Merge pull request #432 from JiQi535/master

update gap_fit command #430

maml/apps/bowsr/model/cgcnn.py

@@ -16,7 +16,7 @@
     from cgcnn.data import AtomCustomJSONInitializer, GaussianDistance
     from cgcnn.model import CrystalGraphConvNet
     from torch import Tensor
-except ImportError as error:
+except ImportError:
     torch = None  # type: ignore
     cgcnn = None  # type: ignore
     Tensor = None  # type: ignore

maml/apps/bowsr/model/megnet.py

@@ -16,7 +16,7 @@
     from megnet.data.crystal import CrystalGraph
     from megnet.data.graph import GaussianDistance
     from megnet.models import MEGNetModel
-except Exception as error:
+except Exception:
     megnet = None
     MEGNetModel = None
     CrystalGraph = None

maml/apps/bowsr/model/tests/test_cgcnn.py

@@ -9,7 +9,7 @@
 
 try:
     import cgcnn
-except ImportError as e:
+except ImportError:
     cgcnn = None
 
 module_dir = os.path.dirname(__file__)

maml/apps/bowsr/optimizer.py

@@ -13,9 +13,17 @@
 from sklearn.gaussian_process import GaussianProcessRegressor
 from sklearn.gaussian_process.kernels import RationalQuadratic
 
-from maml.apps.bowsr.acquisition import AcquisitionFunction, ensure_rng, propose_query_point
+from maml.apps.bowsr.acquisition import (
+    AcquisitionFunction,
+    ensure_rng,
+    propose_query_point,
+)
 from maml.apps.bowsr.model import EnergyModel
-from maml.apps.bowsr.perturbation import LatticePerturbation, WyckoffPerturbation, get_standardized_structure
+from maml.apps.bowsr.perturbation import (
+    LatticePerturbation,
+    WyckoffPerturbation,
+    get_standardized_structure,
+)
 from maml.apps.bowsr.preprocessing import DummyScaler, StandardScaler
 from maml.apps.bowsr.target_space import TargetSpace
 

maml/apps/bowsr/tests/test_acquisition.py

@@ -6,7 +6,12 @@
 from sklearn.gaussian_process import GaussianProcessRegressor
 from sklearn.gaussian_process.kernels import Matern, RationalQuadratic
 
-from maml.apps.bowsr.acquisition import AcquisitionFunction, ensure_rng, predict_mean_std, propose_query_point
+from maml.apps.bowsr.acquisition import (
+    AcquisitionFunction,
+    ensure_rng,
+    predict_mean_std,
+    propose_query_point,
+)
 from maml.apps.bowsr.preprocessing import DummyScaler, StandardScaler
 
 

maml/apps/bowsr/tests/test_target_space.py

@@ -5,7 +5,6 @@
 from pymatgen.core.structure import Structure
 
 from maml.apps.bowsr.acquisition import ensure_rng
-from maml.apps.bowsr.optimizer import struct2perturbation
 from maml.apps.bowsr.perturbation import WyckoffPerturbation
 from maml.apps.bowsr.preprocessing import DummyScaler, StandardScaler
 from maml.apps.bowsr.target_space import TargetSpace
@@ -226,28 +225,28 @@ def test_set_empty(self):
 
         for i in range(10):
             sample = self.space1.uniform_sample()
-            target1 = self.space1.probe(sample)
+            self.space1.probe(sample)
             self.assertEqual(len(self.space1), i + 1)
         self.space1.set_empty()
         self.assertEqual(len(self.space1), 0)
 
         for i in range(20):
             sample = self.space2.uniform_sample()
-            target1 = self.space2.probe(sample)
+            self.space2.probe(sample)
             self.assertEqual(len(self.space2), i + 1)
         self.space2.set_empty()
         self.assertEqual(len(self.space2), 0)
 
         for i in range(15):
             sample = self.space3.uniform_sample()
-            target1 = self.space3.probe(sample)
+            self.space3.probe(sample)
             self.assertEqual(len(self.space3), i + 1)
         self.space3.set_empty()
         self.assertEqual(len(self.space3), 0)
 
         for i in range(10):
             sample = self.space4.uniform_sample()
-            target1 = self.space4.probe(sample)
+            self.space4.probe(sample)
             self.assertEqual(len(self.space4), i + 1)
         self.space4.set_empty()
         self.assertEqual(len(self.space4), 0)

maml/apps/pes/_base.py

@@ -61,7 +61,6 @@ def predict_efs(self, structure):
         Returns:
             energy, forces, stress
         """
-        pass
 
