numpy-逐行标准化

Question

I've been working on a matrix normalization problem, stated as:

Given a matrix M, normalize its elements such that each element is divided with the corresponding column sum if element is not 0.

cwsums = np.sum(class_matrix,axis=1)
cwsums = np.reciprocal(cwsums.astype(np.float32))
cwsums[cwsums == np.inf] = 0
## this is the problem
final_matrix = np.multiply(final_matrix, cwsums)

I can construct a reciprocal mask, which I would like to apply accross the matrix, as an elementwise product, yet I can't seem to get it right. Thank you!

Answer 1

(Addressing edited question) Looks like you meant to sum across rows using axis=0 :

i = 1 / class_matrix.sum(axis=0)
i[~np.isfinite(i)] = 0

class_matrix *= i