HackerRank Python Solution - Numpy Topic - Eye and Identity

Identity:

The identity tool returns an identity array. An identity array is a square matrix with all the main diagonal elements as 1 and the rest as 0. The default type of element is float.

import numpy
print numpy.identity(3) #3 is for  dimension 3 X 3

#Output
[[ 1.  0.  0.]
 [ 0.  1.  0.]
 [ 0.  0.  1.]]

Eye:

The eye tool returns a 2-D array with 1's as the diagonal and 0's elsewhere. The diagonal can be main, upper, or lower depending on the optional parameter k. A positive k is for the upper diagonal, a negative k is for the lower, and a 0 k (default) is for the main diagonal.

import numpy
print numpy.eye(8, 7, k = 1)    # 8 X 7 Dimensional array with first upper diagonal 1.

#Output
[[ 0.  1.  0.  0.  0.  0.  0.]
 [ 0.  0.  1.  0.  0.  0.  0.]
 [ 0.  0.  0.  1.  0.  0.  0.]
 [ 0.  0.  0.  0.  1.  0.  0.]
 [ 0.  0.  0.  0.  0.  1.  0.]
 [ 0.  0.  0.  0.  0.  0.  1.]
 [ 0.  0.  0.  0.  0.  0.  0.]
 [ 0.  0.  0.  0.  0.  0.  0.]]

print numpy.eye(8, 7, k = -2)   # 8 X 7 Dimensional array with second lower diagonal 1.

Task:

Your task is to print an array of size N x M with its main diagonal elements as 1's and 0's everywhere else.

Note:

In order to get alignment correct, please insert the line numpy.set_printoptions(legacy='1.13') below the numpy import. 

Input Format:

A single line containing the space-separated values of N and M.

N denotes the rows. 

M denotes the columns. 

Output Format:

Print the desired N x M array.

Sample Input:

3 3

Sample Output:

[[ 1.  0.  0.]
 [ 0.  1.  0.]
 [ 0.  0.  1.]]

Solution:

import numpy

numpy.set_printoptions(legacy='1.13')

n,m = map(int,input().split())

print (numpy.eye(n,m,k=0))

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