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68 lines
1.4 KiB
Python
68 lines
1.4 KiB
Python
from __future__ import print_function
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from random import randint
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from tempfile import TemporaryFile
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import numpy as np
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import math
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def _inPlaceQuickSort(A,start,end):
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count = 0
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if start<end:
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pivot=randint(start,end)
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temp=A[end]
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A[end]=A[pivot]
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A[pivot]=temp
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p,count= _inPlacePartition(A,start,end)
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count += _inPlaceQuickSort(A,start,p-1)
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count += _inPlaceQuickSort(A,p+1,end)
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return count
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def _inPlacePartition(A,start,end):
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count = 0
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pivot= randint(start,end)
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temp=A[end]
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A[end]=A[pivot]
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A[pivot]=temp
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newPivotIndex=start-1
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for index in range(start,end):
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count += 1
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if A[index]<A[end]:#check if current val is less than pivot value
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newPivotIndex=newPivotIndex+1
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temp=A[newPivotIndex]
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A[newPivotIndex]=A[index]
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A[index]=temp
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temp=A[newPivotIndex+1]
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A[newPivotIndex+1]=A[end]
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A[end]=temp
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return newPivotIndex+1,count
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outfile = TemporaryFile()
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p = 100 # 1000 elements are to be sorted
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mu, sigma = 0, 1 # mean and standard deviation
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X = np.random.normal(mu, sigma, p)
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np.save(outfile, X)
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print('The array is')
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print(X)
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outfile.seek(0) # using the same array
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M = np.load(outfile)
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r = (len(M)-1)
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z = _inPlaceQuickSort(M,0,r)
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print("No of Comparisons for 100 elements selected from a standard normal distribution is :")
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print(z)
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