Numpy eye to get array with ones on diagonal and zeors in other places

numpy.eye(N, M=None, k=0, dtype=, order='C')

Return ndarray ( N, M ) shape.

`N`	Int, number of rows
`M`	Int (optional ), number of columns ( default is equal to N )
`k`	Int (optional ), default is 0,Position of diagonal, Positive value for upper and negative for lower diagonal
`dtype`	data-type( Optional ), Data Type of returned array.
`order`	{'C','F'} Optional, how the output is to be stored. C- style or Fortan style


Shape: (3, 4) Dimension 2	Shape: (4, 3) Dimension 2

Using N and M

import numpy as np
my_data=np.eye(3)
print(my_data)

Output, we used N=3 here, so default value of M is also 3.

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

Let us use different value for M

my_data=np.eye(4,M=3)

Output

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

Using k

We can use k to change the postion of diagonal. Try with positive value of key

my_data=np.eye(4,k=2)

Output

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

Let us try with negative value of k

my_data=np.eye(4,k=-1)

Output

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

dtype

We will try to return string dtype

my_data=np.eye(4,dtype=str)

Output

[['1' '' '' '']
 ['' '1' '' '']
 ['' '' '1' '']
 ['' '' '' '1']]

dtype=float

my_data=np.eye(4,dtype=float)

Output

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

Numpy ones() bincount() arange() linspace()

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Numpy eye()

Using N and M

Using k

dtype

Subhendu Mohapatra