Numpy iterating over 3d vector array

Question

Im trying to iterate over a Numpy Array that contains 3d numpy arrays (3d vectors) inside it. Something like this:

import numpy as np


Matrix = np.zeros(shape=(10, 3))
# => [
    [0,0,0],
    [0,0,0],
    ...
    [0,0,0]
]

I need to iterate over it, getting each 3d Vector. In pseudo code:

for vector in Matrix
    print vector #=> [0,0,0]

Is there any Numpy native way of doing this? What is the fastest way of doing this?

Thanks!

Fran

Terminology note: a 3D numpy array is one whose shape has 3 elements. For example, np.zeros([3, 4, 5]) would be a 3D array. — user2357112
– user2357112, Commented May 20, 2014 at 20:16

user2357112 · Accepted Answer · 2014-05-20 20:17:56Z

2

Your pseudocode is only missing a colon:

for vector in matrix:
    print vector

That said, you will generally want to avoid explicit iteration over a NumPy array. Take advantage of broadcasted operations and NumPy built-in functions as much as possible; it moves the loops into C instead of interpreted Python, and it tends to produce shorter code, too.

answered May 20, 2014 at 20:17

user2357112

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3 Comments

franleplant Over a year ago

Hi! Thanks for answer. Is there any Numpy way of doing this? Like for example with nditer?

user2357112 Over a year ago

@plant: nditer wouldn't simplify your code or make it run faster; it'd just be unnecessary complication. The NumPy way of doing it would be to not use a loop at all and figure out how to get broadcasting and built-in functions to do the job, but if you really want a loop, this is how you would do it.

franleplant Over a year ago

That's a very good clear question. So i'll look into broadcasting. Thanks!

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