(intercepts=array([ 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State(trustregion=Region(center=array([4.16101457e+00, 3.93254256e+03, 9.23281861e-01]), radius=0.006000178279437123, bounds=Bounds(lower=array([1.1, 0. , 0.5]), upper=array([2.0e+01, 1.0e+04, 1.1e+00]))), model_indices=array([68, 75, 76, 77, 78, 79, 80, 81, 83, 84, 86, 87]), model=ScalarModel(intercept=0.07914612489984735, linear_terms=array([ 9.04725864e-05, 3.30565774e-05, -2.19601997e-05]), square_terms=array([[ 4.27792898e-05, -4.53845336e-06, -3.94771372e-04], + [-4.53845336e-06, 5.36493868e-07, 4.14551856e-05], + [-3.94771372e-04, 4.14551856e-05, 3.90706076e-03]]), scale=0.006000178279437123, shift=array([4.16101457e+00, 3.93254256e+03, 9.23281861e-01])), vector_model=VectorModel(intercepts=array([ 0.07188797, 0.11842249, 0.08425784, 0.06302381, 0.02761407, + -0.01169908, -0.04725341, -0.13055541, -0.1675786 , -0.01549265, + -0.18310131, -0.00520398, -0.04192809, -0.02779983, -0.03678838, + -0.05747802, -0.07226194]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.], + [0., 0., 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model=ScalarModel(intercept=0.07916583626576876, linear_terms=array([ 3.46835434e-05, 1.37176019e-05, -3.87853430e-06]), square_terms=array([[ 1.16702087e-05, -1.13065279e-06, -1.02787515e-04], + [-1.13065279e-06, 1.19282548e-07, 9.91369374e-06], + [-1.02787515e-04, 9.91369374e-06, 9.72885293e-04]]), scale=0.0030000891397185614, shift=array([4.16101457e+00, 3.93254256e+03, 9.23281861e-01])), vector_model=VectorModel(intercepts=array([ 0.07188797, 0.11842249, 0.08425784, 0.06302381, 0.02761407, + -0.01169908, -0.04725341, -0.13055541, -0.1675786 , -0.01549265, + -0.18310131, -0.00520398, -0.04192809, -0.02779983, -0.03678838, + -0.05747802, -0.07226194]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]]), square_terms=array([[[0., 0., 0.], + [0., 0., 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3.93254141e+03, 9.23023628e-01]), index=87, x=array([4.16101457e+00, 3.93254256e+03, 9.23281861e-01]), fval=0.07907999189313741, rho=-0.5105398504494335, accepted=False, new_indices=array([], dtype=int32), old_indices_used=array([68, 75, 76, 77, 78, 79, 80, 81, 83, 84, 87, 89]), old_indices_discarded=array([74, 82, 85, 86, 88]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([4.16101457e+00, 3.93254256e+03, 9.23281861e-01]), radius=0.0015000445698592807, bounds=Bounds(lower=array([1.1, 0. , 0.5]), upper=array([2.0e+01, 1.0e+04, 1.1e+00]))), model_indices=array([68, 77, 83, 87, 89, 90]), model=ScalarModel(intercept=0.07909333025755838, linear_terms=array([-1.15137705e-05, -7.91213109e-07, 9.73368802e-05]), square_terms=array([[ 3.75332861e-06, -1.15364186e-07, -2.97559553e-05], + [-1.15364186e-07, 1.95191461e-08, 8.40989334e-07], + [-2.97559553e-05, 8.40989334e-07, 2.56198599e-04]]), scale=0.0015000445698592807, shift=array([4.16101457e+00, 3.93254256e+03, 9.23281861e-01])), vector_model=VectorModel(intercepts=array([ 0.07188797, 0.11842249, 0.08425784, 0.06302381, 0.02761407, + -0.01169908, -0.04725341, -0.13055541, -0.1675786 , -0.01549265, + -0.18310131, -0.00520398, -0.04192809, -0.02779983, -0.03678838, + -0.05747802, -0.07226194]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]]), square_terms=array([[[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], 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step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([4.16101457e+00, 3.93254256e+03, 9.23281861e-01]), radius=0.0007500222849296404, bounds=Bounds(lower=array([1.1, 0. , 0.5]), upper=array([2.0e+01, 1.0e+04, 1.1e+00]))), model_indices=array([ 87, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, + 102, 103]), model=ScalarModel(intercept=0.07910448579668597, linear_terms=array([-9.82149673e-08, 5.86243338e-06, -2.29104355e-05]), square_terms=array([[ 8.28466084e-07, -2.44013709e-08, -6.66789179e-06], + [-2.44013709e-08, 3.18448291e-09, 1.62847966e-07], + [-6.66789179e-06, 1.62847966e-07, 5.95987805e-05]]), scale=0.0007500222849296404, shift=array([4.16101457e+00, 3.93254256e+03, 9.23281861e-01])), vector_model=VectorModel(intercepts=array([ 0.07188797, 0.11842249, 0.08425784, 0.06302381, 0.02761407, + -0.01169908, -0.04725341, -0.13055541, -0.1675786 , -0.01549265, + -0.18310131, -0.00520398, -0.04192809, 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0.5]), upper=array([2.0e+01, 1.0e+04, 1.1e+00]))), model_indices=array([ 87, 92, 93, 96, 97, 98, 99, 100, 101, 102, 103, 104]), model=ScalarModel(intercept=0.07909403564536577, linear_terms=array([-1.22102547e-05, 7.60923217e-06, -5.17261450e-06]), square_terms=array([[ 3.36799435e-06, -1.27039621e-07, -2.66224628e-05], + [-1.27039621e-07, 2.41088585e-08, 9.99863513e-07], + [-2.66224628e-05, 9.99863513e-07, 2.37983666e-04]]), scale=0.0015000445698592807, shift=array([4.16127032e+00, 3.93254191e+03, 9.23567705e-01])), vector_model=VectorModel(intercepts=array([ 0.07188797, 0.11842249, 0.08425784, 0.06302381, 0.02761407, + -0.01169908, -0.04725341, -0.13055541, -0.1675786 , -0.01549265, + -0.18310131, -0.00520398, -0.04192809, -0.02779983, -0.03678838, + -0.05747802, -0.07226194]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], 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scale=393.2276837211913, shift=array([4.05943857e+00, 3.93227684e+03, 8.72088478e-01])), candidate_index=105, candidate_x=array([4.16253783e+00, 3.93254113e+03, 9.23735181e-01]), index=104, x=array([4.16127032e+00, 3.93254191e+03, 9.23567705e-01]), fval=0.07906796375411648, rho=-1.0803986646623365, accepted=False, new_indices=array([], dtype=int32), old_indices_used=array([ 87, 92, 93, 96, 97, 98, 99, 100, 101, 102, 103, 104]), old_indices_discarded=array([68, 77, 83, 89, 90, 91, 94, 95]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([4.16127032e+00, 3.93254191e+03, 9.23567705e-01]), radius=0.0007500222849296404, bounds=Bounds(lower=array([1.1, 0. , 0.5]), upper=array([2.0e+01, 1.0e+04, 1.1e+00]))), model_indices=array([ 87, 92, 93, 94, 95, 96, 97, 98, 99, 101, 102, 104]), model=ScalarModel(intercept=0.07909160054167635, linear_terms=array([-1.29680002e-05, 2.27817382e-06, 1.03758748e-06]), square_terms=array([[ 9.19566779e-07, -3.49328357e-08, -6.93344117e-06], + [-3.49328357e-08, 6.61278422e-09, 2.68258739e-07], + [-6.93344117e-06, 2.68258739e-07, 5.96608551e-05]]), scale=0.0007500222849296404, shift=array([4.16127032e+00, 3.93254191e+03, 9.23567705e-01])), vector_model=VectorModel(intercepts=array([ 0.07188797, 0.11842249, 0.08425784, 0.06302381, 0.02761407, + -0.01169908, -0.04725341, -0.13055541, -0.1675786 , -0.01549265, + -0.18310131, -0.00520398, -0.04192809, -0.02779983, -0.03678838, + -0.05747802, -0.07226194]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]]), square_terms=array([[[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 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fval=0.07906796375411648, rho=-0.13973162244364834, accepted=False, new_indices=array([], dtype=int32), old_indices_used=array([ 87, 92, 93, 94, 95, 96, 97, 98, 99, 101, 102, 104]), old_indices_discarded=array([ 83, 90, 91, 100, 103, 105]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([4.16127032e+00, 3.93254191e+03, 9.23567705e-01]), radius=0.0003750111424648202, bounds=Bounds(lower=array([1.1, 0. , 0.5]), upper=array([2.0e+01, 1.0e+04, 1.1e+00]))), model_indices=array([ 87, 92, 94, 95, 96, 97, 98, 99, 101, 102, 104, 106]), model=ScalarModel(intercept=0.07908661788272847, linear_terms=array([-8.35298009e-06, 7.05475745e-06, 1.43187070e-06]), square_terms=array([[ 2.33438460e-07, -1.55439804e-08, -1.73669039e-06], + [-1.55439804e-08, 5.10319166e-09, 8.60392613e-08], + [-1.73669039e-06, 8.60392613e-08, 1.49265352e-05]]), scale=0.0003750111424648202, shift=array([4.16127032e+00, 3.93254191e+03, 9.23567705e-01])), vector_model=VectorModel(intercepts=array([ 0.07188797, 0.11842249, 0.08425784, 0.06302381, 0.02761407, + -0.01169908, -0.04725341, -0.13055541, -0.1675786 , -0.01549265, + -0.18310131, -0.00520398, -0.04192809, -0.02779983, -0.03678838, + -0.05747802, -0.07226194]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]]), square_terms=array([[[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 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relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([4.16127032e+00, 3.93254191e+03, 9.23567705e-01]), radius=0.0001875055712324101, bounds=Bounds(lower=array([1.1, 0. , 0.5]), upper=array([2.0e+01, 1.0e+04, 1.1e+00]))), model_indices=array([ 87, 94, 95, 98, 102, 104, 106, 107]), model=ScalarModel(intercept=0.0790879150221595, linear_terms=array([-6.18729811e-06, 2.85069426e-06, 5.24029282e-06]), square_terms=array([[ 6.39029879e-08, -5.52613342e-09, -4.58386220e-07], + [-5.52613342e-09, 1.01866206e-09, 2.93309494e-08], + [-4.58386220e-07, 2.93309494e-08, 3.89516694e-06]]), scale=0.0001875055712324101, shift=array([4.16127032e+00, 3.93254191e+03, 9.23567705e-01])), vector_model=VectorModel(intercepts=array([ 0.07188797, 0.11842249, 0.08425784, 0.06302381, 0.02761407, + -0.01169908, -0.04725341, -0.13055541, -0.1675786 , -0.01549265, + -0.18310131, -0.00520398, -0.04192809, -0.02779983, -0.03678838, + -0.05747802, -0.07226194]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]]), square_terms=array([[[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 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model=ScalarModel(intercept=0.07906796375411641, linear_terms=array([-2.77746966e-05, -3.22673327e-05, -4.25319102e-05]), square_terms=array([[ 5.39542744e-08, 4.53199229e-08, -4.64131654e-08], + [ 4.53199229e-08, 4.98555993e-08, 7.22290924e-08], + [-4.64131654e-08, 7.22290924e-08, 1.14321313e-06]]), scale=9.375278561620504e-05, shift=array([4.16127032e+00, 3.93254191e+03, 9.23567705e-01])), vector_model=VectorModel(intercepts=array([ 0.07188797, 0.11842249, 0.08425784, 0.06302381, 0.02761407, + -0.01169908, -0.04725341, -0.13055541, -0.1675786 , -0.01549265, + -0.18310131, -0.00520398, -0.04192809, -0.02779983, -0.03678838, + -0.05747802, -0.07226194]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]]), square_terms=array([[[0., 0., 0.], + [0., 0., 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3.93254196e+03, 9.23633511e-01]), index=104, x=array([4.16127032e+00, 3.93254191e+03, 9.23567705e-01]), fval=0.07906796375411648, rho=-0.11603470278551233, accepted=False, new_indices=array([], dtype=int32), old_indices_used=array([ 95, 104, 107, 108]), old_indices_discarded=array([], dtype=int32), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([4.16127032e+00, 3.93254191e+03, 9.23567705e-01]), radius=4.687639280810252e-05, bounds=Bounds(lower=array([1.1, 0. , 0.5]), upper=array([2.0e+01, 1.0e+04, 1.1e+00]))), model_indices=array([104, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, + 120, 121]), model=ScalarModel(intercept=0.07907082869590354, linear_terms=array([ 2.88136945e-06, -3.08394182e-07, -1.07721092e-06]), square_terms=array([[ 4.46329859e-09, -6.05308320e-10, -2.92877945e-08], + [-6.05308320e-10, 1.34067088e-10, 3.43225360e-09], + [-2.92877945e-08, 3.43225360e-09, 2.44027182e-07]]), 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State(trustregion=Region(center=array([4.46657035e+00, 4.58718267e+03, 9.28413348e-01]), radius=3.583736458824989, bounds=Bounds(lower=array([1.1, 0. , 0.5]), upper=array([2.0e+01, 1.0e+04, 1.1e+00]))), model_indices=array([ 0, 18, 20, 21, 22, 23, 25, 26, 27, 29, 30, 31]), model=ScalarModel(intercept=93.97983279704786, linear_terms=array([-158.16807239, 51.83688273, 84.93922156]), square_terms=array([[133.49622213, -43.70152356, -71.15581564], + [-43.70152356, 14.31811665, 23.35552818], + [-71.15581564, 23.35552818, 39.27068276]]), scale=array([2.88847717, 2.88847717, 0.3 ]), shift=array([4.46657035e+00, 4.58718267e+03, 8.00000000e-01])), vector_model=VectorModel(intercepts=array([ 0.07159608, 0.12121607, 0.09389742, 0.08054577, 0.0538135 , + 0.02465656, -0.00063106, -0.06576639, -0.11100278, 0.0223435 , + -0.16780024, -0.02088758, -0.04018239, -0.0329881 , -0.04664206, + -0.06960775, -0.0857819 ]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + 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8.00000000e-01])), vector_model=VectorModel(intercepts=array([ 0.07159608, 0.12121607, 0.09389742, 0.08054577, 0.0538135 , + 0.02465656, -0.00063106, -0.06576639, -0.11100278, 0.0223435 , + -0.16780024, -0.02088758, -0.04018239, -0.0329881 , -0.04664206, + -0.06960775, -0.0857819 ]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]]), square_terms=array([[[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 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8.21257590e-01]), index=34, x=array([4.28097285e+00, 4.58790479e+03, 9.27938755e-01]), fval=0.08450890381661277, rho=-0.05757584370248203, accepted=False, new_indices=array([], dtype=int32), old_indices_used=array([34, 35, 36, 37, 39, 40, 41, 42, 44, 45, 46, 47]), old_indices_discarded=array([ 0, 38, 43]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([4.28097285e+00, 4.58790479e+03, 9.27938755e-01]), radius=0.11199176433828091, bounds=Bounds(lower=array([1.1, 0. , 0.5]), upper=array([2.0e+01, 1.0e+04, 1.1e+00]))), model_indices=array([34, 35, 36, 39, 40, 41, 42, 44, 45, 46, 47, 48]), model=ScalarModel(intercept=2.3684676382089758, linear_terms=array([-0.10988363, -0.66436773, 2.75173228]), square_terms=array([[ 0.00591366, 0.01676982, -0.07000994], + [ 0.01676982, 0.09679265, -0.40121714], + [-0.07000994, -0.40121714, 1.66585423]]), scale=0.11199176433828091, shift=array([4.28097285e+00, 4.58790479e+03, 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56, 57, 58, 59, 60, 61]), model=ScalarModel(intercept=0.08780533673879214, linear_terms=array([-0.00204222, -0.000514 , 0.02518641]), square_terms=array([[ 9.44732408e-04, 1.61167329e-04, -9.59779358e-03], + [ 1.61167329e-04, 3.11556686e-05, -1.82922922e-03], + [-9.59779358e-03, -1.82922922e-03, 1.08278084e-01]]), scale=0.027997941084570228, shift=array([4.28097285e+00, 4.58790479e+03, 9.27938755e-01])), vector_model=VectorModel(intercepts=array([ 0.07159608, 0.12121607, 0.09389742, 0.08054577, 0.0538135 , + 0.02465656, -0.00063106, -0.06576639, -0.11100278, 0.0223435 , + -0.16780024, -0.02088758, -0.04018239, -0.0329881 , -0.04664206, + -0.06960775, -0.0857819 ]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]]), square_terms=array([[[0., 0., 0.], 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vector_model=VectorModel(intercepts=array([ 0.07159608, 0.12121607, 0.09389742, 0.08054577, 0.0538135 , + 0.02465656, -0.00063106, -0.06576639, -0.11100278, 0.0223435 , + -0.16780024, -0.02088758, -0.04018239, -0.0329881 , -0.04664206, + -0.06960775, -0.0857819 ]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]]), square_terms=array([[[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 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[1.64562500e+01, 6.87500000e+03, 9.87500000e-01], + [1.35031250e+01, 6.56250000e+03, 5.18750000e-01], + [1.17312500e+01, 4.37500000e+03, 5.37500000e-01], + [1.82281250e+01, 4.06250000e+03, 9.68750000e-01], + [4.64375000e+00, 3.12500000e+03, 1.06250000e+00], + [1.23218750e+01, 9.68750000e+03, 1.08125000e+00], + [2.28125000e+00, 9.37500000e+03, 8.37500000e-01]]), 'exploration_results': array([ 0.15183336, 0.16963129, 0.3197984 , 0.64023668, 0.65671129, + 0.81183081, 0.97682658, 1.08889746, 1.16160077, 1.27832959, + 1.4056054 , 1.63187357, 1.68853551, 1.72432777, 1.75966476, + 1.80211806, 1.86015904, 1.93985391, 1.96313642, 2.01014295, + 2.05048939, 2.06445231, 2.29147195, 2.43324345, 2.49173392, + 2.54550964, 3.05245049, 4.00840374, 4.33350039, 58.25645251])}}" diff --git a/code/estimark/content/tables/min/WarmGlowPortfolioShiftAlt_estimate_results.csv b/code/estimark/content/tables/min/WarmGlowPortfolioShiftAlt_estimate_results.csv new file mode 100644 index 0000000..cb15f2c --- /dev/null +++ b/code/estimark/content/tables/min/WarmGlowPortfolioShiftAlt_estimate_results.csv @@ -0,0 +1,13571 @@ +CRRA,4.177600674290874 +BeqFac,2798.51512022846 +BeqShift,1.966935700692675 +time_to_estimate,213.91753792762756 +params,"{'CRRA': 4.177600674290874, 'BeqFac': 2798.51512022846, 'BeqShift': 1.966935700692675}" +criterion,0.050872538941762795 +start_criterion,0.149744421401998 +start_params,"{'CRRA': 4.972059127341761, 'BeqFac': 2235.66869440018, 'BeqShift': 0.0}" +algorithm,multistart_tranquilo_ls +direction,minimize +n_free,3 +message,Absolute criterion change smaller than tolerance. +success, +n_criterion_evaluations, +n_derivative_evaluations, +n_iterations, +history,"{'params': [{'CRRA': 4.968360850653578, 'BeqFac': 3489.450001032764, 'BeqShift': 5.063898656927828}, {'CRRA': 1.7676219917476326, 'BeqFac': 3208.2017347523847, 'BeqShift': 59.767774879194484}, {'CRRA': 16.954188449436767, 'BeqFac': 3208.2017347523847, 'BeqShift': 59.36329156294464}, {'CRRA': 20.0, 'BeqFac': 3654.6597147490415, 'BeqShift': 68.98140770341323}, {'CRRA': 13.880517002473926, 'BeqFac': 3762.6620464840953, 'BeqShift': 0.0}, {'CRRA': 7.980394574068313, 'BeqFac': 3770.698267313143, 'BeqShift': 68.474214057218}, {'CRRA': 20.0, 'BeqFac': 3766.1176162364645, 'BeqShift': 62.246768898687904}, {'CRRA': 1.1, 'BeqFac': 3768.540325045825, 'BeqShift': 44.85155276807863}, {'CRRA': 1.3101094923283654, 'BeqFac': 3450.623397898459, 'BeqShift': 70.0}, {'CRRA': 20.0, 'BeqFac': 3560.402448203421, 'BeqShift': 2.701409905191556}, {'CRRA': 13.071215358144052, 'BeqFac': 3208.2017347523847, 'BeqShift': 1.1192446483918272}, {'CRRA': 1.1, 'BeqFac': 3756.7786109759786, 'BeqShift': 16.46504634175265}, {'CRRA': 19.298974170870512, 'BeqFac': 3208.2017347523847, 'BeqShift': 69.91718013800757}, {'CRRA': 12.880975106243817, 'BeqFac': 3208.2017347523847, 'BeqShift': 0.0}, {'CRRA': 9.251225991471458, 'BeqFac': 3067.5776016121954, 'BeqShift': 0.0}, {'CRRA': 3.6375521204171073, 'BeqFac': 2788.697983380339, 'BeqShift': 0.0}, {'CRRA': 5.92463589656902, 'BeqFac': 2926.953468472006, 'BeqShift': 0.0}, {'CRRA': 2.8027826445672543, 'BeqFac': 2645.705202191627, 'BeqShift': 0.0}, {'CRRA': 5.2002500994259755, 'BeqFac': 2786.3293353318168, 'BeqShift': 0.0}, {'CRRA': 6.053954286705494, 'BeqFac': 2716.017268761722, 'BeqShift': 0.0}, {'CRRA': 8.187236245412365, 'BeqFac': 2786.5716524216164, 'BeqShift': 18.264936837321702}, {'CRRA': 5.031061131954489, 'BeqFac': 2803.9073519743406, 'BeqShift': 0.0}, {'CRRA': 5.1602411817300915, 'BeqFac': 2790.951969685949, 'BeqShift': 0.0}, {'CRRA': 5.115380638236383, 'BeqFac': 2799.7409780072107, 'BeqShift': 0.0}, {'CRRA': 4.969188948943323, 'BeqFac': 2817.3189946497346, 'BeqShift': 0.0}, {'CRRA': 5.094531333414104, 'BeqFac': 2808.2705494870056, 'BeqShift': 0.0}, {'CRRA': 5.117653729382992, 'BeqFac': 2804.1354821678415, 'BeqShift': 0.0}, {'CRRA': 5.1153639498249674, 'BeqFac': 2799.7464982727965, 'BeqShift': 2.1972486130609576}, {'CRRA': 4.457344957675711, 'BeqFac': 2798.642351967053, 'BeqShift': 1.09862604015773}, {'CRRA': 4.323396337115101, 'BeqFac': 2800.8396040473685, 'BeqShift': 2.1547660163343503}, {'CRRA': 3.9411714212557856, 'BeqFac': 2797.543725926895, 'BeqShift': 2.093983387066586}, {'CRRA': 4.29994611299188, 'BeqFac': 2798.7155134039913, 'BeqShift': 1.7713480594884083}, {'CRRA': 4.056025184478589, 'BeqFac': 2797.346363767581, 'BeqShift': 2.24557407349223}, {'CRRA': 4.138045729552536, 'BeqFac': 2798.031127683044, 'BeqShift': 2.212909490426139}, {'CRRA': 4.059989311567537, 'BeqFac': 2796.6669868735166, 'BeqShift': 2.282453732315161}, {'CRRA': 4.026002824798528, 'BeqFac': 2798.713856857443, 'BeqShift': 2.270987106425888}, {'CRRA': 4.142328704202798, 'BeqFac': 2798.371239838438, 'BeqShift': 2.115320067541048}, {'CRRA': 4.035421021891758, 'BeqFac': 2799.057000705553, 'BeqShift': 2.268072829011086}, {'CRRA': 4.162342849386828, 'BeqFac': 2798.7120382787884, 'BeqShift': 2.0820283126821564}, {'CRRA': 4.189180729803071, 'BeqFac': 2798.4313906514644, 'BeqShift': 1.9567124389800021}, {'CRRA': 4.157129843134547, 'BeqFac': 2798.773188323082, 'BeqShift': 2.0571220165181043}, {'CRRA': 4.197784149507958, 'BeqFac': 2798.2613053833006, 'BeqShift': 1.9049698616184068}, {'CRRA': 4.1882127035206445, 'BeqFac': 2798.516512627961, 'BeqShift': 1.9233372105334974}, {'CRRA': 4.196587606858762, 'BeqFac': 2798.6869627340325, 'BeqShift': 1.9121957926636612}, {'CRRA': 4.187761980105835, 'BeqFac': 2798.6017090857436, 'BeqShift': 1.9286485471909265}, {'CRRA': 4.196242132162183, 'BeqFac': 2798.7722084678076, 'BeqShift': 1.912079557485072}, {'CRRA': 4.190550713034702, 'BeqFac': 2798.5165199690787, 'BeqShift': 1.9263643061813749}, {'CRRA': 4.189871366285182, 'BeqFac': 2798.3461525835946, 'BeqShift': 1.923926585872323}, {'CRRA': 4.187709060456282, 'BeqFac': 2798.601712437453, 'BeqShift': 1.929437283451666}, {'CRRA': 4.177600674290874, 'BeqFac': 2798.51512022846, 'BeqShift': 1.966935700692675}], 'criterion': [1.181105432157004, 144.6645524000311, 3.4037821967481316, 8.319436275338557, 1.4593214606471996, 0.7011180013216807, 8.319436275338557, 1643.2967077523338, 1137.5807967428811, 8.319436275342273, 1.1697753502038721, 1668.6551408328123, 6.776870912396954, 1.1406131109915512, 0.5545985836347646, 2.2278811659484714, 0.232036655988764, 18.119098849415735, 0.16384370556335875, 0.2527959294336996, 0.6819421555415957, 0.1642991669381873, 0.1628347112711602, 0.1625021910643016, 0.16817866367514966, 0.1627923319728763, 0.16259635535169853, 0.42498980410057874, 0.06529563513965843, 0.08399250593750511, 0.10068669909272801, 0.05432022221654956, 0.05415908459581581, 0.05275688891668154, 0.05330674080076367, 0.057419127185494, 0.051318965064022795, 0.05612791206991445, 0.051424151471162374, 0.05091436090216683, 0.051068448210695803, 0.050914579506761565, 0.05088712976930869, 0.050908465316813346, 0.050875284135983245, 0.050910162881492554, 0.0508732681045439, 0.050878919485344336, 0.05087623002457618, 0.050872538941762795], 'runtime': [0.0, 1.504941400140524, 1.6768188998103142, 1.8667818000540137, 2.0520103997550905, 2.234589799772948, 2.4240341000258923, 2.6088847001083195, 2.7994983000680804, 2.995965300127864, 3.1924839997664094, 3.3760963999666274, 3.5580016998574138, 4.759761999826878, 5.9858081000857055, 7.170780099928379, 8.360401600133628, 9.697439599782228, 10.887631500139832, 12.083789399825037, 13.26669319998473, 14.449900799896568, 15.622420799918473, 16.798246500082314, 17.96437279973179, 19.288782899733633, 20.466819599736482, 21.645570000167936, 22.826812400016934, 24.006268199998885, 25.212331799790263, 26.400473299901932, 27.575066099874675, 28.895407499745488, 30.087074699811637, 31.28205809975043, 32.452069099992514, 33.63252570014447, 34.80818759975955, 35.983998800162226, 37.16741700004786, 38.50141609972343, 39.70189919974655, 40.88999589998275, 42.06016460014507, 43.238295500166714, 44.42306770011783, 45.59471370000392, 46.93225569976494, 48.113191300071776], 'batches': [0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38]}" +convergence_report,"{'one_step': {'relative_criterion_change': 0.018714300470562203, 'relative_params_change': 0.22317607955398075, 'absolute_criterion_change': 0.0018714300470562203, 'absolute_params_change': 561.5795603000294}, 'five_steps': {'relative_criterion_change': 0.018714300470562203, 'relative_params_change': 0.22317607955398075, 'absolute_criterion_change': 0.0018714300470562203, 'absolute_params_change': 561.5795603000294}}" +multistart_info,"{'start_parameters': [{'CRRA': 4.972059127341761, 'BeqFac': 2235.66869440018, 'BeqShift': 0.0}, {'CRRA': 6.333842432535624, 'BeqFac': 3668.9001041779247, 'BeqShift': 6.573413466501883}, {'CRRA': 4.968360850653578, 'BeqFac': 3489.450001032764, 'BeqShift': 5.063898656927828}], 'local_optima': [Minimize with 3 free parameters terminated. + +The tranquilo_ls algorithm reported: Absolute criterion change smaller than tolerance. + +Independent of the convergence criteria used by tranquilo_ls, the strength of convergence can be assessed by the following criteria: + + one_step five_steps +relative_criterion_change 3.577e-07* 6.797e-06* +relative_params_change 0.0001525 0.0002161 +absolute_criterion_change 3.577e-08* 6.797e-07* +absolute_params_change 0.0007074 0.0007074 + +(***: change <= 1e-10, **: change <= 1e-8, *: change <= 1e-5. Change refers to a change between accepted steps. The first column only considers the last step. The second column considers the last five steps.), Minimize with 3 free parameters terminated. + +The tranquilo_ls algorithm reported: Absolute criterion change smaller than tolerance. + +Independent of the convergence criteria used by tranquilo_ls, the strength of convergence can be assessed by the following criteria: + + one_step five_steps +relative_criterion_change 8.731e-08* 0.000407 +relative_params_change 0.001013 0.02664 +absolute_criterion_change 5.598e-08* 0.000261 +absolute_params_change 0.01402 0.3641 + +(***: change <= 1e-10, **: change <= 1e-8, *: change <= 1e-5. Change refers to a change between accepted steps. The first column only considers the last step. The second column considers the last five steps.), Minimize with 3 free parameters terminated. + +The tranquilo_ls algorithm reported: Absolute criterion change smaller than tolerance. + +Independent of the convergence criteria used by tranquilo_ls, the strength of convergence can be assessed by the following criteria: + + one_step five_steps +relative_criterion_change 7.292e-06* 0.004464 +relative_params_change 0.02086 0.07591 +absolute_criterion_change 7.292e-07* 0.0004464 +absolute_params_change 0.04261 0.2097 + +(***: change <= 1e-10, **: change <= 1e-8, *: change <= 1e-5. Change refers to a change between accepted steps. The first column only considers the last step. The second column considers the last five steps.)], 'exploration_sample': [{'CRRA': 4.972059127341761, 'BeqFac': 2235.66869440018, 'BeqShift': 0.0}, {'CRRA': 9.368749999999999, 'BeqFac': 5625.0, 'BeqShift': 13.125}, {'CRRA': 8.778125, 'BeqFac': 9062.5, 'BeqShift': 19.6875}, {'CRRA': 9.959375, 'BeqFac': 937.5, 'BeqShift': 59.0625}, {'CRRA': 8.1875, 'BeqFac': 3750.0, 'BeqShift': 43.75}, {'CRRA': 10.549999999999999, 'BeqFac': 5000.0, 'BeqShift': 35.0}, {'CRRA': 7.596874999999999, 'BeqFac': 7187.5, 'BeqShift': 50.3125}, {'CRRA': 7.00625, 'BeqFac': 1875.0, 'BeqShift': 21.875}, {'CRRA': 11.73125, 'BeqFac': 4375.0, 'BeqShift': 4.375}, {'CRRA': 12.321874999999999, 'BeqFac': 9687.5, 'BeqShift': 67.8125}, {'CRRA': 6.415625, 'BeqFac': 2812.5, 'BeqShift': 10.9375}, {'CRRA': 12.9125, 'BeqFac': 1250.0, 'BeqShift': 61.25}, {'CRRA': 5.824999999999999, 'BeqFac': 7500.0, 'BeqShift': 52.5}, {'CRRA': 5.234375, 'BeqFac': 8437.5, 'BeqShift': 6.5625}, {'CRRA': 13.503124999999999, 'BeqFac': 6562.5, 'BeqShift': 2.1875}, {'CRRA': 14.093749999999998, 'BeqFac': 8125.0, 'BeqShift': 30.625}, {'CRRA': 14.684375, 'BeqFac': 3437.5, 'BeqShift': 41.5625}, {'CRRA': 4.64375, 'BeqFac': 3125.0, 'BeqShift': 65.625}, {'CRRA': 15.274999999999999, 'BeqFac': 2500.0, 'BeqShift': 17.5}, {'CRRA': 4.053125, 'BeqFac': 1562.5, 'BeqShift': 37.1875}, {'CRRA': 15.865624999999998, 'BeqFac': 7812.5, 'BeqShift': 45.9375}, {'CRRA': 3.4625, 'BeqFac': 6250.0, 'BeqShift': 26.25}, {'CRRA': 16.45625, 'BeqFac': 6875.0, 'BeqShift': 56.875}, {'CRRA': 2.871875, 'BeqFac': 4687.5, 'BeqShift': 32.8125}, {'CRRA': 17.046875, 'BeqFac': 2187.5, 'BeqShift': 15.3125}, {'CRRA': 17.6375, 'BeqFac': 8750.0, 'BeqShift': 8.75}, {'CRRA': 18.228125, 'BeqFac': 4062.5, 'BeqShift': 54.6875}, {'CRRA': 18.81875, 'BeqFac': 625.0, 'BeqShift': 48.125}, {'CRRA': 19.409375, 'BeqFac': 5937.5, 'BeqShift': 24.0625}, {'CRRA': 2.28125, 'BeqFac': 9375.0, 'BeqShift': 39.375}], 'exploration_results': array([ 0.15183333, 0.64211538, 0.64842412, 0.66164015, 0.68191739, + 0.7044766 , 0.74714867, 0.84822968, 0.86260573, 0.97951322, + 0.98915247, 1.12431839, 1.18220644, 1.20662179, 1.30406801, + 1.52011014, 1.78024917, 1.78135807, 2.0971452 , 2.24437522, + 2.48116605, 2.85787595, 2.94379242, 3.4148927 , 3.4976294 , + 4.16035282, 4.94978648, 5.89491246, 7.00125067, 34.37799292])}" +algorithm_output,"{'states': [State(trustregion=Region(center=array([ 4.96836085, 3489.45000103, 5.06389866]), radius=348.9450001032764, bounds=Bounds(lower=array([1.1, 0. , 0. ]), upper=array([ 20., 10000., 70.]))), model_indices=[0], model=ScalarModel(intercept=1.181105432157004, linear_terms=array([0., 0., 0.]), square_terms=array([[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]]), scale=348.9450001032764, shift=array([ 4.96836085, 3489.45000103, 5.06389866])), vector_model=VectorModel(intercepts=array([ 1.57412309e-02, 3.56292054e-02, 1.46671126e-02, 2.00709899e-02, + 1.36314151e-02, 6.48338304e-06, -1.99307165e-02, -2.09559325e-01, + -3.40977225e-01, -3.07739315e-01, -6.19357811e-01, -5.84132142e-01, + 1.74722021e-01, 1.91181275e-01, 1.96930976e-01, 2.05706514e-01, + 2.24752360e-01]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]]), square_terms=array([[[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]]]), scale=348.9450001032764, shift=array([ 4.96836085, 3489.45000103, 5.06389866])), candidate_index=0, candidate_x=array([ 4.96836085, 3489.45000103, 5.06389866]), index=0, x=array([ 4.96836085, 3489.45000103, 5.06389866]), fval=1.181105432157004, rho=nan, accepted=True, new_indices=[0], old_indices_used=[], old_indices_discarded=[], step_length=None, relative_step_length=None, n_evals_per_point=None, n_evals_acceptance=None), State(trustregion=Region(center=array([ 4.96836085, 3489.45000103, 5.06389866]), radius=348.9450001032764, bounds=Bounds(lower=array([1.1, 0. , 0. ]), upper=array([ 20., 10000., 70.]))), model_indices=array([ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12]), model=ScalarModel(intercept=101.00053527176014, linear_terms=array([-267.17329649, 80.95099224, 52.1467112 ]), square_terms=array([[ 361.29036327, -108.39796365, -69.65799497], + [-108.39796365, 32.72200507, 21.00295023], + [ -69.65799497, 21.00295023, 13.52711371]]), scale=array([ 9.45 , 281.24826628, 35. ]), shift=array([ 10.55 , 3489.45000103, 35. ])), vector_model=VectorModel(intercepts=array([ 1.57412309e-02, 3.56292054e-02, 1.46671126e-02, 2.00709899e-02, + 1.36314151e-02, 6.48338304e-06, -1.99307165e-02, -2.09559325e-01, + -3.40977225e-01, -3.07739315e-01, -6.19357811e-01, -5.84132142e-01, + 1.74722021e-01, 1.91181275e-01, 1.96930976e-01, 2.05706514e-01, + 2.24752360e-01]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]]), square_terms=array([[[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]]]), scale=348.9450001032764, shift=array([ 4.96836085, 3489.45000103, 5.06389866])), candidate_index=13, candidate_x=array([ 12.88097511, 3208.20173475, 0. ]), index=13, x=array([ 12.88097511, 3208.20173475, 0. ]), fval=1.1406131109915512, rho=0.00016464076262107032, accepted=True, new_indices=array([ 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12]), old_indices_used=array([0]), old_indices_discarded=array([], dtype=int32), step_length=281.40511690387655, relative_step_length=0.8064454765667648, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 12.88097511, 3208.20173475, 0. ]), radius=174.4725000516382, bounds=Bounds(lower=array([1.1, 0. , 0. ]), upper=array([ 20., 10000., 70.]))), model_indices=array([ 0, 1, 2, 3, 4, 6, 8, 9, 10, 11, 12, 13]), model=ScalarModel(intercept=30.184829913613466, linear_terms=array([-139.32389492, 29.36565848, 48.56265401]), square_terms=array([[ 337.66475622, -70.11282425, -115.6185002 ], + [ -70.11282425, 14.64456015, 24.13989901], + [-115.6185002 , 24.13989901, 39.85365245]]), scale=array([ 9.45 , 140.62413314, 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model=ScalarModel(intercept=3.807942725574409, linear_terms=array([-39.58737235, 12.58807335, 13.34355021]), square_terms=array([[288.79762252, -88.45374867, -92.48750266], + [-88.45374867, 27.21485773, 28.46514941], + [-92.48750266, 28.46514941, 29.83245946]]), scale=array([ 9.45 , 140.62413314, 35. ]), shift=array([ 10.55 , 3067.57760161, 35. ])), vector_model=VectorModel(intercepts=array([ 1.57412309e-02, 3.56292054e-02, 1.46671126e-02, 2.00709899e-02, + 1.36314151e-02, 6.48338304e-06, -1.99307165e-02, -2.09559325e-01, + -3.40977225e-01, -3.07739315e-01, -6.19357811e-01, -5.84132142e-01, + 1.74722021e-01, 1.91181275e-01, 1.96930976e-01, 2.05706514e-01, + 2.24752360e-01]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]]), square_terms=array([[[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]]]), scale=348.9450001032764, shift=array([ 4.96836085, 3489.45000103, 5.06389866])), candidate_index=16, candidate_x=array([ 5.9246359 , 2926.95346847, 0. ]), index=16, x=array([ 5.9246359 , 2926.95346847, 0. ]), fval=0.23203665598876397, rho=0.570002726445654, accepted=True, new_indices=array([], dtype=int32), old_indices_used=array([ 0, 1, 2, 3, 8, 9, 10, 11, 12, 13, 14, 15]), old_indices_discarded=array([4, 5, 6, 7]), step_length=140.66347437444162, relative_step_length=0.8062214637424797, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 5.9246359 , 2926.95346847, 0. ]), radius=348.9450001032764, bounds=Bounds(lower=array([1.1, 0. , 0. ]), upper=array([ 20., 10000., 70.]))), model_indices=array([ 0, 1, 2, 3, 8, 9, 10, 12, 13, 14, 15, 16]), model=ScalarModel(intercept=3.9661830657942825, linear_terms=array([-28.12732145, 11.87395531, 18.45752875]), square_terms=array([[150.75705807, -60.44190282, -91.27776749], + [-60.44190282, 24.37668461, 36.9203391 ], + [-91.27776749, 36.9203391 , 56.05439485]]), scale=array([ 9.45 , 281.24826628, 35. ]), shift=array([ 10.55 , 2926.95346847, 35. ])), vector_model=VectorModel(intercepts=array([ 1.57412309e-02, 3.56292054e-02, 1.46671126e-02, 2.00709899e-02, + 1.36314151e-02, 6.48338304e-06, -1.99307165e-02, -2.09559325e-01, + -3.40977225e-01, -3.07739315e-01, -6.19357811e-01, -5.84132142e-01, + 1.74722021e-01, 1.91181275e-01, 1.96930976e-01, 2.05706514e-01, + 2.24752360e-01]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]]), square_terms=array([[[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 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old_indices_discarded=array([ 4, 5, 6, 7, 11]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 5.9246359 , 2926.95346847, 0. ]), radius=174.4725000516382, bounds=Bounds(lower=array([1.1, 0. , 0. ]), upper=array([ 20., 10000., 70.]))), model_indices=array([ 0, 1, 2, 8, 9, 10, 12, 13, 14, 15, 16, 17]), model=ScalarModel(intercept=9.571328999106925, linear_terms=array([-45.18448012, 9.36031969, 33.66340283]), square_terms=array([[133.09207534, -26.87423247, -93.65514891], + [-26.87423247, 5.44544862, 19.03151488], + [-93.65514891, 19.03151488, 66.85203657]]), scale=array([ 9.45 , 140.62413314, 35. ]), shift=array([ 10.55 , 2926.95346847, 35. ])), vector_model=VectorModel(intercepts=array([ 1.57412309e-02, 3.56292054e-02, 1.46671126e-02, 2.00709899e-02, + 1.36314151e-02, 6.48338304e-06, -1.99307165e-02, -2.09559325e-01, + -3.40977225e-01, -3.07739315e-01, -6.19357811e-01, -5.84132142e-01, + 1.74722021e-01, 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step_length=8.789122808311065, relative_step_length=0.806006476042679, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 5.11538064, 2799.74097801, 0. ]), radius=21.809062506454776, bounds=Bounds(lower=array([1.1, 0. , 0. ]), upper=array([ 20., 10000., 70.]))), model_indices=array([15, 18, 19, 20, 21, 22, 23]), model=ScalarModel(intercept=15.956937372018299, linear_terms=array([68.87495584, 1.01962009, -8.11318965]), square_terms=array([[ 1.50828107e+02, 2.25090089e+00, -1.79474940e+01], + [ 2.25090089e+00, 3.37920630e-02, -2.69729608e-01], + [-1.79474940e+01, -2.69729608e-01, 2.15985383e+00]]), scale=array([ 9.45 , 17.57801664, 8.78900832]), shift=array([ 10.55 , 2799.74097801, 8.78900832])), vector_model=VectorModel(intercepts=array([ 1.57412309e-02, 3.56292054e-02, 1.46671126e-02, 2.00709899e-02, + 1.36314151e-02, 6.48338304e-06, -1.99307165e-02, -2.09559325e-01, + -3.40977225e-01, -3.07739315e-01, -6.19357811e-01, -5.84132142e-01, + 1.74722021e-01, 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model=ScalarModel(intercept=3.0353080773001073, linear_terms=array([20.20386846, 0.10823129, -1.77493216]), square_terms=array([[ 7.18576918e+01, 3.89097471e-01, -6.44170944e+00], + [ 3.89097471e-01, 2.11348833e-03, -3.50355915e-02], + [-6.44170944e+00, -3.50355915e-02, 5.83744149e-01]]), scale=array([6.40219448, 8.78900832, 4.39450416]), shift=array([ 7.50219448, 2799.74097801, 4.39450416])), vector_model=VectorModel(intercepts=array([ 1.57412309e-02, 3.56292054e-02, 1.46671126e-02, 2.00709899e-02, + 1.36314151e-02, 6.48338304e-06, -1.99307165e-02, -2.09559325e-01, + -3.40977225e-01, -3.07739315e-01, -6.19357811e-01, -5.84132142e-01, + 1.74722021e-01, 1.91181275e-01, 1.96930976e-01, 2.05706514e-01, + 2.24752360e-01]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 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model_indices=array([21, 23, 26, 27]), model=ScalarModel(intercept=0.143861477312966, linear_terms=array([ 1.39795372e-01, -1.67256636e-05, 9.44770003e-03]), square_terms=array([[ 4.72932788e-01, -1.19149158e-04, 1.43354432e-01], + [-1.19149158e-04, 3.31626099e-08, -4.20348131e-05], + [ 1.43354432e-01, -4.20348131e-05, 5.61768276e-02]]), scale=array([1.09862604, 1.09862604, 0.54931302]), shift=array([5.11538064e+00, 2.79974098e+03, 5.49313020e-01])), vector_model=VectorModel(intercepts=array([ 1.57412309e-02, 3.56292054e-02, 1.46671126e-02, 2.00709899e-02, + 1.36314151e-02, 6.48338304e-06, -1.99307165e-02, -2.09559325e-01, + -3.40977225e-01, -3.07739315e-01, -6.19357811e-01, -5.84132142e-01, + 1.74722021e-01, 1.91181275e-01, 1.96930976e-01, 2.05706514e-01, + 2.24752360e-01]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + 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scale=348.9450001032764, shift=array([ 4.96836085, 3489.45000103, 5.06389866])), candidate_index=28, candidate_x=array([4.45734496e+00, 2.79864235e+03, 1.09862604e+00]), index=28, x=array([4.45734496e+00, 2.79864235e+03, 1.09862604e+00]), fval=0.06529563513965841, rho=1.475519476069878, accepted=True, new_indices=array([], dtype=int32), old_indices_used=array([21, 23, 26, 27]), old_indices_discarded=array([], dtype=int32), step_length=1.6872964496840501, relative_step_length=1.2378681195926988, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([4.45734496e+00, 2.79864235e+03, 1.09862604e+00]), radius=2.726132813306847, bounds=Bounds(lower=array([1.1, 0. , 0. ]), upper=array([ 20., 10000., 70.]))), model_indices=array([15, 18, 21, 22, 23, 25, 26, 27, 28]), model=ScalarModel(intercept=0.07730703358690492, linear_terms=array([-0.21420423, -0.00177457, -0.09323422]), square_terms=array([[7.19945275e+00, 3.82631907e-02, 1.99911955e+00], + [3.82631907e-02, 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rho=-0.24314171126774836, accepted=False, new_indices=array([], dtype=int32), old_indices_used=array([15, 18, 21, 22, 23, 25, 26, 27, 28]), old_indices_discarded=array([], dtype=int32), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([4.45734496e+00, 2.79864235e+03, 1.09862604e+00]), radius=1.3630664066534235, bounds=Bounds(lower=array([1.1, 0. , 0. ]), upper=array([ 20., 10000., 70.]))), model_indices=array([21, 23, 26, 27, 28, 29]), model=ScalarModel(intercept=0.06904406104722437, linear_terms=array([ 0.00492248, 0.00149362, -0.05074773]), square_terms=array([[ 6.12405684e-01, -2.44364302e-03, 3.09451673e-01], + [-2.44364302e-03, 4.14350874e-05, -2.29602578e-03], + [ 3.09451673e-01, -2.29602578e-03, 2.13954389e-01]]), scale=array([1.09862604, 1.09862604, 1.09862604]), shift=array([4.45734496e+00, 2.79864235e+03, 1.09862604e+00])), vector_model=VectorModel(intercepts=array([ 1.57412309e-02, 3.56292054e-02, 1.46671126e-02, 2.00709899e-02, + 1.36314151e-02, 6.48338304e-06, -1.99307165e-02, -2.09559325e-01, + -3.40977225e-01, -3.07739315e-01, -6.19357811e-01, -5.84132142e-01, + 1.74722021e-01, 1.91181275e-01, 1.96930976e-01, 2.05706514e-01, + 2.24752360e-01]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]]), square_terms=array([[[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + 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State(trustregion=Region(center=array([4.45734496e+00, 2.79864235e+03, 1.09862604e+00]), radius=0.6815332033267117, bounds=Bounds(lower=array([1.1, 0. , 0. ]), upper=array([ 20., 10000., 70.]))), model_indices=array([23, 27, 28, 29, 30]), model=ScalarModel(intercept=0.08513789653811096, linear_terms=array([-0.05873789, -0.00640693, -0.05839653]), square_terms=array([[0.29594537, 0.02020028, 0.12960348], + [0.02020028, 0.00146583, 0.00964012], + [0.12960348, 0.00964012, 0.07540158]]), scale=0.6815332033267117, shift=array([4.45734496e+00, 2.79864235e+03, 1.09862604e+00])), vector_model=VectorModel(intercepts=array([ 1.57412309e-02, 3.56292054e-02, 1.46671126e-02, 2.00709899e-02, + 1.36314151e-02, 6.48338304e-06, -1.99307165e-02, -2.09559325e-01, + -3.40977225e-01, -3.07739315e-01, -6.19357811e-01, -5.84132142e-01, + 1.74722021e-01, 1.91181275e-01, 1.96930976e-01, 2.05706514e-01, + 2.24752360e-01]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 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x=array([4.05602518e+00, 2.79734636e+03, 2.24557407e+00]), fval=0.05415908459581581, rho=0.02787984735130772, accepted=True, new_indices=array([], dtype=int32), old_indices_used=array([21, 23, 26, 27, 28, 29, 30, 31]), old_indices_discarded=array([], dtype=int32), step_length=1.4693394633669328, relative_step_length=1.0779661623195813, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([4.05602518e+00, 2.79734636e+03, 2.24557407e+00]), radius=0.6815332033267117, bounds=Bounds(lower=array([1.1, 0. , 0. ]), upper=array([ 20., 10000., 70.]))), model_indices=array([27, 28, 30, 31, 32]), model=ScalarModel(intercept=0.06019280281239402, linear_terms=array([-0.05311338, -0.00664367, -0.01652794]), square_terms=array([[0.31168089, 0.01963004, 0.09342492], + [0.01963004, 0.00163636, 0.00734946], + [0.09342492, 0.00734946, 0.04083573]]), scale=0.6815332033267117, shift=array([4.05602518e+00, 2.79734636e+03, 2.24557407e+00])), vector_model=VectorModel(intercepts=array([ 1.57412309e-02, 3.56292054e-02, 1.46671126e-02, 2.00709899e-02, + 1.36314151e-02, 6.48338304e-06, -1.99307165e-02, -2.09559325e-01, + -3.40977225e-01, -3.07739315e-01, -6.19357811e-01, -5.84132142e-01, + 1.74722021e-01, 1.91181275e-01, 1.96930976e-01, 2.05706514e-01, + 2.24752360e-01]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]]), square_terms=array([[[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 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1.95671244e+00]), fval=0.05091436090216684, rho=1.1516416598700234, accepted=True, new_indices=array([], dtype=int32), old_indices_used=array([30, 31, 33, 35, 36, 37, 38]), old_indices_discarded=array([], dtype=int32), step_length=0.1759818526107779, relative_step_length=1.032858570950159, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([4.18918073e+00, 2.79843139e+03, 1.95671244e+00]), radius=0.3407666016633559, bounds=Bounds(lower=array([1.1, 0. , 0. ]), upper=array([ 20., 10000., 70.]))), model_indices=array([27, 28, 30, 31, 32, 33, 35, 36, 37, 38, 39]), model=ScalarModel(intercept=0.05221280899533157, linear_terms=array([-0.00115235, -0.00033548, -0.00127409]), square_terms=array([[8.81488941e-02, 2.02195870e-03, 2.52583882e-02], + [2.02195870e-03, 4.98103348e-05, 6.21228724e-04], + [2.52583882e-02, 6.21228724e-04, 9.98002687e-03]]), scale=0.3407666016633559, shift=array([4.18918073e+00, 2.79843139e+03, 1.95671244e+00])), vector_model=VectorModel(intercepts=array([ 1.57412309e-02, 3.56292054e-02, 1.46671126e-02, 2.00709899e-02, + 1.36314151e-02, 6.48338304e-06, -1.99307165e-02, -2.09559325e-01, + -3.40977225e-01, -3.07739315e-01, -6.19357811e-01, -5.84132142e-01, + 1.74722021e-01, 1.91181275e-01, 1.96930976e-01, 2.05706514e-01, + 2.24752360e-01]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]]), square_terms=array([[[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 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step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([4.18918073e+00, 2.79843139e+03, 1.95671244e+00]), radius=0.17038330083167794, bounds=Bounds(lower=array([1.1, 0. , 0. ]), upper=array([ 20., 10000., 70.]))), model_indices=array([31, 33, 35, 36, 37, 38, 39, 40]), model=ScalarModel(intercept=0.05090588732753695, linear_terms=array([ 2.00967052e-03, -4.51302094e-06, 7.70306669e-04]), square_terms=array([[ 6.02617840e-02, -3.14541700e-04, 1.76727179e-02], + [-3.14541700e-04, 1.67055199e-06, -9.60913876e-05], + [ 1.76727179e-02, -9.60913876e-05, 5.78378569e-03]]), scale=0.17038330083167794, shift=array([4.18918073e+00, 2.79843139e+03, 1.95671244e+00])), vector_model=VectorModel(intercepts=array([ 1.57412309e-02, 3.56292054e-02, 1.46671126e-02, 2.00709899e-02, + 1.36314151e-02, 6.48338304e-06, -1.99307165e-02, -2.09559325e-01, + -3.40977225e-01, -3.07739315e-01, -6.19357811e-01, -5.84132142e-01, + 1.74722021e-01, 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35, 36, 37, 38, 39, 40, 42, 43, 44, 45]), model=ScalarModel(intercept=0.06696502522412702, linear_terms=array([-0.0858346 , 0.00810014, -0.09927764]), square_terms=array([[ 0.88479646, -0.05848807, 0.42784336], + [-0.05848807, 0.0040204 , -0.03153559], + [ 0.42784336, -0.03153559, 0.28843495]]), scale=array([1.4077656, 1.4077656, 1.0558242]), shift=array([4.30473286e+00, 2.23637258e+03, 1.05582420e+00])), vector_model=VectorModel(intercepts=array([ 0.06291652, 0.11643581, 0.10823668, 0.12189314, 0.12343863, + 0.12357968, 0.12479589, 0.09434044, 0.01975806, 0.10844278, + -0.14820181, -0.07391777, -0.01698537, -0.01832682, -0.03672083, + -0.06411733, -0.08425918]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]]), square_terms=array([[[0., 0., 0.], + 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2.23496481e+03, 1.76166338e+00]), index=45, x=array([4.30473286e+00, 2.23637258e+03, 7.03882802e-01]), fval=0.11023536150139687, rho=-0.013088870767080768, accepted=False, new_indices=array([], dtype=int32), old_indices_used=array([ 0, 33, 35, 36, 37, 38, 39, 40, 42, 43, 44, 45]), old_indices_discarded=array([19, 20, 21, 22, 24, 25, 26, 27, 28, 29, 31, 32, 34, 41]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([4.30473286e+00, 2.23637258e+03, 7.03882802e-01]), radius=0.8733080837500703, bounds=Bounds(lower=array([1.1, 0. , 0. ]), upper=array([ 20., 10000., 70.]))), model_indices=array([ 0, 33, 35, 36, 37, 38, 39, 40, 42, 43, 44, 45]), model=ScalarModel(intercept=0.11608173487000709, linear_terms=array([-0.11422453, 0.009306 , -0.13028175]), square_terms=array([[ 0.22119912, -0.01462202, 0.14261445], + [-0.01462202, 0.0010051 , -0.01051186], + [ 0.14261445, -0.01051186, 0.12819331]]), scale=array([0.7038828, 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bounds=Bounds(lower=array([1.1, 0. , 0. ]), upper=array([ 20., 10000., 70.]))), model_indices=array([ 0, 33, 35, 37, 38, 39, 43, 44, 45, 46, 47, 48]), model=ScalarModel(intercept=0.04979649389791477, linear_terms=array([ 0.02126238, -0.00028674, 0.00920791]), square_terms=array([[4.06566366e-01, 4.46928765e-03, 1.91750120e-01], + [4.46928765e-03, 1.16197953e-04, 3.26335024e-03], + [1.91750120e-01, 3.26335024e-03, 1.25197817e-01]]), scale=0.8733080837500703, shift=array([4.09437801e+00, 2.23578419e+03, 2.04974325e+00])), vector_model=VectorModel(intercepts=array([ 0.06291652, 0.11643581, 0.10823668, 0.12189314, 0.12343863, + 0.12357968, 0.12479589, 0.09434044, 0.01975806, 0.10844278, + -0.14820181, -0.07391777, -0.01698537, -0.01832682, -0.03672083, + -0.06411733, -0.08425918]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + 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scale=223.566869440018, shift=array([ 4.97205913, 2235.6686944 , 0. ])), candidate_index=49, candidate_x=array([4.04323752e+00, 2.23665792e+03, 2.04109745e+00]), index=49, x=array([4.04323752e+00, 2.23665792e+03, 2.04109745e+00]), fval=0.054092031850175026, rho=3.3244856226041226, accepted=True, new_indices=array([], dtype=int32), old_indices_used=array([ 0, 33, 35, 37, 38, 39, 43, 44, 45, 46, 47, 48]), old_indices_discarded=array([32, 34, 36, 40, 41, 42]), step_length=0.8752719136134174, relative_step_length=1.0022487251634202, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([4.04323752e+00, 2.23665792e+03, 2.04109745e+00]), radius=1.7466161675001406, bounds=Bounds(lower=array([1.1, 0. , 0. ]), upper=array([ 20., 10000., 70.]))), model_indices=array([33, 37, 39, 40, 42, 43, 44, 45, 46, 47, 48, 49]), model=ScalarModel(intercept=0.05261244132650274, linear_terms=array([0.02150317, 0.0042552 , 0.0074365 ]), square_terms=array([[1.33292038, 0.07006399, 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rho=0.4983800116405342, accepted=True, new_indices=array([64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75]), old_indices_used=array([59, 62, 63]), old_indices_discarded=array([], dtype=int32), step_length=0.006920117064447186, relative_step_length=1.0142754896366417, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([4.11051116e+00, 2.23693167e+03, 1.78110356e+00]), radius=0.013645438808594848, bounds=Bounds(lower=array([1.1, 0. , 0. ]), upper=array([ 20., 10000., 70.]))), model_indices=array([59, 64, 65, 66, 67, 68, 70, 72, 73, 74, 75, 76]), model=ScalarModel(intercept=0.05274921512205406, linear_terms=array([-2.32187448e-06, -3.03189290e-06, 1.22926474e-05]), square_terms=array([[3.28191192e-04, 2.38863375e-07, 9.75393216e-05], + [2.38863375e-07, 5.14401342e-09, 7.74187507e-08], + [9.75393216e-05, 7.74187507e-08, 3.33310299e-05]]), scale=0.013645438808594848, shift=array([4.11051116e+00, 2.23693167e+03, 1.78110356e+00])), vector_model=VectorModel(intercepts=array([ 0.06291652, 0.11643581, 0.10823668, 0.12189314, 0.12343863, + 0.12357968, 0.12479589, 0.09434044, 0.01975806, 0.10844278, + -0.14820181, -0.07391777, -0.01698537, -0.01832682, -0.03672083, + -0.06411733, -0.08425918]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]]), square_terms=array([[[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 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1.77787754e+00]), index=79, x=array([4.11150945e+00, 2.23693233e+03, 1.77787754e+00]), fval=0.05274656188125212, rho=1.78595774700254, accepted=True, new_indices=array([], dtype=int32), old_indices_used=array([59, 65, 67, 68, 69, 70, 71, 72, 74, 75, 76, 78]), old_indices_discarded=array([64, 66, 73, 77]), step_length=0.0034420575444361447, relative_step_length=1.0089987116480554, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([4.11150945e+00, 2.23693233e+03, 1.77787754e+00]), radius=0.006822719404297424, bounds=Bounds(lower=array([1.1, 0. , 0. ]), upper=array([ 20., 10000., 70.]))), model_indices=array([59, 67, 68, 69, 70, 71, 72, 75, 76, 77, 78, 79]), model=ScalarModel(intercept=0.05275112021620292, linear_terms=array([-2.70754115e-06, -2.60641528e-06, 9.61700262e-07]), square_terms=array([[ 8.18217273e-05, -1.01517371e-07, 2.42634663e-05], + [-1.01517371e-07, 2.37295809e-09, -3.77829184e-08], + [ 2.42634663e-05, -3.77829184e-08, 8.25403428e-06]]), 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candidate_index=85, candidate_x=array([4.11096719e+00, 2.23693585e+03, 1.77759273e+00]), index=81, x=array([4.11181375e+00, 2.23693575e+03, 1.77757132e+00]), fval=0.05274431641899499, rho=-0.5283398254295653, accepted=False, new_indices=array([], dtype=int32), old_indices_used=array([79, 80, 81, 83, 84]), old_indices_discarded=array([], dtype=int32), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([4.11181375e+00, 2.23693575e+03, 1.77757132e+00]), radius=0.000426419962768589, bounds=Bounds(lower=array([1.1, 0. , 0. ]), upper=array([ 20., 10000., 70.]))), model_indices=array([81, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97]), model=ScalarModel(intercept=0.052744892341673844, linear_terms=array([-1.53029775e-06, 6.24435038e-07, 9.86295933e-07]), square_terms=array([[ 3.39968814e-07, -1.34328271e-09, 9.61921254e-08], + [-1.34328271e-09, 2.43509164e-11, -4.22033363e-10], + [ 9.61921254e-08, 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old_indices_discarded=array([], dtype=int32), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 9.3719594 , 3687.3820962 , 10.89861347]), radius=0.716582051597251, bounds=Bounds(lower=array([1.1, 0. , 0. ]), upper=array([ 20., 10000., 70.]))), model_indices=array([20, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35]), model=ScalarModel(intercept=0.6404926514152791, linear_terms=array([ 0.00985466, -0.00038215, -0.00076534]), square_terms=array([[ 4.62807937e-02, -8.53432130e-05, -1.30425185e-04], + [-8.53432130e-05, 4.67244373e-07, 8.14784874e-07], + [-1.30425185e-04, 8.14784874e-07, 1.55842322e-06]]), scale=0.716582051597251, shift=array([ 9.3719594 , 3687.3820962 , 10.89861347])), vector_model=VectorModel(intercepts=array([ 0.02576631, 0.06184162, 0.05506634, 0.07304972, 0.07539609, + 0.06945224, 0.05266735, -0.15458875, -0.30268525, -0.2894935 , + -0.62376469, -0.61159718, 0.03592713, 0.05727162, 0.065043 , + 0.05645612, 0.0379622 ]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]]), square_terms=array([[[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 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model_indices=array([20, 24, 25, 26, 27, 28, 29, 30, 31, 32, 34, 36]), model=ScalarModel(intercept=0.6404159621901686, linear_terms=array([-0.00235032, 0.0005279 , 0.00042805]), square_terms=array([[1.82912971e-01, 1.19176316e-04, 1.03107378e-04], + [1.19176316e-04, 1.03067442e-06, 6.43619009e-07], + [1.03107378e-04, 6.43619009e-07, 5.28724372e-07]]), scale=1.433164103194502, shift=array([ 9.22439025, 3687.7012643 , 11.54524388])), vector_model=VectorModel(intercepts=array([ 0.02576631, 0.06184162, 0.05506634, 0.07304972, 0.07539609, + 0.06945224, 0.05266735, -0.15458875, -0.30268525, -0.2894935 , + -0.62376469, -0.61159718, 0.03592713, 0.05727162, 0.065043 , + 0.05645612, 0.0379622 ]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]]), square_terms=array([[[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]]]), scale=366.8900104177925, shift=array([ 6.33384243, 3668.90010418, 6.57341347])), candidate_index=37, candidate_x=array([ 9.24396681, 3686.5883311 , 10.6423195 ]), index=36, x=array([ 9.22439025, 3687.7012643 , 11.54524388]), fval=0.6413804650211063, rho=-0.2440687245300182, accepted=False, new_indices=array([], dtype=int32), old_indices_used=array([20, 24, 25, 26, 27, 28, 29, 30, 31, 32, 34, 36]), old_indices_discarded=array([17, 21, 22, 23, 33, 35]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 9.22439025, 3687.7012643 , 11.54524388]), radius=0.716582051597251, bounds=Bounds(lower=array([1.1, 0. , 0. ]), upper=array([ 20., 10000., 70.]))), model_indices=array([20, 24, 25, 26, 27, 28, 30, 31, 32, 33, 34, 36]), model=ScalarModel(intercept=0.6407072788899953, linear_terms=array([-0.00092301, 0.00023655, 0.00071886]), square_terms=array([[4.57691593e-02, 2.68093455e-05, 9.75075250e-05], + [2.68093455e-05, 2.29384837e-07, 4.35992514e-07], + [9.75075250e-05, 4.35992514e-07, 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model_indices=array([69, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85]), model=ScalarModel(intercept=0.6411983788749992, linear_terms=array([ 1.68255446e-06, -5.57235139e-09, -7.04572418e-08]), square_terms=array([[2.81031505e-09, 1.30356265e-13, 1.96626650e-12], + [1.30356265e-13, 9.14800834e-17, 1.10316253e-15], + [1.96626650e-12, 1.10316253e-15, 1.44348922e-14]]), scale=0.0001749467899407351, shift=array([ 9.20680947, 3687.831003 , 11.41242438])), vector_model=VectorModel(intercepts=array([ 0.02576631, 0.06184162, 0.05506634, 0.07304972, 0.07539609, + 0.06945224, 0.05266735, -0.15458875, -0.30268525, -0.2894935 , + -0.62376469, -0.61159718, 0.03592713, 0.05727162, 0.065043 , + 0.05645612, 0.0379622 ]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + 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candidate_index=86, candidate_x=array([ 9.20663468, 3687.83100372, 11.41243184]), index=86, x=array([ 9.20663468, 3687.83100372, 11.41243184]), fval=0.6411977764871175, rho=0.1114790501708937, accepted=True, new_indices=array([74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85]), old_indices_used=array([69, 72, 73]), old_indices_discarded=array([], dtype=int32), step_length=0.00017494678994204872, relative_step_length=1.0000000000075087, n_evals_per_point=1, n_evals_acceptance=1)], 'message': 'Absolute criterion change smaller than tolerance.', 'tranquilo_history': History for least_squares function with 87 entries., 'history': {'params': [{'CRRA': 6.333842432535624, 'BeqFac': 3668.9001041779247, 'BeqShift': 6.573413466501883}, {'CRRA': 2.616981898670428, 'BeqFac': 3373.188231776675, 'BeqShift': 62.17867746421218}, {'CRRA': 18.050369850224293, 'BeqFac': 3373.188231776675, 'BeqShift': 61.4640779436021}, {'CRRA': 20.0, 'BeqFac': 3834.1986261245534, 'BeqShift': 65.26986123883711}, {'CRRA': 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model=ScalarModel(intercept=3.0353080773001073, linear_terms=array([20.20386846, 0.10823129, -1.77493216]), square_terms=array([[ 7.18576918e+01, 3.89097471e-01, -6.44170944e+00], + [ 3.89097471e-01, 2.11348833e-03, -3.50355915e-02], + [-6.44170944e+00, -3.50355915e-02, 5.83744149e-01]]), scale=array([6.40219448, 8.78900832, 4.39450416]), shift=array([ 7.50219448, 2799.74097801, 4.39450416])), vector_model=VectorModel(intercepts=array([ 1.57412309e-02, 3.56292054e-02, 1.46671126e-02, 2.00709899e-02, + 1.36314151e-02, 6.48338304e-06, -1.99307165e-02, -2.09559325e-01, + -3.40977225e-01, -3.07739315e-01, -6.19357811e-01, -5.84132142e-01, + 1.74722021e-01, 1.91181275e-01, 1.96930976e-01, 2.05706514e-01, + 2.24752360e-01]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 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old_indices_discarded=array([], dtype=int32), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 5.11538064, 2799.74097801, 0. ]), radius=2.726132813306847, bounds=Bounds(lower=array([1.1, 0. , 0. ]), upper=array([ 20., 10000., 70.]))), model_indices=array([15, 18, 21, 22, 23, 25, 26]), model=ScalarModel(intercept=0.040656194310767946, linear_terms=array([-0.04424986, -0.00023592, -0.08131239]), square_terms=array([[8.44848189e+00, 2.55963392e-02, 4.42498564e-02], + [2.55963392e-02, 7.77973037e-05, 2.35916270e-04], + [4.42498564e-02, 2.35916270e-04, 8.13123886e-02]]), scale=array([2.19725208, 2.19725208, 1.09862604]), shift=array([5.11538064e+00, 2.79974098e+03, 1.09862604e+00])), vector_model=VectorModel(intercepts=array([ 1.57412309e-02, 3.56292054e-02, 1.46671126e-02, 2.00709899e-02, + 1.36314151e-02, 6.48338304e-06, -1.99307165e-02, -2.09559325e-01, + -3.40977225e-01, -3.07739315e-01, -6.19357811e-01, 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scale=348.9450001032764, shift=array([ 4.96836085, 3489.45000103, 5.06389866])), candidate_index=28, candidate_x=array([4.45734496e+00, 2.79864235e+03, 1.09862604e+00]), index=28, x=array([4.45734496e+00, 2.79864235e+03, 1.09862604e+00]), fval=0.06529563513965841, rho=1.475519476069878, accepted=True, new_indices=array([], dtype=int32), old_indices_used=array([21, 23, 26, 27]), old_indices_discarded=array([], dtype=int32), step_length=1.6872964496840501, relative_step_length=1.2378681195926988, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([4.45734496e+00, 2.79864235e+03, 1.09862604e+00]), radius=2.726132813306847, bounds=Bounds(lower=array([1.1, 0. , 0. ]), upper=array([ 20., 10000., 70.]))), model_indices=array([15, 18, 21, 22, 23, 25, 26, 27, 28]), model=ScalarModel(intercept=0.07730703358690492, linear_terms=array([-0.21420423, -0.00177457, -0.09323422]), square_terms=array([[7.19945275e+00, 3.82631907e-02, 1.99911955e+00], + [3.82631907e-02, 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rho=-0.24314171126774836, accepted=False, new_indices=array([], dtype=int32), old_indices_used=array([15, 18, 21, 22, 23, 25, 26, 27, 28]), old_indices_discarded=array([], dtype=int32), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([4.45734496e+00, 2.79864235e+03, 1.09862604e+00]), radius=1.3630664066534235, bounds=Bounds(lower=array([1.1, 0. , 0. ]), upper=array([ 20., 10000., 70.]))), model_indices=array([21, 23, 26, 27, 28, 29]), model=ScalarModel(intercept=0.06904406104722437, linear_terms=array([ 0.00492248, 0.00149362, -0.05074773]), square_terms=array([[ 6.12405684e-01, -2.44364302e-03, 3.09451673e-01], + [-2.44364302e-03, 4.14350874e-05, -2.29602578e-03], + [ 3.09451673e-01, -2.29602578e-03, 2.13954389e-01]]), scale=array([1.09862604, 1.09862604, 1.09862604]), shift=array([4.45734496e+00, 2.79864235e+03, 1.09862604e+00])), vector_model=VectorModel(intercepts=array([ 1.57412309e-02, 3.56292054e-02, 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State(trustregion=Region(center=array([4.45734496e+00, 2.79864235e+03, 1.09862604e+00]), radius=0.6815332033267117, bounds=Bounds(lower=array([1.1, 0. , 0. ]), upper=array([ 20., 10000., 70.]))), model_indices=array([23, 27, 28, 29, 30]), model=ScalarModel(intercept=0.08513789653811096, linear_terms=array([-0.05873789, -0.00640693, -0.05839653]), square_terms=array([[0.29594537, 0.02020028, 0.12960348], + [0.02020028, 0.00146583, 0.00964012], + [0.12960348, 0.00964012, 0.07540158]]), scale=0.6815332033267117, shift=array([4.45734496e+00, 2.79864235e+03, 1.09862604e+00])), vector_model=VectorModel(intercepts=array([ 1.57412309e-02, 3.56292054e-02, 1.46671126e-02, 2.00709899e-02, + 1.36314151e-02, 6.48338304e-06, -1.99307165e-02, -2.09559325e-01, + -3.40977225e-01, -3.07739315e-01, -6.19357811e-01, -5.84132142e-01, + 1.74722021e-01, 1.91181275e-01, 1.96930976e-01, 2.05706514e-01, + 2.24752360e-01]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 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x=array([4.05602518e+00, 2.79734636e+03, 2.24557407e+00]), fval=0.05415908459581581, rho=0.02787984735130772, accepted=True, new_indices=array([], dtype=int32), old_indices_used=array([21, 23, 26, 27, 28, 29, 30, 31]), old_indices_discarded=array([], dtype=int32), step_length=1.4693394633669328, relative_step_length=1.0779661623195813, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([4.05602518e+00, 2.79734636e+03, 2.24557407e+00]), radius=0.6815332033267117, bounds=Bounds(lower=array([1.1, 0. , 0. ]), upper=array([ 20., 10000., 70.]))), model_indices=array([27, 28, 30, 31, 32]), model=ScalarModel(intercept=0.06019280281239402, linear_terms=array([-0.05311338, -0.00664367, -0.01652794]), square_terms=array([[0.31168089, 0.01963004, 0.09342492], + [0.01963004, 0.00163636, 0.00734946], + [0.09342492, 0.00734946, 0.04083573]]), scale=0.6815332033267117, shift=array([4.05602518e+00, 2.79734636e+03, 2.24557407e+00])), vector_model=VectorModel(intercepts=array([ 1.57412309e-02, 3.56292054e-02, 1.46671126e-02, 2.00709899e-02, + 1.36314151e-02, 6.48338304e-06, -1.99307165e-02, -2.09559325e-01, + -3.40977225e-01, -3.07739315e-01, -6.19357811e-01, -5.84132142e-01, + 1.74722021e-01, 1.91181275e-01, 1.96930976e-01, 2.05706514e-01, + 2.24752360e-01]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]]), square_terms=array([[[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 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model_indices=array([23, 27, 28, 29, 30, 31, 32, 33, 34]), model=ScalarModel(intercept=0.05177155574931393, linear_terms=array([ 2.24054327e-02, -6.65931684e-05, 7.36047043e-03]), square_terms=array([[0.29167665, 0.01447643, 0.13152612], + [0.01447643, 0.0008045 , 0.00750585], + [0.13152612, 0.00750585, 0.07813118]]), scale=0.6815332033267117, shift=array([4.13804573e+00, 2.79803113e+03, 2.21290949e+00])), vector_model=VectorModel(intercepts=array([ 1.57412309e-02, 3.56292054e-02, 1.46671126e-02, 2.00709899e-02, + 1.36314151e-02, 6.48338304e-06, -1.99307165e-02, -2.09559325e-01, + -3.40977225e-01, -3.07739315e-01, -6.19357811e-01, -5.84132142e-01, + 1.74722021e-01, 1.91181275e-01, 1.96930976e-01, 2.05706514e-01, + 2.24752360e-01]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], 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3489.45000103, 5.06389866])), candidate_index=35, candidate_x=array([4.02600282e+00, 2.79871386e+03, 2.27098711e+00]), index=33, x=array([4.13804573e+00, 2.79803113e+03, 2.21290949e+00]), fval=0.05275688891668154, rho=-2.2415296614174687, accepted=False, new_indices=array([], dtype=int32), old_indices_used=array([23, 27, 28, 29, 30, 31, 32, 33, 34]), old_indices_discarded=array([], dtype=int32), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([4.13804573e+00, 2.79803113e+03, 2.21290949e+00]), radius=0.3407666016633559, bounds=Bounds(lower=array([1.1, 0. , 0. ]), upper=array([ 20., 10000., 70.]))), model_indices=array([28, 30, 31, 32, 33, 34, 35]), model=ScalarModel(intercept=0.05243167254991798, linear_terms=array([ 2.14835428e-02, -8.53058917e-05, 7.83429373e-03]), square_terms=array([[2.69010071e-01, 2.03422326e-04, 8.75369596e-02], + [2.03422326e-04, 6.23463910e-07, 8.57167056e-05], + [8.75369596e-02, 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old_indices_used=array([28, 30, 31, 32, 33, 34, 35]), old_indices_discarded=array([], dtype=int32), step_length=0.35386200358029707, relative_step_length=1.0384292411668858, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([4.14232870e+00, 2.79837124e+03, 2.11532007e+00]), radius=0.6815332033267117, bounds=Bounds(lower=array([1.1, 0. , 0. ]), upper=array([ 20., 10000., 70.]))), model_indices=array([23, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36]), model=ScalarModel(intercept=0.0515876639767697, linear_terms=array([ 0.00588415, -0.00077363, -0.00241592]), square_terms=array([[0.31118702, 0.01242837, 0.13629499], + [0.01242837, 0.00054706, 0.00615461], + [0.13629499, 0.00615461, 0.07774976]]), scale=0.6815332033267117, shift=array([4.14232870e+00, 2.79837124e+03, 2.11532007e+00])), vector_model=VectorModel(intercepts=array([ 1.57412309e-02, 3.56292054e-02, 1.46671126e-02, 2.00709899e-02, + 1.36314151e-02, 6.48338304e-06, -1.99307165e-02, -2.09559325e-01, + 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radius=0.3407666016633559, bounds=Bounds(lower=array([1.1, 0. , 0. ]), upper=array([ 20., 10000., 70.]))), model_indices=array([27, 28, 30, 31, 32, 33, 35, 36, 37]), model=ScalarModel(intercept=0.052532543329590564, linear_terms=array([-0.00426995, -0.00027655, -0.00095162]), square_terms=array([[9.08193291e-02, 1.45774993e-03, 2.59401890e-02], + [1.45774993e-03, 2.50681460e-05, 4.39732923e-04], + [2.59401890e-02, 4.39732923e-04, 1.01466646e-02]]), scale=0.3407666016633559, shift=array([4.14232870e+00, 2.79837124e+03, 2.11532007e+00])), vector_model=VectorModel(intercepts=array([ 1.57412309e-02, 3.56292054e-02, 1.46671126e-02, 2.00709899e-02, + 1.36314151e-02, 6.48338304e-06, -1.99307165e-02, -2.09559325e-01, + -3.40977225e-01, -3.07739315e-01, -6.19357811e-01, -5.84132142e-01, + 1.74722021e-01, 1.91181275e-01, 1.96930976e-01, 2.05706514e-01, + 2.24752360e-01]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 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1.95671244e+00]), fval=0.05091436090216684, rho=1.1516416598700234, accepted=True, new_indices=array([], dtype=int32), old_indices_used=array([30, 31, 33, 35, 36, 37, 38]), old_indices_discarded=array([], dtype=int32), step_length=0.1759818526107779, relative_step_length=1.032858570950159, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([4.18918073e+00, 2.79843139e+03, 1.95671244e+00]), radius=0.3407666016633559, bounds=Bounds(lower=array([1.1, 0. , 0. ]), upper=array([ 20., 10000., 70.]))), model_indices=array([27, 28, 30, 31, 32, 33, 35, 36, 37, 38, 39]), model=ScalarModel(intercept=0.05221280899533157, linear_terms=array([-0.00115235, -0.00033548, -0.00127409]), square_terms=array([[8.81488941e-02, 2.02195870e-03, 2.52583882e-02], + [2.02195870e-03, 4.98103348e-05, 6.21228724e-04], + [2.52583882e-02, 6.21228724e-04, 9.98002687e-03]]), scale=0.3407666016633559, shift=array([4.18918073e+00, 2.79843139e+03, 1.95671244e+00])), vector_model=VectorModel(intercepts=array([ 1.57412309e-02, 3.56292054e-02, 1.46671126e-02, 2.00709899e-02, + 1.36314151e-02, 6.48338304e-06, -1.99307165e-02, -2.09559325e-01, + -3.40977225e-01, -3.07739315e-01, -6.19357811e-01, -5.84132142e-01, + 1.74722021e-01, 1.91181275e-01, 1.96930976e-01, 2.05706514e-01, + 2.24752360e-01]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]]), square_terms=array([[[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 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step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([4.18918073e+00, 2.79843139e+03, 1.95671244e+00]), radius=0.17038330083167794, bounds=Bounds(lower=array([1.1, 0. , 0. ]), upper=array([ 20., 10000., 70.]))), model_indices=array([31, 33, 35, 36, 37, 38, 39, 40]), model=ScalarModel(intercept=0.05090588732753695, linear_terms=array([ 2.00967052e-03, -4.51302094e-06, 7.70306669e-04]), square_terms=array([[ 6.02617840e-02, -3.14541700e-04, 1.76727179e-02], + [-3.14541700e-04, 1.67055199e-06, -9.60913876e-05], + [ 1.76727179e-02, -9.60913876e-05, 5.78378569e-03]]), scale=0.17038330083167794, shift=array([4.18918073e+00, 2.79843139e+03, 1.95671244e+00])), vector_model=VectorModel(intercepts=array([ 1.57412309e-02, 3.56292054e-02, 1.46671126e-02, 2.00709899e-02, + 1.36314151e-02, 6.48338304e-06, -1.99307165e-02, -2.09559325e-01, + -3.40977225e-01, -3.07739315e-01, -6.19357811e-01, -5.84132142e-01, + 1.74722021e-01, 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38.50141609972343, 39.70189919974655, 40.88999589998275, 42.06016460014507, 43.238295500166714, 44.42306770011783, 45.59471370000392, 46.93225569976494, 48.113191300071776], 'batches': [0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38]}, 'multistart_info': {...}}], 'exploration_sample': array([[4.97205913e+00, 2.23566869e+03, 0.00000000e+00], + [9.36875000e+00, 5.62500000e+03, 1.31250000e+01], + [8.77812500e+00, 9.06250000e+03, 1.96875000e+01], + [9.95937500e+00, 9.37500000e+02, 5.90625000e+01], + [8.18750000e+00, 3.75000000e+03, 4.37500000e+01], + [1.05500000e+01, 5.00000000e+03, 3.50000000e+01], + [7.59687500e+00, 7.18750000e+03, 5.03125000e+01], + [7.00625000e+00, 1.87500000e+03, 2.18750000e+01], + [1.17312500e+01, 4.37500000e+03, 4.37500000e+00], + [1.23218750e+01, 9.68750000e+03, 6.78125000e+01], + [6.41562500e+00, 2.81250000e+03, 1.09375000e+01], + [1.29125000e+01, 1.25000000e+03, 6.12500000e+01], + [5.82500000e+00, 7.50000000e+03, 5.25000000e+01], + [5.23437500e+00, 8.43750000e+03, 6.56250000e+00], + [1.35031250e+01, 6.56250000e+03, 2.18750000e+00], + [1.40937500e+01, 8.12500000e+03, 3.06250000e+01], + [1.46843750e+01, 3.43750000e+03, 4.15625000e+01], + [4.64375000e+00, 3.12500000e+03, 6.56250000e+01], + [1.52750000e+01, 2.50000000e+03, 1.75000000e+01], + [4.05312500e+00, 1.56250000e+03, 3.71875000e+01], + [1.58656250e+01, 7.81250000e+03, 4.59375000e+01], + [3.46250000e+00, 6.25000000e+03, 2.62500000e+01], + [1.64562500e+01, 6.87500000e+03, 5.68750000e+01], + [2.87187500e+00, 4.68750000e+03, 3.28125000e+01], + [1.70468750e+01, 2.18750000e+03, 1.53125000e+01], + [1.76375000e+01, 8.75000000e+03, 8.75000000e+00], + [1.82281250e+01, 4.06250000e+03, 5.46875000e+01], + [1.88187500e+01, 6.25000000e+02, 4.81250000e+01], + [1.94093750e+01, 5.93750000e+03, 2.40625000e+01], + [2.28125000e+00, 9.37500000e+03, 3.93750000e+01]]), 'exploration_results': array([ 0.15183333, 0.64211538, 0.64842412, 0.66164015, 0.68191739, + 0.7044766 , 0.74714867, 0.84822968, 0.86260573, 0.97951322, + 0.98915247, 1.12431839, 1.18220644, 1.20662179, 1.30406801, + 1.52011014, 1.78024917, 1.78135807, 2.0971452 , 2.24437522, + 2.48116605, 2.85787595, 2.94379242, 3.4148927 , 3.4976294 , + 4.16035282, 4.94978648, 5.89491246, 7.00125067, 34.37799292])}}" diff --git a/code/estimark/content/tables/min/WarmGlowPortfolioShift_estimate_results.csv b/code/estimark/content/tables/min/WarmGlowPortfolioShift_estimate_results.csv new file mode 100644 index 0000000..bdf8df1 --- /dev/null +++ b/code/estimark/content/tables/min/WarmGlowPortfolioShift_estimate_results.csv @@ -0,0 +1,7577 @@ +CRRA,9.206764951619395 +BeqFac,51.48903871676966 +BeqShift,19.177911777729552 +time_to_estimate,169.86824083328247 +params,"{'CRRA': 9.206764951619395, 'BeqFac': 51.48903871676966, 'BeqShift': 19.177911777729552}" +criterion,0.6411981720246629 +start_criterion,3.9192779804696425 +start_params,"{'CRRA': 2.0, 'BeqFac': 1.0, 'BeqShift': 1.0}" +algorithm,multistart_tranquilo_ls +direction,minimize +n_free,3 +message,Absolute criterion change smaller than tolerance. +success, +n_criterion_evaluations, +n_derivative_evaluations, +n_iterations, +history,"{'params': [{'CRRA': 9.02557038439359, 'BeqFac': 50.30567549536045, 'BeqShift': 16.905833666158657}, {'CRRA': 10.430729201623546, 'BeqFac': 52.82847452758671, 'BeqShift': 12.786656125459029}, {'CRRA': 5.792976948374848, 'BeqFac': 52.659631320106804, 'BeqShift': 13.853647314869416}, {'CRRA': 4.750415983244248, 'BeqFac': 52.50140949121589, 'BeqShift': 18.391908003539935}, {'CRRA': 8.544902044207497, 'BeqFac': 45.298212588181066, 'BeqShift': 16.876117502031093}, {'CRRA': 8.272787894438386, 'BeqFac': 48.43106736325208, 'BeqShift': 21.512977330544985}, {'CRRA': 4.597416132398153, 'BeqFac': 47.95443005019735, 'BeqShift': 17.317785905598647}, {'CRRA': 11.274409804550503, 'BeqFac': 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19.177004010104596}, {'CRRA': 9.206730003031863, 'BeqFac': 51.4892505287316, 'BeqShift': 19.177336330476077}, {'CRRA': 9.204354871907853, 'BeqFac': 51.48879269836255, 'BeqShift': 19.1769088851999}, {'CRRA': 9.206415435651937, 'BeqFac': 51.48810049426926, 'BeqShift': 19.176960807842843}, {'CRRA': 9.206764951619395, 'BeqFac': 51.48903871676966, 'BeqShift': 19.177911777729552}], 'criterion': [0.642827121621846, 0.6936548445058819, 1.1943530558235826, 1.7114941855666048, 0.6577901652539007, 0.6751696549414895, 1.8126201136255125, 0.7902864339148857, 1.1611074535973434, 0.6688937629078676, 0.7215885043021786, 1.0515760206083788, 1.1253852503329274, 0.6416850814352149, 0.6452946656927958, 0.6417208504967987, 0.6412114595894461, 0.6416157450984669, 0.6414644516775065, 0.6426434586520711, 0.641777706562999, 0.6436393811721514, 0.6414037841119337, 0.64298288805668, 0.6427203601267164, 0.6439331494764337, 0.64473229572033, 0.6441675229212956, 0.6419840427390942, 0.6416756395896682, 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4.844878800213337, 6.0633915001526475, 7.2610666998662055, 8.584980400279164, 9.761942900251597, 10.943062500096858, 12.49804690014571, 12.680896100122482, 12.863225900102407, 13.049990000203252, 13.235215300228447, 13.421385299880058, 13.612889300100505, 13.813482000026852, 14.012756899930537, 14.206071800086647, 14.40031210007146, 14.598113900050521, 15.857798700220883, 17.073550200089812, 18.39786330005154, 19.95549810025841, 20.136687899939716, 20.316136700101197, 20.503039999864995, 20.68812690023333, 20.880544799845666, 21.061436000280082, 21.258774400223047, 21.45859370008111, 21.63768619997427, 21.82981210015714, 22.024868600070477, 23.232584199868143, 24.429392700083554, 25.615990200079978, 27.17550570005551, 27.352922200225294, 27.533706800080836, 27.874167799949646, 28.064581600017846, 28.25611580023542, 28.4465796998702, 28.64204559987411, 28.83596420008689, 29.02757350029424, 29.219605300109833, 29.419515199959278, 30.668996000196785, 31.875013300217688, 33.06283670011908, 34.25480200024322, 35.44796109991148, 36.63821780029684], 'batches': [0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 3, 4, 5, 6, 7, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 9, 10, 11, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 13, 14, 15, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 17, 18, 19, 20, 21, 22]}" +convergence_report,"{'one_step': {'relative_criterion_change': 2.8119796241753443e-07, 'relative_params_change': 0.3073071893497542, 'absolute_criterion_change': 1.8030361947918294e-07, 'absolute_params_change': 11.624425850056147}, 'five_steps': {'relative_criterion_change': 2.8119796241753443e-07, 'relative_params_change': 0.3073071893497542, 'absolute_criterion_change': 1.8030361947918294e-07, 'absolute_params_change': 11.624425850056147}}" +multistart_info,"{'start_parameters': [{'CRRA': 9.36875, 'BeqFac': 39.375, 'BeqShift': 13.125}, {'CRRA': 9.02557038439359, 'BeqFac': 50.30567549536045, 'BeqShift': 16.905833666158657}, {'CRRA': 9.344871468725385, 'BeqFac': 43.24486525515954, 'BeqShift': 26.496870084805927}], 'local_optima': [Minimize with 3 free parameters terminated. + +The tranquilo_ls algorithm reported: Absolute criterion change smaller than tolerance. + +Independent of the convergence criteria used by tranquilo_ls, the strength of convergence can be assessed by the following criteria: + + one_step five_steps +relative_criterion_change 1.358e-07* 2.622e-05 +relative_params_change 6.705e-06* 0.003894 +absolute_criterion_change 8.706e-08* 1.681e-05 +absolute_params_change 0.0001056 0.08828 + +(***: change <= 1e-10, **: change <= 1e-8, *: change <= 1e-5. Change refers to a change between accepted steps. The first column only considers the last step. The second column considers the last five steps.), Minimize with 3 free parameters terminated. + +The tranquilo_ls algorithm reported: Absolute criterion change smaller than tolerance. + +Independent of the convergence criteria used by tranquilo_ls, the strength of convergence can be assessed by the following criteria: + + one_step five_steps +relative_criterion_change 1.904e-07* 0.0007594 +relative_params_change 3.052e-05 0.1282 +absolute_criterion_change 1.221e-07* 0.0004869 +absolute_params_change 0.0006142 2.522 + +(***: change <= 1e-10, **: change <= 1e-8, *: change <= 1e-5. Change refers to a change between accepted steps. The first column only considers the last step. The second column considers the last five steps.), Minimize with 3 free parameters terminated. + +The tranquilo_ls algorithm reported: Absolute criterion change smaller than tolerance. + +Independent of the convergence criteria used by tranquilo_ls, the strength of convergence can be assessed by the following criteria: + + one_step five_steps +relative_criterion_change 2.728e-05 0.000476 +relative_params_change 0.0002827 0.0766 +absolute_criterion_change 1.75e-05 0.0003053 +absolute_params_change 0.006458 2.233 + +(***: change <= 1e-10, **: change <= 1e-8, *: change <= 1e-5. Change refers to a change between accepted steps. The first column only considers the last step. The second column considers the last five steps.)], 'exploration_sample': [{'CRRA': 9.368749999999999, 'BeqFac': 39.375, 'BeqShift': 13.125}, {'CRRA': 8.778125, 'BeqFac': 63.4375, 'BeqShift': 19.6875}, {'CRRA': 9.959375, 'BeqFac': 6.5625, 'BeqShift': 59.0625}, {'CRRA': 8.1875, 'BeqFac': 26.25, 'BeqShift': 43.75}, {'CRRA': 10.549999999999999, 'BeqFac': 35.0, 'BeqShift': 35.0}, {'CRRA': 7.596874999999999, 'BeqFac': 50.3125, 'BeqShift': 50.3125}, {'CRRA': 7.00625, 'BeqFac': 13.125, 'BeqShift': 21.875}, {'CRRA': 11.73125, 'BeqFac': 30.625, 'BeqShift': 4.375}, {'CRRA': 12.321874999999999, 'BeqFac': 67.8125, 'BeqShift': 67.8125}, {'CRRA': 6.415625, 'BeqFac': 19.6875, 'BeqShift': 10.9375}, {'CRRA': 12.9125, 'BeqFac': 8.75, 'BeqShift': 61.25}, {'CRRA': 5.824999999999999, 'BeqFac': 52.5, 'BeqShift': 52.5}, {'CRRA': 13.503124999999999, 'BeqFac': 45.9375, 'BeqShift': 2.1875}, {'CRRA': 5.234375, 'BeqFac': 59.0625, 'BeqShift': 6.5625}, {'CRRA': 14.093749999999998, 'BeqFac': 56.875, 'BeqShift': 30.625}, {'CRRA': 14.684375, 'BeqFac': 24.0625, 'BeqShift': 41.5625}, {'CRRA': 4.64375, 'BeqFac': 21.875, 'BeqShift': 65.625}, {'CRRA': 15.274999999999999, 'BeqFac': 17.5, 'BeqShift': 17.5}, {'CRRA': 4.053125, 'BeqFac': 10.9375, 'BeqShift': 37.1875}, {'CRRA': 15.865624999999998, 'BeqFac': 54.6875, 'BeqShift': 45.9375}, {'CRRA': 3.4625, 'BeqFac': 43.75, 'BeqShift': 26.25}, {'CRRA': 16.45625, 'BeqFac': 48.125, 'BeqShift': 56.875}, {'CRRA': 17.046875, 'BeqFac': 15.3125, 'BeqShift': 15.3125}, {'CRRA': 2.871875, 'BeqFac': 32.8125, 'BeqShift': 32.8125}, {'CRRA': 2.0, 'BeqFac': 1.0, 'BeqShift': 1.0}, {'CRRA': 2.28125, 'BeqFac': 65.625, 'BeqShift': 39.375}, {'CRRA': 17.6375, 'BeqFac': 61.25, 'BeqShift': 8.75}, {'CRRA': 18.228125, 'BeqFac': 28.4375, 'BeqShift': 54.6875}, {'CRRA': 18.81875, 'BeqFac': 4.375, 'BeqShift': 48.125}, {'CRRA': 19.409375, 'BeqFac': 41.5625, 'BeqShift': 24.0625}], 'exploration_results': array([0.64211564, 0.64842422, 0.66164015, 0.68191739, 0.7044766 , + 0.74714868, 0.84823378, 0.86260589, 0.97951322, 0.98995977, + 1.12431839, 1.18221306, 1.30406647, 1.43719388, 1.52011014, + 1.78024917, 1.78140887, 2.0971452 , 2.2458042 , 2.48116605, + 2.89746811, 2.94379242, 3.4976294 , 3.77142778, 3.92475841, + 4.11872048, 4.16035282, 4.94978648, 5.89491246, 7.00125067])}" +algorithm_output,"{'states': [State(trustregion=Region(center=array([ 9.02557038, 50.3056755 , 16.90583367]), radius=5.030567549536045, bounds=Bounds(lower=array([1.1, 0. , 0. ]), upper=array([20., 70., 70.]))), model_indices=[0], model=ScalarModel(intercept=0.642827121621846, linear_terms=array([0., 0., 0.]), square_terms=array([[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]]), scale=5.030567549536045, shift=array([ 9.02557038, 50.3056755 , 16.90583367])), vector_model=VectorModel(intercepts=array([ 0.04710459, 0.11986993, 0.14282693, 0.18631824, 0.20833381, + 0.22221482, 0.22216466, 0.05252852, -0.09507962, -0.08224758, + -0.42404204, -0.4316247 , -0.11708532, -0.09095589, -0.08150493, + 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relative_step_length=0.9999999999983636, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 9.20673 , 51.48925053, 19.17733633]), radius=0.002456331811296897, bounds=Bounds(lower=array([1.1, 0. , 0. ]), upper=array([20., 70., 70.]))), model_indices=array([16, 49, 50, 51, 52, 53, 57, 59, 60, 61, 62, 63]), model=ScalarModel(intercept=0.6412082340781056, linear_terms=array([1.31850579e-05, 2.29695162e-06, 2.13180893e-06]), square_terms=array([[ 5.40420994e-07, -8.14514929e-11, -9.77509288e-10], + [-8.14514929e-11, 3.15361394e-11, 1.87438472e-11], + [-9.77509288e-10, 1.87438472e-11, 1.66932070e-11]]), scale=0.002456331811296897, shift=array([ 9.20673 , 51.48925053, 19.17733633])), vector_model=VectorModel(intercepts=array([ 0.04710459, 0.11986993, 0.14282693, 0.18631824, 0.20833381, + 0.22221482, 0.22216466, 0.05252852, -0.09507962, -0.08224758, + -0.42404204, -0.4316247 , -0.11708532, -0.09095589, -0.08150493, + -0.08549165, -0.09152337]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]]), square_terms=array([[[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 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model=ScalarModel(intercept=0.6412157536444247, linear_terms=array([9.00633808e-07, 3.16587415e-06, 1.03374985e-06]), square_terms=array([[ 1.36904318e-07, -3.84922396e-10, -1.62548009e-10], + [-3.84922396e-10, 1.84778132e-11, 7.00514318e-12], + [-1.62548009e-10, 7.00514318e-12, 3.33326143e-12]]), scale=0.0012281659056484484, shift=array([ 9.20673 , 51.48925053, 19.17733633])), vector_model=VectorModel(intercepts=array([ 0.04710459, 0.11986993, 0.14282693, 0.18631824, 0.20833381, + 0.22221482, 0.22216466, 0.05252852, -0.09507962, -0.08224758, + -0.42404204, -0.4316247 , -0.11708532, -0.09095589, -0.08150493, + -0.08549165, -0.09152337]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]]), square_terms=array([[[0., 0., 0.], + [0., 0., 0.], + [0., 0., 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index=63, x=array([ 9.20673 , 51.48925053, 19.17733633]), fval=0.6411982941369027, rho=-0.4736163965120041, accepted=False, new_indices=array([], dtype=int32), old_indices_used=array([16, 49, 50, 51, 52, 53, 59, 60, 61, 62, 63, 64]), old_indices_discarded=array([54, 55, 56, 57, 58]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 9.20673 , 51.48925053, 19.17733633]), radius=0.0006140829528242242, bounds=Bounds(lower=array([1.1, 0. , 0. ]), upper=array([20., 70., 70.]))), model_indices=array([16, 62, 63, 64, 65]), model=ScalarModel(intercept=0.6412018772218984, linear_terms=array([-3.72388782e-06, 2.25369895e-05, -6.12278699e-05]), square_terms=array([[ 3.55640239e-08, -1.41336598e-09, 3.35637644e-09], + [-1.41336598e-09, 7.05971511e-10, -1.79557755e-09], + [ 3.35637644e-09, -1.79557755e-09, 4.68337624e-09]]), scale=0.0006140829528242242, shift=array([ 9.20673 , 51.48925053, 19.17733633])), vector_model=VectorModel(intercepts=array([ 0.04710459, 0.11986993, 0.14282693, 0.18631824, 0.20833381, + 0.22221482, 0.22216466, 0.05252852, -0.09507962, -0.08224758, + -0.42404204, -0.4316247 , -0.11708532, -0.09095589, -0.08150493, + -0.08549165, -0.09152337]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]]), square_terms=array([[[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 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'tranquilo_history': History for least_squares function with 67 entries., 'multistart_info': {'start_parameters': [array([ 9.36875, 39.375 , 13.125 ]), array([ 9.02557038, 50.3056755 , 16.90583367]), array([ 9.34487147, 43.24486526, 26.49687008])], 'local_optima': [{'solution_x': array([ 9.20671298, 40.69251276, 14.86951258]), 'solution_criterion': 0.6411983523282824, 'states': [State(trustregion=Region(center=array([ 9.36875, 39.375 , 13.125 ]), radius=3.9375, bounds=Bounds(lower=array([1.1, 0. , 0. ]), upper=array([20., 70., 70.]))), model_indices=[0], model=ScalarModel(intercept=0.6421156352360291, linear_terms=array([0., 0., 0.]), square_terms=array([[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]]), scale=3.9375, shift=array([ 9.36875, 39.375 , 13.125 ])), vector_model=VectorModel(intercepts=array([ 0.04974919, 0.12690831, 0.15323823, 0.19937099, 0.22433814, + 0.23994656, 0.24229912, 0.07800181, -0.06876495, -0.05566806, + -0.39787992, -0.40698777, -0.12931719, -0.10261415, 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x=array([ 9.20683311, 40.69251307, 14.86951513]), fval=0.6411988675251178, rho=-0.12577706131837602, accepted=False, new_indices=array([], dtype=int32), old_indices_used=array([39, 59, 60, 63, 64, 65, 66, 68, 69, 70, 71, 72]), old_indices_discarded=array([61, 62, 67]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 9.20683311, 40.69251307, 14.86951513]), radius=0.0001201629638671875, bounds=Bounds(lower=array([1.1, 0. , 0. ]), upper=array([20., 70., 70.]))), model_indices=array([39, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85]), model=ScalarModel(intercept=0.6411989739004574, linear_terms=array([1.25756181e-06, 2.57916717e-09, 2.59883266e-08]), square_terms=array([[ 1.32183800e-09, -4.80376959e-14, -4.83059862e-13], + [-4.80376959e-14, 1.90720908e-17, 1.91683790e-16], + [-4.83059862e-13, 1.91683790e-16, 1.92652730e-15]]), scale=0.0001201629638671875, shift=array([ 9.20683311, 40.69251307, 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18.418678199872375, 18.612154200207442, 18.802370000164956, 19.001095300074667, 19.19951230008155, 19.384256300050765, 19.578397700097412, 20.827824499923736, 22.191805799957365, 23.37506840005517, 24.930955899879336, 25.10882500000298, 25.28667559986934, 25.46998760011047, 25.65477620018646, 25.8526360001415, 26.044608199968934, 26.240560499951243, 26.441691800020635, 26.632888900116086, 26.829975000116974, 27.029682899825275, 28.241499499883503, 29.427263699937612, 30.612053900025785, 31.790544799994677, 33.12664439994842, 34.315229000058025, 35.509189600124955, 36.6936153001152, 38.252203499898314, 38.43395029986277, 38.61882669990882, 38.80545399989933, 38.99553050007671, 39.18448129994795, 39.37656489992514, 39.579279699828476, 39.78303499985486, 39.96946519985795, 40.164970099925995, 40.370167799759656, 41.57934910012409, 42.91811199998483], 'batches': [0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 3, 4, 5, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 7, 8, 9, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 11, 12, 13, 14, 14, 14, 14, 14, 14, 14, 14, 14, 14, 14, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 23, 23, 23, 23, 23, 23, 23, 23, 23, 23, 23, 24, 25]}}], 'exploration_sample': array([[ 9.36875 , 39.375 , 13.125 ], + [ 8.778125, 63.4375 , 19.6875 ], + [ 9.959375, 6.5625 , 59.0625 ], + [ 8.1875 , 26.25 , 43.75 ], + [10.55 , 35. , 35. ], + [ 7.596875, 50.3125 , 50.3125 ], + [ 7.00625 , 13.125 , 21.875 ], + [11.73125 , 30.625 , 4.375 ], + [12.321875, 67.8125 , 67.8125 ], + [ 6.415625, 19.6875 , 10.9375 ], + [12.9125 , 8.75 , 61.25 ], + [ 5.825 , 52.5 , 52.5 ], + [13.503125, 45.9375 , 2.1875 ], + [ 5.234375, 59.0625 , 6.5625 ], + [14.09375 , 56.875 , 30.625 ], + [14.684375, 24.0625 , 41.5625 ], + [ 4.64375 , 21.875 , 65.625 ], + [15.275 , 17.5 , 17.5 ], + [ 4.053125, 10.9375 , 37.1875 ], + [15.865625, 54.6875 , 45.9375 ], + [ 3.4625 , 43.75 , 26.25 ], + [16.45625 , 48.125 , 56.875 ], + [17.046875, 15.3125 , 15.3125 ], + [ 2.871875, 32.8125 , 32.8125 ], + [ 2. , 1. , 1. ], + [ 2.28125 , 65.625 , 39.375 ], + [17.6375 , 61.25 , 8.75 ], + [18.228125, 28.4375 , 54.6875 ], + [18.81875 , 4.375 , 48.125 ], + [19.409375, 41.5625 , 24.0625 ]]), 'exploration_results': array([0.64211564, 0.64842422, 0.66164015, 0.68191739, 0.7044766 , + 0.74714868, 0.84823378, 0.86260589, 0.97951322, 0.98995977, + 1.12431839, 1.18221306, 1.30406647, 1.43719388, 1.52011014, + 1.78024917, 1.78140887, 2.0971452 , 2.2458042 , 2.48116605, + 2.89746811, 2.94379242, 3.4976294 , 3.77142778, 3.92475841, + 4.11872048, 4.16035282, 4.94978648, 5.89491246, 7.00125067])}}" diff --git a/code/estimark/content/tables/min/WarmGlowPortfolio_estimate_results.csv b/code/estimark/content/tables/min/WarmGlowPortfolio_estimate_results.csv new file mode 100644 index 0000000..34bcfc8 --- /dev/null +++ b/code/estimark/content/tables/min/WarmGlowPortfolio_estimate_results.csv @@ -0,0 +1,6625 @@ +CRRA,4.972059127341761 +BeqFac,2235.66869440018 +time_to_estimate,120.60259437561035 +params,"{'CRRA': 4.972059127341761, 'BeqFac': 2235.66869440018}" +criterion,0.15183333483370898 +start_criterion,0.14974471998399175 +start_params,"{'CRRA': 4.972165469041286, 'BeqFac': 2235.668701887974}" +algorithm,multistart_tranquilo_ls +direction,minimize +n_free,2 +message,Absolute criterion change smaller than tolerance. +success, +n_criterion_evaluations, +n_derivative_evaluations, +n_iterations, +history,"{'params': [{'CRRA': 4.972165469041287, 'BeqFac': 2235.668701887974}, {'CRRA': 1.1, 'BeqFac': 2038.2167591428197}, {'CRRA': 20.0, 'BeqFac': 2200.680349896351}, {'CRRA': 1.1, 'BeqFac': 2429.9412094587697}, {'CRRA': 19.832484492263543, 'BeqFac': 2433.7996818884876}, {'CRRA': 19.93169977776446, 'BeqFac': 2037.53772188746}, {'CRRA': 20.0, 'BeqFac': 2064.4481322185475}, {'CRRA': 1.1, 'BeqFac': 2332.634198828065}, {'CRRA': 20.0, 'BeqFac': 2322.498125139562}, {'CRRA': 18.700329294200046, 'BeqFac': 2433.7996818884876}, {'CRRA': 1.1, 'BeqFac': 2430.302509845014}, {'CRRA': 7.813833384306793, 'BeqFac': 2037.53772188746}, {'CRRA': 8.624550632134087, 'BeqFac': 2433.7996818884876}, {'CRRA': 17.981702297455875, 'BeqFac': 2037.53772188746}, {'CRRA': 18.109298496140873, 'BeqFac': 2136.603211887717}, {'CRRA': 19.930536834777662, 'BeqFac': 2186.135956887845}, {'CRRA': 20.0, 'BeqFac': 2210.9023293879095}, {'CRRA': 4.079012994666991, 'BeqFac': 2248.051888138006}, {'CRRA': 3.121220401269943, 'BeqFac': 2241.86029501299}, {'CRRA': 4.8421373902763785, 'BeqFac': 2239.1595207269393}, {'CRRA': 4.935891618489661, 'BeqFac': 2237.414959439111}, {'CRRA': 4.960910699246413, 'BeqFac': 2234.79536779911}, {'CRRA': 4.975594073396457, 'BeqFac': 2236.1053544720567}, {'CRRA': 5.031762747602235, 'BeqFac': 2235.4503996289804}, {'CRRA': 4.95481938313597, 'BeqFac': 2235.5595356176655}, {'CRRA': 4.962658187223382, 'BeqFac': 2235.723260832982}, {'CRRA': 4.976595860461234, 'BeqFac': 2235.641409064533}, {'CRRA': 4.985643978352027, 'BeqFac': 2235.670829747999}, {'CRRA': 4.965480731774778, 'BeqFac': 2235.6673366817404}, {'CRRA': 4.9715471211216276, 'BeqFac': 2235.672056738335}, {'CRRA': 4.973852096731626, 'BeqFac': 2235.6684476620744}, {'CRRA': 4.9713764830158755, 'BeqFac': 2235.6683781025586}, {'CRRA': 4.972141953092093, 'BeqFac': 2235.669128923647}, {'CRRA': 4.972378447740231, 'BeqFac': 2235.6687118162295}, {'CRRA': 4.972059127341761, 'BeqFac': 2235.66869440018}], 'criterion': [0.15183336484019694, 1599.2256506697936, 8.33792735607635, 1628.996184127626, 7.942067008283367, 8.173798608673742, 8.33777080025052, 1622.3971740217662, 8.338047223703619, 5.70897681494281, 1629.0195228262494, 0.4459772753262474, 0.5044697780491717, 4.621902068591304, 4.800133525579624, 8.171500062212324, 8.337937651588279, 0.5669929910375328, 6.5167800463917995, 0.15533004766705152, 0.1521320528374574, 0.15187972532160543, 0.15186895370600006, 0.15287286421734658, 0.1519085924789972, 0.1518749282368537, 0.15186803665511617, 0.15194576604337082, 0.15186614554536748, 0.15183882851267255, 0.1518437390370875, 0.1518413460232434, 0.15183338142448646, 0.15183419903764392, 0.15183333483370898], 'runtime': [0.0, 3.234110999852419, 3.3567784996703267, 3.607193300034851, 3.782226899638772, 3.974268099758774, 4.16790989972651, 4.338716899976134, 4.589133599773049, 4.924178099725395, 5.076727400068194, 5.272234600037336, 5.437637999653816, 6.631617899984121, 7.839812099933624, 9.029853600077331, 10.224262000061572, 11.426363199949265, 12.594932300038636, 13.766675599850714, 14.943977899849415, 16.25537579972297, 17.437238699756563, 18.621162499766797, 19.853813599795103, 21.03928539995104, 22.241678999736905, 23.42911219969392, 24.757420799694955, 25.978194700088352, 27.192072699777782, 28.37384819984436, 29.543620300013572, 30.743656399659812, 31.96393799968064], 'batches': [0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23]}" +convergence_report, +multistart_info,"{'start_parameters': [{'CRRA': 4.972165469041287, 'BeqFac': 2235.668701887974}, {'CRRA': 5.221879724992187, 'BeqFac': 3777.5556353977354}], 'local_optima': [Minimize with 2 free parameters terminated. + +The tranquilo_ls algorithm reported: Absolute criterion change smaller than tolerance. + +Independent of the convergence criteria used by tranquilo_ls, the strength of convergence can be assessed by the following criteria: + + one_step five_steps +relative_criterion_change 1.976e-07* 1.976e-07* +relative_params_change 2.139e-05 2.139e-05 +absolute_criterion_change 3.001e-08* 3.001e-08* +absolute_params_change 0.0001066 0.0001066 + +(***: change <= 1e-10, **: change <= 1e-8, *: change <= 1e-5. Change refers to a change between accepted steps. The first column only considers the last step. The second column considers the last five steps.), Minimize with 2 free parameters terminated. + +The tranquilo_ls algorithm reported: Absolute criterion change smaller than tolerance. + +Independent of the convergence criteria used by tranquilo_ls, the strength of convergence can be assessed by the following criteria: + + one_step five_steps +relative_criterion_change 2.639e-07* 0.0006443 +relative_params_change 2.12e-06* 0.002311 +absolute_criterion_change 4.695e-08* 0.0001146 +absolute_params_change 1.126e-05 6.64 + +(***: change <= 1e-10, **: change <= 1e-8, *: change <= 1e-5. Change refers to a change between accepted steps. The first column only considers the last step. The second column considers the last five steps.)], 'exploration_sample': [{'CRRA': 4.972165469041286, 'BeqFac': 2235.668701887974}, {'CRRA': 5.824999999999999, 'BeqFac': 7500.0}, {'CRRA': 4.64375, 'BeqFac': 3125.0}, {'CRRA': 7.596874999999999, 'BeqFac': 7187.5}, {'CRRA': 7.00625, 'BeqFac': 1875.0}, {'CRRA': 8.1875, 'BeqFac': 3750.0}, {'CRRA': 9.368749999999999, 'BeqFac': 5625.0}, {'CRRA': 10.549999999999999, 'BeqFac': 5000.0}, {'CRRA': 11.73125, 'BeqFac': 4375.0}, {'CRRA': 12.321874999999999, 'BeqFac': 9687.5}, {'CRRA': 12.9125, 'BeqFac': 1250.0}, {'CRRA': 14.093749999999998, 'BeqFac': 8125.0}, {'CRRA': 15.274999999999999, 'BeqFac': 2500.0}, {'CRRA': 16.45625, 'BeqFac': 6875.0}, {'CRRA': 17.046875, 'BeqFac': 2187.5}, {'CRRA': 17.6375, 'BeqFac': 8750.0}, {'CRRA': 18.81875, 'BeqFac': 625.0}, {'CRRA': 3.4625, 'BeqFac': 6250.0}, {'CRRA': 2.871875, 'BeqFac': 4687.5}, {'CRRA': 2.28125, 'BeqFac': 9375.0}], 'exploration_results': array([1.51833365e-01, 2.18154716e-01, 2.63875842e-01, 3.77381203e-01, + 3.83108040e-01, 4.55042643e-01, 5.57986156e-01, 6.96479632e-01, + 8.83084679e-01, 1.01143958e+00, 1.14406241e+00, 1.54612379e+00, + 2.11582828e+00, 2.96340381e+00, 3.51474071e+00, 4.18178301e+00, + 5.91221015e+00, 7.72175220e+00, 2.55327213e+01, 2.20727523e+02])}" +algorithm_output,"{'states': [State(trustregion=Region(center=array([ 4.97216547, 2235.66870189]), radius=223.5668701887974, bounds=Bounds(lower=array([1.1, 0. ]), upper=array([ 20., 10000.]))), model_indices=[0], model=ScalarModel(intercept=0.15183336484019694, linear_terms=array([0., 0.]), square_terms=array([[0., 0.], + [0., 0.]]), scale=223.5668701887974, shift=array([ 4.97216547, 2235.66870189])), vector_model=VectorModel(intercepts=array([ 0.06291566, 0.1164343 , 0.10823532, 0.12189129, 0.12343732, + 0.12357637, 0.12479259, 0.09432371, 0.01973898, 0.10842372, + -0.14822489, -0.07394217, -0.01698702, -0.0183285 , -0.03672195, + -0.06411929, -0.08426122]), linear_terms=array([[0., 0.], + [0., 0.], + 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relative_step_length=None, n_evals_per_point=None, n_evals_acceptance=None), State(trustregion=Region(center=array([ 4.97216547, 2235.66870189]), radius=223.5668701887974, bounds=Bounds(lower=array([1.1, 0. ]), upper=array([ 20., 10000.]))), model_indices=array([ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12]), model=ScalarModel(intercept=196.12406005340955, linear_terms=array([-428.74914009, 49.95239728]), square_terms=array([[475.26532472, -54.98930881], + [-54.98930881, 6.38449896]]), scale=array([ 9.45 , 198.13098]), shift=array([ 10.55 , 2235.66870189])), vector_model=VectorModel(intercepts=array([ 0.06291566, 0.1164343 , 0.10823532, 0.12189129, 0.12343732, + 0.12357637, 0.12479259, 0.09432371, 0.01973898, 0.10842372, + -0.14822489, -0.07394217, -0.01698702, -0.0183285 , -0.03672195, + -0.06411929, -0.08426122]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + 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n_evals_acceptance=1), State(trustregion=Region(center=array([ 4.97216547, 2235.66870189]), radius=111.7834350943987, bounds=Bounds(lower=array([1.1, 0. ]), upper=array([ 20., 10000.]))), model_indices=array([ 0, 1, 2, 3, 6, 7, 8, 10, 11]), model=ScalarModel(intercept=242.07061318310053, linear_terms=array([-471.89691667, 101.1889206 ]), square_terms=array([[465.88374262, -99.22450662], + [-99.22450662, 21.20996444]]), scale=array([ 9.45 , 99.06549]), shift=array([ 10.55 , 2235.66870189])), vector_model=VectorModel(intercepts=array([ 0.06291566, 0.1164343 , 0.10823532, 0.12189129, 0.12343732, + 0.12357637, 0.12479259, 0.09432371, 0.01973898, 0.10842372, + -0.14822489, -0.07394217, -0.01698702, -0.0183285 , -0.03672195, + -0.06411929, -0.08426122]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=223.5668701887974, shift=array([ 4.97216547, 2235.66870189])), candidate_index=14, candidate_x=array([ 18.1092985 , 2136.60321189]), index=0, x=array([ 4.97216547, 2235.66870189]), fval=0.15183336484019694, rho=-0.007755830036420791, accepted=False, new_indices=array([], dtype=int32), old_indices_used=array([ 0, 1, 2, 3, 6, 7, 8, 10, 11]), old_indices_discarded=array([ 4, 5, 9, 12, 13]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 4.97216547, 2235.66870189]), radius=55.89171754719935, bounds=Bounds(lower=array([1.1, 0. ]), upper=array([ 20., 10000.]))), model_indices=array([ 0, 1, 2, 3, 6, 7, 8, 10, 14]), model=ScalarModel(intercept=298.87379830095927, linear_terms=array([-576.79607872, 19.05034093]), square_terms=array([[562.44777715, -18.48262992], + [-18.48262992, 0.60886349]]), scale=array([ 9.45 , 49.532745]), shift=array([ 10.55 , 2235.66870189])), vector_model=VectorModel(intercepts=array([ 0.06291566, 0.1164343 , 0.10823532, 0.12189129, 0.12343732, + 0.12357637, 0.12479259, 0.09432371, 0.01973898, 0.10842372, + -0.14822489, -0.07394217, -0.01698702, -0.0183285 , -0.03672195, + -0.06411929, -0.08426122]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=223.5668701887974, shift=array([ 4.97216547, 2235.66870189])), candidate_index=15, candidate_x=array([ 19.93053683, 2186.13595689]), index=0, x=array([ 4.97216547, 2235.66870189]), fval=0.15183336484019694, rho=-0.010921826812679862, accepted=False, new_indices=array([], dtype=int32), old_indices_used=array([ 0, 1, 2, 3, 6, 7, 8, 10, 14]), old_indices_discarded=array([ 4, 5, 9, 11, 12, 13]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 4.97216547, 2235.66870189]), radius=27.945858773599674, bounds=Bounds(lower=array([1.1, 0. ]), upper=array([ 20., 10000.]))), model_indices=array([ 0, 2, 7, 8, 14, 15]), model=ScalarModel(intercept=131.07369976203483, linear_terms=array([-204.19706036, 40.77897837]), square_terms=array([[163.90069793, -32.18422025], + [-32.18422025, 6.38059561]]), scale=array([ 9.45 , 24.7663725]), shift=array([ 10.55 , 2235.66870189])), vector_model=VectorModel(intercepts=array([ 0.06291566, 0.1164343 , 0.10823532, 0.12189129, 0.12343732, + 0.12357637, 0.12479259, 0.09432371, 0.01973898, 0.10842372, + -0.14822489, -0.07394217, -0.01698702, -0.0183285 , -0.03672195, + -0.06411929, -0.08426122]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=223.5668701887974, shift=array([ 4.97216547, 2235.66870189])), candidate_index=16, candidate_x=array([ 20. , 2210.90232939]), index=0, x=array([ 4.97216547, 2235.66870189]), fval=0.15183336484019694, rho=-0.029581696796089584, accepted=False, new_indices=array([], dtype=int32), old_indices_used=array([ 0, 2, 7, 8, 14, 15]), old_indices_discarded=array([], dtype=int32), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 4.97216547, 2235.66870189]), radius=13.972929386799837, bounds=Bounds(lower=array([1.1, 0. ]), upper=array([ 20., 10000.]))), model_indices=array([ 0, 2, 15, 16]), model=ScalarModel(intercept=0.9873239325348305, linear_terms=array([2.73907339, 0.01391224]), square_terms=array([[4.36743207e+00, 2.75767161e-02], + [2.75767161e-02, 2.41056737e-04]]), scale=array([ 8.12767586, 12.38318625]), shift=array([ 9.22767586, 2235.66870189])), vector_model=VectorModel(intercepts=array([ 0.06291566, 0.1164343 , 0.10823532, 0.12189129, 0.12343732, + 0.12357637, 0.12479259, 0.09432371, 0.01973898, 0.10842372, + -0.14822489, -0.07394217, -0.01698702, -0.0183285 , -0.03672195, + -0.06411929, -0.08426122]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=223.5668701887974, shift=array([ 4.97216547, 2235.66870189])), candidate_index=17, candidate_x=array([ 4.07901299, 2248.05188814]), index=0, x=array([ 4.97216547, 2235.66870189]), fval=0.15183336484019694, rho=-15.504804046764184, accepted=False, new_indices=array([], dtype=int32), old_indices_used=array([ 0, 2, 15, 16]), old_indices_discarded=array([], dtype=int32), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 4.97216547, 2235.66870189]), radius=6.986464693399919, bounds=Bounds(lower=array([1.1, 0. ]), upper=array([ 20., 10000.]))), model_indices=array([ 0, 16, 17]), model=ScalarModel(intercept=0.3431675848933713, linear_terms=array([1.33281827, 0.32943084]), square_terms=array([[4.36179571, 1.27691822], + [1.27691822, 0.39380953]]), scale=array([5.0318793 , 6.19159313]), shift=array([ 6.1318793 , 2235.66870189])), vector_model=VectorModel(intercepts=array([ 0.06291566, 0.1164343 , 0.10823532, 0.12189129, 0.12343732, + 0.12357637, 0.12479259, 0.09432371, 0.01973898, 0.10842372, + -0.14822489, -0.07394217, -0.01698702, -0.0183285 , -0.03672195, + -0.06411929, -0.08426122]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=223.5668701887974, shift=array([ 4.97216547, 2235.66870189])), candidate_index=18, candidate_x=array([ 3.1212204 , 2241.86029501]), index=0, x=array([ 4.97216547, 2235.66870189]), fval=0.15183336484019694, rho=-100.94273410330236, accepted=False, new_indices=array([], dtype=int32), old_indices_used=array([ 0, 16, 17]), old_indices_discarded=array([], dtype=int32), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 4.97216547, 2235.66870189]), radius=3.4932323466999593, bounds=Bounds(lower=array([1.1, 0. ]), upper=array([ 20., 10000.]))), model_indices=array([ 0, 17, 18]), model=ScalarModel(intercept=0.15183336484019672, linear_terms=array([-0.12431539, -0.0055439 ]), square_terms=array([[59.59210104, 2.34414471], + [ 2.34414471, 0.09228281]]), scale=3.4932323466999593, shift=array([ 4.97216547, 2235.66870189])), vector_model=VectorModel(intercepts=array([ 0.06291566, 0.1164343 , 0.10823532, 0.12189129, 0.12343732, + 0.12357637, 0.12479259, 0.09432371, 0.01973898, 0.10842372, + -0.14822489, -0.07394217, -0.01698702, -0.0183285 , -0.03672195, + -0.06411929, -0.08426122]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=223.5668701887974, shift=array([ 4.97216547, 2235.66870189])), candidate_index=19, candidate_x=array([ 4.84213739, 2239.15952073]), index=0, x=array([ 4.97216547, 2235.66870189]), fval=0.15183336484019694, rho=-4.681921220989647, accepted=False, new_indices=array([], dtype=int32), old_indices_used=array([ 0, 17, 18]), old_indices_discarded=array([], dtype=int32), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 4.97216547, 2235.66870189]), radius=1.7466161733499797, bounds=Bounds(lower=array([1.1, 0. ]), upper=array([ 20., 10000.]))), model_indices=array([ 0, 18, 19]), model=ScalarModel(intercept=0.15183336484019672, linear_terms=array([-0.06103675, -0.00243685]), square_terms=array([[1.34115073e+01, 3.39655978e-01], + [3.39655978e-01, 8.60970305e-03]]), scale=1.7466161733499797, shift=array([ 4.97216547, 2235.66870189])), vector_model=VectorModel(intercepts=array([ 0.06291566, 0.1164343 , 0.10823532, 0.12189129, 0.12343732, + 0.12357637, 0.12479259, 0.09432371, 0.01973898, 0.10842372, + -0.14822489, -0.07394217, -0.01698702, -0.0183285 , -0.03672195, + -0.06411929, -0.08426122]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=223.5668701887974, shift=array([ 4.97216547, 2235.66870189])), candidate_index=20, candidate_x=array([ 4.93589162, 2237.41495944]), index=0, x=array([ 4.97216547, 2235.66870189]), fval=0.15183336484019694, rho=-0.29114147897803394, accepted=False, new_indices=array([], dtype=int32), old_indices_used=array([ 0, 18, 19]), old_indices_discarded=array([], dtype=int32), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 4.97216547, 2235.66870189]), radius=0.8733080866749898, bounds=Bounds(lower=array([1.1, 0. ]), upper=array([ 20., 10000.]))), model_indices=array([ 0, 19, 20]), model=ScalarModel(intercept=0.15183336484019688, linear_terms=array([0.00582774, 0.00013542]), square_terms=array([[3.87857288e-01, 8.27620950e-04], + [8.27620950e-04, 2.06651665e-06]]), scale=0.8733080866749898, shift=array([ 4.97216547, 2235.66870189])), vector_model=VectorModel(intercepts=array([ 0.06291566, 0.1164343 , 0.10823532, 0.12189129, 0.12343732, + 0.12357637, 0.12479259, 0.09432371, 0.01973898, 0.10842372, + -0.14822489, -0.07394217, -0.01698702, -0.0183285 , -0.03672195, + -0.06411929, -0.08426122]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=223.5668701887974, shift=array([ 4.97216547, 2235.66870189])), candidate_index=21, candidate_x=array([ 4.9609107, 2234.7953678]), index=0, x=array([ 4.97216547, 2235.66870189]), fval=0.15183336484019694, rho=-0.27824291525666955, accepted=False, new_indices=array([], dtype=int32), old_indices_used=array([ 0, 19, 20]), old_indices_discarded=array([], dtype=int32), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 4.97216547, 2235.66870189]), radius=0.4366540433374949, bounds=Bounds(lower=array([1.1, 0. ]), upper=array([ 20., 10000.]))), model_indices=array([ 0, 20, 21]), model=ScalarModel(intercept=0.15183336484019702, linear_terms=array([-5.56309005e-04, -4.37454587e-06]), square_terms=array([[ 7.50279995e-02, -3.28466129e-05], + [-3.28466129e-05, 2.15202300e-08]]), scale=0.4366540433374949, shift=array([ 4.97216547, 2235.66870189])), vector_model=VectorModel(intercepts=array([ 0.06291566, 0.1164343 , 0.10823532, 0.12189129, 0.12343732, + 0.12357637, 0.12479259, 0.09432371, 0.01973898, 0.10842372, + -0.14822489, -0.07394217, -0.01698702, -0.0183285 , -0.03672195, + -0.06411929, -0.08426122]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=223.5668701887974, shift=array([ 4.97216547, 2235.66870189])), candidate_index=22, candidate_x=array([ 4.97559407, 2236.10535447]), index=0, x=array([ 4.97216547, 2235.66870189]), fval=0.15183336484019694, rho=-5.330119577173148, accepted=False, new_indices=array([], dtype=int32), old_indices_used=array([ 0, 20, 21]), old_indices_discarded=array([], dtype=int32), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 4.97216547, 2235.66870189]), radius=0.21832702166874746, bounds=Bounds(lower=array([1.1, 0. ]), upper=array([ 20., 10000.]))), model_indices=array([ 0, 21, 22]), model=ScalarModel(intercept=0.15183336484019683, linear_terms=array([-4.45403999e-03, 5.16279055e-05]), square_terms=array([[1.62881565e-02, 6.77124384e-06], + [6.77124384e-06, 2.92278248e-08]]), scale=0.21832702166874746, shift=array([ 4.97216547, 2235.66870189])), vector_model=VectorModel(intercepts=array([ 0.06291566, 0.1164343 , 0.10823532, 0.12189129, 0.12343732, + 0.12357637, 0.12479259, 0.09432371, 0.01973898, 0.10842372, + -0.14822489, -0.07394217, -0.01698702, -0.0183285 , -0.03672195, + -0.06411929, -0.08426122]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=223.5668701887974, shift=array([ 4.97216547, 2235.66870189])), candidate_index=23, candidate_x=array([ 5.03176275, 2235.45039963]), index=0, x=array([ 4.97216547, 2235.66870189]), fval=0.15183336484019694, rho=-1.5692018274741517, accepted=False, new_indices=array([], dtype=int32), old_indices_used=array([ 0, 21, 22]), old_indices_discarded=array([], dtype=int32), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 4.97216547, 2235.66870189]), radius=0.10916351083437373, bounds=Bounds(lower=array([1.1, 0. ]), upper=array([ 20., 10000.]))), model_indices=array([ 0, 22, 23]), model=ScalarModel(intercept=0.1518333648401971, linear_terms=array([7.05546057e-04, 2.78738861e-06]), square_terms=array([[4.43307710e-03, 7.04906076e-07], + [7.04906076e-07, 5.61544409e-10]]), scale=0.10916351083437373, shift=array([ 4.97216547, 2235.66870189])), vector_model=VectorModel(intercepts=array([ 0.06291566, 0.1164343 , 0.10823532, 0.12189129, 0.12343732, + 0.12357637, 0.12479259, 0.09432371, 0.01973898, 0.10842372, + -0.14822489, -0.07394217, -0.01698702, -0.0183285 , -0.03672195, + -0.06411929, -0.08426122]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=223.5668701887974, shift=array([ 4.97216547, 2235.66870189])), candidate_index=24, candidate_x=array([ 4.95481938, 2235.55953562]), index=0, x=array([ 4.97216547, 2235.66870189]), fval=0.15183336484019694, rho=-1.2789338326888193, accepted=False, new_indices=array([], dtype=int32), old_indices_used=array([ 0, 22, 23]), old_indices_discarded=array([], dtype=int32), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 4.97216547, 2235.66870189]), radius=0.054581755417186864, bounds=Bounds(lower=array([1.1, 0. ]), upper=array([ 20., 10000.]))), model_indices=array([ 0, 23, 24]), model=ScalarModel(intercept=0.151833364840197, linear_terms=array([ 2.00591466e-04, -4.01524035e-05]), square_terms=array([[1.12660455e-03, 2.72179550e-06], + [2.72179550e-06, 2.34943617e-08]]), scale=0.054581755417186864, shift=array([ 4.97216547, 2235.66870189])), vector_model=VectorModel(intercepts=array([ 0.06291566, 0.1164343 , 0.10823532, 0.12189129, 0.12343732, + 0.12357637, 0.12479259, 0.09432371, 0.01973898, 0.10842372, + -0.14822489, -0.07394217, -0.01698702, -0.0183285 , -0.03672195, + -0.06411929, -0.08426122]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=223.5668701887974, shift=array([ 4.97216547, 2235.66870189])), candidate_index=25, candidate_x=array([ 4.96265819, 2235.72326083]), index=0, x=array([ 4.97216547, 2235.66870189]), fval=0.15183336484019694, rho=-0.7111299458870474, accepted=False, new_indices=array([], dtype=int32), old_indices_used=array([ 0, 23, 24]), old_indices_discarded=array([], dtype=int32), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 4.97216547, 2235.66870189]), radius=0.027290877708593432, bounds=Bounds(lower=array([1.1, 0. ]), upper=array([ 20., 10000.]))), model_indices=array([ 0, 24, 25]), model=ScalarModel(intercept=0.15183336484019697, linear_terms=array([-4.80890903e-05, 3.50155615e-06]), square_terms=array([[ 2.91958192e-04, -1.28086238e-07], + [-1.28086238e-07, 2.58764850e-09]]), scale=0.027290877708593432, shift=array([ 4.97216547, 2235.66870189])), vector_model=VectorModel(intercepts=array([ 0.06291566, 0.1164343 , 0.10823532, 0.12189129, 0.12343732, + 0.12357637, 0.12479259, 0.09432371, 0.01973898, 0.10842372, + -0.14822489, -0.07394217, -0.01698702, -0.0183285 , -0.03672195, + -0.06411929, -0.08426122]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=223.5668701887974, shift=array([ 4.97216547, 2235.66870189])), candidate_index=26, candidate_x=array([ 4.97659586, 2235.64140906]), index=0, x=array([ 4.97216547, 2235.66870189]), fval=0.15183336484019694, rho=-4.660612278998031, accepted=False, new_indices=array([], dtype=int32), old_indices_used=array([ 0, 24, 25]), old_indices_discarded=array([], dtype=int32), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 4.97216547, 2235.66870189]), radius=0.013645438854296716, bounds=Bounds(lower=array([1.1, 0. ]), upper=array([ 20., 10000.]))), model_indices=array([ 0, 25, 26]), model=ScalarModel(intercept=0.15183336484019688, linear_terms=array([-0.0017766 , -0.00030364]), square_terms=array([[4.26905240e-05, 1.06728380e-06], + [1.06728380e-06, 1.30381617e-06]]), scale=0.013645438854296716, shift=array([ 4.97216547, 2235.66870189])), vector_model=VectorModel(intercepts=array([ 0.06291566, 0.1164343 , 0.10823532, 0.12189129, 0.12343732, + 0.12357637, 0.12479259, 0.09432371, 0.01973898, 0.10842372, + -0.14822489, -0.07394217, -0.01698702, -0.0183285 , -0.03672195, + -0.06411929, -0.08426122]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=223.5668701887974, shift=array([ 4.97216547, 2235.66870189])), candidate_index=27, candidate_x=array([ 4.98564398, 2235.67082975]), index=0, x=array([ 4.97216547, 2235.66870189]), fval=0.15183336484019694, rho=-0.06310400218678887, accepted=False, new_indices=array([], dtype=int32), old_indices_used=array([ 0, 25, 26]), old_indices_discarded=array([], dtype=int32), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 4.97216547, 2235.66870189]), radius=0.006822719427148358, bounds=Bounds(lower=array([1.1, 0. ]), upper=array([ 20., 10000.]))), model_indices=array([ 0, 26, 27]), model=ScalarModel(intercept=0.1518333648401969, linear_terms=array([ 3.88679056e-05, -1.31679513e-06]), square_terms=array([[ 1.84940973e-05, -1.00210163e-07], + [-1.00210163e-07, 6.96346430e-10]]), scale=0.006822719427148358, shift=array([ 4.97216547, 2235.66870189])), vector_model=VectorModel(intercepts=array([ 0.06291566, 0.1164343 , 0.10823532, 0.12189129, 0.12343732, + 0.12357637, 0.12479259, 0.09432371, 0.01973898, 0.10842372, + -0.14822489, -0.07394217, -0.01698702, -0.0183285 , -0.03672195, + -0.06411929, -0.08426122]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=223.5668701887974, shift=array([ 4.97216547, 2235.66870189])), candidate_index=28, candidate_x=array([ 4.96548073, 2235.66733668]), index=0, x=array([ 4.97216547, 2235.66870189]), fval=0.15183336484019694, rho=-1.131884231761533, accepted=False, new_indices=array([], dtype=int32), old_indices_used=array([ 0, 26, 27]), old_indices_discarded=array([], dtype=int32), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 4.97216547, 2235.66870189]), radius=0.003411359713574179, bounds=Bounds(lower=array([1.1, 0. ]), upper=array([ 20., 10000.]))), model_indices=array([ 0, 27, 28]), model=ScalarModel(intercept=0.151833364840197, linear_terms=array([ 0.00012663, -0.00067966]), square_terms=array([[ 4.68892805e-06, -6.61282339e-07], + [-6.61282339e-07, 5.43609914e-06]]), scale=0.003411359713574179, shift=array([ 4.97216547, 2235.66870189])), vector_model=VectorModel(intercepts=array([ 0.06291566, 0.1164343 , 0.10823532, 0.12189129, 0.12343732, + 0.12357637, 0.12479259, 0.09432371, 0.01973898, 0.10842372, + -0.14822489, -0.07394217, -0.01698702, -0.0183285 , -0.03672195, + -0.06411929, -0.08426122]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + 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10000.]))), model_indices=array([ 0, 28, 29]), model=ScalarModel(intercept=0.15183336484019697, linear_terms=array([-6.40650622e-06, 1.55695709e-06]), square_terms=array([[ 1.1627052e-06, -3.2284109e-09], + [-3.2284109e-09, 6.7517919e-11]]), scale=0.0017056798567870895, shift=array([ 4.97216547, 2235.66870189])), vector_model=VectorModel(intercepts=array([ 0.06291566, 0.1164343 , 0.10823532, 0.12189129, 0.12343732, + 0.12357637, 0.12479259, 0.09432371, 0.01973898, 0.10842372, + -0.14822489, -0.07394217, -0.01698702, -0.0183285 , -0.03672195, + -0.06411929, -0.08426122]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], 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4.97216547, 2235.66870189])), vector_model=VectorModel(intercepts=array([ 0.06291566, 0.1164343 , 0.10823532, 0.12189129, 0.12343732, + 0.12357637, 0.12479259, 0.09432371, 0.01973898, 0.10842372, + -0.14822489, -0.07394217, -0.01698702, -0.0183285 , -0.03672195, + -0.06411929, -0.08426122]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=223.5668701887974, shift=array([ 4.97216547, 2235.66870189])), candidate_index=34, candidate_x=array([ 4.97205913, 2235.6686944 ]), index=34, x=array([ 4.97205913, 2235.6686944 ]), fval=0.15183333483370898, rho=0.07308056702929565, accepted=True, new_indices=array([], dtype=int32), old_indices_used=array([ 0, 32, 33]), old_indices_discarded=array([], dtype=int32), step_length=0.00010660499104711433, relative_step_length=0.9999999999805003, n_evals_per_point=1, n_evals_acceptance=1)], 'tranquilo_history': History for least_squares function with 35 entries., 'multistart_info': {'start_parameters': [array([ 4.97216547, 2235.66870189]), array([ 5.22187972, 3777.5556354 ])], 'local_optima': [{'solution_x': array([ 4.97205913, 2235.6686944 ]), 'solution_criterion': 0.15183333483370898, 'states': [State(trustregion=Region(center=array([ 4.97216547, 2235.66870189]), radius=223.5668701887974, bounds=Bounds(lower=array([1.1, 0. ]), upper=array([ 20., 10000.]))), 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2235.66870189])), vector_model=VectorModel(intercepts=array([ 0.06291566, 0.1164343 , 0.10823532, 0.12189129, 0.12343732, + 0.12357637, 0.12479259, 0.09432371, 0.01973898, 0.10842372, + -0.14822489, -0.07394217, -0.01698702, -0.0183285 , -0.03672195, + -0.06411929, -0.08426122]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=223.5668701887974, shift=array([ 4.97216547, 2235.66870189])), candidate_index=14, candidate_x=array([ 18.1092985 , 2136.60321189]), index=0, x=array([ 4.97216547, 2235.66870189]), fval=0.15183336484019694, rho=-0.007755830036420791, accepted=False, new_indices=array([], dtype=int32), old_indices_used=array([ 0, 1, 2, 3, 6, 7, 8, 10, 11]), old_indices_discarded=array([ 4, 5, 9, 12, 13]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 4.97216547, 2235.66870189]), radius=55.89171754719935, bounds=Bounds(lower=array([1.1, 0. ]), upper=array([ 20., 10000.]))), model_indices=array([ 0, 1, 2, 3, 6, 7, 8, 10, 14]), model=ScalarModel(intercept=298.87379830095927, linear_terms=array([-576.79607872, 19.05034093]), square_terms=array([[562.44777715, -18.48262992], + [-18.48262992, 0.60886349]]), scale=array([ 9.45 , 49.532745]), shift=array([ 10.55 , 2235.66870189])), vector_model=VectorModel(intercepts=array([ 0.06291566, 0.1164343 , 0.10823532, 0.12189129, 0.12343732, + 0.12357637, 0.12479259, 0.09432371, 0.01973898, 0.10842372, + -0.14822489, -0.07394217, -0.01698702, -0.0183285 , -0.03672195, + -0.06411929, -0.08426122]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=223.5668701887974, shift=array([ 4.97216547, 2235.66870189])), candidate_index=15, candidate_x=array([ 19.93053683, 2186.13595689]), index=0, x=array([ 4.97216547, 2235.66870189]), fval=0.15183336484019694, rho=-0.010921826812679862, accepted=False, new_indices=array([], dtype=int32), old_indices_used=array([ 0, 1, 2, 3, 6, 7, 8, 10, 14]), old_indices_discarded=array([ 4, 5, 9, 11, 12, 13]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 4.97216547, 2235.66870189]), radius=27.945858773599674, bounds=Bounds(lower=array([1.1, 0. ]), upper=array([ 20., 10000.]))), model_indices=array([ 0, 2, 7, 8, 14, 15]), model=ScalarModel(intercept=131.07369976203483, linear_terms=array([-204.19706036, 40.77897837]), square_terms=array([[163.90069793, -32.18422025], + [-32.18422025, 6.38059561]]), scale=array([ 9.45 , 24.7663725]), shift=array([ 10.55 , 2235.66870189])), vector_model=VectorModel(intercepts=array([ 0.06291566, 0.1164343 , 0.10823532, 0.12189129, 0.12343732, + 0.12357637, 0.12479259, 0.09432371, 0.01973898, 0.10842372, + -0.14822489, -0.07394217, -0.01698702, -0.0183285 , -0.03672195, + -0.06411929, -0.08426122]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=223.5668701887974, shift=array([ 4.97216547, 2235.66870189])), candidate_index=16, candidate_x=array([ 20. , 2210.90232939]), index=0, x=array([ 4.97216547, 2235.66870189]), fval=0.15183336484019694, rho=-0.029581696796089584, accepted=False, new_indices=array([], dtype=int32), old_indices_used=array([ 0, 2, 7, 8, 14, 15]), old_indices_discarded=array([], dtype=int32), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 4.97216547, 2235.66870189]), radius=13.972929386799837, bounds=Bounds(lower=array([1.1, 0. ]), upper=array([ 20., 10000.]))), model_indices=array([ 0, 2, 15, 16]), model=ScalarModel(intercept=0.9873239325348305, linear_terms=array([2.73907339, 0.01391224]), square_terms=array([[4.36743207e+00, 2.75767161e-02], + [2.75767161e-02, 2.41056737e-04]]), scale=array([ 8.12767586, 12.38318625]), shift=array([ 9.22767586, 2235.66870189])), vector_model=VectorModel(intercepts=array([ 0.06291566, 0.1164343 , 0.10823532, 0.12189129, 0.12343732, + 0.12357637, 0.12479259, 0.09432371, 0.01973898, 0.10842372, + -0.14822489, -0.07394217, -0.01698702, -0.0183285 , -0.03672195, + -0.06411929, -0.08426122]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=223.5668701887974, shift=array([ 4.97216547, 2235.66870189])), candidate_index=17, candidate_x=array([ 4.07901299, 2248.05188814]), index=0, x=array([ 4.97216547, 2235.66870189]), fval=0.15183336484019694, rho=-15.504804046764184, accepted=False, new_indices=array([], dtype=int32), old_indices_used=array([ 0, 2, 15, 16]), old_indices_discarded=array([], dtype=int32), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 4.97216547, 2235.66870189]), radius=6.986464693399919, bounds=Bounds(lower=array([1.1, 0. ]), upper=array([ 20., 10000.]))), model_indices=array([ 0, 16, 17]), model=ScalarModel(intercept=0.3431675848933713, linear_terms=array([1.33281827, 0.32943084]), square_terms=array([[4.36179571, 1.27691822], + [1.27691822, 0.39380953]]), scale=array([5.0318793 , 6.19159313]), shift=array([ 6.1318793 , 2235.66870189])), vector_model=VectorModel(intercepts=array([ 0.06291566, 0.1164343 , 0.10823532, 0.12189129, 0.12343732, + 0.12357637, 0.12479259, 0.09432371, 0.01973898, 0.10842372, + -0.14822489, -0.07394217, -0.01698702, -0.0183285 , -0.03672195, + -0.06411929, -0.08426122]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=223.5668701887974, shift=array([ 4.97216547, 2235.66870189])), candidate_index=18, candidate_x=array([ 3.1212204 , 2241.86029501]), index=0, x=array([ 4.97216547, 2235.66870189]), fval=0.15183336484019694, rho=-100.94273410330236, accepted=False, new_indices=array([], dtype=int32), old_indices_used=array([ 0, 16, 17]), old_indices_discarded=array([], dtype=int32), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 4.97216547, 2235.66870189]), radius=3.4932323466999593, bounds=Bounds(lower=array([1.1, 0. ]), upper=array([ 20., 10000.]))), model_indices=array([ 0, 17, 18]), model=ScalarModel(intercept=0.15183336484019672, linear_terms=array([-0.12431539, -0.0055439 ]), square_terms=array([[59.59210104, 2.34414471], + [ 2.34414471, 0.09228281]]), scale=3.4932323466999593, shift=array([ 4.97216547, 2235.66870189])), vector_model=VectorModel(intercepts=array([ 0.06291566, 0.1164343 , 0.10823532, 0.12189129, 0.12343732, + 0.12357637, 0.12479259, 0.09432371, 0.01973898, 0.10842372, + -0.14822489, -0.07394217, -0.01698702, -0.0183285 , -0.03672195, + -0.06411929, -0.08426122]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + 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step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 4.97216547, 2235.66870189]), radius=1.7466161733499797, bounds=Bounds(lower=array([1.1, 0. ]), upper=array([ 20., 10000.]))), model_indices=array([ 0, 18, 19]), model=ScalarModel(intercept=0.15183336484019672, linear_terms=array([-0.06103675, -0.00243685]), square_terms=array([[1.34115073e+01, 3.39655978e-01], + [3.39655978e-01, 8.60970305e-03]]), scale=1.7466161733499797, shift=array([ 4.97216547, 2235.66870189])), vector_model=VectorModel(intercepts=array([ 0.06291566, 0.1164343 , 0.10823532, 0.12189129, 0.12343732, + 0.12357637, 0.12479259, 0.09432371, 0.01973898, 0.10842372, + -0.14822489, -0.07394217, -0.01698702, -0.0183285 , -0.03672195, + -0.06411929, -0.08426122]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=223.5668701887974, shift=array([ 4.97216547, 2235.66870189])), candidate_index=20, candidate_x=array([ 4.93589162, 2237.41495944]), index=0, x=array([ 4.97216547, 2235.66870189]), fval=0.15183336484019694, rho=-0.29114147897803394, accepted=False, new_indices=array([], dtype=int32), old_indices_used=array([ 0, 18, 19]), old_indices_discarded=array([], dtype=int32), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 4.97216547, 2235.66870189]), radius=0.8733080866749898, bounds=Bounds(lower=array([1.1, 0. ]), upper=array([ 20., 10000.]))), model_indices=array([ 0, 19, 20]), model=ScalarModel(intercept=0.15183336484019688, linear_terms=array([0.00582774, 0.00013542]), square_terms=array([[3.87857288e-01, 8.27620950e-04], + [8.27620950e-04, 2.06651665e-06]]), scale=0.8733080866749898, shift=array([ 4.97216547, 2235.66870189])), vector_model=VectorModel(intercepts=array([ 0.06291566, 0.1164343 , 0.10823532, 0.12189129, 0.12343732, + 0.12357637, 0.12479259, 0.09432371, 0.01973898, 0.10842372, + -0.14822489, -0.07394217, -0.01698702, -0.0183285 , -0.03672195, + -0.06411929, -0.08426122]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 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bounds=Bounds(lower=array([1.1, 0. ]), upper=array([ 20., 10000.]))), model_indices=array([ 0, 20, 21]), model=ScalarModel(intercept=0.15183336484019702, linear_terms=array([-5.56309005e-04, -4.37454587e-06]), square_terms=array([[ 7.50279995e-02, -3.28466129e-05], + [-3.28466129e-05, 2.15202300e-08]]), scale=0.4366540433374949, shift=array([ 4.97216547, 2235.66870189])), vector_model=VectorModel(intercepts=array([ 0.06291566, 0.1164343 , 0.10823532, 0.12189129, 0.12343732, + 0.12357637, 0.12479259, 0.09432371, 0.01973898, 0.10842372, + -0.14822489, -0.07394217, -0.01698702, -0.0183285 , -0.03672195, + -0.06411929, -0.08426122]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 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model_indices=array([ 0, 21, 22]), model=ScalarModel(intercept=0.15183336484019683, linear_terms=array([-4.45403999e-03, 5.16279055e-05]), square_terms=array([[1.62881565e-02, 6.77124384e-06], + [6.77124384e-06, 2.92278248e-08]]), scale=0.21832702166874746, shift=array([ 4.97216547, 2235.66870189])), vector_model=VectorModel(intercepts=array([ 0.06291566, 0.1164343 , 0.10823532, 0.12189129, 0.12343732, + 0.12357637, 0.12479259, 0.09432371, 0.01973898, 0.10842372, + -0.14822489, -0.07394217, -0.01698702, -0.0183285 , -0.03672195, + -0.06411929, -0.08426122]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=223.5668701887974, shift=array([ 4.97216547, 2235.66870189])), candidate_index=23, candidate_x=array([ 5.03176275, 2235.45039963]), index=0, x=array([ 4.97216547, 2235.66870189]), fval=0.15183336484019694, rho=-1.5692018274741517, accepted=False, new_indices=array([], dtype=int32), old_indices_used=array([ 0, 21, 22]), old_indices_discarded=array([], dtype=int32), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 4.97216547, 2235.66870189]), radius=0.10916351083437373, bounds=Bounds(lower=array([1.1, 0. ]), upper=array([ 20., 10000.]))), model_indices=array([ 0, 22, 23]), model=ScalarModel(intercept=0.1518333648401971, linear_terms=array([7.05546057e-04, 2.78738861e-06]), square_terms=array([[4.43307710e-03, 7.04906076e-07], + [7.04906076e-07, 5.61544409e-10]]), scale=0.10916351083437373, shift=array([ 4.97216547, 2235.66870189])), vector_model=VectorModel(intercepts=array([ 0.06291566, 0.1164343 , 0.10823532, 0.12189129, 0.12343732, + 0.12357637, 0.12479259, 0.09432371, 0.01973898, 0.10842372, + -0.14822489, -0.07394217, -0.01698702, -0.0183285 , -0.03672195, + -0.06411929, -0.08426122]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=223.5668701887974, shift=array([ 4.97216547, 2235.66870189])), candidate_index=24, candidate_x=array([ 4.95481938, 2235.55953562]), index=0, x=array([ 4.97216547, 2235.66870189]), fval=0.15183336484019694, rho=-1.2789338326888193, accepted=False, new_indices=array([], dtype=int32), old_indices_used=array([ 0, 22, 23]), old_indices_discarded=array([], dtype=int32), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 4.97216547, 2235.66870189]), radius=0.054581755417186864, bounds=Bounds(lower=array([1.1, 0. ]), upper=array([ 20., 10000.]))), model_indices=array([ 0, 23, 24]), model=ScalarModel(intercept=0.151833364840197, linear_terms=array([ 2.00591466e-04, -4.01524035e-05]), square_terms=array([[1.12660455e-03, 2.72179550e-06], + [2.72179550e-06, 2.34943617e-08]]), scale=0.054581755417186864, shift=array([ 4.97216547, 2235.66870189])), vector_model=VectorModel(intercepts=array([ 0.06291566, 0.1164343 , 0.10823532, 0.12189129, 0.12343732, + 0.12357637, 0.12479259, 0.09432371, 0.01973898, 0.10842372, + -0.14822489, -0.07394217, -0.01698702, -0.0183285 , -0.03672195, + -0.06411929, -0.08426122]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=223.5668701887974, shift=array([ 4.97216547, 2235.66870189])), candidate_index=25, candidate_x=array([ 4.96265819, 2235.72326083]), index=0, x=array([ 4.97216547, 2235.66870189]), fval=0.15183336484019694, rho=-0.7111299458870474, accepted=False, new_indices=array([], dtype=int32), old_indices_used=array([ 0, 23, 24]), old_indices_discarded=array([], dtype=int32), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 4.97216547, 2235.66870189]), radius=0.027290877708593432, bounds=Bounds(lower=array([1.1, 0. ]), upper=array([ 20., 10000.]))), model_indices=array([ 0, 24, 25]), model=ScalarModel(intercept=0.15183336484019697, linear_terms=array([-4.80890903e-05, 3.50155615e-06]), square_terms=array([[ 2.91958192e-04, -1.28086238e-07], + [-1.28086238e-07, 2.58764850e-09]]), scale=0.027290877708593432, shift=array([ 4.97216547, 2235.66870189])), vector_model=VectorModel(intercepts=array([ 0.06291566, 0.1164343 , 0.10823532, 0.12189129, 0.12343732, + 0.12357637, 0.12479259, 0.09432371, 0.01973898, 0.10842372, + -0.14822489, -0.07394217, -0.01698702, -0.0183285 , -0.03672195, + -0.06411929, -0.08426122]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=223.5668701887974, shift=array([ 4.97216547, 2235.66870189])), candidate_index=26, candidate_x=array([ 4.97659586, 2235.64140906]), index=0, x=array([ 4.97216547, 2235.66870189]), fval=0.15183336484019694, rho=-4.660612278998031, accepted=False, new_indices=array([], dtype=int32), old_indices_used=array([ 0, 24, 25]), old_indices_discarded=array([], dtype=int32), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 4.97216547, 2235.66870189]), radius=0.013645438854296716, bounds=Bounds(lower=array([1.1, 0. ]), upper=array([ 20., 10000.]))), model_indices=array([ 0, 25, 26]), model=ScalarModel(intercept=0.15183336484019688, linear_terms=array([-0.0017766 , -0.00030364]), square_terms=array([[4.26905240e-05, 1.06728380e-06], + [1.06728380e-06, 1.30381617e-06]]), scale=0.013645438854296716, shift=array([ 4.97216547, 2235.66870189])), vector_model=VectorModel(intercepts=array([ 0.06291566, 0.1164343 , 0.10823532, 0.12189129, 0.12343732, + 0.12357637, 0.12479259, 0.09432371, 0.01973898, 0.10842372, + -0.14822489, -0.07394217, -0.01698702, -0.0183285 , -0.03672195, + -0.06411929, -0.08426122]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=223.5668701887974, shift=array([ 4.97216547, 2235.66870189])), candidate_index=27, candidate_x=array([ 4.98564398, 2235.67082975]), index=0, x=array([ 4.97216547, 2235.66870189]), fval=0.15183336484019694, rho=-0.06310400218678887, accepted=False, new_indices=array([], dtype=int32), old_indices_used=array([ 0, 25, 26]), old_indices_discarded=array([], dtype=int32), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 4.97216547, 2235.66870189]), radius=0.006822719427148358, bounds=Bounds(lower=array([1.1, 0. ]), upper=array([ 20., 10000.]))), model_indices=array([ 0, 26, 27]), model=ScalarModel(intercept=0.1518333648401969, linear_terms=array([ 3.88679056e-05, -1.31679513e-06]), square_terms=array([[ 1.84940973e-05, -1.00210163e-07], + [-1.00210163e-07, 6.96346430e-10]]), scale=0.006822719427148358, shift=array([ 4.97216547, 2235.66870189])), vector_model=VectorModel(intercepts=array([ 0.06291566, 0.1164343 , 0.10823532, 0.12189129, 0.12343732, + 0.12357637, 0.12479259, 0.09432371, 0.01973898, 0.10842372, + -0.14822489, -0.07394217, -0.01698702, -0.0183285 , -0.03672195, + -0.06411929, -0.08426122]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=223.5668701887974, shift=array([ 4.97216547, 2235.66870189])), candidate_index=28, candidate_x=array([ 4.96548073, 2235.66733668]), index=0, x=array([ 4.97216547, 2235.66870189]), fval=0.15183336484019694, rho=-1.131884231761533, accepted=False, new_indices=array([], dtype=int32), old_indices_used=array([ 0, 26, 27]), old_indices_discarded=array([], dtype=int32), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 4.97216547, 2235.66870189]), radius=0.003411359713574179, bounds=Bounds(lower=array([1.1, 0. ]), upper=array([ 20., 10000.]))), model_indices=array([ 0, 27, 28]), model=ScalarModel(intercept=0.151833364840197, linear_terms=array([ 0.00012663, -0.00067966]), square_terms=array([[ 4.68892805e-06, -6.61282339e-07], + [-6.61282339e-07, 5.43609914e-06]]), scale=0.003411359713574179, shift=array([ 4.97216547, 2235.66870189])), vector_model=VectorModel(intercepts=array([ 0.06291566, 0.1164343 , 0.10823532, 0.12189129, 0.12343732, + 0.12357637, 0.12479259, 0.09432371, 0.01973898, 0.10842372, + -0.14822489, -0.07394217, -0.01698702, -0.0183285 , -0.03672195, + -0.06411929, -0.08426122]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=223.5668701887974, shift=array([ 4.97216547, 2235.66870189])), candidate_index=29, candidate_x=array([ 4.97154712, 2235.67205674]), index=0, x=array([ 4.97216547, 2235.66870189]), fval=0.15183336484019694, 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candidate_x=array([ 18.85993617, 3442.77848375]), index=0, x=array([ 5.22187972, 3777.5556354 ]), fval=0.18001363343527702, rho=-0.012941179456654626, accepted=False, new_indices=array([ 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12]), old_indices_used=array([0]), old_indices_discarded=array([], dtype=int32), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 5.22187972, 3777.5556354 ]), radius=188.87778176988678, bounds=Bounds(lower=array([1.1, 0. ]), upper=array([ 20., 10000.]))), model_indices=array([ 0, 1, 2, 3, 5, 7, 8, 9, 12]), model=ScalarModel(intercept=239.29760384959667, linear_terms=array([-485.98520657, -50.56057094]), square_terms=array([[499.68004973, 51.63444647], + [ 51.63444647, 5.35573357]]), scale=array([ 9.45 , 167.38857582]), shift=array([ 10.55 , 3777.5556354])), vector_model=VectorModel(intercepts=array([ 0.06685046, 0.12384426, 0.11810388, 0.133374 , 0.13650311, + 0.13812835, 0.14087628, 0.11546522, 0.042301 , 0.13300251, + -0.12212488, -0.04643257, -0.03720919, -0.03626661, -0.05256766, + -0.07828796, -0.09714704]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=377.75556353977356, shift=array([ 5.22187972, 3777.5556354 ])), candidate_index=14, candidate_x=array([ 18.76448582, 3944.94421122]), index=0, x=array([ 5.22187972, 3777.5556354 ]), fval=0.18001363343527702, rho=-0.009561092191515052, accepted=False, new_indices=array([], dtype=int32), old_indices_used=array([ 0, 1, 2, 3, 5, 7, 8, 9, 12]), old_indices_discarded=array([ 4, 6, 10, 11, 13]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 5.22187972, 3777.5556354 ]), radius=94.43889088494339, bounds=Bounds(lower=array([1.1, 0. ]), upper=array([ 20., 10000.]))), model_indices=array([ 0, 1, 2, 3, 5, 7, 8, 9, 14]), model=ScalarModel(intercept=298.4276026191575, linear_terms=array([-576.46526059, 6.81414363]), square_terms=array([[ 5.62685577e+02, -6.61818552e+00], + [-6.61818552e+00, 7.80289630e-02]]), scale=array([ 9.45 , 83.69428791]), shift=array([ 10.55 , 3777.5556354])), vector_model=VectorModel(intercepts=array([ 0.06685046, 0.12384426, 0.11810388, 0.133374 , 0.13650311, + 0.13812835, 0.14087628, 0.11546522, 0.042301 , 0.13300251, + -0.12212488, 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fval=0.18001363343527702, rho=-0.011495911236178994, accepted=False, new_indices=array([], dtype=int32), old_indices_used=array([ 0, 1, 2, 3, 5, 7, 8, 9, 14]), old_indices_discarded=array([ 4, 6, 10, 11, 12, 13]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 5.22187972, 3777.5556354 ]), radius=47.219445442471695, bounds=Bounds(lower=array([1.1, 0. ]), upper=array([ 20., 10000.]))), model_indices=array([ 0, 2, 7, 8, 14, 15]), model=ScalarModel(intercept=125.45685337509687, linear_terms=array([-251.44927845, 30.0900477 ]), square_terms=array([[258.14181154, -30.52536684], + [-30.52536684, 3.63112862]]), scale=array([ 9.45 , 41.84714396]), shift=array([ 10.55 , 3777.5556354])), vector_model=VectorModel(intercepts=array([ 0.06685046, 0.12384426, 0.11810388, 0.133374 , 0.13650311, + 0.13812835, 0.14087628, 0.11546522, 0.042301 , 0.13300251, + -0.12212488, -0.04643257, -0.03720919, -0.03626661, -0.05256766, + 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accepted=False, new_indices=array([], dtype=int32), old_indices_used=array([ 0, 2, 7, 8, 14, 15]), old_indices_discarded=array([], dtype=int32), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 5.22187972, 3777.5556354 ]), radius=23.609722721235848, bounds=Bounds(lower=array([1.1, 0. ]), upper=array([ 20., 10000.]))), model_indices=array([ 0, 2, 15, 16]), model=ScalarModel(intercept=1.0792632152960797, linear_terms=array([ 2.4820159 , -0.22529719]), square_terms=array([[ 3.14659679, -0.3739566 ], + [-0.3739566 , 0.08599544]]), scale=array([ 9.45 , 20.92357198]), shift=array([ 10.55 , 3777.5556354])), vector_model=VectorModel(intercepts=array([ 0.06685046, 0.12384426, 0.11810388, 0.133374 , 0.13650311, + 0.13812835, 0.14087628, 0.11546522, 0.042301 , 0.13300251, + -0.12212488, -0.04643257, -0.03720919, -0.03626661, -0.05256766, + -0.07828796, -0.09714704]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], 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old_indices_discarded=array([], dtype=int32), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 5.22187972, 3777.5556354 ]), radius=11.804861360617924, bounds=Bounds(lower=array([1.1, 0. ]), upper=array([ 20., 10000.]))), model_indices=array([ 0, 16, 17]), model=ScalarModel(intercept=25.62010487127418, linear_terms=array([117.78318548, 58.17307866]), square_terms=array([[272.64693372, 135.19717176], + [135.19717176, 67.23744252]]), scale=array([ 7.29183286, 10.46178599]), shift=array([ 8.39183286, 3777.5556354 ])), vector_model=VectorModel(intercepts=array([ 0.06685046, 0.12384426, 0.11810388, 0.133374 , 0.13650311, + 0.13812835, 0.14087628, 0.11546522, 0.042301 , 0.13300251, + -0.12212488, -0.04643257, -0.03720919, -0.03626661, -0.05256766, + -0.07828796, -0.09714704]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + 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n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 5.22187972, 3777.5556354 ]), radius=5.902430680308962, bounds=Bounds(lower=array([1.1, 0. ]), upper=array([ 20., 10000.]))), model_indices=array([ 0, 17, 18]), model=ScalarModel(intercept=8.66476096620099, linear_terms=array([145.36114645, -0.79163954]), square_terms=array([[ 1.24486907e+03, -6.74089224e+00], + [-6.74089224e+00, 3.66585907e-02]]), scale=array([4.67638636, 5.23089299]), shift=array([ 5.77638636, 3777.5556354 ])), vector_model=VectorModel(intercepts=array([ 0.06685046, 0.12384426, 0.11810388, 0.133374 , 0.13650311, + 0.13812835, 0.14087628, 0.11546522, 0.042301 , 0.13300251, + -0.12212488, -0.04643257, -0.03720919, -0.03626661, -0.05256766, + -0.07828796, -0.09714704]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 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State(trustregion=Region(center=array([ 5.2556554 , 3782.78652839]), radius=11.804861360617924, bounds=Bounds(lower=array([1.1, 0. ]), upper=array([ 20., 10000.]))), model_indices=array([ 0, 16, 17, 18, 19]), model=ScalarModel(intercept=0.4447192260530918, linear_terms=array([3.28591072, 0.7575156 ]), square_terms=array([[238.5254968 , 72.82153083], + [ 72.82153083, 22.31236539]]), scale=array([ 7.30872069, 10.46178599]), shift=array([ 8.40872069, 