"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "import matplotlib.pyplot as plt\n",
+ "fig, ax = plt.subplots(figsize=(6,4), dpi=120)\n",
+ "\n",
+ "ax.plot(df.y1, ls='None', marker='o', mfc='None', mec='k', label='Observed')\n",
+ "\n",
+ "best_to_trial = np.minimum.accumulate(df.y1.values)\n",
+ "ax.plot(best_to_trial, color='#0033FF', lw=2, label='Best to Trial')\n",
+ "\n",
+ "plt.xticks(range(len(df)))\n",
+ "plt.xlabel('Trial Number')\n",
+ "plt.ylabel('y1 value (Lower is Better)')\n",
+ "plt.title('Advanced Optimization, Ax')\n",
+ "plt.legend()\n",
+ "plt.show()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": []
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 10,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stderr",
+ "output_type": "stream",
+ "text": [
+ "C:\\Users\\MF\\AppData\\Local\\Temp\\ipykernel_22304\\2118524986.py:36: AxParameterWarning:\n",
+ "\n",
+ "`is_ordered` is not specified for `ChoiceParameter` \"c1\". Defaulting to `True` since there are exactly two choices.. To override this behavior (or avoid this warning), specify `is_ordered` during `ChoiceParameter` construction. Note that choice parameters with exactly 2 choices are always considered ordered and that the user-supplied `is_ordered` has no effect in this particular case.\n",
+ "\n",
+ "C:\\Users\\MF\\AppData\\Local\\Temp\\ipykernel_22304\\2118524986.py:36: AxParameterWarning:\n",
+ "\n",
+ "`sort_values` is not specified for `ChoiceParameter` \"c1\". Defaulting to `False` for parameters of `ParameterType` STRING. To override this behavior (or avoid this warning), specify `sort_values` during `ChoiceParameter` construction.\n",
+ "\n",
+ "C:\\Users\\MF\\AppData\\Local\\Temp\\ipykernel_22304\\2118524986.py:37: AxParameterWarning:\n",
+ "\n",
+ "`is_ordered` is not specified for `ChoiceParameter` \"c2\". Defaulting to `True` since there are exactly two choices.. To override this behavior (or avoid this warning), specify `is_ordered` during `ChoiceParameter` construction. Note that choice parameters with exactly 2 choices are always considered ordered and that the user-supplied `is_ordered` has no effect in this particular case.\n",
+ "\n",
+ "C:\\Users\\MF\\AppData\\Local\\Temp\\ipykernel_22304\\2118524986.py:37: AxParameterWarning:\n",
+ "\n",
+ "`sort_values` is not specified for `ChoiceParameter` \"c2\". Defaulting to `False` for parameters of `ParameterType` STRING. To override this behavior (or avoid this warning), specify `sort_values` during `ChoiceParameter` construction.\n",
+ "\n",
+ "C:\\Users\\MF\\AppData\\Local\\Temp\\ipykernel_22304\\2118524986.py:38: AxParameterWarning:\n",
+ "\n",
+ "`is_ordered` is not specified for `ChoiceParameter` \"c3\". Defaulting to `False` since the parameter is a string with more than 2 choices.. To override this behavior (or avoid this warning), specify `is_ordered` during `ChoiceParameter` construction. Note that choice parameters with exactly 2 choices are always considered ordered and that the user-supplied `is_ordered` has no effect in this particular case.\n",
+ "\n",
+ "C:\\Users\\MF\\AppData\\Local\\Temp\\ipykernel_22304\\2118524986.py:38: AxParameterWarning:\n",
+ "\n",
+ "`sort_values` is not specified for `ChoiceParameter` \"c3\". Defaulting to `False` for parameters of `ParameterType` STRING. To override this behavior (or avoid this warning), specify `sort_values` during `ChoiceParameter` construction.\n",
+ "\n",
+ "C:\\Users\\MF\\AppData\\Local\\Temp\\ipykernel_22304\\2118524986.py:39: AxParameterWarning:\n",
+ "\n",
+ "`is_ordered` is not specified for `ChoiceParameter` \"Task\". Defaulting to `True` since there are exactly two choices.. To override this behavior (or avoid this warning), specify `is_ordered` during `ChoiceParameter` construction. Note that choice parameters with exactly 2 choices are always considered ordered and that the user-supplied `is_ordered` has no effect in this particular case.\n",
