RuntimeError: nnz of the result is too large

[davidfstein]

Traceback:

Traceback (most recent call last):
  File "cluster_network.py", line 19, in <module>
    result = mc.run_mcl(matrix, inflation=inflation)
  File "/home/itan_lab/david/.conda/envs/goflof/lib/python3.7/site-packages/markov_clustering/mcl.py", line 228, in run_mcl
    matrix = iterate(matrix, expansion, inflation)
  File "/home/itan_lab/david/.conda/envs/goflof/lib/python3.7/site-packages/markov_clustering/mcl.py", line 132, in iterate
    matrix = expand(matrix, expansion)
  File "/home/itan_lab/david/.conda/envs/goflof/lib/python3.7/site-packages/markov_clustering/mcl.py", line 51, in expand
    return matrix ** power
  File "/home/itan_lab/david/.conda/envs/goflof/lib/python3.7/site-packages/scipy/sparse/base.py", line 667, in __pow__
    return tmp * tmp
  File "/home/itan_lab/david/.conda/envs/goflof/lib/python3.7/site-packages/scipy/sparse/base.py", line 480, in __mul__
    return self._mul_sparse_matrix(other)
  File "/home/itan_lab/david/.conda/envs/goflof/lib/python3.7/site-packages/scipy/sparse/compressed.py", line 509, in _mul_sparse_matrix
    np.asarray(other.indices, dtype=idx_dtype))
RuntimeError: nnz of the result is too large

Script:

import markov_clustering as mc
import networkx as nx
import pandas as pd

g = nx.Graph()

chem_interactions = pd.read_csv('chemical_chemical.links.v5.0.tsv', sep="\t")

chem_interactions.columns = ['chem1', 'chem2', 'score']

chem_interactions = chem_interactions.query('score > 0')

for index, row in chem_interactions.iterrows():
    g.add_edge(row['chem1'], row['chem2'], weight=float(row['score']))

matrix = nx.to_scipy_sparse_matrix(g)

for inflation in [i / 10 for i in range(15, 26)]:
    result = mc.run_mcl(matrix, inflation=inflation)
    clusters = mc.get_clusters(result)
    Q = mc.modularity(matrix=result, clusters=clusters)
    print("inflation:", inflation, "modularity:", Q)

Any idea whats going wrong here?