Numpy bincount to get 2-D array with ones on diagonal and zeors in other places

Numpy

numpy.bincount(x, weights=None, minlength=0)

Return int ndarray .

`x`	Input array of non negative of 1 D
`weight`	(optional ), array of same size of input array. Weight of the elements to be used
`minlength`	Int (optional ), minimum length of bins

Size of the return array

The length of output array is maximum value of input array + 1.If highest value of input array is 5 then there will be 6 elements in output array.

The output array will show number of occurrence of elements starting from 0 to highest value of the input array.

Examples 1

import numpy as np 
ma=np.array([0,2,2,6,5]) 
print(np.bincount(ma))

Output

[1 0 2 0 0 1 1]

If the input array has the highest value of 6, then our output array will have 7 elements. Each element of our output array will show frequency of occurrence of numbers starting from 0 to highest number.

Example 2

Using weight

import numpy as np 
my_array1 = np.array([0,2,2,6,5]) 
my_array2 = np.array([2,2,1,3,4])
my_bin=np.bincount(my_array2,weights=my_array1)
print(my_bin)

Output

[0. 2. 2. 6. 5.]

Example 3

import numpy as np 
my_array1 = np.array([0,2,2,6,5]) 
my_array2 = np.array([2,2,1,3,4])
my_bin=np.bincount(my_array1,my_array2)
print(my_bin)

Output

[2. 0. 3. 0. 0. 4. 3.]

Example 4

import numpy as np 
my_array1 = np.array([0,3,3,5]) 
my_array2 = np.array([2,1,4,6])
my_bin=np.bincount(my_array1,my_array2)
print(my_bin)

Output

[2. 0. 0. 5. 0. 6.]

Numpy ones()

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Numpy bincount()

Size of the return array

Examples 1

Example 2

Example 3

Example 4

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