I want to find the index of the largest element in each row and column of a CSR matrix. What function should I use?

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The **argmax()** function of csr_matrix can be used to find the index of the largest element in each row and column of a CSR matrix. You need to use the argument "axis" to specify row and column.

axis=0 means "for each column which row has the max value"

axis=1 means "for each row which column has the max value"

Here is an example:

>>> import numpy as np

>>> from scipy.sparse import csr_matrix

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

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

>>> data = np.array([1, 2, 5, 3, 1, 4])

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

>>> X.toarray()

array([[1, 0, 2],

[0, 0, 5],

[3, 1, 4]])>>> X.argmax(axis=0)

matrix([[2, 2, 1]])>>> X.argmax(axis=1)

matrix([[2],

[2],

[2]])

>>>