numpy.diag(a, k=0) : Extracts and construct a diagonal array
Parameters :
a : array_like k : [int, optional, 0 by default] Diagonal we require; k>0 means diagonal above main diagonal or vice versa.
Returns :
ndarray
Python
# Python Programming illustrating # numpy.diag method import numpy as geek # matrix creation by array input a = geek.matrix([[ 1 , 21 , 30 ], [ 63 , 434 , 3 ], [ 54 , 54 , 56 ]]) print ( "Main Diagonal elements : \n" , geek.diag(a), "\n" ) print ( "Diagonal above main diagonal : \n" , geek.diag(a, 1 ), "\n" ) print ( "Diagonal below main diagonal : \n" , geek.diag(a, - 1 )) |
Output :
Main Diagonal elements : [ 1 434 56] Diagonal above main diagonal : [21 3] Diagonal below main diagonal : [63 54]
References :
https://docs.scipy.org/doc/numpy/reference/generated/numpy.diagflat.html#numpy.diagflat
Note :
These NumPy-Python programs won’t run on online IDE’s, so run them on your systems to explore them
.
This article is contributed by Mohit Gupta_OMG 😀. If you like Lazyroar and would like to contribute, you can also write an article using write.geeksforgeeks.org or mail your article to review-team@geeksforgeeks.org. See your article appearing on the Lazyroar main page and help other Geeks.
Please write comments if you find anything incorrect, or you want to share more information about the topic discussed above.