Python: Add elements to second axis of numpy array in a loop

Question

This link suggests that we can use a Python list to add elements to it and convert it to numpy array using np.array with unknown length like this:

a = []
for x in y:
    a.append(x)
a = np.array(a)

Let's say x is a numpy.ndarray with shape (h,w) but h and w are unknown, how can we add elements to second axis of ndarray a in a loop to make a becomes (h,w,d) where d is the number of iterations?

I understand we can use dstack to add elements together to become (h,w,d) but I am not too sure how to do this in a loop.

Also play around with np.stack. WIth the default axis value it behaves much like np.array, but you can specify other axis values. — hpaulj
– hpaulj, Commented Dec 12, 2017 at 6:19

tom10 · Accepted Answer · 2017-12-12 05:05:36Z

2

You can do a similar thing, but with x as 2D numpy arrays. That is, if you don't know the number of arrays ahead of time, you can collect them in a list and then convert them to a single 3D array in one step. The code would look very similar to your example:

gen2d = (i*np.ones((2,2)) for i in range(random.randint(1, 10))) # a generator of unknown N

a = []
for x in gen2d:
    a.append(x)
a = np.dstack(a)

a.shape  # (2, 2, 7)

answered Dec 12, 2017 at 5:05

tom10

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