matminer.featurizers.tests package

Submodules

matminer.featurizers.tests.test_bandstructure module

class matminer.featurizers.tests.test_bandstructure.BandstructureFeaturesTest(methodName='runTest')

Bases: pymatgen.util.testing.PymatgenTest

setUp()

Hook method for setting up the test fixture before exercising it.

test_BandFeaturizer()
test_BranchPointEnergy()

matminer.featurizers.tests.test_base module

class matminer.featurizers.tests.test_base.FittableFeaturizer

Bases: matminer.featurizers.base.BaseFeaturizer

This test featurizer tests fitting qualities of BaseFeaturizer, including refittability and different results based on different fits.

citations()

Citation(s) and reference(s) for this feature.

Returns:
(list) each element should be a string citation,
ideally in BibTeX format.
feature_labels()

Generate attribute names.

Returns:
([str]) attribute labels.
featurize(x)

Main featurizer function, which has to be implemented in any derived featurizer subclass.

Args:
x: input data to featurize (type depends on featurizer).
Returns:
(list) one or more features.
fit(X, y=None, **fit_kwargs)

Update the parameters of this featurizer based on available data

Args:
X - [list of tuples], training data
Returns:
self
implementors()

List of implementors of the feature.

Returns:
(list) each element should either be a string with author name (e.g.,
“Anubhav Jain”) or a dictionary with required key “name” and other keys like “email” or “institution” (e.g., {“name”: “Anubhav Jain”, “email”: “ajain@lbl.gov”, “institution”: “LBNL”}).
class matminer.featurizers.tests.test_base.MatrixFeaturizer

Bases: matminer.featurizers.base.BaseFeaturizer

citations()

Citation(s) and reference(s) for this feature.

Returns:
(list) each element should be a string citation,
ideally in BibTeX format.
feature_labels()

Generate attribute names.

Returns:
([str]) attribute labels.
featurize(*x)

Main featurizer function, which has to be implemented in any derived featurizer subclass.

Args:
x: input data to featurize (type depends on featurizer).
Returns:
(list) one or more features.
implementors()

List of implementors of the feature.

Returns:
(list) each element should either be a string with author name (e.g.,
“Anubhav Jain”) or a dictionary with required key “name” and other keys like “email” or “institution” (e.g., {“name”: “Anubhav Jain”, “email”: “ajain@lbl.gov”, “institution”: “LBNL”}).
class matminer.featurizers.tests.test_base.MultiArgs2

Bases: matminer.featurizers.base.BaseFeaturizer

__init__()

Initialize self. See help(type(self)) for accurate signature.

feature_labels()

Generate attribute names.

Returns:
([str]) attribute labels.
featurize(*x)

Main featurizer function, which has to be implemented in any derived featurizer subclass.

Args:
x: input data to featurize (type depends on featurizer).
Returns:
(list) one or more features.
class matminer.featurizers.tests.test_base.MultiTypeFeaturizer

Bases: matminer.featurizers.base.BaseFeaturizer

A featurizer that returns multiple dtypes

feature_labels()

Generate attribute names.

Returns:
([str]) attribute labels.
featurize(*x)

Main featurizer function, which has to be implemented in any derived featurizer subclass.

Args:
x: input data to featurize (type depends on featurizer).
Returns:
(list) one or more features.
class matminer.featurizers.tests.test_base.MultipleFeatureFeaturizer

Bases: matminer.featurizers.base.BaseFeaturizer

citations()

Citation(s) and reference(s) for this feature.

Returns:
(list) each element should be a string citation,
ideally in BibTeX format.
feature_labels()

Generate attribute names.

Returns:
([str]) attribute labels.
featurize(x)

Main featurizer function, which has to be implemented in any derived featurizer subclass.

Args:
x: input data to featurize (type depends on featurizer).
Returns:
(list) one or more features.
implementors()

List of implementors of the feature.

Returns:
(list) each element should either be a string with author name (e.g.,
“Anubhav Jain”) or a dictionary with required key “name” and other keys like “email” or “institution” (e.g., {“name”: “Anubhav Jain”, “email”: “ajain@lbl.gov”, “institution”: “LBNL”}).
class matminer.featurizers.tests.test_base.SingleFeaturizer

Bases: matminer.featurizers.base.BaseFeaturizer

citations()

Citation(s) and reference(s) for this feature.

Returns:
(list) each element should be a string citation,
ideally in BibTeX format.
feature_labels()

Generate attribute names.

Returns:
([str]) attribute labels.
featurize(x)

Main featurizer function, which has to be implemented in any derived featurizer subclass.

Args:
x: input data to featurize (type depends on featurizer).
Returns:
(list) one or more features.
implementors()

List of implementors of the feature.

Returns:
(list) each element should either be a string with author name (e.g.,
“Anubhav Jain”) or a dictionary with required key “name” and other keys like “email” or “institution” (e.g., {“name”: “Anubhav Jain”, “email”: “ajain@lbl.gov”, “institution”: “LBNL”}).
class matminer.featurizers.tests.test_base.SingleFeaturizerMultiArgs

Bases: matminer.featurizers.tests.test_base.SingleFeaturizer

featurize(*x)

Main featurizer function, which has to be implemented in any derived featurizer subclass.

