Parameters :
arr: [array_like] Input array or object whose elements, we need to square.
Return:
An array with square value of each array.
Code # 1: Work
# Python program explaining # square () function import numpy as np arr1 = [ 1 , - 3 , 15 , - 466 ] print ( "Square Value of arr1:" , np.square (arr1)) arr2 = [ 23 , - 56 ] print ( "Square Value of arr2:" , np.square (arr2) ) |
Output:
Square Value of arr1: [1 9 225 217156] Square Value of arr2: [529 3136]
Code # 2: Working with Complex Numbers
# Python program explaining # square () function import numpy as np a = 4 + 3j print ( "Square (4 + 3j):" , np.square (a)) b = 16 + 13j print ( " Square value (16 + 13j): " , np.square (b)) |
Output:
Square (4 + 3j): (7 + 24j) Square value (16 + 13j): (87 + 416j)
Code # 3: Graphical representation of numpy.square ()
# Python program explaining # square () function import numpy as np import matplotlib.pyplot as plt a = np.linspace (start = - 5 , stop = 5 , num = 6 , endpoint = True ) print ( " Graphical Representation: " , np.square (a)) plt.title ( "blue: with square red: without square" ) plt.plot (a, np.square (a)) plt.plot (a, a, color = ’red’ ) plt.show () |
Output:
Graphical Representation: [25. 9. 1. 1. 1. 9. 25.]
Links:
https://docs.scipy.org/doc/numpy-1.13.0/reference/generated/numpy.absolute .html
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