3782.78652839])), vector_model=VectorModel(intercepts=array([ 0.06685046, 0.12384426, 0.11810388, 0.133374 , 0.13650311, + 0.13812835, 0.14087628, 0.11546522, 0.042301 , 0.13300251, + -0.12212488, -0.04643257, -0.03720919, -0.03626661, -0.05256766, + -0.07828796, -0.09714704]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + 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radius=5.902430680308962, bounds=Bounds(lower=array([1.1, 0. ]), upper=array([ 20., 10000.]))), model_indices=array([ 0, 17, 18, 19, 20]), model=ScalarModel(intercept=2.0924308511078555, linear_terms=array([64.90826608, -1.00041399]), square_terms=array([[ 1.10459211e+03, -1.69795324e+01], + [-1.69795324e+01, 2.61125536e-01]]), scale=array([4.6932742 , 5.23089299]), shift=array([ 5.7932742 , 3782.78652839])), vector_model=VectorModel(intercepts=array([ 0.06685046, 0.12384426, 0.11810388, 0.133374 , 0.13650311, + 0.13812835, 0.14087628, 0.11546522, 0.042301 , 0.13300251, + -0.12212488, -0.04643257, -0.03720919, -0.03626661, -0.05256766, + -0.07828796, -0.09714704]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + 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upper=array([ 20., 10000.]))), model_indices=array([ 0, 18, 19, 20, 21]), model=ScalarModel(intercept=0.60991129558898, linear_terms=array([-18.6614341 , 0.97529584]), square_terms=array([[405.20779142, -21.11615795], + [-21.11615795, 1.10050394]]), scale=2.951215340154481, shift=array([ 5.2556554 , 3782.78652839])), vector_model=VectorModel(intercepts=array([ 0.06685046, 0.12384426, 0.11810388, 0.133374 , 0.13650311, + 0.13812835, 0.14087628, 0.11546522, 0.042301 , 0.13300251, + -0.12212488, -0.04643257, -0.03720919, -0.03626661, -0.05256766, + -0.07828796, -0.09714704]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 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model=ScalarModel(intercept=0.41578081033668957, linear_terms=array([-7.17900081, 0.24007703]), square_terms=array([[108.78543013, -3.63193691], + [ -3.63193691, 0.12126679]]), scale=1.4756076700772405, shift=array([ 5.2556554 , 3782.78652839])), vector_model=VectorModel(intercepts=array([ 0.06685046, 0.12384426, 0.11810388, 0.133374 , 0.13650311, + 0.13812835, 0.14087628, 0.11546522, 0.042301 , 0.13300251, + -0.12212488, -0.04643257, -0.03720919, -0.03626661, -0.05256766, + -0.07828796, -0.09714704]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], 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linear_terms=array([-5.28954140e-03, 1.23810918e-05]), square_terms=array([[ 1.91842376e-01, -2.99622408e-05], + [-2.99622408e-05, 9.50955359e-09]]), scale=0.7378038350386202, shift=array([ 5.30368819, 3781.308501 ])), vector_model=VectorModel(intercepts=array([ 0.06685046, 0.12384426, 0.11810388, 0.133374 , 0.13650311, + 0.13812835, 0.14087628, 0.11546522, 0.042301 , 0.13300251, + -0.12212488, -0.04643257, -0.03720919, -0.03626661, -0.05256766, + -0.07828796, -0.09714704]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], 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square_terms=array([[ 1.18917531e+02, -1.26160659e+00], + [-1.26160659e+00, 1.33856432e-02]]), scale=1.4756076700772405, shift=array([ 5.32391471, 3780.570694 ])), vector_model=VectorModel(intercepts=array([ 0.06685046, 0.12384426, 0.11810388, 0.133374 , 0.13650311, + 0.13812835, 0.14087628, 0.11546522, 0.042301 , 0.13300251, + -0.12212488, -0.04643257, -0.03720919, -0.03626661, -0.05256766, + -0.07828796, -0.09714704]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], 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[2.97857263e-07, 1.58135601e-09]]), scale=0.7378038350386202, shift=array([ 5.32391471, 3780.570694 ])), vector_model=VectorModel(intercepts=array([ 0.06685046, 0.12384426, 0.11810388, 0.133374 , 0.13650311, + 0.13812835, 0.14087628, 0.11546522, 0.042301 , 0.13300251, + -0.12212488, -0.04643257, -0.03720919, -0.03626661, -0.05256766, + -0.07828796, -0.09714704]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + 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scale=1.4756076700772405, shift=array([ 5.32396542, 3779.83289016])), vector_model=VectorModel(intercepts=array([ 0.06685046, 0.12384426, 0.11810388, 0.133374 , 0.13650311, + 0.13812835, 0.14087628, 0.11546522, 0.042301 , 0.13300251, + -0.12212488, -0.04643257, -0.03720919, -0.03626661, -0.05256766, + -0.07828796, -0.09714704]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 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shift=array([ 5.32393177, 3778.35728249])), vector_model=VectorModel(intercepts=array([ 0.06685046, 0.12384426, 0.11810388, 0.133374 , 0.13650311, + 0.13812835, 0.14087628, 0.11546522, 0.042301 , 0.13300251, + -0.12212488, -0.04643257, -0.03720919, -0.03626661, -0.05256766, + -0.07828796, -0.09714704]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=377.75556353977356, shift=array([ 5.22187972, 3777.5556354 ])), candidate_index=28, candidate_x=array([ 5.26333048, 3775.40633 ]), index=27, x=array([ 5.32393177, 3778.35728249]), fval=0.17818383067605373, rho=-0.008422541073735482, accepted=False, new_indices=array([], dtype=int32), old_indices_used=array([ 0, 18, 19, 22, 23, 24, 25, 26, 27]), old_indices_discarded=array([21]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 5.32393177, 3778.35728249]), radius=1.4756076700772405, bounds=Bounds(lower=array([1.1, 0. ]), upper=array([ 20., 10000.]))), model_indices=array([ 0, 19, 22, 23, 24, 25, 26, 27, 28]), model=ScalarModel(intercept=0.17816465874227283, linear_terms=array([1.88966570e-04, 2.76343183e-05]), square_terms=array([[ 7.56470495e-01, -1.03969061e-04], + [-1.03969061e-04, 1.75995384e-08]]), scale=1.4756076700772405, shift=array([ 5.32393177, 3778.35728249])), vector_model=VectorModel(intercepts=array([ 0.06685046, 0.12384426, 0.11810388, 0.133374 , 0.13650311, + 0.13812835, 0.14087628, 0.11546522, 0.042301 , 0.13300251, + -0.12212488, -0.04643257, -0.03720919, -0.03626661, -0.05256766, + -0.07828796, -0.09714704]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=377.75556353977356, shift=array([ 5.22187972, 3777.5556354 ])), candidate_index=29, candidate_x=array([ 5.32336038, 3776.88167488]), index=29, x=array([ 5.32336038, 3776.88167488]), fval=0.17816777800820685, rho=0.5798905880546184, accepted=True, new_indices=array([], dtype=int32), old_indices_used=array([ 0, 19, 22, 23, 24, 25, 26, 27, 28]), old_indices_discarded=array([], dtype=int32), step_length=1.4756077161109993, relative_step_length=1.0000000311964756, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 5.32336038, 3776.88167488]), radius=2.951215340154481, bounds=Bounds(lower=array([1.1, 0. ]), upper=array([ 20., 10000.]))), model_indices=array([ 0, 22, 23, 24, 25, 26, 27, 28, 29]), model=ScalarModel(intercept=0.17814522233392394, linear_terms=array([1.70335715e-04, 5.34309034e-05]), square_terms=array([[ 3.02597147e+00, -4.39921704e-04], + [-4.39921704e-04, 7.75356986e-08]]), scale=2.951215340154481, shift=array([ 5.32336038, 3776.88167488])), vector_model=VectorModel(intercepts=array([ 0.06685046, 0.12384426, 0.11810388, 0.133374 , 0.13650311, + 0.13812835, 0.14087628, 0.11546522, 0.042301 , 0.13300251, + -0.12212488, -0.04643257, -0.03720919, -0.03626661, -0.05256766, + -0.07828796, -0.09714704]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=377.75556353977356, shift=array([ 5.22187972, 3777.5556354 ])), candidate_index=30, candidate_x=array([ 5.32276521, 3773.9304596 ]), index=30, x=array([ 5.32276521, 3773.9304596 ]), fval=0.1781338283759018, rho=0.6351225603827869, accepted=True, new_indices=array([], dtype=int32), old_indices_used=array([ 0, 22, 23, 24, 25, 26, 27, 28, 29]), old_indices_discarded=array([18, 19, 21]), step_length=2.9512153448295146, relative_step_length=1.0000000015841046, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 5.32276521, 3773.9304596 ]), radius=5.902430680308962, bounds=Bounds(lower=array([1.1, 0. ]), upper=array([ 20., 10000.]))), model_indices=array([ 0, 22, 24, 25, 26, 27, 28, 29, 30]), model=ScalarModel(intercept=0.22227385671774208, linear_terms=array([ 8.27516735e-01, -9.46109851e-05]), square_terms=array([[ 7.75302897e+00, -1.67049083e-03], + [-1.67049083e-03, 3.94188026e-07]]), scale=array([4.7268291 , 5.23089299]), shift=array([ 5.8268291, 3773.9304596])), vector_model=VectorModel(intercepts=array([ 0.06685046, 0.12384426, 0.11810388, 0.133374 , 0.13650311, + 0.13812835, 0.14087628, 0.11546522, 0.042301 , 0.13300251, + -0.12212488, -0.04643257, -0.03720919, -0.03626661, -0.05256766, + -0.07828796, -0.09714704]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=377.75556353977356, shift=array([ 5.22187972, 3777.5556354 ])), candidate_index=31, candidate_x=array([ 5.32129426, 3768.6995666 ]), index=31, x=array([ 5.32129426, 3768.6995666 ]), fval=0.17807394453160602, rho=0.7154013322715937, accepted=True, new_indices=array([], dtype=int32), old_indices_used=array([ 0, 22, 24, 25, 26, 27, 28, 29, 30]), old_indices_discarded=array([17, 18, 19, 20, 21, 23]), step_length=5.230893201328401, relative_step_length=0.8862269604925865, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 5.32129426, 3768.6995666 ]), radius=11.804861360617924, bounds=Bounds(lower=array([1.1, 0. ]), upper=array([ 20., 10000.]))), model_indices=array([ 0, 25, 26, 27, 28, 29, 30, 31, 32]), model=ScalarModel(intercept=0.5208780387285807, linear_terms=array([1.12839055, 0.01109011]), square_terms=array([[1.51827200e+00, 2.11161638e-02], + [2.11161638e-02, 4.80103617e-04]]), scale=array([ 7.34154012, 10.46178599]), shift=array([ 8.44154012, 3768.6995666 ])), vector_model=VectorModel(intercepts=array([ 0.06685046, 0.12384426, 0.11810388, 0.133374 , 0.13650311, + 0.13812835, 0.14087628, 0.11546522, 0.042301 , 0.13300251, + -0.12212488, -0.04643257, -0.03720919, -0.03626661, -0.05256766, + -0.07828796, -0.09714704]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=377.75556353977356, shift=array([ 5.22187972, 3777.5556354 ])), candidate_index=33, candidate_x=array([2.88314895e+00, 3.77916135e+03]), index=31, x=array([ 5.32129426, 3768.6995666 ]), fval=0.17807394453160602, rho=-248.64296126941807, accepted=False, new_indices=array([32]), old_indices_used=array([ 0, 25, 26, 27, 28, 29, 30, 31]), old_indices_discarded=array([16, 17, 18, 19, 20, 21, 22, 23, 24]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 5.32129426, 3768.6995666 ]), radius=5.902430680308962, bounds=Bounds(lower=array([1.1, 0. ]), upper=array([ 20., 10000.]))), model_indices=array([ 0, 22, 25, 27, 28, 29, 30, 31, 33]), model=ScalarModel(intercept=0.9998902148657269, linear_terms=array([15.98904319, 0.08221525]), square_terms=array([[1.55477573e+02, 8.04599038e-01], + [8.04599038e-01, 4.16601478e-03]]), scale=array([4.72609362, 5.23089299]), shift=array([ 5.82609362, 3768.6995666 ])), vector_model=VectorModel(intercepts=array([ 0.06685046, 0.12384426, 0.11810388, 0.133374 , 0.13650311, + 0.13812835, 0.14087628, 0.11546522, 0.042301 , 0.13300251, + -0.12212488, -0.04643257, -0.03720919, -0.03626661, -0.05256766, + -0.07828796, -0.09714704]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=377.75556353977356, shift=array([ 5.22187972, 3777.5556354 ])), candidate_index=34, candidate_x=array([ 5.31561276, 3773.9304596 ]), index=31, x=array([ 5.32129426, 3768.6995666 ]), fval=0.17807394453160602, rho=-0.031700914237791734, accepted=False, new_indices=array([], dtype=int32), old_indices_used=array([ 0, 22, 25, 27, 28, 29, 30, 31, 33]), old_indices_discarded=array([17, 18, 19, 20, 21, 23, 24, 26, 32]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 5.32129426, 3768.6995666 ]), radius=2.951215340154481, bounds=Bounds(lower=array([1.1, 0. ]), upper=array([ 20., 10000.]))), model_indices=array([ 0, 25, 27, 28, 29, 30, 31, 33, 34]), model=ScalarModel(intercept=0.17875368787838072, linear_terms=array([-0.35344824, -0.00160514]), square_terms=array([[6.02790036e+01, 2.32207919e-01], + [2.32207919e-01, 8.94985816e-04]]), scale=2.951215340154481, shift=array([ 5.32129426, 3768.6995666 ])), vector_model=VectorModel(intercepts=array([ 0.06685046, 0.12384426, 0.11810388, 0.133374 , 0.13650311, + 0.13812835, 0.14087628, 0.11546522, 0.042301 , 0.13300251, + -0.12212488, -0.04643257, -0.03720919, -0.03626661, -0.05256766, + -0.07828796, -0.09714704]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=377.75556353977356, shift=array([ 5.22187972, 3777.5556354 ])), candidate_index=35, candidate_x=array([ 5.3272299 , 3771.65082671]), index=31, x=array([ 5.32129426, 3768.6995666 ]), fval=0.17807394453160602, rho=-0.056632647014796866, accepted=False, new_indices=array([], dtype=int32), old_indices_used=array([ 0, 25, 27, 28, 29, 30, 31, 33, 34]), old_indices_discarded=array([17, 19, 22, 23, 24, 26]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 5.32129426, 3768.6995666 ]), radius=1.4756076700772405, bounds=Bounds(lower=array([1.1, 0. ]), upper=array([ 20., 10000.]))), model_indices=array([28, 30, 31, 34, 35]), model=ScalarModel(intercept=0.1780820131294612, linear_terms=array([1.86739648e-03, 1.59075457e-05]), square_terms=array([[ 7.41957927e-01, -1.22029600e-04], + [-1.22029600e-04, 2.23518326e-08]]), scale=1.4756076700772405, shift=array([ 5.32129426, 3768.6995666 ])), vector_model=VectorModel(intercepts=array([ 0.06685046, 0.12384426, 0.11810388, 0.133374 , 0.13650311, + 0.13812835, 0.14087628, 0.11546522, 0.042301 , 0.13300251, + -0.12212488, -0.04643257, -0.03720919, -0.03626661, -0.05256766, + -0.07828796, -0.09714704]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=377.75556353977356, shift=array([ 5.22187972, 3777.5556354 ])), candidate_index=36, candidate_x=array([ 5.31733777, 3767.22395957]), index=36, x=array([ 5.31733777, 3767.22395957]), fval=0.17803012332934734, rho=2.3606102276820975, accepted=True, new_indices=array([], dtype=int32), old_indices_used=array([28, 30, 31, 34, 35]), old_indices_discarded=array([], dtype=int32), step_length=1.4756123434937174, relative_step_length=1.0000031671131642, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 5.31733777, 3767.22395957]), radius=2.951215340154481, bounds=Bounds(lower=array([1.1, 0. ]), upper=array([ 20., 10000.]))), model_indices=array([ 0, 17, 28, 29, 30, 31, 34, 35, 36]), model=ScalarModel(intercept=0.18731061364611515, linear_terms=array([-2.78859371, -0.01533278]), square_terms=array([[4.21276635e+02, 2.31394055e+00], + [2.31394055e+00, 1.27109474e-02]]), scale=2.951215340154481, shift=array([ 5.31733777, 3767.22395957])), vector_model=VectorModel(intercepts=array([ 0.06685046, 0.12384426, 0.11810388, 0.133374 , 0.13650311, + 0.13812835, 0.14087628, 0.11546522, 0.042301 , 0.13300251, + -0.12212488, -0.04643257, -0.03720919, -0.03626661, -0.05256766, + -0.07828796, -0.09714704]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=377.75556353977356, shift=array([ 5.22187972, 3777.5556354 ])), candidate_index=37, candidate_x=array([ 5.32066257, 3770.17523664]), index=36, x=array([ 5.31733777, 3767.22395957]), fval=0.17803012332934734, rho=-0.007038929660613454, accepted=False, new_indices=array([], dtype=int32), old_indices_used=array([ 0, 17, 28, 29, 30, 31, 34, 35, 36]), old_indices_discarded=array([22, 23, 24, 25, 26, 27, 33]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 5.31733777, 3767.22395957]), radius=1.4756076700772405, bounds=Bounds(lower=array([1.1, 0. ]), upper=array([ 20., 10000.]))), model_indices=array([30, 31, 34, 35, 36, 37]), model=ScalarModel(intercept=0.17803733457425416, linear_terms=array([4.67596486e-03, 1.97718973e-05]), square_terms=array([[ 6.86260197e-01, -1.28093076e-04], + [-1.28093076e-04, 2.65774935e-08]]), scale=1.4756076700772405, shift=array([ 5.31733777, 3767.22395957])), vector_model=VectorModel(intercepts=array([ 0.06685046, 0.12384426, 0.11810388, 0.133374 , 0.13650311, + 0.13812835, 0.14087628, 0.11546522, 0.042301 , 0.13300251, + -0.12212488, -0.04643257, -0.03720919, -0.03626661, -0.05256766, + -0.07828796, -0.09714704]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=377.75556353977356, shift=array([ 5.22187972, 3777.5556354 ])), candidate_index=38, candidate_x=array([ 5.30700832, 3765.7483538 ]), index=38, x=array([ 5.30700832, 3765.7483538 ]), fval=0.17798168290601366, rho=1.3244637262751773, accepted=True, new_indices=array([], dtype=int32), old_indices_used=array([30, 31, 34, 35, 36, 37]), old_indices_discarded=array([], dtype=int32), step_length=1.4756419211239096, relative_step_length=1.000023211485928, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 5.30700832, 3765.7483538 ]), radius=2.951215340154481, bounds=Bounds(lower=array([1.1, 0. ]), upper=array([ 20., 10000.]))), model_indices=array([17, 28, 30, 31, 34, 35, 36, 37, 38]), model=ScalarModel(intercept=0.1853840653395654, linear_terms=array([-2.53255399, -0.00530967]), square_terms=array([[4.34594855e+02, 9.14605265e-01], + [9.14605265e-01, 1.92494707e-03]]), scale=2.951215340154481, shift=array([ 5.30700832, 3765.7483538 ])), vector_model=VectorModel(intercepts=array([ 0.06685046, 0.12384426, 0.11810388, 0.133374 , 0.13650311, + 0.13812835, 0.14087628, 0.11546522, 0.042301 , 0.13300251, + -0.12212488, -0.04643257, -0.03720919, -0.03626661, -0.05256766, + -0.07828796, -0.09714704]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=377.75556353977356, shift=array([ 5.22187972, 3777.5556354 ])), candidate_index=39, candidate_x=array([ 5.33041694, 3762.7971812 ]), index=38, x=array([ 5.30700832, 3765.7483538 ]), fval=0.17798168290601366, rho=-0.013094695227833497, accepted=False, new_indices=array([], dtype=int32), old_indices_used=array([17, 28, 30, 31, 34, 35, 36, 37, 38]), old_indices_discarded=array([ 0, 22, 25, 26, 27, 29, 33]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 5.30700832, 3765.7483538 ]), radius=1.4756076700772405, bounds=Bounds(lower=array([1.1, 0. ]), upper=array([ 20., 10000.]))), model_indices=array([31, 35, 36, 37, 38, 39]), model=ScalarModel(intercept=0.17798153266437608, linear_terms=array([2.67703532e-03, 1.84532996e-05]), square_terms=array([[ 6.87387208e-01, -1.22416627e-04], + [-1.22416627e-04, 2.49928337e-08]]), scale=1.4756076700772405, shift=array([ 5.30700832, 3765.7483538 ])), vector_model=VectorModel(intercepts=array([ 0.06685046, 0.12384426, 0.11810388, 0.133374 , 0.13650311, + 0.13812835, 0.14087628, 0.11546522, 0.042301 , 0.13300251, + -0.12212488, -0.04643257, -0.03720919, -0.03626661, -0.05256766, + -0.07828796, -0.09714704]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=377.75556353977356, shift=array([ 5.22187972, 3777.5556354 ])), candidate_index=40, candidate_x=array([ 5.30099892, 3764.27274717]), index=38, x=array([ 5.30700832, 3765.7483538 ]), fval=0.17798168290601366, rho=-1.7785842210147218, accepted=False, new_indices=array([], dtype=int32), old_indices_used=array([31, 35, 36, 37, 38, 39]), old_indices_discarded=array([], dtype=int32), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 5.30700832, 3765.7483538 ]), radius=0.7378038350386202, bounds=Bounds(lower=array([1.1, 0. ]), upper=array([ 20., 10000.]))), model_indices=array([31, 36, 38, 39, 40]), model=ScalarModel(intercept=0.17800937260106672, linear_terms=array([5.95288503e-06, 5.30714257e-06]), square_terms=array([[ 1.72058207e-01, -2.92041969e-05], + [-2.92041969e-05, 7.60304447e-09]]), scale=0.7378038350386202, shift=array([ 5.30700832, 3765.7483538 ])), vector_model=VectorModel(intercepts=array([ 0.06685046, 0.12384426, 0.11810388, 0.133374 , 0.13650311, + 0.13812835, 0.14087628, 0.11546522, 0.042301 , 0.13300251, + -0.12212488, -0.04643257, -0.03720919, -0.03626661, -0.05256766, + -0.07828796, -0.09714704]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=377.75556353977356, shift=array([ 5.22187972, 3777.5556354 ])), candidate_index=41, candidate_x=array([ 5.30685756, 3765.01054998]), index=41, x=array([ 5.30685756, 3765.01054998]), fval=0.17796989499069643, rho=2.2212294285075673, accepted=True, new_indices=array([], dtype=int32), old_indices_used=array([31, 36, 38, 39, 40]), old_indices_discarded=array([], dtype=int32), step_length=0.7378038354799815, relative_step_length=1.0000000005982095, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 5.30685756, 3765.01054998]), radius=1.4756076700772405, bounds=Bounds(lower=array([1.1, 0. ]), upper=array([ 20., 10000.]))), model_indices=array([31, 35, 36, 37, 38, 39, 40, 41]), model=ScalarModel(intercept=0.17799379519456676, linear_terms=array([9.04133766e-04, 1.68120998e-05]), square_terms=array([[ 6.87741442e-01, -1.22064373e-04], + [-1.22064373e-04, 2.53913004e-08]]), scale=1.4756076700772405, shift=array([ 5.30685756, 3765.01054998])), vector_model=VectorModel(intercepts=array([ 0.06685046, 0.12384426, 0.11810388, 0.133374 , 0.13650311, + 0.13812835, 0.14087628, 0.11546522, 0.042301 , 0.13300251, + -0.12212488, -0.04643257, -0.03720919, -0.03626661, -0.05256766, + -0.07828796, -0.09714704]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=377.75556353977356, shift=array([ 5.22187972, 3777.5556354 ])), candidate_index=42, candidate_x=array([ 5.30465582, 3763.53494268]), index=42, x=array([ 5.30465582, 3763.53494268]), fval=0.1779588833874623, rho=0.6269056309320292, accepted=True, new_indices=array([], dtype=int32), old_indices_used=array([31, 35, 36, 37, 38, 39, 40, 41]), old_indices_discarded=array([], dtype=int32), step_length=1.4756089451393082, relative_step_length=1.0000008640928708, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 5.30465582, 3763.53494268]), radius=2.951215340154481, bounds=Bounds(lower=array([1.1, 0. ]), upper=array([ 20., 10000.]))), model_indices=array([17, 31, 36, 37, 38, 39, 40, 41, 42]), model=ScalarModel(intercept=0.17947899803072848, linear_terms=array([-1.1742621 , 0.00126434]), square_terms=array([[ 4.44709273e+02, -4.57981892e-01], + [-4.57981892e-01, 4.71712559e-04]]), scale=2.951215340154481, shift=array([ 5.30465582, 3763.53494268])), vector_model=VectorModel(intercepts=array([ 0.06685046, 0.12384426, 0.11810388, 0.133374 , 0.13650311, + 0.13812835, 0.14087628, 0.11546522, 0.042301 , 0.13300251, + -0.12212488, -0.04643257, -0.03720919, -0.03626661, -0.05256766, + -0.07828796, -0.09714704]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=377.75556353977356, shift=array([ 5.22187972, 3777.5556354 ])), candidate_index=43, candidate_x=array([ 5.30940925, 3760.58372087]), index=43, x=array([ 5.30940925, 3760.58372087]), fval=0.17791553246894198, rho=0.027004451558225083, accepted=True, new_indices=array([], dtype=int32), old_indices_used=array([17, 31, 36, 37, 38, 39, 40, 41, 42]), old_indices_discarded=array([ 0, 28, 29, 30, 34, 35]), step_length=2.9512256285033613, relative_step_length=1.000003486139673, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 5.30940925, 3760.58372087]), radius=1.4756076700772405, bounds=Bounds(lower=array([1.1, 0. ]), upper=array([ 20., 10000.]))), model_indices=array([17, 36, 38, 39, 40, 41, 42, 43]), model=ScalarModel(intercept=0.1783256875306959, linear_terms=array([-3.07287421e-01, -8.21318424e-05]), square_terms=array([[1.10555074e+02, 3.40646813e-02], + [3.40646813e-02, 1.05016887e-05]]), scale=1.4756076700772405, shift=array([ 5.30940925, 3760.58372087])), vector_model=VectorModel(intercepts=array([ 0.06685046, 0.12384426, 0.11810388, 0.133374 , 0.13650311, + 0.13812835, 0.14087628, 0.11546522, 0.042301 , 0.13300251, + -0.12212488, -0.04643257, -0.03720919, -0.03626661, -0.05256766, + -0.07828796, -0.09714704]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=377.75556353977356, shift=array([ 5.22187972, 3777.5556354 ])), candidate_index=44, candidate_x=array([ 5.31396537, 3759.10811454]), index=43, x=array([ 5.30940925, 3760.58372087]), fval=0.17791553246894198, rho=-0.006804942702733265, accepted=False, new_indices=array([], dtype=int32), old_indices_used=array([17, 36, 38, 39, 40, 41, 42, 43]), old_indices_discarded=array([], dtype=int32), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 5.30940925, 3760.58372087]), radius=0.7378038350386202, bounds=Bounds(lower=array([1.1, 0. ]), upper=array([ 20., 10000.]))), model_indices=array([39, 42, 43, 44]), model=ScalarModel(intercept=0.17792080695215554, linear_terms=array([2.06155976e-03, 1.11830329e-05]), square_terms=array([[ 1.70363006e-01, -3.82501682e-05], + [-3.82501682e-05, 1.24667902e-08]]), scale=0.7378038350386202, shift=array([ 5.30940925, 3760.58372087])), vector_model=VectorModel(intercepts=array([ 0.06685046, 0.12384426, 0.11810388, 0.133374 , 0.13650311, + 0.13812835, 0.14087628, 0.11546522, 0.042301 , 0.13300251, + -0.12212488, -0.04643257, -0.03720919, -0.03626661, -0.05256766, + -0.07828796, -0.09714704]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=377.75556353977356, shift=array([ 5.22187972, 3777.5556354 ])), candidate_index=45, candidate_x=array([ 5.30031607, 3759.84591906]), index=43, x=array([ 5.30940925, 3760.58372087]), fval=0.17791553246894198, rho=-2.0310571357145926, accepted=False, new_indices=array([], dtype=int32), old_indices_used=array([39, 42, 43, 44]), old_indices_discarded=array([], dtype=int32), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 5.30940925, 3760.58372087]), radius=0.3689019175193101, bounds=Bounds(lower=array([1.1, 0. ]), upper=array([ 20., 10000.]))), model_indices=array([43, 44, 45]), model=ScalarModel(intercept=0.17791553246894187, linear_terms=array([-1.17918083e-03, -3.42897503e-06]), square_terms=array([[ 4.43546197e-02, -8.57949761e-06], + [-8.57949761e-06, 4.04624924e-09]]), scale=0.3689019175193101, shift=array([ 5.30940925, 3760.58372087])), vector_model=VectorModel(intercepts=array([ 0.06685046, 0.12384426, 0.11810388, 0.133374 , 0.13650311, + 0.13812835, 0.14087628, 0.11546522, 0.042301 , 0.13300251, + -0.12212488, -0.04643257, -0.03720919, -0.03626661, -0.05256766, + -0.07828796, -0.09714704]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=377.75556353977356, shift=array([ 5.22187972, 3777.5556354 ])), candidate_index=46, candidate_x=array([ 5.31928716, 3760.95262089]), index=43, x=array([ 5.30940925, 3760.58372087]), fval=0.17791553246894198, rho=-2.6149368631946275, accepted=False, new_indices=array([], dtype=int32), old_indices_used=array([43, 44, 45]), old_indices_discarded=array([], dtype=int32), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 5.30940925, 3760.58372087]), radius=0.18445095875965506, bounds=Bounds(lower=array([1.1, 0. ]), upper=array([ 20., 10000.]))), model_indices=array([43, 45, 46]), model=ScalarModel(intercept=0.17791553246894204, linear_terms=array([ 1.84501111e-03, -3.17202089e-05]), square_terms=array([[ 1.06687234e-02, -2.43582255e-06], + [-2.43582255e-06, 7.19700602e-08]]), scale=0.18445095875965506, shift=array([ 5.30940925, 3760.58372087])), vector_model=VectorModel(intercepts=array([ 0.06685046, 0.12384426, 0.11810388, 0.133374 , 0.13650311, + 0.13812835, 0.14087628, 0.11546522, 0.042301 , 0.13300251, + -0.12212488, -0.04643257, -0.03720919, -0.03626661, -0.05256766, + -0.07828796, -0.09714704]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + 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old_indices_discarded=array([], dtype=int32), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 5.30940925, 3760.58372087]), radius=0.09222547937982753, bounds=Bounds(lower=array([1.1, 0. ]), upper=array([ 20., 10000.]))), model_indices=array([43, 46, 47]), model=ScalarModel(intercept=0.17791553246894176, linear_terms=array([-2.17795159e-04, 1.46733396e-05]), square_terms=array([[ 2.85029042e-03, -2.85696802e-06], + [-2.85696802e-06, 7.09340428e-09]]), scale=0.09222547937982753, shift=array([ 5.30940925, 3760.58372087])), vector_model=VectorModel(intercepts=array([ 0.06685046, 0.12384426, 0.11810388, 0.133374 , 0.13650311, + 0.13812835, 0.14087628, 0.11546522, 0.042301 , 0.13300251, + -0.12212488, -0.04643257, -0.03720919, -0.03626661, -0.05256766, + -0.07828796, -0.09714704]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 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relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 5.30940925, 3760.58372087]), radius=0.046112739689913765, bounds=Bounds(lower=array([1.1, 0. ]), upper=array([ 20., 10000.]))), model_indices=array([43, 47, 48]), model=ScalarModel(intercept=0.17791553246894187, linear_terms=array([-3.39208594e-04, -3.23222752e-05]), square_terms=array([[7.54306993e-04, 2.98728975e-06], + [2.98728975e-06, 3.90562555e-08]]), scale=0.046112739689913765, shift=array([ 5.30940925, 3760.58372087])), vector_model=VectorModel(intercepts=array([ 0.06685046, 0.12384426, 0.11810388, 0.133374 , 0.13650311, + 0.13812835, 0.14087628, 0.11546522, 0.042301 , 0.13300251, + -0.12212488, -0.04643257, -0.03720919, -0.03626661, -0.05256766, + -0.07828796, -0.09714704]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], 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State(trustregion=Region(center=array([ 5.30940925, 3760.58372087]), radius=0.023056369844956882, bounds=Bounds(lower=array([1.1, 0. ]), upper=array([ 20., 10000.]))), model_indices=array([43, 48, 49]), model=ScalarModel(intercept=0.17791553246894187, linear_terms=array([6.09438346e-05, 1.13529285e-06]), square_terms=array([[ 1.66872702e-04, -1.24585747e-07], + [-1.24585747e-07, 1.17301795e-09]]), scale=0.023056369844956882, shift=array([ 5.30940925, 3760.58372087])), vector_model=VectorModel(intercepts=array([ 0.06685046, 0.12384426, 0.11810388, 0.133374 , 0.13650311, + 0.13812835, 0.14087628, 0.11546522, 0.042301 , 0.13300251, + -0.12212488, -0.04643257, -0.03720919, -0.03626661, -0.05256766, + -0.07828796, -0.09714704]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 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radius=0.011528184922478441, bounds=Bounds(lower=array([1.1, 0. ]), upper=array([ 20., 10000.]))), model_indices=array([43, 49, 50]), model=ScalarModel(intercept=0.17791553246894215, linear_terms=array([ 0.00048585, -0.00019408]), square_terms=array([[ 5.31813583e-05, -5.75413054e-06], + [-5.75413054e-06, 2.79836435e-06]]), scale=0.011528184922478441, shift=array([ 5.30940925, 3760.58372087])), vector_model=VectorModel(intercepts=array([ 0.06685046, 0.12384426, 0.11810388, 0.133374 , 0.13650311, + 0.13812835, 0.14087628, 0.11546522, 0.042301 , 0.13300251, + -0.12212488, -0.04643257, -0.03720919, -0.03626661, -0.05256766, + -0.07828796, -0.09714704]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + 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10000.]))), model_indices=array([43, 50, 51]), model=ScalarModel(intercept=0.17791553246894196, linear_terms=array([-4.88151251e-05, 9.00611126e-06]), square_terms=array([[ 1.09589251e-05, -5.41537073e-08], + [-5.41537073e-08, 1.87668792e-09]]), scale=0.005764092461239221, shift=array([ 5.30940925, 3760.58372087])), vector_model=VectorModel(intercepts=array([ 0.06685046, 0.12384426, 0.11810388, 0.133374 , 0.13650311, + 0.13812835, 0.14087628, 0.11546522, 0.042301 , 0.13300251, + -0.12212488, -0.04643257, -0.03720919, -0.03626661, -0.05256766, + -0.07828796, -0.09714704]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 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model=ScalarModel(intercept=0.17791553246894182, linear_terms=array([2.12658543e-05, 1.52919564e-04]), square_terms=array([[ 2.67941071e-06, -5.49830816e-08], + [-5.49830816e-08, 3.68065340e-07]]), scale=0.0028820462306196103, shift=array([ 5.30940925, 3760.58372087])), vector_model=VectorModel(intercepts=array([ 0.06685046, 0.12384426, 0.11810388, 0.133374 , 0.13650311, + 0.13812835, 0.14087628, 0.11546522, 0.042301 , 0.13300251, + -0.12212488, -0.04643257, -0.03720919, -0.03626661, -0.05256766, + -0.07828796, -0.09714704]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + 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5.01858339e-06, -2.73111673e-06]), square_terms=array([[ 6.71301844e-07, -6.77682479e-09], + [-6.77682479e-09, 2.94207799e-10]]), scale=0.0014410231153098052, shift=array([ 5.30940925, 3760.58372087])), vector_model=VectorModel(intercepts=array([ 0.06685046, 0.12384426, 0.11810388, 0.133374 , 0.13650311, + 0.13812835, 0.14087628, 0.11546522, 0.042301 , 0.13300251, + -0.12212488, -0.04643257, -0.03720919, -0.03626661, -0.05256766, + -0.07828796, -0.09714704]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + 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-1.81884533e-09], + [-1.81884533e-09, 3.67816759e-11]]), scale=0.0007205115576549026, shift=array([ 5.30940925, 3760.58372087])), vector_model=VectorModel(intercepts=array([ 0.06685046, 0.12384426, 0.11810388, 0.133374 , 0.13650311, + 0.13812835, 0.14087628, 0.11546522, 0.042301 , 0.13300251, + -0.12212488, -0.04643257, -0.03720919, -0.03626661, -0.05256766, + -0.07828796, -0.09714704]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=377.75556353977356, shift=array([ 5.22187972, 3777.5556354 ])), candidate_index=55, candidate_x=array([ 5.31011752, 3760.58385312]), index=43, x=array([ 5.30940925, 3760.58372087]), fval=0.17791553246894198, rho=-3.027754219035174, accepted=False, new_indices=array([], dtype=int32), old_indices_used=array([43, 53, 54]), old_indices_discarded=array([], dtype=int32), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 5.30940925, 3760.58372087]), radius=0.0003602557788274513, bounds=Bounds(lower=array([1.1, 0. ]), upper=array([ 20., 10000.]))), model_indices=array([43, 54, 55]), model=ScalarModel(intercept=0.17791553246894207, linear_terms=array([3.23278987e-06, 1.03878094e-05]), square_terms=array([[ 4.26477773e-08, -3.95820208e-10], + [-3.95820208e-10, 1.42364938e-09]]), scale=0.0003602557788274513, shift=array([ 5.30940925, 3760.58372087])), vector_model=VectorModel(intercepts=array([ 0.06685046, 0.12384426, 0.11810388, 0.133374 , 0.13650311, + 0.13812835, 0.14087628, 0.11546522, 0.042301 , 0.13300251, + -0.12212488, -0.04643257, -0.03720919, -0.03626661, -0.05256766, + -0.07828796, -0.09714704]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=377.75556353977356, shift=array([ 5.22187972, 3777.5556354 ])), candidate_index=56, candidate_x=array([ 5.30930239, 3760.58337624]), index=43, x=array([ 5.30940925, 3760.58372087]), fval=0.17791553246894198, rho=-0.013594556601906208, accepted=False, new_indices=array([], dtype=int32), old_indices_used=array([43, 54, 55]), old_indices_discarded=array([], dtype=int32), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 5.30940925, 3760.58372087]), radius=0.00018012788941372564, bounds=Bounds(lower=array([1.1, 0. ]), upper=array([ 20., 10000.]))), model_indices=array([43, 55, 56]), model=ScalarModel(intercept=0.17791553246894198, linear_terms=array([ 2.76028821e-06, -9.32486831e-07]), square_terms=array([[ 1.07776183e-08, -3.77632159e-10], + [-3.77632159e-10, 2.29706603e-11]]), scale=0.00018012788941372564, shift=array([ 5.30940925, 3760.58372087])), vector_model=VectorModel(intercepts=array([ 0.06685046, 0.12384426, 0.11810388, 0.133374 , 0.13650311, + 0.13812835, 0.14087628, 0.11546522, 0.042301 , 0.13300251, + -0.12212488, -0.04643257, -0.03720919, -0.03626661, -0.05256766, + -0.07828796, -0.09714704]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=377.75556353977356, shift=array([ 5.22187972, 3777.5556354 ])), candidate_index=57, candidate_x=array([ 5.30923847, 3760.58377814]), index=43, x=array([ 5.30940925, 3760.58372087]), fval=0.17791553246894198, rho=-0.058405552122264226, accepted=False, new_indices=array([], dtype=int32), old_indices_used=array([43, 55, 56]), old_indices_discarded=array([], dtype=int32), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 5.30940925, 3760.58372087]), radius=9.006394470686282e-05, bounds=Bounds(lower=array([1.1, 0. ]), upper=array([ 20., 10000.]))), model_indices=array([43, 56, 57]), model=ScalarModel(intercept=0.17791553246894187, linear_terms=array([-9.09462086e-08, -1.01086542e-08]), square_terms=array([[2.14199013e-09, 4.89545745e-13], + [4.89545745e-13, 3.23794403e-15]]), scale=9.006394470686282e-05, shift=array([ 5.30940925, 3760.58372087])), vector_model=VectorModel(intercepts=array([ 0.06685046, 0.12384426, 0.11810388, 0.133374 , 0.13650311, + 0.13812835, 0.14087628, 0.11546522, 0.042301 , 0.13300251, + -0.12212488, -0.04643257, -0.03720919, -0.03626661, -0.05256766, + -0.07828796, -0.09714704]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=377.75556353977356, shift=array([ 5.22187972, 3777.5556354 ])), candidate_index=58, candidate_x=array([ 5.30949887, 3760.58372977]), index=43, x=array([ 5.30940925, 3760.58372087]), fval=0.17791553246894198, rho=-7.4227875403825125, accepted=False, new_indices=array([], dtype=int32), old_indices_used=array([43, 56, 57]), old_indices_discarded=array([], dtype=int32), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 5.30940925, 3760.58372087]), radius=4.503197235343141e-05, bounds=Bounds(lower=array([1.1, 0. ]), upper=array([ 20., 10000.]))), model_indices=array([43, 57, 58]), model=ScalarModel(intercept=0.17791553246894215, linear_terms=array([2.49763551e-07, 8.75365248e-07]), square_terms=array([[5.97075122e-10, 9.86414808e-11], + [9.86414808e-11, 3.99870468e-11]]), scale=4.503197235343141e-05, shift=array([ 5.30940925, 3760.58372087])), vector_model=VectorModel(intercepts=array([ 0.06685046, 0.12384426, 0.11810388, 0.133374 , 0.13650311, + 0.13812835, 0.14087628, 0.11546522, 0.042301 , 0.13300251, + -0.12212488, -0.04643257, -0.03720919, -0.03626661, -0.05256766, + -0.07828796, -0.09714704]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=377.75556353977356, shift=array([ 5.22187972, 3777.5556354 ])), candidate_index=59, candidate_x=array([ 5.3093969 , 3760.58367756]), index=43, x=array([ 5.30940925, 3760.58372087]), fval=0.17791553246894198, rho=-0.05588336662878231, accepted=False, new_indices=array([], dtype=int32), old_indices_used=array([43, 57, 58]), old_indices_discarded=array([], dtype=int32), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 5.30940925, 3760.58372087]), radius=2.2515986176715705e-05, bounds=Bounds(lower=array([1.1, 0. ]), upper=array([ 20., 10000.]))), model_indices=array([43, 58, 59]), model=ScalarModel(intercept=0.17791553246894198, linear_terms=array([ 1.75952660e-07, -7.65912652e-08]), square_terms=array([[ 1.54804745e-10, -2.72364838e-12], + [-2.72364838e-12, 1.48003207e-13]]), scale=2.2515986176715705e-05, shift=array([ 5.30940925, 3760.58372087])), vector_model=VectorModel(intercepts=array([ 0.06685046, 0.12384426, 0.11810388, 0.133374 , 0.13650311, + 0.13812835, 0.14087628, 0.11546522, 0.042301 , 0.13300251, + -0.12212488, -0.04643257, -0.03720919, -0.03626661, -0.05256766, + -0.07828796, -0.09714704]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=377.75556353977356, shift=array([ 5.22187972, 3777.5556354 ])), candidate_index=60, candidate_x=array([ 5.3093886 , 3760.58372985]), index=43, x=array([ 5.30940925, 3760.58372087]), fval=0.17791553246894198, rho=-0.4501440029410156, accepted=False, new_indices=array([], dtype=int32), old_indices_used=array([43, 58, 59]), old_indices_discarded=array([], dtype=int32), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 5.30940925, 3760.58372087]), radius=1.1257993088357853e-05, bounds=Bounds(lower=array([1.1, 0. ]), upper=array([ 20., 10000.]))), model_indices=array([43, 59, 60]), model=ScalarModel(intercept=0.17791553246894212, linear_terms=array([-4.69738998e-08, 1.72050290e-10]), square_terms=array([[ 3.44298654e-11, -7.24102661e-15], + [-7.24102661e-15, 1.66529426e-18]]), scale=1.1257993088357853e-05, shift=array([ 5.30940925, 3760.58372087])), vector_model=VectorModel(intercepts=array([ 0.06685046, 0.12384426, 0.11810388, 0.133374 , 0.13650311, + 0.13812835, 0.14087628, 0.11546522, 0.042301 , 0.13300251, + -0.12212488, -0.04643257, -0.03720919, -0.03626661, -0.05256766, + -0.07828796, -0.09714704]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=377.75556353977356, shift=array([ 5.22187972, 3777.5556354 ])), candidate_index=61, candidate_x=array([ 5.30942051, 3760.58372084]), index=61, x=array([ 5.30942051, 3760.58372084]), fval=0.17791548552127476, rho=0.9998013126948817, accepted=True, new_indices=array([], dtype=int32), old_indices_used=array([43, 59, 60]), old_indices_discarded=array([], dtype=int32), step_length=1.1257993087530534e-05, relative_step_length=0.9999999999265128, n_evals_per_point=1, n_evals_acceptance=1)], 'message': 'Absolute criterion change smaller than tolerance.', 'tranquilo_history': History for least_squares function with 62 entries., 'history': {'params': [{'CRRA': 5.221879724992187, 'BeqFac': 3777.5556353977354}, {'CRRA': 1.1, 'BeqFac': 3476.9035708167335}, {'CRRA': 20.0, 'BeqFac': 3688.8944111418195}, {'CRRA': 1.1, 'BeqFac': 4084.9216049500956}, {'CRRA': 19.360304400268685, 'BeqFac': 4112.332787046263}, {'CRRA': 20.0, 'BeqFac': 3463.4160733070307}, {'CRRA': 19.863685373375603, 'BeqFac': 3442.778483749208}, {'CRRA': 1.1, 'BeqFac': 3921.209349974723}, {'CRRA': 20.0, 'BeqFac': 3917.345783490104}, {'CRRA': 20.0, 'BeqFac': 4104.193678537616}, {'CRRA': 1.6231245796393248, 'BeqFac': 4112.332787046263}, {'CRRA': 7.312867713980317, 'BeqFac': 3442.778483749208}, {'CRRA': 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36.06780719989911, 37.38965609995648, 38.56443569995463, 39.75320369983092, 40.928570999763906, 42.1049975999631, 43.29117719968781, 44.52116549992934, 45.709984899964184, 47.021010799799114, 48.199433099944144, 49.37279489962384, 50.552747999783605, 51.74405709980056, 52.95074549969286, 54.13156419992447, 55.446532499976456, 56.624599299859256, 57.809363099746406, 58.98130919970572, 60.15864789998159, 61.33934499975294, 62.50395749974996], 'batches': [0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50]}}], 'exploration_sample': array([[4.97216547e+00, 2.23566870e+03], + [5.82500000e+00, 7.50000000e+03], + [4.64375000e+00, 3.12500000e+03], + [7.59687500e+00, 7.18750000e+03], + [7.00625000e+00, 1.87500000e+03], + [8.18750000e+00, 3.75000000e+03], + [9.36875000e+00, 5.62500000e+03], + [1.05500000e+01, 5.00000000e+03], + [1.17312500e+01, 4.37500000e+03], + [1.23218750e+01, 9.68750000e+03], + [1.29125000e+01, 1.25000000e+03], + [1.40937500e+01, 8.12500000e+03], + [1.52750000e+01, 2.50000000e+03], + [1.64562500e+01, 6.87500000e+03], + [1.70468750e+01, 2.18750000e+03], + [1.76375000e+01, 8.75000000e+03], + [1.88187500e+01, 6.25000000e+02], + [3.46250000e+00, 6.25000000e+03], + [2.87187500e+00, 4.68750000e+03], + [2.28125000e+00, 9.37500000e+03]]), 'exploration_results': array([1.51833365e-01, 2.18154716e-01, 2.63875842e-01, 3.77381203e-01, + 3.83108040e-01, 4.55042643e-01, 5.57986156e-01, 6.96479632e-01, + 8.83084679e-01, 1.01143958e+00, 1.14406241e+00, 1.54612379e+00, + 2.11582828e+00, 2.96340381e+00, 3.51474071e+00, 4.18178301e+00, + 5.91221015e+00, 7.72175220e+00, 2.55327213e+01, 2.20727523e+02])}}" diff --git a/code/estimark/content/tables/min/WealthPortfolioBeta_estimate_results.csv b/code/estimark/content/tables/min/WealthPortfolioBeta_estimate_results.csv new file mode 100644 index 0000000..8c13be2 --- /dev/null +++ b/code/estimark/content/tables/min/WealthPortfolioBeta_estimate_results.csv @@ -0,0 +1,19638 @@ +CRRA,4.844436801414261 +WealthShare,0.3460128282561451 +DiscFac,0.9323589063936805 +time_to_estimate,217.95789170265198 +params,"{'CRRA': 4.844436801414261, 'WealthShare': 0.3460128282561451, 'DiscFac': 0.9323589063936805}" +criterion,0.17254703939389457 +start_criterion,0.23891445185117913 +start_params,"{'CRRA': 5.338780774481047, 'WealthShare': 0.17065528804872485, 'DiscFac': 1.0}" +algorithm,multistart_tranquilo_ls +direction,minimize +n_free,3 +message,Absolute criterion change smaller than tolerance. +success, +n_criterion_evaluations, +n_derivative_evaluations, +n_iterations, +history,"{'params': [{'CRRA': 5.301397603427972, 'WealthShare': 0.35179042920828707, 'DiscFac': 0.9217000493025207}, {'CRRA': 4.877555010789218, 'WealthShare': 0.01, 'DiscFac': 1.0004206381225442}, {'CRRA': 5.726445053953837, 'WealthShare': 0.038959478718889294, 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58.923332899808884, 58.96633999980986, 59.00750799989328, 59.05656659975648, 59.08834679983556, 59.132794899865985, 60.22101899981499, 61.250512999948114, 62.25834989966825, 63.258237699978054, 64.29787159990519, 65.34936949983239, 66.36967970011756, 67.51696019992232, 68.52077089995146, 69.51590960007161, 70.63079519988969, 70.66824259981513, 70.70960419997573, 70.75069979997352, 70.79406809993088, 70.83469379972667, 70.87575369980186, 70.91594929993153, 70.95578130008653, 70.99587279977277, 71.0371133997105, 71.07846489967778, 72.16604539984837], 'batches': [0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 3, 4, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 50, 51, 52, 53, 54, 55, 56, 56, 56, 56, 56, 56, 56, 56, 56, 56, 56, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 67, 67, 67, 67, 67, 67, 67, 67, 67, 67, 67, 68]}" +convergence_report,"{'one_step': {'relative_criterion_change': 0.003307242007129943, 'relative_params_change': 0.03956657811621874, 'absolute_criterion_change': 0.0005706548168893932, 'absolute_params_change': 0.19167597945625867}, 'five_steps': {'relative_criterion_change': 0.014922806335674835, 'relative_params_change': 0.0806704377224931, 'absolute_criterion_change': 0.0025748860526691453, 'absolute_params_change': 0.36818918796590866}}" +multistart_info,"{'start_parameters': [{'CRRA': 5.338780774481047, 'WealthShare': 0.17065528804872487, 'DiscFac': 1.0}, {'CRRA': 4.472854104495062, 'WealthShare': 0.457530286489798, 'DiscFac': 0.8472036933750238}, {'CRRA': 5.301397603427972, 'WealthShare': 0.35179042920828707, 'DiscFac': 0.9217000493025207}], 'local_optima': [Minimize with 3 free parameters terminated. + +The tranquilo_ls algorithm reported: Absolute criterion change smaller than tolerance. + +Independent of the convergence criteria used by tranquilo_ls, the strength of convergence can be assessed by the following criteria: + + one_step five_steps +relative_criterion_change 6.023e-05 0.0008401 +relative_params_change 0.0007429 0.01168 +absolute_criterion_change 1.055e-05 0.0001471 +absolute_params_change 0.0002607 0.005784 + +(***: change <= 1e-10, **: change <= 1e-8, *: change <= 1e-5. Change refers to a change between accepted steps. The first column only considers the last step. The second column considers the last five steps.), Minimize with 3 free parameters terminated. + +The tranquilo_ls algorithm reported: Absolute criterion change smaller than tolerance. + +Independent of the convergence criteria used by tranquilo_ls, the strength of convergence can be assessed by the following criteria: + + one_step five_steps +relative_criterion_change 4.685e-07* 0.0001119 +relative_params_change 2.549e-06* 0.0008924 +absolute_criterion_change 8.11e-08* 1.938e-05 +absolute_params_change 5.392e-06* 0.0004772 + +(***: change <= 1e-10, **: change <= 1e-8, *: change <= 1e-5. Change refers to a change between accepted steps. The first column only considers the last step. The second column considers the last five steps.), Minimize with 3 free parameters terminated. + +The tranquilo_ls algorithm reported: Absolute criterion change smaller than tolerance. + +Independent of the convergence criteria used by tranquilo_ls, the strength of convergence can be assessed by the following criteria: + + one_step five_steps +relative_criterion_change 1.731e-05 0.0001779 +relative_params_change 8.502e-05 0.003461 +absolute_criterion_change 2.988e-06* 3.07e-05 +absolute_params_change 3.236e-05 0.00824 + +(***: change <= 1e-10, **: change <= 1e-8, *: change <= 1e-5. Change refers to a change between accepted steps. The first column only considers the last step. The second column considers the last five steps.)], 'exploration_sample': [{'CRRA': 5.338780774481047, 'WealthShare': 0.17065528804872485, 'DiscFac': 1.0}, {'CRRA': 3.4625, 'WealthShare': 0.6225, 'DiscFac': 0.7250000000000001}, {'CRRA': 8.1875, 'WealthShare': 0.3775, 'DiscFac': 0.875}, {'CRRA': 10.549999999999999, 'WealthShare': 0.5, 'DiscFac': 0.8}, {'CRRA': 14.684375, 'WealthShare': 0.346875, 'DiscFac': 0.8562500000000001}, {'CRRA': 9.959375, 'WealthShare': 0.101875, 'DiscFac': 1.00625}, {'CRRA': 19.409375, 'WealthShare': 0.591875, 'DiscFac': 0.70625}, {'CRRA': 13.503124999999999, 'WealthShare': 0.653125, 'DiscFac': 0.51875}, {'CRRA': 2.871875, 'WealthShare': 0.469375, 'DiscFac': 0.78125}, {'CRRA': 9.368749999999999, 'WealthShare': 0.56125, 'DiscFac': 0.6125}, {'CRRA': 18.81875, 'WealthShare': 0.07125, 'DiscFac': 0.9125000000000001}, {'CRRA': 17.046875, 'WealthShare': 0.224375, 'DiscFac': 0.6312500000000001}, {'CRRA': 15.274999999999999, 'WealthShare': 0.255, 'DiscFac': 0.65}, {'CRRA': 12.9125, 'WealthShare': 0.1325, 'DiscFac': 1.0250000000000001}, {'CRRA': 11.73125, 'WealthShare': 0.43875, 'DiscFac': 0.5375}, {'CRRA': 18.228125, 'WealthShare': 0.408125, 'DiscFac': 0.96875}, {'CRRA': 7.00625, 'WealthShare': 0.19375, 'DiscFac': 0.6875}, {'CRRA': 6.415625, 'WealthShare': 0.285625, 'DiscFac': 0.59375}, {'CRRA': 4.053125, 'WealthShare': 0.16312500000000002, 'DiscFac': 0.8187500000000001}, {'CRRA': 5.234375, 'WealthShare': 0.836875, 'DiscFac': 0.55625}, {'CRRA': 16.45625, 'WealthShare': 0.68375, 'DiscFac': 0.9875}, {'CRRA': 14.093749999999998, 'WealthShare': 0.80625, 'DiscFac': 0.7625000000000001}, {'CRRA': 4.64375, 'WealthShare': 0.31625000000000003, 'DiscFac': 1.0625}, {'CRRA': 15.865624999999998, 'WealthShare': 0.775625, 'DiscFac': 0.89375}, {'CRRA': 17.6375, 'WealthShare': 0.8674999999999999, 'DiscFac': 0.575}, {'CRRA': 7.596874999999999, 'WealthShare': 0.714375, 'DiscFac': 0.9312500000000001}, {'CRRA': 5.824999999999999, 'WealthShare': 0.745, 'DiscFac': 0.9500000000000001}, {'CRRA': 8.778125, 'WealthShare': 0.898125, 'DiscFac': 0.66875}, {'CRRA': 2.28125, 'WealthShare': 0.92875, 'DiscFac': 0.8375}, {'CRRA': 12.321874999999999, 'WealthShare': 0.959375, 'DiscFac': 1.08125}], 'exploration_results': array([2.42222292e-01, 3.03201302e-01, 3.75385332e-01, 3.98577685e-01, + 4.64539853e-01, 6.05168236e-01, 6.05724112e-01, 7.88383230e-01, + 8.39981988e-01, 1.04605604e+00, 1.22782446e+00, 1.48069565e+00, + 1.56893759e+00, 1.77192100e+00, 1.95139780e+00, 2.44243013e+00, + 2.75221387e+00, 2.82714102e+00, 3.02109383e+00, 6.88603970e+00, + 8.55954606e+00, 9.85239944e+00, 1.14488917e+01, 1.20953777e+01, + 1.29729655e+01, 1.58640798e+01, 3.65763661e+01, 5.66287991e+01, + 4.39985749e+02, 5.91890647e+02])}" +algorithm_output,"{'states': [State(trustregion=Region(center=array([5.3013976 , 0.35179043, 0.92170005]), radius=0.5301397603427972, bounds=Bounds(lower=array([1.1 , 0.01, 0.5 ]), upper=array([20. , 0.99, 1.1 ]))), model_indices=[0], model=ScalarModel(intercept=0.18834408422290103, linear_terms=array([0., 0., 0.]), square_terms=array([[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]]), scale=0.5301397603427972, shift=array([5.3013976 , 0.35179043, 0.92170005])), vector_model=VectorModel(intercepts=array([ 0.05267501, 0.10545582, 0.09377041, 0.09722369, 0.08350715, + 0.06843123, 0.05931804, 0.03774492, -0.03016214, 0.0549344 , + -0.23227729, -0.2172487 , -0.10547152, -0.08018271, -0.07300715, + -0.0770617 , -0.07552639]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]]), square_terms=array([[[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 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old_indices_discarded=[], step_length=None, relative_step_length=None, n_evals_per_point=None, n_evals_acceptance=None), State(trustregion=Region(center=array([5.3013976 , 0.35179043, 0.92170005]), radius=0.5301397603427972, bounds=Bounds(lower=array([1.1 , 0.01, 0.5 ]), upper=array([20. , 0.99, 1.1 ]))), model_indices=array([ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12]), model=ScalarModel(intercept=2.973876171490377, linear_terms=array([ 0.72542682, 14.35685233, 14.83307135]), square_terms=array([[ 0.11413661, 1.93082302, 1.94450878], + [ 1.93082302, 36.39381604, 37.51674902], + [ 1.94450878, 37.51674902, 38.95260216]]), scale=array([0.42729051, 0.38454047, 0.3 ]), shift=array([5.3013976 , 0.39454047, 0.8 ])), vector_model=VectorModel(intercepts=array([ 0.05267501, 0.10545582, 0.09377041, 0.09722369, 0.08350715, + 0.06843123, 0.05931804, 0.03774492, -0.03016214, 0.0549344 , + -0.23227729, -0.2172487 , -0.10547152, -0.08018271, -0.07300715, + -0.0770617 , -0.07552639]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]]), square_terms=array([[[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 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linear_terms=array([-1.30558411, 10.89377008, 12.35168828]), square_terms=array([[ 0.13964041, -1.14158086, -1.299604 ], + [-1.14158086, 9.51269818, 10.71520355], + [-1.299604 , 10.71520355, 12.18421669]]), scale=array([0.21364526, 0.21364526, 0.1959726 ]), shift=array([5.3013976 , 0.35179043, 0.9040274 ])), vector_model=VectorModel(intercepts=array([ 0.05267501, 0.10545582, 0.09377041, 0.09722369, 0.08350715, + 0.06843123, 0.05931804, 0.03774492, -0.03016214, 0.0549344 , + -0.23227729, -0.2172487 , -0.10547152, -0.08018271, -0.07300715, + -0.0770617 , -0.07552639]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]]), square_terms=array([[[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 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fval=0.18834408422290103, rho=-0.29383208425185714, accepted=False, new_indices=array([], dtype=int32), old_indices_used=array([ 0, 1, 2, 3, 4, 5, 7, 8, 9, 10, 12, 13]), old_indices_discarded=array([ 6, 11]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([5.3013976 , 0.35179043, 0.92170005]), radius=0.1325349400856993, bounds=Bounds(lower=array([1.1 , 0.01, 0.5 ]), upper=array([20. , 0.99, 1.1 ]))), model_indices=array([ 0, 1, 2, 3, 4, 5, 7, 8, 10, 12, 13, 14]), model=ScalarModel(intercept=6.9052436115388875, linear_terms=array([-0.69117403, 7.16500457, 9.13260536]), square_terms=array([[ 0.03812681, -0.36969498, -0.4746088 ], + [-0.36969498, 3.7854496 , 4.79829205], + [-0.4746088 , 4.79829205, 6.13906768]]), scale=0.1325349400856993, shift=array([5.3013976 , 0.35179043, 0.92170005])), vector_model=VectorModel(intercepts=array([ 0.05267501, 0.10545582, 0.09377041, 0.09722369, 0.08350715, + 0.06843123, 0.05931804, 0.03774492, -0.03016214, 0.0549344 , + -0.23227729, -0.2172487 , -0.10547152, -0.08018271, -0.07300715, + -0.0770617 , -0.07552639]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]]), square_terms=array([[[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 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upper=array([20. , 0.99, 1.1 ]))), model_indices=array([ 0, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27]), model=ScalarModel(intercept=0.16542657032258398, linear_terms=array([0.01630779, 0.01475797, 0.02073112]), square_terms=array([[ 0.05951927, -0.12255125, -0.23582986], + [-0.12255125, 0.26987927, 0.50459186], + [-0.23582986, 0.50459186, 0.96563619]]), scale=0.06626747004284965, shift=array([5.3013976 , 0.35179043, 0.92170005])), vector_model=VectorModel(intercepts=array([ 0.05267501, 0.10545582, 0.09377041, 0.09722369, 0.08350715, + 0.06843123, 0.05931804, 0.03774492, -0.03016214, 0.0549344 , + -0.23227729, -0.2172487 , -0.10547152, -0.08018271, -0.07300715, + -0.0770617 , -0.07552639]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 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candidate_index=28, candidate_x=array([5.23292383, 0.33864579, 0.91062871]), index=0, x=array([5.3013976 , 0.35179043, 0.92170005]), fval=0.18834408422290103, rho=-4.217700932825573, accepted=False, new_indices=array([16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27]), old_indices_used=array([ 0, 14, 15]), old_indices_discarded=array([], dtype=int32), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([5.3013976 , 0.35179043, 0.92170005]), radius=0.033133735021424825, bounds=Bounds(lower=array([1.1 , 0.01, 0.5 ]), upper=array([20. , 0.99, 1.1 ]))), model_indices=array([ 0, 16, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27]), model=ScalarModel(intercept=0.16782671230459395, linear_terms=array([ 0.0009187 , -0.00784055, -0.02621131]), square_terms=array([[4.57181704e-05, 1.25022351e-03, 2.32119020e-03], + [1.25022351e-03, 9.27555996e-02, 1.94331965e-01], + [2.32119020e-03, 1.94331965e-01, 4.14037852e-01]]), scale=0.033133735021424825, shift=array([5.3013976 , 0.35179043, 0.92170005])), vector_model=VectorModel(intercepts=array([ 0.05267501, 0.10545582, 0.09377041, 0.09722369, 0.08350715, + 0.06843123, 0.05931804, 0.03774492, -0.03016214, 0.0549344 , + -0.23227729, -0.2172487 , -0.10547152, -0.08018271, -0.07300715, + -0.0770617 , -0.07552639]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]]), square_terms=array([[[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + 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relative_step_length=1.000149803912295, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([5.29121744, 0.32407875, 0.9367533 ]), radius=0.06626747004284965, bounds=Bounds(lower=array([1.1 , 0.01, 0.5 ]), upper=array([20. , 0.99, 1.1 ]))), model_indices=array([ 0, 17, 18, 20, 21, 22, 24, 25, 26, 27, 28, 29]), model=ScalarModel(intercept=0.16770628802381632, linear_terms=array([-0.00491028, -0.01260532, -0.02110318]), square_terms=array([[1.33508452e-03, 2.20746795e-02, 4.37252047e-02], + [2.20746795e-02, 3.94713894e-01, 7.95682111e-01], + [4.37252047e-02, 7.95682111e-01, 1.63156707e+00]]), scale=0.06626747004284965, shift=array([5.29121744, 0.32407875, 0.9367533 ])), vector_model=VectorModel(intercepts=array([ 0.05267501, 0.10545582, 0.09377041, 0.09722369, 0.08350715, + 0.06843123, 0.05931804, 0.03774492, -0.03016214, 0.0549344 , + -0.23227729, -0.2172487 , -0.10547152, -0.08018271, -0.07300715, + -0.0770617 , -0.07552639]), linear_terms=array([[0., 0., 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linear_terms=array([ 0.00059146, -0.004534 , -0.01522606]), square_terms=array([[3.03577735e-05, 5.05858062e-04, 7.12748102e-04], + [5.05858062e-04, 9.30360296e-02, 1.93666384e-01], + [7.12748102e-04, 1.93666384e-01, 4.10425108e-01]]), scale=0.033133735021424825, shift=array([5.29121744, 0.32407875, 0.9367533 ])), vector_model=VectorModel(intercepts=array([ 0.05267501, 0.10545582, 0.09377041, 0.09722369, 0.08350715, + 0.06843123, 0.05931804, 0.03774492, -0.03016214, 0.0549344 , + -0.23227729, -0.2172487 , -0.10547152, -0.08018271, -0.07300715, + -0.0770617 , -0.07552639]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]]), square_terms=array([[[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + 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fval=0.1799906266171576, rho=1.161952729888368, accepted=True, new_indices=array([], dtype=int32), old_indices_used=array([ 0, 17, 18, 20, 21, 24, 25, 26, 27, 28, 29, 30]), old_indices_discarded=array([15, 16, 19, 22, 23]), step_length=0.03324491388144948, relative_step_length=1.0033554581139965, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([5.27834936, 0.29684139, 0.95081613]), radius=0.06626747004284965, bounds=Bounds(lower=array([1.1 , 0.01, 0.5 ]), upper=array([20. , 0.99, 1.1 ]))), model_indices=array([ 0, 17, 18, 20, 24, 25, 26, 27, 28, 29, 30, 31]), model=ScalarModel(intercept=0.17004437609421225, linear_terms=array([-0.00047394, -0.007927 , -0.01239616]), square_terms=array([[3.94062801e-04, 1.07905924e-02, 2.16812211e-02], + [1.07905924e-02, 3.74115243e-01, 7.88602520e-01], + [2.16812211e-02, 7.88602520e-01, 1.69226096e+00]]), scale=0.06626747004284965, shift=array([5.27834936, 0.29684139, 0.95081613])), vector_model=VectorModel(intercepts=array([ 0.05267501, 0.10545582, 0.09377041, 0.09722369, 0.08350715, + 0.06843123, 0.05931804, 0.03774492, -0.03016214, 0.0549344 , + -0.23227729, -0.2172487 , -0.10547152, -0.08018271, -0.07300715, + -0.0770617 , -0.07552639]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]]), square_terms=array([[[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 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State(trustregion=Region(center=array([5.27834936, 0.29684139, 0.95081613]), radius=0.033133735021424825, bounds=Bounds(lower=array([1.1 , 0.01, 0.5 ]), upper=array([20. , 0.99, 1.1 ]))), model_indices=array([ 0, 17, 18, 20, 24, 25, 26, 28, 29, 30, 31, 32]), model=ScalarModel(intercept=0.1684737651459072, linear_terms=array([0.00169024, 0.00402826, 0.00597484]), square_terms=array([[ 4.51971473e-04, -5.93887978e-03, -1.50514931e-02], + [-5.93887978e-03, 9.28119628e-02, 2.24673825e-01], + [-1.50514931e-02, 2.24673825e-01, 5.53588350e-01]]), scale=0.033133735021424825, shift=array([5.27834936, 0.29684139, 0.95081613])), vector_model=VectorModel(intercepts=array([ 0.05267501, 0.10545582, 0.09377041, 0.09722369, 0.08350715, + 0.06843123, 0.05931804, 0.03774492, -0.03016214, 0.0549344 , + -0.23227729, -0.2172487 , -0.10547152, -0.08018271, -0.07300715, + -0.0770617 , -0.07552639]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 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bounds=Bounds(lower=array([1.1 , 0.01, 0.5 ]), upper=array([20. , 0.99, 1.1 ]))), model_indices=array([ 0, 17, 18, 28, 29, 34, 36, 37, 39, 40, 42, 43]), model=ScalarModel(intercept=0.17500252339842898, linear_terms=array([0.00143805, 0.00318419, 0.00584766]), square_terms=array([[ 2.32402708e-04, -4.32320857e-03, -9.89988047e-03], + [-4.32320857e-03, 1.00521560e-01, 2.19588637e-01], + [-9.89988047e-03, 2.19588637e-01, 4.87595223e-01]]), scale=0.033133735021424825, shift=array([5.25969725, 0.34546622, 0.93220909])), vector_model=VectorModel(intercepts=array([ 0.05267501, 0.10545582, 0.09377041, 0.09722369, 0.08350715, + 0.06843123, 0.05931804, 0.03774492, -0.03016214, 0.0549344 , + -0.23227729, -0.2172487 , -0.10547152, -0.08018271, -0.07300715, + -0.0770617 , -0.07552639]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + 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scale=0.5301397603427972, shift=array([5.3013976 , 0.35179043, 0.92170005])), candidate_index=45, candidate_x=array([5.22598818, 0.34124333, 0.9330266 ]), index=43, x=array([5.25969725, 0.34546622, 0.93220909]), fval=0.17587143240730305, rho=-0.04773487920840637, accepted=False, new_indices=array([], dtype=int32), old_indices_used=array([ 0, 17, 18, 28, 29, 34, 36, 37, 39, 40, 42, 43]), old_indices_discarded=array([15, 16, 19, 20, 21, 22, 23, 24, 25, 26, 27, 30, 31, 32, 33, 35, 38, + 41, 44]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([5.25969725, 0.34546622, 0.93220909]), radius=0.016566867510712412, bounds=Bounds(lower=array([1.1 , 0.01, 0.5 ]), upper=array([20. , 0.99, 1.1 ]))), model_indices=array([ 0, 17, 18, 28, 29, 34, 36, 37, 39, 42, 43, 45]), model=ScalarModel(intercept=0.1751974222542535, linear_terms=array([0.00059828, 0.00104291, 0.00174938]), square_terms=array([[ 2.32452897e-05, 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old_indices_used=array([ 0, 17, 18, 28, 29, 34, 36, 37, 39, 42, 43, 45]), old_indices_discarded=array([19, 21, 24, 25, 26, 31, 33, 35, 38, 40, 41, 44]), step_length=0.017343162853838502, relative_step_length=1.0468583057493592, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([5.24271155, 0.34212944, 0.93327545]), radius=0.033133735021424825, bounds=Bounds(lower=array([1.1 , 0.01, 0.5 ]), upper=array([20. , 0.99, 1.1 ]))), model_indices=array([17, 18, 28, 29, 34, 36, 37, 42, 43, 44, 45, 46]), model=ScalarModel(intercept=0.1748745633782247, linear_terms=array([ 0.00075962, -0.00172199, -0.00445794]), square_terms=array([[ 3.54305914e-05, -8.55387782e-04, -2.21218821e-03], + [-8.55387782e-04, 1.02537349e-01, 2.22590300e-01], + [-2.21218821e-03, 2.22590300e-01, 4.91024973e-01]]), scale=0.033133735021424825, shift=array([5.24271155, 0.34212944, 0.93327545])), vector_model=VectorModel(intercepts=array([ 0.05267501, 0.10545582, 0.09377041, 0.09722369, 0.08350715, + 0.06843123, 0.05931804, 0.03774492, -0.03016214, 0.0549344 , + -0.23227729, -0.2172487 , -0.10547152, -0.08018271, -0.07300715, + -0.0770617 , -0.07552639]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]]), square_terms=array([[[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], 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State(trustregion=Region(center=array([5.20917798, 0.34014316, 0.93432412]), radius=0.06626747004284965, bounds=Bounds(lower=array([1.1 , 0.01, 0.5 ]), upper=array([20. , 0.99, 1.1 ]))), model_indices=array([17, 18, 21, 28, 33, 36, 37, 43, 44, 45, 46, 47]), model=ScalarModel(intercept=0.17493421876270587, linear_terms=array([-0.00156353, -0.00842537, -0.01190066]), square_terms=array([[0.00281928, 0.03109626, 0.0629877 ], + [0.03109626, 0.34695273, 0.70455773], + [0.0629877 , 0.70455773, 1.45975502]]), scale=0.06626747004284965, shift=array([5.20917798, 0.34014316, 0.93432412])), vector_model=VectorModel(intercepts=array([ 0.05267501, 0.10545582, 0.09377041, 0.09722369, 0.08350715, + 0.06843123, 0.05931804, 0.03774492, -0.03016214, 0.0549344 , + -0.23227729, -0.2172487 , -0.10547152, -0.08018271, -0.07300715, + -0.0770617 , -0.07552639]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + 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[[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]]]), scale=0.5301397603427972, shift=array([5.3013976 , 0.35179043, 0.92170005])), candidate_index=48, candidate_x=array([5.27749183, 0.35670252, 0.9239295 ]), index=47, x=array([5.20917798, 0.34014316, 0.93432412]), fval=0.1752985258377397, rho=-2.6662319197648348, accepted=False, new_indices=array([], dtype=int32), old_indices_used=array([17, 18, 21, 28, 33, 36, 37, 43, 44, 45, 46, 47]), old_indices_discarded=array([ 0, 14, 15, 16, 19, 20, 22, 23, 24, 25, 26, 27, 29, 30, 31, 32, 34, + 35, 38, 39, 40, 41, 42]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([5.20917798, 0.34014316, 0.93432412]), radius=0.033133735021424825, bounds=Bounds(lower=array([1.1 , 0.01, 0.5 ]), upper=array([20. , 0.99, 1.1 ]))), model_indices=array([17, 18, 28, 33, 36, 37, 43, 44, 45, 46, 47, 48]), model=ScalarModel(intercept=0.17451083881940163, linear_terms=array([ 0.00045657, 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rho=0.563659202220171, accepted=True, new_indices=array([], dtype=int32), old_indices_used=array([17, 18, 28, 33, 36, 37, 43, 44, 45, 46, 47, 48]), old_indices_discarded=array([ 0, 15, 16, 19, 20, 21, 22, 23, 24, 25, 26, 27, 29, 30, 31, 32, 34, + 35, 38, 39, 40, 41, 42]), step_length=0.033441763641147204, relative_step_length=1.0092965257168625, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([5.17665032, 0.34743911, 0.93166475]), radius=0.06626747004284965, bounds=Bounds(lower=array([1.1 , 0.01, 0.5 ]), upper=array([20. , 0.99, 1.1 ]))), model_indices=array([17, 18, 21, 28, 33, 36, 43, 44, 45, 46, 47, 49]), model=ScalarModel(intercept=0.17564926316541823, linear_terms=array([-0.00274284, -0.01384935, -0.02471199]), square_terms=array([[0.0035693 , 0.03481689, 0.07133062], + [0.03481689, 0.34263536, 0.7019492 ], + [0.07133062, 0.7019492 , 1.46757845]]), scale=0.06626747004284965, shift=array([5.17665032, 0.34743911, 0.93166475])), vector_model=VectorModel(intercepts=array([ 0.05267501, 0.10545582, 0.09377041, 0.09722369, 0.08350715, + 0.06843123, 0.05931804, 0.03774492, -0.03016214, 0.0549344 , + -0.23227729, -0.2172487 , -0.10547152, -0.08018271, -0.07300715, + -0.0770617 , -0.07552639]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]]), square_terms=array([[[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 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relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([5.17665032, 0.34743911, 0.93166475]), radius=0.033133735021424825, bounds=Bounds(lower=array([1.1 , 0.01, 0.5 ]), upper=array([20. , 0.99, 1.1 ]))), model_indices=array([17, 18, 21, 28, 36, 43, 44, 45, 46, 47, 49, 50]), model=ScalarModel(intercept=0.1762502933918212, linear_terms=array([-0.00155691, -0.00561339, -0.01308175]), square_terms=array([[0.00079825, 0.00800458, 0.01674233], + [0.00800458, 0.08167794, 0.17110631], + [0.01674233, 0.17110631, 0.36563479]]), scale=0.033133735021424825, shift=array([5.17665032, 0.34743911, 0.93166475])), vector_model=VectorModel(intercepts=array([ 0.05267501, 0.10545582, 0.09377041, 0.09722369, 0.08350715, + 0.06843123, 0.05931804, 0.03774492, -0.03016214, 0.0549344 , + -0.23227729, -0.2172487 , -0.10547152, -0.08018271, -0.07300715, + -0.0770617 , -0.07552639]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 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linear_terms=array([0.00019334, 0.00068168, 0.002236 ]), square_terms=array([[6.30086486e-06, 1.31120182e-04, 1.92914840e-04], + [1.31120182e-04, 2.30933740e-02, 4.65644949e-02], + [1.92914840e-04, 4.65644949e-02, 9.56283946e-02]]), scale=0.016566867510712412, shift=array([5.17665032, 0.34743911, 0.93166475])), vector_model=VectorModel(intercepts=array([ 0.05267501, 0.10545582, 0.09377041, 0.09722369, 0.08350715, + 0.06843123, 0.05931804, 0.03774492, -0.03016214, 0.0549344 , + -0.23227729, -0.2172487 , -0.10547152, -0.08018271, -0.07300715, + -0.0770617 , -0.07552639]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]]), square_terms=array([[[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 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fval=0.1749771962623699, rho=-0.48116939358057886, accepted=False, new_indices=array([], dtype=int32), old_indices_used=array([18, 28, 36, 44, 45, 46, 47, 49, 50, 51]), old_indices_discarded=array([], dtype=int32), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([5.17665032, 0.34743911, 0.93166475]), radius=0.008283433755356206, bounds=Bounds(lower=array([1.1 , 0.01, 0.5 ]), upper=array([20. , 0.99, 1.1 ]))), model_indices=array([44, 47, 49, 51, 52]), model=ScalarModel(intercept=0.17496972296461294, linear_terms=array([ 6.97863248e-05, -8.21475281e-05, -4.56887150e-04]), square_terms=array([[1.84361126e-06, 2.04013067e-05, 2.19735979e-05], + [2.04013067e-05, 5.26300747e-03, 1.10824804e-02], + [2.19735979e-05, 1.10824804e-02, 2.38107760e-02]]), scale=0.008283433755356206, shift=array([5.17665032, 0.34743911, 0.93166475])), vector_model=VectorModel(intercepts=array([ 0.05267501, 0.10545582, 0.09377041, 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radius=0.016566867510712412, bounds=Bounds(lower=array([1.1 , 0.01, 0.5 ]), upper=array([20. , 0.99, 1.1 ]))), model_indices=array([18, 28, 36, 44, 45, 46, 47, 49, 50, 51, 52, 53]), model=ScalarModel(intercept=0.1749826973068216, linear_terms=array([0.0001074 , 0.00038707, 0.00171986]), square_terms=array([[7.58231429e-06, 2.29836559e-04, 3.96776253e-04], + [2.29836559e-04, 2.29465979e-02, 4.65350783e-02], + [3.96776253e-04, 4.65350783e-02, 9.61235255e-02]]), scale=0.016566867510712412, shift=array([5.17030197, 0.34249393, 0.93412279])), vector_model=VectorModel(intercepts=array([ 0.05267501, 0.10545582, 0.09377041, 0.09722369, 0.08350715, + 0.06843123, 0.05931804, 0.03774492, -0.03016214, 0.0549344 , + -0.23227729, -0.2172487 , -0.10547152, -0.08018271, -0.07300715, + -0.0770617 , -0.07552639]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 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square_terms=array([[6.93968654e-06, 4.93334629e-05, 2.09902799e-05], + [4.93334629e-05, 2.19685008e-02, 4.66549901e-02], + [2.09902799e-05, 4.66549901e-02, 1.00998973e-01]]), scale=0.016566867510712412, shift=array([5.1369295 , 0.33809681, 0.93594391])), vector_model=VectorModel(intercepts=array([ 0.05267501, 0.10545582, 0.09377041, 0.09722369, 0.08350715, + 0.06843123, 0.05931804, 0.03774492, -0.03016214, 0.0549344 , + -0.23227729, -0.2172487 , -0.10547152, -0.08018271, -0.07300715, + -0.0770617 , -0.07552639]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]]), square_terms=array([[[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 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new_indices=array([], dtype=int32), old_indices_used=array([44, 47, 49, 51, 52, 53, 54, 55, 56, 57, 58, 59]), old_indices_discarded=array([], dtype=int32), step_length=0.01658851744339946, relative_step_length=1.0013068211400284, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([5.12036855, 0.33903597, 0.93576554]), radius=0.033133735021424825, bounds=Bounds(lower=array([1.1 , 0.01, 0.5 ]), upper=array([20. , 0.99, 1.1 ]))), model_indices=array([44, 49, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60]), model=ScalarModel(intercept=0.17429973881169664, linear_terms=array([ 2.70298754e-04, -3.09106006e-05, 1.40978604e-06]), square_terms=array([[2.77478710e-05, 2.26332451e-04, 1.44291033e-04], + [2.26332451e-04, 8.82227523e-02, 1.87432209e-01], + [1.44291033e-04, 1.87432209e-01, 4.05886882e-01]]), scale=0.033133735021424825, shift=array([5.12036855, 0.33903597, 0.93576554])), vector_model=VectorModel(intercepts=array([ 0.05267501, 0.10545582, 0.09377041, 0.09722369, 0.08350715, + 0.06843123, 0.05931804, 0.03774492, -0.03016214, 0.0549344 , + -0.23227729, -0.2172487 , -0.10547152, -0.08018271, -0.07300715, + -0.0770617 , -0.07552639]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]]), square_terms=array([[[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + 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State(trustregion=Region(center=array([5.08741985, 0.34221541, 0.93430985]), radius=0.06626747004284965, bounds=Bounds(lower=array([1.1 , 0.01, 0.5 ]), upper=array([20. , 0.99, 1.1 ]))), model_indices=array([44, 49, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61]), model=ScalarModel(intercept=0.17399871546423445, linear_terms=array([5.54960169e-04, 2.77020491e-05, 2.46039514e-04]), square_terms=array([[1.12760714e-04, 1.09146716e-03, 9.82283047e-04], + [1.09146716e-03, 3.54762285e-01, 7.53825721e-01], + [9.82283047e-04, 7.53825721e-01, 1.63251500e+00]]), scale=0.06626747004284965, shift=array([5.08741985, 0.34221541, 0.93430985])), vector_model=VectorModel(intercepts=array([ 0.05267501, 0.10545582, 0.09377041, 0.09722369, 0.08350715, + 0.06843123, 0.05931804, 0.03774492, -0.03016214, 0.0549344 , + -0.23227729, -0.2172487 , -0.10547152, -0.08018271, -0.07300715, + -0.0770617 , -0.07552639]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 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56, 57, 58, 59, 60, 61, 62]), model=ScalarModel(intercept=0.17340700850452878, linear_terms=array([0.00109183, 0.00472696, 0.00984298]), square_terms=array([[4.56127079e-04, 4.44510297e-03, 4.16551232e-03], + [4.44510297e-03, 1.53012536e+00, 3.24711918e+00], + [4.16551232e-03, 3.24711918e+00, 7.01257022e+00]]), scale=0.1325349400856993, shift=array([5.02154349, 0.34875659, 0.93132 ])), vector_model=VectorModel(intercepts=array([ 0.05267501, 0.10545582, 0.09377041, 0.09722369, 0.08350715, + 0.06843123, 0.05931804, 0.03774492, -0.03016214, 0.0549344 , + -0.23227729, -0.2172487 , -0.10547152, -0.08018271, -0.07300715, + -0.0770617 , -0.07552639]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]]), square_terms=array([[[0., 0., 0.], + [0., 0., 0.], + 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0.92601999]), index=63, x=array([4.88958301, 0.35997157, 0.92601999]), fval=0.17321977271534034, rho=0.16046349138702412, accepted=True, new_indices=array([], dtype=int32), old_indices_used=array([49, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62]), old_indices_discarded=array([ 0, 1, 5, 7, 8, 10, 11, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, + 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, + 41, 42, 43, 44, 45, 46, 47, 48, 50, 51]), step_length=0.13254219715533885, relative_step_length=1.0000547558978399, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([4.88958301, 0.35997157, 0.92601999]), radius=0.2650698801713986, bounds=Bounds(lower=array([1.1 , 0.01, 0.5 ]), upper=array([20. , 0.99, 1.1 ]))), model_indices=array([ 8, 52, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63]), model=ScalarModel(intercept=0.6100711093200124, linear_terms=array([-0.01326482, -4.36274037, -8.18834305]), square_terms=array([[1.44837362e-03, 7.48035154e-02, 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old_indices_used=array([ 8, 52, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63]), old_indices_discarded=array([ 0, 1, 2, 3, 4, 5, 6, 7, 9, 10, 11, 12, 13, 14, 15, 16, 17, + 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, + 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, + 53]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([4.88958301, 0.35997157, 0.92601999]), radius=0.1325349400856993, bounds=Bounds(lower=array([1.1 , 0.01, 0.5 ]), upper=array([20. , 0.99, 1.1 ]))), model_indices=array([ 8, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64]), model=ScalarModel(intercept=0.17454954123079744, linear_terms=array([-5.42519807e-05, -1.01429163e-01, -2.30913425e-01]), square_terms=array([[5.22021113e-04, 2.10949241e-02, 3.90868648e-02], + [2.10949241e-02, 8.25980623e+00, 1.71670369e+01], + [3.90868648e-02, 1.71670369e+01, 3.57832291e+01]]), scale=0.1325349400856993, shift=array([4.88958301, 0.35997157, 0.92601999])), vector_model=VectorModel(intercepts=array([ 0.05267501, 0.10545582, 0.09377041, 0.09722369, 0.08350715, + 0.06843123, 0.05931804, 0.03774492, -0.03016214, 0.0549344 , + -0.23227729, -0.2172487 , -0.10547152, -0.08018271, -0.07300715, + -0.0770617 , -0.07552639]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]]), square_terms=array([[[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 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27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, + 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([4.88958301, 0.35997157, 0.92601999]), radius=0.06626747004284965, bounds=Bounds(lower=array([1.1 , 0.01, 0.5 ]), upper=array([20. , 0.99, 1.1 ]))), model_indices=array([ 8, 54, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65]), model=ScalarModel(intercept=0.17542324482018204, linear_terms=array([-0.00082497, -0.05406882, -0.10601177]), square_terms=array([[1.43516091e-04, 1.15577625e-03, 8.44733923e-04], + [1.15577625e-03, 1.97661939e+00, 4.19325940e+00], + [8.44733923e-04, 4.19325940e+00, 8.92777781e+00]]), scale=0.06626747004284965, shift=array([4.88958301, 0.35997157, 0.92601999])), vector_model=VectorModel(intercepts=array([ 0.05267501, 0.10545582, 0.09377041, 0.09722369, 0.08350715, + 0.06843123, 0.05931804, 0.03774492, -0.03016214, 0.0549344 , + 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candidate_x=array([4.85934517, 0.34730674, 0.93082827]), index=67, x=array([4.85934517, 0.34730674, 0.93082827]), fval=0.17278415445032944, rho=0.24429294106502478, accepted=True, new_indices=array([], dtype=int32), old_indices_used=array([62, 63, 65, 66]), old_indices_discarded=array([], dtype=int32), step_length=0.033133735021424575, relative_step_length=0.9999999999999925, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([4.85934517, 0.34730674, 0.93082827]), radius=0.06626747004284965, bounds=Bounds(lower=array([1.1 , 0.01, 0.5 ]), upper=array([20. , 0.99, 1.1 ]))), model_indices=array([ 8, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67]), model=ScalarModel(intercept=0.17800589377398301, linear_terms=array([-0.00030888, -0.11314456, -0.23802422]), square_terms=array([[ 1.44537530e-04, -2.97382575e-03, -7.90103681e-03], + [-2.97382575e-03, 1.94242721e+00, 4.15401254e+00], + [-7.90103681e-03, 4.15401254e+00, 8.91430260e+00]]), scale=0.06626747004284965, 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relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([4.85934517, 0.34730674, 0.93082827]), radius=0.033133735021424825, bounds=Bounds(lower=array([1.1 , 0.01, 0.5 ]), upper=array([20. , 0.99, 1.1 ]))), model_indices=array([62, 63, 65, 66, 67, 68]), model=ScalarModel(intercept=0.17242592156362221, linear_terms=array([-3.95014403e-05, 7.38523177e-03, 1.66472760e-02]), square_terms=array([[ 3.41520113e-05, -4.66917848e-04, -1.38426097e-03], + [-4.66917848e-04, 2.96431160e-01, 6.38285543e-01], + [-1.38426097e-03, 6.38285543e-01, 1.38203197e+00]]), scale=0.033133735021424825, shift=array([4.85934517, 0.34730674, 0.93082827])), vector_model=VectorModel(intercepts=array([ 0.05267501, 0.10545582, 0.09377041, 0.09722369, 0.08350715, + 0.06843123, 0.05931804, 0.03774492, -0.03016214, 0.0549344 , + -0.23227729, -0.2172487 , -0.10547152, -0.08018271, -0.07300715, + -0.0770617 , -0.07552639]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.], 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square_terms=array([[7.38828522e-06, 1.36373870e-04, 2.09192264e-04], + [1.36373870e-04, 2.30290804e-02, 4.72040978e-02], + [2.09192264e-04, 4.72040978e-02, 9.83617297e-02]]), scale=0.016566867510712412, shift=array([4.85934517, 0.34730674, 0.93082827])), vector_model=VectorModel(intercepts=array([ 0.05267501, 0.10545582, 0.09377041, 0.09722369, 0.08350715, + 0.06843123, 0.05931804, 0.03774492, -0.03016214, 0.0549344 , + -0.23227729, -0.2172487 , -0.10547152, -0.08018271, -0.07300715, + -0.0770617 , -0.07552639]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]]), square_terms=array([[[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 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77, 78, 79, 80, 81, 82, 83]), model=ScalarModel(intercept=0.17275901380787767, linear_terms=array([ 5.13124779e-05, -7.09231772e-04, -1.50668997e-03]), square_terms=array([[ 5.24206101e-07, 2.61469482e-06, -1.23800127e-07], + [ 2.61469482e-06, 1.62536068e-03, 3.42956073e-03], + [-1.23800127e-07, 3.42956073e-03, 7.35873402e-03]]), scale=0.004141716877678103, shift=array([4.85934517, 0.34730674, 0.93082827])), vector_model=VectorModel(intercepts=array([ 0.05267501, 0.10545582, 0.09377041, 0.09722369, 0.08350715, + 0.06843123, 0.05931804, 0.03774492, -0.03016214, 0.0549344 , + -0.23227729, -0.2172487 , -0.10547152, -0.08018271, -0.07300715, + -0.0770617 , -0.07552639]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]]), square_terms=array([[[0., 0., 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x=array([4.84436454, 0.3458171 , 0.93240807]), fval=0.1725720095711579, rho=0.09077331695760522, accepted=True, new_indices=array([], dtype=int32), old_indices_used=array([67, 72, 73, 75, 76, 77, 78, 80, 81, 84, 85, 86]), old_indices_discarded=array([63, 69, 70, 71, 74, 79, 82, 83]), step_length=0.008283749415294117, relative_step_length=1.0000381073775964, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([4.84436454, 0.3458171 , 0.93240807]), radius=0.004141716877678103, bounds=Bounds(lower=array([1.1 , 0.01, 0.5 ]), upper=array([20. , 0.99, 1.1 ]))), model_indices=array([67, 72, 73, 75, 76, 77, 78, 80, 81, 84, 86, 87]), model=ScalarModel(intercept=0.1725764987304485, linear_terms=array([7.05977087e-06, 2.29884404e-05, 1.21152777e-05]), square_terms=array([[5.86956811e-07, 1.16384872e-05, 1.94432612e-05], + [1.16384872e-05, 1.63380924e-03, 3.44140991e-03], + [1.94432612e-05, 3.44140991e-03, 7.36782486e-03]]), scale=0.004141716877678103, 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n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([4.84436454, 0.3458171 , 0.93240807]), radius=0.0020708584388390515, bounds=Bounds(lower=array([1.1 , 0.01, 0.5 ]), upper=array([20. , 0.99, 1.1 ]))), model_indices=array([ 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, + 99, 100]), model=ScalarModel(intercept=0.17258738194234413, linear_terms=array([ 3.33838120e-06, -1.97151771e-08, 5.27903701e-06]), square_terms=array([[ 1.36507244e-07, 3.44142448e-07, -7.87178649e-07], + [ 3.44142448e-07, 4.10506238e-04, 8.69151483e-04], + [-7.87178649e-07, 8.69151483e-04, 1.87129773e-03]]), scale=0.0020708584388390515, shift=array([4.84436454, 0.3458171 , 0.93240807])), vector_model=VectorModel(intercepts=array([ 0.05267501, 0.10545582, 0.09377041, 0.09722369, 0.08350715, + 0.06843123, 0.05931804, 0.03774492, -0.03016214, 0.0549344 , + -0.23227729, -0.2172487 , -0.10547152, -0.08018271, -0.07300715, + -0.0770617 , -0.07552639]), linear_terms=array([[0., 0., 0.], 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0.93232094]), fval=0.1725670999317009, rho=0.19934711308216232, accepted=True, new_indices=array([], dtype=int32), old_indices_used=array([87, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99]), old_indices_discarded=array([ 88, 100, 101]), step_length=0.001038810734087629, relative_step_length=1.0032658095837772, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([4.84334274, 0.34598281, 0.93232094]), radius=0.0020708584388390515, bounds=Bounds(lower=array([1.1 , 0.01, 0.5 ]), upper=array([20. , 0.99, 1.1 ]))), model_indices=array([ 87, 90, 92, 93, 94, 95, 97, 98, 99, 100, 101, 102]), model=ScalarModel(intercept=0.17258247058638926, linear_terms=array([-2.68495297e-05, -2.10095588e-06, -2.07300030e-05]), square_terms=array([[1.91163962e-07, 3.32105210e-06, 5.86912190e-06], + [3.32105210e-06, 4.07207519e-04, 8.64705423e-04], + [5.86912190e-06, 8.64705423e-04, 1.86822036e-03]]), scale=0.0020708584388390515, shift=array([4.84334274, 0.34598281, 0.93232094])), vector_model=VectorModel(intercepts=array([ 0.05267501, 0.10545582, 0.09377041, 0.09722369, 0.08350715, + 0.06843123, 0.05931804, 0.03774492, -0.03016214, 0.0549344 , + -0.23227729, -0.2172487 , -0.10547152, -0.08018271, -0.07300715, + -0.0770617 , -0.07552639]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]]), square_terms=array([[[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 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State(trustregion=Region(center=array([4.84334274, 0.34598281, 0.93232094]), radius=0.0010354292194195258, bounds=Bounds(lower=array([1.1 , 0.01, 0.5 ]), upper=array([20. , 0.99, 1.1 ]))), model_indices=array([ 87, 92, 93, 94, 95, 97, 98, 99, 100, 101, 102, 103]), model=ScalarModel(intercept=0.17258275627245578, linear_terms=array([-1.33291997e-05, -4.54612468e-06, -9.95213586e-06]), square_terms=array([[4.81840647e-08, 1.07426513e-06, 1.94899377e-06], + [1.07426513e-06, 1.02515718e-04, 2.17008681e-04], + [1.94899377e-06, 2.17008681e-04, 4.67269204e-04]]), scale=0.0010354292194195258, shift=array([4.84334274, 0.34598281, 0.93232094])), vector_model=VectorModel(intercepts=array([ 0.05267501, 0.10545582, 0.09377041, 0.09722369, 0.08350715, + 0.06843123, 0.05931804, 0.03774492, -0.03016214, 0.0549344 , + -0.23227729, -0.2172487 , -0.10547152, -0.08018271, -0.07300715, + -0.0770617 , -0.07552639]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 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linear_terms=array([ 2.41019710e-05, -4.48842471e-06, -4.27936350e-05]), square_terms=array([[1.56434406e-07, 3.33318421e-06, 6.03774428e-06], + [3.33318421e-06, 4.15831904e-04, 8.74354178e-04], + [6.03774428e-06, 8.74354178e-04, 1.86706420e-03]]), scale=0.0020708584388390515, shift=array([4.84438244, 0.34597441, 0.93234197])), vector_model=VectorModel(intercepts=array([ 0.05267501, 0.10545582, 0.09377041, 0.09722369, 0.08350715, + 0.06843123, 0.05931804, 0.03774492, -0.03016214, 0.0549344 , + -0.23227729, -0.2172487 , -0.10547152, -0.08018271, -0.07300715, + -0.0770617 , -0.07552639]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]]), square_terms=array([[[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 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0.93234197]), fval=0.1725502344785951, rho=-1.01272054792213, accepted=False, new_indices=array([], dtype=int32), old_indices_used=array([ 87, 89, 90, 92, 96, 97, 98, 100, 101, 102, 103, 104]), old_indices_discarded=array([86, 88, 91, 93, 94, 95, 99]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([4.84438244, 0.34597441, 0.93234197]), radius=0.0010354292194195258, bounds=Bounds(lower=array([1.1 , 0.01, 0.5 ]), upper=array([20. , 0.99, 1.1 ]))), model_indices=array([ 87, 90, 92, 96, 97, 98, 100, 101, 102, 103, 104, 105]), model=ScalarModel(intercept=0.17258372705737116, linear_terms=array([ 4.09478695e-06, -3.55795689e-06, -4.27096698e-05]), square_terms=array([[3.35585618e-08, 2.15061082e-07, 1.37358651e-07], + [2.15061082e-07, 1.03219001e-04, 2.16664028e-04], + [1.37358651e-07, 2.16664028e-04, 4.61793255e-04]]), scale=0.0010354292194195258, shift=array([4.84438244, 0.34597441, 0.93234197])), vector_model=VectorModel(intercepts=array([ 0.05267501, 0.10545582, 0.09377041, 0.09722369, 0.08350715, + 0.06843123, 0.05931804, 0.03774492, -0.03016214, 0.0549344 , + -0.23227729, -0.2172487 , -0.10547152, -0.08018271, -0.07300715, + -0.0770617 , -0.07552639]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]]), square_terms=array([[[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 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n_evals_acceptance=1), State(trustregion=Region(center=array([4.84438244, 0.34597441, 0.93234197]), radius=0.0005177146097097629, bounds=Bounds(lower=array([1.1 , 0.01, 0.5 ]), upper=array([20. , 0.99, 1.1 ]))), model_indices=array([ 87, 90, 92, 96, 97, 98, 100, 102, 103, 104, 105, 106]), model=ScalarModel(intercept=0.1725840937366451, linear_terms=array([ 3.96813424e-06, -3.12252958e-06, -1.95411424e-05]), square_terms=array([[ 8.35946962e-09, 7.31232339e-09, -6.36196010e-08], + [ 7.31232339e-09, 2.56886777e-05, 5.40554793e-05], + [-6.36196010e-08, 5.40554793e-05, 1.15524825e-04]]), scale=0.0005177146097097629, shift=array([4.84438244, 0.34597441, 0.93234197])), vector_model=VectorModel(intercepts=array([ 0.05267501, 0.10545582, 0.09377041, 0.09722369, 0.08350715, + 0.06843123, 0.05931804, 0.03774492, -0.03016214, 0.0549344 , + -0.23227729, -0.2172487 , -0.10547152, -0.08018271, -0.07300715, + -0.0770617 , -0.07552639]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.], + [0., 0., 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linear_terms=array([-1.36437344e-07, -4.51532084e-05, -6.73471361e-05]), square_terms=array([[2.54545043e-09, 5.61432011e-08, 9.86416386e-08], + [5.61432011e-08, 7.19930049e-06, 1.53720182e-05], + [9.86416386e-08, 1.53720182e-05, 3.34119316e-05]]), scale=0.00025885730485488144, shift=array([4.84438244, 0.34597441, 0.93234197])), vector_model=VectorModel(intercepts=array([ 0.05267501, 0.10545582, 0.09377041, 0.09722369, 0.08350715, + 0.06843123, 0.05931804, 0.03774492, -0.03016214, 0.0549344 , + -0.23227729, -0.2172487 , -0.10547152, -0.08018271, -0.07300715, + -0.0770617 , -0.07552639]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]]), square_terms=array([[[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 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0.93234197]), fval=0.1725502344785951, rho=-0.576824163789822, accepted=False, new_indices=array([], dtype=int32), old_indices_used=array([ 87, 102, 103, 104, 106, 107]), old_indices_discarded=array([], dtype=int32), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([4.84438244, 0.34597441, 0.93234197]), radius=0.00012942865242744072, bounds=Bounds(lower=array([1.1 , 0.01, 0.5 ]), upper=array([20. , 0.99, 1.1 ]))), model_indices=array([ 87, 104, 107, 108]), model=ScalarModel(intercept=0.1725502344785952, linear_terms=array([3.44999292e-05, 1.62188504e-06, 5.57565527e-05]), square_terms=array([[ 2.22263556e-08, -7.54974445e-08, -1.28829298e-07], + [-7.54974445e-08, 1.63871850e-06, 3.49355539e-06], + [-1.28829298e-07, 3.49355539e-06, 7.66893361e-06]]), scale=0.00012942865242744072, shift=array([4.84438244, 0.34597441, 0.93234197])), vector_model=VectorModel(intercepts=array([ 0.05267501, 0.10545582, 0.09377041, 0.09722369, 0.08350715, + 0.06843123, 0.05931804, 0.03774492, -0.03016214, 0.0549344 , + -0.23227729, -0.2172487 , -0.10547152, -0.08018271, -0.07300715, + -0.0770617 , -0.07552639]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]]), square_terms=array([[[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + 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bounds=Bounds(lower=array([1.1 , 0.01, 0.5 ]), upper=array([20. , 0.99, 1.1 ]))), model_indices=array([ 87, 104, 108, 109]), model=ScalarModel(intercept=0.17255023447859502, linear_terms=array([-3.73002754e-05, -6.01751396e-06, -3.13820183e-06]), square_terms=array([[ 3.36899890e-08, -2.15013771e-08, -5.98360204e-08], + [-2.15013771e-08, 4.08581107e-07, 8.66434307e-07], + [-5.98360204e-08, 8.66434307e-07, 1.87671962e-06]]), scale=6.471432621372036e-05, shift=array([4.84438244, 0.34597441, 0.93234197])), vector_model=VectorModel(intercepts=array([ 0.05267501, 0.10545582, 0.09377041, 0.09722369, 0.08350715, + 0.06843123, 0.05931804, 0.03774492, -0.03016214, 0.0549344 , + -0.23227729, -0.2172487 , -0.10547152, -0.08018271, -0.07300715, + -0.0770617 , -0.07552639]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + 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shift=array([5.3013976 , 0.35179043, 0.92170005])), candidate_index=110, candidate_x=array([4.84444765, 0.34598474, 0.93234706]), index=110, x=array([4.84444765, 0.34598474, 0.93234706]), fval=0.1725478271950989, rho=0.06209485714691327, accepted=True, new_indices=array([], dtype=int32), old_indices_used=array([ 87, 104, 108, 109]), old_indices_discarded=array([], dtype=int32), step_length=6.622807355566686e-05, relative_step_length=1.0233912246408519, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([4.84444765, 0.34598474, 0.93234706]), radius=3.235716310686018e-05, bounds=Bounds(lower=array([1.1 , 0.01, 0.5 ]), upper=array([20. , 0.99, 1.1 ]))), model_indices=array([104, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 120, 121, + 122]), model=ScalarModel(intercept=0.17255303967876678, linear_terms=array([ 1.01217401e-06, -2.89498110e-06, -1.61527209e-06]), square_terms=array([[3.79200597e-11, 4.15805463e-10, 6.13267869e-10], + [4.15805463e-10, 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old_indices_used=array([104, 110]), old_indices_discarded=array([], dtype=int32), step_length=3.2357163106865805e-05, relative_step_length=1.0000000000001739, n_evals_per_point=1, n_evals_acceptance=1)], 'tranquilo_history': History for least_squares function with 124 entries., 'multistart_info': {'start_parameters': [array([5.33878077, 0.17065529, 1. ]), array([4.4728541 , 0.45753029, 0.84720369]), array([5.3013976 , 0.35179043, 0.92170005])], 'local_optima': [{'solution_x': array([5.21248464, 0.33676407, 0.93666301]), 'solution_criterion': 0.17512192544656371, 'states': [State(trustregion=Region(center=array([5.33878077, 0.17065529, 1. ]), radius=0.5338780774481048, bounds=Bounds(lower=array([1.1 , 0.01, 0.5 ]), upper=array([20. , 0.99, 1.1 ]))), model_indices=[0], model=ScalarModel(intercept=0.24222229239256646, linear_terms=array([0., 0., 0.]), square_terms=array([[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]]), scale=0.5338780774481048, shift=array([5.33878077, 0.17065529, 1. ])), 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State(trustregion=Region(center=array([5.33878077, 0.17065529, 1. ]), radius=0.1334695193620262, bounds=Bounds(lower=array([1.1 , 0.01, 0.5 ]), upper=array([20. , 0.99, 1.1 ]))), model_indices=array([ 0, 1, 2, 3, 4, 5, 6, 8, 10, 12, 13, 14]), model=ScalarModel(intercept=1.8208078161679868, linear_terms=array([-0.19004525, 2.49267386, 3.44430864]), square_terms=array([[ 0.01155517, -0.14231501, -0.19433776], + [-0.14231501, 1.88777533, 2.52140739], + [-0.19433776, 2.52140739, 3.42876704]]), scale=array([0.1075759 , 0.1075759 , 0.10378795]), shift=array([5.33878077, 0.17065529, 0.99621205])), vector_model=VectorModel(intercepts=array([ 0.03980461, 0.08715954, 0.08449923, 0.10710153, 0.11905802, + 0.13160042, 0.14768033, 0.15905648, 0.07367938, 0.12505611, + -0.21199057, -0.25057516, -0.05680053, -0.03662718, -0.03009585, + -0.03160325, -0.02367163]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 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x=array([5.30968909, 0.25995847, 0.96850838]), fval=0.18645615650369046, rho=1.932188396931057, accepted=True, new_indices=array([], dtype=int32), old_indices_used=array([ 0, 16, 18, 19, 20, 21, 22, 23, 25, 27, 28, 29]), old_indices_discarded=array([14, 15, 17, 24, 26]), step_length=0.07028379860830133, relative_step_length=1.0531812648198984, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([5.30968909, 0.25995847, 0.96850838]), radius=0.1334695193620262, bounds=Bounds(lower=array([1.1 , 0.01, 0.5 ]), upper=array([20. , 0.99, 1.1 ]))), model_indices=array([ 0, 16, 17, 18, 19, 21, 22, 23, 25, 28, 29, 30]), model=ScalarModel(intercept=0.1877934505138043, linear_terms=array([-0.03082531, -0.06829227, -0.20801109]), square_terms=array([[ 0.02060883, 0.09482843, 0.45039114], + [ 0.09482843, 0.47240082, 2.15885408], + [ 0.45039114, 2.15885408, 10.7559403 ]]), scale=array([0.1075759, 0.1075759, 0.1075759]), shift=array([5.30968909, 0.25995847, 0.96850838])), vector_model=VectorModel(intercepts=array([ 0.03980461, 0.08715954, 0.08449923, 0.10710153, 0.11905802, + 0.13160042, 0.14768033, 0.15905648, 0.07367938, 0.12505611, + -0.21199057, -0.25057516, -0.05680053, -0.03662718, -0.03009585, + -0.03160325, -0.02367163]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]]), square_terms=array([[[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 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old_indices_used=array([ 0, 16, 18, 19, 21, 22, 23, 28, 29, 30, 31, 32]), old_indices_discarded=array([ 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 17, 20, + 24, 25, 26, 27]), step_length=0.1362670918270145, relative_step_length=1.0209603846508213, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([5.49059454, 0.32570596, 0.93946857]), radius=0.0667347596810131, bounds=Bounds(lower=array([1.1 , 0.01, 0.5 ]), upper=array([20. , 0.99, 1.1 ]))), model_indices=array([ 0, 16, 19, 20, 22, 23, 28, 29, 30, 31, 32, 33]), model=ScalarModel(intercept=0.180667786417314, linear_terms=array([ 0.00742114, -0.04161736, -0.07431271]), square_terms=array([[1.78983921e-03, 2.53213785e-02, 7.69037706e-02], + [2.53213785e-02, 4.62056121e-01, 1.34550576e+00], + [7.69037706e-02, 1.34550576e+00, 4.02143592e+00]]), scale=0.0667347596810131, shift=array([5.49059454, 0.32570596, 0.93946857])), vector_model=VectorModel(intercepts=array([ 0.03980461, 0.08715954, 0.08449923, 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radius=0.03336737984050655, bounds=Bounds(lower=array([1.1 , 0.01, 0.5 ]), upper=array([20. , 0.99, 1.1 ]))), model_indices=array([16, 31, 32, 33, 34]), model=ScalarModel(intercept=0.17885448842070745, linear_terms=array([ 0.00036015, -0.00617824, -0.01541375]), square_terms=array([[ 4.69844786e-05, -5.76980455e-04, -1.75264843e-03], + [-5.76980455e-04, 7.91846870e-02, 1.77376377e-01], + [-1.75264843e-03, 1.77376377e-01, 4.05791772e-01]]), scale=0.03336737984050655, shift=array([5.49059454, 0.32570596, 0.93946857])), vector_model=VectorModel(intercepts=array([ 0.03980461, 0.08715954, 0.08449923, 0.10710153, 0.11905802, + 0.13160042, 0.14768033, 0.15905648, 0.07367938, 0.12505611, + -0.21199057, -0.25057516, -0.05680053, -0.03662718, -0.03009585, + -0.03160325, -0.02367163]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + 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30, 31, 32, 33, 34, 35, 36, 37]), model=ScalarModel(intercept=0.17700172025913433, linear_terms=array([0.00175806, 0.00225572, 0.01143802]), square_terms=array([[1.47745785e-03, 2.63476322e-02, 7.55629276e-02], + [2.63476322e-02, 4.77095203e-01, 1.37390372e+00], + [7.55629276e-02, 1.37390372e+00, 4.02874190e+00]]), scale=0.0667347596810131, shift=array([5.43271536, 0.34232811, 0.93481237])), vector_model=VectorModel(intercepts=array([ 0.03980461, 0.08715954, 0.08449923, 0.10710153, 0.11905802, + 0.13160042, 0.14768033, 0.15905648, 0.07367938, 0.12505611, + -0.21199057, -0.25057516, -0.05680053, -0.03662718, -0.03009585, + -0.03160325, -0.02367163]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]]), square_terms=array([[[0., 0., 0.], + [0., 0., 0.], 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new_indices=array([], dtype=int32), old_indices_used=array([30, 31, 32, 34, 36, 37, 38, 39, 40, 41, 42, 43]), old_indices_discarded=array([ 0, 5, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, + 29, 33, 35]), step_length=0.0667568953608683, relative_step_length=1.0003316964047075, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([5.25577068, 0.36291503, 0.92458747]), radius=0.1334695193620262, bounds=Bounds(lower=array([1.1 , 0.01, 0.5 ]), upper=array([20. , 0.99, 1.1 ]))), model_indices=array([23, 28, 30, 31, 32, 36, 38, 39, 40, 41, 42, 44]), model=ScalarModel(intercept=0.17756581846293762, linear_terms=array([-0.00064376, 0.02147547, 0.0472283 ]), square_terms=array([[ 6.33696631e-04, -1.27178250e-02, -3.69738106e-02], + [-1.27178250e-02, 1.40423713e+00, 3.24790628e+00], + [-3.69738106e-02, 3.24790628e+00, 7.66915637e+00]]), scale=0.1334695193620262, shift=array([5.25577068, 0.36291503, 0.92458747])), vector_model=VectorModel(intercepts=array([ 0.03980461, 0.08715954, 0.08449923, 0.10710153, 0.11905802, + 0.13160042, 0.14768033, 0.15905648, 0.07367938, 0.12505611, + -0.21199057, -0.25057516, -0.05680053, -0.03662718, -0.03009585, + -0.03160325, -0.02367163]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]]), square_terms=array([[[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 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step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([5.25577068, 0.36291503, 0.92458747]), radius=0.0667347596810131, bounds=Bounds(lower=array([1.1 , 0.01, 0.5 ]), upper=array([20. , 0.99, 1.1 ]))), model_indices=array([23, 28, 30, 32, 36, 38, 39, 40, 41, 42, 44, 45]), model=ScalarModel(intercept=0.1766790596574145, linear_terms=array([0.00015191, 0.01298194, 0.03144833]), square_terms=array([[ 1.77245269e-04, -3.57687440e-03, -1.01635519e-02], + [-3.57687440e-03, 3.48864307e-01, 8.05273892e-01], + [-1.01635519e-02, 8.05273892e-01, 1.89795527e+00]]), scale=0.0667347596810131, shift=array([5.25577068, 0.36291503, 0.92458747])), vector_model=VectorModel(intercepts=array([ 0.03980461, 0.08715954, 0.08449923, 0.10710153, 0.11905802, + 0.13160042, 0.14768033, 0.15905648, 0.07367938, 0.12505611, + -0.21199057, -0.25057516, -0.05680053, -0.03662718, -0.03009585, + -0.03160325, -0.02367163]), linear_terms=array([[0., 0., 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45, 46]), model=ScalarModel(intercept=0.17713858067470892, linear_terms=array([-5.23221131e-05, 7.13375398e-03, 1.70648155e-02]), square_terms=array([[ 4.64368650e-05, -9.99022647e-04, -2.78370618e-03], + [-9.99022647e-04, 8.72377819e-02, 2.01029677e-01], + [-2.78370618e-03, 2.01029677e-01, 4.72985220e-01]]), scale=0.03336737984050655, shift=array([5.25577068, 0.36291503, 0.92458747])), vector_model=VectorModel(intercepts=array([ 0.03980461, 0.08715954, 0.08449923, 0.10710153, 0.11905802, + 0.13160042, 0.14768033, 0.15905648, 0.07367938, 0.12505611, + -0.21199057, -0.25057516, -0.05680053, -0.03662718, -0.03009585, + -0.03160325, -0.02367163]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]]), square_terms=array([[[0., 0., 0.], + [0., 0., 0.], + 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index=44, x=array([5.25577068, 0.36291503, 0.92458747]), fval=0.1767393872279913, rho=-1.025962964474662, accepted=False, new_indices=array([], dtype=int32), old_indices_used=array([23, 28, 30, 32, 36, 38, 39, 41, 42, 44, 45, 46]), old_indices_discarded=array([], dtype=int32), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([5.25577068, 0.36291503, 0.92458747]), radius=0.016683689920253274, bounds=Bounds(lower=array([1.1 , 0.01, 0.5 ]), upper=array([20. , 0.99, 1.1 ]))), model_indices=array([42, 44, 46, 47]), model=ScalarModel(intercept=0.17673938722799137, linear_terms=array([-0.01008057, -0.11337789, -0.07673132]), square_terms=array([[0.00876524, 0.08404318, 0.03756224], + [0.08404318, 0.81227781, 0.3730522 ], + [0.03756224, 0.3730522 , 0.1876197 ]]), scale=0.016683689920253274, shift=array([5.25577068, 0.36291503, 0.92458747])), vector_model=VectorModel(intercepts=array([ 0.03980461, 0.08715954, 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x=array([5.21614051, 0.34083281, 0.93444849]), fval=0.17525877839750098, rho=-0.24091601228165707, accepted=False, new_indices=array([], dtype=int32), old_indices_used=array([64, 66, 68, 69]), old_indices_discarded=array([], dtype=int32), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([5.21614051, 0.34083281, 0.93444849]), radius=0.0020854612400316593, bounds=Bounds(lower=array([1.1 , 0.01, 0.5 ]), upper=array([20. , 0.99, 1.1 ]))), model_indices=array([66, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82]), model=ScalarModel(intercept=0.1752716135829646, linear_terms=array([ 2.83868377e-05, -1.19751994e-04, -3.17911081e-04]), square_terms=array([[1.11944911e-07, 1.15337902e-06, 1.26187859e-06], + [1.15337902e-06, 3.96183939e-04, 8.51195967e-04], + [1.26187859e-06, 8.51195967e-04, 1.85994556e-03]]), scale=0.0020854612400316593, shift=array([5.21614051, 0.34083281, 0.93444849])), vector_model=VectorModel(intercepts=array([ 0.03980461, 0.08715954, 0.08449923, 0.10710153, 0.11905802, + 0.13160042, 0.14768033, 0.15905648, 0.07367938, 0.12505611, + -0.21199057, -0.25057516, -0.05680053, -0.03662718, -0.03009585, + -0.03160325, -0.02367163]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]]), square_terms=array([[[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 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radius=3.258533187549468e-05, bounds=Bounds(lower=array([1.1 , 0.01, 0.5 ]), upper=array([20. , 0.99, 1.1 ]))), model_indices=array([ 87, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, + 117, 118]), model=ScalarModel(intercept=0.17512371297297075, linear_terms=array([ 5.29135233e-07, -1.28001197e-06, 4.67328132e-07]), square_terms=array([[ 4.05230733e-11, -1.39196492e-10, -6.43975673e-10], + [-1.39196492e-10, 9.68946293e-08, 2.12097857e-07], + [-6.43975673e-10, 2.12097857e-07, 4.74077527e-07]]), scale=3.258533187549468e-05, shift=array([5.21249646, 0.33673577, 0.93667399])), vector_model=VectorModel(intercepts=array([ 0.03980461, 0.08715954, 0.08449923, 0.10710153, 0.11905802, + 0.13160042, 0.14768033, 0.15905648, 0.07367938, 0.12505611, + -0.21199057, -0.25057516, -0.05680053, -0.03662718, -0.03009585, + -0.03160325, -0.02367163]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 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scale=0.44728541044950626, shift=array([4.4728541 , 0.45753029, 0.84720369])), candidate_index=36, candidate_x=array([4.54190424, 0.34416472, 0.93058415]), index=36, x=array([4.54190424, 0.34416472, 0.93058415]), fval=0.17557093407600716, rho=0.20005246667450538, accepted=True, new_indices=array([], dtype=int32), old_indices_used=array([20, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35]), old_indices_discarded=array([ 0, 15, 16, 17, 18, 19, 21, 22, 23, 24]), step_length=0.0608879546199208, relative_step_length=1.0890219657954956, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([4.54190424, 0.34416472, 0.93058415]), radius=0.11182135261237656, bounds=Bounds(lower=array([1.1 , 0.01, 0.5 ]), upper=array([20. , 0.99, 1.1 ]))), model_indices=array([20, 25, 26, 28, 29, 30, 31, 32, 33, 34, 35, 36]), model=ScalarModel(intercept=0.17568176927667278, linear_terms=array([-0.00016853, -0.01916852, -0.03813775]), square_terms=array([[ 5.84778824e-04, -9.07741680e-03, 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fval=0.17319386240144724, rho=-2.368503752157372, accepted=False, new_indices=array([], dtype=int32), old_indices_used=array([41, 46, 47, 48, 50, 51, 52, 53, 54, 56, 57, 59]), old_indices_discarded=array([33, 34, 37, 40, 42, 43, 44, 45, 49, 55, 58]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([4.65947059, 0.34493224, 0.93264892]), radius=0.006988834538273535, bounds=Bounds(lower=array([1.1 , 0.01, 0.5 ]), upper=array([20. , 0.99, 1.1 ]))), model_indices=array([41, 46, 48, 49, 50, 51, 53, 54, 56, 57, 58, 59]), model=ScalarModel(intercept=0.17322335454301357, linear_terms=array([5.84657279e-05, 5.61600646e-05, 1.11287704e-04]), square_terms=array([[ 1.73166366e-06, -5.21647152e-06, -2.70055797e-05], + [-5.21647152e-06, 4.91675196e-03, 1.02038442e-02], + [-2.70055797e-05, 1.02038442e-02, 2.15010081e-02]]), scale=0.006988834538273535, shift=array([4.65947059, 0.34493224, 0.93264892])), vector_model=VectorModel(intercepts=array([ 0.06583231, 0.12997867, 0.12006044, 0.11918703, 0.09509912, + 0.06536156, 0.03646807, -0.03599738, -0.10970519, -0.02523239, + -0.301317 , -0.26498249, -0.08962614, -0.06116485, -0.05206693, + -0.0551122 , -0.05468477]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]]), square_terms=array([[[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 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n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([4.65246302, 0.34513124, 0.93250988]), radius=0.01397766907654707, bounds=Bounds(lower=array([1.1 , 0.01, 0.5 ]), upper=array([20. , 0.99, 1.1 ]))), model_indices=array([41, 45, 47, 48, 50, 51, 53, 54, 56, 57, 59, 61]), model=ScalarModel(intercept=0.17319833291851128, linear_terms=array([-1.51384574e-04, -7.53489850e-06, -1.33953022e-04]), square_terms=array([[7.88278598e-06, 6.56801117e-05, 6.75420704e-05], + [6.56801117e-05, 1.96414914e-02, 4.08747995e-02], + [6.75420704e-05, 4.08747995e-02, 8.63573595e-02]]), scale=0.01397766907654707, shift=array([4.65246302, 0.34513124, 0.93250988])), vector_model=VectorModel(intercepts=array([ 0.06583231, 0.12997867, 0.12006044, 0.11918703, 0.09509912, + 0.06536156, 0.03646807, -0.03599738, -0.10970519, -0.02523239, + -0.301317 , -0.26498249, -0.08962614, -0.06116485, -0.05206693, + -0.0551122 , -0.05468477]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.], + [0., 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model=ScalarModel(intercept=0.1731417369534366, linear_terms=array([8.53555441e-05, 3.94898724e-05, 4.21614549e-05]), square_terms=array([[ 1.87710384e-06, -1.89887381e-05, -5.59774665e-05], + [-1.89887381e-05, 4.91019732e-03, 1.02046258e-02], + [-5.59774665e-05, 1.02046258e-02, 2.15316921e-02]]), scale=0.006988834538273535, shift=array([4.65246302, 0.34513124, 0.93250988])), vector_model=VectorModel(intercepts=array([ 0.06583231, 0.12997867, 0.12006044, 0.11918703, 0.09509912, + 0.06536156, 0.03646807, -0.03599738, -0.10970519, -0.02523239, + -0.301317 , -0.26498249, -0.08962614, -0.06116485, -0.05206693, + -0.0551122 , -0.05468477]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]]), square_terms=array([[[0., 0., 0.], + [0., 0., 0.], + [0., 0., 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index=61, x=array([4.65246302, 0.34513124, 0.93250988]), fval=0.17314745134607396, rho=-0.7767331150668283, accepted=False, new_indices=array([], dtype=int32), old_indices_used=array([41, 46, 48, 49, 50, 51, 54, 55, 56, 58, 59, 61]), old_indices_discarded=array([37, 44, 45, 47, 52, 53, 57, 60, 62]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([4.65246302, 0.34513124, 0.93250988]), radius=0.0034944172691367677, bounds=Bounds(lower=array([1.1 , 0.01, 0.5 ]), upper=array([20. , 0.99, 1.1 ]))), model_indices=array([41, 46, 48, 49, 50, 51, 54, 56, 58, 59, 61, 63]), model=ScalarModel(intercept=0.17318840104590158, linear_terms=array([8.40920959e-06, 1.60644298e-06, 1.78650732e-05]), square_terms=array([[ 4.56677469e-07, -1.61383200e-06, -7.65761701e-06], + [-1.61383200e-06, 1.22943708e-03, 2.55528223e-03], + [-7.65761701e-06, 2.55528223e-03, 5.39279040e-03]]), scale=0.0034944172691367677, shift=array([4.65246302, 0.34513124, 0.93250988])), vector_model=VectorModel(intercepts=array([ 0.06583231, 0.12997867, 0.12006044, 0.11918703, 0.09509912, + 0.06536156, 0.03646807, -0.03599738, -0.10970519, -0.02523239, + -0.301317 , -0.26498249, -0.08962614, -0.06116485, -0.05206693, + -0.0551122 , -0.05468477]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]]), square_terms=array([[[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 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relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([4.65246302, 0.34513124, 0.93250988]), radius=0.0017472086345683838, bounds=Bounds(lower=array([1.1 , 0.01, 0.5 ]), upper=array([20. , 0.99, 1.1 ]))), model_indices=array([41, 46, 48, 49, 50, 51, 56, 58, 59, 61, 63, 64]), model=ScalarModel(intercept=0.1731833699424632, linear_terms=array([-1.55880845e-06, 2.34892542e-05, 3.50350099e-05]), square_terms=array([[1.14286970e-07, 5.95276640e-07, 1.79303603e-07], + [5.95276640e-07, 3.00448801e-04, 6.27473167e-04], + [1.79303603e-07, 6.27473167e-04, 1.33116839e-03]]), scale=0.0017472086345683838, shift=array([4.65246302, 0.34513124, 0.93250988])), vector_model=VectorModel(intercepts=array([ 0.06583231, 0.12997867, 0.12006044, 0.11918703, 0.09509912, + 0.06536156, 0.03646807, -0.03599738, -0.10970519, -0.02523239, + -0.301317 , -0.26498249, -0.08962614, -0.06116485, -0.05206693, + -0.0551122 , -0.05468477]), linear_terms=array([[0., 0., 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model=ScalarModel(intercept=0.17320359100698507, linear_terms=array([-1.04740719e-05, -4.15791794e-05, 1.53390193e-05]), square_terms=array([[ 3.35637081e-08, 1.29446597e-07, -5.58028919e-08], + [ 1.29446597e-07, 7.70487534e-05, 1.63752882e-04], + [-5.58028919e-08, 1.63752882e-04, 3.53849647e-04]]), scale=0.0008736043172841919, shift=array([4.65246302, 0.34513124, 0.93250988])), vector_model=VectorModel(intercepts=array([ 0.06583231, 0.12997867, 0.12006044, 0.11918703, 0.09509912, + 0.06536156, 0.03646807, -0.03599738, -0.10970519, -0.02523239, + -0.301317 , -0.26498249, -0.08962614, -0.06116485, -0.05206693, + -0.0551122 , -0.05468477]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]]), square_terms=array([[[0., 0., 0.], + [0., 0., 0.], + [0., 0., 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index=78, x=array([4.65266665, 0.34590517, 0.93215796]), fval=0.17313846350417914, rho=0.20010394985498053, accepted=True, new_indices=array([66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77]), old_indices_used=array([61, 64, 65]), old_indices_discarded=array([], dtype=int32), step_length=0.0008742235274298533, relative_step_length=1.0007087993195665, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([4.65266665, 0.34590517, 0.93215796]), radius=0.0017472086345683838, bounds=Bounds(lower=array([1.1 , 0.01, 0.5 ]), upper=array([20. , 0.99, 1.1 ]))), model_indices=array([61, 66, 68, 69, 70, 71, 72, 73, 75, 76, 77, 78]), model=ScalarModel(intercept=0.17316117071960616, linear_terms=array([ 1.17846159e-06, -7.30897908e-05, 3.56834929e-05]), square_terms=array([[ 1.26266358e-07, -2.95552318e-07, -1.85714932e-06], + [-2.95552318e-07, 3.06633677e-04, 6.53705727e-04], + [-1.85714932e-06, 6.53705727e-04, 1.41658448e-03]]), scale=0.0017472086345683838, shift=array([4.65266665, 0.34590517, 0.93215796])), vector_model=VectorModel(intercepts=array([ 0.06583231, 0.12997867, 0.12006044, 0.11918703, 0.09509912, + 0.06536156, 0.03646807, -0.03599738, -0.10970519, -0.02523239, + -0.301317 , -0.26498249, -0.08962614, -0.06116485, -0.05206693, + -0.0551122 , -0.05468477]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]]), square_terms=array([[[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 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step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([4.65266665, 0.34590517, 0.93215796]), radius=0.0008736043172841919, bounds=Bounds(lower=array([1.1 , 0.01, 0.5 ]), upper=array([20. , 0.99, 1.1 ]))), model_indices=array([61, 66, 67, 69, 70, 71, 72, 73, 74, 75, 77, 78]), model=ScalarModel(intercept=0.17315497758754703, linear_terms=array([-1.03031559e-05, -4.11416984e-05, 1.56495230e-05]), square_terms=array([[ 3.02714973e-08, 8.04834807e-08, -1.41448123e-07], + [ 8.04834807e-08, 7.72107726e-05, 1.63938593e-04], + [-1.41448123e-07, 1.63938593e-04, 3.53626006e-04]]), scale=0.0008736043172841919, shift=array([4.65266665, 0.34590517, 0.93215796])), vector_model=VectorModel(intercepts=array([ 0.06583231, 0.12997867, 0.12006044, 0.11918703, 0.09509912, + 0.06536156, 0.03646807, -0.03599738, -0.10970519, -0.02523239, + -0.301317 , -0.26498249, -0.08962614, -0.06116485, -0.05206693, + -0.0551122 , -0.05468477]), 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model=ScalarModel(intercept=0.17317273550338308, linear_terms=array([ 4.91859051e-07, -1.11539853e-05, -3.77793814e-06]), square_terms=array([[ 7.22202027e-09, 2.91274101e-08, -7.91097523e-09], + [ 2.91274101e-08, 1.93478699e-05, 4.10231377e-05], + [-7.91097523e-09, 4.10231377e-05, 8.82835907e-05]]), scale=0.00043680215864209596, shift=array([4.65266665, 0.34590517, 0.93215796])), vector_model=VectorModel(intercepts=array([ 0.06583231, 0.12997867, 0.12006044, 0.11918703, 0.09509912, + 0.06536156, 0.03646807, -0.03599738, -0.10970519, -0.02523239, + -0.301317 , -0.26498249, -0.08962614, -0.06116485, -0.05206693, + -0.0551122 , -0.05468477]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]]), square_terms=array([[[0., 0., 0.], + [0., 0., 0.], + [0., 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index=78, x=array([4.65266665, 0.34590517, 0.93215796]), fval=0.17313846350417914, rho=-2.0772563083934017, accepted=False, new_indices=array([], dtype=int32), old_indices_used=array([61, 66, 67, 69, 71, 72, 73, 74, 75, 77, 78, 80]), old_indices_discarded=array([68, 70, 76, 79]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([4.65266665, 0.34590517, 0.93215796]), radius=0.00021840107932104798, bounds=Bounds(lower=array([1.1 , 0.01, 0.5 ]), upper=array([20. , 0.99, 1.1 ]))), model_indices=array([61, 66, 67, 69, 74, 75, 78, 80, 81]), model=ScalarModel(intercept=0.1731737579944651, linear_terms=array([-3.79844970e-06, -3.69441907e-06, 9.93700675e-07]), square_terms=array([[2.70592783e-09, 4.30842813e-08, 7.31011322e-08], + [4.30842813e-08, 4.85108303e-06, 1.02966777e-05], + [7.31011322e-08, 1.02966777e-05, 2.21791802e-05]]), scale=0.00021840107932104798, shift=array([4.65266665, 0.34590517, 0.93215796])), vector_model=VectorModel(intercepts=array([ 0.06583231, 0.12997867, 0.12006044, 0.11918703, 0.09509912, + 0.06536156, 0.03646807, -0.03599738, -0.10970519, -0.02523239, + -0.301317 , -0.26498249, -0.08962614, -0.06116485, -0.05206693, + -0.0551122 , -0.05468477]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]]), square_terms=array([[[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 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0.35179043, 0.92170005]), fval=0.18834408422290103, rho=-0.21724111958860234, accepted=False, new_indices=array([], dtype=int32), old_indices_used=array([ 0, 1, 2, 3, 4, 5, 7, 8, 10, 12, 13, 14]), old_indices_discarded=array([6, 9]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([5.3013976 , 0.35179043, 0.92170005]), radius=0.06626747004284965, bounds=Bounds(lower=array([1.1 , 0.01, 0.5 ]), upper=array([20. , 0.99, 1.1 ]))), model_indices=array([ 0, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27]), model=ScalarModel(intercept=0.16542657032258398, linear_terms=array([0.01630779, 0.01475797, 0.02073112]), square_terms=array([[ 0.05951927, -0.12255125, -0.23582986], + [-0.12255125, 0.26987927, 0.50459186], + [-0.23582986, 0.50459186, 0.96563619]]), scale=0.06626747004284965, shift=array([5.3013976 , 0.35179043, 0.92170005])), vector_model=VectorModel(intercepts=array([ 0.05267501, 0.10545582, 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radius=0.033133735021424825, bounds=Bounds(lower=array([1.1 , 0.01, 0.5 ]), upper=array([20. , 0.99, 1.1 ]))), model_indices=array([ 0, 16, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27]), model=ScalarModel(intercept=0.16782671230459395, linear_terms=array([ 0.0009187 , -0.00784055, -0.02621131]), square_terms=array([[4.57181704e-05, 1.25022351e-03, 2.32119020e-03], + [1.25022351e-03, 9.27555996e-02, 1.94331965e-01], + [2.32119020e-03, 1.94331965e-01, 4.14037852e-01]]), scale=0.033133735021424825, shift=array([5.3013976 , 0.35179043, 0.92170005])), vector_model=VectorModel(intercepts=array([ 0.05267501, 0.10545582, 0.09377041, 0.09722369, 0.08350715, + 0.06843123, 0.05931804, 0.03774492, -0.03016214, 0.0549344 , + -0.23227729, -0.2172487 , -0.10547152, -0.08018271, -0.07300715, + -0.0770617 , -0.07552639]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 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22, 24, 25, 26, 27, 28, 29]), old_indices_discarded=array([14, 15, 16, 19, 23]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([5.29121744, 0.32407875, 0.9367533 ]), radius=0.033133735021424825, bounds=Bounds(lower=array([1.1 , 0.01, 0.5 ]), upper=array([20. , 0.99, 1.1 ]))), model_indices=array([ 0, 17, 18, 20, 21, 24, 25, 26, 27, 28, 29, 30]), model=ScalarModel(intercept=0.1685046981505246, linear_terms=array([ 0.00059146, -0.004534 , -0.01522606]), square_terms=array([[3.03577735e-05, 5.05858062e-04, 7.12748102e-04], + [5.05858062e-04, 9.30360296e-02, 1.93666384e-01], + [7.12748102e-04, 1.93666384e-01, 4.10425108e-01]]), scale=0.033133735021424825, shift=array([5.29121744, 0.32407875, 0.9367533 ])), vector_model=VectorModel(intercepts=array([ 0.05267501, 0.10545582, 0.09377041, 0.09722369, 0.08350715, + 0.06843123, 0.05931804, 0.03774492, -0.03016214, 0.0549344 , + -0.23227729, -0.2172487 , -0.10547152, -0.08018271, -0.07300715, + -0.0770617 , -0.07552639]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]]), square_terms=array([[[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 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model_indices=array([ 0, 17, 18, 20, 24, 25, 26, 27, 28, 29, 30, 31]), model=ScalarModel(intercept=0.17004437609421225, linear_terms=array([-0.00047394, -0.007927 , -0.01239616]), square_terms=array([[3.94062801e-04, 1.07905924e-02, 2.16812211e-02], + [1.07905924e-02, 3.74115243e-01, 7.88602520e-01], + [2.16812211e-02, 7.88602520e-01, 1.69226096e+00]]), scale=0.06626747004284965, shift=array([5.27834936, 0.29684139, 0.95081613])), vector_model=VectorModel(intercepts=array([ 0.05267501, 0.10545582, 0.09377041, 0.09722369, 0.08350715, + 0.06843123, 0.05931804, 0.03774492, -0.03016214, 0.0549344 , + -0.23227729, -0.2172487 , -0.10547152, -0.08018271, -0.07300715, + -0.0770617 , -0.07552639]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]]), 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candidate_x=array([5.34476989, 0.3113389 , 0.94369486]), index=31, x=array([5.27834936, 0.29684139, 0.95081613]), fval=0.1799906266171576, rho=-2.1259132820697104, accepted=False, new_indices=array([], dtype=int32), old_indices_used=array([ 0, 17, 18, 20, 24, 25, 26, 27, 28, 29, 30, 31]), old_indices_discarded=array([14, 15, 16, 19, 21, 22, 23]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([5.27834936, 0.29684139, 0.95081613]), radius=0.033133735021424825, bounds=Bounds(lower=array([1.1 , 0.01, 0.5 ]), upper=array([20. , 0.99, 1.1 ]))), model_indices=array([ 0, 17, 18, 20, 24, 25, 26, 28, 29, 30, 31, 32]), model=ScalarModel(intercept=0.1684737651459072, linear_terms=array([0.00169024, 0.00402826, 0.00597484]), square_terms=array([[ 4.51971473e-04, -5.93887978e-03, -1.50514931e-02], + [-5.93887978e-03, 9.28119628e-02, 2.24673825e-01], + [-1.50514931e-02, 2.24673825e-01, 5.53588350e-01]]), scale=0.033133735021424825, shift=array([5.27834936, 0.29684139, 0.95081613])), vector_model=VectorModel(intercepts=array([ 0.05267501, 0.10545582, 0.09377041, 0.09722369, 0.08350715, + 0.06843123, 0.05931804, 0.03774492, -0.03016214, 0.0549344 , + -0.23227729, -0.2172487 , -0.10547152, -0.08018271, -0.07300715, + -0.0770617 , -0.07552639]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]]), square_terms=array([[[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + 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relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([5.27834936, 0.29684139, 0.95081613]), radius=0.016566867510712412, bounds=Bounds(lower=array([1.1 , 0.01, 0.5 ]), upper=array([20. , 0.99, 1.1 ]))), model_indices=array([ 0, 17, 24, 25, 26, 28, 29, 31, 32, 33]), model=ScalarModel(intercept=0.1727642107806147, linear_terms=array([ 0.00026785, -0.00558419, -0.00849838]), square_terms=array([[ 2.85834005e-05, -7.58751720e-04, -1.71197263e-03], + [-7.58751720e-04, 2.93707342e-02, 6.18391893e-02], + [-1.71197263e-03, 6.18391893e-02, 1.32214577e-01]]), scale=0.016566867510712412, shift=array([5.27834936, 0.29684139, 0.95081613])), vector_model=VectorModel(intercepts=array([ 0.05267501, 0.10545582, 0.09377041, 0.09722369, 0.08350715, + 0.06843123, 0.05931804, 0.03774492, -0.03016214, 0.0549344 , + -0.23227729, -0.2172487 , -0.10547152, -0.08018271, -0.07300715, + -0.0770617 , -0.07552639]), linear_terms=array([[0., 0., 0.], + [0., 0., 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fval=0.17755692096608, rho=1.8988432161216091, accepted=True, new_indices=array([], dtype=int32), old_indices_used=array([ 0, 17, 18, 24, 25, 26, 28, 29, 31, 32, 33, 34]), old_indices_discarded=array([15, 16, 19, 20, 21, 22, 23, 27, 30]), step_length=0.033281691430788476, relative_step_length=1.004465431055931, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([5.30566766, 0.32537105, 0.9393405 ]), radius=0.06626747004284965, bounds=Bounds(lower=array([1.1 , 0.01, 0.5 ]), upper=array([20. , 0.99, 1.1 ]))), model_indices=array([ 0, 17, 20, 24, 25, 26, 29, 30, 31, 32, 34, 35]), model=ScalarModel(intercept=0.17237609478517008, linear_terms=array([ 0.00518006, -0.00474084, -0.0125618 ]), square_terms=array([[ 2.10162976e-03, -2.78797705e-02, -6.43090686e-02], + [-2.78797705e-02, 4.31690458e-01, 9.58890944e-01], + [-6.43090686e-02, 9.58890944e-01, 2.16354079e+00]]), scale=0.06626747004284965, shift=array([5.30566766, 0.32537105, 0.9393405 ])), vector_model=VectorModel(intercepts=array([ 0.05267501, 0.10545582, 0.09377041, 0.09722369, 0.08350715, + 0.06843123, 0.05931804, 0.03774492, -0.03016214, 0.0549344 , + -0.23227729, -0.2172487 , -0.10547152, -0.08018271, -0.07300715, + -0.0770617 , -0.07552639]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]]), square_terms=array([[[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 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n_evals_acceptance=1), State(trustregion=Region(center=array([5.30566766, 0.32537105, 0.9393405 ]), radius=0.033133735021424825, bounds=Bounds(lower=array([1.1 , 0.01, 0.5 ]), upper=array([20. , 0.99, 1.1 ]))), model_indices=array([ 0, 17, 20, 24, 25, 26, 29, 30, 31, 32, 34, 35]), model=ScalarModel(intercept=0.1723760947851703, linear_terms=array([ 0.00259003, -0.00237042, -0.0062809 ]), square_terms=array([[ 5.25407439e-04, -6.96994262e-03, -1.60772672e-02], + [-6.96994262e-03, 1.07922614e-01, 2.39722736e-01], + [-1.60772672e-02, 2.39722736e-01, 5.40885198e-01]]), scale=0.033133735021424825, shift=array([5.30566766, 0.32537105, 0.9393405 ])), vector_model=VectorModel(intercepts=array([ 0.05267501, 0.10545582, 0.09377041, 0.09722369, 0.08350715, + 0.06843123, 0.05931804, 0.03774492, -0.03016214, 0.0549344 , + -0.23227729, -0.2172487 , -0.10547152, -0.08018271, -0.07300715, + -0.0770617 , -0.07552639]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + 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linear_terms=array([-0.00039037, -0.0076903 , -0.01984056]), square_terms=array([[1.68083117e-05, 5.99857721e-04, 1.30035997e-03], + [5.99857721e-04, 3.07066045e-02, 7.08873570e-02], + [1.30035997e-03, 7.08873570e-02, 1.65894328e-01]]), scale=0.016566867510712412, shift=array([5.30566766, 0.32537105, 0.9393405 ])), vector_model=VectorModel(intercepts=array([ 0.05267501, 0.10545582, 0.09377041, 0.09722369, 0.08350715, + 0.06843123, 0.05931804, 0.03774492, -0.03016214, 0.0549344 , + -0.23227729, -0.2172487 , -0.10547152, -0.08018271, -0.07300715, + -0.0770617 , -0.07552639]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]]), square_terms=array([[[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + 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fval=0.17733908278986127, rho=0.12075915604171515, accepted=True, new_indices=array([], dtype=int32), old_indices_used=array([ 0, 17, 20, 25, 26, 29, 30, 31, 32, 34, 35, 37]), old_indices_discarded=array([22, 24, 27, 28, 33, 36]), step_length=0.01691501274286895, relative_step_length=1.021014547978453, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([5.31420845, 0.31272412, 0.94663622]), radius=0.033133735021424825, bounds=Bounds(lower=array([1.1 , 0.01, 0.5 ]), upper=array([20. , 0.99, 1.1 ]))), model_indices=array([ 0, 20, 25, 26, 29, 30, 31, 32, 34, 35, 37, 38]), model=ScalarModel(intercept=0.17451053131095257, linear_terms=array([ 0.00026766, -0.00034627, -0.00190087]), square_terms=array([[ 2.82594589e-05, -3.98670431e-04, -1.30601253e-03], + [-3.98670431e-04, 1.28325976e-01, 2.92377009e-01], + [-1.30601253e-03, 2.92377009e-01, 6.74940821e-01]]), scale=0.033133735021424825, shift=array([5.31420845, 0.31272412, 0.94663622])), vector_model=VectorModel(intercepts=array([ 0.05267501, 0.10545582, 0.09377041, 0.09722369, 0.08350715, + 0.06843123, 0.05931804, 0.03774492, -0.03016214, 0.0549344 , + -0.23227729, -0.2172487 , -0.10547152, -0.08018271, -0.07300715, + -0.0770617 , -0.07552639]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]]), square_terms=array([[[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 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n_evals_acceptance=1), State(trustregion=Region(center=array([5.31420845, 0.31272412, 0.94663622]), radius=0.016566867510712412, bounds=Bounds(lower=array([1.1 , 0.01, 0.5 ]), upper=array([20. , 0.99, 1.1 ]))), model_indices=array([ 0, 20, 26, 29, 30, 31, 32, 34, 35, 37, 38, 39]), model=ScalarModel(intercept=0.1771813911491111, linear_terms=array([ 1.44498627e-05, -7.05759415e-04, -8.71906755e-04]), square_terms=array([[6.32366784e-06, 6.97090062e-05, 6.24448079e-05], + [6.97090062e-05, 2.21772805e-02, 4.87945740e-02], + [6.24448079e-05, 4.87945740e-02, 1.09441144e-01]]), scale=0.016566867510712412, shift=array([5.31420845, 0.31272412, 0.94663622])), vector_model=VectorModel(intercepts=array([ 0.05267501, 0.10545582, 0.09377041, 0.09722369, 0.08350715, + 0.06843123, 0.05931804, 0.03774492, -0.03016214, 0.0549344 , + -0.23227729, -0.2172487 , -0.10547152, -0.08018271, -0.07300715, + -0.0770617 , -0.07552639]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 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linear_terms=array([-8.72839083e-04, 6.46911097e-05, -1.15041490e-03]), square_terms=array([[1.69827888e-04, 4.48946449e-03, 9.85596140e-03], + [4.48946449e-03, 1.31226175e-01, 2.95972451e-01], + [9.85596140e-03, 2.95972451e-01, 6.76192041e-01]]), scale=0.033133735021424825, shift=array([5.30300313, 0.32433431, 0.9416009 ])), vector_model=VectorModel(intercepts=array([ 0.05267501, 0.10545582, 0.09377041, 0.09722369, 0.08350715, + 0.06843123, 0.05931804, 0.03774492, -0.03016214, 0.0549344 , + -0.23227729, -0.2172487 , -0.10547152, -0.08018271, -0.07300715, + -0.0770617 , -0.07552639]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]]), square_terms=array([[[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 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fval=0.1766329595168218, rho=-0.9795538799146807, accepted=False, new_indices=array([], dtype=int32), old_indices_used=array([ 0, 25, 26, 29, 31, 32, 34, 35, 37, 38, 39, 40]), old_indices_discarded=array([15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 27, 28, 30, 33, 36]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([5.30300313, 0.32433431, 0.9416009 ]), radius=0.016566867510712412, bounds=Bounds(lower=array([1.1 , 0.01, 0.5 ]), upper=array([20. , 0.99, 1.1 ]))), model_indices=array([ 0, 26, 29, 31, 32, 34, 35, 37, 38, 39, 40, 41]), model=ScalarModel(intercept=0.17721715662436963, linear_terms=array([0.00016892, 0.00010182, 0.00044048]), square_terms=array([[6.47390632e-06, 4.70823827e-05, 1.17452629e-05], + [4.70823827e-05, 2.18434219e-02, 4.79874666e-02], + [1.17452629e-05, 4.79874666e-02, 1.07501169e-01]]), scale=0.016566867510712412, shift=array([5.30300313, 0.32433431, 0.9416009 ])), vector_model=VectorModel(intercepts=array([ 0.05267501, 0.10545582, 0.09377041, 0.09722369, 0.08350715, + 0.06843123, 0.05931804, 0.03774492, -0.03016214, 0.0549344 , + -0.23227729, -0.2172487 , -0.10547152, -0.08018271, -0.07300715, + -0.0770617 , -0.07552639]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]]), square_terms=array([[[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 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n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([5.28676541, 0.32788588, 0.93995208]), radius=0.033133735021424825, bounds=Bounds(lower=array([1.1 , 0.01, 0.5 ]), upper=array([20. , 0.99, 1.1 ]))), model_indices=array([ 0, 17, 29, 31, 34, 35, 36, 37, 38, 39, 40, 42]), model=ScalarModel(intercept=0.17584179736570787, linear_terms=array([ 0.00072293, -0.00395619, -0.0056097 ]), square_terms=array([[ 2.77942804e-05, -1.36149379e-04, -6.48042884e-04], + [-1.36149379e-04, 1.20187024e-01, 2.58595324e-01], + [-6.48042884e-04, 2.58595324e-01, 5.64442351e-01]]), scale=0.033133735021424825, shift=array([5.28676541, 0.32788588, 0.93995208])), vector_model=VectorModel(intercepts=array([ 0.05267501, 0.10545582, 0.09377041, 0.09722369, 0.08350715, + 0.06843123, 0.05931804, 0.03774492, -0.03016214, 0.0549344 , + -0.23227729, -0.2172487 , -0.10547152, -0.08018271, -0.07300715, + -0.0770617 , -0.07552639]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.], + [0., 0., 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model=ScalarModel(intercept=0.17516083815911454, linear_terms=array([0.00333895, 0.02345551, 0.04006676]), square_terms=array([[ 9.17825370e-04, -1.49978117e-02, -3.32074698e-02], + [-1.49978117e-02, 3.29043755e-01, 6.85571868e-01], + [-3.32074698e-02, 6.85571868e-01, 1.45766388e+00]]), scale=0.06626747004284965, shift=array([5.25969725, 0.34546622, 0.93220909])), vector_model=VectorModel(intercepts=array([ 0.05267501, 0.10545582, 0.09377041, 0.09722369, 0.08350715, + 0.06843123, 0.05931804, 0.03774492, -0.03016214, 0.0549344 , + -0.23227729, -0.2172487 , -0.10547152, -0.08018271, -0.07300715, + -0.0770617 , -0.07552639]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]]), square_terms=array([[[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 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x=array([5.25969725, 0.34546622, 0.93220909]), fval=0.17587143240730305, rho=-0.2929960708109051, accepted=False, new_indices=array([], dtype=int32), old_indices_used=array([ 0, 17, 18, 21, 24, 28, 31, 35, 36, 37, 38, 43]), old_indices_discarded=array([14, 15, 16, 19, 20, 22, 23, 25, 26, 27, 29, 30, 32, 33, 34, 39, 40, + 41, 42]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([5.25969725, 0.34546622, 0.93220909]), radius=0.033133735021424825, bounds=Bounds(lower=array([1.1 , 0.01, 0.5 ]), upper=array([20. , 0.99, 1.1 ]))), model_indices=array([ 0, 17, 18, 28, 29, 34, 36, 37, 39, 40, 42, 43]), model=ScalarModel(intercept=0.17500252339842898, linear_terms=array([0.00143805, 0.00318419, 0.00584766]), square_terms=array([[ 2.32402708e-04, -4.32320857e-03, -9.89988047e-03], + [-4.32320857e-03, 1.00521560e-01, 2.19588637e-01], + [-9.89988047e-03, 2.19588637e-01, 4.87595223e-01]]), scale=0.033133735021424825, 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41, 44]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([5.25969725, 0.34546622, 0.93220909]), radius=0.016566867510712412, bounds=Bounds(lower=array([1.1 , 0.01, 0.5 ]), upper=array([20. , 0.99, 1.1 ]))), model_indices=array([ 0, 17, 18, 28, 29, 34, 36, 37, 39, 42, 43, 45]), model=ScalarModel(intercept=0.1751974222542535, linear_terms=array([0.00059828, 0.00104291, 0.00174938]), square_terms=array([[ 2.32452897e-05, -6.04410229e-04, -1.41547067e-03], + [-6.04410229e-04, 2.52698536e-02, 5.50888216e-02], + [-1.41547067e-03, 5.50888216e-02, 1.22064179e-01]]), scale=0.016566867510712412, shift=array([5.25969725, 0.34546622, 0.93220909])), vector_model=VectorModel(intercepts=array([ 0.05267501, 0.10545582, 0.09377041, 0.09722369, 0.08350715, + 0.06843123, 0.05931804, 0.03774492, -0.03016214, 0.0549344 , + -0.23227729, -0.2172487 , -0.10547152, -0.08018271, -0.07300715, + -0.0770617 , -0.07552639]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]]), square_terms=array([[[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 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28, 29, 34, 36, 37, 42, 43, 44, 45, 46]), model=ScalarModel(intercept=0.1748745633782247, linear_terms=array([ 0.00075962, -0.00172199, -0.00445794]), square_terms=array([[ 3.54305914e-05, -8.55387782e-04, -2.21218821e-03], + [-8.55387782e-04, 1.02537349e-01, 2.22590300e-01], + [-2.21218821e-03, 2.22590300e-01, 4.91024973e-01]]), scale=0.033133735021424825, shift=array([5.24271155, 0.34212944, 0.93327545])), vector_model=VectorModel(intercepts=array([ 0.05267501, 0.10545582, 0.09377041, 0.09722369, 0.08350715, + 0.06843123, 0.05931804, 0.03774492, -0.03016214, 0.0549344 , + -0.23227729, -0.2172487 , -0.10547152, -0.08018271, -0.07300715, + -0.0770617 , -0.07552639]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]]), square_terms=array([[[0., 0., 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0.34014316, 0.93432412]), index=47, x=array([5.20917798, 0.34014316, 0.93432412]), fval=0.1752985258377397, rho=0.5865083498507621, accepted=True, new_indices=array([], dtype=int32), old_indices_used=array([17, 18, 28, 29, 34, 36, 37, 42, 43, 44, 45, 46]), old_indices_discarded=array([ 0, 15, 16, 19, 20, 21, 22, 23, 24, 25, 26, 27, 30, 31, 32, 33, 35, + 38, 39, 40, 41]), step_length=0.03360870947755719, relative_step_length=1.0143350713653392, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([5.20917798, 0.34014316, 0.93432412]), radius=0.06626747004284965, bounds=Bounds(lower=array([1.1 , 0.01, 0.5 ]), upper=array([20. , 0.99, 1.1 ]))), model_indices=array([17, 18, 21, 28, 33, 36, 37, 43, 44, 45, 46, 47]), model=ScalarModel(intercept=0.17493421876270587, linear_terms=array([-0.00156353, -0.00842537, -0.01190066]), square_terms=array([[0.00281928, 0.03109626, 0.0629877 ], + [0.03109626, 0.34695273, 0.70455773], + [0.0629877 , 0.70455773, 1.45975502]]), 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27, 29, 30, 31, 32, 34, + 35, 38, 39, 40, 41, 42]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([5.20917798, 0.34014316, 0.93432412]), radius=0.033133735021424825, bounds=Bounds(lower=array([1.1 , 0.01, 0.5 ]), upper=array([20. , 0.99, 1.1 ]))), model_indices=array([17, 18, 28, 33, 36, 37, 43, 44, 45, 46, 47, 48]), model=ScalarModel(intercept=0.17451083881940163, linear_terms=array([ 0.00045657, -0.00270283, -0.00529828]), square_terms=array([[4.56076655e-05, 1.60381216e-03, 3.26261075e-03], + [1.60381216e-03, 9.80067681e-02, 2.16994269e-01], + [3.26261075e-03, 2.16994269e-01, 4.88889862e-01]]), scale=0.033133735021424825, shift=array([5.20917798, 0.34014316, 0.93432412])), vector_model=VectorModel(intercepts=array([ 0.05267501, 0.10545582, 0.09377041, 0.09722369, 0.08350715, + 0.06843123, 0.05931804, 0.03774492, -0.03016214, 0.0549344 , + -0.23227729, -0.2172487 , -0.10547152, -0.08018271, -0.07300715, + 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0.5 ]), upper=array([20. , 0.99, 1.1 ]))), model_indices=array([17, 18, 21, 28, 33, 36, 43, 44, 45, 46, 47, 49]), model=ScalarModel(intercept=0.17564926316541823, linear_terms=array([-0.00274284, -0.01384935, -0.02471199]), square_terms=array([[0.0035693 , 0.03481689, 0.07133062], + [0.03481689, 0.34263536, 0.7019492 ], + [0.07133062, 0.7019492 , 1.46757845]]), scale=0.06626747004284965, shift=array([5.17665032, 0.34743911, 0.93166475])), vector_model=VectorModel(intercepts=array([ 0.05267501, 0.10545582, 0.09377041, 0.09722369, 0.08350715, + 0.06843123, 0.05931804, 0.03774492, -0.03016214, 0.0549344 , + -0.23227729, -0.2172487 , -0.10547152, -0.08018271, -0.07300715, + -0.0770617 , -0.07552639]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]]), 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candidate_x=array([5.2442876 , 0.35755943, 0.92465874]), index=49, x=array([5.17665032, 0.34743911, 0.93166475]), fval=0.1749771962623699, rho=-1.2279027031180028, accepted=False, new_indices=array([], dtype=int32), old_indices_used=array([17, 18, 21, 28, 33, 36, 43, 44, 45, 46, 47, 49]), old_indices_discarded=array([ 0, 14, 15, 16, 19, 20, 22, 23, 24, 25, 26, 27, 29, 30, 31, 32, 34, + 35, 37, 38, 39, 40, 41, 42, 48]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([5.17665032, 0.34743911, 0.93166475]), radius=0.033133735021424825, bounds=Bounds(lower=array([1.1 , 0.01, 0.5 ]), upper=array([20. , 0.99, 1.1 ]))), model_indices=array([17, 18, 21, 28, 36, 43, 44, 45, 46, 47, 49, 50]), model=ScalarModel(intercept=0.1762502933918212, linear_terms=array([-0.00155691, -0.00561339, -0.01308175]), square_terms=array([[0.00079825, 0.00800458, 0.01674233], + [0.00800458, 0.08167794, 0.17110631], + [0.01674233, 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24, 25, 26, 29, 31, 33, 34, 35, 37, 38, 39, 40, 41, + 42, 48]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([5.17665032, 0.34743911, 0.93166475]), radius=0.016566867510712412, bounds=Bounds(lower=array([1.1 , 0.01, 0.5 ]), upper=array([20. , 0.99, 1.1 ]))), model_indices=array([18, 28, 36, 44, 45, 46, 47, 49, 50, 51]), model=ScalarModel(intercept=0.17468169315856466, linear_terms=array([0.00019334, 0.00068168, 0.002236 ]), square_terms=array([[6.30086486e-06, 1.31120182e-04, 1.92914840e-04], + [1.31120182e-04, 2.30933740e-02, 4.65644949e-02], + [1.92914840e-04, 4.65644949e-02, 9.56283946e-02]]), scale=0.016566867510712412, shift=array([5.17665032, 0.34743911, 0.93166475])), vector_model=VectorModel(intercepts=array([ 0.05267501, 0.10545582, 0.09377041, 0.09722369, 0.08350715, + 0.06843123, 0.05931804, 0.03774492, -0.03016214, 0.0549344 , + -0.23227729, -0.2172487 , -0.10547152, -0.08018271, -0.07300715, + 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model=ScalarModel(intercept=0.17496972296461294, linear_terms=array([ 6.97863248e-05, -8.21475281e-05, -4.56887150e-04]), square_terms=array([[1.84361126e-06, 2.04013067e-05, 2.19735979e-05], + [2.04013067e-05, 