Compute the multiplicative inverse of more than one matrix at once in Python

To compute the (multiplicative) inverse of a matrix, use the numpy.linalg.inv() method in Python. Given a square matrix a, return the matrix ainv satisfying dot(a, ainv) = dot(ainv, a) = eye(a.shape[0]). The method returns (Multiplicative) inverse of the matrix a. The 1st parameter, a is a Matrix to be inverted.

Steps

At first, import the required libraries-

import numpy as np
from numpy.linalg import inv

Create several matrices using array() −

arr = np.array([[[1., 2.], [3., 4.]], [[1, 3], [3, 5]]])

Display the array −

print("Our Array...\n",arr)

Check the Dimensions −

print("\nDimensions of our Array...\n",arr.ndim)

Get the Datatype −

print("\nDatatype of our Array object...\n",arr.dtype)

Get the Shape −

print("\nShape of our Array object...\n",arr.shape)

To compute the (multiplicative) inverse of a matrix, use the numpy.linalg.inv() method in Python −

print("\nResult...\n",np.linalg.inv(arr))

Example

import numpy as np
from numpy.linalg import inv

# Create several matrices using array()
arr = np.array([[[1., 2.], [3., 4.]], [[1, 3], [3, 5]]])

# Display the array
print("Our Array...\n",arr)

# Check the Dimensions
print("\nDimensions of our Array...\n",arr.ndim)

# Get the Datatype
print("\nDatatype of our Array object...\n",arr.dtype)

# Get the Shape
print("\nShape of our Array object...\n",arr.shape)

# To compute the (multiplicative) inverse of a matrix, use the numpy.linalg.inv() method in Python.
print("\nResult...\n",np.linalg.inv(arr))

Output

Our Array...
[[[1. 2.]
[3. 4.]]

[[1. 3.]
[3. 5.]]]

Dimensions of our Array...
3

Datatype of our Array object...
float64

Shape of our Array object...
(2, 2, 2)

Result...
[[[-2. 1. ]
[ 1.5 -0.5 ]]

[[-1.25 0.75]
[ 0.75 -0.25]]]