Python matrix multiplication 3d Array

Question

I tried to solve a PDE numerically and in the course of this I faced the problem of a triple-nested for loop resembling the 3 spatial dimension. This construct is nested in another time loop, so you can imagine that the computing takes forever for sufficient large node numbers. The code block looks like this

    for jy in range(0,cy-1):
        for jx in range(0,cx-1):
            for jz in range(0,cz-1):
                T[n+1,jx,jy,jz] = T[n,jx,jy,jz] + s*(T[n,jx-1,jy,jz] - 2*T[n,jx,jy,jz] + T[n,jx+1,jy,jz]) + s*(T[n,jx,jy-1,jz] - 2*T[n,jx,jy,jz] + T[n,jx,jy+1,jz]) + s*(T[n,jx,jy,jz-1] - 2*T[n,jx,jy,jz] + T[n,jx,jy,jz+1])

It might look intimidating at first, but is quite easy. I have a 3 dimensional matrix representing a solid bulk material, where each point represents the current temperature. The iteratively calculated next temperature at each point is calculated taking into account each point next to that point - so 6 in total. In the case of a 1-dimensional solid the solution is just a simple matrix multiplication. Is there any chance to represent the 3-loop-system above in a simple matrix solution like in the 1D case?

Best regards!

Look at https://stackoverflow.com/questions/22473053/itertools-equivalent-of-nested-loop-for-x-in-xs-for-y-in-ys — Andrej Kesely, Jul 26 '18 at 20:45

score 0 · Answer 1 · answered Jul 26 '18 at 21:51

0

With numpy you can easily do these kinds of matrix operations,

e.g for a 3x3 matrix

import numpy as np

T = np.random.random((3,3,3))

T = T*T - 2*T ... etc.

answered Jul 26 '18 at 21:51

anonMouse

41
5

score 0 · Answer 2 · answered Jul 27 '18 at 01:55

First off, you need to be a bit more careful with your terminology. A "matrix" is a 2-Dimensional array of numbers. So you are really talking about an array. Numpy, or better yet Scipy, has an data type called an ndarray. You need to be very careful manipulating them, because although they are sometimes used to represent matrices, there are operations that can be performed on 2-D arrays that are not mathematically legal for matrices.

I strongly recommend you use @ and not * to perform multiplication of 1- or 2-D matrices, and be sure to add code to check that the operations you are doing are legal mathematically. As a trivial example, Python lets you add a 1 x n or an n x 1 vector to an n x n matrix, even though that is not mathematically correct. The reason it allows it is, as intimated above, because there is no true matrix type in Python.

It very well may be that you can reformulate your problem to use a 3-D array, and by experimentation find the particular operation you are trying to perform. Just keep in mind that the rules of linear algebra are only casually applied in Python.

Python matrix multiplication 3d Array

2 Answers2