5.26300747e-03, 1.10824804e-02], + [2.19735979e-05, 1.10824804e-02, 2.38107760e-02]]), scale=0.008283433755356206, shift=array([5.17665032, 0.34743911, 0.93166475])), vector_model=VectorModel(intercepts=array([ 0.05267501, 0.10545582, 0.09377041, 0.09722369, 0.08350715, + 0.06843123, 0.05931804, 0.03774492, -0.03016214, 0.0549344 , + -0.23227729, -0.2172487 , -0.10547152, -0.08018271, -0.07300715, + -0.0770617 , -0.07552639]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]]), square_terms=array([[[0., 0., 0.], + [0., 0., 0.], + [0., 0., 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index=53, x=array([5.17030197, 0.34249393, 0.93412279]), fval=0.17478348430580953, rho=1.7260767313376242, accepted=True, new_indices=array([], dtype=int32), old_indices_used=array([44, 47, 49, 51, 52]), old_indices_discarded=array([], dtype=int32), step_length=0.008414173637941258, relative_step_length=1.0157832954842565, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([5.17030197, 0.34249393, 0.93412279]), radius=0.016566867510712412, bounds=Bounds(lower=array([1.1 , 0.01, 0.5 ]), upper=array([20. , 0.99, 1.1 ]))), model_indices=array([18, 28, 36, 44, 45, 46, 47, 49, 50, 51, 52, 53]), model=ScalarModel(intercept=0.1749826973068216, linear_terms=array([0.0001074 , 0.00038707, 0.00171986]), square_terms=array([[7.58231429e-06, 2.29836559e-04, 3.96776253e-04], + [2.29836559e-04, 2.29465979e-02, 4.65350783e-02], + [3.96776253e-04, 4.65350783e-02, 9.61235255e-02]]), scale=0.016566867510712412, shift=array([5.17030197, 0.34249393, 0.93412279])), 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State(trustregion=Region(center=array([5.17030197, 0.34249393, 0.93412279]), radius=0.008283433755356206, bounds=Bounds(lower=array([1.1 , 0.01, 0.5 ]), upper=array([20. , 0.99, 1.1 ]))), model_indices=array([44, 47, 49, 51, 52, 53, 54]), model=ScalarModel(intercept=0.1747885766485168, linear_terms=array([ 7.81846919e-05, 3.99579562e-05, -9.60174366e-05]), square_terms=array([[1.77118649e-06, 1.19372381e-05, 4.26127615e-06], + [1.19372381e-05, 5.37799886e-03, 1.13872076e-02], + [4.26127615e-06, 1.13872076e-02, 2.45888809e-02]]), scale=0.008283433755356206, shift=array([5.17030197, 0.34249393, 0.93412279])), vector_model=VectorModel(intercepts=array([ 0.05267501, 0.10545582, 0.09377041, 0.09722369, 0.08350715, + 0.06843123, 0.05931804, 0.03774492, -0.03016214, 0.0549344 , + -0.23227729, -0.2172487 , -0.10547152, -0.08018271, -0.07300715, + -0.0770617 , -0.07552639]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 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candidate_x=array([5.14420282, 0.34178406, 0.93435027]), index=58, x=array([5.14420282, 0.34178406, 0.93435027]), fval=0.1744823721068387, rho=1.3631217507153135, accepted=True, new_indices=array([], dtype=int32), old_indices_used=array([54, 55, 56, 57]), old_indices_discarded=array([], dtype=int32), step_length=0.0042475620970457, relative_step_length=1.0255558799632232, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([5.14420282, 0.34178406, 0.93435027]), radius=0.008283433755356206, bounds=Bounds(lower=array([1.1 , 0.01, 0.5 ]), upper=array([20. , 0.99, 1.1 ]))), model_indices=array([49, 52, 53, 54, 55, 56, 57, 58]), model=ScalarModel(intercept=0.17448263024954638, linear_terms=array([8.45063966e-05, 2.93674559e-04, 4.11365018e-04]), square_terms=array([[1.72519621e-06, 1.48187759e-05, 1.09062891e-05], + [1.48187759e-05, 6.27266360e-03, 1.32612134e-02], + [1.09062891e-05, 1.32612134e-02, 2.85049653e-02]]), scale=0.008283433755356206, 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relative_step_length=1.0030673053597174, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([5.1369295 , 0.33809681, 0.93594391]), radius=0.016566867510712412, bounds=Bounds(lower=array([1.1 , 0.01, 0.5 ]), upper=array([20. , 0.99, 1.1 ]))), model_indices=array([44, 47, 49, 51, 52, 53, 54, 55, 56, 57, 58, 59]), model=ScalarModel(intercept=0.1744379176106382, linear_terms=array([ 0.00014316, -0.0007016 , -0.00153491]), square_terms=array([[6.93968654e-06, 4.93334629e-05, 2.09902799e-05], + [4.93334629e-05, 2.19685008e-02, 4.66549901e-02], + [2.09902799e-05, 4.66549901e-02, 1.00998973e-01]]), scale=0.016566867510712412, shift=array([5.1369295 , 0.33809681, 0.93594391])), vector_model=VectorModel(intercepts=array([ 0.05267501, 0.10545582, 0.09377041, 0.09722369, 0.08350715, + 0.06843123, 0.05931804, 0.03774492, -0.03016214, 0.0549344 , + -0.23227729, -0.2172487 , -0.10547152, -0.08018271, -0.07300715, + -0.0770617 , -0.07552639]), linear_terms=array([[0., 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model=ScalarModel(intercept=0.17429973881169664, linear_terms=array([ 2.70298754e-04, -3.09106006e-05, 1.40978604e-06]), square_terms=array([[2.77478710e-05, 2.26332451e-04, 1.44291033e-04], + [2.26332451e-04, 8.82227523e-02, 1.87432209e-01], + [1.44291033e-04, 1.87432209e-01, 4.05886882e-01]]), scale=0.033133735021424825, shift=array([5.12036855, 0.33903597, 0.93576554])), vector_model=VectorModel(intercepts=array([ 0.05267501, 0.10545582, 0.09377041, 0.09722369, 0.08350715, + 0.06843123, 0.05931804, 0.03774492, -0.03016214, 0.0549344 , + -0.23227729, -0.2172487 , -0.10547152, -0.08018271, -0.07300715, + -0.0770617 , -0.07552639]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]]), square_terms=array([[[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], 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x=array([5.08741985, 0.34221541, 0.93430985]), fval=0.17398999224518474, rho=1.2760574583541893, accepted=True, new_indices=array([], dtype=int32), old_indices_used=array([44, 49, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60]), old_indices_discarded=array([17, 18, 21, 24, 28, 31, 33, 34, 36, 37, 39, 43, 45, 46, 47, 48, 50]), step_length=0.03313373505039257, relative_step_length=1.0000000008742673, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([5.08741985, 0.34221541, 0.93430985]), radius=0.06626747004284965, bounds=Bounds(lower=array([1.1 , 0.01, 0.5 ]), upper=array([20. , 0.99, 1.1 ]))), model_indices=array([44, 49, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61]), model=ScalarModel(intercept=0.17399871546423445, linear_terms=array([5.54960169e-04, 2.77020491e-05, 2.46039514e-04]), square_terms=array([[1.12760714e-04, 1.09146716e-03, 9.82283047e-04], + [1.09146716e-03, 3.54762285e-01, 7.53825721e-01], + [9.82283047e-04, 7.53825721e-01, 1.63251500e+00]]), scale=0.06626747004284965, shift=array([5.08741985, 0.34221541, 0.93430985])), vector_model=VectorModel(intercepts=array([ 0.05267501, 0.10545582, 0.09377041, 0.09722369, 0.08350715, + 0.06843123, 0.05931804, 0.03774492, -0.03016214, 0.0549344 , + -0.23227729, -0.2172487 , -0.10547152, -0.08018271, -0.07300715, + -0.0770617 , -0.07552639]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]]), square_terms=array([[[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + 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25, 26, 27, 28, + 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 45, 46, + 47, 48, 50, 51]), step_length=0.0662677999938465, relative_step_length=1.000004979079428, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([5.02154349, 0.34875659, 0.93132 ]), radius=0.1325349400856993, bounds=Bounds(lower=array([1.1 , 0.01, 0.5 ]), upper=array([20. , 0.99, 1.1 ]))), model_indices=array([49, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62]), model=ScalarModel(intercept=0.17340700850452878, linear_terms=array([0.00109183, 0.00472696, 0.00984298]), square_terms=array([[4.56127079e-04, 4.44510297e-03, 4.16551232e-03], + [4.44510297e-03, 1.53012536e+00, 3.24711918e+00], + [4.16551232e-03, 3.24711918e+00, 7.01257022e+00]]), scale=0.1325349400856993, shift=array([5.02154349, 0.34875659, 0.93132 ])), vector_model=VectorModel(intercepts=array([ 0.05267501, 0.10545582, 0.09377041, 0.09722369, 0.08350715, + 0.06843123, 0.05931804, 0.03774492, -0.03016214, 0.0549344 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step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([4.84436454, 0.3458171 , 0.93240807]), radius=0.0010354292194195258, bounds=Bounds(lower=array([1.1 , 0.01, 0.5 ]), upper=array([20. , 0.99, 1.1 ]))), model_indices=array([87, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99]), model=ScalarModel(intercept=0.1725830437240501, linear_terms=array([ 2.41233698e-05, -2.61891003e-06, 5.11296505e-06]), square_terms=array([[ 4.37386430e-08, -5.79574560e-07, -1.57888647e-06], + [-5.79574560e-07, 1.02556710e-04, 2.17206204e-04], + [-1.57888647e-06, 2.17206204e-04, 4.67922792e-04]]), scale=0.0010354292194195258, shift=array([4.84436454, 0.3458171 , 0.93240807])), vector_model=VectorModel(intercepts=array([ 0.05267501, 0.10545582, 0.09377041, 0.09722369, 0.08350715, + 0.06843123, 0.05931804, 0.03774492, -0.03016214, 0.0549344 , + -0.23227729, -0.2172487 , -0.10547152, -0.08018271, -0.07300715, + -0.0770617 , -0.07552639]), 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100, 101, 102]), model=ScalarModel(intercept=0.17258247058638926, linear_terms=array([-2.68495297e-05, -2.10095588e-06, -2.07300030e-05]), square_terms=array([[1.91163962e-07, 3.32105210e-06, 5.86912190e-06], + [3.32105210e-06, 4.07207519e-04, 8.64705423e-04], + [5.86912190e-06, 8.64705423e-04, 1.86822036e-03]]), scale=0.0020708584388390515, shift=array([4.84334274, 0.34598281, 0.93232094])), vector_model=VectorModel(intercepts=array([ 0.05267501, 0.10545582, 0.09377041, 0.09722369, 0.08350715, + 0.06843123, 0.05931804, 0.03774492, -0.03016214, 0.0549344 , + -0.23227729, -0.2172487 , -0.10547152, -0.08018271, -0.07300715, + -0.0770617 , -0.07552639]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]]), square_terms=array([[[0., 0., 0.], + [0., 0., 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105]), model=ScalarModel(intercept=0.17258372705737116, linear_terms=array([ 4.09478695e-06, -3.55795689e-06, -4.27096698e-05]), square_terms=array([[3.35585618e-08, 2.15061082e-07, 1.37358651e-07], + [2.15061082e-07, 1.03219001e-04, 2.16664028e-04], + [1.37358651e-07, 2.16664028e-04, 4.61793255e-04]]), scale=0.0010354292194195258, shift=array([4.84438244, 0.34597441, 0.93234197])), vector_model=VectorModel(intercepts=array([ 0.05267501, 0.10545582, 0.09377041, 0.09722369, 0.08350715, + 0.06843123, 0.05931804, 0.03774492, -0.03016214, 0.0549344 , + -0.23227729, -0.2172487 , -0.10547152, -0.08018271, -0.07300715, + -0.0770617 , -0.07552639]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]]), square_terms=array([[[0., 0., 0.], + [0., 0., 0.], + [0., 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scale=0.5301397603427972, shift=array([5.3013976 , 0.35179043, 0.92170005])), candidate_index=123, candidate_x=array([4.8444368 , 0.34601283, 0.93235891]), index=123, x=array([4.8444368 , 0.34601283, 0.93235891]), fval=0.17254703939389457, rho=0.23884848773610878, accepted=True, new_indices=array([111, 112, 113, 114, 115, 116, 117, 118, 119, 120, 121, 122]), old_indices_used=array([104, 110]), old_indices_discarded=array([], dtype=int32), step_length=3.2357163106865805e-05, relative_step_length=1.0000000000001739, n_evals_per_point=1, n_evals_acceptance=1)], 'message': 'Absolute criterion change smaller than tolerance.', 'tranquilo_history': History for least_squares function with 124 entries., 'history': {'params': [{'CRRA': 5.301397603427972, 'WealthShare': 0.35179042920828707, 'DiscFac': 0.9217000493025207}, {'CRRA': 4.877555010789218, 'WealthShare': 0.01, 'DiscFac': 1.0004206381225442}, {'CRRA': 5.726445053953837, 'WealthShare': 0.038959478718889294, 'DiscFac': 1.1}, {'CRRA': 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5.339711633059152, 'WealthShare': 0.1818133180189851, 'WealthShift': 0.5560016722167602}, {'CRRA': 5.343603112819564, 'WealthShare': 0.19111935148758147, 'WealthShift': 0.583635269726531}, {'CRRA': 5.357006673348122, 'WealthShare': 0.19188292905024867, 'WealthShift': 0.6148773843412922}, {'CRRA': 5.379320769171532, 'WealthShare': 0.19348564036573143, 'WealthShift': 0.6785740404127536}, {'CRRA': 5.396894343341963, 'WealthShare': 0.19686825435639313, 'WealthShift': 0.8111685602635299}, {'CRRA': 5.374904869685874, 'WealthShare': 0.1916097636070166, 'WealthShift': 0.6115911010028502}, {'CRRA': 5.381102737463579, 'WealthShare': 0.19245387451236218, 'WealthShift': 0.644242921597286}, {'CRRA': 5.385016494822117, 'WealthShare': 0.19444457826407383, 'WealthShift': 0.6943233146265385}, {'CRRA': 5.370954455466027, 'WealthShare': 0.19380066310620106, 'WealthShift': 0.6787912227300882}, {'CRRA': 5.36576159111423, 'WealthShare': 0.1944841827989484, 'WealthShift': 0.6946412707076063}, {'CRRA': 5.362530858243278, 'WealthShare': 0.19371235845028822, 'WealthShift': 0.67917279093371}, {'CRRA': 5.371252044414068, 'WealthShare': 0.19515406179895806, 'WealthShift': 0.6748494653651586}, {'CRRA': 5.371040357003462, 'WealthShare': 0.19512570949497798, 'WealthShift': 0.6804574712649102}, {'CRRA': 5.370362032234467, 'WealthShare': 0.19301496853268316, 'WealthShift': 0.6791361950445876}, {'CRRA': 5.370417235247351, 'WealthShare': 0.1946836539449308, 'WealthShift': 0.6789290949944624}, {'CRRA': 5.371700118481283, 'WealthShare': 0.19407592989865619, 'WealthShift': 0.679466131617694}, {'CRRA': 5.370996809733228, 'WealthShare': 0.1932546349189789, 'WealthShift': 0.6779038972651502}, {'CRRA': 5.371282416198062, 'WealthShare': 0.1928112110018877, 'WealthShift': 0.6787645124805319}, {'CRRA': 5.3710903886459365, 'WealthShare': 0.1934205187933144, 'WealthShift': 0.6797526277529055}, {'CRRA': 5.3704769790314755, 'WealthShare': 0.19429995636141595, 'WealthShift': 0.6780101915875183}, {'CRRA': 5.371545682473069, 'WealthShare': 0.19411655863874636, 'WealthShift': 0.6779925063945972}, {'CRRA': 5.370195456559467, 'WealthShare': 0.19397745856737997, 'WealthShift': 0.6794840078126839}, {'CRRA': 5.370050397316498, 'WealthShare': 0.19350353913218477, 'WealthShift': 0.6783649794283761}, {'CRRA': 5.371962513757795, 'WealthShare': 0.19354151125781988, 'WealthShift': 0.6787284059664366}, {'CRRA': 5.37138823145291, 'WealthShare': 0.19474863411072363, 'WealthShift': 0.6787693935361694}, {'CRRA': 5.3710792065342154, 'WealthShare': 0.19443913068868013, 'WealthShift': 0.679621235613119}, {'CRRA': 5.3704034370938185, 'WealthShare': 0.19458142919799615, 'WealthShift': 0.6776431911313305}, {'CRRA': 5.371320550989001, 'WealthShare': 0.19446077911052448, 'WealthShift': 0.678607008167103}, {'CRRA': 5.3713519822030475, 'WealthShare': 0.1944618633719279, 'WealthShift': 0.6791772691529462}, {'CRRA': 5.371266391432918, 'WealthShare': 0.1943943314688513, 'WealthShift': 0.679443956662166}], 'criterion': [0.24222229239256646, 1.478112872055069, 1.1738993056575204, 7.66561489336726, 18.738700547401976, 19.22108795656615, 15.506705787934324, 12.31515961934518, 0.23576937639679463, 9.707223917852335, 1.2482439718131173, 20.90388989527211, 0.7443512934453255, 0.24479444524730848, 0.2614718904910609, 0.270639050852218, 0.24095668076641172, 0.2399553333009884, 0.2377361837426363, 0.2568729292948785, 0.23880933776883706, 0.2357308733203971, 0.23672808947597423, 0.23462018780083854, 0.23526585311770365, 0.23386060852077306, 0.23281729277673047, 0.23109088667954464, 0.23231088686731985, 0.22984874056451765, 0.2321432347041099, 0.2311825152488482, 0.2298724029405645, 0.23262807844020333, 0.23060109795757228, 0.2333646350605909, 0.22998277512898735, 0.23771152142310734, 0.23273062652367485, 0.23024047517833396, 0.23539451131722727, 0.23520968963219913, 0.23708932322781573, 0.23014224071617864, 0.24191165473844944, 0.23307446207864127, 0.22981068942013977, 0.22970924468774562, 0.22961013657146467, 0.22981789832329552, 0.22973138822808242, 0.22962474605065475, 0.22963112451216366, 0.22958113184400364, 0.22959160086907093, 0.22960873266061366, 0.22963318479728462, 0.22961335501541685, 0.22966650476648243, 0.22957347491137076, 0.22954657256751673, 0.2296255367268235, 0.2297114465837029, 0.22962539796630416, 0.2295392655379997, 0.2295439897979808, 0.22956976961891207, 0.22960795862685532, 0.22960143762896604, 0.2295819805696318, 0.22953900680686223, 0.22956535348444274, 0.2295484781109926, 0.2295457973718279, 0.22953817348169658], 'runtime': [0.0, 1.078445800114423, 1.1149003999307752, 1.1535559999756515, 1.1922693997621536, 1.2300137002021074, 1.2728542000986636, 1.3101439997553825, 1.3493002001196146, 1.3861357998102903, 1.4237115997821093, 1.4617324001155794, 1.5002863998524845, 2.6419434999115765, 3.6615598001517355, 4.674209500197321, 5.7083767000585794, 6.739310999866575, 7.906286799814552, 8.925660899840295, 9.94611269980669, 10.963380999863148, 11.982361000031233, 13.00331459986046, 14.01534829987213, 15.032428000122309, 16.052119500003755, 17.067473100032657, 18.08538859989494, 19.095149700064212, 20.1070157000795, 21.11918029980734, 22.27491270005703, 23.287277800031006, 24.42046120017767, 24.446721899788827, 24.48540070001036, 24.524533899966627, 24.56690760003403, 24.604305800050497, 24.64112879987806, 24.678917500190437, 24.717683599796146, 24.75592500017956, 24.79437270015478, 24.83348789997399, 25.926029299851507, 26.96925489977002, 28.003000599797815, 29.01732419990003, 30.056552299764007, 31.073117999825627, 32.104939199984074, 33.1367243998684, 34.14407660020515, 35.153611599933356, 36.16626589978114, 37.30677030002698, 38.441172500140965, 38.47760089999065, 38.51622289977968, 38.55528979981318, 38.59801559988409, 38.63672780012712, 38.67566310008988, 38.71459549991414, 38.75300749996677, 38.79171779984608, 38.83782930020243, 38.870700700208545, 39.96831429982558, 40.98857139982283, 42.03050069976598, 43.07035129982978, 44.10055600013584], 'batches': [0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 23, 23, 23, 23, 23, 23, 23, 23, 23, 23, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 36, 36, 36, 36, 36, 36, 36, 36, 36, 36, 36, 37, 38, 39, 40, 41]}" +convergence_report, +multistart_info,"{'start_parameters': [{'CRRA': 5.338780774481047, 'WealthShare': 0.17065528804872487, 'WealthShift': 0.0}, {'CRRA': 5.812664276213293, 'WealthShare': 0.23295294896519178, 'WealthShift': 6.996179195190264}, {'CRRA': 5.6712914737321025, 'WealthShare': 0.19427609444130123, 'WealthShift': 6.289245513555226}], 'local_optima': [Minimize with 3 free parameters terminated. + +The tranquilo_ls algorithm reported: Absolute criterion change smaller than tolerance. + +Independent of the convergence criteria used by tranquilo_ls, the strength of convergence can be assessed by the following criteria: + + one_step five_steps +relative_criterion_change 3.63e-06* 0.0001872 +relative_params_change 0.0003499 0.003202 +absolute_criterion_change 8.333e-07* 4.296e-05 +absolute_params_change 0.0002617 0.001639 + +(***: change <= 1e-10, **: change <= 1e-8, *: change <= 1e-5. Change refers to a change between accepted steps. The first column only considers the last step. The second column considers the last five steps.), Minimize with 3 free parameters terminated. + +The tranquilo_ls algorithm reported: Absolute criterion change smaller than tolerance. + +Independent of the convergence criteria used by tranquilo_ls, the strength of convergence can be assessed by the following criteria: + + one_step five_steps +relative_criterion_change 1.133e-05 7.917e-05 +relative_params_change 0.0002288 0.001211 +absolute_criterion_change 2.602e-06* 1.818e-05 +absolute_params_change 8.54e-05 0.001737 + +(***: change <= 1e-10, **: change <= 1e-8, *: change <= 1e-5. Change refers to a change between accepted steps. The first column only considers the last step. The second column considers the last five steps.), Minimize with 3 free parameters terminated. + +The tranquilo_ls algorithm reported: Absolute criterion change smaller than tolerance. + +Independent of the convergence criteria used by tranquilo_ls, the strength of convergence can be assessed by the following criteria: + + one_step five_steps +relative_criterion_change 2.534e-06* 0.001255 +relative_params_change 5.552e-05 0.0427 +absolute_criterion_change 5.817e-07* 0.000288 +absolute_params_change 8.297e-05 0.08045 + +(***: change <= 1e-10, **: change <= 1e-8, *: change <= 1e-5. Change refers to a change between accepted steps. The first column only considers the last step. The second column considers the last five steps.)], 'exploration_sample': [{'CRRA': 5.338780774481047, 'WealthShare': 0.17065528804872485, 'WealthShift': 0.0}, {'CRRA': 6.415625, 'WealthShare': 0.285625, 'WealthShift': 15.625}, {'CRRA': 7.00625, 'WealthShare': 0.19375, 'WealthShift': 31.25}, {'CRRA': 9.959375, 'WealthShare': 0.101875, 'WealthShift': 84.375}, {'CRRA': 8.1875, 'WealthShare': 0.3775, 'WealthShift': 62.5}, {'CRRA': 4.64375, 'WealthShare': 0.31625000000000003, 'WealthShift': 93.75}, {'CRRA': 12.9125, 'WealthShare': 0.1325, 'WealthShift': 87.5}, {'CRRA': 4.053125, 'WealthShare': 0.16312500000000002, 'WealthShift': 53.125}, {'CRRA': 2.871875, 'WealthShare': 0.469375, 'WealthShift': 46.875}, {'CRRA': 18.81875, 'WealthShare': 0.07125, 'WealthShift': 68.75}, {'CRRA': 15.274999999999999, 'WealthShare': 0.255, 'WealthShift': 25.0}, {'CRRA': 11.73125, 'WealthShare': 0.43875, 'WealthShift': 6.25}, {'CRRA': 17.046875, 'WealthShare': 0.224375, 'WealthShift': 21.875}, {'CRRA': 3.4625, 'WealthShare': 0.6225, 'WealthShift': 37.5}, {'CRRA': 14.684375, 'WealthShare': 0.346875, 'WealthShift': 59.375}, {'CRRA': 10.549999999999999, 'WealthShare': 0.5, 'WealthShift': 50.0}, {'CRRA': 9.368749999999999, 'WealthShare': 0.56125, 'WealthShift': 18.75}, {'CRRA': 13.503124999999999, 'WealthShare': 0.653125, 'WealthShift': 3.125}, {'CRRA': 18.228125, 'WealthShare': 0.408125, 'WealthShift': 78.125}, {'CRRA': 5.824999999999999, 'WealthShare': 0.745, 'WealthShift': 75.0}, {'CRRA': 7.596874999999999, 'WealthShare': 0.714375, 'WealthShift': 71.875}, {'CRRA': 19.409375, 'WealthShare': 0.591875, 'WealthShift': 34.375}, {'CRRA': 16.45625, 'WealthShare': 0.68375, 'WealthShift': 81.25}, {'CRRA': 17.6375, 'WealthShare': 0.8674999999999999, 'WealthShift': 12.5}, {'CRRA': 15.865624999999998, 'WealthShare': 0.775625, 'WealthShift': 65.625}, {'CRRA': 14.093749999999998, 'WealthShare': 0.80625, 'WealthShift': 43.75}, {'CRRA': 5.234375, 'WealthShare': 0.836875, 'WealthShift': 9.375}, {'CRRA': 8.778125, 'WealthShare': 0.898125, 'WealthShift': 28.125}, {'CRRA': 2.28125, 'WealthShare': 0.92875, 'WealthShift': 56.25}, {'CRRA': 12.321874999999999, 'WealthShare': 0.959375, 'WealthShift': 96.875}], 'exploration_results': array([2.42222292e-01, 4.68695243e-01, 6.55725054e-01, 7.71100519e-01, + 1.19425789e+00, 1.58158215e+00, 1.58170972e+00, 2.10988168e+00, + 2.53770191e+00, 3.19288105e+00, 3.47314230e+00, 3.48315006e+00, + 3.92293459e+00, 4.56511870e+00, 5.33390087e+00, 5.34621006e+00, + 6.48994604e+00, 9.32970623e+00, 1.17999718e+01, 1.57570577e+01, + 1.66647063e+01, 2.65180559e+01, 4.77377487e+01, 8.29741042e+01, + 8.62618718e+01, 8.81150175e+01, 1.31509063e+02, 1.97370096e+02, + 6.42774449e+02, 7.33084130e+02])}" +algorithm_output,"{'states': [State(trustregion=Region(center=array([5.33878077, 0.17065529, 0. ]), radius=0.5338780774481048, bounds=Bounds(lower=array([1.1 , 0.01, 0. ]), upper=array([ 20. , 0.99, 100. ]))), model_indices=[0], model=ScalarModel(intercept=0.24222229239256646, linear_terms=array([0., 0., 0.]), square_terms=array([[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]]), scale=0.5338780774481048, shift=array([5.33878077, 0.17065529, 0. ])), vector_model=VectorModel(intercepts=array([ 0.03980461, 0.08715954, 0.08449923, 0.10710153, 0.11905802, + 0.13160042, 0.14768033, 0.15905648, 0.07367938, 0.12505611, + -0.21199057, -0.25057516, -0.05680053, -0.03662718, -0.03009585, + -0.03160325, -0.02367163]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]]), square_terms=array([[[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]]]), scale=0.5338780774481048, shift=array([5.33878077, 0.17065529, 0. ])), candidate_index=0, candidate_x=array([5.33878077, 0.17065529, 0. ]), index=0, x=array([5.33878077, 0.17065529, 0. ]), fval=0.24222229239256646, rho=nan, accepted=True, new_indices=[0], old_indices_used=[], old_indices_discarded=[], step_length=None, relative_step_length=None, n_evals_per_point=None, n_evals_acceptance=None), State(trustregion=Region(center=array([5.33878077, 0.17065529, 0. ]), radius=0.5338780774481048, bounds=Bounds(lower=array([1.1 , 0.01, 0. ]), upper=array([ 20. , 0.99, 100. ]))), model_indices=array([ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12]), model=ScalarModel(intercept=2.225040705891025, linear_terms=array([-0.41697775, 7.48428914, -0.17091496]), square_terms=array([[ 4.61705353e-02, -7.15556597e-01, 1.51914511e-02], + [-7.15556597e-01, 1.37527722e+01, -2.97488982e-01], + [ 1.51914511e-02, -2.97488982e-01, 6.91651527e-03]]), scale=array([0.43030358, 0.29547944, 0.21515179]), shift=array([5.33878077, 0.30547944, 0.21515179])), vector_model=VectorModel(intercepts=array([ 0.03980461, 0.08715954, 0.08449923, 0.10710153, 0.11905802, + 0.13160042, 0.14768033, 0.15905648, 0.07367938, 0.12505611, + -0.21199057, -0.25057516, -0.05680053, -0.03662718, -0.03009585, + -0.03160325, -0.02367163]), 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State(trustregion=Region(center=array([5.33002354, 0.17880899, 0.16290546]), radius=0.03336737984050655, bounds=Bounds(lower=array([1.1 , 0.01, 0. ]), upper=array([ 20. , 0.99, 100. ]))), model_indices=array([ 0, 16, 17, 18, 19, 20, 21, 22]), model=ScalarModel(intercept=0.2353621409779833, linear_terms=array([-8.14409317e-06, 3.93183005e-03, -1.42315911e-03]), square_terms=array([[ 3.70635713e-05, 8.65491261e-04, -3.88139805e-05], + [ 8.65491261e-04, 9.48655967e-02, -3.68813140e-03], + [-3.88139805e-05, -3.68813140e-03, 1.59862148e-04]]), scale=0.03336737984050655, shift=array([5.33002354, 0.17880899, 0.16290546])), vector_model=VectorModel(intercepts=array([ 0.03980461, 0.08715954, 0.08449923, 0.10710153, 0.11905802, + 0.13160042, 0.14768033, 0.15905648, 0.07367938, 0.12505611, + -0.21199057, -0.25057516, -0.05680053, -0.03662718, -0.03009585, + -0.03160325, -0.02367163]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], 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candidate_x=array([5.33291758, 0.18962821, 0.56908272]), index=29, x=array([5.33291758, 0.18962821, 0.56908272]), fval=0.22984874056451765, rho=0.8791826602762222, accepted=True, new_indices=array([], dtype=int32), old_indices_used=array([ 8, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28]), old_indices_discarded=array([ 0, 1, 2, 3, 4, 5, 6, 7, 10, 12, 13, 14, 15, 16, 17]), step_length=0.13468817595672403, relative_step_length=1.0091305985106032, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([5.33291758, 0.18962821, 0.56908272]), radius=0.2669390387240524, bounds=Bounds(lower=array([1.1 , 0.01, 0. ]), upper=array([ 20. , 0.99, 100. ]))), model_indices=array([ 2, 8, 19, 21, 22, 23, 24, 25, 26, 27, 28, 29]), model=ScalarModel(intercept=0.2472192748047931, linear_terms=array([ 0.00288894, 0.29428743, -0.01173496]), square_terms=array([[ 1.76702756e-03, 4.10334146e-02, -1.66808852e-03], + [ 4.10334146e-02, 2.64561735e+00, -8.66366920e-02], + 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vector_model=VectorModel(intercepts=array([ 0.03980461, 0.08715954, 0.08449923, 0.10710153, 0.11905802, + 0.13160042, 0.14768033, 0.15905648, 0.07367938, 0.12505611, + -0.21199057, -0.25057516, -0.05680053, -0.03662718, -0.03009585, + -0.03160325, -0.02367163]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]]), square_terms=array([[[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 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0.18962821, 0.56908272]), radius=0.016683689920253274, bounds=Bounds(lower=array([1.1 , 0.01, 0. ]), upper=array([ 20. , 0.99, 100. ]))), model_indices=array([29, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45]), model=ScalarModel(intercept=0.22990493283945845, linear_terms=array([-1.03738771e-04, -1.68226271e-03, -6.74238130e-05]), square_terms=array([[ 9.10673381e-06, 2.28039022e-04, -8.01399215e-06], + [ 2.28039022e-04, 2.35834730e-02, -6.68846684e-04], + [-8.01399215e-06, -6.68846684e-04, 1.97600773e-05]]), scale=0.016683689920253274, shift=array([5.33291758, 0.18962821, 0.56908272])), vector_model=VectorModel(intercepts=array([ 0.03980461, 0.08715954, 0.08449923, 0.10710153, 0.11905802, + 0.13160042, 0.14768033, 0.15905648, 0.07367938, 0.12505611, + -0.21199057, -0.25057516, -0.05680053, -0.03662718, -0.03009585, + -0.03160325, -0.02367163]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + 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candidate_x=array([5.33878077, 0.17065529, 0. ]), index=0, x=array([5.33878077, 0.17065529, 0. ]), fval=0.24222229239256646, rho=nan, accepted=True, new_indices=[0], old_indices_used=[], old_indices_discarded=[], step_length=None, relative_step_length=None, n_evals_per_point=None, n_evals_acceptance=None), State(trustregion=Region(center=array([5.33878077, 0.17065529, 0. ]), radius=0.5338780774481048, bounds=Bounds(lower=array([1.1 , 0.01, 0. ]), upper=array([ 20. , 0.99, 100. ]))), model_indices=array([ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12]), model=ScalarModel(intercept=2.225040705891025, linear_terms=array([-0.41697775, 7.48428914, -0.17091496]), square_terms=array([[ 4.61705353e-02, -7.15556597e-01, 1.51914511e-02], + [-7.15556597e-01, 1.37527722e+01, -2.97488982e-01], + [ 1.51914511e-02, -2.97488982e-01, 6.91651527e-03]]), scale=array([0.43030358, 0.29547944, 0.21515179]), shift=array([5.33878077, 0.30547944, 0.21515179])), vector_model=VectorModel(intercepts=array([ 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bounds=Bounds(lower=array([1.1 , 0.01, 0. ]), upper=array([ 20. , 0.99, 100. ]))), model_indices=array([ 0, 1, 2, 4, 5, 7, 8, 9, 10, 11, 12, 13]), model=ScalarModel(intercept=0.425381512628019, linear_terms=array([-0.05492339, 1.6515207 , -0.01207703]), square_terms=array([[ 8.17527296e-03, -1.66195924e-01, 1.66474843e-03], + [-1.66195924e-01, 5.78105326e+00, -4.38301566e-02], + [ 1.66474843e-03, -4.38301566e-02, 4.71218119e-04]]), scale=array([0.21515179, 0.18790354, 0.1075759 ]), shift=array([5.33878077, 0.19790354, 0.1075759 ])), vector_model=VectorModel(intercepts=array([ 0.03980461, 0.08715954, 0.08449923, 0.10710153, 0.11905802, + 0.13160042, 0.14768033, 0.15905648, 0.07367938, 0.12505611, + -0.21199057, -0.25057516, -0.05680053, -0.03662718, -0.03009585, + -0.03160325, -0.02367163]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + 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scale=0.5338780774481048, shift=array([5.33878077, 0.17065529, 0. ])), candidate_index=14, candidate_x=array([5.55393257, 0.1482009 , 0. ]), index=0, x=array([5.33878077, 0.17065529, 0. ]), fval=0.24222229239256646, rho=-0.2762680450576785, accepted=False, new_indices=array([], dtype=int32), old_indices_used=array([ 0, 1, 2, 4, 5, 7, 8, 9, 10, 11, 12, 13]), old_indices_discarded=array([3, 6]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([5.33878077, 0.17065529, 0. ]), radius=0.1334695193620262, bounds=Bounds(lower=array([1.1 , 0.01, 0. ]), upper=array([ 20. , 0.99, 100. ]))), model_indices=array([ 0, 1, 2, 4, 7, 8, 9, 10, 11, 12, 13, 14]), model=ScalarModel(intercept=0.25159110698009957, linear_terms=array([-0.01524465, 0.47423814, -0.00627023]), square_terms=array([[ 2.17792939e-03, -4.77186682e-02, 7.80957785e-04], + [-4.77186682e-02, 1.83079477e+00, -2.76050226e-02], + [ 7.80957785e-04, -2.76050226e-02, 4.40535462e-04]]), scale=array([0.1075759 , 0.1075759 , 0.05378795]), shift=array([5.33878077, 0.17065529, 0.05378795])), vector_model=VectorModel(intercepts=array([ 0.03980461, 0.08715954, 0.08449923, 0.10710153, 0.11905802, + 0.13160042, 0.14768033, 0.15905648, 0.07367938, 0.12505611, + -0.21199057, -0.25057516, -0.05680053, -0.03662718, -0.03009585, + -0.03160325, -0.02367163]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]]), square_terms=array([[[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 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relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([5.33878077, 0.17065529, 0. ]), radius=0.0667347596810131, bounds=Bounds(lower=array([1.1 , 0.01, 0. ]), upper=array([ 20. , 0.99, 100. ]))), model_indices=array([ 0, 10, 14, 15]), model=ScalarModel(intercept=0.1884967041414315, linear_terms=array([-0.00049831, 0.00705515, -0.03692845]), square_terms=array([[ 1.08791636e-04, 3.07187991e-03, -1.03846231e-03], + [ 3.07187991e-03, 2.45954542e-01, 6.85505606e-03], + [-1.03846231e-03, 6.85505606e-03, 3.35942789e-02]]), scale=array([0.05378795, 0.05378795, 0.02689397]), shift=array([5.33878077, 0.17065529, 0.02689397])), vector_model=VectorModel(intercepts=array([ 0.03980461, 0.08715954, 0.08449923, 0.10710153, 0.11905802, + 0.13160042, 0.14768033, 0.15905648, 0.07367938, 0.12505611, + -0.21199057, -0.25057516, -0.05680053, -0.03662718, -0.03009585, + -0.03160325, -0.02367163]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.], + [0., 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0.08449923, 0.10710153, 0.11905802, + 0.13160042, 0.14768033, 0.15905648, 0.07367938, 0.12505611, + -0.21199057, -0.25057516, -0.05680053, -0.03662718, -0.03009585, + -0.03160325, -0.02367163]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]]), square_terms=array([[[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 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0.27682373, 0.28194461]), shift=array([5.67791134, 0.28682373, 6.82432251])), vector_model=VectorModel(intercepts=array([ 0.02515583, 0.06381521, 0.06386806, 0.09321649, 0.1132282 , + 0.13241041, 0.15213805, 0.11382721, -0.00122978, 0.01828718, + -0.34841965, -0.40948853, -0.01328219, 0.01123573, 0.02522056, + 0.04033998, 0.06941292]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]]), square_terms=array([[[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 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x=array([5.67220534, 0.2794848 , 6.39080358]), fval=0.3078435872229235, rho=1.1650054937337413, accepted=True, new_indices=array([], dtype=int32), old_indices_used=array([35, 36, 37, 38, 39, 40, 41, 42]), old_indices_discarded=array([], dtype=int32), step_length=0.04628805319266375, relative_step_length=1.0585904540463658, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([5.67220534, 0.2794848 , 6.39080358]), radius=0.0874522399398783, bounds=Bounds(lower=array([1.1 , 0.01, 0. ]), upper=array([ 20. , 0.99, 100. ]))), model_indices=array([10, 30, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43]), model=ScalarModel(intercept=0.312469012000744, linear_terms=array([0.0006424 , 0.02844622, 0.0008161 ]), square_terms=array([[ 5.62722956e-04, 7.63491905e-03, -8.19951703e-05], + [ 7.63491905e-03, 2.06477523e-01, -1.47782624e-03], + [-8.19951703e-05, -1.47782624e-03, 1.63030415e-05]]), scale=0.0874522399398783, shift=array([5.67220534, 0.2794848 , 6.39080358])), vector_model=VectorModel(intercepts=array([ 0.02515583, 0.06381521, 0.06386806, 0.09321649, 0.1132282 , + 0.13241041, 0.15213805, 0.11382721, -0.00122978, 0.01828718, + -0.34841965, -0.40948853, -0.01328219, 0.01123573, 0.02522056, + 0.04033998, 0.06941292]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]]), square_terms=array([[[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 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State(trustregion=Region(center=array([5.67220534, 0.2794848 , 6.39080358]), radius=0.04372611996993915, bounds=Bounds(lower=array([1.1 , 0.01, 0. ]), upper=array([ 20. , 0.99, 100. ]))), model_indices=array([35, 36, 37, 38, 39, 40, 41, 42, 43, 44]), model=ScalarModel(intercept=0.30810133617053853, linear_terms=array([-5.37601995e-05, -7.00924716e-04, 6.13829298e-04]), square_terms=array([[ 1.69906512e-04, 3.48813268e-03, -4.47825909e-05], + [ 3.48813268e-03, 1.22865562e-01, -1.30475046e-03], + [-4.47825909e-05, -1.30475046e-03, 1.56904743e-05]]), scale=0.04372611996993915, shift=array([5.67220534, 0.2794848 , 6.39080358])), vector_model=VectorModel(intercepts=array([ 0.02515583, 0.06381521, 0.06386806, 0.09321649, 0.1132282 , + 0.13241041, 0.15213805, 0.11382721, -0.00122978, 0.01828718, + -0.34841965, -0.40948853, -0.01328219, 0.01123573, 0.02522056, + 0.04033998, 0.06941292]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 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41, 42, 43, 44, 45, 46, 47, 48]), model=ScalarModel(intercept=1.0215763649772467, linear_terms=array([ 0.14375631, 4.04635095, -0.05668364]), square_terms=array([[ 2.61048432e-02, 4.02728139e-01, -7.94395225e-03], + [ 4.02728139e-01, 1.13099345e+01, -1.85248296e-01], + [-7.94395225e-03, -1.85248296e-01, 3.39233697e-03]]), scale=array([0.56388923, 0.41557528, 0.56388923]), shift=array([5.52684234, 0.42557528, 5.80609831])), vector_model=VectorModel(intercepts=array([ 0.02515583, 0.06381521, 0.06386806, 0.09321649, 0.1132282 , + 0.13241041, 0.15213805, 0.11382721, -0.00122978, 0.01828718, + -0.34841965, -0.40948853, -0.01328219, 0.01123573, 0.02522056, + 0.04033998, 0.06941292]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]]), 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candidate_x=array([5.47795249, 0.27137126, 5.24220908]), index=49, x=array([5.47795249, 0.27137126, 5.24220908]), fval=0.2889275687162242, rho=0.9414379695286359, accepted=True, new_indices=array([], dtype=int32), old_indices_used=array([36, 37, 38, 39, 41, 42, 43, 44, 45, 46, 47, 48]), old_indices_discarded=array([ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, + 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, + 34, 35, 40]), step_length=0.5660353098175912, relative_step_length=0.8090634816883041, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([5.47795249, 0.27137126, 5.24220908]), radius=1.3992358390380528, bounds=Bounds(lower=array([1.1 , 0.01, 0. ]), upper=array([ 20. , 0.99, 100. ]))), model_indices=array([ 4, 10, 11, 30, 35, 37, 41, 44, 46, 47, 48, 49]), model=ScalarModel(intercept=8.401379808041456, linear_terms=array([20.48337965, 36.87386893, -0.97232092]), square_terms=array([[ 2.73718279e+01, 4.74699169e+01, 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old_indices_used=array([ 4, 10, 11, 30, 35, 37, 41, 44, 46, 47, 48, 49]), old_indices_discarded=array([ 0, 1, 2, 3, 5, 6, 7, 8, 9, 12, 13, 14, 15, 16, 17, 18, 19, + 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 31, 32, 33, 34, 36, 38, 39, + 40, 42, 43, 45]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([5.47795249, 0.27137126, 5.24220908]), radius=0.6996179195190264, bounds=Bounds(lower=array([1.1 , 0.01, 0. ]), upper=array([ 20. , 0.99, 100. ]))), model_indices=array([36, 37, 38, 41, 42, 43, 44, 45, 46, 47, 48, 49]), model=ScalarModel(intercept=1.0328048943255177, linear_terms=array([ 0.14706337, 4.05118743, -0.06028908]), square_terms=array([[ 2.63006632e-02, 3.99779202e-01, -8.22079292e-03], + [ 3.99779202e-01, 1.10294613e+01, -1.88747720e-01], + [-8.22079292e-03, -1.88747720e-01, 3.58770611e-03]]), scale=array([0.56388923, 0.41263024, 0.56388923]), shift=array([5.47795249, 0.42263024, 5.24220908])), vector_model=VectorModel(intercepts=array([ 0.02515583, 0.06381521, 0.06386806, 0.09321649, 0.1132282 , + 0.13241041, 0.15213805, 0.11382721, -0.00122978, 0.01828718, + -0.34841965, -0.40948853, -0.01328219, 0.01123573, 0.02522056, + 0.04033998, 0.06941292]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]]), square_terms=array([[[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 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+ 34, 35, 39, 40, 50]), step_length=0.569074661100749, relative_step_length=0.8134077833397645, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([5.4014905 , 0.26603536, 4.67831985]), radius=1.3992358390380528, bounds=Bounds(lower=array([1.1 , 0.01, 0. ]), upper=array([ 20. , 0.99, 100. ]))), model_indices=array([37, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51]), model=ScalarModel(intercept=1.629273584089034, linear_terms=array([ 0.61497725, 5.59543793, -0.20069807]), square_terms=array([[ 0.18910149, 1.29985268, -0.05669145], + [ 1.29985268, 11.59567242, -0.45769195], + [-0.05669145, -0.45769195, 0.01956068]]), scale=array([1.12777846, 0.49 , 1.12777846]), shift=array([5.4014905 , 0.5 , 4.67831985])), vector_model=VectorModel(intercepts=array([ 0.02515583, 0.06381521, 0.06386806, 0.09321649, 0.1132282 , + 0.13241041, 0.15213805, 0.11382721, -0.00122978, 0.01828718, + -0.34841965, -0.40948853, -0.01328219, 0.01123573, 0.02522056, + 0.04033998, 0.06941292]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]]), square_terms=array([[[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + 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radius=2.7984716780761056, bounds=Bounds(lower=array([1.1 , 0.01, 0. ]), upper=array([ 20. , 0.99, 100. ]))), model_indices=array([37, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52]), model=ScalarModel(intercept=1.488299231526368, linear_terms=array([ 0.68708864, 4.68077783, -0.25965598]), square_terms=array([[ 0.36780394, 1.27824646, -0.10258544], + [ 1.27824646, 8.94190812, -0.55744366], + [-0.10258544, -0.55744366, 0.04079265]]), scale=array([2.25555691, 0.49 , 2.25555691]), shift=array([5.58019624, 0.5 , 3.55054139])), vector_model=VectorModel(intercepts=array([ 0.02515583, 0.06381521, 0.06386806, 0.09321649, 0.1132282 , + 0.13241041, 0.15213805, 0.11382721, -0.00122978, 0.01828718, + -0.34841965, -0.40948853, -0.01328219, 0.01123573, 0.02522056, + 0.04033998, 0.06941292]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]]), square_terms=array([[[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]]]), scale=0.6996179195190264, shift=array([5.81266428, 0.23295295, 6.9961792 ])), candidate_index=53, candidate_x=array([5.08211349, 0.22842295, 1.29498448]), index=53, x=array([5.08211349, 0.22842295, 1.29498448]), fval=0.24778697688048176, rho=0.5404450920215796, accepted=True, new_indices=array([], dtype=int32), old_indices_used=array([37, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52]), old_indices_discarded=array([ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, + 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, + 34, 35, 36, 38, 39, 40, 41]), step_length=2.309907709026206, relative_step_length=0.8254175760014203, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([5.08211349, 0.22842295, 1.29498448]), radius=5.596943356152211, bounds=Bounds(lower=array([1.1 , 0.01, 0. ]), upper=array([ 20. , 0.99, 100. ]))), model_indices=array([ 4, 9, 11, 14, 29, 30, 47, 49, 50, 51, 52, 53]), model=ScalarModel(intercept=11.714007670319425, linear_terms=array([24.50039079, 41.60470357, -4.28313711]), square_terms=array([[27.62848504, 45.16147148, -4.78880059], + [45.16147148, 75.49315113, -7.88257189], + [-4.78880059, -7.88257189, 0.83480515]]), scale=array([4.24661366, 0.49 , 2.90304915]), shift=array([5.34661366, 0.5 , 2.90304915])), vector_model=VectorModel(intercepts=array([ 0.02515583, 0.06381521, 0.06386806, 0.09321649, 0.1132282 , + 0.13241041, 0.15213805, 0.11382721, -0.00122978, 0.01828718, + -0.34841965, -0.40948853, -0.01328219, 0.01123573, 0.02522056, + 0.04033998, 0.06941292]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]]), square_terms=array([[[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 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rho=-2.6229548840900434, accepted=False, new_indices=array([], dtype=int32), old_indices_used=array([ 4, 9, 11, 14, 29, 30, 47, 49, 50, 51, 52, 53]), old_indices_discarded=array([ 0, 1, 2, 3, 5, 6, 7, 8, 10, 12, 13, 15, 16, 17, 18, 19, 20, + 21, 22, 23, 24, 25, 26, 27, 28, 31, 32, 33, 34, 35, 36, 37, 38, 39, + 40, 41, 42, 43, 44, 45, 46, 48]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([5.08211349, 0.22842295, 1.29498448]), radius=2.7984716780761056, bounds=Bounds(lower=array([1.1 , 0.01, 0. ]), upper=array([ 20. , 0.99, 100. ]))), model_indices=array([37, 42, 44, 46, 47, 48, 49, 50, 51, 52, 53, 54]), model=ScalarModel(intercept=1.7564665441870613, linear_terms=array([ 0.48912219, 5.07900078, -0.29740787]), square_terms=array([[ 0.1529226 , 0.60855853, -0.04226286], + [ 0.60855853, 8.41899891, -0.52187489], + [-0.04226286, -0.52187489, 0.03505869]]), scale=array([2.25555691, 0.49 , 1.7752707 ]), shift=array([5.08211349, 0.5 , 1.7752707 ])), vector_model=VectorModel(intercepts=array([ 0.02515583, 0.06381521, 0.06386806, 0.09321649, 0.1132282 , + 0.13241041, 0.15213805, 0.11382721, -0.00122978, 0.01828718, + -0.34841965, -0.40948853, -0.01328219, 0.01123573, 0.02522056, + 0.04033998, 0.06941292]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]]), square_terms=array([[[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + 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24, 25, 26, 27, 28, 29, 30, 31, 32, 33, + 34, 35, 36, 38, 39, 40, 41, 43, 45]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([5.08211349, 0.22842295, 1.29498448]), radius=1.3992358390380528, bounds=Bounds(lower=array([1.1 , 0.01, 0. ]), upper=array([ 20. , 0.99, 100. ]))), model_indices=array([37, 44, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55]), model=ScalarModel(intercept=1.413470861366983, linear_terms=array([-0.20579534, 3.45109869, -0.17983883]), square_terms=array([[ 0.08818994, -0.14324532, 0.0077864 ], + [-0.14324532, 5.59046525, -0.27774519], + [ 0.0077864 , -0.27774519, 0.01448073]]), scale=array([1.12777846, 0.49 , 1.12777846]), shift=array([5.08211349, 0.5 , 1.29498448])), vector_model=VectorModel(intercepts=array([ 0.02515583, 0.06381521, 0.06386806, 0.09321649, 0.1132282 , + 0.13241041, 0.15213805, 0.11382721, -0.00122978, 0.01828718, + -0.34841965, -0.40948853, -0.01328219, 0.01123573, 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radius=0.6996179195190264, bounds=Bounds(lower=array([1.1 , 0.01, 0. ]), upper=array([ 20. , 0.99, 100. ]))), model_indices=array([50, 51, 52, 53, 54, 55, 56]), model=ScalarModel(intercept=0.8726934072149458, linear_terms=array([-0.0783212 , 2.00091325, -0.09456309]), square_terms=array([[ 0.0203444 , -0.03857019, 0.00397376], + [-0.03857019, 3.83246439, -0.14592643], + [ 0.00397376, -0.14592643, 0.00645507]]), scale=array([0.56388923, 0.39115609, 0.56388923]), shift=array([5.08211349, 0.40115609, 1.29498448])), vector_model=VectorModel(intercepts=array([ 0.02515583, 0.06381521, 0.06386806, 0.09321649, 0.1132282 , + 0.13241041, 0.15213805, 0.11382721, -0.00122978, 0.01828718, + -0.34841965, -0.40948853, -0.01328219, 0.01123573, 0.02522056, + 0.04033998, 0.06941292]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 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0.1132282 , + 0.13241041, 0.15213805, 0.11382721, -0.00122978, 0.01828718, + -0.34841965, -0.40948853, -0.01328219, 0.01123573, 0.02522056, + 0.04033998, 0.06941292]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]]), square_terms=array([[[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + 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relative_step_length=1.0600922623051872, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([5.33869833, 0.20073019, 0.94626119]), radius=0.3498089597595132, bounds=Bounds(lower=array([1.1 , 0.01, 0. ]), upper=array([ 20. , 0.99, 100. ]))), model_indices=array([53, 57, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69]), model=ScalarModel(intercept=0.34007729667017145, linear_terms=array([ 0.02037288, 1.09201706, -0.02759842]), square_terms=array([[ 3.67439486e-03, 9.39073880e-02, -3.03941614e-03], + [ 9.39073880e-02, 5.48630084e+00, -1.48255420e-01], + [-3.03941614e-03, -1.48255420e-01, 4.16295796e-03]]), scale=array([0.28194461, 0.2363374 , 0.28194461]), shift=array([5.33869833, 0.2463374 , 0.94626119])), vector_model=VectorModel(intercepts=array([ 0.02515583, 0.06381521, 0.06386806, 0.09321649, 0.1132282 , + 0.13241041, 0.15213805, 0.11382721, -0.00122978, 0.01828718, + -0.34841965, -0.40948853, -0.01328219, 0.01123573, 0.02522056, + 0.04033998, 0.06941292]), 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model=ScalarModel(intercept=0.23105408610332923, linear_terms=array([-0.0006138 , -0.00195249, 0.00093336]), square_terms=array([[ 1.24533163e-03, 2.89626025e-02, -9.10786552e-04], + [ 2.89626025e-02, 2.67981548e+00, -6.39153209e-02], + [-9.10786552e-04, -6.39153209e-02, 1.59136186e-03]]), scale=0.1749044798797566, shift=array([5.33869833, 0.20073019, 0.94626119])), vector_model=VectorModel(intercepts=array([ 0.02515583, 0.06381521, 0.06386806, 0.09321649, 0.1132282 , + 0.13241041, 0.15213805, 0.11382721, -0.00122978, 0.01828718, + -0.34841965, -0.40948853, -0.01328219, 0.01123573, 0.02522056, + 0.04033998, 0.06941292]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]]), square_terms=array([[[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 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x=array([5.37701979, 0.19637249, 0.77552158]), fval=0.22975800522408243, rho=0.8228733999861161, accepted=True, new_indices=array([], dtype=int32), old_indices_used=array([53, 60, 62, 64, 65, 66, 67, 68, 69, 70]), old_indices_discarded=array([], dtype=int32), step_length=0.17504153263478317, relative_step_length=1.0007835863044834, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([5.37701979, 0.19637249, 0.77552158]), radius=0.3498089597595132, bounds=Bounds(lower=array([1.1 , 0.01, 0. ]), upper=array([ 20. , 0.99, 100. ]))), model_indices=array([53, 57, 60, 62, 64, 65, 66, 67, 68, 69, 70, 71]), model=ScalarModel(intercept=0.32928826166731434, linear_terms=array([ 0.01408983, 0.97330408, -0.02555177]), square_terms=array([[ 3.33165512e-03, 6.78396125e-02, -2.45923055e-03], + [ 6.78396125e-02, 4.77687728e+00, -1.33384029e-01], + [-2.45923055e-03, -1.33384029e-01, 3.89493474e-03]]), scale=array([0.28194461, 0.23415855, 0.28194461]), shift=array([5.37701979, 0.24415855, 0.77552158])), vector_model=VectorModel(intercepts=array([ 0.02515583, 0.06381521, 0.06386806, 0.09321649, 0.1132282 , + 0.13241041, 0.15213805, 0.11382721, -0.00122978, 0.01828718, + -0.34841965, -0.40948853, -0.01328219, 0.01123573, 0.02522056, + 0.04033998, 0.06941292]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]]), square_terms=array([[[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 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x=array([5.37273054, 0.19594589, 0.75010477]), fval=0.2296397835138107, rho=-0.38591559280998283, accepted=False, new_indices=array([], dtype=int32), old_indices_used=array([53, 62, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73]), old_indices_discarded=array([], dtype=int32), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([5.37273054, 0.19594589, 0.75010477]), radius=0.0874522399398783, bounds=Bounds(lower=array([1.1 , 0.01, 0. ]), upper=array([ 20. , 0.99, 100. ]))), model_indices=array([67, 68, 69, 70, 71, 72, 73, 74]), model=ScalarModel(intercept=0.22990165696401943, linear_terms=array([-0.00100953, -0.06567983, 0.00157013]), square_terms=array([[ 2.70902173e-04, 3.76414885e-03, -1.47804139e-04], + [ 3.76414885e-03, 2.99310015e-01, -8.25967854e-03], + [-1.47804139e-04, -8.25967854e-03, 2.46108361e-04]]), scale=0.0874522399398783, shift=array([5.37273054, 0.19594589, 0.75010477])), vector_model=VectorModel(intercepts=array([ 0.02515583, 0.06381521, 0.06386806, 0.09321649, 0.1132282 , + 0.13241041, 0.15213805, 0.11382721, -0.00122978, 0.01828718, + -0.34841965, -0.40948853, -0.01328219, 0.01123573, 0.02522056, + 0.04033998, 0.06941292]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]]), square_terms=array([[[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 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x=array([5.81071335, 0.1944286 , 5.9101968 ]), fval=0.4418926380517428, rho=0.06149806074678534, accepted=True, new_indices=array([], dtype=int32), old_indices_used=array([ 0, 4, 9, 10, 14]), old_indices_discarded=array([], dtype=int32), step_length=0.1701936646856471, relative_step_length=1.0824424921484033, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([5.81071335, 0.1944286 , 5.9101968 ]), radius=0.07861556891944033, bounds=Bounds(lower=array([1.1 , 0.01, 0. ]), upper=array([ 20. , 0.99, 100. ]))), model_indices=array([10, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27]), model=ScalarModel(intercept=0.42076836552635977, linear_terms=array([ 0.0093902 , -0.20121153, 0.01715171]), square_terms=array([[ 3.61193666e-04, -1.49324928e-03, 1.63080186e-04], + [-1.49324928e-03, 2.01402114e-01, -1.10062539e-02], + [ 1.63080186e-04, -1.10062539e-02, 6.88503559e-04]]), scale=0.07861556891944033, shift=array([5.81071335, 0.1944286 , 5.9101968 ])), 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n_evals_acceptance=1), State(trustregion=Region(center=array([5.77865656, 0.2644669 , 5.8815059 ]), radius=0.15723113783888065, bounds=Bounds(lower=array([1.1 , 0.01, 0. ]), upper=array([ 20. , 0.99, 100. ]))), model_indices=array([15, 16, 17, 18, 19, 20, 21, 22, 24, 25, 27, 28]), model=ScalarModel(intercept=0.307142003498755, linear_terms=array([ 0.00474574, -0.038802 , 0.00425179]), square_terms=array([[ 1.96783841e-03, 3.22213113e-02, -7.26159397e-04], + [ 3.22213113e-02, 1.04637626e+00, -2.21910765e-02], + [-7.26159397e-04, -2.21910765e-02, 5.03716123e-04]]), scale=0.15723113783888065, shift=array([5.77865656, 0.2644669 , 5.8815059 ])), vector_model=VectorModel(intercepts=array([ 0.02354116, 0.05893189, 0.05511322, 0.08007337, 0.09513781, + 0.10839155, 0.1198678 , 0.04749388, -0.0746656 , -0.05874137, + -0.42316514, -0.47259966, 0.00921586, 0.03275234, 0.0475013 , + 0.0622027 , 0.08758365]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 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linear_terms=array([0.02481206, 0.09068621, 0.01471639]), square_terms=array([[ 0.00524969, -0.04974247, 0.00452186], + [-0.04974247, 2.08525407, -0.1402769 ], + [ 0.00452186, -0.1402769 , 0.01062439]]), scale=array([0.25345533, 0.25345533, 0.25345533]), shift=array([5.64790948, 0.27241524, 5.79374048])), vector_model=VectorModel(intercepts=array([ 0.02354116, 0.05893189, 0.05511322, 0.08007337, 0.09513781, + 0.10839155, 0.1198678 , 0.04749388, -0.0746656 , -0.05874137, + -0.42316514, -0.47259966, 0.00921586, 0.03275234, 0.0475013 , + 0.0622027 , 0.08758365]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]]), square_terms=array([[[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + 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candidate_x=array([5.5943578 , 0.27431124, 5.75363516]), index=35, x=array([5.5943578 , 0.27431124, 5.75363516]), fval=0.29668989844277605, rho=2.3974430325385168, accepted=True, new_indices=array([], dtype=int32), old_indices_used=array([18, 21, 28, 29, 31, 32, 33, 34]), old_indices_discarded=array([], dtype=int32), step_length=0.04084790948344249, relative_step_length=1.0391811709790089, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([5.5943578 , 0.27431124, 5.75363516]), radius=0.07861556891944033, bounds=Bounds(lower=array([1.1 , 0.01, 0. ]), upper=array([ 20. , 0.99, 100. ]))), model_indices=array([18, 19, 21, 23, 24, 28, 29, 31, 32, 33, 34, 35]), model=ScalarModel(intercept=0.2995054829562912, linear_terms=array([1.59717607e-03, 8.40278740e-03, 2.79653900e-05]), square_terms=array([[ 2.92809658e-04, 4.55607833e-03, -1.77568617e-05], + [ 4.55607833e-03, 2.75571107e-01, 8.33702661e-05], + [-1.77568617e-05, 8.33702661e-05, 5.08567335e-06]]), scale=0.07861556891944033, shift=array([5.5943578 , 0.27431124, 5.75363516])), vector_model=VectorModel(intercepts=array([ 0.02354116, 0.05893189, 0.05511322, 0.08007337, 0.09513781, + 0.10839155, 0.1198678 , 0.04749388, -0.0746656 , -0.05874137, + -0.42316514, -0.47259966, 0.00921586, 0.03275234, 0.0475013 , + 0.0622027 , 0.08758365]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]]), square_terms=array([[[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 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step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([5.5943578 , 0.27431124, 5.75363516]), radius=0.03930778445972016, bounds=Bounds(lower=array([1.1 , 0.01, 0. ]), upper=array([ 20. , 0.99, 100. ]))), model_indices=array([29, 31, 32, 33, 34, 35, 36]), model=ScalarModel(intercept=0.2968263734417504, linear_terms=array([-0.00013262, -0.00109787, 0.00071038]), square_terms=array([[ 1.17780580e-04, 2.56942060e-03, -3.82135280e-05], + [ 2.56942060e-03, 1.01712962e-01, -1.29146121e-03], + [-3.82135280e-05, -1.29146121e-03, 1.79763784e-05]]), scale=0.03930778445972016, shift=array([5.5943578 , 0.27431124, 5.75363516])), vector_model=VectorModel(intercepts=array([ 0.02354116, 0.05893189, 0.05511322, 0.08007337, 0.09513781, + 0.10839155, 0.1198678 , 0.04749388, -0.0746656 , -0.05874137, + -0.42316514, -0.47259966, 0.00921586, 0.03275234, 0.0475013 , + 0.0622027 , 0.08758365]), linear_terms=array([[0., 0., 0.], + [0., 0., 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linear_terms=array([0.00063314, 0.00259505, 0.00077565]), square_terms=array([[ 4.13948227e-04, 8.30470975e-03, -6.37384456e-05], + [ 8.30470975e-03, 3.46745608e-01, -1.95444378e-03], + [-6.37384456e-05, -1.95444378e-03, 1.51370328e-05]]), scale=0.07861556891944033, shift=array([5.59967088, 0.27409353, 5.71352946])), vector_model=VectorModel(intercepts=array([ 0.02354116, 0.05893189, 0.05511322, 0.08007337, 0.09513781, + 0.10839155, 0.1198678 , 0.04749388, -0.0746656 , -0.05874137, + -0.42316514, -0.47259966, 0.00921586, 0.03275234, 0.0475013 , + 0.0622027 , 0.08758365]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]]), square_terms=array([[[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 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fval=0.29502502944321474, rho=1.0288115202626666, accepted=True, new_indices=array([], dtype=int32), old_indices_used=array([18, 21, 23, 28, 29, 31, 32, 33, 34, 35, 36, 37]), old_indices_discarded=array([10, 15, 16, 17, 19, 20, 22, 24, 25, 26, 27, 30]), step_length=0.0786238847613481, relative_step_length=1.0001057785629752, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([5.55934649, 0.27409052, 5.64603383]), radius=0.15723113783888065, bounds=Bounds(lower=array([1.1 , 0.01, 0. ]), upper=array([ 20. , 0.99, 100. ]))), model_indices=array([10, 21, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38]), model=ScalarModel(intercept=0.3048638716861844, linear_terms=array([ 0.00790086, 0.02682295, -0.0070564 ]), square_terms=array([[ 1.11247314e-03, -4.07052752e-03, -3.87937482e-04], + [-4.07052752e-03, 7.45474880e-01, 2.67385638e-02], + [-3.87937482e-04, 2.67385638e-02, 1.19103427e-03]]), scale=0.15723113783888065, shift=array([5.55934649, 0.27409052, 5.64603383])), vector_model=VectorModel(intercepts=array([ 0.02354116, 0.05893189, 0.05511322, 0.08007337, 0.09513781, + 0.10839155, 0.1198678 , 0.04749388, -0.0746656 , -0.05874137, + -0.42316514, -0.47259966, 0.00921586, 0.03275234, 0.0475013 , + 0.0622027 , 0.08758365]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]]), square_terms=array([[[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 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n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([5.55934649, 0.27409052, 5.64603383]), radius=0.07861556891944033, bounds=Bounds(lower=array([1.1 , 0.01, 0. ]), upper=array([ 20. , 0.99, 100. ]))), model_indices=array([21, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39]), model=ScalarModel(intercept=0.29531157794914653, linear_terms=array([-0.00079777, 0.00028918, 0.00139716]), square_terms=array([[ 6.60562106e-04, 1.23198516e-02, -1.27064144e-04], + [ 1.23198516e-02, 3.59764181e-01, -3.16811387e-03], + [-1.27064144e-04, -3.16811387e-03, 3.32377356e-05]]), scale=0.07861556891944033, shift=array([5.55934649, 0.27409052, 5.64603383])), vector_model=VectorModel(intercepts=array([ 0.02354116, 0.05893189, 0.05511322, 0.08007337, 0.09513781, + 0.10839155, 0.1198678 , 0.04749388, -0.0746656 , -0.05874137, + -0.42316514, -0.47259966, 0.00921586, 0.03275234, 0.0475013 , + 0.0622027 , 0.08758365]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + 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0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]]]), scale=0.6289245513555226, shift=array([5.67129147, 0.19427609, 6.28924551])), candidate_index=40, candidate_x=array([5.59413123, 0.27222346, 5.57554581]), index=40, x=array([5.59413123, 0.27222346, 5.57554581]), fval=0.29391931624328554, rho=0.6999956958554849, accepted=True, new_indices=array([], dtype=int32), old_indices_used=array([21, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39]), old_indices_discarded=array([10, 15, 17, 18, 19, 23, 24, 27, 28]), step_length=0.07862585606855259, relative_step_length=1.0001308538404499, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([5.59413123, 0.27222346, 5.57554581]), radius=0.15723113783888065, bounds=Bounds(lower=array([1.1 , 0.01, 0. ]), upper=array([ 20. , 0.99, 100. ]))), model_indices=array([29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40]), model=ScalarModel(intercept=0.29355339341176606, linear_terms=array([-0.00019797, -0.00071454, 0.00299404]), square_terms=array([[ 2.02380756e-03, 4.26701579e-02, -6.18734942e-04], + [ 4.26701579e-02, 1.62234158e+00, -2.01145634e-02], + [-6.18734942e-04, -2.01145634e-02, 2.76548771e-04]]), scale=0.15723113783888065, shift=array([5.59413123, 0.27222346, 5.57554581])), vector_model=VectorModel(intercepts=array([ 0.02354116, 0.05893189, 0.05511322, 0.08007337, 0.09513781, + 0.10839155, 0.1198678 , 0.04749388, -0.0746656 , -0.05874137, + -0.42316514, -0.47259966, 0.00921586, 0.03275234, 0.0475013 , + 0.0622027 , 0.08758365]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]]), square_terms=array([[[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 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x=array([5.59773281, 0.27023777, 5.41715529]), fval=0.29147518333688877, rho=0.8159702169964561, accepted=True, new_indices=array([], dtype=int32), old_indices_used=array([29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40]), old_indices_discarded=array([ 0, 4, 9, 10, 11, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, + 26, 27, 28]), step_length=0.15844390380935744, relative_step_length=1.0077132684221846, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([5.59773281, 0.27023777, 5.41715529]), radius=0.3144622756777613, bounds=Bounds(lower=array([1.1 , 0.01, 0. ]), upper=array([ 20. , 0.99, 100. ]))), model_indices=array([29, 30, 31, 32, 33, 35, 36, 37, 38, 39, 40, 41]), model=ScalarModel(intercept=0.2911350818408353, linear_terms=array([2.41630387e-05, 7.16611760e-04, 4.34790153e-03]), square_terms=array([[ 5.27549003e-03, 1.10723873e-01, -1.61625725e-03], + [ 1.10723873e-01, 4.21106621e+00, -5.16302574e-02], + [-1.61625725e-03, -5.16302574e-02, 7.03695581e-04]]), scale=array([0.25345533, 0.25345533, 0.25345533]), shift=array([5.59773281, 0.27023777, 5.41715529])), vector_model=VectorModel(intercepts=array([ 0.02354116, 0.05893189, 0.05511322, 0.08007337, 0.09513781, + 0.10839155, 0.1198678 , 0.04749388, -0.0746656 , -0.05874137, + -0.42316514, -0.47259966, 0.00921586, 0.03275234, 0.0475013 , + 0.0622027 , 0.08758365]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]]), square_terms=array([[[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 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1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, + 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 34]), step_length=0.25504244694828304, relative_step_length=0.8110430619971487, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([5.56942636, 0.2678314 , 5.16369996]), radius=0.6289245513555226, bounds=Bounds(lower=array([1.1 , 0.01, 0. ]), upper=array([ 20. , 0.99, 100. ]))), model_indices=array([29, 30, 31, 33, 35, 36, 37, 38, 39, 40, 41, 42]), model=ScalarModel(intercept=0.7970330746584172, linear_terms=array([ 0.10907961, 3.12734191, -0.04329691]), square_terms=array([[ 2.11126557e-02, 3.34560090e-01, -6.62328982e-03], + [ 3.34560090e-01, 9.59024924e+00, -1.58399852e-01], + [-6.62328982e-03, -1.58399852e-01, 2.90681443e-03]]), scale=array([0.50691066, 0.38237103, 0.50691066]), shift=array([5.56942636, 0.39237103, 5.16369996])), vector_model=VectorModel(intercepts=array([ 0.02354116, 0.05893189, 0.05511322, 0.08007337, 0.09513781, + 0.10839155, 0.1198678 , 0.04749388, -0.0746656 , -0.05874137, + -0.42316514, -0.47259966, 0.00921586, 0.03275234, 0.0475013 , + 0.0622027 , 0.08758365]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]]), square_terms=array([[[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 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State(trustregion=Region(center=array([5.51152948, 0.26288937, 4.6567893 ]), radius=1.2578491027110452, bounds=Bounds(lower=array([1.1 , 0.01, 0. ]), upper=array([ 20. , 0.99, 100. ]))), model_indices=array([ 4, 10, 24, 28, 29, 30, 31, 34, 40, 41, 42, 43]), model=ScalarModel(intercept=5.024125827775805, linear_terms=array([ 6.42333612, 21.1370778 , 1.00694802]), square_terms=array([[ 4.65892503, 14.70300577, 0.73508329], + [14.70300577, 47.22213909, 2.32311952], + [ 0.73508329, 2.32311952, 0.12514989]]), scale=array([1.01382132, 0.49 , 1.01382132]), shift=array([5.51152948, 0.5 , 4.6567893 ])), vector_model=VectorModel(intercepts=array([ 0.02354116, 0.05893189, 0.05511322, 0.08007337, 0.09513781, + 0.10839155, 0.1198678 , 0.04749388, -0.0746656 , -0.05874137, + -0.42316514, -0.47259966, 0.00921586, 0.03275234, 0.0475013 , + 0.0622027 , 0.08758365]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 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linear_terms=array([ 0.11039741, 3.19266153, -0.04690528]), square_terms=array([[ 2.07035863e-02, 3.28080415e-01, -6.81650621e-03], + [ 3.28080415e-01, 9.51207209e+00, -1.64188087e-01], + [-6.81650621e-03, -1.64188087e-01, 3.14212476e-03]]), scale=array([0.50691066, 0.37990001, 0.50691066]), shift=array([5.51152948, 0.38990001, 4.6567893 ])), vector_model=VectorModel(intercepts=array([ 0.02354116, 0.05893189, 0.05511322, 0.08007337, 0.09513781, + 0.10839155, 0.1198678 , 0.04749388, -0.0746656 , -0.05874137, + -0.42316514, -0.47259966, 0.00921586, 0.03275234, 0.0475013 , + 0.0622027 , 0.08758365]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]]), square_terms=array([[[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], 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4.14987865]), fval=0.27060072197678664, rho=1.0027114346640618, accepted=True, new_indices=array([], dtype=int32), old_indices_used=array([30, 31, 33, 35, 36, 37, 38, 39, 40, 41, 42, 43]), old_indices_discarded=array([ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, + 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 32, 34, 44]), step_length=0.5128070669439712, relative_step_length=0.8153713602668505, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([5.43415317, 0.25783182, 4.14987865]), radius=1.2578491027110452, bounds=Bounds(lower=array([1.1 , 0.01, 0. ]), upper=array([ 20. , 0.99, 100. ]))), model_indices=array([30, 31, 35, 36, 37, 38, 39, 40, 41, 42, 43, 45]), model=ScalarModel(intercept=2.2313260222378055, linear_terms=array([ 0.39940297, 7.9100079 , -0.20216257]), square_terms=array([[ 7.68147957e-02, 8.04452650e-01, -2.69071098e-02], + [ 8.04452650e-01, 1.59550602e+01, -4.40323323e-01], + [-2.69071098e-02, -4.40323323e-01, 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7, 8, 9, 10, 11, 12, 13, 14, 15, 16, + 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 32, 33, 34, 44]), step_length=1.0462520903512822, relative_step_length=0.8317786991271787, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([5.17672719, 0.2345587 , 3.13605733]), radius=2.5156982054220904, bounds=Bounds(lower=array([1.1 , 0.01, 0. ]), upper=array([ 20. , 0.99, 100. ]))), model_indices=array([30, 31, 36, 37, 38, 39, 40, 41, 42, 43, 45, 46]), model=ScalarModel(intercept=2.4157379520152538, linear_terms=array([ 0.63641679, 8.35461052, -0.44234772]), square_terms=array([[ 0.2316333 , 1.26480581, -0.09114979], + [ 1.26480581, 16.17103872, -0.91725459], + [-0.09114979, -0.91725459, 0.05713252]]), scale=array([2.02764263, 0.49 , 2.02764263]), shift=array([5.17672719, 0.5 , 3.13605733])), vector_model=VectorModel(intercepts=array([ 0.02354116, 0.05893189, 0.05511322, 0.08007337, 0.09513781, + 0.10839155, 0.1198678 , 0.04749388, -0.0746656 , -0.05874137, + 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model=ScalarModel(intercept=2.578020554580501, linear_terms=array([ 1.21626104, 8.06658535, -0.46481816]), square_terms=array([[ 0.45089658, 2.05574383, -0.14024761], + [ 2.05574383, 13.89162144, -0.83270766], + [-0.14024761, -0.83270766, 0.05320328]]), scale=array([2.02764263, 0.49 , 1.56802866]), shift=array([5.14044679, 0.5 , 1.56802866])), vector_model=VectorModel(intercepts=array([ 0.02354116, 0.05893189, 0.05511322, 0.08007337, 0.09513781, + 0.10839155, 0.1198678 , 0.04749388, -0.0746656 , -0.05874137, + -0.42316514, -0.47259966, 0.00921586, 0.03275234, 0.0475013 , + 0.0622027 , 0.08758365]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]]), square_terms=array([[[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], 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vector_model=VectorModel(intercepts=array([ 0.02354116, 0.05893189, 0.05511322, 0.08007337, 0.09513781, + 0.10839155, 0.1198678 , 0.04749388, -0.0746656 , -0.05874137, + -0.42316514, -0.47259966, 0.00921586, 0.03275234, 0.0475013 , + 0.0622027 , 0.08758365]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]]), square_terms=array([[[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 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index=71, x=array([5.37502587, 0.19456137, 0.68757298]), fval=0.22954649382876313, rho=-2.030261445123912, accepted=False, new_indices=array([], dtype=int32), old_indices_used=array([ 71, 93, 94, 95, 96, 97, 98, 99, 100, 101, 102, 104]), old_indices_discarded=array([ 91, 92, 103]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([5.37502587, 0.19456137, 0.68757298]), radius=7.677301652289094e-05, bounds=Bounds(lower=array([1.1 , 0.01, 0. ]), upper=array([ 20. , 0.99, 100. ]))), model_indices=array([ 71, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, + 116, 117]), model=ScalarModel(intercept=0.22954896050293003, linear_terms=array([ 3.28680984e-06, -4.77347360e-07, 1.37109067e-07]), square_terms=array([[ 2.55761258e-10, 4.01597052e-09, -1.56505450e-10], + [ 4.01597052e-09, 5.03977931e-07, -1.41568103e-08], + [-1.56505450e-10, -1.41568103e-08, 4.17172147e-10]]), scale=7.677301652289094e-05, 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6.55725054e-01, 7.71100519e-01, + 1.19425789e+00, 1.58158215e+00, 1.58170972e+00, 2.10988168e+00, + 2.53770191e+00, 3.19288105e+00, 3.47314230e+00, 3.48315006e+00, + 3.92293459e+00, 4.56511870e+00, 5.33390087e+00, 5.34621006e+00, + 6.48994604e+00, 9.32970623e+00, 1.17999718e+01, 1.57570577e+01, + 1.66647063e+01, 2.65180559e+01, 4.77377487e+01, 8.29741042e+01, + 8.62618718e+01, 8.81150175e+01, 1.31509063e+02, 1.97370096e+02, + 6.42774449e+02, 7.33084130e+02])}}" diff --git a/code/estimark/content/tables/min/WealthPortfolio_estimate_results.csv b/code/estimark/content/tables/min/WealthPortfolio_estimate_results.csv new file mode 100644 index 0000000..d2043bc --- /dev/null +++ b/code/estimark/content/tables/min/WealthPortfolio_estimate_results.csv @@ -0,0 +1,7041 @@ +CRRA,5.338780774481047 +WealthShare,0.17065528804872485 +time_to_estimate,87.05302119255066 +params,"{'CRRA': 5.338780774481047, 'WealthShare': 0.17065528804872485}" +criterion,0.24222229239256732 +start_criterion,2.0450859311174514 +start_params,"{'CRRA': 4.844436801414261, 'WealthShare': 0.3460128282561451}" +algorithm,multistart_tranquilo_ls +direction,minimize +n_free,2 +message,Absolute criterion change smaller than tolerance. +success, +n_criterion_evaluations, +n_derivative_evaluations, +n_iterations, +history,"{'params': [{'CRRA': 7.00625, 'WealthShare': 0.19375}, {'CRRA': 6.385337260354661, 'WealthShare': 0.0589657827107465}, {'CRRA': 7.627162739645338, 'WealthShare': 0.2909337034881926}, {'CRRA': 6.385337260354661, 'WealthShare': 0.4422314188083436}, {'CRRA': 7.627162739645338, 'WealthShare': 0.6717516331999257}, {'CRRA': 7.627162739645338, 'WealthShare': 0.010000476301985028}, {'CRRA': 7.556316959078161, 'WealthShare': 0.01}, {'CRRA': 6.385337260354661, 'WealthShare': 0.4716198511344087}, {'CRRA': 7.627162739645338, 'WealthShare': 0.751444172509113}, {'CRRA': 7.435546062237209, 'WealthShare': 0.8146627396453386}, {'CRRA': 6.407783701100443, 'WealthShare': 0.8146627396453386}, {'CRRA': 6.6651666175265545, 'WealthShare': 0.01}, {'CRRA': 6.48493214278919, 'WealthShare': 0.8146627396453386}, {'CRRA': 6.385337260354661, 'WealthShare': 0.1237617248187634}, {'CRRA': 6.0748808905319915, 'WealthShare': 0.20052322401594325}, {'CRRA': 6.2532427503011325, 'WealthShare': 0.19438789449563343}, {'CRRA': 6.3382227136719385, 'WealthShare': 0.1578819528196836}, {'CRRA': 6.493450898583273, 'WealthShare': 0.13740842870128234}, {'CRRA': 6.4256753849363895, 'WealthShare': 0.15294566470705245}, {'CRRA': 6.294459741840304, 'WealthShare': 0.16000090800258274}, {'CRRA': 6.382143835462875, 'WealthShare': 0.16046020191691993}, {'CRRA': 6.250679533322458, 'WealthShare': 0.16091446504625906}, {'CRRA': 6.163102752485386, 'WealthShare': 0.16148208803528766}, {'CRRA': 6.007874567574052, 'WealthShare': 0.16384849824047343}, {'CRRA': 5.697418197751382, 'WealthShare': 0.17249887954427012}, {'CRRA': 5.236146802438669, 'WealthShare': 0.17615356090029882}, {'CRRA': 5.425169945432182, 'WealthShare': 0.18194646890715233}, {'CRRA': 4.9779501150979595, 'WealthShare': 0.1792004931237239}, {'CRRA': 5.546603172261339, 'WealthShare': 0.48660993072296815}, {'CRRA': 5.215889834469423, 'WealthShare': 0.1769811233053123}, {'CRRA': 5.274171299031127, 'WealthShare': 0.17638843122996792}, {'CRRA': 5.259275228360069, 'WealthShare': 0.1764508677785662}, {'CRRA': 5.361747939266923, 'WealthShare': 0.17587789924445918}, {'CRRA': 5.500670574988, 'WealthShare': 0.1750124128151594}, {'CRRA': 5.361212623821769, 'WealthShare': 0.08830141029970982}, {'CRRA': 5.448965805526602, 'WealthShare': 0.16786346171002578}, {'CRRA': 5.521017950385663, 'WealthShare': 0.16734145638561265}, {'CRRA': 5.361392263936586, 'WealthShare': 0.1687594482598058}, {'CRRA': 5.408532775180341, 'WealthShare': 0.16829680110424536}, {'CRRA': 5.4146764839922925, 'WealthShare': 0.16830439279425335}, {'CRRA': 5.317605072265502, 'WealthShare': 0.16916422003343717}, {'CRRA': 5.230029569186239, 'WealthShare': 0.16984189173088587}, {'CRRA': 5.361391583162623, 'WealthShare': 0.16869150649947118}, {'CRRA': 5.339508482161973, 'WealthShare': 0.17080481516331386}, {'CRRA': 5.368957473427081, 'WealthShare': 0.1704982684436756}, {'CRRA': 5.3283746442860265, 'WealthShare': 0.170903000375076}, {'CRRA': 5.328563448185613, 'WealthShare': 0.17111248155527758}, {'CRRA': 5.334036845737762, 'WealthShare': 0.17107114051345143}, {'CRRA': 5.342235745297582, 'WealthShare': 0.1697818067119096}, {'CRRA': 5.3408803356615, 'WealthShare': 0.17109939320809675}, {'CRRA': 5.338823528524706, 'WealthShare': 0.17065422827949905}, {'CRRA': 5.340193277829363, 'WealthShare': 0.17078798862632172}, {'CRRA': 5.338140970895526, 'WealthShare': 0.17083226059338175}, {'CRRA': 5.338518273170905, 'WealthShare': 0.17049811328240777}, {'CRRA': 5.338781916239757, 'WealthShare': 0.1708201405184341}, {'CRRA': 5.338915212045181, 'WealthShare': 0.17067448290561968}, {'CRRA': 5.338780774481047, 'WealthShare': 0.17065528804872485}], 'criterion': [0.3273843758368489, 0.5699740200328935, 0.842575503738206, 3.810658336120194, 20.623483705368287, 0.6910521757749679, 0.6995225156927494, 4.9395441503578565, 42.99134020288109, 86.6456059148058, 105.27402392078089, 0.8474994237274145, 103.66743022564344, 0.30690596890028216, 0.29210255832128873, 0.28576369985789285, 0.26145704727673624, 0.28242718110045806, 0.26615570282764395, 0.2594527871161228, 0.26221365404602937, 0.2577870645585467, 0.25523533119834385, 0.25064066883423725, 0.24497093468209197, 0.24406000199271466, 0.24743835677691237, 0.24950377050231112, 6.8114635382632684, 0.244474337584774, 0.24364090572406066, 0.24383728429031426, 0.2434506325404963, 0.24360441582812653, 0.5131462702699118, 0.24274413357026287, 0.24315059044862256, 0.2425520875633037, 0.24267761171614233, 0.24262874555716651, 0.24241985946629965, 0.24303623087126985, 0.24256813594664275, 0.24222716621340298, 0.24232942620846887, 0.24226459021544208, 0.24228552258028713, 0.2422627008915168, 0.24227972390907074, 0.24224781333659, 0.24222315394360727, 0.2422366702780749, 0.24222456968889083, 0.2422369639832645, 0.24222420706924647, 0.2422233576238524, 0.2422222923925673], 'runtime': [0.0, 3.0856837001629174, 3.092791900038719, 3.145945300348103, 3.198699700180441, 3.1877071000635624, 3.257912500295788, 3.279559100046754, 3.320520000066608, 3.3423851002007723, 3.399885100312531, 3.4487606999464333, 3.469572300091386, 4.5710685001686215, 5.594150300137699, 6.609584300313145, 7.625805400311947, 8.643067300319672, 9.653973900247365, 10.668333900161088, 11.684152700006962, 12.696534700226039, 13.830191600136459, 14.843372600153089, 15.85343430005014, 16.867383300326765, 17.886160700116307, 18.908616400323808, 19.927985700313002, 20.95058420021087, 21.96936420025304, 22.98745770007372, 24.00510139996186, 25.026439000386745, 26.052888700272888, 27.192030200269073, 28.2193304002285, 29.282562700100243, 30.321563200093806, 31.38996300008148, 32.42062650015578, 33.43918160023168, 34.45591269992292, 35.487439500167966, 36.49907220015302, 37.50863410020247, 38.52129440009594, 39.53660099999979, 40.67266120016575, 41.69906500028446, 42.72594740008935, 43.75388570036739, 44.77801220025867, 45.799775400198996, 46.81848719995469, 47.845374200027436, 48.87321070022881], 'batches': [0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45]}" +convergence_report, +multistart_info,"{'start_parameters': [{'CRRA': 7.00625, 'WealthShare': 0.19375}, {'CRRA': 7.557071776832622, 'WealthShare': 0.15947986291737937}], 'local_optima': [Minimize with 2 free parameters terminated. + +The tranquilo_ls algorithm reported: Absolute criterion change smaller than tolerance. + +Independent of the convergence criteria used by tranquilo_ls, the strength of convergence can be assessed by the following criteria: + + one_step five_steps +relative_criterion_change 3.557e-06* 0.002154 +relative_params_change 1.013e-05 0.02634 +absolute_criterion_change 8.616e-07* 0.0005218 +absolute_params_change 4.277e-05 0.1102 + +(***: change <= 1e-10, **: change <= 1e-8, *: change <= 1e-5. Change refers to a change between accepted steps. The first column only considers the last step. The second column considers the last five steps.), Minimize with 2 free parameters terminated. + +The tranquilo_ls algorithm reported: Absolute criterion change smaller than tolerance. + +Independent of the convergence criteria used by tranquilo_ls, the strength of convergence can be assessed by the following criteria: + + one_step five_steps +relative_criterion_change 1.266e-06* 0.2375 +relative_params_change 0.006515 0.369 +absolute_criterion_change 3.068e-07* 0.05754 +absolute_params_change 0.02362 1.523 + +(***: change <= 1e-10, **: change <= 1e-8, *: change <= 1e-5. Change refers to a change between accepted steps. The first column only considers the last step. The second column considers the last five steps.)], 'exploration_sample': [{'CRRA': 7.00625, 'WealthShare': 0.19375}, {'CRRA': 12.9125, 'WealthShare': 0.1325}, {'CRRA': 4.64375, 'WealthShare': 0.31625000000000003}, {'CRRA': 8.1875, 'WealthShare': 0.3775}, {'CRRA': 4.844436801414261, 'WealthShare': 0.3460128282561451}, {'CRRA': 15.274999999999999, 'WealthShare': 0.255}, {'CRRA': 17.046875, 'WealthShare': 0.224375}, {'CRRA': 11.73125, 'WealthShare': 0.43875}, {'CRRA': 18.81875, 'WealthShare': 0.07125}, {'CRRA': 10.549999999999999, 'WealthShare': 0.5}, {'CRRA': 9.368749999999999, 'WealthShare': 0.56125}, {'CRRA': 16.45625, 'WealthShare': 0.68375}, {'CRRA': 2.871875, 'WealthShare': 0.469375}, {'CRRA': 7.596874999999999, 'WealthShare': 0.714375}, {'CRRA': 14.093749999999998, 'WealthShare': 0.80625}, {'CRRA': 3.4625, 'WealthShare': 0.6225}, {'CRRA': 17.6375, 'WealthShare': 0.8674999999999999}, {'CRRA': 5.824999999999999, 'WealthShare': 0.745}, {'CRRA': 12.321874999999999, 'WealthShare': 0.959375}, {'CRRA': 2.28125, 'WealthShare': 0.92875}], 'exploration_results': array([3.27384376e-01, 1.14034055e+00, 1.50312179e+00, 1.79325436e+00, + 2.03621762e+00, 2.08879824e+00, 2.54067782e+00, 2.64114350e+00, + 2.73814230e+00, 3.83228381e+00, 6.46248546e+00, 9.30118040e+00, + 1.59966394e+01, 3.03715662e+01, 3.38771067e+01, 4.26926083e+01, + 5.84656546e+01, 5.90505617e+01, 5.22500282e+02, 9.01924413e+02])}" +algorithm_output,"{'states': [State(trustregion=Region(center=array([7.00625, 0.19375]), radius=0.700625, bounds=Bounds(lower=array([1.1 , 0.01]), upper=array([20. , 0.99]))), model_indices=[0], model=ScalarModel(intercept=0.3273843758368489, linear_terms=array([0., 0.]), square_terms=array([[0., 0.], + [0., 0.]]), scale=0.700625, shift=array([7.00625, 0.19375])), vector_model=VectorModel(intercepts=array([ 0.04424533, 0.09706756, 0.09964179, 0.12817482, 0.14600609, + 0.16462579, 0.18727309, 0.2198423 , 0.14621231, 0.21589468, + -0.09902459, -0.11677074, -0.13794235, -0.11385871, -0.10645744, + -0.10854051, -0.10625494]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=0.700625, shift=array([7.00625, 0.19375])), candidate_index=0, candidate_x=array([7.00625, 0.19375]), index=0, x=array([7.00625, 0.19375]), fval=0.32738437583684893, rho=nan, accepted=True, new_indices=[0], old_indices_used=[], old_indices_discarded=[], step_length=None, relative_step_length=None, n_evals_per_point=None, n_evals_acceptance=None), State(trustregion=Region(center=array([7.00625, 0.19375]), radius=0.700625, bounds=Bounds(lower=array([1.1 , 0.01]), upper=array([20. , 0.99]))), model_indices=array([ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12]), model=ScalarModel(intercept=11.224951550903995, linear_terms=array([-1.37625354, 32.5154691 ]), square_terms=array([[ 0.09351784, -2.07104056], + [-2.07104056, 48.22141916]]), scale=array([0.62091274, 0.40233137]), shift=array([7.00625 , 0.41233137])), vector_model=VectorModel(intercepts=array([ 0.04424533, 0.09706756, 0.09964179, 0.12817482, 0.14600609, + 0.16462579, 0.18727309, 0.2198423 , 0.14621231, 0.21589468, + -0.09902459, -0.11677074, -0.13794235, -0.11385871, -0.10645744, + -0.10854051, -0.10625494]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=0.700625, shift=array([7.00625, 0.19375])), candidate_index=13, candidate_x=array([6.38533726, 0.12376172]), index=13, x=array([6.38533726, 0.12376172]), fval=0.30690596890028216, rho=0.04742895556261184, accepted=True, new_indices=array([ 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12]), old_indices_used=array([0]), old_indices_discarded=array([], dtype=int32), step_length=0.6248447718567584, relative_step_length=0.8918391034530002, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([6.38533726, 0.12376172]), radius=0.3503125, bounds=Bounds(lower=array([1.1 , 0.01]), upper=array([20. , 0.99]))), model_indices=array([ 0, 1, 3, 6, 7, 10, 11, 12, 13]), model=ScalarModel(intercept=0.7313551856043823, linear_terms=array([0.5632349 , 4.14900217]), square_terms=array([[ 0.31889798, 2.36106382], + [ 2.36106382, 17.56884109]]), scale=array([0.31045637, 0.21210905]), shift=array([6.38533726, 0.22210905])), vector_model=VectorModel(intercepts=array([ 0.04424533, 0.09706756, 0.09964179, 0.12817482, 0.14600609, + 0.16462579, 0.18727309, 0.2198423 , 0.14621231, 0.21589468, + -0.09902459, -0.11677074, -0.13794235, -0.11385871, -0.10645744, + -0.10854051, -0.10625494]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=0.700625, shift=array([7.00625, 0.19375])), candidate_index=14, candidate_x=array([6.07488089, 0.20052322]), index=14, x=array([6.07488089, 0.20052322]), fval=0.2921025583212886, rho=0.03221406908218355, accepted=True, new_indices=array([], dtype=int32), old_indices_used=array([ 0, 1, 3, 6, 7, 10, 11, 12, 13]), old_indices_discarded=array([2, 4, 5, 8, 9]), step_length=0.3198053866376689, relative_step_length=0.9129145738095811, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([6.07488089, 0.20052322]), radius=0.17515625, bounds=Bounds(lower=array([1.1 , 0.01]), upper=array([20. , 0.99]))), model_indices=array([ 1, 3, 7, 10, 11, 12, 13, 14]), model=ScalarModel(intercept=0.5857130929401587, linear_terms=array([-0.66733221, -2.49758335]), square_terms=array([[ 0.71346148, 2.85346922], + [ 2.85346922, 11.61097172]]), scale=0.17515625, shift=array([6.07488089, 0.20052322])), vector_model=VectorModel(intercepts=array([ 0.04424533, 0.09706756, 0.09964179, 0.12817482, 0.14600609, + 0.16462579, 0.18727309, 0.2198423 , 0.14621231, 0.21589468, + -0.09902459, -0.11677074, -0.13794235, -0.11385871, -0.10645744, + -0.10854051, -0.10625494]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=0.700625, shift=array([7.00625, 0.19375])), candidate_index=15, candidate_x=array([6.25324275, 0.19438789]), index=15, x=array([6.25324275, 0.19438789]), fval=0.28576369985789285, rho=0.020008399324012414, accepted=True, new_indices=array([], dtype=int32), old_indices_used=array([ 1, 3, 7, 10, 11, 12, 13, 14]), old_indices_discarded=array([], dtype=int32), step_length=0.17846735076374473, relative_step_length=1.0189036974914953, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([6.25324275, 0.19438789]), radius=0.087578125, bounds=Bounds(lower=array([1.1 , 0.01]), upper=array([20. , 0.99]))), model_indices=array([ 1, 3, 7, 13, 14, 15]), model=ScalarModel(intercept=0.2909351370686484, linear_terms=array([0.01016955, 0.239779 ]), square_terms=array([[0.00441972, 0.04993243], + [0.04993243, 0.684917 ]]), scale=0.087578125, shift=array([6.25324275, 0.19438789])), vector_model=VectorModel(intercepts=array([ 0.04424533, 0.09706756, 0.09964179, 0.12817482, 0.14600609, + 0.16462579, 0.18727309, 0.2198423 , 0.14621231, 0.21589468, + -0.09902459, -0.11677074, -0.13794235, -0.11385871, -0.10645744, + -0.10854051, -0.10625494]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 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10, 11, 13, 14, 15, 16]), model=ScalarModel(intercept=0.2600470730558603, linear_terms=array([-0.10978373, -0.38806688]), square_terms=array([[0.34292001, 1.58579951], + [1.58579951, 7.51750345]]), scale=array([0.15522818, 0.15155507]), shift=array([6.33822271, 0.16155507])), vector_model=VectorModel(intercepts=array([ 0.04424533, 0.09706756, 0.09964179, 0.12817482, 0.14600609, + 0.16462579, 0.18727309, 0.2198423 , 0.14621231, 0.21589468, + -0.09902459, -0.11677074, -0.13794235, -0.11385871, -0.10645744, + -0.10854051, -0.10625494]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 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linear_terms=array([-0.00725813, -0.0120927 ]), square_terms=array([[0.00459974, 0.05116398], + [0.05116398, 0.68633371]]), scale=0.087578125, shift=array([6.33822271, 0.15788195])), vector_model=VectorModel(intercepts=array([ 0.04424533, 0.09706756, 0.09964179, 0.12817482, 0.14600609, + 0.16462579, 0.18727309, 0.2198423 , 0.14621231, 0.21589468, + -0.09902459, -0.11677074, -0.13794235, -0.11385871, -0.10645744, + -0.10854051, -0.10625494]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + 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1.19696569e-01]]), scale=0.0437890625, shift=array([6.33822271, 0.15788195])), vector_model=VectorModel(intercepts=array([ 0.04424533, 0.09706756, 0.09964179, 0.12817482, 0.14600609, + 0.16462579, 0.18727309, 0.2198423 , 0.14621231, 0.21589468, + -0.09902459, -0.11677074, -0.13794235, -0.11385871, -0.10645744, + -0.10854051, -0.10625494]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=0.700625, shift=array([7.00625, 0.19375])), candidate_index=19, candidate_x=array([6.29445974, 0.16000091]), index=19, x=array([6.29445974, 0.16000091]), fval=0.2594527871161228, rho=0.5388880366161921, accepted=True, new_indices=array([], dtype=int32), old_indices_used=array([ 1, 13, 15, 16, 17, 18]), old_indices_discarded=array([], dtype=int32), step_length=0.04381424054578142, relative_step_length=1.0005749848099947, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([6.29445974, 0.16000091]), radius=0.087578125, bounds=Bounds(lower=array([1.1 , 0.01]), upper=array([20. , 0.99]))), model_indices=array([ 1, 3, 13, 14, 15, 16, 17, 18, 19]), model=ScalarModel(intercept=0.2541677101008941, linear_terms=array([-0.00368238, -0.03323817]), square_terms=array([[0.00145555, 0.02969193], + [0.02969193, 0.6672799 ]]), scale=0.087578125, shift=array([6.29445974, 0.16000091])), vector_model=VectorModel(intercepts=array([ 0.04424533, 0.09706756, 0.09964179, 0.12817482, 0.14600609, + 0.16462579, 0.18727309, 0.2198423 , 0.14621231, 0.21589468, + -0.09902459, -0.11677074, -0.13794235, -0.11385871, -0.10645744, + -0.10854051, -0.10625494]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=0.700625, shift=array([7.00625, 0.19375])), candidate_index=20, candidate_x=array([6.38214384, 0.1604602 ]), index=19, x=array([6.29445974, 0.16000091]), fval=0.2594527871161228, rho=-0.930670096284453, accepted=False, new_indices=array([], dtype=int32), old_indices_used=array([ 1, 3, 13, 14, 15, 16, 17, 18, 19]), old_indices_discarded=array([ 7, 11]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([6.29445974, 0.16000091]), radius=0.0437890625, bounds=Bounds(lower=array([1.1 , 0.01]), upper=array([20. , 0.99]))), model_indices=array([ 1, 13, 15, 16, 17, 18, 19, 20]), model=ScalarModel(intercept=0.25622931078220434, linear_terms=array([ 0.0032415 , -0.00073259]), square_terms=array([[1.03290011e-04, 1.82810922e-03], + [1.82810922e-03, 1.19546137e-01]]), scale=0.0437890625, shift=array([6.29445974, 0.16000091])), vector_model=VectorModel(intercepts=array([ 0.04424533, 0.09706756, 0.09964179, 0.12817482, 0.14600609, + 0.16462579, 0.18727309, 0.2198423 , 0.14621231, 0.21589468, + -0.09902459, -0.11677074, -0.13794235, -0.11385871, -0.10645744, + -0.10854051, -0.10625494]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=0.700625, shift=array([7.00625, 0.19375])), candidate_index=21, candidate_x=array([6.25067953, 0.16091447]), index=21, x=array([6.25067953, 0.16091447]), fval=0.2577870645585467, rho=0.517848980651204, accepted=True, new_indices=array([], dtype=int32), old_indices_used=array([ 1, 13, 15, 16, 17, 18, 19, 20]), old_indices_discarded=array([], dtype=int32), step_length=0.043789739030257874, relative_step_length=1.0000154497543279, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([6.25067953, 0.16091447]), radius=0.087578125, bounds=Bounds(lower=array([1.1 , 0.01]), upper=array([20. , 0.99]))), model_indices=array([ 1, 13, 14, 15, 16, 18, 19, 20, 21]), model=ScalarModel(intercept=0.25500561017058476, linear_terms=array([0.00514188, 0.00157206]), square_terms=array([[3.29759763e-04, 4.68476327e-03], + [4.68476327e-03, 4.75402508e-01]]), scale=0.087578125, shift=array([6.25067953, 0.16091447])), vector_model=VectorModel(intercepts=array([ 0.04424533, 0.09706756, 0.09964179, 0.12817482, 0.14600609, + 0.16462579, 0.18727309, 0.2198423 , 0.14621231, 0.21589468, + -0.09902459, 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rho=0.5116649557870464, accepted=True, new_indices=array([], dtype=int32), old_indices_used=array([ 1, 13, 14, 15, 16, 18, 19, 20, 21]), old_indices_discarded=array([ 3, 7, 17]), step_length=0.08757862032278296, relative_step_length=1.0000056557819998, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([6.16310275, 0.16148209]), radius=0.17515625, bounds=Bounds(lower=array([1.1 , 0.01]), upper=array([20. , 0.99]))), model_indices=array([ 1, 13, 14, 15, 16, 19, 20, 21, 22]), model=ScalarModel(intercept=0.2515880836028085, linear_terms=array([0.00754998, 0.01225116]), square_terms=array([[8.67053730e-04, 1.69602107e-02], + [1.69602107e-02, 1.46374627e+00]]), scale=array([0.15522818, 0.15335514]), shift=array([6.16310275, 0.16335514])), vector_model=VectorModel(intercepts=array([ 0.04424533, 0.09706756, 0.09964179, 0.12817482, 0.14600609, + 0.16462579, 0.18727309, 0.2198423 , 0.14621231, 0.21589468, + -0.09902459, -0.11677074, -0.13794235, -0.11385871, 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new_indices=array([], dtype=int32), old_indices_used=array([ 1, 13, 14, 15, 16, 19, 20, 21, 22]), old_indices_discarded=array([ 0, 3, 7, 10, 11, 12, 17, 18]), step_length=0.1552462214938793, relative_step_length=0.8863298996974375, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([6.00787457, 0.1638485 ]), radius=0.3503125, bounds=Bounds(lower=array([1.1 , 0.01]), upper=array([20. , 0.99]))), model_indices=array([13, 14, 15, 16, 19, 20, 21, 22, 23]), model=ScalarModel(intercept=0.43332719746500753, linear_terms=array([0.03146291, 1.14425379]), square_terms=array([[2.68439891e-03, 7.19387302e-02], + [7.19387302e-02, 3.57398202e+00]]), scale=array([0.31045637, 0.23215243]), shift=array([6.00787457, 0.24215243])), vector_model=VectorModel(intercepts=array([ 0.04424533, 0.09706756, 0.09964179, 0.12817482, 0.14600609, + 0.16462579, 0.18727309, 0.2198423 , 0.14621231, 0.21589468, + -0.09902459, -0.11677074, -0.13794235, -0.11385871, -0.10645744, + 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dtype=int32), old_indices_used=array([13, 14, 15, 16, 19, 20, 21, 22, 23]), old_indices_discarded=array([ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 17, 18]), step_length=0.3105768611152018, relative_step_length=0.8865708791870166, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([5.6974182 , 0.17249888]), radius=0.700625, bounds=Bounds(lower=array([1.1 , 0.01]), upper=array([20. , 0.99]))), model_indices=array([ 1, 13, 14, 15, 16, 19, 22, 23, 24]), model=ScalarModel(intercept=1.9359689768705584, linear_terms=array([0.14431675, 5.7192291 ]), square_terms=array([[0.01061289, 0.22387827], + [0.22387827, 9.66222181]]), scale=array([0.62091274, 0.39170581]), shift=array([5.6974182 , 0.40170581])), vector_model=VectorModel(intercepts=array([ 0.04424533, 0.09706756, 0.09964179, 0.12817482, 0.14600609, + 0.16462579, 0.18727309, 0.2198423 , 0.14621231, 0.21589468, + -0.09902459, -0.11677074, -0.13794235, -0.11385871, -0.10645744, + -0.10854051, -0.10625494]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=0.700625, shift=array([7.00625, 0.19375])), candidate_index=25, candidate_x=array([5.2361468 , 0.17615356]), index=25, x=array([5.2361468 , 0.17615356]), fval=0.2440600019927147, rho=0.12172165982234218, accepted=True, new_indices=array([], dtype=int32), old_indices_used=array([ 1, 13, 14, 15, 16, 19, 22, 23, 24]), old_indices_discarded=array([ 0, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 17, 18, 20, 21]), step_length=0.46128587321697967, relative_step_length=0.6583919689091592, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([5.2361468 , 0.17615356]), radius=1.40125, bounds=Bounds(lower=array([1.1 , 0.01]), upper=array([20. , 0.99]))), model_indices=array([ 1, 7, 10, 14, 16, 17, 22, 24, 25]), model=ScalarModel(intercept=19.556928495798605, linear_terms=array([ 2.66108959, 60.1251518 ]), square_terms=array([[ 0.19711181, 4.14595444], + [ 4.14595444, 93.60232406]]), scale=array([1.24182548, 0.49 ]), shift=array([5.2361468, 0.5 ])), vector_model=VectorModel(intercepts=array([ 0.04424533, 0.09706756, 0.09964179, 0.12817482, 0.14600609, + 0.16462579, 0.18727309, 0.2198423 , 0.14621231, 0.21589468, + -0.09902459, -0.11677074, -0.13794235, -0.11385871, -0.10645744, + -0.10854051, -0.10625494]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=0.700625, shift=array([7.00625, 0.19375])), candidate_index=26, candidate_x=array([5.42516995, 0.18194647]), index=25, x=array([5.2361468 , 0.17615356]), fval=0.2440600019927147, rho=-0.2074474380333275, accepted=False, new_indices=array([], dtype=int32), old_indices_used=array([ 1, 7, 10, 14, 16, 17, 22, 24, 25]), old_indices_discarded=array([ 0, 2, 3, 4, 5, 6, 8, 9, 11, 12, 13, 15, 18, 19, 20, 21, 23]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([5.2361468 , 0.17615356]), radius=0.700625, bounds=Bounds(lower=array([1.1 , 0.01]), upper=array([20. , 0.99]))), model_indices=array([14, 15, 19, 21, 22, 23, 24, 25, 26]), model=ScalarModel(intercept=2.023039226033913, linear_terms=array([0.11112348, 6.16604764]), square_terms=array([[9.99812684e-03, 1.87643817e-01], + [1.87643817e-01, 1.06798417e+01]]), scale=array([0.62091274, 0.39353315]), shift=array([5.2361468 , 0.40353315])), vector_model=VectorModel(intercepts=array([ 0.04424533, 0.09706756, 0.09964179, 0.12817482, 0.14600609, + 0.16462579, 0.18727309, 0.2198423 , 0.14621231, 0.21589468, + -0.09902459, -0.11677074, -0.13794235, -0.11385871, -0.10645744, + -0.10854051, -0.10625494]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=0.700625, shift=array([7.00625, 0.19375])), candidate_index=27, candidate_x=array([4.97795012, 0.17920049]), index=25, x=array([5.2361468 , 0.17615356]), fval=0.2440600019927147, rho=-9.379349103371986, accepted=False, new_indices=array([], dtype=int32), old_indices_used=array([14, 15, 19, 21, 22, 23, 24, 25, 26]), old_indices_discarded=array([ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 16, 17, 18, + 20]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([5.2361468 , 0.17615356]), radius=0.3503125, bounds=Bounds(lower=array([1.1 , 0.01]), upper=array([20. , 0.99]))), model_indices=array([14, 21, 22, 23, 24, 25, 26, 27, 28]), model=ScalarModel(intercept=0.5871067495424316, linear_terms=array([0.02508987, 2.27718757]), square_terms=array([[2.83476082e-03, 8.32114910e-02], + [8.32114910e-02, 7.59032634e+00]]), scale=array([0.31045637, 0.23830497]), shift=array([5.2361468 , 0.24830497])), vector_model=VectorModel(intercepts=array([ 0.04424533, 0.09706756, 0.09964179, 0.12817482, 0.14600609, + 0.16462579, 0.18727309, 0.2198423 , 0.14621231, 0.21589468, + -0.09902459, -0.11677074, -0.13794235, -0.11385871, -0.10645744, + -0.10854051, -0.10625494]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=0.700625, shift=array([7.00625, 0.19375])), candidate_index=29, candidate_x=array([5.21588983, 0.17698112]), index=25, x=array([5.2361468 , 0.17615356]), fval=0.2440600019927147, rho=-12.575485760554423, accepted=False, new_indices=array([28]), old_indices_used=array([14, 21, 22, 23, 24, 25, 26, 27]), old_indices_discarded=array([ 1, 3, 7, 10, 11, 12, 13, 15, 16, 17, 18, 19, 20]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([5.2361468 , 0.17615356]), radius=0.17515625, bounds=Bounds(lower=array([1.1 , 0.01]), upper=array([20. , 0.99]))), model_indices=array([14, 23, 24, 25, 26, 27, 28, 29]), model=ScalarModel(intercept=0.24537978825844767, linear_terms=array([-0.00017886, -0.00847909]), square_terms=array([[6.40294020e-04, 1.45475512e-02], + [1.45475512e-02, 3.24873183e+00]]), scale=array([0.15522818, 0.15522818]), shift=array([5.2361468 , 0.17615356])), vector_model=VectorModel(intercepts=array([ 0.04424533, 0.09706756, 0.09964179, 0.12817482, 0.14600609, + 0.16462579, 0.18727309, 0.2198423 , 0.14621231, 0.21589468, + -0.09902459, -0.11677074, -0.13794235, -0.11385871, -0.10645744, + -0.10854051, -0.10625494]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], 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old_indices_discarded=array([], dtype=int32), step_length=0.03802522196097743, relative_step_length=0.21709314946499153, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([5.2741713 , 0.17638843]), radius=0.17515625, bounds=Bounds(lower=array([1.1 , 0.01]), upper=array([20. , 0.99]))), model_indices=array([14, 23, 24, 25, 26, 27, 28, 29, 30]), model=ScalarModel(intercept=0.24506470035985778, linear_terms=array([5.54445372e-05, 8.93470786e-05]), square_terms=array([[6.38751471e-04, 1.45480845e-02], + [1.45480845e-02, 3.24873994e+00]]), scale=array([0.15522818, 0.15522818]), shift=array([5.2741713 , 0.17638843])), vector_model=VectorModel(intercepts=array([ 0.04424533, 0.09706756, 0.09964179, 0.12817482, 0.14600609, + 0.16462579, 0.18727309, 0.2198423 , 0.14621231, 0.21589468, + -0.09902459, -0.11677074, -0.13794235, -0.11385871, -0.10645744, + -0.10854051, -0.10625494]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 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square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=0.700625, shift=array([7.00625, 0.19375])), candidate_index=33, candidate_x=array([5.50067057, 0.17501241]), index=32, x=array([5.36174794, 0.1758779 ]), fval=0.24345063254049631, rho=-0.6330830612424933, accepted=False, new_indices=array([], dtype=int32), old_indices_used=array([24, 25, 26, 27, 28, 29, 30, 31, 32]), old_indices_discarded=array([14, 22, 23]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([5.36174794, 0.1758779 ]), radius=0.087578125, bounds=Bounds(lower=array([1.1 , 0.01]), upper=array([20. , 0.99]))), model_indices=array([24, 25, 26, 29, 30, 31, 32, 33, 34]), model=ScalarModel(intercept=0.2435599842214549, linear_terms=array([0.00032528, 0.05273933]), square_terms=array([[2.32924566e-04, 6.28242993e-03], + [6.28242993e-03, 6.44662821e-01]]), scale=0.087578125, shift=array([5.36174794, 0.1758779 ])), vector_model=VectorModel(intercepts=array([ 0.04424533, 0.09706756, 0.09964179, 0.12817482, 0.14600609, + 0.16462579, 0.18727309, 0.2198423 , 0.14621231, 0.21589468, + -0.09902459, -0.11677074, -0.13794235, -0.11385871, -0.10645744, + -0.10854051, -0.10625494]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + 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0.99]))), model_indices=array([25, 26, 29, 30, 31, 32, 33, 34, 35]), model=ScalarModel(intercept=0.2411702136529787, linear_terms=array([-0.00029148, -0.00161231]), square_terms=array([[7.59338494e-04, 1.81333427e-02], + [1.81333427e-02, 2.02348592e+00]]), scale=array([0.15522818, 0.15522818]), shift=array([5.44896581, 0.16786346])), vector_model=VectorModel(intercepts=array([ 0.04424533, 0.09706756, 0.09964179, 0.12817482, 0.14600609, + 0.16462579, 0.18727309, 0.2198423 , 0.14621231, 0.21589468, + -0.09902459, -0.11677074, -0.13794235, -0.11385871, -0.10645744, + -0.10854051, -0.10625494]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 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35, 36]), model=ScalarModel(intercept=0.24163478548943507, linear_terms=array([ 0.00016458, -0.00055621]), square_terms=array([[2.57908296e-04, 6.00198503e-03], + [6.00198503e-03, 6.44118485e-01]]), scale=0.087578125, shift=array([5.44896581, 0.16786346])), vector_model=VectorModel(intercepts=array([ 0.04424533, 0.09706756, 0.09964179, 0.12817482, 0.14600609, + 0.16462579, 0.18727309, 0.2198423 , 0.14621231, 0.21589468, + -0.09902459, -0.11677074, -0.13794235, -0.11385871, -0.10645744, + -0.10854051, -0.10625494]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], 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linear_terms=array([-0.00018881, 0.00035398]), square_terms=array([[8.05230298e-04, 1.86970634e-02], + [1.86970634e-02, 2.02386702e+00]]), scale=array([0.15522818, 0.15522818]), shift=array([5.36139226, 0.16875945])), vector_model=VectorModel(intercepts=array([ 0.04424533, 0.09706756, 0.09964179, 0.12817482, 0.14600609, + 0.16462579, 0.18727309, 0.2198423 , 0.14621231, 0.21589468, + -0.09902459, -0.11677074, -0.13794235, -0.11385871, -0.10645744, + -0.10854051, -0.10625494]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], 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square_terms=array([[2.60518703e-04, 5.70133267e-03], + [5.70133267e-03, 6.43763482e-01]]), scale=0.087578125, shift=array([5.36139226, 0.16875945])), vector_model=VectorModel(intercepts=array([ 0.04424533, 0.09706756, 0.09964179, 0.12817482, 0.14600609, + 0.16462579, 0.18727309, 0.2198423 , 0.14621231, 0.21589468, + -0.09902459, -0.11677074, -0.13794235, -0.11385871, -0.10645744, + -0.10854051, -0.10625494]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 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1.60944325e-01]]), scale=0.0437890625, shift=array([5.36139226, 0.16875945])), vector_model=VectorModel(intercepts=array([ 0.04424533, 0.09706756, 0.09964179, 0.12817482, 0.14600609, + 0.16462579, 0.18727309, 0.2198423 , 0.14621231, 0.21589468, + -0.09902459, -0.11677074, -0.13794235, -0.11385871, -0.10645744, + -0.10854051, -0.10625494]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=0.700625, shift=array([7.00625, 0.19375])), candidate_index=40, candidate_x=array([5.31760507, 0.16916422]), index=40, x=array([5.31760507, 0.16916422]), fval=0.24241985946629963, rho=7.194700985609317, accepted=True, new_indices=array([], dtype=int32), old_indices_used=array([26, 30, 31, 32, 34, 35, 37, 38, 39]), old_indices_discarded=array([25, 29, 33, 36]), step_length=0.043789062500000274, relative_step_length=1.0000000000000062, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([5.31760507, 0.16916422]), radius=0.087578125, bounds=Bounds(lower=array([1.1 , 0.01]), upper=array([20. , 0.99]))), model_indices=array([25, 30, 31, 32, 34, 37, 38, 39, 40]), model=ScalarModel(intercept=0.24205486457802278, linear_terms=array([0.00023275, 0.000779 ]), square_terms=array([[3.03100394e-04, 5.73493197e-03], + [5.73493197e-03, 6.43806788e-01]]), scale=0.087578125, shift=array([5.31760507, 0.16916422])), vector_model=VectorModel(intercepts=array([ 0.04424533, 0.09706756, 0.09964179, 0.12817482, 0.14600609, + 0.16462579, 0.18727309, 0.2198423 , 0.14621231, 0.21589468, + -0.09902459, -0.11677074, -0.13794235, -0.11385871, -0.10645744, + -0.10854051, -0.10625494]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=0.700625, shift=array([7.00625, 0.19375])), candidate_index=41, candidate_x=array([5.23002957, 0.16984189]), index=40, x=array([5.31760507, 0.16916422]), fval=0.24241985946629963, rho=-6.146531737571127, accepted=False, new_indices=array([], dtype=int32), old_indices_used=array([25, 30, 31, 32, 34, 37, 38, 39, 40]), old_indices_discarded=array([24, 26, 27, 28, 29, 33, 35, 36]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([5.31760507, 0.16916422]), radius=0.0437890625, bounds=Bounds(lower=array([1.1 , 0.01]), upper=array([20. , 0.99]))), model_indices=array([25, 30, 31, 32, 34, 37, 38, 40, 41]), model=ScalarModel(intercept=0.24213302949529256, linear_terms=array([-3.78622622e-05, 2.41519221e-04]), square_terms=array([[6.90966248e-05, 1.48098964e-03], + [1.48098964e-03, 1.60965844e-01]]), scale=0.0437890625, shift=array([5.31760507, 0.16916422])), vector_model=VectorModel(intercepts=array([ 0.04424533, 0.09706756, 0.09964179, 0.12817482, 0.14600609, + 0.16462579, 0.18727309, 0.2198423 , 0.14621231, 0.21589468, + -0.09902459, -0.11677074, -0.13794235, -0.11385871, -0.10645744, + -0.10854051, -0.10625494]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=0.700625, shift=array([7.00625, 0.19375])), candidate_index=42, candidate_x=array([5.36139158, 0.16869151]), index=40, x=array([5.31760507, 0.16916422]), fval=0.24241985946629963, rho=-11.833264403894546, accepted=False, new_indices=array([], dtype=int32), old_indices_used=array([25, 30, 31, 32, 34, 37, 38, 40, 41]), old_indices_discarded=array([26, 29, 33, 35, 36, 39]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([5.31760507, 0.16916422]), radius=0.02189453125, bounds=Bounds(lower=array([1.1 , 0.01]), upper=array([20. , 0.99]))), model_indices=array([25, 30, 31, 32, 37, 38, 40, 41, 42]), model=ScalarModel(intercept=0.24265765523257948, linear_terms=array([-0.00010296, -0.00348716]), square_terms=array([[1.52341867e-05, 3.50476207e-04], + [3.50476207e-04, 4.17971723e-02]]), scale=0.02189453125, shift=array([5.31760507, 0.16916422])), vector_model=VectorModel(intercepts=array([ 0.04424533, 0.09706756, 0.09964179, 0.12817482, 0.14600609, + 0.16462579, 0.18727309, 0.2198423 , 0.14621231, 0.21589468, + -0.09902459, -0.11677074, -0.13794235, -0.11385871, -0.10645744, + -0.10854051, -0.10625494]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=0.700625, shift=array([7.00625, 0.19375])), candidate_index=43, candidate_x=array([5.33950848, 0.17080482]), index=43, x=array([5.33950848, 0.17080482]), fval=0.24222716621340298, rho=0.9043831615651715, accepted=True, new_indices=array([], dtype=int32), old_indices_used=array([25, 30, 31, 32, 37, 38, 40, 41, 42]), old_indices_discarded=array([26, 29, 34, 39]), step_length=0.021964765363485655, relative_step_length=1.0032078381895322, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([5.33950848, 0.17080482]), radius=0.0437890625, bounds=Bounds(lower=array([1.1 , 0.01]), upper=array([20. , 0.99]))), model_indices=array([30, 31, 32, 37, 38, 39, 40, 42, 43]), model=ScalarModel(intercept=0.2423976703093635, linear_terms=array([-3.01430010e-05, 2.34992933e-04]), square_terms=array([[5.91513482e-05, 1.37667035e-03], + [1.37667035e-03, 1.65820314e-01]]), scale=0.0437890625, shift=array([5.33950848, 0.17080482])), vector_model=VectorModel(intercepts=array([ 0.04424533, 0.09706756, 0.09964179, 0.12817482, 0.14600609, + 0.16462579, 0.18727309, 0.2198423 , 0.14621231, 0.21589468, + -0.09902459, -0.11677074, -0.13794235, -0.11385871, -0.10645744, + -0.10854051, -0.10625494]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=0.700625, shift=array([7.00625, 0.19375])), candidate_index=44, candidate_x=array([5.36895747, 0.17049827]), index=43, x=array([5.33950848, 0.17080482]), fval=0.24222716621340298, rho=-9.331642519757773, accepted=False, new_indices=array([], dtype=int32), old_indices_used=array([30, 31, 32, 37, 38, 39, 40, 42, 43]), old_indices_discarded=array([25, 26, 29, 33, 34, 35, 36, 41]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([5.33950848, 0.17080482]), radius=0.02189453125, bounds=Bounds(lower=array([1.1 , 0.01]), upper=array([20. , 0.99]))), model_indices=array([30, 32, 37, 38, 39, 40, 42, 43, 44]), model=ScalarModel(intercept=0.24235348524537714, linear_terms=array([ 5.95198861e-06, -8.48814584e-06]), square_terms=array([[1.47776329e-05, 3.48481891e-04], + [3.48481891e-04, 4.14093403e-02]]), scale=0.02189453125, shift=array([5.33950848, 0.17080482])), vector_model=VectorModel(intercepts=array([ 0.04424533, 0.09706756, 0.09964179, 0.12817482, 0.14600609, + 0.16462579, 0.18727309, 0.2198423 , 0.14621231, 0.21589468, + -0.09902459, -0.11677074, -0.13794235, -0.11385871, -0.10645744, + -0.10854051, -0.10625494]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=0.700625, shift=array([7.00625, 0.19375])), candidate_index=45, candidate_x=array([5.32837464, 0.170903 ]), index=43, x=array([5.33950848, 0.17080482]), fval=0.24222716621340298, rho=-24.42199537270614, accepted=False, new_indices=array([], dtype=int32), old_indices_used=array([30, 32, 37, 38, 39, 40, 42, 43, 44]), old_indices_discarded=array([25, 26, 31, 34]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([5.33950848, 0.17080482]), radius=0.010947265625, bounds=Bounds(lower=array([1.1 , 0.01]), upper=array([20. , 0.99]))), model_indices=array([32, 37, 40, 42, 43, 44, 45]), model=ScalarModel(intercept=0.2422806237585476, linear_terms=array([ 2.67171372e-05, -2.05431480e-04]), square_terms=array([[3.68279483e-06, 8.49740419e-05], + [8.49740419e-05, 1.03070513e-02]]), scale=0.010947265625, shift=array([5.33950848, 0.17080482])), vector_model=VectorModel(intercepts=array([ 0.04424533, 0.09706756, 0.09964179, 0.12817482, 0.14600609, + 0.16462579, 0.18727309, 0.2198423 , 0.14621231, 0.21589468, + -0.09902459, -0.11677074, -0.13794235, -0.11385871, -0.10645744, + -0.10854051, -0.10625494]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=0.700625, shift=array([7.00625, 0.19375])), candidate_index=46, candidate_x=array([5.32856345, 0.17111248]), index=43, x=array([5.33950848, 0.17080482]), fval=0.24222716621340298, rho=-2.0149510031231594, accepted=False, new_indices=array([], dtype=int32), old_indices_used=array([32, 37, 40, 42, 43, 44, 45]), old_indices_discarded=array([], dtype=int32), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([5.33950848, 0.17080482]), radius=0.0054736328125, bounds=Bounds(lower=array([1.1 , 0.01]), upper=array([20. , 0.99]))), model_indices=array([32, 37, 40, 42, 43, 45, 46]), model=ScalarModel(intercept=0.24229025426011608, linear_terms=array([ 1.48827190e-05, -1.05452116e-04]), square_terms=array([[9.09604685e-07, 2.07560472e-05], + [2.07560472e-05, 2.57873989e-03]]), scale=0.0054736328125, shift=array([5.33950848, 0.17080482])), vector_model=VectorModel(intercepts=array([ 0.04424533, 0.09706756, 0.09964179, 0.12817482, 0.14600609, + 0.16462579, 0.18727309, 0.2198423 , 0.14621231, 0.21589468, + -0.09902459, -0.11677074, -0.13794235, -0.11385871, -0.10645744, + -0.10854051, -0.10625494]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 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n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([5.33950848, 0.17080482]), radius=0.00273681640625, bounds=Bounds(lower=array([1.1 , 0.01]), upper=array([20. , 0.99]))), model_indices=array([43, 45, 46, 47]), model=ScalarModel(intercept=0.24222624543591792, linear_terms=array([-7.33525171e-06, 2.20337847e-04]), square_terms=array([[2.41748426e-07, 5.48721051e-06], + [5.48721051e-06, 5.94912648e-04]]), scale=0.00273681640625, shift=array([5.33950848, 0.17080482])), vector_model=VectorModel(intercepts=array([ 0.04424533, 0.09706756, 0.09964179, 0.12817482, 0.14600609, + 0.16462579, 0.18727309, 0.2198423 , 0.14621231, 0.21589468, + -0.09902459, -0.11677074, -0.13794235, -0.11385871, -0.10645744, + -0.10854051, -0.10625494]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=0.700625, shift=array([7.00625, 0.19375])), candidate_index=48, candidate_x=array([5.34223575, 0.16978181]), index=43, x=array([5.33950848, 0.17080482]), fval=0.24222716621340298, rho=-1.050453647514022, accepted=False, new_indices=array([], dtype=int32), old_indices_used=array([43, 45, 46, 47]), old_indices_discarded=array([], dtype=int32), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([5.33950848, 0.17080482]), radius=0.001368408203125, bounds=Bounds(lower=array([1.1 , 0.01]), upper=array([20. , 0.99]))), model_indices=array([43, 47, 48]), model=ScalarModel(intercept=0.24222716621340284, linear_terms=array([-1.02551120e-05, -3.95148592e-05]), square_terms=array([[6.98218857e-08, 1.88148453e-06], + [1.88148453e-06, 1.65041401e-04]]), scale=0.001368408203125, shift=array([5.33950848, 0.17080482])), vector_model=VectorModel(intercepts=array([ 0.04424533, 0.09706756, 0.09964179, 0.12817482, 0.14600609, + 0.16462579, 0.18727309, 0.2198423 , 0.14621231, 0.21589468, + -0.09902459, -0.11677074, -0.13794235, -0.11385871, -0.10645744, + -0.10854051, -0.10625494]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + 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48, 49]), model=ScalarModel(intercept=0.24222716621340307, linear_terms=array([6.14670909e-06, 1.02989082e-05]), square_terms=array([[1.43372945e-08, 1.96028127e-07], + [1.96028127e-07, 3.98197561e-05]]), scale=0.0006842041015625, shift=array([5.33950848, 0.17080482])), vector_model=VectorModel(intercepts=array([ 0.04424533, 0.09706756, 0.09964179, 0.12817482, 0.14600609, + 0.16462579, 0.18727309, 0.2198423 , 0.14621231, 0.21589468, + -0.09902459, -0.11677074, -0.13794235, -0.11385871, -0.10645744, + -0.10854051, -0.10625494]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + 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linear_terms=array([-3.89600052e-06, -1.76546459e-05]), square_terms=array([[6.25029901e-08, 1.54407834e-06], + [1.54407834e-06, 1.61121526e-04]]), scale=0.001368408203125, shift=array([5.33882353, 0.17065423])), vector_model=VectorModel(intercepts=array([ 0.04424533, 0.09706756, 0.09964179, 0.12817482, 0.14600609, + 0.16462579, 0.18727309, 0.2198423 , 0.14621231, 0.21589468, + -0.09902459, -0.11677074, -0.13794235, -0.11385871, -0.10645744, + -0.10854051, -0.10625494]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=0.700625, shift=array([7.00625, 0.19375])), candidate_index=51, candidate_x=array([5.34019328, 0.17078799]), index=50, x=array([5.33882353, 0.17065423]), fval=0.24222315394360727, rho=-2.8921828205303095, accepted=False, new_indices=array([], dtype=int32), old_indices_used=array([43, 47, 48, 49, 50]), old_indices_discarded=array([], dtype=int32), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([5.33882353, 0.17065423]), radius=0.0006842041015625, bounds=Bounds(lower=array([1.1 , 0.01]), upper=array([20. , 0.99]))), model_indices=array([43, 49, 50, 51]), model=ScalarModel(intercept=0.24222219917408055, linear_terms=array([ 7.93230033e-06, -1.17711940e-05]), square_terms=array([[1.62310723e-08, 3.63400305e-07], + [3.63400305e-07, 3.86016620e-05]]), scale=0.0006842041015625, shift=array([5.33882353, 0.17065423])), vector_model=VectorModel(intercepts=array([ 0.04424533, 0.09706756, 0.09964179, 0.12817482, 0.14600609, + 0.16462579, 0.18727309, 0.2198423 , 0.14621231, 0.21589468, + -0.09902459, -0.11677074, -0.13794235, -0.11385871, -0.10645744, + -0.10854051, -0.10625494]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=0.700625, shift=array([7.00625, 0.19375])), candidate_index=52, candidate_x=array([5.33814097, 0.17083226]), index=50, x=array([5.33882353, 0.17065423]), fval=0.24222315394360727, rho=-0.14512140450342684, accepted=False, new_indices=array([], dtype=int32), old_indices_used=array([43, 49, 50, 51]), old_indices_discarded=array([], dtype=int32), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([5.33882353, 0.17065423]), radius=0.00034210205078125, bounds=Bounds(lower=array([1.1 , 0.01]), upper=array([20. , 0.99]))), model_indices=array([43, 50, 51, 52]), model=ScalarModel(intercept=0.24222319841032375, linear_terms=array([1.99763146e-06, 5.57738554e-06]), square_terms=array([[3.72373755e-09, 9.11821416e-08], + [9.11821416e-08, 9.85528901e-06]]), scale=0.00034210205078125, shift=array([5.33882353, 0.17065423])), vector_model=VectorModel(intercepts=array([ 0.04424533, 0.09706756, 0.09964179, 0.12817482, 0.14600609, + 0.16462579, 0.18727309, 0.2198423 , 0.14621231, 0.21589468, + -0.09902459, -0.11677074, -0.13794235, -0.11385871, -0.10645744, + -0.10854051, -0.10625494]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=0.700625, shift=array([7.00625, 0.19375])), candidate_index=53, candidate_x=array([5.33851827, 0.17049811]), index=50, x=array([5.33882353, 0.17065423]), fval=0.24222315394360727, rho=-4.232464647796792, accepted=False, new_indices=array([], dtype=int32), old_indices_used=array([43, 50, 51, 52]), old_indices_discarded=array([], dtype=int32), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([5.33882353, 0.17065423]), radius=0.000171051025390625, bounds=Bounds(lower=array([1.1 , 0.01]), upper=array([20. , 0.99]))), model_indices=array([43, 50, 52, 53]), model=ScalarModel(intercept=0.24222851970904374, linear_terms=array([ 9.20804052e-08, -5.32837905e-06]), square_terms=array([[9.45290458e-10, 2.30234760e-08], + [2.30234760e-08, 2.43134636e-06]]), scale=0.000171051025390625, shift=array([5.33882353, 0.17065423])), vector_model=VectorModel(intercepts=array([ 0.04424533, 0.09706756, 0.09964179, 0.12817482, 0.14600609, + 0.16462579, 0.18727309, 0.2198423 , 0.14621231, 0.21589468, + -0.09902459, -0.11677074, -0.13794235, -0.11385871, -0.10645744, + -0.10854051, -0.10625494]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=0.700625, shift=array([7.00625, 0.19375])), candidate_index=54, candidate_x=array([5.33878192, 0.17082014]), index=50, x=array([5.33882353, 0.17065423]), fval=0.24222315394360727, rho=-0.2598782806832573, accepted=False, new_indices=array([], dtype=int32), old_indices_used=array([43, 50, 52, 53]), old_indices_discarded=array([], dtype=int32), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([5.33882353, 0.17065423]), radius=8.55255126953125e-05, bounds=Bounds(lower=array([1.1 , 0.01]), upper=array([20. , 0.99]))), model_indices=array([50, 53, 54]), model=ScalarModel(intercept=0.2422231539436072, linear_terms=array([-3.14907959e-06, -8.42234292e-07]), square_terms=array([[3.63526659e-10, 1.13163660e-09], + [1.13163660e-09, 6.14271368e-07]]), scale=8.55255126953125e-05, shift=array([5.33882353, 0.17065423])), vector_model=VectorModel(intercepts=array([ 0.04424533, 0.09706756, 0.09964179, 0.12817482, 0.14600609, + 0.16462579, 0.18727309, 0.2198423 , 0.14621231, 0.21589468, + -0.09902459, -0.11677074, -0.13794235, -0.11385871, 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new_indices=array([], dtype=int32), old_indices_used=array([50, 53, 54]), old_indices_discarded=array([], dtype=int32), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([5.33882353, 0.17065423]), radius=4.276275634765625e-05, bounds=Bounds(lower=array([1.1 , 0.01]), upper=array([20. , 0.99]))), model_indices=array([50, 54, 55]), model=ScalarModel(intercept=0.24222315394360722, linear_terms=array([ 8.70513659e-08, -4.37510681e-09]), square_terms=array([[8.02169837e-11, 1.60425228e-09], + [1.60425228e-09, 1.54231322e-07]]), scale=4.276275634765625e-05, shift=array([5.33882353, 0.17065423])), vector_model=VectorModel(intercepts=array([ 0.04424533, 0.09706756, 0.09964179, 0.12817482, 0.14600609, + 0.16462579, 0.18727309, 0.2198423 , 0.14621231, 0.21589468, + -0.09902459, -0.11677074, -0.13794235, -0.11385871, -0.10645744, + -0.10854051, -0.10625494]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 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step_length=4.276717619883001e-05, relative_step_length=1.000103357490285, n_evals_per_point=1, n_evals_acceptance=1)], 'tranquilo_history': History for least_squares function with 57 entries., 'multistart_info': {'start_parameters': [array([7.00625, 0.19375]), array([7.55707178, 0.15947986])], 'local_optima': [{'solution_x': array([5.33878077, 0.17065529]), 'solution_criterion': 0.24222229239256732, 'states': [State(trustregion=Region(center=array([7.00625, 0.19375]), radius=0.700625, bounds=Bounds(lower=array([1.1 , 0.01]), upper=array([20. , 0.99]))), model_indices=[0], model=ScalarModel(intercept=0.3273843758368489, linear_terms=array([0., 0.]), square_terms=array([[0., 0.], + [0., 0.]]), scale=0.700625, shift=array([7.00625, 0.19375])), vector_model=VectorModel(intercepts=array([ 0.04424533, 0.09706756, 0.09964179, 0.12817482, 0.14600609, + 0.16462579, 0.18727309, 0.2198423 , 0.14621231, 0.21589468, + -0.09902459, -0.11677074, -0.13794235, -0.11385871, -0.10645744, + -0.10854051, 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step_length=None, relative_step_length=None, n_evals_per_point=None, n_evals_acceptance=None), State(trustregion=Region(center=array([7.00625, 0.19375]), radius=0.700625, bounds=Bounds(lower=array([1.1 , 0.01]), upper=array([20. , 0.99]))), model_indices=array([ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12]), model=ScalarModel(intercept=11.224951550903995, linear_terms=array([-1.37625354, 32.5154691 ]), square_terms=array([[ 0.09351784, -2.07104056], + [-2.07104056, 48.22141916]]), scale=array([0.62091274, 0.40233137]), shift=array([7.00625 , 0.41233137])), vector_model=VectorModel(intercepts=array([ 0.04424533, 0.09706756, 0.09964179, 0.12817482, 0.14600609, + 0.16462579, 0.18727309, 0.2198423 , 0.14621231, 0.21589468, + -0.09902459, -0.11677074, -0.13794235, -0.11385871, -0.10645744, + -0.10854051, -0.10625494]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + 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0.99]))), model_indices=array([ 1, 3, 7, 13, 14, 15]), model=ScalarModel(intercept=0.2909351370686484, linear_terms=array([0.01016955, 0.239779 ]), square_terms=array([[0.00441972, 0.04993243], + [0.04993243, 0.684917 ]]), scale=0.087578125, shift=array([6.25324275, 0.19438789])), vector_model=VectorModel(intercepts=array([ 0.04424533, 0.09706756, 0.09964179, 0.12817482, 0.14600609, + 0.16462579, 0.18727309, 0.2198423 , 0.14621231, 0.21589468, + -0.09902459, -0.11677074, -0.13794235, -0.11385871, -0.10645744, + -0.10854051, -0.10625494]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + 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linear_terms=array([-0.10978373, -0.38806688]), square_terms=array([[0.34292001, 1.58579951], + [1.58579951, 7.51750345]]), scale=array([0.15522818, 0.15155507]), shift=array([6.33822271, 0.16155507])), vector_model=VectorModel(intercepts=array([ 0.04424533, 0.09706756, 0.09964179, 0.12817482, 0.14600609, + 0.16462579, 0.18727309, 0.2198423 , 0.14621231, 0.21589468, + -0.09902459, -0.11677074, -0.13794235, -0.11385871, -0.10645744, + -0.10854051, -0.10625494]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], 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0.68633371]]), scale=0.087578125, shift=array([6.33822271, 0.15788195])), vector_model=VectorModel(intercepts=array([ 0.04424533, 0.09706756, 0.09964179, 0.12817482, 0.14600609, + 0.16462579, 0.18727309, 0.2198423 , 0.14621231, 0.21589468, + -0.09902459, -0.11677074, -0.13794235, -0.11385871, -0.10645744, + -0.10854051, -0.10625494]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=0.700625, shift=array([7.00625, 0.19375])), candidate_index=18, candidate_x=array([6.42567538, 0.15294566]), index=16, x=array([6.33822271, 0.15788195]), fval=0.2614570472767362, rho=-0.7750579998984433, accepted=False, new_indices=array([], dtype=int32), old_indices_used=array([ 1, 3, 7, 11, 13, 14, 15, 16, 17]), old_indices_discarded=array([], dtype=int32), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([6.33822271, 0.15788195]), radius=0.0437890625, bounds=Bounds(lower=array([1.1 , 0.01]), upper=array([20. , 0.99]))), model_indices=array([ 1, 13, 15, 16, 17, 18]), model=ScalarModel(intercept=0.2588317231036329, linear_terms=array([ 0.00363168, -0.00423961]), square_terms=array([[1.17813939e-04, 1.72772939e-03], + [1.72772939e-03, 1.19696569e-01]]), scale=0.0437890625, shift=array([6.33822271, 0.15788195])), vector_model=VectorModel(intercepts=array([ 0.04424533, 0.09706756, 0.09964179, 0.12817482, 0.14600609, + 0.16462579, 0.18727309, 0.2198423 , 0.14621231, 0.21589468, + -0.09902459, -0.11677074, -0.13794235, -0.11385871, -0.10645744, + -0.10854051, -0.10625494]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=0.700625, shift=array([7.00625, 0.19375])), candidate_index=19, candidate_x=array([6.29445974, 0.16000091]), index=19, x=array([6.29445974, 0.16000091]), fval=0.2594527871161228, rho=0.5388880366161921, accepted=True, new_indices=array([], dtype=int32), old_indices_used=array([ 1, 13, 15, 16, 17, 18]), old_indices_discarded=array([], dtype=int32), step_length=0.04381424054578142, relative_step_length=1.0005749848099947, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([6.29445974, 0.16000091]), radius=0.087578125, bounds=Bounds(lower=array([1.1 , 0.01]), upper=array([20. , 0.99]))), model_indices=array([ 1, 3, 13, 14, 15, 16, 17, 18, 19]), model=ScalarModel(intercept=0.2541677101008941, linear_terms=array([-0.00368238, -0.03323817]), square_terms=array([[0.00145555, 0.02969193], + [0.02969193, 0.6672799 ]]), scale=0.087578125, shift=array([6.29445974, 0.16000091])), vector_model=VectorModel(intercepts=array([ 0.04424533, 0.09706756, 0.09964179, 0.12817482, 0.14600609, + 0.16462579, 0.18727309, 0.2198423 , 0.14621231, 0.21589468, + -0.09902459, -0.11677074, -0.13794235, -0.11385871, -0.10645744, + -0.10854051, -0.10625494]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=0.700625, shift=array([7.00625, 0.19375])), candidate_index=20, candidate_x=array([6.38214384, 0.1604602 ]), index=19, x=array([6.29445974, 0.16000091]), fval=0.2594527871161228, rho=-0.930670096284453, accepted=False, new_indices=array([], dtype=int32), old_indices_used=array([ 1, 3, 13, 14, 15, 16, 17, 18, 19]), old_indices_discarded=array([ 7, 11]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([6.29445974, 0.16000091]), radius=0.0437890625, bounds=Bounds(lower=array([1.1 , 0.01]), upper=array([20. , 0.99]))), model_indices=array([ 1, 13, 15, 16, 17, 18, 19, 20]), model=ScalarModel(intercept=0.25622931078220434, linear_terms=array([ 0.0032415 , -0.00073259]), square_terms=array([[1.03290011e-04, 1.82810922e-03], + [1.82810922e-03, 1.19546137e-01]]), scale=0.0437890625, shift=array([6.29445974, 0.16000091])), vector_model=VectorModel(intercepts=array([ 0.04424533, 0.09706756, 0.09964179, 0.12817482, 0.14600609, + 0.16462579, 0.18727309, 0.2198423 , 0.14621231, 0.21589468, + -0.09902459, -0.11677074, -0.13794235, -0.11385871, -0.10645744, + -0.10854051, -0.10625494]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=0.700625, shift=array([7.00625, 0.19375])), candidate_index=21, candidate_x=array([6.25067953, 0.16091447]), index=21, x=array([6.25067953, 0.16091447]), fval=0.2577870645585467, rho=0.517848980651204, accepted=True, new_indices=array([], dtype=int32), old_indices_used=array([ 1, 13, 15, 16, 17, 18, 19, 20]), old_indices_discarded=array([], dtype=int32), step_length=0.043789739030257874, relative_step_length=1.0000154497543279, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([6.25067953, 0.16091447]), radius=0.087578125, bounds=Bounds(lower=array([1.1 , 0.01]), upper=array([20. , 0.99]))), model_indices=array([ 1, 13, 14, 15, 16, 18, 19, 20, 21]), model=ScalarModel(intercept=0.25500561017058476, linear_terms=array([0.00514188, 0.00157206]), square_terms=array([[3.29759763e-04, 4.68476327e-03], + [4.68476327e-03, 4.75402508e-01]]), scale=0.087578125, shift=array([6.25067953, 0.16091447])), vector_model=VectorModel(intercepts=array([ 0.04424533, 0.09706756, 0.09964179, 0.12817482, 0.14600609, + 0.16462579, 0.18727309, 0.2198423 , 0.14621231, 0.21589468, + -0.09902459, -0.11677074, -0.13794235, -0.11385871, -0.10645744, + -0.10854051, -0.10625494]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=0.700625, shift=array([7.00625, 0.19375])), candidate_index=22, candidate_x=array([6.16310275, 0.16148209]), index=22, x=array([6.16310275, 0.16148209]), fval=0.2552353311983439, rho=0.5116649557870464, accepted=True, new_indices=array([], dtype=int32), old_indices_used=array([ 1, 13, 14, 15, 16, 18, 19, 20, 21]), old_indices_discarded=array([ 3, 7, 17]), step_length=0.08757862032278296, relative_step_length=1.0000056557819998, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([6.16310275, 0.16148209]), radius=0.17515625, bounds=Bounds(lower=array([1.1 , 0.01]), upper=array([20. , 0.99]))), model_indices=array([ 1, 13, 14, 15, 16, 19, 20, 21, 22]), model=ScalarModel(intercept=0.2515880836028085, linear_terms=array([0.00754998, 0.01225116]), square_terms=array([[8.67053730e-04, 1.69602107e-02], + [1.69602107e-02, 1.46374627e+00]]), scale=array([0.15522818, 0.15335514]), shift=array([6.16310275, 0.16335514])), vector_model=VectorModel(intercepts=array([ 0.04424533, 0.09706756, 0.09964179, 0.12817482, 0.14600609, + 0.16462579, 0.18727309, 0.2198423 , 0.14621231, 0.21589468, + -0.09902459, -0.11677074, -0.13794235, -0.11385871, -0.10645744, + -0.10854051, -0.10625494]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=0.700625, shift=array([7.00625, 0.19375])), candidate_index=23, candidate_x=array([6.00787457, 0.1638485 ]), index=23, x=array([6.00787457, 0.1638485 ]), fval=0.25064066883423725, rho=0.6486363276282296, accepted=True, new_indices=array([], dtype=int32), old_indices_used=array([ 1, 13, 14, 15, 16, 19, 20, 21, 22]), old_indices_discarded=array([ 0, 3, 7, 10, 11, 12, 17, 18]), step_length=0.1552462214938793, relative_step_length=0.8863298996974375, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([6.00787457, 0.1638485 ]), radius=0.3503125, bounds=Bounds(lower=array([1.1 , 0.01]), upper=array([20. , 0.99]))), model_indices=array([13, 14, 15, 16, 19, 20, 21, 22, 23]), model=ScalarModel(intercept=0.43332719746500753, linear_terms=array([0.03146291, 1.14425379]), square_terms=array([[2.68439891e-03, 7.19387302e-02], + [7.19387302e-02, 3.57398202e+00]]), scale=array([0.31045637, 0.23215243]), shift=array([6.00787457, 0.24215243])), vector_model=VectorModel(intercepts=array([ 0.04424533, 0.09706756, 0.09964179, 0.12817482, 0.14600609, + 0.16462579, 0.18727309, 0.2198423 , 0.14621231, 0.21589468, + -0.09902459, -0.11677074, -0.13794235, -0.11385871, -0.10645744, + -0.10854051, -0.10625494]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=0.700625, shift=array([7.00625, 0.19375])), candidate_index=24, candidate_x=array([5.6974182 , 0.17249888]), index=24, x=array([5.6974182 , 0.17249888]), fval=0.244970934682092, rho=0.6800504779079048, accepted=True, new_indices=array([], dtype=int32), old_indices_used=array([13, 14, 15, 16, 19, 20, 21, 22, 23]), old_indices_discarded=array([ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 17, 18]), step_length=0.3105768611152018, relative_step_length=0.8865708791870166, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([5.6974182 , 0.17249888]), radius=0.700625, bounds=Bounds(lower=array([1.1 , 0.01]), upper=array([20. , 0.99]))), model_indices=array([ 1, 13, 14, 15, 16, 19, 22, 23, 24]), model=ScalarModel(intercept=1.9359689768705584, linear_terms=array([0.14431675, 5.7192291 ]), square_terms=array([[0.01061289, 0.22387827], + [0.22387827, 9.66222181]]), scale=array([0.62091274, 0.39170581]), shift=array([5.6974182 , 0.40170581])), vector_model=VectorModel(intercepts=array([ 0.04424533, 0.09706756, 0.09964179, 0.12817482, 0.14600609, + 0.16462579, 0.18727309, 0.2198423 , 0.14621231, 0.21589468, + -0.09902459, -0.11677074, -0.13794235, -0.11385871, -0.10645744, + -0.10854051, -0.10625494]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 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17, 18, 20, 21]), step_length=0.46128587321697967, relative_step_length=0.6583919689091592, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([5.2361468 , 0.17615356]), radius=1.40125, bounds=Bounds(lower=array([1.1 , 0.01]), upper=array([20. , 0.99]))), model_indices=array([ 1, 7, 10, 14, 16, 17, 22, 24, 25]), model=ScalarModel(intercept=19.556928495798605, linear_terms=array([ 2.66108959, 60.1251518 ]), square_terms=array([[ 0.19711181, 4.14595444], + [ 4.14595444, 93.60232406]]), scale=array([1.24182548, 0.49 ]), shift=array([5.2361468, 0.5 ])), vector_model=VectorModel(intercepts=array([ 0.04424533, 0.09706756, 0.09964179, 0.12817482, 0.14600609, + 0.16462579, 0.18727309, 0.2198423 , 0.14621231, 0.21589468, + -0.09902459, -0.11677074, -0.13794235, -0.11385871, -0.10645744, + -0.10854051, -0.10625494]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], 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relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([5.2361468 , 0.17615356]), radius=0.700625, bounds=Bounds(lower=array([1.1 , 0.01]), upper=array([20. , 0.99]))), model_indices=array([14, 15, 19, 21, 22, 23, 24, 25, 26]), model=ScalarModel(intercept=2.023039226033913, linear_terms=array([0.11112348, 6.16604764]), square_terms=array([[9.99812684e-03, 1.87643817e-01], + [1.87643817e-01, 1.06798417e+01]]), scale=array([0.62091274, 0.39353315]), shift=array([5.2361468 , 0.40353315])), vector_model=VectorModel(intercepts=array([ 0.04424533, 0.09706756, 0.09964179, 0.12817482, 0.14600609, + 0.16462579, 0.18727309, 0.2198423 , 0.14621231, 0.21589468, + -0.09902459, -0.11677074, -0.13794235, -0.11385871, -0.10645744, + -0.10854051, -0.10625494]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=0.700625, shift=array([7.00625, 0.19375])), candidate_index=27, candidate_x=array([4.97795012, 0.17920049]), index=25, x=array([5.2361468 , 0.17615356]), fval=0.2440600019927147, rho=-9.379349103371986, accepted=False, new_indices=array([], dtype=int32), old_indices_used=array([14, 15, 19, 21, 22, 23, 24, 25, 26]), old_indices_discarded=array([ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 16, 17, 18, + 20]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([5.2361468 , 0.17615356]), radius=0.3503125, bounds=Bounds(lower=array([1.1 , 0.01]), upper=array([20. , 0.99]))), model_indices=array([14, 21, 22, 23, 24, 25, 26, 27, 28]), model=ScalarModel(intercept=0.5871067495424316, linear_terms=array([0.02508987, 2.27718757]), square_terms=array([[2.83476082e-03, 8.32114910e-02], + [8.32114910e-02, 7.59032634e+00]]), scale=array([0.31045637, 0.23830497]), shift=array([5.2361468 , 0.24830497])), vector_model=VectorModel(intercepts=array([ 0.04424533, 0.09706756, 0.09964179, 0.12817482, 0.14600609, + 0.16462579, 0.18727309, 0.2198423 , 0.14621231, 0.21589468, + -0.09902459, -0.11677074, -0.13794235, -0.11385871, -0.10645744, + -0.10854051, -0.10625494]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 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State(trustregion=Region(center=array([5.2361468 , 0.17615356]), radius=0.17515625, bounds=Bounds(lower=array([1.1 , 0.01]), upper=array([20. , 0.99]))), model_indices=array([14, 23, 24, 25, 26, 27, 28, 29]), model=ScalarModel(intercept=0.24537978825844767, linear_terms=array([-0.00017886, -0.00847909]), square_terms=array([[6.40294020e-04, 1.45475512e-02], + [1.45475512e-02, 3.24873183e+00]]), scale=array([0.15522818, 0.15522818]), shift=array([5.2361468 , 0.17615356])), vector_model=VectorModel(intercepts=array([ 0.04424533, 0.09706756, 0.09964179, 0.12817482, 0.14600609, + 0.16462579, 0.18727309, 0.2198423 , 0.14621231, 0.21589468, + -0.09902459, -0.11677074, -0.13794235, -0.11385871, -0.10645744, + -0.10854051, -0.10625494]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + 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0.17638843]), radius=0.17515625, bounds=Bounds(lower=array([1.1 , 0.01]), upper=array([20. , 0.99]))), model_indices=array([14, 23, 24, 25, 26, 27, 28, 29, 30]), model=ScalarModel(intercept=0.24506470035985778, linear_terms=array([5.54445372e-05, 8.93470786e-05]), square_terms=array([[6.38751471e-04, 1.45480845e-02], + [1.45480845e-02, 3.24873994e+00]]), scale=array([0.15522818, 0.15522818]), shift=array([5.2741713 , 0.17638843])), vector_model=VectorModel(intercepts=array([ 0.04424533, 0.09706756, 0.09964179, 0.12817482, 0.14600609, + 0.16462579, 0.18727309, 0.2198423 , 0.14621231, 0.21589468, + -0.09902459, -0.11677074, -0.13794235, -0.11385871, -0.10645744, + -0.10854051, -0.10625494]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + 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upper=array([20. , 0.99]))), model_indices=array([24, 25, 26, 27, 28, 29, 30, 31]), model=ScalarModel(intercept=0.24474192813793477, linear_terms=array([-0.00048722, -0.00034972]), square_terms=array([[2.32194110e-04, 6.38817516e-03], + [6.38817516e-03, 1.03554328e+00]]), scale=0.087578125, shift=array([5.2741713 , 0.17638843])), vector_model=VectorModel(intercepts=array([ 0.04424533, 0.09706756, 0.09964179, 0.12817482, 0.14600609, + 0.16462579, 0.18727309, 0.2198423 , 0.14621231, 0.21589468, + -0.09902459, -0.11677074, -0.13794235, -0.11385871, -0.10645744, + -0.10854051, -0.10625494]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 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31, 32]), model=ScalarModel(intercept=0.2442299698961134, linear_terms=array([-0.00054183, 0.00016305]), square_terms=array([[7.30553468e-04, 2.00849094e-02], + [2.00849094e-02, 3.25315131e+00]]), scale=array([0.15522818, 0.15522818]), shift=array([5.36174794, 0.1758779 ])), vector_model=VectorModel(intercepts=array([ 0.04424533, 0.09706756, 0.09964179, 0.12817482, 0.14600609, + 0.16462579, 0.18727309, 0.2198423 , 0.14621231, 0.21589468, + -0.09902459, -0.11677074, -0.13794235, -0.11385871, -0.10645744, + -0.10854051, -0.10625494]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 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linear_terms=array([0.00032528, 0.05273933]), square_terms=array([[2.32924566e-04, 6.28242993e-03], + [6.28242993e-03, 6.44662821e-01]]), scale=0.087578125, shift=array([5.36174794, 0.1758779 ])), vector_model=VectorModel(intercepts=array([ 0.04424533, 0.09706756, 0.09964179, 0.12817482, 0.14600609, + 0.16462579, 0.18727309, 0.2198423 , 0.14621231, 0.21589468, + -0.09902459, -0.11677074, -0.13794235, -0.11385871, -0.10645744, + -0.10854051, -0.10625494]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + 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1.81333427e-02], + [1.81333427e-02, 2.02348592e+00]]), scale=array([0.15522818, 0.15522818]), shift=array([5.44896581, 0.16786346])), vector_model=VectorModel(intercepts=array([ 0.04424533, 0.09706756, 0.09964179, 0.12817482, 0.14600609, + 0.16462579, 0.18727309, 0.2198423 , 0.14621231, 0.21589468, + -0.09902459, -0.11677074, -0.13794235, -0.11385871, -0.10645744, + -0.10854051, -0.10625494]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=0.700625, shift=array([7.00625, 0.19375])), candidate_index=36, candidate_x=array([5.52101795, 0.16734146]), index=35, x=array([5.44896581, 0.16786346]), fval=0.24274413357026287, rho=-6.259192132860256, accepted=False, new_indices=array([], dtype=int32), old_indices_used=array([25, 26, 29, 30, 31, 32, 33, 34, 35]), old_indices_discarded=array([14, 15, 19, 21, 22, 23, 24, 27, 28]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([5.44896581, 0.16786346]), radius=0.087578125, bounds=Bounds(lower=array([1.1 , 0.01]), upper=array([20. , 0.99]))), model_indices=array([25, 26, 30, 31, 32, 33, 34, 35, 36]), model=ScalarModel(intercept=0.24163478548943507, linear_terms=array([ 0.00016458, -0.00055621]), square_terms=array([[2.57908296e-04, 6.00198503e-03], + [6.00198503e-03, 6.44118485e-01]]), scale=0.087578125, shift=array([5.44896581, 0.16786346])), vector_model=VectorModel(intercepts=array([ 0.04424533, 0.09706756, 0.09964179, 0.12817482, 0.14600609, + 0.16462579, 0.18727309, 0.2198423 , 0.14621231, 0.21589468, + -0.09902459, -0.11677074, -0.13794235, -0.11385871, -0.10645744, + -0.10854051, -0.10625494]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=0.700625, shift=array([7.00625, 0.19375])), candidate_index=37, candidate_x=array([5.36139226, 