Append 元素到每个元素的索引

Question

So basically I want to create a new array for each element and append the coordinates of the element to the original value (so adding the x and y position to the original element):

[ [7,2,4],[1,5,3] ]

then becomes

[ [[0,0,7][0,1,2][0,2,4]],
 [[1,0,1][1,1,5][1,2,3]] ]

I've been looking for different ways to make this work with the axis system in NumPy but I'm probably overseeing some more obvious way.

Answer 1

You can try np.meshgrid to create a grid and then np.stack to combine it with input array:

import numpy as np

a = np.asarray([[7,2,4],[1,5,3]])
result = np.stack(np.meshgrid(range(a.shape[1]), range(a.shape[0]))[::-1] + [a], axis=-1)

Output:

array([[[0, 0, 7],
        [0, 1, 2],
        [0, 2, 4]],

       [[1, 0, 1],
        [1, 1, 5],
        [1, 2, 3]]])

Let me know if it helps.

Answer 2

Without numpy you could use list comprehension:

old_list = [ [7,2,4],[1,5,3] ]
new_list = [ [[i,j,old_list[i][j]] for j in range(len(old_list[i]))] for i in range(old_list) ]

I'd assume that numpy is faster but the sublists are not required to have equal length in this solution.

Answer 3

Another approach using enumerate

In [38]: merge = list()
    ...: for i,j in enumerate(val):
    ...:     merge.append([[i, m, n] for m, n in enumerate(j)])
    ...:

In [39]: merge
Out[39]: [[[0, 0, 7], [0, 1, 2], [0, 2, 4]], [[1, 0, 1], [1, 1, 5], [1, 2, 3]]]

Answer 4

Hope it useful

a = np.array([[7,2,4], [1,5,3]])
idx = np.argwhere(a)
idx = idx.reshape((*(a.shape), -1))
a = np.expand_dims(a, axis=-1)
a = np.concatenate((idx, a), axis=-1)