zero_safe_normalization.py

import numpy as np
import sys

def zero_safe_normalization(a):
    norms = np.sum(a*a, axis=1)
    zero_indices = np.nonzero(norms == 0)[0].tolist()
    if zero_indices:
        sys.stderr.write('Detect %d zero norms: %s\n' %(len(zero_indices), str(zero_indices)))
        norms[zero_indices] = 1.0 # don't worry, 0/1 = 0
    a /= norms[:,np.newaxis]

if __name__ == '__main__':
    test_matrix = np.random.rand(10, 5)
    test_matrix[7] = 0.0
    zero_safe_normalization(test_matrix)
    print(test_matrix)