def test_en_diff(self):
featurizer = ElectronegativityDiff()
features = dict(zip(featurizer.feature_labels(), featurizer.featurize(self.df["composition"][1])))
self.assertAlmostEqual(features["minimum EN difference"], 1.6099999999)
self.assertAlmostEqual(features["maximum EN difference"], 1.6099999999)
self.assertAlmostEqual(features["range EN difference"], 0)
self.assertAlmostEqual(features["mean EN difference"], 1.6099999999)
self.assertAlmostEqual(features["std_dev EN difference"], 0)
ignore_errors=True)
#AtomicOrbital
from matminer.featurizers.composition import AtomicOrbitals
atomic_orbitals = AtomicOrbitals()
atomic_orbitals.set_n_jobs(28)
labels.append(atomic_orbitals.feature_labels())
df = atomic_orbitals.featurize_dataframe(df,
'composition',
ignore_errors=True)
#ElectronegativityDiff
from matminer.featurizers.composition import ElectronegativityDiff
electronegativity_diff = ElectronegativityDiff()
electronegativity_diff.set_n_jobs(28)
labels.append(electronegativity_diff.feature_labels())
df = electronegativity_diff.featurize_dataframe(df,
'composition_oxid',
ignore_errors=True)
#ElectronAffinity
from matminer.featurizers.composition import ElectronAffinity
electron_affinity = ElectronAffinity()
electron_affinity.set_n_jobs(28)
labels.append(electron_affinity.feature_labels())
df = electron_affinity.featurize_dataframe(df,
'composition_oxid',
ignore_errors=True)
if args.functionalize is True:
#FunctionFeaturizer