E.g.

array([[1, 0, 2],

[0, 0, 1],

[3, 1, 2]])

Result should be: [4,1,5]

0 votes

The **sum()** function of Numpy can be used to calculate the sum of a CSR matrix by row or column. Once you have the sum, you can use** **the** flatten()** function to get the result as a list or an array.

Here is an example:

>>> from scipy.sparse import csr_matrix

>>> import numpy as np

>>> row = np.array([0, 0, 1, 2, 2, 2])

>>> col = np.array([0, 2, 2, 0, 1, 2])

>>> data = np.array([1, 2, 1, 3, 1, 2])

>>> X=csr_matrix((data, (row, col)), shape=(3, 3))

>>> X

<3x3 sparse matrix of type '<class 'numpy.int64'>'

with 6 stored elements in Compressed Sparse Row format>

>>> X.toarray()

array([[1, 0, 2],

[0, 0, 1],

[3, 1, 2]])>>> np.array(np.sum(X, axis=0)).flatten()# to sum by column

array([4, 1, 5])

>>> np.array(np.sum(X, axis=1)).flatten()# to sum by row

array([3, 1, 6])