0.16875945]), index=37, x=array([5.36139226, 0.16875945]), fval=0.24255208756330368, rho=2.7825937304103108, accepted=True, new_indices=array([], dtype=int32), old_indices_used=array([25, 26, 30, 31, 32, 33, 34, 35, 36]), old_indices_discarded=array([24, 28, 29]), step_length=0.08757812500000042, relative_step_length=1.0000000000000047, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([5.36139226, 0.16875945]), radius=0.17515625, bounds=Bounds(lower=array([1.1 , 0.01]), upper=array([20. , 0.99]))), model_indices=array([25, 26, 29, 31, 33, 34, 35, 36, 37]), model=ScalarModel(intercept=0.2417800168998051, linear_terms=array([-0.00018881, 0.00035398]), square_terms=array([[8.05230298e-04, 1.86970634e-02], + [1.86970634e-02, 2.02386702e+00]]), scale=array([0.15522818, 0.15522818]), shift=array([5.36139226, 0.16875945])), vector_model=VectorModel(intercepts=array([ 0.04424533, 0.09706756, 0.09964179, 0.12817482, 0.14600609, + 0.16462579, 0.18727309, 0.2198423 , 0.14621231, 0.21589468, + -0.09902459, -0.11677074, -0.13794235, -0.11385871, -0.10645744, + -0.10854051, -0.10625494]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=0.700625, shift=array([7.00625, 0.19375])), candidate_index=38, candidate_x=array([5.40853278, 0.1682968 ]), index=37, x=array([5.36139226, 0.16875945]), fval=0.24255208756330368, rho=-4.2991999497290685, accepted=False, new_indices=array([], dtype=int32), old_indices_used=array([25, 26, 29, 31, 33, 34, 35, 36, 37]), old_indices_discarded=array([14, 22, 23, 24, 27, 28, 30, 32]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([5.36139226, 0.16875945]), radius=0.087578125, bounds=Bounds(lower=array([1.1 , 0.01]), upper=array([20. , 0.99]))), model_indices=array([25, 26, 30, 31, 32, 34, 35, 37, 38]), model=ScalarModel(intercept=0.24170158357350824, linear_terms=array([-0.00012888, -0.00012381]), square_terms=array([[2.60518703e-04, 5.70133267e-03], + [5.70133267e-03, 6.43763482e-01]]), scale=0.087578125, shift=array([5.36139226, 0.16875945])), vector_model=VectorModel(intercepts=array([ 0.04424533, 0.09706756, 0.09964179, 0.12817482, 0.14600609, + 0.16462579, 0.18727309, 0.2198423 , 0.14621231, 0.21589468, + -0.09902459, -0.11677074, -0.13794235, -0.11385871, -0.10645744, + -0.10854051, -0.10625494]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=0.700625, shift=array([7.00625, 0.19375])), candidate_index=39, candidate_x=array([5.41467648, 0.16830439]), index=37, x=array([5.36139226, 0.16875945]), fval=0.24255208756330368, rho=-1.9714007957034316, accepted=False, new_indices=array([], dtype=int32), old_indices_used=array([25, 26, 30, 31, 32, 34, 35, 37, 38]), old_indices_discarded=array([24, 27, 28, 29, 33, 36]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([5.36139226, 0.16875945]), radius=0.0437890625, bounds=Bounds(lower=array([1.1 , 0.01]), upper=array([20. , 0.99]))), model_indices=array([26, 30, 31, 32, 34, 35, 37, 38, 39]), model=ScalarModel(intercept=0.2417553910728286, linear_terms=array([ 4.54049262e-05, -4.56249946e-05]), square_terms=array([[6.76405313e-05, 1.43316796e-03], + [1.43316796e-03, 1.60944325e-01]]), scale=0.0437890625, shift=array([5.36139226, 0.16875945])), vector_model=VectorModel(intercepts=array([ 0.04424533, 0.09706756, 0.09964179, 0.12817482, 0.14600609, + 0.16462579, 0.18727309, 0.2198423 , 0.14621231, 0.21589468, + -0.09902459, -0.11677074, -0.13794235, -0.11385871, -0.10645744, + -0.10854051, -0.10625494]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=0.700625, shift=array([7.00625, 0.19375])), candidate_index=40, candidate_x=array([5.31760507, 0.16916422]), index=40, x=array([5.31760507, 0.16916422]), fval=0.24241985946629963, rho=7.194700985609317, accepted=True, new_indices=array([], dtype=int32), old_indices_used=array([26, 30, 31, 32, 34, 35, 37, 38, 39]), old_indices_discarded=array([25, 29, 33, 36]), step_length=0.043789062500000274, relative_step_length=1.0000000000000062, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([5.31760507, 0.16916422]), radius=0.087578125, bounds=Bounds(lower=array([1.1 , 0.01]), upper=array([20. , 0.99]))), model_indices=array([25, 30, 31, 32, 34, 37, 38, 39, 40]), model=ScalarModel(intercept=0.24205486457802278, linear_terms=array([0.00023275, 0.000779 ]), square_terms=array([[3.03100394e-04, 5.73493197e-03], + [5.73493197e-03, 6.43806788e-01]]), scale=0.087578125, shift=array([5.31760507, 0.16916422])), vector_model=VectorModel(intercepts=array([ 0.04424533, 0.09706756, 0.09964179, 0.12817482, 0.14600609, + 0.16462579, 0.18727309, 0.2198423 , 0.14621231, 0.21589468, + -0.09902459, -0.11677074, -0.13794235, -0.11385871, -0.10645744, + -0.10854051, -0.10625494]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=0.700625, shift=array([7.00625, 0.19375])), candidate_index=41, candidate_x=array([5.23002957, 0.16984189]), index=40, x=array([5.31760507, 0.16916422]), fval=0.24241985946629963, rho=-6.146531737571127, accepted=False, new_indices=array([], dtype=int32), old_indices_used=array([25, 30, 31, 32, 34, 37, 38, 39, 40]), old_indices_discarded=array([24, 26, 27, 28, 29, 33, 35, 36]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([5.31760507, 0.16916422]), radius=0.0437890625, bounds=Bounds(lower=array([1.1 , 0.01]), upper=array([20. , 0.99]))), model_indices=array([25, 30, 31, 32, 34, 37, 38, 40, 41]), model=ScalarModel(intercept=0.24213302949529256, linear_terms=array([-3.78622622e-05, 2.41519221e-04]), square_terms=array([[6.90966248e-05, 1.48098964e-03], + [1.48098964e-03, 1.60965844e-01]]), scale=0.0437890625, shift=array([5.31760507, 0.16916422])), vector_model=VectorModel(intercepts=array([ 0.04424533, 0.09706756, 0.09964179, 0.12817482, 0.14600609, + 0.16462579, 0.18727309, 0.2198423 , 0.14621231, 0.21589468, + -0.09902459, -0.11677074, -0.13794235, -0.11385871, -0.10645744, + -0.10854051, -0.10625494]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=0.700625, shift=array([7.00625, 0.19375])), candidate_index=42, candidate_x=array([5.36139158, 0.16869151]), index=40, x=array([5.31760507, 0.16916422]), fval=0.24241985946629963, rho=-11.833264403894546, accepted=False, new_indices=array([], dtype=int32), old_indices_used=array([25, 30, 31, 32, 34, 37, 38, 40, 41]), old_indices_discarded=array([26, 29, 33, 35, 36, 39]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([5.31760507, 0.16916422]), radius=0.02189453125, bounds=Bounds(lower=array([1.1 , 0.01]), upper=array([20. , 0.99]))), model_indices=array([25, 30, 31, 32, 37, 38, 40, 41, 42]), model=ScalarModel(intercept=0.24265765523257948, linear_terms=array([-0.00010296, -0.00348716]), square_terms=array([[1.52341867e-05, 3.50476207e-04], + [3.50476207e-04, 4.17971723e-02]]), scale=0.02189453125, shift=array([5.31760507, 0.16916422])), vector_model=VectorModel(intercepts=array([ 0.04424533, 0.09706756, 0.09964179, 0.12817482, 0.14600609, + 0.16462579, 0.18727309, 0.2198423 , 0.14621231, 0.21589468, + -0.09902459, -0.11677074, -0.13794235, -0.11385871, -0.10645744, + -0.10854051, -0.10625494]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + 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old_indices_discarded=array([26, 29, 34, 39]), step_length=0.021964765363485655, relative_step_length=1.0032078381895322, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([5.33950848, 0.17080482]), radius=0.0437890625, bounds=Bounds(lower=array([1.1 , 0.01]), upper=array([20. , 0.99]))), model_indices=array([30, 31, 32, 37, 38, 39, 40, 42, 43]), model=ScalarModel(intercept=0.2423976703093635, linear_terms=array([-3.01430010e-05, 2.34992933e-04]), square_terms=array([[5.91513482e-05, 1.37667035e-03], + [1.37667035e-03, 1.65820314e-01]]), scale=0.0437890625, shift=array([5.33950848, 0.17080482])), vector_model=VectorModel(intercepts=array([ 0.04424533, 0.09706756, 0.09964179, 0.12817482, 0.14600609, + 0.16462579, 0.18727309, 0.2198423 , 0.14621231, 0.21589468, + -0.09902459, -0.11677074, -0.13794235, -0.11385871, -0.10645744, + -0.10854051, -0.10625494]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], 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41]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([5.33950848, 0.17080482]), radius=0.02189453125, bounds=Bounds(lower=array([1.1 , 0.01]), upper=array([20. , 0.99]))), model_indices=array([30, 32, 37, 38, 39, 40, 42, 43, 44]), model=ScalarModel(intercept=0.24235348524537714, linear_terms=array([ 5.95198861e-06, -8.48814584e-06]), square_terms=array([[1.47776329e-05, 3.48481891e-04], + [3.48481891e-04, 4.14093403e-02]]), scale=0.02189453125, shift=array([5.33950848, 0.17080482])), vector_model=VectorModel(intercepts=array([ 0.04424533, 0.09706756, 0.09964179, 0.12817482, 0.14600609, + 0.16462579, 0.18727309, 0.2198423 , 0.14621231, 0.21589468, + -0.09902459, -0.11677074, -0.13794235, -0.11385871, -0.10645744, + -0.10854051, -0.10625494]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 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n_evals_acceptance=1), State(trustregion=Region(center=array([5.33950848, 0.17080482]), radius=0.010947265625, bounds=Bounds(lower=array([1.1 , 0.01]), upper=array([20. , 0.99]))), model_indices=array([32, 37, 40, 42, 43, 44, 45]), model=ScalarModel(intercept=0.2422806237585476, linear_terms=array([ 2.67171372e-05, -2.05431480e-04]), square_terms=array([[3.68279483e-06, 8.49740419e-05], + [8.49740419e-05, 1.03070513e-02]]), scale=0.010947265625, shift=array([5.33950848, 0.17080482])), vector_model=VectorModel(intercepts=array([ 0.04424533, 0.09706756, 0.09964179, 0.12817482, 0.14600609, + 0.16462579, 0.18727309, 0.2198423 , 0.14621231, 0.21589468, + -0.09902459, -0.11677074, -0.13794235, -0.11385871, -0.10645744, + -0.10854051, -0.10625494]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=0.700625, shift=array([7.00625, 0.19375])), candidate_index=46, candidate_x=array([5.32856345, 0.17111248]), index=43, x=array([5.33950848, 0.17080482]), fval=0.24222716621340298, rho=-2.0149510031231594, accepted=False, new_indices=array([], dtype=int32), old_indices_used=array([32, 37, 40, 42, 43, 44, 45]), old_indices_discarded=array([], dtype=int32), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([5.33950848, 0.17080482]), radius=0.0054736328125, bounds=Bounds(lower=array([1.1 , 0.01]), upper=array([20. , 0.99]))), model_indices=array([32, 37, 40, 42, 43, 45, 46]), model=ScalarModel(intercept=0.24229025426011608, linear_terms=array([ 1.48827190e-05, -1.05452116e-04]), square_terms=array([[9.09604685e-07, 2.07560472e-05], + [2.07560472e-05, 2.57873989e-03]]), scale=0.0054736328125, shift=array([5.33950848, 0.17080482])), vector_model=VectorModel(intercepts=array([ 0.04424533, 0.09706756, 0.09964179, 0.12817482, 0.14600609, + 0.16462579, 0.18727309, 0.2198423 , 0.14621231, 0.21589468, + -0.09902459, -0.11677074, -0.13794235, -0.11385871, -0.10645744, + -0.10854051, -0.10625494]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 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0.99]))), model_indices=array([43, 45, 46, 47]), model=ScalarModel(intercept=0.24222624543591792, linear_terms=array([-7.33525171e-06, 2.20337847e-04]), square_terms=array([[2.41748426e-07, 5.48721051e-06], + [5.48721051e-06, 5.94912648e-04]]), scale=0.00273681640625, shift=array([5.33950848, 0.17080482])), vector_model=VectorModel(intercepts=array([ 0.04424533, 0.09706756, 0.09964179, 0.12817482, 0.14600609, + 0.16462579, 0.18727309, 0.2198423 , 0.14621231, 0.21589468, + -0.09902459, -0.11677074, -0.13794235, -0.11385871, -0.10645744, + -0.10854051, -0.10625494]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + 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linear_terms=array([-1.02551120e-05, -3.95148592e-05]), square_terms=array([[6.98218857e-08, 1.88148453e-06], + [1.88148453e-06, 1.65041401e-04]]), scale=0.001368408203125, shift=array([5.33950848, 0.17080482])), vector_model=VectorModel(intercepts=array([ 0.04424533, 0.09706756, 0.09964179, 0.12817482, 0.14600609, + 0.16462579, 0.18727309, 0.2198423 , 0.14621231, 0.21589468, + -0.09902459, -0.11677074, -0.13794235, -0.11385871, -0.10645744, + -0.10854051, -0.10625494]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + 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3.98197561e-05]]), scale=0.0006842041015625, shift=array([5.33950848, 0.17080482])), vector_model=VectorModel(intercepts=array([ 0.04424533, 0.09706756, 0.09964179, 0.12817482, 0.14600609, + 0.16462579, 0.18727309, 0.2198423 , 0.14621231, 0.21589468, + -0.09902459, -0.11677074, -0.13794235, -0.11385871, -0.10645744, + -0.10854051, -0.10625494]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + 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vector_model=VectorModel(intercepts=array([ 0.04424533, 0.09706756, 0.09964179, 0.12817482, 0.14600609, + 0.16462579, 0.18727309, 0.2198423 , 0.14621231, 0.21589468, + -0.09902459, -0.11677074, -0.13794235, -0.11385871, -0.10645744, + -0.10854051, -0.10625494]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=0.700625, 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State(trustregion=Region(center=array([5.33882353, 0.17065423]), radius=4.276275634765625e-05, bounds=Bounds(lower=array([1.1 , 0.01]), upper=array([20. , 0.99]))), model_indices=array([50, 54, 55]), model=ScalarModel(intercept=0.24222315394360722, linear_terms=array([ 8.70513659e-08, -4.37510681e-09]), square_terms=array([[8.02169837e-11, 1.60425228e-09], + [1.60425228e-09, 1.54231322e-07]]), scale=4.276275634765625e-05, shift=array([5.33882353, 0.17065423])), vector_model=VectorModel(intercepts=array([ 0.04424533, 0.09706756, 0.09964179, 0.12817482, 0.14600609, + 0.16462579, 0.18727309, 0.2198423 , 0.14621231, 0.21589468, + -0.09902459, -0.11677074, -0.13794235, -0.11385871, -0.10645744, + -0.10854051, -0.10625494]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + 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radius=0.7557071776832622, bounds=Bounds(lower=array([1.1 , 0.01]), upper=array([20. , 0.99]))), model_indices=array([ 1, 3, 7, 13, 14, 15, 16, 17, 18]), model=ScalarModel(intercept=2.8790620949739303, linear_terms=array([0.26988009, 8.74126763]), square_terms=array([[ 0.01986858, 0.45368432], + [ 0.45368432, 14.46207235]]), scale=array([0.66972805, 0.41452844]), shift=array([5.24647936, 0.42452844])), vector_model=VectorModel(intercepts=array([ 0.04372593, 0.09723622, 0.10188573, 0.13262325, 0.15154936, + 0.16923117, 0.18861608, 0.18401939, 0.09682264, 0.1552954 , + -0.16489717, -0.1798028 , -0.14271083, -0.11811719, -0.10957416, + -0.11108474, -0.1079118 ]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + 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bounds=Bounds(lower=array([1.1 , 0.01]), upper=array([20. , 0.99]))), model_indices=array([ 1, 3, 13, 14, 15, 16, 17, 18, 19]), model=ScalarModel(intercept=0.5133453029704279, linear_terms=array([0.0412064 , 1.66429691]), square_terms=array([[4.79896476e-03, 1.29982477e-01], + [1.29982477e-01, 5.02450715e+00]]), scale=array([0.33486402, 0.24709642]), shift=array([5.24647936, 0.25709642])), vector_model=VectorModel(intercepts=array([ 0.04372593, 0.09723622, 0.10188573, 0.13262325, 0.15154936, + 0.16923117, 0.18861608, 0.18401939, 0.09682264, 0.1552954 , + -0.16489717, -0.1798028 , -0.14271083, -0.11811719, -0.10957416, + -0.11108474, -0.1079118 ]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + 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0.99]))), model_indices=array([14, 15, 16, 17, 18, 19, 20]), model=ScalarModel(intercept=0.24991953890636176, linear_terms=array([-0.00132101, 0.11413806]), square_terms=array([[1.14227713e-03, 1.94139880e-02], + [1.94139880e-02, 2.74832485e+00]]), scale=array([0.16743201, 0.16338042]), shift=array([5.24647936, 0.17338042])), vector_model=VectorModel(intercepts=array([ 0.04372593, 0.09723622, 0.10188573, 0.13262325, 0.15154936, + 0.16923117, 0.18861608, 0.18401939, 0.09682264, 0.1552954 , + -0.16489717, -0.1798028 , -0.14271083, -0.11811719, -0.10957416, + -0.11108474, -0.1079118 ]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + 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model=ScalarModel(intercept=0.24280392898324044, linear_terms=array([-0.00042791, -0.02448472]), square_terms=array([[2.79194455e-04, 7.31380916e-03], + [7.31380916e-03, 7.13962361e-01]]), scale=0.09446339721040778, shift=array([5.24647936, 0.16932883])), vector_model=VectorModel(intercepts=array([ 0.04372593, 0.09723622, 0.10188573, 0.13262325, 0.15154936, + 0.16923117, 0.18861608, 0.18401939, 0.09682264, 0.1552954 , + -0.16489717, -0.1798028 , -0.14271083, -0.11811719, -0.10957416, + -0.11108474, -0.1079118 ]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + 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linear_terms=array([0.00244388, 0.06648202]), square_terms=array([[1.19336081e-03, 3.24541529e-02], + [3.24541529e-02, 2.37275707e+00]]), scale=array([0.16743201, 0.16451471]), shift=array([5.34091551, 0.17451471])), vector_model=VectorModel(intercepts=array([ 0.04372593, 0.09723622, 0.10188573, 0.13262325, 0.15154936, + 0.16923117, 0.18861608, 0.18401939, 0.09682264, 0.1552954 , + -0.16489717, -0.1798028 , -0.14271083, -0.11811719, -0.10957416, + -0.11108474, -0.1079118 ]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], 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square_terms=array([[2.79537451e-04, 7.66237713e-03], + [7.66237713e-03, 7.24390446e-01]]), scale=0.09446339721040778, shift=array([5.34091551, 0.17159741])), vector_model=VectorModel(intercepts=array([ 0.04372593, 0.09723622, 0.10188573, 0.13262325, 0.15154936, + 0.16923117, 0.18861608, 0.18401939, 0.09682264, 0.1552954 , + -0.16489717, -0.1798028 , -0.14271083, -0.11811719, -0.10957416, + -0.11108474, -0.1079118 ]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + 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1.76208417e-01]]), scale=0.04723169860520389, shift=array([5.34091551, 0.17159741])), vector_model=VectorModel(intercepts=array([ 0.04372593, 0.09723622, 0.10188573, 0.13262325, 0.15154936, + 0.16923117, 0.18861608, 0.18401939, 0.09682264, 0.1552954 , + -0.16489717, -0.1798028 , -0.14271083, -0.11811719, -0.10957416, + -0.11108474, -0.1079118 ]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=0.7557071776832622, shift=array([7.55707178, 0.15947986])), candidate_index=25, candidate_x=array([5.38814784, 0.17148398]), index=22, x=array([5.34091551, 0.17159741]), fval=0.2423262078217145, rho=-0.24046453118083538, accepted=False, new_indices=array([], dtype=int32), old_indices_used=array([14, 17, 18, 21, 22, 23, 24]), old_indices_discarded=array([], dtype=int32), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([5.34091551, 0.17159741]), radius=0.023615849302601945, bounds=Bounds(lower=array([1.1 , 0.01]), upper=array([20. , 0.99]))), model_indices=array([17, 18, 21, 22, 24, 25]), model=ScalarModel(intercept=0.24243549485529609, linear_terms=array([-4.62482233e-05, 1.22755071e-03]), square_terms=array([[1.80610011e-05, 4.38168169e-04], + [4.38168169e-04, 4.79017603e-02]]), scale=0.023615849302601945, shift=array([5.34091551, 0.17159741])), vector_model=VectorModel(intercepts=array([ 0.04372593, 0.09723622, 0.10188573, 0.13262325, 0.15154936, + 0.16923117, 0.18861608, 0.18401939, 0.09682264, 0.1552954 , + -0.16489717, -0.1798028 , -0.14271083, -0.11811719, -0.10957416, + -0.11108474, -0.1079118 ]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=0.7557071776832622, shift=array([7.55707178, 0.15947986])), candidate_index=26, candidate_x=array([5.36452368, 0.17077702]), index=26, x=array([5.36452368, 0.17077702]), fval=0.24232590102301266, rho=0.004636863515290328, accepted=True, new_indices=array([], dtype=int32), old_indices_used=array([17, 18, 21, 22, 24, 25]), old_indices_discarded=array([], dtype=int32), step_length=0.023622419090119764, relative_step_length=1.0002781939973293, n_evals_per_point=1, n_evals_acceptance=1)], 'message': 'Absolute criterion change smaller than tolerance.', 'tranquilo_history': History for least_squares function with 27 entries., 'history': {'params': [{'CRRA': 7.557071776832622, 'WealthShare': 0.15947986291737937}, {'CRRA': 6.887343728211803, 'WealthShare': 0.013137857270913678}, {'CRRA': 8.22679982545344, 'WealthShare': 0.33278788031954126}, {'CRRA': 6.887343728211803, 'WealthShare': 0.4927195085070417}, {'CRRA': 8.22679982545344, 'WealthShare': 0.8233666446704474}, {'CRRA': 7.6877492399818115, 'WealthShare': 0.01}, {'CRRA': 8.22679982545344, 'WealthShare': 0.014431776924461504}, {'CRRA': 6.887343728211803, 'WealthShare': 0.5044867019135671}, {'CRRA': 8.22679982545344, 'WealthShare': 0.6439347881014327}, {'CRRA': 8.22679982545344, 'WealthShare': 0.8286676871687395}, {'CRRA': 6.888144129782968, 'WealthShare': 0.829207911538198}, {'CRRA': 7.292700445703663, 'WealthShare': 0.01}, {'CRRA': 7.3755390376972425, 'WealthShare': 0.829207911538198}, {'CRRA': 6.887343728211803, 'WealthShare': 0.13052177573508408}, {'CRRA': 5.547887630970166, 'WealthShare': 0.13840761057808626}, {'CRRA': 4.770403559848555, 'WealthShare': 0.12211118058865711}, {'CRRA': 4.355881206682243, 'WealthShare': 0.19138224232966042}, {'CRRA': 5.413982512136979, 'WealthShare': 0.16362415189967155}, {'CRRA': 5.246479361728566, 'WealthShare': 0.16932882505745808}, {'CRRA': 5.762063127158538, 'WealthShare': 0.1639652195341865}, {'CRRA': 5.581343386038975, 'WealthShare': 0.16885692016159012}, {'CRRA': 5.292164748029701, 'WealthShare': 0.16625553267531312}, {'CRRA': 5.340915514376363, 'WealthShare': 0.17159741175699056}, {'CRRA': 5.199939503168527, 'WealthShare': 0.1717711380449}, {'CRRA': 5.243544072816682, 'WealthShare': 0.17223972982564176}, {'CRRA': 5.388147840073009, 'WealthShare': 0.17148397634254275}, {'CRRA': 5.364523683205526, 'WealthShare': 0.17077701660648517}], 'criterion': [0.3237027602159698, 0.7812967907209172, 1.2463667430775796, 5.3731601742222, 83.85576746268217, 0.6845161962193543, 0.6204394025802298, 5.923680424712876, 14.623295430433139, 89.28677844528951, 112.97532984686313, 0.7343607833893859, 103.50996033506941, 0.2998665188430385, 0.281460321662095, 0.37742949555588207, 0.2981488331322679, 0.24430617695746668, 0.24296186338597675, 0.24637026776611792, 0.24311726730149846, 0.24366070482725372, 0.24232620782171452, 0.24322374032290844, 0.2429668792738361, 0.24236046007028705, 0.24232590102301269], 'runtime': [0.0, 1.0775652001611888, 1.1048381002619863, 1.1430752002634108, 1.181620600167662, 1.2234753998927772, 1.2626859000883996, 1.3012720001861453, 1.3398684998974204, 1.3782349000684917, 1.4174270001240075, 1.4558502002619207, 1.4946371000260115, 2.5929303001612425, 3.6385490000247955, 4.827053700108081, 5.851515099871904, 6.857261700090021, 7.868444700259715, 8.889939799904823, 9.900565400253981, 10.905832400079817, 11.924034600146115, 12.952283100225031, 13.976015199907124, 14.989212099928409, 16.00469780014828], 'batches': [0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15]}}], 'exploration_sample': array([[ 7.00625 , 0.19375 ], + [12.9125 , 0.1325 ], + [ 4.64375 , 0.31625 ], + [ 8.1875 , 0.3775 ], + [ 4.8444368 , 0.34601283], + [15.275 , 0.255 ], + [17.046875 , 0.224375 ], + [11.73125 , 0.43875 ], + [18.81875 , 0.07125 ], + [10.55 , 0.5 ], + [ 9.36875 , 0.56125 ], + [16.45625 , 0.68375 ], + [ 2.871875 , 0.469375 ], + [ 7.596875 , 0.714375 ], + [14.09375 , 0.80625 ], + [ 3.4625 , 0.6225 ], + [17.6375 , 0.8675 ], + [ 5.825 , 0.745 ], + [12.321875 , 0.959375 ], + [ 2.28125 , 0.92875 ]]), 'exploration_results': array([3.27384376e-01, 1.14034055e+00, 1.50312179e+00, 1.79325436e+00, + 2.03621762e+00, 2.08879824e+00, 2.54067782e+00, 2.64114350e+00, + 2.73814230e+00, 3.83228381e+00, 6.46248546e+00, 9.30118040e+00, + 1.59966394e+01, 3.03715662e+01, 3.38771067e+01, 4.26926083e+01, + 5.84656546e+01, 5.90505617e+01, 5.22500282e+02, 9.01924413e+02])}}" diff --git a/code/estimark/estimation.py b/code/estimark/estimation.py index 31730ad..47be7b6 100644 --- a/code/estimark/estimation.py +++ b/code/estimark/estimation.py @@ -247,8 +247,6 @@ def simulate_moments(params, agent=None, emp_moments=None): agent.PermShkStd = init_subjective_labor["PermShkStd"] agent.update_income_process() - agent.LivPrb = init_calibration["LivPrb"] - agent.update() # Solve the model for these parameters, then simulate wealth data @@ -266,8 +264,6 @@ def simulate_moments(params, agent=None, emp_moments=None): agent.PermShkStd = init_subjective_labor["PermShkStd"] agent.update_income_process() - agent.LivPrb = [1.0] * agent.T_cycle - agent.update() max_sim_age = agent.T_cycle + 1 @@ -883,8 +879,8 @@ def estimate( if __name__ == "__main__": # Set booleans to determine which tasks should be done # Which agent type to estimate ("IndShock" or "Portfolio") - local_agent_name = "WarmGlowPortfolio" - local_params_to_estimate = ["CRRA", "BeqFac", "BeqShift"] + local_agent_name = "WealthPortfolio" + local_params_to_estimate = ["CRRA", "WealthShare","WealthShift"] local_estimate_model = True # Whether to estimate the model # Whether to get standard errors via bootstrap local_compute_se_bootstrap = False diff --git a/code/estimark/parameters.py b/code/estimark/parameters.py index ccf946b..7527eea 100644 --- a/code/estimark/parameters.py +++ b/code/estimark/parameters.py @@ -12,10 +12,12 @@ import numpy as np from HARK.Calibration.Income.IncomeTools import Cagetti_income, parse_income_spec -from HARK.ConsumptionSaving.ConsIndShockModel import init_lifecycle from HARK.Calibration.life_tables.us_ssa.SSATools import parse_ssa_life_table from HARK.distribution import DiscreteDistribution -from HARK.ConsumptionSaving.ConsPortfolioModel import portfolio_constructor_dict +from HARK.ConsumptionSaving.ConsPortfolioModel import ( + PortfolioConsumerType_constructors_default, +) +from HARK.ConsumptionSaving.ConsWealthPortfolioModel import make_ChiFromOmega_function # --------------------------------------------------------------------------------- # - Define all of the model parameters for EstimatingMicroDSOPs and ConsumerExamples - @@ -69,23 +71,23 @@ # Initial guess of the coefficient of relative risk aversion during estimation (rho) init_CRRA = 2.0 # Bounds for rho; if violated, objective function returns "penalty value" -bounds_CRRA = [2.0, 20.0] +bounds_CRRA = [1.1, 20.0] # Initial guess of the adjustment to the discount factor during estimation (beth) init_DiscFac = 1.0 # Bounds for beth; if violated, objective function returns "penalty value" bounds_DiscFac = [0.5, 1.1] -init_WealthShare = 0.3 # Initial guess of the wealth share parameter -bounds_WealthShare = [0.0, 0.7] # Bounds for the wealth share parameter +init_WealthShare = 0.05 # Initial guess of the wealth share parameter +bounds_WealthShare = [0.01, 0.99] # Bounds for the wealth share parameter init_WealthShift = 0.0 # Initial guess of the wealth shift parameter bounds_WealthShift = [0.0, 100.0] # Bounds for the wealth shift parameter init_BeqFac = 1.0 # Initial guess of the bequest factor -bounds_BeqFac = [0.0, 70.0] # Bounds for the bequest factor +bounds_BeqFac = [0.0, 100.0] # Bounds for the bequest factor -init_BeqShift = 1.0 # Initial guess of the bequest shift parameter +init_BeqShift = 0.0 # Initial guess of the bequest shift parameter bounds_BeqShift = [0.0, 70.0] # Bounds for the bequest shift parameter ###################################################################### @@ -202,7 +204,6 @@ # Dictionary that can be passed to ConsumerType to instantiate init_calibration = { - **init_lifecycle, "CRRA": init_CRRA, "DiscFac": init_DiscFac, "Rfree": Rfree, @@ -236,10 +237,10 @@ "neutral_measure": True, # Harmemberg "sim_common_Rrisky": False, # idiosyncratic risky return "WealthShift": init_WealthShift, + "ChiFromOmega_N": 501, # Number of gridpoints in chi-from-omega function + "ChiFromOmega_bound": 15, # Highest gridpoint to use for it } -init_calibration["constructors"] = portfolio_constructor_dict - Eq_prem = 0.03 RiskyStd = 0.20 diff --git a/content/tables/TRP/Portfolio_estimate_results.csv b/content/tables/TRP/Portfolio_estimate_results.csv index 23bc33b..dbb6cf4 100644 --- a/content/tables/TRP/Portfolio_estimate_results.csv +++ b/content/tables/TRP/Portfolio_estimate_results.csv @@ -1,37 +1,37 @@ -CRRA,8.716345008762879 -time_to_estimate,68.365642786026 -params,{'CRRA': 8.716345008762879} -criterion,0.5809829309750734 -start_criterion,0.5848636211662066 -start_params,{'CRRA': 8.716348333785895} +CRRA,9.252342476844415 +time_to_estimate,59.81896948814392 +params,{'CRRA': 9.252342476844415} +criterion,0.6423583236273489 +start_criterion,0.6339645453827032 +start_params,{'CRRA': 9.252398949005967} algorithm,multistart_tranquilo_ls direction,minimize n_free,1 -message,Relative gradient norm smaller than tolerance. +message,Absolute criterion change smaller than tolerance. success, n_criterion_evaluations, n_derivative_evaluations, n_iterations, -history,"{'params': [{'CRRA': 8.716348333785895}, {'CRRA': 7.844713500407305}, {'CRRA': 9.587983167164484}, {'CRRA': 7.844713500407305}, {'CRRA': 7.844713500407305}, {'CRRA': 9.587983167164484}, {'CRRA': 7.844713500407305}, {'CRRA': 7.844713500407305}, {'CRRA': 9.587983167164484}, {'CRRA': 7.844713500407305}, {'CRRA': 9.587983167164484}, {'CRRA': 7.844713500407305}, {'CRRA': 9.587983167164484}, {'CRRA': 7.844713500407305}, {'CRRA': 8.73971363306202}, {'CRRA': 8.2805309170966}, {'CRRA': 8.722786945774285}, {'CRRA': 8.934257042130543}, {'CRRA': 8.680629898921989}, {'CRRA': 8.704919617664325}, {'CRRA': 8.722256879041424}, {'CRRA': 8.713060012226341}, {'CRRA': 8.702729039514354}, {'CRRA': 8.723157980921664}, {'CRRA': 8.71975315735378}, {'CRRA': 8.718050745569837}, {'CRRA': 8.717199539677866}, {'CRRA': 8.715922730839909}, {'CRRA': 8.716135532312903}, {'CRRA': 8.716454734522392}, {'CRRA': 8.716401534154143}, {'CRRA': 8.71632173360177}, {'CRRA': 8.716335033693833}, {'CRRA': 8.716354983831925}, {'CRRA': 8.716345008762879}], 'criterion': [0.5809829529263784, 0.6215225605118492, 0.616398761646436, 0.6215225605118492, 0.6215225605118492, 0.616398761646436, 0.6215225605118492, 0.6215225605118492, 0.616398761646436, 0.6215225605118492, 0.616398761646436, 0.6215225605118492, 0.616398761646436, 0.6215225605118492, 0.5812368523248607, 0.5910589793661437, 0.581000020955638, 0.5834925076553559, 0.5811816170500297, 0.5810735507484359, 0.5809932748829817, 0.5810277694582143, 0.5810794571175792, 0.5810061927319683, 0.5810024456983157, 0.5810062954215335, 0.5809992243680815, 0.5809911717283618, 0.5809868267358838, 0.5809837207174353, 0.5809833042991954, 0.580983183361962, 0.580982966533811, 0.580982996832338, 0.5809829309750735], 'runtime': [0.0, 3.8568142960029945, 4.11743933300022, 4.373802340000111, 4.6027023880014895, 4.945095448001666, 5.257756480001262, 5.505722768000851, 5.731880481002008, 6.070771706003143, 6.2871199030014395, 6.552499433000776, 6.807547802000045, 18.16403710099985, 19.635794812002132, 21.11454787200273, 22.568926558000385, 24.026774695001222, 25.597418042001664, 27.083524646001024, 28.611894326000765, 30.128650472001027, 31.639469095000095, 33.12961519900273, 34.73270601100012, 36.20504977500241, 37.66801647700049, 39.144029448001675, 40.61999973700222, 42.19290338600331, 43.67094396900211, 45.17842763700173, 46.709763128001214, 48.223182736001036, 49.70291212600205], 'batches': [0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23]}" +history,"{'params': [{'CRRA': 9.252398949005968}, {'CRRA': 8.32715905410537}, {'CRRA': 10.177638843906566}, {'CRRA': 8.32715905410537}, {'CRRA': 8.32715905410537}, {'CRRA': 10.177638843906566}, {'CRRA': 8.32715905410537}, {'CRRA': 8.32715905410537}, {'CRRA': 10.177638843906566}, {'CRRA': 8.32715905410537}, {'CRRA': 10.177638843906566}, {'CRRA': 8.32715905410537}, {'CRRA': 10.177638843906566}, {'CRRA': 8.32715905410537}, {'CRRA': 9.250471173613674}, {'CRRA': 8.78977900155567}, {'CRRA': 9.23120907149584}, {'CRRA': 9.238513428928496}, {'CRRA': 9.191477678194621}, {'CRRA': 9.310226442437255}, {'CRRA': 9.25067493918715}, {'CRRA': 9.250726122006544}, {'CRRA': 9.249064681404075}, {'CRRA': 9.253920740493475}, {'CRRA': 9.256013167345424}, {'CRRA': 9.254206058175695}, {'CRRA': 9.251495394421104}, {'CRRA': 9.251947171713537}, {'CRRA': 9.252624837652185}, {'CRRA': 9.252511893329077}, {'CRRA': 9.252342476844415}], 'criterion': [0.6423583869781233, 0.6726932800669494, 0.6724707147424193, 0.6726932800669494, 0.6726932800669494, 0.6724707147424193, 0.6726932800669494, 0.6726932800669494, 0.6724707147424193, 0.6726932800669494, 0.6724707147424193, 0.6726932800669494, 0.6724707147424193, 0.6726932800669494, 0.6423691326265972, 0.6492941434834837, 0.6423764030742694, 0.6423752558032019, 0.6425217924878079, 0.6425146733526689, 0.6423685181986346, 0.6423683643642798, 0.6423801867774521, 0.6423693080646328, 0.6423866017619942, 0.6423727772903676, 0.6423636962874574, 0.6423598024158105, 0.6423594854558661, 0.6423587872768556, 0.6423583236273489], 'runtime': [0.0, 3.3926007600093726, 3.6385346090246458, 3.8182367410045117, 4.073105274001136, 4.283541666023666, 4.494341033016099, 4.736494988028426, 4.96336116202292, 5.179848953004694, 5.533184596017236, 5.69610069601913, 5.942016065004282, 21.336237280018395, 22.686877734027803, 24.069558680028422, 25.560004253027728, 26.859713567013387, 28.15134494501399, 29.419637827028055, 30.714213685016148, 32.14109974101302, 33.454856365016894, 34.775876878004055, 36.0627207980142, 37.38446952102822, 38.785011164000025, 40.11220667202724, 41.4234611930151, 42.74076091501047, 44.06118227602565], 'batches': [0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19]}" convergence_report, -multistart_info,"{'start_parameters': [{'CRRA': 8.716348333785895}], 'local_optima': [Minimize with 1 free parameters terminated. +multistart_info,"{'start_parameters': [{'CRRA': 9.252398949005968}], 'local_optima': [Minimize with 1 free parameters terminated. -The tranquilo_ls algorithm reported: Relative gradient norm smaller than tolerance. +The tranquilo_ls algorithm reported: Absolute criterion change smaller than tolerance. Independent of the convergence criteria used by tranquilo_ls, the strength of convergence can be assessed by the following criteria: one_step five_steps -relative_criterion_change 3.778e-08* 3.778e-08* -relative_params_change 3.815e-07* 3.815e-07* -absolute_criterion_change 2.195e-08* 2.195e-08* -absolute_params_change 3.325e-06* 3.325e-06* +relative_criterion_change 9.862e-08* 9.862e-08* +relative_params_change 6.104e-06* 6.104e-06* +absolute_criterion_change 6.335e-08* 6.335e-08* +absolute_params_change 5.647e-05 5.647e-05 -(***: change <= 1e-10, **: change <= 1e-8, *: change <= 1e-5. Change refers to a change between accepted steps. The first column only considers the last step. The second column considers the last five steps.)], 'exploration_sample': [{'CRRA': 8.716348333785895}, {'CRRA': 8.75}, {'CRRA': 11.0}, {'CRRA': 6.5}, {'CRRA': 13.25}, {'CRRA': 5.375}, {'CRRA': 14.375}, {'CRRA': 15.5}, {'CRRA': 4.25}, {'CRRA': 17.75}], 'exploration_results': array([0.58098295, 0.58135073, 0.79603543, 0.87638025, 1.31383932, - 1.34510497, 1.64731945, 2.01799056, 2.20855304, 2.8319413 ])}" -algorithm_output,"{'states': [State(trustregion=Region(center=array([8.71634833]), radius=0.8716348333785895, bounds=Bounds(lower=array([2.]), upper=array([20.]))), model_indices=[0], model=ScalarModel(intercept=0.5809829529263784, linear_terms=array([0.]), square_terms=array([[0.]]), scale=0.8716348333785895, shift=array([8.71634833])), vector_model=VectorModel(intercepts=array([ 0.05724941, 0.13067239, 0.15239639, 0.19379346, 0.21974974, - 0.23556449, 0.2356215 , 0.0872458 , -0.05175871, -0.04146828, - -0.38600975, -0.40563272, -0.07724253, -0.05219307, -0.04259932, - -0.04528749, -0.04943203]), linear_terms=array([[0.], +(***: change <= 1e-10, **: change <= 1e-8, *: change <= 1e-5. Change refers to a change between accepted steps. The first column only considers the last step. The second column considers the last five steps.)], 'exploration_sample': [{'CRRA': 9.252398949005967}, {'CRRA': 8.1875}, {'CRRA': 10.549999999999999}, {'CRRA': 12.9125}, {'CRRA': 5.824999999999999}, {'CRRA': 14.093749999999998}, {'CRRA': 15.274999999999999}, {'CRRA': 4.64375}, {'CRRA': 17.6375}, {'CRRA': 3.4625}], 'exploration_results': array([0.64235839, 0.6831279 , 0.69939713, 1.02360977, 1.18227674, + 1.26376333, 1.54278366, 1.78141341, 2.1808234 , 2.89794431])}" +algorithm_output,"{'states': [State(trustregion=Region(center=array([9.25239895]), radius=0.9252398949005969, bounds=Bounds(lower=array([1.1]), upper=array([20.]))), model_indices=[0], model=ScalarModel(intercept=0.6423583869781233, linear_terms=array([0.]), square_terms=array([[0.]]), scale=0.9252398949005969, shift=array([9.25239895])), vector_model=VectorModel(intercepts=array([ 0.04871317, 0.12404612, 0.14884861, 0.1938165 , 0.21740855, + 0.23242116, 0.2333601 , 0.06702318, -0.0801855 , -0.06712552, + -0.40905258, -0.41755015, -0.12516662, -0.098803 , -0.08942985, + -0.09321084, -0.09959793]), linear_terms=array([[0.], [0.], [0.], [0.], @@ -79,10 +79,10 @@ algorithm_output,"{'states': [State(trustregion=Region(center=array([8.71634833] [[0.]], - [[0.]]]), scale=0.8716348333785895, shift=array([8.71634833])), candidate_index=0, candidate_x=array([8.71634833]), index=0, x=array([8.71634833]), fval=0.5809829529263782, rho=nan, accepted=True, new_indices=[0], old_indices_used=[], old_indices_discarded=[], step_length=None, relative_step_length=None, n_evals_per_point=None, n_evals_acceptance=None), State(trustregion=Region(center=array([8.71634833]), radius=0.8716348333785895, bounds=Bounds(lower=array([2.]), upper=array([20.]))), model_indices=array([ 0, 1, 2, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13]), model=ScalarModel(intercept=0.577061750786993, linear_terms=array([-0.00226603]), square_terms=array([[0.08453366]]), scale=0.8716348333785895, shift=array([8.71634833])), vector_model=VectorModel(intercepts=array([ 0.05724941, 0.13067239, 0.15239639, 0.19379346, 0.21974974, - 0.23556449, 0.2356215 , 0.0872458 , -0.05175871, -0.04146828, - -0.38600975, -0.40563272, -0.07724253, -0.05219307, -0.04259932, - -0.04528749, -0.04943203]), linear_terms=array([[0.], + [[0.]]]), scale=0.9252398949005969, shift=array([9.25239895])), candidate_index=0, candidate_x=array([9.25239895]), index=0, x=array([9.25239895]), fval=0.6423583869781233, rho=nan, accepted=True, new_indices=[0], old_indices_used=[], old_indices_discarded=[], step_length=None, relative_step_length=None, n_evals_per_point=None, n_evals_acceptance=None), State(trustregion=Region(center=array([9.25239895]), radius=0.9252398949005969, bounds=Bounds(lower=array([1.1]), upper=array([20.]))), model_indices=array([ 0, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13]), model=ScalarModel(intercept=0.6366130167243159, linear_terms=array([0.00015204]), square_terms=array([[0.07297192]]), scale=0.9252398949005969, shift=array([9.25239895])), vector_model=VectorModel(intercepts=array([ 0.04871317, 0.12404612, 0.14884861, 0.1938165 , 0.21740855, + 0.23242116, 0.2333601 , 0.06702318, -0.0801855 , -0.06712552, + -0.40905258, -0.41755015, -0.12516662, -0.098803 , -0.08942985, + -0.09321084, -0.09959793]), linear_terms=array([[0.], [0.], [0.], [0.], @@ -130,10 +130,10 @@ algorithm_output,"{'states': [State(trustregion=Region(center=array([8.71634833] [[0.]], - [[0.]]]), scale=0.8716348333785895, shift=array([8.71634833])), candidate_index=14, candidate_x=array([8.73971363]), index=0, x=array([8.71634833]), fval=0.5809829529263782, rho=-8.359656805672962, accepted=False, new_indices=array([ 1, 2, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13]), old_indices_used=array([0]), old_indices_discarded=array([], dtype=int64), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([8.71634833]), radius=0.43581741668929475, bounds=Bounds(lower=array([2.]), upper=array([20.]))), model_indices=array([ 0, 11, 12, 13, 14, 15]), model=ScalarModel(intercept=0.5788831585760169, linear_terms=array([-0.00031441]), square_terms=array([[0.02128156]]), scale=0.43581741668929475, shift=array([8.71634833])), vector_model=VectorModel(intercepts=array([ 0.05724941, 0.13067239, 0.15239639, 0.19379346, 0.21974974, - 0.23556449, 0.2356215 , 0.0872458 , -0.05175871, -0.04146828, - -0.38600975, -0.40563272, -0.07724253, -0.05219307, -0.04259932, - -0.04528749, -0.04943203]), linear_terms=array([[0.], + [[0.]]]), scale=0.9252398949005969, shift=array([9.25239895])), candidate_index=14, candidate_x=array([9.25047117]), index=0, x=array([9.25239895]), fval=0.6423583869781233, rho=-67.84262787184853, accepted=False, new_indices=array([ 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13]), old_indices_used=array([0]), old_indices_discarded=array([], dtype=int64), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([9.25239895]), radius=0.46261994745029844, bounds=Bounds(lower=array([1.1]), upper=array([20.]))), model_indices=array([ 0, 11, 12, 13, 14, 15]), model=ScalarModel(intercept=0.6391740801217988, linear_terms=array([0.00084041]), square_terms=array([[0.01834804]]), scale=0.46261994745029844, shift=array([9.25239895])), vector_model=VectorModel(intercepts=array([ 0.04871317, 0.12404612, 0.14884861, 0.1938165 , 0.21740855, + 0.23242116, 0.2333601 , 0.06702318, -0.0801855 , -0.06712552, + -0.40905258, -0.41755015, -0.12516662, -0.098803 , -0.08942985, + -0.09321084, -0.09959793]), linear_terms=array([[0.], [0.], [0.], [0.], @@ -181,10 +181,10 @@ algorithm_output,"{'states': [State(trustregion=Region(center=array([8.71634833] [[0.]], - [[0.]]]), scale=0.8716348333785895, shift=array([8.71634833])), candidate_index=16, candidate_x=array([8.72278695]), index=0, x=array([8.71634833]), fval=0.5809829529263782, rho=-7.349105297615672, accepted=False, new_indices=array([15]), old_indices_used=array([ 0, 11, 12, 13, 14]), old_indices_discarded=array([ 1, 2, 3, 4, 5, 6, 7, 8, 9, 10]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([8.71634833]), radius=0.21790870834464737, bounds=Bounds(lower=array([2.]), upper=array([20.]))), model_indices=array([ 0, 13, 14, 15, 16, 17]), model=ScalarModel(intercept=0.5808510433773434, linear_terms=array([0.00091457]), square_terms=array([[0.00557954]]), scale=0.21790870834464737, shift=array([8.71634833])), vector_model=VectorModel(intercepts=array([ 0.05724941, 0.13067239, 0.15239639, 0.19379346, 0.21974974, - 0.23556449, 0.2356215 , 0.0872458 , -0.05175871, -0.04146828, - -0.38600975, -0.40563272, -0.07724253, -0.05219307, -0.04259932, - -0.04528749, -0.04943203]), linear_terms=array([[0.], + [[0.]]]), scale=0.9252398949005969, shift=array([9.25239895])), candidate_index=16, candidate_x=array([9.23120907]), index=0, x=array([9.25239895]), fval=0.6423583869781233, rho=-0.9360366242557278, accepted=False, new_indices=array([15]), old_indices_used=array([ 0, 11, 12, 13, 14]), old_indices_discarded=array([ 1, 2, 3, 4, 5, 6, 7, 8, 9, 10]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([9.25239895]), radius=0.23130997372514922, bounds=Bounds(lower=array([1.1]), upper=array([20.]))), model_indices=array([ 0, 12, 13, 14, 15, 16]), model=ScalarModel(intercept=0.640036605619869, linear_terms=array([0.00027282]), square_terms=array([[0.0045447]]), scale=0.23130997372514922, shift=array([9.25239895])), vector_model=VectorModel(intercepts=array([ 0.04871317, 0.12404612, 0.14884861, 0.1938165 , 0.21740855, + 0.23242116, 0.2333601 , 0.06702318, -0.0801855 , -0.06712552, + -0.40905258, -0.41755015, -0.12516662, -0.098803 , -0.08942985, + -0.09321084, -0.09959793]), linear_terms=array([[0.], [0.], [0.], [0.], @@ -232,10 +232,10 @@ algorithm_output,"{'states': [State(trustregion=Region(center=array([8.71634833] [[0.]], - [[0.]]]), scale=0.8716348333785895, shift=array([8.71634833])), candidate_index=18, candidate_x=array([8.6806299]), index=0, x=array([8.71634833]), fval=0.5809829529263782, rho=-2.650424420149406, accepted=False, new_indices=array([17]), old_indices_used=array([ 0, 13, 14, 15, 16]), old_indices_discarded=array([ 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([8.71634833]), radius=0.10895435417232369, bounds=Bounds(lower=array([2.]), upper=array([20.]))), model_indices=array([ 0, 14, 15, 16, 17, 18]), model=ScalarModel(intercept=0.5809473819558783, linear_terms=array([0.00014108]), square_terms=array([[0.00134501]]), scale=0.10895435417232369, shift=array([8.71634833])), vector_model=VectorModel(intercepts=array([ 0.05724941, 0.13067239, 0.15239639, 0.19379346, 0.21974974, - 0.23556449, 0.2356215 , 0.0872458 , -0.05175871, -0.04146828, - -0.38600975, -0.40563272, -0.07724253, -0.05219307, -0.04259932, - -0.04528749, -0.04943203]), linear_terms=array([[0.], + [[0.]]]), scale=0.9252398949005969, shift=array([9.25239895])), candidate_index=17, candidate_x=array([9.23851343]), index=0, x=array([9.25239895]), fval=0.6423583869781233, rho=-2.0600316699171524, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([ 0, 12, 13, 14, 15, 16]), old_indices_discarded=array([ 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([9.25239895]), radius=0.11565498686257461, bounds=Bounds(lower=array([1.1]), upper=array([20.]))), model_indices=array([ 0, 14, 15, 16, 17]), model=ScalarModel(intercept=0.6424111679010795, linear_terms=array([0.00061553]), square_terms=array([[0.00116854]]), scale=0.11565498686257461, shift=array([9.25239895])), vector_model=VectorModel(intercepts=array([ 0.04871317, 0.12404612, 0.14884861, 0.1938165 , 0.21740855, + 0.23242116, 0.2333601 , 0.06702318, -0.0801855 , -0.06712552, + -0.40905258, -0.41755015, -0.12516662, -0.098803 , -0.08942985, + -0.09321084, -0.09959793]), linear_terms=array([[0.], [0.], [0.], [0.], @@ -283,10 +283,10 @@ algorithm_output,"{'states': [State(trustregion=Region(center=array([8.71634833] [[0.]], - [[0.]]]), scale=0.8716348333785895, shift=array([8.71634833])), candidate_index=19, candidate_x=array([8.70491962]), index=0, x=array([8.71634833]), fval=0.5809829529263782, rho=-12.24378157908205, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([ 0, 14, 15, 16, 17, 18]), old_indices_discarded=array([], dtype=int64), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([8.71634833]), radius=0.05447717708616184, bounds=Bounds(lower=array([2.]), upper=array([20.]))), model_indices=array([ 0, 14, 16, 17, 18, 19]), model=ScalarModel(intercept=0.5810689282474453, linear_terms=array([-3.48991295e-05]), square_terms=array([[0.00032177]]), scale=0.05447717708616184, shift=array([8.71634833])), vector_model=VectorModel(intercepts=array([ 0.05724941, 0.13067239, 0.15239639, 0.19379346, 0.21974974, - 0.23556449, 0.2356215 , 0.0872458 , -0.05175871, -0.04146828, - -0.38600975, -0.40563272, -0.07724253, -0.05219307, -0.04259932, - -0.04528749, -0.04943203]), linear_terms=array([[0.], + [[0.]]]), scale=0.9252398949005969, shift=array([9.25239895])), candidate_index=18, candidate_x=array([9.19147768]), index=0, x=array([9.25239895]), fval=0.6423583869781233, rho=-1.0079617617718157, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([ 0, 14, 15, 16, 17]), old_indices_discarded=array([], dtype=int64), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([9.25239895]), radius=0.057827493431287305, bounds=Bounds(lower=array([1.1]), upper=array([20.]))), model_indices=array([ 0, 14, 16, 17, 19]), model=ScalarModel(intercept=0.6423642263710555, linear_terms=array([8.47856679e-06]), square_terms=array([[0.00028439]]), scale=0.057827493431287305, shift=array([9.25239895])), vector_model=VectorModel(intercepts=array([ 0.04871317, 0.12404612, 0.14884861, 0.1938165 , 0.21740855, + 0.23242116, 0.2333601 , 0.06702318, -0.0801855 , -0.06712552, + -0.40905258, -0.41755015, -0.12516662, -0.098803 , -0.08942985, + -0.09321084, -0.09959793]), linear_terms=array([[0.], [0.], [0.], [0.], @@ -334,10 +334,10 @@ algorithm_output,"{'states': [State(trustregion=Region(center=array([8.71634833] [[0.]], - [[0.]]]), scale=0.8716348333785895, shift=array([8.71634833])), candidate_index=20, candidate_x=array([8.72225688]), index=0, x=array([8.71634833]), fval=0.5809829529263782, rho=-5.453953845413641, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([ 0, 14, 16, 17, 18, 19]), old_indices_discarded=array([], dtype=int64), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([8.71634833]), radius=0.02723858854308092, bounds=Bounds(lower=array([2.]), upper=array([20.]))), model_indices=array([ 0, 14, 16, 18, 19, 20]), model=ScalarModel(intercept=0.5810604563262121, linear_terms=array([9.66932908e-06]), square_terms=array([[8.00952314e-05]]), scale=0.02723858854308092, shift=array([8.71634833])), vector_model=VectorModel(intercepts=array([ 0.05724941, 0.13067239, 0.15239639, 0.19379346, 0.21974974, - 0.23556449, 0.2356215 , 0.0872458 , -0.05175871, -0.04146828, - -0.38600975, -0.40563272, -0.07724253, -0.05219307, -0.04259932, - -0.04528749, -0.04943203]), linear_terms=array([[0.], + [[0.]]]), scale=0.9252398949005969, shift=array([9.25239895])), candidate_index=20, candidate_x=array([9.25067494]), index=0, x=array([9.25239895]), fval=0.6423583869781233, rho=-80.16115218067975, accepted=False, new_indices=array([19]), old_indices_used=array([ 0, 14, 16, 17]), old_indices_discarded=array([18]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([9.25239895]), radius=0.028913746715643653, bounds=Bounds(lower=array([1.1]), upper=array([20.]))), model_indices=array([ 0, 14, 16, 17, 19, 20]), model=ScalarModel(intercept=0.6423649815517477, linear_terms=array([4.11261778e-06]), square_terms=array([[7.10839727e-05]]), scale=0.028913746715643653, shift=array([9.25239895])), vector_model=VectorModel(intercepts=array([ 0.04871317, 0.12404612, 0.14884861, 0.1938165 , 0.21740855, + 0.23242116, 0.2333601 , 0.06702318, -0.0801855 , -0.06712552, + -0.40905258, -0.41755015, -0.12516662, -0.098803 , -0.08942985, + -0.09321084, -0.09959793]), linear_terms=array([[0.], [0.], [0.], [0.], @@ -385,10 +385,10 @@ algorithm_output,"{'states': [State(trustregion=Region(center=array([8.71634833] [[0.]], - [[0.]]]), scale=0.8716348333785895, shift=array([8.71634833])), candidate_index=21, candidate_x=array([8.71306001]), index=0, x=array([8.71634833]), fval=0.5809829529263782, rho=-76.78603089822361, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([ 0, 14, 16, 18, 19, 20]), old_indices_discarded=array([], dtype=int64), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([8.71634833]), radius=0.01361929427154046, bounds=Bounds(lower=array([2.]), upper=array([20.]))), model_indices=array([ 0, 14, 16, 19, 20, 21]), model=ScalarModel(intercept=0.5810304488299523, linear_terms=array([5.90878084e-05]), square_terms=array([[1.97212099e-05]]), scale=0.01361929427154046, shift=array([8.71634833])), vector_model=VectorModel(intercepts=array([ 0.05724941, 0.13067239, 0.15239639, 0.19379346, 0.21974974, - 0.23556449, 0.2356215 , 0.0872458 , -0.05175871, -0.04146828, - -0.38600975, -0.40563272, -0.07724253, -0.05219307, -0.04259932, - -0.04528749, -0.04943203]), linear_terms=array([[0.], + [[0.]]]), scale=0.9252398949005969, shift=array([9.25239895])), candidate_index=21, candidate_x=array([9.25072612]), index=0, x=array([9.25239895]), fval=0.6423583869781233, rho=-83.86519702867479, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([ 0, 14, 16, 17, 19, 20]), old_indices_discarded=array([18]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([9.25239895]), radius=0.014456873357821826, bounds=Bounds(lower=array([1.1]), upper=array([20.]))), model_indices=array([ 0, 14, 16, 17, 20, 21]), model=ScalarModel(intercept=0.6423665985864432, linear_terms=array([4.15685709e-06]), square_terms=array([[1.80234953e-05]]), scale=0.014456873357821826, shift=array([9.25239895])), vector_model=VectorModel(intercepts=array([ 0.04871317, 0.12404612, 0.14884861, 0.1938165 , 0.21740855, + 0.23242116, 0.2333601 , 0.06702318, -0.0801855 , -0.06712552, + -0.40905258, -0.41755015, -0.12516662, -0.098803 , -0.08942985, + -0.09321084, -0.09959793]), linear_terms=array([[0.], [0.], [0.], [0.], @@ -436,10 +436,10 @@ algorithm_output,"{'states': [State(trustregion=Region(center=array([8.71634833] [[0.]], - [[0.]]]), scale=0.8716348333785895, shift=array([8.71634833])), candidate_index=22, candidate_x=array([8.70272904]), index=0, x=array([8.71634833]), fval=0.5809829529263782, rho=-1.9603833733683345, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([ 0, 14, 16, 19, 20, 21]), old_indices_discarded=array([18]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([8.71634833]), radius=0.00680964713577023, bounds=Bounds(lower=array([2.]), upper=array([20.]))), model_indices=array([ 0, 16, 19, 20, 21, 22]), model=ScalarModel(intercept=0.5810113909999253, linear_terms=array([-2.82339932e-05]), square_terms=array([[5.14620885e-06]]), scale=0.00680964713577023, shift=array([8.71634833])), vector_model=VectorModel(intercepts=array([ 0.05724941, 0.13067239, 0.15239639, 0.19379346, 0.21974974, - 0.23556449, 0.2356215 , 0.0872458 , -0.05175871, -0.04146828, - -0.38600975, -0.40563272, -0.07724253, -0.05219307, -0.04259932, - -0.04528749, -0.04943203]), linear_terms=array([[0.], + [[0.]]]), scale=0.9252398949005969, shift=array([9.25239895])), candidate_index=22, candidate_x=array([9.24906468]), index=0, x=array([9.25239895]), fval=0.6423583869781233, rho=-45.476949115574584, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([ 0, 14, 16, 17, 20, 21]), old_indices_discarded=array([18, 19]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([9.25239895]), radius=0.007228436678910913, bounds=Bounds(lower=array([1.1]), upper=array([20.]))), model_indices=array([ 0, 14, 17, 20, 21, 22]), model=ScalarModel(intercept=0.6423679396996458, linear_terms=array([-9.52115187e-07]), square_terms=array([[4.52250154e-06]]), scale=0.007228436678910913, shift=array([9.25239895])), vector_model=VectorModel(intercepts=array([ 0.04871317, 0.12404612, 0.14884861, 0.1938165 , 0.21740855, + 0.23242116, 0.2333601 , 0.06702318, -0.0801855 , -0.06712552, + -0.40905258, -0.41755015, -0.12516662, -0.098803 , -0.08942985, + -0.09321084, -0.09959793]), linear_terms=array([[0.], [0.], [0.], [0.], @@ -487,10 +487,10 @@ algorithm_output,"{'states': [State(trustregion=Region(center=array([8.71634833] [[0.]], - [[0.]]]), scale=0.8716348333785895, shift=array([8.71634833])), candidate_index=23, candidate_x=array([8.72315798]), index=0, x=array([8.71634833]), fval=0.5809829529263782, rho=-0.9056508430762129, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([ 0, 16, 19, 20, 21, 22]), old_indices_discarded=array([14]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([8.71634833]), radius=0.003404823567885115, bounds=Bounds(lower=array([2.]), upper=array([20.]))), model_indices=array([ 0, 16, 19, 20, 21, 23]), model=ScalarModel(intercept=0.5810141894422566, linear_terms=array([-1.22543489e-05]), square_terms=array([[1.28104557e-06]]), scale=0.003404823567885115, shift=array([8.71634833])), vector_model=VectorModel(intercepts=array([ 0.05724941, 0.13067239, 0.15239639, 0.19379346, 0.21974974, - 0.23556449, 0.2356215 , 0.0872458 , -0.05175871, -0.04146828, - -0.38600975, -0.40563272, -0.07724253, -0.05219307, -0.04259932, - -0.04528749, -0.04943203]), linear_terms=array([[0.], + [[0.]]]), scale=0.9252398949005969, shift=array([9.25239895])), candidate_index=23, candidate_x=array([9.25392074]), index=0, x=array([9.25239895]), fval=0.6423583869781233, rho=-108.96714719747298, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([ 0, 14, 17, 20, 21, 22]), old_indices_discarded=array([16]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([9.25239895]), radius=0.0036142183394554566, bounds=Bounds(lower=array([1.1]), upper=array([20.]))), model_indices=array([ 0, 14, 20, 21, 22, 23]), model=ScalarModel(intercept=0.6423659966814586, linear_terms=array([-8.6015844e-06]), square_terms=array([[1.06092272e-06]]), scale=0.0036142183394554566, shift=array([9.25239895])), vector_model=VectorModel(intercepts=array([ 0.04871317, 0.12404612, 0.14884861, 0.1938165 , 0.21740855, + 0.23242116, 0.2333601 , 0.06702318, -0.0801855 , -0.06712552, + -0.40905258, -0.41755015, -0.12516662, -0.098803 , -0.08942985, + -0.09321084, -0.09959793]), linear_terms=array([[0.], [0.], [0.], [0.], @@ -538,10 +538,10 @@ algorithm_output,"{'states': [State(trustregion=Region(center=array([8.71634833] [[0.]], - [[0.]]]), scale=0.8716348333785895, shift=array([8.71634833])), candidate_index=24, candidate_x=array([8.71975316]), index=0, x=array([8.71634833]), fval=0.5809829529263782, rho=-1.6784108611740982, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([ 0, 16, 19, 20, 21, 23]), old_indices_discarded=array([22]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([8.71634833]), radius=0.0017024117839425576, bounds=Bounds(lower=array([2.]), upper=array([20.]))), model_indices=array([ 0, 16, 20, 21, 23, 24]), model=ScalarModel(intercept=0.5810061421847691, linear_terms=array([-2.83894013e-06]), square_terms=array([[3.17081569e-07]]), scale=0.0017024117839425576, shift=array([8.71634833])), vector_model=VectorModel(intercepts=array([ 0.05724941, 0.13067239, 0.15239639, 0.19379346, 0.21974974, - 0.23556449, 0.2356215 , 0.0872458 , -0.05175871, -0.04146828, - -0.38600975, -0.40563272, -0.07724253, -0.05219307, -0.04259932, - -0.04528749, -0.04943203]), linear_terms=array([[0.], + [[0.]]]), scale=0.9252398949005969, shift=array([9.25239895])), candidate_index=24, candidate_x=array([9.25601317]), index=0, x=array([9.25239895]), fval=0.6423583869781233, rho=-3.495769267406339, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([ 0, 14, 20, 21, 22, 23]), old_indices_discarded=array([17]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([9.25239895]), radius=0.0018071091697277283, bounds=Bounds(lower=array([1.1]), upper=array([20.]))), model_indices=array([ 0, 14, 20, 21, 22, 23]), model=ScalarModel(intercept=0.6423659966814583, linear_terms=array([-4.3007922e-06]), square_terms=array([[2.65230679e-07]]), scale=0.0018071091697277283, shift=array([9.25239895])), vector_model=VectorModel(intercepts=array([ 0.04871317, 0.12404612, 0.14884861, 0.1938165 , 0.21740855, + 0.23242116, 0.2333601 , 0.06702318, -0.0801855 , -0.06712552, + -0.40905258, -0.41755015, -0.12516662, -0.098803 , -0.08942985, + -0.09321084, -0.09959793]), linear_terms=array([[0.], [0.], [0.], [0.], @@ -589,10 +589,10 @@ algorithm_output,"{'states': [State(trustregion=Region(center=array([8.71634833] [[0.]], - [[0.]]]), scale=0.8716348333785895, shift=array([8.71634833])), candidate_index=25, candidate_x=array([8.71805075]), index=0, x=array([8.71634833]), fval=0.5809829529263782, rho=-8.708588590543586, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([ 0, 16, 20, 21, 23, 24]), old_indices_discarded=array([], dtype=int64), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([8.71634833]), radius=0.0008512058919712788, bounds=Bounds(lower=array([2.]), upper=array([20.]))), model_indices=array([ 0, 21, 24, 25]), model=ScalarModel(intercept=0.58100601810774, linear_terms=array([-2.81344906e-06]), square_terms=array([[8.02862641e-08]]), scale=0.0008512058919712788, shift=array([8.71634833])), vector_model=VectorModel(intercepts=array([ 0.05724941, 0.13067239, 0.15239639, 0.19379346, 0.21974974, - 0.23556449, 0.2356215 , 0.0872458 , -0.05175871, -0.04146828, - -0.38600975, -0.40563272, -0.07724253, -0.05219307, -0.04259932, - -0.04528749, -0.04943203]), linear_terms=array([[0.], + [[0.]]]), scale=0.9252398949005969, shift=array([9.25239895])), candidate_index=25, candidate_x=array([9.25420606]), index=0, x=array([9.25239895]), fval=0.6423583869781233, rho=-3.4524236211503827, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([ 0, 14, 20, 21, 22, 23]), old_indices_discarded=array([24]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([9.25239895]), radius=0.0009035545848638641, bounds=Bounds(lower=array([1.1]), upper=array([20.]))), model_indices=array([ 0, 14, 20, 21, 23, 25]), model=ScalarModel(intercept=0.6423677993194055, linear_terms=array([4.10125993e-07]), square_terms=array([[6.47204357e-08]]), scale=0.0009035545848638641, shift=array([9.25239895])), vector_model=VectorModel(intercepts=array([ 0.04871317, 0.12404612, 0.14884861, 0.1938165 , 0.21740855, + 0.23242116, 0.2333601 , 0.06702318, -0.0801855 , -0.06712552, + -0.40905258, -0.41755015, -0.12516662, -0.098803 , -0.08942985, + -0.09321084, -0.09959793]), linear_terms=array([[0.], [0.], [0.], [0.], @@ -640,10 +640,10 @@ algorithm_output,"{'states': [State(trustregion=Region(center=array([8.71634833] [[0.]], - [[0.]]]), scale=0.8716348333785895, shift=array([8.71634833])), candidate_index=26, candidate_x=array([8.71719954]), index=0, x=array([8.71634833]), fval=0.5809829529263782, rho=-5.867164360379236, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([ 0, 21, 24, 25]), old_indices_discarded=array([], dtype=int64), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([8.71634833]), radius=0.0004256029459856394, bounds=Bounds(lower=array([2.]), upper=array([20.]))), model_indices=array([ 0, 25, 26]), model=ScalarModel(intercept=0.580984499299932, linear_terms=array([5.79698962e-06]), square_terms=array([[1.92842594e-08]]), scale=0.0004256029459856394, shift=array([8.71634833])), vector_model=VectorModel(intercepts=array([ 0.05724941, 0.13067239, 0.15239639, 0.19379346, 0.21974974, - 0.23556449, 0.2356215 , 0.0872458 , -0.05175871, -0.04146828, - -0.38600975, -0.40563272, -0.07724253, -0.05219307, -0.04259932, - -0.04528749, -0.04943203]), linear_terms=array([[0.], + [[0.]]]), scale=0.9252398949005969, shift=array([9.25239895])), candidate_index=26, candidate_x=array([9.25149539]), index=0, x=array([9.25239895]), fval=0.6423583869781233, rho=-14.054500660204207, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([ 0, 14, 20, 21, 23, 25]), old_indices_discarded=array([22, 24]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([9.25239895]), radius=0.00045177729243193207, bounds=Bounds(lower=array([1.1]), upper=array([20.]))), model_indices=array([ 0, 20, 21, 23, 25, 26]), model=ScalarModel(intercept=0.6423669214956031, linear_terms=array([4.45886181e-07]), square_terms=array([[1.61297046e-08]]), scale=0.00045177729243193207, shift=array([9.25239895])), vector_model=VectorModel(intercepts=array([ 0.04871317, 0.12404612, 0.14884861, 0.1938165 , 0.21740855, + 0.23242116, 0.2333601 , 0.06702318, -0.0801855 , -0.06712552, + -0.40905258, -0.41755015, -0.12516662, -0.098803 , -0.08942985, + -0.09321084, -0.09959793]), linear_terms=array([[0.], [0.], [0.], [0.], @@ -691,10 +691,10 @@ algorithm_output,"{'states': [State(trustregion=Region(center=array([8.71634833] [[0.]], - [[0.]]]), scale=0.8716348333785895, shift=array([8.71634833])), candidate_index=27, candidate_x=array([8.71592273]), index=0, x=array([8.71634833]), fval=0.5809829529263782, rho=-1.4201327974934779, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([ 0, 25, 26]), old_indices_discarded=array([], dtype=int64), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([8.71634833]), radius=0.0002128014729928197, bounds=Bounds(lower=array([2.]), upper=array([20.]))), model_indices=array([ 0, 26, 27]), model=ScalarModel(intercept=0.580989949385854, linear_terms=array([1.72599501e-06]), square_terms=array([[4.88198337e-09]]), scale=0.0002128014729928197, shift=array([8.71634833])), vector_model=VectorModel(intercepts=array([ 0.05724941, 0.13067239, 0.15239639, 0.19379346, 0.21974974, - 0.23556449, 0.2356215 , 0.0872458 , -0.05175871, -0.04146828, - -0.38600975, -0.40563272, -0.07724253, -0.05219307, -0.04259932, - -0.04528749, -0.04943203]), linear_terms=array([[0.], + [[0.]]]), scale=0.9252398949005969, shift=array([9.25239895])), candidate_index=27, candidate_x=array([9.25194717]), index=0, x=array([9.25239895]), fval=0.6423583869781233, rho=-3.232911680156261, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([ 0, 20, 21, 23, 25, 26]), old_indices_discarded=array([14]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([9.25239895]), radius=0.00022588864621596604, bounds=Bounds(lower=array([1.1]), upper=array([20.]))), model_indices=array([ 0, 26, 27]), model=ScalarModel(intercept=0.6423579766776862, linear_terms=array([-1.31913132e-06]), square_terms=array([[4.08571524e-09]]), scale=0.00022588864621596604, shift=array([9.25239895])), vector_model=VectorModel(intercepts=array([ 0.04871317, 0.12404612, 0.14884861, 0.1938165 , 0.21740855, + 0.23242116, 0.2333601 , 0.06702318, -0.0801855 , -0.06712552, + -0.40905258, -0.41755015, -0.12516662, -0.098803 , -0.08942985, + -0.09321084, -0.09959793]), linear_terms=array([[0.], [0.], [0.], [0.], @@ -742,10 +742,10 @@ algorithm_output,"{'states': [State(trustregion=Region(center=array([8.71634833] [[0.]], - [[0.]]]), scale=0.8716348333785895, shift=array([8.71634833])), candidate_index=28, candidate_x=array([8.71613553]), index=0, x=array([8.71634833]), fval=0.5809829529263782, rho=-2.24757069052044, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([ 0, 26, 27]), old_indices_discarded=array([], dtype=int64), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([8.71634833]), radius=0.00010640073649640985, bounds=Bounds(lower=array([2.]), upper=array([20.]))), model_indices=array([ 0, 27, 28]), model=ScalarModel(intercept=0.5809828752663786, linear_terms=array([-2.05209442e-06]), square_terms=array([[1.30245009e-09]]), scale=0.00010640073649640985, shift=array([8.71634833])), vector_model=VectorModel(intercepts=array([ 0.05724941, 0.13067239, 0.15239639, 0.19379346, 0.21974974, - 0.23556449, 0.2356215 , 0.0872458 , -0.05175871, -0.04146828, - -0.38600975, -0.40563272, -0.07724253, -0.05219307, -0.04259932, - -0.04528749, -0.04943203]), linear_terms=array([[0.], + [[0.]]]), scale=0.9252398949005969, shift=array([9.25239895])), candidate_index=28, candidate_x=array([9.25262484]), index=0, x=array([9.25239895]), fval=0.6423583869781233, rho=-0.8340197126941936, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([ 0, 26, 27]), old_indices_discarded=array([], dtype=int64), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([9.25239895]), radius=0.00011294432310798302, bounds=Bounds(lower=array([1.1]), upper=array([20.]))), model_indices=array([ 0, 27, 28]), model=ScalarModel(intercept=0.6423591585016506, linear_terms=array([-9.46880328e-08]), square_terms=array([[9.96719279e-10]]), scale=0.00011294432310798302, shift=array([9.25239895])), vector_model=VectorModel(intercepts=array([ 0.04871317, 0.12404612, 0.14884861, 0.1938165 , 0.21740855, + 0.23242116, 0.2333601 , 0.06702318, -0.0801855 , -0.06712552, + -0.40905258, -0.41755015, -0.12516662, -0.098803 , -0.08942985, + -0.09321084, -0.09959793]), linear_terms=array([[0.], [0.], [0.], [0.], @@ -793,10 +793,10 @@ algorithm_output,"{'states': [State(trustregion=Region(center=array([8.71634833] [[0.]], - [[0.]]]), scale=0.8716348333785895, shift=array([8.71634833])), candidate_index=29, candidate_x=array([8.71645473]), index=0, x=array([8.71634833]), fval=0.5809829529263782, rho=-0.37426873931064897, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([ 0, 27, 28]), old_indices_discarded=array([], dtype=int64), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([8.71634833]), radius=5.3200368248204925e-05, bounds=Bounds(lower=array([2.]), upper=array([20.]))), model_indices=array([ 0, 28, 29]), model=ScalarModel(intercept=0.580984111264387, linear_terms=array([-5.81699654e-07]), square_terms=array([[3.18428398e-10]]), scale=5.3200368248204925e-05, shift=array([8.71634833])), vector_model=VectorModel(intercepts=array([ 0.05724941, 0.13067239, 0.15239639, 0.19379346, 0.21974974, - 0.23556449, 0.2356215 , 0.0872458 , -0.05175871, -0.04146828, - -0.38600975, -0.40563272, -0.07724253, -0.05219307, -0.04259932, - -0.04528749, -0.04943203]), linear_terms=array([[0.], + [[0.]]]), scale=0.9252398949005969, shift=array([9.25239895])), candidate_index=29, candidate_x=array([9.25251189]), index=0, x=array([9.25239895]), fval=0.6423583869781233, rho=-4.249921661170417, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([ 0, 27, 28]), old_indices_discarded=array([], dtype=int64), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([9.25239895]), radius=5.647216155399151e-05, bounds=Bounds(lower=array([1.1]), upper=array([20.]))), model_indices=array([ 0, 28, 29]), model=ScalarModel(intercept=0.6423583374948495, linear_terms=array([2.74128743e-07]), square_terms=array([[2.45374978e-10]]), scale=5.647216155399151e-05, shift=array([9.25239895])), vector_model=VectorModel(intercepts=array([ 0.04871317, 0.12404612, 0.14884861, 0.1938165 , 0.21740855, + 0.23242116, 0.2333601 , 0.06702318, -0.0801855 , -0.06712552, + -0.40905258, -0.41755015, -0.12516662, -0.098803 , -0.08942985, + -0.09321084, -0.09959793]), linear_terms=array([[0.], [0.], [0.], [0.], @@ -844,10 +844,10 @@ algorithm_output,"{'states': [State(trustregion=Region(center=array([8.71634833] [[0.]], - [[0.]]]), scale=0.8716348333785895, shift=array([8.71634833])), candidate_index=30, candidate_x=array([8.71640153]), index=0, x=array([8.71634833]), fval=0.5809829529263782, rho=-0.604210460646522, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([ 0, 28, 29]), old_indices_discarded=array([], dtype=int64), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([8.71634833]), radius=2.6600184124102462e-05, bounds=Bounds(lower=array([2.]), upper=array([20.]))), model_indices=array([ 0, 29, 30]), model=ScalarModel(intercept=0.5809829421366142, linear_terms=array([1.9179464e-07]), square_terms=array([[7.65325303e-11]]), scale=2.6600184124102462e-05, shift=array([8.71634833])), vector_model=VectorModel(intercepts=array([ 0.05724941, 0.13067239, 0.15239639, 0.19379346, 0.21974974, - 0.23556449, 0.2356215 , 0.0872458 , -0.05175871, -0.04146828, - -0.38600975, -0.40563272, -0.07724253, -0.05219307, -0.04259932, - -0.04528749, -0.04943203]), linear_terms=array([[0.], + [[0.]]]), scale=0.9252398949005969, shift=array([9.25239895])), candidate_index=30, candidate_x=array([9.25234248]), index=30, x=array([9.25234248]), fval=0.6423583236273489, rho=0.2312020963811631, accepted=True, new_indices=array([], dtype=int64), old_indices_used=array([ 0, 28, 29]), old_indices_discarded=array([], dtype=int64), step_length=5.647216155324486e-05, relative_step_length=0.9999999999867785, n_evals_per_point=1, n_evals_acceptance=1)], 'tranquilo_history': History for least_squares function with 31 entries., 'multistart_info': {'start_parameters': [array([9.25239895])], 'local_optima': [{'solution_x': array([9.25234248]), 'solution_criterion': 0.6423583236273489, 'states': [State(trustregion=Region(center=array([9.25239895]), radius=0.9252398949005969, bounds=Bounds(lower=array([1.1]), upper=array([20.]))), model_indices=[0], model=ScalarModel(intercept=0.6423583869781233, linear_terms=array([0.]), square_terms=array([[0.]]), scale=0.9252398949005969, shift=array([9.25239895])), vector_model=VectorModel(intercepts=array([ 0.04871317, 0.12404612, 0.14884861, 0.1938165 , 0.21740855, + 0.23242116, 0.2333601 , 0.06702318, -0.0801855 , -0.06712552, + -0.40905258, -0.41755015, -0.12516662, -0.098803 , -0.08942985, + -0.09321084, -0.09959793]), linear_terms=array([[0.], [0.], [0.], [0.], @@ -895,10 +895,10 @@ algorithm_output,"{'states': [State(trustregion=Region(center=array([8.71634833] [[0.]], - [[0.]]]), scale=0.8716348333785895, shift=array([8.71634833])), candidate_index=31, candidate_x=array([8.71632173]), index=0, x=array([8.71634833]), fval=0.5809829529263782, rho=-1.2017101678755195, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([ 0, 29, 30]), old_indices_discarded=array([], dtype=int64), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([8.71634833]), radius=1.3300092062051231e-05, bounds=Bounds(lower=array([2.]), upper=array([20.]))), model_indices=array([ 0, 30, 31]), model=ScalarModel(intercept=0.5809831269288415, linear_terms=array([2.98038573e-08]), square_terms=array([[1.93209568e-11]]), scale=1.3300092062051231e-05, shift=array([8.71634833])), vector_model=VectorModel(intercepts=array([ 0.05724941, 0.13067239, 0.15239639, 0.19379346, 0.21974974, - 0.23556449, 0.2356215 , 0.0872458 , -0.05175871, -0.04146828, - -0.38600975, -0.40563272, -0.07724253, -0.05219307, -0.04259932, - -0.04528749, -0.04943203]), linear_terms=array([[0.], + [[0.]]]), scale=0.9252398949005969, shift=array([9.25239895])), candidate_index=0, candidate_x=array([9.25239895]), index=0, x=array([9.25239895]), fval=0.6423583869781233, rho=nan, accepted=True, new_indices=[0], old_indices_used=[], old_indices_discarded=[], step_length=None, relative_step_length=None, n_evals_per_point=None, n_evals_acceptance=None), State(trustregion=Region(center=array([9.25239895]), radius=0.9252398949005969, bounds=Bounds(lower=array([1.1]), upper=array([20.]))), model_indices=array([ 0, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13]), model=ScalarModel(intercept=0.6366130167243159, linear_terms=array([0.00015204]), square_terms=array([[0.07297192]]), scale=0.9252398949005969, shift=array([9.25239895])), vector_model=VectorModel(intercepts=array([ 0.04871317, 0.12404612, 0.14884861, 0.1938165 , 0.21740855, + 0.23242116, 0.2333601 , 0.06702318, -0.0801855 , -0.06712552, + -0.40905258, -0.41755015, -0.12516662, -0.098803 , -0.08942985, + -0.09321084, -0.09959793]), linear_terms=array([[0.], [0.], [0.], [0.], @@ -946,10 +946,10 @@ algorithm_output,"{'states': [State(trustregion=Region(center=array([8.71634833] [[0.]], - [[0.]]]), scale=0.8716348333785895, shift=array([8.71634833])), candidate_index=32, candidate_x=array([8.71633503]), index=0, x=array([8.71634833]), fval=0.5809829529263782, rho=-0.456714199690376, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([ 0, 30, 31]), old_indices_discarded=array([], dtype=int64), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([8.71634833]), radius=6.650046031025616e-06, bounds=Bounds(lower=array([2.]), upper=array([20.]))), model_indices=array([ 0, 31, 32]), model=ScalarModel(intercept=0.5809829190596839, linear_terms=array([-5.75988436e-08]), square_terms=array([[5.00246283e-12]]), scale=6.650046031025616e-06, shift=array([8.71634833])), vector_model=VectorModel(intercepts=array([ 0.05724941, 0.13067239, 0.15239639, 0.19379346, 0.21974974, - 0.23556449, 0.2356215 , 0.0872458 , -0.05175871, -0.04146828, - -0.38600975, -0.40563272, -0.07724253, -0.05219307, -0.04259932, - -0.04528749, -0.04943203]), linear_terms=array([[0.], + [[0.]]]), scale=0.9252398949005969, shift=array([9.25239895])), candidate_index=14, candidate_x=array([9.25047117]), index=0, x=array([9.25239895]), fval=0.6423583869781233, rho=-67.84262787184853, accepted=False, new_indices=array([ 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13]), old_indices_used=array([0]), old_indices_discarded=array([], dtype=int64), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([9.25239895]), radius=0.46261994745029844, bounds=Bounds(lower=array([1.1]), upper=array([20.]))), model_indices=array([ 0, 11, 12, 13, 14, 15]), model=ScalarModel(intercept=0.6391740801217988, linear_terms=array([0.00084041]), square_terms=array([[0.01834804]]), scale=0.46261994745029844, shift=array([9.25239895])), vector_model=VectorModel(intercepts=array([ 0.04871317, 0.12404612, 0.14884861, 0.1938165 , 0.21740855, + 0.23242116, 0.2333601 , 0.06702318, -0.0801855 , -0.06712552, + -0.40905258, -0.41755015, -0.12516662, -0.098803 , -0.08942985, + -0.09321084, -0.09959793]), linear_terms=array([[0.], [0.], [0.], [0.], @@ -997,10 +997,10 @@ algorithm_output,"{'states': [State(trustregion=Region(center=array([8.71634833] [[0.]], - [[0.]]]), scale=0.8716348333785895, shift=array([8.71634833])), candidate_index=33, candidate_x=array([8.71635498]), index=0, x=array([8.71634833]), fval=0.5809829529263782, rho=-0.7623046526241213, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([ 0, 31, 32]), old_indices_discarded=array([], dtype=int64), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([8.71634833]), radius=3.325023015512808e-06, bounds=Bounds(lower=array([2.]), upper=array([20.]))), model_indices=array([ 0, 32, 33]), model=ScalarModel(intercept=0.5809829746559877, linear_terms=array([3.84376872e-09]), square_terms=array([[1.20998353e-12]]), scale=3.325023015512808e-06, shift=array([8.71634833])), vector_model=VectorModel(intercepts=array([ 0.05724941, 0.13067239, 0.15239639, 0.19379346, 0.21974974, - 0.23556449, 0.2356215 , 0.0872458 , -0.05175871, -0.04146828, - -0.38600975, -0.40563272, -0.07724253, -0.05219307, -0.04259932, - -0.04528749, -0.04943203]), linear_terms=array([[0.], + [[0.]]]), scale=0.9252398949005969, shift=array([9.25239895])), candidate_index=16, candidate_x=array([9.23120907]), index=0, x=array([9.25239895]), fval=0.6423583869781233, rho=-0.9360366242557278, accepted=False, new_indices=array([15]), old_indices_used=array([ 0, 11, 12, 13, 14]), old_indices_discarded=array([ 1, 2, 3, 4, 5, 6, 7, 8, 9, 10]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([9.25239895]), radius=0.23130997372514922, bounds=Bounds(lower=array([1.1]), upper=array([20.]))), model_indices=array([ 0, 12, 13, 14, 15, 16]), model=ScalarModel(intercept=0.640036605619869, linear_terms=array([0.00027282]), square_terms=array([[0.0045447]]), scale=0.23130997372514922, shift=array([9.25239895])), vector_model=VectorModel(intercepts=array([ 0.04871317, 0.12404612, 0.14884861, 0.1938165 , 0.21740855, + 0.23242116, 0.2333601 , 0.06702318, -0.0801855 , -0.06712552, + -0.40905258, -0.41755015, -0.12516662, -0.098803 , -0.08942985, + -0.09321084, -0.09959793]), linear_terms=array([[0.], [0.], [0.], [0.], @@ -1048,10 +1048,10 @@ algorithm_output,"{'states': [State(trustregion=Region(center=array([8.71634833] [[0.]], - [[0.]]]), scale=0.8716348333785895, shift=array([8.71634833])), candidate_index=34, candidate_x=array([8.71634501]), index=34, x=array([8.71634501]), fval=0.5809829309750734, rho=5.711779695149159, accepted=True, new_indices=array([], dtype=int64), old_indices_used=array([ 0, 32, 33]), old_indices_discarded=array([], dtype=int64), step_length=3.3250230160319916e-06, relative_step_length=1.0000000001561444, n_evals_per_point=1, n_evals_acceptance=1)], 'tranquilo_history': History for least_squares function with 35 entries., 'multistart_info': {'start_parameters': [array([8.71634833])], 'local_optima': [{'solution_x': array([8.71634501]), 'solution_criterion': 0.5809829309750734, 'states': [State(trustregion=Region(center=array([8.71634833]), radius=0.8716348333785895, bounds=Bounds(lower=array([2.]), upper=array([20.]))), model_indices=[0], model=ScalarModel(intercept=0.5809829529263784, linear_terms=array([0.]), square_terms=array([[0.]]), scale=0.8716348333785895, shift=array([8.71634833])), vector_model=VectorModel(intercepts=array([ 0.05724941, 0.13067239, 0.15239639, 0.19379346, 0.21974974, - 0.23556449, 0.2356215 , 0.0872458 , -0.05175871, -0.04146828, - -0.38600975, -0.40563272, -0.07724253, -0.05219307, -0.04259932, - -0.04528749, -0.04943203]), linear_terms=array([[0.], + [[0.]]]), scale=0.9252398949005969, shift=array([9.25239895])), candidate_index=17, candidate_x=array([9.23851343]), index=0, x=array([9.25239895]), fval=0.6423583869781233, rho=-2.0600316699171524, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([ 0, 12, 13, 14, 15, 16]), old_indices_discarded=array([ 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([9.25239895]), radius=0.11565498686257461, bounds=Bounds(lower=array([1.1]), upper=array([20.]))), model_indices=array([ 0, 14, 15, 16, 17]), model=ScalarModel(intercept=0.6424111679010795, linear_terms=array([0.00061553]), square_terms=array([[0.00116854]]), scale=0.11565498686257461, shift=array([9.25239895])), vector_model=VectorModel(intercepts=array([ 0.04871317, 0.12404612, 0.14884861, 0.1938165 , 0.21740855, + 0.23242116, 0.2333601 , 0.06702318, -0.0801855 , -0.06712552, + -0.40905258, -0.41755015, -0.12516662, -0.098803 , -0.08942985, + -0.09321084, -0.09959793]), linear_terms=array([[0.], [0.], [0.], [0.], @@ -1099,10 +1099,10 @@ algorithm_output,"{'states': [State(trustregion=Region(center=array([8.71634833] [[0.]], - [[0.]]]), scale=0.8716348333785895, shift=array([8.71634833])), candidate_index=0, candidate_x=array([8.71634833]), index=0, x=array([8.71634833]), fval=0.5809829529263782, rho=nan, accepted=True, new_indices=[0], old_indices_used=[], old_indices_discarded=[], step_length=None, relative_step_length=None, n_evals_per_point=None, n_evals_acceptance=None), State(trustregion=Region(center=array([8.71634833]), radius=0.8716348333785895, bounds=Bounds(lower=array([2.]), upper=array([20.]))), model_indices=array([ 0, 1, 2, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13]), model=ScalarModel(intercept=0.577061750786993, linear_terms=array([-0.00226603]), square_terms=array([[0.08453366]]), scale=0.8716348333785895, shift=array([8.71634833])), vector_model=VectorModel(intercepts=array([ 0.05724941, 0.13067239, 0.15239639, 0.19379346, 0.21974974, - 0.23556449, 0.2356215 , 0.0872458 , -0.05175871, -0.04146828, - -0.38600975, -0.40563272, -0.07724253, -0.05219307, -0.04259932, - -0.04528749, -0.04943203]), linear_terms=array([[0.], + [[0.]]]), scale=0.9252398949005969, shift=array([9.25239895])), candidate_index=18, candidate_x=array([9.19147768]), index=0, x=array([9.25239895]), fval=0.6423583869781233, rho=-1.0079617617718157, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([ 0, 14, 15, 16, 17]), old_indices_discarded=array([], dtype=int64), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([9.25239895]), radius=0.057827493431287305, bounds=Bounds(lower=array([1.1]), upper=array([20.]))), model_indices=array([ 0, 14, 16, 17, 19]), model=ScalarModel(intercept=0.6423642263710555, linear_terms=array([8.47856679e-06]), square_terms=array([[0.00028439]]), scale=0.057827493431287305, shift=array([9.25239895])), vector_model=VectorModel(intercepts=array([ 0.04871317, 0.12404612, 0.14884861, 0.1938165 , 0.21740855, + 0.23242116, 0.2333601 , 0.06702318, -0.0801855 , -0.06712552, + -0.40905258, -0.41755015, -0.12516662, -0.098803 , -0.08942985, + -0.09321084, -0.09959793]), linear_terms=array([[0.], [0.], [0.], [0.], @@ -1150,10 +1150,10 @@ algorithm_output,"{'states': [State(trustregion=Region(center=array([8.71634833] [[0.]], - [[0.]]]), scale=0.8716348333785895, shift=array([8.71634833])), candidate_index=14, candidate_x=array([8.73971363]), index=0, x=array([8.71634833]), fval=0.5809829529263782, rho=-8.359656805672962, accepted=False, new_indices=array([ 1, 2, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13]), old_indices_used=array([0]), old_indices_discarded=array([], dtype=int64), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([8.71634833]), radius=0.43581741668929475, bounds=Bounds(lower=array([2.]), upper=array([20.]))), model_indices=array([ 0, 11, 12, 13, 14, 15]), model=ScalarModel(intercept=0.5788831585760169, linear_terms=array([-0.00031441]), square_terms=array([[0.02128156]]), scale=0.43581741668929475, shift=array([8.71634833])), vector_model=VectorModel(intercepts=array([ 0.05724941, 0.13067239, 0.15239639, 0.19379346, 0.21974974, - 0.23556449, 0.2356215 , 0.0872458 , -0.05175871, -0.04146828, - -0.38600975, -0.40563272, -0.07724253, -0.05219307, -0.04259932, - -0.04528749, -0.04943203]), linear_terms=array([[0.], + [[0.]]]), scale=0.9252398949005969, shift=array([9.25239895])), candidate_index=20, candidate_x=array([9.25067494]), index=0, x=array([9.25239895]), fval=0.6423583869781233, rho=-80.16115218067975, accepted=False, new_indices=array([19]), old_indices_used=array([ 0, 14, 16, 17]), old_indices_discarded=array([18]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([9.25239895]), radius=0.028913746715643653, bounds=Bounds(lower=array([1.1]), upper=array([20.]))), model_indices=array([ 0, 14, 16, 17, 19, 20]), model=ScalarModel(intercept=0.6423649815517477, linear_terms=array([4.11261778e-06]), square_terms=array([[7.10839727e-05]]), scale=0.028913746715643653, shift=array([9.25239895])), vector_model=VectorModel(intercepts=array([ 0.04871317, 0.12404612, 0.14884861, 0.1938165 , 0.21740855, + 0.23242116, 0.2333601 , 0.06702318, -0.0801855 , -0.06712552, + -0.40905258, -0.41755015, -0.12516662, -0.098803 , -0.08942985, + -0.09321084, -0.09959793]), linear_terms=array([[0.], [0.], [0.], [0.], @@ -1201,10 +1201,10 @@ algorithm_output,"{'states': [State(trustregion=Region(center=array([8.71634833] [[0.]], - [[0.]]]), scale=0.8716348333785895, shift=array([8.71634833])), candidate_index=16, candidate_x=array([8.72278695]), index=0, x=array([8.71634833]), fval=0.5809829529263782, rho=-7.349105297615672, accepted=False, new_indices=array([15]), old_indices_used=array([ 0, 11, 12, 13, 14]), old_indices_discarded=array([ 1, 2, 3, 4, 5, 6, 7, 8, 9, 10]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([8.71634833]), radius=0.21790870834464737, bounds=Bounds(lower=array([2.]), upper=array([20.]))), model_indices=array([ 0, 13, 14, 15, 16, 17]), model=ScalarModel(intercept=0.5808510433773434, linear_terms=array([0.00091457]), square_terms=array([[0.00557954]]), scale=0.21790870834464737, shift=array([8.71634833])), vector_model=VectorModel(intercepts=array([ 0.05724941, 0.13067239, 0.15239639, 0.19379346, 0.21974974, - 0.23556449, 0.2356215 , 0.0872458 , -0.05175871, -0.04146828, - -0.38600975, -0.40563272, -0.07724253, -0.05219307, -0.04259932, - -0.04528749, -0.04943203]), linear_terms=array([[0.], + [[0.]]]), scale=0.9252398949005969, shift=array([9.25239895])), candidate_index=21, candidate_x=array([9.25072612]), index=0, x=array([9.25239895]), fval=0.6423583869781233, rho=-83.86519702867479, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([ 0, 14, 16, 17, 19, 20]), old_indices_discarded=array([18]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([9.25239895]), radius=0.014456873357821826, bounds=Bounds(lower=array([1.1]), upper=array([20.]))), model_indices=array([ 0, 14, 16, 17, 20, 21]), model=ScalarModel(intercept=0.6423665985864432, linear_terms=array([4.15685709e-06]), square_terms=array([[1.80234953e-05]]), scale=0.014456873357821826, shift=array([9.25239895])), vector_model=VectorModel(intercepts=array([ 0.04871317, 0.12404612, 0.14884861, 0.1938165 , 0.21740855, + 0.23242116, 0.2333601 , 0.06702318, -0.0801855 , -0.06712552, + -0.40905258, -0.41755015, -0.12516662, -0.098803 , -0.08942985, + -0.09321084, -0.09959793]), linear_terms=array([[0.], [0.], [0.], [0.], @@ -1252,10 +1252,10 @@ algorithm_output,"{'states': [State(trustregion=Region(center=array([8.71634833] [[0.]], - [[0.]]]), scale=0.8716348333785895, shift=array([8.71634833])), candidate_index=18, candidate_x=array([8.6806299]), index=0, x=array([8.71634833]), fval=0.5809829529263782, rho=-2.650424420149406, accepted=False, new_indices=array([17]), old_indices_used=array([ 0, 13, 14, 15, 16]), old_indices_discarded=array([ 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([8.71634833]), radius=0.10895435417232369, bounds=Bounds(lower=array([2.]), upper=array([20.]))), model_indices=array([ 0, 14, 15, 16, 17, 18]), model=ScalarModel(intercept=0.5809473819558783, linear_terms=array([0.00014108]), square_terms=array([[0.00134501]]), scale=0.10895435417232369, shift=array([8.71634833])), vector_model=VectorModel(intercepts=array([ 0.05724941, 0.13067239, 0.15239639, 0.19379346, 0.21974974, - 0.23556449, 0.2356215 , 0.0872458 , -0.05175871, -0.04146828, - -0.38600975, -0.40563272, -0.07724253, -0.05219307, -0.04259932, - -0.04528749, -0.04943203]), linear_terms=array([[0.], + [[0.]]]), scale=0.9252398949005969, shift=array([9.25239895])), candidate_index=22, candidate_x=array([9.24906468]), index=0, x=array([9.25239895]), fval=0.6423583869781233, rho=-45.476949115574584, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([ 0, 14, 16, 17, 20, 21]), old_indices_discarded=array([18, 19]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([9.25239895]), radius=0.007228436678910913, bounds=Bounds(lower=array([1.1]), upper=array([20.]))), model_indices=array([ 0, 14, 17, 20, 21, 22]), model=ScalarModel(intercept=0.6423679396996458, linear_terms=array([-9.52115187e-07]), square_terms=array([[4.52250154e-06]]), scale=0.007228436678910913, shift=array([9.25239895])), vector_model=VectorModel(intercepts=array([ 0.04871317, 0.12404612, 0.14884861, 0.1938165 , 0.21740855, + 0.23242116, 0.2333601 , 0.06702318, -0.0801855 , -0.06712552, + -0.40905258, -0.41755015, -0.12516662, -0.098803 , -0.08942985, + -0.09321084, -0.09959793]), linear_terms=array([[0.], [0.], [0.], [0.], @@ -1303,10 +1303,10 @@ algorithm_output,"{'states': [State(trustregion=Region(center=array([8.71634833] [[0.]], - [[0.]]]), scale=0.8716348333785895, shift=array([8.71634833])), candidate_index=19, candidate_x=array([8.70491962]), index=0, x=array([8.71634833]), fval=0.5809829529263782, rho=-12.24378157908205, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([ 0, 14, 15, 16, 17, 18]), old_indices_discarded=array([], dtype=int64), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([8.71634833]), radius=0.05447717708616184, bounds=Bounds(lower=array([2.]), upper=array([20.]))), model_indices=array([ 0, 14, 16, 17, 18, 19]), model=ScalarModel(intercept=0.5810689282474453, linear_terms=array([-3.48991295e-05]), square_terms=array([[0.00032177]]), scale=0.05447717708616184, shift=array([8.71634833])), vector_model=VectorModel(intercepts=array([ 0.05724941, 0.13067239, 0.15239639, 0.19379346, 0.21974974, - 0.23556449, 0.2356215 , 0.0872458 , -0.05175871, -0.04146828, - -0.38600975, -0.40563272, -0.07724253, -0.05219307, -0.04259932, - -0.04528749, -0.04943203]), linear_terms=array([[0.], + [[0.]]]), scale=0.9252398949005969, shift=array([9.25239895])), candidate_index=23, candidate_x=array([9.25392074]), index=0, x=array([9.25239895]), fval=0.6423583869781233, rho=-108.96714719747298, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([ 0, 14, 17, 20, 21, 22]), old_indices_discarded=array([16]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([9.25239895]), radius=0.0036142183394554566, bounds=Bounds(lower=array([1.1]), upper=array([20.]))), model_indices=array([ 0, 14, 20, 21, 22, 23]), model=ScalarModel(intercept=0.6423659966814586, linear_terms=array([-8.6015844e-06]), square_terms=array([[1.06092272e-06]]), scale=0.0036142183394554566, shift=array([9.25239895])), vector_model=VectorModel(intercepts=array([ 0.04871317, 0.12404612, 0.14884861, 0.1938165 , 0.21740855, + 0.23242116, 0.2333601 , 0.06702318, -0.0801855 , -0.06712552, + -0.40905258, -0.41755015, -0.12516662, -0.098803 , -0.08942985, + -0.09321084, -0.09959793]), linear_terms=array([[0.], [0.], [0.], [0.], @@ -1354,10 +1354,10 @@ algorithm_output,"{'states': [State(trustregion=Region(center=array([8.71634833] [[0.]], - [[0.]]]), scale=0.8716348333785895, shift=array([8.71634833])), candidate_index=20, candidate_x=array([8.72225688]), index=0, x=array([8.71634833]), fval=0.5809829529263782, rho=-5.453953845413641, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([ 0, 14, 16, 17, 18, 19]), old_indices_discarded=array([], dtype=int64), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([8.71634833]), radius=0.02723858854308092, bounds=Bounds(lower=array([2.]), upper=array([20.]))), model_indices=array([ 0, 14, 16, 18, 19, 20]), model=ScalarModel(intercept=0.5810604563262121, linear_terms=array([9.66932908e-06]), square_terms=array([[8.00952314e-05]]), scale=0.02723858854308092, shift=array([8.71634833])), vector_model=VectorModel(intercepts=array([ 0.05724941, 0.13067239, 0.15239639, 0.19379346, 0.21974974, - 0.23556449, 0.2356215 , 0.0872458 , -0.05175871, -0.04146828, - -0.38600975, -0.40563272, -0.07724253, -0.05219307, -0.04259932, - -0.04528749, -0.04943203]), linear_terms=array([[0.], + [[0.]]]), scale=0.9252398949005969, shift=array([9.25239895])), candidate_index=24, candidate_x=array([9.25601317]), index=0, x=array([9.25239895]), fval=0.6423583869781233, rho=-3.495769267406339, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([ 0, 14, 20, 21, 22, 23]), old_indices_discarded=array([17]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([9.25239895]), radius=0.0018071091697277283, bounds=Bounds(lower=array([1.1]), upper=array([20.]))), model_indices=array([ 0, 14, 20, 21, 22, 23]), model=ScalarModel(intercept=0.6423659966814583, linear_terms=array([-4.3007922e-06]), square_terms=array([[2.65230679e-07]]), scale=0.0018071091697277283, shift=array([9.25239895])), vector_model=VectorModel(intercepts=array([ 0.04871317, 0.12404612, 0.14884861, 0.1938165 , 0.21740855, + 0.23242116, 0.2333601 , 0.06702318, -0.0801855 , -0.06712552, + -0.40905258, -0.41755015, -0.12516662, -0.098803 , -0.08942985, + -0.09321084, -0.09959793]), linear_terms=array([[0.], [0.], [0.], [0.], @@ -1405,10 +1405,10 @@ algorithm_output,"{'states': [State(trustregion=Region(center=array([8.71634833] [[0.]], - [[0.]]]), scale=0.8716348333785895, shift=array([8.71634833])), candidate_index=21, candidate_x=array([8.71306001]), index=0, x=array([8.71634833]), fval=0.5809829529263782, rho=-76.78603089822361, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([ 0, 14, 16, 18, 19, 20]), old_indices_discarded=array([], dtype=int64), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([8.71634833]), radius=0.01361929427154046, bounds=Bounds(lower=array([2.]), upper=array([20.]))), model_indices=array([ 0, 14, 16, 19, 20, 21]), model=ScalarModel(intercept=0.5810304488299523, linear_terms=array([5.90878084e-05]), square_terms=array([[1.97212099e-05]]), scale=0.01361929427154046, shift=array([8.71634833])), vector_model=VectorModel(intercepts=array([ 0.05724941, 0.13067239, 0.15239639, 0.19379346, 0.21974974, - 0.23556449, 0.2356215 , 0.0872458 , -0.05175871, -0.04146828, - -0.38600975, -0.40563272, -0.07724253, -0.05219307, -0.04259932, - -0.04528749, -0.04943203]), linear_terms=array([[0.], + [[0.]]]), scale=0.9252398949005969, shift=array([9.25239895])), candidate_index=25, candidate_x=array([9.25420606]), index=0, x=array([9.25239895]), fval=0.6423583869781233, rho=-3.4524236211503827, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([ 0, 14, 20, 21, 22, 23]), old_indices_discarded=array([24]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([9.25239895]), radius=0.0009035545848638641, bounds=Bounds(lower=array([1.1]), upper=array([20.]))), model_indices=array([ 0, 14, 20, 21, 23, 25]), model=ScalarModel(intercept=0.6423677993194055, linear_terms=array([4.10125993e-07]), square_terms=array([[6.47204357e-08]]), scale=0.0009035545848638641, shift=array([9.25239895])), vector_model=VectorModel(intercepts=array([ 0.04871317, 0.12404612, 0.14884861, 0.1938165 , 0.21740855, + 0.23242116, 0.2333601 , 0.06702318, -0.0801855 , -0.06712552, + -0.40905258, -0.41755015, -0.12516662, -0.098803 , -0.08942985, + -0.09321084, -0.09959793]), linear_terms=array([[0.], [0.], [0.], [0.], @@ -1456,10 +1456,10 @@ algorithm_output,"{'states': [State(trustregion=Region(center=array([8.71634833] [[0.]], - [[0.]]]), scale=0.8716348333785895, shift=array([8.71634833])), candidate_index=22, candidate_x=array([8.70272904]), index=0, x=array([8.71634833]), fval=0.5809829529263782, rho=-1.9603833733683345, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([ 0, 14, 16, 19, 20, 21]), old_indices_discarded=array([18]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([8.71634833]), radius=0.00680964713577023, bounds=Bounds(lower=array([2.]), upper=array([20.]))), model_indices=array([ 0, 16, 19, 20, 21, 22]), model=ScalarModel(intercept=0.5810113909999253, linear_terms=array([-2.82339932e-05]), square_terms=array([[5.14620885e-06]]), scale=0.00680964713577023, shift=array([8.71634833])), vector_model=VectorModel(intercepts=array([ 0.05724941, 0.13067239, 0.15239639, 0.19379346, 0.21974974, - 0.23556449, 0.2356215 , 0.0872458 , -0.05175871, -0.04146828, - -0.38600975, -0.40563272, -0.07724253, -0.05219307, -0.04259932, - -0.04528749, -0.04943203]), linear_terms=array([[0.], + [[0.]]]), scale=0.9252398949005969, shift=array([9.25239895])), candidate_index=26, candidate_x=array([9.25149539]), index=0, x=array([9.25239895]), fval=0.6423583869781233, rho=-14.054500660204207, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([ 0, 14, 20, 21, 23, 25]), old_indices_discarded=array([22, 24]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([9.25239895]), radius=0.00045177729243193207, bounds=Bounds(lower=array([1.1]), upper=array([20.]))), model_indices=array([ 0, 20, 21, 23, 25, 26]), model=ScalarModel(intercept=0.6423669214956031, linear_terms=array([4.45886181e-07]), square_terms=array([[1.61297046e-08]]), scale=0.00045177729243193207, shift=array([9.25239895])), vector_model=VectorModel(intercepts=array([ 0.04871317, 0.12404612, 0.14884861, 0.1938165 , 0.21740855, + 0.23242116, 0.2333601 , 0.06702318, -0.0801855 , -0.06712552, + -0.40905258, -0.41755015, -0.12516662, -0.098803 , -0.08942985, + -0.09321084, -0.09959793]), linear_terms=array([[0.], [0.], [0.], [0.], @@ -1507,10 +1507,10 @@ algorithm_output,"{'states': [State(trustregion=Region(center=array([8.71634833] [[0.]], - [[0.]]]), scale=0.8716348333785895, shift=array([8.71634833])), candidate_index=23, candidate_x=array([8.72315798]), index=0, x=array([8.71634833]), fval=0.5809829529263782, rho=-0.9056508430762129, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([ 0, 16, 19, 20, 21, 22]), old_indices_discarded=array([14]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([8.71634833]), radius=0.003404823567885115, bounds=Bounds(lower=array([2.]), upper=array([20.]))), model_indices=array([ 0, 16, 19, 20, 21, 23]), model=ScalarModel(intercept=0.5810141894422566, linear_terms=array([-1.22543489e-05]), square_terms=array([[1.28104557e-06]]), scale=0.003404823567885115, shift=array([8.71634833])), vector_model=VectorModel(intercepts=array([ 0.05724941, 0.13067239, 0.15239639, 0.19379346, 0.21974974, - 0.23556449, 0.2356215 , 0.0872458 , -0.05175871, -0.04146828, - -0.38600975, -0.40563272, -0.07724253, -0.05219307, -0.04259932, - -0.04528749, -0.04943203]), linear_terms=array([[0.], + [[0.]]]), scale=0.9252398949005969, shift=array([9.25239895])), candidate_index=27, candidate_x=array([9.25194717]), index=0, x=array([9.25239895]), fval=0.6423583869781233, rho=-3.232911680156261, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([ 0, 20, 21, 23, 25, 26]), old_indices_discarded=array([14]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([9.25239895]), radius=0.00022588864621596604, bounds=Bounds(lower=array([1.1]), upper=array([20.]))), model_indices=array([ 0, 26, 27]), model=ScalarModel(intercept=0.6423579766776862, linear_terms=array([-1.31913132e-06]), square_terms=array([[4.08571524e-09]]), scale=0.00022588864621596604, shift=array([9.25239895])), vector_model=VectorModel(intercepts=array([ 0.04871317, 0.12404612, 0.14884861, 0.1938165 , 0.21740855, + 0.23242116, 0.2333601 , 0.06702318, -0.0801855 , -0.06712552, + -0.40905258, -0.41755015, -0.12516662, -0.098803 , -0.08942985, + -0.09321084, -0.09959793]), linear_terms=array([[0.], [0.], [0.], [0.], @@ -1558,10 +1558,10 @@ algorithm_output,"{'states': [State(trustregion=Region(center=array([8.71634833] [[0.]], - [[0.]]]), scale=0.8716348333785895, shift=array([8.71634833])), candidate_index=24, candidate_x=array([8.71975316]), index=0, x=array([8.71634833]), fval=0.5809829529263782, rho=-1.6784108611740982, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([ 0, 16, 19, 20, 21, 23]), old_indices_discarded=array([22]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([8.71634833]), radius=0.0017024117839425576, bounds=Bounds(lower=array([2.]), upper=array([20.]))), model_indices=array([ 0, 16, 20, 21, 23, 24]), model=ScalarModel(intercept=0.5810061421847691, linear_terms=array([-2.83894013e-06]), square_terms=array([[3.17081569e-07]]), scale=0.0017024117839425576, shift=array([8.71634833])), vector_model=VectorModel(intercepts=array([ 0.05724941, 0.13067239, 0.15239639, 0.19379346, 0.21974974, - 0.23556449, 0.2356215 , 0.0872458 , -0.05175871, -0.04146828, - -0.38600975, -0.40563272, -0.07724253, -0.05219307, -0.04259932, - -0.04528749, -0.04943203]), linear_terms=array([[0.], + [[0.]]]), scale=0.9252398949005969, shift=array([9.25239895])), candidate_index=28, candidate_x=array([9.25262484]), index=0, x=array([9.25239895]), fval=0.6423583869781233, rho=-0.8340197126941936, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([ 0, 26, 27]), old_indices_discarded=array([], dtype=int64), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([9.25239895]), radius=0.00011294432310798302, bounds=Bounds(lower=array([1.1]), upper=array([20.]))), model_indices=array([ 0, 27, 28]), model=ScalarModel(intercept=0.6423591585016506, linear_terms=array([-9.46880328e-08]), square_terms=array([[9.96719279e-10]]), scale=0.00011294432310798302, shift=array([9.25239895])), vector_model=VectorModel(intercepts=array([ 0.04871317, 0.12404612, 0.14884861, 0.1938165 , 0.21740855, + 0.23242116, 0.2333601 , 0.06702318, -0.0801855 , -0.06712552, + -0.40905258, -0.41755015, -0.12516662, -0.098803 , -0.08942985, + -0.09321084, -0.09959793]), linear_terms=array([[0.], [0.], [0.], [0.], @@ -1609,10 +1609,10 @@ algorithm_output,"{'states': [State(trustregion=Region(center=array([8.71634833] [[0.]], - [[0.]]]), scale=0.8716348333785895, shift=array([8.71634833])), candidate_index=25, candidate_x=array([8.71805075]), index=0, x=array([8.71634833]), fval=0.5809829529263782, rho=-8.708588590543586, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([ 0, 16, 20, 21, 23, 24]), old_indices_discarded=array([], dtype=int64), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([8.71634833]), radius=0.0008512058919712788, bounds=Bounds(lower=array([2.]), upper=array([20.]))), model_indices=array([ 0, 21, 24, 25]), model=ScalarModel(intercept=0.58100601810774, linear_terms=array([-2.81344906e-06]), square_terms=array([[8.02862641e-08]]), scale=0.0008512058919712788, shift=array([8.71634833])), vector_model=VectorModel(intercepts=array([ 0.05724941, 0.13067239, 0.15239639, 0.19379346, 0.21974974, - 0.23556449, 0.2356215 , 0.0872458 , -0.05175871, -0.04146828, - -0.38600975, -0.40563272, -0.07724253, -0.05219307, -0.04259932, - -0.04528749, -0.04943203]), linear_terms=array([[0.], + [[0.]]]), scale=0.9252398949005969, shift=array([9.25239895])), candidate_index=29, candidate_x=array([9.25251189]), index=0, x=array([9.25239895]), fval=0.6423583869781233, rho=-4.249921661170417, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([ 0, 27, 28]), old_indices_discarded=array([], dtype=int64), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([9.25239895]), radius=5.647216155399151e-05, bounds=Bounds(lower=array([1.1]), upper=array([20.]))), model_indices=array([ 0, 28, 29]), model=ScalarModel(intercept=0.6423583374948495, linear_terms=array([2.74128743e-07]), square_terms=array([[2.45374978e-10]]), scale=5.647216155399151e-05, shift=array([9.25239895])), vector_model=VectorModel(intercepts=array([ 0.04871317, 0.12404612, 0.14884861, 0.1938165 , 0.21740855, + 0.23242116, 0.2333601 , 0.06702318, -0.0801855 , -0.06712552, + -0.40905258, -0.41755015, -0.12516662, -0.098803 , -0.08942985, + -0.09321084, -0.09959793]), linear_terms=array([[0.], [0.], [0.], [0.], @@ -1660,422 +1660,14 @@ algorithm_output,"{'states': [State(trustregion=Region(center=array([8.71634833] [[0.]], - [[0.]]]), scale=0.8716348333785895, shift=array([8.71634833])), candidate_index=26, candidate_x=array([8.71719954]), index=0, x=array([8.71634833]), fval=0.5809829529263782, rho=-5.867164360379236, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([ 0, 21, 24, 25]), old_indices_discarded=array([], dtype=int64), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([8.71634833]), radius=0.0004256029459856394, bounds=Bounds(lower=array([2.]), upper=array([20.]))), model_indices=array([ 0, 25, 26]), model=ScalarModel(intercept=0.580984499299932, linear_terms=array([5.79698962e-06]), square_terms=array([[1.92842594e-08]]), scale=0.0004256029459856394, shift=array([8.71634833])), vector_model=VectorModel(intercepts=array([ 0.05724941, 0.13067239, 0.15239639, 0.19379346, 0.21974974, - 0.23556449, 0.2356215 , 0.0872458 , -0.05175871, -0.04146828, - -0.38600975, -0.40563272, -0.07724253, -0.05219307, -0.04259932, - -0.04528749, -0.04943203]), linear_terms=array([[0.], - [0.], - [0.], - [0.], - [0.], - [0.], - [0.], - [0.], - [0.], - [0.], - [0.], - [0.], - [0.], - [0.], - [0.], - [0.], - [0.]]), square_terms=array([[[0.]], - - [[0.]], - - [[0.]], - - [[0.]], - - [[0.]], - - [[0.]], - - [[0.]], - - [[0.]], - - [[0.]], - - [[0.]], - - [[0.]], - - [[0.]], - - [[0.]], - - [[0.]], - - [[0.]], - - [[0.]], - - [[0.]]]), scale=0.8716348333785895, shift=array([8.71634833])), candidate_index=27, candidate_x=array([8.71592273]), index=0, x=array([8.71634833]), fval=0.5809829529263782, rho=-1.4201327974934779, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([ 0, 25, 26]), old_indices_discarded=array([], dtype=int64), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([8.71634833]), radius=0.0002128014729928197, bounds=Bounds(lower=array([2.]), upper=array([20.]))), model_indices=array([ 0, 26, 27]), model=ScalarModel(intercept=0.580989949385854, linear_terms=array([1.72599501e-06]), square_terms=array([[4.88198337e-09]]), scale=0.0002128014729928197, shift=array([8.71634833])), vector_model=VectorModel(intercepts=array([ 0.05724941, 0.13067239, 0.15239639, 0.19379346, 0.21974974, - 0.23556449, 0.2356215 , 0.0872458 , -0.05175871, -0.04146828, - -0.38600975, -0.40563272, -0.07724253, -0.05219307, -0.04259932, - -0.04528749, -0.04943203]), linear_terms=array([[0.], - [0.], - [0.], - [0.], - [0.], - [0.], - [0.], - [0.], - [0.], - [0.], - [0.], - [0.], - [0.], - [0.], - [0.], - [0.], - [0.]]), square_terms=array([[[0.]], - - [[0.]], - - [[0.]], - - [[0.]], - - [[0.]], - - [[0.]], - - [[0.]], - - [[0.]], - - [[0.]], - - [[0.]], - - [[0.]], - - [[0.]], - - [[0.]], - - [[0.]], - - [[0.]], - - [[0.]], - - [[0.]]]), scale=0.8716348333785895, shift=array([8.71634833])), candidate_index=28, candidate_x=array([8.71613553]), index=0, x=array([8.71634833]), fval=0.5809829529263782, rho=-2.24757069052044, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([ 0, 26, 27]), old_indices_discarded=array([], dtype=int64), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([8.71634833]), radius=0.00010640073649640985, bounds=Bounds(lower=array([2.]), upper=array([20.]))), model_indices=array([ 0, 27, 28]), model=ScalarModel(intercept=0.5809828752663786, linear_terms=array([-2.05209442e-06]), square_terms=array([[1.30245009e-09]]), scale=0.00010640073649640985, shift=array([8.71634833])), vector_model=VectorModel(intercepts=array([ 0.05724941, 0.13067239, 0.15239639, 0.19379346, 0.21974974, - 0.23556449, 0.2356215 , 0.0872458 , -0.05175871, -0.04146828, - -0.38600975, -0.40563272, -0.07724253, -0.05219307, -0.04259932, - -0.04528749, -0.04943203]), linear_terms=array([[0.], - [0.], - [0.], - [0.], - [0.], - [0.], - [0.], - [0.], - [0.], - [0.], - [0.], - [0.], - [0.], - [0.], - [0.], - [0.], - [0.]]), square_terms=array([[[0.]], - - [[0.]], - - [[0.]], - - [[0.]], - - [[0.]], - - [[0.]], - - [[0.]], - - [[0.]], - - [[0.]], - - [[0.]], - - [[0.]], - - [[0.]], - - [[0.]], - - [[0.]], - - [[0.]], - - [[0.]], - - [[0.]]]), scale=0.8716348333785895, shift=array([8.71634833])), candidate_index=29, candidate_x=array([8.71645473]), index=0, x=array([8.71634833]), fval=0.5809829529263782, rho=-0.37426873931064897, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([ 0, 27, 28]), old_indices_discarded=array([], dtype=int64), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([8.71634833]), radius=5.3200368248204925e-05, bounds=Bounds(lower=array([2.]), upper=array([20.]))), model_indices=array([ 0, 28, 29]), model=ScalarModel(intercept=0.580984111264387, linear_terms=array([-5.81699654e-07]), square_terms=array([[3.18428398e-10]]), scale=5.3200368248204925e-05, shift=array([8.71634833])), vector_model=VectorModel(intercepts=array([ 0.05724941, 0.13067239, 0.15239639, 0.19379346, 0.21974974, - 0.23556449, 0.2356215 , 0.0872458 , -0.05175871, -0.04146828, - -0.38600975, -0.40563272, -0.07724253, -0.05219307, -0.04259932, - -0.04528749, -0.04943203]), linear_terms=array([[0.], - [0.], - [0.], - [0.], - [0.], - [0.], - [0.], - [0.], - [0.], - [0.], - [0.], - [0.], - [0.], - [0.], - [0.], - [0.], - [0.]]), square_terms=array([[[0.]], - - [[0.]], - - [[0.]], - - [[0.]], - - [[0.]], - - [[0.]], - - [[0.]], - - [[0.]], - - [[0.]], - - [[0.]], - - [[0.]], - - [[0.]], - - [[0.]], - - [[0.]], - - [[0.]], - - [[0.]], - - [[0.]]]), scale=0.8716348333785895, shift=array([8.71634833])), candidate_index=30, candidate_x=array([8.71640153]), index=0, x=array([8.71634833]), fval=0.5809829529263782, rho=-0.604210460646522, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([ 0, 28, 29]), old_indices_discarded=array([], dtype=int64), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([8.71634833]), radius=2.6600184124102462e-05, bounds=Bounds(lower=array([2.]), upper=array([20.]))), model_indices=array([ 0, 29, 30]), model=ScalarModel(intercept=0.5809829421366142, linear_terms=array([1.9179464e-07]), square_terms=array([[7.65325303e-11]]), scale=2.6600184124102462e-05, shift=array([8.71634833])), vector_model=VectorModel(intercepts=array([ 0.05724941, 0.13067239, 0.15239639, 0.19379346, 0.21974974, - 0.23556449, 0.2356215 , 0.0872458 , -0.05175871, -0.04146828, - -0.38600975, -0.40563272, -0.07724253, -0.05219307, -0.04259932, - -0.04528749, -0.04943203]), linear_terms=array([[0.], - [0.], - [0.], - [0.], - [0.], - [0.], - [0.], - [0.], - [0.], - [0.], - [0.], - [0.], - [0.], - [0.], - [0.], - [0.], - [0.]]), square_terms=array([[[0.]], - - [[0.]], - - [[0.]], - - [[0.]], - - [[0.]], - - [[0.]], - - [[0.]], - - [[0.]], - - [[0.]], - - [[0.]], - - [[0.]], - - [[0.]], - - [[0.]], - - [[0.]], - - [[0.]], - - [[0.]], - - [[0.]]]), scale=0.8716348333785895, shift=array([8.71634833])), candidate_index=31, candidate_x=array([8.71632173]), index=0, x=array([8.71634833]), fval=0.5809829529263782, rho=-1.2017101678755195, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([ 0, 29, 30]), old_indices_discarded=array([], dtype=int64), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([8.71634833]), radius=1.3300092062051231e-05, bounds=Bounds(lower=array([2.]), upper=array([20.]))), model_indices=array([ 0, 30, 31]), model=ScalarModel(intercept=0.5809831269288415, linear_terms=array([2.98038573e-08]), square_terms=array([[1.93209568e-11]]), scale=1.3300092062051231e-05, shift=array([8.71634833])), vector_model=VectorModel(intercepts=array([ 0.05724941, 0.13067239, 0.15239639, 0.19379346, 0.21974974, - 0.23556449, 0.2356215 , 0.0872458 , -0.05175871, -0.04146828, - -0.38600975, -0.40563272, -0.07724253, -0.05219307, -0.04259932, - -0.04528749, -0.04943203]), linear_terms=array([[0.], - [0.], - [0.], - [0.], - [0.], - [0.], - [0.], - [0.], - [0.], - [0.], - [0.], - [0.], - [0.], - [0.], - [0.], - [0.], - [0.]]), square_terms=array([[[0.]], - - [[0.]], - - [[0.]], - - [[0.]], - - [[0.]], - - [[0.]], - - [[0.]], - - [[0.]], - - [[0.]], - - [[0.]], - - [[0.]], - - [[0.]], - - [[0.]], - - [[0.]], - - [[0.]], - - [[0.]], - - [[0.]]]), scale=0.8716348333785895, shift=array([8.71634833])), candidate_index=32, candidate_x=array([8.71633503]), index=0, x=array([8.71634833]), fval=0.5809829529263782, rho=-0.456714199690376, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([ 0, 30, 31]), old_indices_discarded=array([], dtype=int64), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([8.71634833]), radius=6.650046031025616e-06, bounds=Bounds(lower=array([2.]), upper=array([20.]))), model_indices=array([ 0, 31, 32]), model=ScalarModel(intercept=0.5809829190596839, linear_terms=array([-5.75988436e-08]), square_terms=array([[5.00246283e-12]]), scale=6.650046031025616e-06, shift=array([8.71634833])), vector_model=VectorModel(intercepts=array([ 0.05724941, 0.13067239, 0.15239639, 0.19379346, 0.21974974, - 0.23556449, 0.2356215 , 0.0872458 , -0.05175871, -0.04146828, - -0.38600975, -0.40563272, -0.07724253, -0.05219307, -0.04259932, - -0.04528749, -0.04943203]), linear_terms=array([[0.], - [0.], - [0.], - [0.], - [0.], - [0.], - [0.], - [0.], - [0.], - [0.], - [0.], - [0.], - [0.], - [0.], - [0.], - [0.], - [0.]]), square_terms=array([[[0.]], - - [[0.]], - - [[0.]], - - [[0.]], - - [[0.]], - - [[0.]], - - [[0.]], - - [[0.]], - - [[0.]], - - [[0.]], - - [[0.]], - - [[0.]], - - [[0.]], - - [[0.]], - - [[0.]], - - [[0.]], - - [[0.]]]), scale=0.8716348333785895, shift=array([8.71634833])), candidate_index=33, candidate_x=array([8.71635498]), index=0, x=array([8.71634833]), fval=0.5809829529263782, rho=-0.7623046526241213, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([ 0, 31, 32]), old_indices_discarded=array([], dtype=int64), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([8.71634833]), radius=3.325023015512808e-06, bounds=Bounds(lower=array([2.]), upper=array([20.]))), model_indices=array([ 0, 32, 33]), model=ScalarModel(intercept=0.5809829746559877, linear_terms=array([3.84376872e-09]), square_terms=array([[1.20998353e-12]]), scale=3.325023015512808e-06, shift=array([8.71634833])), vector_model=VectorModel(intercepts=array([ 0.05724941, 0.13067239, 0.15239639, 0.19379346, 0.21974974, - 0.23556449, 0.2356215 , 0.0872458 , -0.05175871, -0.04146828, - -0.38600975, -0.40563272, -0.07724253, -0.05219307, -0.04259932, - -0.04528749, -0.04943203]), linear_terms=array([[0.], - [0.], - [0.], - [0.], - [0.], - [0.], - [0.], - [0.], - [0.], - [0.], - [0.], - [0.], - [0.], - [0.], - [0.], - [0.], - [0.]]), square_terms=array([[[0.]], - - [[0.]], - - [[0.]], - - [[0.]], - - [[0.]], - - [[0.]], - - [[0.]], - - [[0.]], - - [[0.]], - - [[0.]], - - [[0.]], - - [[0.]], - - [[0.]], - - [[0.]], - - [[0.]], - - [[0.]], - - [[0.]]]), scale=0.8716348333785895, shift=array([8.71634833])), candidate_index=34, candidate_x=array([8.71634501]), index=34, x=array([8.71634501]), fval=0.5809829309750734, rho=5.711779695149159, accepted=True, new_indices=array([], dtype=int64), old_indices_used=array([ 0, 32, 33]), old_indices_discarded=array([], dtype=int64), step_length=3.3250230160319916e-06, relative_step_length=1.0000000001561444, n_evals_per_point=1, n_evals_acceptance=1)], 'message': 'Relative gradient norm smaller than tolerance.', 'tranquilo_history': History for least_squares function with 35 entries., 'history': {'params': [{'CRRA': 8.716348333785895}, {'CRRA': 7.844713500407305}, {'CRRA': 9.587983167164484}, {'CRRA': 7.844713500407305}, {'CRRA': 7.844713500407305}, {'CRRA': 9.587983167164484}, {'CRRA': 7.844713500407305}, {'CRRA': 7.844713500407305}, {'CRRA': 9.587983167164484}, {'CRRA': 7.844713500407305}, {'CRRA': 9.587983167164484}, {'CRRA': 7.844713500407305}, {'CRRA': 9.587983167164484}, {'CRRA': 7.844713500407305}, {'CRRA': 8.73971363306202}, {'CRRA': 8.2805309170966}, {'CRRA': 8.722786945774285}, {'CRRA': 8.934257042130543}, {'CRRA': 8.680629898921989}, {'CRRA': 8.704919617664325}, {'CRRA': 8.722256879041424}, {'CRRA': 8.713060012226341}, {'CRRA': 8.702729039514354}, {'CRRA': 8.723157980921664}, {'CRRA': 8.71975315735378}, {'CRRA': 8.718050745569837}, {'CRRA': 8.717199539677866}, {'CRRA': 8.715922730839909}, {'CRRA': 8.716135532312903}, {'CRRA': 8.716454734522392}, {'CRRA': 8.716401534154143}, {'CRRA': 8.71632173360177}, {'CRRA': 8.716335033693833}, {'CRRA': 8.716354983831925}, {'CRRA': 8.716345008762879}], 'criterion': [0.5809829529263784, 0.6215225605118492, 0.616398761646436, 0.6215225605118492, 0.6215225605118492, 0.616398761646436, 0.6215225605118492, 0.6215225605118492, 0.616398761646436, 0.6215225605118492, 0.616398761646436, 0.6215225605118492, 0.616398761646436, 0.6215225605118492, 0.5812368523248607, 0.5910589793661437, 0.581000020955638, 0.5834925076553559, 0.5811816170500297, 0.5810735507484359, 0.5809932748829817, 0.5810277694582143, 0.5810794571175792, 0.5810061927319683, 0.5810024456983157, 0.5810062954215335, 0.5809992243680815, 0.5809911717283618, 0.5809868267358838, 0.5809837207174353, 0.5809833042991954, 0.580983183361962, 0.580982966533811, 0.580982996832338, 0.5809829309750735], 'runtime': [0.0, 3.8568142960029945, 4.11743933300022, 4.373802340000111, 4.6027023880014895, 4.945095448001666, 5.257756480001262, 5.505722768000851, 5.731880481002008, 6.070771706003143, 6.2871199030014395, 6.552499433000776, 6.807547802000045, 18.16403710099985, 19.635794812002132, 21.11454787200273, 22.568926558000385, 24.026774695001222, 25.597418042001664, 27.083524646001024, 28.611894326000765, 30.128650472001027, 31.639469095000095, 33.12961519900273, 34.73270601100012, 36.20504977500241, 37.66801647700049, 39.144029448001675, 40.61999973700222, 42.19290338600331, 43.67094396900211, 45.17842763700173, 46.709763128001214, 48.223182736001036, 49.70291212600205], 'batches': [0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23]}, 'multistart_info': {...}}], 'exploration_sample': array([[ 8.71634833], - [ 8.75 ], - [11. ], - [ 6.5 ], - [13.25 ], - [ 5.375 ], - [14.375 ], - [15.5 ], - [ 4.25 ], - [17.75 ]]), 'exploration_results': array([0.58098295, 0.58135073, 0.79603543, 0.87638025, 1.31383932, - 1.34510497, 1.64731945, 2.01799056, 2.20855304, 2.8319413 ])}}" + [[0.]]]), scale=0.9252398949005969, shift=array([9.25239895])), candidate_index=30, candidate_x=array([9.25234248]), index=30, x=array([9.25234248]), fval=0.6423583236273489, rho=0.2312020963811631, accepted=True, new_indices=array([], dtype=int64), old_indices_used=array([ 0, 28, 29]), old_indices_discarded=array([], dtype=int64), step_length=5.647216155324486e-05, relative_step_length=0.9999999999867785, n_evals_per_point=1, n_evals_acceptance=1)], 'message': 'Absolute criterion change smaller than tolerance.', 'tranquilo_history': History for least_squares function with 31 entries., 'history': {'params': [{'CRRA': 9.252398949005968}, {'CRRA': 8.32715905410537}, {'CRRA': 10.177638843906566}, {'CRRA': 8.32715905410537}, {'CRRA': 8.32715905410537}, {'CRRA': 10.177638843906566}, {'CRRA': 8.32715905410537}, {'CRRA': 8.32715905410537}, {'CRRA': 10.177638843906566}, {'CRRA': 8.32715905410537}, {'CRRA': 10.177638843906566}, {'CRRA': 8.32715905410537}, {'CRRA': 10.177638843906566}, {'CRRA': 8.32715905410537}, {'CRRA': 9.250471173613674}, {'CRRA': 8.78977900155567}, {'CRRA': 9.23120907149584}, {'CRRA': 9.238513428928496}, {'CRRA': 9.191477678194621}, {'CRRA': 9.310226442437255}, {'CRRA': 9.25067493918715}, {'CRRA': 9.250726122006544}, {'CRRA': 9.249064681404075}, {'CRRA': 9.253920740493475}, {'CRRA': 9.256013167345424}, {'CRRA': 9.254206058175695}, {'CRRA': 9.251495394421104}, {'CRRA': 9.251947171713537}, {'CRRA': 9.252624837652185}, {'CRRA': 9.252511893329077}, {'CRRA': 9.252342476844415}], 'criterion': [0.6423583869781233, 0.6726932800669494, 0.6724707147424193, 0.6726932800669494, 0.6726932800669494, 0.6724707147424193, 0.6726932800669494, 0.6726932800669494, 0.6724707147424193, 0.6726932800669494, 0.6724707147424193, 0.6726932800669494, 0.6724707147424193, 0.6726932800669494, 0.6423691326265972, 0.6492941434834837, 0.6423764030742694, 0.6423752558032019, 0.6425217924878079, 0.6425146733526689, 0.6423685181986346, 0.6423683643642798, 0.6423801867774521, 0.6423693080646328, 0.6423866017619942, 0.6423727772903676, 0.6423636962874574, 0.6423598024158105, 0.6423594854558661, 0.6423587872768556, 0.6423583236273489], 'runtime': [0.0, 3.3926007600093726, 3.6385346090246458, 3.8182367410045117, 4.073105274001136, 4.283541666023666, 4.494341033016099, 4.736494988028426, 4.96336116202292, 5.179848953004694, 5.533184596017236, 5.69610069601913, 5.942016065004282, 21.336237280018395, 22.686877734027803, 24.069558680028422, 25.560004253027728, 26.859713567013387, 28.15134494501399, 29.419637827028055, 30.714213685016148, 32.14109974101302, 33.454856365016894, 34.775876878004055, 36.0627207980142, 37.38446952102822, 38.785011164000025, 40.11220667202724, 41.4234611930151, 42.74076091501047, 44.06118227602565], 'batches': [0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19]}, 'multistart_info': {...}}], 'exploration_sample': array([[ 9.25239895], + [ 8.1875 ], + [10.55 ], + [12.9125 ], + [ 5.825 ], + [14.09375 ], + [15.275 ], + [ 4.64375 ], + [17.6375 ], + [ 3.4625 ]]), 'exploration_results': array([0.64235839, 0.6831279 , 0.69939713, 1.02360977, 1.18227674, + 1.26376333, 1.54278366, 1.78141341, 2.1808234 , 2.89794431])}}" diff --git a/content/tables/TRP/WarmGlowPortfolio_estimate_results.csv b/content/tables/TRP/WarmGlowPortfolio_estimate_results.csv index 5d93dc9..4c88d3b 100644 --- a/content/tables/TRP/WarmGlowPortfolio_estimate_results.csv +++ b/content/tables/TRP/WarmGlowPortfolio_estimate_results.csv @@ -1,11 +1,11 @@ -CRRA,8.71634411092518 -BeqShift,26.2099921551288 -BeqFac,43.5442268893279 -time_to_estimate,231.98215889930725 -params,"{'CRRA': 8.71634411092518, 'BeqShift': 26.2099921551288, 'BeqFac': 43.5442268893279}" -criterion,0.580982924948752 -start_criterion,0.5848633967947563 -start_params,"{'CRRA': 8.716360103468407, 'BeqShift': 26.210013017331125, 'BeqFac': 43.544357345708256}" +CRRA,9.206778216146489 +BeqShift,50.64405071849033 +BeqFac,26.1368726540768 +time_to_estimate,189.59267950057983 +params,"{'CRRA': 9.206778216146489, 'BeqShift': 50.64405071849033, 'BeqFac': 26.1368726540768}" +criterion,0.6411981580830574 +start_criterion,0.6327697843473623 +start_params,"{'CRRA': 9.206831729527266, 'BeqShift': 51.48987537348443, 'BeqFac': 25.99186716077577}" algorithm,multistart_tranquilo_ls direction,minimize n_free,3 @@ -14,19 +14,19 @@ success, n_criterion_evaluations, n_derivative_evaluations, n_iterations, -history,"{'params': [{'CRRA': 8.716360103468407, 'BeqShift': 26.210013017331125, 'BeqFac': 43.544357345708256}, {'CRRA': 9.932657005357095, 'BeqShift': 28.39374194086523, 'BeqFac': 39.97881946181417}, {'CRRA': 5.918243061415689, 'BeqShift': 28.24758428370863, 'BeqFac': 40.90239691452949}, {'CRRA': 5.015808790423334, 'BeqShift': 28.110626722137255, 'BeqFac': 44.83070803316905}, {'CRRA': 8.300300428061735, 'BeqShift': 21.875576039056437, 'BeqFac': 43.51864753487957}, {'CRRA': 8.064756587407645, 'BeqShift': 24.587354418521986, 'BeqFac': 47.53227691561879}, {'CRRA': 4.883363295674027, 'BeqShift': 24.174800468994693, 'BeqFac': 43.900946634722075}, {'CRRA': 10.66294571363579, 'BeqShift': 30.090341510755252, 'BeqFac': 43.20529125787657}, {'CRRA': 12.192787024479657, 'BeqShift': 25.08882139484883, 'BeqFac': 41.17402070821325}, {'CRRA': 8.139678425612232, 'BeqShift': 29.192318662246315, 'BeqFac': 46.6643576420607}, {'CRRA': 7.6526612313494695, 'BeqShift': 24.127560137239733, 'BeqFac': 39.871069271222495}, {'CRRA': 11.838688260695706, 'BeqShift': 23.50144007371468, 'BeqFac': 44.913959497503406}, {'CRRA': 12.084121496303712, 'BeqShift': 27.363721387937847, 'BeqFac': 46.051995829028236}, {'CRRA': 8.933510052757214, 'BeqShift': 28.89771693179309, 'BeqFac': 47.01135568172765}, {'CRRA': 8.902197657290548, 'BeqShift': 27.26532816290852, 'BeqFac': 45.51595825166366}, {'CRRA': 8.789531280592655, 'BeqShift': 27.24792252348393, 'BeqFac': 43.87862901543856}, {'CRRA': 8.438898172182274, 'BeqShift': 25.74203409793529, 'BeqFac': 43.52768520458141}, {'CRRA': 8.95452321895985, 'BeqShift': 25.723672513520988, 'BeqFac': 43.59929910919278}, {'CRRA': 9.193380580191135, 'BeqShift': 25.950208406861826, 'BeqFac': 43.57929130866401}, {'CRRA': 8.759379321032199, 'BeqShift': 26.74189493613109, 'BeqFac': 43.43703389079022}, {'CRRA': 9.121893970098535, 'BeqShift': 26.289739056327704, 'BeqFac': 43.190163339090965}, {'CRRA': 8.42489763807857, 'BeqShift': 26.66821912606228, 'BeqFac': 43.58129169005073}, {'CRRA': 9.222551897489526, 'BeqShift': 26.408476324513323, 'BeqFac': 43.51887135014868}, {'CRRA': 8.220249156584092, 'BeqShift': 26.23216760824491, 'BeqFac': 43.321533524978356}, {'CRRA': 8.275934945026309, 'BeqShift': 26.526907387440193, 'BeqFac': 43.50110239678783}, {'CRRA': 8.971989511020418, 'BeqShift': 25.94797311169433, 'BeqFac': 43.14154715908167}, {'CRRA': 8.879291795207399, 'BeqShift': 26.701627021873662, 'BeqFac': 43.37691694745742}, {'CRRA': 8.339587636467582, 'BeqShift': 25.97701041352158, 'BeqFac': 43.228098516061145}, {'CRRA': 8.721542494966268, 'BeqShift': 25.667491313784154, 'BeqFac': 43.50056309988404}, {'CRRA': 8.72148001415611, 'BeqShift': 26.49966574129904, 'BeqFac': 43.48319190238889}, {'CRRA': 8.719961249267806, 'BeqShift': 26.086503929719097, 'BeqFac': 43.60192377476015}, {'CRRA': 8.70227014372693, 'BeqShift': 26.19502754258787, 'BeqFac': 43.60921168993903}, {'CRRA': 8.746253639842156, 'BeqShift': 26.268638946237054, 'BeqFac': 43.527078621004456}, {'CRRA': 8.735825068994972, 'BeqShift': 26.22020576804663, 'BeqFac': 43.479964796959955}, {'CRRA': 8.702275571141982, 'BeqShift': 26.15705518265819, 'BeqFac': 43.50403029423779}, {'CRRA': 8.66964142550509, 'BeqShift': 26.21832950346317, 'BeqFac': 43.49559897645562}, {'CRRA': 8.760054988864033, 'BeqShift': 26.182468946612165, 'BeqFac': 43.588643444462754}, {'CRRA': 8.656722450025475, 'BeqShift': 26.225411621344165, 'BeqFac': 43.57326081731067}, {'CRRA': 8.666897961093134, 'BeqShift': 26.164166515025016, 'BeqFac': 43.55334467469664}, {'CRRA': 8.757696064842552, 'BeqShift': 26.1604710737382, 'BeqFac': 43.522767729993475}, {'CRRA': 8.683807002439183, 'BeqShift': 26.269054953742927, 'BeqFac': 43.53521826793601}, {'CRRA': 8.731121407792553, 'BeqShift': 26.25431509007844, 'BeqFac': 43.59384075332478}, {'CRRA': 8.783544769619962, 'BeqShift': 26.220590062049666, 'BeqFac': 43.54248007547535}, {'CRRA': 8.709865116042218, 'BeqShift': 26.24896623007267, 'BeqFac': 43.6000552444956}, {'CRRA': 8.71117159923056, 'BeqShift': 26.241718296795003, 'BeqFac': 43.55620009421021}, {'CRRA': 8.71370725364789, 'BeqShift': 26.225630440183046, 'BeqFac': 43.551033485324}, {'CRRA': 8.72246703454562, 'BeqShift': 26.211077986668773, 'BeqFac': 43.550179899251106}, {'CRRA': 8.721321184614803, 'BeqShift': 26.214134204244186, 'BeqFac': 43.53881348523763}, {'CRRA': 8.721469232395883, 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50.306263335998665, 50.53438860499955, 50.74307388899979, 50.96201847699922, 51.216817012998945, 51.44749346900062, 51.67675439700179, 51.945428234001156, 52.18559794600151, 52.43835590600065, 54.163996731000225], 'batches': [0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 3, 4, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 6, 7, 8, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 10, 11, 12, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 14, 15, 16, 17, 17, 17, 17, 17, 17, 17, 17, 17, 17, 17, 17, 18, 19, 20, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 22]}" -convergence_report, -multistart_info,"{'start_parameters': [{'CRRA': 8.716360103468407, 'BeqShift': 26.210013017331125, 'BeqFac': 43.544357345708256}, {'CRRA': 8.730568763382836, 'BeqShift': 26.226901459993915, 'BeqFac': 43.631196839161476}, {'CRRA': 8.619299408414172, 'BeqShift': 30.632884752878972, 'BeqFac': 44.786228146351164}], 'local_optima': [Minimize with 3 free parameters terminated. +history,"{'params': [{'CRRA': 9.128106374273193, 'BeqShift': 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45.830064534694614, 'BeqFac': 25.437581737917117}, {'CRRA': 12.907750238863407, 'BeqShift': 50.164708878465945, 'BeqFac': 26.714801688023883}, {'CRRA': 9.308015155295243, 'BeqShift': 50.37166272775331, 'BeqFac': 28.558762945887366}, {'CRRA': 9.26556410189128, 'BeqShift': 50.1466458784944, 'BeqFac': 26.074204341762798}, {'CRRA': 9.306771879635068, 'BeqShift': 49.57690311934757, 'BeqFac': 24.92860973348605}, {'CRRA': 9.175898510068395, 'BeqShift': 50.75145652974846, 'BeqFac': 25.98737882491696}, {'CRRA': 9.263797896208295, 'BeqShift': 50.372350451393935, 'BeqFac': 24.823779893176457}, {'CRRA': 9.154459573389804, 'BeqShift': 51.29445206167982, 'BeqFac': 26.26698771558419}, {'CRRA': 9.202041402977615, 'BeqShift': 50.559384394363455, 'BeqFac': 26.260409837048027}, {'CRRA': 9.147471035061725, 'BeqShift': 50.44050518128637, 'BeqFac': 26.85791599392265}, {'CRRA': 9.224646740112595, 'BeqShift': 50.85076502735223, 'BeqFac': 26.351855097884435}, {'CRRA': 9.21160542953121, 'BeqShift': 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50.64530232098181, 'BeqFac': 26.136893913002943}, {'CRRA': 9.2065434947578, 'BeqShift': 50.64418718230116, 'BeqFac': 26.13674914949305}, {'CRRA': 9.20661679269972, 'BeqShift': 50.643932653337664, 'BeqFac': 26.137283679150954}, {'CRRA': 9.2065595869972, 'BeqShift': 50.644783362471536, 'BeqFac': 26.136735373390117}, {'CRRA': 9.206944767351247, 'BeqShift': 50.643965368292854, 'BeqFac': 26.13636749731083}, {'CRRA': 9.206226751341177, 'BeqShift': 50.644175383761606, 'BeqFac': 26.136243764551427}, {'CRRA': 9.206139999933411, 'BeqShift': 50.64434589304829, 'BeqFac': 26.136339414991006}, {'CRRA': 9.20692991957421, 'BeqShift': 50.64378902036765, 'BeqFac': 26.13696828979672}, {'CRRA': 9.206030525524028, 'BeqShift': 50.6444124709626, 'BeqFac': 26.13695405708431}, {'CRRA': 9.206033510436992, 'BeqShift': 50.64400644035142, 'BeqFac': 26.13700040210868}, {'CRRA': 9.206910984777197, 'BeqShift': 50.64373643105872, 'BeqFac': 26.136616281363658}, {'CRRA': 9.20619643081797, 'BeqShift': 50.644622612155665, 'BeqFac': 26.136535077074925}, {'CRRA': 9.20642878297644, 'BeqShift': 50.6444960576583, 'BeqFac': 26.137246459012054}, {'CRRA': 9.207127002456316, 'BeqShift': 50.64430039244862, 'BeqFac': 26.1367999605648}, {'CRRA': 9.207114719797469, 'BeqShift': 50.64419857360247, 'BeqFac': 26.13692076455369}, {'CRRA': 9.206778216146489, 'BeqShift': 50.64405071849033, 'BeqFac': 26.1368726540768}], 'criterion': [0.6419131545898231, 0.6992405625490731, 1.1240845476970416, 1.577376990569092, 0.6524642769901355, 0.6664887878432892, 1.6647770568284477, 0.7958273217414884, 1.1577117413885285, 0.6612605763524525, 0.7056652645879914, 1.051463755129049, 1.1229714048823773, 0.6417128790724664, 0.6415610317693744, 0.6416973103739135, 0.64141783218841, 0.6415718165830668, 0.6414915855271336, 0.6412798714314748, 0.6416690245253375, 0.6413838490259491, 0.6412533792921618, 0.6413209357438362, 0.6412698132156118, 0.6414892120617004, 0.641391882855679, 0.6412912681201268, 0.6412600044422002, 0.6414014712692039, 0.641212422800454, 0.64138920463213, 0.6412599767231901, 0.6413894182130144, 0.641240011408127, 0.6412958845272176, 0.6412931073773732, 0.6412860311722518, 0.6412856091678842, 0.641299080615386, 0.6412654340898993, 0.6412040518376516, 0.6412798376316433, 0.6412586069868993, 0.6412003819983737, 0.6411989063826031, 0.641198632121119, 0.641198805868094, 0.6412003147825824, 0.6412028895752717, 0.6412042395231233, 0.6412001224290423, 0.641205979879279, 0.6412059242494071, 0.6411998771542384, 0.6412033613190102, 0.6411998007566294, 0.6412026671203108, 0.6412025111397647, 0.6411981580830574], 'runtime': [0.0, 1.6225000619888306, 1.8208623389946297, 2.0214831299963407, 2.3780758359935135, 2.6056774169846904, 2.8214367309992667, 3.026432433980517, 3.247528671985492, 3.475298994977493, 3.716090304980753, 3.926765499985777, 4.1696615399851, 5.700570738990791, 7.090572686982341, 8.46942359500099, 9.826952342991717, 11.1874410599994, 12.670953125983942, 14.073503133986378, 15.415775064000627, 16.777498332987307, 18.136912931979168, 19.44478028998128, 20.9249066929915, 22.26256391199422, 23.626468014990678, 25.251971355988644, 25.453611488977913, 25.659738533984637, 25.865622649987927, 26.112973237002734, 26.36346254197997, 26.55055605797679, 26.754232481995132, 26.958369220985333, 27.18434452699148, 27.420230353978695, 27.644893939985195, 29.20647358399583, 30.686982325976714, 32.02958239999134, 33.3786810519814, 34.71376580098877, 36.05778275799821, 37.38048776300275, 39.191983733995585, 39.40957244997844, 39.614045912981965, 39.824004255002365, 40.0257615079754, 40.23395056297886, 40.45599366599345, 40.66358802097966, 40.90082527400227, 41.12791417900007, 41.331096677982714, 41.55513457299094, 43.058433758997126, 44.375435253983596], 'batches': [0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 17, 18, 19, 20, 21, 22, 23, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 25, 26]}" +convergence_report,"{'one_step': {'relative_criterion_change': 3.3680601244564846e-08, 'relative_params_change': 0.15745854181285046, 'absolute_criterion_change': 2.159593948114491e-08, 'absolute_params_change': 5.969365090497884}, 'five_steps': {'relative_criterion_change': 8.826656507099289e-07, 'relative_params_change': 0.15745854181285046, 'absolute_criterion_change': 5.659635894383896e-07, 'absolute_params_change': 5.969365090497884}}" +multistart_info,"{'start_parameters': [{'CRRA': 9.206831729527266, 'BeqShift': 51.48987537348444, 'BeqFac': 25.99186716077577}, {'CRRA': 9.275122078746548, 'BeqShift': 46.36962222316765, 'BeqFac': 22.931039835503583}, {'CRRA': 9.128106374273193, 'BeqShift': 48.86990017445058, 'BeqFac': 23.900475106498696}], 'local_optima': [Minimize with 3 free parameters terminated. The tranquilo_ls algorithm reported: Absolute criterion change smaller than tolerance. Independent of the convergence criteria used by tranquilo_ls, the strength of convergence can be assessed by the following criteria: one_step five_steps -relative_criterion_change 1.135e-07* 1.817e-07* -relative_params_change 4.612e-06* 5.873e-06* -absolute_criterion_change 6.594e-08* 1.056e-07* -absolute_params_change 0.0001211 0.0002164 +relative_criterion_change 7.038e-07* 7.038e-07* +relative_params_change 4.652e-05 4.652e-05 +absolute_criterion_change 4.513e-07* 4.513e-07* +absolute_params_change 0.001257 0.001257 (***: change <= 1e-10, **: change <= 1e-8, *: change <= 1e-5. Change refers to a change between accepted steps. The first column only considers the last step. The second column considers the last five steps.), Minimize with 3 free parameters terminated. @@ -35,10 +35,10 @@ The tranquilo_ls algorithm reported: Absolute criterion change smaller than tole Independent of the convergence criteria used by tranquilo_ls, the strength of convergence can be assessed by the following criteria: one_step five_steps -relative_criterion_change 3.209e-09** 0.0001263 -relative_params_change 9.295e-08* 0.0148 -absolute_criterion_change 1.864e-09** 7.341e-05 -absolute_params_change 2.755e-06* 0.5454 +relative_criterion_change 7.979e-07* 3.031e-05 +relative_params_change 3.723e-05 0.0001754 +absolute_criterion_change 5.116e-07* 1.944e-05 +absolute_params_change 0.001147 0.001754 (***: change <= 1e-10, **: change <= 1e-8, *: change <= 1e-5. Change refers to a change between accepted steps. The first column only considers the last step. The second column considers the last five steps.), Minimize with 3 free parameters terminated. @@ -47,23 +47,23 @@ The tranquilo_ls algorithm reported: Absolute criterion change smaller than tole Independent of the convergence criteria used by tranquilo_ls, the strength of convergence can be assessed by the following criteria: one_step five_steps -relative_criterion_change 9.151e-07* 3.044e-05 -relative_params_change 5.519e-05 0.0005307 -absolute_criterion_change 5.316e-07* 1.768e-05 -absolute_params_change 0.002224 0.0125 +relative_criterion_change 7.393e-07* 2.225e-05 +relative_params_change 2.367e-05 0.0004532 +absolute_criterion_change 4.74e-07* 1.426e-05 +absolute_params_change 0.0004571 0.01895 -(***: change <= 1e-10, **: change <= 1e-8, *: change <= 1e-5. Change refers to a change between accepted steps. The first column only considers the last step. The second column considers the last five steps.)], 'exploration_sample': [{'CRRA': 8.716360103468407, 'BeqShift': 26.210013017331125, 'BeqFac': 43.544357345708256}, {'CRRA': 8.75, 'BeqShift': 26.25, 'BeqFac': 43.75}, {'CRRA': 8.1875, 'BeqShift': 50.3125, 'BeqFac': 50.3125}, {'CRRA': 9.3125, 'BeqShift': 63.4375, 'BeqFac': 19.6875}, {'CRRA': 9.875, 'BeqShift': 39.375, 'BeqFac': 13.125}, {'CRRA': 7.625, 'BeqShift': 13.125, 'BeqFac': 21.875}, {'CRRA': 10.4375, 'BeqShift': 6.5625, 'BeqFac': 59.0625}, {'CRRA': 7.0625, 'BeqShift': 19.6875, 'BeqFac': 10.9375}, {'CRRA': 11.0, 'BeqShift': 35.0, 'BeqFac': 35.0}, {'CRRA': 6.5, 'BeqShift': 52.5, 'BeqFac': 52.5}, {'CRRA': 12.125, 'BeqShift': 30.625, 'BeqFac': 4.375}, {'CRRA': 5.9375, 'BeqShift': 59.0625, 'BeqFac': 6.5625}, {'CRRA': 12.6875, 'BeqShift': 67.8125, 'BeqFac': 67.8125}, {'CRRA': 13.25, 'BeqShift': 8.75, 'BeqFac': 61.25}, {'CRRA': 5.375, 'BeqShift': 21.875, 'BeqFac': 65.625}, {'CRRA': 13.8125, 'BeqShift': 45.9375, 'BeqFac': 2.1875}, {'CRRA': 14.375, 'BeqShift': 56.875, 'BeqFac': 30.625}, {'CRRA': 4.8125, 'BeqShift': 10.9375, 'BeqFac': 37.1875}, {'CRRA': 14.9375, 'BeqShift': 24.0625, 'BeqFac': 41.5625}, {'CRRA': 15.5, 'BeqShift': 17.5, 'BeqFac': 17.5}, {'CRRA': 4.25, 'BeqShift': 43.75, 'BeqFac': 26.25}, {'CRRA': 16.0625, 'BeqShift': 54.6875, 'BeqFac': 45.9375}, {'CRRA': 16.625, 'BeqShift': 48.125, 'BeqFac': 56.875}, {'CRRA': 17.1875, 'BeqShift': 15.3125, 'BeqFac': 15.3125}, {'CRRA': 17.75, 'BeqShift': 61.25, 'BeqFac': 8.75}, {'CRRA': 3.6875, 'BeqShift': 32.8125, 'BeqFac': 32.8125}, {'CRRA': 18.3125, 'BeqShift': 28.4375, 'BeqFac': 54.6875}, {'CRRA': 18.875, 'BeqShift': 4.375, 'BeqFac': 48.125}, {'CRRA': 19.4375, 'BeqShift': 41.5625, 'BeqFac': 24.0625}, {'CRRA': 3.125, 'BeqShift': 65.625, 'BeqFac': 39.375}], 'exploration_results': array([0.58098303, 0.58135073, 0.59596536, 0.59810812, 0.64175636, - 0.64554292, 0.70865511, 0.73685363, 0.79603543, 0.87638025, - 1.02597222, 1.07322978, 1.16326542, 1.31383946, 1.34509291, - 1.47533535, 1.64731945, 1.71236488, 1.82840862, 2.01799056, - 2.20854806, 2.21491217, 2.41653621, 2.62180443, 2.8319413 , - 2.89241208, 3.04574895, 3.26411584, 3.48627997, 3.72249175])}" -algorithm_output,"{'states': [State(trustregion=Region(center=array([ 8.7163601 , 26.21001302, 43.54435735]), radius=4.354435734570826, bounds=Bounds(lower=array([2., 0., 0.]), upper=array([20., 70., 70.]))), model_indices=[0], model=ScalarModel(intercept=0.5809830305379234, linear_terms=array([0., 0., 0.]), square_terms=array([[0., 0., 0.], +(***: change <= 1e-10, **: change <= 1e-8, *: change <= 1e-5. Change refers to a change between accepted steps. The first column only considers the last step. The second column considers the last five steps.)], 'exploration_sample': [{'CRRA': 9.206831729527266, 'BeqShift': 51.48987537348443, 'BeqFac': 25.99186716077577}, {'CRRA': 9.368749999999999, 'BeqShift': 39.375, 'BeqFac': 18.75}, {'CRRA': 8.778125, 'BeqShift': 63.4375, 'BeqFac': 28.125}, {'CRRA': 9.959375, 'BeqShift': 6.5625, 'BeqFac': 84.375}, {'CRRA': 8.1875, 'BeqShift': 26.25, 'BeqFac': 62.5}, {'CRRA': 10.549999999999999, 'BeqShift': 35.0, 'BeqFac': 50.0}, {'CRRA': 7.596874999999999, 'BeqShift': 50.3125, 'BeqFac': 71.875}, {'CRRA': 7.00625, 'BeqShift': 13.125, 'BeqFac': 31.25}, {'CRRA': 11.73125, 'BeqShift': 30.625, 'BeqFac': 6.25}, {'CRRA': 12.321874999999999, 'BeqShift': 67.8125, 'BeqFac': 96.875}, {'CRRA': 6.415625, 'BeqShift': 19.6875, 'BeqFac': 15.625}, {'CRRA': 12.9125, 'BeqShift': 8.75, 'BeqFac': 87.5}, {'CRRA': 5.824999999999999, 'BeqShift': 52.5, 'BeqFac': 75.0}, {'CRRA': 13.503124999999999, 'BeqShift': 45.9375, 'BeqFac': 3.125}, {'CRRA': 5.234375, 'BeqShift': 59.0625, 'BeqFac': 9.375}, {'CRRA': 14.093749999999998, 'BeqShift': 56.875, 'BeqFac': 43.75}, {'CRRA': 14.684375, 'BeqShift': 24.0625, 'BeqFac': 59.375}, {'CRRA': 4.64375, 'BeqShift': 21.875, 'BeqFac': 93.75}, {'CRRA': 15.274999999999999, 'BeqShift': 17.5, 'BeqFac': 25.0}, {'CRRA': 4.053125, 'BeqShift': 10.9375, 'BeqFac': 53.125}, {'CRRA': 15.865624999999998, 'BeqShift': 54.6875, 'BeqFac': 65.625}, {'CRRA': 3.4625, 'BeqShift': 43.75, 'BeqFac': 37.5}, {'CRRA': 16.45625, 'BeqShift': 48.125, 'BeqFac': 81.25}, {'CRRA': 17.046875, 'BeqShift': 15.3125, 'BeqFac': 21.875}, {'CRRA': 2.871875, 'BeqShift': 32.8125, 'BeqFac': 46.875}, {'CRRA': 2.28125, 'BeqShift': 65.625, 'BeqFac': 56.25}, {'CRRA': 17.6375, 'BeqShift': 61.25, 'BeqFac': 12.5}, {'CRRA': 18.228125, 'BeqShift': 28.4375, 'BeqFac': 78.125}, {'CRRA': 18.81875, 'BeqShift': 4.375, 'BeqFac': 68.75}, {'CRRA': 19.409375, 'BeqShift': 41.5625, 'BeqFac': 34.375}], 'exploration_results': array([0.64119885, 0.64211564, 0.64842422, 0.66164008, 0.68191739, + 0.7044766 , 0.74714868, 0.84823283, 0.8626059 , 0.97951322, + 0.98996599, 1.12431839, 1.18221304, 1.30406645, 1.43892243, + 1.52011014, 1.78024917, 1.78131285, 2.0971452 , 2.24344059, + 2.48116605, 2.89787 , 2.94379242, 3.4976294 , 3.77080322, + 4.13701934, 4.16035282, 4.94978648, 5.89491246, 7.00125067])}" +algorithm_output,"{'states': [State(trustregion=Region(center=array([ 9.12810637, 48.86990017, 23.90047511]), radius=4.886990017445058, bounds=Bounds(lower=array([1.1, 0. , 0. ]), upper=array([ 20., 70., 100.]))), model_indices=[0], model=ScalarModel(intercept=0.6419131545898231, linear_terms=array([0., 0., 0.]), square_terms=array([[0., 0., 0.], [0., 0., 0.], - [0., 0., 0.]]), scale=4.354435734570826, shift=array([ 8.7163601 , 26.21001302, 43.54435735])), vector_model=VectorModel(intercepts=array([ 0.05724953, 0.13067265, 0.1523968 , 0.19379396, 0.21975026, - 0.23556517, 0.23562227, 0.08724666, -0.05175769, -0.04146735, - -0.38600879, -0.40563182, -0.07724305, -0.05219358, -0.04259982, - -0.04528797, -0.04943255]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.]]), scale=4.886990017445058, shift=array([ 9.12810637, 48.86990017, 23.90047511])), vector_model=VectorModel(intercepts=array([ 0.0478985 , 0.12198145, 0.14591097, 0.19026117, 0.21318417, + 0.22770334, 0.22810381, 0.06014365, -0.08704274, -0.07443179, + -0.41631926, -0.42444642, -0.1208239 , -0.09458291, -0.08510185, + -0.08890017, -0.09498552]), linear_terms=array([[0., 0., 0.], [0., 0., 0.], [0., 0., 0.], [0., 0., 0.], @@ -145,12 +145,12 @@ algorithm_output,"{'states': [State(trustregion=Region(center=array([ 8.7163601 [[0., 0., 0.], [0., 0., 0.], - [0., 0., 0.]]]), scale=4.354435734570826, shift=array([ 8.7163601 , 26.21001302, 