+ "\n",
+ "C:\\Users\\MF\\AppData\\Local\\Temp\\ipykernel_22304\\2118524986.py:39: AxParameterWarning:\n",
+ "\n",
+ "`sort_values` is not specified for `ChoiceParameter` \"Task\". Defaulting to `False` for parameters of `ParameterType` STRING. To override this behavior (or avoid this warning), specify `sort_values` during `ChoiceParameter` construction.\n",
+ "\n",
+ "[WARNING 09-08 22:00:07] ax.service.ax_client: Random seed set to 42. Note that this setting only affects the Sobol quasi-random generator and BoTorch-powered Bayesian optimization models. For the latter models, setting random seed to the same number for two optimizations will make the generated trials similar, but not exactly the same, and over time the trials will diverge more.\n",
+ "[INFO 09-08 22:00:07] ax.service.utils.instantiation: Inferred value type of ParameterType.FLOAT for parameter x1. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
+ "[INFO 09-08 22:00:07] ax.service.utils.instantiation: Inferred value type of ParameterType.FLOAT for parameter x2. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
+ "[INFO 09-08 22:00:07] ax.service.utils.instantiation: Inferred value type of ParameterType.FLOAT for parameter x3. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
+ "[INFO 09-08 22:00:07] ax.service.utils.instantiation: Inferred value type of ParameterType.FLOAT for parameter x4. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
+ "[INFO 09-08 22:00:07] ax.service.utils.instantiation: Inferred value type of ParameterType.FLOAT for parameter x5. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
+ "[INFO 09-08 22:00:07] ax.service.utils.instantiation: Inferred value type of ParameterType.FLOAT for parameter x6. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
+ "[INFO 09-08 22:00:07] ax.service.utils.instantiation: Inferred value type of ParameterType.FLOAT for parameter x7. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
+ "[INFO 09-08 22:00:07] ax.service.utils.instantiation: Inferred value type of ParameterType.FLOAT for parameter x8. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
+ "[INFO 09-08 22:00:07] ax.service.utils.instantiation: Inferred value type of ParameterType.FLOAT for parameter x9. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
+ "[INFO 09-08 22:00:07] ax.service.utils.instantiation: Inferred value type of ParameterType.FLOAT for parameter x10. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
+ "[INFO 09-08 22:00:07] ax.service.utils.instantiation: Inferred value type of ParameterType.FLOAT for parameter x11. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
+ "[INFO 09-08 22:00:07] ax.service.utils.instantiation: Inferred value type of ParameterType.FLOAT for parameter x12. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
+ "[INFO 09-08 22:00:07] ax.service.utils.instantiation: Inferred value type of ParameterType.FLOAT for parameter x13. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
+ "[INFO 09-08 22:00:07] ax.service.utils.instantiation: Inferred value type of ParameterType.FLOAT for parameter x14. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
+ "[INFO 09-08 22:00:07] ax.service.utils.instantiation: Inferred value type of ParameterType.FLOAT for parameter x15. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
+ "[INFO 09-08 22:00:07] ax.service.utils.instantiation: Inferred value type of ParameterType.FLOAT for parameter x16. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
+ "[INFO 09-08 22:00:07] ax.service.utils.instantiation: Inferred value type of ParameterType.FLOAT for parameter x17. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
