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-Algorithm implementing QuickSort Algorithm where the pivot element is chosen randomly between first and last elements of the array and the array elements are taken from a Standard Normal Distribution.
-
-This is different from the ordinary quicksort in the sense, that it applies more to real life problems , where elements usually follow a normal distribution. Also the pivot is randomized to make it a more generic one.
-
-
-#Array Elements
-
-The array elements are taken from a Standard Normal Distribution , having mean = 0 and standard deviation 1.
-
-The code
-
-```python
-
->>> import numpy as np 
->>> from tempfile import TemporaryFile
->>> outfile = TemporaryFile()    
->>> p = 100 # 100 elements are to be sorted
->>> mu, sigma = 0, 1 # mean and standard deviation
->>> X = np.random.normal(mu, sigma, p)
->>> np.save(outfile, X)
->>> print('The array is')
->>> print(X)
-
-```
-
----------------------
-
-#Plotting the function for Checking 'The Number of Swappings' taking place between Normal Distribution QuickSort and Ordinary QuickSort 
-
-```python
->>>import matplotlib.pyplot as plt
-
-    # Normal Disrtibution is red
->>> plt.plot([1,2,4,16,32,64,128,256,512,1024,2048],[1,1,6,15,43,136,340,800,2156,6821,16325],linewidth=2, color='r')
-                                                                                      #Simple QuickSort is green
->>> plt.plot([1,2,4,16,32,64,128,256,512,1024,2048],[1,1,4,16,67,122,362,949,2131,5086,12866],linewidth=2, color='g')
->>> plt.show()
-```