43.54435735])), candidate_index=0, candidate_x=array([ 8.7163601 , 26.21001302, 43.54435735]), index=0, x=array([ 8.7163601 , 26.21001302, 43.54435735]), fval=0.5809830305379233, rho=nan, accepted=True, new_indices=[0], old_indices_used=[], old_indices_discarded=[], step_length=None, relative_step_length=None, n_evals_per_point=None, n_evals_acceptance=None), State(trustregion=Region(center=array([ 8.7163601 , 26.21001302, 43.54435735]), radius=4.354435734570826, bounds=Bounds(lower=array([2., 0., 0.]), upper=array([20., 70., 70.]))), model_indices=array([ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12]), model=ScalarModel(intercept=0.5494101543857126, linear_terms=array([-0.10049343, -0.00119912, -0.0013463 ]), square_terms=array([[ 2.21011540e+00, -3.46388367e-03, -9.65392550e-03], - [-3.46388367e-03, 5.33163535e-05, 9.02566112e-05], - [-9.65392550e-03, 9.02566112e-05, 1.72745213e-04]]), scale=4.354435734570826, shift=array([ 8.7163601 , 26.21001302, 43.54435735])), vector_model=VectorModel(intercepts=array([ 0.05724953, 0.13067265, 0.1523968 , 0.19379396, 0.21975026, - 0.23556517, 0.23562227, 0.08724666, -0.05175769, -0.04146735, - -0.38600879, -0.40563182, -0.07724305, -0.05219358, -0.04259982, - -0.04528797, -0.04943255]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.]]]), scale=4.886990017445058, shift=array([ 9.12810637, 48.86990017, 23.90047511])), candidate_index=0, candidate_x=array([ 9.12810637, 48.86990017, 23.90047511]), index=0, x=array([ 9.12810637, 48.86990017, 23.90047511]), fval=0.6419131545898232, rho=nan, accepted=True, new_indices=[0], old_indices_used=[], old_indices_discarded=[], step_length=None, relative_step_length=None, n_evals_per_point=None, n_evals_acceptance=None), State(trustregion=Region(center=array([ 9.12810637, 48.86990017, 23.90047511]), radius=4.886990017445058, bounds=Bounds(lower=array([1.1, 0. , 0. ]), upper=array([ 20., 70., 100.]))), model_indices=array([ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12]), model=ScalarModel(intercept=0.5838053927491154, linear_terms=array([-0.0784591 , -0.00113294, -0.00430834]), square_terms=array([[ 2.37622930e+00, -9.44902309e-03, -6.59043823e-03], + [-9.44902309e-03, 5.65537660e-05, 7.53932158e-05], + [-6.59043823e-03, 7.53932158e-05, 2.21756861e-04]]), scale=4.886990017445058, shift=array([ 9.12810637, 48.86990017, 23.90047511])), vector_model=VectorModel(intercepts=array([ 0.0478985 , 0.12198145, 0.14591097, 0.19026117, 0.21318417, + 0.22770334, 0.22810381, 0.06014365, -0.08704274, -0.07443179, + -0.41631926, -0.42444642, -0.1208239 , -0.09458291, -0.08510185, + -0.08890017, -0.09498552]), linear_terms=array([[0., 0., 0.], [0., 0., 0.], [0., 0., 0.], [0., 0., 0.], @@ -232,12 +232,12 @@ algorithm_output,"{'states': [State(trustregion=Region(center=array([ 8.7163601 [[0., 0., 0.], [0., 0., 0.], - [0., 0., 0.]]]), scale=4.354435734570826, shift=array([ 8.7163601 , 26.21001302, 43.54435735])), candidate_index=13, candidate_x=array([ 8.93351005, 28.89771693, 47.01135568]), index=0, x=array([ 8.7163601 , 26.21001302, 43.54435735]), fval=0.5809830305379233, rho=-0.558271347973752, accepted=False, new_indices=array([ 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12]), old_indices_used=array([0]), old_indices_discarded=array([], dtype=int64), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 8.7163601 , 26.21001302, 43.54435735]), radius=2.177217867285413, bounds=Bounds(lower=array([2., 0., 0.]), upper=array([20., 70., 70.]))), model_indices=array([ 0, 1, 2, 3, 4, 5, 6, 7, 9, 10, 11, 12]), model=ScalarModel(intercept=0.5525084893634734, linear_terms=array([-0.03730237, -0.00205422, -0.0037379 ]), square_terms=array([[ 5.75556074e-01, -4.87451781e-03, -1.08745730e-02], - [-4.87451781e-03, 1.20368007e-04, 2.44297801e-04], - [-1.08745730e-02, 2.44297801e-04, 5.02318123e-04]]), scale=2.177217867285413, shift=array([ 8.7163601 , 26.21001302, 43.54435735])), vector_model=VectorModel(intercepts=array([ 0.05724953, 0.13067265, 0.1523968 , 0.19379396, 0.21975026, - 0.23556517, 0.23562227, 0.08724666, -0.05175769, -0.04146735, - -0.38600879, -0.40563182, -0.07724305, -0.05219358, -0.04259982, - -0.04528797, -0.04943255]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.]]]), scale=4.886990017445058, shift=array([ 9.12810637, 48.86990017, 23.90047511])), candidate_index=13, candidate_x=array([ 9.30801516, 50.37166273, 28.55876295]), index=13, x=array([ 9.30801516, 50.37166273, 28.55876295]), fval=0.6417128790724664, rho=0.03368406179865712, accepted=True, new_indices=array([ 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12]), old_indices_used=array([0]), old_indices_discarded=array([], dtype=int64), step_length=4.897683486158282, relative_step_length=1.0021881503082781, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 9.30801516, 50.37166273, 28.55876295]), radius=2.443495008722529, bounds=Bounds(lower=array([1.1, 0. , 0. ]), upper=array([ 20., 70., 100.]))), model_indices=array([ 0, 2, 3, 4, 5, 6, 7, 8, 9, 11, 12, 13]), model=ScalarModel(intercept=0.6096236821586578, linear_terms=array([0.02840541, 0.00191562, 0.02107148]), square_terms=array([[5.95634493e-01, 4.34268068e-04, 1.74066775e-02], + [4.34268068e-04, 2.73557040e-05, 2.15252435e-04], + [1.74066775e-02, 2.15252435e-04, 2.09032328e-03]]), scale=2.443495008722529, shift=array([ 9.30801516, 50.37166273, 28.55876295])), vector_model=VectorModel(intercepts=array([ 0.0478985 , 0.12198145, 0.14591097, 0.19026117, 0.21318417, + 0.22770334, 0.22810381, 0.06014365, -0.08704274, -0.07443179, + -0.41631926, -0.42444642, -0.1208239 , -0.09458291, -0.08510185, + -0.08890017, -0.09498552]), linear_terms=array([[0., 0., 0.], [0., 0., 0.], [0., 0., 0.], [0., 0., 0.], @@ -319,12 +319,12 @@ algorithm_output,"{'states': [State(trustregion=Region(center=array([ 8.7163601 [[0., 0., 0.], [0., 0., 0.], - [0., 0., 0.]]]), scale=4.354435734570826, shift=array([ 8.7163601 , 26.21001302, 43.54435735])), candidate_index=14, candidate_x=array([ 8.90219766, 27.26532816, 45.51595825]), index=0, x=array([ 8.7163601 , 26.21001302, 43.54435735]), fval=0.5809830305379233, rho=-0.28629030520190707, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([ 0, 1, 2, 3, 4, 5, 6, 7, 9, 10, 11, 12]), old_indices_discarded=array([ 8, 13]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 8.7163601 , 26.21001302, 43.54435735]), radius=1.0886089336427065, bounds=Bounds(lower=array([2., 0., 0.]), upper=array([20., 70., 70.]))), model_indices=array([ 0, 1, 2, 3, 4, 5, 6, 7, 9, 10, 12, 14]), model=ScalarModel(intercept=0.5596299470764778, linear_terms=array([-0.00611761, -0.00353072, -0.0011418 ]), square_terms=array([[ 1.52462308e-01, -4.10493124e-03, -1.51631574e-03], - [-4.10493124e-03, 2.53887208e-04, 9.81815973e-05], - [-1.51631574e-03, 9.81815973e-05, 3.84430453e-05]]), scale=1.0886089336427065, shift=array([ 8.7163601 , 26.21001302, 43.54435735])), vector_model=VectorModel(intercepts=array([ 0.05724953, 0.13067265, 0.1523968 , 0.19379396, 0.21975026, - 0.23556517, 0.23562227, 0.08724666, -0.05175769, -0.04146735, - -0.38600879, -0.40563182, -0.07724305, -0.05219358, -0.04259982, - -0.04528797, -0.04943255]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.]]]), scale=4.886990017445058, shift=array([ 9.12810637, 48.86990017, 23.90047511])), candidate_index=14, candidate_x=array([ 9.2655641 , 50.14664588, 26.07420434]), index=14, x=array([ 9.2655641 , 50.14664588, 26.07420434]), fval=0.6415610317693744, rho=0.00737246118082768, accepted=True, new_indices=array([], dtype=int64), old_indices_used=array([ 0, 2, 3, 4, 5, 6, 7, 8, 9, 11, 12, 13]), old_indices_discarded=array([ 1, 10]), step_length=2.4950884015831862, relative_step_length=1.0211145890114302, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 9.2655641 , 50.14664588, 26.07420434]), radius=1.2217475043612644, bounds=Bounds(lower=array([1.1, 0. , 0. ]), upper=array([ 20., 70., 100.]))), model_indices=array([ 0, 3, 5, 6, 7, 9, 11, 12, 13, 14]), model=ScalarModel(intercept=0.5911089857829682, linear_terms=array([0.00422151, 0.00795934, 0.0161826 ]), square_terms=array([[0.15195804, 0.00362337, 0.00870881], + [0.00362337, 0.00041071, 0.00091153], + [0.00870881, 0.00091153, 0.00203185]]), scale=1.2217475043612644, shift=array([ 9.2655641 , 50.14664588, 26.07420434])), vector_model=VectorModel(intercepts=array([ 0.0478985 , 0.12198145, 0.14591097, 0.19026117, 0.21318417, + 0.22770334, 0.22810381, 0.06014365, -0.08704274, -0.07443179, + -0.41631926, -0.42444642, -0.1208239 , -0.09458291, -0.08510185, + -0.08890017, -0.09498552]), linear_terms=array([[0., 0., 0.], [0., 0., 0.], [0., 0., 0.], [0., 0., 0.], @@ -406,12 +406,12 @@ algorithm_output,"{'states': [State(trustregion=Region(center=array([ 8.7163601 [[0., 0., 0.], [0., 0., 0.], - [0., 0., 0.]]]), scale=4.354435734570826, shift=array([ 8.7163601 , 26.21001302, 43.54435735])), candidate_index=15, candidate_x=array([ 8.78953128, 27.24792252, 43.87862902]), index=0, x=array([ 8.7163601 , 26.21001302, 43.54435735]), fval=0.5809830305379233, rho=-0.13557088222916855, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([ 0, 1, 2, 3, 4, 5, 6, 7, 9, 10, 12, 14]), old_indices_discarded=array([ 8, 11, 13]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 8.7163601 , 26.21001302, 43.54435735]), radius=0.5443044668213532, bounds=Bounds(lower=array([2., 0., 0.]), upper=array([20., 70., 70.]))), model_indices=array([ 0, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27]), model=ScalarModel(intercept=0.5805771869323699, linear_terms=array([-2.39835685e-04, 1.49460494e-04, 1.19283566e-05]), square_terms=array([[3.27992106e-02, 7.19591335e-05, 2.68136949e-05], - [7.19591335e-05, 3.22752858e-07, 8.54387610e-08], - [2.68136949e-05, 8.54387610e-08, 5.88930115e-08]]), scale=0.5443044668213532, shift=array([ 8.7163601 , 26.21001302, 43.54435735])), vector_model=VectorModel(intercepts=array([ 0.05724953, 0.13067265, 0.1523968 , 0.19379396, 0.21975026, - 0.23556517, 0.23562227, 0.08724666, -0.05175769, -0.04146735, - -0.38600879, -0.40563182, -0.07724305, -0.05219358, -0.04259982, - -0.04528797, -0.04943255]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.]]]), scale=4.886990017445058, shift=array([ 9.12810637, 48.86990017, 23.90047511])), candidate_index=15, candidate_x=array([ 9.30677188, 49.57690312, 24.92860973]), index=14, x=array([ 9.2655641 , 50.14664588, 26.07420434]), fval=0.6415610317693744, rho=-0.007719959864419043, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([ 0, 3, 5, 6, 7, 9, 11, 12, 13, 14]), old_indices_discarded=array([], dtype=int64), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 9.2655641 , 50.14664588, 26.07420434]), radius=0.6108737521806322, bounds=Bounds(lower=array([1.1, 0. , 0. ]), upper=array([ 20., 70., 100.]))), model_indices=array([ 0, 9, 13, 14, 15]), model=ScalarModel(intercept=0.6412075612871301, linear_terms=array([ 5.18605429e-03, -5.96658930e-04, 8.53007592e-05]), square_terms=array([[ 3.43820818e-02, -5.19387823e-05, 5.05459631e-06], + [-5.19387823e-05, 6.87957385e-07, -9.67077712e-08], + [ 5.05459631e-06, -9.67077712e-08, 1.41737452e-08]]), scale=0.6108737521806322, shift=array([ 9.2655641 , 50.14664588, 26.07420434])), vector_model=VectorModel(intercepts=array([ 0.0478985 , 0.12198145, 0.14591097, 0.19026117, 0.21318417, + 0.22770334, 0.22810381, 0.06014365, -0.08704274, -0.07443179, + -0.41631926, -0.42444642, -0.1208239 , -0.09458291, -0.08510185, + -0.08890017, -0.09498552]), linear_terms=array([[0., 0., 0.], [0., 0., 0.], [0., 0., 0.], [0., 0., 0.], @@ -493,12 +493,12 @@ algorithm_output,"{'states': [State(trustregion=Region(center=array([ 8.7163601 [[0., 0., 0.], [0., 0., 0.], - [0., 0., 0.]]]), scale=4.354435734570826, shift=array([ 8.7163601 , 26.21001302, 43.54435735])), candidate_index=28, candidate_x=array([ 8.72154249, 25.66749131, 43.5005631 ]), index=0, x=array([ 8.7163601 , 26.21001302, 43.54435735]), fval=0.5809830305379233, rho=-0.07054714598212536, accepted=False, new_indices=array([16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27]), old_indices_used=array([ 0, 14, 15]), old_indices_discarded=array([], dtype=int64), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 8.7163601 , 26.21001302, 43.54435735]), radius=0.2721522334106766, bounds=Bounds(lower=array([2., 0., 0.]), upper=array([20., 70., 70.]))), model_indices=array([ 0, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 27]), model=ScalarModel(intercept=0.5805345814914069, linear_terms=array([-1.47123164e-04, -1.00826212e-05, 1.86558018e-06]), square_terms=array([[ 8.18773219e-03, -3.04389064e-06, 1.71271905e-05], - [-3.04389064e-06, 1.00762684e-08, -2.18614176e-08], - [ 1.71271905e-05, -2.18614176e-08, 1.18364761e-07]]), scale=0.2721522334106766, shift=array([ 8.7163601 , 26.21001302, 43.54435735])), vector_model=VectorModel(intercepts=array([ 0.05724953, 0.13067265, 0.1523968 , 0.19379396, 0.21975026, - 0.23556517, 0.23562227, 0.08724666, -0.05175769, -0.04146735, - -0.38600879, -0.40563182, -0.07724305, -0.05219358, -0.04259982, - -0.04528797, -0.04943255]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.]]]), scale=4.886990017445058, shift=array([ 9.12810637, 48.86990017, 23.90047511])), candidate_index=16, candidate_x=array([ 9.17589851, 50.75145653, 25.98737882]), index=16, x=array([ 9.17589851, 50.75145653, 25.98737882]), fval=0.6414178321884101, rho=0.14527765423064729, accepted=True, new_indices=array([], dtype=int64), old_indices_used=array([ 0, 9, 13, 14, 15]), old_indices_discarded=array([], dtype=int64), step_length=0.6175552708890588, relative_step_length=1.0109376424909002, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 9.17589851, 50.75145653, 25.98737882]), radius=1.2217475043612644, bounds=Bounds(lower=array([1.1, 0. , 0. ]), upper=array([ 20., 70., 100.]))), model_indices=array([ 0, 2, 3, 5, 7, 9, 11, 12, 13, 14, 15, 16]), model=ScalarModel(intercept=0.6052901828442077, linear_terms=array([-0.00707459, 0.00285906, 0.00874449]), square_terms=array([[1.45487940e-01, 8.88677433e-04, 3.95549893e-03], + [8.88677433e-04, 3.27781430e-05, 1.13238367e-04], + [3.95549893e-03, 1.13238367e-04, 4.03782515e-04]]), scale=1.2217475043612644, shift=array([ 9.17589851, 50.75145653, 25.98737882])), vector_model=VectorModel(intercepts=array([ 0.0478985 , 0.12198145, 0.14591097, 0.19026117, 0.21318417, + 0.22770334, 0.22810381, 0.06014365, -0.08704274, -0.07443179, + -0.41631926, -0.42444642, -0.1208239 , -0.09458291, -0.08510185, + -0.08890017, -0.09498552]), linear_terms=array([[0., 0., 0.], [0., 0., 0.], [0., 0., 0.], [0., 0., 0.], @@ -580,12 +580,12 @@ algorithm_output,"{'states': [State(trustregion=Region(center=array([ 8.7163601 [[0., 0., 0.], [0., 0., 0.], - [0., 0., 0.]]]), scale=4.354435734570826, shift=array([ 8.7163601 , 26.21001302, 43.54435735])), candidate_index=29, candidate_x=array([ 8.72148001, 26.49966574, 43.4831919 ]), index=0, x=array([ 8.7163601 , 26.21001302, 43.54435735]), fval=0.5809830305379233, rho=-0.9035564705080065, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([ 0, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 27]), old_indices_discarded=array([15, 26, 28]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 8.7163601 , 26.21001302, 43.54435735]), radius=0.1360761167053383, bounds=Bounds(lower=array([2., 0., 0.]), upper=array([20., 70., 70.]))), model_indices=array([ 0, 17, 18, 19, 20, 21, 22, 23, 24, 25, 27, 29]), model=ScalarModel(intercept=0.5805204784499093, linear_terms=array([-5.38579889e-05, 3.15850486e-05, -1.48626515e-05]), square_terms=array([[2.04967440e-03, 3.29163803e-06, 3.96956751e-06], - [3.29163803e-06, 1.12292861e-08, 1.32171424e-08], - [3.96956751e-06, 1.32171424e-08, 2.27968740e-08]]), scale=0.1360761167053383, shift=array([ 8.7163601 , 26.21001302, 43.54435735])), vector_model=VectorModel(intercepts=array([ 0.05724953, 0.13067265, 0.1523968 , 0.19379396, 0.21975026, - 0.23556517, 0.23562227, 0.08724666, -0.05175769, -0.04146735, - -0.38600879, -0.40563182, -0.07724305, -0.05219358, -0.04259982, - -0.04528797, -0.04943255]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.]]]), scale=4.886990017445058, shift=array([ 9.12810637, 48.86990017, 23.90047511])), candidate_index=17, candidate_x=array([ 9.2637979 , 50.37235045, 24.82377989]), index=16, x=array([ 9.17589851, 50.75145653, 25.98737882]), fval=0.6414178321884101, rho=-0.016345474533435187, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([ 0, 2, 3, 5, 7, 9, 11, 12, 13, 14, 15, 16]), old_indices_discarded=array([], dtype=int64), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 9.17589851, 50.75145653, 25.98737882]), radius=0.6108737521806322, bounds=Bounds(lower=array([1.1, 0. , 0. ]), upper=array([ 20., 70., 100.]))), model_indices=array([ 0, 9, 13, 14, 15, 16, 17]), model=ScalarModel(intercept=0.6408680252047284, linear_terms=array([ 1.22608587e-03, -1.52831904e-04, -7.93126783e-05]), square_terms=array([[ 3.46548267e-02, 3.74686901e-06, -1.56196185e-05], + [ 3.74686901e-06, 4.51202398e-08, 1.43733385e-08], + [-1.56196185e-05, 1.43733385e-08, 1.99575801e-08]]), scale=0.6108737521806322, shift=array([ 9.17589851, 50.75145653, 25.98737882])), vector_model=VectorModel(intercepts=array([ 0.0478985 , 0.12198145, 0.14591097, 0.19026117, 0.21318417, + 0.22770334, 0.22810381, 0.06014365, -0.08704274, -0.07443179, + -0.41631926, -0.42444642, -0.1208239 , -0.09458291, -0.08510185, + -0.08890017, -0.09498552]), linear_terms=array([[0., 0., 0.], [0., 0., 0.], [0., 0., 0.], [0., 0., 0.], @@ -667,12 +667,12 @@ algorithm_output,"{'states': [State(trustregion=Region(center=array([ 8.7163601 [[0., 0., 0.], [0., 0., 0.], - [0., 0., 0.]]]), scale=4.354435734570826, shift=array([ 8.7163601 , 26.21001302, 43.54435735])), candidate_index=30, candidate_x=array([ 8.71996125, 26.08650393, 43.60192377]), index=0, x=array([ 8.7163601 , 26.21001302, 43.54435735]), fval=0.5809830305379233, rho=-0.560974012620415, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([ 0, 17, 18, 19, 20, 21, 22, 23, 24, 25, 27, 29]), old_indices_discarded=array([16, 26, 28]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 8.7163601 , 26.21001302, 43.54435735]), radius=0.06803805835266916, bounds=Bounds(lower=array([2., 0., 0.]), upper=array([20., 70., 70.]))), model_indices=array([ 0, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42]), model=ScalarModel(intercept=0.5811362406009375, linear_terms=array([ 5.13417290e-05, -2.24031655e-05, -3.20307025e-05]), square_terms=array([[5.05495050e-04, 3.61720496e-07, 5.45942913e-07], - [3.61720496e-07, 2.17855514e-09, 2.75774644e-09], - [5.45942913e-07, 2.75774644e-09, 4.07900817e-09]]), scale=0.06803805835266916, shift=array([ 8.7163601 , 26.21001302, 43.54435735])), vector_model=VectorModel(intercepts=array([ 0.05724953, 0.13067265, 0.1523968 , 0.19379396, 0.21975026, - 0.23556517, 0.23562227, 0.08724666, -0.05175769, -0.04146735, - -0.38600879, -0.40563182, -0.07724305, -0.05219358, -0.04259982, - -0.04528797, -0.04943255]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.]]]), scale=4.886990017445058, shift=array([ 9.12810637, 48.86990017, 23.90047511])), candidate_index=18, candidate_x=array([ 9.15445957, 51.29445206, 26.26698772]), index=16, x=array([ 9.17589851, 50.75145653, 25.98737882]), fval=0.6414178321884101, rho=-0.3807981173026105, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([ 0, 9, 13, 14, 15, 16, 17]), old_indices_discarded=array([], dtype=int64), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 9.17589851, 50.75145653, 25.98737882]), radius=0.3054368760903161, bounds=Bounds(lower=array([1.1, 0. , 0. ]), upper=array([ 20., 70., 100.]))), model_indices=array([14, 16, 17, 18]), model=ScalarModel(intercept=0.6414178321884101, linear_terms=array([-7.14351462e-04, 3.57051786e-06, -4.34650781e-06]), square_terms=array([[ 8.31583940e-03, -5.01950042e-06, -1.11678712e-06], + [-5.01950042e-06, 3.13345575e-08, 6.31491818e-09], + [-1.11678712e-06, 6.31491818e-09, 1.42073640e-09]]), scale=0.3054368760903161, shift=array([ 9.17589851, 50.75145653, 25.98737882])), vector_model=VectorModel(intercepts=array([ 0.0478985 , 0.12198145, 0.14591097, 0.19026117, 0.21318417, + 0.22770334, 0.22810381, 0.06014365, -0.08704274, -0.07443179, + -0.41631926, -0.42444642, -0.1208239 , -0.09458291, -0.08510185, + -0.08890017, -0.09498552]), linear_terms=array([[0., 0., 0.], [0., 0., 0.], [0., 0., 0.], [0., 0., 0.], @@ -754,12 +754,12 @@ algorithm_output,"{'states': [State(trustregion=Region(center=array([ 8.7163601 [[0., 0., 0.], [0., 0., 0.], - [0., 0., 0.]]]), scale=4.354435734570826, shift=array([ 8.7163601 , 26.21001302, 43.54435735])), candidate_index=43, candidate_x=array([ 8.70986512, 26.24896623, 43.60005524]), index=0, x=array([ 8.7163601 , 26.21001302, 43.54435735]), fval=0.5809830305379233, rho=-0.8471869049261229, accepted=False, new_indices=array([31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42]), old_indices_used=array([ 0, 29, 30]), old_indices_discarded=array([], dtype=int64), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 8.7163601 , 26.21001302, 43.54435735]), radius=0.03401902917633458, bounds=Bounds(lower=array([2., 0., 0.]), upper=array([20., 70., 70.]))), model_indices=array([ 0, 31, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42]), model=ScalarModel(intercept=0.5811459446716418, linear_terms=array([ 2.15988882e-05, -1.47914448e-05, -5.52422900e-06]), square_terms=array([[ 1.26489115e-04, 1.09571037e-07, 3.94365824e-08], - [ 1.09571037e-07, 2.78995467e-09, -1.24194007e-10], - [ 3.94365824e-08, -1.24194007e-10, 2.35991172e-10]]), scale=0.03401902917633458, shift=array([ 8.7163601 , 26.21001302, 43.54435735])), vector_model=VectorModel(intercepts=array([ 0.05724953, 0.13067265, 0.1523968 , 0.19379396, 0.21975026, - 0.23556517, 0.23562227, 0.08724666, -0.05175769, -0.04146735, - -0.38600879, -0.40563182, -0.07724305, -0.05219358, -0.04259982, - -0.04528797, -0.04943255]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.]]]), scale=4.886990017445058, shift=array([ 9.12810637, 48.86990017, 23.90047511])), candidate_index=19, candidate_x=array([ 9.2020414 , 50.55938439, 26.26040984]), index=19, x=array([ 9.2020414 , 50.55938439, 26.26040984]), fval=0.6412798714314748, rho=3.766886757176218, accepted=True, new_indices=array([], dtype=int64), old_indices_used=array([14, 16, 17, 18]), old_indices_discarded=array([], dtype=int64), step_length=0.3348448739735063, relative_step_length=1.0962817530732418, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 9.2020414 , 50.55938439, 26.26040984]), radius=0.6108737521806322, bounds=Bounds(lower=array([1.1, 0. , 0. ]), upper=array([ 20., 70., 100.]))), model_indices=array([ 0, 9, 13, 14, 15, 16, 17, 18, 19]), model=ScalarModel(intercept=0.6411413456382316, linear_terms=array([ 3.14313654e-03, 2.74625666e-05, -1.27910543e-04]), square_terms=array([[ 3.47663383e-02, 2.63538243e-05, -2.12337211e-05], + [ 2.63538243e-05, 5.29791904e-08, -3.77184755e-08], + [-2.12337211e-05, -3.77184755e-08, 4.60609078e-08]]), scale=0.6108737521806322, shift=array([ 9.2020414 , 50.55938439, 26.26040984])), vector_model=VectorModel(intercepts=array([ 0.0478985 , 0.12198145, 0.14591097, 0.19026117, 0.21318417, + 0.22770334, 0.22810381, 0.06014365, -0.08704274, -0.07443179, + -0.41631926, -0.42444642, -0.1208239 , -0.09458291, -0.08510185, + -0.08890017, -0.09498552]), linear_terms=array([[0., 0., 0.], [0., 0., 0.], [0., 0., 0.], [0., 0., 0.], @@ -841,12 +841,12 @@ algorithm_output,"{'states': [State(trustregion=Region(center=array([ 8.7163601 [[0., 0., 0.], [0., 0., 0.], - [0., 0., 0.]]]), scale=4.354435734570826, shift=array([ 8.7163601 , 26.21001302, 43.54435735])), candidate_index=44, candidate_x=array([ 8.7111716 , 26.2417183 , 43.55620009]), index=0, x=array([ 8.7163601 , 26.21001302, 43.54435735]), fval=0.5809830305379233, rho=-2.4752213951973463, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([ 0, 31, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42]), old_indices_discarded=array([30, 32, 43]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 8.7163601 , 26.21001302, 43.54435735]), radius=0.01700951458816729, bounds=Bounds(lower=array([2., 0., 0.]), upper=array([20., 70., 70.]))), model_indices=array([ 0, 31, 33, 35, 36, 37, 38, 39, 40, 41, 42, 44]), model=ScalarModel(intercept=0.5811498347258051, linear_terms=array([ 8.19881459e-06, -1.98216693e-05, -8.47308716e-06]), square_terms=array([[3.16511989e-05, 9.81407579e-08, 4.20337638e-08], - [9.81407579e-08, 3.30385011e-09, 1.09448244e-09], - [4.20337638e-08, 1.09448244e-09, 5.17961167e-10]]), scale=0.01700951458816729, shift=array([ 8.7163601 , 26.21001302, 43.54435735])), vector_model=VectorModel(intercepts=array([ 0.05724953, 0.13067265, 0.1523968 , 0.19379396, 0.21975026, - 0.23556517, 0.23562227, 0.08724666, -0.05175769, -0.04146735, - -0.38600879, -0.40563182, -0.07724305, -0.05219358, -0.04259982, - -0.04528797, -0.04943255]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.]]]), scale=4.886990017445058, shift=array([ 9.12810637, 48.86990017, 23.90047511])), candidate_index=20, candidate_x=array([ 9.14747104, 50.44050518, 26.85791599]), index=19, x=array([ 9.2020414 , 50.55938439, 26.26040984]), fval=0.6412798714314748, rho=-1.4403818757718805, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([ 0, 9, 13, 14, 15, 16, 17, 18, 19]), old_indices_discarded=array([], dtype=int64), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 9.2020414 , 50.55938439, 26.26040984]), radius=0.3054368760903161, bounds=Bounds(lower=array([1.1, 0. , 0. ]), upper=array([ 20., 70., 100.]))), model_indices=array([14, 16, 17, 18, 19, 20]), model=ScalarModel(intercept=0.6413874688839755, linear_terms=array([-6.33748043e-04, -5.73186109e-05, -1.79357454e-05]), square_terms=array([[8.46968425e-03, 2.56443878e-06, 1.01117391e-07], + [2.56443878e-06, 9.68297991e-09, 2.15723240e-09], + [1.01117391e-07, 2.15723240e-09, 1.06370393e-09]]), scale=0.3054368760903161, shift=array([ 9.2020414 , 50.55938439, 26.26040984])), vector_model=VectorModel(intercepts=array([ 0.0478985 , 0.12198145, 0.14591097, 0.19026117, 0.21318417, + 0.22770334, 0.22810381, 0.06014365, -0.08704274, -0.07443179, + -0.41631926, -0.42444642, -0.1208239 , -0.09458291, -0.08510185, + -0.08890017, -0.09498552]), linear_terms=array([[0., 0., 0.], [0., 0., 0.], [0., 0., 0.], [0., 0., 0.], @@ -928,12 +928,12 @@ algorithm_output,"{'states': [State(trustregion=Region(center=array([ 8.7163601 [[0., 0., 0.], [0., 0., 0.], - [0., 0., 0.]]]), scale=4.354435734570826, shift=array([ 8.7163601 , 26.21001302, 43.54435735])), candidate_index=45, candidate_x=array([ 8.71370725, 26.22563044, 43.55103349]), index=0, x=array([ 8.7163601 , 26.21001302, 43.54435735]), fval=0.5809830305379233, rho=-1.638710716456882, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([ 0, 31, 33, 35, 36, 37, 38, 39, 40, 41, 42, 44]), old_indices_discarded=array([32, 34, 43]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 8.7163601 , 26.21001302, 43.54435735]), radius=0.008504757294083645, bounds=Bounds(lower=array([2., 0., 0.]), upper=array([20., 70., 70.]))), model_indices=array([ 0, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57]), model=ScalarModel(intercept=0.5810060157553625, linear_terms=array([-2.44013081e-05, 2.00200467e-06, -1.83538122e-06]), square_terms=array([[ 7.96683033e-06, -8.28976078e-09, 4.99596045e-09], - [-8.28976078e-09, 1.35876689e-10, -1.12232380e-10], - [ 4.99596045e-09, -1.12232380e-10, 1.03220726e-10]]), scale=0.008504757294083645, shift=array([ 8.7163601 , 26.21001302, 43.54435735])), vector_model=VectorModel(intercepts=array([ 0.05724953, 0.13067265, 0.1523968 , 0.19379396, 0.21975026, - 0.23556517, 0.23562227, 0.08724666, -0.05175769, -0.04146735, - -0.38600879, -0.40563182, -0.07724305, -0.05219358, -0.04259982, - -0.04528797, -0.04943255]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.]]]), scale=4.886990017445058, shift=array([ 9.12810637, 48.86990017, 23.90047511])), candidate_index=21, candidate_x=array([ 9.22464674, 50.85076503, 26.3518551 ]), index=19, x=array([ 9.2020414 , 50.55938439, 26.26040984]), fval=0.6412798714314748, rho=-1.2442024876135518, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([14, 16, 17, 18, 19, 20]), old_indices_discarded=array([], dtype=int64), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 9.2020414 , 50.55938439, 26.26040984]), radius=0.15271843804515806, bounds=Bounds(lower=array([1.1, 0. , 0. ]), upper=array([ 20., 70., 100.]))), model_indices=array([14, 16, 18, 19, 20, 21]), model=ScalarModel(intercept=0.6413861775924228, linear_terms=array([-1.34889295e-04, -1.17794331e-05, 1.72033189e-05]), square_terms=array([[ 2.12047970e-03, 7.30611322e-07, -4.58026451e-07], + [ 7.30611322e-07, 1.91216963e-09, 3.03077874e-10], + [-4.58026451e-07, 3.03077874e-10, 3.30402692e-09]]), scale=0.15271843804515806, shift=array([ 9.2020414 , 50.55938439, 26.26040984])), vector_model=VectorModel(intercepts=array([ 0.0478985 , 0.12198145, 0.14591097, 0.19026117, 0.21318417, + 0.22770334, 0.22810381, 0.06014365, -0.08704274, -0.07443179, + -0.41631926, -0.42444642, -0.1208239 , -0.09458291, -0.08510185, + -0.08890017, -0.09498552]), linear_terms=array([[0., 0., 0.], [0., 0., 0.], [0., 0., 0.], [0., 0., 0.], @@ -1015,12 +1015,12 @@ algorithm_output,"{'states': [State(trustregion=Region(center=array([ 8.7163601 [[0., 0., 0.], [0., 0., 0.], - [0., 0., 0.]]]), scale=4.354435734570826, shift=array([ 8.7163601 , 26.21001302, 43.54435735])), candidate_index=58, candidate_x=array([ 8.72480793, 26.21067241, 43.54362912]), index=0, x=array([ 8.7163601 , 26.21001302, 43.54435735]), fval=0.5809830305379233, rho=-1.7285305581264891, accepted=False, new_indices=array([46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57]), old_indices_used=array([ 0, 44, 45]), old_indices_discarded=array([], dtype=int64), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 8.7163601 , 26.21001302, 43.54435735]), radius=0.004252378647041822, bounds=Bounds(lower=array([2., 0., 0.]), upper=array([20., 70., 70.]))), model_indices=array([ 0, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 58]), model=ScalarModel(intercept=0.5810059947082536, linear_terms=array([-8.13588391e-06, -6.46820598e-07, -3.84429557e-06]), square_terms=array([[ 1.97355344e-06, -3.12745979e-10, 4.93097236e-09], - [-3.12745979e-10, 1.61347657e-10, -1.79142315e-11], - [ 4.93097236e-09, -1.79142315e-11, 3.42610125e-11]]), scale=0.004252378647041822, shift=array([ 8.7163601 , 26.21001302, 43.54435735])), vector_model=VectorModel(intercepts=array([ 0.05724953, 0.13067265, 0.1523968 , 0.19379396, 0.21975026, - 0.23556517, 0.23562227, 0.08724666, -0.05175769, -0.04146735, - -0.38600879, -0.40563182, -0.07724305, -0.05219358, -0.04259982, - -0.04528797, -0.04943255]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.]]]), scale=4.886990017445058, shift=array([ 9.12810637, 48.86990017, 23.90047511])), candidate_index=22, candidate_x=array([ 9.21160543, 50.6453772 , 26.13455164]), index=22, x=array([ 9.21160543, 50.6453772 , 26.13455164]), fval=0.6412533792921618, rho=1.0576140080519945, accepted=True, new_indices=array([], dtype=int64), old_indices_used=array([14, 16, 18, 19, 20, 21]), old_indices_discarded=array([], dtype=int64), step_length=0.15273021841934944, relative_step_length=1.0000771378645708, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 9.21160543, 50.6453772 , 26.13455164]), radius=0.3054368760903161, bounds=Bounds(lower=array([1.1, 0. , 0. ]), upper=array([ 20., 70., 100.]))), model_indices=array([14, 16, 17, 18, 19, 20, 21, 22]), model=ScalarModel(intercept=0.6413638550561954, linear_terms=array([-2.14082253e-04, -4.27982472e-05, -1.00993546e-05]), square_terms=array([[8.50926454e-03, 4.22952742e-06, 1.16007861e-06], + [4.22952742e-06, 1.36024420e-08, 5.92380689e-09], + [1.16007861e-06, 5.92380689e-09, 4.14150417e-09]]), scale=0.3054368760903161, shift=array([ 9.21160543, 50.6453772 , 26.13455164])), vector_model=VectorModel(intercepts=array([ 0.0478985 , 0.12198145, 0.14591097, 0.19026117, 0.21318417, + 0.22770334, 0.22810381, 0.06014365, -0.08704274, -0.07443179, + -0.41631926, -0.42444642, -0.1208239 , -0.09458291, -0.08510185, + -0.08890017, -0.09498552]), linear_terms=array([[0., 0., 0.], [0., 0., 0.], [0., 0., 0.], [0., 0., 0.], @@ -1102,12 +1102,12 @@ algorithm_output,"{'states': [State(trustregion=Region(center=array([ 8.7163601 [[0., 0., 0.], [0., 0., 0.], - [0., 0., 0.]]]), scale=4.354435734570826, shift=array([ 8.7163601 , 26.21001302, 43.54435735])), candidate_index=59, candidate_x=array([ 8.72022764, 26.21084589, 43.54591659]), index=0, x=array([ 8.7163601 , 26.21001302, 43.54435735]), fval=0.5809830305379233, rho=-2.6934710432582296, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([ 0, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 58]), old_indices_discarded=array([45, 56, 57]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 8.7163601 , 26.21001302, 43.54435735]), radius=0.002126189323520911, bounds=Bounds(lower=array([2., 0., 0.]), upper=array([20., 70., 70.]))), model_indices=array([ 0, 47, 48, 49, 50, 51, 52, 53, 54, 55, 58, 59]), model=ScalarModel(intercept=0.5810059980495079, linear_terms=array([-4.03231693e-06, -5.25555887e-07, -2.23095895e-06]), square_terms=array([[ 4.93387827e-07, -2.69532463e-10, 1.04721040e-09], - [-2.69532463e-10, 7.48188612e-12, 1.98300290e-11], - [ 1.04721040e-09, 1.98300290e-11, 9.63514775e-11]]), scale=0.002126189323520911, shift=array([ 8.7163601 , 26.21001302, 43.54435735])), vector_model=VectorModel(intercepts=array([ 0.05724953, 0.13067265, 0.1523968 , 0.19379396, 0.21975026, - 0.23556517, 0.23562227, 0.08724666, -0.05175769, -0.04146735, - -0.38600879, -0.40563182, -0.07724305, -0.05219358, -0.04259982, - -0.04528797, -0.04943255]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.]]]), scale=4.886990017445058, shift=array([ 9.12810637, 48.86990017, 23.90047511])), candidate_index=23, candidate_x=array([ 9.21909393, 50.94264606, 26.20464947]), index=22, x=array([ 9.21160543, 50.6453772 , 26.13455164]), fval=0.6412533792921618, rho=-1.4513449695755447, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([14, 16, 17, 18, 19, 20, 21, 22]), old_indices_discarded=array([], dtype=int64), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 9.21160543, 50.6453772 , 26.13455164]), radius=0.15271843804515806, bounds=Bounds(lower=array([1.1, 0. , 0. ]), upper=array([ 20., 70., 100.]))), model_indices=array([14, 16, 18, 19, 20, 21, 22, 23]), model=ScalarModel(intercept=0.6413399722336997, linear_terms=array([-1.41886991e-05, -1.22506996e-05, 2.10449721e-05]), square_terms=array([[ 2.12392194e-03, 8.98039493e-07, -4.74231704e-07], + [ 8.98039493e-07, 2.50309927e-09, 5.64263262e-12], + [-4.74231704e-07, 5.64263262e-12, 3.29687601e-09]]), scale=0.15271843804515806, shift=array([ 9.21160543, 50.6453772 , 26.13455164])), vector_model=VectorModel(intercepts=array([ 0.0478985 , 0.12198145, 0.14591097, 0.19026117, 0.21318417, + 0.22770334, 0.22810381, 0.06014365, -0.08704274, -0.07443179, + -0.41631926, -0.42444642, -0.1208239 , -0.09458291, -0.08510185, + -0.08890017, -0.09498552]), linear_terms=array([[0., 0., 0.], [0., 0., 0.], [0., 0., 0.], [0., 0., 0.], @@ -1189,12 +1189,12 @@ algorithm_output,"{'states': [State(trustregion=Region(center=array([ 8.7163601 [[0., 0., 0.], [0., 0., 0.], - [0., 0., 0.]]]), scale=4.354435734570826, shift=array([ 8.7163601 , 26.21001302, 43.54435735])), candidate_index=60, candidate_x=array([ 8.71821579, 26.21037748, 43.54532909]), index=0, x=array([ 8.7163601 , 26.21001302, 43.54435735]), fval=0.5809830305379233, rho=-5.430468463123208, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([ 0, 47, 48, 49, 50, 51, 52, 53, 54, 55, 58, 59]), old_indices_discarded=array([46, 56, 57]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 8.7163601 , 26.21001302, 43.54435735]), radius=0.0010630946617604556, bounds=Bounds(lower=array([2., 0., 0.]), upper=array([20., 70., 70.]))), model_indices=array([ 0, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72]), model=ScalarModel(intercept=0.5809896098134266, linear_terms=array([ 5.88223897e-06, -1.55577712e-06, -1.64353073e-06]), square_terms=array([[ 1.20376454e-07, 2.16332482e-10, -2.81822174e-10], - [ 2.16332482e-10, 3.19650170e-12, 4.38885234e-12], - [-2.81822174e-10, 4.38885234e-12, 5.06103427e-11]]), scale=0.0010630946617604556, shift=array([ 8.7163601 , 26.21001302, 43.54435735])), vector_model=VectorModel(intercepts=array([ 0.05724953, 0.13067265, 0.1523968 , 0.19379396, 0.21975026, - 0.23556517, 0.23562227, 0.08724666, -0.05175769, -0.04146735, - -0.38600879, -0.40563182, -0.07724305, -0.05219358, -0.04259982, - -0.04528797, -0.04943255]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.]]]), scale=4.886990017445058, shift=array([ 9.12810637, 48.86990017, 23.90047511])), candidate_index=24, candidate_x=array([ 9.21254927, 50.72755054, 25.9933501 ]), index=22, x=array([ 9.21160543, 50.6453772 , 26.13455164]), fval=0.6412533792921618, rho=-0.6299099565848705, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([14, 16, 18, 19, 20, 21, 22, 23]), old_indices_discarded=array([], dtype=int64), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 9.21160543, 50.6453772 , 26.13455164]), radius=0.07635921902257903, bounds=Bounds(lower=array([1.1, 0. , 0. ]), upper=array([ 20., 70., 100.]))), model_indices=array([16, 19, 21, 22, 23, 24]), model=ScalarModel(intercept=0.6412636200468966, linear_terms=array([-1.85982564e-04, 2.34556335e-05, 1.68033597e-05]), square_terms=array([[ 5.32130898e-04, -3.65300183e-08, -4.57058856e-08], + [-3.65300183e-08, 2.84261585e-09, 1.19188371e-09], + [-4.57058856e-08, 1.19188371e-09, 8.22139690e-10]]), scale=0.07635921902257903, shift=array([ 9.21160543, 50.6453772 , 26.13455164])), vector_model=VectorModel(intercepts=array([ 0.0478985 , 0.12198145, 0.14591097, 0.19026117, 0.21318417, + 0.22770334, 0.22810381, 0.06014365, -0.08704274, -0.07443179, + -0.41631926, -0.42444642, -0.1208239 , -0.09458291, -0.08510185, + -0.08890017, -0.09498552]), linear_terms=array([[0., 0., 0.], [0., 0., 0.], [0., 0., 0.], [0., 0., 0.], @@ -1276,12 +1276,12 @@ algorithm_output,"{'states': [State(trustregion=Region(center=array([ 8.7163601 [[0., 0., 0.], [0., 0., 0.], - [0., 0., 0.]]]), scale=4.354435734570826, shift=array([ 8.7163601 , 26.21001302, 43.54435735])), candidate_index=73, candidate_x=array([ 8.71536928, 26.21028616, 43.54462906]), index=0, x=array([ 8.7163601 , 26.21001302, 43.54435735]), fval=0.5809830305379233, rho=-2.9872067713886064, accepted=False, new_indices=array([61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72]), old_indices_used=array([ 0, 59, 60]), old_indices_discarded=array([], dtype=int64), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 8.7163601 , 26.21001302, 43.54435735]), radius=0.0005315473308802278, bounds=Bounds(lower=array([2., 0., 0.]), upper=array([20., 70., 70.]))), model_indices=array([ 0, 61, 62, 63, 65, 66, 67, 68, 69, 70, 71, 73]), model=ScalarModel(intercept=0.5809916477871087, linear_terms=array([-8.28665877e-07, -2.86476957e-07, -1.24886973e-06]), square_terms=array([[3.13215641e-08, 2.70941570e-11, 7.85016001e-11], - [2.70941570e-11, 1.36435914e-13, 4.46280590e-13], - [7.85016001e-11, 4.46280590e-13, 2.25290922e-12]]), scale=0.0005315473308802278, shift=array([ 8.7163601 , 26.21001302, 43.54435735])), vector_model=VectorModel(intercepts=array([ 0.05724953, 0.13067265, 0.1523968 , 0.19379396, 0.21975026, - 0.23556517, 0.23562227, 0.08724666, -0.05175769, -0.04146735, - -0.38600879, -0.40563182, -0.07724305, -0.05219358, -0.04259982, - -0.04528797, -0.04943255]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.]]]), scale=4.886990017445058, shift=array([ 9.12810637, 48.86990017, 23.90047511])), candidate_index=25, candidate_x=array([ 9.23690342, 50.5838021 , 26.09045508]), index=22, x=array([ 9.21160543, 50.6453772 , 26.13455164]), fval=0.6412533792921618, rho=-3.865430938711674, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([16, 19, 21, 22, 23, 24]), old_indices_discarded=array([], dtype=int64), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 9.21160543, 50.6453772 , 26.13455164]), radius=0.038179609511289514, bounds=Bounds(lower=array([1.1, 0. , 0. ]), upper=array([ 20., 70., 100.]))), model_indices=array([16, 19, 22, 24, 25]), model=ScalarModel(intercept=0.6412400317662156, linear_terms=array([-1.51811080e-04, -1.33574181e-04, -8.96571588e-05]), square_terms=array([[1.33253248e-04, 3.18742679e-07, 2.22600759e-07], + [3.18742679e-07, 7.45315433e-08, 5.15360719e-08], + [2.22600759e-07, 5.15360719e-08, 3.57710222e-08]]), scale=0.038179609511289514, shift=array([ 9.21160543, 50.6453772 , 26.13455164])), vector_model=VectorModel(intercepts=array([ 0.0478985 , 0.12198145, 0.14591097, 0.19026117, 0.21318417, + 0.22770334, 0.22810381, 0.06014365, -0.08704274, -0.07443179, + -0.41631926, -0.42444642, -0.1208239 , -0.09458291, -0.08510185, + -0.08890017, -0.09498552]), linear_terms=array([[0., 0., 0.], [0., 0., 0.], [0., 0., 0.], [0., 0., 0.], @@ -1363,12 +1363,12 @@ algorithm_output,"{'states': [State(trustregion=Region(center=array([ 8.7163601 [[0., 0., 0.], [0., 0., 0.], - [0., 0., 0.]]]), scale=4.354435734570826, shift=array([ 8.7163601 , 26.21001302, 43.54435735])), candidate_index=74, candidate_x=array([ 8.71664582, 26.21011384, 43.54479689]), index=0, x=array([ 8.7163601 , 26.21001302, 43.54435735]), fval=0.5809830305379233, rho=-2.5168773401923845, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([ 0, 61, 62, 63, 65, 66, 67, 68, 69, 70, 71, 73]), old_indices_discarded=array([60, 64, 72]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 8.7163601 , 26.21001302, 43.54435735]), radius=0.0002657736654401139, bounds=Bounds(lower=array([2., 0., 0.]), upper=array([20., 70., 70.]))), model_indices=array([ 0, 62, 63, 65, 66, 67, 68, 69, 70, 71, 73, 74]), model=ScalarModel(intercept=0.5809924325261797, linear_terms=array([-6.50169305e-07, -6.61619661e-07, -7.50887963e-07]), square_terms=array([[7.84875238e-09, 2.64831149e-11, 2.50892034e-11], - [2.64831149e-11, 5.83683628e-13, 6.19203568e-13], - [2.50892034e-11, 6.19203568e-13, 7.85763475e-13]]), scale=0.0002657736654401139, shift=array([ 8.7163601 , 26.21001302, 43.54435735])), vector_model=VectorModel(intercepts=array([ 0.05724953, 0.13067265, 0.1523968 , 0.19379396, 0.21975026, - 0.23556517, 0.23562227, 0.08724666, -0.05175769, -0.04146735, - -0.38600879, -0.40563182, -0.07724305, -0.05219358, -0.04259982, - -0.04528797, -0.04943255]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.]]]), scale=4.886990017445058, shift=array([ 9.12810637, 48.86990017, 23.90047511])), candidate_index=26, candidate_x=array([ 9.2299355 , 50.67331247, 26.15330102]), index=22, x=array([ 9.21160543, 50.6453772 , 26.13455164]), fval=0.6412533792921618, rho=-0.6957078218562044, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([16, 19, 22, 24, 25]), old_indices_discarded=array([], dtype=int64), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 9.21160543, 50.6453772 , 26.13455164]), radius=0.019089804755644757, bounds=Bounds(lower=array([1.1, 0. , 0. ]), upper=array([ 20., 70., 100.]))), model_indices=array([22, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38]), model=ScalarModel(intercept=0.6412949003105258, linear_terms=array([ 7.79166084e-05, -1.08575400e-05, -7.85152239e-06]), square_terms=array([[ 3.29424647e-05, 2.40761818e-08, -1.09908809e-08], + [ 2.40761818e-08, 3.71198501e-10, 2.17963621e-10], + [-1.09908809e-08, 2.17963621e-10, 2.48160791e-10]]), scale=0.019089804755644757, shift=array([ 9.21160543, 50.6453772 , 26.13455164])), vector_model=VectorModel(intercepts=array([ 0.0478985 , 0.12198145, 0.14591097, 0.19026117, 0.21318417, + 0.22770334, 0.22810381, 0.06014365, -0.08704274, -0.07443179, + -0.41631926, -0.42444642, -0.1208239 , -0.09458291, -0.08510185, + -0.08890017, -0.09498552]), linear_terms=array([[0., 0., 0.], [0., 0., 0.], [0., 0., 0.], [0., 0., 0.], @@ -1450,12 +1450,12 @@ algorithm_output,"{'states': [State(trustregion=Region(center=array([ 8.7163601 [[0., 0., 0.], [0., 0., 0.], - [0., 0., 0.]]]), scale=4.354435734570826, shift=array([ 8.7163601 , 26.21001302, 43.54435735])), candidate_index=75, candidate_x=array([ 8.71650441, 26.21016084, 43.54452511]), index=0, x=array([ 8.7163601 , 26.21001302, 43.54435735]), fval=0.5809830305379233, rho=-1.0197333317217874, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([ 0, 62, 63, 65, 66, 67, 68, 69, 70, 71, 73, 74]), old_indices_discarded=array([61, 64, 72]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 8.7163601 , 26.21001302, 43.54435735]), radius=0.00013288683272005695, bounds=Bounds(lower=array([2., 0., 0.]), upper=array([20., 70., 70.]))), model_indices=array([ 0, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87]), model=ScalarModel(intercept=0.5809836227584936, linear_terms=array([7.90333338e-08, 1.02805278e-07, 6.42865768e-07]), square_terms=array([[ 1.94876940e-09, -1.25425316e-12, -9.63319991e-12], - [-1.25425316e-12, 3.83332866e-14, 1.37583472e-13], - [-9.63319991e-12, 1.37583472e-13, 6.66770684e-13]]), scale=0.00013288683272005695, shift=array([ 8.7163601 , 26.21001302, 43.54435735])), vector_model=VectorModel(intercepts=array([ 0.05724953, 0.13067265, 0.1523968 , 0.19379396, 0.21975026, - 0.23556517, 0.23562227, 0.08724666, -0.05175769, -0.04146735, - -0.38600879, -0.40563182, -0.07724305, -0.05219358, -0.04259982, - -0.04528797, -0.04943255]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.]]]), scale=4.886990017445058, shift=array([ 9.12810637, 48.86990017, 23.90047511])), candidate_index=39, candidate_x=array([ 9.19367375, 50.65189736, 26.13394921]), index=22, x=array([ 9.21160543, 50.6453772 , 26.13455164]), fval=0.6412533792921618, rho=-0.7356352461674331, accepted=False, new_indices=array([27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38]), old_indices_used=array([22, 25, 26]), old_indices_discarded=array([], dtype=int64), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 9.21160543, 50.6453772 , 26.13455164]), radius=0.009544902377822378, bounds=Bounds(lower=array([1.1, 0. , 0. ]), upper=array([ 20., 70., 100.]))), model_indices=array([22, 27, 28, 29, 30, 31, 33, 34, 35, 37, 38, 39]), model=ScalarModel(intercept=0.6413009360685263, linear_terms=array([ 2.98872405e-05, -9.59030521e-06, -4.27533832e-06]), square_terms=array([[8.22114603e-06, 2.13676999e-08, 1.22020370e-08], + [2.13676999e-08, 2.01378174e-10, 1.00233499e-10], + [1.22020370e-08, 1.00233499e-10, 1.15290113e-10]]), scale=0.009544902377822378, shift=array([ 9.21160543, 50.6453772 , 26.13455164])), vector_model=VectorModel(intercepts=array([ 0.0478985 , 0.12198145, 0.14591097, 0.19026117, 0.21318417, + 0.22770334, 0.22810381, 0.06014365, -0.08704274, -0.07443179, + -0.41631926, -0.42444642, -0.1208239 , -0.09458291, -0.08510185, + -0.08890017, -0.09498552]), linear_terms=array([[0., 0., 0.], [0., 0., 0.], [0., 0., 0.], [0., 0., 0.], @@ -1537,12 +1537,882 @@ algorithm_output,"{'states': [State(trustregion=Region(center=array([ 8.7163601 [[0., 0., 0.], [0., 0., 0.], - [0., 0., 0.]]]), scale=4.354435734570826, shift=array([ 8.7163601 , 26.21001302, 43.54435735])), candidate_index=88, candidate_x=array([ 8.71634411, 26.20999216, 43.54422689]), index=88, x=array([ 8.71634411, 26.20999216, 43.54422689]), fval=0.580982924948752, rho=0.16077632892686486, accepted=True, new_indices=array([76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87]), old_indices_used=array([ 0, 74, 75]), old_indices_discarded=array([], dtype=int64), step_length=0.00013307839832203612, relative_step_length=1.0014415694772614, n_evals_per_point=1, n_evals_acceptance=1)], 'tranquilo_history': History for least_squares function with 89 entries., 'multistart_info': {'start_parameters': [array([ 8.7163601 , 26.21001302, 43.54435735]), array([ 8.73056876, 26.22690146, 43.63119684]), array([ 8.61929941, 30.63288475, 44.78622815])], 'local_optima': [{'solution_x': array([ 8.71634411, 26.20999216, 43.54422689]), 'solution_criterion': 0.580982924948752, 'states': [State(trustregion=Region(center=array([ 8.7163601 , 26.21001302, 43.54435735]), radius=4.354435734570826, bounds=Bounds(lower=array([2., 0., 0.]), upper=array([20., 70., 70.]))), model_indices=[0], model=ScalarModel(intercept=0.5809830305379234, linear_terms=array([0., 0., 0.]), square_terms=array([[0., 0., 0.], + [0., 0., 0.]]]), scale=4.886990017445058, shift=array([ 9.12810637, 48.86990017, 23.90047511])), candidate_index=40, candidate_x=array([ 9.20314317, 50.64928872, 26.1365999 ]), index=22, x=array([ 9.21160543, 50.6453772 , 26.13455164]), fval=0.6412533792921618, rho=-0.4286316408626921, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([22, 27, 28, 29, 30, 31, 33, 34, 35, 37, 38, 39]), old_indices_discarded=array([26, 32, 36]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 9.21160543, 50.6453772 , 26.13455164]), radius=0.004772451188911189, bounds=Bounds(lower=array([1.1, 0. , 0. ]), upper=array([ 20., 70., 100.]))), model_indices=array([22, 27, 28, 29, 30, 31, 33, 34, 35, 37, 38, 40]), model=ScalarModel(intercept=0.6412973906154201, linear_terms=array([ 1.75398422e-05, -5.99250886e-06, -2.51011929e-06]), square_terms=array([[2.05767865e-06, 4.69879566e-09, 2.64315982e-09], + [4.69879566e-09, 6.35990905e-11, 1.90355049e-11], + [2.64315982e-09, 1.90355049e-11, 1.83491578e-11]]), scale=0.004772451188911189, shift=array([ 9.21160543, 50.6453772 , 26.13455164])), vector_model=VectorModel(intercepts=array([ 0.0478985 , 0.12198145, 0.14591097, 0.19026117, 0.21318417, + 0.22770334, 0.22810381, 0.06014365, -0.08704274, -0.07443179, + -0.41631926, -0.42444642, -0.1208239 , -0.09458291, -0.08510185, + -0.08890017, -0.09498552]), linear_terms=array([[0., 0., 0.], [0., 0., 0.], - [0., 0., 0.]]), scale=4.354435734570826, shift=array([ 8.7163601 , 26.21001302, 43.54435735])), vector_model=VectorModel(intercepts=array([ 0.05724953, 0.13067265, 0.1523968 , 0.19379396, 0.21975026, - 0.23556517, 0.23562227, 0.08724666, -0.05175769, -0.04146735, - -0.38600879, -0.40563182, -0.07724305, -0.05219358, -0.04259982, - -0.04528797, -0.04943255]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]]), square_terms=array([[[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]]]), scale=4.886990017445058, shift=array([ 9.12810637, 48.86990017, 23.90047511])), candidate_index=41, candidate_x=array([ 9.20724051, 50.64712891, 26.13536112]), index=41, x=array([ 9.20724051, 50.64712891, 26.13536112]), fval=0.6412040518376516, rho=2.769849739315419, accepted=True, new_indices=array([], dtype=int64), old_indices_used=array([22, 27, 28, 29, 30, 31, 33, 34, 35, 37, 38, 40]), old_indices_discarded=array([32, 36, 39]), step_length=0.004772451188911595, relative_step_length=1.000000000000085, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 9.20724051, 50.64712891, 26.13536112]), radius=0.009544902377822378, bounds=Bounds(lower=array([1.1, 0. , 0. ]), upper=array([ 20., 70., 100.]))), model_indices=array([22, 27, 28, 30, 32, 34, 35, 37, 38, 39, 40, 41]), model=ScalarModel(intercept=0.6412558733517228, linear_terms=array([-1.69255546e-05, -4.39895767e-06, -2.08824813e-06]), square_terms=array([[8.21955555e-06, 2.05881180e-08, 6.90866621e-09], + [2.05881180e-08, 1.57618492e-10, 7.22730875e-11], + [6.90866621e-09, 7.22730875e-11, 5.92353119e-11]]), scale=0.009544902377822378, shift=array([ 9.20724051, 50.64712891, 26.13536112])), vector_model=VectorModel(intercepts=array([ 0.0478985 , 0.12198145, 0.14591097, 0.19026117, 0.21318417, + 0.22770334, 0.22810381, 0.06014365, -0.08704274, -0.07443179, + -0.41631926, -0.42444642, -0.1208239 , -0.09458291, -0.08510185, + -0.08890017, -0.09498552]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]]), square_terms=array([[[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]]]), scale=4.886990017445058, shift=array([ 9.12810637, 48.86990017, 23.90047511])), candidate_index=42, candidate_x=array([ 9.21317423, 50.65319986, 26.13972458]), index=41, x=array([ 9.20724051, 50.64712891, 26.13536112]), fval=0.6412040518376516, rho=-5.9786318496293385, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([22, 27, 28, 30, 32, 34, 35, 37, 38, 39, 40, 41]), old_indices_discarded=array([26, 29, 31, 33, 36]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 9.20724051, 50.64712891, 26.13536112]), radius=0.004772451188911189, bounds=Bounds(lower=array([1.1, 0. , 0. ]), upper=array([ 20., 70., 100.]))), model_indices=array([22, 27, 30, 32, 34, 35, 37, 38, 39, 40, 41, 42]), model=ScalarModel(intercept=0.6412588576917913, linear_terms=array([-6.83670642e-06, -1.11357466e-06, -5.72399169e-07]), square_terms=array([[2.05052218e-06, 6.90899197e-09, 1.39972212e-09], + [6.90899197e-09, 9.18556326e-11, 2.86773343e-11], + [1.39972212e-09, 2.86773343e-11, 1.40014692e-11]]), scale=0.004772451188911189, shift=array([ 9.20724051, 50.64712891, 26.13536112])), vector_model=VectorModel(intercepts=array([ 0.0478985 , 0.12198145, 0.14591097, 0.19026117, 0.21318417, + 0.22770334, 0.22810381, 0.06014365, -0.08704274, -0.07443179, + -0.41631926, -0.42444642, -0.1208239 , -0.09458291, 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rho=0.6634184250305409, accepted=True, new_indices=array([], dtype=int64), old_indices_used=array([45, 46, 48, 50, 51, 52, 53, 54, 55, 56, 57, 58]), old_indices_discarded=array([44, 47, 49]), step_length=0.0002982781993076994, relative_step_length=1.0000000000025147, n_evals_per_point=1, n_evals_acceptance=1)], 'tranquilo_history': History for least_squares function with 60 entries., 'multistart_info': {'start_parameters': [array([ 9.20683173, 51.48987537, 25.99186716]), array([ 9.27512208, 46.36962222, 22.93103984]), array([ 9.12810637, 48.86990017, 23.90047511])], 'local_optima': [{'solution_x': array([ 9.20658168, 51.49004107, 25.99177342]), 'solution_criterion': 0.6411987240466468, 'states': [State(trustregion=Region(center=array([ 9.20683173, 51.48987537, 25.99186716]), radius=5.148987537348444, bounds=Bounds(lower=array([1.1, 0. , 0. ]), upper=array([ 20., 70., 100.]))), model_indices=[0], model=ScalarModel(intercept=0.6411988508284691, linear_terms=array([0., 0., 0.]), square_terms=array([[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]]), scale=5.148987537348444, shift=array([ 9.20683173, 51.48987537, 25.99186716])), vector_model=VectorModel(intercepts=array([ 0.04848873, 0.12360457, 0.14833762, 0.19329553, 0.21683843, + 0.23172151, 0.23264264, 0.0658259 , -0.08093415, -0.06795128, + -0.41008598, -0.4187298 , -0.12365674, -0.09727986, -0.0878388 , + -0.09147924, -0.09757891]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]]), square_terms=array([[[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]]]), scale=5.148987537348444, shift=array([ 9.20683173, 51.48987537, 25.99186716])), candidate_index=0, candidate_x=array([ 9.20683173, 51.48987537, 25.99186716]), index=0, x=array([ 9.20683173, 51.48987537, 25.99186716]), fval=0.6411988508284691, rho=nan, accepted=True, new_indices=[0], old_indices_used=[], old_indices_discarded=[], step_length=None, relative_step_length=None, n_evals_per_point=None, n_evals_acceptance=None), State(trustregion=Region(center=array([ 9.20683173, 51.48987537, 25.99186716]), radius=5.148987537348444, bounds=Bounds(lower=array([1.1, 0. , 0. ]), upper=array([ 20., 70., 100.]))), model_indices=array([ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12]), model=ScalarModel(intercept=0.577099034852349, linear_terms=array([-0.05437769, -0.00133237, -0.00445358]), square_terms=array([[ 2.64363755e+00, -1.20940035e-02, -7.41335774e-03], + [-1.20940035e-02, 7.53100996e-05, 9.59315557e-05], + [-7.41335774e-03, 9.59315557e-05, 2.83957639e-04]]), scale=5.148987537348444, shift=array([ 9.20683173, 51.48987537, 25.99186716])), vector_model=VectorModel(intercepts=array([ 0.04848873, 0.12360457, 0.14833762, 0.19329553, 0.21683843, + 0.23172151, 0.23264264, 0.0658259 , -0.08093415, -0.06795128, + -0.41008598, -0.4187298 , -0.12365674, -0.09727986, -0.0878388 , + -0.09147924, -0.09757891]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]]), square_terms=array([[[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]]]), scale=5.148987537348444, shift=array([ 9.20683173, 51.48987537, 25.99186716])), candidate_index=13, candidate_x=array([ 9.33401434, 53.19570811, 30.87305492]), index=0, x=array([ 9.20683173, 51.48987537, 25.99186716]), fval=0.6411988508284691, rho=-0.09810705368372, accepted=False, new_indices=array([ 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12]), old_indices_used=array([0]), old_indices_discarded=array([], dtype=int64), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 9.20683173, 51.48987537, 25.99186716]), radius=2.574493768674222, bounds=Bounds(lower=array([1.1, 0. , 0. ]), upper=array([ 20., 70., 100.]))), model_indices=array([ 0, 1, 2, 3, 4, 5, 6, 8, 9, 10, 11, 12]), model=ScalarModel(intercept=0.5758510743673294, linear_terms=array([-0.0284062 , -0.00246908, -0.00205258]), square_terms=array([[ 6.60453986e-01, -3.47466598e-03, -1.80209326e-03], + [-3.47466598e-03, 4.17175646e-05, 4.54497838e-05], + [-1.80209326e-03, 4.54497838e-05, 6.70501402e-05]]), scale=2.574493768674222, shift=array([ 9.20683173, 51.48987537, 25.99186716])), vector_model=VectorModel(intercepts=array([ 0.04848873, 0.12360457, 0.14833762, 0.19329553, 0.21683843, + 0.23172151, 0.23264264, 0.0658259 , -0.08093415, -0.06795128, + -0.41008598, -0.4187298 , -0.12365674, -0.09727986, -0.0878388 , + -0.09147924, -0.09757891]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]]), square_terms=array([[[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]]]), scale=5.148987537348444, shift=array([ 9.20683173, 51.48987537, 25.99186716])), candidate_index=14, candidate_x=array([ 9.33189635, 53.49930647, 27.60036285]), index=0, x=array([ 9.20683173, 51.48987537, 25.99186716]), fval=0.6411988508284691, rho=-0.13056351453261902, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([ 0, 1, 2, 3, 4, 5, 6, 8, 9, 10, 11, 12]), old_indices_discarded=array([ 7, 13]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 9.20683173, 51.48987537, 25.99186716]), radius=1.287246884337111, bounds=Bounds(lower=array([1.1, 0. , 0. ]), upper=array([ 20., 70., 100.]))), model_indices=array([ 0, 1, 2, 3, 4, 5, 8, 9, 10, 11, 12, 14]), model=ScalarModel(intercept=0.5893107379228858, linear_terms=array([-0.01558663, -0.00510477, 0.0007044 ]), square_terms=array([[ 1.57482213e-01, -2.47144499e-03, 4.20037179e-04], + [-2.47144499e-03, 2.07713086e-04, -1.46683639e-05], + [ 4.20037179e-04, -1.46683639e-05, 1.89757814e-06]]), scale=1.287246884337111, shift=array([ 9.20683173, 51.48987537, 25.99186716])), vector_model=VectorModel(intercepts=array([ 0.04848873, 0.12360457, 0.14833762, 0.19329553, 0.21683843, + 0.23172151, 0.23264264, 0.0658259 , -0.08093415, -0.06795128, + -0.41008598, -0.4187298 , -0.12365674, -0.09727986, -0.0878388 , + -0.09147924, -0.09757891]), linear_terms=array([[0., 0., 0.], [0., 0., 0.], [0., 0., 0.], [0., 0., 0.], @@ -1624,12 +2494,12 @@ algorithm_output,"{'states': [State(trustregion=Region(center=array([ 8.7163601 [[0., 0., 0.], [0., 0., 0.], - [0., 0., 0.]]]), scale=4.354435734570826, shift=array([ 8.7163601 , 26.21001302, 43.54435735])), candidate_index=0, candidate_x=array([ 8.7163601 , 26.21001302, 43.54435735]), index=0, x=array([ 8.7163601 , 26.21001302, 43.54435735]), fval=0.5809830305379233, rho=nan, accepted=True, new_indices=[0], old_indices_used=[], old_indices_discarded=[], step_length=None, relative_step_length=None, n_evals_per_point=None, n_evals_acceptance=None), State(trustregion=Region(center=array([ 8.7163601 , 26.21001302, 43.54435735]), radius=4.354435734570826, bounds=Bounds(lower=array([2., 0., 0.]), upper=array([20., 70., 70.]))), model_indices=array([ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12]), model=ScalarModel(intercept=0.5494101543857126, linear_terms=array([-0.10049343, -0.00119912, -0.0013463 ]), square_terms=array([[ 2.21011540e+00, -3.46388367e-03, -9.65392550e-03], - [-3.46388367e-03, 5.33163535e-05, 9.02566112e-05], - [-9.65392550e-03, 9.02566112e-05, 1.72745213e-04]]), scale=4.354435734570826, shift=array([ 8.7163601 , 26.21001302, 43.54435735])), vector_model=VectorModel(intercepts=array([ 0.05724953, 0.13067265, 0.1523968 , 0.19379396, 0.21975026, - 0.23556517, 0.23562227, 0.08724666, -0.05175769, -0.04146735, - -0.38600879, -0.40563182, -0.07724305, -0.05219358, -0.04259982, - -0.04528797, -0.04943255]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.]]]), scale=5.148987537348444, shift=array([ 9.20683173, 51.48987537, 25.99186716])), candidate_index=15, candidate_x=array([ 9.34996065, 52.76373404, 25.81051104]), index=0, x=array([ 9.20683173, 51.48987537, 25.99186716]), fval=0.6411988508284691, rho=-0.11385902017059198, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([ 0, 1, 2, 3, 4, 5, 8, 9, 10, 11, 12, 14]), old_indices_discarded=array([ 6, 7, 13]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 9.20683173, 51.48987537, 25.99186716]), radius=0.6436234421685555, bounds=Bounds(lower=array([1.1, 0. , 0. ]), upper=array([ 20., 70., 100.]))), model_indices=array([ 0, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27]), model=ScalarModel(intercept=0.6402147674526484, linear_terms=array([-0.00034196, 0.00014716, 0.00011216]), square_terms=array([[3.74756501e-02, 2.15030692e-05, 1.57785121e-05], + [2.15030692e-05, 6.58166572e-08, 3.83598315e-08], + [1.57785121e-05, 3.83598315e-08, 5.78693093e-08]]), scale=0.6436234421685555, shift=array([ 9.20683173, 51.48987537, 25.99186716])), vector_model=VectorModel(intercepts=array([ 0.04848873, 0.12360457, 0.14833762, 0.19329553, 0.21683843, + 0.23172151, 0.23264264, 0.0658259 , -0.08093415, -0.06795128, + -0.41008598, -0.4187298 , -0.12365674, -0.09727986, -0.0878388 , + -0.09147924, -0.09757891]), linear_terms=array([[0., 0., 0.], [0., 0., 0.], [0., 0., 0.], [0., 0., 0.], @@ -1711,12 +2581,12 @@ algorithm_output,"{'states': [State(trustregion=Region(center=array([ 8.7163601 [[0., 0., 0.], [0., 0., 0.], - [0., 0., 0.]]]), scale=4.354435734570826, shift=array([ 8.7163601 , 26.21001302, 43.54435735])), candidate_index=13, candidate_x=array([ 8.93351005, 28.89771693, 47.01135568]), index=0, x=array([ 8.7163601 , 26.21001302, 43.54435735]), fval=0.5809830305379233, rho=-0.558271347973752, accepted=False, new_indices=array([ 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12]), old_indices_used=array([0]), old_indices_discarded=array([], dtype=int64), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 8.7163601 , 26.21001302, 43.54435735]), radius=2.177217867285413, bounds=Bounds(lower=array([2., 0., 0.]), upper=array([20., 70., 70.]))), model_indices=array([ 0, 1, 2, 3, 4, 5, 6, 7, 9, 10, 11, 12]), model=ScalarModel(intercept=0.5525084893634734, linear_terms=array([-0.03730237, -0.00205422, -0.0037379 ]), square_terms=array([[ 5.75556074e-01, -4.87451781e-03, -1.08745730e-02], - [-4.87451781e-03, 1.20368007e-04, 2.44297801e-04], - [-1.08745730e-02, 2.44297801e-04, 5.02318123e-04]]), scale=2.177217867285413, shift=array([ 8.7163601 , 26.21001302, 43.54435735])), vector_model=VectorModel(intercepts=array([ 0.05724953, 0.13067265, 0.1523968 , 0.19379396, 0.21975026, - 0.23556517, 0.23562227, 0.08724666, -0.05175769, -0.04146735, - -0.38600879, -0.40563182, -0.07724305, -0.05219358, -0.04259982, - -0.04528797, -0.04943255]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.]]]), scale=5.148987537348444, shift=array([ 9.20683173, 51.48987537, 25.99186716])), candidate_index=28, candidate_x=array([ 9.21313161, 50.97798884, 25.60175485]), index=0, x=array([ 9.20683173, 51.48987537, 25.99186716]), fval=0.6411988508284691, rho=-0.4308702401838545, accepted=False, new_indices=array([16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27]), old_indices_used=array([ 0, 14, 15]), old_indices_discarded=array([], dtype=int64), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 9.20683173, 51.48987537, 25.99186716]), radius=0.32181172108427775, bounds=Bounds(lower=array([1.1, 0. , 0. ]), upper=array([ 20., 70., 100.]))), model_indices=array([ 0, 16, 17, 18, 19, 21, 22, 23, 24, 25, 26, 27]), model=ScalarModel(intercept=0.640144273855586, linear_terms=array([-2.05822944e-04, -1.09807039e-04, 6.94001699e-05]), square_terms=array([[ 9.36041691e-03, -3.38163136e-06, 9.06517069e-06], + [-3.38163136e-06, 4.99770966e-08, -3.22003356e-08], + [ 9.06517069e-06, -3.22003356e-08, 4.04731428e-08]]), scale=0.32181172108427775, shift=array([ 9.20683173, 51.48987537, 25.99186716])), vector_model=VectorModel(intercepts=array([ 0.04848873, 0.12360457, 0.14833762, 0.19329553, 0.21683843, + 0.23172151, 0.23264264, 0.0658259 , -0.08093415, -0.06795128, + -0.41008598, -0.4187298 , -0.12365674, -0.09727986, -0.0878388 , + -0.09147924, -0.09757891]), linear_terms=array([[0., 0., 0.], [0., 0., 0.], [0., 0., 0.], [0., 0., 0.], @@ -1798,12 +2668,12 @@ algorithm_output,"{'states': [State(trustregion=Region(center=array([ 8.7163601 [[0., 0., 0.], [0., 0., 0.], - [0., 0., 0.]]]), scale=4.354435734570826, shift=array([ 8.7163601 , 26.21001302, 43.54435735])), candidate_index=14, candidate_x=array([ 8.90219766, 27.26532816, 45.51595825]), index=0, x=array([ 8.7163601 , 26.21001302, 43.54435735]), fval=0.5809830305379233, rho=-0.28629030520190707, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([ 0, 1, 2, 3, 4, 5, 6, 7, 9, 10, 11, 12]), old_indices_discarded=array([ 8, 13]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 8.7163601 , 26.21001302, 43.54435735]), radius=1.0886089336427065, bounds=Bounds(lower=array([2., 0., 0.]), upper=array([20., 70., 70.]))), model_indices=array([ 0, 1, 2, 3, 4, 5, 6, 7, 9, 10, 12, 14]), model=ScalarModel(intercept=0.5596299470764778, linear_terms=array([-0.00611761, -0.00353072, -0.0011418 ]), square_terms=array([[ 1.52462308e-01, -4.10493124e-03, -1.51631574e-03], - [-4.10493124e-03, 2.53887208e-04, 9.81815973e-05], - [-1.51631574e-03, 9.81815973e-05, 3.84430453e-05]]), scale=1.0886089336427065, shift=array([ 8.7163601 , 26.21001302, 43.54435735])), vector_model=VectorModel(intercepts=array([ 0.05724953, 0.13067265, 0.1523968 , 0.19379396, 0.21975026, - 0.23556517, 0.23562227, 0.08724666, -0.05175769, -0.04146735, - -0.38600879, -0.40563182, -0.07724305, -0.05219358, -0.04259982, - -0.04528797, -0.04943255]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.]]]), scale=5.148987537348444, shift=array([ 9.20683173, 51.48987537, 25.99186716])), candidate_index=29, candidate_x=array([ 9.21407231, 51.76171238, 25.81970303]), index=0, x=array([ 9.20683173, 51.48987537, 25.99186716]), fval=0.6411988508284691, rho=-0.6555276541732982, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([ 0, 16, 17, 18, 19, 21, 22, 23, 24, 25, 26, 27]), old_indices_discarded=array([15, 20, 28]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 9.20683173, 51.48987537, 25.99186716]), radius=0.16090586054213887, bounds=Bounds(lower=array([1.1, 0. , 0. ]), upper=array([ 20., 70., 100.]))), model_indices=array([ 0, 16, 17, 18, 19, 21, 22, 23, 24, 26, 27, 29]), model=ScalarModel(intercept=0.6401375835808683, linear_terms=array([-1.21532046e-04, 4.55539802e-05, 5.12717895e-05]), square_terms=array([[2.33891702e-03, 2.43888922e-06, 2.77356802e-06], + [2.43888922e-06, 1.42208051e-08, 1.00057806e-08], + [2.77356802e-06, 1.00057806e-08, 1.51206072e-08]]), scale=0.16090586054213887, shift=array([ 9.20683173, 51.48987537, 25.99186716])), vector_model=VectorModel(intercepts=array([ 0.04848873, 0.12360457, 0.14833762, 0.19329553, 0.21683843, + 0.23172151, 0.23264264, 0.0658259 , -0.08093415, -0.06795128, + -0.41008598, -0.4187298 , -0.12365674, -0.09727986, -0.0878388 , + -0.09147924, -0.09757891]), linear_terms=array([[0., 0., 0.], [0., 0., 0.], [0., 0., 0.], [0., 0., 0.], @@ -1885,12 +2755,12 @@ algorithm_output,"{'states': [State(trustregion=Region(center=array([ 8.7163601 [[0., 0., 0.], [0., 0., 0.], - [0., 0., 0.]]]), scale=4.354435734570826, shift=array([ 8.7163601 , 26.21001302, 43.54435735])), candidate_index=15, candidate_x=array([ 8.78953128, 27.24792252, 43.87862902]), index=0, x=array([ 8.7163601 , 26.21001302, 43.54435735]), fval=0.5809830305379233, rho=-0.13557088222916855, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([ 0, 1, 2, 3, 4, 5, 6, 7, 9, 10, 12, 14]), old_indices_discarded=array([ 8, 11, 13]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 8.7163601 , 26.21001302, 43.54435735]), radius=0.5443044668213532, bounds=Bounds(lower=array([2., 0., 0.]), upper=array([20., 70., 70.]))), model_indices=array([ 0, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27]), model=ScalarModel(intercept=0.5805771869323699, linear_terms=array([-2.39835685e-04, 1.49460494e-04, 1.19283566e-05]), square_terms=array([[3.27992106e-02, 7.19591335e-05, 2.68136949e-05], - [7.19591335e-05, 3.22752858e-07, 8.54387610e-08], - [2.68136949e-05, 8.54387610e-08, 5.88930115e-08]]), scale=0.5443044668213532, shift=array([ 8.7163601 , 26.21001302, 43.54435735])), vector_model=VectorModel(intercepts=array([ 0.05724953, 0.13067265, 0.1523968 , 0.19379396, 0.21975026, - 0.23556517, 0.23562227, 0.08724666, -0.05175769, -0.04146735, - -0.38600879, -0.40563182, -0.07724305, -0.05219358, -0.04259982, - -0.04528797, -0.04943255]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.]]]), scale=5.148987537348444, shift=array([ 9.20683173, 51.48987537, 25.99186716])), candidate_index=30, candidate_x=array([ 9.21519997, 51.38314652, 25.87173596]), index=0, x=array([ 9.20683173, 51.48987537, 25.99186716]), fval=0.6411988508284691, rho=-1.2479692844655803, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([ 0, 16, 17, 18, 19, 21, 22, 23, 24, 26, 27, 29]), old_indices_discarded=array([20, 25, 28]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 9.20683173, 51.48987537, 25.99186716]), radius=0.08045293027106944, bounds=Bounds(lower=array([1.1, 0. , 0. ]), upper=array([ 20., 70., 100.]))), model_indices=array([ 0, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42]), model=ScalarModel(intercept=0.6413807790403127, linear_terms=array([-6.87288309e-05, -3.64270026e-05, 8.78179857e-06]), square_terms=array([[ 5.86255249e-04, 2.16800229e-07, -5.03319249e-07], + [ 2.16800229e-07, 5.36195721e-09, -2.57378877e-09], + [-5.03319249e-07, -2.57378877e-09, 3.38987925e-09]]), scale=0.08045293027106944, shift=array([ 9.20683173, 51.48987537, 25.99186716])), vector_model=VectorModel(intercepts=array([ 0.04848873, 0.12360457, 0.14833762, 0.19329553, 0.21683843, + 0.23172151, 0.23264264, 0.0658259 , -0.08093415, -0.06795128, + -0.41008598, -0.4187298 , -0.12365674, -0.09727986, -0.0878388 , + -0.09147924, -0.09757891]), linear_terms=array([[0., 0., 0.], [0., 0., 0.], [0., 0., 0.], [0., 0., 0.], @@ -1972,12 +2842,12 @@ algorithm_output,"{'states': [State(trustregion=Region(center=array([ 8.7163601 [[0., 0., 0.], [0., 0., 0.], - [0., 0., 0.]]]), scale=4.354435734570826, shift=array([ 8.7163601 , 26.21001302, 43.54435735])), candidate_index=28, candidate_x=array([ 8.72154249, 25.66749131, 43.5005631 ]), index=0, x=array([ 8.7163601 , 26.21001302, 43.54435735]), fval=0.5809830305379233, rho=-0.07054714598212536, accepted=False, new_indices=array([16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27]), old_indices_used=array([ 0, 14, 15]), old_indices_discarded=array([], dtype=int64), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 8.7163601 , 26.21001302, 43.54435735]), radius=0.2721522334106766, bounds=Bounds(lower=array([2., 0., 0.]), upper=array([20., 70., 70.]))), model_indices=array([ 0, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 27]), model=ScalarModel(intercept=0.5805345814914069, linear_terms=array([-1.47123164e-04, -1.00826212e-05, 1.86558018e-06]), square_terms=array([[ 8.18773219e-03, -3.04389064e-06, 1.71271905e-05], - [-3.04389064e-06, 1.00762684e-08, -2.18614176e-08], - [ 1.71271905e-05, -2.18614176e-08, 1.18364761e-07]]), scale=0.2721522334106766, shift=array([ 8.7163601 , 26.21001302, 43.54435735])), vector_model=VectorModel(intercepts=array([ 0.05724953, 0.13067265, 0.1523968 , 0.19379396, 0.21975026, - 0.23556517, 0.23562227, 0.08724666, -0.05175769, -0.04146735, - -0.38600879, -0.40563182, -0.07724305, -0.05219358, -0.04259982, - -0.04528797, -0.04943255]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.]]]), scale=5.148987537348444, shift=array([ 9.20683173, 51.48987537, 25.99186716])), candidate_index=43, candidate_x=array([ 9.21565369, 51.56787536, 25.97317301]), index=0, x=array([ 9.20683173, 51.48987537, 25.99186716]), fval=0.6411988508284691, rho=-2.2350763518376344, accepted=False, new_indices=array([31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42]), old_indices_used=array([ 0, 29, 30]), old_indices_discarded=array([], dtype=int64), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 9.20683173, 51.48987537, 25.99186716]), radius=0.04022646513553472, bounds=Bounds(lower=array([1.1, 0. , 0. ]), upper=array([ 20., 70., 100.]))), model_indices=array([ 0, 31, 32, 33, 34, 35, 36, 37, 38, 40, 41, 42]), model=ScalarModel(intercept=0.6413827428619181, linear_terms=array([-5.68830793e-05, -6.97428000e-05, -5.78950371e-06]), square_terms=array([[1.46566718e-04, 1.91014436e-07, 1.56910312e-07], + [1.91014436e-07, 1.58064073e-08, 3.63198578e-09], + [1.56910312e-07, 3.63198578e-09, 7.76262350e-09]]), scale=0.04022646513553472, shift=array([ 9.20683173, 51.48987537, 25.99186716])), vector_model=VectorModel(intercepts=array([ 0.04848873, 0.12360457, 0.14833762, 0.19329553, 0.21683843, + 0.23172151, 0.23264264, 0.0658259 , -0.08093415, -0.06795128, + -0.41008598, -0.4187298 , -0.12365674, -0.09727986, -0.0878388 , + -0.09147924, -0.09757891]), linear_terms=array([[0., 0., 0.], [0., 0., 0.], [0., 0., 0.], [0., 0., 0.], @@ -2059,12 +2929,12 @@ algorithm_output,"{'states': [State(trustregion=Region(center=array([ 8.7163601 [[0., 0., 0.], [0., 0., 0.], - [0., 0., 0.]]]), scale=4.354435734570826, shift=array([ 8.7163601 , 26.21001302, 43.54435735])), candidate_index=29, candidate_x=array([ 8.72148001, 26.49966574, 43.4831919 ]), index=0, x=array([ 8.7163601 , 26.21001302, 43.54435735]), fval=0.5809830305379233, rho=-0.9035564705080065, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([ 0, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 27]), old_indices_discarded=array([15, 26, 28]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 8.7163601 , 26.21001302, 43.54435735]), radius=0.1360761167053383, bounds=Bounds(lower=array([2., 0., 0.]), upper=array([20., 70., 70.]))), model_indices=array([ 0, 17, 18, 19, 20, 21, 22, 23, 24, 25, 27, 29]), model=ScalarModel(intercept=0.5805204784499093, linear_terms=array([-5.38579889e-05, 3.15850486e-05, -1.48626515e-05]), square_terms=array([[2.04967440e-03, 3.29163803e-06, 3.96956751e-06], - [3.29163803e-06, 1.12292861e-08, 1.32171424e-08], - [3.96956751e-06, 1.32171424e-08, 2.27968740e-08]]), scale=0.1360761167053383, shift=array([ 8.7163601 , 26.21001302, 43.54435735])), vector_model=VectorModel(intercepts=array([ 0.05724953, 0.13067265, 0.1523968 , 0.19379396, 0.21975026, - 0.23556517, 0.23562227, 0.08724666, -0.05175769, -0.04146735, - -0.38600879, -0.40563182, -0.07724305, -0.05219358, -0.04259982, - -0.04528797, -0.04943255]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.]]]), scale=5.148987537348444, shift=array([ 9.20683173, 51.48987537, 25.99186716])), candidate_index=44, candidate_x=array([ 9.21725848, 51.52873506, 25.99507102]), index=0, x=array([ 9.20683173, 51.48987537, 25.99186716]), fval=0.6411988508284691, rho=-1.3484993659269786, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([ 0, 31, 32, 33, 34, 35, 36, 37, 38, 40, 41, 42]), old_indices_discarded=array([30, 39, 43]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 9.20683173, 51.48987537, 25.99186716]), radius=0.02011323256776736, bounds=Bounds(lower=array([1.1, 0. , 0. ]), upper=array([ 20., 70., 100.]))), model_indices=array([ 0, 31, 32, 33, 35, 36, 37, 38, 40, 41, 42, 44]), model=ScalarModel(intercept=0.6413942783338986, linear_terms=array([-3.20943867e-05, -3.91002224e-05, -1.05813254e-05]), square_terms=array([[3.67028934e-05, 9.25969229e-08, 7.70162092e-08], + [9.25969229e-08, 6.16329040e-09, 2.79926237e-09], + [7.70162092e-08, 2.79926237e-09, 2.51326114e-09]]), scale=0.02011323256776736, shift=array([ 9.20683173, 51.48987537, 25.99186716])), vector_model=VectorModel(intercepts=array([ 0.04848873, 0.12360457, 0.14833762, 0.19329553, 0.21683843, + 0.23172151, 0.23264264, 0.0658259 , -0.08093415, -0.06795128, + -0.41008598, -0.4187298 , -0.12365674, -0.09727986, -0.0878388 , + -0.09147924, -0.09757891]), linear_terms=array([[0., 0., 0.], [0., 0., 0.], [0., 0., 0.], [0., 0., 0.], @@ -2146,12 +3016,12 @@ algorithm_output,"{'states': [State(trustregion=Region(center=array([ 8.7163601 [[0., 0., 0.], [0., 0., 0.], - [0., 0., 0.]]]), scale=4.354435734570826, shift=array([ 8.7163601 , 26.21001302, 43.54435735])), candidate_index=30, candidate_x=array([ 8.71996125, 26.08650393, 43.60192377]), index=0, x=array([ 8.7163601 , 26.21001302, 43.54435735]), fval=0.5809830305379233, rho=-0.560974012620415, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([ 0, 17, 18, 19, 20, 21, 22, 23, 24, 25, 27, 29]), old_indices_discarded=array([16, 26, 28]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 8.7163601 , 26.21001302, 43.54435735]), radius=0.06803805835266916, bounds=Bounds(lower=array([2., 0., 0.]), upper=array([20., 70., 70.]))), model_indices=array([ 0, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42]), model=ScalarModel(intercept=0.5811362406009375, linear_terms=array([ 5.13417290e-05, -2.24031655e-05, -3.20307025e-05]), square_terms=array([[5.05495050e-04, 3.61720496e-07, 5.45942913e-07], - [3.61720496e-07, 2.17855514e-09, 2.75774644e-09], - [5.45942913e-07, 2.75774644e-09, 4.07900817e-09]]), scale=0.06803805835266916, shift=array([ 8.7163601 , 26.21001302, 43.54435735])), vector_model=VectorModel(intercepts=array([ 0.05724953, 0.13067265, 0.1523968 , 0.19379396, 0.21975026, - 0.23556517, 0.23562227, 0.08724666, -0.05175769, -0.04146735, - -0.38600879, -0.40563182, -0.07724305, -0.05219358, -0.04259982, - -0.04528797, -0.04943255]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.]]]), scale=5.148987537348444, shift=array([ 9.20683173, 51.48987537, 25.99186716])), candidate_index=45, candidate_x=array([ 9.21483693, 51.50785987, 25.99672395]), index=0, x=array([ 9.20683173, 51.48987537, 25.99186716]), fval=0.6411988508284691, rho=-1.8697559665017334, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([ 0, 31, 32, 33, 35, 36, 37, 38, 40, 41, 42, 44]), old_indices_discarded=array([34, 39, 43]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 9.20683173, 51.48987537, 25.99186716]), radius=0.01005661628388368, bounds=Bounds(lower=array([1.1, 0. , 0. ]), upper=array([ 20., 70., 100.]))), model_indices=array([ 0, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57]), model=ScalarModel(intercept=0.6412559421570525, linear_terms=array([-9.51327476e-06, 1.32879771e-05, 8.73910006e-06]), square_terms=array([[ 9.24100090e-06, -4.73635941e-09, -1.50247903e-08], + [-4.73635941e-09, 2.89689424e-10, 7.47144718e-11], + [-1.50247903e-08, 7.47144718e-11, 1.64721337e-10]]), scale=0.01005661628388368, shift=array([ 9.20683173, 51.48987537, 25.99186716])), vector_model=VectorModel(intercepts=array([ 0.04848873, 0.12360457, 0.14833762, 0.19329553, 0.21683843, + 0.23172151, 0.23264264, 0.0658259 , -0.08093415, -0.06795128, + -0.41008598, -0.4187298 , -0.12365674, -0.09727986, -0.0878388 , + -0.09147924, -0.09757891]), linear_terms=array([[0., 0., 0.], [0., 0., 0.], [0., 0., 0.], [0., 0., 0.], @@ -2233,12 +3103,12 @@ algorithm_output,"{'states': [State(trustregion=Region(center=array([ 8.7163601 [[0., 0., 0.], [0., 0., 0.], - [0., 0., 0.]]]), scale=4.354435734570826, shift=array([ 8.7163601 , 26.21001302, 43.54435735])), candidate_index=43, candidate_x=array([ 8.70986512, 26.24896623, 43.60005524]), index=0, x=array([ 8.7163601 , 26.21001302, 43.54435735]), fval=0.5809830305379233, rho=-0.8471869049261229, accepted=False, new_indices=array([31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42]), old_indices_used=array([ 0, 29, 30]), old_indices_discarded=array([], dtype=int64), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 8.7163601 , 26.21001302, 43.54435735]), radius=0.03401902917633458, bounds=Bounds(lower=array([2., 0., 0.]), upper=array([20., 70., 70.]))), model_indices=array([ 0, 31, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42]), model=ScalarModel(intercept=0.5811459446716418, linear_terms=array([ 2.15988882e-05, -1.47914448e-05, -5.52422900e-06]), square_terms=array([[ 1.26489115e-04, 1.09571037e-07, 3.94365824e-08], - [ 1.09571037e-07, 2.78995467e-09, -1.24194007e-10], - [ 3.94365824e-08, -1.24194007e-10, 2.35991172e-10]]), scale=0.03401902917633458, shift=array([ 8.7163601 , 26.21001302, 43.54435735])), vector_model=VectorModel(intercepts=array([ 0.05724953, 0.13067265, 0.1523968 , 0.19379396, 0.21975026, - 0.23556517, 0.23562227, 0.08724666, -0.05175769, -0.04146735, - -0.38600879, -0.40563182, -0.07724305, -0.05219358, -0.04259982, - -0.04528797, -0.04943255]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.]]]), scale=5.148987537348444, shift=array([ 9.20683173, 51.48987537, 25.99186716])), candidate_index=58, candidate_x=array([ 9.21046974, 51.48202748, 25.98670836]), index=0, x=array([ 9.20683173, 51.48987537, 25.99186716]), fval=0.6411988508284691, rho=-2.2048759160947164, accepted=False, new_indices=array([46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57]), old_indices_used=array([ 0, 44, 45]), old_indices_discarded=array([], dtype=int64), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 9.20683173, 51.48987537, 25.99186716]), radius=0.00502830814194184, bounds=Bounds(lower=array([1.1, 0. , 0. ]), upper=array([ 20., 70., 100.]))), model_indices=array([ 0, 46, 47, 48, 49, 50, 51, 52, 54, 55, 56, 57]), model=ScalarModel(intercept=0.6412532241492871, linear_terms=array([-3.16145510e-06, 3.88469830e-06, 1.93075386e-06]), square_terms=array([[ 2.30697473e-06, -2.42890651e-09, -2.37176868e-09], + [-2.42890651e-09, 3.85116505e-11, 7.38815414e-12], + [-2.37176868e-09, 7.38815414e-12, 3.61043992e-11]]), scale=0.00502830814194184, shift=array([ 9.20683173, 51.48987537, 25.99186716])), vector_model=VectorModel(intercepts=array([ 0.04848873, 0.12360457, 0.14833762, 0.19329553, 0.21683843, + 0.23172151, 0.23264264, 0.0658259 , -0.08093415, -0.06795128, + -0.41008598, -0.4187298 , -0.12365674, -0.09727986, -0.0878388 , + -0.09147924, -0.09757891]), linear_terms=array([[0., 0., 0.], [0., 0., 0.], [0., 0., 0.], [0., 0., 0.], @@ -2320,12 +3190,12 @@ algorithm_output,"{'states': [State(trustregion=Region(center=array([ 8.7163601 [[0., 0., 0.], [0., 0., 0.], - [0., 0., 0.]]]), scale=4.354435734570826, shift=array([ 8.7163601 , 26.21001302, 43.54435735])), candidate_index=44, candidate_x=array([ 8.7111716 , 26.2417183 , 43.55620009]), index=0, x=array([ 8.7163601 , 26.21001302, 43.54435735]), fval=0.5809830305379233, rho=-2.4752213951973463, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([ 0, 31, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42]), old_indices_discarded=array([30, 32, 43]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 8.7163601 , 26.21001302, 43.54435735]), radius=0.01700951458816729, bounds=Bounds(lower=array([2., 0., 0.]), upper=array([20., 70., 70.]))), model_indices=array([ 0, 31, 33, 35, 36, 37, 38, 39, 40, 41, 42, 44]), model=ScalarModel(intercept=0.5811498347258051, linear_terms=array([ 8.19881459e-06, -1.98216693e-05, -8.47308716e-06]), square_terms=array([[3.16511989e-05, 9.81407579e-08, 4.20337638e-08], - [9.81407579e-08, 3.30385011e-09, 1.09448244e-09], - [4.20337638e-08, 1.09448244e-09, 5.17961167e-10]]), scale=0.01700951458816729, shift=array([ 8.7163601 , 26.21001302, 43.54435735])), vector_model=VectorModel(intercepts=array([ 0.05724953, 0.13067265, 0.1523968 , 0.19379396, 0.21975026, - 0.23556517, 0.23562227, 0.08724666, -0.05175769, -0.04146735, - -0.38600879, -0.40563182, -0.07724305, -0.05219358, -0.04259982, - -0.04528797, -0.04943255]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.]]]), scale=5.148987537348444, shift=array([ 9.20683173, 51.48987537, 25.99186716])), candidate_index=59, candidate_x=array([ 9.20905677, 51.48583314, 25.98985865]), index=0, x=array([ 9.20683173, 51.48987537, 25.99186716]), fval=0.6411988508284691, rho=-4.375996109540071, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([ 0, 46, 47, 48, 49, 50, 51, 52, 54, 55, 56, 57]), old_indices_discarded=array([45, 53, 58]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 9.20683173, 51.48987537, 25.99186716]), radius=0.00251415407097092, bounds=Bounds(lower=array([1.1, 0. , 0. ]), upper=array([ 20., 70., 100.]))), model_indices=array([ 0, 47, 48, 49, 50, 51, 52, 54, 55, 56, 57, 59]), model=ScalarModel(intercept=0.641257540030709, linear_terms=array([-1.56329417e-06, 5.26882951e-06, 4.74793679e-06]), square_terms=array([[ 5.76813598e-07, -1.21814516e-09, -1.24595987e-09], + [-1.21814516e-09, 3.52205771e-11, 3.14265057e-11], + [-1.24595987e-09, 3.14265057e-11, 4.30058797e-11]]), scale=0.00251415407097092, shift=array([ 9.20683173, 51.48987537, 25.99186716])), vector_model=VectorModel(intercepts=array([ 0.04848873, 0.12360457, 0.14833762, 0.19329553, 0.21683843, + 0.23172151, 0.23264264, 0.0658259 , -0.08093415, -0.06795128, + -0.41008598, -0.4187298 , -0.12365674, -0.09727986, -0.0878388 , + -0.09147924, -0.09757891]), linear_terms=array([[0., 0., 0.], [0., 0., 0.], [0., 0., 0.], [0., 0., 0.], @@ -2407,12 +3277,12 @@ algorithm_output,"{'states': [State(trustregion=Region(center=array([ 8.7163601 [[0., 0., 0.], [0., 0., 0.], - [0., 0., 0.]]]), scale=4.354435734570826, shift=array([ 8.7163601 , 26.21001302, 43.54435735])), candidate_index=45, candidate_x=array([ 8.71370725, 26.22563044, 43.55103349]), index=0, x=array([ 8.7163601 , 26.21001302, 43.54435735]), fval=0.5809830305379233, rho=-1.638710716456882, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([ 0, 31, 33, 35, 36, 37, 38, 39, 40, 41, 42, 44]), old_indices_discarded=array([32, 34, 43]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 8.7163601 , 26.21001302, 43.54435735]), radius=0.008504757294083645, bounds=Bounds(lower=array([2., 0., 0.]), upper=array([20., 70., 70.]))), model_indices=array([ 0, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57]), model=ScalarModel(intercept=0.5810060157553625, linear_terms=array([-2.44013081e-05, 2.00200467e-06, -1.83538122e-06]), square_terms=array([[ 7.96683033e-06, -8.28976078e-09, 4.99596045e-09], - [-8.28976078e-09, 1.35876689e-10, -1.12232380e-10], - [ 4.99596045e-09, -1.12232380e-10, 1.03220726e-10]]), scale=0.008504757294083645, shift=array([ 8.7163601 , 26.21001302, 43.54435735])), vector_model=VectorModel(intercepts=array([ 0.05724953, 0.13067265, 0.1523968 , 0.19379396, 0.21975026, - 0.23556517, 0.23562227, 0.08724666, -0.05175769, -0.04146735, - -0.38600879, -0.40563182, -0.07724305, -0.05219358, -0.04259982, - -0.04528797, -0.04943255]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.]]]), scale=5.148987537348444, shift=array([ 9.20683173, 51.48987537, 25.99186716])), candidate_index=60, candidate_x=array([ 9.20735201, 51.48797467, 25.99015438]), index=0, x=array([ 9.20683173, 51.48987537, 25.99186716]), fval=0.6411988508284691, rho=-0.8818739691224265, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([ 0, 47, 48, 49, 50, 51, 52, 54, 55, 56, 57, 59]), old_indices_discarded=array([46, 53, 58]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 9.20683173, 51.48987537, 25.99186716]), radius=0.00125707703548546, bounds=Bounds(lower=array([1.1, 0. , 0. ]), upper=array([ 20., 70., 100.]))), model_indices=array([ 0, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72]), model=ScalarModel(intercept=0.6412049552732294, linear_terms=array([ 3.72377171e-06, -1.82881098e-06, -5.03992414e-07]), square_terms=array([[1.46537462e-07, 7.87116195e-10, 2.29063663e-10], + [7.87116195e-10, 1.39179684e-11, 3.03878402e-12], + [2.29063663e-10, 3.03878402e-12, 8.63730755e-13]]), scale=0.00125707703548546, shift=array([ 9.20683173, 51.48987537, 25.99186716])), vector_model=VectorModel(intercepts=array([ 0.04848873, 0.12360457, 0.14833762, 0.19329553, 0.21683843, + 0.23172151, 0.23264264, 0.0658259 , -0.08093415, -0.06795128, + -0.41008598, -0.4187298 , -0.12365674, -0.09727986, -0.0878388 , + -0.09147924, -0.09757891]), linear_terms=array([[0., 0., 0.], [0., 0., 0.], [0., 0., 0.], [0., 0., 0.], @@ -2494,12 +3364,12 @@ algorithm_output,"{'states': [State(trustregion=Region(center=array([ 8.7163601 [[0., 0., 0.], [0., 0., 0.], - [0., 0., 0.]]]), scale=4.354435734570826, shift=array([ 8.7163601 , 26.21001302, 43.54435735])), candidate_index=58, candidate_x=array([ 8.72480793, 26.21067241, 43.54362912]), index=0, x=array([ 8.7163601 , 26.21001302, 43.54435735]), fval=0.5809830305379233, rho=-1.7285305581264891, accepted=False, new_indices=array([46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57]), old_indices_used=array([ 0, 44, 45]), old_indices_discarded=array([], dtype=int64), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 8.7163601 , 26.21001302, 43.54435735]), radius=0.004252378647041822, bounds=Bounds(lower=array([2., 0., 0.]), upper=array([20., 70., 70.]))), model_indices=array([ 0, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 58]), model=ScalarModel(intercept=0.5810059947082536, linear_terms=array([-8.13588391e-06, -6.46820598e-07, -3.84429557e-06]), square_terms=array([[ 1.97355344e-06, -3.12745979e-10, 4.93097236e-09], - [-3.12745979e-10, 1.61347657e-10, -1.79142315e-11], - [ 4.93097236e-09, -1.79142315e-11, 3.42610125e-11]]), scale=0.004252378647041822, shift=array([ 8.7163601 , 26.21001302, 43.54435735])), vector_model=VectorModel(intercepts=array([ 0.05724953, 0.13067265, 0.1523968 , 0.19379396, 0.21975026, - 0.23556517, 0.23562227, 0.08724666, -0.05175769, -0.04146735, - -0.38600879, -0.40563182, -0.07724305, -0.05219358, -0.04259982, - -0.04528797, -0.04943255]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.]]]), scale=5.148987537348444, shift=array([ 9.20683173, 51.48987537, 25.99186716])), candidate_index=73, candidate_x=array([ 9.20572253, 51.49044404, 25.99203004]), index=0, x=array([ 9.20683173, 51.48987537, 25.99186716]), fval=0.6411988508284691, rho=-2.968221572845718, accepted=False, new_indices=array([61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72]), old_indices_used=array([ 0, 59, 60]), old_indices_discarded=array([], dtype=int64), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 9.20683173, 51.48987537, 25.99186716]), radius=0.00062853851774273, bounds=Bounds(lower=array([1.1, 0. , 0. ]), upper=array([ 20., 70., 100.]))), model_indices=array([ 0, 61, 62, 63, 64, 66, 67, 69, 70, 71, 72, 73]), model=ScalarModel(intercept=0.6412066960749747, linear_terms=array([ 9.00045805e-07, -5.31489227e-07, 8.19697450e-07]), square_terms=array([[ 3.69602827e-08, 8.29347553e-11, -5.74182412e-11], + [ 8.29347553e-11, 1.14617076e-12, -7.27051952e-13], + [-5.74182412e-11, -7.27051952e-13, 1.51026310e-12]]), scale=0.00062853851774273, shift=array([ 9.20683173, 51.48987537, 25.99186716])), vector_model=VectorModel(intercepts=array([ 0.04848873, 0.12360457, 0.14833762, 0.19329553, 0.21683843, + 0.23172151, 0.23264264, 0.0658259 , -0.08093415, -0.06795128, + -0.41008598, -0.4187298 , -0.12365674, -0.09727986, -0.0878388 , + -0.09147924, -0.09757891]), linear_terms=array([[0., 0., 0.], [0., 0., 0.], [0., 0., 0.], [0., 0., 0.], @@ -2581,12 +3451,12 @@ algorithm_output,"{'states': [State(trustregion=Region(center=array([ 8.7163601 [[0., 0., 0.], [0., 0., 0.], - [0., 0., 0.]]]), scale=4.354435734570826, shift=array([ 8.7163601 , 26.21001302, 43.54435735])), candidate_index=59, candidate_x=array([ 8.72022764, 26.21084589, 43.54591659]), index=0, x=array([ 8.7163601 , 26.21001302, 43.54435735]), fval=0.5809830305379233, rho=-2.6934710432582296, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([ 0, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 58]), old_indices_discarded=array([45, 56, 57]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 8.7163601 , 26.21001302, 43.54435735]), radius=0.002126189323520911, bounds=Bounds(lower=array([2., 0., 0.]), upper=array([20., 70., 70.]))), model_indices=array([ 0, 47, 48, 49, 50, 51, 52, 53, 54, 55, 58, 59]), model=ScalarModel(intercept=0.5810059980495079, linear_terms=array([-4.03231693e-06, -5.25555887e-07, -2.23095895e-06]), square_terms=array([[ 4.93387827e-07, -2.69532463e-10, 1.04721040e-09], - [-2.69532463e-10, 7.48188612e-12, 1.98300290e-11], - [ 1.04721040e-09, 1.98300290e-11, 9.63514775e-11]]), scale=0.002126189323520911, shift=array([ 8.7163601 , 26.21001302, 43.54435735])), vector_model=VectorModel(intercepts=array([ 0.05724953, 0.13067265, 0.1523968 , 0.19379396, 0.21975026, - 0.23556517, 0.23562227, 0.08724666, -0.05175769, -0.04146735, - -0.38600879, -0.40563182, -0.07724305, -0.05219358, -0.04259982, - -0.04528797, -0.04943255]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.]]]), scale=5.148987537348444, shift=array([ 9.20683173, 51.48987537, 25.99186716])), candidate_index=74, candidate_x=array([ 9.20641163, 51.49013045, 25.99147378]), index=0, x=array([ 9.20683173, 51.48987537, 25.99186716]), fval=0.6411988508284691, rho=-0.8803124320987271, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([ 0, 61, 62, 63, 64, 66, 67, 69, 70, 71, 72, 73]), old_indices_discarded=array([60, 65, 68]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 9.20683173, 51.48987537, 25.99186716]), radius=0.000314269258871365, bounds=Bounds(lower=array([1.1, 0. , 0. ]), upper=array([ 20., 70., 100.]))), model_indices=array([ 0, 61, 62, 63, 64, 66, 67, 69, 70, 71, 72, 74]), model=ScalarModel(intercept=0.6412058603389366, linear_terms=array([ 8.89707068e-07, -5.84463472e-07, 3.30323888e-07]), square_terms=array([[ 9.19824922e-09, 3.54441471e-11, -1.06455208e-11], + [ 3.54441471e-11, 8.88211681e-13, -3.88896604e-13], + [-1.06455208e-11, -3.88896604e-13, 2.67769208e-13]]), scale=0.000314269258871365, shift=array([ 9.20683173, 51.48987537, 25.99186716])), vector_model=VectorModel(intercepts=array([ 0.04848873, 0.12360457, 0.14833762, 0.19329553, 0.21683843, + 0.23172151, 0.23264264, 0.0658259 , -0.08093415, -0.06795128, + -0.41008598, -0.4187298 , -0.12365674, -0.09727986, -0.0878388 , + -0.09147924, -0.09757891]), linear_terms=array([[0., 0., 0.], [0., 0., 0.], [0., 0., 0.], [0., 0., 0.], @@ -2668,12 +3538,12 @@ algorithm_output,"{'states': [State(trustregion=Region(center=array([ 8.7163601 [[0., 0., 0.], [0., 0., 0.], - [0., 0., 0.]]]), scale=4.354435734570826, shift=array([ 8.7163601 , 26.21001302, 43.54435735])), candidate_index=60, candidate_x=array([ 8.71821579, 26.21037748, 43.54532909]), index=0, x=array([ 8.7163601 , 26.21001302, 43.54435735]), fval=0.5809830305379233, rho=-5.430468463123208, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([ 0, 47, 48, 49, 50, 51, 52, 53, 54, 55, 58, 59]), old_indices_discarded=array([46, 56, 57]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 8.7163601 , 26.21001302, 43.54435735]), radius=0.0010630946617604556, bounds=Bounds(lower=array([2., 0., 0.]), upper=array([20., 70., 70.]))), model_indices=array([ 0, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72]), model=ScalarModel(intercept=0.5809896098134266, linear_terms=array([ 5.88223897e-06, -1.55577712e-06, -1.64353073e-06]), square_terms=array([[ 1.20376454e-07, 2.16332482e-10, -2.81822174e-10], - [ 2.16332482e-10, 3.19650170e-12, 4.38885234e-12], - [-2.81822174e-10, 4.38885234e-12, 5.06103427e-11]]), scale=0.0010630946617604556, shift=array([ 8.7163601 , 26.21001302, 43.54435735])), vector_model=VectorModel(intercepts=array([ 0.05724953, 0.13067265, 0.1523968 , 0.19379396, 0.21975026, - 0.23556517, 0.23562227, 0.08724666, -0.05175769, -0.04146735, - -0.38600879, -0.40563182, -0.07724305, -0.05219358, -0.04259982, - -0.04528797, -0.04943255]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.]]]), scale=5.148987537348444, shift=array([ 9.20683173, 51.48987537, 25.99186716])), candidate_index=75, candidate_x=array([ 9.20658168, 51.49004107, 25.99177342]), index=75, x=array([ 9.20658168, 51.49004107, 25.99177342]), fval=0.6411987240466468, rho=0.11404565445920974, accepted=True, new_indices=array([], dtype=int64), old_indices_used=array([ 0, 61, 62, 63, 64, 66, 67, 69, 70, 71, 72, 74]), old_indices_discarded=array([65, 68, 73]), step_length=0.00031426925887290564, relative_step_length=1.0000000000049023, n_evals_per_point=1, n_evals_acceptance=1)], 'message': 'Absolute criterion change smaller than tolerance.', 'tranquilo_history': History for least_squares function with 76 entries., 'history': {'params': [{'CRRA': 9.206831729527266, 'BeqShift': 51.48987537348444, 'BeqFac': 25.99186716077577}, {'CRRA': 10.645065744515577, 'BeqShift': 54.07206826772235, 'BeqFac': 21.775727287046788}, {'CRRA': 5.898143611067358, 'BeqShift': 53.899241292871714, 'BeqFac': 22.867829475179303}, {'CRRA': 4.831042590899532, 'BeqShift': 53.73729315064104, 'BeqFac': 27.512937642034817}, {'CRRA': 8.714853844435495, 'BeqShift': 46.36453575591438, 'BeqFac': 25.961466093079782}, {'CRRA': 8.436330431999226, 'BeqShift': 49.57113103737977, 'BeqFac': 30.707460504454108}, {'CRRA': 4.674429830162727, 'BeqShift': 49.08329856628939, 'BeqFac': 26.41352312655501}, {'CRRA': 11.508609883596527, 'BeqShift': 56.07824554848442, 'BeqFac': 25.59093184630501}, {'CRRA': 13.317600605658994, 'BeqShift': 50.164100452681794, 'BeqFac': 23.18901633239281}, {'CRRA': 8.524923222134564, 'BeqShift': 55.01636090094755, 'BeqFac': 29.681172416770217}, {'CRRA': 7.949040233708621, 'BeqShift': 49.02743831382652, 'BeqFac': 21.648315970788577}, {'CRRA': 12.898889610055392, 'BeqShift': 48.28707042221219, 'BeqFac': 27.611379961190053}, {'CRRA': 13.189106930605947, 'BeqShift': 52.854100357866734, 'BeqFac': 28.95707323702586}, {'CRRA': 9.334014335528215, 'BeqShift': 53.19570810758337, 'BeqFac': 30.87305491840859}, {'CRRA': 9.331896347838615, 'BeqShift': 53.499306466487155, 'BeqFac': 27.600362850409002}, {'CRRA': 9.34996064759815, 'BeqShift': 52.76373403744627, 'BeqFac': 25.8105110401989}, {'CRRA': 8.768145155763168, 'BeqShift': 51.15270853472118, 'BeqFac': 26.320688918186082}, {'CRRA': 9.336314028921963, 'BeqShift': 50.95995044416142, 'BeqFac': 26.333429803250553}, {'CRRA': 9.807719976610574, 'BeqShift': 51.29466255520573, 'BeqFac': 26.11465317547506}, {'CRRA': 8.89542891591178, 'BeqShift': 52.000746158841054, 'BeqFac': 26.2291232748179}, {'CRRA': 9.508492419887414, 'BeqShift': 51.4419044962169, 'BeqFac': 25.425341999697707}, {'CRRA': 9.149333596877364, 'BeqShift': 51.55590706355393, 'BeqFac': 26.629507275540547}, {'CRRA': 9.559434901173226, 'BeqShift': 51.86378059124025, 'BeqFac': 26.379316546875536}, {'CRRA': 9.020913407532865, 'BeqShift': 51.83633373290359, 'BeqFac': 25.482306449923495}, {'CRRA': 8.586324176646961, 'BeqShift': 51.643847532229756, 'BeqFac': 25.917610265751122}, {'CRRA': 9.351451479392471, 'BeqShift': 50.92347860605638, 'BeqFac': 25.72255142580124}, {'CRRA': 9.685109175598889, 'BeqShift': 51.875183342908095, 'BeqFac': 25.79941044203952}, {'CRRA': 8.813607918284164, 'BeqShift': 51.15149494486946, 'BeqFac': 25.610914597966836}, {'CRRA': 9.213131607257464, 'BeqShift': 50.97798883637481, 'BeqFac': 25.601754852662797}, {'CRRA': 9.214072305669143, 'BeqShift': 51.76171237766068, 'BeqFac': 25.819703029938704}, {'CRRA': 9.215199966232754, 'BeqShift': 51.383146519484995, 'BeqFac': 25.871735957845736}, {'CRRA': 9.216716853924463, 'BeqShift': 51.45554902814732, 'BeqFac': 26.063955026055925}, {'CRRA': 9.209001964927008, 'BeqShift': 51.57027756477344, 'BeqFac': 25.99000928472032}, {'CRRA': 9.260948249030404, 'BeqShift': 51.459961040179294, 'BeqFac': 25.940396693816776}, {'CRRA': 9.164115003882157, 'BeqShift': 51.48828419604994, 'BeqFac': 25.923709817123495}, {'CRRA': 9.152415514988588, 'BeqShift': 51.51127945983985, 'BeqFac': 25.936609449352183}, {'CRRA': 9.258945844608023, 'BeqShift': 51.43617836453795, 'BeqFac': 26.021420912293166}, {'CRRA': 9.13765155127113, 'BeqShift': 51.520258306282926, 'BeqFac': 26.019501456862578}, {'CRRA': 9.13805410331009, 'BeqShift': 51.465500109866035, 'BeqFac': 26.02575165051171}, {'CRRA': 9.256392255530317, 'BeqShift': 51.42908605270587, 'BeqFac': 25.973948267651938}, {'CRRA': 9.16002591030256, 'BeqShift': 51.54859841761539, 'BeqFac': 25.96299687563862}, {'CRRA': 9.191361442109994, 'BeqShift': 51.53153099502889, 'BeqFac': 26.058935434871454}, {'CRRA': 9.28552488291613, 'BeqShift': 51.5051431471955, 'BeqFac': 25.998719655564255}, {'CRRA': 9.215653691748056, 'BeqShift': 51.56787535677344, 'BeqFac': 25.973173007733177}, {'CRRA': 9.217258479367231, 'BeqShift': 51.52873506174412, 'BeqFac': 25.99507101751433}, {'CRRA': 9.214836927573717, 'BeqShift': 51.50785986872361, 'BeqFac': 25.996723952354124}, {'CRRA': 9.209651766210712, 'BeqShift': 51.49513663085736, 'BeqFac': 25.99996049723493}, {'CRRA': 9.208701255170737, 'BeqShift': 51.49622402762192, 'BeqFac': 25.98429517321686}, {'CRRA': 9.215660055602429, 'BeqShift': 51.48515334501299, 'BeqFac': 25.990919196163183}, {'CRRA': 9.206523852476087, 'BeqShift': 51.47983630391069, 'BeqFac': 25.99135939616887}, {'CRRA': 9.215593617070299, 'BeqShift': 51.494466933010806, 'BeqFac': 25.990055410550067}, {'CRRA': 9.200600029211254, 'BeqShift': 51.489408082474476, 'BeqFac': 25.983987878996018}, {'CRRA': 9.202056910518746, 'BeqShift': 51.4985986022183, 'BeqFac': 25.99036985820988}, {'CRRA': 9.199952271658832, 'BeqShift': 51.494158012124466, 'BeqFac': 25.997822628582473}, {'CRRA': 9.202832918600851, 'BeqShift': 51.48461895430094, 'BeqFac': 25.99945103179415}, {'CRRA': 9.197631593711648, 'BeqShift': 51.4859009692788, 'BeqFac': 25.9910322097199}, {'CRRA': 9.212388436732526, 'BeqShift': 51.486760833293516, 'BeqFac': 25.999649074134023}, {'CRRA': 9.209709692582527, 'BeqShift': 51.485589254001, 'BeqFac': 25.98323686301106}, {'CRRA': 9.210469735704372, 'BeqShift': 51.4820274750257, 'BeqFac': 25.986708362239256}, {'CRRA': 9.209056767205885, 'BeqShift': 51.485833142057444, 'BeqFac': 25.989858650594726}, {'CRRA': 9.207352009637313, 'BeqShift': 51.487974673061665, 'BeqFac': 25.990154384045987}, {'CRRA': 9.206033267962942, 'BeqShift': 51.48892847027486, 'BeqFac': 25.99165250729892}, {'CRRA': 9.20625076627364, 'BeqShift': 51.48954487612994, 'BeqFac': 25.99080250314547}, {'CRRA': 9.207385437338509, 'BeqShift': 51.4901041143817, 'BeqFac': 25.990762023709685}, {'CRRA': 9.20786345727462, 'BeqShift': 51.48925106513229, 'BeqFac': 25.99151216836751}, {'CRRA': 9.206699996184838, 'BeqShift': 51.49044175026341, 'BeqFac': 25.99298165902336}, {'CRRA': 9.207890451003037, 'BeqShift': 51.490550648528775, 'BeqFac': 25.99180923734023}, {'CRRA': 9.205641049397624, 'BeqShift': 51.49022640393504, 'BeqFac': 25.992065405888624}, {'CRRA': 9.207123731752882, 'BeqShift': 51.48870624359994, 'BeqFac': 25.99222508910179}, {'CRRA': 9.206871681897509, 'BeqShift': 51.491119753601566, 'BeqFac': 25.992040840381208}, {'CRRA': 9.20627785134761, 'BeqShift': 51.49072642980771, 'BeqFac': 25.99112610425305}, {'CRRA': 9.207689904457064, 'BeqShift': 51.48974575980235, 'BeqFac': 25.992776544499193}, {'CRRA': 9.206213144709368, 'BeqShift': 51.489361553265844, 'BeqFac': 25.99283338242693}, {'CRRA': 9.205722528052792, 'BeqShift': 51.49044404355336, 'BeqFac': 25.99203003838284}, {'CRRA': 9.206411630301693, 'BeqShift': 51.49013045462568, 'BeqFac': 25.99147378047824}, {'CRRA': 9.206581683381966, 'BeqShift': 51.49004107027674, 'BeqFac': 25.991773423561632}], 'criterion': [0.6411988508284691, 0.7136701554488605, 1.1553085127439813, 1.6619035528363348, 0.6504948960140015, 0.6639451678306449, 1.7607975696784457, 0.8253755448011229, 1.2439318019269798, 0.6588184500529425, 0.7041559181497187, 1.1206043415760254, 1.2046592051476548, 0.6417198728389927, 0.6417144055001947, 0.6418917111895248, 0.6486031736486461, 0.6417108151257079, 0.6542291407170552, 0.6452036132572929, 0.6441713894463951, 0.6416200619812618, 0.6452949238884177, 0.642921991646109, 0.6559282000407003, 0.6419383920000038, 0.6492863049409738, 0.6473575114093272, 0.641279330621222, 0.6412855638727839, 0.641288495076587, 0.6412989045079037, 0.6412206663047342, 0.6415788206576513, 0.6414585261551051, 0.6415322264833758, 0.6415878833754038, 0.6418151874407122, 0.6418071545085757, 0.6416102719258475, 0.6414745280854367, 0.641286085725572, 0.6415895986896133, 0.6412912258239737, 0.6413034891294414, 0.6412873656104298, 0.6412260570112958, 0.6412189480175701, 0.6412912662026417, 0.6411990307875036, 0.6412908448226428, 0.6412881531688578, 0.6412797780147156, 0.6412928715551321, 0.6412706312266355, 0.6412870264856968, 0.6412663965848409, 0.6412268431063756, 0.6412378441264139, 0.6412210191801184, 0.6412054900518386, 0.6412059287684259, 0.6412025159963317, 0.6412059582365031, 0.6412123451799037, 0.6411983995301935, 0.6412126350810481, 0.6412121905286331, 0.6412026255836385, 0.6411993681322627, 0.6412020947202761, 0.6412101244767981, 0.641203101264691, 0.6412110847442477, 0.6412000146663274, 0.6411987240466468], 'runtime': [0.0, 1.7674728150013834, 1.971279171993956, 2.1699622180021834, 2.4078327319875825, 2.6349312469828874, 2.8703876420040615, 3.0949717510084156, 3.331537355988985, 3.5810636919923127, 3.7896313270030078, 4.032132853986695, 4.268133122008294, 5.7164638779941015, 7.061364024004433, 8.404509437998058, 10.2552733909979, 10.469754358986393, 10.700817857985385, 10.935404510004446, 11.156862239993643, 11.354435465007555, 11.626386560994433, 11.879323094006395, 12.171966446010629, 12.425181676982902, 12.670657834009035, 12.888932864996605, 14.365909608983202, 15.711069712007884, 17.080602344998624, 18.97552325000288, 19.160451968986308, 19.375511763006216, 19.60766480700113, 19.85564505698858, 20.04778404100216, 20.298691281990614, 20.54271566699026, 20.797930906002875, 21.058459894004045, 21.340124403999653, 21.56825467100134, 23.25028569099959, 24.63702903498779, 26.02356418099953, 27.74768948700512, 27.94462815899169, 28.154294089006726, 28.355741470004432, 28.71203763000085, 28.931574468006147, 29.164977904001717, 29.363440007989993, 29.5702488120005, 29.8512691789947, 30.101471366011538, 30.310745497001335, 32.004218265006784, 33.50335030199494, 34.96903544300585, 36.74690315898624, 36.96303538099164, 37.17741673300043, 37.41295213898411, 37.66523804501048, 37.88733551898622, 38.11805283499416, 38.390439902985236, 38.58656119299121, 39.043486090988154, 39.249697869003285, 39.467651521990774, 41.00770620300318, 42.36208155300119, 43.689884113002336], 'batches': [0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 3, 4, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 6, 7, 8, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 10, 11, 12, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 14, 15, 16, 17, 17, 17, 17, 17, 17, 17, 17, 17, 17, 17, 17, 18, 19, 20]}}, {'solution_x': array([ 9.20676289, 45.59590683, 22.9510348 ]), 'solution_criterion': 0.6411981796789968, 'states': [State(trustregion=Region(center=array([ 9.27512208, 46.36962222, 22.93103984]), radius=4.6369622223167655, bounds=Bounds(lower=array([1.1, 0. , 0. ]), upper=array([ 20., 70., 100.]))), model_indices=[0], model=ScalarModel(intercept=0.6414958683212747, linear_terms=array([0., 0., 0.]), square_terms=array([[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]]), scale=4.6369622223167655, shift=array([ 9.27512208, 46.36962222, 22.93103984])), vector_model=VectorModel(intercepts=array([ 0.04902536, 0.12501084, 0.1503711 , 0.19587102, 0.21991184, + 0.23522003, 0.23681939, 0.07111459, -0.07579182, -0.06299477, + -0.40502842, -0.41381428, -0.12605813, -0.09953675, -0.09019229, + -0.09362869, -0.09977548]), linear_terms=array([[0., 0., 0.], [0., 0., 0.], [0., 0., 0.], [0., 0., 0.], @@ -2755,12 +3625,12 @@ algorithm_output,"{'states': [State(trustregion=Region(center=array([ 8.7163601 [[0., 0., 0.], [0., 0., 0.], - [0., 0., 0.]]]), scale=4.354435734570826, shift=array([ 8.7163601 , 26.21001302, 43.54435735])), candidate_index=73, candidate_x=array([ 8.71536928, 26.21028616, 43.54462906]), index=0, x=array([ 8.7163601 , 26.21001302, 43.54435735]), fval=0.5809830305379233, rho=-2.9872067713886064, accepted=False, new_indices=array([61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72]), old_indices_used=array([ 0, 59, 60]), old_indices_discarded=array([], dtype=int64), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 8.7163601 , 26.21001302, 43.54435735]), radius=0.0005315473308802278, bounds=Bounds(lower=array([2., 0., 0.]), upper=array([20., 70., 70.]))), model_indices=array([ 0, 61, 62, 63, 65, 66, 67, 68, 69, 70, 71, 73]), model=ScalarModel(intercept=0.5809916477871087, linear_terms=array([-8.28665877e-07, -2.86476957e-07, -1.24886973e-06]), square_terms=array([[3.13215641e-08, 2.70941570e-11, 7.85016001e-11], - [2.70941570e-11, 1.36435914e-13, 4.46280590e-13], - [7.85016001e-11, 4.46280590e-13, 2.25290922e-12]]), scale=0.0005315473308802278, shift=array([ 8.7163601 , 26.21001302, 43.54435735])), vector_model=VectorModel(intercepts=array([ 0.05724953, 0.13067265, 0.1523968 , 0.19379396, 0.21975026, - 0.23556517, 0.23562227, 0.08724666, -0.05175769, -0.04146735, - -0.38600879, -0.40563182, -0.07724305, -0.05219358, -0.04259982, - -0.04528797, -0.04943255]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.]]]), scale=4.6369622223167655, shift=array([ 9.27512208, 46.36962222, 22.93103984])), candidate_index=0, candidate_x=array([ 9.27512208, 46.36962222, 22.93103984]), index=0, x=array([ 9.27512208, 46.36962222, 22.93103984]), fval=0.6414958683212746, rho=nan, accepted=True, new_indices=[0], old_indices_used=[], old_indices_discarded=[], step_length=None, relative_step_length=None, n_evals_per_point=None, n_evals_acceptance=None), State(trustregion=Region(center=array([ 9.27512208, 46.36962222, 22.93103984]), radius=4.6369622223167655, bounds=Bounds(lower=array([1.1, 0. , 0. ]), upper=array([ 20., 70., 100.]))), model_indices=array([ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12]), model=ScalarModel(intercept=0.5881261163934798, linear_terms=array([-0.01066396, -0.00125612, -0.00395789]), square_terms=array([[ 2.09022435e+00, -7.43148824e-03, -4.96555300e-03], + [-7.43148824e-03, 3.88929180e-05, 4.45740439e-05], + [-4.96555300e-03, 4.45740439e-05, 1.50833837e-04]]), scale=4.6369622223167655, shift=array([ 9.27512208, 46.36962222, 22.93103984])), vector_model=VectorModel(intercepts=array([ 0.04902536, 0.12501084, 0.1503711 , 0.19587102, 0.21991184, + 0.23522003, 0.23681939, 0.07111459, -0.07579182, -0.06299477, + -0.40502842, -0.41381428, -0.12605813, -0.09953675, -0.09019229, + -0.09362869, -0.09977548]), linear_terms=array([[0., 0., 0.], [0., 0., 0.], [0., 0., 0.], [0., 0., 0.], @@ -2842,12 +3712,12 @@ algorithm_output,"{'states': [State(trustregion=Region(center=array([ 8.7163601 [[0., 0., 0.], [0., 0., 0.], - [0., 0., 0.]]]), scale=4.354435734570826, shift=array([ 8.7163601 , 26.21001302, 43.54435735])), candidate_index=74, candidate_x=array([ 8.71664582, 26.21011384, 43.54479689]), index=0, x=array([ 8.7163601 , 26.21001302, 43.54435735]), fval=0.5809830305379233, rho=-2.5168773401923845, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([ 0, 61, 62, 63, 65, 66, 67, 68, 69, 70, 71, 73]), old_indices_discarded=array([60, 64, 72]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 8.7163601 , 26.21001302, 43.54435735]), radius=0.0002657736654401139, bounds=Bounds(lower=array([2., 0., 0.]), upper=array([20., 70., 70.]))), model_indices=array([ 0, 62, 63, 65, 66, 67, 68, 69, 70, 71, 73, 74]), model=ScalarModel(intercept=0.5809924325261797, linear_terms=array([-6.50169305e-07, -6.61619661e-07, -7.50887963e-07]), square_terms=array([[7.84875238e-09, 2.64831149e-11, 2.50892034e-11], - [2.64831149e-11, 5.83683628e-13, 6.19203568e-13], - [2.50892034e-11, 6.19203568e-13, 7.85763475e-13]]), scale=0.0002657736654401139, shift=array([ 8.7163601 , 26.21001302, 43.54435735])), vector_model=VectorModel(intercepts=array([ 0.05724953, 0.13067265, 0.1523968 , 0.19379396, 0.21975026, - 0.23556517, 0.23562227, 0.08724666, -0.05175769, -0.04146735, - -0.38600879, -0.40563182, -0.07724305, -0.05219358, -0.04259982, - -0.04528797, -0.04943255]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.]]]), scale=4.6369622223167655, shift=array([ 9.27512208, 46.36962222, 22.93103984])), candidate_index=13, candidate_x=array([ 9.31433205, 47.82012341, 27.33908379]), index=0, x=array([ 9.27512208, 46.36962222, 22.93103984]), fval=0.6414958683212746, rho=-0.06744979380670008, accepted=False, new_indices=array([ 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12]), old_indices_used=array([0]), old_indices_discarded=array([], dtype=int64), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 9.27512208, 46.36962222, 22.93103984]), radius=2.3184811111583827, bounds=Bounds(lower=array([1.1, 0. , 0. ]), upper=array([ 20., 70., 100.]))), model_indices=array([ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 12]), model=ScalarModel(intercept=0.5921591562782017, linear_terms=array([ 2.93089963e-03, -4.76516299e-03, 4.03398872e-05]), square_terms=array([[ 5.30904188e-01, -5.61712335e-03, 5.76543930e-04], + [-5.61712335e-03, 1.61886965e-04, 6.50802775e-06], + [ 5.76543930e-04, 6.50802775e-06, 3.52139536e-06]]), scale=2.3184811111583827, shift=array([ 9.27512208, 46.36962222, 22.93103984])), vector_model=VectorModel(intercepts=array([ 0.04902536, 0.12501084, 0.1503711 , 0.19587102, 0.21991184, + 0.23522003, 0.23681939, 0.07111459, -0.07579182, -0.06299477, + -0.40502842, -0.41381428, -0.12605813, -0.09953675, -0.09019229, + -0.09362869, -0.09977548]), linear_terms=array([[0., 0., 0.], [0., 0., 0.], [0., 0., 0.], [0., 0., 0.], @@ -2929,12 +3799,12 @@ algorithm_output,"{'states': [State(trustregion=Region(center=array([ 8.7163601 [[0., 0., 0.], [0., 0., 0.], - [0., 0., 0.]]]), scale=4.354435734570826, shift=array([ 8.7163601 , 26.21001302, 43.54435735])), candidate_index=75, candidate_x=array([ 8.71650441, 26.21016084, 43.54452511]), index=0, x=array([ 8.7163601 , 26.21001302, 43.54435735]), fval=0.5809830305379233, rho=-1.0197333317217874, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([ 0, 62, 63, 65, 66, 67, 68, 69, 70, 71, 73, 74]), old_indices_discarded=array([61, 64, 72]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 8.7163601 , 26.21001302, 43.54435735]), radius=0.00013288683272005695, bounds=Bounds(lower=array([2., 0., 0.]), upper=array([20., 70., 70.]))), model_indices=array([ 0, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87]), model=ScalarModel(intercept=0.5809836227584936, linear_terms=array([7.90333338e-08, 1.02805278e-07, 6.42865768e-07]), square_terms=array([[ 1.94876940e-09, -1.25425316e-12, -9.63319991e-12], - [-1.25425316e-12, 3.83332866e-14, 1.37583472e-13], - [-9.63319991e-12, 1.37583472e-13, 6.66770684e-13]]), scale=0.00013288683272005695, shift=array([ 8.7163601 , 26.21001302, 43.54435735])), vector_model=VectorModel(intercepts=array([ 0.05724953, 0.13067265, 0.1523968 , 0.19379396, 0.21975026, - 0.23556517, 0.23562227, 0.08724666, -0.05175769, -0.04146735, - -0.38600879, -0.40563182, -0.07724305, -0.05219358, -0.04259982, - -0.04528797, -0.04943255]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.]]]), scale=4.6369622223167655, shift=array([ 9.27512208, 46.36962222, 22.93103984])), candidate_index=14, candidate_x=array([ 9.28679021, 48.6892354 , 22.90614115]), index=0, x=array([ 9.27512208, 46.36962222, 22.93103984]), fval=0.6414958683212746, rho=-0.024819974400623245, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 12]), old_indices_discarded=array([11, 13]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 9.27512208, 46.36962222, 22.93103984]), radius=1.1592405555791914, bounds=Bounds(lower=array([1.1, 0. , 0. ]), upper=array([ 20., 70., 100.]))), model_indices=array([ 0, 1, 3, 4, 5, 6, 7, 8, 9, 10, 12, 14]), model=ScalarModel(intercept=0.5957412470858591, linear_terms=array([ 0.00248444, -0.00089163, -0.00022855]), square_terms=array([[ 1.32806446e-01, -8.94595704e-04, 1.75001583e-04], + [-8.94595704e-04, 1.45793768e-05, -1.42593512e-06], + [ 1.75001583e-04, -1.42593512e-06, 6.46034765e-07]]), scale=1.1592405555791914, shift=array([ 9.27512208, 46.36962222, 22.93103984])), vector_model=VectorModel(intercepts=array([ 0.04902536, 0.12501084, 0.1503711 , 0.19587102, 0.21991184, + 0.23522003, 0.23681939, 0.07111459, -0.07579182, -0.06299477, + -0.40502842, -0.41381428, -0.12605813, -0.09953675, -0.09019229, + -0.09362869, -0.09977548]), linear_terms=array([[0., 0., 0.], [0., 0., 0.], [0., 0., 0.], [0., 0., 0.], @@ -3016,12 +3886,99 @@ algorithm_output,"{'states': [State(trustregion=Region(center=array([ 8.7163601 [[0., 0., 0.], [0., 0., 0.], - [0., 0., 0.]]]), scale=4.354435734570826, shift=array([ 8.7163601 , 26.21001302, 43.54435735])), candidate_index=88, candidate_x=array([ 8.71634411, 26.20999216, 43.54422689]), index=88, x=array([ 8.71634411, 26.20999216, 43.54422689]), fval=0.580982924948752, rho=0.16077632892686486, accepted=True, new_indices=array([76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87]), old_indices_used=array([ 0, 74, 75]), old_indices_discarded=array([], dtype=int64), step_length=0.00013307839832203612, relative_step_length=1.0014415694772614, n_evals_per_point=1, n_evals_acceptance=1)], 'message': 'Absolute criterion change smaller than tolerance.', 'tranquilo_history': History for least_squares function with 89 entries., 'history': {'params': [{'CRRA': 8.716360103468407, 'BeqShift': 26.210013017331125, 'BeqFac': 43.544357345708256}, {'CRRA': 9.932657005357095, 'BeqShift': 28.39374194086523, 'BeqFac': 39.97881946181417}, {'CRRA': 5.918243061415689, 'BeqShift': 28.24758428370863, 'BeqFac': 40.90239691452949}, {'CRRA': 5.015808790423334, 'BeqShift': 28.110626722137255, 'BeqFac': 44.83070803316905}, {'CRRA': 8.300300428061735, 'BeqShift': 21.875576039056437, 'BeqFac': 43.51864753487957}, {'CRRA': 8.064756587407645, 'BeqShift': 24.587354418521986, 'BeqFac': 47.53227691561879}, {'CRRA': 4.883363295674027, 'BeqShift': 24.174800468994693, 'BeqFac': 43.900946634722075}, {'CRRA': 10.66294571363579, 'BeqShift': 30.090341510755252, 'BeqFac': 43.20529125787657}, {'CRRA': 12.192787024479657, 'BeqShift': 25.08882139484883, 'BeqFac': 41.17402070821325}, {'CRRA': 8.139678425612232, 'BeqShift': 29.192318662246315, 'BeqFac': 46.6643576420607}, {'CRRA': 7.6526612313494695, 'BeqShift': 24.127560137239733, 'BeqFac': 39.871069271222495}, {'CRRA': 11.838688260695706, 'BeqShift': 23.50144007371468, 'BeqFac': 44.913959497503406}, {'CRRA': 12.084121496303712, 'BeqShift': 27.363721387937847, 'BeqFac': 46.051995829028236}, {'CRRA': 8.933510052757214, 'BeqShift': 28.89771693179309, 'BeqFac': 47.01135568172765}, {'CRRA': 8.902197657290548, 'BeqShift': 27.26532816290852, 'BeqFac': 45.51595825166366}, {'CRRA': 8.789531280592655, 'BeqShift': 27.24792252348393, 'BeqFac': 43.87862901543856}, {'CRRA': 8.438898172182274, 'BeqShift': 25.74203409793529, 'BeqFac': 43.52768520458141}, {'CRRA': 8.95452321895985, 'BeqShift': 25.723672513520988, 'BeqFac': 43.59929910919278}, {'CRRA': 9.193380580191135, 'BeqShift': 25.950208406861826, 'BeqFac': 43.57929130866401}, {'CRRA': 8.759379321032199, 'BeqShift': 26.74189493613109, 'BeqFac': 43.43703389079022}, {'CRRA': 9.121893970098535, 'BeqShift': 26.289739056327704, 'BeqFac': 43.190163339090965}, {'CRRA': 8.42489763807857, 'BeqShift': 26.66821912606228, 'BeqFac': 43.58129169005073}, {'CRRA': 9.222551897489526, 'BeqShift': 26.408476324513323, 'BeqFac': 43.51887135014868}, {'CRRA': 8.220249156584092, 'BeqShift': 26.23216760824491, 'BeqFac': 43.321533524978356}, {'CRRA': 8.275934945026309, 'BeqShift': 26.526907387440193, 'BeqFac': 43.50110239678783}, {'CRRA': 8.971989511020418, 'BeqShift': 25.94797311169433, 'BeqFac': 43.14154715908167}, {'CRRA': 8.879291795207399, 'BeqShift': 26.701627021873662, 'BeqFac': 43.37691694745742}, {'CRRA': 8.339587636467582, 'BeqShift': 25.97701041352158, 'BeqFac': 43.228098516061145}, {'CRRA': 8.721542494966268, 'BeqShift': 25.667491313784154, 'BeqFac': 43.50056309988404}, {'CRRA': 8.72148001415611, 'BeqShift': 26.49966574129904, 'BeqFac': 43.48319190238889}, {'CRRA': 8.719961249267806, 'BeqShift': 26.086503929719097, 'BeqFac': 43.60192377476015}, {'CRRA': 8.70227014372693, 'BeqShift': 26.19502754258787, 'BeqFac': 43.60921168993903}, {'CRRA': 8.746253639842156, 'BeqShift': 26.268638946237054, 'BeqFac': 43.527078621004456}, {'CRRA': 8.735825068994972, 'BeqShift': 26.22020576804663, 'BeqFac': 43.479964796959955}, {'CRRA': 8.702275571141982, 'BeqShift': 26.15705518265819, 'BeqFac': 43.50403029423779}, {'CRRA': 8.66964142550509, 'BeqShift': 26.21832950346317, 'BeqFac': 43.49559897645562}, {'CRRA': 8.760054988864033, 'BeqShift': 26.182468946612165, 'BeqFac': 43.588643444462754}, {'CRRA': 8.656722450025475, 'BeqShift': 26.225411621344165, 'BeqFac': 43.57326081731067}, {'CRRA': 8.666897961093134, 'BeqShift': 26.164166515025016, 'BeqFac': 43.55334467469664}, {'CRRA': 8.757696064842552, 'BeqShift': 26.1604710737382, 'BeqFac': 43.522767729993475}, {'CRRA': 8.683807002439183, 'BeqShift': 26.269054953742927, 'BeqFac': 43.53521826793601}, {'CRRA': 8.731121407792553, 'BeqShift': 26.25431509007844, 'BeqFac': 43.59384075332478}, {'CRRA': 8.783544769619962, 'BeqShift': 26.220590062049666, 'BeqFac': 43.54248007547535}, {'CRRA': 8.709865116042218, 'BeqShift': 26.24896623007267, 'BeqFac': 43.6000552444956}, {'CRRA': 8.71117159923056, 'BeqShift': 26.241718296795003, 'BeqFac': 43.55620009421021}, {'CRRA': 8.71370725364789, 'BeqShift': 26.225630440183046, 'BeqFac': 43.551033485324}, {'CRRA': 8.72246703454562, 'BeqShift': 26.211077986668773, 'BeqFac': 43.550179899251106}, {'CRRA': 8.721321184614803, 'BeqShift': 26.214134204244186, 'BeqFac': 43.53881348523763}, {'CRRA': 8.721469232395883, 'BeqShift': 26.204318326978143, 'BeqFac': 43.54807193855503}, {'CRRA': 8.717423606979448, 'BeqShift': 26.202326688287133, 'BeqFac': 43.54783875386312}, {'CRRA': 8.72178417807686, 'BeqShift': 26.21389516270332, 'BeqFac': 43.53908105358382}, {'CRRA': 8.711315430712853, 'BeqShift': 26.207879562908214, 'BeqFac': 43.53785115283946}, {'CRRA': 8.711429995623595, 'BeqShift': 26.214491955056907, 'BeqFac': 43.5390692411217}, {'CRRA': 8.711221360054209, 'BeqShift': 26.205209203115178, 'BeqFac': 43.549137260114705}, {'CRRA': 8.71621556208304, 'BeqShift': 26.203737241196166, 'BeqFac': 43.55009534521358}, {'CRRA': 8.710502049029929, 'BeqShift': 26.203879217364104, 'BeqFac': 43.54498231994107}, {'CRRA': 8.718762923541307, 'BeqShift': 26.203570276322477, 'BeqFac': 43.54936218742644}, {'CRRA': 8.717558258907546, 'BeqShift': 26.203840292462818, 'BeqFac': 43.53863084696337}, {'CRRA': 8.72480793091163, 'BeqShift': 26.2106724072216, 'BeqFac': 43.543629119717835}, {'CRRA': 8.720227637354252, 'BeqShift': 26.210845889025343, 'BeqFac': 43.545916586081205}, {'CRRA': 8.718215787389259, 'BeqShift': 26.210377477934934, 'BeqFac': 43.54532908985854}, {'CRRA': 8.716230502918005, 'BeqShift': 26.208966998602442, 'BeqFac': 43.54449597750997}, {'CRRA': 8.716031966868922, 'BeqShift': 26.210809658810987, 'BeqFac': 43.54373456245182}, {'CRRA': 8.717055334990912, 'BeqShift': 26.209736929883633, 'BeqFac': 43.54360196559777}, {'CRRA': 8.717022063722597, 'BeqShift': 26.209462110527834, 'BeqFac': 43.54373406360854}, {'CRRA': 8.716467071382185, 'BeqShift': 26.210631680878627, 'BeqFac': 43.5452152405388}, {'CRRA': 8.716881184912003, 'BeqShift': 26.210854676087738, 'BeqFac': 43.54474497301176}, {'CRRA': 8.715626045111092, 'BeqShift': 26.209460726540016, 'BeqFac': 43.544892419039655}, {'CRRA': 8.716667624955434, 'BeqShift': 26.209012780197085, 'BeqFac': 43.54454476627961}, {'CRRA': 8.7167905585188, 'BeqShift': 26.21091612265495, 'BeqFac': 43.54471690027092}, {'CRRA': 8.716800305842533, 'BeqShift': 26.21066593541213, 'BeqFac': 43.54364313977915}, {'CRRA': 8.71726616538714, 'BeqShift': 26.2094778244427, 'BeqFac': 43.54420638004506}, {'CRRA': 8.716297255551318, 'BeqShift': 26.210215379132627, 'BeqFac': 43.545399108685366}, {'CRRA': 8.715369277140347, 'BeqShift': 26.210286158864736, 'BeqFac': 43.54462905722826}, {'CRRA': 8.716645816872003, 'BeqShift': 26.210113842727615, 'BeqFac': 43.54479689209034}, {'CRRA': 8.71650441136394, 'BeqShift': 26.210160839209045, 'BeqFac': 43.54452511288601}, {'CRRA': 8.716482705613553, 'BeqShift': 26.209991695144257, 'BeqFac': 43.544403961034746}, {'CRRA': 8.716354127767197, 'BeqShift': 26.209896320629642, 'BeqFac': 43.54442063141887}, {'CRRA': 8.716271674228379, 'BeqShift': 26.209937695038132, 'BeqFac': 43.54429280322615}, {'CRRA': 8.716369991582406, 'BeqShift': 26.209981718521654, 'BeqFac': 43.54422857645712}, {'CRRA': 8.716379030949353, 'BeqShift': 26.209994764939445, 'BeqFac': 43.544487605107044}, {'CRRA': 8.71647598926772, 'BeqShift': 26.21004251401661, 'BeqFac': 43.54429938591725}, {'CRRA': 8.716250311197832, 'BeqShift': 26.210075661118708, 'BeqFac': 43.54431635395897}, {'CRRA': 8.716245527958769, 'BeqShift': 26.20997640149947, 'BeqFac': 43.54441383149208}, {'CRRA': 8.716417964002375, 'BeqShift': 26.209899857684015, 'BeqFac': 43.54431853896677}, {'CRRA': 8.716354098327871, 'BeqShift': 26.210107129142152, 'BeqFac': 43.544263719773696}, {'CRRA': 8.716296801977995, 'BeqShift': 26.210091804229435, 'BeqFac': 43.54444362697086}, {'CRRA': 8.716398370826282, 'BeqShift': 26.210139009246113, 'BeqFac': 43.54437524981363}, {'CRRA': 8.71634411092518, 'BeqShift': 26.2099921551288, 'BeqFac': 43.5442268893279}], 'criterion': [0.5809830305379234, 0.6475050788757654, 1.0812966367450123, 1.5677388243521588, 0.5901410990942234, 0.6034055925734466, 1.660725043221378, 0.7412131279833819, 1.0419717777787227, 0.5987026459231682, 0.6422649548790325, 0.9615289646063448, 1.016675693290777, 0.5834707143779694, 0.5827531103899377, 0.5815161074949304, 0.585174047158889, 0.5838830805006481, 0.5921910367463035, 0.5813599843315268, 0.5892274277903787, 0.5854703586450424, 0.5935622970023258, 0.5940793398254625, 0.5912868642773532, 0.5844363123872142, 0.5823584265399021, 0.5885623323237705, 0.5809937017550751, 0.5809944050369751, 0.5810030552078739, 0.5810768041773333, 0.5812987528245467, 0.5811718845584521, 0.58107682417594, 0.58126674677391, 0.5813540748082379, 0.5813991522255589, 0.5813010563480635, 0.5813803476786684, 0.5812020652707865, 0.5810720977094285, 0.5814693508105266, 0.5810183623332761, 0.5810264658549772, 0.58101979276163, 0.5809954982668705, 0.5809959127241888, 0.5809945167598772, 0.5810035987588107, 0.5809913471858298, 0.5810275896675526, 0.5810284226733449, 0.5810268544220232, 0.580985133604185, 0.5810218017764479, 0.5810081287064058, 0.5810042557581923, 0.5810175949103867, 0.581004896210661, 0.5810071456990064, 0.580984817642274, 0.5809889914168228, 0.5809960593392647, 0.580995333870111, 0.5809838515556087, 0.5809922632611042, 0.5809969342497421, 0.5809873807513505, 0.5809902392432829, 0.5809904662685499, 0.581000808424819, 0.5809835829991066, 0.5810017001549396, 0.5809868760963334, 0.5809842479268352, 0.5809840174986693, 0.5809829910809239, 0.5809840363991541, 0.5809830958361404, 0.5809831555381243, 0.580983946207735, 0.5809844150897633, 0.5809844999237543, 0.580983412772242, 0.5809829908865543, 0.5809835910375566, 0.5809832832992563, 0.580982924948752], 'runtime': [0.0, 2.131810189999669, 2.345900324999093, 2.601077030001761, 2.8178930249996483, 3.0646434359987325, 3.3117362250013684, 3.520140584998444, 3.772116549000202, 3.976670534000732, 4.229006272998959, 4.496662006000406, 4.7315624529983324, 6.387398062001012, 8.030480844001431, 9.685418334000133, 11.656430210001417, 11.903623591999349, 12.101536465001118, 12.321709553998517, 12.565143309999257, 12.814643690999219, 13.184783972999867, 13.439273255000444, 13.673015806001786, 13.894198917998438, 14.1235472139997, 14.357036713001435, 16.012400743999024, 17.547351240998978, 19.202105248001317, 21.21159297900158, 21.427835012000287, 21.648751348999212, 21.856372833000933, 22.081527148999157, 22.356989476000308, 22.561750371001835, 22.796074032001343, 23.039378629000566, 23.285717481001484, 23.6037466960006, 23.858030995001172, 25.704047907998756, 27.409221097001137, 28.970009754000785, 30.853769288001786, 31.0709398350009, 31.29622375300096, 31.52033615899927, 31.76830091100055, 32.019284524001705, 32.30085659600081, 32.55359189400042, 32.82333408900013, 33.085036558000866, 33.32605499800047, 33.585456917000556, 35.37460987400118, 36.90067361099864, 38.4480029059996, 40.459870106999006, 40.68037438399915, 40.898782464999385, 41.12036123700091, 41.33660625699849, 41.557244245999755, 41.77525416199933, 42.01495132299897, 42.244514887999685, 42.48345003600116, 42.753107841999736, 43.007700661000854, 44.73651604499901, 46.25735140300094, 47.84435955200024, 49.718590238000615, 49.92832028599878, 50.306263335998665, 50.53438860499955, 50.74307388899979, 50.96201847699922, 51.216817012998945, 51.44749346900062, 51.67675439700179, 51.945428234001156, 52.18559794600151, 52.43835590600065, 54.163996731000225], 'batches': [0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 3, 4, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 6, 7, 8, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 10, 11, 12, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 14, 15, 16, 17, 17, 17, 17, 17, 17, 17, 17, 17, 17, 17, 17, 18, 19, 20, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 22]}, 'multistart_info': {...