How to unpack nested numpy.ndarray?

Question

Suppose I have a numpy array e constructed as follow:

import numpy as np
a = np.array([1,2])
b = np.array([3,4])
c = np.array([5,6])
d = np.array([7,8])
e = np.empty((2,2), dtype=object)

e[0,0] = a
e[0,1] = b
e[1,0] = c
e[1,1] = d

>>> e
array([[array([1, 2]), array([3, 4])],
   [array([5, 6]), array([7, 8])]], dtype=object)

I don't know how to unpack the array e so that it becomes:

array([[1, 2, 3, 4],
   [5, 6, 7, 8]])

Any hint is appreciated.

Building an array like that e array in the first place is usually a mistake. Consider changing the code that produces e. — user2357112
– user2357112, Commented Jun 26, 2020 at 7:59
hello ito. I think what you're trying to do is "flatten" arrays which contain multiple arrays into one. You can use the + sign to combine two arrays, or checkout an existing stackoverflow question about flattening nested arrays. — c8999c 3f964f64
– c8999c 3f964f64, Commented Jun 26, 2020 at 8:18
@c8999c3f964f64 Adding two numpy arrays will try to broadcast them to compatible shapes, and add them elementwise. You cannot concatenate numpy arrays using +. — Jan Christoph Terasa
– Jan Christoph Terasa, Commented Jun 26, 2020 at 8:22
I was thinking of array([1, 2] + [3, 4]), are you sure this wouldnt work in numpy? sry for assuming otherwise! — c8999c 3f964f64
– c8999c 3f964f64, Commented Jun 26, 2020 at 8:27
@c8999c3f964f64 array([1,2] + [3,4]) is manipulation of lists not numpy.ndarrays. It works differently than array([1,2]) + array([3,4]) — Chris
– Chris, Commented Jun 26, 2020 at 8:55

Chris · Accepted Answer · 2020-06-26 08:12:41Z

4

Use numpy.block:

e = np.block([[a,b],[c,d]])
print(e)

Output:

array([[1, 2, 3, 4],
       [5, 6, 7, 8]])

answered Jun 26, 2020 at 8:12

Chris

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1 Comment

Jan Christoph Terasa Over a year ago

That is very nice. Looks like useful syntactic sugar for my convoluted vstack + hstack method.

Jan Christoph Terasa · Accepted Answer · 2020-06-26 08:08:31Z

1

You need to stack your arrays properly:

import numpy as np
a = np.array([1,2])
b = np.array([3,4])
c = np.array([5,6])
d = np.array([7,8])
e = np.vstack((np.hstack((a, b)), np.hstack((c, d))))

answered Jun 26, 2020 at 8:08

Jan Christoph Terasa

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