Fix mypy errors (ab558d41) · Commits · 钟慕尧 / deepchem

deepchem/molnet/load_function/material_datasets/load_bandgap.py

+10 −14

Original line number	Diff line number	Diff line
		@@ -9,7 +9,7 @@ from deepchem.trans import Transformer
		from deepchem.splits.splitters import Splitter
		from deepchem.molnet.defaults import get_defaults

		from typing import List, Tuple, Dict, Optional, Union
		from typing import List, Tuple, Dict, Optional, Union, Any, Type

		logger = logging.getLogger(__name__)

		@@ -39,22 +39,19 @@ DEFAULT_SPLITTERS = {k: DEFAULT_SPLITTERS[k] for k in splitters}


		def load_bandgap(
		featurizer: MaterialCompositionFeaturizer = DEFAULT_FEATURIZERS[
		'ElementPropertyFingerprint'],
		transformers: List[Transformer] = [
		DEFAULT_TRANSFORMERS['NormalizationTransformer']
		],
		splitter: Splitter = DEFAULT_SPLITTERS['RandomSplitter'],
		featurizer=DEFAULT_FEATURIZERS['ElementPropertyFingerprint'],
		transformers: List = [DEFAULT_TRANSFORMERS['NormalizationTransformer']],
		splitter=DEFAULT_SPLITTERS['RandomSplitter'],
		reload: bool = True,
		data_dir: Optional[str] = None,
		save_dir: Optional[str] = None,
		featurizer_kwargs: Dict[str, object] = {'data_source': 'matminer'},
		splitter_kwargs: Dict[str, object] = {
		featurizer_kwargs: Dict[str, Any] = {'data_source': 'matminer'},
		splitter_kwargs: Dict[str, Any] = {
		'frac_train': 0.8,
		'frac_valid': 0.1,
		'frac_test': 0.1
		},
		transformer_kwargs: Dict[str, Dict[str, object]] = {
		transformer_kwargs: Dict[str, Dict[str, Any]] = {
		'NormalizationTransformer': {
		'transform_X': True
		}
		@@ -86,9 +83,9 @@ def load_bandgap(
		Path to datasets.
		save_dir : str, optional
		Path to featurized datasets.
		featurizer_kwargs : dict
		featurizer_kwargs : Optional[Dict[str, Any]]
		Specify parameters to featurizer, e.g. {"size": 1024}
		splitter_kwargs : dict
		splitter_kwargs : Optional[Dict[str, Any]]
		Specify parameters to splitter, e.g. {"seed": 42}
		transformer_kwargs : dict
		Maps transformer names to constructor arguments, e.g.
		@@ -158,8 +155,7 @@ def load_bandgap(
		return my_tasks, all_dataset, transformers

		# First type of supported featurizers
		supported_featurizers = ['ElementPropertyFingerprint'
		] # type: List[Featurizer]
		supported_featurizers = ['ElementPropertyFingerprint'] # type: List[str]

		# Load .tar.gz file
		if featurizer.__class__.__name__ in supported_featurizers:

deepchem/molnet/load_function/material_datasets/load_perovskite.py

+10 −13

Original line number	Diff line number	Diff line
		@@ -9,7 +9,7 @@ from deepchem.trans import Transformer
		from deepchem.splits.splitters import Splitter
		from deepchem.molnet.defaults import get_defaults

		from typing import List, Tuple, Dict, Optional, Union
		from typing import List, Tuple, Dict, Optional, Union, Any, Type, Callable

		logger = logging.getLogger(__name__)

		@@ -37,22 +37,19 @@ DEFAULT_SPLITTERS = {k: DEFAULT_SPLITTERS[k] for k in splitters}


		def load_perovskite(
		featurizer: MaterialStructureFeaturizer = DEFAULT_FEATURIZERS[
		'SineCoulombMatrix'],
		transformers: List[Transformer] = [
		DEFAULT_TRANSFORMERS['NormalizationTransformer']
		],
		splitter: Splitter = DEFAULT_SPLITTERS['RandomSplitter'],
		featurizer=DEFAULT_FEATURIZERS['SineCoulombMatrix'],
		transformers: List = [DEFAULT_TRANSFORMERS['NormalizationTransformer']],
		splitter=DEFAULT_SPLITTERS['RandomSplitter'],
		reload: bool = True,
		data_dir: Optional[str] = None,
		save_dir: Optional[str] = None,
		featurizer_kwargs: Dict[str, object] = None,
		splitter_kwargs: Dict[str, object] = {
		featurizer_kwargs: Dict[str, Any] = {},
		splitter_kwargs: Dict[str, Any] = {
		'frac_train': 0.8,
		'frac_valid': 0.1,
		'frac_test': 0.1
		},
		transformer_kwargs: Dict[str, Dict[str, object]] = {
		transformer_kwargs: Dict[str, Dict[str, Any]] = {
		'NormalizationTransformer': {
		'transform_X': True
		}
		@@ -84,9 +81,9 @@ def load_perovskite(
		Path to datasets.
		save_dir : str, optional
		Path to featurized datasets.
		featurizer_kwargs : dict
		featurizer_kwargs : Optional[Dict[str, Any]]
		Specify parameters to featurizer, e.g. {"size": 1024}
		splitter_kwargs : dict
		splitter_kwargs : Optional[Dict[str, Any]]
		Specify parameters to splitter, e.g. {"seed": 42}
		transformer_kwargs : dict
		Maps transformer names to constructor arguments, e.g.
		@@ -157,7 +154,7 @@ def load_perovskite(

		# First type of supported featurizers
		supported_featurizers = ['StructureGraphFeaturizer',
		'SineCoulombMatrix'] # type: List[Featurizer]
		'SineCoulombMatrix'] # type: List[str]

		# Load .tar.gz file
		if featurizer.__class__.__name__ in supported_featurizers:

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