}}, {'solution_x': array([ 8.72184655, 25.97850258, 43.14570818]), 'solution_criterion': 0.5809908420715011, 'states': [State(trustregion=Region(center=array([ 8.73056876, 26.22690146, 43.63119684]), radius=4.363119683916148, bounds=Bounds(lower=array([2., 0., 0.]), upper=array([20., 70., 70.]))), model_indices=[0], model=ScalarModel(intercept=0.5810642477242686, linear_terms=array([0., 0., 0.]), square_terms=array([[0., 0., 0.], + [0., 0., 0.]]]), scale=4.6369622223167655, shift=array([ 9.27512208, 46.36962222, 22.93103984])), candidate_index=15, candidate_x=array([ 9.26068266, 47.48958436, 23.2307316 ]), index=0, x=array([ 9.27512208, 46.36962222, 22.93103984]), fval=0.6414958683212746, rho=-0.08922847434749884, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([ 0, 1, 3, 4, 5, 6, 7, 8, 9, 10, 12, 14]), old_indices_discarded=array([ 2, 11, 13]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 9.27512208, 46.36962222, 22.93103984]), radius=0.5796202777895957, bounds=Bounds(lower=array([1.1, 0. , 0. ]), upper=array([ 20., 70., 100.]))), model_indices=array([ 0, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27]), model=ScalarModel(intercept=0.6406308340870236, linear_terms=array([ 2.46442757e-03, 2.37028145e-04, -1.79444704e-05]), square_terms=array([[ 3.02073781e-02, 1.65031915e-05, 5.41504947e-06], + [ 1.65031915e-05, 1.22265702e-07, -8.95972132e-09], + [ 5.41504947e-06, -8.95972132e-09, 3.91122560e-08]]), scale=0.5796202777895957, shift=array([ 9.27512208, 46.36962222, 22.93103984])), vector_model=VectorModel(intercepts=array([ 0.04902536, 0.12501084, 0.1503711 , 0.19587102, 0.21991184, + 0.23522003, 0.23681939, 0.07111459, -0.07579182, -0.06299477, + -0.40502842, -0.41381428, -0.12605813, -0.09953675, -0.09019229, + -0.09362869, -0.09977548]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.], [0., 0., 0.], - [0., 0., 0.]]), scale=4.363119683916148, shift=array([ 8.73056876, 26.22690146, 43.63119684])), vector_model=VectorModel(intercepts=array([ 0.05736286, 0.13097505, 0.15289447, 0.19437164, 0.22039886, - 0.23631479, 0.23653827, 0.08827519, -0.0506954 , -0.04028249, - -0.38487098, -0.40453749, -0.07787386, -0.05280456, -0.04320692, - -0.04588722, -0.05004941]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]]), square_terms=array([[[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]]]), scale=4.6369622223167655, shift=array([ 9.27512208, 46.36962222, 22.93103984])), candidate_index=28, candidate_x=array([ 9.2285044 , 45.73915809, 22.98019649]), index=28, x=array([ 9.2285044 , 45.73915809, 22.98019649]), fval=0.6413920207839838, rho=0.2897773418727435, accepted=True, new_indices=array([16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27]), old_indices_used=array([ 0, 14, 15]), old_indices_discarded=array([], dtype=int64), step_length=0.6340935281815585, relative_step_length=1.0939809259256745, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 9.2285044 , 45.73915809, 22.98019649]), radius=1.1592405555791914, bounds=Bounds(lower=array([1.1, 0. , 0. ]), upper=array([ 20., 70., 100.]))), model_indices=array([ 0, 16, 18, 20, 21, 22, 23, 24, 25, 26, 27, 28]), model=ScalarModel(intercept=0.6408049220810728, linear_terms=array([ 2.84779294e-04, -7.53428271e-04, -4.79516493e-05]), square_terms=array([[ 1.20811694e-01, -7.93957752e-05, -3.19967655e-05], + [-7.93957752e-05, 1.20566655e-06, 6.57148266e-08], + [-3.19967655e-05, 6.57148266e-08, 1.19721232e-07]]), scale=1.1592405555791914, shift=array([ 9.2285044 , 45.73915809, 22.98019649])), vector_model=VectorModel(intercepts=array([ 0.04902536, 0.12501084, 0.1503711 , 0.19587102, 0.21991184, + 0.23522003, 0.23681939, 0.07111459, -0.07579182, -0.06299477, + -0.40502842, -0.41381428, -0.12605813, -0.09953675, -0.09019229, + -0.09362869, -0.09977548]), linear_terms=array([[0., 0., 0.], [0., 0., 0.], [0., 0., 0.], [0., 0., 0.], @@ -3103,12 +4060,12 @@ algorithm_output,"{'states': [State(trustregion=Region(center=array([ 8.7163601 [[0., 0., 0.], [0., 0., 0.], - [0., 0., 0.]]]), scale=4.363119683916148, shift=array([ 8.73056876, 26.22690146, 43.63119684])), candidate_index=0, candidate_x=array([ 8.73056876, 26.22690146, 43.63119684]), index=0, x=array([ 8.73056876, 26.22690146, 43.63119684]), fval=0.5810642477242686, rho=nan, accepted=True, new_indices=[0], old_indices_used=[], old_indices_discarded=[], step_length=None, relative_step_length=None, n_evals_per_point=None, n_evals_acceptance=None), State(trustregion=Region(center=array([ 8.73056876, 26.22690146, 43.63119684]), radius=4.363119683916148, bounds=Bounds(lower=array([2., 0., 0.]), upper=array([20., 70., 70.]))), model_indices=array([ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12]), model=ScalarModel(intercept=0.5490042089099434, linear_terms=array([-0.09443139, -0.00120678, -0.00136192]), square_terms=array([[ 2.21383078e+00, -3.44959400e-03, -9.71238006e-03], - [-3.44959400e-03, 5.31921184e-05, 9.05019364e-05], - [-9.71238006e-03, 9.05019364e-05, 1.73387316e-04]]), scale=4.363119683916148, shift=array([ 8.73056876, 26.22690146, 43.63119684])), vector_model=VectorModel(intercepts=array([ 0.05736286, 0.13097505, 0.15289447, 0.19437164, 0.22039886, - 0.23631479, 0.23653827, 0.08827519, -0.0506954 , -0.04028249, - -0.38487098, -0.40453749, -0.07787386, -0.05280456, -0.04320692, - -0.04588722, -0.05004941]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.]]]), scale=4.6369622223167655, shift=array([ 9.27512208, 46.36962222, 22.93103984])), candidate_index=29, candidate_x=array([ 9.22656371, 46.89606098, 23.05376338]), index=28, x=array([ 9.2285044 , 45.73915809, 22.98019649]), fval=0.6413920207839838, rho=-0.015254435543014998, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([ 0, 16, 18, 20, 21, 22, 23, 24, 25, 26, 27, 28]), old_indices_discarded=array([ 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 17, 19]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 9.2285044 , 45.73915809, 22.98019649]), radius=0.5796202777895957, bounds=Bounds(lower=array([1.1, 0. , 0. ]), upper=array([ 20., 70., 100.]))), model_indices=array([ 0, 16, 17, 18, 20, 21, 22, 23, 24, 25, 27, 28]), model=ScalarModel(intercept=0.6409384183159138, linear_terms=array([ 1.61766905e-04, -5.10943921e-04, 6.04893594e-05]), square_terms=array([[ 3.01982385e-02, -4.69113992e-05, 8.73747171e-06], + [-4.69113992e-05, 5.89438354e-07, -8.80750748e-08], + [ 8.73747171e-06, -8.80750748e-08, 4.25622534e-08]]), scale=0.5796202777895957, shift=array([ 9.2285044 , 45.73915809, 22.98019649])), vector_model=VectorModel(intercepts=array([ 0.04902536, 0.12501084, 0.1503711 , 0.19587102, 0.21991184, + 0.23522003, 0.23681939, 0.07111459, -0.07579182, -0.06299477, + -0.40502842, -0.41381428, -0.12605813, -0.09953675, -0.09019229, + -0.09362869, -0.09977548]), linear_terms=array([[0., 0., 0.], [0., 0., 0.], [0., 0., 0.], [0., 0., 0.], @@ -3190,12 +4147,12 @@ algorithm_output,"{'states': [State(trustregion=Region(center=array([ 8.7163601 [[0., 0., 0.], [0., 0., 0.], - [0., 0., 0.]]]), scale=4.363119683916148, shift=array([ 8.73056876, 26.22690146, 43.63119684])), candidate_index=13, candidate_x=array([ 8.93591879, 28.92635966, 47.10123384]), index=0, x=array([ 8.73056876, 26.22690146, 43.63119684]), fval=0.5810642477242686, rho=-0.5914714186034357, accepted=False, new_indices=array([ 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12]), old_indices_used=array([0]), old_indices_discarded=array([], dtype=int64), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 8.73056876, 26.22690146, 43.63119684]), radius=2.181559841958074, bounds=Bounds(lower=array([2., 0., 0.]), upper=array([20., 70., 70.]))), model_indices=array([ 0, 1, 2, 3, 4, 5, 6, 7, 8, 10, 11, 12]), model=ScalarModel(intercept=0.5461904709818534, linear_terms=array([-0.05482891, -0.00349741, -0.00374811]), square_terms=array([[ 5.57147203e-01, -1.01092638e-02, -1.24009374e-02], - [-1.01092638e-02, 5.57043157e-04, 6.64749325e-04], - [-1.24009374e-02, 6.64749325e-04, 7.95808296e-04]]), scale=2.181559841958074, shift=array([ 8.73056876, 26.22690146, 43.63119684])), vector_model=VectorModel(intercepts=array([ 0.05736286, 0.13097505, 0.15289447, 0.19437164, 0.22039886, - 0.23631479, 0.23653827, 0.08827519, -0.0506954 , -0.04028249, - -0.38487098, -0.40453749, -0.07787386, -0.05280456, -0.04320692, - -0.04588722, -0.05004941]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.]]]), scale=4.6369622223167655, shift=array([ 9.27512208, 46.36962222, 22.93103984])), candidate_index=30, candidate_x=array([ 9.22635001, 46.31476639, 22.91208979]), index=28, x=array([ 9.2285044 , 45.73915809, 22.98019649]), fval=0.6413920207839838, rho=-0.023574344078806802, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([ 0, 16, 17, 18, 20, 21, 22, 23, 24, 25, 27, 28]), old_indices_discarded=array([15, 19, 26, 29]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 9.2285044 , 45.73915809, 22.98019649]), radius=0.28981013889479784, bounds=Bounds(lower=array([1.1, 0. , 0. ]), upper=array([ 20., 70., 100.]))), model_indices=array([ 0, 16, 17, 18, 20, 21, 23, 24, 25, 27, 28, 30]), model=ScalarModel(intercept=0.6409846094096279, linear_terms=array([ 7.15842404e-05, -2.42504599e-04, 9.71440835e-06]), square_terms=array([[ 7.54356286e-03, -1.39281443e-05, -4.55681710e-07], + [-1.39281443e-05, 1.45840224e-07, -4.80821837e-09], + [-4.55681710e-07, -4.80821837e-09, 1.00622502e-08]]), scale=0.28981013889479784, shift=array([ 9.2285044 , 45.73915809, 22.98019649])), vector_model=VectorModel(intercepts=array([ 0.04902536, 0.12501084, 0.1503711 , 0.19587102, 0.21991184, + 0.23522003, 0.23681939, 0.07111459, -0.07579182, -0.06299477, + -0.40502842, -0.41381428, -0.12605813, -0.09953675, -0.09019229, + -0.09362869, -0.09977548]), linear_terms=array([[0., 0., 0.], [0., 0., 0.], [0., 0., 0.], [0., 0., 0.], @@ -3277,12 +4234,12 @@ algorithm_output,"{'states': [State(trustregion=Region(center=array([ 8.7163601 [[0., 0., 0.], [0., 0., 0.], - [0., 0., 0.]]]), scale=4.363119683916148, shift=array([ 8.73056876, 26.22690146, 43.63119684])), candidate_index=14, candidate_x=array([ 9.00968631, 27.80613651, 45.35855833]), index=0, x=array([ 8.73056876, 26.22690146, 43.63119684]), fval=0.5810642477242686, rho=-0.47769355458072915, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([ 0, 1, 2, 3, 4, 5, 6, 7, 8, 10, 11, 12]), old_indices_discarded=array([ 9, 13]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 8.73056876, 26.22690146, 43.63119684]), radius=1.090779920979037, bounds=Bounds(lower=array([2., 0., 0.]), upper=array([20., 70., 70.]))), model_indices=array([ 0, 1, 3, 4, 5, 6, 7, 8, 10, 11, 12, 14]), model=ScalarModel(intercept=0.5491201549326032, linear_terms=array([-0.02327252, -0.00081592, -0.00130552]), square_terms=array([[ 1.38654411e-01, -9.55670174e-04, -1.96836051e-03], - [-9.55670174e-04, 5.10140882e-05, 5.27488136e-05], - [-1.96836051e-03, 5.27488136e-05, 6.33353720e-05]]), scale=1.090779920979037, shift=array([ 8.73056876, 26.22690146, 43.63119684])), vector_model=VectorModel(intercepts=array([ 0.05736286, 0.13097505, 0.15289447, 0.19437164, 0.22039886, - 0.23631479, 0.23653827, 0.08827519, -0.0506954 , -0.04028249, - -0.38487098, -0.40453749, -0.07787386, -0.05280456, -0.04320692, - -0.04588722, -0.05004941]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.]]]), scale=4.6369622223167655, shift=array([ 9.27512208, 46.36962222, 22.93103984])), candidate_index=31, candidate_x=array([ 9.22635723, 46.0287285 , 22.96858695]), index=28, x=array([ 9.2285044 , 45.73915809, 22.98019649]), fval=0.6413920207839838, rho=-0.04985791456251465, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([ 0, 16, 17, 18, 20, 21, 23, 24, 25, 27, 28, 30]), old_indices_discarded=array([19, 22, 26, 29]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 9.2285044 , 45.73915809, 22.98019649]), radius=0.14490506944739892, bounds=Bounds(lower=array([1.1, 0. , 0. ]), upper=array([ 20., 70., 100.]))), model_indices=array([ 0, 16, 17, 25, 27, 28, 30, 31]), model=ScalarModel(intercept=0.6408971198477394, linear_terms=array([3.58738624e-04, 8.59942564e-05, 2.59392791e-05]), square_terms=array([[1.90666144e-03, 1.38680699e-06, 1.32065566e-06], + [1.38680699e-06, 1.93796783e-08, 5.05745577e-09], + [1.32065566e-06, 5.05745577e-09, 3.87895449e-09]]), scale=0.14490506944739892, shift=array([ 9.2285044 , 45.73915809, 22.98019649])), vector_model=VectorModel(intercepts=array([ 0.04902536, 0.12501084, 0.1503711 , 0.19587102, 0.21991184, + 0.23522003, 0.23681939, 0.07111459, -0.07579182, -0.06299477, + -0.40502842, -0.41381428, -0.12605813, -0.09953675, -0.09019229, + -0.09362869, -0.09977548]), linear_terms=array([[0., 0., 0.], [0., 0., 0.], [0., 0., 0.], [0., 0., 0.], @@ -3364,12 +4321,12 @@ algorithm_output,"{'states': [State(trustregion=Region(center=array([ 8.7163601 [[0., 0., 0.], [0., 0., 0.], - [0., 0., 0.]]]), scale=4.363119683916148, shift=array([ 8.73056876, 26.22690146, 43.63119684])), candidate_index=15, candidate_x=array([ 8.92810837, 26.77175054, 44.56950835]), index=0, x=array([ 8.73056876, 26.22690146, 43.63119684]), fval=0.5810642477242686, rho=-0.5969228256587084, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([ 0, 1, 3, 4, 5, 6, 7, 8, 10, 11, 12, 14]), old_indices_discarded=array([ 2, 9, 13]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 8.73056876, 26.22690146, 43.63119684]), radius=0.5453899604895185, bounds=Bounds(lower=array([2., 0., 0.]), upper=array([20., 70., 70.]))), model_indices=array([ 0, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27]), model=ScalarModel(intercept=0.5805875738974011, linear_terms=array([5.57946124e-04, 4.54992362e-05, 8.89692366e-05]), square_terms=array([[3.28402405e-02, 1.49675240e-05, 2.79070142e-05], - [1.49675240e-05, 2.45183160e-08, 5.39756339e-09], - [2.79070142e-05, 5.39756339e-09, 1.03960721e-07]]), scale=0.5453899604895185, shift=array([ 8.73056876, 26.22690146, 43.63119684])), vector_model=VectorModel(intercepts=array([ 0.05736286, 0.13097505, 0.15289447, 0.19437164, 0.22039886, - 0.23631479, 0.23653827, 0.08827519, -0.0506954 , -0.04028249, - -0.38487098, -0.40453749, -0.07787386, -0.05280456, -0.04320692, - -0.04588722, -0.05004941]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.]]]), scale=4.6369622223167655, shift=array([ 9.27512208, 46.36962222, 22.93103984])), candidate_index=32, candidate_x=array([ 9.20259338, 45.60122914, 22.93885113]), index=32, x=array([ 9.20259338, 45.60122914, 22.93885113]), fval=0.6412746242553712, rho=0.9575028532009756, accepted=True, new_indices=array([], dtype=int64), old_indices_used=array([ 0, 16, 17, 25, 27, 28, 30, 31]), old_indices_discarded=array([], dtype=int64), step_length=0.14630521557629694, relative_step_length=1.0096625061789593, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 9.20259338, 45.60122914, 22.93885113]), radius=0.28981013889479784, bounds=Bounds(lower=array([1.1, 0. , 0. ]), upper=array([ 20., 70., 100.]))), model_indices=array([ 0, 16, 17, 18, 20, 23, 25, 27, 28, 30, 31, 32]), model=ScalarModel(intercept=0.6411605508243214, linear_terms=array([-8.00766779e-04, -1.87173267e-04, -9.01420202e-05]), square_terms=array([[ 7.52619899e-03, -1.73444797e-05, -9.14217214e-06], + [-1.73444797e-05, 1.82296565e-07, 7.89294303e-08], + [-9.14217214e-06, 7.89294303e-08, 5.07950448e-08]]), scale=0.28981013889479784, shift=array([ 9.20259338, 45.60122914, 22.93885113])), vector_model=VectorModel(intercepts=array([ 0.04902536, 0.12501084, 0.1503711 , 0.19587102, 0.21991184, + 0.23522003, 0.23681939, 0.07111459, -0.07579182, -0.06299477, + -0.40502842, -0.41381428, -0.12605813, -0.09953675, -0.09019229, + -0.09362869, -0.09977548]), linear_terms=array([[0., 0., 0.], [0., 0., 0.], [0., 0., 0.], [0., 0., 0.], @@ -3451,12 +4408,12 @@ algorithm_output,"{'states': [State(trustregion=Region(center=array([ 8.7163601 [[0., 0., 0.], [0., 0., 0.], - [0., 0., 0.]]]), scale=4.363119683916148, shift=array([ 8.73056876, 26.22690146, 43.63119684])), candidate_index=28, candidate_x=array([ 8.72185488, 25.97850255, 43.14570821]), index=28, x=array([ 8.72185488, 25.97850255, 43.14570821]), fval=0.580990887775828, rho=0.7047649435838701, accepted=True, new_indices=array([16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27]), old_indices_used=array([ 0, 14, 15]), old_indices_discarded=array([], dtype=int64), step_length=0.5454146727537617, relative_step_length=1.0000453111828846, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 8.72185488, 25.97850255, 43.14570821]), radius=1.090779920979037, bounds=Bounds(lower=array([2., 0., 0.]), upper=array([20., 70., 70.]))), model_indices=array([ 0, 16, 17, 18, 19, 20, 21, 22, 23, 25, 27, 28]), model=ScalarModel(intercept=0.5806221446855274, linear_terms=array([ 1.26782219e-05, 3.53680271e-05, -6.72390186e-05]), square_terms=array([[ 1.30887314e-01, -4.00526576e-05, -3.45746489e-04], - [-4.00526576e-05, 1.08637079e-07, 8.35919158e-08], - [-3.45746489e-04, 8.35919158e-08, 1.79915231e-06]]), scale=1.090779920979037, shift=array([ 8.72185488, 25.97850255, 43.14570821])), vector_model=VectorModel(intercepts=array([ 0.05736286, 0.13097505, 0.15289447, 0.19437164, 0.22039886, - 0.23631479, 0.23653827, 0.08827519, -0.0506954 , -0.04028249, - -0.38487098, -0.40453749, -0.07787386, -0.05280456, -0.04320692, - -0.04588722, -0.05004941]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.]]]), scale=4.6369622223167655, shift=array([ 9.27512208, 46.36962222, 22.93103984])), candidate_index=33, candidate_x=array([ 9.23332219, 45.86150172, 23.06431621]), index=32, x=array([ 9.20259338, 45.60122914, 22.93885113]), fval=0.6412746242553712, rho=-0.6705794028601634, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([ 0, 16, 17, 18, 20, 23, 25, 27, 28, 30, 31, 32]), old_indices_discarded=array([19, 21, 22, 24, 26, 29]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 9.20259338, 45.60122914, 22.93885113]), radius=0.14490506944739892, bounds=Bounds(lower=array([1.1, 0. , 0. ]), upper=array([ 20., 70., 100.]))), model_indices=array([16, 17, 25, 27, 28, 30, 31, 32, 33]), model=ScalarModel(intercept=0.6410877940168466, linear_terms=array([ 9.26976569e-06, -6.82886493e-06, 3.85534656e-05]), square_terms=array([[ 1.90630255e-03, -7.29591096e-07, 1.56080907e-06], + [-7.29591096e-07, 3.03219948e-09, -2.68050753e-09], + [ 1.56080907e-06, -2.68050753e-09, 5.16628251e-09]]), scale=0.14490506944739892, shift=array([ 9.20259338, 45.60122914, 22.93885113])), vector_model=VectorModel(intercepts=array([ 0.04902536, 0.12501084, 0.1503711 , 0.19587102, 0.21991184, + 0.23522003, 0.23681939, 0.07111459, -0.07579182, -0.06299477, + -0.40502842, -0.41381428, -0.12605813, -0.09953675, -0.09019229, + -0.09362869, -0.09977548]), linear_terms=array([[0., 0., 0.], [0., 0., 0.], [0., 0., 0.], [0., 0., 0.], @@ -3538,12 +4495,12 @@ algorithm_output,"{'states': [State(trustregion=Region(center=array([ 8.7163601 [[0., 0., 0.], [0., 0., 0.], - [0., 0., 0.]]]), scale=4.363119683916148, shift=array([ 8.73056876, 26.22690146, 43.63119684])), candidate_index=29, candidate_x=array([ 8.72413546, 25.46645445, 44.10886825]), index=28, x=array([ 8.72185488, 25.97850255, 43.14570821]), fval=0.580990887775828, rho=-0.35328193701142446, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([ 0, 16, 17, 18, 19, 20, 21, 22, 23, 25, 27, 28]), old_indices_discarded=array([ 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 24, 26]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 8.72185488, 25.97850255, 43.14570821]), radius=0.5453899604895185, bounds=Bounds(lower=array([2., 0., 0.]), upper=array([20., 70., 70.]))), model_indices=array([ 0, 16, 17, 18, 20, 22, 23, 24, 25, 26, 27, 28]), model=ScalarModel(intercept=0.5807233256761218, linear_terms=array([ 0.00018277, -0.00020824, -0.00022326]), square_terms=array([[ 3.28558014e-02, -8.98515877e-05, -1.75565770e-04], - [-8.98515877e-05, 6.10157409e-07, 8.86164765e-07], - [-1.75565770e-04, 8.86164765e-07, 1.55938085e-06]]), scale=0.5453899604895185, shift=array([ 8.72185488, 25.97850255, 43.14570821])), vector_model=VectorModel(intercepts=array([ 0.05736286, 0.13097505, 0.15289447, 0.19437164, 0.22039886, - 0.23631479, 0.23653827, 0.08827519, -0.0506954 , -0.04028249, - -0.38487098, -0.40453749, -0.07787386, -0.05280456, -0.04320692, - -0.04588722, -0.05004941]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.]]]), scale=4.6369622223167655, shift=array([ 9.27512208, 46.36962222, 22.93103984])), candidate_index=34, candidate_x=array([ 9.20202687, 45.62648809, 22.79616498]), index=32, x=array([ 9.20259338, 45.60122914, 22.93885113]), fval=0.6412746242553712, rho=-0.13620936166915193, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([16, 17, 25, 27, 28, 30, 31, 32, 33]), old_indices_discarded=array([], dtype=int64), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 9.20259338, 45.60122914, 22.93885113]), radius=0.07245253472369946, bounds=Bounds(lower=array([1.1, 0. , 0. ]), upper=array([ 20., 70., 100.]))), model_indices=array([28, 32, 33, 34]), model=ScalarModel(intercept=0.6412746242553713, linear_terms=array([ 1.51821685e-04, 1.72405095e-05, -2.51853925e-07]), square_terms=array([[4.74437325e-04, 9.62985593e-08, 5.90606931e-08], + [9.62985593e-08, 3.24675398e-09, 3.85599517e-10], + [5.90606931e-08, 3.85599517e-10, 1.13736902e-10]]), scale=0.07245253472369946, shift=array([ 9.20259338, 45.60122914, 22.93885113])), vector_model=VectorModel(intercepts=array([ 0.04902536, 0.12501084, 0.1503711 , 0.19587102, 0.21991184, + 0.23522003, 0.23681939, 0.07111459, -0.07579182, -0.06299477, + -0.40502842, -0.41381428, -0.12605813, -0.09953675, -0.09019229, + -0.09362869, -0.09977548]), linear_terms=array([[0., 0., 0.], [0., 0., 0.], [0., 0., 0.], [0., 0., 0.], @@ -3625,12 +4582,12 @@ algorithm_output,"{'states': [State(trustregion=Region(center=array([ 8.7163601 [[0., 0., 0.], [0., 0., 0.], - [0., 0., 0.]]]), scale=4.363119683916148, shift=array([ 8.73056876, 26.22690146, 43.63119684])), candidate_index=30, candidate_x=array([ 8.72196737, 26.35103764, 43.54405232]), index=28, x=array([ 8.72185488, 25.97850255, 43.14570821]), fval=0.580990887775828, rho=-0.0023779073384515904, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([ 0, 16, 17, 18, 20, 22, 23, 24, 25, 26, 27, 28]), old_indices_discarded=array([15, 19, 21, 29]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 8.72185488, 25.97850255, 43.14570821]), radius=0.27269498024475924, bounds=Bounds(lower=array([2., 0., 0.]), upper=array([20., 70., 70.]))), model_indices=array([ 0, 16, 17, 18, 20, 22, 23, 25, 26, 27, 28, 30]), model=ScalarModel(intercept=0.5806880077878134, linear_terms=array([ 3.95885700e-05, -4.58270648e-05, -5.27705117e-05]), square_terms=array([[ 8.18480929e-03, -1.22056837e-06, -2.24743441e-05], - [-1.22056837e-06, 1.95797493e-08, 1.03792864e-08], - [-2.24743441e-05, 1.03792864e-08, 9.94564042e-08]]), scale=0.27269498024475924, shift=array([ 8.72185488, 25.97850255, 43.14570821])), vector_model=VectorModel(intercepts=array([ 0.05736286, 0.13097505, 0.15289447, 0.19437164, 0.22039886, - 0.23631479, 0.23653827, 0.08827519, -0.0506954 , -0.04028249, - -0.38487098, -0.40453749, -0.07787386, -0.05280456, -0.04320692, - -0.04588722, -0.05004941]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.]]]), scale=4.6369622223167655, shift=array([ 9.27512208, 46.36962222, 22.93103984])), candidate_index=35, candidate_x=array([ 9.18023587, 45.52896803, 22.9399869 ]), index=32, x=array([ 9.20259338, 45.60122914, 22.93885113]), fval=0.6412746242553712, rho=-3.7502853225457637, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([28, 32, 33, 34]), old_indices_discarded=array([], dtype=int64), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 9.20259338, 45.60122914, 22.93885113]), radius=0.03622626736184973, bounds=Bounds(lower=array([1.1, 0. , 0. ]), upper=array([ 20., 70., 100.]))), model_indices=array([28, 32, 34, 35]), model=ScalarModel(intercept=0.6412746242553709, linear_terms=array([-6.64869792e-04, 1.39932037e-04, 2.60605822e-05]), square_terms=array([[ 1.29547503e-04, -1.26581071e-06, -2.36967452e-07], + [-1.26581071e-06, 1.14410595e-07, 2.17757353e-08], + [-2.36967452e-07, 2.17757353e-08, 4.15737620e-09]]), scale=0.03622626736184973, shift=array([ 9.20259338, 45.60122914, 22.93885113])), vector_model=VectorModel(intercepts=array([ 0.04902536, 0.12501084, 0.1503711 , 0.19587102, 0.21991184, + 0.23522003, 0.23681939, 0.07111459, -0.07579182, -0.06299477, + -0.40502842, -0.41381428, -0.12605813, -0.09953675, -0.09019229, + -0.09362869, -0.09977548]), linear_terms=array([[0., 0., 0.], [0., 0., 0.], [0., 0., 0.], [0., 0., 0.], @@ -3712,12 +4669,12 @@ algorithm_output,"{'states': [State(trustregion=Region(center=array([ 8.7163601 [[0., 0., 0.], [0., 0., 0.], - [0., 0., 0.]]]), scale=4.363119683916148, shift=array([ 8.73056876, 26.22690146, 43.63119684])), candidate_index=31, candidate_x=array([ 8.72113357, 26.15752473, 43.35141019]), index=28, x=array([ 8.72185488, 25.97850255, 43.14570821]), fval=0.580990887775828, rho=-0.09385503572082314, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([ 0, 16, 17, 18, 20, 22, 23, 25, 26, 27, 28, 30]), old_indices_discarded=array([19, 21, 24, 29]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 8.72185488, 25.97850255, 43.14570821]), radius=0.13634749012237962, bounds=Bounds(lower=array([2., 0., 0.]), upper=array([20., 70., 70.]))), model_indices=array([ 0, 16, 17, 20, 23, 25, 27, 28, 30, 31]), model=ScalarModel(intercept=0.5806420787403895, linear_terms=array([ 1.04584464e-04, -4.42371793e-05, 5.86654137e-05]), square_terms=array([[ 2.07066925e-03, -1.00068104e-06, 5.73673262e-06], - [-1.00068104e-06, 3.07087921e-08, -1.90410228e-08], - [ 5.73673262e-06, -1.90410228e-08, 4.67071094e-08]]), scale=0.13634749012237962, shift=array([ 8.72185488, 25.97850255, 43.14570821])), vector_model=VectorModel(intercepts=array([ 0.05736286, 0.13097505, 0.15289447, 0.19437164, 0.22039886, - 0.23631479, 0.23653827, 0.08827519, -0.0506954 , -0.04028249, - -0.38487098, -0.40453749, -0.07787386, -0.05280456, -0.04320692, - -0.04588722, -0.05004941]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.]]]), scale=4.6369622223167655, shift=array([ 9.27512208, 46.36962222, 22.93103984])), candidate_index=36, candidate_x=array([ 9.23849715, 45.59719351, 22.94149216]), index=32, x=array([ 9.20259338, 45.60122914, 22.93885113]), fval=0.6412746242553712, rho=-0.40687960405411, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([28, 32, 34, 35]), old_indices_discarded=array([], dtype=int64), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 9.20259338, 45.60122914, 22.93885113]), radius=0.018113133680924865, bounds=Bounds(lower=array([1.1, 0. , 0. ]), upper=array([ 20., 70., 100.]))), model_indices=array([32, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48]), model=ScalarModel(intercept=0.6413039707695232, linear_terms=array([ 1.78846812e-05, -2.43776919e-05, 6.28993170e-07]), square_terms=array([[ 2.97194280e-05, 1.17262526e-07, -9.61426736e-08], + [ 1.17262526e-07, 2.47166769e-09, 2.00862617e-10], + [-9.61426736e-08, 2.00862617e-10, 1.63762035e-09]]), scale=0.018113133680924865, shift=array([ 9.20259338, 45.60122914, 22.93885113])), vector_model=VectorModel(intercepts=array([ 0.04902536, 0.12501084, 0.1503711 , 0.19587102, 0.21991184, + 0.23522003, 0.23681939, 0.07111459, -0.07579182, -0.06299477, + -0.40502842, -0.41381428, -0.12605813, -0.09953675, -0.09019229, + -0.09362869, -0.09977548]), linear_terms=array([[0., 0., 0.], [0., 0., 0.], [0., 0., 0.], [0., 0., 0.], @@ -3799,12 +4756,12 @@ algorithm_output,"{'states': [State(trustregion=Region(center=array([ 8.7163601 [[0., 0., 0.], [0., 0., 0.], - [0., 0., 0.]]]), scale=4.363119683916148, shift=array([ 8.73056876, 26.22690146, 43.63119684])), candidate_index=32, candidate_x=array([ 8.71553259, 26.06070155, 43.03708759]), index=28, x=array([ 8.72185488, 25.97850255, 43.14570821]), fval=0.580990887775828, rho=-0.10234664819442942, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([ 0, 16, 17, 20, 23, 25, 27, 28, 30, 31]), old_indices_discarded=array([], dtype=int64), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 8.72185488, 25.97850255, 43.14570821]), radius=0.06817374506118981, bounds=Bounds(lower=array([2., 0., 0.]), upper=array([20., 70., 70.]))), model_indices=array([25, 28, 31, 32]), model=ScalarModel(intercept=0.5809908877758275, linear_terms=array([ 7.06537639e-06, 3.74867801e-06, -1.07375396e-06]), square_terms=array([[ 4.99954315e-04, -1.25224134e-07, 6.68454662e-08], - [-1.25224134e-07, 1.50532620e-09, -1.13703811e-09], - [ 6.68454662e-08, -1.13703811e-09, 8.91212690e-10]]), scale=0.06817374506118981, shift=array([ 8.72185488, 25.97850255, 43.14570821])), vector_model=VectorModel(intercepts=array([ 0.05736286, 0.13097505, 0.15289447, 0.19437164, 0.22039886, - 0.23631479, 0.23653827, 0.08827519, -0.0506954 , -0.04028249, - -0.38487098, -0.40453749, -0.07787386, -0.05280456, -0.04320692, - -0.04588722, -0.05004941]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.]]]), scale=4.6369622223167655, shift=array([ 9.27512208, 46.36962222, 22.93103984])), candidate_index=49, candidate_x=array([ 9.19659884, 45.61914756, 22.93836602]), index=32, x=array([ 9.20259338, 45.60122914, 22.93885113]), fval=0.6412746242553712, rho=-0.6855188838995444, accepted=False, new_indices=array([37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48]), old_indices_used=array([32, 35, 36]), old_indices_discarded=array([], dtype=int64), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 9.20259338, 45.60122914, 22.93885113]), radius=0.009056566840462433, bounds=Bounds(lower=array([1.1, 0. , 0. ]), upper=array([ 20., 70., 100.]))), model_indices=array([32, 37, 38, 39, 40, 41, 42, 43, 44, 46, 47, 48]), model=ScalarModel(intercept=0.6412899966619717, linear_terms=array([-8.75824082e-06, -4.68883192e-07, -4.22220147e-07]), square_terms=array([[ 7.43343085e-06, 7.40486950e-10, -2.50861630e-08], + [ 7.40486950e-10, 4.06402636e-10, 3.14282337e-10], + [-2.50861630e-08, 3.14282337e-10, 4.97087023e-10]]), scale=0.009056566840462433, shift=array([ 9.20259338, 45.60122914, 22.93885113])), vector_model=VectorModel(intercepts=array([ 0.04902536, 0.12501084, 0.1503711 , 0.19587102, 0.21991184, + 0.23522003, 0.23681939, 0.07111459, -0.07579182, -0.06299477, + -0.40502842, -0.41381428, -0.12605813, -0.09953675, -0.09019229, + -0.09362869, -0.09977548]), linear_terms=array([[0., 0., 0.], [0., 0., 0.], [0., 0., 0.], [0., 0., 0.], @@ -3886,12 +4843,12 @@ algorithm_output,"{'states': [State(trustregion=Region(center=array([ 8.7163601 [[0., 0., 0.], [0., 0., 0.], - [0., 0., 0.]]]), scale=4.363119683916148, shift=array([ 8.73056876, 26.22690146, 43.63119684])), candidate_index=33, candidate_x=array([ 8.72088012, 25.91296479, 43.1644737 ]), index=28, x=array([ 8.72185488, 25.97850255, 43.14570821]), fval=0.580990887775828, rho=-1.954075119734427, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([25, 28, 31, 32]), old_indices_discarded=array([], dtype=int64), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 8.72185488, 25.97850255, 43.14570821]), radius=0.034086872530594906, bounds=Bounds(lower=array([2., 0., 0.]), upper=array([20., 70., 70.]))), model_indices=array([28, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45]), model=ScalarModel(intercept=0.5811086864651188, linear_terms=array([1.13396661e-04, 1.51063018e-05, 2.72776743e-05]), square_terms=array([[ 1.24677294e-04, -1.49585595e-07, -2.36287959e-07], - [-1.49585595e-07, 1.04238561e-09, 1.61365682e-09], - [-2.36287959e-07, 1.61365682e-09, 2.71907818e-09]]), scale=0.034086872530594906, shift=array([ 8.72185488, 25.97850255, 43.14570821])), vector_model=VectorModel(intercepts=array([ 0.05736286, 0.13097505, 0.15289447, 0.19437164, 0.22039886, - 0.23631479, 0.23653827, 0.08827519, -0.0506954 , -0.04028249, - -0.38487098, -0.40453749, -0.07787386, -0.05280456, -0.04320692, - -0.04588722, -0.05004941]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.]]]), scale=4.6369622223167655, shift=array([ 9.27512208, 46.36962222, 22.93103984])), candidate_index=50, candidate_x=array([ 9.21071609, 45.59986349, 22.94261649]), index=50, x=array([ 9.21071609, 45.59986349, 22.94261649]), fval=0.6412423314571071, rho=6.484931348405917, accepted=True, new_indices=array([], dtype=int64), old_indices_used=array([32, 37, 38, 39, 40, 41, 42, 43, 44, 46, 47, 48]), old_indices_discarded=array([36, 45, 49]), step_length=0.00905656684046146, relative_step_length=0.9999999999998925, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 9.21071609, 45.59986349, 22.94261649]), radius=0.018113133680924865, bounds=Bounds(lower=array([1.1, 0. , 0. ]), upper=array([ 20., 70., 100.]))), model_indices=array([32, 37, 38, 39, 42, 43, 44, 45, 47, 48, 49, 50]), model=ScalarModel(intercept=0.6412781189403443, linear_terms=array([-2.11788424e-05, -3.70967270e-06, -2.31489028e-05]), square_terms=array([[2.98553111e-05, 2.06031515e-08, 1.49854249e-08], + [2.06031515e-08, 2.15439326e-09, 1.93523563e-09], + [1.49854249e-08, 1.93523563e-09, 2.51993300e-09]]), scale=0.018113133680924865, shift=array([ 9.21071609, 45.59986349, 22.94261649])), vector_model=VectorModel(intercepts=array([ 0.04902536, 0.12501084, 0.1503711 , 0.19587102, 0.21991184, + 0.23522003, 0.23681939, 0.07111459, -0.07579182, -0.06299477, + -0.40502842, -0.41381428, -0.12605813, -0.09953675, -0.09019229, + -0.09362869, -0.09977548]), linear_terms=array([[0., 0., 0.], [0., 0., 0.], [0., 0., 0.], [0., 0., 0.], @@ -3973,12 +4930,12 @@ algorithm_output,"{'states': [State(trustregion=Region(center=array([ 8.7163601 [[0., 0., 0.], [0., 0., 0.], - [0., 0., 0.]]]), scale=4.363119683916148, shift=array([ 8.73056876, 26.22690146, 43.63119684])), candidate_index=46, candidate_x=array([ 8.69857687, 25.96606633, 43.12327065]), index=28, x=array([ 8.72185488, 25.97850255, 43.14570821]), fval=0.580990887775828, rho=-1.3833936672204055, accepted=False, new_indices=array([34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45]), old_indices_used=array([28, 32, 33]), old_indices_discarded=array([], dtype=int64), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 8.72185488, 25.97850255, 43.14570821]), radius=0.017043436265297453, bounds=Bounds(lower=array([2., 0., 0.]), upper=array([20., 70., 70.]))), model_indices=array([28, 34, 35, 36, 37, 39, 40, 41, 42, 43, 44, 45]), model=ScalarModel(intercept=0.5811171305203005, linear_terms=array([ 5.76506446e-05, -3.62583561e-06, 6.89029454e-06]), square_terms=array([[ 3.11396488e-05, -1.16519026e-08, -1.37227588e-08], - [-1.16519026e-08, 5.49503533e-10, -2.38852506e-10], - [-1.37227588e-08, -2.38852506e-10, 2.80652166e-10]]), scale=0.017043436265297453, shift=array([ 8.72185488, 25.97850255, 43.14570821])), vector_model=VectorModel(intercepts=array([ 0.05736286, 0.13097505, 0.15289447, 0.19437164, 0.22039886, - 0.23631479, 0.23653827, 0.08827519, -0.0506954 , -0.04028249, - -0.38487098, -0.40453749, -0.07787386, -0.05280456, -0.04320692, - -0.04588722, -0.05004941]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.]]]), scale=4.6369622223167655, shift=array([ 9.27512208, 46.36962222, 22.93103984])), candidate_index=51, candidate_x=array([ 9.21780334, 45.60262928, 22.9599168 ]), index=50, x=array([ 9.21071609, 45.59986349, 22.94261649]), fval=0.6412423314571071, rho=-2.280933910129145, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([32, 37, 38, 39, 42, 43, 44, 45, 47, 48, 49, 50]), old_indices_discarded=array([35, 36, 40, 41, 46]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 9.21071609, 45.59986349, 22.94261649]), radius=0.009056566840462433, bounds=Bounds(lower=array([1.1, 0. , 0. ]), upper=array([ 20., 70., 100.]))), model_indices=array([32, 37, 38, 39, 42, 44, 45, 47, 48, 49, 50, 51]), model=ScalarModel(intercept=0.6412840152428855, linear_terms=array([ 1.53216145e-06, 8.28819200e-07, -1.52798571e-06]), square_terms=array([[7.46594783e-06, 5.70100161e-09, 7.34594153e-09], + [5.70100161e-09, 3.61079251e-10, 8.20620599e-11], + [7.34594153e-09, 8.20620599e-11, 1.00086054e-10]]), scale=0.009056566840462433, shift=array([ 9.21071609, 45.59986349, 22.94261649])), vector_model=VectorModel(intercepts=array([ 0.04902536, 0.12501084, 0.1503711 , 0.19587102, 0.21991184, + 0.23522003, 0.23681939, 0.07111459, -0.07579182, -0.06299477, + -0.40502842, -0.41381428, -0.12605813, -0.09953675, -0.09019229, + -0.09362869, -0.09977548]), linear_terms=array([[0., 0., 0.], [0., 0., 0.], [0., 0., 0.], [0., 0., 0.], @@ -4060,12 +5017,12 @@ algorithm_output,"{'states': [State(trustregion=Region(center=array([ 8.7163601 [[0., 0., 0.], [0., 0., 0.], - [0., 0., 0.]]]), scale=4.363119683916148, shift=array([ 8.73056876, 26.22690146, 43.63119684])), candidate_index=47, candidate_x=array([ 8.70611379, 25.97673235, 43.13941827]), index=28, x=array([ 8.72185488, 25.97850255, 43.14570821]), fval=0.580990887775828, rho=-1.8228066353216037, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([28, 34, 35, 36, 37, 39, 40, 41, 42, 43, 44, 45]), old_indices_discarded=array([33, 38, 46]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 8.72185488, 25.97850255, 43.14570821]), radius=0.008521718132648726, bounds=Bounds(lower=array([2., 0., 0.]), upper=array([20., 70., 70.]))), model_indices=array([28, 34, 35, 36, 37, 39, 40, 41, 43, 44, 45, 47]), model=ScalarModel(intercept=0.5811100336023113, linear_terms=array([2.60155074e-05, 1.80174566e-06, 5.58592582e-06]), square_terms=array([[ 7.80001662e-06, -1.29180218e-08, -9.49077948e-09], - [-1.29180218e-08, 1.92735319e-10, -8.20867493e-12], - [-9.49077948e-09, -8.20867493e-12, 1.31513879e-10]]), scale=0.008521718132648726, shift=array([ 8.72185488, 25.97850255, 43.14570821])), vector_model=VectorModel(intercepts=array([ 0.05736286, 0.13097505, 0.15289447, 0.19437164, 0.22039886, - 0.23631479, 0.23653827, 0.08827519, -0.0506954 , -0.04028249, - -0.38487098, -0.40453749, -0.07787386, -0.05280456, -0.04320692, - -0.04588722, -0.05004941]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.]]]), scale=4.6369622223167655, shift=array([ 9.27512208, 46.36962222, 22.93103984])), candidate_index=52, candidate_x=array([ 9.20919782, 45.59544441, 22.95078009]), index=52, x=array([ 9.20919782, 45.59544441, 22.95078009]), fval=0.6412216190982429, rho=10.70802381239341, accepted=True, new_indices=array([], dtype=int64), old_indices_used=array([32, 37, 38, 39, 42, 44, 45, 47, 48, 49, 50, 51]), old_indices_discarded=array([36, 40, 41, 43, 46]), step_length=0.009406262300279364, relative_step_length=1.0386123644839214, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 9.20919782, 45.59544441, 22.95078009]), radius=0.018113133680924865, bounds=Bounds(lower=array([1.1, 0. , 0. ]), upper=array([ 20., 70., 100.]))), model_indices=array([32, 37, 39, 42, 43, 44, 45, 47, 48, 50, 51, 52]), model=ScalarModel(intercept=0.6412682696446266, linear_terms=array([-1.06086822e-05, 3.89954644e-05, -2.40744738e-05]), square_terms=array([[ 2.98828945e-05, -1.49158925e-08, 5.43108663e-08], + [-1.49158925e-08, 4.82998378e-09, -1.07526917e-09], + [ 5.43108663e-08, -1.07526917e-09, 1.09420463e-09]]), scale=0.018113133680924865, shift=array([ 9.20919782, 45.59544441, 22.95078009])), vector_model=VectorModel(intercepts=array([ 0.04902536, 0.12501084, 0.1503711 , 0.19587102, 0.21991184, + 0.23522003, 0.23681939, 0.07111459, -0.07579182, -0.06299477, + -0.40502842, -0.41381428, -0.12605813, -0.09953675, -0.09019229, + -0.09362869, -0.09977548]), linear_terms=array([[0., 0., 0.], [0., 0., 0.], [0., 0., 0.], [0., 0., 0.], @@ -4147,12 +5104,12 @@ algorithm_output,"{'states': [State(trustregion=Region(center=array([ 8.7163601 [[0., 0., 0.], [0., 0., 0.], - [0., 0., 0.]]]), scale=4.363119683916148, shift=array([ 8.73056876, 26.22690146, 43.63119684])), candidate_index=48, candidate_x=array([ 8.71396379, 25.9770619 , 43.14283159]), index=28, x=array([ 8.72185488, 25.97850255, 43.14570821]), fval=0.580990887775828, rho=-1.10957294130167, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([28, 34, 35, 36, 37, 39, 40, 41, 43, 44, 45, 47]), old_indices_discarded=array([38, 42, 46]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 8.72185488, 25.97850255, 43.14570821]), radius=0.004260859066324363, bounds=Bounds(lower=array([2., 0., 0.]), upper=array([20., 70., 70.]))), model_indices=array([28, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60]), model=ScalarModel(intercept=0.5810063645730235, linear_terms=array([-6.56020665e-06, -6.22425921e-07, -3.82458273e-06]), square_terms=array([[1.96889901e-06, 4.61265002e-09, 1.23910532e-08], - [4.61265002e-09, 5.67556032e-11, 2.24648202e-10], - [1.23910532e-08, 2.24648202e-10, 1.04044909e-09]]), scale=0.004260859066324363, shift=array([ 8.72185488, 25.97850255, 43.14570821])), vector_model=VectorModel(intercepts=array([ 0.05736286, 0.13097505, 0.15289447, 0.19437164, 0.22039886, - 0.23631479, 0.23653827, 0.08827519, -0.0506954 , -0.04028249, - -0.38487098, -0.40453749, -0.07787386, -0.05280456, -0.04320692, - -0.04588722, -0.05004941]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.]]]), scale=4.6369622223167655, shift=array([ 9.27512208, 46.36962222, 22.93103984])), candidate_index=53, candidate_x=array([ 9.21171307, 45.58016496, 22.96021119]), index=52, x=array([ 9.20919782, 45.59544441, 22.95078009]), fval=0.6412216190982429, rho=-0.7048640670081282, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([32, 37, 39, 42, 43, 44, 45, 47, 48, 50, 51, 52]), old_indices_discarded=array([35, 36, 38, 40, 41, 46, 49]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 9.20919782, 45.59544441, 22.95078009]), radius=0.009056566840462433, bounds=Bounds(lower=array([1.1, 0. , 0. ]), upper=array([ 20., 70., 100.]))), model_indices=array([32, 37, 39, 42, 44, 45, 47, 48, 50, 51, 52, 53]), model=ScalarModel(intercept=0.6412725618779757, linear_terms=array([-1.25153127e-06, 1.15292460e-05, -7.79485816e-06]), square_terms=array([[7.46927647e-06, 6.54768333e-09, 7.38429733e-09], + [6.54768333e-09, 6.79583317e-10, 1.04654917e-11], + [7.38429733e-09, 1.04654917e-11, 1.48042845e-10]]), scale=0.009056566840462433, shift=array([ 9.20919782, 45.59544441, 22.95078009])), vector_model=VectorModel(intercepts=array([ 0.04902536, 0.12501084, 0.1503711 , 0.19587102, 0.21991184, + 0.23522003, 0.23681939, 0.07111459, -0.07579182, -0.06299477, + -0.40502842, -0.41381428, -0.12605813, -0.09953675, -0.09019229, + -0.09362869, -0.09977548]), linear_terms=array([[0., 0., 0.], [0., 0., 0.], [0., 0., 0.], [0., 0., 0.], @@ -4234,12 +5191,12 @@ algorithm_output,"{'states': [State(trustregion=Region(center=array([ 8.7163601 [[0., 0., 0.], [0., 0., 0.], - [0., 0., 0.]]]), scale=4.363119683916148, shift=array([ 8.73056876, 26.22690146, 43.63119684])), candidate_index=61, candidate_x=array([ 8.72470448, 25.97945088, 43.14873068]), index=28, x=array([ 8.72185488, 25.97850255, 43.14570821]), fval=0.580990887775828, rho=-3.922909252116266, accepted=False, new_indices=array([49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60]), old_indices_used=array([28, 47, 48]), old_indices_discarded=array([], dtype=int64), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 8.72185488, 25.97850255, 43.14570821]), radius=0.0021304295331621816, bounds=Bounds(lower=array([2., 0., 0.]), upper=array([20., 70., 70.]))), model_indices=array([28, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61]), model=ScalarModel(intercept=0.581007869957291, linear_terms=array([4.14314601e-06, 3.46219546e-06, 9.16989650e-07]), square_terms=array([[ 4.73464369e-07, -3.44895739e-09, -6.25894439e-10], - [-3.44895739e-09, 5.23722004e-11, 8.21683908e-12], - [-6.25894439e-10, 8.21683908e-12, 3.08838918e-12]]), scale=0.0021304295331621816, shift=array([ 8.72185488, 25.97850255, 43.14570821])), vector_model=VectorModel(intercepts=array([ 0.05736286, 0.13097505, 0.15289447, 0.19437164, 0.22039886, - 0.23631479, 0.23653827, 0.08827519, -0.0506954 , -0.04028249, - -0.38487098, -0.40453749, -0.07787386, -0.05280456, -0.04320692, - -0.04588722, -0.05004941]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.]]]), scale=4.6369622223167655, shift=array([ 9.27512208, 46.36962222, 22.93103984])), candidate_index=54, candidate_x=array([ 9.20972781, 45.58795377, 22.95584422]), index=52, x=array([ 9.20919782, 45.59544441, 22.95078009]), fval=0.6412216190982429, rho=-0.3919786874561503, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([32, 37, 39, 42, 44, 45, 47, 48, 50, 51, 52, 53]), old_indices_discarded=array([36, 38, 40, 41, 43, 46, 49]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 9.20919782, 45.59544441, 22.95078009]), radius=0.004528283420231216, bounds=Bounds(lower=array([1.1, 0. , 0. ]), upper=array([ 20., 70., 100.]))), model_indices=array([32, 37, 42, 44, 45, 47, 48, 50, 51, 52, 53, 54]), model=ScalarModel(intercept=0.6412695031423565, linear_terms=array([-5.52474194e-07, 6.85950407e-06, -5.63927150e-06]), square_terms=array([[ 1.86711180e-06, 1.32728269e-09, 2.80810292e-09], + [ 1.32728269e-09, 1.78679129e-10, -2.22631529e-11], + [ 2.80810292e-09, -2.22631529e-11, 4.90120302e-11]]), scale=0.004528283420231216, shift=array([ 9.20919782, 45.59544441, 22.95078009])), vector_model=VectorModel(intercepts=array([ 0.04902536, 0.12501084, 0.1503711 , 0.19587102, 0.21991184, + 0.23522003, 0.23681939, 0.07111459, -0.07579182, -0.06299477, + -0.40502842, -0.41381428, -0.12605813, -0.09953675, -0.09019229, + -0.09362869, -0.09977548]), linear_terms=array([[0., 0., 0.], [0., 0., 0.], [0., 0., 0.], [0., 0., 0.], @@ -4321,12 +5278,12 @@ algorithm_output,"{'states': [State(trustregion=Region(center=array([ 8.7163601 [[0., 0., 0.], [0., 0., 0.], - [0., 0., 0.]]]), scale=4.363119683916148, shift=array([ 8.73056876, 26.22690146, 43.63119684])), candidate_index=62, candidate_x=array([ 8.72030525, 25.97708983, 43.14533188]), index=28, x=array([ 8.72185488, 25.97850255, 43.14570821]), fval=0.580990887775828, rho=-2.593871278947555, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([28, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61]), old_indices_discarded=array([48, 49, 50]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 8.72185488, 25.97850255, 43.14570821]), radius=0.0010652147665810908, bounds=Bounds(lower=array([2., 0., 0.]), upper=array([20., 70., 70.]))), model_indices=array([28, 51, 52, 54, 55, 56, 57, 58, 59, 60, 61, 62]), model=ScalarModel(intercept=0.581007952943693, linear_terms=array([1.98812639e-06, 1.65136096e-06, 4.57207645e-07]), square_terms=array([[ 1.18977847e-07, -5.41259807e-10, -2.30266367e-10], - [-5.41259807e-10, 8.12720771e-12, 1.80859978e-12], - [-2.30266367e-10, 1.80859978e-12, 1.15800095e-12]]), scale=0.0010652147665810908, shift=array([ 8.72185488, 25.97850255, 43.14570821])), vector_model=VectorModel(intercepts=array([ 0.05736286, 0.13097505, 0.15289447, 0.19437164, 0.22039886, - 0.23631479, 0.23653827, 0.08827519, -0.0506954 , -0.04028249, - -0.38487098, -0.40453749, -0.07787386, -0.05280456, -0.04320692, - -0.04588722, -0.05004941]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.]]]), scale=4.6369622223167655, shift=array([ 9.27512208, 46.36962222, 22.93103984])), candidate_index=55, candidate_x=array([ 9.20943004, 45.59195102, 22.95365198]), index=52, x=array([ 9.20919782, 45.59544441, 22.95078009]), fval=0.6412216190982429, rho=-0.1964321529222822, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([32, 37, 42, 44, 45, 47, 48, 50, 51, 52, 53, 54]), old_indices_discarded=array([], dtype=int64), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 9.20919782, 45.59544441, 22.95078009]), radius=0.002264141710115608, bounds=Bounds(lower=array([1.1, 0. , 0. ]), upper=array([ 20., 70., 100.]))), model_indices=array([37, 42, 50, 52, 54, 55]), model=ScalarModel(intercept=0.6412192039265117, linear_terms=array([-1.70585100e-05, -1.91702725e-05, -2.07860044e-05]), square_terms=array([[4.77656571e-07, 4.70371007e-09, 6.34361770e-09], + [4.70371007e-09, 6.95489985e-10, 7.38921113e-10], + [6.34361770e-09, 7.38921113e-10, 8.02053934e-10]]), scale=0.002264141710115608, shift=array([ 9.20919782, 45.59544441, 22.95078009])), vector_model=VectorModel(intercepts=array([ 0.04902536, 0.12501084, 0.1503711 , 0.19587102, 0.21991184, + 0.23522003, 0.23681939, 0.07111459, -0.07579182, -0.06299477, + -0.40502842, -0.41381428, -0.12605813, -0.09953675, -0.09019229, + -0.09362869, -0.09977548]), linear_terms=array([[0., 0., 0.], [0., 0., 0.], [0., 0., 0.], [0., 0., 0.], @@ -4408,12 +5365,12 @@ algorithm_output,"{'states': [State(trustregion=Region(center=array([ 8.7163601 [[0., 0., 0.], [0., 0., 0.], - [0., 0., 0.]]]), scale=4.363119683916148, shift=array([ 8.73056876, 26.22690146, 43.63119684])), candidate_index=63, candidate_x=array([ 8.72106413, 25.97781499, 43.14551672]), index=28, x=array([ 8.72185488, 25.97850255, 43.14570821]), fval=0.580990887775828, rho=-2.6470619847259935, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([28, 51, 52, 54, 55, 56, 57, 58, 59, 60, 61, 62]), old_indices_discarded=array([49, 50, 53]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 8.72185488, 25.97850255, 43.14570821]), radius=0.0005326073832905454, bounds=Bounds(lower=array([2., 0., 0.]), upper=array([20., 70., 70.]))), model_indices=array([28, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75]), model=ScalarModel(intercept=0.580992825150933, linear_terms=array([-2.09690368e-06, -1.32178647e-06, -4.34809356e-07]), square_terms=array([[3.16780553e-08, 2.19616885e-10, 5.91910735e-11], - [2.19616885e-10, 1.25669148e-11, 3.61684196e-12], - [5.91910735e-11, 3.61684196e-12, 1.06608815e-12]]), scale=0.0005326073832905454, shift=array([ 8.72185488, 25.97850255, 43.14570821])), vector_model=VectorModel(intercepts=array([ 0.05736286, 0.13097505, 0.15289447, 0.19437164, 0.22039886, - 0.23631479, 0.23653827, 0.08827519, -0.0506954 , -0.04028249, - -0.38487098, -0.40453749, -0.07787386, -0.05280456, -0.04320692, - -0.04588722, -0.05004941]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.]]]), scale=4.6369622223167655, shift=array([ 9.27512208, 46.36962222, 22.93103984])), candidate_index=56, candidate_x=array([ 9.21035845, 45.59676801, 22.95221521]), index=52, x=array([ 9.20919782, 45.59544441, 22.95078009]), fval=0.6412216190982429, rho=-0.4353628908997743, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([37, 42, 50, 52, 54, 55]), old_indices_discarded=array([], dtype=int64), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 9.20919782, 45.59544441, 22.95078009]), radius=0.001132070855057804, bounds=Bounds(lower=array([1.1, 0. , 0. ]), upper=array([ 20., 70., 100.]))), model_indices=array([52, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68]), model=ScalarModel(intercept=0.6412231453306527, linear_terms=array([9.79372427e-06, 8.30626977e-07, 4.41893963e-07]), square_terms=array([[ 1.08649853e-07, -1.87783273e-10, -4.03006738e-11], + [-1.87783273e-10, 4.59613271e-12, 1.92334535e-12], + [-4.03006738e-11, 1.92334535e-12, 8.81906257e-13]]), scale=0.001132070855057804, shift=array([ 9.20919782, 45.59544441, 22.95078009])), vector_model=VectorModel(intercepts=array([ 0.04902536, 0.12501084, 0.1503711 , 0.19587102, 0.21991184, + 0.23522003, 0.23681939, 0.07111459, -0.07579182, -0.06299477, + -0.40502842, -0.41381428, -0.12605813, -0.09953675, -0.09019229, + -0.09362869, -0.09977548]), linear_terms=array([[0., 0., 0.], [0., 0., 0.], [0., 0., 0.], [0., 0., 0.], @@ -4495,12 +5452,12 @@ algorithm_output,"{'states': [State(trustregion=Region(center=array([ 8.7163601 [[0., 0., 0.], [0., 0., 0.], - [0., 0., 0.]]]), scale=4.363119683916148, shift=array([ 8.73056876, 26.22690146, 43.63119684])), candidate_index=76, candidate_x=array([ 8.72230512, 25.97877463, 43.14579142]), index=28, x=array([ 8.72185488, 25.97850255, 43.14570821]), fval=0.580990887775828, rho=-1.0309330308500069, accepted=False, new_indices=array([64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75]), old_indices_used=array([28, 62, 63]), old_indices_discarded=array([], dtype=int64), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 8.72185488, 25.97850255, 43.14570821]), radius=0.0002663036916452727, bounds=Bounds(lower=array([2., 0., 0.]), upper=array([20., 70., 70.]))), model_indices=array([28, 64, 65, 66, 67, 68, 69, 70, 71, 73, 74, 76]), model=ScalarModel(intercept=0.5809927657181087, linear_terms=array([-2.06201573e-07, 2.86254219e-07, -8.46476238e-08]), square_terms=array([[ 7.78476295e-09, -1.68622776e-11, 4.35673315e-12], - [-1.68622776e-11, 3.05210650e-13, -4.62753551e-14], - [ 4.35673315e-12, -4.62753551e-14, 5.97582683e-14]]), scale=0.0002663036916452727, shift=array([ 8.72185488, 25.97850255, 43.14570821])), vector_model=VectorModel(intercepts=array([ 0.05736286, 0.13097505, 0.15289447, 0.19437164, 0.22039886, - 0.23631479, 0.23653827, 0.08827519, -0.0506954 , -0.04028249, - -0.38487098, -0.40453749, -0.07787386, -0.05280456, -0.04320692, - -0.04588722, -0.05004941]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.]]]), scale=4.6369622223167655, shift=array([ 9.27512208, 46.36962222, 22.93103984])), candidate_index=69, candidate_x=array([ 9.20807174, 45.59534284, 22.95072352]), index=69, x=array([ 9.20807174, 45.59534284, 22.95072352]), fval=0.6412143824581863, rho=0.739578726104902, accepted=True, new_indices=array([57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68]), old_indices_used=array([52, 55, 56]), old_indices_discarded=array([], dtype=int64), step_length=0.0011320708550585452, relative_step_length=1.0000000000006546, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 9.20807174, 45.59534284, 22.95072352]), radius=0.002264141710115608, bounds=Bounds(lower=array([1.1, 0. , 0. ]), upper=array([ 20., 70., 100.]))), model_indices=array([52, 57, 58, 59, 60, 61, 62, 63, 65, 67, 68, 69]), model=ScalarModel(intercept=0.6412131794518777, linear_terms=array([ 1.94153193e-05, 3.55006418e-07, -8.32585471e-08]), square_terms=array([[ 4.34534062e-07, -3.23553362e-10, 9.72098765e-10], + [-3.23553362e-10, 1.06006138e-12, -2.24653152e-12], + [ 9.72098765e-10, -2.24653152e-12, 7.26875070e-12]]), scale=0.002264141710115608, shift=array([ 9.20807174, 45.59534284, 22.95072352])), vector_model=VectorModel(intercepts=array([ 0.04902536, 0.12501084, 0.1503711 , 0.19587102, 0.21991184, + 0.23522003, 0.23681939, 0.07111459, -0.07579182, -0.06299477, + -0.40502842, -0.41381428, -0.12605813, -0.09953675, -0.09019229, + -0.09362869, -0.09977548]), linear_terms=array([[0., 0., 0.], [0., 0., 0.], [0., 0., 0.], [0., 0., 0.], @@ -4582,12 +5539,12 @@ algorithm_output,"{'states': [State(trustregion=Region(center=array([ 8.7163601 [[0., 0., 0.], [0., 0., 0.], - [0., 0., 0.]]]), scale=4.363119683916148, shift=array([ 8.73056876, 26.22690146, 43.63119684])), candidate_index=77, candidate_x=array([ 8.72200462, 25.97829015, 43.14577101]), index=28, x=array([ 8.72185488, 25.97850255, 43.14570821]), fval=0.580990887775828, rho=-2.6545028657866205, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([28, 64, 65, 66, 67, 68, 69, 70, 71, 73, 74, 76]), old_indices_discarded=array([63, 72, 75]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 8.72185488, 25.97850255, 43.14570821]), radius=0.00013315184582263635, bounds=Bounds(lower=array([2., 0., 0.]), upper=array([20., 70., 70.]))), model_indices=array([28, 64, 65, 66, 68, 69, 70, 71, 73, 74, 76, 77]), model=ScalarModel(intercept=0.5809928326881444, linear_terms=array([-9.70252520e-08, 6.80074887e-08, -1.32668023e-07]), square_terms=array([[ 1.94595930e-09, -2.51233769e-12, 3.33055322e-12], - [-2.51233769e-12, 3.03645152e-14, -1.82122892e-14], - [ 3.33055322e-12, -1.82122892e-14, 6.63416407e-14]]), scale=0.00013315184582263635, shift=array([ 8.72185488, 25.97850255, 43.14570821])), vector_model=VectorModel(intercepts=array([ 0.05736286, 0.13097505, 0.15289447, 0.19437164, 0.22039886, - 0.23631479, 0.23653827, 0.08827519, -0.0506954 , -0.04028249, - -0.38487098, -0.40453749, -0.07787386, -0.05280456, -0.04320692, - -0.04588722, -0.05004941]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.]]]), scale=4.6369622223167655, shift=array([ 9.27512208, 46.36962222, 22.93103984])), candidate_index=70, candidate_x=array([ 9.20580884, 45.59527628, 22.95075811]), index=70, x=array([ 9.20580884, 45.59527628, 22.95075811]), fval=0.6412099333022344, rho=0.23173453857046095, accepted=True, new_indices=array([], dtype=int64), old_indices_used=array([52, 57, 58, 59, 60, 61, 62, 63, 65, 67, 68, 69]), old_indices_discarded=array([37, 42, 50, 54, 55, 56, 64, 66]), step_length=0.00226414171011655, relative_step_length=1.0000000000004161, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 9.20580884, 45.59527628, 22.95075811]), radius=0.004528283420231216, bounds=Bounds(lower=array([1.1, 0. , 0. ]), upper=array([ 20., 70., 100.]))), model_indices=array([52, 57, 58, 59, 60, 61, 62, 63, 64, 67, 68, 70]), model=ScalarModel(intercept=0.6412064122584149, linear_terms=array([ 2.26657859e-05, -3.18696222e-06, 2.54922192e-06]), square_terms=array([[ 1.82543914e-06, 1.06656974e-08, -3.02946807e-09], + [ 1.06656974e-08, 2.19743985e-10, -5.76034095e-11], + [-3.02946807e-09, -5.76034095e-11, 2.90254095e-11]]), scale=0.004528283420231216, shift=array([ 9.20580884, 45.59527628, 22.95075811])), vector_model=VectorModel(intercepts=array([ 0.04902536, 0.12501084, 0.1503711 , 0.19587102, 0.21991184, + 0.23522003, 0.23681939, 0.07111459, -0.07579182, -0.06299477, + -0.40502842, -0.41381428, -0.12605813, -0.09953675, -0.09019229, + -0.09362869, -0.09977548]), linear_terms=array([[0., 0., 0.], [0., 0., 0.], [0., 0., 0.], [0., 0., 0.], @@ -4669,12 +5626,12 @@ algorithm_output,"{'states': [State(trustregion=Region(center=array([ 8.7163601 [[0., 0., 0.], [0., 0., 0.], - [0., 0., 0.]]]), scale=4.363119683916148, shift=array([ 8.73056876, 26.22690146, 43.63119684])), candidate_index=78, candidate_x=array([ 8.72192711, 25.97845136, 43.14580806]), index=28, x=array([ 8.72185488, 25.97850255, 43.14570821]), fval=0.580990887775828, rho=-2.609791754278253, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([28, 64, 65, 66, 68, 69, 70, 71, 73, 74, 76, 77]), old_indices_discarded=array([67, 72, 75]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 8.72185488, 25.97850255, 43.14570821]), radius=6.657592291131817e-05, bounds=Bounds(lower=array([2., 0., 0.]), upper=array([20., 70., 70.]))), model_indices=array([28, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90]), model=ScalarModel(intercept=0.5809911195463036, linear_terms=array([ 4.82378283e-08, -1.32336737e-07, 9.26434829e-08]), square_terms=array([[ 4.83251114e-10, 1.04941086e-12, -7.62859369e-13], - [ 1.04941086e-12, 5.22648209e-14, -3.61875784e-14], - [-7.62859369e-13, -3.61875784e-14, 2.50903019e-14]]), scale=6.657592291131817e-05, shift=array([ 8.72185488, 25.97850255, 43.14570821])), vector_model=VectorModel(intercepts=array([ 0.05736286, 0.13097505, 0.15289447, 0.19437164, 0.22039886, - 0.23631479, 0.23653827, 0.08827519, -0.0506954 , -0.04028249, - -0.38487098, -0.40453749, -0.07787386, -0.05280456, -0.04320692, - -0.04588722, -0.05004941]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.]]]), scale=4.6369622223167655, shift=array([ 9.27512208, 46.36962222, 22.93103984])), candidate_index=71, candidate_x=array([ 9.20139767, 45.59606286, 22.9501037 ]), index=70, x=array([ 9.20580884, 45.59527628, 22.95075811]), fval=0.6412099333022344, rho=-3.284681929947907, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([52, 57, 58, 59, 60, 61, 62, 63, 64, 67, 68, 70]), old_indices_discarded=array([32, 37, 42, 44, 45, 47, 48, 50, 51, 53, 54, 55, 56, 65, 66, 69]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 9.20580884, 45.59527628, 22.95075811]), radius=0.002264141710115608, bounds=Bounds(lower=array([1.1, 0. , 0. ]), upper=array([ 20., 70., 100.]))), model_indices=array([52, 57, 58, 60, 62, 63, 64, 65, 66, 68, 69, 70]), model=ScalarModel(intercept=0.6412079518224751, linear_terms=array([ 8.65500838e-06, 3.77131685e-07, -1.47696736e-06]), square_terms=array([[ 4.64008756e-07, -3.22180177e-10, 3.94868556e-09], + [-3.22180177e-10, 1.69138274e-12, -1.39191756e-12], + [ 3.94868556e-09, -1.39191756e-12, 7.67133561e-11]]), scale=0.002264141710115608, shift=array([ 9.20580884, 45.59527628, 22.95075811])), vector_model=VectorModel(intercepts=array([ 0.04902536, 0.12501084, 0.1503711 , 0.19587102, 0.21991184, + 0.23522003, 0.23681939, 0.07111459, -0.07579182, -0.06299477, + -0.40502842, -0.41381428, -0.12605813, -0.09953675, -0.09019229, + -0.09362869, -0.09977548]), linear_terms=array([[0., 0., 0.], [0., 0., 0.], [0., 0., 0.], [0., 0., 0.], @@ -4756,12 +5713,12 @@ algorithm_output,"{'states': [State(trustregion=Region(center=array([ 8.7163601 [[0., 0., 0.], [0., 0., 0.], - [0., 0., 0.]]]), scale=4.363119683916148, shift=array([ 8.73056876, 26.22690146, 43.63119684])), candidate_index=91, candidate_x=array([ 8.72183585, 25.97855488, 43.14567157]), index=28, x=array([ 8.72185488, 25.97850255, 43.14570821]), fval=0.580990887775828, rho=-0.1763831210104783, accepted=False, new_indices=array([79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90]), old_indices_used=array([28, 77, 78]), old_indices_discarded=array([], dtype=int64), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 8.72185488, 25.97850255, 43.14570821]), radius=3.328796145565909e-05, bounds=Bounds(lower=array([2., 0., 0.]), upper=array([20., 70., 70.]))), model_indices=array([28, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 90]), model=ScalarModel(intercept=0.5809911615842549, linear_terms=array([-5.67313523e-09, 4.10531291e-08, 4.04327659e-08]), square_terms=array([[ 1.21071477e-10, -1.95768053e-13, -1.69802029e-13], - [-1.95768053e-13, 4.69351511e-15, 4.70532428e-15], - [-1.69802029e-13, 4.70532428e-15, 4.79077377e-15]]), scale=3.328796145565909e-05, shift=array([ 8.72185488, 25.97850255, 43.14570821])), vector_model=VectorModel(intercepts=array([ 0.05736286, 0.13097505, 0.15289447, 0.19437164, 0.22039886, - 0.23631479, 0.23653827, 0.08827519, -0.0506954 , -0.04028249, - -0.38487098, -0.40453749, -0.07787386, -0.05280456, -0.04320692, - -0.04588722, -0.05004941]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.]]]), scale=4.6369622223167655, shift=array([ 9.27512208, 46.36962222, 22.93103984])), candidate_index=72, candidate_x=array([ 9.20359224, 45.5951304 , 22.95119601]), index=70, x=array([ 9.20580884, 45.59527628, 22.95075811]), fval=0.6412099333022344, rho=-5.550713913269525, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([52, 57, 58, 60, 62, 63, 64, 65, 66, 68, 69, 70]), old_indices_discarded=array([37, 50, 54, 55, 56, 59, 61, 67, 71]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 9.20580884, 45.59527628, 22.95075811]), radius=0.001132070855057804, bounds=Bounds(lower=array([1.1, 0. , 0. ]), upper=array([ 20., 70., 100.]))), model_indices=array([52, 57, 58, 60, 62, 63, 64, 65, 66, 69, 70, 72]), model=ScalarModel(intercept=0.6412309039854828, linear_terms=array([-4.88020617e-06, 1.30537143e-06, 2.03420926e-06]), square_terms=array([[ 1.18870178e-07, -4.72177435e-10, 1.32325984e-10], + [-4.72177435e-10, 4.20642500e-12, 1.33038186e-12], + [ 1.32325984e-10, 1.33038186e-12, 7.96019463e-12]]), scale=0.001132070855057804, shift=array([ 9.20580884, 45.59527628, 22.95075811])), vector_model=VectorModel(intercepts=array([ 0.04902536, 0.12501084, 0.1503711 , 0.19587102, 0.21991184, + 0.23522003, 0.23681939, 0.07111459, -0.07579182, -0.06299477, + -0.40502842, -0.41381428, -0.12605813, -0.09953675, -0.09019229, + -0.09362869, -0.09977548]), linear_terms=array([[0., 0., 0.], [0., 0., 0.], [0., 0., 0.], [0., 0., 0.], @@ -4843,12 +5800,12 @@ algorithm_output,"{'states': [State(trustregion=Region(center=array([ 8.7163601 [[0., 0., 0.], [0., 0., 0.], - [0., 0., 0.]]]), scale=4.363119683916148, shift=array([ 8.73056876, 26.22690146, 43.63119684])), candidate_index=92, candidate_x=array([ 8.72185813, 25.97847892, 43.14568494]), index=28, x=array([ 8.72185488, 25.97850255, 43.14570821]), fval=0.580990887775828, rho=-0.36129754705210065, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([28, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 90]), old_indices_discarded=array([78, 89, 91]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 8.72185488, 25.97850255, 43.14570821]), radius=1.6643980727829544e-05, bounds=Bounds(lower=array([2., 0., 0.]), upper=array([20., 70., 70.]))), model_indices=array([28, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 92]), model=ScalarModel(intercept=0.5809911428552326, linear_terms=array([-4.87047264e-09, 2.05018677e-08, 2.69544046e-08]), square_terms=array([[ 3.02758584e-11, -5.07302654e-14, -5.67306466e-14], - [-5.07302654e-14, 1.15995007e-15, 1.55126606e-15], - [-5.67306466e-14, 1.55126606e-15, 2.12965813e-15]]), scale=1.6643980727829544e-05, shift=array([ 8.72185488, 25.97850255, 43.14570821])), vector_model=VectorModel(intercepts=array([ 0.05736286, 0.13097505, 0.15289447, 0.19437164, 0.22039886, - 0.23631479, 0.23653827, 0.08827519, -0.0506954 , -0.04028249, - -0.38487098, -0.40453749, -0.07787386, -0.05280456, -0.04320692, - -0.04588722, -0.05004941]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.]]]), scale=4.6369622223167655, shift=array([ 9.27512208, 46.36962222, 22.93103984])), candidate_index=73, candidate_x=array([ 9.20681941, 45.59500922, 22.95032335]), index=73, x=array([ 9.20681941, 45.59500922, 22.95032335]), fval=0.6411986913191434, rho=2.082556410838997, accepted=True, new_indices=array([], dtype=int64), old_indices_used=array([52, 57, 58, 60, 62, 63, 64, 65, 66, 69, 70, 72]), old_indices_discarded=array([37, 56, 59, 61, 67, 68, 71]), step_length=0.0011320708550586268, relative_step_length=1.0000000000007268, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 9.20681941, 45.59500922, 22.95032335]), radius=0.002264141710115608, bounds=Bounds(lower=array([1.1, 0. , 0. ]), upper=array([ 20., 70., 100.]))), model_indices=array([52, 57, 60, 62, 63, 64, 65, 66, 68, 69, 70, 73]), model=ScalarModel(intercept=0.6412078927766048, linear_terms=array([1.22594415e-05, 1.61897835e-06, 1.54845803e-06]), square_terms=array([[4.62123158e-07, 3.86924729e-10, 1.77696551e-09], + [3.86924729e-10, 3.00481457e-11, 2.10497761e-11], + [1.77696551e-09, 2.10497761e-11, 3.85820221e-11]]), scale=0.002264141710115608, shift=array([ 9.20681941, 45.59500922, 22.95032335])), vector_model=VectorModel(intercepts=array([ 0.04902536, 0.12501084, 0.1503711 , 0.19587102, 0.21991184, + 0.23522003, 0.23681939, 0.07111459, -0.07579182, -0.06299477, + -0.40502842, -0.41381428, -0.12605813, -0.09953675, -0.09019229, + -0.09362869, -0.09977548]), linear_terms=array([[0., 0., 0.], [0., 0., 0.], [0., 0., 0.], [0., 0., 0.], @@ -4930,13 +5887,12 @@ algorithm_output,"{'states': [State(trustregion=Region(center=array([ 8.7163601 [[0., 0., 0.], [0., 0., 0.], - [0., 0., 0.]]]), scale=4.363119683916148, shift=array([ 8.73056876, 26.22690146, 43.63119684])), candidate_index=93, candidate_x=array([ 8.72185725, 25.97849257, 43.14569509]), index=28, x=array([ 8.72185488, 25.97850255, 43.14570821]), fval=0.580990887775828, rho=-0.4446936876589159, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([28, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 92]), old_indices_discarded=array([89, 90, 91]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 8.72185488, 25.97850255, 43.14570821]), radius=8.321990363914772e-06, bounds=Bounds(lower=array([2., 0., 0.]), upper=array([20., 70., 70.]))), model_indices=array([ 28, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 102, 103, - 104, 105]), model=ScalarModel(intercept=0.580990888501083, linear_terms=array([ 5.13740068e-08, -2.20416267e-10, 1.53921334e-10]), square_terms=array([[ 7.45463956e-12, -3.79678926e-16, 2.65124389e-16], - [-3.79678926e-16, 1.42002227e-18, -9.91713495e-19], - [ 2.65124389e-16, -9.91713495e-19, 6.92591726e-19]]), scale=8.321990363914772e-06, shift=array([ 8.72185488, 25.97850255, 43.14570821])), vector_model=VectorModel(intercepts=array([ 0.05736286, 0.13097505, 0.15289447, 0.19437164, 0.22039886, - 0.23631479, 0.23653827, 0.08827519, -0.0506954 , -0.04028249, - -0.38487098, -0.40453749, -0.07787386, -0.05280456, -0.04320692, - -0.04588722, -0.05004941]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.]]]), scale=4.6369622223167655, shift=array([ 9.27512208, 46.36962222, 22.93103984])), candidate_index=74, candidate_x=array([ 9.20458071, 45.59476332, 22.95009077]), index=73, x=array([ 9.20681941, 45.59500922, 22.95032335]), fval=0.6411986913191434, rho=-3.1170682302761343, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([52, 57, 60, 62, 63, 64, 65, 66, 68, 69, 70, 73]), old_indices_discarded=array([37, 42, 50, 54, 55, 56, 58, 59, 61, 67, 71, 72]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 9.20681941, 45.59500922, 22.95032335]), radius=0.001132070855057804, bounds=Bounds(lower=array([1.1, 0. , 0. ]), upper=array([ 20., 70., 100.]))), model_indices=array([52, 60, 62, 63, 64, 65, 66, 68, 69, 70, 73, 74]), model=ScalarModel(intercept=0.6412191013317629, linear_terms=array([ 2.28385122e-07, -3.55775509e-06, -2.81988253e-06]), square_terms=array([[1.17199564e-07, 1.00094460e-09, 1.07118366e-09], + [1.00094460e-09, 7.51571130e-11, 4.49726145e-11], + [1.07118366e-09, 4.49726145e-11, 3.36729964e-11]]), scale=0.001132070855057804, shift=array([ 9.20681941, 45.59500922, 22.95032335])), vector_model=VectorModel(intercepts=array([ 0.04902536, 0.12501084, 0.1503711 , 0.19587102, 0.21991184, + 0.23522003, 0.23681939, 0.07111459, -0.07579182, -0.06299477, + -0.40502842, -0.41381428, -0.12605813, -0.09953675, -0.09019229, + -0.09362869, -0.09977548]), linear_terms=array([[0., 0., 0.], [0., 0., 0.], [0., 0., 0.], [0., 0., 0.], @@ -5018,12 +5974,99 @@ algorithm_output,"{'states': [State(trustregion=Region(center=array([ 8.7163601 [[0., 0., 0.], [0., 0., 0.], - [0., 0., 0.]]]), scale=4.363119683916148, shift=array([ 8.73056876, 26.22690146, 43.63119684])), candidate_index=106, candidate_x=array([ 8.72184655, 25.97850258, 43.14570818]), index=106, x=array([ 8.72184655, 25.97850258, 43.14570818]), fval=0.5809908420715011, rho=0.8896915045316948, accepted=True, new_indices=array([ 94, 95, 96, 97, 98, 99, 100, 101, 102, 103, 104, 105]), old_indices_used=array([28, 92, 93]), old_indices_discarded=array([], dtype=int64), step_length=8.321990363923781e-06, relative_step_length=1.0000000000010825, n_evals_per_point=1, n_evals_acceptance=1)], 'message': 'Absolute criterion change smaller than tolerance.', 'tranquilo_history': History for least_squares function with 107 entries., 'history': {'params': [{'CRRA': 8.730568763382836, 'BeqShift': 26.226901459993915, 'BeqFac': 43.631196839161476}, {'CRRA': 9.949291297736602, 'BeqShift': 28.414985343047878, 'BeqFac': 40.058548286455185}, {'CRRA': 5.926871501954608, 'BeqShift': 28.2685362070939, 'BeqFac': 40.98396760808412}, {'CRRA': 5.022637527401453, 'BeqShift': 28.131305514260603, 'BeqFac': 44.92011286571352}, {'CRRA': 8.313679349896171, 'BeqShift': 21.88382041542586, 'BeqFac': 43.605435755858345}, {'CRRA': 8.077665769669487, 'BeqShift': 24.601006831091386, 'BeqFac': 47.627069423802105}, {'CRRA': 4.889927899699559, 'BeqShift': 24.187630134871227, 'BeqFac': 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56.69282733900036, 56.958761409001454, 58.702945762001036, 60.25639303199932, 61.837962672001595, 63.729368251999404, 63.931022800999926, 64.14350845800072, 64.37552506700013, 64.5975766340016, 64.82816389800064, 65.07999363099952, 65.35795656399932, 65.64683953699932, 65.91545314099858, 66.18508422399827, 66.44458016499993, 68.24928989299951], 'batches': [0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 3, 4, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 6, 7, 8, 9, 10, 11, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 13, 14, 15, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 17, 18, 19, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 21, 22, 23, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 25, 26, 27, 28, 28, 28, 28, 28, 28, 28, 28, 28, 28, 28, 28, 29]}}, {'solution_x': array([ 8.71659533, 30.1919926 , 43.48487919]), 'solution_criterion': 0.5809857023401898, 'states': [State(trustregion=Region(center=array([ 8.61929941, 30.63288475, 44.78622815]), radius=4.478622814635116, bounds=Bounds(lower=array([2., 0., 0.]), upper=array([20., 70., 70.]))), model_indices=[0], model=ScalarModel(intercept=0.5817437469029839, linear_terms=array([0., 0., 0.]), square_terms=array([[0., 0., 0.], + [0., 0., 0.]]]), scale=4.6369622223167655, shift=array([ 9.27512208, 46.36962222, 22.93103984])), candidate_index=75, candidate_x=array([ 9.20676289, 45.59590683, 22.9510348 ]), index=75, x=array([ 9.20676289, 45.59590683, 22.9510348 ]), fval=0.6411981796789968, rho=0.11112145416657117, accepted=True, new_indices=array([], dtype=int64), old_indices_used=array([52, 60, 62, 63, 64, 65, 66, 68, 69, 70, 73, 74]), old_indices_discarded=array([37, 55, 56, 57, 58, 59, 61, 67, 71, 72]), step_length=0.001146756546700263, relative_step_length=1.0129724138527612, n_evals_per_point=1, n_evals_acceptance=1)], 'message': 'Absolute criterion change smaller than tolerance.', 'tranquilo_history': History for least_squares function with 76 entries., 'history': {'params': [{'CRRA': 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14.179368020995753, 15.653090578009142, 16.994580495986156, 18.357182284002192, 19.705602222995367, 21.04331421799725, 22.417964649997884, 23.896489750011824, 25.255145269999048, 26.928867835988058, 27.130844291998073, 27.332218597002793, 27.547404995013494, 27.755795565986773, 27.95879005698953, 28.1782835139893, 28.405464440002106, 28.623744148004334, 28.849743405997287, 29.07042433001334, 29.29202069499297, 30.858199643989792, 32.29883034800878, 33.61103138100589, 34.95829149801284, 36.28989908398944, 37.61273319501197, 38.92644273501355, 40.405719091999345, 42.020477666985244, 42.23188165400643, 42.419221985997865, 42.61211350100348, 42.82002458401257, 43.071859533985844, 43.302178378013195, 43.526629612984834, 43.74864653201075, 44.01000660698628, 44.239456754003186, 44.456551846000366, 45.957625095994445, 47.28305418801028, 48.59726462900289, 50.04799928399734, 51.38564965699334, 52.75495930900797, 54.07810187200084], 'batches': [0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 3, 4, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 25, 26, 27, 28, 29, 30, 31]}}, {'solution_x': array([ 9.20677822, 50.64405072, 26.13687265]), 'solution_criterion': 0.6411981580830574, 'states': [State(trustregion=Region(center=array([ 9.12810637, 48.86990017, 23.90047511]), radius=4.886990017445058, bounds=Bounds(lower=array([1.1, 0. , 0. ]), upper=array([ 20., 70., 100.]))), model_indices=[0], model=ScalarModel(intercept=0.6419131545898231, linear_terms=array([0., 0., 0.]), square_terms=array([[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]]), scale=4.886990017445058, shift=array([ 9.12810637, 48.86990017, 23.90047511])), vector_model=VectorModel(intercepts=array([ 0.0478985 , 0.12198145, 0.14591097, 0.19026117, 0.21318417, + 0.22770334, 0.22810381, 0.06014365, -0.08704274, -0.07443179, + -0.41631926, -0.42444642, -0.1208239 , -0.09458291, -0.08510185, + -0.08890017, -0.09498552]), linear_terms=array([[0., 0., 0.], [0., 0., 0.], - [0., 0., 0.]]), scale=4.478622814635116, shift=array([ 8.61929941, 30.63288475, 44.78622815])), vector_model=VectorModel(intercepts=array([ 0.05636335, 0.12853108, 0.14924217, 0.18993758, 0.21521994, - 0.23001617, 0.22967204, 0.07916353, -0.05984866, -0.04940366, - -0.39450878, -0.41347779, -0.07279885, -0.04799423, -0.03835929, - -0.04123765, -0.04533498]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]]), square_terms=array([[[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]], + + [[0., 0., 0.], + [0., 0., 0.], + [0., 0., 0.]]]), scale=4.886990017445058, shift=array([ 9.12810637, 48.86990017, 23.90047511])), candidate_index=0, candidate_x=array([ 9.12810637, 48.86990017, 23.90047511]), index=0, x=array([ 9.12810637, 48.86990017, 23.90047511]), fval=0.6419131545898232, rho=nan, accepted=True, new_indices=[0], old_indices_used=[], old_indices_discarded=[], step_length=None, relative_step_length=None, n_evals_per_point=None, n_evals_acceptance=None), State(trustregion=Region(center=array([ 9.12810637, 48.86990017, 23.90047511]), radius=4.886990017445058, bounds=Bounds(lower=array([1.1, 0. , 0. ]), upper=array([ 20., 70., 100.]))), model_indices=array([ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12]), model=ScalarModel(intercept=0.5838053927491154, linear_terms=array([-0.0784591 , -0.00113294, -0.00430834]), square_terms=array([[ 2.37622930e+00, -9.44902309e-03, -6.59043823e-03], + [-9.44902309e-03, 5.65537660e-05, 7.53932158e-05], + [-6.59043823e-03, 7.53932158e-05, 2.21756861e-04]]), scale=4.886990017445058, shift=array([ 9.12810637, 48.86990017, 23.90047511])), vector_model=VectorModel(intercepts=array([ 0.0478985 , 0.12198145, 0.14591097, 0.19026117, 0.21318417, + 0.22770334, 0.22810381, 0.06014365, -0.08704274, -0.07443179, + -0.41631926, -0.42444642, -0.1208239 , -0.09458291, -0.08510185, + -0.08890017, -0.09498552]), linear_terms=array([[0., 0., 0.], [0., 0., 0.], [0., 0., 0.], [0., 0., 0.], @@ -5105,12 +6148,12 @@ algorithm_output,"{'states': [State(trustregion=Region(center=array([ 8.7163601 [[0., 0., 0.], [0., 0., 0.], - [0., 0., 0.]]]), scale=4.478622814635116, shift=array([ 8.61929941, 30.63288475, 44.78622815])), candidate_index=0, candidate_x=array([ 8.61929941, 30.63288475, 44.78622815]), index=0, x=array([ 8.61929941, 30.63288475, 44.78622815]), fval=0.5817437469029839, rho=nan, accepted=True, new_indices=[0], old_indices_used=[], old_indices_discarded=[], step_length=None, relative_step_length=None, n_evals_per_point=None, n_evals_acceptance=None), State(trustregion=Region(center=array([ 8.61929941, 30.63288475, 44.78622815]), radius=4.478622814635116, bounds=Bounds(lower=array([2., 0., 0.]), upper=array([20., 70., 70.]))), model_indices=array([ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12]), model=ScalarModel(intercept=0.551116613139294, linear_terms=array([-0.15950819, -0.00120337, -0.00108333]), square_terms=array([[ 2.38616430e+00, -4.10653794e-03, -1.09420531e-02], - [-4.10653794e-03, 7.15666826e-05, 1.17979027e-04], - [-1.09420531e-02, 1.17979027e-04, 2.13703709e-04]]), scale=4.478622814635116, shift=array([ 8.61929941, 30.63288475, 44.78622815])), vector_model=VectorModel(intercepts=array([ 0.05636335, 0.12853108, 0.14924217, 0.18993758, 0.21521994, - 0.23001617, 0.22967204, 0.07916353, -0.05984866, -0.04940366, - -0.39450878, -0.41347779, -0.07279885, -0.04799423, -0.03835929, - -0.04123765, -0.04533498]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.]]]), scale=4.886990017445058, shift=array([ 9.12810637, 48.86990017, 23.90047511])), candidate_index=13, candidate_x=array([ 9.30801516, 50.37166273, 28.55876295]), index=13, x=array([ 9.30801516, 50.37166273, 28.55876295]), fval=0.6417128790724664, rho=0.03368406179865712, accepted=True, new_indices=array([ 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12]), old_indices_used=array([0]), old_indices_discarded=array([], dtype=int64), step_length=4.897683486158282, relative_step_length=1.0021881503082781, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 9.30801516, 50.37166273, 28.55876295]), radius=2.443495008722529, bounds=Bounds(lower=array([1.1, 0. , 0. ]), upper=array([ 20., 70., 100.]))), model_indices=array([ 0, 2, 3, 4, 5, 6, 7, 8, 9, 11, 12, 13]), model=ScalarModel(intercept=0.6096236821586578, linear_terms=array([0.02840541, 0.00191562, 0.02107148]), square_terms=array([[5.95634493e-01, 4.34268068e-04, 1.74066775e-02], + [4.34268068e-04, 2.73557040e-05, 2.15252435e-04], + [1.74066775e-02, 2.15252435e-04, 2.09032328e-03]]), scale=2.443495008722529, shift=array([ 9.30801516, 50.37166273, 28.55876295])), vector_model=VectorModel(intercepts=array([ 0.0478985 , 0.12198145, 0.14591097, 0.19026117, 0.21318417, + 0.22770334, 0.22810381, 0.06014365, -0.08704274, -0.07443179, + -0.41631926, -0.42444642, -0.1208239 , -0.09458291, -0.08510185, + -0.08890017, -0.09498552]), linear_terms=array([[0., 0., 0.], [0., 0., 0.], [0., 0., 0.], [0., 0., 0.], @@ -5192,12 +6235,12 @@ algorithm_output,"{'states': [State(trustregion=Region(center=array([ 8.7163601 [[0., 0., 0.], [0., 0., 0.], - [0., 0., 0.]]]), scale=4.478622814635116, shift=array([ 8.61929941, 30.63288475, 44.78622815])), candidate_index=13, candidate_x=array([ 8.93933358, 33.54102695, 48.25947215]), index=0, x=array([ 8.61929941, 30.63288475, 44.78622815]), fval=0.5817437469029839, rho=-0.24596923075387786, accepted=False, new_indices=array([ 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12]), old_indices_used=array([0]), old_indices_discarded=array([], dtype=int64), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 8.61929941, 30.63288475, 44.78622815]), radius=2.239311407317558, bounds=Bounds(lower=array([2., 0., 0.]), upper=array([20., 70., 70.]))), model_indices=array([ 0, 1, 2, 3, 4, 6, 7, 8, 9, 10, 11, 12]), model=ScalarModel(intercept=0.5489260020611669, linear_terms=array([-0.08858917, 0.00066969, -0.00339882]), square_terms=array([[ 6.01147999e-01, 4.59265044e-03, -1.69524922e-02], - [ 4.59265044e-03, 6.52907673e-05, -2.93517677e-04], - [-1.69524922e-02, -2.93517677e-04, 1.37842595e-03]]), scale=2.239311407317558, shift=array([ 8.61929941, 30.63288475, 44.78622815])), vector_model=VectorModel(intercepts=array([ 0.05636335, 0.12853108, 0.14924217, 0.18993758, 0.21521994, - 0.23001617, 0.22967204, 0.07916353, -0.05984866, -0.04940366, - -0.39450878, -0.41347779, -0.07279885, -0.04799423, -0.03835929, - -0.04123765, -0.04533498]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.]]]), scale=4.886990017445058, shift=array([ 9.12810637, 48.86990017, 23.90047511])), candidate_index=14, candidate_x=array([ 9.2655641 , 50.14664588, 26.07420434]), index=14, x=array([ 9.2655641 , 50.14664588, 26.07420434]), fval=0.6415610317693744, rho=0.00737246118082768, accepted=True, new_indices=array([], dtype=int64), old_indices_used=array([ 0, 2, 3, 4, 5, 6, 7, 8, 9, 11, 12, 13]), old_indices_discarded=array([ 1, 10]), step_length=2.4950884015831862, relative_step_length=1.0211145890114302, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 9.2655641 , 50.14664588, 26.07420434]), radius=1.2217475043612644, bounds=Bounds(lower=array([1.1, 0. , 0. ]), upper=array([ 20., 70., 100.]))), model_indices=array([ 0, 3, 5, 6, 7, 9, 11, 12, 13, 14]), model=ScalarModel(intercept=0.5911089857829682, linear_terms=array([0.00422151, 0.00795934, 0.0161826 ]), square_terms=array([[0.15195804, 0.00362337, 0.00870881], + [0.00362337, 0.00041071, 0.00091153], + [0.00870881, 0.00091153, 0.00203185]]), scale=1.2217475043612644, shift=array([ 9.2655641 , 50.14664588, 26.07420434])), vector_model=VectorModel(intercepts=array([ 0.0478985 , 0.12198145, 0.14591097, 0.19026117, 0.21318417, + 0.22770334, 0.22810381, 0.06014365, -0.08704274, -0.07443179, + -0.41631926, -0.42444642, -0.1208239 , -0.09458291, -0.08510185, + -0.08890017, -0.09498552]), linear_terms=array([[0., 0., 0.], [0., 0., 0.], [0., 0., 0.], [0., 0., 0.], @@ -5279,12 +6322,12 @@ algorithm_output,"{'states': [State(trustregion=Region(center=array([ 8.7163601 [[0., 0., 0.], [0., 0., 0.], - [0., 0., 0.]]]), scale=4.478622814635116, shift=array([ 8.61929941, 30.63288475, 44.78622815])), candidate_index=14, candidate_x=array([ 9.01668349, 30.07548008, 47.13402121]), index=0, x=array([ 8.61929941, 30.63288475, 44.78622815]), fval=0.5817437469029839, rho=-0.32279631611652204, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([ 0, 1, 2, 3, 4, 6, 7, 8, 9, 10, 11, 12]), old_indices_discarded=array([ 5, 13]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 8.61929941, 30.63288475, 44.78622815]), radius=1.119655703658779, bounds=Bounds(lower=array([2., 0., 0.]), upper=array([20., 70., 70.]))), model_indices=array([ 0, 1, 2, 3, 4, 6, 7, 8, 9, 10, 12, 14]), model=ScalarModel(intercept=0.5525998822096978, linear_terms=array([-0.03600176, -0.00085714, -0.00048257]), square_terms=array([[ 1.53786091e-01, -1.17996659e-03, -1.14527434e-03], - [-1.17996659e-03, 2.49710554e-05, 3.19147624e-05], - [-1.14527434e-03, 3.19147624e-05, 4.39648355e-05]]), scale=1.119655703658779, shift=array([ 8.61929941, 30.63288475, 44.78622815])), vector_model=VectorModel(intercepts=array([ 0.05636335, 0.12853108, 0.14924217, 0.18993758, 0.21521994, - 0.23001617, 0.22967204, 0.07916353, -0.05984866, -0.04940366, - -0.39450878, -0.41347779, -0.07279885, -0.04799423, -0.03835929, - -0.04123765, -0.04533498]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.]]]), scale=4.886990017445058, shift=array([ 9.12810637, 48.86990017, 23.90047511])), candidate_index=15, candidate_x=array([ 9.30677188, 49.57690312, 24.92860973]), index=14, x=array([ 9.2655641 , 50.14664588, 26.07420434]), fval=0.6415610317693744, rho=-0.007719959864419043, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([ 0, 3, 5, 6, 7, 9, 11, 12, 13, 14]), old_indices_discarded=array([], dtype=int64), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 9.2655641 , 50.14664588, 26.07420434]), radius=0.6108737521806322, bounds=Bounds(lower=array([1.1, 0. , 0. ]), upper=array([ 20., 70., 100.]))), model_indices=array([ 0, 9, 13, 14, 15]), model=ScalarModel(intercept=0.6412075612871301, linear_terms=array([ 5.18605429e-03, -5.96658930e-04, 8.53007592e-05]), square_terms=array([[ 3.43820818e-02, -5.19387823e-05, 5.05459631e-06], + [-5.19387823e-05, 6.87957385e-07, -9.67077712e-08], + [ 5.05459631e-06, -9.67077712e-08, 1.41737452e-08]]), scale=0.6108737521806322, shift=array([ 9.2655641 , 50.14664588, 26.07420434])), vector_model=VectorModel(intercepts=array([ 0.0478985 , 0.12198145, 0.14591097, 0.19026117, 0.21318417, + 0.22770334, 0.22810381, 0.06014365, -0.08704274, -0.07443179, + -0.41631926, -0.42444642, -0.1208239 , -0.09458291, -0.08510185, + -0.08890017, -0.09498552]), linear_terms=array([[0., 0., 0.], [0., 0., 0.], [0., 0., 0.], [0., 0., 0.], @@ -5366,12 +6409,12 @@ algorithm_output,"{'states': [State(trustregion=Region(center=array([ 8.7163601 [[0., 0., 0.], [0., 0., 0.], - [0., 0., 0.]]]), scale=4.478622814635116, shift=array([ 8.61929941, 30.63288475, 44.78622815])), candidate_index=15, candidate_x=array([ 8.89065926, 31.56342106, 45.38407316]), index=0, x=array([ 8.61929941, 30.63288475, 44.78622815]), fval=0.5817437469029839, rho=-0.1492175053283073, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([ 0, 1, 2, 3, 4, 6, 7, 8, 9, 10, 12, 14]), old_indices_discarded=array([ 5, 11, 13]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 8.61929941, 30.63288475, 44.78622815]), radius=0.5598278518293895, bounds=Bounds(lower=array([2., 0., 0.]), upper=array([20., 70., 70.]))), model_indices=array([ 0, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27]), model=ScalarModel(intercept=0.5810543453707367, linear_terms=array([-5.81789488e-03, 1.01002249e-04, 4.01683878e-05]), square_terms=array([[ 3.52415079e-02, 5.39565577e-05, -9.29511518e-06], - [ 5.39565577e-05, 1.70456927e-07, -1.28008791e-08], - [-9.29511518e-06, -1.28008791e-08, 8.47286341e-09]]), scale=0.5598278518293895, shift=array([ 8.61929941, 30.63288475, 44.78622815])), vector_model=VectorModel(intercepts=array([ 0.05636335, 0.12853108, 0.14924217, 0.18993758, 0.21521994, - 0.23001617, 0.22967204, 0.07916353, -0.05984866, -0.04940366, - -0.39450878, -0.41347779, -0.07279885, -0.04799423, -0.03835929, - -0.04123765, -0.04533498]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.]]]), scale=4.886990017445058, shift=array([ 9.12810637, 48.86990017, 23.90047511])), candidate_index=16, candidate_x=array([ 9.17589851, 50.75145653, 25.98737882]), index=16, x=array([ 9.17589851, 50.75145653, 25.98737882]), fval=0.6414178321884101, rho=0.14527765423064729, accepted=True, new_indices=array([], dtype=int64), old_indices_used=array([ 0, 9, 13, 14, 15]), old_indices_discarded=array([], dtype=int64), step_length=0.6175552708890588, relative_step_length=1.0109376424909002, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 9.17589851, 50.75145653, 25.98737882]), radius=1.2217475043612644, bounds=Bounds(lower=array([1.1, 0. , 0. ]), upper=array([ 20., 70., 100.]))), model_indices=array([ 0, 2, 3, 5, 7, 9, 11, 12, 13, 14, 15, 16]), model=ScalarModel(intercept=0.6052901828442077, linear_terms=array([-0.00707459, 0.00285906, 0.00874449]), square_terms=array([[1.45487940e-01, 8.88677433e-04, 3.95549893e-03], + [8.88677433e-04, 3.27781430e-05, 1.13238367e-04], + [3.95549893e-03, 1.13238367e-04, 4.03782515e-04]]), scale=1.2217475043612644, shift=array([ 9.17589851, 50.75145653, 25.98737882])), vector_model=VectorModel(intercepts=array([ 0.0478985 , 0.12198145, 0.14591097, 0.19026117, 0.21318417, + 0.22770334, 0.22810381, 0.06014365, -0.08704274, -0.07443179, + -0.41631926, -0.42444642, -0.1208239 , -0.09458291, -0.08510185, + -0.08890017, -0.09498552]), linear_terms=array([[0., 0., 0.], [0., 0., 0.], [0., 0., 0.], [0., 0., 0.], @@ -5453,12 +6496,12 @@ algorithm_output,"{'states': [State(trustregion=Region(center=array([ 8.7163601 [[0., 0., 0.], [0., 0., 0.], - [0., 0., 0.]]]), scale=4.478622814635116, shift=array([ 8.61929941, 30.63288475, 44.78622815])), candidate_index=28, candidate_x=array([ 8.71216816, 30.10678621, 44.60110323]), index=28, x=array([ 8.71216816, 30.10678621, 44.60110323]), fval=0.5810307193110972, rho=1.1958611481420225, accepted=True, new_indices=array([16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27]), old_indices_used=array([ 0, 14, 15]), old_indices_discarded=array([], dtype=int64), step_length=0.5653985486228839, relative_step_length=1.0099507317745813, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 8.71216816, 30.10678621, 44.60110323]), radius=1.119655703658779, bounds=Bounds(lower=array([2., 0., 0.]), upper=array([20., 70., 70.]))), model_indices=array([ 0, 16, 17, 18, 19, 20, 21, 22, 23, 25, 27, 28]), model=ScalarModel(intercept=0.5805805589900205, linear_terms=array([-4.09170264e-05, -4.08926017e-05, 4.97264385e-04]), square_terms=array([[ 1.40472646e-01, -2.01083077e-04, 3.24535811e-04], - [-2.01083077e-04, 6.63267818e-07, -9.81557130e-07], - [ 3.24535811e-04, -9.81557130e-07, 2.55004665e-06]]), scale=1.119655703658779, shift=array([ 8.71216816, 30.10678621, 44.60110323])), vector_model=VectorModel(intercepts=array([ 0.05636335, 0.12853108, 0.14924217, 0.18993758, 0.21521994, - 0.23001617, 0.22967204, 0.07916353, -0.05984866, -0.04940366, - -0.39450878, -0.41347779, -0.07279885, -0.04799423, -0.03835929, - -0.04123765, -0.04533498]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.]]]), scale=4.886990017445058, shift=array([ 9.12810637, 48.86990017, 23.90047511])), candidate_index=17, candidate_x=array([ 9.2637979 , 50.37235045, 24.82377989]), index=16, x=array([ 9.17589851, 50.75145653, 25.98737882]), fval=0.6414178321884101, rho=-0.016345474533435187, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([ 0, 2, 3, 5, 7, 9, 11, 12, 13, 14, 15, 16]), old_indices_discarded=array([], dtype=int64), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 9.17589851, 50.75145653, 25.98737882]), radius=0.6108737521806322, bounds=Bounds(lower=array([1.1, 0. , 0. ]), upper=array([ 20., 70., 100.]))), model_indices=array([ 0, 9, 13, 14, 15, 16, 17]), model=ScalarModel(intercept=0.6408680252047284, linear_terms=array([ 1.22608587e-03, -1.52831904e-04, -7.93126783e-05]), square_terms=array([[ 3.46548267e-02, 3.74686901e-06, -1.56196185e-05], + [ 3.74686901e-06, 4.51202398e-08, 1.43733385e-08], + [-1.56196185e-05, 1.43733385e-08, 1.99575801e-08]]), scale=0.6108737521806322, shift=array([ 9.17589851, 50.75145653, 25.98737882])), vector_model=VectorModel(intercepts=array([ 0.0478985 , 0.12198145, 0.14591097, 0.19026117, 0.21318417, + 0.22770334, 0.22810381, 0.06014365, -0.08704274, -0.07443179, + -0.41631926, -0.42444642, -0.1208239 , -0.09458291, -0.08510185, + -0.08890017, -0.09498552]), linear_terms=array([[0., 0., 0.], [0., 0., 0.], [0., 0., 0.], [0., 0., 0.], @@ -5540,12 +6583,12 @@ algorithm_output,"{'states': [State(trustregion=Region(center=array([ 8.7163601 [[0., 0., 0.], [0., 0., 0.], - [0., 0., 0.]]]), scale=4.478622814635116, shift=array([ 8.61929941, 30.63288475, 44.78622815])), candidate_index=29, candidate_x=array([ 8.71519205, 30.1977784 , 43.48514914]), index=29, x=array([ 8.71519205, 30.1977784 , 43.48514914]), fval=0.5810044729696282, rho=0.05269172043885907, accepted=True, new_indices=array([], dtype=int64), old_indices_used=array([ 0, 16, 17, 18, 19, 20, 21, 22, 23, 25, 27, 28]), old_indices_discarded=array([ 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 24, 26]), step_length=1.1196616751197728, relative_step_length=1.000005333301098, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 8.71519205, 30.1977784 , 43.48514914]), radius=0.5598278518293895, bounds=Bounds(lower=array([2., 0., 0.]), upper=array([20., 70., 70.]))), model_indices=array([ 0, 16, 17, 18, 20, 22, 23, 25, 26, 27, 28, 29]), model=ScalarModel(intercept=0.5809232754244636, linear_terms=array([ 0.00051302, -0.00014673, -0.00013056]), square_terms=array([[ 3.52219126e-02, -1.24541614e-04, -9.94564748e-05], - [-1.24541614e-04, 8.93054779e-07, 6.68754521e-07], - [-9.94564748e-05, 6.68754521e-07, 5.52689254e-07]]), scale=0.5598278518293895, shift=array([ 8.71519205, 30.1977784 , 43.48514914])), vector_model=VectorModel(intercepts=array([ 0.05636335, 0.12853108, 0.14924217, 0.18993758, 0.21521994, - 0.23001617, 0.22967204, 0.07916353, -0.05984866, -0.04940366, - -0.39450878, -0.41347779, -0.07279885, -0.04799423, -0.03835929, - -0.04123765, -0.04533498]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.]]]), scale=4.886990017445058, shift=array([ 9.12810637, 48.86990017, 23.90047511])), candidate_index=18, candidate_x=array([ 9.15445957, 51.29445206, 26.26698772]), index=16, x=array([ 9.17589851, 50.75145653, 25.98737882]), fval=0.6414178321884101, rho=-0.3807981173026105, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([ 0, 9, 13, 14, 15, 16, 17]), old_indices_discarded=array([], dtype=int64), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 9.17589851, 50.75145653, 25.98737882]), radius=0.3054368760903161, bounds=Bounds(lower=array([1.1, 0. , 0. ]), upper=array([ 20., 70., 100.]))), model_indices=array([14, 16, 17, 18]), model=ScalarModel(intercept=0.6414178321884101, linear_terms=array([-7.14351462e-04, 3.57051786e-06, -4.34650781e-06]), square_terms=array([[ 8.31583940e-03, -5.01950042e-06, -1.11678712e-06], + [-5.01950042e-06, 3.13345575e-08, 6.31491818e-09], + [-1.11678712e-06, 6.31491818e-09, 1.42073640e-09]]), scale=0.3054368760903161, shift=array([ 9.17589851, 50.75145653, 25.98737882])), vector_model=VectorModel(intercepts=array([ 0.0478985 , 0.12198145, 0.14591097, 0.19026117, 0.21318417, + 0.22770334, 0.22810381, 0.06014365, -0.08704274, -0.07443179, + -0.41631926, -0.42444642, -0.1208239 , -0.09458291, -0.08510185, + -0.08890017, -0.09498552]), linear_terms=array([[0., 0., 0.], [0., 0., 0.], [0., 0., 0.], [0., 0., 0.], @@ -5627,12 +6670,12 @@ algorithm_output,"{'states': [State(trustregion=Region(center=array([ 8.7163601 [[0., 0., 0.], [0., 0., 0.], - [0., 0., 0.]]]), scale=4.478622814635116, shift=array([ 8.61929941, 30.63288475, 44.78622815])), candidate_index=30, candidate_x=array([ 8.70959841, 30.61569435, 43.85769299]), index=29, x=array([ 8.71519205, 30.1977784 , 43.48514914]), fval=0.5810044729696282, rho=-0.07035616608114603, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([ 0, 16, 17, 18, 20, 22, 23, 25, 26, 27, 28, 29]), old_indices_discarded=array([15, 19, 21, 24]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 8.71519205, 30.1977784 , 43.48514914]), radius=0.2799139259146948, bounds=Bounds(lower=array([2., 0., 0.]), upper=array([20., 70., 70.]))), model_indices=array([ 0, 16, 17, 20, 23, 25, 27, 28, 29, 30]), model=ScalarModel(intercept=0.5809916683508421, linear_terms=array([ 4.69237284e-04, -1.74716418e-04, -2.37379179e-05]), square_terms=array([[ 8.88799300e-03, -6.11424506e-05, -1.86583110e-05], - [-6.11424506e-05, 8.65448353e-07, 2.34894202e-07], - [-1.86583110e-05, 2.34894202e-07, 7.49851957e-08]]), scale=0.2799139259146948, shift=array([ 8.71519205, 30.1977784 , 43.48514914])), vector_model=VectorModel(intercepts=array([ 0.05636335, 0.12853108, 0.14924217, 0.18993758, 0.21521994, - 0.23001617, 0.22967204, 0.07916353, -0.05984866, -0.04940366, - -0.39450878, -0.41347779, -0.07279885, -0.04799423, -0.03835929, - -0.04123765, -0.04533498]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.]]]), scale=4.886990017445058, shift=array([ 9.12810637, 48.86990017, 23.90047511])), candidate_index=19, candidate_x=array([ 9.2020414 , 50.55938439, 26.26040984]), index=19, x=array([ 9.2020414 , 50.55938439, 26.26040984]), fval=0.6412798714314748, rho=3.766886757176218, accepted=True, new_indices=array([], dtype=int64), old_indices_used=array([14, 16, 17, 18]), old_indices_discarded=array([], dtype=int64), step_length=0.3348448739735063, relative_step_length=1.0962817530732418, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 9.2020414 , 50.55938439, 26.26040984]), radius=0.6108737521806322, bounds=Bounds(lower=array([1.1, 0. , 0. ]), upper=array([ 20., 70., 100.]))), model_indices=array([ 0, 9, 13, 14, 15, 16, 17, 18, 19]), model=ScalarModel(intercept=0.6411413456382316, linear_terms=array([ 3.14313654e-03, 2.74625666e-05, -1.27910543e-04]), square_terms=array([[ 3.47663383e-02, 2.63538243e-05, -2.12337211e-05], + [ 2.63538243e-05, 5.29791904e-08, -3.77184755e-08], + [-2.12337211e-05, -3.77184755e-08, 4.60609078e-08]]), scale=0.6108737521806322, shift=array([ 9.2020414 , 50.55938439, 26.26040984])), vector_model=VectorModel(intercepts=array([ 0.0478985 , 0.12198145, 0.14591097, 0.19026117, 0.21318417, + 0.22770334, 0.22810381, 0.06014365, -0.08704274, -0.07443179, + -0.41631926, -0.42444642, -0.1208239 , -0.09458291, -0.08510185, + -0.08890017, -0.09498552]), linear_terms=array([[0., 0., 0.], [0., 0., 0.], [0., 0., 0.], [0., 0., 0.], @@ -5714,12 +6757,12 @@ algorithm_output,"{'states': [State(trustregion=Region(center=array([ 8.7163601 [[0., 0., 0.], [0., 0., 0.], - [0., 0., 0.]]]), scale=4.478622814635116, shift=array([ 8.61929941, 30.63288475, 44.78622815])), candidate_index=31, candidate_x=array([ 8.70264436, 30.47535209, 43.52191107]), index=29, x=array([ 8.71519205, 30.1977784 , 43.48514914]), fval=0.5810044729696282, rho=-0.40193712788777264, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([ 0, 16, 17, 20, 23, 25, 27, 28, 29, 30]), old_indices_discarded=array([], dtype=int64), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 8.71519205, 30.1977784 , 43.48514914]), radius=0.1399569629573474, bounds=Bounds(lower=array([2., 0., 0.]), upper=array([20., 70., 70.]))), model_indices=array([29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43]), model=ScalarModel(intercept=0.5811719685076451, linear_terms=array([ 5.82974790e-05, -4.84978777e-05, -1.04335763e-05]), square_terms=array([[2.16991967e-03, 2.11144242e-06, 7.84027301e-07], - [2.11144242e-06, 7.61438508e-09, 4.42927407e-09], - [7.84027301e-07, 4.42927407e-09, 5.20934120e-09]]), scale=0.1399569629573474, shift=array([ 8.71519205, 30.1977784 , 43.48514914])), vector_model=VectorModel(intercepts=array([ 0.05636335, 0.12853108, 0.14924217, 0.18993758, 0.21521994, - 0.23001617, 0.22967204, 0.07916353, -0.05984866, -0.04940366, - -0.39450878, -0.41347779, -0.07279885, -0.04799423, -0.03835929, - -0.04123765, -0.04533498]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.]]]), scale=4.886990017445058, shift=array([ 9.12810637, 48.86990017, 23.90047511])), candidate_index=20, candidate_x=array([ 9.14747104, 50.44050518, 26.85791599]), index=19, x=array([ 9.2020414 , 50.55938439, 26.26040984]), fval=0.6412798714314748, rho=-1.4403818757718805, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([ 0, 9, 13, 14, 15, 16, 17, 18, 19]), old_indices_discarded=array([], dtype=int64), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 9.2020414 , 50.55938439, 26.26040984]), radius=0.3054368760903161, bounds=Bounds(lower=array([1.1, 0. , 0. ]), upper=array([ 20., 70., 100.]))), model_indices=array([14, 16, 17, 18, 19, 20]), model=ScalarModel(intercept=0.6413874688839755, linear_terms=array([-6.33748043e-04, -5.73186109e-05, -1.79357454e-05]), square_terms=array([[8.46968425e-03, 2.56443878e-06, 1.01117391e-07], + [2.56443878e-06, 9.68297991e-09, 2.15723240e-09], + [1.01117391e-07, 2.15723240e-09, 1.06370393e-09]]), scale=0.3054368760903161, shift=array([ 9.2020414 , 50.55938439, 26.26040984])), vector_model=VectorModel(intercepts=array([ 0.0478985 , 0.12198145, 0.14591097, 0.19026117, 0.21318417, + 0.22770334, 0.22810381, 0.06014365, -0.08704274, -0.07443179, + -0.41631926, -0.42444642, -0.1208239 , -0.09458291, -0.08510185, + -0.08890017, -0.09498552]), linear_terms=array([[0., 0., 0.], [0., 0., 0.], [0., 0., 0.], [0., 0., 0.], @@ -5801,12 +6844,12 @@ algorithm_output,"{'states': [State(trustregion=Region(center=array([ 8.7163601 [[0., 0., 0.], [0., 0., 0.], - [0., 0., 0.]]]), scale=4.478622814635116, shift=array([ 8.61929941, 30.63288475, 44.78622815])), candidate_index=44, candidate_x=array([ 8.71137556, 30.33456935, 43.51459275]), index=29, x=array([ 8.71519205, 30.1977784 , 43.48514914]), fval=0.5810044729696282, rho=-0.4668748924555768, accepted=False, new_indices=array([32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43]), old_indices_used=array([29, 30, 31]), old_indices_discarded=array([], dtype=int64), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 8.71519205, 30.1977784 , 43.48514914]), radius=0.0699784814786737, bounds=Bounds(lower=array([2., 0., 0.]), upper=array([20., 70., 70.]))), model_indices=array([29, 32, 33, 34, 36, 37, 38, 39, 40, 41, 42, 43]), model=ScalarModel(intercept=0.5811755929112121, linear_terms=array([ 2.68260518e-05, -3.71723007e-05, -2.02323612e-05]), square_terms=array([[5.42914749e-04, 3.65677900e-07, 8.94947676e-07], - [3.65677900e-07, 1.91131055e-09, 2.40909704e-09], - [8.94947676e-07, 2.40909704e-09, 1.04598894e-08]]), scale=0.0699784814786737, shift=array([ 8.71519205, 30.1977784 , 43.48514914])), vector_model=VectorModel(intercepts=array([ 0.05636335, 0.12853108, 0.14924217, 0.18993758, 0.21521994, - 0.23001617, 0.22967204, 0.07916353, -0.05984866, -0.04940366, - -0.39450878, -0.41347779, -0.07279885, -0.04799423, -0.03835929, - -0.04123765, -0.04533498]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.]]]), scale=4.886990017445058, shift=array([ 9.12810637, 48.86990017, 23.90047511])), candidate_index=21, candidate_x=array([ 9.22464674, 50.85076503, 26.3518551 ]), index=19, x=array([ 9.2020414 , 50.55938439, 26.26040984]), fval=0.6412798714314748, rho=-1.2442024876135518, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([14, 16, 17, 18, 19, 20]), old_indices_discarded=array([], dtype=int64), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 9.2020414 , 50.55938439, 26.26040984]), radius=0.15271843804515806, bounds=Bounds(lower=array([1.1, 0. , 0. ]), upper=array([ 20., 70., 100.]))), model_indices=array([14, 16, 18, 19, 20, 21]), model=ScalarModel(intercept=0.6413861775924228, linear_terms=array([-1.34889295e-04, -1.17794331e-05, 1.72033189e-05]), square_terms=array([[ 2.12047970e-03, 7.30611322e-07, -4.58026451e-07], + [ 7.30611322e-07, 1.91216963e-09, 3.03077874e-10], + [-4.58026451e-07, 3.03077874e-10, 3.30402692e-09]]), scale=0.15271843804515806, shift=array([ 9.2020414 , 50.55938439, 26.26040984])), vector_model=VectorModel(intercepts=array([ 0.0478985 , 0.12198145, 0.14591097, 0.19026117, 0.21318417, + 0.22770334, 0.22810381, 0.06014365, -0.08704274, -0.07443179, + -0.41631926, -0.42444642, -0.1208239 , -0.09458291, -0.08510185, + -0.08890017, -0.09498552]), linear_terms=array([[0., 0., 0.], [0., 0., 0.], [0., 0., 0.], [0., 0., 0.], @@ -5888,12 +6931,12 @@ algorithm_output,"{'states': [State(trustregion=Region(center=array([ 8.7163601 [[0., 0., 0.], [0., 0., 0.], - [0., 0., 0.]]]), scale=4.478622814635116, shift=array([ 8.61929941, 30.63288475, 44.78622815])), candidate_index=45, candidate_x=array([ 8.71189526, 30.25916366, 43.51860519]), index=29, x=array([ 8.71519205, 30.1977784 , 43.48514914]), fval=0.5810044729696282, rho=-0.637216222558351, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([29, 32, 33, 34, 36, 37, 38, 39, 40, 41, 42, 43]), old_indices_discarded=array([31, 35, 44]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 8.71519205, 30.1977784 , 43.48514914]), radius=0.03498924073933685, bounds=Bounds(lower=array([2., 0., 0.]), upper=array([20., 70., 70.]))), model_indices=array([29, 33, 34, 36, 37, 38, 39, 40, 41, 42, 43, 45]), model=ScalarModel(intercept=0.5811682864926774, linear_terms=array([ 1.35896407e-05, -2.11634993e-05, -1.21073982e-05]), square_terms=array([[1.35795683e-04, 2.29337743e-07, 4.25726895e-08], - [2.29337743e-07, 1.21935342e-09, 9.13472367e-10], - [4.25726895e-08, 9.13472367e-10, 1.66636912e-09]]), scale=0.03498924073933685, shift=array([ 8.71519205, 30.1977784 , 43.48514914])), vector_model=VectorModel(intercepts=array([ 0.05636335, 0.12853108, 0.14924217, 0.18993758, 0.21521994, - 0.23001617, 0.22967204, 0.07916353, -0.05984866, -0.04940366, - -0.39450878, -0.41347779, -0.07279885, -0.04799423, -0.03835929, - -0.04123765, -0.04533498]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.]]]), scale=4.886990017445058, shift=array([ 9.12810637, 48.86990017, 23.90047511])), candidate_index=22, candidate_x=array([ 9.21160543, 50.6453772 , 26.13455164]), index=22, x=array([ 9.21160543, 50.6453772 , 26.13455164]), fval=0.6412533792921618, rho=1.0576140080519945, accepted=True, new_indices=array([], dtype=int64), old_indices_used=array([14, 16, 18, 19, 20, 21]), old_indices_discarded=array([], dtype=int64), step_length=0.15273021841934944, relative_step_length=1.0000771378645708, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 9.21160543, 50.6453772 , 26.13455164]), radius=0.3054368760903161, bounds=Bounds(lower=array([1.1, 0. , 0. ]), upper=array([ 20., 70., 100.]))), model_indices=array([14, 16, 17, 18, 19, 20, 21, 22]), model=ScalarModel(intercept=0.6413638550561954, linear_terms=array([-2.14082253e-04, -4.27982472e-05, -1.00993546e-05]), square_terms=array([[8.50926454e-03, 4.22952742e-06, 1.16007861e-06], + [4.22952742e-06, 1.36024420e-08, 5.92380689e-09], + [1.16007861e-06, 5.92380689e-09, 4.14150417e-09]]), scale=0.3054368760903161, shift=array([ 9.21160543, 50.6453772 , 26.13455164])), vector_model=VectorModel(intercepts=array([ 0.0478985 , 0.12198145, 0.14591097, 0.19026117, 0.21318417, + 0.22770334, 0.22810381, 0.06014365, -0.08704274, -0.07443179, + -0.41631926, -0.42444642, -0.1208239 , -0.09458291, -0.08510185, + -0.08890017, -0.09498552]), linear_terms=array([[0., 0., 0.], [0., 0., 0.], [0., 0., 0.], [0., 0., 0.], @@ -5975,12 +7018,12 @@ algorithm_output,"{'states': [State(trustregion=Region(center=array([ 8.7163601 [[0., 0., 0.], [0., 0., 0.], - [0., 0., 0.]]]), scale=4.478622814635116, shift=array([ 8.61929941, 30.63288475, 44.78622815])), candidate_index=46, candidate_x=array([ 8.71217687, 30.22808613, 43.50247584]), index=29, x=array([ 8.71519205, 30.1977784 , 43.48514914]), fval=0.5810044729696282, rho=-1.0479709055237976, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([29, 33, 34, 36, 37, 38, 39, 40, 41, 42, 43, 45]), old_indices_discarded=array([32, 35, 44]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 8.71519205, 30.1977784 , 43.48514914]), radius=0.017494620369668423, bounds=Bounds(lower=array([2., 0., 0.]), upper=array([20., 70., 70.]))), model_indices=array([29, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58]), model=ScalarModel(intercept=0.581030726939361, linear_terms=array([-4.08627009e-05, 3.13321130e-06, -6.66967828e-06]), square_terms=array([[ 3.32118482e-05, -2.83206163e-08, 6.94603370e-08], - [-2.83206163e-08, 3.50240341e-10, -3.44199142e-10], - [ 6.94603370e-08, -3.44199142e-10, 1.35231783e-09]]), scale=0.017494620369668423, shift=array([ 8.71519205, 30.1977784 , 43.48514914])), vector_model=VectorModel(intercepts=array([ 0.05636335, 0.12853108, 0.14924217, 0.18993758, 0.21521994, - 0.23001617, 0.22967204, 0.07916353, -0.05984866, -0.04940366, - -0.39450878, -0.41347779, -0.07279885, -0.04799423, -0.03835929, - -0.04123765, -0.04533498]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.]]]), scale=4.886990017445058, shift=array([ 9.12810637, 48.86990017, 23.90047511])), candidate_index=23, candidate_x=array([ 9.21909393, 50.94264606, 26.20464947]), index=22, x=array([ 9.21160543, 50.6453772 , 26.13455164]), fval=0.6412533792921618, rho=-1.4513449695755447, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([14, 16, 17, 18, 19, 20, 21, 22]), old_indices_discarded=array([], dtype=int64), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 9.21160543, 50.6453772 , 26.13455164]), radius=0.15271843804515806, bounds=Bounds(lower=array([1.1, 0. , 0. ]), upper=array([ 20., 70., 100.]))), model_indices=array([14, 16, 18, 19, 20, 21, 22, 23]), model=ScalarModel(intercept=0.6413399722336997, linear_terms=array([-1.41886991e-05, -1.22506996e-05, 2.10449721e-05]), square_terms=array([[ 2.12392194e-03, 8.98039493e-07, -4.74231704e-07], + [ 8.98039493e-07, 2.50309927e-09, 5.64263262e-12], + [-4.74231704e-07, 5.64263262e-12, 3.29687601e-09]]), scale=0.15271843804515806, shift=array([ 9.21160543, 50.6453772 , 26.13455164])), vector_model=VectorModel(intercepts=array([ 0.0478985 , 0.12198145, 0.14591097, 0.19026117, 0.21318417, + 0.22770334, 0.22810381, 0.06014365, -0.08704274, -0.07443179, + -0.41631926, -0.42444642, -0.1208239 , -0.09458291, -0.08510185, + -0.08890017, -0.09498552]), linear_terms=array([[0., 0., 0.], [0., 0., 0.], [0., 0., 0.], [0., 0., 0.], @@ -6062,12 +7105,12 @@ algorithm_output,"{'states': [State(trustregion=Region(center=array([ 8.7163601 [[0., 0., 0.], [0., 0., 0.], - [0., 0., 0.]]]), scale=4.478622814635116, shift=array([ 8.61929941, 30.63288475, 44.78622815])), candidate_index=59, candidate_x=array([ 8.72752569, 30.1908117 , 43.49541599]), index=29, x=array([ 8.71519205, 30.1977784 , 43.48514914]), fval=0.5810044729696282, rho=-1.249566223316225, accepted=False, new_indices=array([47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58]), old_indices_used=array([29, 45, 46]), old_indices_discarded=array([], dtype=int64), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 8.71519205, 30.1977784 , 43.48514914]), radius=0.008747310184834212, bounds=Bounds(lower=array([2., 0., 0.]), upper=array([20., 70., 70.]))), model_indices=array([29, 47, 49, 51, 52, 53, 54, 55, 56, 57, 58, 59]), model=ScalarModel(intercept=0.5810400285495558, linear_terms=array([-2.12991487e-05, 1.04096274e-05, 4.98665413e-06]), square_terms=array([[ 8.31610838e-06, -5.75066841e-08, -2.91342291e-08], - [-5.75066841e-08, 1.79808754e-09, 8.02895496e-10], - [-2.91342291e-08, 8.02895496e-10, 3.84032566e-10]]), scale=0.008747310184834212, shift=array([ 8.71519205, 30.1977784 , 43.48514914])), vector_model=VectorModel(intercepts=array([ 0.05636335, 0.12853108, 0.14924217, 0.18993758, 0.21521994, - 0.23001617, 0.22967204, 0.07916353, -0.05984866, -0.04940366, - -0.39450878, -0.41347779, -0.07279885, -0.04799423, -0.03835929, - -0.04123765, -0.04533498]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.]]]), scale=4.886990017445058, shift=array([ 9.12810637, 48.86990017, 23.90047511])), candidate_index=24, candidate_x=array([ 9.21254927, 50.72755054, 25.9933501 ]), index=22, x=array([ 9.21160543, 50.6453772 , 26.13455164]), fval=0.6412533792921618, rho=-0.6299099565848705, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([14, 16, 18, 19, 20, 21, 22, 23]), old_indices_discarded=array([], dtype=int64), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 9.21160543, 50.6453772 , 26.13455164]), radius=0.07635921902257903, bounds=Bounds(lower=array([1.1, 0. , 0. ]), upper=array([ 20., 70., 100.]))), model_indices=array([16, 19, 21, 22, 23, 24]), model=ScalarModel(intercept=0.6412636200468966, linear_terms=array([-1.85982564e-04, 2.34556335e-05, 1.68033597e-05]), square_terms=array([[ 5.32130898e-04, -3.65300183e-08, -4.57058856e-08], + [-3.65300183e-08, 2.84261585e-09, 1.19188371e-09], + [-4.57058856e-08, 1.19188371e-09, 8.22139690e-10]]), scale=0.07635921902257903, shift=array([ 9.21160543, 50.6453772 , 26.13455164])), vector_model=VectorModel(intercepts=array([ 0.0478985 , 0.12198145, 0.14591097, 0.19026117, 0.21318417, + 0.22770334, 0.22810381, 0.06014365, -0.08704274, -0.07443179, + -0.41631926, -0.42444642, -0.1208239 , -0.09458291, -0.08510185, + -0.08890017, -0.09498552]), linear_terms=array([[0., 0., 0.], [0., 0., 0.], [0., 0., 0.], [0., 0., 0.], @@ -6149,12 +7192,12 @@ algorithm_output,"{'states': [State(trustregion=Region(center=array([ 8.7163601 [[0., 0., 0.], [0., 0., 0.], - [0., 0., 0.]]]), scale=4.478622814635116, shift=array([ 8.61929941, 30.63288475, 44.78622815])), candidate_index=60, candidate_x=array([ 8.72118485, 30.19223386, 43.4820091 ]), index=60, x=array([ 8.72118485, 30.19223386, 43.4820091 ]), fval=0.5809970671183026, rho=0.35272641202738353, accepted=True, new_indices=array([], dtype=int64), old_indices_used=array([29, 47, 49, 51, 52, 53, 54, 55, 56, 57, 58, 59]), old_indices_discarded=array([46, 48, 50]), step_length=0.008747310184833827, relative_step_length=0.9999999999999559, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 8.72118485, 30.19223386, 43.4820091 ]), radius=0.017494620369668423, bounds=Bounds(lower=array([2., 0., 0.]), upper=array([20., 70., 70.]))), model_indices=array([29, 47, 48, 49, 50, 51, 52, 55, 57, 58, 59, 60]), model=ScalarModel(intercept=0.5810149765165715, linear_terms=array([-1.63731024e-05, 2.10954851e-05, 6.08819722e-06]), square_terms=array([[ 3.30165012e-05, -2.57755935e-07, -9.09898149e-08], - [-2.57755935e-07, 8.82049069e-09, 1.91154579e-09], - [-9.09898149e-08, 1.91154579e-09, 9.96672766e-10]]), scale=0.017494620369668423, shift=array([ 8.72118485, 30.19223386, 43.4820091 ])), vector_model=VectorModel(intercepts=array([ 0.05636335, 0.12853108, 0.14924217, 0.18993758, 0.21521994, - 0.23001617, 0.22967204, 0.07916353, -0.05984866, -0.04940366, - -0.39450878, -0.41347779, -0.07279885, -0.04799423, -0.03835929, - -0.04123765, -0.04533498]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.]]]), scale=4.886990017445058, shift=array([ 9.12810637, 48.86990017, 23.90047511])), candidate_index=25, candidate_x=array([ 9.23690342, 50.5838021 , 26.09045508]), index=22, x=array([ 9.21160543, 50.6453772 , 26.13455164]), fval=0.6412533792921618, rho=-3.865430938711674, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([16, 19, 21, 22, 23, 24]), old_indices_discarded=array([], dtype=int64), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 9.21160543, 50.6453772 , 26.13455164]), radius=0.038179609511289514, bounds=Bounds(lower=array([1.1, 0. , 0. ]), upper=array([ 20., 70., 100.]))), model_indices=array([16, 19, 22, 24, 25]), model=ScalarModel(intercept=0.6412400317662156, linear_terms=array([-1.51811080e-04, -1.33574181e-04, -8.96571588e-05]), square_terms=array([[1.33253248e-04, 3.18742679e-07, 2.22600759e-07], + [3.18742679e-07, 7.45315433e-08, 5.15360719e-08], + [2.22600759e-07, 5.15360719e-08, 3.57710222e-08]]), scale=0.038179609511289514, shift=array([ 9.21160543, 50.6453772 , 26.13455164])), vector_model=VectorModel(intercepts=array([ 0.0478985 , 0.12198145, 0.14591097, 0.19026117, 0.21318417, + 0.22770334, 0.22810381, 0.06014365, -0.08704274, -0.07443179, + -0.41631926, -0.42444642, -0.1208239 , -0.09458291, -0.08510185, + -0.08890017, -0.09498552]), linear_terms=array([[0., 0., 0.], [0., 0., 0.], [0., 0., 0.], [0., 0., 0.], @@ -6236,12 +7279,12 @@ algorithm_output,"{'states': [State(trustregion=Region(center=array([ 8.7163601 [[0., 0., 0.], [0., 0., 0.], - [0., 0., 0.]]]), scale=4.478622814635116, shift=array([ 8.61929941, 30.63288475, 44.78622815])), candidate_index=61, candidate_x=array([ 8.72630559, 30.17552115, 43.47718926]), index=60, x=array([ 8.72118485, 30.19223386, 43.4820091 ]), fval=0.5809970671183026, rho=-1.0659936229882716, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([29, 47, 48, 49, 50, 51, 52, 55, 57, 58, 59, 60]), old_indices_discarded=array([45, 46, 53, 54, 56]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 8.72118485, 30.19223386, 43.4820091 ]), radius=0.008747310184834212, bounds=Bounds(lower=array([2., 0., 0.]), upper=array([20., 70., 70.]))), model_indices=array([29, 47, 48, 49, 50, 51, 55, 57, 58, 59, 60, 61]), model=ScalarModel(intercept=0.581010765887341, linear_terms=array([1.97477188e-05, 1.24676548e-06, 3.11203543e-06]), square_terms=array([[ 7.97732833e-06, -7.67146898e-09, -1.46698243e-08], - [-7.67146898e-09, 6.35108040e-11, 5.37429008e-11], - [-1.46698243e-08, 5.37429008e-11, 8.92643356e-11]]), scale=0.008747310184834212, shift=array([ 8.72118485, 30.19223386, 43.4820091 ])), vector_model=VectorModel(intercepts=array([ 0.05636335, 0.12853108, 0.14924217, 0.18993758, 0.21521994, - 0.23001617, 0.22967204, 0.07916353, -0.05984866, -0.04940366, - -0.39450878, -0.41347779, -0.07279885, -0.04799423, -0.03835929, - -0.04123765, -0.04533498]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.]]]), scale=4.886990017445058, shift=array([ 9.12810637, 48.86990017, 23.90047511])), candidate_index=26, candidate_x=array([ 9.2299355 , 50.67331247, 26.15330102]), index=22, x=array([ 9.21160543, 50.6453772 , 26.13455164]), fval=0.6412533792921618, rho=-0.6957078218562044, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([16, 19, 22, 24, 25]), old_indices_discarded=array([], dtype=int64), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 9.21160543, 50.6453772 , 26.13455164]), radius=0.019089804755644757, bounds=Bounds(lower=array([1.1, 0. , 0. ]), upper=array([ 20., 70., 100.]))), model_indices=array([22, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38]), model=ScalarModel(intercept=0.6412949003105258, linear_terms=array([ 7.79166084e-05, -1.08575400e-05, -7.85152239e-06]), square_terms=array([[ 3.29424647e-05, 2.40761818e-08, -1.09908809e-08], + [ 2.40761818e-08, 3.71198501e-10, 2.17963621e-10], + [-1.09908809e-08, 2.17963621e-10, 2.48160791e-10]]), scale=0.019089804755644757, shift=array([ 9.21160543, 50.6453772 , 26.13455164])), vector_model=VectorModel(intercepts=array([ 0.0478985 , 0.12198145, 0.14591097, 0.19026117, 0.21318417, + 0.22770334, 0.22810381, 0.06014365, -0.08704274, -0.07443179, + -0.41631926, -0.42444642, -0.1208239 , -0.09458291, -0.08510185, + -0.08890017, -0.09498552]), linear_terms=array([[0., 0., 0.], [0., 0., 0.], [0., 0., 0.], [0., 0., 0.], @@ -6323,12 +7366,12 @@ algorithm_output,"{'states': [State(trustregion=Region(center=array([ 8.7163601 [[0., 0., 0.], [0., 0., 0.], - [0., 0., 0.]]]), scale=4.478622814635116, shift=array([ 8.61929941, 30.63288475, 44.78622815])), candidate_index=62, candidate_x=array([ 8.71311469, 30.19043317, 43.47915507]), index=60, x=array([ 8.72118485, 30.19223386, 43.4820091 ]), fval=0.5809970671183026, rho=-1.859495514054163, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([29, 47, 48, 49, 50, 51, 55, 57, 58, 59, 60, 61]), old_indices_discarded=array([46, 52, 53, 54, 56]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 8.72118485, 30.19223386, 43.4820091 ]), radius=0.004373655092417106, bounds=Bounds(lower=array([2., 0., 0.]), upper=array([20., 70., 70.]))), model_indices=array([29, 48, 49, 50, 51, 55, 57, 58, 59, 60, 61, 62]), model=ScalarModel(intercept=0.5810135859965463, linear_terms=array([ 5.44994786e-06, 2.54930007e-07, -3.13321491e-08]), square_terms=array([[ 2.01373535e-06, -1.45768458e-09, -4.68971992e-10], - [-1.45768458e-09, 1.90425949e-11, 6.19158838e-13], - [-4.68971992e-10, 6.19158838e-13, 1.04170875e-11]]), scale=0.004373655092417106, shift=array([ 8.72118485, 30.19223386, 43.4820091 ])), vector_model=VectorModel(intercepts=array([ 0.05636335, 0.12853108, 0.14924217, 0.18993758, 0.21521994, - 0.23001617, 0.22967204, 0.07916353, -0.05984866, -0.04940366, - -0.39450878, -0.41347779, -0.07279885, -0.04799423, -0.03835929, - -0.04123765, -0.04533498]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.]]]), scale=4.886990017445058, shift=array([ 9.12810637, 48.86990017, 23.90047511])), candidate_index=39, candidate_x=array([ 9.19367375, 50.65189736, 26.13394921]), index=22, x=array([ 9.21160543, 50.6453772 , 26.13455164]), fval=0.6412533792921618, rho=-0.7356352461674331, accepted=False, new_indices=array([27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38]), old_indices_used=array([22, 25, 26]), old_indices_discarded=array([], dtype=int64), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 9.21160543, 50.6453772 , 26.13455164]), radius=0.009544902377822378, bounds=Bounds(lower=array([1.1, 0. , 0. ]), upper=array([ 20., 70., 100.]))), model_indices=array([22, 27, 28, 29, 30, 31, 33, 34, 35, 37, 38, 39]), model=ScalarModel(intercept=0.6413009360685263, linear_terms=array([ 2.98872405e-05, -9.59030521e-06, -4.27533832e-06]), square_terms=array([[8.22114603e-06, 2.13676999e-08, 1.22020370e-08], + [2.13676999e-08, 2.01378174e-10, 1.00233499e-10], + [1.22020370e-08, 1.00233499e-10, 1.15290113e-10]]), scale=0.009544902377822378, shift=array([ 9.21160543, 50.6453772 , 26.13455164])), vector_model=VectorModel(intercepts=array([ 0.0478985 , 0.12198145, 0.14591097, 0.19026117, 0.21318417, + 0.22770334, 0.22810381, 0.06014365, -0.08704274, -0.07443179, + -0.41631926, -0.42444642, -0.1208239 , -0.09458291, -0.08510185, + -0.08890017, -0.09498552]), linear_terms=array([[0., 0., 0.], [0., 0., 0.], [0., 0., 0.], [0., 0., 0.], @@ -6410,12 +7453,12 @@ algorithm_output,"{'states': [State(trustregion=Region(center=array([ 8.7163601 [[0., 0., 0.], [0., 0., 0.], - [0., 0., 0.]]]), scale=4.478622814635116, shift=array([ 8.61929941, 30.63288475, 44.78622815])), candidate_index=63, candidate_x=array([ 8.71696364, 30.19129264, 43.4813577 ]), index=63, x=array([ 8.71696364, 30.19129264, 43.4813577 ]), fval=0.5809940602322323, rho=0.6876571311811749, accepted=True, new_indices=array([], dtype=int64), old_indices_used=array([29, 48, 49, 50, 51, 55, 57, 58, 59, 60, 61, 62]), old_indices_discarded=array([47, 52, 54, 56]), step_length=0.004373655092417327, relative_step_length=1.0000000000000506, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 8.71696364, 30.19129264, 43.4813577 ]), radius=0.008747310184834212, bounds=Bounds(lower=array([2., 0., 0.]), upper=array([20., 70., 70.]))), model_indices=array([29, 49, 50, 52, 55, 56, 57, 58, 59, 60, 62, 63]), model=ScalarModel(intercept=0.5810162623490366, linear_terms=array([-2.18742055e-05, 2.95911716e-06, 3.64060464e-06]), square_terms=array([[ 8.35787282e-06, -3.51486099e-08, -3.14316233e-08], - [-3.51486099e-08, 1.07538520e-09, 6.53390883e-10], - [-3.14316233e-08, 6.53390883e-10, 4.53012757e-10]]), scale=0.008747310184834212, shift=array([ 8.71696364, 30.19129264, 43.4813577 ])), vector_model=VectorModel(intercepts=array([ 0.05636335, 0.12853108, 0.14924217, 0.18993758, 0.21521994, - 0.23001617, 0.22967204, 0.07916353, -0.05984866, -0.04940366, - -0.39450878, -0.41347779, -0.07279885, -0.04799423, -0.03835929, - -0.04123765, -0.04533498]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.]]]), scale=4.886990017445058, shift=array([ 9.12810637, 48.86990017, 23.90047511])), candidate_index=40, candidate_x=array([ 9.20314317, 50.64928872, 26.1365999 ]), index=22, x=array([ 9.21160543, 50.6453772 , 26.13455164]), fval=0.6412533792921618, rho=-0.4286316408626921, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([22, 27, 28, 29, 30, 31, 33, 34, 35, 37, 38, 39]), old_indices_discarded=array([26, 32, 36]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 9.21160543, 50.6453772 , 26.13455164]), radius=0.004772451188911189, bounds=Bounds(lower=array([1.1, 0. , 0. ]), upper=array([ 20., 70., 100.]))), model_indices=array([22, 27, 28, 29, 30, 31, 33, 34, 35, 37, 38, 40]), model=ScalarModel(intercept=0.6412973906154201, linear_terms=array([ 1.75398422e-05, -5.99250886e-06, -2.51011929e-06]), square_terms=array([[2.05767865e-06, 4.69879566e-09, 2.64315982e-09], + [4.69879566e-09, 6.35990905e-11, 1.90355049e-11], + [2.64315982e-09, 1.90355049e-11, 1.83491578e-11]]), scale=0.004772451188911189, shift=array([ 9.21160543, 50.6453772 , 26.13455164])), vector_model=VectorModel(intercepts=array([ 0.0478985 , 0.12198145, 0.14591097, 0.19026117, 0.21318417, + 0.22770334, 0.22810381, 0.06014365, -0.08704274, -0.07443179, + -0.41631926, -0.42444642, -0.1208239 , -0.09458291, -0.08510185, + -0.08890017, -0.09498552]), linear_terms=array([[0., 0., 0.], [0., 0., 0.], [0., 0., 0.], [0., 0., 0.], @@ -6497,12 +7540,12 @@ algorithm_output,"{'states': [State(trustregion=Region(center=array([ 8.7163601 [[0., 0., 0.], [0., 0., 0.], - [0., 0., 0.]]]), scale=4.478622814635116, shift=array([ 8.61929941, 30.63288475, 44.78622815])), candidate_index=64, candidate_x=array([ 8.72568695, 30.19188723, 43.48161406]), index=63, x=array([ 8.71696364, 30.19129264, 43.4813577 ]), fval=0.5809940602322323, rho=-1.4879325275781943, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([29, 49, 50, 52, 55, 56, 57, 58, 59, 60, 62, 63]), old_indices_discarded=array([46, 47, 48, 51, 53, 54, 61]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 8.71696364, 30.19129264, 43.4813577 ]), radius=0.004373655092417106, bounds=Bounds(lower=array([2., 0., 0.]), upper=array([20., 70., 70.]))), model_indices=array([29, 49, 50, 52, 55, 56, 57, 58, 60, 62, 63, 64]), model=ScalarModel(intercept=0.5810158380560159, linear_terms=array([-1.14491258e-05, -1.79223413e-06, -1.60737967e-06]), square_terms=array([[ 2.08990992e-06, -1.33357108e-09, 7.11041707e-10], - [-1.33357108e-09, 1.61733420e-10, 6.27226354e-11], - [ 7.11041707e-10, 6.27226354e-11, 5.07354617e-11]]), scale=0.004373655092417106, shift=array([ 8.71696364, 30.19129264, 43.4813577 ])), vector_model=VectorModel(intercepts=array([ 0.05636335, 0.12853108, 0.14924217, 0.18993758, 0.21521994, - 0.23001617, 0.22967204, 0.07916353, -0.05984866, -0.04940366, - -0.39450878, -0.41347779, -0.07279885, -0.04799423, -0.03835929, - -0.04123765, -0.04533498]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.]]]), scale=4.886990017445058, shift=array([ 9.12810637, 48.86990017, 23.90047511])), candidate_index=41, candidate_x=array([ 9.20724051, 50.64712891, 26.13536112]), index=41, x=array([ 9.20724051, 50.64712891, 26.13536112]), fval=0.6412040518376516, rho=2.769849739315419, accepted=True, new_indices=array([], dtype=int64), old_indices_used=array([22, 27, 28, 29, 30, 31, 33, 34, 35, 37, 38, 40]), old_indices_discarded=array([32, 36, 39]), step_length=0.004772451188911595, relative_step_length=1.000000000000085, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 9.20724051, 50.64712891, 26.13536112]), radius=0.009544902377822378, bounds=Bounds(lower=array([1.1, 0. , 0. ]), upper=array([ 20., 70., 100.]))), model_indices=array([22, 27, 28, 30, 32, 34, 35, 37, 38, 39, 40, 41]), model=ScalarModel(intercept=0.6412558733517228, linear_terms=array([-1.69255546e-05, -4.39895767e-06, -2.08824813e-06]), square_terms=array([[8.21955555e-06, 2.05881180e-08, 6.90866621e-09], + [2.05881180e-08, 1.57618492e-10, 7.22730875e-11], + [6.90866621e-09, 7.22730875e-11, 5.92353119e-11]]), scale=0.009544902377822378, shift=array([ 9.20724051, 50.64712891, 26.13536112])), vector_model=VectorModel(intercepts=array([ 0.0478985 , 0.12198145, 0.14591097, 0.19026117, 0.21318417, + 0.22770334, 0.22810381, 0.06014365, -0.08704274, -0.07443179, + -0.41631926, -0.42444642, -0.1208239 , -0.09458291, -0.08510185, + -0.08890017, -0.09498552]), linear_terms=array([[0., 0., 0.], [0., 0., 0.], [0., 0., 0.], [0., 0., 0.], @@ -6584,12 +7627,12 @@ algorithm_output,"{'states': [State(trustregion=Region(center=array([ 8.7163601 [[0., 0., 0.], [0., 0., 0.], - [0., 0., 0.]]]), scale=4.478622814635116, shift=array([ 8.61929941, 30.63288475, 44.78622815])), candidate_index=65, candidate_x=array([ 8.72119014, 30.19236943, 43.48168334]), index=63, x=array([ 8.71696364, 30.19129264, 43.4813577 ]), fval=0.5809940602322323, rho=-0.27867246046764915, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([29, 49, 50, 52, 55, 56, 57, 58, 60, 62, 63, 64]), old_indices_discarded=array([47, 48, 51, 53, 54, 59, 61]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 8.71696364, 30.19129264, 43.4813577 ]), radius=0.002186827546208553, bounds=Bounds(lower=array([2., 0., 0.]), upper=array([20., 70., 70.]))), model_indices=array([29, 58, 60, 62, 63, 64, 65]), model=ScalarModel(intercept=0.5810025507032616, linear_terms=array([-4.32671366e-07, 5.73768870e-06, -6.99465711e-06]), square_terms=array([[ 5.11034683e-07, -4.85097692e-09, 4.33675326e-09], - [-4.85097692e-09, 3.49563434e-10, -2.59960532e-10], - [ 4.33675326e-09, -2.59960532e-10, 2.23711601e-10]]), scale=0.002186827546208553, shift=array([ 8.71696364, 30.19129264, 43.4813577 ])), vector_model=VectorModel(intercepts=array([ 0.05636335, 0.12853108, 0.14924217, 0.18993758, 0.21521994, - 0.23001617, 0.22967204, 0.07916353, -0.05984866, -0.04940366, - -0.39450878, -0.41347779, -0.07279885, -0.04799423, -0.03835929, - -0.04123765, -0.04533498]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.]]]), scale=4.886990017445058, shift=array([ 9.12810637, 48.86990017, 23.90047511])), candidate_index=42, candidate_x=array([ 9.21317423, 50.65319986, 26.13972458]), index=41, x=array([ 9.20724051, 50.64712891, 26.13536112]), fval=0.6412040518376516, rho=-5.9786318496293385, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([22, 27, 28, 30, 32, 34, 35, 37, 38, 39, 40, 41]), old_indices_discarded=array([26, 29, 31, 33, 36]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 9.20724051, 50.64712891, 26.13536112]), radius=0.004772451188911189, bounds=Bounds(lower=array([1.1, 0. , 0. ]), upper=array([ 20., 70., 100.]))), model_indices=array([22, 27, 30, 32, 34, 35, 37, 38, 39, 40, 41, 42]), model=ScalarModel(intercept=0.6412588576917913, linear_terms=array([-6.83670642e-06, -1.11357466e-06, -5.72399169e-07]), square_terms=array([[2.05052218e-06, 6.90899197e-09, 1.39972212e-09], + [6.90899197e-09, 9.18556326e-11, 2.86773343e-11], + [1.39972212e-09, 2.86773343e-11, 1.40014692e-11]]), scale=0.004772451188911189, shift=array([ 9.20724051, 50.64712891, 26.13536112])), vector_model=VectorModel(intercepts=array([ 0.0478985 , 0.12198145, 0.14591097, 0.19026117, 0.21318417, + 0.22770334, 0.22810381, 0.06014365, -0.08704274, -0.07443179, + -0.41631926, -0.42444642, -0.1208239 , -0.09458291, -0.08510185, + -0.08890017, -0.09498552]), linear_terms=array([[0., 0., 0.], [0., 0., 0.], [0., 0., 0.], [0., 0., 0.], @@ -6671,12 +7714,12 @@ algorithm_output,"{'states': [State(trustregion=Region(center=array([ 8.7163601 [[0., 0., 0.], [0., 0., 0.], - [0., 0., 0.]]]), scale=4.478622814635116, shift=array([ 8.61929941, 30.63288475, 44.78622815])), candidate_index=66, candidate_x=array([ 8.7170637 , 30.18986701, 43.4830957 ]), index=63, x=array([ 8.71696364, 30.19129264, 43.4813577 ]), fval=0.5809940602322323, rho=-0.2341225549581441, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([29, 58, 60, 62, 63, 64, 65]), old_indices_discarded=array([], dtype=int64), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 8.71696364, 30.19129264, 43.4813577 ]), radius=0.0010934137731042765, bounds=Bounds(lower=array([2., 0., 0.]), upper=array([20., 70., 70.]))), model_indices=array([60, 62, 63, 65, 66]), model=ScalarModel(intercept=0.5809942233388103, linear_terms=array([ 9.53806929e-06, -2.74709261e-05, -2.17251803e-05]), square_terms=array([[1.23378026e-07, 7.17532371e-09, 5.85035624e-09], - [7.17532371e-09, 6.84407244e-09, 5.79028654e-09], - [5.85035624e-09, 5.79028654e-09, 4.90303982e-09]]), scale=0.0010934137731042765, shift=array([ 8.71696364, 30.19129264, 43.4813577 ])), vector_model=VectorModel(intercepts=array([ 0.05636335, 0.12853108, 0.14924217, 0.18993758, 0.21521994, - 0.23001617, 0.22967204, 0.07916353, -0.05984866, -0.04940366, - -0.39450878, -0.41347779, -0.07279885, -0.04799423, -0.03835929, - -0.04123765, -0.04533498]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.]]]), scale=4.886990017445058, shift=array([ 9.12810637, 48.86990017, 23.90047511])), candidate_index=43, candidate_x=array([ 9.21199791, 50.6471936 , 26.13498794]), index=41, x=array([ 9.20724051, 50.64712891, 26.13536112]), fval=0.6412040518376516, rho=-9.46039138436527, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([22, 27, 30, 32, 34, 35, 37, 38, 39, 40, 41, 42]), old_indices_discarded=array([28, 29, 31, 33, 36]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 9.20724051, 50.64712891, 26.13536112]), radius=0.0023862255944555946, bounds=Bounds(lower=array([1.1, 0. , 0. ]), upper=array([ 20., 70., 100.]))), model_indices=array([22, 40, 41, 42, 43]), model=ScalarModel(intercept=0.6412405831157186, linear_terms=array([ 4.52303257e-06, 2.81196588e-05, -2.35968467e-05]), square_terms=array([[ 5.12190353e-07, -7.84167461e-09, 9.55156040e-09], + [-7.84167461e-09, 1.32218333e-09, -1.32903857e-09], + [ 9.55156040e-09, -1.32903857e-09, 1.49501369e-09]]), scale=0.0023862255944555946, shift=array([ 9.20724051, 50.64712891, 26.13536112])), vector_model=VectorModel(intercepts=array([ 0.0478985 , 0.12198145, 0.14591097, 0.19026117, 0.21318417, + 0.22770334, 0.22810381, 0.06014365, -0.08704274, -0.07443179, + -0.41631926, -0.42444642, -0.1208239 , -0.09458291, -0.08510185, + -0.08890017, -0.09498552]), linear_terms=array([[0., 0., 0.], [0., 0., 0.], [0., 0., 0.], [0., 0., 0.], @@ -6758,12 +7801,12 @@ algorithm_output,"{'states': [State(trustregion=Region(center=array([ 8.7163601 [[0., 0., 0.], [0., 0., 0.], - [0., 0., 0.]]]), scale=4.478622814635116, shift=array([ 8.61929941, 30.63288475, 44.78622815])), candidate_index=67, candidate_x=array([ 8.71667657, 30.19212127, 43.482013 ]), index=67, x=array([ 8.71667657, 30.19212127, 43.482013 ]), fval=0.5809875877418589, rho=0.17812964392865507, accepted=True, new_indices=array([], dtype=int64), old_indices_used=array([60, 62, 63, 65, 66]), old_indices_discarded=array([], dtype=int64), step_length=0.0010947490473563208, relative_step_length=1.0012211975785281, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 8.71667657, 30.19212127, 43.482013 ]), radius=0.002186827546208553, bounds=Bounds(lower=array([2., 0., 0.]), upper=array([20., 70., 70.]))), model_indices=array([29, 60, 62, 63, 64, 65, 66, 67]), model=ScalarModel(intercept=0.5810016958604285, linear_terms=array([-1.04911739e-07, 6.34428681e-06, -1.39161955e-05]), square_terms=array([[ 5.10504210e-07, -6.35963391e-09, 1.31298318e-08], - [-6.35963391e-09, 6.95093749e-10, -1.20574348e-09], - [ 1.31298318e-08, -1.20574348e-09, 2.28475330e-09]]), scale=0.002186827546208553, shift=array([ 8.71667657, 30.19212127, 43.482013 ])), vector_model=VectorModel(intercepts=array([ 0.05636335, 0.12853108, 0.14924217, 0.18993758, 0.21521994, - 0.23001617, 0.22967204, 0.07916353, -0.05984866, -0.04940366, - -0.39450878, -0.41347779, -0.07279885, -0.04799423, -0.03835929, - -0.04123765, -0.04533498]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.]]]), scale=4.886990017445058, shift=array([ 9.12810637, 48.86990017, 23.90047511])), candidate_index=44, candidate_x=array([ 9.20694996, 50.64530232, 26.13689391]), index=44, x=array([ 9.20694996, 50.64530232, 26.13689391]), fval=0.6412003819983737, rho=0.09857365047199054, accepted=True, new_indices=array([], dtype=int64), old_indices_used=array([22, 40, 41, 42, 43]), old_indices_discarded=array([], dtype=int64), step_length=0.002402151221322381, relative_step_length=1.0066739820844222, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 9.20694996, 50.64530232, 26.13689391]), radius=0.0011931127972277973, bounds=Bounds(lower=array([1.1, 0. , 0. ]), upper=array([ 20., 70., 100.]))), model_indices=array([22, 40, 41, 43, 44]), model=ScalarModel(intercept=0.641203279969248, linear_terms=array([7.68329827e-06, 2.09695197e-05, 2.72233817e-06]), square_terms=array([[ 1.26006786e-07, -3.28572663e-09, -8.55594767e-11], + [-3.28572663e-09, 5.92079298e-10, 1.02968247e-10], + [-8.55594767e-11, 1.02968247e-10, 6.19322113e-11]]), scale=0.0011931127972277973, shift=array([ 9.20694996, 50.64530232, 26.13689391])), vector_model=VectorModel(intercepts=array([ 0.0478985 , 0.12198145, 0.14591097, 0.19026117, 0.21318417, + 0.22770334, 0.22810381, 0.06014365, -0.08704274, -0.07443179, + -0.41631926, -0.42444642, -0.1208239 , -0.09458291, -0.08510185, + -0.08890017, -0.09498552]), linear_terms=array([[0., 0., 0.], [0., 0., 0.], [0., 0., 0.], [0., 0., 0.], @@ -6845,12 +7888,12 @@ algorithm_output,"{'states': [State(trustregion=Region(center=array([ 8.7163601 [[0., 0., 0.], [0., 0., 0.], - [0., 0., 0.]]]), scale=4.478622814635116, shift=array([ 8.61929941, 30.63288475, 44.78622815])), candidate_index=68, candidate_x=array([ 8.71668923, 30.19119919, 43.48403566]), index=67, x=array([ 8.71667657, 30.19212127, 43.482013 ]), fval=0.5809875877418589, rho=-0.01885681869454688, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([29, 60, 62, 63, 64, 65, 66, 67]), old_indices_discarded=array([], dtype=int64), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 8.71667657, 30.19212127, 43.482013 ]), radius=0.0010934137731042765, bounds=Bounds(lower=array([2., 0., 0.]), upper=array([20., 70., 70.]))), model_indices=array([60, 62, 63, 65, 66, 67, 68]), model=ScalarModel(intercept=0.5809913991373031, linear_terms=array([ 5.82146679e-07, -7.25837372e-06, -8.06838748e-06]), square_terms=array([[1.29709108e-07, 1.45470515e-09, 2.52818053e-09], - [1.45470515e-09, 8.84182254e-11, 1.39508621e-10], - [2.52818053e-09, 1.39508621e-10, 3.76198397e-10]]), scale=0.0010934137731042765, shift=array([ 8.71667657, 30.19212127, 43.482013 ])), vector_model=VectorModel(intercepts=array([ 0.05636335, 0.12853108, 0.14924217, 0.18993758, 0.21521994, - 0.23001617, 0.22967204, 0.07916353, -0.05984866, -0.04940366, - -0.39450878, -0.41347779, -0.07279885, -0.04799423, -0.03835929, - -0.04123765, -0.04533498]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.]]]), scale=4.886990017445058, shift=array([ 9.12810637, 48.86990017, 23.90047511])), candidate_index=45, candidate_x=array([ 9.20654349, 50.64418718, 26.13674915]), index=45, x=array([ 9.20654349, 50.64418718, 26.13674915]), fval=0.6411989063826031, rho=0.06546551794973687, accepted=True, new_indices=array([], dtype=int64), old_indices_used=array([22, 40, 41, 43, 44]), old_indices_discarded=array([], dtype=int64), step_length=0.001195701055462824, relative_step_length=1.0021693323892262, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 9.20654349, 50.64418718, 26.13674915]), radius=0.0005965563986138987, bounds=Bounds(lower=array([1.1, 0. , 0. ]), upper=array([ 20., 70., 100.]))), model_indices=array([44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57]), model=ScalarModel(intercept=0.6412016028005694, linear_terms=array([-2.55858927e-06, -7.29526994e-08, -7.87710385e-07]), square_terms=array([[3.41315492e-08, 1.04426797e-11, 7.35805731e-11], + [1.04426797e-11, 2.63347216e-13, 5.28969670e-13], + [7.35805731e-11, 5.28969670e-13, 2.04887560e-12]]), scale=0.0005965563986138987, shift=array([ 9.20654349, 50.64418718, 26.13674915])), vector_model=VectorModel(intercepts=array([ 0.0478985 , 0.12198145, 0.14591097, 0.19026117, 0.21318417, + 0.22770334, 0.22810381, 0.06014365, -0.08704274, -0.07443179, + -0.41631926, -0.42444642, -0.1208239 , -0.09458291, -0.08510185, + -0.08890017, -0.09498552]), linear_terms=array([[0., 0., 0.], [0., 0., 0.], [0., 0., 0.], [0., 0., 0.], @@ -6932,12 +7975,12 @@ algorithm_output,"{'states': [State(trustregion=Region(center=array([ 8.7163601 [[0., 0., 0.], [0., 0., 0.], - [0., 0., 0.]]]), scale=4.478622814635116, shift=array([ 8.61929941, 30.63288475, 44.78622815])), candidate_index=69, candidate_x=array([ 8.71661807, 30.19285581, 43.4828295 ]), index=69, x=array([ 8.71661807, 30.19285581, 43.4828295 ]), fval=0.5809862339899541, rho=0.12383361727103867, accepted=True, new_indices=array([], dtype=int64), old_indices_used=array([60, 62, 63, 65, 66, 67, 68]), old_indices_discarded=array([], dtype=int64), step_length=0.001099839116580275, relative_step_length=1.005876406200515, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 8.71661807, 30.19285581, 43.4828295 ]), radius=0.002186827546208553, bounds=Bounds(lower=array([2., 0., 0.]), upper=array([20., 70., 70.]))), model_indices=array([29, 60, 62, 63, 64, 65, 66, 67, 68, 69]), model=ScalarModel(intercept=0.5809972693618909, linear_terms=array([ 1.45918232e-07, 5.80236040e-06, -1.37772265e-05]), square_terms=array([[ 5.10620333e-07, -4.83250533e-09, 1.10023209e-08], - [-4.83250533e-09, 4.25564369e-10, -7.56168652e-10], - [ 1.10023209e-08, -7.56168652e-10, 1.54814055e-09]]), scale=0.002186827546208553, shift=array([ 8.71661807, 30.19285581, 43.4828295 ])), vector_model=VectorModel(intercepts=array([ 0.05636335, 0.12853108, 0.14924217, 0.18993758, 0.21521994, - 0.23001617, 0.22967204, 0.07916353, -0.05984866, -0.04940366, - -0.39450878, -0.41347779, -0.07279885, -0.04799423, -0.03835929, - -0.04123765, -0.04533498]), linear_terms=array([[0., 0., 0.], + [0., 0., 0.]]]), scale=4.886990017445058, shift=array([ 9.12810637, 48.86990017, 23.90047511])), candidate_index=58, candidate_x=array([ 9.20711472, 50.64419857, 26.13692076]), index=45, x=array([ 9.20654349, 50.64418718, 26.13674915]), fval=0.6411989063826031, rho=-1.3540135264197082, accepted=False, new_indices=array([46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57]), old_indices_used=array([44, 45]), old_indices_discarded=array([], dtype=int64), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([ 9.20654349, 50.64418718, 26.13674915]), radius=0.00029827819930694933, bounds=Bounds(lower=array([1.1, 0. , 0. ]), upper=array([ 20., 70., 100.]))), model_indices=array([45, 46, 48, 50, 51, 52, 53, 54, 55, 56, 57, 58]), model=ScalarModel(intercept=0.6412021137195624, linear_terms=array([-9.14153413e-07, 4.95084351e-07, -4.46123326e-07]), square_terms=array([[ 8.50301604e-09, -1.62114960e-11, 2.28942335e-11], + [-1.62114960e-11, 1.09677906e-12, 8.83835907e-14], + [ 2.28942335e-11, 8.83835907e-14, 1.02199200e-12]]), scale=0.00029827819930694933, shift=array([ 9.20654349, 50.64418718, 26.13674915])), vector_model=VectorModel(intercepts=array([ 0.0478985 , 0.12198145, 0.14591097, 0.19026117, 0.21318417, + 0.22770334, 0.22810381, 0.06014365, -0.08704274, -0.07443179, + -0.41631926, -0.42444642, -0.1208239 , -0.09458291, -0.08510185, + -0.08890017, -0.09498552]), linear_terms=array([[0., 0., 0.], [0., 0., 0.], [0., 0., 0.], [0., 0., 0.], @@ -7019,38 +8062,38 @@ algorithm_output,"{'states': [State(trustregion=Region(center=array([ 8.7163601 [[0., 0., 0.], [0., 0., 0.], - [0., 0., 0.]]]), scale=4.478622814635116, shift=array([ 8.61929941, 30.63288475, 44.78622815])), candidate_index=70, candidate_x=array([ 8.71659533, 30.1919926 , 43.48487919]), index=70, x=array([ 8.71659533, 30.1919926 , 43.48487919]), fval=0.5809857023401898, rho=0.03496716931364283, accepted=True, new_indices=array([], dtype=int64), old_indices_used=array([29, 60, 62, 63, 64, 65, 66, 67, 68, 69]), old_indices_discarded=array([], dtype=int64), step_length=0.0022241591417129824, relative_step_length=1.017071120020028, n_evals_per_point=1, n_evals_acceptance=1)], 'message': 'Absolute criterion change smaller than tolerance.', 'tranquilo_history': History for least_squares function with 71 entries., 'history': {'params': [{'CRRA': 8.619299408414172, 'BeqShift': 30.632884752878972, 'BeqFac': 44.786228146351164}, {'CRRA': 9.87028469932594, 'BeqShift': 32.87889290963555, 'BeqFac': 41.11900229054743}, {'CRRA': 5.741380985353151, 'BeqShift': 32.72856688399732, 'BeqFac': 42.068919869528784}, {'CRRA': 4.813209584708213, 'BeqShift': 32.58770333765523, 'BeqFac': 46.10926513384073}, {'CRRA': 8.191373847420756, 'BeqShift': 26.174831052515337, 'BeqFac': 44.75978510014355}, {'CRRA': 7.949112373626343, 'BeqShift': 28.963948462628103, 'BeqFac': 48.88788187542876}, {'CRRA': 4.676986787855213, 'BeqShift': 28.539628609667208, 'BeqFac': 45.152987245022125}, {'CRRA': 10.621401002226143, 'BeqShift': 34.623878943229755, 'BeqFac': 44.437492004817145}, {'CRRA': 12.19487288587812, 'BeqShift': 29.479717112773272, 'BeqFac': 42.34829028478874}, {'CRRA': 8.026170958102279, 'BeqShift': 33.700244777391696, 'BeqFac': 47.995209828633264}, {'CRRA': 7.525264193070008, 'BeqShift': 28.49104099913274, 'BeqFac': 41.00817909983321}, {'CRRA': 11.830675341400363, 'BeqShift': 27.847064196595205, 'BeqFac': 46.19489090265377}, {'CRRA': 12.083108252451714, 'BeqShift': 31.819496508108845, 'BeqFac': 47.36538365738336}, {'CRRA': 8.939333576200067, 'BeqShift': 33.541026945442, 'BeqFac': 48.25947214692842}, {'CRRA': 9.016683493657053, 'BeqShift': 30.075480082310545, 'BeqFac': 47.13402120519507}, {'CRRA': 8.890659259166057, 'BeqShift': 31.563421063550116, 'BeqFac': 45.384073162889614}, {'CRRA': 8.333924353780768, 'BeqShift': 30.151559228073392, 'BeqFac': 44.769080521223366}, {'CRRA': 8.86425485790588, 'BeqShift': 30.132673977289265, 'BeqFac': 44.842736830924125}, {'CRRA': 9.109924352798405, 'BeqShift': 30.365670600065236, 'BeqFac': 44.82215841448146}, {'CRRA': 8.663545519964131, 'BeqShift': 31.17993576968866, 'BeqFac': 44.675843861672135}, {'CRRA': 9.036398968014376, 'BeqShift': 30.714884552379, 'BeqFac': 44.42193264274567}, {'CRRA': 8.31952452903284, 'BeqShift': 31.104158749662574, 'BeqFac': 44.824215846089736}, {'CRRA': 9.139927626505786, 'BeqShift': 30.837008168539334, 'BeqFac': 44.76001529855078}, {'CRRA': 8.10903953991589, 'BeqShift': 30.655671185464865, 'BeqFac': 44.55704946328043}, {'CRRA': 8.166313468794495, 'BeqShift': 30.958816846567288, 'BeqFac': 44.74173958046354}, {'CRRA': 8.88221928289176, 'BeqShift': 30.363371555012144, 'BeqFac': 44.37192994521556}, {'CRRA': 8.786877858603715, 'BeqShift': 31.138519427713675, 'BeqFac': 44.6140124028177}, {'CRRA': 8.231781514134681, 'BeqShift': 30.393236991171065, 'BeqFac': 44.460949718530486}, {'CRRA': 8.712168160171553, 'BeqShift': 30.106786207026033, 'BeqFac': 44.60110323235169}, {'CRRA': 8.715192049073268, 'BeqShift': 30.197778400970996, 'BeqFac': 43.48514913675949}, {'CRRA': 8.70959840958466, 'BeqShift': 30.615694348492802, 'BeqFac': 43.85769299261434}, {'CRRA': 8.70264436143721, 'BeqShift': 30.47535208659141, 'BeqFac': 43.52191106824116}, {'CRRA': 8.687739857895615, 'BeqShift': 30.14668760717131, 'BeqFac': 43.612522836826294}, {'CRRA': 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8.714894721756652, 'BeqShift': 30.184868882543878, 'BeqFac': 43.496952427500865}, {'CRRA': 8.703141800610878, 'BeqShift': 30.185160933107316, 'BeqFac': 43.48643473334571}, {'CRRA': 8.720134744501067, 'BeqShift': 30.18452542922955, 'BeqFac': 43.49544429308697}, {'CRRA': 8.71765670195245, 'BeqShift': 30.18508086305389, 'BeqFac': 43.473369503534826}, {'CRRA': 8.727525685533275, 'BeqShift': 30.19081169846414, 'BeqFac': 43.495415986798925}, {'CRRA': 8.72118485073508, 'BeqShift': 30.192233861866722, 'BeqFac': 43.48200909697741}, {'CRRA': 8.726305588666097, 'BeqShift': 30.17552115093885, 'BeqFac': 43.47718925754808}, {'CRRA': 8.713114690174143, 'BeqShift': 30.190433172346413, 'BeqFac': 43.479155071532205}, {'CRRA': 8.716963638848423, 'BeqShift': 30.191292636605958, 'BeqFac': 43.48135769534717}, {'CRRA': 8.72568695107164, 'BeqShift': 30.19188722629156, 'BeqFac': 43.48161405921307}, {'CRRA': 8.721190141764092, 'BeqShift': 30.192369431994443, 'BeqFac': 43.48168333880651}, {'CRRA': 8.71706370258679, 'BeqShift': 30.189867011065672, 'BeqFac': 43.48309569914911}, {'CRRA': 8.716676567991986, 'BeqShift': 30.192121272653946, 'BeqFac': 43.482013002984885}, {'CRRA': 8.716689234293632, 'BeqShift': 30.19119918903792, 'BeqFac': 43.48403566238886}, {'CRRA': 8.716618066868186, 'BeqShift': 30.192855814398573, 'BeqFac': 43.48282950290912}, {'CRRA': 8.716595327316808, 'BeqShift': 30.191992596593977, 'BeqFac': 43.48487919113475}], 'criterion': [0.5817437469029839, 0.641322433452693, 1.1587349701553809, 1.7121929127035629, 0.5957490079994376, 0.61204935483071, 1.81870467661179, 0.7351499044140605, 1.042467627473152, 0.6061392239938227, 0.6585883680886361, 0.9597830757193228, 1.016452335069872, 0.5836095852842079, 0.5857807296266231, 0.5825697659851035, 0.5887821232029997, 0.5821430339742288, 0.5887383910148893, 0.5813236105131235, 0.5862584770649847, 0.5894238440800942, 0.5898844479077643, 0.600503473991078, 0.5971575645859035, 0.5824107567829471, 0.5814952123155697, 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26.136735373390117}, {'CRRA': 9.206944767351247, 'BeqShift': 50.643965368292854, 'BeqFac': 26.13636749731083}, {'CRRA': 9.206226751341177, 'BeqShift': 50.644175383761606, 'BeqFac': 26.136243764551427}, {'CRRA': 9.206139999933411, 'BeqShift': 50.64434589304829, 'BeqFac': 26.136339414991006}, {'CRRA': 9.20692991957421, 'BeqShift': 50.64378902036765, 'BeqFac': 26.13696828979672}, {'CRRA': 9.206030525524028, 'BeqShift': 50.6444124709626, 'BeqFac': 26.13695405708431}, {'CRRA': 9.206033510436992, 'BeqShift': 50.64400644035142, 'BeqFac': 26.13700040210868}, {'CRRA': 9.206910984777197, 'BeqShift': 50.64373643105872, 'BeqFac': 26.136616281363658}, {'CRRA': 9.20619643081797, 'BeqShift': 50.644622612155665, 'BeqFac': 26.136535077074925}, {'CRRA': 9.20642878297644, 'BeqShift': 50.6444960576583, 'BeqFac': 26.137246459012054}, {'CRRA': 9.207127002456316, 'BeqShift': 50.64430039244862, 'BeqFac': 26.1367999605648}, {'CRRA': 9.207114719797469, 'BeqShift': 50.64419857360247, 'BeqFac': 26.13692076455369}, {'CRRA': 9.206778216146489, 'BeqShift': 50.64405071849033, 'BeqFac': 26.1368726540768}], 'criterion': [0.6419131545898231, 0.6992405625490731, 1.1240845476970416, 1.577376990569092, 0.6524642769901355, 0.6664887878432892, 1.6647770568284477, 0.7958273217414884, 1.1577117413885285, 0.6612605763524525, 0.7056652645879914, 1.051463755129049, 1.1229714048823773, 0.6417128790724664, 0.6415610317693744, 0.6416973103739135, 0.64141783218841, 0.6415718165830668, 0.6414915855271336, 0.6412798714314748, 0.6416690245253375, 0.6413838490259491, 0.6412533792921618, 0.6413209357438362, 0.6412698132156118, 0.6414892120617004, 0.641391882855679, 0.6412912681201268, 0.6412600044422002, 0.6414014712692039, 0.641212422800454, 0.64138920463213, 0.6412599767231901, 0.6413894182130144, 0.641240011408127, 0.6412958845272176, 0.6412931073773732, 0.6412860311722518, 0.6412856091678842, 0.641299080615386, 0.6412654340898993, 0.6412040518376516, 0.6412798376316433, 0.6412586069868993, 0.6412003819983737, 0.6411989063826031, 0.641198632121119, 0.641198805868094, 0.6412003147825824, 0.6412028895752717, 0.6412042395231233, 0.6412001224290423, 0.641205979879279, 0.6412059242494071, 0.6411998771542384, 0.6412033613190102, 0.6411998007566294, 0.6412026671203108, 0.6412025111397647, 0.6411981580830574], 'runtime': [0.0, 1.6225000619888306, 1.8208623389946297, 2.0214831299963407, 2.3780758359935135, 2.6056774169846904, 2.8214367309992667, 3.026432433980517, 3.247528671985492, 3.475298994977493, 3.716090304980753, 3.926765499985777, 4.1696615399851, 5.700570738990791, 7.090572686982341, 8.46942359500099, 9.826952342991717, 11.1874410599994, 12.670953125983942, 14.073503133986378, 15.415775064000627, 16.777498332987307, 18.136912931979168, 19.44478028998128, 20.9249066929915, 22.26256391199422, 23.626468014990678, 25.251971355988644, 25.453611488977913, 25.659738533984637, 25.865622649987927, 26.112973237002734, 26.36346254197997, 26.55055605797679, 26.754232481995132, 26.958369220985333, 27.18434452699148, 27.420230353978695, 27.644893939985195, 29.20647358399583, 30.686982325976714, 32.02958239999134, 33.3786810519814, 34.71376580098877, 36.05778275799821, 37.38048776300275, 39.191983733995585, 39.40957244997844, 39.614045912981965, 39.824004255002365, 40.0257615079754, 40.23395056297886, 40.45599366599345, 40.66358802097966, 40.90082527400227, 41.12791417900007, 41.331096677982714, 41.55513457299094, 43.058433758997126, 44.375435253983596], 'batches': [0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 17, 18, 19, 20, 21, 22, 23, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 25, 26]}, 'multistart_info': {...