def test_presets(self):
target = "K_VRH"
df = copy.copy(self.test_df.iloc[:self.limit])
af = AutoFeaturizer(preset="fast")
df = af.fit_transform(df, target)
known_feats = CompositionFeaturizers().fast + \
StructureFeaturizers().fast
n_structure_featurizers = len(af.featurizers["structure"])
n_composition_featurizers = len(af.featurizers["composition"])
n_featurizers = n_structure_featurizers + n_composition_featurizers
self.assertEqual(n_featurizers, len(known_feats))
def test_presets(self):
target = "K_VRH"
df = copy.copy(self.test_df.iloc[: self.limit])
af = AutoFeaturizer(preset="express")
df = af.fit_transform(df, target)
known_feats = (
CompositionFeaturizers().express + StructureFeaturizers().express
)
n_structure_featurizers = len(af.featurizers["structure"])
n_composition_featurizers = len(af.featurizers["composition"])
n_removed_featurizers = len(af.removed_featurizers)
n_featurizers = (
n_structure_featurizers
+ n_composition_featurizers
+ n_removed_featurizers
)
self.assertEqual(n_featurizers, len(known_feats))
def _tidy_column(self, df, featurizer_type):
"""
Various conversions to homogenize columns for featurization input.
For example, take a column of compositions and ensure they are decorated
with oxidation states, are not strings, etc.
Args:
df (pandas.DataFrame)
featurizer_type: The key defining the featurizer input. For example,
composition featurizers should have featurizer_type of
"composition".
Returns:
df (pandas.DataFrame): DataFrame with featurizer_type column
ready for featurization.
"""
# todo: Make the following conversions more robust (no [0] type checking)
type_tester = df[featurizer_type].iloc[0]
if featurizer_type == self.composition_col:
# Convert formulas to composition objects
if isinstance(type_tester, str):
self.logger.info(
self._log_prefix +
"Compositions detected as strings. Attempting "
"conversion to Composition objects...")
stc = StrToComposition(overwrite_data=True,
target_col_id=featurizer_type)
df = stc.featurize_dataframe(df,
featurizer_type,
multiindex=self.multiindex,
ignore_errors=True,
inplace=False)
elif isinstance(type_tester, dict):
self.logger.info(self._log_prefix +
"Compositions detected as dicts. Attempting "
"conversion to Composition objects...")
df[featurizer_type] = [
Composition.from_dict(d) for d in df[featurizer_type]
]
# Convert non-oxidstate containing comps to oxidstate comps
if self.guess_oxistates:
self.logger.info(
self._log_prefix +
"Guessing oxidation states of compositions, as"
" they were not present in input.")
cto = CompositionToOxidComposition(
target_col_id=featurizer_type,
overwrite_data=True,
return_original_on_error=True,
max_sites=-50)
try:
df = cto.featurize_dataframe(df,
featurizer_type,
multiindex=self.multiindex,
inplace=False)
except Exception as e:
self.logger.info(self._log_prefix +
"Could not decorate oxidation states due "
"to {}. Excluding featurizers based on "
"composition oxistates".format(e))
classes_require_oxi = [
c.__class__.__name__
for c in CompositionFeaturizers().need_oxi
]
self.exclude.extend(classes_require_oxi)
else:
# Convert structure/bs/dos dicts to objects (robust already)
if isinstance(type_tester, (dict, str)):
self.logger.info(self._log_prefix.capitalize() +
"{} detected as string or dict. Attempting "
"conversion to {} objects..."
"".format(featurizer_type, featurizer_type))
if isinstance(type_tester, str):
raise ValueError("{} column is type {}. Cannot convert."
"".format(featurizer_type,
type(type_tester)))
dto = DictToObject(overwrite_data=True,
target_col_id=featurizer_type)
df = dto.featurize_dataframe(df,
featurizer_type,
inplace=False)
# Decorate with oxidstates
if featurizer_type == self.structure_col and \
self.guess_oxistates:
self.logger.info(
self._log_prefix +
"Guessing oxidation states of structures if they were "
"not present in input.")
sto = StructureToOxidStructure(
target_col_id=featurizer_type,
overwrite_data=True,
return_original_on_error=True,
max_sites=-50)
try:
df = sto.featurize_dataframe(
df,
featurizer_type,
multiindex=self.multiindex,
inplace=False)
except Exception as e:
self.logger.info(
self._log_prefix +
"Could not decorate oxidation states on structures "
"due to {}.".format(e))
return df
def setUp(self):
self.required_attrs = ["express", "heavy", "debug", "all"]
self.c = CompositionFeaturizers()
self.s = StructureFeaturizers()
self.b = BSFeaturizers()
self.d = DOSFeaturizers()