python - Find the index of the n smallest values in a 3 dimensional numpy array -


given 3 dimensional numpy array, how find indexes of top n smallest values ? index of minimum value can found as: 

i,j,k = np.where(my_array == my_array.min())

here's 1 approach generic n-dims , generic n smallest numbers -

def smallestn_indices(a, n):     idx = a.ravel().argsort()[:n]     return np.stack(np.unravel_index(idx, a.shape)).t

each row of the 2d output array hold indexing tuple corresponds 1 of smallest array numbers.

we can use argpartition, might not maintain order. so, need bit more additional work argsort there -

def smallestn_indices_argparitition(a, n, maintain_order=false):     idx = np.argpartition(a.ravel(),n)[:n]     if maintain_order:         idx = idx[a.ravel()[idx].argsort()]     return np.stack(np.unravel_index(idx, a.shape)).t

sample run -

in [141]: np.random.seed(1234)      ...: = np.random.randint(111,999,(2,5,4,3))      ...:   in [142]: smallestn_indices(a, n=3) out[142]:  array([[0, 3, 2, 0],        [1, 2, 3, 0],        [1, 2, 2, 1]])  in [143]: smallestn_indices_argparitition(a, n=3) out[143]:  array([[1, 2, 3, 0],        [0, 3, 2, 0],        [1, 2, 2, 1]])  in [144]: smallestn_indices_argparitition(a, n=3, maintain_order=true) out[144]:  array([[0, 3, 2, 0],        [1, 2, 3, 0],        [1, 2, 2, 1]])

runtime test -

in [145]: = np.random.randint(111,999,(20,50,40,30))  in [146]: %timeit smallestn_indices(a, n=3)      ...: %timeit smallestn_indices_argparitition(a, n=3)      ...: %timeit smallestn_indices_argparitition(a, n=3, maintain_order=true)      ...:  10 loops, best of 3: 97.6 ms per loop 100 loops, best of 3: 8.32 ms per loop 100 loops, best of 3: 8.34 ms per loop

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