[FIXED] Paddin new axis in 3d matrix returns error

Issue

What I need to do is to extend a 2D matrix to 3D and fill the 3rd axis with an arbitrary number of zero. The error returned is:

all the input arrays must have same number of dimensions, but the array at index 0 has 3 dimension(s) and the array at index 1 has 0 dimension(s)

What should I correct?

import numpy as np

kernel = np.ones((3,3)) / 9
kernel = kernel[..., None]
print(type(kernel))

print(np.shape(kernel))
print(kernel)

i = 1
for i in range(27):
    np.append(kernel, 0, axis = 2)

print(kernel)

Solution

What should I use instead of np.append()?

Use concatenate():

import numpy as np

kernel = np.ones((3,3)) / 9
kernel = kernel[..., None]
print(type(kernel))

print(np.shape(kernel))
print(kernel)
print('-----------------------------')

append_values = np.zeros((3,3))
append_values = append_values[..., None]
i = 1
for i in range(2):
    kernel = np.concatenate((kernel, append_values), axis=2)

print(kernel.shape)
print(kernel)

But best generate the append_values array already with the required shape in the third dimension to avoid looping:

append_values = np.zeros((3,3,2)) # or (3,3,27)
kernel = np.concatenate((kernel, append_values), axis=2)
print(kernel.shape)
print(kernel)

Answered By - Claudio