def __init__(self, exclude=None):
super(CompositionFeaturizers, self).__init__(exclude=exclude)
self._fast_featurizers = [
cf.AtomicOrbitals(),
cf.ElementProperty.from_preset("matminer"),
cf.ElementProperty.from_preset("magpie"),
cf.ElementProperty.from_preset("matscholar_el"),
cf.ElementProperty.from_preset("deml"),
cf.ElementFraction(),
cf.Stoichiometry(),
cf.TMetalFraction(),
cf.BandCenter(),
cf.ValenceOrbital()
]
self._slow_featurizers = [
cf.Miedema(),
cf.AtomicPackingEfficiency(), # slower than the rest
cf.CohesiveEnergy() # requires mpid present
]
self._need_oxi_featurizers = [
cf.YangSolidSolution(),
cf.CationProperty.from_preset(preset_name='deml'),
cf.OxidationStates.from_preset(preset_name='deml'),
cf.ElectronAffinity(),
cf.ElectronegativityDiff(),
cf.IonProperty()
]
self._intermetallics_only = [
cf.YangSolidSolution(),
cf.Miedema(),
]
def express(self):
fs = [
cf.ElementProperty.from_preset("magpie"),
cf.OxidationStates.from_preset(preset_name='deml'),
cf.ElectronAffinity(),
cf.IonProperty(),
cf.YangSolidSolution(),
cf.Miedema(),
]
return self._get_featurizers(fs)
def all(self):
fs = [
cf.AtomicOrbitals(),
cf.ElementProperty.from_preset("matminer"),
cf.ElementProperty.from_preset("magpie"),
cf.ElementProperty.from_preset("matscholar_el"),
cf.ElementProperty.from_preset("deml"),
cf.ElementFraction(),
cf.Stoichiometry(),
cf.TMetalFraction(),
cf.BandCenter(),
cf.ValenceOrbital(),
cf.YangSolidSolution(),
cf.CationProperty.from_preset(preset_name='deml'),
cf.OxidationStates.from_preset(preset_name='deml'),
cf.ElectronAffinity(),
cf.ElectronegativityDiff(),
cf.IonProperty(),
cf.Miedema(),
cf.AtomicPackingEfficiency(), # slower than the rest
cf.CohesiveEnergy() # requires mpid present
]
return self._get_featurizers(fs)
# ### adding features based on compositions from matminer package # In[11]: # element property ep_feat = composition.ElementProperty.from_preset(preset_name="magpie") df_ft = ep_feat.featurize_dataframe(df_ft, col_id="composition", ignore_errors=True)# input the "composition" column to the featurizer # atomic orbitals ao_feat = composition.AtomicOrbitals() df_ft = ao_feat.featurize_dataframe(df_ft, col_id="composition", ignore_errors=True) # band center bc_feat = composition.BandCenter() df_ft = bc_feat.featurize_dataframe(df_ft, col_id="composition", ignore_errors=True) # miedema m_feat = composition.Miedema() df_ft = m_feat.featurize_dataframe(df_ft, col_id="composition", ignore_errors=True) # stoichiometry s_feat = composition.Stoichiometry() df_ft = s_feat.featurize_dataframe(df_ft, col_id="composition", ignore_errors=True) # t metal fraction tmf_feat = composition.TMetalFraction() df_ft = tmf_feat.featurize_dataframe(df_ft, col_id="composition", ignore_errors=True) # # valence orbital # vo_feat = composition.ValenceOrbital() # df_ft = vo_feat.featurize_dataframe(df_ft, col_id="composition", ignore_errors=True) # # yang solid solution # yss_feat = composition.YangSolidSolution() # df_ft = yss_feat.featurize_dataframe(df_ft, col_id="composition", ignore_errors=True) # # atomic packing efficiency # ape_feat = composition.AtomicPackingEfficiency()