what is the fastest way to fill every row in 2d array that contains all zeros with different value.
Only the rows that all contain Zero..
the only idea I have is a loop and using np.all() to check every row
array([[2, 6, 9, 7, 0],
[0, 0, 0, 0, 0],
[3, 8, 5, 4, 7]])
array([[2, 6, 9, 7, 0],
[1, 1, 1, 1, 1],
[3, 8, 5, 4, 7]])
Well, if this is sufficient:
a = np.array([[2, 6, 9, 7, 0],
[0, 0, 0, 0, 0],
[3, 8, 5, 4, 7]])
a[~a.any(axis=1)] = 1
Slight note: I use ~np.any(...) instead of np.all(a==0) because the a array is larger than the boolean array returned by all or any. The a==0 creates a 2D boolean array. Negating the 1D boolean array created by any requires less work and memory.