0

I have numpy array like:

x = np.array([
 ...
 [[0, 0, 0, 0],
 [0, 1, 1, 0],
 [0, 1, 1, 0],
 [0, 0, 0, 0]]
 ...
])

with shape (4800, 4, 4).

So i need to replace every 0 with [1, 1, 2] and every 1 with [5, 5, 9]

Result should be like this:

[[[1, 1, 2], [1, 1, 2], [1, 1, 2], [1, 1, 2]],
[[1, 1, 2], [5, 5, 9], [5, 5, 9], [1, 1, 2]],
[[1, 1, 2], [5, 5, 9], [5, 5, 9], [1, 1, 2]],
[[1, 1, 2], [1, 1, 2], [1, 1, 2], [1, 1, 2]]]

How do I do this?

asked Oct 20, 2022 at 14:03

2 Answers 2

3

Take advantage of the fact that you have 0 and 1, define a mapper array and index it:

 # 0 1
mapper = np.array([[1, 1, 2], [5, 5, 9]])
out = mapper[a]

output:

array([[[[1, 1, 2],
 [1, 1, 2],
 [1, 1, 2],
 [1, 1, 2]],
 [[1, 1, 2],
 [5, 5, 9],
 [5, 5, 9],
 [1, 1, 2]],
 [[1, 1, 2],
 [5, 5, 9],
 [5, 5, 9],
 [1, 1, 2]],
 [[1, 1, 2],
 [1, 1, 2],
 [1, 1, 2],
 [1, 1, 2]]]])
answered Oct 20, 2022 at 14:15
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1

You can create a new array and assign the values according to the value in the old one.

import numpy as np
x = np.array([
 [[0, 0, 0, 0],
 [0, 1, 1, 0],
 [0, 1, 1, 0],
 [0, 0, 0, 0]]
])
x_new = np.zeros((*(x.shape), 3))
x_new[x==0] = [1, 1, 2]
x_new[x==1] = [5, 5, 9]
print(x_new)

This results in the following output:

[[[[1. 1. 2.]
 [1. 1. 2.]
 [1. 1. 2.]
 [1. 1. 2.]]
 [[1. 1. 2.]
 [5. 5. 9.]
 [5. 5. 9.]
 [1. 1. 2.]]
 [[1. 1. 2.]
 [5. 5. 9.]
 [5. 5. 9.]
 [1. 1. 2.]]
 [[1. 1. 2.]
 [1. 1. 2.]
 [1. 1. 2.]
 [1. 1. 2.]]]]
answered Oct 20, 2022 at 14:17

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