     @abc.abstractmethod
     def write_param(self):
@@ -84,5 +83,3 @@ class Potential(PotentialMixin, BaseModel):  # type: ignore
     Potential models that can be used to fit structure-[energy, force, stress]
     pairs
     """
-
-    pass

maml/apps/pes/_gap.py

@@ -312,7 +312,7 @@ def train(
             param = kwargs.get(param_name) if kwargs.get(param_name) else soap_params.get(param_name)
             gap_command.append(param_name + "=" + f"{param}")
         gap_command.append("add_species=T")
-        exe_command.append("gap.2020.01=" + "{" + "{}".format(" ".join(gap_command)) + "}")
+        exe_command.append("gap=" + "{" + "{}".format(" ".join(gap_command)) + "}")
 
         for param_name in preprocess_params:
             param = kwargs.get(param_name) if kwargs.get(param_name) else soap_params.get(param_name)

maml/apps/pes/_lammps.py

@@ -17,7 +17,11 @@
 from pymatgen.io.lammps.data import LammpsData
 
 from maml.apps.pes._base import Potential
-from maml.utils import get_lammps_lattice_and_rotation, stress_list_to_matrix, stress_matrix_to_list
+from maml.utils import (
+    get_lammps_lattice_and_rotation,
+    stress_list_to_matrix,
+    stress_matrix_to_list,
+)
 
 logging.basicConfig()
 logger = logging.getLogger(__name__)

maml/apps/pes/_snap.py

@@ -12,7 +12,12 @@
 
 from maml.base import SKLModel
 from maml.describers import BispectrumCoefficients
-from maml.utils import check_structures_forces_stresses, convert_docs, pool_from, stress_format_change
+from maml.utils import (
+    check_structures_forces_stresses,
+    convert_docs,
+    pool_from,
+    stress_format_change,
+)
 
 from ._lammps import LammpsPotential
 

maml/apps/symbolic/tests/test_selectors.py

@@ -10,12 +10,23 @@
 try:
     import cvxpy as cp
 
-    from maml.apps.symbolic._selectors_cvxpy import AdaptiveLassoCP, DantzigSelectorCP, LassoCP, cp
+    from maml.apps.symbolic._selectors_cvxpy import (
+        AdaptiveLassoCP,
+        DantzigSelectorCP,
+        LassoCP,
+        cp,
+    )
 
 except ImportError:
     cp = None  # noqa
 
-from maml.apps.symbolic._selectors import SCAD, AdaptiveLasso, DantzigSelector, L0BrutalForce, Lasso
+from maml.apps.symbolic._selectors import (
+    SCAD,
+    AdaptiveLasso,
+    DantzigSelector,
+    L0BrutalForce,
+    Lasso,
+)
 
 CWD = os.path.abspath(os.path.dirname(__file__))
 

maml/base/__init__.py

@@ -5,10 +5,21 @@
 Define abstract base classes.
 """
 from ._data import BaseDataSource  # noqa
-from ._describer import BaseDescriber, DummyDescriber, SequentialDescriber, describer_type  # noqa
+from ._describer import (  # noqa
+    BaseDescriber,
+    DummyDescriber,
+    SequentialDescriber,
+    describer_type,
+)
 from ._feature_batch import get_feature_batch
 from ._mixin import TargetScalerMixin
-from ._model import BaseModel, KerasModel, SKLModel, is_keras_model, is_sklearn_model  # noqa
+from ._model import (  # noqa
+    BaseModel,
+    KerasModel,
+    SKLModel,
+    is_keras_model,
+    is_sklearn_model,
+)
 
