Cleaning up voxels (71a40f4c) · Commits · 钟慕尧 / deepchem

deepchem/feat/grid_featurizers.py

+20 −62

Original line number	Diff line number	Diff line
		@@ -50,9 +50,10 @@ class ChargeVoxelizer(ComplexFeaturizer):
		a local charge array. Sum contributions to get an effective
		charge at each voxel.

		Creates a tensor output of shape `(voxels_per_edge,
		voxels_per_edge, voxels_per_edge, 1)` for each macromolecular
		complex that computes the effective charge at each voxel.
		Let `voxels_per_edge = int(box_width/voxel_width)`. Creates a
		tensor output of shape `(voxels_per_edge, voxels_per_edge,
		voxels_per_edge, 1)` for each macromolecular complex that computes
		the effective charge at each voxel.
		"""
		def __init__(self,
		cutoff=4.5,
		@@ -76,7 +77,6 @@ class ChargeVoxelizer(ComplexFeaturizer):
		self.cutoff = cutoff
		self.box_width = box_width
		self.voxel_width = voxel_width
		self.voxels_per_edge = int(self.box_width / self.voxel_width)
		self.reduce_to_contacts = reduce_to_contacts

		def _featurize_complex(self, molecular_complex):
		@@ -110,7 +110,6 @@ class ChargeVoxelizer(ComplexFeaturizer):
		sum([
		voxelize(
		convert_atom_to_voxel,
		self.voxels_per_edge,
		self.box_width,
		self.voxel_width,
		None,
		@@ -135,9 +134,10 @@ class SaltBridgeVoxelizer(ComplexFeaturizer):
		interact in a salt-bridge, the interaction is double counted
		in both voxels.

		Creates a tensor output of shape `(voxels_per_edge,
		voxels_per_edge, voxels_per_edge, 1)` for each macromolecular
		the number of salt bridges at each voxel.
		Let `voxels_per_edge = int(box_width/voxel_width)`. Creates a
		tensor output of shape `(voxels_per_edge, voxels_per_edge,
		voxels_per_edge, 1)` for each macromolecular the number of salt
		bridges at each voxel.
		"""
		def __init__(self,
		cutoff=5.0,
		@@ -162,7 +162,6 @@ class SaltBridgeVoxelizer(ComplexFeaturizer):
		self.cutoff = cutoff
		self.box_width = box_width
		self.voxel_width = voxel_width
		self.voxels_per_edge = int(self.box_width / self.voxel_width)
		self.reduce_to_contacts = reduce_to_contacts

		def _featurize_complex(self, molecular_complex):
		@@ -195,7 +194,6 @@ class SaltBridgeVoxelizer(ComplexFeaturizer):
		pairwise_features.append(
		voxelize(
		convert_atom_pair_to_voxel,
		self.voxels_per_edge,
		self.box_width,
		self.voxel_width,
		None, xyzs,
		@@ -218,9 +216,10 @@ class CationPiVoxelizer(ComplexFeaturizer):
		bridge in the voxel in which it originated to create a local
		cation-pi array.

		Creates a tensor output of shape `(voxels_per_edge,
		voxels_per_edge, voxels_per_edge, 1)` for each macromolecular
		the number of cation-pi interactions at each voxel.
		Let `voxels_per_edge = int(box_width/voxel_width)`. Creates a
		tensor output of shape `(voxels_per_edge, voxels_per_edge,
		voxels_per_edge, 1)` for each macromolecular the number of cation-pi
		interactions at each voxel.
		"""
		def __init__(self,
		distance_cutoff=6.5,
		@@ -251,7 +250,6 @@ class CationPiVoxelizer(ComplexFeaturizer):
		self.angle_cutoff = angle_cutoff
		self.box_width = box_width
		self.voxel_width = voxel_width
		self.voxels_per_edge = int(self.box_width / self.voxel_width)

		def _featurize_complex(self, molecular_complex):
		"""
		@@ -282,7 +280,6 @@ class CationPiVoxelizer(ComplexFeaturizer):
		sum([
		voxelize(
		convert_atom_to_voxel,
		self.voxels_per_edge,
		self.box_width,
		self.voxel_width,
		None,
		@@ -310,11 +307,12 @@ class PiStackVoxelizer(ComplexFeaturizer):
		localize this salt bridge in the voxel in which it originated
		to create a local pi-stacking array.