}}], 'exploration_sample': array([[ 9.20683173, 51.48987537, 25.99186716], + [ 9.36875 , 39.375 , 18.75 ], + [ 8.778125 , 63.4375 , 28.125 ], + [ 9.959375 , 6.5625 , 84.375 ], + [ 8.1875 , 26.25 , 62.5 ], + [10.55 , 35. , 50. ], + [ 7.596875 , 50.3125 , 71.875 ], + [ 7.00625 , 13.125 , 31.25 ], + [11.73125 , 30.625 , 6.25 ], + [12.321875 , 67.8125 , 96.875 ], + [ 6.415625 , 19.6875 , 15.625 ], + [12.9125 , 8.75 , 87.5 ], + [ 5.825 , 52.5 , 75. ], + [13.503125 , 45.9375 , 3.125 ], + [ 5.234375 , 59.0625 , 9.375 ], + [14.09375 , 56.875 , 43.75 ], + [14.684375 , 24.0625 , 59.375 ], + [ 4.64375 , 21.875 , 93.75 ], + [15.275 , 17.5 , 25. ], + [ 4.053125 , 10.9375 , 53.125 ], + [15.865625 , 54.6875 , 65.625 ], + [ 3.4625 , 43.75 , 37.5 ], + [16.45625 , 48.125 , 81.25 ], + [17.046875 , 15.3125 , 21.875 ], + [ 2.871875 , 32.8125 , 46.875 ], + [ 2.28125 , 65.625 , 56.25 ], + [17.6375 , 61.25 , 12.5 ], + [18.228125 , 28.4375 , 78.125 ], + [18.81875 , 4.375 , 68.75 ], + [19.409375 , 41.5625 , 34.375 ]]), 'exploration_results': array([0.64119885, 0.64211564, 0.64842422, 0.66164008, 0.68191739, + 0.7044766 , 0.74714868, 0.84823283, 0.8626059 , 0.97951322, + 0.98996599, 1.12431839, 1.18221304, 1.30406645, 1.43892243, + 1.52011014, 1.78024917, 1.78131285, 2.0971452 , 2.24344059, + 2.48116605, 2.89787 , 2.94379242, 3.4976294 , 3.77080322, + 4.13701934, 4.16035282, 4.94978648, 5.89491246, 7.00125067])}}" diff --git a/content/tables/TRP/WealthPortfolio_estimate_results.csv b/content/tables/TRP/WealthPortfolio_estimate_results.csv index c8d35c5..e97119b 100644 --- a/content/tables/TRP/WealthPortfolio_estimate_results.csv +++ b/content/tables/TRP/WealthPortfolio_estimate_results.csv @@ -1,10 +1,10 @@ -CRRA,3.4648806974271817 -WealthShare,0.531080509819149 -time_to_estimate,185.89632892608643 -params,"{'CRRA': 3.4648806974271817, 'WealthShare': 0.531080509819149}" -criterion,0.3956142498671711 -start_criterion,0.39563281477082374 -start_params,"{'CRRA': 3.4649554641078373, 'WealthShare': 0.5311168059313219}" +CRRA,5.35399091577092 +WealthShare,0.1710302407154898 +time_to_estimate,208.24305033683777 +params,"{'CRRA': 5.35399091577092, 'WealthShare': 0.1710302407154898}" +criterion,0.24222754644165564 +start_criterion,0.2389045493044743 +start_params,"{'CRRA': 5.354006322483765, 'WealthShare': 0.17100463259932858}" algorithm,multistart_tranquilo_ls direction,minimize n_free,2 @@ -13,21 +13,1629 @@ success, n_criterion_evaluations, n_derivative_evaluations, n_iterations, -history,"{'params': [{'CRRA': 3.4649554641078373, 'WealthShare': 0.5311168059313219}, {'CRRA': 3.157881781329135, 'WealthShare': 0.2473224681244135}, {'CRRA': 3.7624746846917523, 'WealthShare': 0.2240431231526196}, {'CRRA': 3.157881781329135, 'WealthShare': 0.39945742240679216}, {'CRRA': 3.7720291468865397, 'WealthShare': 0.47185802634006707}, {'CRRA': 3.6802362818077867, 'WealthShare': 0.2240431231526196}, {'CRRA': 3.441211346545693, 'WealthShare': 0.2240431231526196}, {'CRRA': 3.414421953240863, 'WealthShare': 0.7}, {'CRRA': 3.7021523455480567, 'WealthShare': 0.7}, {'CRRA': 3.7720291468865397, 'WealthShare': 0.6686480732500195}, {'CRRA': 3.157881781329135, 'WealthShare': 0.644517740993325}, {'CRRA': 3.172045493464639, 'WealthShare': 0.2240431231526196}, {'CRRA': 3.157881781329135, 'WealthShare': 0.6866039476106396}, {'CRRA': 3.455278172006866, 'WealthShare': 0.6436952348818475}, {'CRRA': 3.482717703228099, 'WealthShare': 0.6417742340652457}, {'CRRA': 3.441630262094873, 'WealthShare': 0.6145412189122421}, {'CRRA': 3.4225129052316277, 'WealthShare': 0.5409370822026279}, {'CRRA': 3.48570373260534, 'WealthShare': 0.5385055107833469}, {'CRRA': 3.45413017601394, 'WealthShare': 0.5314546894521868}, {'CRRA': 3.4703702709656685, 'WealthShare': 0.5312990270552305}, {'CRRA': 3.462248200145725, 'WealthShare': 0.530847877975147}, {'CRRA': 3.4638025081397066, 'WealthShare': 0.5318415196290966}, {'CRRA': 3.4656314186145827, 'WealthShare': 0.5309971525911571}, {'CRRA': 3.464712119677216, 'WealthShare': 0.5308816871763512}, {'CRRA': 3.464890623443189, 'WealthShare': 0.5312730750051059}, {'CRRA': 3.4650398450169457, 'WealthShare': 0.5311228495266765}, {'CRRA': 3.464920807106532, 'WealthShare': 0.531090434133886}, {'CRRA': 3.4649978061511297, 'WealthShare': 0.5311258572691309}, {'CRRA': 3.464880230664965, 'WealthShare': 0.5310703256463739}, {'CRRA': 3.464952398623187, 'WealthShare': 0.5311262977250806}, {'CRRA': 3.4648399335878723, 'WealthShare': 0.5310574559629038}, {'CRRA': 3.4648901610076788, 'WealthShare': 0.5310516536477853}, {'CRRA': 3.464878050381357, 'WealthShare': 0.5310806726349607}, {'CRRA': 3.4648589045442115, 'WealthShare': 0.5310913913171672}, {'CRRA': 3.4648769489031097, 'WealthShare': 0.5310911893148121}, {'CRRA': 3.464881847329815, 'WealthShare': 0.5310769861229598}, {'CRRA': 3.4648806974271817, 'WealthShare': 0.531080509819149}], 'criterion': [0.39562420447382873, nan, nan, 1249.0421729795332, 4.5855832763431605, nan, nan, 1.782112614018569, 1.7275923424114168, 1.518523655995384, 1.4474192855818668, nan, 1.7651374405691542, 1.3785818478738974, 1.3585841212907663, 1.1259853008712912, 0.4233413203746081, 0.4129242103340959, 0.3956984921310528, 0.3956976570754178, 0.39572955785625985, 0.3959256106740631, 0.3956710774610568, 0.3956905152391518, 0.3956413061786618, 0.3956329828030912, 0.39561894207152565, 0.3956373587107717, 0.39561748522412454, 0.3956373350012253, 0.3956257638497452, 0.3956308352280355, 0.39561434141034263, 0.3956187731851536, 0.39561882078905886, 0.39561494406024583, 0.39561424986717103], 'runtime': [0.0, 1.4629678609999246, 1.5032358759999624, 1.5490633109984628, 1.6017019739992975, 1.6470571870013373, 1.7097121350016096, 1.7486153659992851, 1.8122890449994884, 1.8663734100009606, 1.925586204000865, 1.9781071479992534, 2.021414527000161, 66.43172447599864, 67.78483922300074, 69.72082065200084, 71.04146697300166, 72.39164718100074, 73.7096145530013, 75.03324087600049, 76.35381426299864, 77.68544955800098, 79.02472872300132, 80.4109739480009, 81.81492040900048, 83.37987046299895, 84.72980602900134, 86.15332707500056, 87.53151713899933, 88.87330793100045, 90.2113333640009, 91.54731987999912, 92.89468507399943, 94.22075996399872, 95.6565283150012, 97.04244493000078, 98.44442257500123], 'batches': [0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25]}" -convergence_report, -multistart_info,"{'start_parameters': [{'CRRA': 3.4649554641078373, 'WealthShare': 0.5311168059313219}, {'CRRA': 4.3538465594405755, 'WealthShare': 0.5292995697261916}], 'local_optima': [Minimize with 2 free parameters terminated. +history,"{'params': [{'CRRA': 5.837906205607757, 'WealthShare': 0.17768435978844974}, {'CRRA': 5.521440822118637, 'WealthShare': 0.01}, {'CRRA': 6.355277172375491, 'WealthShare': 0.01}, {'CRRA': 5.320535238840023, 'WealthShare': 0.01}, {'CRRA': 6.330844268900851, 'WealthShare': 0.6950553265561836}, {'CRRA': 6.355277172375491, 'WealthShare': 0.34431980448135446}, {'CRRA': 6.226403636138772, 'WealthShare': 0.01}, {'CRRA': 5.320535238840023, 'WealthShare': 0.01}, {'CRRA': 5.875481040447152, 'WealthShare': 0.6950553265561836}, {'CRRA': 6.343115925559374, 'WealthShare': 0.6950553265561836}, {'CRRA': 5.42192271850144, 'WealthShare': 0.6950553265561836}, {'CRRA': 5.320535238840023, 'WealthShare': 0.3927845660013606}, {'CRRA': 5.320535238840023, 'WealthShare': 0.6950553265561836}, {'CRRA': 6.260289192255453, 'WealthShare': 0.1414416437258815}, {'CRRA': 5.586422994097967, 'WealthShare': 0.12009017405786418}, {'CRRA': 5.696471798014226, 'WealthShare': 0.13230174451397797}, {'CRRA': 5.910749514856811, 'WealthShare': 0.15649323241599017}, {'CRRA': 5.801270203852185, 'WealthShare': 0.16823018219702343}, {'CRRA': 5.874111015856876, 'WealthShare': 0.15737844781264468}, {'CRRA': 5.764781908128255, 'WealthShare': 0.16842199875974878}, {'CRRA': 5.83762293702503, 'WealthShare': 0.15849023997730602}, {'CRRA': 5.728295327191924, 'WealthShare': 0.1687167695944529}, {'CRRA': 5.655320864957503, 'WealthShare': 0.16922976706263002}, {'CRRA': 5.801158262739447, 'WealthShare': 0.159625327541431}, {'CRRA': 5.582345042721493, 'WealthShare': 0.16957706599752984}, {'CRRA': 5.728061206699304, 'WealthShare': 0.1612420849769127}, {'CRRA': 5.655213987125576, 'WealthShare': 0.16219328110045608}, {'CRRA': 5.54577405830501, 'WealthShare': 0.1641467052653886}, {'CRRA': 5.564089269324569, 'WealthShare': 0.16867455696897235}, {'CRRA': 5.527610331306062, 'WealthShare': 0.1695245283248613}, {'CRRA': 5.454569298934131, 'WealthShare': 0.1657673350712589}, {'CRRA': 5.491057478350771, 'WealthShare': 0.16462446060590527}, {'CRRA': 5.509363764950676, 'WealthShare': 0.16935796524808727}, {'CRRA': 5.472878982838546, 'WealthShare': 0.1697534682609821}, {'CRRA': 5.39990991296233, 'WealthShare': 0.1705867470386037}, {'CRRA': 5.2539840063420415, 'WealthShare': 0.166169845381478}, {'CRRA': 5.326948348474455, 'WealthShare': 0.17199264976389753}, {'CRRA': 5.363429877974597, 'WealthShare': 0.17140117312121952}, {'CRRA': 5.381674772858575, 'WealthShare': 0.17165503946704128}, {'CRRA': 5.354324915656451, 'WealthShare': 0.16988722969298148}, {'CRRA': 5.358866777462407, 'WealthShare': 0.17113518644845302}, {'CRRA': 5.349755525044417, 'WealthShare': 0.17069814042911424}, {'CRRA': 5.354305613394689, 'WealthShare': 0.17110730029989854}, {'CRRA': 5.345135297716727, 'WealthShare': 0.17071002327939397}, {'CRRA': 5.349745787974868, 'WealthShare': 0.17125844781552682}, {'CRRA': 5.352024899000856, 'WealthShare': 0.17108068833293297}, {'CRRA': 5.355446817343039, 'WealthShare': 0.1712165807131758}, {'CRRA': 5.353737844217815, 'WealthShare': 0.17136997487615657}, {'CRRA': 5.354591141806533, 'WealthShare': 0.17114188868178082}, {'CRRA': 5.354307242363997, 'WealthShare': 0.17096478260213566}, {'CRRA': 5.354234900928805, 'WealthShare': 0.17109845000305954}, {'CRRA': 5.354273892151148, 'WealthShare': 0.17096136013364222}, {'CRRA': 5.3541640557109185, 'WealthShare': 0.17110619605176702}, {'CRRA': 5.35426853425294, 'WealthShare': 0.1711185203084774}, {'CRRA': 5.354235173394749, 'WealthShare': 0.1710806362107799}, {'CRRA': 5.354200577562492, 'WealthShare': 0.17107210010953106}, {'CRRA': 5.354130693185321, 'WealthShare': 0.17105814085154764}, {'CRRA': 5.35399091577092, 'WealthShare': 0.1710302407154898}], 'criterion': [0.2500179178839741, 1.1792461131204435, 0.9197765436682048, 1.2595171604963433, 33.16445541254984, 1.4878207969751798, 0.9532709482124387, 1.2595171604963433, 36.93789575006835, 33.071347222276614, 41.45067088403316, 2.9856980365173467, 42.60257108837822, 0.27371069489945155, 0.3353446406768353, 0.29385520517736274, 0.25245645388982746, 0.24610730524369168, 0.2512862430006085, 0.24542189740001585, 0.25015888395593905, 0.24507292693629096, 0.2440744520975429, 0.2488794160642582, 0.24318410996735987, 0.24711505738750136, 0.24589227104352215, 0.24442274744445994, 0.24306721295336706, 0.24288435328669916, 0.2433661384295173, 0.24398380010235204, 0.2428345891015183, 0.24267293680244378, 0.24231674775792228, 0.2439014107925056, 0.24236160354034061, 0.2423113173928428, 0.24240633196487957, 0.24234281133746066, 0.2422660131172327, 0.24228370883608596, 0.2422367332032626, 0.24227422877909757, 0.2422985499732716, 0.2422412748554663, 0.2422567765689739, 0.24229594886956057, 0.2422455073255868, 0.24223700359046088, 0.2422350327190185, 0.24223767262404658, 0.24223687844797048, 0.24223948283887395, 0.24223166413037345, 0.2422301948200769, 0.24222785386695275, 0.24222754644165562], 'runtime': [0.0, 1.3006106629909482, 1.3461875649809372, 1.392138064984465, 1.4359841749828774, 1.5009825789893512, 1.550953859987203, 1.593609842006117, 1.638624159997562, 1.686485532001825, 1.7453936449892353, 1.7891343509836588, 1.8489449310000055, 3.2682942989922594, 4.4358367919921875, 5.712266588991042, 6.875062373001128, 8.065197699994314, 9.26269722500001, 10.43409699498443, 11.618591404985636, 12.797749530989677, 13.943540325999493, 15.100036732997978, 16.27896274998784, 17.441876513999887, 18.707559181988472, 19.848269279988017, 21.01465619399096, 22.18544425399159, 23.350925145001383, 24.513529393996578, 25.67127582000103, 26.822254801983945, 27.962893974996405, 29.11491555799148, 30.30321866099257, 31.654834265005775, 32.9144726920058, 34.122135265992256, 35.37244299199665, 36.586844901001314, 37.83399780999753, 39.01701513200533, 40.18066080898279, 41.38312898899312, 42.55371054899297, 43.73981825000374, 45.013344446982956, 46.170059423981, 47.351473324000835, 48.54954139099573, 49.72759446298005, 50.919856733991764, 52.213698393985396, 53.48934546398232, 54.798059503984405, 56.106529726006556], 'batches': [0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46]}" +convergence_report,"{'one_step': {'relative_criterion_change': 4.409062648304273e-07, 'relative_params_change': 6.0459488881039185e-06, 'absolute_criterion_change': 1.0679964274062925e-07, 'absolute_params_change': 2.8559467214664423e-05}, 'five_steps': {'relative_criterion_change': 4.409062648304273e-07, 'relative_params_change': 6.0459488881039185e-06, 'absolute_criterion_change': 1.0679964274062925e-07, 'absolute_params_change': 2.8559467214664423e-05}}" +multistart_info,"{'start_parameters': [{'CRRA': 5.354006322483765, 'WealthShare': 0.17100463259932858}, {'CRRA': 5.837906205607757, 'WealthShare': 0.17768435978844974}], 'local_optima': [Minimize with 2 free parameters terminated. -The tranquilo_ls algorithm reported: Absolute criterion change smaller than tolerance., Minimize with 2 free parameters terminated. +The tranquilo_ls algorithm reported: Absolute criterion change smaller than tolerance. -The tranquilo_ls algorithm reported: Absolute criterion change smaller than tolerance.], 'exploration_sample': [{'CRRA': 3.4649554641078373, 'WealthShare': 0.5311168059313219}, {'CRRA': 6.5, 'WealthShare': 0.5249999999999999}, {'CRRA': 8.1875, 'WealthShare': 0.5031249999999999}, {'CRRA': 14.375, 'WealthShare': 0.56875}, {'CRRA': 16.625, 'WealthShare': 0.48124999999999996}, {'CRRA': 17.75, 'WealthShare': 0.6124999999999999}, {'CRRA': 3.125, 'WealthShare': 0.65625}, {'CRRA': 12.6875, 'WealthShare': 0.678125}, {'CRRA': 4.25, 'WealthShare': 0.4375}, {'CRRA': 9.875, 'WealthShare': 0.39375}, {'CRRA': 11.0, 'WealthShare': 0.35}, {'CRRA': 12.125, 'WealthShare': 0.30624999999999997}, {'CRRA': 3.6875, 'WealthShare': 0.328125}, {'CRRA': 8.75, 'WealthShare': 0.26249999999999996}], 'exploration_results': array([3.95624204e-01, 5.40772083e-01, 6.64838810e-01, 9.93508418e-01, - 1.09516320e+00, 1.28240377e+00, 1.55241851e+00, 1.58146070e+00, - 2.50692199e+01, 5.43503566e+01, 5.78231367e+02, 2.16882760e+03, - 2.24574771e+03, 2.24849469e+03])}" -algorithm_output,"{'states': [State(trustregion=Region(center=array([3.46495546, 0.53111681]), radius=0.34649554641078373, bounds=Bounds(lower=array([2., 0.]), upper=array([20. , 0.7]))), model_indices=[0], model=ScalarModel(intercept=0.39562420447382873, linear_terms=array([0., 0.]), square_terms=array([[0., 0.], - [0., 0.]]), scale=0.34649554641078373, shift=array([3.46495546, 0.53111681])), vector_model=VectorModel(intercepts=array([ 0.12634366, 0.23737133, 0.24789398, 0.25225032, 0.22803295, - 0.18688178, 0.14271092, 0.01053395, -0.07344733, 0.01546678, - -0.23684551, -0.16533737, -0.03497767, -0.00162142, 0.01248823, - 0.01256806, 0.01508461]), linear_terms=array([[0., 0.], +Independent of the convergence criteria used by tranquilo_ls, the strength of convergence can be assessed by the following criteria: + + one_step five_steps +relative_criterion_change 3.06e-07* 7.996e-06* +relative_params_change 7.965e-05 0.0001471 +absolute_criterion_change 7.413e-08* 1.937e-06* +absolute_params_change 1.634e-05 5.063e-05 + +(***: change <= 1e-10, **: change <= 1e-8, *: change <= 1e-5. Change refers to a change between accepted steps. The first column only considers the last step. The second column considers the last five steps.), Minimize with 2 free parameters terminated. + +The tranquilo_ls algorithm reported: Absolute criterion change smaller than tolerance. + +Independent of the convergence criteria used by tranquilo_ls, the strength of convergence can be assessed by the following criteria: + + one_step five_steps +relative_criterion_change 1.269e-06* 3.793e-05 +relative_params_change 0.0001652 0.0004544 +absolute_criterion_change 3.074e-07* 9.187e-06* +absolute_params_change 0.0001425 0.000324 + +(***: change <= 1e-10, **: change <= 1e-8, *: change <= 1e-5. Change refers to a change between accepted steps. The first column only considers the last step. The second column considers the last five steps.)], 'exploration_sample': [{'CRRA': 5.354006322483765, 'WealthShare': 0.17100463259932858}, {'CRRA': 7.00625, 'WealthShare': 0.19375}, {'CRRA': 12.9125, 'WealthShare': 0.1325}, {'CRRA': 4.64375, 'WealthShare': 0.31625000000000003}, {'CRRA': 8.1875, 'WealthShare': 0.3775}, {'CRRA': 15.274999999999999, 'WealthShare': 0.255}, {'CRRA': 17.046875, 'WealthShare': 0.224375}, {'CRRA': 11.73125, 'WealthShare': 0.43875}, {'CRRA': 18.81875, 'WealthShare': 0.07125}, {'CRRA': 10.549999999999999, 'WealthShare': 0.5}, {'CRRA': 9.368749999999999, 'WealthShare': 0.56125}, {'CRRA': 16.45625, 'WealthShare': 0.68375}, {'CRRA': 2.871875, 'WealthShare': 0.469375}, {'CRRA': 7.596874999999999, 'WealthShare': 0.714375}, {'CRRA': 14.093749999999998, 'WealthShare': 0.80625}, {'CRRA': 3.4625, 'WealthShare': 0.6225}, {'CRRA': 17.6375, 'WealthShare': 0.8674999999999999}, {'CRRA': 5.824999999999999, 'WealthShare': 0.745}, {'CRRA': 12.321874999999999, 'WealthShare': 0.959375}, {'CRRA': 2.28125, 'WealthShare': 0.92875}], 'exploration_results': array([2.42229590e-01, 3.27384376e-01, 1.14034055e+00, 1.50312179e+00, + 1.79325436e+00, 2.08879824e+00, 2.54067782e+00, 2.64114350e+00, + 2.73814230e+00, 3.83228381e+00, 6.46248546e+00, 9.30118040e+00, + 1.59966394e+01, 3.03715662e+01, 3.38771067e+01, 4.26926083e+01, + 5.84656546e+01, 5.90505617e+01, 5.22500282e+02, 9.01924413e+02])}" +algorithm_output,"{'states': [State(trustregion=Region(center=array([5.83790621, 0.17768436]), radius=0.5837906205607757, bounds=Bounds(lower=array([1.1 , 0.01]), upper=array([20. , 0.99]))), model_indices=[0], model=ScalarModel(intercept=0.2500179178839741, linear_terms=array([0., 0.]), square_terms=array([[0., 0.], + [0., 0.]]), scale=0.5837906205607757, shift=array([5.83790621, 0.17768436])), vector_model=VectorModel(intercepts=array([ 0.04097031, 0.08957803, 0.08816081, 0.11232093, 0.12575895, + 0.13980376, 0.15781889, 0.17546538, 0.09348822, 0.15053254, + -0.17880431, -0.21077511, -0.08570458, -0.06416478, -0.05745986, + -0.05902133, -0.05316704]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=0.5837906205607757, shift=array([5.83790621, 0.17768436])), candidate_index=0, candidate_x=array([5.83790621, 0.17768436]), index=0, x=array([5.83790621, 0.17768436]), fval=0.25001791788397415, rho=nan, accepted=True, new_indices=[0], old_indices_used=[], old_indices_discarded=[], step_length=None, relative_step_length=None, n_evals_per_point=None, n_evals_acceptance=None), State(trustregion=Region(center=array([5.83790621, 0.17768436]), radius=0.5837906205607757, bounds=Bounds(lower=array([1.1 , 0.01]), upper=array([20. , 0.99]))), model_indices=array([ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12]), model=ScalarModel(intercept=5.453595147945511, linear_terms=array([-0.61048798, 16.31048865]), square_terms=array([[ 0.04668694, -0.92878469], + [-0.92878469, 25.23647844]]), scale=array([0.51737097, 0.34252766]), shift=array([5.83790621, 0.35252766])), vector_model=VectorModel(intercepts=array([ 0.04097031, 0.08957803, 0.08816081, 0.11232093, 0.12575895, + 0.13980376, 0.15781889, 0.17546538, 0.09348822, 0.15053254, + -0.17880431, -0.21077511, -0.08570458, -0.06416478, -0.05745986, + -0.05902133, -0.05316704]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=0.5837906205607757, shift=array([5.83790621, 0.17768436])), candidate_index=13, candidate_x=array([6.26028919, 0.14144164]), index=0, x=array([5.83790621, 0.17768436]), fval=0.25001791788397415, rho=-0.09994429546320836, accepted=False, new_indices=array([ 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12]), old_indices_used=array([0]), old_indices_discarded=array([], dtype=int64), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([5.83790621, 0.17768436]), radius=0.29189531028038784, bounds=Bounds(lower=array([1.1 , 0.01]), upper=array([20. , 0.99]))), model_indices=array([ 0, 1, 2, 3, 5, 6, 7, 8, 13]), model=ScalarModel(intercept=1.029847416702383, linear_terms=array([-0.15206957, 3.84463924]), square_terms=array([[ 0.02831952, -0.37138794], + [-0.37138794, 8.69674828]]), scale=array([0.25868548, 0.21318492]), shift=array([5.83790621, 0.22318492])), vector_model=VectorModel(intercepts=array([ 0.04097031, 0.08957803, 0.08816081, 0.11232093, 0.12575895, + 0.13980376, 0.15781889, 0.17546538, 0.09348822, 0.15053254, + -0.17880431, -0.21077511, -0.08570458, -0.06416478, -0.05745986, + -0.05902133, -0.05316704]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=0.5837906205607757, shift=array([5.83790621, 0.17768436])), candidate_index=14, candidate_x=array([5.58642299, 0.12009017]), index=0, x=array([5.83790621, 0.17768436]), fval=0.25001791788397415, rho=-0.36587111256709887, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([ 0, 1, 2, 3, 5, 6, 7, 8, 13]), old_indices_discarded=array([ 4, 9, 10, 11, 12]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([5.83790621, 0.17768436]), radius=0.14594765514019392, bounds=Bounds(lower=array([1.1 , 0.01]), upper=array([20. , 0.99]))), model_indices=array([ 0, 1, 3, 5, 6, 7, 8, 13, 14]), model=ScalarModel(intercept=0.3307652689377624, linear_terms=array([-0.05352468, 1.12834325]), square_terms=array([[ 0.01880846, -0.24791449], + [-0.24791449, 4.39579594]]), scale=0.14594765514019392, shift=array([5.83790621, 0.17768436])), vector_model=VectorModel(intercepts=array([ 0.04097031, 0.08957803, 0.08816081, 0.11232093, 0.12575895, + 0.13980376, 0.15781889, 0.17546538, 0.09348822, 0.15053254, + -0.17880431, -0.21077511, -0.08570458, -0.06416478, -0.05745986, + -0.05902133, -0.05316704]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], 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State(trustregion=Region(center=array([5.83790621, 0.17768436]), radius=0.07297382757009696, bounds=Bounds(lower=array([1.1 , 0.01]), upper=array([20. , 0.99]))), model_indices=array([ 0, 1, 14, 15]), model=ScalarModel(intercept=0.2547685338865855, linear_terms=array([-0.01144467, 0.12662975]), square_terms=array([[0.00075227, 0.00196842], + [0.00196842, 0.43154335]]), scale=0.07297382757009696, shift=array([5.83790621, 0.17768436])), vector_model=VectorModel(intercepts=array([ 0.04097031, 0.08957803, 0.08816081, 0.11232093, 0.12575895, + 0.13980376, 0.15781889, 0.17546538, 0.09348822, 0.15053254, + -0.17880431, -0.21077511, -0.08570458, -0.06416478, -0.05745986, + -0.05902133, -0.05316704]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + 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0.01]), upper=array([20. , 0.99]))), model_indices=array([ 0, 15, 16]), model=ScalarModel(intercept=0.250017917883974, linear_terms=array([0.00170653, 0.02764723]), square_terms=array([[5.79166409e-05, 1.55153703e-03], + [1.55153703e-03, 9.94464848e-02]]), scale=0.03648691378504848, shift=array([5.83790621, 0.17768436])), vector_model=VectorModel(intercepts=array([ 0.04097031, 0.08957803, 0.08816081, 0.11232093, 0.12575895, + 0.13980376, 0.15781889, 0.17546538, 0.09348822, 0.15053254, + -0.17880431, -0.21077511, -0.08570458, -0.06416478, -0.05745986, + -0.05902133, -0.05316704]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + 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model=ScalarModel(intercept=0.253495790709351, linear_terms=array([-0.0041094 , 0.05810197]), square_terms=array([[1.86338211e-04, 5.35098646e-03], + [5.35098646e-03, 4.21903878e-01]]), scale=0.07297382757009696, shift=array([5.8012702 , 0.16823018])), vector_model=VectorModel(intercepts=array([ 0.04097031, 0.08957803, 0.08816081, 0.11232093, 0.12575895, + 0.13980376, 0.15781889, 0.17546538, 0.09348822, 0.15053254, + -0.17880431, -0.21077511, -0.08570458, -0.06416478, -0.05745986, + -0.05902133, -0.05316704]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + 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square_terms=array([[5.55180026e-05, 1.53917542e-03], + [1.53917542e-03, 9.97372256e-02]]), scale=0.03648691378504848, shift=array([5.8012702 , 0.16823018])), vector_model=VectorModel(intercepts=array([ 0.04097031, 0.08957803, 0.08816081, 0.11232093, 0.12575895, + 0.13980376, 0.15781889, 0.17546538, 0.09348822, 0.15053254, + -0.17880431, -0.21077511, -0.08570458, -0.06416478, -0.05745986, + -0.05902133, -0.05316704]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + 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[5.87973754e-03, 4.19729698e-01]]), scale=0.07297382757009696, shift=array([5.76478191, 0.168422 ])), vector_model=VectorModel(intercepts=array([ 0.04097031, 0.08957803, 0.08816081, 0.11232093, 0.12575895, + 0.13980376, 0.15781889, 0.17546538, 0.09348822, 0.15053254, + -0.17880431, -0.21077511, -0.08570458, -0.06416478, -0.05745986, + -0.05902133, -0.05316704]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=0.5837906205607757, shift=array([5.83790621, 0.17768436])), candidate_index=20, candidate_x=array([5.83762294, 0.15849024]), index=19, x=array([5.76478191, 0.168422 ]), fval=0.2454218974000159, rho=-0.7653738840742371, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([ 0, 1, 14, 15, 16, 17, 18, 19]), old_indices_discarded=array([], dtype=int64), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([5.76478191, 0.168422 ]), radius=0.03648691378504848, bounds=Bounds(lower=array([1.1 , 0.01]), upper=array([20. , 0.99]))), model_indices=array([ 0, 15, 16, 17, 18, 19, 20]), model=ScalarModel(intercept=0.24478338352931536, linear_terms=array([0.00104386, 0.00067952]), square_terms=array([[5.17736477e-05, 1.49720466e-03], + [1.49720466e-03, 1.00208068e-01]]), scale=0.03648691378504848, shift=array([5.76478191, 0.168422 ])), vector_model=VectorModel(intercepts=array([ 0.04097031, 0.08957803, 0.08816081, 0.11232093, 0.12575895, + 0.13980376, 0.15781889, 0.17546538, 0.09348822, 0.15053254, + -0.17880431, -0.21077511, -0.08570458, -0.06416478, -0.05745986, + -0.05902133, -0.05316704]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=0.5837906205607757, shift=array([5.83790621, 0.17768436])), candidate_index=21, candidate_x=array([5.72829533, 0.16871677]), index=21, x=array([5.72829533, 0.16871677]), fval=0.24507292693629099, rho=0.3416935494926942, accepted=True, new_indices=array([], dtype=int64), old_indices_used=array([ 0, 15, 16, 17, 18, 19, 20]), old_indices_discarded=array([], dtype=int64), step_length=0.03648777162651111, relative_step_length=1.0000235109351172, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([5.72829533, 0.16871677]), radius=0.07297382757009696, bounds=Bounds(lower=array([1.1 , 0.01]), upper=array([20. , 0.99]))), model_indices=array([ 0, 14, 15, 16, 17, 18, 19, 20, 21]), model=ScalarModel(intercept=0.24391675099982854, linear_terms=array([0.00218857, 0.00331565]), square_terms=array([[2.17190744e-04, 6.18094476e-03], + [6.18094476e-03, 4.05581192e-01]]), scale=0.07297382757009696, shift=array([5.72829533, 0.16871677])), vector_model=VectorModel(intercepts=array([ 0.04097031, 0.08957803, 0.08816081, 0.11232093, 0.12575895, + 0.13980376, 0.15781889, 0.17546538, 0.09348822, 0.15053254, + -0.17880431, -0.21077511, -0.08570458, -0.06416478, -0.05745986, + -0.05902133, -0.05316704]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=0.5837906205607757, shift=array([5.83790621, 0.17768436])), candidate_index=22, candidate_x=array([5.65532086, 0.16922977]), index=22, x=array([5.65532086, 0.16922977]), fval=0.24407445209754292, rho=0.4777137071010113, accepted=True, new_indices=array([], dtype=int64), old_indices_used=array([ 0, 14, 15, 16, 17, 18, 19, 20, 21]), old_indices_discarded=array([1]), step_length=0.07297626535254732, relative_step_length=1.0000334062571683, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([5.65532086, 0.16922977]), radius=0.14594765514019392, bounds=Bounds(lower=array([1.1 , 0.01]), upper=array([20. , 0.99]))), model_indices=array([ 0, 1, 14, 15, 17, 19, 20, 21, 22]), model=ScalarModel(intercept=0.2530356753079221, linear_terms=array([-0.00506925, 0.09004345]), square_terms=array([[5.16559769e-04, 2.11789911e-02], + [2.11789911e-02, 1.68392550e+00]]), scale=0.14594765514019392, shift=array([5.65532086, 0.16922977])), vector_model=VectorModel(intercepts=array([ 0.04097031, 0.08957803, 0.08816081, 0.11232093, 0.12575895, + 0.13980376, 0.15781889, 0.17546538, 0.09348822, 0.15053254, + -0.17880431, -0.21077511, -0.08570458, -0.06416478, -0.05745986, + -0.05902133, -0.05316704]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=0.5837906205607757, shift=array([5.83790621, 0.17768436])), candidate_index=23, candidate_x=array([5.80115826, 0.15962533]), index=22, x=array([5.65532086, 0.16922977]), fval=0.24407445209754292, rho=-0.5666553713621563, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([ 0, 1, 14, 15, 17, 19, 20, 21, 22]), old_indices_discarded=array([ 2, 3, 5, 6, 7, 8, 10, 11, 12, 13, 16, 18]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([5.65532086, 0.16922977]), radius=0.07297382757009696, bounds=Bounds(lower=array([1.1 , 0.01]), upper=array([20. , 0.99]))), model_indices=array([ 0, 14, 15, 17, 19, 20, 21, 22, 23]), model=ScalarModel(intercept=0.24311624432173012, linear_terms=array([0.00154361, 0.00363361]), square_terms=array([[1.87587564e-04, 5.59513446e-03], + [5.59513446e-03, 4.10801212e-01]]), scale=0.07297382757009696, shift=array([5.65532086, 0.16922977])), vector_model=VectorModel(intercepts=array([ 0.04097031, 0.08957803, 0.08816081, 0.11232093, 0.12575895, + 0.13980376, 0.15781889, 0.17546538, 0.09348822, 0.15053254, + -0.17880431, -0.21077511, -0.08570458, -0.06416478, -0.05745986, + -0.05902133, -0.05316704]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=0.5837906205607757, shift=array([5.83790621, 0.17768436])), candidate_index=24, candidate_x=array([5.58234504, 0.16957707]), index=24, x=array([5.58234504, 0.16957707]), fval=0.24318410996735987, rho=0.6121148476317633, accepted=True, new_indices=array([], dtype=int64), old_indices_used=array([ 0, 14, 15, 17, 19, 20, 21, 22, 23]), old_indices_discarded=array([ 1, 16, 18]), step_length=0.0729766486457952, relative_step_length=1.0000386587327563, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([5.58234504, 0.16957707]), radius=0.14594765514019392, bounds=Bounds(lower=array([1.1 , 0.01]), upper=array([20. , 0.99]))), model_indices=array([ 1, 14, 15, 17, 19, 21, 22, 23, 24]), model=ScalarModel(intercept=0.2489283617541748, linear_terms=array([0.00068245, 0.07288776]), square_terms=array([[5.95004131e-04, 2.31002626e-02], + [2.31002626e-02, 1.68009048e+00]]), scale=0.14594765514019392, shift=array([5.58234504, 0.16957707])), vector_model=VectorModel(intercepts=array([ 0.04097031, 0.08957803, 0.08816081, 0.11232093, 0.12575895, + 0.13980376, 0.15781889, 0.17546538, 0.09348822, 0.15053254, + -0.17880431, -0.21077511, -0.08570458, -0.06416478, -0.05745986, + -0.05902133, -0.05316704]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=0.5837906205607757, shift=array([5.83790621, 0.17768436])), candidate_index=25, candidate_x=array([5.72806121, 0.16124208]), index=24, x=array([5.58234504, 0.16957707]), fval=0.24318410996735987, rho=-2.230953042384717, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([ 1, 14, 15, 17, 19, 21, 22, 23, 24]), old_indices_discarded=array([ 0, 3, 6, 7, 8, 10, 11, 12, 13, 16, 18, 20]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([5.58234504, 0.16957707]), radius=0.07297382757009696, bounds=Bounds(lower=array([1.1 , 0.01]), upper=array([20. , 0.99]))), model_indices=array([ 1, 14, 15, 17, 19, 21, 22, 24, 25]), model=ScalarModel(intercept=0.24930004394171532, linear_terms=array([-2.38904522e-06, 3.69499149e-02]), square_terms=array([[1.38670904e-04, 5.63202076e-03], + [5.63202076e-03, 4.20322174e-01]]), scale=0.07297382757009696, shift=array([5.58234504, 0.16957707])), vector_model=VectorModel(intercepts=array([ 0.04097031, 0.08957803, 0.08816081, 0.11232093, 0.12575895, + 0.13980376, 0.15781889, 0.17546538, 0.09348822, 0.15053254, + -0.17880431, -0.21077511, -0.08570458, -0.06416478, -0.05745986, + -0.05902133, -0.05316704]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=0.5837906205607757, shift=array([5.83790621, 0.17768436])), candidate_index=26, candidate_x=array([5.65521399, 0.16219328]), index=24, x=array([5.58234504, 0.16957707]), fval=0.24318410996735987, rho=-1.2961620458518521, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([ 1, 14, 15, 17, 19, 21, 22, 24, 25]), old_indices_discarded=array([ 0, 3, 7, 11, 16, 18, 20, 23]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([5.58234504, 0.16957707]), radius=0.03648691378504848, bounds=Bounds(lower=array([1.1 , 0.01]), upper=array([20. , 0.99]))), model_indices=array([ 1, 14, 15, 21, 22, 24, 25, 26]), model=ScalarModel(intercept=0.24709268914155363, linear_terms=array([0.00119193, 0.01731959]), square_terms=array([[5.69678824e-05, 1.57856574e-03], + [1.57856574e-03, 1.04842584e-01]]), scale=0.03648691378504848, shift=array([5.58234504, 0.16957707])), vector_model=VectorModel(intercepts=array([ 0.04097031, 0.08957803, 0.08816081, 0.11232093, 0.12575895, + 0.13980376, 0.15781889, 0.17546538, 0.09348822, 0.15053254, + -0.17880431, -0.21077511, -0.08570458, -0.06416478, -0.05745986, + -0.05902133, -0.05316704]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=0.5837906205607757, shift=array([5.83790621, 0.17768436])), candidate_index=27, candidate_x=array([5.54577406, 0.16414671]), index=24, x=array([5.58234504, 0.16957707]), fval=0.24318410996735987, rho=-0.5277296110416976, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([ 1, 14, 15, 21, 22, 24, 25, 26]), old_indices_discarded=array([], dtype=int64), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([5.58234504, 0.16957707]), radius=0.01824345689252424, bounds=Bounds(lower=array([1.1 , 0.01]), upper=array([20. , 0.99]))), model_indices=array([14, 22, 24, 26, 27]), model=ScalarModel(intercept=0.2435860331988614, linear_terms=array([0.00019367, 0.00162664]), square_terms=array([[1.03223473e-05, 3.21675100e-04], + [3.21675100e-04, 2.62070841e-02]]), scale=0.01824345689252424, shift=array([5.58234504, 0.16957707])), vector_model=VectorModel(intercepts=array([ 0.04097031, 0.08957803, 0.08816081, 0.11232093, 0.12575895, + 0.13980376, 0.15781889, 0.17546538, 0.09348822, 0.15053254, + -0.17880431, -0.21077511, -0.08570458, -0.06416478, -0.05745986, + -0.05902133, -0.05316704]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=0.5837906205607757, shift=array([5.83790621, 0.17768436])), candidate_index=28, candidate_x=array([5.56408927, 0.16867456]), index=28, x=array([5.56408927, 0.16867456]), fval=0.24306721295336703, rho=0.5286886005963327, accepted=True, new_indices=array([], dtype=int64), old_indices_used=array([14, 22, 24, 26, 27]), old_indices_discarded=array([], dtype=int64), step_length=0.018278068411800873, relative_step_length=1.0018972018012011, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([5.56408927, 0.16867456]), radius=0.03648691378504848, bounds=Bounds(lower=array([1.1 , 0.01]), upper=array([20. , 0.99]))), model_indices=array([14, 15, 21, 22, 24, 25, 26, 27, 28]), model=ScalarModel(intercept=0.242964314677221, linear_terms=array([ 0.00054927, -0.00108451]), square_terms=array([[4.50168218e-05, 1.34975492e-03], + [1.34975492e-03, 1.03947965e-01]]), scale=0.03648691378504848, shift=array([5.56408927, 0.16867456])), vector_model=VectorModel(intercepts=array([ 0.04097031, 0.08957803, 0.08816081, 0.11232093, 0.12575895, + 0.13980376, 0.15781889, 0.17546538, 0.09348822, 0.15053254, + -0.17880431, -0.21077511, -0.08570458, -0.06416478, -0.05745986, + -0.05902133, -0.05316704]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=0.5837906205607757, shift=array([5.83790621, 0.17768436])), candidate_index=29, candidate_x=array([5.52761033, 0.16952453]), index=29, x=array([5.52761033, 0.16952453]), fval=0.24288435328669916, rho=0.32939034392246147, accepted=True, new_indices=array([], dtype=int64), old_indices_used=array([14, 15, 21, 22, 24, 25, 26, 27, 28]), old_indices_discarded=array([1]), step_length=0.036488838982131434, relative_step_length=1.0000527640428647, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([5.52761033, 0.16952453]), radius=0.07297382757009696, bounds=Bounds(lower=array([1.1 , 0.01]), upper=array([20. , 0.99]))), model_indices=array([ 1, 14, 15, 22, 24, 26, 27, 28, 29]), model=ScalarModel(intercept=0.2420019335469184, linear_terms=array([0.00573273, 0.02861724]), square_terms=array([[0.00050338, 0.00674964], + [0.00674964, 0.41972427]]), scale=0.07297382757009696, shift=array([5.52761033, 0.16952453])), vector_model=VectorModel(intercepts=array([ 0.04097031, 0.08957803, 0.08816081, 0.11232093, 0.12575895, + 0.13980376, 0.15781889, 0.17546538, 0.09348822, 0.15053254, + -0.17880431, -0.21077511, -0.08570458, -0.06416478, -0.05745986, + -0.05902133, -0.05316704]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=0.5837906205607757, shift=array([5.83790621, 0.17768436])), candidate_index=30, candidate_x=array([5.4545693 , 0.16576734]), index=29, x=array([5.52761033, 0.16952453]), fval=0.24288435328669916, rho=-0.07956672210493755, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([ 1, 14, 15, 22, 24, 26, 27, 28, 29]), old_indices_discarded=array([ 0, 3, 7, 11, 17, 18, 19, 20, 21, 23, 25]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([5.52761033, 0.16952453]), radius=0.03648691378504848, bounds=Bounds(lower=array([1.1 , 0.01]), upper=array([20. , 0.99]))), model_indices=array([ 1, 14, 22, 24, 26, 27, 28, 29, 30]), model=ScalarModel(intercept=0.24488473081300505, linear_terms=array([0.0009977 , 0.01563392]), square_terms=array([[5.57194237e-05, 1.40119061e-03], + [1.40119061e-03, 1.05208668e-01]]), scale=0.03648691378504848, shift=array([5.52761033, 0.16952453])), vector_model=VectorModel(intercepts=array([ 0.04097031, 0.08957803, 0.08816081, 0.11232093, 0.12575895, + 0.13980376, 0.15781889, 0.17546538, 0.09348822, 0.15053254, + -0.17880431, -0.21077511, -0.08570458, -0.06416478, -0.05745986, + -0.05902133, -0.05316704]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=0.5837906205607757, shift=array([5.83790621, 0.17768436])), candidate_index=31, candidate_x=array([5.49105748, 0.16462446]), index=29, x=array([5.52761033, 0.16952453]), fval=0.24288435328669916, rho=-0.5685237934133627, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([ 1, 14, 22, 24, 26, 27, 28, 29, 30]), old_indices_discarded=array([15]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([5.52761033, 0.16952453]), radius=0.01824345689252424, bounds=Bounds(lower=array([1.1 , 0.01]), upper=array([20. , 0.99]))), model_indices=array([14, 24, 27, 28, 29, 30, 31]), model=ScalarModel(intercept=0.24302431962819412, linear_terms=array([7.55308733e-05, 5.46770179e-04]), square_terms=array([[9.74635032e-06, 3.06763575e-04], + [3.06763575e-04, 2.62189415e-02]]), scale=0.01824345689252424, shift=array([5.52761033, 0.16952453])), vector_model=VectorModel(intercepts=array([ 0.04097031, 0.08957803, 0.08816081, 0.11232093, 0.12575895, + 0.13980376, 0.15781889, 0.17546538, 0.09348822, 0.15053254, + -0.17880431, -0.21077511, -0.08570458, -0.06416478, -0.05745986, + -0.05902133, -0.05316704]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=0.5837906205607757, shift=array([5.83790621, 0.17768436])), candidate_index=32, candidate_x=array([5.50936376, 0.16935797]), index=32, x=array([5.50936376, 0.16935797]), fval=0.24283458910151834, rho=0.693413890433385, accepted=True, new_indices=array([], dtype=int64), old_indices_used=array([14, 24, 27, 28, 29, 30, 31]), old_indices_discarded=array([], dtype=int64), step_length=0.018247326571858506, relative_step_length=1.000212113272011, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([5.50936376, 0.16935797]), radius=0.03648691378504848, bounds=Bounds(lower=array([1.1 , 0.01]), upper=array([20. , 0.99]))), model_indices=array([14, 22, 24, 27, 28, 29, 30, 31, 32]), model=ScalarModel(intercept=0.2429324718675529, linear_terms=array([1.80345936e-04, 8.51487840e-05]), square_terms=array([[3.88321243e-05, 1.22404574e-03], + [1.22404574e-03, 1.04906924e-01]]), scale=0.03648691378504848, shift=array([5.50936376, 0.16935797])), vector_model=VectorModel(intercepts=array([ 0.04097031, 0.08957803, 0.08816081, 0.11232093, 0.12575895, + 0.13980376, 0.15781889, 0.17546538, 0.09348822, 0.15053254, + -0.17880431, -0.21077511, -0.08570458, -0.06416478, -0.05745986, + -0.05902133, -0.05316704]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=0.5837906205607757, shift=array([5.83790621, 0.17768436])), candidate_index=33, candidate_x=array([5.47287898, 0.16975347]), index=33, x=array([5.47287898, 0.16975347]), fval=0.24267293680244376, rho=0.9673817824711848, accepted=True, new_indices=array([], dtype=int64), old_indices_used=array([14, 22, 24, 27, 28, 29, 30, 31, 32]), old_indices_discarded=array([ 1, 26]), step_length=0.0364869257187115, relative_step_length=1.000000327066934, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([5.47287898, 0.16975347]), radius=0.07297382757009696, bounds=Bounds(lower=array([1.1 , 0.01]), upper=array([20. , 0.99]))), model_indices=array([14, 24, 27, 28, 29, 30, 31, 32, 33]), model=ScalarModel(intercept=0.2427761119591001, linear_terms=array([ 2.39189726e-04, -1.29669188e-05]), square_terms=array([[1.58583544e-04, 4.77994302e-03], + [4.77994302e-03, 4.19573360e-01]]), scale=0.07297382757009696, shift=array([5.47287898, 0.16975347])), vector_model=VectorModel(intercepts=array([ 0.04097031, 0.08957803, 0.08816081, 0.11232093, 0.12575895, + 0.13980376, 0.15781889, 0.17546538, 0.09348822, 0.15053254, + -0.17880431, -0.21077511, -0.08570458, -0.06416478, -0.05745986, + -0.05902133, -0.05316704]), linear_terms=array([[0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.], + [0., 0.]]), square_terms=array([[[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]], + + [[0., 0.], + [0., 0.]]]), scale=0.5837906205607757, shift=array([5.83790621, 0.17768436])), candidate_index=34, candidate_x=array([5.39990991, 0.17058675]), index=34, x=array([5.39990991, 0.17058675]), fval=0.24231674775792228, rho=1.9020634332530058, accepted=True, new_indices=array([], dtype=int64), old_indices_used=array([14, 24, 27, 28, 29, 30, 31, 32, 33]), old_indices_discarded=array([ 1, 3, 7, 11, 15, 17, 19, 21, 22, 23, 25, 26]), step_length=0.07297382758305467, relative_step_length=1.0000000001775664, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([5.39990991, 0.17058675]), radius=0.14594765514019392, bounds=Bounds(lower=array([1.1 , 0.01]), upper=array([20. , 0.99]))), model_indices=array([ 7, 27, 28, 29, 30, 31, 32, 33, 34]), model=ScalarModel(intercept=0.2430089349062019, linear_terms=array([0.00175618, 0.07611165]), square_terms=array([[7.68632058e-04, 2.17025796e-02], + [2.17025796e-02, 1.79761440e+00]]), scale=0.14594765514019392, shift=array([5.39990991, 0.17058675])), vector_model=VectorModel(intercepts=array([ 0.04097031, 0.08957803, 0.08816081, 0.11232093, 0.12575895, + 0.13980376, 0.15781889, 0.17546538, 0.09348822, 0.15053254, + -0.17880431, -0.21077511, -0.08570458, -0.06416478, -0.05745986, + -0.05902133, -0.05316704]), linear_terms=array([[0., 0.], [0., 0.], [0., 0.], [0., 0.], @@ -92,11 +1700,12 @@ algorithm_output,"{'states': [State(trustregion=Region(center=array([3.46495546, [0., 0.]], [[0., 0.], - [0., 0.]]]), scale=0.34649554641078373, shift=array([3.46495546, 0.53111681])), candidate_index=0, candidate_x=array([3.46495546, 0.53111681]), index=0, x=array([3.46495546, 0.53111681]), fval=0.3956242044738288, rho=nan, accepted=True, new_indices=[0], old_indices_used=[], old_indices_discarded=[], step_length=None, relative_step_length=None, n_evals_per_point=None, n_evals_acceptance=None), State(trustregion=Region(center=array([3.46495546, 0.53111681]), radius=0.34649554641078373, bounds=Bounds(lower=array([2., 0.]), upper=array([20. , 0.7]))), model_indices=array([ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12]), model=ScalarModel(intercept=398.1451650304675, linear_terms=array([ -116.94879171, -1047.56476915]), square_terms=array([[ 17.3576769 , 153.91041078], - [ 153.91041078, 1378.58236955]]), scale=array([0.30707368, 0.23797844]), shift=array([3.46495546, 0.46202156])), vector_model=VectorModel(intercepts=array([ 0.12634366, 0.23737133, 0.24789398, 0.25225032, 0.22803295, - 0.18688178, 0.14271092, 0.01053395, -0.07344733, 0.01546678, - -0.23684551, -0.16533737, -0.03497767, -0.00162142, 0.01248823, - 0.01256806, 0.01508461]), linear_terms=array([[0., 0.], + [0., 0.]]]), scale=0.5837906205607757, shift=array([5.83790621, 0.17768436])), candidate_index=35, candidate_x=array([5.25398401, 0.16616985]), index=34, x=array([5.39990991, 0.17058675]), fval=0.24231674775792228, rho=-0.72186797844346, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([ 7, 27, 28, 29, 30, 31, 32, 33, 34]), old_indices_discarded=array([ 0, 1, 3, 8, 10, 11, 12, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, + 24, 25, 26]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([5.39990991, 0.17058675]), radius=0.07297382757009696, bounds=Bounds(lower=array([1.1 , 0.01]), upper=array([20. , 0.99]))), model_indices=array([27, 28, 29, 30, 31, 32, 33, 34, 35]), model=ScalarModel(intercept=0.24231384996316413, linear_terms=array([ 0.00018402, -0.00403364]), square_terms=array([[1.69468241e-04, 4.40244170e-03], + [4.40244170e-03, 4.37739735e-01]]), scale=0.07297382757009696, shift=array([5.39990991, 0.17058675])), vector_model=VectorModel(intercepts=array([ 0.04097031, 0.08957803, 0.08816081, 0.11232093, 0.12575895, + 0.13980376, 0.15781889, 0.17546538, 0.09348822, 0.15053254, + -0.17880431, -0.21077511, -0.08570458, -0.06416478, -0.05745986, + -0.05902133, -0.05316704]), linear_terms=array([[0., 0.], [0., 0.], [0., 0.], [0., 0.], @@ -161,11 +1770,11 @@ algorithm_output,"{'states': [State(trustregion=Region(center=array([3.46495546, [0., 0.]], [[0., 0.], - [0., 0.]]]), scale=0.34649554641078373, shift=array([3.46495546, 0.53111681])), candidate_index=13, candidate_x=array([3.45527817, 0.64369523]), index=0, x=array([3.46495546, 0.53111681]), fval=0.3956242044738288, rho=-0.006468163493285016, accepted=False, new_indices=array([ 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12]), old_indices_used=array([0]), old_indices_discarded=array([], dtype=int64), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([3.46495546, 0.53111681]), radius=0.17324777320539186, bounds=Bounds(lower=array([2., 0.]), upper=array([20. , 0.7]))), model_indices=array([ 0, 3, 4, 6, 7, 8, 9, 10, 13]), model=ScalarModel(intercept=125.67421265200598, linear_terms=array([ -52.73202436, -339.91391334]), square_terms=array([[ 11.15682933, 71.374677 ], - [ 71.374677 , 460.17276361]]), scale=array([0.15353684, 0.15353684]), shift=array([3.46495546, 0.53111681])), vector_model=VectorModel(intercepts=array([ 0.12634366, 0.23737133, 0.24789398, 0.25225032, 0.22803295, - 0.18688178, 0.14271092, 0.01053395, -0.07344733, 0.01546678, - -0.23684551, -0.16533737, -0.03497767, -0.00162142, 0.01248823, - 0.01256806, 0.01508461]), linear_terms=array([[0., 0.], + [0., 0.]]]), scale=0.5837906205607757, shift=array([5.83790621, 0.17768436])), candidate_index=36, candidate_x=array([5.32694835, 0.17199265]), index=34, x=array([5.39990991, 0.17058675]), fval=0.24231674775792228, rho=-0.24843012199644884, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([27, 28, 29, 30, 31, 32, 33, 34, 35]), old_indices_discarded=array([ 1, 3, 7, 11, 14, 15, 21, 22, 24, 25, 26]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([5.39990991, 0.17058675]), radius=0.03648691378504848, bounds=Bounds(lower=array([1.1 , 0.01]), upper=array([20. , 0.99]))), model_indices=array([27, 29, 30, 31, 32, 33, 34, 35, 36]), model=ScalarModel(intercept=0.24238669883858652, linear_terms=array([ 8.94506136e-05, -1.39054452e-03]), square_terms=array([[4.22380429e-05, 1.09259613e-03], + [1.09259613e-03, 1.11165757e-01]]), scale=0.03648691378504848, shift=array([5.39990991, 0.17058675])), vector_model=VectorModel(intercepts=array([ 0.04097031, 0.08957803, 0.08816081, 0.11232093, 0.12575895, + 0.13980376, 0.15781889, 0.17546538, 0.09348822, 0.15053254, + -0.17880431, -0.21077511, -0.08570458, -0.06416478, -0.05745986, + -0.05902133, -0.05316704]), linear_terms=array([[0., 0.], [0., 0.], [0., 0.], [0., 0.], @@ -230,11 +1839,11 @@ algorithm_output,"{'states': [State(trustregion=Region(center=array([3.46495546, [0., 0.]], [[0., 0.], - [0., 0.]]]), scale=0.34649554641078373, shift=array([3.46495546, 0.53111681])), candidate_index=14, candidate_x=array([3.4827177 , 0.64177423]), index=0, x=array([3.46495546, 0.53111681]), fval=0.3956242044738288, rho=-0.007670421589594419, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([ 0, 3, 4, 6, 7, 8, 9, 10, 13]), old_indices_discarded=array([ 1, 2, 5, 11, 12]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([3.46495546, 0.53111681]), radius=0.08662388660269593, bounds=Bounds(lower=array([2., 0.]), upper=array([20. , 0.7]))), model_indices=array([ 0, 3, 4, 6, 7, 8, 10, 13, 14]), model=ScalarModel(intercept=108.36487966410208, linear_terms=array([ -37.40492364, -183.61193868]), square_terms=array([[ 6.50173301, 31.74217224], - [ 31.74217224, 155.75249716]]), scale=0.08662388660269593, shift=array([3.46495546, 0.53111681])), vector_model=VectorModel(intercepts=array([ 0.12634366, 0.23737133, 0.24789398, 0.25225032, 0.22803295, - 0.18688178, 0.14271092, 0.01053395, -0.07344733, 0.01546678, - -0.23684551, -0.16533737, -0.03497767, -0.00162142, 0.01248823, - 0.01256806, 0.01508461]), linear_terms=array([[0., 0.], + [0., 0.]]]), scale=0.5837906205607757, shift=array([5.83790621, 0.17768436])), candidate_index=37, candidate_x=array([5.36342988, 0.17140117]), index=37, x=array([5.36342988, 0.17140117]), fval=0.24231131739284278, rho=0.05653604311640793, accepted=True, new_indices=array([], dtype=int64), old_indices_used=array([27, 29, 30, 31, 32, 33, 34, 35, 36]), old_indices_discarded=array([ 3, 7, 28]), step_length=0.03648912499019746, relative_step_length=1.0000606026906524, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([5.36342988, 0.17140117]), radius=0.01824345689252424, bounds=Bounds(lower=array([1.1 , 0.01]), upper=array([20. , 0.99]))), model_indices=array([34, 36, 37]), model=ScalarModel(intercept=0.2423113173928431, linear_terms=array([-2.76319807e-05, -7.53809665e-04]), square_terms=array([[1.12978733e-05, 3.07815866e-04], + [3.07815866e-04, 3.20364135e-02]]), scale=0.01824345689252424, shift=array([5.36342988, 0.17140117])), vector_model=VectorModel(intercepts=array([ 0.04097031, 0.08957803, 0.08816081, 0.11232093, 0.12575895, + 0.13980376, 0.15781889, 0.17546538, 0.09348822, 0.15053254, + -0.17880431, -0.21077511, -0.08570458, -0.06416478, -0.05745986, + -0.05902133, -0.05316704]), linear_terms=array([[0., 0.], [0., 0.], [0., 0.], [0., 0.], @@ -299,11 +1908,11 @@ algorithm_output,"{'states': [State(trustregion=Region(center=array([3.46495546, [0., 0.]], [[0., 0.], - [0., 0.]]]), scale=0.34649554641078373, shift=array([3.46495546, 0.53111681])), candidate_index=15, candidate_x=array([3.44163026, 0.61454122]), index=0, x=array([3.46495546, 0.53111681]), fval=0.3956242044738288, rho=-0.007123789024766916, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([ 0, 3, 4, 6, 7, 8, 10, 13, 14]), old_indices_discarded=array([ 1, 2, 5, 9, 11, 12]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([3.46495546, 0.53111681]), radius=0.043311943301347966, bounds=Bounds(lower=array([2., 0.]), upper=array([20. , 0.7]))), model_indices=array([ 0, 7, 13, 14, 15]), model=ScalarModel(intercept=0.4067828643254545, linear_terms=array([0.02410679, 0.02614154]), square_terms=array([[0.03171362, 0.08913027], - [0.08913027, 0.25640891]]), scale=0.043311943301347966, shift=array([3.46495546, 0.53111681])), vector_model=VectorModel(intercepts=array([ 0.12634366, 0.23737133, 0.24789398, 0.25225032, 0.22803295, - 0.18688178, 0.14271092, 0.01053395, -0.07344733, 0.01546678, - -0.23684551, -0.16533737, -0.03497767, -0.00162142, 0.01248823, - 0.01256806, 0.01508461]), linear_terms=array([[0., 0.], + [0., 0.]]]), scale=0.5837906205607757, shift=array([5.83790621, 0.17768436])), candidate_index=38, candidate_x=array([5.38167477, 0.17165504]), index=37, x=array([5.36342988, 0.17140117]), fval=0.24231131739284278, rho=-3.7871858271077357, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([34, 36, 37]), old_indices_discarded=array([], dtype=int64), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([5.36342988, 0.17140117]), radius=0.00912172844626212, bounds=Bounds(lower=array([1.1 , 0.01]), upper=array([20. , 0.99]))), model_indices=array([34, 36, 37, 38]), model=ScalarModel(intercept=0.24232506941100967, linear_terms=array([1.70862499e-05, 1.21892565e-03]), square_terms=array([[2.52449325e-06, 5.92746750e-05], + [5.92746750e-05, 6.98298434e-03]]), scale=0.00912172844626212, shift=array([5.36342988, 0.17140117])), vector_model=VectorModel(intercepts=array([ 0.04097031, 0.08957803, 0.08816081, 0.11232093, 0.12575895, + 0.13980376, 0.15781889, 0.17546538, 0.09348822, 0.15053254, + -0.17880431, -0.21077511, -0.08570458, -0.06416478, -0.05745986, + -0.05902133, -0.05316704]), linear_terms=array([[0., 0.], [0., 0.], [0., 0.], [0., 0.], @@ -368,11 +1977,11 @@ algorithm_output,"{'states': [State(trustregion=Region(center=array([3.46495546, [0., 0.]], [[0., 0.], - [0., 0.]]]), scale=0.34649554641078373, shift=array([3.46495546, 0.53111681])), candidate_index=16, candidate_x=array([3.42251291, 0.54093708]), index=0, x=array([3.46495546, 0.53111681]), fval=0.3956242044738288, rho=-1.767498399877576, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([ 0, 7, 13, 14, 15]), old_indices_discarded=array([], dtype=int64), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([3.46495546, 0.53111681]), radius=0.021655971650673983, bounds=Bounds(lower=array([2., 0.]), upper=array([20. , 0.7]))), model_indices=array([ 0, 15, 16]), model=ScalarModel(intercept=0.395624204473829, linear_terms=array([-0.00396938, -0.02118094]), square_terms=array([[ 0.00266011, -0.01595618], - [-0.01595618, 0.09972197]]), scale=0.021655971650673983, shift=array([3.46495546, 0.53111681])), vector_model=VectorModel(intercepts=array([ 0.12634366, 0.23737133, 0.24789398, 0.25225032, 0.22803295, - 0.18688178, 0.14271092, 0.01053395, -0.07344733, 0.01546678, - -0.23684551, -0.16533737, -0.03497767, -0.00162142, 0.01248823, - 0.01256806, 0.01508461]), linear_terms=array([[0., 0.], + [0., 0.]]]), scale=0.5837906205607757, shift=array([5.83790621, 0.17768436])), candidate_index=39, candidate_x=array([5.35432492, 0.16988723]), index=37, x=array([5.36342988, 0.17140117]), fval=0.24231131739284278, rho=-0.28093054493142594, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([34, 36, 37, 38]), old_indices_discarded=array([], dtype=int64), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([5.36342988, 0.17140117]), radius=0.00456086422313106, bounds=Bounds(lower=array([1.1 , 0.01]), upper=array([20. , 0.99]))), model_indices=array([37, 38, 39]), model=ScalarModel(intercept=0.2423113173928428, linear_terms=array([1.93621445e-05, 1.20738405e-04]), square_terms=array([[6.05669989e-07, 1.43497719e-05], + [1.43497719e-05, 1.80621102e-03]]), scale=0.00456086422313106, shift=array([5.36342988, 0.17140117])), vector_model=VectorModel(intercepts=array([ 0.04097031, 0.08957803, 0.08816081, 0.11232093, 0.12575895, + 0.13980376, 0.15781889, 0.17546538, 0.09348822, 0.15053254, + -0.17880431, -0.21077511, -0.08570458, -0.06416478, -0.05745986, + -0.05902133, -0.05316704]), linear_terms=array([[0., 0.], [0., 0.], [0., 0.], [0., 0.], @@ -437,11 +2046,11 @@ algorithm_output,"{'states': [State(trustregion=Region(center=array([3.46495546, [0., 0.]], [[0., 0.], - [0., 0.]]]), scale=0.34649554641078373, shift=array([3.46495546, 0.53111681])), candidate_index=17, candidate_x=array([3.48570373, 0.53850551]), index=0, x=array([3.46495546, 0.53111681]), fval=0.3956242044738288, rho=-1.8762782320552598, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([ 0, 15, 16]), old_indices_discarded=array([], dtype=int64), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([3.46495546, 0.53111681]), radius=0.010827985825336991, bounds=Bounds(lower=array([2., 0.]), upper=array([20. , 0.7]))), model_indices=array([ 0, 16, 17]), model=ScalarModel(intercept=0.3956242044738289, linear_terms=array([ 4.07367956e-05, -1.83671069e-03]), square_terms=array([[1.84435895e-05, 5.41486888e-04], - [5.41486888e-04, 7.61693918e-02]]), scale=0.010827985825336991, shift=array([3.46495546, 0.53111681])), vector_model=VectorModel(intercepts=array([ 0.12634366, 0.23737133, 0.24789398, 0.25225032, 0.22803295, - 0.18688178, 0.14271092, 0.01053395, -0.07344733, 0.01546678, - -0.23684551, -0.16533737, -0.03497767, -0.00162142, 0.01248823, - 0.01256806, 0.01508461]), linear_terms=array([[0., 0.], + [0., 0.]]]), scale=0.5837906205607757, shift=array([5.83790621, 0.17768436])), candidate_index=40, candidate_x=array([5.35886678, 0.17113519]), index=40, x=array([5.35886678, 0.17113519]), fval=0.2422660131172327, rho=2.040639609470749, accepted=True, new_indices=array([], dtype=int64), old_indices_used=array([37, 38, 39]), old_indices_discarded=array([], dtype=int64), step_length=0.004570846223013415, relative_step_length=1.0021886202688801, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([5.35886678, 0.17113519]), radius=0.00912172844626212, bounds=Bounds(lower=array([1.1 , 0.01]), upper=array([20. , 0.99]))), model_indices=array([34, 36, 37, 38, 39, 40]), model=ScalarModel(intercept=0.24230697792475, linear_terms=array([4.91531731e-06, 4.01574216e-04]), square_terms=array([[2.56045838e-06, 6.11904777e-05], + [6.11904777e-05, 7.09374545e-03]]), scale=0.00912172844626212, shift=array([5.35886678, 0.17113519])), vector_model=VectorModel(intercepts=array([ 0.04097031, 0.08957803, 0.08816081, 0.11232093, 0.12575895, + 0.13980376, 0.15781889, 0.17546538, 0.09348822, 0.15053254, + -0.17880431, -0.21077511, -0.08570458, -0.06416478, -0.05745986, + -0.05902133, -0.05316704]), linear_terms=array([[0., 0.], [0., 0.], [0., 0.], [0., 0.], @@ -506,11 +2115,11 @@ algorithm_output,"{'states': [State(trustregion=Region(center=array([3.46495546, [0., 0.]], [[0., 0.], - [0., 0.]]]), scale=0.34649554641078373, shift=array([3.46495546, 0.53111681])), candidate_index=18, candidate_x=array([3.45413018, 0.53145469]), index=0, x=array([3.46495546, 0.53111681]), fval=0.3956242044738288, rho=-1.0824080447097881, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([ 0, 16, 17]), old_indices_discarded=array([], dtype=int64), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([3.46495546, 0.53111681]), radius=0.005413992912668496, bounds=Bounds(lower=array([2., 0.]), upper=array([20. , 0.7]))), model_indices=array([ 0, 17, 18]), model=ScalarModel(intercept=0.3956242044738293, linear_terms=array([-4.32323065e-05, -7.39757806e-04]), square_terms=array([[3.72492981e-06, 8.85042531e-05], - [8.85042531e-05, 1.93125519e-02]]), scale=0.005413992912668496, shift=array([3.46495546, 0.53111681])), vector_model=VectorModel(intercepts=array([ 0.12634366, 0.23737133, 0.24789398, 0.25225032, 0.22803295, - 0.18688178, 0.14271092, 0.01053395, -0.07344733, 0.01546678, - -0.23684551, -0.16533737, -0.03497767, -0.00162142, 0.01248823, - 0.01256806, 0.01508461]), linear_terms=array([[0., 0.], + [0., 0.]]]), scale=0.5837906205607757, shift=array([5.83790621, 0.17768436])), candidate_index=41, candidate_x=array([5.34975553, 0.17069814]), index=40, x=array([5.35886678, 0.17113519]), fval=0.2422660131172327, rho=-1.4993631427071992, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([34, 36, 37, 38, 39, 40]), old_indices_discarded=array([], dtype=int64), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([5.35886678, 0.17113519]), radius=0.00456086422313106, bounds=Bounds(lower=array([1.1 , 0.01]), upper=array([20. , 0.99]))), model_indices=array([37, 39, 40, 41]), model=ScalarModel(intercept=0.24228491419551926, linear_terms=array([8.49239494e-06, 2.39836883e-05]), square_terms=array([[6.14732854e-07, 1.27371737e-05], + [1.27371737e-05, 1.83146540e-03]]), scale=0.00456086422313106, shift=array([5.35886678, 0.17113519])), vector_model=VectorModel(intercepts=array([ 0.04097031, 0.08957803, 0.08816081, 0.11232093, 0.12575895, + 0.13980376, 0.15781889, 0.17546538, 0.09348822, 0.15053254, + -0.17880431, -0.21077511, -0.08570458, -0.06416478, -0.05745986, + -0.05902133, -0.05316704]), linear_terms=array([[0., 0.], [0., 0.], [0., 0.], [0., 0.], @@ -575,11 +2184,11 @@ algorithm_output,"{'states': [State(trustregion=Region(center=array([3.46495546, [0., 0.]], [[0., 0.], - [0., 0.]]]), scale=0.34649554641078373, shift=array([3.46495546, 0.53111681])), candidate_index=19, candidate_x=array([3.47037027, 0.53129903]), index=0, x=array([3.46495546, 0.53111681]), fval=0.3956242044738288, rho=-1.4029450751291208, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([ 0, 17, 18]), old_indices_discarded=array([], dtype=int64), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([3.46495546, 0.53111681]), radius=0.002706996456334248, bounds=Bounds(lower=array([2., 0.]), upper=array([20. , 0.7]))), model_indices=array([ 0, 18, 19]), model=ScalarModel(intercept=0.39562420447382884, linear_terms=array([7.88883877e-06, 5.75417387e-04]), square_terms=array([[1.03638106e-06, 3.35311076e-05], - [3.35311076e-05, 5.45100791e-03]]), scale=0.002706996456334248, shift=array([3.46495546, 0.53111681])), vector_model=VectorModel(intercepts=array([ 0.12634366, 0.23737133, 0.24789398, 0.25225032, 0.22803295, - 0.18688178, 0.14271092, 0.01053395, -0.07344733, 0.01546678, - -0.23684551, -0.16533737, -0.03497767, -0.00162142, 0.01248823, - 0.01256806, 0.01508461]), linear_terms=array([[0., 0.], + [0., 0.]]]), scale=0.5837906205607757, shift=array([5.83790621, 0.17768436])), candidate_index=42, candidate_x=array([5.35430561, 0.1711073 ]), index=42, x=array([5.35430561, 0.1711073 ]), fval=0.2422367332032626, rho=3.562002347325252, accepted=True, new_indices=array([], dtype=int64), old_indices_used=array([37, 39, 40, 41]), old_indices_discarded=array([], dtype=int64), step_length=0.004561249312406207, relative_step_length=1.0000844334004055, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([5.35430561, 0.1711073 ]), radius=0.00912172844626212, bounds=Bounds(lower=array([1.1 , 0.01]), upper=array([20. , 0.99]))), model_indices=array([34, 36, 37, 38, 39, 40, 41, 42]), model=ScalarModel(intercept=0.24229278798868248, linear_terms=array([5.19719019e-06, 3.68333221e-04]), square_terms=array([[2.55059029e-06, 6.04556474e-05], + [6.04556474e-05, 7.06166757e-03]]), scale=0.00912172844626212, shift=array([5.35430561, 0.1711073 ])), vector_model=VectorModel(intercepts=array([ 0.04097031, 0.08957803, 0.08816081, 0.11232093, 0.12575895, + 0.13980376, 0.15781889, 0.17546538, 0.09348822, 0.15053254, + -0.17880431, -0.21077511, -0.08570458, -0.06416478, -0.05745986, + -0.05902133, -0.05316704]), linear_terms=array([[0., 0.], [0., 0.], [0., 0.], [0., 0.], @@ -644,11 +2253,11 @@ algorithm_output,"{'states': [State(trustregion=Region(center=array([3.46495546, [0., 0.]], [[0., 0.], - [0., 0.]]]), scale=0.34649554641078373, shift=array([3.46495546, 0.53111681])), candidate_index=20, candidate_x=array([3.4622482 , 0.53084788]), index=0, x=array([3.46495546, 0.53111681]), fval=0.3956242044738288, rho=-3.071032863387669, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([ 0, 18, 19]), old_indices_discarded=array([], dtype=int64), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([3.46495546, 0.53111681]), radius=0.001353498228167124, bounds=Bounds(lower=array([2., 0.]), upper=array([20. , 0.7]))), model_indices=array([ 0, 19, 20]), model=ScalarModel(intercept=0.39562420447382896, linear_terms=array([ 3.95806434e-05, -7.71242464e-04]), square_terms=array([[2.52497796e-07, 7.82520747e-06], - [7.82520747e-06, 1.40171465e-03]]), scale=0.001353498228167124, shift=array([3.46495546, 0.53111681])), vector_model=VectorModel(intercepts=array([ 0.12634366, 0.23737133, 0.24789398, 0.25225032, 0.22803295, - 0.18688178, 0.14271092, 0.01053395, -0.07344733, 0.01546678, - -0.23684551, -0.16533737, -0.03497767, -0.00162142, 0.01248823, - 0.01256806, 0.01508461]), linear_terms=array([[0., 0.], + [0., 0.]]]), scale=0.5837906205607757, shift=array([5.83790621, 0.17768436])), candidate_index=43, candidate_x=array([5.3451353 , 0.17071002]), index=42, x=array([5.35430561, 0.1711073 ]), fval=0.2422367332032626, rho=-3.526203505209563, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([34, 36, 37, 38, 39, 40, 41, 42]), old_indices_discarded=array([], dtype=int64), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([5.35430561, 0.1711073 ]), radius=0.00456086422313106, bounds=Bounds(lower=array([1.1 , 0.01]), upper=array([20. , 0.99]))), model_indices=array([37, 39, 40, 41, 42, 43]), model=ScalarModel(intercept=0.24226761562351934, linear_terms=array([ 9.11408781e-06, -4.65800448e-05]), square_terms=array([[6.22234181e-07, 1.39495570e-05], + [1.39495570e-05, 1.81742371e-03]]), scale=0.00456086422313106, shift=array([5.35430561, 0.1711073 ])), vector_model=VectorModel(intercepts=array([ 0.04097031, 0.08957803, 0.08816081, 0.11232093, 0.12575895, + 0.13980376, 0.15781889, 0.17546538, 0.09348822, 0.15053254, + -0.17880431, -0.21077511, -0.08570458, -0.06416478, -0.05745986, + -0.05902133, -0.05316704]), linear_terms=array([[0., 0.], [0., 0.], [0., 0.], [0., 0.], @@ -713,11 +2322,11 @@ algorithm_output,"{'states': [State(trustregion=Region(center=array([3.46495546, [0., 0.]], [[0., 0.], - [0., 0.]]]), scale=0.34649554641078373, shift=array([3.46495546, 0.53111681])), candidate_index=21, candidate_x=array([3.46380251, 0.53184152]), index=0, x=array([3.46495546, 0.53111681]), fval=0.3956242044738288, rho=-1.2094240011644295, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([ 0, 19, 20]), old_indices_discarded=array([], dtype=int64), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([3.46495546, 0.53111681]), radius=0.000676749114083562, bounds=Bounds(lower=array([2., 0.]), upper=array([20. , 0.7]))), model_indices=array([ 0, 20, 21]), model=ScalarModel(intercept=0.39562420447382907, linear_terms=array([-2.47391859e-05, 6.26517286e-05]), square_terms=array([[7.13464682e-08, 2.31692454e-06], - [2.31692454e-06, 3.42334740e-04]]), scale=0.000676749114083562, shift=array([3.46495546, 0.53111681])), vector_model=VectorModel(intercepts=array([ 0.12634366, 0.23737133, 0.24789398, 0.25225032, 0.22803295, - 0.18688178, 0.14271092, 0.01053395, -0.07344733, 0.01546678, - -0.23684551, -0.16533737, -0.03497767, -0.00162142, 0.01248823, - 0.01256806, 0.01508461]), linear_terms=array([[0., 0.], + [0., 0.]]]), scale=0.5837906205607757, shift=array([5.83790621, 0.17768436])), candidate_index=44, candidate_x=array([5.34974579, 0.17125845]), index=42, x=array([5.35430561, 0.1711073 ]), fval=0.2422367332032626, rho=-6.3021226718174725, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([37, 39, 40, 41, 42, 43]), old_indices_discarded=array([], dtype=int64), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([5.35430561, 0.1711073 ]), radius=0.00228043211156553, bounds=Bounds(lower=array([1.1 , 0.01]), upper=array([20. , 0.99]))), model_indices=array([37, 39, 40, 41, 42, 43, 44]), model=ScalarModel(intercept=0.24227590126096604, linear_terms=array([1.99857765e-06, 8.90347166e-06]), square_terms=array([[1.57449078e-07, 3.62430439e-06], + [3.62430439e-06, 4.50545254e-04]]), scale=0.00228043211156553, shift=array([5.35430561, 0.1711073 ])), vector_model=VectorModel(intercepts=array([ 0.04097031, 0.08957803, 0.08816081, 0.11232093, 0.12575895, + 0.13980376, 0.15781889, 0.17546538, 0.09348822, 0.15053254, + -0.17880431, -0.21077511, -0.08570458, -0.06416478, -0.05745986, + -0.05902133, -0.05316704]), linear_terms=array([[0., 0.], [0., 0.], [0., 0.], [0., 0.], @@ -782,11 +2391,11 @@ algorithm_output,"{'states': [State(trustregion=Region(center=array([3.46495546, [0., 0.]], [[0., 0.], - [0., 0.]]]), scale=0.34649554641078373, shift=array([3.46495546, 0.53111681])), candidate_index=22, candidate_x=array([3.46563142, 0.53099715]), index=0, x=array([3.46495546, 0.53111681]), fval=0.3956242044738288, rho=-1.5213482982504996, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([ 0, 20, 21]), old_indices_discarded=array([], dtype=int64), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([3.46495546, 0.53111681]), radius=0.000338374557041781, bounds=Bounds(lower=array([2., 0.]), upper=array([20. , 0.7]))), model_indices=array([ 0, 21, 22]), model=ScalarModel(intercept=0.3956242044738295, linear_terms=array([4.17314453e-05, 1.17395874e-04]), square_terms=array([[3.64249375e-08, 5.60771045e-07], - [5.60771045e-07, 8.54779012e-05]]), scale=0.000338374557041781, shift=array([3.46495546, 0.53111681])), vector_model=VectorModel(intercepts=array([ 0.12634366, 0.23737133, 0.24789398, 0.25225032, 0.22803295, - 0.18688178, 0.14271092, 0.01053395, -0.07344733, 0.01546678, - -0.23684551, -0.16533737, -0.03497767, -0.00162142, 0.01248823, - 0.01256806, 0.01508461]), linear_terms=array([[0., 0.], + [0., 0.]]]), scale=0.5837906205607757, shift=array([5.83790621, 0.17768436])), candidate_index=45, candidate_x=array([5.3520249 , 0.17108069]), index=42, x=array([5.35430561, 0.1711073 ]), fval=0.2422367332032626, rho=-2.3278538400000417, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([37, 39, 40, 41, 42, 43, 44]), old_indices_discarded=array([], dtype=int64), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([5.35430561, 0.1711073 ]), radius=0.001140216055782765, bounds=Bounds(lower=array([1.1 , 0.01]), upper=array([20. , 0.99]))), model_indices=array([39, 40, 41, 42, 44, 45]), model=ScalarModel(intercept=0.2422604755293883, linear_terms=array([-2.61201951e-06, -1.20401397e-05]), square_terms=array([[4.05327539e-08, 9.79447033e-07], + [9.79447033e-07, 1.12921382e-04]]), scale=0.001140216055782765, shift=array([5.35430561, 0.1711073 ])), vector_model=VectorModel(intercepts=array([ 0.04097031, 0.08957803, 0.08816081, 0.11232093, 0.12575895, + 0.13980376, 0.15781889, 0.17546538, 0.09348822, 0.15053254, + -0.17880431, -0.21077511, -0.08570458, -0.06416478, -0.05745986, + -0.05902133, -0.05316704]), linear_terms=array([[0., 0.], [0., 0.], [0., 0.], [0., 0.], @@ -851,11 +2460,11 @@ algorithm_output,"{'states': [State(trustregion=Region(center=array([3.46495546, [0., 0.]], [[0., 0.], - [0., 0.]]]), scale=0.34649554641078373, shift=array([3.46495546, 0.53111681])), candidate_index=23, candidate_x=array([3.46471212, 0.53088169]), index=0, x=array([3.46495546, 0.53111681]), fval=0.3956242044738288, rho=-0.7314294930171341, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([ 0, 21, 22]), old_indices_discarded=array([], dtype=int64), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([3.46495546, 0.53111681]), radius=0.0001691872785208905, bounds=Bounds(lower=array([2., 0.]), upper=array([20. , 0.7]))), model_indices=array([ 0, 22, 23]), model=ScalarModel(intercept=0.39562420447382884, linear_terms=array([ 3.96412519e-06, -3.67838187e-05]), square_terms=array([[4.68995790e-09, 1.27645371e-07], - [1.27645371e-07, 2.13686504e-05]]), scale=0.0001691872785208905, shift=array([3.46495546, 0.53111681])), vector_model=VectorModel(intercepts=array([ 0.12634366, 0.23737133, 0.24789398, 0.25225032, 0.22803295, - 0.18688178, 0.14271092, 0.01053395, -0.07344733, 0.01546678, - -0.23684551, -0.16533737, -0.03497767, -0.00162142, 0.01248823, - 0.01256806, 0.01508461]), linear_terms=array([[0., 0.], + [0., 0.]]]), scale=0.5837906205607757, shift=array([5.83790621, 0.17768436])), candidate_index=46, candidate_x=array([5.35544682, 0.17121658]), index=42, x=array([5.35430561, 0.1711073 ]), fval=0.2422367332032626, rho=-6.392707920855079, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([39, 40, 41, 42, 44, 45]), old_indices_discarded=array([], dtype=int64), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([5.35430561, 0.1711073 ]), radius=0.0005701080278913825, bounds=Bounds(lower=array([1.1 , 0.01]), upper=array([20. , 0.99]))), model_indices=array([39, 42, 45, 46]), model=ScalarModel(intercept=0.24224718857995056, linear_terms=array([ 2.51070195e-06, -1.40348420e-05]), square_terms=array([[9.89078864e-09, 2.54954799e-07], + [2.54954799e-07, 2.83831506e-05]]), scale=0.0005701080278913825, shift=array([5.35430561, 0.1711073 ])), vector_model=VectorModel(intercepts=array([ 0.04097031, 0.08957803, 0.08816081, 0.11232093, 0.12575895, + 0.13980376, 0.15781889, 0.17546538, 0.09348822, 0.15053254, + -0.17880431, -0.21077511, -0.08570458, -0.06416478, -0.05745986, + -0.05902133, -0.05316704]), linear_terms=array([[0., 0.], [0., 0.], [0., 0.], [0., 0.], @@ -920,11 +2529,11 @@ algorithm_output,"{'states': [State(trustregion=Region(center=array([3.46495546, [0., 0.]], [[0., 0.], - [0., 0.]]]), scale=0.34649554641078373, shift=array([3.46495546, 0.53111681])), candidate_index=24, candidate_x=array([3.46489062, 0.53127308]), index=0, x=array([3.46495546, 0.53111681]), fval=0.3956242044738288, rho=-0.6471968813314769, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([ 0, 22, 23]), old_indices_discarded=array([], dtype=int64), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([3.46495546, 0.53111681]), radius=8.459363926044525e-05, bounds=Bounds(lower=array([2., 0.]), upper=array([20. , 0.7]))), model_indices=array([ 0, 23, 24]), model=ScalarModel(intercept=0.3956242044738286, linear_terms=array([-1.43573588e-05, -1.48085006e-06]), square_terms=array([[4.31731173e-09, 7.89922153e-08], - [7.89922153e-08, 5.24133786e-06]]), scale=8.459363926044525e-05, shift=array([3.46495546, 0.53111681])), vector_model=VectorModel(intercepts=array([ 0.12634366, 0.23737133, 0.24789398, 0.25225032, 0.22803295, - 0.18688178, 0.14271092, 0.01053395, -0.07344733, 0.01546678, - -0.23684551, -0.16533737, -0.03497767, -0.00162142, 0.01248823, - 0.01256806, 0.01508461]), linear_terms=array([[0., 0.], + [0., 0.]]]), scale=0.5837906205607757, shift=array([5.83790621, 0.17768436])), candidate_index=47, candidate_x=array([5.35373784, 0.17136997]), index=42, x=array([5.35430561, 0.1711073 ]), fval=0.2422367332032626, rho=-9.761421022287955, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([39, 42, 45, 46]), old_indices_discarded=array([], dtype=int64), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([5.35430561, 0.1711073 ]), radius=0.00028505401394569125, bounds=Bounds(lower=array([1.1 , 0.01]), upper=array([20. , 0.99]))), model_indices=array([39, 42, 46, 47]), model=ScalarModel(intercept=0.2422674286871516, linear_terms=array([-4.83904426e-06, -1.53169699e-06]), square_terms=array([[3.15265250e-09, 9.17365476e-08], + [9.17365476e-08, 7.04918151e-06]]), scale=0.00028505401394569125, shift=array([5.35430561, 0.1711073 ])), vector_model=VectorModel(intercepts=array([ 0.04097031, 0.08957803, 0.08816081, 0.11232093, 0.12575895, + 0.13980376, 0.15781889, 0.17546538, 0.09348822, 0.15053254, + -0.17880431, -0.21077511, -0.08570458, -0.06416478, -0.05745986, + -0.05902133, -0.05316704]), linear_terms=array([[0., 0.], [0., 0.], [0., 0.], [0., 0.], @@ -989,11 +2598,11 @@ algorithm_output,"{'states': [State(trustregion=Region(center=array([3.46495546, [0., 0.]], [[0., 0.], - [0., 0.]]]), scale=0.34649554641078373, shift=array([3.46495546, 0.53111681])), candidate_index=25, candidate_x=array([3.46503985, 0.53112285]), index=0, x=array([3.46495546, 0.53111681]), fval=0.3956242044738288, rho=-0.6093566693728825, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([ 0, 23, 24]), old_indices_discarded=array([], dtype=int64), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([3.46495546, 0.53111681]), radius=4.229681963022262e-05, bounds=Bounds(lower=array([2., 0.]), upper=array([20. , 0.7]))), model_indices=array([ 0, 24, 25]), model=ScalarModel(intercept=0.39562420447382896, linear_terms=array([4.10906912e-06, 3.94319598e-06]), square_terms=array([[4.31197929e-10, 1.14627443e-08], - [1.14627443e-08, 1.30357041e-06]]), scale=4.229681963022262e-05, shift=array([3.46495546, 0.53111681])), vector_model=VectorModel(intercepts=array([ 0.12634366, 0.23737133, 0.24789398, 0.25225032, 0.22803295, - 0.18688178, 0.14271092, 0.01053395, -0.07344733, 0.01546678, - -0.23684551, -0.16533737, -0.03497767, -0.00162142, 0.01248823, - 0.01256806, 0.01508461]), linear_terms=array([[0., 0.], + [0., 0.]]]), scale=0.5837906205607757, shift=array([5.83790621, 0.17768436])), candidate_index=48, candidate_x=array([5.35459114, 0.17114189]), index=42, x=array([5.35430561, 0.1711073 ]), fval=0.2422367332032626, rho=-1.76601101681869, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([39, 42, 46, 47]), old_indices_discarded=array([], dtype=int64), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([5.35430561, 0.1711073 ]), radius=0.00014252700697284563, bounds=Bounds(lower=array([1.1 , 0.01]), upper=array([20. , 0.99]))), model_indices=array([42, 47, 48]), model=ScalarModel(intercept=0.24223673320326256, linear_terms=array([5.02372003e-07, 3.17577167e-05]), square_terms=array([[7.11686537e-10, 2.09000216e-08], + [2.09000216e-08, 1.66981772e-06]]), scale=0.00014252700697284563, shift=array([5.35430561, 0.1711073 ])), vector_model=VectorModel(intercepts=array([ 0.04097031, 0.08957803, 0.08816081, 0.11232093, 0.12575895, + 0.13980376, 0.15781889, 0.17546538, 0.09348822, 0.15053254, + -0.17880431, -0.21077511, -0.08570458, -0.06416478, -0.05745986, + -0.05902133, -0.05316704]), linear_terms=array([[0., 0.], [0., 0.], [0., 0.], [0., 0.], @@ -1058,11 +2667,11 @@ algorithm_output,"{'states': [State(trustregion=Region(center=array([3.46495546, [0., 0.]], [[0., 0.], - [0., 0.]]]), scale=0.34649554641078373, shift=array([3.46495546, 0.53111681])), candidate_index=26, candidate_x=array([3.46492081, 0.53109043]), index=26, x=array([3.46492081, 0.53109043]), fval=0.39561894207152565, rho=0.945446153415508, accepted=True, new_indices=array([], dtype=int64), old_indices_used=array([ 0, 24, 25]), old_indices_discarded=array([], dtype=int64), step_length=4.3549735239972725e-05, relative_step_length=1.0296219815273024, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([3.46492081, 0.53109043]), radius=8.459363926044525e-05, bounds=Bounds(lower=array([2., 0.]), upper=array([20. , 0.7]))), model_indices=array([ 0, 23, 24, 25, 26]), model=ScalarModel(intercept=0.395634570533063, linear_terms=array([-8.04050131e-06, -5.94565060e-06]), square_terms=array([[2.94137802e-09, 6.60314146e-08], - [6.60314146e-08, 5.25498164e-06]]), scale=8.459363926044525e-05, shift=array([3.46492081, 0.53109043])), vector_model=VectorModel(intercepts=array([ 0.12634366, 0.23737133, 0.24789398, 0.25225032, 0.22803295, - 0.18688178, 0.14271092, 0.01053395, -0.07344733, 0.01546678, - -0.23684551, -0.16533737, -0.03497767, -0.00162142, 0.01248823, - 0.01256806, 0.01508461]), linear_terms=array([[0., 0.], + [0., 0.]]]), scale=0.5837906205607757, shift=array([5.83790621, 0.17768436])), candidate_index=49, candidate_x=array([5.35430724, 0.17096478]), index=42, x=array([5.35430561, 0.1711073 ]), fval=0.2422367332032626, rho=-0.0087460529528702, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([42, 47, 48]), old_indices_discarded=array([], dtype=int64), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([5.35430561, 0.1711073 ]), radius=7.126350348642281e-05, bounds=Bounds(lower=array([1.1 , 0.01]), upper=array([20. , 0.99]))), model_indices=array([42, 48, 49]), model=ScalarModel(intercept=0.24223673320326244, linear_terms=array([2.13529941e-06, 3.25430275e-07]), square_terms=array([[1.72071804e-10, 4.10474480e-09], + [4.10474480e-09, 4.36348657e-07]]), scale=7.126350348642281e-05, shift=array([5.35430561, 0.1711073 ])), vector_model=VectorModel(intercepts=array([ 0.04097031, 0.08957803, 0.08816081, 0.11232093, 0.12575895, + 0.13980376, 0.15781889, 0.17546538, 0.09348822, 0.15053254, + -0.17880431, -0.21077511, -0.08570458, -0.06416478, -0.05745986, + -0.05902133, -0.05316704]), linear_terms=array([[0., 0.], [0., 0.], [0., 0.], [0., 0.], @@ -1127,11 +2736,11 @@ algorithm_output,"{'states': [State(trustregion=Region(center=array([3.46495546, [0., 0.]], [[0., 0.], - [0., 0.]]]), scale=0.34649554641078373, shift=array([3.46495546, 0.53111681])), candidate_index=27, candidate_x=array([3.46499781, 0.53112586]), index=26, x=array([3.46492081, 0.53109043]), fval=0.39561894207152565, rho=-1.9757700237645563, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([ 0, 23, 24, 25, 26]), old_indices_discarded=array([], dtype=int64), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([3.46492081, 0.53109043]), radius=4.229681963022262e-05, bounds=Bounds(lower=array([2., 0.]), upper=array([20. , 0.7]))), model_indices=array([ 0, 24, 25, 26, 27]), model=ScalarModel(intercept=0.39561947944969, linear_terms=array([4.97404407e-06, 3.10920139e-06]), square_terms=array([[1.49952556e-09, 2.29109605e-08], - [2.29109605e-08, 1.32167738e-06]]), scale=4.229681963022262e-05, shift=array([3.46492081, 0.53109043])), vector_model=VectorModel(intercepts=array([ 0.12634366, 0.23737133, 0.24789398, 0.25225032, 0.22803295, - 0.18688178, 0.14271092, 0.01053395, -0.07344733, 0.01546678, - -0.23684551, -0.16533737, -0.03497767, -0.00162142, 0.01248823, - 0.01256806, 0.01508461]), linear_terms=array([[0., 0.], + [0., 0.]]]), scale=0.5837906205607757, shift=array([5.83790621, 0.17768436])), candidate_index=50, candidate_x=array([5.3542349 , 0.17109845]), index=50, x=array([5.3542349 , 0.17109845]), fval=0.24223503271901853, rho=0.788996851874173, accepted=True, new_indices=array([], dtype=int64), old_indices_used=array([42, 48, 49]), old_indices_discarded=array([], dtype=int64), step_length=7.12641605962148e-05, relative_step_length=1.0000092208460127, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([5.3542349 , 0.17109845]), radius=0.00014252700697284563, bounds=Bounds(lower=array([1.1 , 0.01]), upper=array([20. , 0.99]))), model_indices=array([42, 47, 48, 49, 50]), model=ScalarModel(intercept=0.24224492204264927, linear_terms=array([-3.76156364e-06, 1.64186210e-05]), square_terms=array([[9.45521287e-10, 2.62809647e-08], + [2.62809647e-08, 1.70525908e-06]]), scale=0.00014252700697284563, shift=array([5.3542349 , 0.17109845])), vector_model=VectorModel(intercepts=array([ 0.04097031, 0.08957803, 0.08816081, 0.11232093, 0.12575895, + 0.13980376, 0.15781889, 0.17546538, 0.09348822, 0.15053254, + -0.17880431, -0.21077511, -0.08570458, -0.06416478, -0.05745986, + -0.05902133, -0.05316704]), linear_terms=array([[0., 0.], [0., 0.], [0., 0.], [0., 0.], @@ -1196,11 +2805,11 @@ algorithm_output,"{'states': [State(trustregion=Region(center=array([3.46495546, [0., 0.]], [[0., 0.], - [0., 0.]]]), scale=0.34649554641078373, shift=array([3.46495546, 0.53111681])), candidate_index=28, candidate_x=array([3.46488023, 0.53107033]), index=28, x=array([3.46488023, 0.53107033]), fval=0.3956174852241245, rho=0.23924371384284093, accepted=True, new_indices=array([], dtype=int64), old_indices_used=array([ 0, 24, 25, 26, 27]), old_indices_discarded=array([], dtype=int64), step_length=4.528574698820532e-05, relative_step_length=1.0706655342910698, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([3.46488023, 0.53107033]), radius=8.459363926044525e-05, bounds=Bounds(lower=array([2., 0.]), upper=array([20. , 0.7]))), model_indices=array([ 0, 23, 24, 25, 26, 27, 28]), model=ScalarModel(intercept=0.395637640546523, linear_terms=array([-5.47337741e-06, -7.74435957e-06]), square_terms=array([[3.28485118e-09, 7.34686091e-08], - [7.34686091e-08, 5.25424073e-06]]), scale=8.459363926044525e-05, shift=array([3.46488023, 0.53107033])), vector_model=VectorModel(intercepts=array([ 0.12634366, 0.23737133, 0.24789398, 0.25225032, 0.22803295, - 0.18688178, 0.14271092, 0.01053395, -0.07344733, 0.01546678, - -0.23684551, -0.16533737, -0.03497767, -0.00162142, 0.01248823, - 0.01256806, 0.01508461]), linear_terms=array([[0., 0.], + [0., 0.]]]), scale=0.5837906205607757, shift=array([5.83790621, 0.17768436])), candidate_index=51, candidate_x=array([5.35427389, 0.17096136]), index=50, x=array([5.3542349 , 0.17109845]), fval=0.24223503271901853, rho=-0.16458879109056918, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([42, 47, 48, 49, 50]), old_indices_discarded=array([], dtype=int64), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([5.3542349 , 0.17109845]), radius=7.126350348642281e-05, bounds=Bounds(lower=array([1.1 , 0.01]), upper=array([20. , 0.99]))), model_indices=array([42, 49, 50, 51]), model=ScalarModel(intercept=0.2422353089967809, linear_terms=array([ 1.17750480e-06, -1.71985531e-07]), square_terms=array([[1.67731546e-10, 4.23329742e-09], + [4.23329742e-09, 4.36229157e-07]]), scale=7.126350348642281e-05, shift=array([5.3542349 , 0.17109845])), vector_model=VectorModel(intercepts=array([ 0.04097031, 0.08957803, 0.08816081, 0.11232093, 0.12575895, + 0.13980376, 0.15781889, 0.17546538, 0.09348822, 0.15053254, + -0.17880431, -0.21077511, -0.08570458, -0.06416478, -0.05745986, + -0.05902133, -0.05316704]), linear_terms=array([[0., 0.], [0., 0.], [0., 0.], [0., 0.], @@ -1265,11 +2874,11 @@ algorithm_output,"{'states': [State(trustregion=Region(center=array([3.46495546, [0., 0.]], [[0., 0.], - [0., 0.]]]), scale=0.34649554641078373, shift=array([3.46495546, 0.53111681])), candidate_index=29, candidate_x=array([3.4649524, 0.5311263]), index=28, x=array([3.46488023, 0.53107033]), fval=0.3956174852241245, rho=-2.3079169286750476, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([ 0, 23, 24, 25, 26, 27, 28]), old_indices_discarded=array([], dtype=int64), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([3.46488023, 0.53107033]), radius=4.229681963022262e-05, bounds=Bounds(lower=array([2., 0.]), upper=array([20. , 0.7]))), model_indices=array([ 0, 24, 25, 26, 27, 28, 29]), model=ScalarModel(intercept=0.39561746207201964, linear_terms=array([4.33228260e-06, 1.81465673e-06]), square_terms=array([[2.25926255e-09, 3.07816141e-08], - [3.07816141e-08, 1.33239024e-06]]), scale=4.229681963022262e-05, shift=array([3.46488023, 0.53107033])), vector_model=VectorModel(intercepts=array([ 0.12634366, 0.23737133, 0.24789398, 0.25225032, 0.22803295, - 0.18688178, 0.14271092, 0.01053395, -0.07344733, 0.01546678, - -0.23684551, -0.16533737, -0.03497767, -0.00162142, 0.01248823, - 0.01256806, 0.01508461]), linear_terms=array([[0., 0.], + [0., 0.]]]), scale=0.5837906205607757, shift=array([5.83790621, 0.17768436])), candidate_index=52, candidate_x=array([5.35416406, 0.1711062 ]), index=50, x=array([5.3542349 , 0.17109845]), fval=0.24223503271901853, rho=-1.5548413629872948, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([42, 49, 50, 51]), old_indices_discarded=array([], dtype=int64), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([5.3542349 , 0.17109845]), radius=3.563175174321141e-05, bounds=Bounds(lower=array([1.1 , 0.01]), upper=array([20. , 0.99]))), model_indices=array([42, 49, 50, 51, 52]), model=ScalarModel(intercept=0.24223624887821155, linear_terms=array([-5.72724933e-08, -9.62016662e-08]), square_terms=array([[4.08764832e-11, 1.01998995e-09], + [1.01998995e-09, 1.09056071e-07]]), scale=3.563175174321141e-05, shift=array([5.3542349 , 0.17109845])), vector_model=VectorModel(intercepts=array([ 0.04097031, 0.08957803, 0.08816081, 0.11232093, 0.12575895, + 0.13980376, 0.15781889, 0.17546538, 0.09348822, 0.15053254, + -0.17880431, -0.21077511, -0.08570458, -0.06416478, -0.05745986, + -0.05902133, -0.05316704]), linear_terms=array([[0., 0.], [0., 0.], [0., 0.], [0., 0.], @@ -1334,11 +2943,11 @@ algorithm_output,"{'states': [State(trustregion=Region(center=array([3.46495546, [0., 0.]], [[0., 0.], - [0., 0.]]]), scale=0.34649554641078373, shift=array([3.46495546, 0.53111681])), candidate_index=30, candidate_x=array([3.46483993, 0.53105746]), index=28, x=array([3.46488023, 0.53107033]), fval=0.3956174852241245, rho=-1.7965848703934482, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([ 0, 24, 25, 26, 27, 28, 29]), old_indices_discarded=array([], dtype=int64), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([3.46488023, 0.53107033]), radius=2.114840981511131e-05, bounds=Bounds(lower=array([2., 0.]), upper=array([20. , 0.7]))), model_indices=array([ 0, 26, 28, 29, 30]), model=ScalarModel(intercept=0.3956181532627989, linear_terms=array([-1.02960929e-05, 1.97454974e-05]), square_terms=array([[1.22430642e-09, 3.27096094e-09], - [3.27096094e-09, 3.60528919e-07]]), scale=2.114840981511131e-05, shift=array([3.46488023, 0.53107033])), vector_model=VectorModel(intercepts=array([ 0.12634366, 0.23737133, 0.24789398, 0.25225032, 0.22803295, - 0.18688178, 0.14271092, 0.01053395, -0.07344733, 0.01546678, - -0.23684551, -0.16533737, -0.03497767, -0.00162142, 0.01248823, - 0.01256806, 0.01508461]), linear_terms=array([[0., 0.], + [0., 0.]]]), scale=0.5837906205607757, shift=array([5.83790621, 0.17768436])), candidate_index=53, candidate_x=array([5.35426853, 0.17111852]), index=50, x=array([5.3542349 , 0.17109845]), fval=0.24223503271901853, rho=-49.234038408931376, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([42, 49, 50, 51, 52]), old_indices_discarded=array([], dtype=int64), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([5.3542349 , 0.17109845]), radius=1.7815875871605703e-05, bounds=Bounds(lower=array([1.1 , 0.01]), upper=array([20. , 0.99]))), model_indices=array([42, 50, 52, 53]), model=ScalarModel(intercept=0.24223497560711219, linear_terms=array([-4.74432307e-08, 4.02785705e-06]), square_terms=array([[1.01749646e-11, 2.52377502e-10], + [2.52377502e-10, 2.76008124e-08]]), scale=1.7815875871605703e-05, shift=array([5.3542349 , 0.17109845])), vector_model=VectorModel(intercepts=array([ 0.04097031, 0.08957803, 0.08816081, 0.11232093, 0.12575895, + 0.13980376, 0.15781889, 0.17546538, 0.09348822, 0.15053254, + -0.17880431, -0.21077511, -0.08570458, -0.06416478, -0.05745986, + -0.05902133, -0.05316704]), linear_terms=array([[0., 0.], [0., 0.], [0., 0.], [0., 0.], @@ -1403,11 +3012,11 @@ algorithm_output,"{'states': [State(trustregion=Region(center=array([3.46495546, [0., 0.]], [[0., 0.], - [0., 0.]]]), scale=0.34649554641078373, shift=array([3.46495546, 0.53111681])), candidate_index=31, candidate_x=array([3.46489016, 0.53105165]), index=28, x=array([3.46488023, 0.53107033]), fval=0.3956174852241245, rho=-0.6032905672690827, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([ 0, 26, 28, 29, 30]), old_indices_discarded=array([], dtype=int64), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([3.46488023, 0.53107033]), radius=1.0574204907555656e-05, bounds=Bounds(lower=array([2., 0.]), upper=array([20. , 0.7]))), model_indices=array([26, 28, 30, 31]), model=ScalarModel(intercept=0.3956218068343813, linear_terms=array([ 8.49414347e-07, -4.25281774e-06]), square_terms=array([[6.27885661e-11, 1.47178033e-09], - [1.47178033e-09, 8.86369949e-08]]), scale=1.0574204907555656e-05, shift=array([3.46488023, 0.53107033])), vector_model=VectorModel(intercepts=array([ 0.12634366, 0.23737133, 0.24789398, 0.25225032, 0.22803295, - 0.18688178, 0.14271092, 0.01053395, -0.07344733, 0.01546678, - -0.23684551, -0.16533737, -0.03497767, -0.00162142, 0.01248823, - 0.01256806, 0.01508461]), linear_terms=array([[0., 0.], + [0., 0.]]]), scale=0.5837906205607757, shift=array([5.83790621, 0.17768436])), candidate_index=54, candidate_x=array([5.35423517, 0.17108064]), index=54, x=array([5.35423517, 0.17108064]), fval=0.24223166413037348, rho=0.8391433969707881, accepted=True, new_indices=array([], dtype=int64), old_indices_used=array([42, 50, 52, 53]), old_indices_discarded=array([], dtype=int64), step_length=1.7815875871611863e-05, relative_step_length=1.0000000000003457, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([5.35423517, 0.17108064]), radius=3.563175174321141e-05, bounds=Bounds(lower=array([1.1 , 0.01]), upper=array([20. , 0.99]))), model_indices=array([42, 49, 50, 51, 52, 53, 54]), model=ScalarModel(intercept=0.24223597836991295, linear_terms=array([4.47141236e-07, 1.37410695e-07]), square_terms=array([[4.06123488e-11, 1.05080752e-09], + [1.05080752e-09, 1.09096371e-07]]), scale=3.563175174321141e-05, shift=array([5.35423517, 0.17108064])), vector_model=VectorModel(intercepts=array([ 0.04097031, 0.08957803, 0.08816081, 0.11232093, 0.12575895, + 0.13980376, 0.15781889, 0.17546538, 0.09348822, 0.15053254, + -0.17880431, -0.21077511, -0.08570458, -0.06416478, -0.05745986, + -0.05902133, -0.05316704]), linear_terms=array([[0., 0.], [0., 0.], [0., 0.], [0., 0.], @@ -1472,11 +3081,11 @@ algorithm_output,"{'states': [State(trustregion=Region(center=array([3.46495546, [0., 0.]], [[0., 0.], - [0., 0.]]]), scale=0.34649554641078373, shift=array([3.46495546, 0.53111681])), candidate_index=32, candidate_x=array([3.46487805, 0.53108067]), index=32, x=array([3.46487805, 0.53108067]), fval=0.39561434141034263, rho=0.7320668912639801, accepted=True, new_indices=array([], dtype=int64), old_indices_used=array([26, 28, 30, 31]), old_indices_discarded=array([], dtype=int64), step_length=1.0574204907534214e-05, relative_step_length=0.9999999999979723, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([3.46487805, 0.53108067]), radius=2.114840981511131e-05, bounds=Bounds(lower=array([2., 0.]), upper=array([20. , 0.7]))), model_indices=array([ 0, 26, 28, 29, 30, 31, 32]), model=ScalarModel(intercept=0.39562151267207407, linear_terms=array([ 2.2572996e-06, -1.4393150e-06]), square_terms=array([[2.89592558e-10, 5.93358722e-09], - [5.93358722e-09, 3.53991775e-07]]), scale=2.114840981511131e-05, shift=array([3.46487805, 0.53108067])), vector_model=VectorModel(intercepts=array([ 0.12634366, 0.23737133, 0.24789398, 0.25225032, 0.22803295, - 0.18688178, 0.14271092, 0.01053395, -0.07344733, 0.01546678, - -0.23684551, -0.16533737, -0.03497767, -0.00162142, 0.01248823, - 0.01256806, 0.01508461]), linear_terms=array([[0., 0.], + [0., 0.]]]), scale=0.5837906205607757, shift=array([5.83790621, 0.17768436])), candidate_index=55, candidate_x=array([5.35420058, 0.1710721 ]), index=55, x=array([5.35420058, 0.1710721 ]), fval=0.24223019482007688, rho=3.168897351422072, accepted=True, new_indices=array([], dtype=int64), old_indices_used=array([42, 49, 50, 51, 52, 53, 54]), old_indices_discarded=array([], dtype=int64), step_length=3.563336405853496e-05, relative_step_length=1.0000452493982102, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([5.35420058, 0.1710721 ]), radius=7.126350348642281e-05, bounds=Bounds(lower=array([1.1 , 0.01]), upper=array([20. , 0.99]))), model_indices=array([42, 49, 50, 51, 52, 53, 54, 55]), model=ScalarModel(intercept=0.24223407516118386, linear_terms=array([2.08971335e-06, 5.06945130e-07]), square_terms=array([[1.70894503e-10, 4.32417031e-09], + [4.32417031e-09, 4.36442958e-07]]), scale=7.126350348642281e-05, shift=array([5.35420058, 0.1710721 ])), vector_model=VectorModel(intercepts=array([ 0.04097031, 0.08957803, 0.08816081, 0.11232093, 0.12575895, + 0.13980376, 0.15781889, 0.17546538, 0.09348822, 0.15053254, + -0.17880431, -0.21077511, -0.08570458, -0.06416478, -0.05745986, + -0.05902133, -0.05316704]), linear_terms=array([[0., 0.], [0., 0.], [0., 0.], [0., 0.], @@ -1541,11 +3150,11 @@ algorithm_output,"{'states': [State(trustregion=Region(center=array([3.46495546, [0., 0.]], [[0., 0.], - [0., 0.]]]), scale=0.34649554641078373, shift=array([3.46495546, 0.53111681])), candidate_index=33, candidate_x=array([3.4648589 , 0.53109139]), index=32, x=array([3.46487805, 0.53108067]), fval=0.39561434141034263, rho=-1.623253391085488, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([ 0, 26, 28, 29, 30, 31, 32]), old_indices_discarded=array([], dtype=int64), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([3.46487805, 0.53108067]), radius=1.0574204907555656e-05, bounds=Bounds(lower=array([2., 0.]), upper=array([20. , 0.7]))), model_indices=array([26, 28, 30, 31, 32, 33]), model=ScalarModel(intercept=0.3956188473763767, linear_terms=array([ 2.78366342e-07, -3.10528724e-06]), square_terms=array([[2.68451586e-11, 9.59160265e-10], - [9.59160265e-10, 9.09248316e-08]]), scale=1.0574204907555656e-05, shift=array([3.46487805, 0.53108067])), vector_model=VectorModel(intercepts=array([ 0.12634366, 0.23737133, 0.24789398, 0.25225032, 0.22803295, - 0.18688178, 0.14271092, 0.01053395, -0.07344733, 0.01546678, - -0.23684551, -0.16533737, -0.03497767, -0.00162142, 0.01248823, - 0.01256806, 0.01508461]), linear_terms=array([[0., 0.], + [0., 0.]]]), scale=0.5837906205607757, shift=array([5.83790621, 0.17768436])), candidate_index=56, candidate_x=array([5.35413069, 0.17105814]), index=56, x=array([5.35413069, 0.17105814]), fval=0.24222785386695275, rho=1.0942674916087185, accepted=True, new_indices=array([], dtype=int64), old_indices_used=array([42, 49, 50, 51, 52, 53, 54, 55]), old_indices_discarded=array([], dtype=int64), step_length=7.126490760503242e-05, relative_step_length=1.0000197031936533, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([5.35413069, 0.17105814]), radius=0.00014252700697284563, bounds=Bounds(lower=array([1.1 , 0.01]), upper=array([20. , 0.99]))), model_indices=array([42, 49, 50, 51, 52, 53, 54, 55, 56]), model=ScalarModel(intercept=0.24222977403320833, linear_terms=array([6.45945040e-06, 1.64764211e-06]), square_terms=array([[7.69583087e-10, 1.76987495e-08], + [1.76987495e-08, 1.74604758e-06]]), scale=0.00014252700697284563, shift=array([5.35413069, 0.17105814])), vector_model=VectorModel(intercepts=array([ 0.04097031, 0.08957803, 0.08816081, 0.11232093, 0.12575895, + 0.13980376, 0.15781889, 0.17546538, 0.09348822, 0.15053254, + -0.17880431, -0.21077511, -0.08570458, -0.06416478, -0.05745986, + -0.05902133, -0.05316704]), linear_terms=array([[0., 0.], [0., 0.], [0., 0.], [0., 0.], @@ -1610,11 +3219,11 @@ algorithm_output,"{'states': [State(trustregion=Region(center=array([3.46495546, [0., 0.]], [[0., 0.], - [0., 0.]]]), scale=0.34649554641078373, shift=array([3.46495546, 0.53111681])), candidate_index=34, candidate_x=array([3.46487695, 0.53109119]), index=32, x=array([3.46487805, 0.53108067]), fval=0.39561434141034263, rho=-1.4578840149671246, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([26, 28, 30, 31, 32, 33]), old_indices_discarded=array([], dtype=int64), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([3.46487805, 0.53108067]), radius=5.287102453777828e-06, bounds=Bounds(lower=array([2., 0.]), upper=array([20. , 0.7]))), model_indices=array([28, 32, 33, 34]), model=ScalarModel(intercept=0.39561689494513136, linear_terms=array([-3.07255257e-07, 3.15050176e-07]), square_terms=array([[8.41877738e-12, 1.23132438e-10], - [1.23132438e-10, 2.40117515e-08]]), scale=5.287102453777828e-06, shift=array([3.46487805, 0.53108067])), vector_model=VectorModel(intercepts=array([ 0.12634366, 0.23737133, 0.24789398, 0.25225032, 0.22803295, - 0.18688178, 0.14271092, 0.01053395, -0.07344733, 0.01546678, - -0.23684551, -0.16533737, -0.03497767, -0.00162142, 0.01248823, - 0.01256806, 0.01508461]), linear_terms=array([[0., 0.], + [0., 0.]]]), scale=0.5837906205607757, shift=array([5.83790621, 0.17768436])), candidate_index=57, candidate_x=array([5.35399092, 0.17103024]), index=57, x=array([5.35399092, 0.17103024]), fval=0.24222754644165564, rho=0.046437840364656036, accepted=True, new_indices=array([], dtype=int64), old_indices_used=array([42, 49, 50, 51, 52, 53, 54, 55, 56]), old_indices_discarded=array([47, 48]), step_length=0.0001425347086457425, relative_step_length=1.0000540365861912, n_evals_per_point=1, n_evals_acceptance=1)], 'tranquilo_history': History for least_squares function with 58 entries., 'multistart_info': {'start_parameters': [array([5.35400632, 0.17100463]), array([5.83790621, 0.17768436])], 'local_optima': [{'solution_x': array([5.35396236, 0.17102975]), 'solution_criterion': 0.24222765324129839, 'states': [State(trustregion=Region(center=array([5.35400632, 0.17100463]), radius=0.5354006322483765, bounds=Bounds(lower=array([1.1 , 0.01]), upper=array([20. , 0.99]))), model_indices=[0], model=ScalarModel(intercept=0.24222959010961218, linear_terms=array([0., 0.]), square_terms=array([[0., 0.], + [0., 0.]]), scale=0.5354006322483765, shift=array([5.35400632, 0.17100463])), vector_model=VectorModel(intercepts=array([ 0.03985211, 0.08726933, 0.08463892, 0.10727527, 0.11929469, + 0.13193558, 0.14806457, 0.15973009, 0.07453542, 0.12630368, + -0.21049255, -0.24911785, -0.05784038, -0.03761571, -0.03108242, + -0.03262226, -0.02475777]), linear_terms=array([[0., 0.], [0., 0.], [0., 0.], [0., 0.], @@ -1679,11 +3288,11 @@ algorithm_output,"{'states': [State(trustregion=Region(center=array([3.46495546, [0., 0.]], [[0., 0.], - [0., 0.]]]), scale=0.34649554641078373, shift=array([3.46495546, 0.53111681])), candidate_index=35, candidate_x=array([3.46488185, 0.53107699]), index=32, x=array([3.46487805, 0.53108067]), fval=0.39561434141034263, rho=-1.3868295186228046, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([28, 32, 33, 34]), old_indices_discarded=array([], dtype=int64), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([3.46487805, 0.53108067]), radius=2.643551226888914e-06, bounds=Bounds(lower=array([2., 0.]), upper=array([20. , 0.7]))), model_indices=array([28, 32, 34, 35]), model=ScalarModel(intercept=0.39561680085702, linear_terms=array([-8.88271352e-07, 5.51333878e-08]), square_terms=array([[ 5.09917383e-11, -1.34033240e-10], - [-1.34033240e-10, 5.95211095e-09]]), scale=2.643551226888914e-06, shift=array([3.46487805, 0.53108067])), vector_model=VectorModel(intercepts=array([ 0.12634366, 0.23737133, 0.24789398, 0.25225032, 0.22803295, - 0.18688178, 0.14271092, 0.01053395, -0.07344733, 0.01546678, - -0.23684551, -0.16533737, -0.03497767, -0.00162142, 0.01248823, - 0.01256806, 0.01508461]), linear_terms=array([[0., 0.], + [0., 0.]]]), scale=0.5354006322483765, shift=array([5.35400632, 0.17100463])), candidate_index=0, candidate_x=array([5.35400632, 0.17100463]), index=0, x=array([5.35400632, 0.17100463]), fval=0.24222959010961218, rho=nan, accepted=True, new_indices=[0], old_indices_used=[], old_indices_discarded=[], step_length=None, relative_step_length=None, n_evals_per_point=None, n_evals_acceptance=None), State(trustregion=Region(center=array([5.35400632, 0.17100463]), radius=0.5354006322483765, bounds=Bounds(lower=array([1.1 , 0.01]), upper=array([20. , 0.99]))), model_indices=array([ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12]), model=ScalarModel(intercept=3.4205094337836357, linear_terms=array([-0.2805156 , 11.21176097]), square_terms=array([[ 1.79834702e-02, -4.41911648e-01], + [-4.41911648e-01, 1.94960999e+01]]), scale=array([0.47448646, 0.31774554]), shift=array([5.35400632, 0.32774554])), vector_model=VectorModel(intercepts=array([ 0.03985211, 0.08726933, 0.08463892, 0.10727527, 0.11929469, + 0.13193558, 0.14806457, 0.15973009, 0.07453542, 0.12630368, + -0.21049255, -0.24911785, -0.05784038, -0.03761571, -0.03108242, + -0.03262226, -0.02475777]), linear_terms=array([[0., 0.], [0., 0.], [0., 0.], [0., 0.], @@ -1748,11 +3357,11 @@ algorithm_output,"{'states': [State(trustregion=Region(center=array([3.46495546, [0., 0.]], [[0., 0.], - [0., 0.]]]), scale=0.34649554641078373, shift=array([3.46495546, 0.53111681])), candidate_index=36, candidate_x=array([3.4648807 , 0.53108051]), index=36, x=array([3.4648807 , 0.53108051]), fval=0.3956142498671711, rho=0.10253535956354096, accepted=True, new_indices=array([], dtype=int64), old_indices_used=array([28, 32, 34, 35]), old_indices_discarded=array([], dtype=int64), step_length=2.652048375671223e-06, relative_step_length=1.0032142932188641, n_evals_per_point=1, n_evals_acceptance=1)], 'tranquilo_history': History for least_squares function with 37 entries., 'multistart_info': {'start_parameters': [array([3.46495546, 0.53111681]), array([4.35384656, 0.52929957])], 'local_optima': [{'solution_x': array([3.4648807 , 0.53108051]), 'solution_criterion': 0.3956142498671711, 'states': [State(trustregion=Region(center=array([3.46495546, 0.53111681]), radius=0.34649554641078373, bounds=Bounds(lower=array([2., 0.]), upper=array([20. , 0.7]))), model_indices=[0], model=ScalarModel(intercept=0.39562420447382873, linear_terms=array([0., 0.]), square_terms=array([[0., 0.], - [0., 0.]]), scale=0.34649554641078373, shift=array([3.46495546, 0.53111681])), vector_model=VectorModel(intercepts=array([ 0.12634366, 0.23737133, 0.24789398, 0.25225032, 0.22803295, - 0.18688178, 0.14271092, 0.01053395, -0.07344733, 0.01546678, - -0.23684551, -0.16533737, -0.03497767, -0.00162142, 0.01248823, - 0.01256806, 0.01508461]), linear_terms=array([[0., 0.], + [0., 0.]]]), scale=0.5354006322483765, shift=array([5.35400632, 0.17100463])), candidate_index=13, candidate_x=array([5.82849278, 0.15221958]), index=0, x=array([5.35400632, 0.17100463]), fval=0.24222959010961218, rho=-0.15263749851610584, accepted=False, new_indices=array([ 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12]), old_indices_used=array([0]), old_indices_discarded=array([], dtype=int64), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([5.35400632, 0.17100463]), radius=0.26770031612418826, bounds=Bounds(lower=array([1.1 , 0.01]), upper=array([20. , 0.99]))), model_indices=array([ 0, 1, 2, 3, 5, 6, 7, 11, 13]), model=ScalarModel(intercept=0.34521638850922853, linear_terms=array([0.02481357, 0.95677547]), square_terms=array([[0.00728307, 0.06008121], + [0.06008121, 3.79651515]]), scale=array([0.23724323, 0.19912393]), shift=array([5.35400632, 0.20912393])), vector_model=VectorModel(intercepts=array([ 0.03985211, 0.08726933, 0.08463892, 0.10727527, 0.11929469, + 0.13193558, 0.14806457, 0.15973009, 0.07453542, 0.12630368, + -0.21049255, -0.24911785, -0.05784038, -0.03761571, -0.03108242, + -0.03262226, -0.02475777]), linear_terms=array([[0., 0.], [0., 0.], [0., 0.], [0., 0.], @@ -1817,11 +3426,11 @@ algorithm_output,"{'states': [State(trustregion=Region(center=array([3.46495546, [0., 0.]], [[0., 0.], - [0., 0.]]]), scale=0.34649554641078373, shift=array([3.46495546, 0.53111681])), candidate_index=0, candidate_x=array([3.46495546, 0.53111681]), index=0, x=array([3.46495546, 0.53111681]), fval=0.3956242044738288, rho=nan, accepted=True, new_indices=[0], old_indices_used=[], old_indices_discarded=[], step_length=None, relative_step_length=None, n_evals_per_point=None, n_evals_acceptance=None), State(trustregion=Region(center=array([3.46495546, 0.53111681]), radius=0.34649554641078373, bounds=Bounds(lower=array([2., 0.]), upper=array([20. , 0.7]))), model_indices=array([ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12]), model=ScalarModel(intercept=398.1451650304675, linear_terms=array([ -116.94879171, -1047.56476915]), square_terms=array([[ 17.3576769 , 153.91041078], - [ 153.91041078, 1378.58236955]]), scale=array([0.30707368, 0.23797844]), shift=array([3.46495546, 0.46202156])), vector_model=VectorModel(intercepts=array([ 0.12634366, 0.23737133, 0.24789398, 0.25225032, 0.22803295, - 0.18688178, 0.14271092, 0.01053395, -0.07344733, 0.01546678, - -0.23684551, -0.16533737, -0.03497767, -0.00162142, 0.01248823, - 0.01256806, 0.01508461]), linear_terms=array([[0., 0.], + [0., 0.]]]), scale=0.5354006322483765, shift=array([5.35400632, 0.17100463])), candidate_index=14, candidate_x=array([5.11676309, 0.16209309]), index=0, x=array([5.35400632, 0.17100463]), fval=0.24222959010961218, rho=-0.46139147245990136, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([ 0, 1, 2, 3, 5, 6, 7, 11, 13]), old_indices_discarded=array([ 4, 8, 9, 10, 12]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([5.35400632, 0.17100463]), radius=0.13385015806209413, bounds=Bounds(lower=array([1.1 , 0.01]), upper=array([20. , 0.99]))), model_indices=array([ 0, 1, 2, 5, 6, 7, 11, 13, 14]), model=ScalarModel(intercept=0.2362023136012516, linear_terms=array([0.00800373, 0.11292454]), square_terms=array([[0.00196812, 0.02971222], + [0.02971222, 1.6263466 ]]), scale=0.13385015806209413, shift=array([5.35400632, 0.17100463])), vector_model=VectorModel(intercepts=array([ 0.03985211, 0.08726933, 0.08463892, 0.10727527, 0.11929469, + 0.13193558, 0.14806457, 0.15973009, 0.07453542, 0.12630368, + -0.21049255, -0.24911785, -0.05784038, -0.03761571, -0.03108242, + -0.03262226, -0.02475777]), linear_terms=array([[0., 0.], [0., 0.], [0., 0.], [0., 0.], @@ -1886,11 +3495,11 @@ algorithm_output,"{'states': [State(trustregion=Region(center=array([3.46495546, [0., 0.]], [[0., 0.], - [0., 0.]]]), scale=0.34649554641078373, shift=array([3.46495546, 0.53111681])), candidate_index=13, candidate_x=array([3.45527817, 0.64369523]), index=0, x=array([3.46495546, 0.53111681]), fval=0.3956242044738288, rho=-0.006468163493285016, accepted=False, new_indices=array([ 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12]), old_indices_used=array([0]), old_indices_discarded=array([], dtype=int64), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([3.46495546, 0.53111681]), radius=0.17324777320539186, bounds=Bounds(lower=array([2., 0.]), upper=array([20. , 0.7]))), model_indices=array([ 0, 3, 4, 6, 7, 8, 9, 10, 13]), model=ScalarModel(intercept=125.67421265200598, linear_terms=array([ -52.73202436, -339.91391334]), square_terms=array([[ 11.15682933, 71.374677 ], - [ 71.374677 , 460.17276361]]), scale=array([0.15353684, 0.15353684]), shift=array([3.46495546, 0.53111681])), vector_model=VectorModel(intercepts=array([ 0.12634366, 0.23737133, 0.24789398, 0.25225032, 0.22803295, - 0.18688178, 0.14271092, 0.01053395, -0.07344733, 0.01546678, - -0.23684551, -0.16533737, -0.03497767, -0.00162142, 0.01248823, - 0.01256806, 0.01508461]), linear_terms=array([[0., 0.], + [0., 0.]]]), scale=0.5354006322483765, shift=array([5.35400632, 0.17100463])), candidate_index=15, candidate_x=array([5.22005581, 0.16417695]), index=0, x=array([5.35400632, 0.17100463]), fval=0.24222959010961218, rho=-0.3296965309559252, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([ 0, 1, 2, 5, 6, 7, 11, 13, 14]), old_indices_discarded=array([ 3, 4, 9, 10, 12]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([5.35400632, 0.17100463]), radius=0.06692507903104707, bounds=Bounds(lower=array([1.1 , 0.01]), upper=array([20. , 0.99]))), model_indices=array([ 0, 1, 14, 15]), model=ScalarModel(intercept=0.2425514564515167, linear_terms=array([-0.00173243, 0.04533645]), square_terms=array([[1.04215022e-04, 4.03453276e-03], + [4.03453276e-03, 4.06638215e-01]]), scale=0.06692507903104707, shift=array([5.35400632, 0.17100463])), vector_model=VectorModel(intercepts=array([ 0.03985211, 0.08726933, 0.08463892, 0.10727527, 0.11929469, + 0.13193558, 0.14806457, 0.15973009, 0.07453542, 0.12630368, + -0.21049255, -0.24911785, -0.05784038, -0.03761571, -0.03108242, + -0.03262226, -0.02475777]), linear_terms=array([[0., 0.], [0., 0.], [0., 0.], [0., 0.], @@ -1955,11 +3564,11 @@ algorithm_output,"{'states': [State(trustregion=Region(center=array([3.46495546, [0., 0.]], [[0., 0.], - [0., 0.]]]), scale=0.34649554641078373, shift=array([3.46495546, 0.53111681])), candidate_index=14, candidate_x=array([3.4827177 , 0.64177423]), index=0, x=array([3.46495546, 0.53111681]), fval=0.3956242044738288, rho=-0.007670421589594419, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([ 0, 3, 4, 6, 7, 8, 9, 10, 13]), old_indices_discarded=array([ 1, 2, 5, 11, 12]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([3.46495546, 0.53111681]), radius=0.08662388660269593, bounds=Bounds(lower=array([2., 0.]), upper=array([20. , 0.7]))), model_indices=array([ 0, 3, 4, 6, 7, 8, 10, 13, 14]), model=ScalarModel(intercept=108.36487966410208, linear_terms=array([ -37.40492364, -183.61193868]), square_terms=array([[ 6.50173301, 31.74217224], - [ 31.74217224, 155.75249716]]), scale=0.08662388660269593, shift=array([3.46495546, 0.53111681])), vector_model=VectorModel(intercepts=array([ 0.12634366, 0.23737133, 0.24789398, 0.25225032, 0.22803295, - 0.18688178, 0.14271092, 0.01053395, -0.07344733, 0.01546678, - -0.23684551, -0.16533737, -0.03497767, -0.00162142, 0.01248823, - 0.01256806, 0.01508461]), linear_terms=array([[0., 0.], + [0., 0.]]]), scale=0.5354006322483765, shift=array([5.35400632, 0.17100463])), candidate_index=16, candidate_x=array([5.42085343, 0.16292196]), index=0, x=array([5.35400632, 0.17100463]), fval=0.24222959010961218, rho=-0.527969662572183, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([ 0, 1, 14, 15]), old_indices_discarded=array([], dtype=int64), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([5.35400632, 0.17100463]), radius=0.03346253951552353, bounds=Bounds(lower=array([1.1 , 0.01]), upper=array([20. , 0.99]))), model_indices=array([ 0, 15, 16]), model=ScalarModel(intercept=0.2422295901096121, linear_terms=array([ 2.26580939e-05, -4.08992370e-05]), square_terms=array([[3.81901974e-05, 9.69943906e-04], + [9.69943906e-04, 9.61508064e-02]]), scale=0.03346253951552353, shift=array([5.35400632, 0.17100463])), vector_model=VectorModel(intercepts=array([ 0.03985211, 0.08726933, 0.08463892, 0.10727527, 0.11929469, + 0.13193558, 0.14806457, 0.15973009, 0.07453542, 0.12630368, + -0.21049255, -0.24911785, -0.05784038, -0.03761571, -0.03108242, + -0.03262226, -0.02475777]), linear_terms=array([[0., 0.], [0., 0.], [0., 0.], [0., 0.], @@ -2024,11 +3633,11 @@ algorithm_output,"{'states': [State(trustregion=Region(center=array([3.46495546, [0., 0.]], [[0., 0.], - [0., 0.]]]), scale=0.34649554641078373, shift=array([3.46495546, 0.53111681])), candidate_index=15, candidate_x=array([3.44163026, 0.61454122]), index=0, x=array([3.46495546, 0.53111681]), fval=0.3956242044738288, rho=-0.007123789024766916, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([ 0, 3, 4, 6, 7, 8, 10, 13, 14]), old_indices_discarded=array([ 1, 2, 5, 9, 11, 12]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([3.46495546, 0.53111681]), radius=0.043311943301347966, bounds=Bounds(lower=array([2., 0.]), upper=array([20. , 0.7]))), model_indices=array([ 0, 7, 13, 14, 15]), model=ScalarModel(intercept=0.4067828643254545, linear_terms=array([0.02410679, 0.02614154]), square_terms=array([[0.03171362, 0.08913027], - [0.08913027, 0.25640891]]), scale=0.043311943301347966, shift=array([3.46495546, 0.53111681])), vector_model=VectorModel(intercepts=array([ 0.12634366, 0.23737133, 0.24789398, 0.25225032, 0.22803295, - 0.18688178, 0.14271092, 0.01053395, -0.07344733, 0.01546678, - -0.23684551, -0.16533737, -0.03497767, -0.00162142, 0.01248823, - 0.01256806, 0.01508461]), linear_terms=array([[0., 0.], + [0., 0.]]]), scale=0.5354006322483765, shift=array([5.35400632, 0.17100463])), candidate_index=17, candidate_x=array([5.32054565, 0.17135825]), index=0, x=array([5.35400632, 0.17100463]), fval=0.24222959010961218, rho=-12.961189488478485, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([ 0, 15, 16]), old_indices_discarded=array([], dtype=int64), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([5.35400632, 0.17100463]), radius=0.016731269757761767, bounds=Bounds(lower=array([1.1 , 0.01]), upper=array([20. , 0.99]))), model_indices=array([ 0, 16, 17]), model=ScalarModel(intercept=0.2422295901096123, linear_terms=array([-5.65606521e-05, -5.81926201e-04]), square_terms=array([[9.07975120e-06, 2.17792130e-04], + [2.17792130e-04, 2.36612418e-02]]), scale=0.016731269757761767, shift=array([5.35400632, 0.17100463])), vector_model=VectorModel(intercepts=array([ 0.03985211, 0.08726933, 0.08463892, 0.10727527, 0.11929469, + 0.13193558, 0.14806457, 0.15973009, 0.07453542, 0.12630368, + -0.21049255, -0.24911785, -0.05784038, -0.03761571, -0.03108242, + -0.03262226, -0.02475777]), linear_terms=array([[0., 0.], [0., 0.], [0., 0.], [0., 0.], @@ -2093,11 +3702,11 @@ algorithm_output,"{'states': [State(trustregion=Region(center=array([3.46495546, [0., 0.]], [[0., 0.], - [0., 0.]]]), scale=0.34649554641078373, shift=array([3.46495546, 0.53111681])), candidate_index=16, candidate_x=array([3.42251291, 0.54093708]), index=0, x=array([3.46495546, 0.53111681]), fval=0.3956242044738288, rho=-1.767498399877576, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([ 0, 7, 13, 14, 15]), old_indices_discarded=array([], dtype=int64), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([3.46495546, 0.53111681]), radius=0.021655971650673983, bounds=Bounds(lower=array([2., 0.]), upper=array([20. , 0.7]))), model_indices=array([ 0, 15, 16]), model=ScalarModel(intercept=0.395624204473829, linear_terms=array([-0.00396938, -0.02118094]), square_terms=array([[ 0.00266011, -0.01595618], - [-0.01595618, 0.09972197]]), scale=0.021655971650673983, shift=array([3.46495546, 0.53111681])), vector_model=VectorModel(intercepts=array([ 0.12634366, 0.23737133, 0.24789398, 0.25225032, 0.22803295, - 0.18688178, 0.14271092, 0.01053395, -0.07344733, 0.01546678, - -0.23684551, -0.16533737, -0.03497767, -0.00162142, 0.01248823, - 0.01256806, 0.01508461]), linear_terms=array([[0., 0.], + [0., 0.]]]), scale=0.5354006322483765, shift=array([5.35400632, 0.17100463])), candidate_index=18, candidate_x=array([5.3707404 , 0.17126161]), index=0, x=array([5.35400632, 0.17100463]), fval=0.24222959010961218, rho=-2.7201415121532704, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([ 0, 16, 17]), old_indices_discarded=array([], dtype=int64), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([5.35400632, 0.17100463]), radius=0.008365634878880883, bounds=Bounds(lower=array([1.1 , 0.01]), upper=array([20. , 0.99]))), model_indices=array([ 0, 17, 18]), model=ScalarModel(intercept=0.2422295901096123, linear_terms=array([1.34598825e-05, 3.65869991e-03]), square_terms=array([[2.16122199e-06, 4.72270582e-05], + [4.72270582e-05, 5.52216987e-03]]), scale=0.008365634878880883, shift=array([5.35400632, 0.17100463])), vector_model=VectorModel(intercepts=array([ 0.03985211, 0.08726933, 0.08463892, 0.10727527, 0.11929469, + 0.13193558, 0.14806457, 0.15973009, 0.07453542, 0.12630368, + -0.21049255, -0.24911785, -0.05784038, -0.03761571, -0.03108242, + -0.03262226, -0.02475777]), linear_terms=array([[0., 0.], [0., 0.], [0., 0.], [0., 0.], @@ -2162,11 +3771,11 @@ algorithm_output,"{'states': [State(trustregion=Region(center=array([3.46495546, [0., 0.]], [[0., 0.], - [0., 0.]]]), scale=0.34649554641078373, shift=array([3.46495546, 0.53111681])), candidate_index=17, candidate_x=array([3.48570373, 0.53850551]), index=0, x=array([3.46495546, 0.53111681]), fval=0.3956242044738288, rho=-1.8762782320552598, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([ 0, 15, 16]), old_indices_discarded=array([], dtype=int64), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([3.46495546, 0.53111681]), radius=0.010827985825336991, bounds=Bounds(lower=array([2., 0.]), upper=array([20. , 0.7]))), model_indices=array([ 0, 16, 17]), model=ScalarModel(intercept=0.3956242044738289, linear_terms=array([ 4.07367956e-05, -1.83671069e-03]), square_terms=array([[1.84435895e-05, 5.41486888e-04], - [5.41486888e-04, 7.61693918e-02]]), scale=0.010827985825336991, shift=array([3.46495546, 0.53111681])), vector_model=VectorModel(intercepts=array([ 0.12634366, 0.23737133, 0.24789398, 0.25225032, 0.22803295, - 0.18688178, 0.14271092, 0.01053395, -0.07344733, 0.01546678, - -0.23684551, -0.16533737, -0.03497767, -0.00162142, 0.01248823, - 0.01256806, 0.01508461]), linear_terms=array([[0., 0.], + [0., 0.]]]), scale=0.5354006322483765, shift=array([5.35400632, 0.17100463])), candidate_index=19, candidate_x=array([5.36046292, 0.16542818]), index=0, x=array([5.35400632, 0.17100463]), fval=0.24222959010961218, rho=-1.2036288742643446, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([ 0, 17, 18]), old_indices_discarded=array([], dtype=int64), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([5.35400632, 0.17100463]), radius=0.004182817439440442, bounds=Bounds(lower=array([1.1 , 0.01]), upper=array([20. , 0.99]))), model_indices=array([ 0, 18, 19]), model=ScalarModel(intercept=0.24222959010961212, linear_terms=array([ 3.60728759e-05, -8.14075763e-05]), square_terms=array([[5.09140331e-07, 1.18923756e-05], + [1.18923756e-05, 1.50154474e-03]]), scale=0.004182817439440442, shift=array([5.35400632, 0.17100463])), vector_model=VectorModel(intercepts=array([ 0.03985211, 0.08726933, 0.08463892, 0.10727527, 0.11929469, + 0.13193558, 0.14806457, 0.15973009, 0.07453542, 0.12630368, + -0.21049255, -0.24911785, -0.05784038, -0.03761571, -0.03108242, + -0.03262226, -0.02475777]), linear_terms=array([[0., 0.], [0., 0.], [0., 0.], [0., 0.], @@ -2231,11 +3840,11 @@ algorithm_output,"{'states': [State(trustregion=Region(center=array([3.46495546, [0., 0.]], [[0., 0.], - [0., 0.]]]), scale=0.34649554641078373, shift=array([3.46495546, 0.53111681])), candidate_index=18, candidate_x=array([3.45413018, 0.53145469]), index=0, x=array([3.46495546, 0.53111681]), fval=0.3956242044738288, rho=-1.0824080447097881, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([ 0, 16, 17]), old_indices_discarded=array([], dtype=int64), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([3.46495546, 0.53111681]), radius=0.005413992912668496, bounds=Bounds(lower=array([2., 0.]), upper=array([20. , 0.7]))), model_indices=array([ 0, 17, 18]), model=ScalarModel(intercept=0.3956242044738293, linear_terms=array([-4.32323065e-05, -7.39757806e-04]), square_terms=array([[3.72492981e-06, 8.85042531e-05], - [8.85042531e-05, 1.93125519e-02]]), scale=0.005413992912668496, shift=array([3.46495546, 0.53111681])), vector_model=VectorModel(intercepts=array([ 0.12634366, 0.23737133, 0.24789398, 0.25225032, 0.22803295, - 0.18688178, 0.14271092, 0.01053395, -0.07344733, 0.01546678, - -0.23684551, -0.16533737, -0.03497767, -0.00162142, 0.01248823, - 0.01256806, 0.01508461]), linear_terms=array([[0., 0.], + [0., 0.]]]), scale=0.5354006322483765, shift=array([5.35400632, 0.17100463])), candidate_index=20, candidate_x=array([5.34982539, 0.17125839]), index=0, x=array([5.35400632, 0.17100463]), fval=0.24222959010961218, rho=-1.7584614706899044, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([ 0, 18, 19]), old_indices_discarded=array([], dtype=int64), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([5.35400632, 0.17100463]), radius=0.002091408719720221, bounds=Bounds(lower=array([1.1 , 0.01]), upper=array([20. , 0.99]))), model_indices=array([ 0, 19, 20]), model=ScalarModel(intercept=0.2422295901096121, linear_terms=array([-3.94682286e-05, -1.07284576e-04]), square_terms=array([[1.63719723e-07, 3.86879923e-06], + [3.86879923e-06, 3.77411497e-04]]), scale=0.002091408719720221, shift=array([5.35400632, 0.17100463])), vector_model=VectorModel(intercepts=array([ 0.03985211, 0.08726933, 0.08463892, 0.10727527, 0.11929469, + 0.13193558, 0.14806457, 0.15973009, 0.07453542, 0.12630368, + -0.21049255, -0.24911785, -0.05784038, -0.03761571, -0.03108242, + -0.03262226, -0.02475777]), linear_terms=array([[0., 0.], [0., 0.], [0., 0.], [0., 0.], @@ -2300,11 +3909,11 @@ algorithm_output,"{'states': [State(trustregion=Region(center=array([3.46495546, [0., 0.]], [[0., 0.], - [0., 0.]]]), scale=0.34649554641078373, shift=array([3.46495546, 0.53111681])), candidate_index=19, candidate_x=array([3.47037027, 0.53129903]), index=0, x=array([3.46495546, 0.53111681]), fval=0.3956242044738288, rho=-1.4029450751291208, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([ 0, 17, 18]), old_indices_discarded=array([], dtype=int64), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([3.46495546, 0.53111681]), radius=0.002706996456334248, bounds=Bounds(lower=array([2., 0.]), upper=array([20. , 0.7]))), model_indices=array([ 0, 18, 19]), model=ScalarModel(intercept=0.39562420447382884, linear_terms=array([7.88883877e-06, 5.75417387e-04]), square_terms=array([[1.03638106e-06, 3.35311076e-05], - [3.35311076e-05, 5.45100791e-03]]), scale=0.002706996456334248, shift=array([3.46495546, 0.53111681])), vector_model=VectorModel(intercepts=array([ 0.12634366, 0.23737133, 0.24789398, 0.25225032, 0.22803295, - 0.18688178, 0.14271092, 0.01053395, -0.07344733, 0.01546678, - -0.23684551, -0.16533737, -0.03497767, -0.00162142, 0.01248823, - 0.01256806, 0.01508461]), linear_terms=array([[0., 0.], + [0., 0.]]]), scale=0.5354006322483765, shift=array([5.35400632, 0.17100463])), candidate_index=21, candidate_x=array([5.35610317, 0.17152493]), index=0, x=array([5.35400632, 0.17100463]), fval=0.24222959010961218, rho=-1.5793099561442583, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([ 0, 19, 20]), old_indices_discarded=array([], dtype=int64), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([5.35400632, 0.17100463]), radius=0.0010457043598601104, bounds=Bounds(lower=array([1.1 , 0.01]), upper=array([20. , 0.99]))), model_indices=array([ 0, 20, 21]), model=ScalarModel(intercept=0.242229590109612, linear_terms=array([-6.14047801e-06, 1.70331260e-04]), square_terms=array([[3.55438753e-08, 8.12487591e-07], + [8.12487591e-07, 9.07168416e-05]]), scale=0.0010457043598601104, shift=array([5.35400632, 0.17100463])), vector_model=VectorModel(intercepts=array([ 0.03985211, 0.08726933, 0.08463892, 0.10727527, 0.11929469, + 0.13193558, 0.14806457, 0.15973009, 0.07453542, 0.12630368, + -0.21049255, -0.24911785, -0.05784038, -0.03761571, -0.03108242, + -0.03262226, -0.02475777]), linear_terms=array([[0., 0.], [0., 0.], [0., 0.], [0., 0.], @@ -2369,11 +3978,11 @@ algorithm_output,"{'states': [State(trustregion=Region(center=array([3.46495546, [0., 0.]], [[0., 0.], - [0., 0.]]]), scale=0.34649554641078373, shift=array([3.46495546, 0.53111681])), candidate_index=20, candidate_x=array([3.4622482 , 0.53084788]), index=0, x=array([3.46495546, 0.53111681]), fval=0.3956242044738288, rho=-3.071032863387669, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([ 0, 18, 19]), old_indices_discarded=array([], dtype=int64), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([3.46495546, 0.53111681]), radius=0.001353498228167124, bounds=Bounds(lower=array([2., 0.]), upper=array([20. , 0.7]))), model_indices=array([ 0, 19, 20]), model=ScalarModel(intercept=0.39562420447382896, linear_terms=array([ 3.95806434e-05, -7.71242464e-04]), square_terms=array([[2.52497796e-07, 7.82520747e-06], - [7.82520747e-06, 1.40171465e-03]]), scale=0.001353498228167124, shift=array([3.46495546, 0.53111681])), vector_model=VectorModel(intercepts=array([ 0.12634366, 0.23737133, 0.24789398, 0.25225032, 0.22803295, - 0.18688178, 0.14271092, 0.01053395, -0.07344733, 0.01546678, - -0.23684551, -0.16533737, -0.03497767, -0.00162142, 0.01248823, - 0.01256806, 0.01508461]), linear_terms=array([[0., 0.], + [0., 0.]]]), scale=0.5354006322483765, shift=array([5.35400632, 0.17100463])), candidate_index=22, candidate_x=array([5.35431584, 0.17000579]), index=0, x=array([5.35400632, 0.17100463]), fval=0.24222959010961218, rho=-0.7125655885495248, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([ 0, 20, 21]), old_indices_discarded=array([], dtype=int64), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([5.35400632, 0.17100463]), radius=0.0005228521799300552, bounds=Bounds(lower=array([1.1 , 0.01]), upper=array([20. , 0.99]))), model_indices=array([ 0, 21, 22]), model=ScalarModel(intercept=0.24222959010961226, linear_terms=array([ 2.21750742e-05, -1.65754846e-05]), square_terms=array([[8.04044878e-09, 8.13963755e-08], + [8.13963755e-08, 2.36740749e-05]]), scale=0.0005228521799300552, shift=array([5.35400632, 0.17100463])), vector_model=VectorModel(intercepts=array([ 0.03985211, 0.08726933, 0.08463892, 0.10727527, 0.11929469, + 0.13193558, 0.14806457, 0.15973009, 0.07453542, 0.12630368, + -0.21049255, -0.24911785, -0.05784038, -0.03761571, -0.03108242, + -0.03262226, -0.02475777]), linear_terms=array([[0., 0.], [0., 0.], [0., 0.], [0., 0.], @@ -2438,11 +4047,11 @@ algorithm_output,"{'states': [State(trustregion=Region(center=array([3.46495546, [0., 0.]], [[0., 0.], - [0., 0.]]]), scale=0.34649554641078373, shift=array([3.46495546, 0.53111681])), candidate_index=21, candidate_x=array([3.46380251, 0.53184152]), index=0, x=array([3.46495546, 0.53111681]), fval=0.3956242044738288, rho=-1.2094240011644295, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([ 0, 19, 20]), old_indices_discarded=array([], dtype=int64), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([3.46495546, 0.53111681]), radius=0.000676749114083562, bounds=Bounds(lower=array([2., 0.]), upper=array([20. , 0.7]))), model_indices=array([ 0, 20, 21]), model=ScalarModel(intercept=0.39562420447382907, linear_terms=array([-2.47391859e-05, 6.26517286e-05]), square_terms=array([[7.13464682e-08, 2.31692454e-06], - [2.31692454e-06, 3.42334740e-04]]), scale=0.000676749114083562, shift=array([3.46495546, 0.53111681])), vector_model=VectorModel(intercepts=array([ 0.12634366, 0.23737133, 0.24789398, 0.25225032, 0.22803295, - 0.18688178, 0.14271092, 0.01053395, -0.07344733, 0.01546678, - -0.23684551, -0.16533737, -0.03497767, -0.00162142, 0.01248823, - 0.01256806, 0.01508461]), linear_terms=array([[0., 0.], + [0., 0.]]]), scale=0.5354006322483765, shift=array([5.35400632, 0.17100463])), candidate_index=23, candidate_x=array([5.35350687, 0.17119025]), index=0, x=array([5.35400632, 0.17100463]), fval=0.24222959010961218, rho=-1.4644750163969473, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([ 0, 21, 22]), old_indices_discarded=array([], dtype=int64), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([5.35400632, 0.17100463]), radius=0.0002614260899650276, bounds=Bounds(lower=array([1.1 , 0.01]), upper=array([20. , 0.99]))), model_indices=array([ 0, 22, 23]), model=ScalarModel(intercept=0.2422295901096124, linear_terms=array([-2.62742633e-05, -1.98653516e-05]), square_terms=array([[8.22172600e-09, 8.86003727e-08], + [8.86003727e-08, 5.96022144e-06]]), scale=0.0002614260899650276, shift=array([5.35400632, 0.17100463])), vector_model=VectorModel(intercepts=array([ 0.03985211, 0.08726933, 0.08463892, 0.10727527, 0.11929469, + 0.13193558, 0.14806457, 0.15973009, 0.07453542, 0.12630368, + -0.21049255, -0.24911785, -0.05784038, -0.03761571, -0.03108242, + -0.03262226, -0.02475777]), linear_terms=array([[0., 0.], [0., 0.], [0., 0.], [0., 0.], @@ -2507,11 +4116,11 @@ algorithm_output,"{'states': [State(trustregion=Region(center=array([3.46495546, [0., 0.]], [[0., 0.], - [0., 0.]]]), scale=0.34649554641078373, shift=array([3.46495546, 0.53111681])), candidate_index=22, candidate_x=array([3.46563142, 0.53099715]), index=0, x=array([3.46495546, 0.53111681]), fval=0.3956242044738288, rho=-1.5213482982504996, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([ 0, 20, 21]), old_indices_discarded=array([], dtype=int64), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([3.46495546, 0.53111681]), radius=0.000338374557041781, bounds=Bounds(lower=array([2., 0.]), upper=array([20. , 0.7]))), model_indices=array([ 0, 21, 22]), model=ScalarModel(intercept=0.3956242044738295, linear_terms=array([4.17314453e-05, 1.17395874e-04]), square_terms=array([[3.64249375e-08, 5.60771045e-07], - [5.60771045e-07, 8.54779012e-05]]), scale=0.000338374557041781, shift=array([3.46495546, 0.53111681])), vector_model=VectorModel(intercepts=array([ 0.12634366, 0.23737133, 0.24789398, 0.25225032, 0.22803295, - 0.18688178, 0.14271092, 0.01053395, -0.07344733, 0.01546678, - -0.23684551, -0.16533737, -0.03497767, -0.00162142, 0.01248823, - 0.01256806, 0.01508461]), linear_terms=array([[0., 0.], + [0., 0.]]]), scale=0.5354006322483765, shift=array([5.35400632, 0.17100463])), candidate_index=24, candidate_x=array([5.35423597, 0.1711491 ]), index=0, x=array([5.35400632, 0.17100463]), fval=0.24222959010961218, rho=-0.6200026560932351, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([ 0, 22, 23]), old_indices_discarded=array([], dtype=int64), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([5.35400632, 0.17100463]), radius=0.0001307130449825138, bounds=Bounds(lower=array([1.1 , 0.01]), upper=array([20. , 0.99]))), model_indices=array([ 0, 23, 24]), model=ScalarModel(intercept=0.24222959010961245, linear_terms=array([-1.79500884e-06, 2.05867756e-05]), square_terms=array([[5.79123464e-10, 1.50701874e-08], + [1.50701874e-08, 1.46264317e-06]]), scale=0.0001307130449825138, shift=array([5.35400632, 0.17100463])), vector_model=VectorModel(intercepts=array([ 0.03985211, 0.08726933, 0.08463892, 0.10727527, 0.11929469, + 0.13193558, 0.14806457, 0.15973009, 0.07453542, 0.12630368, + -0.21049255, -0.24911785, -0.05784038, -0.03761571, -0.03108242, + -0.03262226, -0.02475777]), linear_terms=array([[0., 0.], [0., 0.], [0., 0.], [0., 0.], @@ -2576,11 +4185,11 @@ algorithm_output,"{'states': [State(trustregion=Region(center=array([3.46495546, [0., 0.]], [[0., 0.], - [0., 0.]]]), scale=0.34649554641078373, shift=array([3.46495546, 0.53111681])), candidate_index=23, candidate_x=array([3.46471212, 0.53088169]), index=0, x=array([3.46495546, 0.53111681]), fval=0.3956242044738288, rho=-0.7314294930171341, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([ 0, 21, 22]), old_indices_discarded=array([], dtype=int64), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([3.46495546, 0.53111681]), radius=0.0001691872785208905, bounds=Bounds(lower=array([2., 0.]), upper=array([20. , 0.7]))), model_indices=array([ 0, 22, 23]), model=ScalarModel(intercept=0.39562420447382884, linear_terms=array([ 3.96412519e-06, -3.67838187e-05]), square_terms=array([[4.68995790e-09, 1.27645371e-07], - [1.27645371e-07, 2.13686504e-05]]), scale=0.0001691872785208905, shift=array([3.46495546, 0.53111681])), vector_model=VectorModel(intercepts=array([ 0.12634366, 0.23737133, 0.24789398, 0.25225032, 0.22803295, - 0.18688178, 0.14271092, 0.01053395, -0.07344733, 0.01546678, - -0.23684551, -0.16533737, -0.03497767, -0.00162142, 0.01248823, - 0.01256806, 0.01508461]), linear_terms=array([[0., 0.], + [0., 0.]]]), scale=0.5354006322483765, shift=array([5.35400632, 0.17100463])), candidate_index=25, candidate_x=array([5.35402239, 0.17087491]), index=0, x=array([5.35400632, 0.17100463]), fval=0.24222959010961218, rho=-0.9579828303290001, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([ 0, 23, 24]), old_indices_discarded=array([], dtype=int64), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([5.35400632, 0.17100463]), radius=6.53565224912569e-05, bounds=Bounds(lower=array([1.1 , 0.01]), upper=array([20. , 0.99]))), model_indices=array([ 0, 24, 25]), model=ScalarModel(intercept=0.24222959010961237, linear_terms=array([ 1.05788421e-05, -7.94918103e-06]), square_terms=array([[5.36753228e-10, 3.62921811e-09], + [3.62921811e-09, 3.65110140e-07]]), scale=6.53565224912569e-05, shift=array([5.35400632, 0.17100463])), vector_model=VectorModel(intercepts=array([ 0.03985211, 0.08726933, 0.08463892, 0.10727527, 0.11929469, + 0.13193558, 0.14806457, 0.15973009, 0.07453542, 0.12630368, + -0.21049255, -0.24911785, -0.05784038, -0.03761571, -0.03108242, + -0.03262226, -0.02475777]), linear_terms=array([[0., 0.], [0., 0.], [0., 0.], [0., 0.], @@ -2645,11 +4254,11 @@ algorithm_output,"{'states': [State(trustregion=Region(center=array([3.46495546, [0., 0.]], [[0., 0.], - [0., 0.]]]), scale=0.34649554641078373, shift=array([3.46495546, 0.53111681])), candidate_index=24, candidate_x=array([3.46489062, 0.53127308]), index=0, x=array([3.46495546, 0.53111681]), fval=0.3956242044738288, rho=-0.6471968813314769, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([ 0, 22, 23]), old_indices_discarded=array([], dtype=int64), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([3.46495546, 0.53111681]), radius=8.459363926044525e-05, bounds=Bounds(lower=array([2., 0.]), upper=array([20. , 0.7]))), model_indices=array([ 0, 23, 24]), model=ScalarModel(intercept=0.3956242044738286, linear_terms=array([-1.43573588e-05, -1.48085006e-06]), square_terms=array([[4.31731173e-09, 7.89922153e-08], - [7.89922153e-08, 5.24133786e-06]]), scale=8.459363926044525e-05, shift=array([3.46495546, 0.53111681])), vector_model=VectorModel(intercepts=array([ 0.12634366, 0.23737133, 0.24789398, 0.25225032, 0.22803295, - 0.18688178, 0.14271092, 0.01053395, -0.07344733, 0.01546678, - -0.23684551, -0.16533737, -0.03497767, -0.00162142, 0.01248823, - 0.01256806, 0.01508461]), linear_terms=array([[0., 0.], + [0., 0.]]]), scale=0.5354006322483765, shift=array([5.35400632, 0.17100463])), candidate_index=26, candidate_x=array([5.35395333, 0.17104337]), index=26, x=array([5.35395333, 0.17104337]), fval=0.2422277273737417, rho=0.14083638536414766, accepted=True, new_indices=array([], dtype=int64), old_indices_used=array([ 0, 24, 25]), old_indices_discarded=array([], dtype=int64), step_length=6.563987106445188e-05, relative_step_length=1.0043354291567896, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([5.35395333, 0.17104337]), radius=0.0001307130449825138, bounds=Bounds(lower=array([1.1 , 0.01]), upper=array([20. , 0.99]))), model_indices=array([ 0, 23, 24, 25, 26]), model=ScalarModel(intercept=0.24224352491633633, linear_terms=array([-3.08093940e-06, 5.60854271e-06]), square_terms=array([[6.31003624e-10, 1.52848775e-08], + [1.52848775e-08, 1.46005813e-06]]), scale=0.0001307130449825138, shift=array([5.35395333, 0.17104337])), vector_model=VectorModel(intercepts=array([ 0.03985211, 0.08726933, 0.08463892, 0.10727527, 0.11929469, + 0.13193558, 0.14806457, 0.15973009, 0.07453542, 0.12630368, + -0.21049255, -0.24911785, -0.05784038, -0.03761571, -0.03108242, + -0.03262226, -0.02475777]), linear_terms=array([[0., 0.], [0., 0.], [0., 0.], [0., 0.], @@ -2714,11 +4323,11 @@ algorithm_output,"{'states': [State(trustregion=Region(center=array([3.46495546, [0., 0.]], [[0., 0.], - [0., 0.]]]), scale=0.34649554641078373, shift=array([3.46495546, 0.53111681])), candidate_index=25, candidate_x=array([3.46503985, 0.53112285]), index=0, x=array([3.46495546, 0.53111681]), fval=0.3956242044738288, rho=-0.6093566693728825, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([ 0, 23, 24]), old_indices_discarded=array([], dtype=int64), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([3.46495546, 0.53111681]), radius=4.229681963022262e-05, bounds=Bounds(lower=array([2., 0.]), upper=array([20. , 0.7]))), model_indices=array([ 0, 24, 25]), model=ScalarModel(intercept=0.39562420447382896, linear_terms=array([4.10906912e-06, 3.94319598e-06]), square_terms=array([[4.31197929e-10, 1.14627443e-08], - [1.14627443e-08, 1.30357041e-06]]), scale=4.229681963022262e-05, shift=array([3.46495546, 0.53111681])), vector_model=VectorModel(intercepts=array([ 0.12634366, 0.23737133, 0.24789398, 0.25225032, 0.22803295, - 0.18688178, 0.14271092, 0.01053395, -0.07344733, 0.01546678, - -0.23684551, -0.16533737, -0.03497767, -0.00162142, 0.01248823, - 0.01256806, 0.01508461]), linear_terms=array([[0., 0.], + [0., 0.]]]), scale=0.5354006322483765, shift=array([5.35400632, 0.17100463])), candidate_index=27, candidate_x=array([5.35402897, 0.17093677]), index=26, x=array([5.35395333, 0.17104337]), fval=0.2422277273737417, rho=-2.4450769350997383, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([ 0, 23, 24, 25, 26]), old_indices_discarded=array([], dtype=int64), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([5.35395333, 0.17104337]), radius=6.53565224912569e-05, bounds=Bounds(lower=array([1.1 , 0.01]), upper=array([20. , 0.99]))), model_indices=array([ 0, 24, 25, 26, 27]), model=ScalarModel(intercept=0.24222502087756123, linear_terms=array([ 7.45158661e-06, -5.05511895e-06]), square_terms=array([[2.70437387e-10, 3.09657346e-09], + [3.09657346e-09, 3.66169028e-07]]), scale=6.53565224912569e-05, shift=array([5.35395333, 0.17104337])), vector_model=VectorModel(intercepts=array([ 0.03985211, 0.08726933, 0.08463892, 0.10727527, 0.11929469, + 0.13193558, 0.14806457, 0.15973009, 0.07453542, 0.12630368, + -0.21049255, -0.24911785, -0.05784038, -0.03761571, -0.03108242, + -0.03262226, -0.02475777]), linear_terms=array([[0., 0.], [0., 0.], [0., 0.], [0., 0.], @@ -2783,11 +4392,11 @@ algorithm_output,"{'states': [State(trustregion=Region(center=array([3.46495546, [0., 0.]], [[0., 0.], - [0., 0.]]]), scale=0.34649554641078373, shift=array([3.46495546, 0.53111681])), candidate_index=26, candidate_x=array([3.46492081, 0.53109043]), index=26, x=array([3.46492081, 0.53109043]), fval=0.39561894207152565, rho=0.945446153415508, accepted=True, new_indices=array([], dtype=int64), old_indices_used=array([ 0, 24, 25]), old_indices_discarded=array([], dtype=int64), step_length=4.3549735239972725e-05, relative_step_length=1.0296219815273024, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([3.46492081, 0.53109043]), radius=8.459363926044525e-05, bounds=Bounds(lower=array([2., 0.]), upper=array([20. , 0.7]))), model_indices=array([ 0, 23, 24, 25, 26]), model=ScalarModel(intercept=0.395634570533063, linear_terms=array([-8.04050131e-06, -5.94565060e-06]), square_terms=array([[2.94137802e-09, 6.60314146e-08], - [6.60314146e-08, 5.25498164e-06]]), scale=8.459363926044525e-05, shift=array([3.46492081, 0.53109043])), vector_model=VectorModel(intercepts=array([ 0.12634366, 0.23737133, 0.24789398, 0.25225032, 0.22803295, - 0.18688178, 0.14271092, 0.01053395, -0.07344733, 0.01546678, - -0.23684551, -0.16533737, -0.03497767, -0.00162142, 0.01248823, - 0.01256806, 0.01508461]), linear_terms=array([[0., 0.], + [0., 0.]]]), scale=0.5354006322483765, shift=array([5.35400632, 0.17100463])), candidate_index=28, candidate_x=array([5.35389811, 0.17107935]), index=26, x=array([5.35395333, 0.17104337]), fval=0.2422277273737417, rho=-0.5341074942650346, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([ 0, 24, 25, 26, 27]), old_indices_discarded=array([], dtype=int64), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([5.35395333, 0.17104337]), radius=3.267826124562845e-05, bounds=Bounds(lower=array([1.1 , 0.01]), upper=array([20. , 0.99]))), model_indices=array([ 0, 26, 27, 28]), model=ScalarModel(intercept=0.2422294912910428, linear_terms=array([-6.90237896e-06, -8.63730234e-06]), square_terms=array([[3.99937459e-10, 9.87661306e-10], + [9.87661306e-10, 9.14882246e-08]]), scale=3.267826124562845e-05, shift=array([5.35395333, 0.17104337])), vector_model=VectorModel(intercepts=array([ 0.03985211, 0.08726933, 0.08463892, 0.10727527, 0.11929469, + 0.13193558, 0.14806457, 0.15973009, 0.07453542, 0.12630368, + -0.21049255, -0.24911785, -0.05784038, -0.03761571, -0.03108242, + -0.03262226, -0.02475777]), linear_terms=array([[0., 0.], [0., 0.], [0., 0.], [0., 0.], @@ -2852,11 +4461,11 @@ algorithm_output,"{'states': [State(trustregion=Region(center=array([3.46495546, [0., 0.]], [[0., 0.], - [0., 0.]]]), scale=0.34649554641078373, shift=array([3.46495546, 0.53111681])), candidate_index=27, candidate_x=array([3.46499781, 0.53112586]), index=26, x=array([3.46492081, 0.53109043]), fval=0.39561894207152565, rho=-1.9757700237645563, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([ 0, 23, 24, 25, 26]), old_indices_discarded=array([], dtype=int64), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([3.46492081, 0.53109043]), radius=4.229681963022262e-05, bounds=Bounds(lower=array([2., 0.]), upper=array([20. , 0.7]))), model_indices=array([ 0, 24, 25, 26, 27]), model=ScalarModel(intercept=0.39561947944969, linear_terms=array([4.97404407e-06, 3.10920139e-06]), square_terms=array([[1.49952556e-09, 2.29109605e-08], - [2.29109605e-08, 1.32167738e-06]]), scale=4.229681963022262e-05, shift=array([3.46492081, 