Construct dataset first time, even with reload=True (814b3d11) · Commits · 钟慕尧 / deepchem

deepchem/molnet/load_function/pdbbind_datasets.py

+9 −8

Original line number	Diff line number	Diff line
		@@ -20,6 +20,7 @@ from deepchem.feat.atomic_coordinates import ComplexNeighborListFragmentAtomicCo
		from deepchem.feat.graph_features import AtomicConvFeaturizer

		logger = logging.getLogger(__name__)
		DEFAULT_DATA_DIR = deepchem.utils.get_data_dir()


		def featurize_pdbbind(data_dir=None, feat="grid", subset="core"):
		@@ -178,11 +179,11 @@ def load_pdbbind(reload=True,
		deepchem_dir = deepchem.utils.get_data_dir()

		if data_dir == None:
		data_dir = deepchem_dir
		data_dir = DEFAULT_DATA_DIR
		data_folder = os.path.join(data_dir, "pdbbind", "v2015")

		if save_dir == None:
		save_dir = os.path.join(deepchem_dir, "from-pdbbind")
		save_dir = os.path.join(DEFAULT_DATA_DIR, "from-pdbbind")
		if load_binding_pocket:
		save_folder = os.path.join(
		save_dir, "protein_pocket-%s-%s-%s" % (subset, featurizer, split))
		@@ -197,15 +198,15 @@ def load_pdbbind(reload=True,

		if reload:
		if not os.path.exists(save_folder):
		raise IOError("Cannot find saved dataset from %s!" % save_folder)
		print("\nLoading featurized and splitted dataset from:\n%s\n" % save_folder)
		print(
		"Dataset does not exist at {}. Reconstructing...".format(save_folder))
		else:
		print(
		"\nLoading featurized and splitted dataset from:\n%s\n" % save_folder)
		loaded, all_dataset, transformers = deepchem.utils.save.load_dataset_from_disk(
		save_folder)
		if loaded:
		return pdbbind_tasks, all_dataset, transformers
		else:
		raise IOError("Failed to load featurized and splitted dataset from:\n%s\n"
		% save_folder)

		dataset_file = os.path.join(data_dir, "pdbbind_v2015.tar.gz")
		if not os.path.exists(dataset_file):

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