NumPy identity() function

The numpy.matlib.identity() function is used to return an identity matrix of the given size. Let us understand the concept of identity matrix first.

An Identity matrix is a matrix with all the diagonal elements initialized to 1 and rest all other elements to zero.

Syntax of matlib.identity():

The required syntax to use this function is as follows:

numpy.matlib.identity(n, dtype)

Parameters:

Let us now cover the parameters used with this function:

  • n
    This parameter is used to indicate the size of the returned identity matrix.
  • dtype
    This parameter is used to indicate the data type of the matrix. The default value of this parameter is float.

Returned Values:

This method will return a n x n matrix with its main diagonal elements set to one, and all other elements set to zero.

Example 1:

Below we have a basic example for this method:

import numpy as np  
import numpy.matlib  
  
a = numpy.matlib.identity(4)
print("The Identity matrix as output is :")
print(a)


The Identity matrix as output is :
[[1. 0. 0. 0.]
[0. 1. 0. 0.]
[0. 0. 1. 0.]
[0. 0. 0. 1.]]

Example 2:

Given below is a basic example where we will mention the dtype for the elements of the array

import numpy as np  
import numpy.matlib  
  
a = numpy.matlib.identity(6, dtype = int)
print("The Identity matrix as an output is :")
print(a)


The Identity matrix as an output is :
[[1 0 0 0 0 0]
[0 1 0 0 0 0]
[0 0 1 0 0 0]
[0 0 0 1 0 0]
[0 0 0 0 1 0]
[0 0 0 0 0 1]]

Difference between identity() and eye():

There is a difference between identity() and the Numpy eye() function and that is identity function returns a square matrix having ones on the main diagonal like this;

while the eye() function returns a matrix having 1 on the diagonal and 0 elsewhere, which is based on the value of K parameter. If value of K > 0 then it implies the diagonal above main diagonal and vice-versa

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