Skip to content
Related Articles

Related Articles

numpy matrix operations | eye() function
  • Last Updated : 21 Feb, 2019

numpy.matlib.eye() is another function for doing matrix operations in numpy. It returns a matrix with ones on the diagonal and zeros elsewhere.

Syntax : numpy.matlib.eye(n, M=None, k=0, dtype=’float’, order=’C’)

Parameters :
n : [int] Number of rows in the output matrix.
M : [int, optional] Number of columns in the output matrix, defaults is n.
k : [int, optional] Index of the diagonal. 0 refers to the main diagonal, a positive value refers to an upper diagonal, and a negative value to a lower diagonal.Default is 0.
dtype : [optional] Desired output data-type.
order : Whether to store multi-dimensional data in row-major (C-style) or column-major (Fortran-style) order in memory.

Return : A n x M matrix where all elements are equal to zero, except for the k-th diagonal, whose values are equal to one.

Code #1 :



filter_none

edit
close

play_arrow

link
brightness_4
code

# Python program explaining
# numpy.matlib.eye() function
  
# importing matrix library from numpy
import numpy as geek
import numpy.matlib
  
# desired 3 x 3 output matrix 
out_mat = geek.matlib.eye(3, k = 0
print ("Output matrix : ", out_mat) 

chevron_right


Output :

Output matrix :  
[[ 1.  0.  0.]
 [ 0.  1.  0.]
 [ 0.  0.  1.]]

 

Code #2 :

filter_none

edit
close

play_arrow

link
brightness_4
code

# Python program explaining
# numpy.matlib.eye() function
  
# importing numpy and matrix library
import numpy as geek
import numpy.matlib
  
# desired 4 x 5 output matrix 
out_mat = geek.matlib.eye(n = 4, M = 5, k = 1, dtype = int
print ("Output matrix : ", out_mat) 

chevron_right


Output :

Output matrix :  
[[0 1 0 0 0]
 [0 0 1 0 0]
 [0 0 0 1 0]
 [0 0 0 0 1]]

Attention geek! Strengthen your foundations with the Python Programming Foundation Course and learn the basics.

To begin with, your interview preparations Enhance your Data Structures concepts with the Python DS Course.

My Personal Notes arrow_drop_up
Recommended Articles
Page :