Loading deepchem/feat/molecule_featurizers/mol_graph_conv_featurizer.py +3 −3 Original line number Diff line number Diff line Loading @@ -79,9 +79,9 @@ class MolGraphConvFeaturizer(MolecularFeaturizer): to modify return values of `construct_atom_feature` or `construct_bond_feature`. The default node representation are constructed by concatenating the following values, and the feature length is 38. and the feature length is 39. - Atom type: A one-hot vector of this atom, "C", "N", "O", "F", "P", "S", "Br", "I", "other atoms". - Atom type: A one-hot vector of this atom, "C", "N", "O", "F", "P", "S", "Cl", "Br", "I", "other atoms". - Chirality: A one-hot vector of the chirality, "R" or "S". - Formal charge: Integer electronic charge. - Partial charge: Calculated partial charge. Loading Loading @@ -111,7 +111,7 @@ class MolGraphConvFeaturizer(MolecularFeaturizer): >>> type(out[0]) <class 'deepchem.feat.graph_data.GraphData'> >>> out[0].num_node_features 38 39 >>> out[0].num_edge_features 11 Loading deepchem/feat/tests/test_mol_graph_conv_featurizer.py +4 −4 Original line number Diff line number Diff line Loading @@ -13,13 +13,13 @@ class TestMolGraphConvFeaturizer(unittest.TestCase): # assert "C1=CC=CN=C1" assert graph_feat[0].num_nodes == 6 assert graph_feat[0].num_node_features == 38 assert graph_feat[0].num_node_features == 39 assert graph_feat[0].num_edges == 12 assert graph_feat[0].num_edge_features == 11 # assert "O=C(NCc1cc(OC)c(O)cc1)CCCC/C=C/C(C)C" assert graph_feat[1].num_nodes == 22 assert graph_feat[1].num_node_features == 38 assert graph_feat[1].num_node_features == 39 assert graph_feat[1].num_edges == 44 assert graph_feat[1].num_edge_features == 11 Loading @@ -31,12 +31,12 @@ class TestMolGraphConvFeaturizer(unittest.TestCase): # assert "C1=CC=CN=C1" assert graph_feat[0].num_nodes == 6 assert graph_feat[0].num_node_features == 38 assert graph_feat[0].num_node_features == 39 assert graph_feat[0].num_edges == 12 + 6 assert graph_feat[0].num_edge_features == 11 # assert "O=C(NCc1cc(OC)c(O)cc1)CCCC/C=C/C(C)C" assert graph_feat[1].num_nodes == 22 assert graph_feat[1].num_node_features == 38 assert graph_feat[1].num_node_features == 39 assert graph_feat[1].num_edges == 44 + 22 assert graph_feat[1].num_edge_features == 11 deepchem/models/torch_models/gat.py +6 −6 Original line number Diff line number Diff line Loading @@ -48,7 +48,7 @@ class GAT(nn.Module): def __init__( self, in_node_dim: int = 38, in_node_dim: int = 39, hidden_node_dim: int = 64, heads: int = 4, dropout: float = 0.0, Loading @@ -59,8 +59,8 @@ class GAT(nn.Module): """ Parameters ---------- in_node_dim: int, default 38 The length of the initial node feature vectors. The 38 is in_node_dim: int, default 39 The length of the initial node feature vectors. The 39 is based on `MolGraphConvFeaturizer`. hidden_node_dim: int, default 64 The length of the hidden node feature vectors. Loading Loading @@ -152,7 +152,7 @@ class GATModel(TorchModel): """ def __init__(self, in_node_dim: int = 38, in_node_dim: int = 39, hidden_node_dim: int = 64, heads: int = 4, dropout: float = 0.0, Loading @@ -165,8 +165,8 @@ class GATModel(TorchModel): Parameters ---------- in_node_dim: int, default 38 The length of the initial node feature vectors. The 38 is in_node_dim: int, default 39 The length of the initial node feature vectors. The 39 is based on `MolGraphConvFeaturizer`. hidden_node_dim: int, default 64 The length of the hidden node feature vectors. Loading deepchem/utils/molecule_feature_utils.py +1 −0 Original line number Diff line number Diff line Loading @@ -24,6 +24,7 @@ DEFAULT_ATOM_TYPE_SET = [ "F", "P", "S", "Cl", "Br", "I", ] Loading deepchem/utils/test/test_molecule_feature_utils.py +3 −3 Original line number Diff line number Diff line Loading @@ -33,15 +33,15 @@ class TestGraphConvUtils(unittest.TestCase): atoms = self.mol.GetAtoms() assert atoms[0].GetSymbol() == "C" one_hot = get_atom_type_one_hot(atoms[0]) assert one_hot == [1.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0] assert one_hot == [1.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0] # check unknown atoms atoms = self.mol_copper_sulfate.GetAtoms() assert atoms[0].GetSymbol() == "Cu" one_hot = get_atom_type_one_hot(atoms[0]) assert one_hot == [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 1.0] assert one_hot == [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 1.0] one_hot = get_atom_type_one_hot(atoms[0], include_unknown_set=False) assert one_hot == [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0] assert one_hot == [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0] # check original set atoms = self.mol.GetAtoms() Loading Loading
