decagon-pytorch/src/decagon_pytorch/normalize.py

import numpy as np
import scipy.sparse as sp


def normalize_adjacency_matrix(self, adj):
    adj = sp.coo_matrix(adj)
    if adj.shape[0] == adj.shape[1]:
        adj_ = adj + sp.eye(adj.shape[0])
        rowsum = np.array(adj_.sum(1))
        degree_mat_inv_sqrt = sp.diags(np.power(rowsum, -0.5).flatten())
        adj_normalized = adj_.dot(degree_mat_inv_sqrt).transpose().dot(degree_mat_inv_sqrt).tocoo()
    else:
        rowsum = np.array(adj.sum(1))
        colsum = np.array(adj.sum(0))
        rowdegree_mat_inv = sp.diags(np.nan_to_num(np.power(rowsum, -0.5)).flatten())
        coldegree_mat_inv = sp.diags(np.nan_to_num(np.power(colsum, -0.5)).flatten())
        adj_normalized = rowdegree_mat_inv.dot(adj).dot(coldegree_mat_inv).tocoo()
    return preprocessing.sparse_to_tuple(adj_normalized)