Finding the Determinant of a Matrix
The determinant of a square matrix is a value derived arithmetically from the coefficients of the matrix. In the linalg module, we use the linalg.det() function to find the determinant of a matrix.
Syntax: scipy.linalg.det(a , overwrite_a , check_finite)
Parameters:
- a: It is a square matrix.
- overwrite_a (Optional): It grants permission to overwrite data in a.
- check_finite (Optional): It checks if the input square matrix consists of only finite numbers.
Returns:
- Floating point value
The scipy.linalg.det takes a square matrix A and returns D, the determinant of A. The determinant is a specific property of the linear transformation of a matrix. The determinant of a 2×2 matrix is given by:
From the above Python code, the determinant is calculated as:
Example:
Python
# Importing the required libraries from scipy import linalg import numpy as np # Initializing the matrix A A = np.array([[9 , 6] , [4 , 5]]) # Finding the determinant of matrix A D = linalg.det(A) print(D) |
Output:
21.0
SciPy Linear Algebra – SciPy Linalg
The SciPy package includes the features of the NumPy package in Python. It uses NumPy arrays as the fundamental data structure. It has all the features included in the linear algebra of the NumPy module and some extended functionality. It consists of a linalg submodule, and there is an overlap in the functionality provided by the SciPy and NumPy submodules.
Let’s discuss some methods provided by the module and its functionality with some examples.