Merge pull request #4 from GreeleyGroup/enh/graphs

ENH: Add AtomsGraph class to create graph representation of selected atoms in a slab

.gitignore

@@ -0,0 +1 @@
+*POSCAR*

src/graphs.py

@@ -0,0 +1,119 @@
+"""Classes to create bulk, surface, and adsorbate graphs."""
+
+import abc
+
+import networkx as nx
+import numpy as np
+from ase.neighborlist import build_neighbor_list
+
+
+class AtomsGraph:
+    """Create graph representation of a collection of atoms."""
+
+    def __init__(self, atoms, select_idx, max_atoms=50):
+        """Initialize variables of the class.
+
+        Parameters
+        ----------
+        atoms: ase.Atoms object
+            Atoms object containing all the atoms in the slab
+        select_idx: list or np.ndarray
+            List of indices of atoms that are to be included in the graph
+        neighbor_list: ase.neighborlist.NeighborList object
+            Neighbor list that defines bonds between atoms
+        max_atoms: int (default = 50)
+            The maximum number of atoms in the graph. Graphs that have fewer
+            atoms are padded with 0s to reach this value.
+        """
+        # Save parameters
+        self.atoms = atoms
+        self.select_idx = select_idx
+        self.max_atoms = max_atoms
+
+        # Create graph
+        self.create_graph()
+
+    def create_graph(self):
+        """Create a graph from an atoms object and neighbor_list."""
+        # Create neighbor list of atoms
+        self.neighbor_list = build_neighbor_list(
+            self.atoms, bothways=True, self_interaction=False
+        )
+
+        # Create NetworkX Multigraph
+        graph = nx.MultiGraph()
+
+        # Iterate over selected atoms and add them as nodes
+        for atom in self.atoms:
+            if atom.index in self.select_idx and atom.index not in list(graph.nodes()):
+                graph.add_node(
+                    atom.index,
+                    atomic_number=atom.number,
+                    symbol=atom.symbol,
+                    position=atom.position,
+                )
+
+        # Iterate over nodes, identify neighbors, and add edges between them
+        for n in graph.nodes():
+            # Get neighbors from neighbor list
+            neighbor_idx, _ = self.neighbor_list.get_neighbors(n)
+            # Iterate over neighbors
+            for nn in neighbor_idx:
+                # If neighbor is not in graph, add it as a node
+                if not graph.has_node(nn):
+                    graph.add_node(
+                        nn,
+                        atomic_number=self.atoms[nn].number,
+                        symbol=self.atoms[nn].symbol,
+                        position=self.atoms[nn].position,
+                    )
+                # Calculate bond distance
+                bond_dist = np.linalg.norm(
+                    graph.nodes[n].position - graph.nodes[nn].position
+                )
+                graph.add_edge(n, nn, bond_distance=bond_dist)
+
+        # Assign graph object
+        self.graph = graph
+
+    def featurize(self, node_featurizer, bond_featurizer):
+        """Featurize nodes and edges of the graph.
+
+        Parameters
+        ----------
+        node_featurizer: TODO
+            Object that featurizes atoms
+        bond_featurizer: TODO
+            Object that featurizes bonds
+        """
+        pass
+
+    def plot(self, filename=None):
+        """Plot the graph using NetworkX.
+
+        Parameters
+        ----------
+        filename: str (optional)
+            If provided, the plot is saved with the given filename.
+        """
+        pass
+
+    def get_node_tensor(self):
+        """Get the node matrix of the graph as a PyTorch Tensor.
+
+        Returns
+        -------
+        node_matrix: torch.Tensor
+            Node matrix
+        """
+        pass
+
+    def get_edge_tensor(self):
+        """Get the edge matrix of the graph as a PyTorch Tensor.
+
+        Returns
+        -------
+        edge_matrix: torch.Tensor
+            Edge tensor
+        """
+        pass