Tile rows of a 2D numpy array based on values in separate numpy vector

Question

I have a source array:

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

And a vector that indicates how many times I want to tile each row of the array:

count = array([3, 1, 2])

I want to get:

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

Is there a vectorized/numpy way to achieve this?

Currently I'm using an iterative loop approach and it's horribly slow when len(a) and/or count contains high values.

Stephen Rauch · Accepted Answer · 2017-05-25 05:41:39Z

1

numpy.repeat() is what you are after:

Code:

np.repeat(a, count, axis=0)

Test Code:

import numpy as np

a = np.array([[1, 1, 2, 2],
              [3, 4, 5, 6],
              [7, 7, 7, 8]])

count = np.array([3, 1, 2])

print(np.repeat(a, count, axis=0))

Results:

[[1 1 2 2]
 [1 1 2 2]
 [1 1 2 2]
 [3 4 5 6]
 [7 7 7 8]
 [7 7 7 8]]

answered May 25, 2017 at 5:41

Stephen Rauch♦

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