+ "[INFO 09-08 22:00:07] ax.service.utils.instantiation: Inferred value type of ParameterType.FLOAT for parameter x18. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
+ "[INFO 09-08 22:00:07] ax.service.utils.instantiation: Inferred value type of ParameterType.FLOAT for parameter x19. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
+ "[INFO 09-08 22:00:07] ax.service.utils.instantiation: Inferred value type of ParameterType.FLOAT for parameter x20. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
+ "[INFO 09-08 22:00:07] ax.service.utils.instantiation: Inferred value type of ParameterType.STRING for parameter Task. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\service\\utils\\instantiation.py:244: AxParameterWarning:\n",
+ "\n",
+ "`is_ordered` is not specified for `ChoiceParameter` \"Task\". Defaulting to `True` since there are exactly two choices.. To override this behavior (or avoid this warning), specify `is_ordered` during `ChoiceParameter` construction. Note that choice parameters with exactly 2 choices are always considered ordered and that the user-supplied `is_ordered` has no effect in this particular case.\n",
+ "\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\service\\utils\\instantiation.py:244: AxParameterWarning:\n",
+ "\n",
+ "`sort_values` is not specified for `ChoiceParameter` \"Task\". Defaulting to `False` for parameters of `ParameterType` STRING. To override this behavior (or avoid this warning), specify `sort_values` during `ChoiceParameter` construction.\n",
+ "\n",
+ "[INFO 09-08 22:00:07] ax.service.utils.instantiation: Created search space: SearchSpace(parameters=[RangeParameter(name='x1', parameter_type=FLOAT, range=[0.0, 1.0]), RangeParameter(name='x2', parameter_type=FLOAT, range=[0.0, 1.0]), RangeParameter(name='x3', parameter_type=FLOAT, range=[0.0, 1.0]), RangeParameter(name='x4', parameter_type=FLOAT, range=[0.0, 1.0]), RangeParameter(name='x5', parameter_type=FLOAT, range=[0.0, 1.0]), RangeParameter(name='x6', parameter_type=FLOAT, range=[0.0, 1.0]), RangeParameter(name='x7', parameter_type=FLOAT, range=[0.0, 1.0]), RangeParameter(name='x8', parameter_type=FLOAT, range=[0.0, 1.0]), RangeParameter(name='x9', parameter_type=FLOAT, range=[0.0, 1.0]), RangeParameter(name='x10', parameter_type=FLOAT, range=[0.0, 1.0]), RangeParameter(name='x11', parameter_type=FLOAT, range=[0.0, 1.0]), RangeParameter(name='x12', parameter_type=FLOAT, range=[0.0, 1.0]), RangeParameter(name='x13', parameter_type=FLOAT, range=[0.0, 1.0]), RangeParameter(name='x14', parameter_type=FLOAT, range=[0.0, 1.0]), RangeParameter(name='x15', parameter_type=FLOAT, range=[0.0, 1.0]), RangeParameter(name='x16', parameter_type=FLOAT, range=[0.0, 1.0]), RangeParameter(name='x17', parameter_type=FLOAT, range=[0.0, 1.0]), RangeParameter(name='x18', parameter_type=FLOAT, range=[0.0, 1.0]), RangeParameter(name='x19', parameter_type=FLOAT, range=[0.0, 1.0]), RangeParameter(name='x20', parameter_type=FLOAT, range=[0.0, 1.0]), ChoiceParameter(name='Task', parameter_type=STRING, values=['y1', 'y2'], is_ordered=True, is_task=True, sort_values=False, target_value='y2')], parameter_constraints=[OrderConstraint(x19 <= x20), ParameterConstraint(1.0*x15 + 1.0*x6 <= 1.0)]).\n"
+ ]
+ }
+ ],
+ "source": [
+ "import numpy as np\n",
+ "from ax.core.observation import ObservationFeatures\n",
+ "from ax.modelbridge.generation_strategy import GenerationStep, GenerationStrategy\n",
+ "from ax.modelbridge.registry import Models\n",
+ "from ax.modelbridge.transforms.task_encode import TaskEncode\n",
+ "from ax.modelbridge.transforms.unit_x import UnitX\n",
+ "from ax.service.ax_client import AxClient, ObjectiveProperties\n",
+ "\n",
