在numpy数组中映射值

Question

How do I go from a 2D numpy array where I only have three distinct values: -1, 0, and 1 and map them to the colors red (255,0,0), green (0,255,0), and blue (255,0,0)? The array is quite large, but to give you an idea of what I am looking for, imagine I have the input

array([[ 1,  0, -1],
       [-1,  1,  1],
       [ 0,  0,  1]])

I want the output:

array([[(0, 0, 255), (0, 255, 0), (255, 0, 0)],
       [(255, 0, 0), (0, 0, 255), (0, 0, 255)],
       [(0, 255, 0), (0, 255, 0), (0, 0, 255)]])

I could for-loop and have conditions but I was wondering if there is a one or two liner using a lambda function that could accomplish this? Thanks!

Answer 1

You might want to consider a structured array, as it allows tuples without the datatype being object .

import numpy as np

replacements = {-1: (255, 0, 0), 0: (0, 255, 0), 1: (0, 0, 255)}

arr = np.array([[ 1,  0, -1],
                [-1,  1,  1],
                [ 0,  0,  1]])

new = np.zeros(arr.shape, dtype=np.dtype([('r', np.int32), ('g', np.int32), ('b', np.int32)]))

for n, tup in replacements.items():
    new[arr == n] = tup

print(new)

Output:

[[(  0,   0, 255) (  0, 255,   0) (255,   0,   0)]
 [(255,   0,   0) (  0,   0, 255) (  0,   0, 255)]
 [(  0, 255,   0) (  0, 255,   0) (  0,   0, 255)]]

---

Another option is using an 3D array, where the last dimension is 3 . The first "layer" would be red, the second "layer" would be green, and the third "layer" blue. This option is compatible with plt.imshow() .

import numpy as np

arr = np.array([[ 1,  0, -1],
                [-1,  1,  1],
                [ 0,  0,  1]])

new = np.zeros((*arr.shape, 3))

for i in range(-1, 2):
    new[i + 1, arr == i] = 255

Output:

array([[[  0.,   0., 255.],
        [255.,   0.,   0.],
        [  0.,   0.,   0.]],

       [[  0., 255.,   0.],
        [  0.,   0.,   0.],
        [255., 255.,   0.]],

       [[255.,   0.,   0.],
        [  0., 255., 255.],
        [  0.,   0., 255.]]])