Merge pull request #100 from joegomes/master (ce801541) · Commits · 钟慕尧 / deepchem

datasets/gbd3k.pkl.gz

0 → 100644

+405 KiB

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deepchem/featurizers/featurize.py

+12 −10

Original line number	Diff line number	Diff line
		@@ -140,18 +140,15 @@ class DataFeaturizer(object):
		for j in range(len(interval_points)-1):
		log("Sharding and standardizing into shard-%s / %s shards" % (str(j+1), len(interval_points)-1), self.verbose)
		raw_df_shard = raw_df.iloc[range(interval_points[j], interval_points[j+1])]

		df = self._standardize_df(raw_df_shard)
		log("Aggregating User-Specified Features", self.verbose)
		self._add_user_specified_features(df)

		for compound_featurizer in self.compound_featurizers:
		log("Currently feauturizing feature_type: %s"
		log("Currently featurizing feature_type: %s"
		% compound_featurizer.__class__.__name__, self.verbose)
		self._featurize_compounds(df, compound_featurizer, worker_pool=worker_pool)

		for complex_featurizer in self.complex_featurizers:
		log("Currently feauturizing feature_type: %s"
		log("Currently featurizing feature_type: %s"
		% complex_featurizer.__class__.__name__, self.verbose)
		self._featurize_complexes(df, complex_featurizer, worker_pool=worker_pool)

		@@ -161,8 +158,7 @@ class DataFeaturizer(object):

		featurizers = self.compound_featurizers + self.complex_featurizers
		samples = FeaturizedSamples(samples_dir=samples_dir, featurizers=featurizers,
		dataset_files=shard_files,
		reload_data=False)
		dataset_files=shard_files, reload_data=False)

		return samples

		@@ -192,6 +188,9 @@ class DataFeaturizer(object):
		df["smiles"] = ori_df[[self.smiles_field]]
		for task in self.tasks:
		df[task] = ori_df[[task]]
		if self.user_specified_features is not None:
		for feature in self.user_specified_features:
		df[feature] = ori_df[[feature]]
		if self.split_field is not None:
		df["split"] = ori_df[[self.split_field]]
		if self.protein_pdb_field is not None:
		@@ -200,6 +199,9 @@ class DataFeaturizer(object):
		df["ligand_pdb"] = ori_df[[self.ligand_pdb_field]]
		if self.ligand_mol2_field is not None:
		df["ligand_mol2"] = ori_df[[self.ligand_mol2_field]]
		if self.user_specified_features is not None:
		log("Aggregating User-Specified Features", self.verbose)
		self._add_user_specified_features(df)
		return df


		@@ -277,15 +279,15 @@ class DataFeaturizer(object):
		into final features dataframe
		"""
		if self.user_specified_features is not None:
		log("Adding user-defined features.", self.verbose)
		#log("Adding user-defined features.", self.verbose)
		features_data = []
		for _, row in df.iterrows():
		# pandas rows are tuples (row_num, row_data)
		feature_list = []
		for feature_name in self.user_specified_features:
		feature_list.append(row[feature_name])
		features_data.append({"user-specified-features": np.array(feature_list)})
		df["user-specified-features"] = pd.DataFrame(features_data)
		features_data.append(np.array(feature_list))
		df["user-specified-features"] = features_data


		def map_function(data_tuple, featurizer):

deepchem/models/init.py

+1 −1

Original line number	Diff line number	Diff line
		@@ -77,7 +77,7 @@ class Model(object):
		"""
		Factory method that initializes model of requested type.
		"""
		if model_instance.__class__ in non_sklearn_models:
		if model_instance.__class__ in Model.non_sklearn_models:
		model = model_instance(task_types, model_params, initialize_raw_model)
		else:
		model = Model.registered_model_classes["SklearnModel"](model_instance,

deepchem/utils/dataset.py

+5 −1

Original line number	Diff line number	Diff line
		@@ -30,9 +30,13 @@ class Dataset(object):
		os.makedirs(data_dir)
		self.data_dir = data_dir

		if featurizers is not None:
		feature_types = [featurizer.__class__.__name__ for featurizer in featurizers]
		else:
		feature_types = None

		if use_user_specified_features:
		feature_types += ["user-specified-features"]
		feature_types = ["user-specified-features"]

		if samples is not None and feature_types is not None:
		if not isinstance(feature_types, list):

deepchem/utils/test/gbd3k.pkl.gz

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+405 KiB

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