		Creates a tensor output of shape `(voxels_per_edge,
		voxels_per_edge, voxels_per_edge, 2)` for each macromolecular
		Each voxel has 2 fields, with the first tracking the number
		of pi-pi parallel interactions, and the second tracking the
		number of pi-T interactions.
		Let `voxels_per_edge = int(box_width/voxel_width)`. Creates a
		tensor output of shape `(voxels_per_edge, voxels_per_edge,
		voxels_per_edge, 2)` for each macromolecular Each voxel has 2
		fields, with the first tracking the number of pi-pi parallel
		interactions, and the second tracking the number of pi-T
		interactions.
		"""
		def __init__(self,
		distance_cutoff=4.4,
		@@ -341,7 +339,6 @@ class PiStackVoxelizer(ComplexFeaturizer):
		self.angle_cutoff = angle_cutoff
		self.box_width = box_width
		self.voxel_width = voxel_width
		self.voxels_per_edge = int(self.box_width / self.voxel_width)

		def _featurize_complex(self, molecular_complex):
		"""
		@@ -379,7 +376,6 @@ class PiStackVoxelizer(ComplexFeaturizer):
		angle_cutoff=self.angle_cutoff))
		pi_parallel_tensor = voxelize(
		convert_atom_to_voxel,
		self.voxels_per_edge,
		self.box_width,
		self.voxel_width,
		None,
		@@ -388,7 +384,6 @@ class PiStackVoxelizer(ComplexFeaturizer):
		nb_channel=1)
		pi_parallel_tensor += voxelize(
		convert_atom_to_voxel,
		self.voxels_per_edge,
		self.box_width,
		self.voxel_width,
		None,
		@@ -398,7 +393,6 @@ class PiStackVoxelizer(ComplexFeaturizer):

		pi_t_tensor = voxelize(
		convert_atom_to_voxel,
		self.voxels_per_edge,
		self.box_width,
		self.voxel_width,
		None,
		@@ -407,7 +401,6 @@ class PiStackVoxelizer(ComplexFeaturizer):
		nb_channel=1)
		pi_t_tensor += voxelize(
		convert_atom_to_voxel,
		self.voxels_per_edge,
		self.box_width,
		self.voxel_width,
		None,
		@@ -512,7 +505,8 @@ class HydrogenBondVoxelizer(ComplexFeaturizer):
		different voxels interact in a hydrogen bond, the interaction
		is double counted in both voxels.

		Creates a tensor output of shape `(voxels_per_edge, voxels_per_edge,
		Let `voxels_per_edge = int(box_width/voxel_width)`. Creates a
		tensor output of shape `(voxels_per_edge, voxels_per_edge,
		voxels_per_edge, 3)` (assuming the default for `distance_bins` which
		has 3 bins) for each macromolecular the number of hydrogen bonds at
		each voxel.
		@@ -558,7 +552,6 @@ class HydrogenBondVoxelizer(ComplexFeaturizer):
		self.angle_cutoffs = angle_cutoffs
		self.box_width = box_width
		self.voxel_width = voxel_width
		self.voxels_per_edge = int(self.box_width / self.voxel_width)
		self.reduce_to_contacts = reduce_to_contacts

		def _featurize_complex(self, molecular_complex):
		@@ -588,12 +581,9 @@ class HydrogenBondVoxelizer(ComplexFeaturizer):
		frag2_xyz = subtract_centroid(frag2[0], centroid)
		xyzs = [frag1_xyz, frag2_xyz]
		rdks = [frag1[1], frag2[1]]
		#(lig_xyz, lig_rdk), (prot_xyz, prot_rdk) = mol, protein
		#distances = compute_pairwise_distances(prot_xyz, lig_xyz)
		pairwise_features.append(np.concatenate([
		voxelize(
		convert_atom_pair_to_voxel,
		self.voxels_per_edge,
		self.box_width,
		self.voxel_width,
		#None, (prot_xyz, lig_xyz),
		@@ -605,37 +595,5 @@ class HydrogenBondVoxelizer(ComplexFeaturizer):
		self.angle_cutoffs)
		], axis=-1)
		)
		#############################################
		#print("""list(voxelize(
		# convert_atom_pair_to_voxel,
		# self.voxels_per_edge,
		# self.box_width,
		# self.voxel_width,
		# #None, (prot_xyz, lig_xyz),
		# None, xyzs,
		# feature_list=hbond_list,
		# nb_channel=1) for hbond_list in compute_hydrogen_bonds(
		# frag1, frag2,
		# distances, self.distance_bins,
		# self.angle_cutoffs))""")
		#print(list(voxelize(
		# convert_atom_pair_to_voxel,
		# self.voxels_per_edge,
		# self.box_width,
		# self.voxel_width,
		# #None, (prot_xyz, lig_xyz),
		# None, xyzs,
		# feature_list=hbond_list,
		# nb_channel=1) for hbond_list in compute_hydrogen_bonds(
		# frag1, frag2,
		# distances, self.distance_bins,
		# self.angle_cutoffs)))
		#print("compute_hydrogen_bonds(frag1, frag2, distances, self.distance_bins, self.angle_cutoffs)")
		#print(compute_hydrogen_bonds(frag1, frag2, distances, self.distance_bins, self.angle_cutoffs))
		##############################################
		################################################
		#print("pairwise_features")
		#print(pairwise_features)
		################################################
		# Features are of shape (voxels_per_edge, voxels_per_edge, voxels_per_edge, 1) so we should concatenate on the last axis.
		return np.concatenate(pairwise_features, axis=-1)

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