Which numpy function to choose?

Question

numpy

Good day, there is a task for each element of the array to calculate the gradient in x and y:
Example:
There is a matrix

[10, 20, 30],
[15, 25, 35],
[20, 40, 60]

Accordingly, for the number 25 (in the center), the x gradient will be equal to |35-15| = 20, and for y |20-40|=20
You can implement it yourself in several lines, but maybe there are some functions in numpy that allow you to do this faster?

Answer 1

Well then something like this:

import numpy


if __name__ == '__main__':

    a = numpy.array()

    xdiff = numpy.zeros_like(a)
    xdiff[:, 1:-1] = a[:, 2:]-a[:, :-2]
    print(xdiff)