Merge pull request #2020 from ncfrey/material_featurizer_renames (0b8b1347) · Commits · 钟慕尧 / deepchem

deepchem/feat/init.py

+2 −2

Original line number	Diff line number	Diff line
		@@ -3,8 +3,8 @@ Making it easy to import in classes.
		"""
		from deepchem.feat.base_classes import Featurizer
		from deepchem.feat.base_classes import MolecularFeaturizer
		from deepchem.feat.base_classes import StructureFeaturizer
		from deepchem.feat.base_classes import CompositionFeaturizer
		from deepchem.feat.base_classes import MaterialStructureFeaturizer
		from deepchem.feat.base_classes import MaterialCompositionFeaturizer
		from deepchem.feat.base_classes import ComplexFeaturizer
		from deepchem.feat.base_classes import UserDefinedFeaturizer
		from deepchem.feat.graph_features import ConvMolFeaturizer

deepchem/feat/base_classes.py

+43 −18

Original line number	Diff line number	Diff line
		@@ -9,8 +9,6 @@ from typing import Iterable, Union, Dict, Any

		logger = logging.getLogger(__name__)

		JSON = Dict[str, Any]


		class Featurizer(object):
		"""Abstract class for calculating a set of features for a datapoint.
		@@ -23,15 +21,18 @@ class Featurizer(object):
		new datatype.
		"""

		def featurize(self, datapoints, log_every_n=1000):
		def featurize(self, datapoints: Iterable[Any],
		log_every_n: int = 1000) -> np.ndarray:
		"""Calculate features for datapoints.

		Parameters
		----------
		datapoints: iterable
		datapoints: Iterable[Any]
		A sequence of objects that you'd like to featurize. Subclassses of
		`Featurizer` should instantiate the `_featurize` method that featurizes
		objects in the sequence.
		log_every_n: int, default 1000
		Logs featurization progress every `log_every_n` steps.

		Returns
		-------
		@@ -68,7 +69,8 @@ class Featurizer(object):
		Parameters
		----------
		datapoint: object
		a single datapoint in a sequence of objects
		Any blob of data you like. Subclass should instantiate
		this.
		"""
		raise NotImplementedError('Featurizer is not defined.')

		@@ -220,12 +222,12 @@ class MolecularFeaturizer(Featurizer):
		return features


		class StructureFeaturizer(Featurizer):
		class MaterialStructureFeaturizer(Featurizer):
		"""
		Abstract class for calculating a set of features for an
		inorganic crystal structure.

		The defining feature of a `StructureFeaturizer` is that it
		The defining feature of a `MaterialStructureFeaturizer` is that it
		operates on 3D crystal structures with periodic boundary conditions.
		Inorganic crystal structures are represented by Pymatgen structure
		objects. Featurizers for inorganic crystal structures that are subclasses of
		@@ -244,15 +246,16 @@ class StructureFeaturizer(Featurizer):

		"""

		def featurize(self, structures: Iterable[JSON],
		def featurize(self,
		structures: Iterable[Dict[str, Any]],
		log_every_n: int = 1000) -> np.ndarray:
		"""Calculate features for crystal structures.

		Parameters
		----------
		structures: Iterable[JSON]
		structures: Iterable[Dict[str, Any]]
		Iterable sequence of pymatgen structure dictionaries.
		Json-serializable dictionary representation of pymatgen.core.structure
		Dictionary representations of pymatgen.Structure
		https://pymatgen.org/pymatgen.core.structure.html
		log_every_n: int, default 1000
		Logging messages reported every `log_every_n` samples.
		@@ -265,7 +268,6 @@ class StructureFeaturizer(Featurizer):

		"""

		# Convert iterables to list
		structures = list(structures)

		try:
		@@ -288,13 +290,25 @@ class StructureFeaturizer(Featurizer):
		features = np.asarray(features)
		return features

		def __call__(self, structures: Iterable[Dict[str, Any]]):
		"""Calculate features for crystal structures.

		Parameters
		----------
		structures: Iterable[Dict[str, Any]]
		An iterable of pymatgen.Structure dictionaries.

		"""

		return self.featurize(structures)

		class CompositionFeaturizer(Featurizer):

		class MaterialCompositionFeaturizer(Featurizer):
		"""
		Abstract class for calculating a set of features for an
		inorganic crystal composition.

