Numpy.ndarray: iteration by specific axes of an array

Question

I have a multidimensional array. And I have to iterate via some of its axes. If I needed all axes, I could use nditer, but if I need only the specific ones, I have to do it manually:

my_array = np.arange(3 * 4 * 5).reshape((3, 4, 5))
for i in range(my_array.shape[0]):
    for j in range(my_array.shape[1]):
        print(i, j)
        # Here should be some processing of the 3rd dimension items of the (i,j)

Cannot you advice me a simpler way to do it?

gg349 · Accepted Answer · 2014-05-28 15:41:34Z

1

Consider passing to a single loop, and using ndindex (docs):

my_array = np.arange(3 * 4 * 5).reshape((3, 4, 5))
for ij in np.ndindex(my_array.shape[:2]):
    i,j=ij
    print(i,j)

answered May 28, 2014 at 15:41

gg349

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3 Comments

Felix Over a year ago

Thank you, comrade! It's just what I need. ^__^

hpaulj Over a year ago

np.ndindex uses nditer. np.ndindex((2,3))._it is an nditer instance. Check the code in index_tricks.py for more details.

gg349 Over a year ago

yes, that's where the source of ndindex is (link), and I am not surprised that it uses as_strided. Am I missing your point?

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