G.mat got an asymmetric sparse matrix

[garyhsu29]

Hello! Thanks for the great great work! I encountered an issue while using nodevectors to train the prone embeddings: I ran G = cg.read_edgelist("..", directed=True, sep=',') g2v = ProNE() g2v.fit(G)

and I got:

ValueError Traceback (most recent call last) Input In [34], in <cell line: 2>() 1 g2v = ProNE() ----> 2 g2v.fit(G)

File ~/miniforge3/envs/alphaA/lib/python3.8/site-packages/nodevectors/prone.py:82, in ProNE.fit(self, graph) 78 G = cg.csrgraph(graph) 79 features_matrix = self.pre_factorization(G.mat, 80 self.n_components, 81 self.exponent) ---> 82 vectors = ProNE.chebyshev_gaussian( 83 G.mat, features_matrix, self.n_components, 84 step=self.step, mu=self.mu, theta=self.theta) 85 self.model = dict(zip(G.nodes(), vectors))

File ~/miniforge3/envs/alphaA/lib/python3.8/site-packages/nodevectors/prone.py:154, in ProNE.chebyshev_gaussian(G, a, n_components, step, mu, theta) 151 return a 152 print(G.shape) --> 154 A = sparse.eye(nnodes) + G 155 DA = preprocessing.normalize(A, norm='l1') 156 # L is graph laplacian

File ~/miniforge3/envs/alphaA/lib/python3.8/site-packages/scipy/sparse/base.py:414, in spmatrix.add(self, other) 412 elif isspmatrix(other): 413 if other.shape != self.shape: --> 414 raise ValueError("inconsistent shapes") 415 return self._add_sparse(other) 416 elif isdense(other):

ValueError: inconsistent shapes

I further check the error and it showed that the G.mat is an asymmetric sparse matrix with shape (830421x830420) Could you please give me any clue on this?