Efficient way to normalize a Scipy Sparse Matrix

Question

I\'d like to write a function that normalizes the rows of a large sparse matrix (such that they sum to one).

from pylab import *
import scipy.sparse as sp

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Answer 1

This has been implemented in scikit-learn sklearn.preprocessing.normalize.

from sklearn.preprocessing import normalize
w_normalized = normalize(w, norm='l1', axis=1)

axis=1 should normalize by rows, axis=0 to normalize by column. Use the optional argument copy=False to modify the matrix in place.