deepchem/feat/molecule_featurizers/mol_graph_conv_featurizer.py +3 −3 Original line number Diff line number Diff line Loading @@ -79,9 +79,9 @@ class MolGraphConvFeaturizer(MolecularFeaturizer): to modify return values of `construct_atom_feature` or `construct_bond_feature`. The default node representation are constructed by concatenating the following values, and the feature length is 38. and the feature length is 39. - Atom type: A one-hot vector of this atom, "C", "N", "O", "F", "P", "S", "Br", "I", "other atoms". - Atom type: A one-hot vector of this atom, "C", "N", "O", "F", "P", "S", "Cl", "Br", "I", "other atoms". - Chirality: A one-hot vector of the chirality, "R" or "S". - Formal charge: Integer electronic charge. - Partial charge: Calculated partial charge. Loading Loading @@ -111,7 +111,7 @@ class MolGraphConvFeaturizer(MolecularFeaturizer): >>> type(out[0]) <class 'deepchem.feat.graph_data.GraphData'> >>> out[0].num_node_features 38 39 >>> out[0].num_edge_features 11 Loading
deepchem/feat/tests/test_mol_graph_conv_featurizer.py +4 −4 Original line number Diff line number Diff line Loading @@ -13,13 +13,13 @@ class TestMolGraphConvFeaturizer(unittest.TestCase): # assert "C1=CC=CN=C1" assert graph_feat[0].num_nodes == 6 assert graph_feat[0].num_node_features == 38 assert graph_feat[0].num_node_features == 39 assert graph_feat[0].num_edges == 12 assert graph_feat[0].num_edge_features == 11 # assert "O=C(NCc1cc(OC)c(O)cc1)CCCC/C=C/C(C)C" assert graph_feat[1].num_nodes == 22 assert graph_feat[1].num_node_features == 38 assert graph_feat[1].num_node_features == 39 assert graph_feat[1].num_edges == 44 assert graph_feat[1].num_edge_features == 11 Loading @@ -31,12 +31,12 @@ class TestMolGraphConvFeaturizer(unittest.TestCase): # assert "C1=CC=CN=C1" assert graph_feat[0].num_nodes == 6 assert graph_feat[0].num_node_features == 38 assert graph_feat[0].num_node_features == 39 assert graph_feat[0].num_edges == 12 + 6 assert graph_feat[0].num_edge_features == 11 # assert "O=C(NCc1cc(OC)c(O)cc1)CCCC/C=C/C(C)C" assert graph_feat[1].num_nodes == 22 assert graph_feat[1].num_node_features == 38 assert graph_feat[1].num_node_features == 39 assert graph_feat[1].num_edges == 44 + 22 assert graph_feat[1].num_edge_features == 11
deepchem/models/torch_models/gat.py +6 −6 Original line number Diff line number Diff line Loading @@ -48,7 +48,7 @@ class GAT(nn.Module): def __init__( self, in_node_dim: int = 38, in_node_dim: int = 39, hidden_node_dim: int = 64, heads: int = 4, dropout: float = 0.0, Loading @@ -59,8 +59,8 @@ class GAT(nn.Module): """ Parameters ---------- in_node_dim: int, default 38 The length of the initial node feature vectors. The 38 is in_node_dim: int, default 39 The length of the initial node feature vectors. The 39 is based on `MolGraphConvFeaturizer`. hidden_node_dim: int, default 64 The length of the hidden node feature vectors. Loading Loading @@ -152,7 +152,7 @@ class GATModel(TorchModel): """ def __init__(self, in_node_dim: int = 38, in_node_dim: int = 39, hidden_node_dim: int = 64, heads: int = 4, dropout: float = 0.0, Loading @@ -165,8 +165,8 @@ class GATModel(TorchModel): Parameters ---------- in_node_dim: int, default 38 The length of the initial node feature vectors. The 38 is in_node_dim: int, default 39 The length of the initial node feature vectors. The 39 is based on `MolGraphConvFeaturizer`. hidden_node_dim: int, default 64 The length of the hidden node feature vectors. Loading
deepchem/utils/molecule_feature_utils.py +1 −0 Original line number Diff line number Diff line Loading @@ -24,6 +24,7 @@ DEFAULT_ATOM_TYPE_SET = [ "F", "P", "S", "Cl", "Br", "I", ] Loading
deepchem/utils/test/test_molecule_feature_utils.py +3 −3 Original line number Diff line number Diff line Loading @@ -33,15 +33,15 @@ class TestGraphConvUtils(unittest.TestCase): atoms = self.mol.GetAtoms() assert atoms[0].GetSymbol() == "C" one_hot = get_atom_type_one_hot(atoms[0]) assert one_hot == [1.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0] assert one_hot == [1.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0] # check unknown atoms atoms = self.mol_copper_sulfate.GetAtoms() assert atoms[0].GetSymbol() == "Cu" one_hot = get_atom_type_one_hot(atoms[0]) assert one_hot == [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 1.0] assert one_hot == [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 1.0] one_hot = get_atom_type_one_hot(atoms[0], include_unknown_set=False) assert one_hot == [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0] assert one_hot == [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0] # check original set atoms = self.mol.GetAtoms() Loading
