A special number that can be calculated from a square matrix is known as the Determinant of a square matrix. The Numpy provides us the feature to calculate the determinant of a square matrix using numpy.linalg.det() function.
Syntax:
numpy.linalg.det(array)
Example 1: Calculating Determinant of a 2X2 Numpy matrix using numpy.linalg.det() function
Python3
# importing Numpy package import numpy as np # creating a 2X2 Numpy matrix n_array = np.array([[ 50 , 29 ], [ 30 , 44 ]]) # Displaying the Matrix print ( "Numpy Matrix is:" ) print (n_array) # calculating the determinant of matrix det = np.linalg.det(n_array) print ( "\nDeterminant of given 2X2 matrix:" ) print ( int (det)) |
Output:
In the above example, we calculate the Determinant of the 2X2 square matrix.
Example 2: Calculating Determinant of a 3X3 Numpy matrix using numpy.linalg.det() function
Python3
# importing Numpy package import numpy as np # creating a 3X3 Numpy matrix n_array = np.array([[ 55 , 25 , 15 ], [ 30 , 44 , 2 ], [ 11 , 45 , 77 ]]) # Displaying the Matrix print ( "Numpy Matrix is:" ) print (n_array) # calculating the determinant of matrix det = np.linalg.det(n_array) print ( "\nDeterminant of given 3X3 square matrix:" ) print ( int (det)) |
Output:
In the above example, we calculate the Determinant of the 3X3 square matrix.
Example 3: Calculating Determinant of a 5X5 Numpy matrix using numpy.linalg.det() function
Python3
# importing Numpy package import numpy as np # creating a 5X5 Numpy matrix n_array = np.array([[ 5 , 2 , 1 , 4 , 6 ], [ 9 , 4 , 2 , 5 , 2 ], [ 11 , 5 , 7 , 3 , 9 ], [ 5 , 6 , 6 , 7 , 2 ], [ 7 , 5 , 9 , 3 , 3 ]]) # Displaying the Matrix print ( "Numpy Matrix is:" ) print (n_array) # calculating the determinant of matrix det = np.linalg.det(n_array) print ( "\nDeterminant of given 5X5 square matrix:" ) print ( int (det)) |
Output:
In the above example, we calculate the Determinant of the 5X5 square matrix.