Python Numpy matrix.byteswap() Function

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NumPy Library 

NumPy is a library in python that is created to work efficiently with arrays in python. It is fast, easy to learn, and provides efficient storage. It also provides a better way of handling data for the process. We can create an n-dimensional array in NumPy. To use NumPy simply have to import it into our program and then we can easily use the functionality of NumPy in our program.

NumPy is a Python library that is frequently used for scientific and statistical analysis. NumPy arrays are grids of the same datatype’s values.

Numpy matrix.byteswap() Function:

Using the matrix.byteswap() method, we can swap the bytes position of an element in a specified matrix with one or more dimensions. It would not work on a string or character matrix.

Syntax:

 matrix.byteswap()

Return Value:

The byte swapped matrix is returned by the byteswap() function.

Numpy matrix.byteswap() Function in Python

For 1-Dimensional (1D) Matrix

Approach:

  • Import numpy module using the import keyword
  • Create a matrix(1-Dimensional) using the matrix() function of numpy module by passing some random 1D matrix as an argument to it and store it in a variable
  • Apply byteswap() function on the given matrix to swap the place/position of bytes of an element in a given matrix.
  • Store it in another variable
  • Print the given matrix after byte swapping.
  • The Exit of the Program.

Below is the implementation:

# Import numpy module using the import keyword
import numpy as np
            
# Create a matrix(1-Dimensional) using the matrix() function of numpy module by passing 
# some random 1D matrix as an argument to it and store it in a variable
gvn_matrx = np.matrix('[2, 1, 6, 3]')
            
# Apply byteswap() function on the given matrix to swap the place/position of bytes of an 
# element in a given matrix.
# Store it in another variable
rslt = gvn_matrx.byteswap()
# Print the given matrix after byte swapping.
print("The given matrix after byte swapping:")
print(rslt)

Output:

The given matrix after byte swapping:
[[144115188075855872 72057594037927936 432345564227567616
216172782113783808]]

For 2-Dimensional (2D) Matrix

Approach:

  • Import numpy module using the import keyword
  • Create a matrix(2-Dimensional) using the matrix() function of numpy module by passing some random 2D matrix as an argument to it and store it in a variable
  • Apply byteswap() function on the given matrix to swap the place/position of bytes of an element in a given matrix.
  • Store it in another variable
  • Print the given matrix after byte swapping.
  • The Exit of the Program.

Below is the implementation:

# Import numpy module using the import keyword
import numpy as np
            
# Create a matrix(2-Dimensional) using the matrix() function of numpy module by passing 
# some random 2D matrix as an argument to it and store it in a variable
gvn_matrx = np.matrix('[5, 4; 1, 3]')
            
# Apply byteswap() function on the given matrix to swap the place/position of bytes of an 
# element in a given matrix.
# Store it in another variable
rslt = gvn_matrx.byteswap()
# Print the given matrix after byte swapping.
print("The given matrix after byte swapping:")
print(rslt)

Output:

The given matrix after byte swapping:
[[360287970189639680 288230376151711744]
 [ 72057594037927936 216172782113783808]]