0.53109043])), vector_model=VectorModel(intercepts=array([ 0.12634366, 0.23737133, 0.24789398, 0.25225032, 0.22803295, - 0.18688178, 0.14271092, 0.01053395, -0.07344733, 0.01546678, - -0.23684551, -0.16533737, -0.03497767, -0.00162142, 0.01248823, - 0.01256806, 0.01508461]), linear_terms=array([[0., 0.], + [0., 0.]]]), scale=0.5354006322483765, shift=array([5.35400632, 0.17100463])), candidate_index=29, candidate_x=array([5.3539736 , 0.17106901]), index=26, x=array([5.35395333, 0.17104337]), fval=0.2422277273737417, rho=-0.24050336499745487, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([ 0, 26, 27, 28]), old_indices_discarded=array([], dtype=int64), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([5.35395333, 0.17104337]), radius=1.6339130622814225e-05, bounds=Bounds(lower=array([1.1 , 0.01]), upper=array([20. , 0.99]))), model_indices=array([ 0, 26, 28, 29]), model=ScalarModel(intercept=0.24222996390810195, linear_terms=array([-2.12423430e-07, 3.41299828e-07]), square_terms=array([[8.81693417e-12, 1.70394692e-10], + [1.70394692e-10, 2.28517123e-08]]), scale=1.6339130622814225e-05, shift=array([5.35395333, 0.17104337])), vector_model=VectorModel(intercepts=array([ 0.03985211, 0.08726933, 0.08463892, 0.10727527, 0.11929469, + 0.13193558, 0.14806457, 0.15973009, 0.07453542, 0.12630368, + -0.21049255, -0.24911785, -0.05784038, -0.03761571, -0.03108242, + -0.03262226, -0.02475777]), linear_terms=array([[0., 0.], [0., 0.], [0., 0.], [0., 0.], @@ -2921,11 +4530,11 @@ algorithm_output,"{'states': [State(trustregion=Region(center=array([3.46495546, [0., 0.]], [[0., 0.], - [0., 0.]]]), scale=0.34649554641078373, shift=array([3.46495546, 0.53111681])), candidate_index=28, candidate_x=array([3.46488023, 0.53107033]), index=28, x=array([3.46488023, 0.53107033]), fval=0.3956174852241245, rho=0.23924371384284093, accepted=True, new_indices=array([], dtype=int64), old_indices_used=array([ 0, 24, 25, 26, 27]), old_indices_discarded=array([], dtype=int64), step_length=4.528574698820532e-05, relative_step_length=1.0706655342910698, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([3.46488023, 0.53107033]), radius=8.459363926044525e-05, bounds=Bounds(lower=array([2., 0.]), upper=array([20. , 0.7]))), model_indices=array([ 0, 23, 24, 25, 26, 27, 28]), model=ScalarModel(intercept=0.395637640546523, linear_terms=array([-5.47337741e-06, -7.74435957e-06]), square_terms=array([[3.28485118e-09, 7.34686091e-08], - [7.34686091e-08, 5.25424073e-06]]), scale=8.459363926044525e-05, shift=array([3.46488023, 0.53107033])), vector_model=VectorModel(intercepts=array([ 0.12634366, 0.23737133, 0.24789398, 0.25225032, 0.22803295, - 0.18688178, 0.14271092, 0.01053395, -0.07344733, 0.01546678, - -0.23684551, -0.16533737, -0.03497767, -0.00162142, 0.01248823, - 0.01256806, 0.01508461]), linear_terms=array([[0., 0.], + [0., 0.]]]), scale=0.5354006322483765, shift=array([5.35400632, 0.17100463])), candidate_index=30, candidate_x=array([5.35396236, 0.17102975]), index=30, x=array([5.35396236, 0.17102975]), fval=0.24222765324129839, rho=0.1881625207794738, accepted=True, new_indices=array([], dtype=int64), old_indices_used=array([ 0, 26, 28, 29]), old_indices_discarded=array([], dtype=int64), step_length=1.6339130622582518e-05, relative_step_length=0.9999999999858189, n_evals_per_point=1, n_evals_acceptance=1)], 'message': 'Absolute criterion change smaller than tolerance.', 'tranquilo_history': History for least_squares function with 31 entries., 'history': {'params': [{'CRRA': 5.354006322483765, 'WealthShare': 0.17100463259932858}, {'CRRA': 5.109526968790541, 'WealthShare': 0.01}, {'CRRA': 5.828492778686707, 'WealthShare': 0.15204504729462334}, {'CRRA': 4.879519866280823, 'WealthShare': 0.3315815110617215}, {'CRRA': 5.828492778686707, 'WealthShare': 0.49970354850069737}, {'CRRA': 5.650144671106818, 'WealthShare': 0.01}, {'CRRA': 5.828492778686707, 'WealthShare': 0.010830254980025156}, {'CRRA': 4.879519866280823, 'WealthShare': 0.2883553842161002}, {'CRRA': 5.828492778686707, 'WealthShare': 0.6450105503098645}, {'CRRA': 5.694966409211402, 'WealthShare': 0.64549108880227}, {'CRRA': 4.889974668525427, 'WealthShare': 0.64549108880227}, {'CRRA': 4.8798282733752, 'WealthShare': 0.01}, {'CRRA': 4.9304750591958575, 'WealthShare': 0.64549108880227}, {'CRRA': 5.828492778686707, 'WealthShare': 0.1522195849634129}, {'CRRA': 5.116763094382295, 'WealthShare': 0.162093093389721}, {'CRRA': 5.220055806675767, 'WealthShare': 0.16417695361641313}, {'CRRA': 5.420853433224794, 'WealthShare': 0.1629219620717402}, {'CRRA': 5.320545651419049, 'WealthShare': 0.17135824640963598}, {'CRRA': 5.370740404051837, 'WealthShare': 0.17126161290924083}, {'CRRA': 5.360462921972393, 'WealthShare': 0.1654281801257648}, {'CRRA': 5.34982538641343, 'WealthShare': 0.17125838633404758}, {'CRRA': 5.356103173754721, 'WealthShare': 0.17152493029175916}, {'CRRA': 5.3543158433102125, 'WealthShare': 0.17000578603141864}, {'CRRA': 5.35350687499139, 'WealthShare': 0.171190245201562}, {'CRRA': 5.354235972636878, 'WealthShare': 0.17114910483656004}, {'CRRA': 5.354022385759902, 'WealthShare': 0.17087491031408678}, {'CRRA': 5.353953334391117, 'WealthShare': 0.1710433734654895}, {'CRRA': 5.354028970281308, 'WealthShare': 0.17093676618504597}, {'CRRA': 5.353898112243326, 'WealthShare': 0.17107935423371562}, {'CRRA': 5.353973599154986, 'WealthShare': 0.17106900953584717}, {'CRRA': 5.353962360456047, 'WealthShare': 0.17102975372461904}], 'criterion': [0.24222959010961218, 1.3526915601449605, 0.2557979077425905, 1.6976202707447787, 7.111771579168412, 1.1321339712554153, 1.0630922980278235, 0.9704855162793572, 24.20832805041196, 25.143500249276755, 31.418132454405693, 1.466178734043127, 31.038987308177695, 0.25560122414249775, 0.2484456388278747, 0.2452469160005554, 0.24469779683963266, 0.24234464265008338, 0.24237873573754437, 0.2437043378605563, 0.2422976408174732, 0.24231413788529724, 0.24231749216591117, 0.2422670790738343, 0.24225011378979655, 0.2422486854656542, 0.2422277273737417, 0.2422421007520363, 0.24223254767968563, 0.24223037955292165, 0.2422276532412984], 'runtime': [0.0, 1.2662754060002044, 1.309790532977786, 1.3521457499882672, 1.39415722200647, 1.4378280069795437, 1.4971206579939462, 1.5400017309875693, 1.5876122879853938, 1.6510058109997772, 1.696333269996103, 1.749355880980147, 1.8118952319782693, 104.28601489798166, 105.44708380999509, 106.8947216969973, 108.07735092300572, 109.80713732200093, 111.00220471099601, 112.19977979498799, 113.38472365800408, 114.5276050149987, 115.70550290797837, 116.90770325798076, 118.22135159099707, 119.39549850899493, 120.57577711797785, 121.75113257797784, 122.92057242800365, 124.09315577999223, 125.26397062599426], 'batches': [0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19]}}, {'solution_x': array([5.35399092, 0.17103024]), 'solution_criterion': 0.24222754644165564, 'states': [State(trustregion=Region(center=array([5.83790621, 0.17768436]), radius=0.5837906205607757, bounds=Bounds(lower=array([1.1 , 0.01]), upper=array([20. , 0.99]))), model_indices=[0], model=ScalarModel(intercept=0.2500179178839741, linear_terms=array([0., 0.]), square_terms=array([[0., 0.], + [0., 0.]]), scale=0.5837906205607757, shift=array([5.83790621, 0.17768436])), vector_model=VectorModel(intercepts=array([ 0.04097031, 0.08957803, 0.08816081, 0.11232093, 0.12575895, + 0.13980376, 0.15781889, 0.17546538, 0.09348822, 0.15053254, + -0.17880431, -0.21077511, -0.08570458, -0.06416478, -0.05745986, + -0.05902133, -0.05316704]), linear_terms=array([[0., 0.], [0., 0.], [0., 0.], [0., 0.], @@ -2990,11 +4599,11 @@ algorithm_output,"{'states': [State(trustregion=Region(center=array([3.46495546, [0., 0.]], [[0., 0.], - [0., 0.]]]), scale=0.34649554641078373, shift=array([3.46495546, 0.53111681])), candidate_index=29, candidate_x=array([3.4649524, 0.5311263]), index=28, x=array([3.46488023, 0.53107033]), fval=0.3956174852241245, rho=-2.3079169286750476, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([ 0, 23, 24, 25, 26, 27, 28]), old_indices_discarded=array([], dtype=int64), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([3.46488023, 0.53107033]), radius=4.229681963022262e-05, bounds=Bounds(lower=array([2., 0.]), upper=array([20. , 0.7]))), model_indices=array([ 0, 24, 25, 26, 27, 28, 29]), model=ScalarModel(intercept=0.39561746207201964, linear_terms=array([4.33228260e-06, 1.81465673e-06]), square_terms=array([[2.25926255e-09, 3.07816141e-08], - [3.07816141e-08, 1.33239024e-06]]), scale=4.229681963022262e-05, shift=array([3.46488023, 0.53107033])), vector_model=VectorModel(intercepts=array([ 0.12634366, 0.23737133, 0.24789398, 0.25225032, 0.22803295, - 0.18688178, 0.14271092, 0.01053395, -0.07344733, 0.01546678, - -0.23684551, -0.16533737, -0.03497767, -0.00162142, 0.01248823, - 0.01256806, 0.01508461]), linear_terms=array([[0., 0.], + [0., 0.]]]), scale=0.5837906205607757, shift=array([5.83790621, 0.17768436])), candidate_index=0, candidate_x=array([5.83790621, 0.17768436]), index=0, x=array([5.83790621, 0.17768436]), fval=0.25001791788397415, rho=nan, accepted=True, new_indices=[0], old_indices_used=[], old_indices_discarded=[], step_length=None, relative_step_length=None, n_evals_per_point=None, n_evals_acceptance=None), State(trustregion=Region(center=array([5.83790621, 0.17768436]), radius=0.5837906205607757, bounds=Bounds(lower=array([1.1 , 0.01]), upper=array([20. , 0.99]))), model_indices=array([ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12]), model=ScalarModel(intercept=5.453595147945511, linear_terms=array([-0.61048798, 16.31048865]), square_terms=array([[ 0.04668694, -0.92878469], + [-0.92878469, 25.23647844]]), scale=array([0.51737097, 0.34252766]), shift=array([5.83790621, 0.35252766])), vector_model=VectorModel(intercepts=array([ 0.04097031, 0.08957803, 0.08816081, 0.11232093, 0.12575895, + 0.13980376, 0.15781889, 0.17546538, 0.09348822, 0.15053254, + -0.17880431, -0.21077511, -0.08570458, -0.06416478, -0.05745986, + -0.05902133, -0.05316704]), linear_terms=array([[0., 0.], [0., 0.], [0., 0.], [0., 0.], @@ -3059,11 +4668,11 @@ algorithm_output,"{'states': [State(trustregion=Region(center=array([3.46495546, [0., 0.]], [[0., 0.], - [0., 0.]]]), scale=0.34649554641078373, shift=array([3.46495546, 0.53111681])), candidate_index=30, candidate_x=array([3.46483993, 0.53105746]), index=28, x=array([3.46488023, 0.53107033]), fval=0.3956174852241245, rho=-1.7965848703934482, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([ 0, 24, 25, 26, 27, 28, 29]), old_indices_discarded=array([], dtype=int64), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([3.46488023, 0.53107033]), radius=2.114840981511131e-05, bounds=Bounds(lower=array([2., 0.]), upper=array([20. , 0.7]))), model_indices=array([ 0, 26, 28, 29, 30]), model=ScalarModel(intercept=0.3956181532627989, linear_terms=array([-1.02960929e-05, 1.97454974e-05]), square_terms=array([[1.22430642e-09, 3.27096094e-09], - [3.27096094e-09, 3.60528919e-07]]), scale=2.114840981511131e-05, shift=array([3.46488023, 0.53107033])), vector_model=VectorModel(intercepts=array([ 0.12634366, 0.23737133, 0.24789398, 0.25225032, 0.22803295, - 0.18688178, 0.14271092, 0.01053395, -0.07344733, 0.01546678, - -0.23684551, -0.16533737, -0.03497767, -0.00162142, 0.01248823, - 0.01256806, 0.01508461]), linear_terms=array([[0., 0.], + [0., 0.]]]), scale=0.5837906205607757, shift=array([5.83790621, 0.17768436])), candidate_index=13, candidate_x=array([6.26028919, 0.14144164]), index=0, x=array([5.83790621, 0.17768436]), fval=0.25001791788397415, rho=-0.09994429546320836, accepted=False, new_indices=array([ 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12]), old_indices_used=array([0]), old_indices_discarded=array([], dtype=int64), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([5.83790621, 0.17768436]), radius=0.29189531028038784, bounds=Bounds(lower=array([1.1 , 0.01]), upper=array([20. , 0.99]))), model_indices=array([ 0, 1, 2, 3, 5, 6, 7, 8, 13]), model=ScalarModel(intercept=1.029847416702383, linear_terms=array([-0.15206957, 3.84463924]), square_terms=array([[ 0.02831952, -0.37138794], + [-0.37138794, 8.69674828]]), scale=array([0.25868548, 0.21318492]), shift=array([5.83790621, 0.22318492])), vector_model=VectorModel(intercepts=array([ 0.04097031, 0.08957803, 0.08816081, 0.11232093, 0.12575895, + 0.13980376, 0.15781889, 0.17546538, 0.09348822, 0.15053254, + -0.17880431, -0.21077511, -0.08570458, -0.06416478, -0.05745986, + -0.05902133, -0.05316704]), linear_terms=array([[0., 0.], [0., 0.], [0., 0.], [0., 0.], @@ -3128,11 +4737,11 @@ algorithm_output,"{'states': [State(trustregion=Region(center=array([3.46495546, [0., 0.]], [[0., 0.], - [0., 0.]]]), scale=0.34649554641078373, shift=array([3.46495546, 0.53111681])), candidate_index=31, candidate_x=array([3.46489016, 0.53105165]), index=28, x=array([3.46488023, 0.53107033]), fval=0.3956174852241245, rho=-0.6032905672690827, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([ 0, 26, 28, 29, 30]), old_indices_discarded=array([], dtype=int64), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([3.46488023, 0.53107033]), radius=1.0574204907555656e-05, bounds=Bounds(lower=array([2., 0.]), upper=array([20. , 0.7]))), model_indices=array([26, 28, 30, 31]), model=ScalarModel(intercept=0.3956218068343813, linear_terms=array([ 8.49414347e-07, -4.25281774e-06]), square_terms=array([[6.27885661e-11, 1.47178033e-09], - [1.47178033e-09, 8.86369949e-08]]), scale=1.0574204907555656e-05, shift=array([3.46488023, 0.53107033])), vector_model=VectorModel(intercepts=array([ 0.12634366, 0.23737133, 0.24789398, 0.25225032, 0.22803295, - 0.18688178, 0.14271092, 0.01053395, -0.07344733, 0.01546678, - -0.23684551, -0.16533737, -0.03497767, -0.00162142, 0.01248823, - 0.01256806, 0.01508461]), linear_terms=array([[0., 0.], + [0., 0.]]]), scale=0.5837906205607757, shift=array([5.83790621, 0.17768436])), candidate_index=14, candidate_x=array([5.58642299, 0.12009017]), index=0, x=array([5.83790621, 0.17768436]), fval=0.25001791788397415, rho=-0.36587111256709887, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([ 0, 1, 2, 3, 5, 6, 7, 8, 13]), old_indices_discarded=array([ 4, 9, 10, 11, 12]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([5.83790621, 0.17768436]), radius=0.14594765514019392, bounds=Bounds(lower=array([1.1 , 0.01]), upper=array([20. , 0.99]))), model_indices=array([ 0, 1, 3, 5, 6, 7, 8, 13, 14]), model=ScalarModel(intercept=0.3307652689377624, linear_terms=array([-0.05352468, 1.12834325]), square_terms=array([[ 0.01880846, -0.24791449], + [-0.24791449, 4.39579594]]), scale=0.14594765514019392, shift=array([5.83790621, 0.17768436])), vector_model=VectorModel(intercepts=array([ 0.04097031, 0.08957803, 0.08816081, 0.11232093, 0.12575895, + 0.13980376, 0.15781889, 0.17546538, 0.09348822, 0.15053254, + -0.17880431, -0.21077511, -0.08570458, -0.06416478, -0.05745986, + -0.05902133, -0.05316704]), linear_terms=array([[0., 0.], [0., 0.], [0., 0.], [0., 0.], @@ -3197,11 +4806,11 @@ algorithm_output,"{'states': [State(trustregion=Region(center=array([3.46495546, [0., 0.]], [[0., 0.], - [0., 0.]]]), scale=0.34649554641078373, shift=array([3.46495546, 0.53111681])), candidate_index=32, candidate_x=array([3.46487805, 0.53108067]), index=32, x=array([3.46487805, 0.53108067]), fval=0.39561434141034263, rho=0.7320668912639801, accepted=True, new_indices=array([], dtype=int64), old_indices_used=array([26, 28, 30, 31]), old_indices_discarded=array([], dtype=int64), step_length=1.0574204907534214e-05, relative_step_length=0.9999999999979723, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([3.46487805, 0.53108067]), radius=2.114840981511131e-05, bounds=Bounds(lower=array([2., 0.]), upper=array([20. , 0.7]))), model_indices=array([ 0, 26, 28, 29, 30, 31, 32]), model=ScalarModel(intercept=0.39562151267207407, linear_terms=array([ 2.2572996e-06, -1.4393150e-06]), square_terms=array([[2.89592558e-10, 5.93358722e-09], - [5.93358722e-09, 3.53991775e-07]]), scale=2.114840981511131e-05, shift=array([3.46487805, 0.53108067])), vector_model=VectorModel(intercepts=array([ 0.12634366, 0.23737133, 0.24789398, 0.25225032, 0.22803295, - 0.18688178, 0.14271092, 0.01053395, -0.07344733, 0.01546678, - -0.23684551, -0.16533737, -0.03497767, -0.00162142, 0.01248823, - 0.01256806, 0.01508461]), linear_terms=array([[0., 0.], + [0., 0.]]]), scale=0.5837906205607757, shift=array([5.83790621, 0.17768436])), candidate_index=15, candidate_x=array([5.6964718 , 0.13230174]), index=0, x=array([5.83790621, 0.17768436]), fval=0.25001791788397415, rho=-0.287744747266337, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([ 0, 1, 3, 5, 6, 7, 8, 13, 14]), old_indices_discarded=array([ 2, 4, 9, 10, 11]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([5.83790621, 0.17768436]), radius=0.07297382757009696, bounds=Bounds(lower=array([1.1 , 0.01]), upper=array([20. , 0.99]))), model_indices=array([ 0, 1, 14, 15]), model=ScalarModel(intercept=0.2547685338865855, linear_terms=array([-0.01144467, 0.12662975]), square_terms=array([[0.00075227, 0.00196842], + [0.00196842, 0.43154335]]), scale=0.07297382757009696, shift=array([5.83790621, 0.17768436])), vector_model=VectorModel(intercepts=array([ 0.04097031, 0.08957803, 0.08816081, 0.11232093, 0.12575895, + 0.13980376, 0.15781889, 0.17546538, 0.09348822, 0.15053254, + -0.17880431, -0.21077511, -0.08570458, -0.06416478, -0.05745986, + -0.05902133, -0.05316704]), linear_terms=array([[0., 0.], [0., 0.], [0., 0.], [0., 0.], @@ -3266,11 +4875,11 @@ algorithm_output,"{'states': [State(trustregion=Region(center=array([3.46495546, [0., 0.]], [[0., 0.], - [0., 0.]]]), scale=0.34649554641078373, shift=array([3.46495546, 0.53111681])), candidate_index=33, candidate_x=array([3.4648589 , 0.53109139]), index=32, x=array([3.46487805, 0.53108067]), fval=0.39561434141034263, rho=-1.623253391085488, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([ 0, 26, 28, 29, 30, 31, 32]), old_indices_discarded=array([], dtype=int64), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([3.46487805, 0.53108067]), radius=1.0574204907555656e-05, bounds=Bounds(lower=array([2., 0.]), upper=array([20. , 0.7]))), model_indices=array([26, 28, 30, 31, 32, 33]), model=ScalarModel(intercept=0.3956188473763767, linear_terms=array([ 2.78366342e-07, -3.10528724e-06]), square_terms=array([[2.68451586e-11, 9.59160265e-10], - [9.59160265e-10, 9.09248316e-08]]), scale=1.0574204907555656e-05, shift=array([3.46487805, 0.53108067])), vector_model=VectorModel(intercepts=array([ 0.12634366, 0.23737133, 0.24789398, 0.25225032, 0.22803295, - 0.18688178, 0.14271092, 0.01053395, -0.07344733, 0.01546678, - -0.23684551, -0.16533737, -0.03497767, -0.00162142, 0.01248823, - 0.01256806, 0.01508461]), linear_terms=array([[0., 0.], + [0., 0.]]]), scale=0.5837906205607757, shift=array([5.83790621, 0.17768436])), candidate_index=16, candidate_x=array([5.91074951, 0.15649323]), index=0, x=array([5.83790621, 0.17768436]), fval=0.25001791788397415, rho=-0.08075482115611035, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([ 0, 1, 14, 15]), old_indices_discarded=array([], dtype=int64), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([5.83790621, 0.17768436]), radius=0.03648691378504848, bounds=Bounds(lower=array([1.1 , 0.01]), upper=array([20. , 0.99]))), model_indices=array([ 0, 15, 16]), model=ScalarModel(intercept=0.250017917883974, linear_terms=array([0.00170653, 0.02764723]), square_terms=array([[5.79166409e-05, 1.55153703e-03], + [1.55153703e-03, 9.94464848e-02]]), scale=0.03648691378504848, shift=array([5.83790621, 0.17768436])), vector_model=VectorModel(intercepts=array([ 0.04097031, 0.08957803, 0.08816081, 0.11232093, 0.12575895, + 0.13980376, 0.15781889, 0.17546538, 0.09348822, 0.15053254, + -0.17880431, -0.21077511, -0.08570458, -0.06416478, -0.05745986, + -0.05902133, -0.05316704]), linear_terms=array([[0., 0.], [0., 0.], [0., 0.], [0., 0.], @@ -3335,11 +4944,11 @@ algorithm_output,"{'states': [State(trustregion=Region(center=array([3.46495546, [0., 0.]], [[0., 0.], - [0., 0.]]]), scale=0.34649554641078373, shift=array([3.46495546, 0.53111681])), candidate_index=34, candidate_x=array([3.46487695, 0.53109119]), index=32, x=array([3.46487805, 0.53108067]), fval=0.39561434141034263, rho=-1.4578840149671246, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([26, 28, 30, 31, 32, 33]), old_indices_discarded=array([], dtype=int64), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([3.46487805, 0.53108067]), radius=5.287102453777828e-06, bounds=Bounds(lower=array([2., 0.]), upper=array([20. , 0.7]))), model_indices=array([28, 32, 33, 34]), model=ScalarModel(intercept=0.39561689494513136, linear_terms=array([-3.07255257e-07, 3.15050176e-07]), square_terms=array([[8.41877738e-12, 1.23132438e-10], - [1.23132438e-10, 2.40117515e-08]]), scale=5.287102453777828e-06, shift=array([3.46487805, 0.53108067])), vector_model=VectorModel(intercepts=array([ 0.12634366, 0.23737133, 0.24789398, 0.25225032, 0.22803295, - 0.18688178, 0.14271092, 0.01053395, -0.07344733, 0.01546678, - -0.23684551, -0.16533737, -0.03497767, -0.00162142, 0.01248823, - 0.01256806, 0.01508461]), linear_terms=array([[0., 0.], + [0., 0.]]]), scale=0.5837906205607757, shift=array([5.83790621, 0.17768436])), candidate_index=17, candidate_x=array([5.8012702 , 0.16823018]), index=17, x=array([5.8012702 , 0.16823018]), fval=0.24610730524369165, rho=0.7658862060878359, accepted=True, new_indices=array([], dtype=int64), old_indices_used=array([ 0, 15, 16]), old_indices_discarded=array([], dtype=int64), step_length=0.03783620090025583, relative_step_length=1.0369800285975477, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([5.8012702 , 0.16823018]), radius=0.07297382757009696, bounds=Bounds(lower=array([1.1 , 0.01]), upper=array([20. , 0.99]))), model_indices=array([ 0, 1, 14, 15, 16, 17]), model=ScalarModel(intercept=0.253495790709351, linear_terms=array([-0.0041094 , 0.05810197]), square_terms=array([[1.86338211e-04, 5.35098646e-03], + [5.35098646e-03, 4.21903878e-01]]), scale=0.07297382757009696, shift=array([5.8012702 , 0.16823018])), vector_model=VectorModel(intercepts=array([ 0.04097031, 0.08957803, 0.08816081, 0.11232093, 0.12575895, + 0.13980376, 0.15781889, 0.17546538, 0.09348822, 0.15053254, + -0.17880431, -0.21077511, -0.08570458, -0.06416478, -0.05745986, + -0.05902133, -0.05316704]), linear_terms=array([[0., 0.], [0., 0.], [0., 0.], [0., 0.], @@ -3404,11 +5013,11 @@ algorithm_output,"{'states': [State(trustregion=Region(center=array([3.46495546, [0., 0.]], [[0., 0.], - [0., 0.]]]), scale=0.34649554641078373, shift=array([3.46495546, 0.53111681])), candidate_index=35, candidate_x=array([3.46488185, 0.53107699]), index=32, x=array([3.46487805, 0.53108067]), fval=0.39561434141034263, rho=-1.3868295186228046, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([28, 32, 33, 34]), old_indices_discarded=array([], dtype=int64), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([3.46487805, 0.53108067]), radius=2.643551226888914e-06, bounds=Bounds(lower=array([2., 0.]), upper=array([20. , 0.7]))), model_indices=array([28, 32, 34, 35]), model=ScalarModel(intercept=0.39561680085702, linear_terms=array([-8.88271352e-07, 5.51333878e-08]), square_terms=array([[ 5.09917383e-11, -1.34033240e-10], - [-1.34033240e-10, 5.95211095e-09]]), scale=2.643551226888914e-06, shift=array([3.46487805, 0.53108067])), vector_model=VectorModel(intercepts=array([ 0.12634366, 0.23737133, 0.24789398, 0.25225032, 0.22803295, - 0.18688178, 0.14271092, 0.01053395, -0.07344733, 0.01546678, - -0.23684551, -0.16533737, -0.03497767, -0.00162142, 0.01248823, - 0.01256806, 0.01508461]), linear_terms=array([[0., 0.], + [0., 0.]]]), scale=0.5837906205607757, shift=array([5.83790621, 0.17768436])), candidate_index=18, candidate_x=array([5.87411102, 0.15737845]), index=17, x=array([5.8012702 , 0.16823018]), fval=0.24610730524369165, rho=-0.5899514667309471, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([ 0, 1, 14, 15, 16, 17]), old_indices_discarded=array([], dtype=int64), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([5.8012702 , 0.16823018]), radius=0.03648691378504848, bounds=Bounds(lower=array([1.1 , 0.01]), upper=array([20. , 0.99]))), model_indices=array([ 0, 15, 16, 17, 18]), model=ScalarModel(intercept=0.2454286818777391, linear_terms=array([0.00117876, 0.00100895]), square_terms=array([[5.55180026e-05, 1.53917542e-03], + [1.53917542e-03, 9.97372256e-02]]), scale=0.03648691378504848, shift=array([5.8012702 , 0.16823018])), vector_model=VectorModel(intercepts=array([ 0.04097031, 0.08957803, 0.08816081, 0.11232093, 0.12575895, + 0.13980376, 0.15781889, 0.17546538, 0.09348822, 0.15053254, + -0.17880431, -0.21077511, -0.08570458, -0.06416478, -0.05745986, + -0.05902133, -0.05316704]), linear_terms=array([[0., 0.], [0., 0.], [0., 0.], [0., 0.], @@ -3473,11 +5082,11 @@ algorithm_output,"{'states': [State(trustregion=Region(center=array([3.46495546, [0., 0.]], [[0., 0.], - [0., 0.]]]), scale=0.34649554641078373, shift=array([3.46495546, 0.53111681])), candidate_index=36, candidate_x=array([3.4648807 , 0.53108051]), index=36, x=array([3.4648807 , 0.53108051]), fval=0.3956142498671711, rho=0.10253535956354096, accepted=True, new_indices=array([], dtype=int64), old_indices_used=array([28, 32, 34, 35]), old_indices_discarded=array([], dtype=int64), step_length=2.652048375671223e-06, relative_step_length=1.0032142932188641, n_evals_per_point=1, n_evals_acceptance=1)], 'message': 'Absolute criterion change smaller than tolerance.', 'tranquilo_history': History for least_squares function with 37 entries., 'history': {'params': [{'CRRA': 3.4649554641078373, 'WealthShare': 0.5311168059313219}, {'CRRA': 3.157881781329135, 'WealthShare': 0.2473224681244135}, {'CRRA': 3.7624746846917523, 'WealthShare': 0.2240431231526196}, {'CRRA': 3.157881781329135, 'WealthShare': 0.39945742240679216}, {'CRRA': 3.7720291468865397, 'WealthShare': 0.47185802634006707}, {'CRRA': 3.6802362818077867, 'WealthShare': 0.2240431231526196}, {'CRRA': 3.441211346545693, 'WealthShare': 0.2240431231526196}, {'CRRA': 3.414421953240863, 'WealthShare': 0.7}, {'CRRA': 3.7021523455480567, 'WealthShare': 0.7}, {'CRRA': 3.7720291468865397, 'WealthShare': 0.6686480732500195}, {'CRRA': 3.157881781329135, 'WealthShare': 0.644517740993325}, {'CRRA': 3.172045493464639, 'WealthShare': 0.2240431231526196}, {'CRRA': 3.157881781329135, 'WealthShare': 0.6866039476106396}, {'CRRA': 3.455278172006866, 'WealthShare': 0.6436952348818475}, {'CRRA': 3.482717703228099, 'WealthShare': 0.6417742340652457}, {'CRRA': 3.441630262094873, 'WealthShare': 0.6145412189122421}, {'CRRA': 3.4225129052316277, 'WealthShare': 0.5409370822026279}, {'CRRA': 3.48570373260534, 'WealthShare': 0.5385055107833469}, {'CRRA': 3.45413017601394, 'WealthShare': 0.5314546894521868}, {'CRRA': 3.4703702709656685, 'WealthShare': 0.5312990270552305}, {'CRRA': 3.462248200145725, 'WealthShare': 0.530847877975147}, {'CRRA': 3.4638025081397066, 'WealthShare': 0.5318415196290966}, {'CRRA': 3.4656314186145827, 'WealthShare': 0.5309971525911571}, {'CRRA': 3.464712119677216, 'WealthShare': 0.5308816871763512}, {'CRRA': 3.464890623443189, 'WealthShare': 0.5312730750051059}, {'CRRA': 3.4650398450169457, 'WealthShare': 0.5311228495266765}, {'CRRA': 3.464920807106532, 'WealthShare': 0.531090434133886}, {'CRRA': 3.4649978061511297, 'WealthShare': 0.5311258572691309}, {'CRRA': 3.464880230664965, 'WealthShare': 0.5310703256463739}, {'CRRA': 3.464952398623187, 'WealthShare': 0.5311262977250806}, {'CRRA': 3.4648399335878723, 'WealthShare': 0.5310574559629038}, {'CRRA': 3.4648901610076788, 'WealthShare': 0.5310516536477853}, {'CRRA': 3.464878050381357, 'WealthShare': 0.5310806726349607}, {'CRRA': 3.4648589045442115, 'WealthShare': 0.5310913913171672}, {'CRRA': 3.4648769489031097, 'WealthShare': 0.5310911893148121}, {'CRRA': 3.464881847329815, 'WealthShare': 0.5310769861229598}, {'CRRA': 3.4648806974271817, 'WealthShare': 0.531080509819149}], 'criterion': [0.39562420447382873, nan, nan, 1249.0421729795332, 4.5855832763431605, nan, nan, 1.782112614018569, 1.7275923424114168, 1.518523655995384, 1.4474192855818668, nan, 1.7651374405691542, 1.3785818478738974, 1.3585841212907663, 1.1259853008712912, 0.4233413203746081, 0.4129242103340959, 0.3956984921310528, 0.3956976570754178, 0.39572955785625985, 0.3959256106740631, 0.3956710774610568, 0.3956905152391518, 0.3956413061786618, 0.3956329828030912, 0.39561894207152565, 0.3956373587107717, 0.39561748522412454, 0.3956373350012253, 0.3956257638497452, 0.3956308352280355, 0.39561434141034263, 0.3956187731851536, 0.39561882078905886, 0.39561494406024583, 0.39561424986717103], 'runtime': [0.0, 1.4629678609999246, 1.5032358759999624, 1.5490633109984628, 1.6017019739992975, 1.6470571870013373, 1.7097121350016096, 1.7486153659992851, 1.8122890449994884, 1.8663734100009606, 1.925586204000865, 1.9781071479992534, 2.021414527000161, 66.43172447599864, 67.78483922300074, 69.72082065200084, 71.04146697300166, 72.39164718100074, 73.7096145530013, 75.03324087600049, 76.35381426299864, 77.68544955800098, 79.02472872300132, 80.4109739480009, 81.81492040900048, 83.37987046299895, 84.72980602900134, 86.15332707500056, 87.53151713899933, 88.87330793100045, 90.2113333640009, 91.54731987999912, 92.89468507399943, 94.22075996399872, 95.6565283150012, 97.04244493000078, 98.44442257500123], 'batches': [0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25]}, 'multistart_info': {...}}, {'solution_x': array([3.45814229, 0.53129297]), 'solution_criterion': 0.39565506510735315, 'states': [State(trustregion=Region(center=array([4.35384656, 0.52929957]), radius=0.43538465594405756, bounds=Bounds(lower=array([2., 0.]), upper=array([20. , 0.7]))), model_indices=[0], model=ScalarModel(intercept=0.4255893672451761, linear_terms=array([0., 0.]), square_terms=array([[0., 0.], - [0., 0.]]), scale=0.43538465594405756, shift=array([4.35384656, 0.52929957])), vector_model=VectorModel(intercepts=array([ 0.12803165, 0.23858248, 0.24705727, 0.24876636, 0.22173997, - 0.1770757 , 0.12976233, -0.01593805, -0.10083657, -0.01010953, - -0.25513117, -0.16998206, -0.10775377, -0.0739005 , -0.05953791, - -0.05947176, -0.05768123]), linear_terms=array([[0., 0.], + [0., 0.]]]), scale=0.5837906205607757, shift=array([5.83790621, 0.17768436])), candidate_index=19, candidate_x=array([5.76478191, 0.168422 ]), index=19, x=array([5.76478191, 0.168422 ]), fval=0.2454218974000159, rho=0.5947364727296277, accepted=True, new_indices=array([], dtype=int64), old_indices_used=array([ 0, 15, 16, 17, 18]), old_indices_discarded=array([], dtype=int64), step_length=0.03648879990395198, relative_step_length=1.0000516930238224, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([5.76478191, 0.168422 ]), radius=0.07297382757009696, bounds=Bounds(lower=array([1.1 , 0.01]), upper=array([20. , 0.99]))), model_indices=array([ 0, 1, 14, 15, 16, 17, 18, 19]), model=ScalarModel(intercept=0.253681629181515, linear_terms=array([-0.00232564, 0.05166204]), square_terms=array([[1.50344993e-04, 5.87973754e-03], + [5.87973754e-03, 4.19729698e-01]]), scale=0.07297382757009696, shift=array([5.76478191, 0.168422 ])), vector_model=VectorModel(intercepts=array([ 0.04097031, 0.08957803, 0.08816081, 0.11232093, 0.12575895, + 0.13980376, 0.15781889, 0.17546538, 0.09348822, 0.15053254, + -0.17880431, -0.21077511, -0.08570458, -0.06416478, -0.05745986, + -0.05902133, -0.05316704]), linear_terms=array([[0., 0.], [0., 0.], [0., 0.], [0., 0.], @@ -3542,11 +5151,11 @@ algorithm_output,"{'states': [State(trustregion=Region(center=array([3.46495546, [0., 0.]], [[0., 0.], - [0., 0.]]]), scale=0.43538465594405756, shift=array([4.35384656, 0.52929957])), candidate_index=0, candidate_x=array([4.35384656, 0.52929957]), index=0, x=array([4.35384656, 0.52929957]), fval=0.4255893672451761, rho=nan, accepted=True, new_indices=[0], old_indices_used=[], old_indices_discarded=[], step_length=None, relative_step_length=None, n_evals_per_point=None, n_evals_acceptance=None), State(trustregion=Region(center=array([4.35384656, 0.52929957]), radius=0.43538465594405756, bounds=Bounds(lower=array([2., 0.]), upper=array([20. , 0.7]))), model_indices=array([ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12]), model=ScalarModel(intercept=377.6978507262316, linear_terms=array([ -36.37981997, -999.11364507]), square_terms=array([[ 1.79076521, 48.16028899], - [ 48.16028899, 1322.02799655]]), scale=array([0.38584961, 0.27827502]), shift=array([4.35384656, 0.42172498])), vector_model=VectorModel(intercepts=array([ 0.12803165, 0.23858248, 0.24705727, 0.24876636, 0.22173997, - 0.1770757 , 0.12976233, -0.01593805, -0.10083657, -0.01010953, - -0.25513117, -0.16998206, -0.10775377, -0.0739005 , -0.05953791, - -0.05947176, -0.05768123]), linear_terms=array([[0., 0.], + [0., 0.]]]), scale=0.5837906205607757, shift=array([5.83790621, 0.17768436])), candidate_index=20, candidate_x=array([5.83762294, 0.15849024]), index=19, x=array([5.76478191, 0.168422 ]), fval=0.2454218974000159, rho=-0.7653738840742371, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([ 0, 1, 14, 15, 16, 17, 18, 19]), old_indices_discarded=array([], dtype=int64), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([5.76478191, 0.168422 ]), radius=0.03648691378504848, bounds=Bounds(lower=array([1.1 , 0.01]), upper=array([20. , 0.99]))), model_indices=array([ 0, 15, 16, 17, 18, 19, 20]), model=ScalarModel(intercept=0.24478338352931536, linear_terms=array([0.00104386, 0.00067952]), square_terms=array([[5.17736477e-05, 1.49720466e-03], + [1.49720466e-03, 1.00208068e-01]]), scale=0.03648691378504848, shift=array([5.76478191, 0.168422 ])), vector_model=VectorModel(intercepts=array([ 0.04097031, 0.08957803, 0.08816081, 0.11232093, 0.12575895, + 0.13980376, 0.15781889, 0.17546538, 0.09348822, 0.15053254, + -0.17880431, -0.21077511, -0.08570458, -0.06416478, -0.05745986, + -0.05902133, -0.05316704]), linear_terms=array([[0., 0.], [0., 0.], [0., 0.], [0., 0.], @@ -3611,11 +5220,11 @@ algorithm_output,"{'states': [State(trustregion=Region(center=array([3.46495546, [0., 0.]], [[0., 0.], - [0., 0.]]]), scale=0.43538465594405756, shift=array([4.35384656, 0.52929957])), candidate_index=13, candidate_x=array([4.17339648, 0.63677034]), index=0, x=array([4.35384656, 0.52929957]), fval=0.4255893672451761, rho=-0.00924668015262282, accepted=False, new_indices=array([ 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12]), old_indices_used=array([0]), old_indices_discarded=array([], dtype=int64), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([4.35384656, 0.52929957]), radius=0.21769232797202878, bounds=Bounds(lower=array([2., 0.]), upper=array([20. , 0.7]))), model_indices=array([ 0, 2, 3, 4, 8, 9, 11, 12, 13]), model=ScalarModel(intercept=63.54209178730432, linear_terms=array([ 0.60854793, -233.82637595]), square_terms=array([[ 2.29242839e-02, -1.10709122e+00], - [-1.10709122e+00, 4.31404981e+02]]), scale=array([0.1929248 , 0.18181262]), shift=array([4.35384656, 0.51818738])), vector_model=VectorModel(intercepts=array([ 0.12803165, 0.23858248, 0.24705727, 0.24876636, 0.22173997, - 0.1770757 , 0.12976233, -0.01593805, -0.10083657, -0.01010953, - -0.25513117, -0.16998206, -0.10775377, -0.0739005 , -0.05953791, - -0.05947176, -0.05768123]), linear_terms=array([[0., 0.], + [0., 0.]]]), scale=0.5837906205607757, shift=array([5.83790621, 0.17768436])), candidate_index=21, candidate_x=array([5.72829533, 0.16871677]), index=21, x=array([5.72829533, 0.16871677]), fval=0.24507292693629099, rho=0.3416935494926942, accepted=True, new_indices=array([], dtype=int64), old_indices_used=array([ 0, 15, 16, 17, 18, 19, 20]), old_indices_discarded=array([], dtype=int64), step_length=0.03648777162651111, relative_step_length=1.0000235109351172, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([5.72829533, 0.16871677]), radius=0.07297382757009696, bounds=Bounds(lower=array([1.1 , 0.01]), upper=array([20. , 0.99]))), model_indices=array([ 0, 14, 15, 16, 17, 18, 19, 20, 21]), model=ScalarModel(intercept=0.24391675099982854, linear_terms=array([0.00218857, 0.00331565]), square_terms=array([[2.17190744e-04, 6.18094476e-03], + [6.18094476e-03, 4.05581192e-01]]), scale=0.07297382757009696, shift=array([5.72829533, 0.16871677])), vector_model=VectorModel(intercepts=array([ 0.04097031, 0.08957803, 0.08816081, 0.11232093, 0.12575895, + 0.13980376, 0.15781889, 0.17546538, 0.09348822, 0.15053254, + -0.17880431, -0.21077511, -0.08570458, -0.06416478, -0.05745986, + -0.05902133, -0.05316704]), linear_terms=array([[0., 0.], [0., 0.], [0., 0.], [0., 0.], @@ -3680,11 +5289,11 @@ algorithm_output,"{'states': [State(trustregion=Region(center=array([3.46495546, [0., 0.]], [[0., 0.], - [0., 0.]]]), scale=0.43538465594405756, shift=array([4.35384656, 0.52929957])), candidate_index=14, candidate_x=array([4.27227034, 0.61653459]), index=0, x=array([4.35384656, 0.52929957]), fval=0.4255893672451761, rho=-0.013438966434662449, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([ 0, 2, 3, 4, 8, 9, 11, 12, 13]), old_indices_discarded=array([ 1, 5, 6, 7, 10]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([4.35384656, 0.52929957]), radius=0.10884616398601439, bounds=Bounds(lower=array([2., 0.]), upper=array([20. , 0.7]))), model_indices=array([ 0, 2, 3, 4, 8, 9, 12, 13, 14]), model=ScalarModel(intercept=0.6281511524220714, linear_terms=array([ 0.16811021, -1.64996024]), square_terms=array([[ 0.05467892, -0.47706158], - [-0.47706158, 4.26415814]]), scale=0.10884616398601439, shift=array([4.35384656, 0.52929957])), vector_model=VectorModel(intercepts=array([ 0.12803165, 0.23858248, 0.24705727, 0.24876636, 0.22173997, - 0.1770757 , 0.12976233, -0.01593805, -0.10083657, -0.01010953, - -0.25513117, -0.16998206, -0.10775377, -0.0739005 , -0.05953791, - -0.05947176, -0.05768123]), linear_terms=array([[0., 0.], + [0., 0.]]]), scale=0.5837906205607757, shift=array([5.83790621, 0.17768436])), candidate_index=22, candidate_x=array([5.65532086, 0.16922977]), index=22, x=array([5.65532086, 0.16922977]), fval=0.24407445209754292, rho=0.4777137071010113, accepted=True, new_indices=array([], dtype=int64), old_indices_used=array([ 0, 14, 15, 16, 17, 18, 19, 20, 21]), old_indices_discarded=array([1]), step_length=0.07297626535254732, relative_step_length=1.0000334062571683, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([5.65532086, 0.16922977]), radius=0.14594765514019392, bounds=Bounds(lower=array([1.1 , 0.01]), upper=array([20. , 0.99]))), model_indices=array([ 0, 1, 14, 15, 17, 19, 20, 21, 22]), model=ScalarModel(intercept=0.2530356753079221, linear_terms=array([-0.00506925, 0.09004345]), square_terms=array([[5.16559769e-04, 2.11789911e-02], + [2.11789911e-02, 1.68392550e+00]]), scale=0.14594765514019392, shift=array([5.65532086, 0.16922977])), vector_model=VectorModel(intercepts=array([ 0.04097031, 0.08957803, 0.08816081, 0.11232093, 0.12575895, + 0.13980376, 0.15781889, 0.17546538, 0.09348822, 0.15053254, + -0.17880431, -0.21077511, -0.08570458, -0.06416478, -0.05745986, + -0.05902133, -0.05316704]), linear_terms=array([[0., 0.], [0., 0.], [0., 0.], [0., 0.], @@ -3749,11 +5358,11 @@ algorithm_output,"{'states': [State(trustregion=Region(center=array([3.46495546, [0., 0.]], [[0., 0.], - [0., 0.]]]), scale=0.43538465594405756, shift=array([4.35384656, 0.52929957])), candidate_index=15, candidate_x=array([4.45724418, 0.58279373]), index=0, x=array([4.35384656, 0.52929957]), fval=0.4255893672451761, rho=-1.140692253191956, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([ 0, 2, 3, 4, 8, 9, 12, 13, 14]), old_indices_discarded=array([ 1, 5, 6, 7, 10, 11]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([4.35384656, 0.52929957]), radius=0.054423081993007195, bounds=Bounds(lower=array([2., 0.]), upper=array([20. , 0.7]))), model_indices=array([ 0, 12, 13, 14, 15]), model=ScalarModel(intercept=0.46584348277778886, linear_terms=array([-0.00010277, 0.08576083]), square_terms=array([[ 0.00041137, -0.00810852], - [-0.00810852, 0.24585694]]), scale=0.054423081993007195, shift=array([4.35384656, 0.52929957])), vector_model=VectorModel(intercepts=array([ 0.12803165, 0.23858248, 0.24705727, 0.24876636, 0.22173997, - 0.1770757 , 0.12976233, -0.01593805, -0.10083657, -0.01010953, - -0.25513117, -0.16998206, -0.10775377, -0.0739005 , -0.05953791, - -0.05947176, -0.05768123]), linear_terms=array([[0., 0.], + [0., 0.]]]), scale=0.5837906205607757, shift=array([5.83790621, 0.17768436])), candidate_index=23, candidate_x=array([5.80115826, 0.15962533]), index=22, x=array([5.65532086, 0.16922977]), fval=0.24407445209754292, rho=-0.5666553713621563, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([ 0, 1, 14, 15, 17, 19, 20, 21, 22]), old_indices_discarded=array([ 2, 3, 5, 6, 7, 8, 10, 11, 12, 13, 16, 18]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([5.65532086, 0.16922977]), radius=0.07297382757009696, bounds=Bounds(lower=array([1.1 , 0.01]), upper=array([20. , 0.99]))), model_indices=array([ 0, 14, 15, 17, 19, 20, 21, 22, 23]), model=ScalarModel(intercept=0.24311624432173012, linear_terms=array([0.00154361, 0.00363361]), square_terms=array([[1.87587564e-04, 5.59513446e-03], + [5.59513446e-03, 4.10801212e-01]]), scale=0.07297382757009696, shift=array([5.65532086, 0.16922977])), vector_model=VectorModel(intercepts=array([ 0.04097031, 0.08957803, 0.08816081, 0.11232093, 0.12575895, + 0.13980376, 0.15781889, 0.17546538, 0.09348822, 0.15053254, + -0.17880431, -0.21077511, -0.08570458, -0.06416478, -0.05745986, + -0.05902133, -0.05316704]), linear_terms=array([[0., 0.], [0., 0.], [0., 0.], [0., 0.], @@ -3818,11 +5427,11 @@ algorithm_output,"{'states': [State(trustregion=Region(center=array([3.46495546, [0., 0.]], [[0., 0.], - [0., 0.]]]), scale=0.43538465594405756, shift=array([4.35384656, 0.52929957])), candidate_index=16, candidate_x=array([4.30009828, 0.50875867]), index=0, x=array([4.35384656, 0.52929957]), fval=0.4255893672451761, rho=-6.943883313244753, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([ 0, 12, 13, 14, 15]), old_indices_discarded=array([], dtype=int64), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([4.35384656, 0.52929957]), radius=0.027211540996503598, bounds=Bounds(lower=array([2., 0.]), upper=array([20. , 0.7]))), model_indices=array([ 0, 14, 15, 16]), model=ScalarModel(intercept=0.41424994080991806, linear_terms=array([ 0.00226417, -0.0371532 ]), square_terms=array([[0.00154248, 0.01657008], - [0.01657008, 0.18573226]]), scale=0.027211540996503598, shift=array([4.35384656, 0.52929957])), vector_model=VectorModel(intercepts=array([ 0.12803165, 0.23858248, 0.24705727, 0.24876636, 0.22173997, - 0.1770757 , 0.12976233, -0.01593805, -0.10083657, -0.01010953, - -0.25513117, -0.16998206, -0.10775377, -0.0739005 , -0.05953791, - -0.05947176, -0.05768123]), linear_terms=array([[0., 0.], + [0., 0.]]]), scale=0.5837906205607757, shift=array([5.83790621, 0.17768436])), candidate_index=24, candidate_x=array([5.58234504, 0.16957707]), index=24, x=array([5.58234504, 0.16957707]), fval=0.24318410996735987, rho=0.6121148476317633, accepted=True, new_indices=array([], dtype=int64), old_indices_used=array([ 0, 14, 15, 17, 19, 20, 21, 22, 23]), old_indices_discarded=array([ 1, 16, 18]), step_length=0.0729766486457952, relative_step_length=1.0000386587327563, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([5.58234504, 0.16957707]), radius=0.14594765514019392, bounds=Bounds(lower=array([1.1 , 0.01]), upper=array([20. , 0.99]))), model_indices=array([ 1, 14, 15, 17, 19, 21, 22, 23, 24]), model=ScalarModel(intercept=0.2489283617541748, linear_terms=array([0.00068245, 0.07288776]), square_terms=array([[5.95004131e-04, 2.31002626e-02], + [2.31002626e-02, 1.68009048e+00]]), scale=0.14594765514019392, shift=array([5.58234504, 0.16957707])), vector_model=VectorModel(intercepts=array([ 0.04097031, 0.08957803, 0.08816081, 0.11232093, 0.12575895, + 0.13980376, 0.15781889, 0.17546538, 0.09348822, 0.15053254, + -0.17880431, -0.21077511, -0.08570458, -0.06416478, -0.05745986, + -0.05902133, -0.05316704]), linear_terms=array([[0., 0.], [0., 0.], [0., 0.], [0., 0.], @@ -3887,11 +5496,11 @@ algorithm_output,"{'states': [State(trustregion=Region(center=array([3.46495546, [0., 0.]], [[0., 0.], - [0., 0.]]]), scale=0.43538465594405756, shift=array([4.35384656, 0.52929957])), candidate_index=17, candidate_x=array([4.32720493, 0.53689501]), index=0, x=array([4.35384656, 0.52929957]), fval=0.4255893672451761, rho=-2.2673247572907647, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([ 0, 14, 15, 16]), old_indices_discarded=array([], dtype=int64), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([4.35384656, 0.52929957]), radius=0.013605770498251799, bounds=Bounds(lower=array([2., 0.]), upper=array([20. , 0.7]))), model_indices=array([ 0, 16, 17]), model=ScalarModel(intercept=0.42558936724517604, linear_terms=array([0.00318577, 0.02380746]), square_terms=array([[0.00023327, 0.00516068], - [0.00516068, 0.12107919]]), scale=0.013605770498251799, shift=array([4.35384656, 0.52929957])), vector_model=VectorModel(intercepts=array([ 0.12803165, 0.23858248, 0.24705727, 0.24876636, 0.22173997, - 0.1770757 , 0.12976233, -0.01593805, -0.10083657, -0.01010953, - -0.25513117, -0.16998206, -0.10775377, -0.0739005 , -0.05953791, - -0.05947176, -0.05768123]), linear_terms=array([[0., 0.], + [0., 0.]]]), scale=0.5837906205607757, shift=array([5.83790621, 0.17768436])), candidate_index=25, candidate_x=array([5.72806121, 0.16124208]), index=24, x=array([5.58234504, 0.16957707]), fval=0.24318410996735987, rho=-2.230953042384717, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([ 1, 14, 15, 17, 19, 21, 22, 23, 24]), old_indices_discarded=array([ 0, 3, 6, 7, 8, 10, 11, 12, 13, 16, 18, 20]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([5.58234504, 0.16957707]), radius=0.07297382757009696, bounds=Bounds(lower=array([1.1 , 0.01]), upper=array([20. , 0.99]))), model_indices=array([ 1, 14, 15, 17, 19, 21, 22, 24, 25]), model=ScalarModel(intercept=0.24930004394171532, linear_terms=array([-2.38904522e-06, 3.69499149e-02]), square_terms=array([[1.38670904e-04, 5.63202076e-03], + [5.63202076e-03, 4.20322174e-01]]), scale=0.07297382757009696, shift=array([5.58234504, 0.16957707])), vector_model=VectorModel(intercepts=array([ 0.04097031, 0.08957803, 0.08816081, 0.11232093, 0.12575895, + 0.13980376, 0.15781889, 0.17546538, 0.09348822, 0.15053254, + -0.17880431, -0.21077511, -0.08570458, -0.06416478, -0.05745986, + -0.05902133, -0.05316704]), linear_terms=array([[0., 0.], [0., 0.], [0., 0.], [0., 0.], @@ -3956,11 +5565,11 @@ algorithm_output,"{'states': [State(trustregion=Region(center=array([3.46495546, [0., 0.]], [[0., 0.], - [0., 0.]]]), scale=0.43538465594405756, shift=array([4.35384656, 0.52929957])), candidate_index=18, candidate_x=array([4.34014088, 0.52724505]), index=18, x=array([4.34014088, 0.52724505]), fval=0.42336352037134833, rho=0.49240177012117414, accepted=True, new_indices=array([], dtype=int64), old_indices_used=array([ 0, 16, 17]), old_indices_discarded=array([], dtype=int64), step_length=0.01385880791623352, relative_step_length=1.0185978014265515, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([4.34014088, 0.52724505]), radius=0.027211540996503598, bounds=Bounds(lower=array([2., 0.]), upper=array([20. , 0.7]))), model_indices=array([ 0, 14, 15, 16, 17, 18]), model=ScalarModel(intercept=0.4188488070632087, linear_terms=array([ 0.00256517, -0.03310186]), square_terms=array([[0.00129691, 0.01458337], - [0.01458337, 0.17209804]]), scale=0.027211540996503598, shift=array([4.34014088, 0.52724505])), vector_model=VectorModel(intercepts=array([ 0.12803165, 0.23858248, 0.24705727, 0.24876636, 0.22173997, - 0.1770757 , 0.12976233, -0.01593805, -0.10083657, -0.01010953, - -0.25513117, -0.16998206, -0.10775377, -0.0739005 , -0.05953791, - -0.05947176, -0.05768123]), linear_terms=array([[0., 0.], + [0., 0.]]]), scale=0.5837906205607757, shift=array([5.83790621, 0.17768436])), candidate_index=26, candidate_x=array([5.65521399, 0.16219328]), index=24, x=array([5.58234504, 0.16957707]), fval=0.24318410996735987, rho=-1.2961620458518521, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([ 1, 14, 15, 17, 19, 21, 22, 24, 25]), old_indices_discarded=array([ 0, 3, 7, 11, 16, 18, 20, 23]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([5.58234504, 0.16957707]), radius=0.03648691378504848, bounds=Bounds(lower=array([1.1 , 0.01]), upper=array([20. , 0.99]))), model_indices=array([ 1, 14, 15, 21, 22, 24, 25, 26]), model=ScalarModel(intercept=0.24709268914155363, linear_terms=array([0.00119193, 0.01731959]), square_terms=array([[5.69678824e-05, 1.57856574e-03], + [1.57856574e-03, 1.04842584e-01]]), scale=0.03648691378504848, shift=array([5.58234504, 0.16957707])), vector_model=VectorModel(intercepts=array([ 0.04097031, 0.08957803, 0.08816081, 0.11232093, 0.12575895, + 0.13980376, 0.15781889, 0.17546538, 0.09348822, 0.15053254, + -0.17880431, -0.21077511, -0.08570458, -0.06416478, -0.05745986, + -0.05902133, -0.05316704]), linear_terms=array([[0., 0.], [0., 0.], [0., 0.], [0., 0.], @@ -4025,11 +5634,11 @@ algorithm_output,"{'states': [State(trustregion=Region(center=array([3.46495546, [0., 0.]], [[0., 0.], - [0., 0.]]]), scale=0.43538465594405756, shift=array([4.35384656, 0.52929957])), candidate_index=19, candidate_x=array([4.3134484, 0.5345173]), index=18, x=array([4.34014088, 0.52724505]), fval=0.42336352037134833, rho=-1.5617520822417594, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([ 0, 14, 15, 16, 17, 18]), old_indices_discarded=array([], dtype=int64), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([4.34014088, 0.52724505]), radius=0.013605770498251799, bounds=Bounds(lower=array([2., 0.]), upper=array([20. , 0.7]))), model_indices=array([ 0, 16, 17, 18, 19]), model=ScalarModel(intercept=0.4217976887258373, linear_terms=array([0.00192926, 0.00338483]), square_terms=array([[0.00016241, 0.00437066], - [0.00437066, 0.12615737]]), scale=0.013605770498251799, shift=array([4.34014088, 0.52724505])), vector_model=VectorModel(intercepts=array([ 0.12803165, 0.23858248, 0.24705727, 0.24876636, 0.22173997, - 0.1770757 , 0.12976233, -0.01593805, -0.10083657, -0.01010953, - -0.25513117, -0.16998206, -0.10775377, -0.0739005 , -0.05953791, - -0.05947176, -0.05768123]), linear_terms=array([[0., 0.], + [0., 0.]]]), scale=0.5837906205607757, shift=array([5.83790621, 0.17768436])), candidate_index=27, candidate_x=array([5.54577406, 0.16414671]), index=24, x=array([5.58234504, 0.16957707]), fval=0.24318410996735987, rho=-0.5277296110416976, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([ 1, 14, 15, 21, 22, 24, 25, 26]), old_indices_discarded=array([], dtype=int64), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([5.58234504, 0.16957707]), radius=0.01824345689252424, bounds=Bounds(lower=array([1.1 , 0.01]), upper=array([20. , 0.99]))), model_indices=array([14, 22, 24, 26, 27]), model=ScalarModel(intercept=0.2435860331988614, linear_terms=array([0.00019367, 0.00162664]), square_terms=array([[1.03223473e-05, 3.21675100e-04], + [3.21675100e-04, 2.62070841e-02]]), scale=0.01824345689252424, shift=array([5.58234504, 0.16957707])), vector_model=VectorModel(intercepts=array([ 0.04097031, 0.08957803, 0.08816081, 0.11232093, 0.12575895, + 0.13980376, 0.15781889, 0.17546538, 0.09348822, 0.15053254, + -0.17880431, -0.21077511, -0.08570458, -0.06416478, -0.05745986, + -0.05902133, -0.05316704]), linear_terms=array([[0., 0.], [0., 0.], [0., 0.], [0., 0.], @@ -4094,11 +5703,11 @@ algorithm_output,"{'states': [State(trustregion=Region(center=array([3.46495546, [0., 0.]], [[0., 0.], - [0., 0.]]]), scale=0.43538465594405756, shift=array([4.35384656, 0.52929957])), candidate_index=20, candidate_x=array([4.32653059, 0.52735003]), index=20, x=array([4.32653059, 0.52735003]), fval=0.4227151200490358, rho=0.35001305891523005, accepted=True, new_indices=array([], dtype=int64), old_indices_used=array([ 0, 16, 17, 18, 19]), old_indices_discarded=array([], dtype=int64), step_length=0.013610701636007961, relative_step_length=1.0003624298790572, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([4.32653059, 0.52735003]), radius=0.027211540996503598, bounds=Bounds(lower=array([2., 0.]), upper=array([20. , 0.7]))), model_indices=array([ 0, 14, 16, 17, 18, 19, 20]), model=ScalarModel(intercept=0.4198431543361459, linear_terms=array([ 0.01022161, -0.02062274]), square_terms=array([[0.01372817, 0.05304624], - [0.05304624, 0.21005163]]), scale=0.027211540996503598, shift=array([4.32653059, 0.52735003])), vector_model=VectorModel(intercepts=array([ 0.12803165, 0.23858248, 0.24705727, 0.24876636, 0.22173997, - 0.1770757 , 0.12976233, -0.01593805, -0.10083657, -0.01010953, - -0.25513117, -0.16998206, -0.10775377, -0.0739005 , -0.05953791, - -0.05947176, -0.05768123]), linear_terms=array([[0., 0.], + [0., 0.]]]), scale=0.5837906205607757, shift=array([5.83790621, 0.17768436])), candidate_index=28, candidate_x=array([5.56408927, 0.16867456]), index=28, x=array([5.56408927, 0.16867456]), fval=0.24306721295336703, rho=0.5286886005963327, accepted=True, new_indices=array([], dtype=int64), old_indices_used=array([14, 22, 24, 26, 27]), old_indices_discarded=array([], dtype=int64), step_length=0.018278068411800873, relative_step_length=1.0018972018012011, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([5.56408927, 0.16867456]), radius=0.03648691378504848, bounds=Bounds(lower=array([1.1 , 0.01]), upper=array([20. , 0.99]))), model_indices=array([14, 15, 21, 22, 24, 25, 26, 27, 28]), model=ScalarModel(intercept=0.242964314677221, linear_terms=array([ 0.00054927, -0.00108451]), square_terms=array([[4.50168218e-05, 1.34975492e-03], + [1.34975492e-03, 1.03947965e-01]]), scale=0.03648691378504848, shift=array([5.56408927, 0.16867456])), vector_model=VectorModel(intercepts=array([ 0.04097031, 0.08957803, 0.08816081, 0.11232093, 0.12575895, + 0.13980376, 0.15781889, 0.17546538, 0.09348822, 0.15053254, + -0.17880431, -0.21077511, -0.08570458, -0.06416478, -0.05745986, + -0.05902133, -0.05316704]), linear_terms=array([[0., 0.], [0., 0.], [0., 0.], [0., 0.], @@ -4163,11 +5772,11 @@ algorithm_output,"{'states': [State(trustregion=Region(center=array([3.46495546, [0., 0.]], [[0., 0.], - [0., 0.]]]), scale=0.43538465594405756, shift=array([4.35384656, 0.52929957])), candidate_index=21, candidate_x=array([4.30063979, 0.53595945]), index=20, x=array([4.32653059, 0.52735003]), fval=0.4227151200490358, rho=-1.1682048675203691, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([ 0, 14, 16, 17, 18, 19, 20]), old_indices_discarded=array([], dtype=int64), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([4.32653059, 0.52735003]), radius=0.013605770498251799, bounds=Bounds(lower=array([2., 0.]), upper=array([20. , 0.7]))), model_indices=array([ 0, 16, 17, 18, 19, 20, 21]), model=ScalarModel(intercept=0.4204323756910675, linear_terms=array([0.00172787, 0.0018322 ]), square_terms=array([[1.25467660e-04, 3.83652575e-03], - [3.83652575e-03, 1.27959664e-01]]), scale=0.013605770498251799, shift=array([4.32653059, 0.52735003])), vector_model=VectorModel(intercepts=array([ 0.12803165, 0.23858248, 0.24705727, 0.24876636, 0.22173997, - 0.1770757 , 0.12976233, -0.01593805, -0.10083657, -0.01010953, - -0.25513117, -0.16998206, -0.10775377, -0.0739005 , -0.05953791, - -0.05947176, -0.05768123]), linear_terms=array([[0., 0.], + [0., 0.]]]), scale=0.5837906205607757, shift=array([5.83790621, 0.17768436])), candidate_index=29, candidate_x=array([5.52761033, 0.16952453]), index=29, x=array([5.52761033, 0.16952453]), fval=0.24288435328669916, rho=0.32939034392246147, accepted=True, new_indices=array([], dtype=int64), old_indices_used=array([14, 15, 21, 22, 24, 25, 26, 27, 28]), old_indices_discarded=array([1]), step_length=0.036488838982131434, relative_step_length=1.0000527640428647, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([5.52761033, 0.16952453]), radius=0.07297382757009696, bounds=Bounds(lower=array([1.1 , 0.01]), upper=array([20. , 0.99]))), model_indices=array([ 1, 14, 15, 22, 24, 26, 27, 28, 29]), model=ScalarModel(intercept=0.2420019335469184, linear_terms=array([0.00573273, 0.02861724]), square_terms=array([[0.00050338, 0.00674964], + [0.00674964, 0.41972427]]), scale=0.07297382757009696, shift=array([5.52761033, 0.16952453])), vector_model=VectorModel(intercepts=array([ 0.04097031, 0.08957803, 0.08816081, 0.11232093, 0.12575895, + 0.13980376, 0.15781889, 0.17546538, 0.09348822, 0.15053254, + -0.17880431, -0.21077511, -0.08570458, -0.06416478, -0.05745986, + -0.05902133, -0.05316704]), linear_terms=array([[0., 0.], [0., 0.], [0., 0.], [0., 0.], @@ -4232,11 +5841,11 @@ algorithm_output,"{'states': [State(trustregion=Region(center=array([3.46495546, [0., 0.]], [[0., 0.], - [0., 0.]]]), scale=0.43538465594405756, shift=array([4.35384656, 0.52929957])), candidate_index=22, candidate_x=array([4.31292501, 0.52756041]), index=22, x=array([4.31292501, 0.52756041]), fval=0.4221166083604152, rho=0.35608507650218485, accepted=True, new_indices=array([], dtype=int64), old_indices_used=array([ 0, 16, 17, 18, 19, 20, 21]), old_indices_discarded=array([], dtype=int64), step_length=0.013607203574844651, relative_step_length=1.000105328587825, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([4.31292501, 0.52756041]), radius=0.027211540996503598, bounds=Bounds(lower=array([2., 0.]), upper=array([20. , 0.7]))), model_indices=array([ 0, 14, 16, 17, 18, 19, 20, 21, 22]), model=ScalarModel(intercept=0.4179242296054027, linear_terms=array([ 0.00656792, -0.02736466]), square_terms=array([[0.00663765, 0.035017 ], - [0.035017 , 0.19042756]]), scale=0.027211540996503598, shift=array([4.31292501, 0.52756041])), vector_model=VectorModel(intercepts=array([ 0.12803165, 0.23858248, 0.24705727, 0.24876636, 0.22173997, - 0.1770757 , 0.12976233, -0.01593805, -0.10083657, -0.01010953, - -0.25513117, -0.16998206, -0.10775377, -0.0739005 , -0.05953791, - -0.05947176, -0.05768123]), linear_terms=array([[0., 0.], + [0., 0.]]]), scale=0.5837906205607757, shift=array([5.83790621, 0.17768436])), candidate_index=30, candidate_x=array([5.4545693 , 0.16576734]), index=29, x=array([5.52761033, 0.16952453]), fval=0.24288435328669916, rho=-0.07956672210493755, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([ 1, 14, 15, 22, 24, 26, 27, 28, 29]), old_indices_discarded=array([ 0, 3, 7, 11, 17, 18, 19, 20, 21, 23, 25]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([5.52761033, 0.16952453]), radius=0.03648691378504848, bounds=Bounds(lower=array([1.1 , 0.01]), upper=array([20. , 0.99]))), model_indices=array([ 1, 14, 22, 24, 26, 27, 28, 29, 30]), model=ScalarModel(intercept=0.24488473081300505, linear_terms=array([0.0009977 , 0.01563392]), square_terms=array([[5.57194237e-05, 1.40119061e-03], + [1.40119061e-03, 1.05208668e-01]]), scale=0.03648691378504848, shift=array([5.52761033, 0.16952453])), vector_model=VectorModel(intercepts=array([ 0.04097031, 0.08957803, 0.08816081, 0.11232093, 0.12575895, + 0.13980376, 0.15781889, 0.17546538, 0.09348822, 0.15053254, + -0.17880431, -0.21077511, -0.08570458, -0.06416478, -0.05745986, + -0.05902133, -0.05316704]), linear_terms=array([[0., 0.], [0., 0.], [0., 0.], [0., 0.], @@ -4301,11 +5910,11 @@ algorithm_output,"{'states': [State(trustregion=Region(center=array([3.46495546, [0., 0.]], [[0., 0.], - [0., 0.]]]), scale=0.43538465594405756, shift=array([4.35384656, 0.52929957])), candidate_index=23, candidate_x=array([4.28677221, 0.53579466]), index=22, x=array([4.31292501, 0.52756041]), fval=0.4221166083604152, rho=-1.3261945112043694, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([ 0, 14, 16, 17, 18, 19, 20, 21, 22]), old_indices_discarded=array([], dtype=int64), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([4.31292501, 0.52756041]), radius=0.013605770498251799, bounds=Bounds(lower=array([2., 0.]), upper=array([20. , 0.7]))), model_indices=array([ 0, 16, 17, 18, 19, 20, 21, 22, 23]), model=ScalarModel(intercept=0.41933669049850225, linear_terms=array([0.00147192, 0.00204465]), square_terms=array([[7.97042691e-05, 3.00715987e-03], - [3.00715987e-03, 1.28937739e-01]]), scale=0.013605770498251799, shift=array([4.31292501, 0.52756041])), vector_model=VectorModel(intercepts=array([ 0.12803165, 0.23858248, 0.24705727, 0.24876636, 0.22173997, - 0.1770757 , 0.12976233, -0.01593805, -0.10083657, -0.01010953, - -0.25513117, -0.16998206, -0.10775377, -0.0739005 , -0.05953791, - -0.05947176, -0.05768123]), linear_terms=array([[0., 0.], + [0., 0.]]]), scale=0.5837906205607757, shift=array([5.83790621, 0.17768436])), candidate_index=31, candidate_x=array([5.49105748, 0.16462446]), index=29, x=array([5.52761033, 0.16952453]), fval=0.24288435328669916, rho=-0.5685237934133627, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([ 1, 14, 22, 24, 26, 27, 28, 29, 30]), old_indices_discarded=array([15]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([5.52761033, 0.16952453]), radius=0.01824345689252424, bounds=Bounds(lower=array([1.1 , 0.01]), upper=array([20. , 0.99]))), model_indices=array([14, 24, 27, 28, 29, 30, 31]), model=ScalarModel(intercept=0.24302431962819412, linear_terms=array([7.55308733e-05, 5.46770179e-04]), square_terms=array([[9.74635032e-06, 3.06763575e-04], + [3.06763575e-04, 2.62189415e-02]]), scale=0.01824345689252424, shift=array([5.52761033, 0.16952453])), vector_model=VectorModel(intercepts=array([ 0.04097031, 0.08957803, 0.08816081, 0.11232093, 0.12575895, + 0.13980376, 0.15781889, 0.17546538, 0.09348822, 0.15053254, + -0.17880431, -0.21077511, -0.08570458, -0.06416478, -0.05745986, + -0.05902133, -0.05316704]), linear_terms=array([[0., 0.], [0., 0.], [0., 0.], [0., 0.], @@ -4370,11 +5979,11 @@ algorithm_output,"{'states': [State(trustregion=Region(center=array([3.46495546, [0., 0.]], [[0., 0.], - [0., 0.]]]), scale=0.43538465594405756, shift=array([4.35384656, 0.52929957])), candidate_index=24, candidate_x=array([4.29931788, 0.52766091]), index=24, x=array([4.29931788, 0.52766091]), fval=0.42146435277136396, rho=0.45428058494400997, accepted=True, new_indices=array([], dtype=int64), old_indices_used=array([ 0, 16, 17, 18, 19, 20, 21, 22, 23]), old_indices_discarded=array([], dtype=int64), step_length=0.013607497793214447, relative_step_length=1.00012695311617, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([4.29931788, 0.52766091]), radius=0.027211540996503598, bounds=Bounds(lower=array([2., 0.]), upper=array([20. , 0.7]))), model_indices=array([16, 17, 18, 19, 20, 21, 22, 23, 24]), model=ScalarModel(intercept=0.4184095833653808, linear_terms=array([0.00275098, 0.0031198 ]), square_terms=array([[2.61851776e-04, 1.07493803e-02], - [1.07493803e-02, 5.13447851e-01]]), scale=0.027211540996503598, shift=array([4.29931788, 0.52766091])), vector_model=VectorModel(intercepts=array([ 0.12803165, 0.23858248, 0.24705727, 0.24876636, 0.22173997, - 0.1770757 , 0.12976233, -0.01593805, -0.10083657, -0.01010953, - -0.25513117, -0.16998206, -0.10775377, -0.0739005 , -0.05953791, - -0.05947176, -0.05768123]), linear_terms=array([[0., 0.], + [0., 0.]]]), scale=0.5837906205607757, shift=array([5.83790621, 0.17768436])), candidate_index=32, candidate_x=array([5.50936376, 0.16935797]), index=32, x=array([5.50936376, 0.16935797]), fval=0.24283458910151834, rho=0.693413890433385, accepted=True, new_indices=array([], dtype=int64), old_indices_used=array([14, 24, 27, 28, 29, 30, 31]), old_indices_discarded=array([], dtype=int64), step_length=0.018247326571858506, relative_step_length=1.000212113272011, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([5.50936376, 0.16935797]), radius=0.03648691378504848, bounds=Bounds(lower=array([1.1 , 0.01]), upper=array([20. , 0.99]))), model_indices=array([14, 22, 24, 27, 28, 29, 30, 31, 32]), model=ScalarModel(intercept=0.2429324718675529, linear_terms=array([1.80345936e-04, 8.51487840e-05]), square_terms=array([[3.88321243e-05, 1.22404574e-03], + [1.22404574e-03, 1.04906924e-01]]), scale=0.03648691378504848, shift=array([5.50936376, 0.16935797])), vector_model=VectorModel(intercepts=array([ 0.04097031, 0.08957803, 0.08816081, 0.11232093, 0.12575895, + 0.13980376, 0.15781889, 0.17546538, 0.09348822, 0.15053254, + -0.17880431, -0.21077511, -0.08570458, -0.06416478, -0.05745986, + -0.05902133, -0.05316704]), linear_terms=array([[0., 0.], [0., 0.], [0., 0.], [0., 0.], @@ -4439,11 +6048,11 @@ algorithm_output,"{'states': [State(trustregion=Region(center=array([3.46495546, [0., 0.]], [[0., 0.], - [0., 0.]]]), scale=0.43538465594405756, shift=array([4.35384656, 0.52929957])), candidate_index=25, candidate_x=array([4.2721088 , 0.52806313]), index=25, x=array([4.2721088 , 0.52806313]), fval=0.4203523177729453, rho=0.415481639342676, accepted=True, new_indices=array([], dtype=int64), old_indices_used=array([16, 17, 18, 19, 20, 21, 22, 23, 24]), old_indices_discarded=array([ 0, 14]), step_length=0.027212055736458622, relative_step_length=1.0000189162368678, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([4.2721088 , 0.52806313]), radius=0.054423081993007195, bounds=Bounds(lower=array([2., 0.]), upper=array([20. , 0.7]))), model_indices=array([16, 17, 19, 20, 21, 22, 23, 24, 25]), model=ScalarModel(intercept=0.41821670449455145, linear_terms=array([0.00208564, 0.02997407]), square_terms=array([[1.27585814e-04, 9.28441079e-04], - [9.28441079e-04, 2.06908074e+00]]), scale=0.054423081993007195, shift=array([4.2721088 , 0.52806313])), vector_model=VectorModel(intercepts=array([ 0.12803165, 0.23858248, 0.24705727, 0.24876636, 0.22173997, - 0.1770757 , 0.12976233, -0.01593805, -0.10083657, -0.01010953, - -0.25513117, -0.16998206, -0.10775377, -0.0739005 , -0.05953791, - -0.05947176, -0.05768123]), linear_terms=array([[0., 0.], + [0., 0.]]]), scale=0.5837906205607757, shift=array([5.83790621, 0.17768436])), candidate_index=33, candidate_x=array([5.47287898, 0.16975347]), index=33, x=array([5.47287898, 0.16975347]), fval=0.24267293680244376, rho=0.9673817824711848, accepted=True, new_indices=array([], dtype=int64), old_indices_used=array([14, 22, 24, 27, 28, 29, 30, 31, 32]), old_indices_discarded=array([ 1, 26]), step_length=0.0364869257187115, relative_step_length=1.000000327066934, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([5.47287898, 0.16975347]), radius=0.07297382757009696, bounds=Bounds(lower=array([1.1 , 0.01]), upper=array([20. , 0.99]))), model_indices=array([14, 24, 27, 28, 29, 30, 31, 32, 33]), model=ScalarModel(intercept=0.2427761119591001, linear_terms=array([ 2.39189726e-04, -1.29669188e-05]), square_terms=array([[1.58583544e-04, 4.77994302e-03], + [4.77994302e-03, 4.19573360e-01]]), scale=0.07297382757009696, shift=array([5.47287898, 0.16975347])), vector_model=VectorModel(intercepts=array([ 0.04097031, 0.08957803, 0.08816081, 0.11232093, 0.12575895, + 0.13980376, 0.15781889, 0.17546538, 0.09348822, 0.15053254, + -0.17880431, -0.21077511, -0.08570458, -0.06416478, -0.05745986, + -0.05902133, -0.05316704]), linear_terms=array([[0., 0.], [0., 0.], [0., 0.], [0., 0.], @@ -4508,11 +6117,11 @@ algorithm_output,"{'states': [State(trustregion=Region(center=array([3.46495546, [0., 0.]], [[0., 0.], - [0., 0.]]]), scale=0.43538465594405756, shift=array([4.35384656, 0.52929957])), candidate_index=26, candidate_x=array([4.21768543, 0.52729986]), index=26, x=array([4.21768543, 0.52729986]), fval=0.41722780024581224, rho=1.4038193287047533, accepted=True, new_indices=array([], dtype=int64), old_indices_used=array([16, 17, 19, 20, 21, 22, 23, 24, 25]), old_indices_discarded=array([ 0, 12, 13, 14, 15, 18]), step_length=0.05442872015072826, relative_step_length=1.0001035986481213, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([4.21768543, 0.52729986]), radius=0.10884616398601439, bounds=Bounds(lower=array([2., 0.]), upper=array([20. , 0.7]))), model_indices=array([14, 16, 19, 20, 21, 23, 24, 25, 26]), model=ScalarModel(intercept=0.4155355084148145, linear_terms=array([ 0.00478031, -0.11092267]), square_terms=array([[8.53509923e-04, 2.73143966e-02], - [2.73143966e-02, 2.54714414e+00]]), scale=0.10884616398601439, shift=array([4.21768543, 0.52729986])), vector_model=VectorModel(intercepts=array([ 0.12803165, 0.23858248, 0.24705727, 0.24876636, 0.22173997, - 0.1770757 , 0.12976233, -0.01593805, -0.10083657, -0.01010953, - -0.25513117, -0.16998206, -0.10775377, -0.0739005 , -0.05953791, - -0.05947176, -0.05768123]), linear_terms=array([[0., 0.], + [0., 0.]]]), scale=0.5837906205607757, shift=array([5.83790621, 0.17768436])), candidate_index=34, candidate_x=array([5.39990991, 0.17058675]), index=34, x=array([5.39990991, 0.17058675]), fval=0.24231674775792228, rho=1.9020634332530058, accepted=True, new_indices=array([], dtype=int64), old_indices_used=array([14, 24, 27, 28, 29, 30, 31, 32, 33]), old_indices_discarded=array([ 1, 3, 7, 11, 15, 17, 19, 21, 22, 23, 25, 26]), step_length=0.07297382758305467, relative_step_length=1.0000000001775664, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([5.39990991, 0.17058675]), radius=0.14594765514019392, bounds=Bounds(lower=array([1.1 , 0.01]), upper=array([20. , 0.99]))), model_indices=array([ 7, 27, 28, 29, 30, 31, 32, 33, 34]), model=ScalarModel(intercept=0.2430089349062019, linear_terms=array([0.00175618, 0.07611165]), square_terms=array([[7.68632058e-04, 2.17025796e-02], + [2.17025796e-02, 1.79761440e+00]]), scale=0.14594765514019392, shift=array([5.39990991, 0.17058675])), vector_model=VectorModel(intercepts=array([ 0.04097031, 0.08957803, 0.08816081, 0.11232093, 0.12575895, + 0.13980376, 0.15781889, 0.17546538, 0.09348822, 0.15053254, + -0.17880431, -0.21077511, -0.08570458, -0.06416478, -0.05745986, + -0.05902133, -0.05316704]), linear_terms=array([[0., 0.], [0., 0.], [0., 0.], [0., 0.], @@ -4577,11 +6186,12 @@ algorithm_output,"{'states': [State(trustregion=Region(center=array([3.46495546, [0., 0.]], [[0., 0.], - [0., 0.]]]), scale=0.43538465594405756, shift=array([4.35384656, 0.52929957])), candidate_index=27, candidate_x=array([4.10889878, 0.53319394]), index=26, x=array([4.21768543, 0.52729986]), fval=0.41722780024581224, rho=-0.375457200154938, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([14, 16, 19, 20, 21, 23, 24, 25, 26]), old_indices_discarded=array([ 0, 1, 2, 3, 4, 6, 7, 8, 9, 10, 11, 12, 13, 15, 17, 18, 22]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([4.21768543, 0.52729986]), radius=0.054423081993007195, bounds=Bounds(lower=array([2., 0.]), upper=array([20. , 0.7]))), model_indices=array([14, 16, 19, 21, 22, 23, 24, 25, 26]), model=ScalarModel(intercept=0.4157441380311584, linear_terms=array([ 0.00225524, -0.05425405]), square_terms=array([[1.98743839e-04, 6.07733025e-03], - [6.07733025e-03, 6.36250180e-01]]), scale=0.054423081993007195, shift=array([4.21768543, 0.52729986])), vector_model=VectorModel(intercepts=array([ 0.12803165, 0.23858248, 0.24705727, 0.24876636, 0.22173997, - 0.1770757 , 0.12976233, -0.01593805, -0.10083657, -0.01010953, - -0.25513117, -0.16998206, -0.10775377, -0.0739005 , -0.05953791, - -0.05947176, -0.05768123]), linear_terms=array([[0., 0.], + [0., 0.]]]), scale=0.5837906205607757, shift=array([5.83790621, 0.17768436])), candidate_index=35, candidate_x=array([5.25398401, 0.16616985]), index=34, x=array([5.39990991, 0.17058675]), fval=0.24231674775792228, rho=-0.72186797844346, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([ 7, 27, 28, 29, 30, 31, 32, 33, 34]), old_indices_discarded=array([ 0, 1, 3, 8, 10, 11, 12, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, + 24, 25, 26]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([5.39990991, 0.17058675]), radius=0.07297382757009696, bounds=Bounds(lower=array([1.1 , 0.01]), upper=array([20. , 0.99]))), model_indices=array([27, 28, 29, 30, 31, 32, 33, 34, 35]), model=ScalarModel(intercept=0.24231384996316413, linear_terms=array([ 0.00018402, -0.00403364]), square_terms=array([[1.69468241e-04, 4.40244170e-03], + [4.40244170e-03, 4.37739735e-01]]), scale=0.07297382757009696, shift=array([5.39990991, 0.17058675])), vector_model=VectorModel(intercepts=array([ 0.04097031, 0.08957803, 0.08816081, 0.11232093, 0.12575895, + 0.13980376, 0.15781889, 0.17546538, 0.09348822, 0.15053254, + -0.17880431, -0.21077511, -0.08570458, -0.06416478, -0.05745986, + -0.05902133, -0.05316704]), linear_terms=array([[0., 0.], [0., 0.], [0., 0.], [0., 0.], @@ -4646,11 +6256,11 @@ algorithm_output,"{'states': [State(trustregion=Region(center=array([3.46495546, [0., 0.]], [[0., 0.], - [0., 0.]]]), scale=0.43538465594405756, shift=array([4.35384656, 0.52929957])), candidate_index=28, candidate_x=array([4.16331044, 0.53243871]), index=26, x=array([4.21768543, 0.52729986]), fval=0.41722780024581224, rho=-0.790875052540013, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([14, 16, 19, 21, 22, 23, 24, 25, 26]), old_indices_discarded=array([ 0, 3, 12, 13, 15, 17, 18, 20, 27]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([4.21768543, 0.52729986]), radius=0.027211540996503598, bounds=Bounds(lower=array([2., 0.]), upper=array([20. , 0.7]))), model_indices=array([16, 19, 21, 22, 23, 24, 25, 26, 28]), model=ScalarModel(intercept=0.4157766194646605, linear_terms=array([0.00104003, 0.00040517]), square_terms=array([[3.42546244e-05, 3.00583172e-04], - [3.00583172e-04, 5.26747271e-01]]), scale=0.027211540996503598, shift=array([4.21768543, 0.52729986])), vector_model=VectorModel(intercepts=array([ 0.12803165, 0.23858248, 0.24705727, 0.24876636, 0.22173997, - 0.1770757 , 0.12976233, -0.01593805, -0.10083657, -0.01010953, - -0.25513117, -0.16998206, -0.10775377, -0.0739005 , -0.05953791, - -0.05947176, -0.05768123]), linear_terms=array([[0., 0.], + [0., 0.]]]), scale=0.5837906205607757, shift=array([5.83790621, 0.17768436])), candidate_index=36, candidate_x=array([5.32694835, 0.17199265]), index=34, x=array([5.39990991, 0.17058675]), fval=0.24231674775792228, rho=-0.24843012199644884, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([27, 28, 29, 30, 31, 32, 33, 34, 35]), old_indices_discarded=array([ 1, 3, 7, 11, 14, 15, 21, 22, 24, 25, 26]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([5.39990991, 0.17058675]), radius=0.03648691378504848, bounds=Bounds(lower=array([1.1 , 0.01]), upper=array([20. , 0.99]))), model_indices=array([27, 29, 30, 31, 32, 33, 34, 35, 36]), model=ScalarModel(intercept=0.24238669883858652, linear_terms=array([ 8.94506136e-05, -1.39054452e-03]), square_terms=array([[4.22380429e-05, 1.09259613e-03], + [1.09259613e-03, 1.11165757e-01]]), scale=0.03648691378504848, shift=array([5.39990991, 0.17058675])), vector_model=VectorModel(intercepts=array([ 0.04097031, 0.08957803, 0.08816081, 0.11232093, 0.12575895, + 0.13980376, 0.15781889, 0.17546538, 0.09348822, 0.15053254, + -0.17880431, -0.21077511, -0.08570458, -0.06416478, -0.05745986, + -0.05902133, -0.05316704]), linear_terms=array([[0., 0.], [0., 0.], [0., 0.], [0., 0.], @@ -4715,11 +6325,11 @@ algorithm_output,"{'states': [State(trustregion=Region(center=array([3.46495546, [0., 0.]], [[0., 0.], - [0., 0.]]]), scale=0.43538465594405756, shift=array([4.35384656, 0.52929957])), candidate_index=29, candidate_x=array([4.19047388, 0.52729447]), index=29, x=array([4.19047388, 0.52729447]), fval=0.4159082029410586, rho=1.290041780996001, accepted=True, new_indices=array([], dtype=int64), old_indices_used=array([16, 19, 21, 22, 23, 24, 25, 26, 28]), old_indices_discarded=array([13, 14, 17, 18, 20, 27]), step_length=0.027211549013772696, relative_step_length=1.0000002946275295, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([4.19047388, 0.52729447]), radius=0.054423081993007195, bounds=Bounds(lower=array([2., 0.]), upper=array([20. , 0.7]))), model_indices=array([13, 21, 23, 24, 25, 26, 27, 28, 29]), model=ScalarModel(intercept=0.419336202207792, linear_terms=array([ 0.00280698, -0.02565343]), square_terms=array([[1.81863462e-04, 4.12189123e-03], - [4.12189123e-03, 4.49239418e-01]]), scale=0.054423081993007195, shift=array([4.19047388, 0.52729447])), vector_model=VectorModel(intercepts=array([ 0.12803165, 0.23858248, 0.24705727, 0.24876636, 0.22173997, - 0.1770757 , 0.12976233, -0.01593805, -0.10083657, -0.01010953, - -0.25513117, -0.16998206, -0.10775377, -0.0739005 , -0.05953791, - -0.05947176, -0.05768123]), linear_terms=array([[0., 0.], + [0., 0.]]]), scale=0.5837906205607757, shift=array([5.83790621, 0.17768436])), candidate_index=37, candidate_x=array([5.36342988, 0.17140117]), index=37, x=array([5.36342988, 0.17140117]), fval=0.24231131739284278, rho=0.05653604311640793, accepted=True, new_indices=array([], dtype=int64), old_indices_used=array([27, 29, 30, 31, 32, 33, 34, 35, 36]), old_indices_discarded=array([ 3, 7, 28]), step_length=0.03648912499019746, relative_step_length=1.0000606026906524, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([5.36342988, 0.17140117]), radius=0.01824345689252424, bounds=Bounds(lower=array([1.1 , 0.01]), upper=array([20. , 0.99]))), model_indices=array([34, 36, 37]), model=ScalarModel(intercept=0.2423113173928431, linear_terms=array([-2.76319807e-05, -7.53809665e-04]), square_terms=array([[1.12978733e-05, 3.07815866e-04], + [3.07815866e-04, 3.20364135e-02]]), scale=0.01824345689252424, shift=array([5.36342988, 0.17140117])), vector_model=VectorModel(intercepts=array([ 0.04097031, 0.08957803, 0.08816081, 0.11232093, 0.12575895, + 0.13980376, 0.15781889, 0.17546538, 0.09348822, 0.15053254, + -0.17880431, -0.21077511, -0.08570458, -0.06416478, -0.05745986, + -0.05902133, -0.05316704]), linear_terms=array([[0., 0.], [0., 0.], [0., 0.], [0., 0.], @@ -4784,11 +6394,11 @@ algorithm_output,"{'states': [State(trustregion=Region(center=array([3.46495546, [0., 0.]], [[0., 0.], - [0., 0.]]]), scale=0.43538465594405756, shift=array([4.35384656, 0.52929957])), candidate_index=30, candidate_x=array([4.13608198, 0.53087819]), index=29, x=array([4.19047388, 0.52729447]), fval=0.4159082029410586, rho=-0.1753086475657199, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([13, 21, 23, 24, 25, 26, 27, 28, 29]), old_indices_discarded=array([ 0, 3, 10, 12, 14, 16, 17, 18, 19, 20, 22]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([4.19047388, 0.52729447]), radius=0.027211540996503598, bounds=Bounds(lower=array([2., 0.]), upper=array([20. , 0.7]))), model_indices=array([21, 23, 24, 25, 26, 27, 28, 29, 30]), model=ScalarModel(intercept=0.41620512281643746, linear_terms=array([ 0.0011879 , -0.00439214]), square_terms=array([[3.88216150e-05, 1.20059762e-03], - [1.20059762e-03, 3.87561022e-01]]), scale=0.027211540996503598, shift=array([4.19047388, 0.52729447])), vector_model=VectorModel(intercepts=array([ 0.12803165, 0.23858248, 0.24705727, 0.24876636, 0.22173997, - 0.1770757 , 0.12976233, -0.01593805, -0.10083657, -0.01010953, - -0.25513117, -0.16998206, -0.10775377, -0.0739005 , -0.05953791, - -0.05947176, -0.05768123]), linear_terms=array([[0., 0.], + [0., 0.]]]), scale=0.5837906205607757, shift=array([5.83790621, 0.17768436])), candidate_index=38, candidate_x=array([5.38167477, 0.17165504]), index=37, x=array([5.36342988, 0.17140117]), fval=0.24231131739284278, rho=-3.7871858271077357, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([34, 36, 37]), old_indices_discarded=array([], dtype=int64), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([5.36342988, 0.17140117]), radius=0.00912172844626212, bounds=Bounds(lower=array([1.1 , 0.01]), upper=array([20. , 0.99]))), model_indices=array([34, 36, 37, 38]), model=ScalarModel(intercept=0.24232506941100967, linear_terms=array([1.70862499e-05, 1.21892565e-03]), square_terms=array([[2.52449325e-06, 5.92746750e-05], + [5.92746750e-05, 6.98298434e-03]]), scale=0.00912172844626212, shift=array([5.36342988, 0.17140117])), vector_model=VectorModel(intercepts=array([ 0.04097031, 0.08957803, 0.08816081, 0.11232093, 0.12575895, + 0.13980376, 0.15781889, 0.17546538, 0.09348822, 0.15053254, + -0.17880431, -0.21077511, -0.08570458, -0.06416478, -0.05745986, + -0.05902133, -0.05316704]), linear_terms=array([[0., 0.], [0., 0.], [0., 0.], [0., 0.], @@ -4853,11 +6463,11 @@ algorithm_output,"{'states': [State(trustregion=Region(center=array([3.46495546, [0., 0.]], [[0., 0.], - [0., 0.]]]), scale=0.43538465594405756, shift=array([4.35384656, 0.52929957])), candidate_index=31, candidate_x=array([4.16326343, 0.52768596]), index=31, x=array([4.16326343, 0.52768596]), fval=0.4147450264942464, rho=0.9622612552817411, accepted=True, new_indices=array([], dtype=int64), old_indices_used=array([21, 23, 24, 25, 26, 27, 28, 29, 30]), old_indices_discarded=array([13, 14, 16, 19, 20, 22]), step_length=0.027213270544096283, relative_step_length=1.0000635593402412, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([4.16326343, 0.52768596]), radius=0.054423081993007195, bounds=Bounds(lower=array([2., 0.]), upper=array([20. , 0.7]))), model_indices=array([13, 23, 25, 26, 27, 28, 29, 30, 31]), model=ScalarModel(intercept=0.41737978594990033, linear_terms=array([ 0.00250072, -0.02705455]), square_terms=array([[1.60659979e-04, 2.77932556e-03], - [2.77932556e-03, 4.50348306e-01]]), scale=0.054423081993007195, shift=array([4.16326343, 0.52768596])), vector_model=VectorModel(intercepts=array([ 0.12803165, 0.23858248, 0.24705727, 0.24876636, 0.22173997, - 0.1770757 , 0.12976233, -0.01593805, -0.10083657, -0.01010953, - -0.25513117, -0.16998206, -0.10775377, -0.0739005 , -0.05953791, - -0.05947176, -0.05768123]), linear_terms=array([[0., 0.], + [0., 0.]]]), scale=0.5837906205607757, shift=array([5.83790621, 0.17768436])), candidate_index=39, candidate_x=array([5.35432492, 0.16988723]), index=37, x=array([5.36342988, 0.17140117]), fval=0.24231131739284278, rho=-0.28093054493142594, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([34, 36, 37, 38]), old_indices_discarded=array([], dtype=int64), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([5.36342988, 0.17140117]), radius=0.00456086422313106, bounds=Bounds(lower=array([1.1 , 0.01]), upper=array([20. , 0.99]))), model_indices=array([37, 38, 39]), model=ScalarModel(intercept=0.2423113173928428, linear_terms=array([1.93621445e-05, 1.20738405e-04]), square_terms=array([[6.05669989e-07, 1.43497719e-05], + [1.43497719e-05, 1.80621102e-03]]), scale=0.00456086422313106, shift=array([5.36342988, 0.17140117])), vector_model=VectorModel(intercepts=array([ 0.04097031, 0.08957803, 0.08816081, 0.11232093, 0.12575895, + 0.13980376, 0.15781889, 0.17546538, 0.09348822, 0.15053254, + -0.17880431, -0.21077511, -0.08570458, -0.06416478, -0.05745986, + -0.05902133, -0.05316704]), linear_terms=array([[0., 0.], [0., 0.], [0., 0.], [0., 0.], @@ -4922,11 +6532,11 @@ algorithm_output,"{'states': [State(trustregion=Region(center=array([3.46495546, [0., 0.]], [[0., 0.], - [0., 0.]]]), scale=0.43538465594405756, shift=array([4.35384656, 0.52929957])), candidate_index=32, candidate_x=array([4.10886226, 0.53127106]), index=31, x=array([4.16326343, 0.52768596]), fval=0.4147450264942464, rho=-0.3454910541878925, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([13, 23, 25, 26, 27, 28, 29, 30, 31]), old_indices_discarded=array([ 0, 3, 7, 10, 12, 14, 16, 17, 18, 19, 20, 21, 22, 24]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([4.16326343, 0.52768596]), radius=0.027211540996503598, bounds=Bounds(lower=array([2., 0.]), upper=array([20. , 0.7]))), model_indices=array([13, 25, 26, 27, 28, 29, 30, 31, 32]), model=ScalarModel(intercept=0.41712290354550663, linear_terms=array([ 0.0002951 , -0.01442513]), square_terms=array([[ 8.51774713e-05, -2.38977644e-03], - [-2.38977644e-03, 1.12743185e-01]]), scale=0.027211540996503598, shift=array([4.16326343, 0.52768596])), vector_model=VectorModel(intercepts=array([ 0.12803165, 0.23858248, 0.24705727, 0.24876636, 0.22173997, - 0.1770757 , 0.12976233, -0.01593805, -0.10083657, -0.01010953, - -0.25513117, -0.16998206, -0.10775377, -0.0739005 , -0.05953791, - -0.05947176, -0.05768123]), linear_terms=array([[0., 0.], + [0., 0.]]]), scale=0.5837906205607757, shift=array([5.83790621, 0.17768436])), candidate_index=40, candidate_x=array([5.35886678, 0.17113519]), index=40, x=array([5.35886678, 0.17113519]), fval=0.2422660131172327, rho=2.040639609470749, accepted=True, new_indices=array([], dtype=int64), old_indices_used=array([37, 38, 39]), old_indices_discarded=array([], dtype=int64), step_length=0.004570846223013415, relative_step_length=1.0021886202688801, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([5.35886678, 0.17113519]), radius=0.00912172844626212, bounds=Bounds(lower=array([1.1 , 0.01]), upper=array([20. , 0.99]))), model_indices=array([34, 36, 37, 38, 39, 40]), model=ScalarModel(intercept=0.24230697792475, linear_terms=array([4.91531731e-06, 4.01574216e-04]), square_terms=array([[2.56045838e-06, 6.11904777e-05], + [6.11904777e-05, 7.09374545e-03]]), scale=0.00912172844626212, shift=array([5.35886678, 0.17113519])), vector_model=VectorModel(intercepts=array([ 0.04097031, 0.08957803, 0.08816081, 0.11232093, 0.12575895, + 0.13980376, 0.15781889, 0.17546538, 0.09348822, 0.15053254, + -0.17880431, -0.21077511, -0.08570458, -0.06416478, -0.05745986, + -0.05902133, -0.05316704]), linear_terms=array([[0., 0.], [0., 0.], [0., 0.], [0., 0.], @@ -4991,11 +6601,11 @@ algorithm_output,"{'states': [State(trustregion=Region(center=array([3.46495546, [0., 0.]], [[0., 0.], - [0., 0.]]]), scale=0.43538465594405756, shift=array([4.35384656, 0.52929957])), candidate_index=33, candidate_x=array([4.19017076, 0.53174348]), index=31, x=array([4.16326343, 0.52768596]), fval=0.4147450264942464, rho=-6.903973036572866, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([13, 25, 26, 27, 28, 29, 30, 31, 32]), old_indices_discarded=array([23, 24]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([4.16326343, 0.52768596]), radius=0.013605770498251799, bounds=Bounds(lower=array([2., 0.]), upper=array([20. , 0.7]))), model_indices=array([26, 27, 28, 29, 30, 31, 32, 33]), model=ScalarModel(intercept=0.41476994342026424, linear_terms=array([0.00059698, 0.00042173]), square_terms=array([[1.09428262e-05, 4.00314018e-04], - [4.00314018e-04, 1.04070807e-01]]), scale=0.013605770498251799, shift=array([4.16326343, 0.52768596])), vector_model=VectorModel(intercepts=array([ 0.12803165, 0.23858248, 0.24705727, 0.24876636, 0.22173997, - 0.1770757 , 0.12976233, -0.01593805, -0.10083657, -0.01010953, - -0.25513117, -0.16998206, -0.10775377, -0.0739005 , -0.05953791, - -0.05947176, -0.05768123]), linear_terms=array([[0., 0.], + [0., 0.]]]), scale=0.5837906205607757, shift=array([5.83790621, 0.17768436])), candidate_index=41, candidate_x=array([5.34975553, 0.17069814]), index=40, x=array([5.35886678, 0.17113519]), fval=0.2422660131172327, rho=-1.4993631427071992, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([34, 36, 37, 38, 39, 40]), old_indices_discarded=array([], dtype=int64), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([5.35886678, 0.17113519]), radius=0.00456086422313106, bounds=Bounds(lower=array([1.1 , 0.01]), upper=array([20. , 0.99]))), model_indices=array([37, 39, 40, 41]), model=ScalarModel(intercept=0.24228491419551926, linear_terms=array([8.49239494e-06, 2.39836883e-05]), square_terms=array([[6.14732854e-07, 1.27371737e-05], + [1.27371737e-05, 1.83146540e-03]]), scale=0.00456086422313106, shift=array([5.35886678, 0.17113519])), vector_model=VectorModel(intercepts=array([ 0.04097031, 0.08957803, 0.08816081, 0.11232093, 0.12575895, + 0.13980376, 0.15781889, 0.17546538, 0.09348822, 0.15053254, + -0.17880431, -0.21077511, -0.08570458, -0.06416478, -0.05745986, + -0.05902133, -0.05316704]), linear_terms=array([[0., 0.], [0., 0.], [0., 0.], [0., 0.], @@ -5060,11 +6670,11 @@ algorithm_output,"{'states': [State(trustregion=Region(center=array([3.46495546, [0., 0.]], [[0., 0.], - [0., 0.]]]), scale=0.43538465594405756, shift=array([4.35384656, 0.52929957])), candidate_index=34, candidate_x=array([4.14965755, 0.52768318]), index=34, x=array([4.14965755, 0.52768318]), fval=0.4141230097680078, rho=1.0515671278451089, accepted=True, new_indices=array([], dtype=int64), old_indices_used=array([26, 27, 28, 29, 30, 31, 32, 33]), old_indices_discarded=array([], dtype=int64), step_length=0.01360588208381092, relative_step_length=1.0000082013406837, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([4.14965755, 0.52768318]), radius=0.027211540996503598, bounds=Bounds(lower=array([2., 0.]), upper=array([20. , 0.7]))), model_indices=array([26, 27, 28, 29, 30, 31, 32, 33, 34]), model=ScalarModel(intercept=0.41416002106153477, linear_terms=array([1.1774986e-03, 1.1351855e-05]), square_terms=array([[4.39254618e-05, 1.63867085e-03], - [1.63867085e-03, 4.17803811e-01]]), scale=0.027211540996503598, shift=array([4.14965755, 0.52768318])), vector_model=VectorModel(intercepts=array([ 0.12803165, 0.23858248, 0.24705727, 0.24876636, 0.22173997, - 0.1770757 , 0.12976233, -0.01593805, -0.10083657, -0.01010953, - -0.25513117, -0.16998206, -0.10775377, -0.0739005 , -0.05953791, - -0.05947176, -0.05768123]), linear_terms=array([[0., 0.], + [0., 0.]]]), scale=0.5837906205607757, shift=array([5.83790621, 0.17768436])), candidate_index=42, candidate_x=array([5.35430561, 0.1711073 ]), index=42, x=array([5.35430561, 0.1711073 ]), fval=0.2422367332032626, rho=3.562002347325252, accepted=True, new_indices=array([], dtype=int64), old_indices_used=array([37, 39, 40, 41]), old_indices_discarded=array([], dtype=int64), step_length=0.004561249312406207, relative_step_length=1.0000844334004055, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([5.35430561, 0.1711073 ]), radius=0.00912172844626212, bounds=Bounds(lower=array([1.1 , 0.01]), upper=array([20. , 0.99]))), model_indices=array([34, 36, 37, 38, 39, 40, 41, 42]), model=ScalarModel(intercept=0.24229278798868248, linear_terms=array([5.19719019e-06, 3.68333221e-04]), square_terms=array([[2.55059029e-06, 6.04556474e-05], + [6.04556474e-05, 7.06166757e-03]]), scale=0.00912172844626212, shift=array([5.35430561, 0.1711073 ])), vector_model=VectorModel(intercepts=array([ 0.04097031, 0.08957803, 0.08816081, 0.11232093, 0.12575895, + 0.13980376, 0.15781889, 0.17546538, 0.09348822, 0.15053254, + -0.17880431, -0.21077511, -0.08570458, -0.06416478, -0.05745986, + -0.05902133, -0.05316704]), linear_terms=array([[0., 0.], [0., 0.], [0., 0.], [0., 0.], @@ -5129,11 +6739,11 @@ algorithm_output,"{'states': [State(trustregion=Region(center=array([3.46495546, [0., 0.]], [[0., 0.], - [0., 0.]]]), scale=0.43538465594405756, shift=array([4.35384656, 0.52929957])), candidate_index=35, candidate_x=array([4.12244621, 0.52778888]), index=35, x=array([4.12244621, 0.52778888]), fval=0.4129111617525009, rho=1.0458719092673594, accepted=True, new_indices=array([], dtype=int64), old_indices_used=array([26, 27, 28, 29, 30, 31, 32, 33, 34]), old_indices_discarded=array([13, 25]), step_length=0.027211541016215826, relative_step_length=1.000000000724407, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([4.12244621, 0.52778888]), radius=0.054423081993007195, bounds=Bounds(lower=array([2., 0.]), upper=array([20. , 0.7]))), model_indices=array([27, 28, 29, 30, 31, 32, 33, 34, 35]), model=ScalarModel(intercept=0.4129670465375432, linear_terms=array([2.29864339e-03, 2.26642316e-05]), square_terms=array([[1.78050089e-04, 6.65081441e-03], - [6.65081441e-03, 1.67840804e+00]]), scale=0.054423081993007195, shift=array([4.12244621, 0.52778888])), vector_model=VectorModel(intercepts=array([ 0.12803165, 0.23858248, 0.24705727, 0.24876636, 0.22173997, - 0.1770757 , 0.12976233, -0.01593805, -0.10083657, -0.01010953, - -0.25513117, -0.16998206, -0.10775377, -0.0739005 , -0.05953791, - -0.05947176, -0.05768123]), linear_terms=array([[0., 0.], + [0., 0.]]]), scale=0.5837906205607757, shift=array([5.83790621, 0.17768436])), candidate_index=43, candidate_x=array([5.3451353 , 0.17071002]), index=42, x=array([5.35430561, 0.1711073 ]), fval=0.2422367332032626, rho=-3.526203505209563, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([34, 36, 37, 38, 39, 40, 41, 42]), old_indices_discarded=array([], dtype=int64), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([5.35430561, 0.1711073 ]), radius=0.00456086422313106, bounds=Bounds(lower=array([1.1 , 0.01]), upper=array([20. , 0.99]))), model_indices=array([37, 39, 40, 41, 42, 43]), model=ScalarModel(intercept=0.24226761562351934, linear_terms=array([ 9.11408781e-06, -4.65800448e-05]), square_terms=array([[6.22234181e-07, 1.39495570e-05], + [1.39495570e-05, 1.81742371e-03]]), scale=0.00456086422313106, shift=array([5.35430561, 0.1711073 ])), vector_model=VectorModel(intercepts=array([ 0.04097031, 0.08957803, 0.08816081, 0.11232093, 0.12575895, + 0.13980376, 0.15781889, 0.17546538, 0.09348822, 0.15053254, + -0.17880431, -0.21077511, -0.08570458, -0.06416478, -0.05745986, + -0.05902133, -0.05316704]), linear_terms=array([[0., 0.], [0., 0.], [0., 0.], [0., 0.], @@ -5198,12 +6808,11 @@ algorithm_output,"{'states': [State(trustregion=Region(center=array([3.46495546, [0., 0.]], [[0., 0.], - [0., 0.]]]), scale=0.43538465594405756, shift=array([4.35384656, 0.52929957])), candidate_index=36, candidate_x=array([4.06802355, 0.52800352]), index=36, x=array([4.06802355, 0.52800352]), fval=0.4105781041382112, rho=1.049655382284479, accepted=True, new_indices=array([], dtype=int64), old_indices_used=array([27, 28, 29, 30, 31, 32, 33, 34, 35]), old_indices_discarded=array([ 0, 3, 7, 10, 12, 13, 14, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, - 26]), step_length=0.05442308200261207, relative_step_length=1.0000000001764853, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([4.06802355, 0.52800352]), radius=0.10884616398601439, bounds=Bounds(lower=array([2., 0.]), upper=array([20. , 0.7]))), model_indices=array([ 3, 27, 28, 30, 31, 32, 34, 35, 36]), model=ScalarModel(intercept=0.4105302177904308, linear_terms=array([ 0.00465869, -0.00537636]), square_terms=array([[8.19757769e-04, 3.15606956e-02], - [3.15606956e-02, 6.69515735e+00]]), scale=0.10884616398601439, shift=array([4.06802355, 0.52800352])), vector_model=VectorModel(intercepts=array([ 0.12803165, 0.23858248, 0.24705727, 0.24876636, 0.22173997, - 0.1770757 , 0.12976233, -0.01593805, -0.10083657, -0.01010953, - -0.25513117, -0.16998206, -0.10775377, -0.0739005 , -0.05953791, - -0.05947176, -0.05768123]), linear_terms=array([[0., 0.], + [0., 0.]]]), scale=0.5837906205607757, shift=array([5.83790621, 0.17768436])), candidate_index=44, candidate_x=array([5.34974579, 0.17125845]), index=42, x=array([5.35430561, 0.1711073 ]), fval=0.2422367332032626, rho=-6.3021226718174725, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([37, 39, 40, 41, 42, 43]), old_indices_discarded=array([], dtype=int64), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([5.35430561, 0.1711073 ]), radius=0.00228043211156553, bounds=Bounds(lower=array([1.1 , 0.01]), upper=array([20. , 0.99]))), model_indices=array([37, 39, 40, 41, 42, 43, 44]), model=ScalarModel(intercept=0.24227590126096604, linear_terms=array([1.99857765e-06, 8.90347166e-06]), square_terms=array([[1.57449078e-07, 3.62430439e-06], + [3.62430439e-06, 4.50545254e-04]]), scale=0.00228043211156553, shift=array([5.35430561, 0.1711073 ])), vector_model=VectorModel(intercepts=array([ 0.04097031, 0.08957803, 0.08816081, 0.11232093, 0.12575895, + 0.13980376, 0.15781889, 0.17546538, 0.09348822, 0.15053254, + -0.17880431, -0.21077511, -0.08570458, -0.06416478, -0.05745986, + -0.05902133, -0.05316704]), linear_terms=array([[0., 0.], [0., 0.], [0., 0.], [0., 0.], @@ -5268,12 +6877,11 @@ algorithm_output,"{'states': [State(trustregion=Region(center=array([3.46495546, [0., 0.]], [[0., 0.], - [0., 0.]]]), scale=0.43538465594405756, shift=array([4.35384656, 0.52929957])), candidate_index=37, candidate_x=array([3.95917901, 0.52860366]), index=37, x=array([3.95917901, 0.52860366]), fval=0.4064480043592752, rho=0.9493076658123384, accepted=True, new_indices=array([], dtype=int64), old_indices_used=array([ 3, 27, 28, 30, 31, 32, 34, 35, 36]), old_indices_discarded=array([ 0, 1, 7, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, - 24, 25, 26, 29, 33]), step_length=0.10884619681239267, relative_step_length=1.0000003015850727, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([3.95917901, 0.52860366]), radius=0.21769232797202878, bounds=Bounds(lower=array([2., 0.]), upper=array([20. , 0.7]))), model_indices=array([ 7, 10, 27, 28, 30, 34, 35, 36, 37]), model=ScalarModel(intercept=0.4210970131942301, linear_terms=array([ 0.0050181 , -0.35861903]), square_terms=array([[0.0035888 , 0.06796084], - [0.06796084, 3.49546927]]), scale=array([0.1929248 , 0.18216057]), shift=array([3.95917901, 0.51783943])), vector_model=VectorModel(intercepts=array([ 0.12803165, 0.23858248, 0.24705727, 0.24876636, 0.22173997, - 0.1770757 , 0.12976233, -0.01593805, -0.10083657, -0.01010953, - -0.25513117, -0.16998206, -0.10775377, -0.0739005 , -0.05953791, - -0.05947176, -0.05768123]), linear_terms=array([[0., 0.], + [0., 0.]]]), scale=0.5837906205607757, shift=array([5.83790621, 0.17768436])), candidate_index=45, candidate_x=array([5.3520249 , 0.17108069]), index=42, x=array([5.35430561, 0.1711073 ]), fval=0.2422367332032626, rho=-2.3278538400000417, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([37, 39, 40, 41, 42, 43, 44]), old_indices_discarded=array([], dtype=int64), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([5.35430561, 0.1711073 ]), radius=0.001140216055782765, bounds=Bounds(lower=array([1.1 , 0.01]), upper=array([20. , 0.99]))), model_indices=array([39, 40, 41, 42, 44, 45]), model=ScalarModel(intercept=0.2422604755293883, linear_terms=array([-2.61201951e-06, -1.20401397e-05]), square_terms=array([[4.05327539e-08, 9.79447033e-07], + [9.79447033e-07, 1.12921382e-04]]), scale=0.001140216055782765, shift=array([5.35430561, 0.1711073 ])), vector_model=VectorModel(intercepts=array([ 0.04097031, 0.08957803, 0.08816081, 0.11232093, 0.12575895, + 0.13980376, 0.15781889, 0.17546538, 0.09348822, 0.15053254, + -0.17880431, -0.21077511, -0.08570458, -0.06416478, -0.05745986, + -0.05902133, -0.05316704]), linear_terms=array([[0., 0.], [0., 0.], [0., 0.], [0., 0.], @@ -5338,12 +6946,11 @@ algorithm_output,"{'states': [State(trustregion=Region(center=array([3.46495546, [0., 0.]], [[0., 0.], - [0., 0.]]]), scale=0.43538465594405756, shift=array([4.35384656, 0.52929957])), candidate_index=38, candidate_x=array([3.76625421, 0.54006993]), index=37, x=array([3.95917901, 0.52860366]), fval=0.4064480043592752, rho=-1.6801989983272398, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([ 7, 10, 27, 28, 30, 34, 35, 36, 37]), old_indices_discarded=array([ 0, 1, 2, 3, 4, 5, 6, 8, 9, 11, 12, 13, 14, 15, 16, 17, 18, - 19, 20, 21, 22, 23, 24, 25, 26, 29, 31, 32, 33]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([3.95917901, 0.52860366]), radius=0.10884616398601439, bounds=Bounds(lower=array([2., 0.]), upper=array([20. , 0.7]))), model_indices=array([ 3, 7, 10, 27, 30, 32, 35, 36, 37]), model=ScalarModel(intercept=0.4108870507012534, linear_terms=array([ 0.00245588, -0.04058322]), square_terms=array([[ 7.60010574e-04, -1.05525541e-02], - [-1.05525541e-02, 1.18209112e+00]]), scale=0.10884616398601439, shift=array([3.95917901, 0.52860366])), vector_model=VectorModel(intercepts=array([ 0.12803165, 0.23858248, 0.24705727, 0.24876636, 0.22173997, - 0.1770757 , 0.12976233, -0.01593805, -0.10083657, -0.01010953, - -0.25513117, -0.16998206, -0.10775377, -0.0739005 , -0.05953791, - -0.05947176, -0.05768123]), linear_terms=array([[0., 0.], + [0., 0.]]]), scale=0.5837906205607757, shift=array([5.83790621, 0.17768436])), candidate_index=46, candidate_x=array([5.35544682, 0.17121658]), index=42, x=array([5.35430561, 0.1711073 ]), fval=0.2422367332032626, rho=-6.392707920855079, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([39, 40, 41, 42, 44, 45]), old_indices_discarded=array([], dtype=int64), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([5.35430561, 0.1711073 ]), radius=0.0005701080278913825, bounds=Bounds(lower=array([1.1 , 0.01]), upper=array([20. , 0.99]))), model_indices=array([39, 42, 45, 46]), model=ScalarModel(intercept=0.24224718857995056, linear_terms=array([ 2.51070195e-06, -1.40348420e-05]), square_terms=array([[9.89078864e-09, 2.54954799e-07], + [2.54954799e-07, 2.83831506e-05]]), scale=0.0005701080278913825, shift=array([5.35430561, 0.1711073 ])), vector_model=VectorModel(intercepts=array([ 0.04097031, 0.08957803, 0.08816081, 0.11232093, 0.12575895, + 0.13980376, 0.15781889, 0.17546538, 0.09348822, 0.15053254, + -0.17880431, -0.21077511, -0.08570458, -0.06416478, -0.05745986, + -0.05902133, -0.05316704]), linear_terms=array([[0., 0.], [0., 0.], [0., 0.], [0., 0.], @@ -5408,12 +7015,11 @@ algorithm_output,"{'states': [State(trustregion=Region(center=array([3.46495546, [0., 0.]], [[0., 0.], - [0., 0.]]]), scale=0.43538465594405756, shift=array([4.35384656, 0.52929957])), candidate_index=39, candidate_x=array([3.85031918, 0.5313654 ]), index=39, x=array([3.85031918, 0.5313654 ]), fval=0.4044417040226724, rho=0.8163938340465363, accepted=True, new_indices=array([], dtype=int64), old_indices_used=array([ 3, 7, 10, 27, 30, 32, 35, 36, 37]), old_indices_discarded=array([ 0, 1, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, - 26, 28, 29, 31, 33, 34, 38]), step_length=0.10889485569607045, relative_step_length=1.000447344290997, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([3.85031918, 0.5313654 ]), radius=0.21769232797202878, bounds=Bounds(lower=array([2., 0.]), upper=array([20. , 0.7]))), model_indices=array([ 3, 7, 10, 27, 32, 36, 37, 38, 39]), model=ScalarModel(intercept=0.41660202825227327, linear_terms=array([ 0.00360366, -0.19199293]), square_terms=array([[ 3.17912479e-03, -5.20769451e-02], - [-5.20769451e-02, 3.23351548e+00]]), scale=array([0.1929248, 0.1807797]), shift=array([3.85031918, 0.5192203 ])), vector_model=VectorModel(intercepts=array([ 0.12803165, 0.23858248, 0.24705727, 0.24876636, 0.22173997, - 0.1770757 , 0.12976233, -0.01593805, -0.10083657, -0.01010953, - -0.25513117, -0.16998206, -0.10775377, -0.0739005 , -0.05953791, - -0.05947176, -0.05768123]), linear_terms=array([[0., 0.], + [0., 0.]]]), scale=0.5837906205607757, shift=array([5.83790621, 0.17768436])), candidate_index=47, candidate_x=array([5.35373784, 0.17136997]), index=42, x=array([5.35430561, 0.1711073 ]), fval=0.2422367332032626, rho=-9.761421022287955, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([39, 42, 45, 46]), old_indices_discarded=array([], dtype=int64), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([5.35430561, 0.1711073 ]), radius=0.00028505401394569125, bounds=Bounds(lower=array([1.1 , 0.01]), upper=array([20. , 0.99]))), model_indices=array([39, 42, 46, 47]), model=ScalarModel(intercept=0.2422674286871516, linear_terms=array([-4.83904426e-06, -1.53169699e-06]), square_terms=array([[3.15265250e-09, 9.17365476e-08], + [9.17365476e-08, 7.04918151e-06]]), scale=0.00028505401394569125, shift=array([5.35430561, 0.1711073 ])), vector_model=VectorModel(intercepts=array([ 0.04097031, 0.08957803, 0.08816081, 0.11232093, 0.12575895, + 0.13980376, 0.15781889, 0.17546538, 0.09348822, 0.15053254, + -0.17880431, -0.21077511, -0.08570458, -0.06416478, -0.05745986, + -0.05902133, -0.05316704]), linear_terms=array([[0., 0.], [0., 0.], [0., 0.], [0., 0.], @@ -5478,12 +7084,11 @@ algorithm_output,"{'states': [State(trustregion=Region(center=array([3.46495546, [0., 0.]], [[0., 0.], - [0., 0.]]]), scale=0.43538465594405756, shift=array([4.35384656, 0.52929957])), candidate_index=40, candidate_x=array([3.80815126, 0.52931788]), index=40, x=array([3.80815126, 0.52931788]), fval=0.40143193903456315, rho=19.491210808282354, accepted=True, new_indices=array([], dtype=int64), old_indices_used=array([ 3, 7, 10, 27, 32, 36, 37, 38, 39]), old_indices_discarded=array([ 0, 1, 2, 4, 5, 6, 8, 9, 11, 12, 13, 14, 15, 16, 17, 18, 19, - 20, 21, 22, 23, 24, 25, 26, 28, 29, 30, 31, 33, 34, 35]), step_length=0.042217599815912346, relative_step_length=0.193932419250608, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([3.80815126, 0.52931788]), radius=0.21769232797202878, bounds=Bounds(lower=array([2., 0.]), upper=array([20. , 0.7]))), model_indices=array([ 3, 7, 10, 32, 36, 37, 38, 39, 40]), model=ScalarModel(intercept=0.4162992313547448, linear_terms=array([ 0.00399048, -0.24713241]), square_terms=array([[ 2.77240574e-03, -3.67512298e-02], - [-3.67512298e-02, 3.34648611e+00]]), scale=array([0.1929248 , 0.18180346]), shift=array([3.80815126, 0.51819654])), vector_model=VectorModel(intercepts=array([ 0.12803165, 0.23858248, 0.24705727, 0.24876636, 0.22173997, - 0.1770757 , 0.12976233, -0.01593805, -0.10083657, -0.01010953, - -0.25513117, -0.16998206, -0.10775377, -0.0739005 , -0.05953791, - -0.05947176, -0.05768123]), linear_terms=array([[0., 0.], + [0., 0.]]]), scale=0.5837906205607757, shift=array([5.83790621, 0.17768436])), candidate_index=48, candidate_x=array([5.35459114, 0.17114189]), index=42, x=array([5.35430561, 0.1711073 ]), fval=0.2422367332032626, rho=-1.76601101681869, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([39, 42, 46, 47]), old_indices_discarded=array([], dtype=int64), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([5.35430561, 0.1711073 ]), radius=0.00014252700697284563, bounds=Bounds(lower=array([1.1 , 0.01]), upper=array([20. , 0.99]))), model_indices=array([42, 47, 48]), model=ScalarModel(intercept=0.24223673320326256, linear_terms=array([5.02372003e-07, 3.17577167e-05]), square_terms=array([[7.11686537e-10, 2.09000216e-08], + [2.09000216e-08, 1.66981772e-06]]), scale=0.00014252700697284563, shift=array([5.35430561, 0.1711073 ])), vector_model=VectorModel(intercepts=array([ 0.04097031, 0.08957803, 0.08816081, 0.11232093, 0.12575895, + 0.13980376, 0.15781889, 0.17546538, 0.09348822, 0.15053254, + -0.17880431, -0.21077511, -0.08570458, -0.06416478, -0.05745986, + -0.05902133, -0.05316704]), linear_terms=array([[0., 0.], [0., 0.], [0., 0.], [0., 0.], @@ -5548,12 +7153,11 @@ algorithm_output,"{'states': [State(trustregion=Region(center=array([3.46495546, [0., 0.]], [[0., 0.], - [0., 0.]]]), scale=0.43538465594405756, shift=array([4.35384656, 0.52929957])), candidate_index=41, candidate_x=array([3.70419109, 0.53054654]), index=41, x=array([3.70419109, 0.53054654]), fval=0.39896516136601756, rho=4.025569031416574, accepted=True, new_indices=array([], dtype=int64), old_indices_used=array([ 3, 7, 10, 32, 36, 37, 38, 39, 40]), old_indices_discarded=array([ 0, 1, 2, 4, 5, 6, 8, 9, 11, 12, 13, 14, 15, 16, 17, 18, 19, - 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 33, 34, 35]), step_length=0.10396742981901862, relative_step_length=0.47758885573761406, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([3.70419109, 0.53054654]), radius=0.21769232797202878, bounds=Bounds(lower=array([2., 0.]), upper=array([20. , 0.7]))), model_indices=array([ 3, 7, 10, 36, 37, 38, 39, 40, 41]), model=ScalarModel(intercept=0.4134756509382537, linear_terms=array([ 0.00269932, -0.26210657]), square_terms=array([[ 2.57585927e-03, -1.37577342e-02], - [-1.37577342e-02, 3.35890733e+00]]), scale=array([0.1929248 , 0.18118913]), shift=array([3.70419109, 0.51881087])), vector_model=VectorModel(intercepts=array([ 0.12803165, 0.23858248, 0.24705727, 0.24876636, 0.22173997, - 0.1770757 , 0.12976233, -0.01593805, -0.10083657, -0.01010953, - -0.25513117, -0.16998206, -0.10775377, -0.0739005 , -0.05953791, - -0.05947176, -0.05768123]), linear_terms=array([[0., 0.], + [0., 0.]]]), scale=0.5837906205607757, shift=array([5.83790621, 0.17768436])), candidate_index=49, candidate_x=array([5.35430724, 0.17096478]), index=42, x=array([5.35430561, 0.1711073 ]), fval=0.2422367332032626, rho=-0.0087460529528702, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([42, 47, 48]), old_indices_discarded=array([], dtype=int64), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([5.35430561, 0.1711073 ]), radius=7.126350348642281e-05, bounds=Bounds(lower=array([1.1 , 0.01]), upper=array([20. , 0.99]))), model_indices=array([42, 48, 49]), model=ScalarModel(intercept=0.24223673320326244, linear_terms=array([2.13529941e-06, 3.25430275e-07]), square_terms=array([[1.72071804e-10, 4.10474480e-09], + [4.10474480e-09, 4.36348657e-07]]), scale=7.126350348642281e-05, shift=array([5.35430561, 0.1711073 ])), vector_model=VectorModel(intercepts=array([ 0.04097031, 0.08957803, 0.08816081, 0.11232093, 0.12575895, + 0.13980376, 0.15781889, 0.17546538, 0.09348822, 0.15053254, + -0.17880431, -0.21077511, -0.08570458, -0.06416478, -0.05745986, + -0.05902133, -0.05316704]), linear_terms=array([[0., 0.], [0., 0.], [0., 0.], [0., 0.], @@ -5618,12 +7222,11 @@ algorithm_output,"{'states': [State(trustregion=Region(center=array([3.46495546, [0., 0.]], [[0., 0.], - [0., 0.]]]), scale=0.43538465594405756, shift=array([4.35384656, 0.52929957])), candidate_index=42, candidate_x=array([3.5797031 , 0.53247078]), index=42, x=array([3.5797031 , 0.53247078]), fval=0.3979187604888005, rho=1.2761750079319616, accepted=True, new_indices=array([], dtype=int64), old_indices_used=array([ 3, 7, 10, 36, 37, 38, 39, 40, 41]), old_indices_discarded=array([ 0, 1, 2, 4, 6, 8, 9, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, - 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35]), step_length=0.1245028628330165, relative_step_length=0.5719212247526418, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([3.5797031 , 0.53247078]), radius=0.43538465594405756, bounds=Bounds(lower=array([2., 0.]), upper=array([20. , 0.7]))), model_indices=array([ 3, 7, 10, 37, 38, 39, 40, 41, 42]), model=ScalarModel(intercept=1.029047915986792, linear_terms=array([-0.03579457, -3.1006231 ]), square_terms=array([[0.0131399 , 0.10624136], - [0.10624136, 7.61557266]]), scale=array([0.38584961, 0.27668941]), shift=array([3.5797031 , 0.42331059])), vector_model=VectorModel(intercepts=array([ 0.12803165, 0.23858248, 0.24705727, 0.24876636, 0.22173997, - 0.1770757 , 0.12976233, -0.01593805, -0.10083657, -0.01010953, - -0.25513117, -0.16998206, -0.10775377, -0.0739005 , -0.05953791, - -0.05947176, -0.05768123]), linear_terms=array([[0., 0.], + [0., 0.]]]), scale=0.5837906205607757, shift=array([5.83790621, 0.17768436])), candidate_index=50, candidate_x=array([5.3542349 , 0.17109845]), index=50, x=array([5.3542349 , 0.17109845]), fval=0.24223503271901853, rho=0.788996851874173, accepted=True, new_indices=array([], dtype=int64), old_indices_used=array([42, 48, 49]), old_indices_discarded=array([], dtype=int64), step_length=7.12641605962148e-05, relative_step_length=1.0000092208460127, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([5.3542349 , 0.17109845]), radius=0.00014252700697284563, bounds=Bounds(lower=array([1.1 , 0.01]), upper=array([20. , 0.99]))), model_indices=array([42, 47, 48, 49, 50]), model=ScalarModel(intercept=0.24224492204264927, linear_terms=array([-3.76156364e-06, 1.64186210e-05]), square_terms=array([[9.45521287e-10, 2.62809647e-08], + [2.62809647e-08, 1.70525908e-06]]), scale=0.00014252700697284563, shift=array([5.3542349 , 0.17109845])), vector_model=VectorModel(intercepts=array([ 0.04097031, 0.08957803, 0.08816081, 0.11232093, 0.12575895, + 0.13980376, 0.15781889, 0.17546538, 0.09348822, 0.15053254, + -0.17880431, -0.21077511, -0.08570458, -0.06416478, -0.05745986, + -0.05902133, -0.05316704]), linear_terms=array([[0., 0.], [0., 0.], [0., 0.], [0., 0.], @@ -5688,12 +7291,11 @@ algorithm_output,"{'states': [State(trustregion=Region(center=array([3.46495546, [0., 0.]], [[0., 0.], - [0., 0.]]]), scale=0.43538465594405756, shift=array([4.35384656, 0.52929957])), candidate_index=43, candidate_x=array([3.33276529, 0.53843292]), index=42, x=array([3.5797031 , 0.53247078]), fval=0.3979187604888005, rho=-4.283280658583433, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([ 3, 7, 10, 37, 38, 39, 40, 41, 42]), old_indices_discarded=array([ 0, 1, 2, 4, 5, 6, 8, 9, 11, 12, 13, 14, 15, 16, 17, 18, 19, - 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([3.5797031 , 0.53247078]), radius=0.21769232797202878, bounds=Bounds(lower=array([2., 0.]), upper=array([20. , 0.7]))), model_indices=array([ 3, 10, 37, 38, 39, 40, 41, 42, 43]), model=ScalarModel(intercept=0.4112188064553157, linear_terms=array([ 0.00073757, -0.26718967]), square_terms=array([[ 3.33287034e-03, -2.53619579e-03], - [-2.53619579e-03, 3.70057636e+00]]), scale=array([0.1929248 , 0.18022701]), shift=array([3.5797031 , 0.51977299])), vector_model=VectorModel(intercepts=array([ 0.12803165, 0.23858248, 0.24705727, 0.24876636, 0.22173997, - 0.1770757 , 0.12976233, -0.01593805, -0.10083657, -0.01010953, - -0.25513117, -0.16998206, -0.10775377, -0.0739005 , -0.05953791, - -0.05947176, -0.05768123]), linear_terms=array([[0., 0.], + [0., 0.]]]), scale=0.5837906205607757, shift=array([5.83790621, 0.17768436])), candidate_index=51, candidate_x=array([5.35427389, 0.17096136]), index=50, x=array([5.3542349 , 0.17109845]), fval=0.24223503271901853, rho=-0.16458879109056918, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([42, 47, 48, 49, 50]), old_indices_discarded=array([], dtype=int64), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([5.3542349 , 0.17109845]), radius=7.126350348642281e-05, bounds=Bounds(lower=array([1.1 , 0.01]), upper=array([20. , 0.99]))), model_indices=array([42, 49, 50, 51]), model=ScalarModel(intercept=0.2422353089967809, linear_terms=array([ 1.17750480e-06, -1.71985531e-07]), square_terms=array([[1.67731546e-10, 4.23329742e-09], + [4.23329742e-09, 4.36229157e-07]]), scale=7.126350348642281e-05, shift=array([5.3542349 , 0.17109845])), vector_model=VectorModel(intercepts=array([ 0.04097031, 0.08957803, 0.08816081, 0.11232093, 0.12575895, + 0.13980376, 0.15781889, 0.17546538, 0.09348822, 0.15053254, + -0.17880431, -0.21077511, -0.08570458, -0.06416478, -0.05745986, + -0.05902133, -0.05316704]), linear_terms=array([[0., 0.], [0., 0.], [0., 0.], [0., 0.], @@ -5758,12 +7360,11 @@ algorithm_output,"{'states': [State(trustregion=Region(center=array([3.46495546, [0., 0.]], [[0., 0.], - [0., 0.]]]), scale=0.43538465594405756, shift=array([4.35384656, 0.52929957])), candidate_index=44, candidate_x=array([3.54759141, 0.53276521]), index=44, x=array([3.54759141, 0.53276521]), fval=0.39775315254456883, rho=3.1973343535335847, accepted=True, new_indices=array([], dtype=int64), old_indices_used=array([ 3, 10, 37, 38, 39, 40, 41, 42, 43]), old_indices_discarded=array([ 0, 1, 6, 7, 9, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, - 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36]), step_length=0.03211304587119773, relative_step_length=0.14751574467669767, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([3.54759141, 0.53276521]), radius=0.21769232797202878, bounds=Bounds(lower=array([2., 0.]), upper=array([20. , 0.7]))), model_indices=array([ 3, 37, 38, 39, 40, 41, 42, 43, 44]), model=ScalarModel(intercept=0.4293548516074232, linear_terms=array([-0.00372995, -1.09697576]), square_terms=array([[3.71943617e-03, 8.67343685e-02], - [8.67343685e-02, 1.83358032e+01]]), scale=array([0.1929248, 0.1800798]), shift=array([3.54759141, 0.5199202 ])), vector_model=VectorModel(intercepts=array([ 0.12803165, 0.23858248, 0.24705727, 0.24876636, 0.22173997, - 0.1770757 , 0.12976233, -0.01593805, -0.10083657, -0.01010953, - -0.25513117, -0.16998206, -0.10775377, -0.0739005 , -0.05953791, - -0.05947176, -0.05768123]), linear_terms=array([[0., 0.], + [0., 0.]]]), scale=0.5837906205607757, shift=array([5.83790621, 0.17768436])), candidate_index=52, candidate_x=array([5.35416406, 0.1711062 ]), index=50, x=array([5.3542349 , 0.17109845]), fval=0.24223503271901853, rho=-1.5548413629872948, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([42, 49, 50, 51]), old_indices_discarded=array([], dtype=int64), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([5.3542349 , 0.17109845]), radius=3.563175174321141e-05, bounds=Bounds(lower=array([1.1 , 0.01]), upper=array([20. , 0.99]))), model_indices=array([42, 49, 50, 51, 52]), model=ScalarModel(intercept=0.24223624887821155, linear_terms=array([-5.72724933e-08, -9.62016662e-08]), square_terms=array([[4.08764832e-11, 1.01998995e-09], + [1.01998995e-09, 1.09056071e-07]]), scale=3.563175174321141e-05, shift=array([5.3542349 , 0.17109845])), vector_model=VectorModel(intercepts=array([ 0.04097031, 0.08957803, 0.08816081, 0.11232093, 0.12575895, + 0.13980376, 0.15781889, 0.17546538, 0.09348822, 0.15053254, + -0.17880431, -0.21077511, -0.08570458, -0.06416478, -0.05745986, + -0.05902133, -0.05316704]), linear_terms=array([[0., 0.], [0., 0.], [0., 0.], [0., 0.], @@ -5828,12 +7429,11 @@ algorithm_output,"{'states': [State(trustregion=Region(center=array([3.46495546, [0., 0.]], [[0., 0.], - [0., 0.]]]), scale=0.43538465594405756, shift=array([4.35384656, 0.52929957])), candidate_index=45, candidate_x=array([3.46252494, 0.53106944]), index=45, x=array([3.46252494, 0.53106944]), fval=0.3956555018961593, rho=1.3668370710605215, accepted=True, new_indices=array([], dtype=int64), old_indices_used=array([ 3, 37, 38, 39, 40, 41, 42, 43, 44]), old_indices_discarded=array([ 0, 1, 6, 7, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, - 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36]), step_length=0.08508336488699537, relative_step_length=0.39084227579176656, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([3.46252494, 0.53106944]), radius=0.21769232797202878, bounds=Bounds(lower=array([2., 0.]), upper=array([20. , 0.7]))), model_indices=array([38, 39, 40, 41, 42, 43, 44, 45, 46]), model=ScalarModel(intercept=0.4140549602916846, linear_terms=array([-0.00147289, -0.33289269]), square_terms=array([[0.00357896, 0.01082371], - [0.01082371, 3.51995054]]), scale=array([0.1929248 , 0.18092768]), shift=array([3.46252494, 0.51907232])), vector_model=VectorModel(intercepts=array([ 0.12803165, 0.23858248, 0.24705727, 0.24876636, 0.22173997, - 0.1770757 , 0.12976233, -0.01593805, -0.10083657, -0.01010953, - -0.25513117, -0.16998206, -0.10775377, -0.0739005 , -0.05953791, - -0.05947176, -0.05768123]), linear_terms=array([[0., 0.], + [0., 0.]]]), scale=0.5837906205607757, shift=array([5.83790621, 0.17768436])), candidate_index=53, candidate_x=array([5.35426853, 0.17111852]), index=50, x=array([5.3542349 , 0.17109845]), fval=0.24223503271901853, rho=-49.234038408931376, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([42, 49, 50, 51, 52]), old_indices_discarded=array([], dtype=int64), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([5.3542349 , 0.17109845]), radius=1.7815875871605703e-05, bounds=Bounds(lower=array([1.1 , 0.01]), upper=array([20. , 0.99]))), model_indices=array([42, 50, 52, 53]), model=ScalarModel(intercept=0.24223497560711219, linear_terms=array([-4.74432307e-08, 4.02785705e-06]), square_terms=array([[1.01749646e-11, 2.52377502e-10], + [2.52377502e-10, 2.76008124e-08]]), scale=1.7815875871605703e-05, shift=array([5.3542349 , 0.17109845])), vector_model=VectorModel(intercepts=array([ 0.04097031, 0.08957803, 0.08816081, 0.11232093, 0.12575895, + 0.13980376, 0.15781889, 0.17546538, 0.09348822, 0.15053254, + -0.17880431, -0.21077511, -0.08570458, -0.06416478, -0.05745986, + -0.05902133, -0.05316704]), linear_terms=array([[0., 0.], [0., 0.], [0., 0.], [0., 0.], @@ -5898,12 +7498,11 @@ algorithm_output,"{'states': [State(trustregion=Region(center=array([3.46495546, [0., 0.]], [[0., 0.], - [0., 0.]]]), scale=0.43538465594405756, shift=array([4.35384656, 0.52929957])), candidate_index=47, candidate_x=array([3.48696957, 0.53611272]), index=45, x=array([3.46252494, 0.53106944]), fval=0.3956555018961593, rho=-6.022189477944362, accepted=False, new_indices=array([46]), old_indices_used=array([38, 39, 40, 41, 42, 43, 44, 45]), old_indices_discarded=array([ 0, 1, 3, 7, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, - 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([3.46252494, 0.53106944]), radius=0.10884616398601439, bounds=Bounds(lower=array([2., 0.]), upper=array([20. , 0.7]))), model_indices=array([38, 40, 41, 42, 43, 44, 45, 46, 47]), model=ScalarModel(intercept=0.4004145101752352, linear_terms=array([-0.0005299 , -0.05352972]), square_terms=array([[1.14945205e-03, 2.47670203e-03], - [2.47670203e-03, 1.26283024e+00]]), scale=0.10884616398601439, shift=array([3.46252494, 0.53106944])), vector_model=VectorModel(intercepts=array([ 0.12803165, 0.23858248, 0.24705727, 0.24876636, 0.22173997, - 0.1770757 , 0.12976233, -0.01593805, -0.10083657, -0.01010953, - -0.25513117, -0.16998206, -0.10775377, -0.0739005 , -0.05953791, - -0.05947176, -0.05768123]), linear_terms=array([[0., 0.], + [0., 0.]]]), scale=0.5837906205607757, shift=array([5.83790621, 0.17768436])), candidate_index=54, candidate_x=array([5.35423517, 0.17108064]), index=54, x=array([5.35423517, 0.17108064]), fval=0.24223166413037348, rho=0.8391433969707881, accepted=True, new_indices=array([], dtype=int64), old_indices_used=array([42, 50, 52, 53]), old_indices_discarded=array([], dtype=int64), step_length=1.7815875871611863e-05, relative_step_length=1.0000000000003457, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([5.35423517, 0.17108064]), radius=3.563175174321141e-05, bounds=Bounds(lower=array([1.1 , 0.01]), upper=array([20. , 0.99]))), model_indices=array([42, 49, 50, 51, 52, 53, 54]), model=ScalarModel(intercept=0.24223597836991295, linear_terms=array([4.47141236e-07, 1.37410695e-07]), square_terms=array([[4.06123488e-11, 1.05080752e-09], + [1.05080752e-09, 1.09096371e-07]]), scale=3.563175174321141e-05, shift=array([5.35423517, 0.17108064])), vector_model=VectorModel(intercepts=array([ 0.04097031, 0.08957803, 0.08816081, 0.11232093, 0.12575895, + 0.13980376, 0.15781889, 0.17546538, 0.09348822, 0.15053254, + -0.17880431, -0.21077511, -0.08570458, -0.06416478, -0.05745986, + -0.05902133, -0.05316704]), linear_terms=array([[0., 0.], [0., 0.], [0., 0.], [0., 0.], @@ -5968,11 +7567,11 @@ algorithm_output,"{'states': [State(trustregion=Region(center=array([3.46495546, [0., 0.]], [[0., 0.], - [0., 0.]]]), scale=0.43538465594405756, shift=array([4.35384656, 0.52929957])), candidate_index=48, candidate_x=array([3.5712846 , 0.53540815]), index=45, x=array([3.46252494, 0.53106944]), fval=0.3956555018961593, rho=-8.397857410291905, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([38, 40, 41, 42, 43, 44, 45, 46, 47]), old_indices_discarded=array([ 3, 7, 10, 37, 39]), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([3.46252494, 0.53106944]), radius=0.054423081993007195, bounds=Bounds(lower=array([2., 0.]), upper=array([20. , 0.7]))), model_indices=array([41, 42, 43, 44, 45, 46, 47, 48]), model=ScalarModel(intercept=0.4012375879096973, linear_terms=array([-0.00126986, -0.02448196]), square_terms=array([[ 0.00034905, -0.00401173], - [-0.00401173, 0.30043817]]), scale=0.054423081993007195, shift=array([3.46252494, 0.53106944])), vector_model=VectorModel(intercepts=array([ 0.12803165, 0.23858248, 0.24705727, 0.24876636, 0.22173997, - 0.1770757 , 0.12976233, -0.01593805, -0.10083657, -0.01010953, - -0.25513117, -0.16998206, -0.10775377, -0.0739005 , -0.05953791, - -0.05947176, -0.05768123]), linear_terms=array([[0., 0.], + [0., 0.]]]), scale=0.5837906205607757, shift=array([5.83790621, 0.17768436])), candidate_index=55, candidate_x=array([5.35420058, 0.1710721 ]), index=55, x=array([5.35420058, 0.1710721 ]), fval=0.24223019482007688, rho=3.168897351422072, accepted=True, new_indices=array([], dtype=int64), old_indices_used=array([42, 49, 50, 51, 52, 53, 54]), old_indices_discarded=array([], dtype=int64), step_length=3.563336405853496e-05, relative_step_length=1.0000452493982102, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([5.35420058, 0.1710721 ]), radius=7.126350348642281e-05, bounds=Bounds(lower=array([1.1 , 0.01]), upper=array([20. , 0.99]))), model_indices=array([42, 49, 50, 51, 52, 53, 54, 55]), model=ScalarModel(intercept=0.24223407516118386, linear_terms=array([2.08971335e-06, 5.06945130e-07]), square_terms=array([[1.70894503e-10, 4.32417031e-09], + [4.32417031e-09, 4.36442958e-07]]), scale=7.126350348642281e-05, shift=array([5.35420058, 0.1710721 ])), vector_model=VectorModel(intercepts=array([ 0.04097031, 0.08957803, 0.08816081, 0.11232093, 0.12575895, + 0.13980376, 0.15781889, 0.17546538, 0.09348822, 0.15053254, + -0.17880431, -0.21077511, -0.08570458, -0.06416478, -0.05745986, + -0.05902133, -0.05316704]), linear_terms=array([[0., 0.], [0., 0.], [0., 0.], [0., 0.], @@ -6037,11 +7636,11 @@ algorithm_output,"{'states': [State(trustregion=Region(center=array([3.46495546, [0., 0.]], [[0., 0.], - [0., 0.]]]), scale=0.43538465594405756, shift=array([4.35384656, 0.52929957])), candidate_index=49, candidate_x=array([3.51686799, 0.53620761]), index=45, x=array([3.46252494, 0.53106944]), fval=0.3956555018961593, rho=-3.8203621406115498, accepted=False, new_indices=array([], dtype=int64), old_indices_used=array([41, 42, 43, 44, 45, 46, 47, 48]), old_indices_discarded=array([], dtype=int64), step_length=0.0, relative_step_length=0.0, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([3.46252494, 0.53106944]), radius=0.027211540996503598, bounds=Bounds(lower=array([2., 0.]), upper=array([20. , 0.7]))), model_indices=array([42, 43, 44, 45, 47, 48, 49]), model=ScalarModel(intercept=0.39578369763499904, linear_terms=array([-7.18657393e-06, -3.63731051e-03]), square_terms=array([[1.01436423e-04, 2.86359452e-03], - [2.86359452e-03, 4.98920464e-01]]), scale=0.027211540996503598, shift=array([3.46252494, 0.53106944])), vector_model=VectorModel(intercepts=array([ 0.12803165, 0.23858248, 0.24705727, 0.24876636, 0.22173997, - 0.1770757 , 0.12976233, -0.01593805, -0.10083657, -0.01010953, - -0.25513117, -0.16998206, -0.10775377, -0.0739005 , -0.05953791, - -0.05947176, -0.05768123]), linear_terms=array([[0., 0.], + [0., 0.]]]), scale=0.5837906205607757, shift=array([5.83790621, 0.17768436])), candidate_index=56, candidate_x=array([5.35413069, 0.17105814]), index=56, x=array([5.35413069, 0.17105814]), fval=0.24222785386695275, rho=1.0942674916087185, accepted=True, new_indices=array([], dtype=int64), old_indices_used=array([42, 49, 50, 51, 52, 53, 54, 55]), old_indices_discarded=array([], dtype=int64), step_length=7.126490760503242e-05, relative_step_length=1.0000197031936533, n_evals_per_point=1, n_evals_acceptance=1), State(trustregion=Region(center=array([5.35413069, 0.17105814]), radius=0.00014252700697284563, bounds=Bounds(lower=array([1.1 , 0.01]), upper=array([20. , 0.99]))), model_indices=array([42, 49, 50, 51, 52, 53, 54, 55, 56]), model=ScalarModel(intercept=0.24222977403320833, linear_terms=array([6.45945040e-06, 1.64764211e-06]), square_terms=array([[7.69583087e-10, 1.76987495e-08], + [1.76987495e-08, 1.74604758e-06]]), scale=0.00014252700697284563, shift=array([5.35413069, 0.17105814])), vector_model=VectorModel(intercepts=array([ 0.04097031, 0.08957803, 0.08816081, 0.11232093, 0.12575895, + 0.13980376, 0.15781889, 0.17546538, 0.09348822, 0.15053254, + -0.17880431, -0.21077511, -0.08570458, -0.06416478, -0.05745986, + -0.05902133, -0.05316704]), linear_terms=array([[0., 0.], [0., 0.], [0., 0.], [0., 0.], @@ -6106,20 +7705,27 @@ algorithm_output,"{'states': [State(trustregion=Region(center=array([3.46495546, [0., 0.]], [[0., 0.], - [0., 0.]]]), scale=0.43538465594405756, shift=array([4.35384656, 0.52929957])), candidate_index=50, candidate_x=array([3.45814229, 0.53129297]), index=50, x=array([3.45814229, 0.53129297]), fval=0.39565506510735315, rho=0.03041470819550846, accepted=True, new_indices=array([], dtype=int64), old_indices_used=array([42, 43, 44, 45, 47, 48, 49]), old_indices_discarded=array([], dtype=int64), step_length=0.004388346253974881, relative_step_length=0.1612678331792653, n_evals_per_point=1, n_evals_acceptance=1)], 'message': 'Absolute criterion change smaller than tolerance.', 'tranquilo_history': History for least_squares function with 51 entries., 'history': {'params': [{'CRRA': 4.3538465594405755, 'WealthShare': 0.5292995697261916}, {'CRRA': 3.9679969544139664, 'WealthShare': 0.16095959172523663}, {'CRRA': 4.739696164467184, 'WealthShare': 0.4494277926494151}, {'CRRA': 3.9679969544139664, 'WealthShare': 0.5367644630742497}, {'CRRA': 4.705143256220924, 'WealthShare': 0.7}, {'CRRA': 4.739696164467184, 'WealthShare': 0.15540848163294244}, {'CRRA': 4.533200888371263, 'WealthShare': 0.14344996469958265}, {'CRRA': 3.9736045544130407, 'WealthShare': 0.7}, {'CRRA': 4.739696164467184, 'WealthShare': 0.6120017700494169}, {'CRRA': 4.608911584608707, 'WealthShare': 0.7}, {'CRRA': 3.9679969544139664, 'WealthShare': 0.6749605070220508}, {'CRRA': 4.255098551650559, 'WealthShare': 0.14344996469958265}, {'CRRA': 4.330627531593957, 'WealthShare': 0.7}, {'CRRA': 4.173396484643287, 'WealthShare': 0.6367703391312025}, {'CRRA': 4.272270335288372, 'WealthShare': 0.6165345901496717}, {'CRRA': 4.457244178676869, 'WealthShare': 0.5827937283899468}, {'CRRA': 4.30009827804007, 'WealthShare': 0.5087586712987278}, {'CRRA': 4.327204932058983, 'WealthShare': 0.5368950136458573}, {'CRRA': 4.340140884936644, 'WealthShare': 0.527245051960064}, {'CRRA': 4.313448396733487, 'WealthShare': 0.5345172976637097}, {'CRRA': 4.326530588150123, 'WealthShare': 0.5273500300875811}, {'CRRA': 4.300639790015823, 'WealthShare': 0.5359594454885787}, {'CRRA': 4.312925010999421, 'WealthShare': 0.5275604095626945}, {'CRRA': 4.286772205288626, 'WealthShare': 0.5357946609799572}, {'CRRA': 4.299317884307625, 'WealthShare': 0.5276609052628335}, {'CRRA': 4.272108801385839, 'WealthShare': 0.5280631290307891}, {'CRRA': 4.217685433280995, 'WealthShare': 0.5272998588486066}, {'CRRA': 4.10889878313327, 'WealthShare': 0.5331939368621268}, {'CRRA': 4.16331043756309, 'WealthShare': 0.5324387139560688}, {'CRRA': 4.1904738848015395, 'WealthShare': 0.5272944663378364}, {'CRRA': 4.136081979140245, 'WealthShare': 0.5308781894093191}, {'CRRA': 4.1632634304940535, 'WealthShare': 0.5276859635745996}, {'CRRA': 4.108862264648033, 'WealthShare': 0.5312710580088051}, {'CRRA': 4.190170762071212, 'WealthShare': 0.5317434838519692}, {'CRRA': 4.14965754869514, 'WealthShare': 0.5276831792304251}, {'CRRA': 4.122446212961515, 'WealthShare': 0.5277888772395245}, {'CRRA': 4.0680235542384935, 'WealthShare': 0.5280035215512422}, {'CRRA': 3.959179011891613, 'WealthShare': 0.5286036563862734}, {'CRRA': 3.7662542093783085, 'WealthShare': 0.5400699276845887}, {'CRRA': 3.850319182960075, 'WealthShare': 0.5313654025846621}, {'CRRA': 3.808151263909425, 'WealthShare': 0.5293178828278925}, {'CRRA': 3.7041910943241505, 'WealthShare': 0.5305465418422328}, {'CRRA': 3.579703102276506, 'WealthShare': 0.5324707792398705}, {'CRRA': 3.3327652945132527, 'WealthShare': 0.5384329188383193}, {'CRRA': 3.5475914062047367, 'WealthShare': 0.5327652117787955}, {'CRRA': 3.462524942039848, 'WealthShare': 0.5310694361517393}, {'CRRA': 3.2696001395265437, 'WealthShare': 0.7}, {'CRRA': 3.4869695713947886, 'WealthShare': 0.536112719272605}, {'CRRA': 3.57128459904662, 'WealthShare': 0.5354081482002142}, {'CRRA': 3.5168679879087708, 'WealthShare': 0.536207608192228}, {'CRRA': 3.458142292811352, 'WealthShare': 0.5312929726917929}], 'criterion': [0.4255893672451761, nan, 9.124153051671854, 0.42532694175658003, 1.6431260060984585, nan, nan, 1.6925564929577084, 1.0588779200952572, 1.647240228339158, 1.5395875593628365, nan, 1.662212349847188, 1.2586192847229414, 1.0959870474392037, 0.8068961580841107, 0.5476452591210548, 0.4463146451499565, 0.4233635203713483, 0.4365071917419876, 0.42271512004903583, 0.4408126156744072, 0.42211660836041526, 0.43934757573564687, 0.42146435277136396, 0.4203523177729453, 0.41722780024581224, 0.4202696569579592, 0.4211931719510672, 0.41590820294105857, 0.4165570373136448, 0.4147450264942464, 0.4159222997312866, 0.42107246900031176, 0.4141230097680078, 0.4129111617525009, 0.4105781041382112, 0.40644800435927525, 0.43024717774897203, 0.4044417040226723, 0.4014319390345631, 0.39896516136601756, 0.3979187604888004, 0.4107422301122492, 0.39775315254456883, 0.3956555018961592, 1.818883294632069, 0.404293993994037, 0.40394849436141755, 0.4049946429348531, 0.3956550651073532], 'runtime': [0.0, 1.4411268759977247, 1.4892239869986952, 1.5549724159973266, 1.6080741769983433, 1.6501846190003562, 1.70581522700013, 1.7505924289980612, 1.8027306119984132, 1.845262945000286, 1.8922586379994755, 1.9405474230006803, 2.001285777998419, 3.6608718389979913, 5.001907497997308, 6.358722542998294, 7.7012831199972425, 9.051228116997663, 10.380444955000712, 11.715638096997282, 13.033358475000568, 14.394261231998826, 15.831687227997463, 17.217701428999135, 18.74322806499913, 20.090383061997272, 21.436301722998905, 22.783943230999284, 24.145193038999423, 25.486011446999328, 26.843342323998513, 28.18244986799982, 29.500718518000212, 30.816817842998717, 32.213965736998944, 33.60315380300017, 35.16254370399838, 36.514185840998834, 37.89015734699933, 39.26447279999775, 40.65795199099739, 42.03239085200039, 43.38251523099825, 44.792622369997844, 46.16991744400002, 47.65026999499969, 49.12483912699827, 50.628065025997785, 52.297021327998664, 53.8177060909984, 55.35751821399754], 'batches': [0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39]}}], 'exploration_sample': array([[ 3.46495546, 0.53111681], - [ 6.5 , 0.525 ], - [ 8.1875 , 0.503125 ], - [14.375 , 0.56875 ], - [16.625 , 0.48125 ], - [17.75 , 0.6125 ], - [ 3.125 , 0.65625 ], - [12.6875 , 0.678125 ], - [ 4.25 , 0.4375 ], - [ 9.875 , 0.39375 ], - [11. , 0.35 ], - [12.125 , 0.30625 ], - [ 3.6875 , 0.328125 ], - [ 8.75 , 0.2625 ]]), 'exploration_results': array([3.95624204e-01, 5.40772083e-01, 6.64838810e-01, 9.93508418e-01, - 1.09516320e+00, 1.28240377e+00, 1.55241851e+00, 1.58146070e+00, - 2.50692199e+01, 5.43503566e+01, 5.78231367e+02, 2.16882760e+03, - 2.24574771e+03, 2.24849469e+03])}}" + [0., 0.]]]), scale=0.5837906205607757, shift=array([5.83790621, 0.17768436])), candidate_index=57, candidate_x=array([5.35399092, 0.17103024]), index=57, x=array([5.35399092, 0.17103024]), fval=0.24222754644165564, rho=0.046437840364656036, accepted=True, new_indices=array([], dtype=int64), old_indices_used=array([42, 49, 50, 51, 52, 53, 54, 55, 56]), old_indices_discarded=array([47, 48]), step_length=0.0001425347086457425, relative_step_length=1.0000540365861912, n_evals_per_point=1, n_evals_acceptance=1)], 'message': 'Absolute criterion change smaller than tolerance.', 'tranquilo_history': History for least_squares function with 58 entries., 'history': {'params': [{'CRRA': 5.837906205607757, 'WealthShare': 0.17768435978844974}, {'CRRA': 5.521440822118637, 'WealthShare': 0.01}, {'CRRA': 6.355277172375491, 'WealthShare': 0.01}, {'CRRA': 5.320535238840023, 'WealthShare': 0.01}, {'CRRA': 6.330844268900851, 'WealthShare': 0.6950553265561836}, {'CRRA': 6.355277172375491, 'WealthShare': 0.34431980448135446}, {'CRRA': 6.226403636138772, 'WealthShare': 0.01}, {'CRRA': 5.320535238840023, 'WealthShare': 0.01}, {'CRRA': 5.875481040447152, 'WealthShare': 0.6950553265561836}, {'CRRA': 6.343115925559374, 'WealthShare': 0.6950553265561836}, {'CRRA': 5.42192271850144, 'WealthShare': 0.6950553265561836}, {'CRRA': 5.320535238840023, 'WealthShare': 0.3927845660013606}, {'CRRA': 5.320535238840023, 'WealthShare': 0.6950553265561836}, {'CRRA': 6.260289192255453, 'WealthShare': 0.1414416437258815}, {'CRRA': 5.586422994097967, 'WealthShare': 0.12009017405786418}, {'CRRA': 5.696471798014226, 'WealthShare': 0.13230174451397797}, {'CRRA': 5.910749514856811, 'WealthShare': 0.15649323241599017}, {'CRRA': 5.801270203852185, 'WealthShare': 0.16823018219702343}, {'CRRA': 5.874111015856876, 'WealthShare': 0.15737844781264468}, {'CRRA': 5.764781908128255, 'WealthShare': 0.16842199875974878}, {'CRRA': 5.83762293702503, 'WealthShare': 0.15849023997730602}, {'CRRA': 5.728295327191924, 'WealthShare': 0.1687167695944529}, {'CRRA': 5.655320864957503, 'WealthShare': 0.16922976706263002}, {'CRRA': 5.801158262739447, 'WealthShare': 0.159625327541431}, {'CRRA': 5.582345042721493, 'WealthShare': 0.16957706599752984}, {'CRRA': 5.728061206699304, 'WealthShare': 0.1612420849769127}, {'CRRA': 5.655213987125576, 'WealthShare': 0.16219328110045608}, {'CRRA': 5.54577405830501, 'WealthShare': 0.1641467052653886}, {'CRRA': 5.564089269324569, 'WealthShare': 0.16867455696897235}, {'CRRA': 5.527610331306062, 'WealthShare': 0.1695245283248613}, {'CRRA': 5.454569298934131, 'WealthShare': 0.1657673350712589}, {'CRRA': 5.491057478350771, 'WealthShare': 0.16462446060590527}, {'CRRA': 5.509363764950676, 'WealthShare': 0.16935796524808727}, {'CRRA': 5.472878982838546, 'WealthShare': 0.1697534682609821}, {'CRRA': 5.39990991296233, 'WealthShare': 0.1705867470386037}, {'CRRA': 5.2539840063420415, 'WealthShare': 0.166169845381478}, {'CRRA': 5.326948348474455, 'WealthShare': 0.17199264976389753}, {'CRRA': 5.363429877974597, 'WealthShare': 0.17140117312121952}, {'CRRA': 5.381674772858575, 'WealthShare': 0.17165503946704128}, {'CRRA': 5.354324915656451, 'WealthShare': 0.16988722969298148}, {'CRRA': 5.358866777462407, 'WealthShare': 0.17113518644845302}, {'CRRA': 5.349755525044417, 'WealthShare': 0.17069814042911424}, {'CRRA': 5.354305613394689, 'WealthShare': 0.17110730029989854}, {'CRRA': 5.345135297716727, 'WealthShare': 0.17071002327939397}, {'CRRA': 5.349745787974868, 'WealthShare': 0.17125844781552682}, {'CRRA': 5.352024899000856, 'WealthShare': 0.17108068833293297}, {'CRRA': 5.355446817343039, 'WealthShare': 0.1712165807131758}, {'CRRA': 5.353737844217815, 'WealthShare': 0.17136997487615657}, {'CRRA': 5.354591141806533, 'WealthShare': 0.17114188868178082}, {'CRRA': 5.354307242363997, 'WealthShare': 0.17096478260213566}, {'CRRA': 5.354234900928805, 'WealthShare': 0.17109845000305954}, {'CRRA': 5.354273892151148, 'WealthShare': 0.17096136013364222}, {'CRRA': 5.3541640557109185, 'WealthShare': 0.17110619605176702}, {'CRRA': 5.35426853425294, 'WealthShare': 0.1711185203084774}, {'CRRA': 5.354235173394749, 'WealthShare': 0.1710806362107799}, {'CRRA': 5.354200577562492, 'WealthShare': 0.17107210010953106}, {'CRRA': 5.354130693185321, 'WealthShare': 0.17105814085154764}, {'CRRA': 5.35399091577092, 'WealthShare': 0.1710302407154898}], 'criterion': [0.2500179178839741, 1.1792461131204435, 0.9197765436682048, 1.2595171604963433, 33.16445541254984, 1.4878207969751798, 0.9532709482124387, 1.2595171604963433, 36.93789575006835, 33.071347222276614, 41.45067088403316, 2.9856980365173467, 42.60257108837822, 0.27371069489945155, 0.3353446406768353, 0.29385520517736274, 0.25245645388982746, 0.24610730524369168, 0.2512862430006085, 0.24542189740001585, 0.25015888395593905, 0.24507292693629096, 0.2440744520975429, 0.2488794160642582, 0.24318410996735987, 0.24711505738750136, 0.24589227104352215, 0.24442274744445994, 0.24306721295336706, 0.24288435328669916, 0.2433661384295173, 0.24398380010235204, 0.2428345891015183, 0.24267293680244378, 0.24231674775792228, 0.2439014107925056, 0.24236160354034061, 0.2423113173928428, 0.24240633196487957, 0.24234281133746066, 0.2422660131172327, 0.24228370883608596, 0.2422367332032626, 0.24227422877909757, 0.2422985499732716, 0.2422412748554663, 0.2422567765689739, 0.24229594886956057, 0.2422455073255868, 0.24223700359046088, 0.2422350327190185, 0.24223767262404658, 0.24223687844797048, 0.24223948283887395, 0.24223166413037345, 0.2422301948200769, 0.24222785386695275, 0.24222754644165562], 'runtime': [0.0, 1.3006106629909482, 1.3461875649809372, 1.392138064984465, 1.4359841749828774, 1.5009825789893512, 1.550953859987203, 1.593609842006117, 1.638624159997562, 1.686485532001825, 1.7453936449892353, 1.7891343509836588, 1.8489449310000055, 3.2682942989922594, 4.4358367919921875, 5.712266588991042, 6.875062373001128, 8.065197699994314, 9.26269722500001, 10.43409699498443, 11.618591404985636, 12.797749530989677, 13.943540325999493, 15.100036732997978, 16.27896274998784, 17.441876513999887, 18.707559181988472, 19.848269279988017, 21.01465619399096, 22.18544425399159, 23.350925145001383, 24.513529393996578, 25.67127582000103, 26.822254801983945, 27.962893974996405, 29.11491555799148, 30.30321866099257, 31.654834265005775, 32.9144726920058, 34.122135265992256, 35.37244299199665, 36.586844901001314, 37.83399780999753, 39.01701513200533, 40.18066080898279, 41.38312898899312, 42.55371054899297, 43.73981825000374, 45.013344446982956, 46.170059423981, 47.351473324000835, 48.54954139099573, 49.72759446298005, 50.919856733991764, 52.213698393985396, 53.48934546398232, 54.798059503984405, 56.106529726006556], 'batches': [0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46]}, 'multistart_info': {...}}], 'exploration_sample': array([[ 5.35400632, 0.17100463], + [ 7.00625 , 0.19375 ], + [12.9125 , 0.1325 ], + [ 4.64375 , 0.31625 ], + [ 8.1875 , 0.3775 ], + [15.275 , 0.255 ], + [17.046875 , 0.224375 ], + [11.73125 , 0.43875 ], + [18.81875 , 0.07125 ], + [10.55 , 0.5 ], + [ 9.36875 , 0.56125 ], + [16.45625 , 0.68375 ], + [ 2.871875 , 0.469375 ], + [ 7.596875 , 0.714375 ], + [14.09375 , 0.80625 ], + [ 3.4625 , 0.6225 ], + [17.6375 , 0.8675 ], + [ 5.825 , 0.745 ], + [12.321875 , 0.959375 ], + [ 2.28125 , 0.92875 ]]), 'exploration_results': array([2.42229590e-01, 3.27384376e-01, 1.14034055e+00, 1.50312179e+00, + 1.79325436e+00, 2.08879824e+00, 2.54067782e+00, 2.64114350e+00, + 2.73814230e+00, 3.83228381e+00, 6.46248546e+00, 9.30118040e+00, + 1.59966394e+01, 3.03715662e+01, 3.38771067e+01, 4.26926083e+01, + 5.84656546e+01, 5.90505617e+01, 5.22500282e+02, 9.01924413e+02])}}" diff --git a/environment.yml b/environment.yml index 0fa131a..93d7053 100644 --- a/environment.yml +++ b/environment.yml @@ -4,7 +4,6 @@ channels: dependencies: - python=3.12 - estimagic=0.4.7 - - econ-ark=0.15.1 - jupyter - statsmodels - jupyterlab @@ -15,6 +14,7 @@ dependencies: - openpyxl - pip - pip: + - git+https://github.com/econ-ark/HARK@master - DFO-LS - tranquilo - black[jupyter]