+ "from ax import SearchSpace, ParameterType, RangeParameter, ChoiceParameter\n",
+ "from ax.modelbridge.transforms.unit_x import UnitX\n",
+ "from ax.modelbridge.transforms.task_encode import TaskEncode\n",
+ "\n",
+ "# Define the search space\n",
+ "search_space = SearchSpace(\n",
+ " parameters=[\n",
+ " RangeParameter(name=\"x1\", parameter_type=ParameterType.FLOAT, lower=0.0, upper=1.0),\n",
+ " RangeParameter(name=\"x2\", parameter_type=ParameterType.FLOAT, lower=0.0, upper=1.0),\n",
+ " RangeParameter(name=\"x3\", parameter_type=ParameterType.FLOAT, lower=0.0, upper=1.0),\n",
+ " RangeParameter(name=\"x4\", parameter_type=ParameterType.FLOAT, lower=0.0, upper=1.0),\n",
+ " RangeParameter(name=\"x5\", parameter_type=ParameterType.FLOAT, lower=0.0, upper=1.0),\n",
+ " RangeParameter(name=\"x6\", parameter_type=ParameterType.FLOAT, lower=0.0, upper=1.0),\n",
+ " RangeParameter(name=\"x7\", parameter_type=ParameterType.FLOAT, lower=0.0, upper=1.0),\n",
+ " RangeParameter(name=\"x8\", parameter_type=ParameterType.FLOAT, lower=0.0, upper=1.0),\n",
+ " RangeParameter(name=\"x9\", parameter_type=ParameterType.FLOAT, lower=0.0, upper=1.0),\n",
+ " RangeParameter(name=\"x10\", parameter_type=ParameterType.FLOAT, lower=0.0, upper=1.0),\n",
+ " RangeParameter(name=\"x11\", parameter_type=ParameterType.FLOAT, lower=0.0, upper=1.0),\n",
+ " RangeParameter(name=\"x12\", parameter_type=ParameterType.FLOAT, lower=0.0, upper=1.0),\n",
+ " RangeParameter(name=\"x13\", parameter_type=ParameterType.FLOAT, lower=0.0, upper=1.0),\n",
+ " RangeParameter(name=\"x14\", parameter_type=ParameterType.FLOAT, lower=0.0, upper=1.0),\n",
+ " RangeParameter(name=\"x15\", parameter_type=ParameterType.FLOAT, lower=0.0, upper=1.0),\n",
+ " RangeParameter(name=\"x16\", parameter_type=ParameterType.FLOAT, lower=0.0, upper=1.0),\n",
+ " RangeParameter(name=\"x17\", parameter_type=ParameterType.FLOAT, lower=0.0, upper=1.0),\n",
+ " RangeParameter(name=\"x18\", parameter_type=ParameterType.FLOAT, lower=0.0, upper=1.0),\n",
+ " RangeParameter(name=\"x19\", parameter_type=ParameterType.FLOAT, lower=0.0, upper=1.0),\n",
+ " RangeParameter(name=\"x20\", parameter_type=ParameterType.FLOAT, lower=0.0, upper=1.0),\n",
+ " ChoiceParameter(name=\"c1\", parameter_type=ParameterType.STRING, values=[\"c1_0\", \"c1_1\"]),\n",
+ " ChoiceParameter(name=\"c2\", parameter_type=ParameterType.STRING, values=[\"c2_0\", \"c2_1\"]),\n",
+ " ChoiceParameter(name=\"c3\", parameter_type=ParameterType.STRING, values=[\"c3_0\", \"c3_1\", \"c3_2\"]),\n",
+ " ChoiceParameter(\n",
+ " name=\"Task\", \n",
+ " parameter_type=ParameterType.STRING, \n",
+ " values=[\"y1\", \"y2\"], \n",
+ " is_task=True, \n",
+ " target_value=\"y2\" # Specify the target value\n",
+ " ),\n",
+ " ]\n",
+ ")\n",
+ "\n",
+ "# Create the transforms\n",
+ "transforms = [TaskEncode, UnitX]\n",
+ "\n",
+ "# Generation strategy with the transforms\n",
+ "gs = GenerationStrategy(\n",
+ " name=\"MultiTaskOp\", \n",
+ " steps=[\n",
+ " GenerationStep(\n",
+ " model=Models.SOBOL, \n",
+ " num_trials=5,\n",
+ " model_kwargs={\"deduplicate\": True, \"transforms\": transforms},\n",
+ " ),\n",
+ " GenerationStep(\n",
+ " model=Models.BOTORCH_MODULAR,\n",
+ " num_trials=-1, \n",
+ " model_kwargs={\"transforms\": transforms},\n",
+ " ),\n",
+ " ],\n",
+ ")\n",
+ "\n",
+ "# Create the Ax client with the generation strategy\n",
+ "ax_client = AxClient(generation_strategy=gs, random_seed=42, verbose_logging=False)\n",
+ "\n",
+ "# Create the experiment\n",
+ "ax_client.create_experiment(\n",
+ " name=\"MultiTaskOp\", \n",
+ " parameters=[\n",
+ " {\"name\": \"x1\", \"type\": \"range\", \"bounds\": [0.0, 1.0]},\n",
+ " {\"name\": \"x2\", \"type\": \"range\", \"bounds\": [0.0, 1.0]},\n",
+ " {\"name\": \"x3\", \"type\": \"range\", \"bounds\": [0.0, 1.0]},\n",