 __all__ = [
     "BaseDataSource",

maml/base/_data.py

@@ -16,4 +16,3 @@ def get(self, *args, **kwargs) -> pd.DataFrame:
         """
         Get data from sources
         """
-        pass

maml/describers/__init__.py

@@ -5,10 +5,20 @@
 
 from ._composition import ElementProperty, ElementStats  # noqa
 from ._site import SmoothOverlapAtomicPosition  # noqa
-from ._site import BispectrumCoefficients, BPSymmetryFunctions, MEGNetSite, SiteElementProperty  # noqa
+from ._site import (  # noqa
+    BispectrumCoefficients,
+    BPSymmetryFunctions,
+    MEGNetSite,
+    SiteElementProperty,
+)
 from ._structure import CoulombMatrix  # noqa
 from ._structure import SortedCoulombMatrix  # noqa
-from ._structure import CoulombEigenSpectrum, DistinctSiteProperty, MEGNetStructure, RandomizedCoulombMatrix
+from ._structure import (
+    CoulombEigenSpectrum,
+    DistinctSiteProperty,
+    MEGNetStructure,
+    RandomizedCoulombMatrix,
+)
 
 __all__ = [
     "BispectrumCoefficients",

maml/describers/_composition.py

@@ -27,7 +27,9 @@
 
 
 try:
-    from matminer.featurizers.composition import ElementProperty as MatminerElementProperty  # noqa
+    from matminer.featurizers.composition import (  # noqa
+        ElementProperty as MatminerElementProperty,
+    )
 
     ElementProperty = wrap_matminer_describer(
         "ElementProperty", MatminerElementProperty, to_composition, describer_type="composition"

maml/models/dl/tests/test_atomsets.py

@@ -1,7 +1,7 @@
 """
 Test models
 """
-from unittest import TestCase, main, skip
+from unittest import TestCase, main
 
 import numpy as np
 

maml/utils/__init__.py

@@ -9,11 +9,26 @@
 from ._lammps import stress_format_change  # noqa
 from ._lammps import stress_list_to_matrix  # noqa
 from ._lammps import write_data_from_structure  # noqa
-from ._lammps import check_structures_forces_stresses, get_lammps_lattice_and_rotation, stress_matrix_to_list  # noqa
+from ._lammps import (  # noqa
+    check_structures_forces_stresses,
+    get_lammps_lattice_and_rotation,
+    stress_matrix_to_list,
+)
 from ._material import to_composition  # noqa
 from ._preprocessing import DummyScaler, Scaler, StandardScaler  # noqa
-from ._signal_processing import cwt, fft_magnitude, get_sp_method, spectrogram, wvd  # noqa
-from ._stats import STATS_KWARGS, Stats, get_full_stats_and_funcs, stats_list_conversion  # noqa
+from ._signal_processing import (  # noqa
+    cwt,
+    fft_magnitude,
+    get_sp_method,
+    spectrogram,
+    wvd,
+)
+from ._stats import (  # noqa
+    STATS_KWARGS,
+    Stats,
+    get_full_stats_and_funcs,
+    stats_list_conversion,
+)
 from ._tempfile import MultiScratchDir  # noqa
 from ._value_profile import ConstantValue, LinearProfile, ValueProfile  # noqa
 

maml/utils/_data_split.py

@@ -24,7 +24,6 @@ def split(self, mat_ids, **kwargs):
         Returns: (train_ids, val_ids, test_ids) or
             (train_ids, test_ids)
         """
-        pass
 
 
 class ShuffleSplitter(DataSplitter):

requirements-ci.txt

@@ -5,4 +5,4 @@ mypy==0.941
 pydocstyle==6.1.1
 pylint==2.12.2
 black==22.1.0
-flake8==4.0.1
+flake8==4.0.1

requirements-dl.txt

@@ -1,2 +1,2 @@
 tensorflow==2.8.0
-torch==1.11.0
+torch==1.11.0

requirements.txt

@@ -7,4 +7,4 @@ scikit-learn==1.0.2
 h5py==3.6.0
 joblib==1.1.0
 tqdm==4.63.0
-pymongo==4.0.1
+pymongo==4.0.1

tasks.py

@@ -9,8 +9,6 @@
 import json
 import os
 import re
-import subprocess
-import webbrowser
 
 import requests
 from invoke import task