numpy.square() in Python – Tutorial
Python numpy.square() function returns a new array with the element value as the square of the source array elements. The source array remains unchanged.
Python numpy.square() Examples
It’s a utility function to quickly get the square of the matrix elements. Let’s look at the examples of numpy square() function with integer, float, and complex type array elements.
1. numpy.square() int array
import numpy as np
# ints
array_2d = np.array([[1, 2, 3], [4, 5, 6]])
print(f'Source Array:\n{array_2d}')
array_2d_square = np.square(array_2d)
print(f'Squared Array:\n{array_2d_square}')
Output:
Source Array:
[[1 2 3]
[4 5 6]]
Squared Array:
[[ 1 4 9]
[16 25 36]]
2. numpy square() floating point array
import numpy as np
array_2d_float = np.array([1.2, 2.3, 5])
print(f'Source Array:\n{array_2d_float}')
array_2d_float_square = np.square(array_2d_float)
print(f'Squared Array:\n{array_2d_float_square}')
Output:
Source Array:
[1.2 2.3 5. ]
Squared Array:
[ 1.44 5.29 25. ]
Notice that the integer in the floating-point array has been converted to a floating-point number.
3. numpy.square() complex numbers array
arr = np.array([1 + 2j, 2 + 3j, 4])
print(f'Source Array:\n{arr}')
arr_square = np.square(arr)
print(f'Squared Array:\n{arr_square}')
Output:
Source Array:
[1.+2.j 2.+3.j 4.+0.j]
Squared Array:
[-3. +4.j -5.+12.j 16. +0.j]
