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 :

Python3

# 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)

Output :

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

Code #2 :

Python3

# 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)

Output :

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

numpy matrix operations | identity() function

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numpy matrix operations | eye() function

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