		The defining feature of a `CompositionFeaturizer` is that it
		The defining feature of a `MaterialCompositionFeaturizer` is that it
		operates on 3D crystal chemical compositions.
		Inorganic crystal compositions are represented by Pymatgen composition
		objects. Featurizers for inorganic crystal compositions that are
		@@ -332,7 +346,6 @@ class CompositionFeaturizer(Featurizer):

		"""

		# Convert iterables to list
		compositions = list(compositions)

		try:
		@@ -355,6 +368,18 @@ class CompositionFeaturizer(Featurizer):
		features = np.asarray(features)
		return features

		def __call__(self, compositions: Iterable[str]):
		"""Calculate features for crystal compositions.

		Parameters
		----------
		compositions: Iterable[str]
		An iterable of crystal compositions.

		"""

		return self.featurize(compositions)


		class UserDefinedFeaturizer(Featurizer):
		"""Directs usage of user-computed featurizations."""

deepchem/feat/materials_featurizers.py

+6 −6

Original line number	Diff line number	Diff line
		@@ -4,11 +4,11 @@ Featurizers for inorganic crystals.

		import numpy as np

		from deepchem.feat import StructureFeaturizer, CompositionFeaturizer
		from deepchem.feat import MaterialStructureFeaturizer, MaterialCompositionFeaturizer
		from deepchem.utils import pad_array


		class ElementPropertyFingerprint(CompositionFeaturizer):
		class ElementPropertyFingerprint(MaterialCompositionFeaturizer):
		"""
		Fingerprint of elemental properties from composition.

		@@ -50,7 +50,7 @@ class ElementPropertyFingerprint(CompositionFeaturizer):

		self.data_source = data_source

		def _featurize(self, composition: "pymatgen.Composition"):
		def _featurize(self, composition):
		"""
		Calculate chemical fingerprint from crystal composition.

		@@ -81,7 +81,7 @@ class ElementPropertyFingerprint(CompositionFeaturizer):
		return np.array(feats)


		class SineCoulombMatrix(StructureFeaturizer):
		class SineCoulombMatrix(MaterialStructureFeaturizer):
		"""
		Calculate sine Coulomb matrix for crystals.

		@@ -124,7 +124,7 @@ class SineCoulombMatrix(StructureFeaturizer):
		self.max_atoms = int(max_atoms)
		self.flatten = flatten

		def _featurize(self, struct: "pymatgen.Structure"):
		def _featurize(self, struct):
		"""
		Calculate sine Coulomb matrix from pymatgen structure.

		@@ -164,7 +164,7 @@ class SineCoulombMatrix(StructureFeaturizer):
		return features


		class StructureGraphFeaturizer(StructureFeaturizer):
		class StructureGraphFeaturizer(MaterialStructureFeaturizer):
		"""
		Calculate structure graph features for crystals.

docs/featurizers.rst

+8 −8

Original line number	Diff line number	Diff line
		@@ -161,17 +161,17 @@ AtomConvFeaturizer
		.. autoclass:: deepchem.feat.NeighborListComplexAtomicCoordinates
		:members:

		StructureFeaturizer
		-------------------
		MaterialStructureFeaturizer
		---------------------------

		Structure Featurizers are those that work with datasets of crystals with
		Material Structure Featurizers are those that work with datasets of crystals with
		periodic boundary conditions. For inorganic crystal structures, these
		featurizers operate on pymatgen.Structure objects, which include a
		lattice and 3D coordinates that specify a periodic crystal structure.
		They should be applied on systems that have periodic boundary conditions.
		Structure featurizers are not designed to work with molecules.

		.. autoclass:: deepchem.feat.StructureFeaturizer
		.. autoclass:: deepchem.feat.MaterialStructureFeaturizer
		:members:

		SineCoulombMatrix
		@@ -186,17 +186,17 @@ StructureGraphFeaturizer
		.. autoclass:: deepchem.feat.StructureGraphFeaturizer
		:members:

		CompositionFeaturizer
		---------------------
		MaterialCompositionFeaturizer
		-----------------------------

		Composition Featurizers are those that work with datasets of crystal
		Material Composition Featurizers are those that work with datasets of crystal
		compositions with periodic boundary conditions.
		For inorganic crystal structures, these featurizers operate on chemical
		compositions (e.g. "MoS2"). They should be applied on systems that have
		periodic boundary conditions. Composition featurizers are not designed
		to work with molecules.

		.. autoclass:: deepchem.feat.CompositionFeaturizer
		.. autoclass:: deepchem.feat.MaterialCompositionFeaturizer
		:members:

		ElementPropertyFingerprint

Admin message