Loading deepchem/utils/molecule_graph.py 0 → 100644 +59 −0 Original line number Diff line number Diff line from typing import Optional import numpy as np class MoleculeGraphData(object): """Molecule Graph Data class for sparse pattern""" def __init__(self, node_features: Optional[np.ndarray] = None, edge_index: Optional[np.ndarray] = None, edge_features: Optional[np.ndarray] = None, graph_features: Optional[np.ndarray] = None, y : Optional[np.ndarray] = None,): """ Parameters ---------- node_features : np.ndarray, optional (default None) Node feature matrix with shape [num_nodes, num_node_features] edge_index : np.ndarray, optional (default None) Graph connectivity in COO format with shape [2, num_edges] edge_features : np.ndarray, optional (default None) Edge feature matrix with shape [num_edges, num_edge_features] graph_features : np.ndarray, optional (default None) Graph feature vector with shape [num_graph_features,] y : np.ndarray, optional (default None) Graph or node targets with arbitrary shape """ super(MoleculeGraphData, self).__init__() # validate params if node_features is not None and isinstance(node_features, np.ndarray) is False: raise ValueError('node_features must be np.ndarray or None.') if edge_index is not None: if isinstance(edge_index, np.ndarray) is False: raise ValueError('edge_index must be np.ndarray or None.') elif edge_index.shape[0] != 2: raise ValueError('The shape of edge_index is [2, num_edges].') if edge_features is not None: if instance(edge_features, np.ndarray) is False: raise ValueError('edge_features must be np.ndarray or None.') elif edge_index.shape[1] != edge_features.shape[0]: raise ValueError('The first dimension of edge_features must be the \ same as the second dimension of edge_index.') if graph_features is not None and isinstance(graph_features, np.ndarray) is False: raise ValueError('graph_features must be np.ndarray or None.') if y is not None and isinstance(y, np.ndarray) is False: raise ValueError('y must be np.ndarray or None.') self.node_features = node_features self.edge_index = edge_index self.edge_features = edge_features self.graph_features = graph_features self.y = y self.num_nodes, self.num_node_features = None, None self.num_edges, self.num_edge_features = None, None if self.node_features is not None: self.num_nodes, self.num_node_features = self.node_features.shape if self.node_features is not None: self.num_edges, self.num_edge_features = self.edge_features.shape Loading
deepchem/utils/molecule_graph.py 0 → 100644 +59 −0 Original line number Diff line number Diff line from typing import Optional import numpy as np class MoleculeGraphData(object): """Molecule Graph Data class for sparse pattern""" def __init__(self, node_features: Optional[np.ndarray] = None, edge_index: Optional[np.ndarray] = None, edge_features: Optional[np.ndarray] = None, graph_features: Optional[np.ndarray] = None, y : Optional[np.ndarray] = None,): """ Parameters ---------- node_features : np.ndarray, optional (default None) Node feature matrix with shape [num_nodes, num_node_features] edge_index : np.ndarray, optional (default None) Graph connectivity in COO format with shape [2, num_edges] edge_features : np.ndarray, optional (default None) Edge feature matrix with shape [num_edges, num_edge_features] graph_features : np.ndarray, optional (default None) Graph feature vector with shape [num_graph_features,] y : np.ndarray, optional (default None) Graph or node targets with arbitrary shape """ super(MoleculeGraphData, self).__init__() # validate params if node_features is not None and isinstance(node_features, np.ndarray) is False: raise ValueError('node_features must be np.ndarray or None.') if edge_index is not None: if isinstance(edge_index, np.ndarray) is False: raise ValueError('edge_index must be np.ndarray or None.') elif edge_index.shape[0] != 2: raise ValueError('The shape of edge_index is [2, num_edges].') if edge_features is not None: if instance(edge_features, np.ndarray) is False: raise ValueError('edge_features must be np.ndarray or None.') elif edge_index.shape[1] != edge_features.shape[0]: raise ValueError('The first dimension of edge_features must be the \ same as the second dimension of edge_index.') if graph_features is not None and isinstance(graph_features, np.ndarray) is False: raise ValueError('graph_features must be np.ndarray or None.') if y is not None and isinstance(y, np.ndarray) is False: raise ValueError('y must be np.ndarray or None.') self.node_features = node_features self.edge_index = edge_index self.edge_features = edge_features self.graph_features = graph_features self.y = y self.num_nodes, self.num_node_features = None, None self.num_edges, self.num_edge_features = None, None if self.node_features is not None: self.num_nodes, self.num_node_features = self.node_features.shape if self.node_features is not None: self.num_edges, self.num_edge_features = self.edge_features.shape
