To compute the multiplicative inverse of a matrix object with 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 an array −
arr = np.array([[ 5, 10], [ 15, 20 ]])
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 object with matrix(), use the numpy.linalg.inv() method in Python −
print("\nResult...\n",np.linalg.inv(np.matrix(arr)))
Example
import numpy as np from numpy.linalg import inv # Create an array arr = np.array([[ 5, 10], [ 15, 20 ]]) # 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 object with matrx(), use the numpy.linalg.inv() method in Python. print("\nResult...\n",np.linalg.inv(np.matrix(arr)))
Output
Our Array... [[ 5 10] [15 20]] Dimensions of our Array... 2 Datatype of our Array object... int64 Shape of our Array object... (2, 2) Result... [[-0.4 0.2] [ 0.3 -0.1]]