Numpy pad zeroes of given size

Question

I have read most related questions here, but I cannot seem to figure out how to use np.pad in this case. Maybe it is not meant for this particular problem.

Let's say I have a list of Numpy arrays. Every array is the same length, e.g. 2. The list itself has to be padded to be e.g. 5 arrays and can be transformed into a numpy array as well. The padded elements should be arrays filled with zeroes. As an example

arr = [array([0, 1]), array([1, 0]), array([1, 1])]
expected_output = array([array([0, 1]), array([1, 0]), array([1, 1]), array([0, 0]), array([0, 0])])

The following seems to work, but I feel there must be a better and more efficient way. In reality this is run hundreds of thousands if not millions of times so speed is important. Perhaps with np.pad?

import numpy as np

def pad_array(l, item_size, pad_size=5):
  s = len(l)

  if s < pad_size:
    zeros = np.zeros(item_size)
    for _ in range(pad_size-s):
      # not sure if I need a `copy` of zeros here?
      l.append(zeros)

  return np.array(l)

B = [np.array([0,1]), np.array([1,0]), np.array([1,1])]
AB = pad_array(B, 2)

print(AB)

@DanielMesejo It is. (Shape 1xn.) I'm not sure why that's important, nor why you deleted your answer as that seemed fine. (Even though it could use some more explanation.) — Bram Vanroy, Feb 11 '19 at 13:03
What should happen if pad_size is less than the length of the input list? — Dani Mesejo, Feb 11 '19 at 13:05
In reality that cannot happen because pad_size is derived from the input data. So in such a case, just return the np.array variant. — Bram Vanroy, Feb 11 '19 at 13:06
For what are you using the `item_size` parameter? If all arrays are of the same size, you can get rid of that and just use the length of the first array like `zeros = np.zeros(len(l[0]))` here. — Teshan Shanuka J, Feb 11 '19 at 16:03

score 2 · Answer 1 · answered Feb 11 '19 at 13:39

It seems like you want to pad zeros at the end of the axis 0, speaking in numpy terms. So what you need is,

output = numpy.pad(arr, ((0,2),(0,0)), 'constant')

The trick is the pad_width parameter, which you need to specify as pad_width=((0,2),(0,0)) to get your expected output. This is you telling pad() to insert 0 padding at the beginning and 2 padding at the end of the axis 0, and to insert 0 padding at the beginning and 0 padding at the end of the axis 1. The format of pad_width is ((before_1, after_1), … (before_N, after_N)) according to the documentation

mode='constant' tells pad() to pad with the value specified by parameter constant_values which defaults to 0.

Dani Mesejo · Accepted Answer · 2019-02-11T13:11:07.223

You could re-write your function like this:

import numpy as np


def pad_array(l, item_size, pad_size=5):

    if pad_size < len(l):
        return np.array(l)

    s = len(l)
    res = np.zeros((pad_size, item_size))  # create an array of (item_size, pad_size)
    res[:s] = l  # set the first rows equal to the elements of l

    return res


B = [np.array([0, 1]), np.array([1, 0]), np.array([1, 1])]
AB = pad_array(B, 2)

print(AB)

Output

[[0. 1.]
 [1. 0.]
 [1. 1.]
 [0. 0.]
 [0. 0.]]

The idea is to create an array of zeroes and then fill the first rows with the values from the input list.

Numpy pad zeroes of given size

2 Answers2