+ " {\"name\": \"x4\", \"type\": \"range\", \"bounds\": [0.0, 1.0]},\n",
+ " {\"name\": \"x5\", \"type\": \"range\", \"bounds\": [0.0, 1.0]},\n",
+ " {\"name\": \"x6\", \"type\": \"range\", \"bounds\": [0.0, 1.0]},\n",
+ " {\"name\": \"x7\", \"type\": \"range\", \"bounds\": [0.0, 1.0]},\n",
+ " {\"name\": \"x8\", \"type\": \"range\", \"bounds\": [0.0, 1.0]},\n",
+ " {\"name\": \"x9\", \"type\": \"range\", \"bounds\": [0.0, 1.0]},\n",
+ " {\"name\": \"x10\", \"type\": \"range\", \"bounds\": [0.0, 1.0]},\n",
+ " {\"name\": \"x11\", \"type\": \"range\", \"bounds\": [0.0, 1.0]},\n",
+ " {\"name\": \"x12\", \"type\": \"range\", \"bounds\": [0.0, 1.0]},\n",
+ " {\"name\": \"x13\", \"type\": \"range\", \"bounds\": [0.0, 1.0]},\n",
+ " {\"name\": \"x14\", \"type\": \"range\", \"bounds\": [0.0, 1.0]},\n",
+ " {\"name\": \"x15\", \"type\": \"range\", \"bounds\": [0.0, 1.0]},\n",
+ " {\"name\": \"x16\", \"type\": \"range\", \"bounds\": [0.0, 1.0]},\n",
+ " {\"name\": \"x17\", \"type\": \"range\", \"bounds\": [0.0, 1.0]},\n",
+ " {\"name\": \"x18\", \"type\": \"range\", \"bounds\": [0.0, 1.0]},\n",
+ " {\"name\": \"x19\", \"type\": \"range\", \"bounds\": [0.0, 1.0]},\n",
+ " {\"name\": \"x20\", \"type\": \"range\", \"bounds\": [0.0, 1.0]},\n",
+ " # Add all other parameters similarly...\n",
+ " {\"name\": \"Task\", \"type\": \"choice\", \"values\": [\"y1\", \"y2\"], \"is_task\": True, \"target_value\": \"y2\"},\n",
+ " ],\n",
+ " parameter_constraints=[\n",
+ " \"x19 <= x20\",\n",
+ " \"x6 + x15 <= 1.0\",\n",
+ " ],\n",
+ " objectives={\n",
+ " \"Objective\": ObjectiveProperties(minimize=False),\n",
+ " },\n",
+ ")\n",
+ " "
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": []
+ }
+ ],
+ "metadata": {
+ "kernelspec": {
+ "display_name": "BayBE",
+ "language": "python",
+ "name": "python3"
+ },
+ "language_info": {
+ "codemirror_mode": {
+ "name": "ipython",
+ "version": 3
+ },
+ "file_extension": ".py",
+ "mimetype": "text/x-python",
+ "name": "python",
+ "nbconvert_exporter": "python",
+ "pygments_lexer": "ipython3",
+ "version": "3.10.14"
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
diff --git a/notebooks/HF-API-BayBE.ipynb b/notebooks/HF-API-BayBE.ipynb
new file mode 100644
index 0000000..3f7beda
--- /dev/null
+++ b/notebooks/HF-API-BayBE.ipynb
@@ -0,0 +1,4898 @@
+{
+ "cells": [
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "Use the Advanced Optimization benchmark from AC hugging face (https://huggingface.co/spaces/AccelerationConsortium/crabnet-hyperparameter)\n",
+ "- Optimize (minimize) y1\n",
+ " - If y1 is greater than 0.2, the result is considered \"bad\" no matter how good the other values are\n",
+ "- Transfer learning: \n",
+ " - higher fidelity means more expensive computation \n",
+ " - treat fidelity1 = 0.5 as \"source' and fidelity1 = 1.0 as \"target\"\n",
+ "- Multi-task: \n",
+ " - since y1 and y2 are correlated \n",
+ " - treat y1 as task1, then y2 as task 2"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 1,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Loaded as API: https://accelerationconsortium-crabnet-hyperparameter.hf.space ✔\n"
+ ]
+ }
+ ],
+ "source": [
+ "from baybe import Campaign\n",
+ "from baybe.objectives import SingleTargetObjective\n",
+ "from baybe.parameters import NumericalContinuousParameter, CategoricalParameter\n",
+ "from baybe.searchspace import SearchSpace\n",
+ "from baybe.targets import NumericalTarget\n",
+ "from baybe.constraints import ContinuousLinearInequalityConstraint\n",
+ "import numpy as np\n",
+ "import pandas as pd\n",
+ "import torch\n",
+ "# load the Advanced Optimization from AC huggingface\n",
+ "from gradio_client import Client\n",
+ "client = Client(\"AccelerationConsortium/crabnet-hyperparameter\")\n",
+ "\n",
