scikit_coo_to_csr.py

import numpy as np
from numpy import array
from scipy.sparse import coo_matrix

row = np.array([82, 8, 56, 86, 48, 20, 22, 98, 65, 98])
col = np.array([80, 13, 51, 74, 16, 40, 64, 57, 40, 30])
data = np.array([0.6805822, 0.23116356, 0.8527678, 0.3512172, 0.03575957, 0.2307719, 0.6499588, 0.66925836, 0.8698123, 0.041548133])

coo = coo_matrix((data, (row, col)), shape=(100, 100))

>>> csr.indices
array([13, 40, 64, 16, 51, 40, 80, 74, 30, 57], dtype=int32)
>>> csr.data
array([ 0.23116356,  0.2307719 ,  0.6499588 ,  0.03575957,  0.8527678 ,
        0.8698123 ,  0.6805822 ,  0.3512172 ,  0.04154813,  0.66925836])
>>> csr.indptr
array([ 0,  0,  0,  0,  0,  0,  0,  0,  0,  1,  1,  1,  1,  1,  1,  1,  1,
        1,  1,  1,  1,  2,  2,  3,  3,  3,  3,  3,  3,  3,  3,  3,  3,  3,
        3,  3,  3,  3,  3,  3,  3,  3,  3,  3,  3,  3,  3,  3,  3,  4,  4,
        4,  4,  4,  4,  4,  4,  5,  5,  5,  5,  5,  5,  5,  5,  5,  6,  6,
        6,  6,  6,  6,  6,  6,  6,  6,  6,  6,  6,  6,  6,  6,  6,  7,  7,
        7,  7,  8,  8,  8,  8,  8,  8,  8,  8,  8,  8,  8,  8, 10, 10], dtype=int32)
     
>>> csr.indptr.size
101

https://github.com/scipy/scipy/blob/11b1ebe4f4dd8c605501dad17fb416f006231442/scipy/sparse/sparsetools/coo.h#L34