Time for action – inverting matrices
The inverse of a matrix A
in linear algebra is the matrix A-1
, which, when multiplied with the original matrix, is equal to the identity matrix I
. This can be written as follows:
A A-1 = I
The inv()
function in the numpy.linalg
package can invert an example matrix with the following steps:
- Create the example matrix with the
mat()
function we used in the previous chapters:A = np.mat("0 1 2;1 0 3;4 -3 8") print("A\n", A)
The
A
matrix appears as follows:A [[ 0 1 2] [ 1 0 3] [ 4 -3 8]]
- Invert the matrix with the
inv()
function:inverse = np.linalg.inv(A) print("inverse of A\n", inverse)
The inverse matrix appears as follows:
inverse of A [[-4.5 7. -1.5] [-2. 4. -1. ] [ 1.5 -2. 0.5]]
Tip
If the matrix is singular, ...
Get NumPy : Beginner's Guide - Third Edition now with the O’Reilly learning platform.
O’Reilly members experience books, live events, courses curated by job role, and more from O’Reilly and nearly 200 top publishers.