+ "from baybe.utils.random import set_random_seed\n",
+ "#set_random_seed(17) \n",
+ "\n",
+ "# seed = 104 for x19 < x20 constraint error\n",
+ "# seed = 188 for x6+x15 <= 1.0 constraint error"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 2,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# define the function \n",
+ "def adv_opt(c1, c2, c3, x2, x3, x4, x5, x6, x7, x8, x9, x11, x12, x13, x14, x15, x16, x17, x18): \n",
+ " result = client.predict(\n",
+ " \t0.669938, # float (numeric value between 0.0 and 1.0) in 'x1' Slider component\n",
+ "\t\tx2,\t# float (numeric value between 0.0 and 1.0)\tin 'x2' Slider component\n",
+ "\t\tx3,\t# float (numeric value between 0.0 and 1.0) in 'x3' Slider component\n",
+ "\t\tx4,\t# float (numeric value between 0.0 and 1.0) in 'x4' Slider component\n",
+ "\t\tx5,\t# float (numeric value between 0.0 and 1.0) in 'x5' Slider component\n",
+ "\t\tx6,\t# float (numeric value between 0.0 and 1.0) in 'x6' Slider component\n",
+ "\t\tx7,\t# float (numeric value between 0.0 and 1.0) in 'x7' Slider component\n",
+ "\t\tx8,\t# float (numeric value between 0.0 and 1.0) in 'x8' Slider component\n",
+ "\t\tx9,\t# float (numeric value between 0.0 and 1.0) in 'x9' Slider component\n",
+ "\t\t0.5291,\t# float (numeric value between 0.0 and 1.0) in 'x10' Slider component\n",
+ "\t\tx11,\t# float (numeric value between 0.0 and 1.0) in 'x11' Slider component\n",
+ "\t\tx12,\t# float (numeric value between 0.0 and 1.0000000000000002) in 'x12' Slider component\n",
+ "\t\tx13,\t# float (numeric value between 0.0 and 1.0) in 'x13' Slider component\n",
+ "\t\tx14,\t# float (numeric value between 0.0 and 1.0) in 'x14' Slider component\n",
+ "\t\tx15,\t# float (numeric value between 0.0 and 1.0) in 'x15' Slider component\n",
+ "\t\tx16,\t# float (numeric value between 0.0 and 1.0) in 'x16' Slider component\n",
+ "\t\tx17,\t# float (numeric value between 0.0 and 1.0) in 'x17' Slider component\n",
+ "\t\tx18,\t# float (numeric value between 0.0 and 1.0) in 'x18' Slider component\n",
+ "\t\t0.079598,\t# float (numeric value between 0.0 and 0.9999999999999998) in 'x19' Slider component\n",
+ "\t\t0.632394,\t# float (numeric value between 0.0 and 0.9999999999999998) in 'x20' Slider component\n",
+ "\t\tc1,\t# Literal['c1_0', 'c1_1'] in 'c1' Radio component\n",
+ "\t\tc2,\t# Literal['c2_0', 'c2_1'] in 'c2' Radio component\n",
+ "\t\tc3,\t# Literal['c3_0', 'c3_1', 'c3_2'] in 'c3' Radio component\n",
+ "\t\t0.5,\t# float (numeric value between 0.0 and 1.0) in 'fidelity1' Slider component\n",
+ "\t\tapi_name=\"/predict\",\n",
+ " )\n",
+ " return result['data'][0][0]\t\t\t# return y1 value only\n",
+ "\n",
+ "\n",
+ "# def adv_opt(**params):\n",
+ "# result = client.predict(\n",
+ "# params['x1'], # float (numeric value between 0.0 and 1.0) in 'x1' Slider component\n",
+ "# params['x2'], # float (numeric value between 0.0 and 1.0) in 'x2' Slider component\n",
+ "# params['x3'], # float (numeric value between 0.0 and 1.0) in 'x3' Slider component\n",
+ "# params['x4'], # float (numeric value between 0.0 and 1.0) in 'x4' Slider component\n",
+ "# params['x5'], # float (numeric value between 0.0 and 1.0) in 'x5' Slider component\n",
+ "# params['x6'], # float (numeric value between 0.0 and 1.0) in 'x6' Slider component\n",
+ "# params['x7'], # float (numeric value between 0.0 and 1.0) in 'x7' Slider component\n",
+ "# params['x8'], # float (numeric value between 0.0 and 1.0) in 'x8' Slider component\n",
+ "# params['x9'], # float (numeric value between 0.0 and 1.0) in 'x9' Slider component\n",
+ "# params['x10'], # float (numeric value between 0.0 and 1.0) in 'x10' Slider component\n",
+ "# params['x11'], # float (numeric value between 0.0 and 1.0) in 'x11' Slider component\n",
