numpy.absolute(arr, out = None, ufunc ‘absolute’) : This mathematical function helps user to calculate absolute value of each element. For complex input, a + ib, the absolute value is .
Parameters :
arr : [array_like] Input array or object whose elements, we need to test.
Return :
An array with absolute value of each array.
Code #1 : Working
# Python program explaining # absolute () function import numpy as np arr1 = [ 1 , - 3 , 15 , - 466 ] print ( "Absolute Value of arr1 : \n" , np.absolute(arr1)) arr2 = [ 23 , - 56 ] print ( "\nAbsolute Value of arr2 : \n" , np.absolute(arr2)) |
Output :
Absolute Value of arr1 : [ 1 3 15 466] Absolute Value of arr2 : [23 56]
Code #2 : Working with complex numbers
# Python program explaining # absolute () function import numpy as np a = 4 + 3j print ( "Absolute(4 + 3j) : " , np.absolute(a)) b = 16 + 13j print ( "\nAbsolute value(16 + 13j) : " , np.absolute(b)) |
Output :
Absolute(4 + 3j) : 5.0 Absolute value(16 + 13j) : 20.6155281281
Code #3: Graphical Representation of numpy.absolute()
# Python program explaining # absolute () function import numpy as np import matplotlib.pyplot as plt a = np.linspace(start = - 5 , stop = 5 , num = 6 , endpoint = True ) print ( "Graphical Representation : \n" , np.absolute(a)) plt.title( "blue : with absolute\nred : without absolute" ) plt.plot(a, np.absolute(a)) plt.plot(a, a, color = 'red' ) plt.show() |
Output :
Graphical Representation : [ 5. 3. 1. 1. 3. 5.]
References :
https://docs.scipy.org/doc/numpy-1.13.0/reference/generated/numpy.absolute.html
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