Args:
x: input data to featurize (type depends on featurizer).
Returns:
(list) one or more features.
class matminer.featurizers.tests.test_base.TestBaseClass(methodName='runTest')

Bases: pymatgen.util.testing.PymatgenTest

static make_test_data()
setUp()

Hook method for setting up the test fixture before exercising it.

test_caching()

Test whether MultiFeaturizer properly caches

test_dataframe()
test_featurize_many()
test_fittable()
test_ignore_errors()
test_indices()
test_inplace()
test_matrix()

Test the ability to add features that are matrices to a dataframe

test_multifeature_no_zero_index()

Test whether multifeaturizer can handle series that lack a entry with index==0

test_multifeatures_multiargs()
test_multiindex_in_multifeaturizer()
test_multiindex_inplace()
test_multiindex_return()
test_multiple()
test_multiprocessing_df()
test_multitype_multifeat()

Test Multifeaturizer when a featurizer returns a non-numeric type

test_stacked_featurizer()

matminer.featurizers.tests.test_composition module

class matminer.featurizers.tests.test_composition.CompositionFeaturesTest(methodName='runTest')

Bases: pymatgen.util.testing.PymatgenTest

setUp()

Hook method for setting up the test fixture before exercising it.

test_ape()
test_atomic_orbitals()
test_band_center()
test_cation_properties()
test_cohesive_energy()
test_elec_affin()
test_elem()
test_elem_deml()
test_elem_matminer()
test_elem_matscholar_el()
test_en_diff()
test_fere_corr()
test_fraction()
test_ionic()
test_miedema_all()
test_miedema_ss()
test_oxidation_states()
test_stoich()
test_tm_fraction()
test_valence()
test_yang()

matminer.featurizers.tests.test_conversions module

class matminer.featurizers.tests.test_conversions.TestConversions(methodName='runTest')

Bases: unittest.case.TestCase

test_composition_to_oxidcomposition()
test_composition_to_structurefromMP()
test_conversion_multiindex()
test_conversion_multiindex_dynamic()
test_conversion_overwrite()
test_dict_to_object()
test_json_to_object()
test_str_to_composition()
test_structure_to_composition()
test_structure_to_oxidstructure()
test_to_istructure()

matminer.featurizers.tests.test_dos module

class matminer.featurizers.tests.test_dos.DOSFeaturesTest(methodName='runTest')

Bases: pymatgen.util.testing.PymatgenTest

setUp()

Hook method for setting up the test fixture before exercising it.

test_DOSFeaturizer()
test_DopingFermi()
test_DosAsymmetry()
test_Hybridization()
test_SiteDOS()

matminer.featurizers.tests.test_function module

class matminer.featurizers.tests.test_function.TestFunctionFeaturizer(methodName='runTest')

Bases: unittest.case.TestCase

setUp()

Hook method for setting up the test fixture before exercising it.

test_featurize()
test_featurize_labels()
test_helper_functions()
test_multi_featurizer()

matminer.featurizers.tests.test_site module

class matminer.featurizers.tests.test_site.FingerprintTests(methodName='runTest')

Bases: pymatgen.util.testing.PymatgenTest

setUp()

Hook method for setting up the test fixture before exercising it.

tearDown()

Hook method for deconstructing the test fixture after testing it.

test_AverageBondAngle()
test_AverageBondLength()
test_afs()
test_bop()
test_chemenv_site_fingerprint()
test_chemicalSRO()
test_cns()
test_crystal_nn_fingerprint()
test_crystal_site_fingerprint()
test_dataframe()
test_ewald_site()
test_gaussiansymmfunc()
test_grdf()
test_local_prop_diff()
test_off_center_cscl()
test_op_site_fingerprint()
test_simple_cubic()

Test with an easy structure

test_site_elem_prop()
test_voronoifingerprint()

matminer.featurizers.tests.test_structure module

class matminer.featurizers.tests.test_structure.StructureFeaturesTest(methodName='runTest')

Bases: pymatgen.util.testing.PymatgenTest

setUp()

Hook method for setting up the test fixture before exercising it.

test_SOAP()
test_bob()
test_bondfractions()
test_cgcnn_featurizer()
test_composition_features()
test_coulomb_matrix()
test_density_features()
test_dimensionality()
test_ewald()
test_global_symmetry()
test_jarvisCFID()
test_min_relative_distances()
test_orbital_field_matrix()
test_ordering_param()
test_packing_efficiency()
test_prdf()
test_rdf_and_peaks()
test_redf()
test_sine_coulomb_matrix()
test_sitestatsfingerprint()
test_ward_prb_2017_efftcn()

Test the effective coordination number attributes of Ward 2017

test_ward_prb_2017_lpd()

Test the local property difference attributes from Ward 2017

test_ward_prb_2017_strhet()
test_xrd_powderPattern()

Module contents