+ "# params['x12'], # float (numeric value between 0.0 and 1.0) in 'x12' Slider component\n",
+ "# params['x13'], # float (numeric value between 0.0 and 1.0) in 'x13' Slider component\n",
+ "# params['x14'], # float (numeric value between 0.0 and 1.0) in 'x14' Slider component\n",
+ "# params['x15'], # float (numeric value between 0.0 and 1.0) in 'x15' Slider component\n",
+ "# params['x16'], # float (numeric value between 0.0 and 1.0) in 'x16' Slider component\n",
+ "# params['x17'], # float (numeric value between 0.0 and 1.0) in 'x17' Slider component\n",
+ "# params['x18'], # float (numeric value between 0.0 and 1.0) in 'x18' Slider component\n",
+ "# params['x19'], # float (numeric value between 0.0 and 1.0) in 'x19' Slider component\n",
+ "# params['x20'], # float (numeric value between 0.0 and 1.0) in 'x20' Slider component\n",
+ "# params['c1'], # Literal['c1_0', 'c1_1'] in 'c1' Radio component\n",
+ "# params['c2'], # Literal['c2_0', 'c2_1'] in 'c2' Radio component\n",
+ "# params['c3'], # Literal['c3_0', 'c3_1', 'c3_2'] in 'c3' Radio component\n",
+ "# 0.5, # float (numeric value between 0.0 and 1.0) in 'fidelity1' Slider component\n",
+ "# api_name=\"/predict\",\n",
+ "# )\n",
+ "# return result['data'][0][0] # return y1 value only\n",
+ "\n",
+ "WRAPPED_FUNCTION = adv_opt"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 3,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# define and create the search space\n",
+ "parameters = [\n",
+ " # NumericalContinuousParameter(name=\"x1\", bounds=(0.0, 1.0)), \n",
+ " # NumericalContinuousParameter(name=\"x2\", bounds=(0.0, 1.0)),\n",
+ " # NumericalContinuousParameter(name=\"x3\", bounds=(0.0, 1.0)),\n",
+ " # NumericalContinuousParameter(name=\"x4\", bounds=(0.0, 1.0)),\n",
+ " # NumericalContinuousParameter(name=\"x5\", bounds=(0.0, 1.0)),\n",
+ " # NumericalContinuousParameter(name=\"x6\", bounds=(0.0, 1.0)),\n",
+ " # NumericalContinuousParameter(name=\"x7\", bounds=(0.0, 1.0)),\n",
+ " # NumericalContinuousParameter(name=\"x8\", bounds=(0.0, 1.0)),\n",
+ " # NumericalContinuousParameter(name=\"x9\", bounds=(0.0, 1.0)),\n",
+ " # NumericalContinuousParameter(name=\"x10\", bounds=(0.0, 1.0)),\n",
+ " # NumericalContinuousParameter(name=\"x11\", bounds=(0.0, 1.0)),\n",
+ " # NumericalContinuousParameter(name=\"x12\", bounds=(0.0, 1.0)),\n",
+ " # NumericalContinuousParameter(name=\"x13\", bounds=(0.0, 1.0)),\n",
+ " # NumericalContinuousParameter(name=\"x14\", bounds=(0.0, 1.0)),\n",
+ " # NumericalContinuousParameter(name=\"x15\", bounds=(0.0, 1.0)),\n",
+ " # NumericalContinuousParameter(name=\"x16\", bounds=(0.0, 1.0)),\n",
+ " # NumericalContinuousParameter(name=\"x17\", bounds=(0.0, 1.0)),\n",
+ " # NumericalContinuousParameter(name=\"x18\", bounds=(0.0, 1.0)),\n",
+ " # NumericalContinuousParameter(name=\"x19\", bounds=(0.0, 1.0)),\n",
+ " # NumericalContinuousParameter(name=\"x20\", bounds=(0.0, 1.0)),\n",
+ " \n",
+ " # NumericalContinuousParameter(name=\"x1\", bounds=(0.0, 1.0)), \n",
+ " NumericalContinuousParameter(name=\"x2\", bounds=(0.0, 1.0)),\n",
+ " NumericalContinuousParameter(name=\"x3\", bounds=(0.0, 1.0)),\n",
+ " NumericalContinuousParameter(name=\"x4\", bounds=(0.0, 1.0)),\n",
+ " NumericalContinuousParameter(name=\"x5\", bounds=(0.0, 1.0)),\n",
+ " NumericalContinuousParameter(name=\"x6\", bounds=(0.0, 1.0)),\n",
+ " NumericalContinuousParameter(name=\"x7\", bounds=(0.0, 1.0)),\n",
+ " NumericalContinuousParameter(name=\"x8\", bounds=(0.0, 1.0)),\n",
+ " NumericalContinuousParameter(name=\"x9\", bounds=(0.0, 1.0)),\n",
+ " #NumericalContinuousParameter(name=\"x10\", bounds=(0.0, 1.0)),\n",
+ " NumericalContinuousParameter(name=\"x11\", bounds=(0.0, 1.0)),\n",
+ " NumericalContinuousParameter(name=\"x12\", bounds=(0.0, 1.0)),\n",
