numpy.absolute() in Python

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  \sqrt { a^2 + b^2 }.

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

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# 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))

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Output :

Absolute Value of arr1 : 
 [  1   3  15 466]

Absolute Value of arr2 : 
 [23 56]

 
Code #2 : Working with complex numbers

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# 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))

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Output :

Absolute(4 + 3j) :  5.0

Absolute value(16 + 13j) :  20.6155281281

 
Code #3: Graphical Representation of numpy.absolute()

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# 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()

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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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