Solve linear equation in python XA = B

Question

A linear equation XA = B, we know the 'X = B * inv(A)'. where A, B, X are all matrix.

in the matlab it can be solve:

X = B / A

it avoid doing inverse a matrix which is fast. is there any equal form in python using numpy?

Can't you just do `x = b * 1/a`? Or am I just really bad at this — wanderer0810, Oct 15 '18 at 23:59
sorry for the confusion, they are all matrix, I will update them — jason, Oct 16 '18 at 00:00
I am afraid there is no such function in numpy. see http://mathesaurus.sourceforge.net/matlab-numpy.html. — Heaven, Oct 16 '18 at 00:03
Good resource, is there any way we can solve `XA = B` in python? — jason, Oct 16 '18 at 00:06
Have you seen [this related](https://stackoverflow.com/questions/1007442/mrdivide-function-in-matlab-what-is-it-doing-and-how-can-i-do-it-in-python)? — jedwards, Oct 16 '18 at 00:12

score 2 · Accepted Answer · answered Oct 16 '18 at 00:10

2

Use numpy linalg.inv function:

import numpy as np
x = np.matmul(b, np.linalg.inv(a))

answered Oct 16 '18 at 00:10

Osman Mamun

cool. it has same result as matlab. – jason Oct 16 '18 at 00:15
2

@jason it may give the same answer, but it will take a lot longer due to inverting `a` if `a` is large. Look into using `np.linalg.solve(a, b)` (or `np.linalg.lstsq(a, b)` if `a` is not linearly independent) instead. These do a similar short circuit to `MATLAB` without doing the full inverse. – Daniel F Oct 16 '18 at 06:29

score 0 · Answer 2 · answered Oct 16 '18 at 00:15

0

import numpy as np
a = np.array([[1,7],[2,9]])
b = np.array([[2,6],[7,5]])

# XA = B
# X = BA^-1

x = np.matmul(b,np.linalg.inv(a))

answered Oct 16 '18 at 00:15

César Rodriguez

While this code may answer the question, providing additional context regarding how and/or why it solves the problem would improve the answer's long-term value. – Nic3500 Oct 16 '18 at 03:35

2 Answers2