With the help of Numpy matrix.transpose()
method, we can find the transpose of the matrix by using the matrix.transpose()
method in Python.
Numpy matrix.transpose() Syntax
Syntax :
matrix.transpose()
Parameter: No parameters; transposes the matrix it is called on.
Return : Return transposed matrix
What is Numpy matrix.transpose()?
`numpy.matrix.transpose()` is a function in the NumPy library that computes the transpose of a matrix. It swaps the rows and columns of the matrix, effectively reflecting it along its main diagonal. The function is called on a NumPy matrix object, and it does not take any parameters. The result is a new matrix representing the transposed version of the original matrix.
NumPy Matrix transpose() – Transpose of an Array in Python
There are numerous examples of `numpy.matrix.transpose()`. Here, we illustrate commonly used instances of `numpy.matrix.transpose()` for clarity.
- Matrix Transformation
- Matrix Multiplication
NumPy Matrix Transformation
Example 1: In this example, the code uses the NumPy library to create a 2×3 matrix. It then calculates the transpose of the original matrix using the `transpose()` function. Finally, it prints both the original and transposed matrices to the console.
import numpy as np
# Original matrix original_matrix = np.matrix([[ 1 , 2 , 3 ], [ 4 , 5 , 6 ]])
# Transposed matrix transposed_matrix = original_matrix.transpose()
print ( "Original Matrix:" )
print (original_matrix)
print ( "\nTransposed Matrix:" )
print (transposed_matrix)
|
Output:
Original Matrix: [[1 2 3] [4 5 6]] Transposed Matrix: [[1 4] [2 5] [3 6]]
Example 2: In this example This Python code uses the NumPy library to create a 3×3 matrix named ‘gfg’. It then applies the transpose() method to the matrix and assigns the result to ‘geek’. Finally, it prints the transposed matrix ‘geek’.
# import the important module in python import numpy as np
# make matrix with numpy gfg = np.matrix( '[4, 1, 9; 12, 3, 1; 4, 5, 6]' )
# applying matrix.transpose() method geek = gfg.transpose()
print (geek)
|
Output:
[[ 4 12 4]
[ 1 3 5]
[ 9 1 6]]
Transpose of an Array Like Object
In this example code uses NumPy to create two 2×2 matrices, `matrix_a` and `matrix_b`. It then transposes `matrix_b` using the `transpose()` function and performs matrix multiplication between `matrix_a` and the transposed `matrix_b`. The result is printed to the console.
import numpy as np
# Matrices for multiplication matrix_a = np.matrix([[ 1 , 2 ], [ 3 , 4 ]])
matrix_b = np.matrix([[ 5 , 6 ], [ 7 , 8 ]])
# Transpose one matrix before multiplication result = matrix_a * matrix_b.transpose()
print ( "Result of Matrix Multiplication:" )
print (result)
|
Output:
Result of Matrix Multiplication:
[[17 23]
[39 53]]