+ " NumericalContinuousParameter(name=\"x13\", bounds=(0.0, 1.0)),\n",
+ " NumericalContinuousParameter(name=\"x14\", bounds=(0.0, 1.0)),\n",
+ " NumericalContinuousParameter(name=\"x15\", bounds=(0.0, 1.0)),\n",
+ " NumericalContinuousParameter(name=\"x16\", bounds=(0.0, 1.0)),\n",
+ " NumericalContinuousParameter(name=\"x17\", bounds=(0.0, 1.0)),\n",
+ " NumericalContinuousParameter(name=\"x18\", bounds=(0.0, 1.0)),\n",
+ " # NumericalContinuousParameter(name=\"x19\", bounds=(0.0, 1.0)),\n",
+ " # NumericalContinuousParameter(name=\"x20\", bounds=(0.0, 1.0)),\n",
+ " CategoricalParameter(name='c1', values=['c1_0', 'c1_1'], encoding=\"OHE\"),\n",
+ " CategoricalParameter(name='c2', values=['c2_0', 'c2_1'], encoding=\"OHE\"),\n",
+ " CategoricalParameter(name='c3', values=['c3_0', 'c3_1', 'c3_2'], encoding=\"OHE\"),\n",
+ "]\n",
+ "\n",
+ "constraints = [\n",
+ " # ContinuousLinearInequalityConstraint(parameters=[\"x19\", \"x20\"], coefficients=[-1.0, 1.0], rhs=0.0),\n",
+ " ContinuousLinearInequalityConstraint(parameters=[\"x6\", \"x15\"], coefficients=[-1.0, -1.0], rhs=-1.0), \n",
+ "]\n",
+ "\n",
+ "searchspace = SearchSpace.from_product(parameters=parameters, constraints=constraints)\n",
+ "\n",
+ "# define objective\n",
+ "objective = SingleTargetObjective(target=NumericalTarget(name=\"Target\", mode=\"MIN\"))\n",
+ "\n",
+ "# create campaign\n",
+ "campaign = Campaign(searchspace=searchspace, objective=objective)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 4,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stderr",
+ "output_type": "stream",
+ "text": [
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\acquisition\\monte_carlo.py:393: NumericsWarning: qExpectedImprovement has known numerical issues that lead to suboptimal optimization performance. It is strongly recommended to simply replace\n",
+ "\n",
+ "\t qExpectedImprovement \t --> \t qLogExpectedImprovement \n",
+ "\n",
+ "instead, which fixes the issues and has the same API. See https://arxiv.org/abs/2310.20708 for details.\n",
+ " legacy_ei_numerics_warning(legacy_name=type(self).__name__)\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n",
+ "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\botorch\\optim\\initializers.py:433: BadInitialCandidatesWarning: Unable to find non-zero acquisition function values - initial conditions are being selected randomly.\n",
+ " warnings.warn(\n"
+ ]
+ }
+ ],
+ "source": [
+ "from copy import deepcopy\n",
+ "random_seed_list = [17, 28, 42, 87, 99, 131, 518, 1047, 1598, 2024]\n",
+ "round = 50\n",
+ "\n",
+ "results = pd.DataFrame()\n",
+ "for i in range(len(random_seed_list)):\n",
+ " set_random_seed(random_seed_list[i])\n",
+ "\n",
+ " # copy the campaign\n",
+ " campaign_i = deepcopy(campaign)\n",
+ "\n",
+ " for k in range(round): \n",
+ " recommendation = campaign_i.recommend(batch_size=1)\n",
+ " # select the numerical columns\n",
+ " numerical_cols = recommendation.select_dtypes(include='number')\n",
+ " # replace values less than 1e-8 with 0 in numerical columns\n",
+ " numerical_cols = numerical_cols.map(lambda x: 0 if x < 1e-6 else x)\n",
+ " # update the original DataFrame\n",
+ " recommendation.update(numerical_cols)\n",
+ "\n",
+ " # target value are looked up via the botorch wrapper\n",
+ " target_values = []\n",
+ " for index, row in recommendation.iterrows():\n",
+ " # print(row.to_dict())\n",
+ " # print(WRAPPED_FUNCTION(**row.to_dict()))\n",
+ " target_values.append(WRAPPED_FUNCTION(**row.to_dict()))\n",
+ "\n",
+ " recommendation[\"Target\"] = target_values\n",
+ "\n",
+ " campaign_i.add_measurements(recommendation) \n",
+ " results = pd.concat([results, campaign_i.measurements])"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 11,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/html": [
+ "