FIX: formatting in tested module (d3c6a575) · Commits · 钟慕尧 / deepchem

deepchem/feat/rdkit_grid_featurizer.py

+12 −11

Original line number	Diff line number	Diff line
		@@ -74,7 +74,8 @@ def generate_random__unit_vector():
		theta = np.random.uniform(low=0.0, high=2 * np.pi)
		z = np.random.uniform(low=-1.0, high=1.0)
		u = np.array(
		[np.sqrt(1 - z*2) np.cos(theta), np.sqrt(1 - z*2) np.sin(theta), z])
		[np.sqrt(1 - z*2) np.cos(theta),
		np.sqrt(1 - z*2) np.sin(theta), z])
		return (u)


		@@ -142,8 +143,8 @@ def compute_pairwise_distances(protein_xyz, ligand_xyz):
		atom and the j"th ligand atom
		"""

		pairwise_distances = np.zeros(
		(np.shape(protein_xyz)[0], np.shape(ligand_xyz)[0]))
		pairwise_distances = np.zeros((np.shape(protein_xyz)[0],
		np.shape(ligand_xyz)[0]))
		for j in range(0, np.shape(ligand_xyz)[0]):
		differences = protein_xyz - ligand_xyz[j, :]
		squared_differences = np.square(differences)
		@@ -347,8 +348,8 @@ def compute_splif_features_in_range(protein,
		atoms. Returns a dictionary mapping (protein_index_i, ligand_index_j) -->
		(protein_ecfp_i, ligand_ecfp_j)
		"""
		contacts = np.nonzero((pairwise_distances > contact_bin[0]) & (
		pairwise_distances < contact_bin[1]))
		contacts = np.nonzero((pairwise_distances > contact_bin[0]) &
		(pairwise_distances < contact_bin[1]))
		protein_atoms = set([int(c) for c in contacts[0].tolist()])
		contacts = zip(contacts[0], contacts[1])

		@@ -509,8 +510,8 @@ def get_formal_charge(atom):


		def is_salt_bridge(atom_i, atom_j):
		if np.abs(2.0 - np.abs(get_formal_charge(atom_i) - get_formal_charge(
		atom_j))) < 0.01:
		if np.abs(2.0 - np.abs(get_formal_charge(atom_i) - get_formal_charge(atom_j))
		) < 0.01:
		return True
		else:
		return False
		@@ -555,8 +556,8 @@ def compute_hbonds_in_range(protein, protein_xyz, ligand, ligand_xyz,
		a distance bin and an angle cutoff.
		"""

		contacts = np.nonzero((pairwise_distances > hbond_dist_bin[0]) & (
		pairwise_distances < hbond_dist_bin[1]))
		contacts = np.nonzero((pairwise_distances > hbond_dist_bin[0]) &
		(pairwise_distances < hbond_dist_bin[1]))
		protein_atoms = set([int(c) for c in contacts[0].tolist()])
		protein_ecfp_dict = compute_all_ecfp(
		protein, indices=protein_atoms, degree=ecfp_degree)
		@@ -1112,8 +1113,8 @@ class RdkitGridFeaturizer(ComplexFeaturizer):
		for voxel in voxels:
		try:
		if hash_function is not None:
		feature_tensor[voxel[0], voxel[1], voxel[2], hash_function(
		features, channel_power)] += 1.0
		feature_tensor[voxel[0], voxel[1], voxel[2],
		hash_function(features, channel_power)] += 1.0
		else:
		feature_tensor[voxel[0], voxel[1], voxel[3], 0] += features
		except:

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