Week covered:

- THE MASTER METHOD
- QUICKSORT - ALGORITHM
- QUICKSORT - ANALYSIS

**Programming assignment:**
The file contains all of the integers between 1 and 10,000 (inclusive, with no repeats) in unsorted order. Your task is to compute the total number of comparisons used to sort the given input file by QuickSort.

The file contains all of the integers between 1 and 10,000 (inclusive, with no repeats) in unsorted order. The integer in the ith row of the file gives you the ith entry of an input array.

Your task is to compute the total number of comparisons used to sort the given input file by QuickSort. As you know, the number of comparisons depends on which elements are chosen as pivots, so we'll ask you to explore three different pivoting rules. You should not count comparisons one-by-one. Rather, when there is a recursive call on a subarray of length m, you should simply add m−1 to your running total of comparisons. (This is because the pivot element is compared to each of the other m−1 elements in the subarray in this recursive call.)

WARNING: The Partition subroutine can be implemented in several different ways, and different implementations can give you differing numbers of comparisons. For this problem, you should implement the Partition subroutine exactly as it is described in the video lectures (otherwise you might get the wrong answer).

DIRECTIONS FOR THIS PROBLEM:

For the first part of the programming assignment, you should always use the first element of the array as the pivot element.

HOW TO GIVE US YOUR ANSWER: Type the numeric answer in the space provided.

import os def quick_sort (arr): def swap(l, a,b): temp = l[a] l[a] = l[b] l[b] = temp return l def find_median(x): candi = sorted([x[0],x[-1],x[int(ceil(len(x)/2.))-1]])[1] return swap(x, 0, x.index(candi)) if len(arr)==0 or len(arr)==1: return arr arr = find_median(arr) pivot = arr[0] i = 1 for j in range(i,len(arr)): if arr[j]<pivot: arr = swap(arr, i, j) i += 1 i -= 1 arr = swap(arr, 0, i) return quick_sort(arr[:i])+[arr[i]]+quick_sort(arr[i+1:]) from math import ceil def quick_sort_count (arr, index, median=False): def swap(l, a,b): temp = l[a] l[a] = l[b] l[b] = temp return l def find_median(x): candi = sorted([x[0],x[-1],x[int(ceil(len(x)/2.))-1]])[1] return swap(x, 0, x.index(candi)) if len(arr)==0 or len(arr)==1: return arr, 0 if index != 0: arr = swap(arr, index, 0) if median: arr = find_median(arr) pivot = arr[0] i = 1 for j in range(i,len(arr)): if arr[j]<pivot: arr = swap(arr, i, j) i += 1 arr = swap(arr, 0, i-1) arr[:i-1], t1 = quick_sort_count(arr[:i-1], index, median) arr[i:], t2 = quick_sort_count(arr[i:], index, median) return arr, len(arr)+t1+t2-1 def test (l): from random import shuffle x=range(l) # Test the quick_sort_count # a = [0, 9, 8, 7, 6, 5, 4, 3, 2, 1] # b = [0, 1, 2, 3, 4, 5, 6, 7, 8, 9] # c = [1, 11, 5, 15, 2, 12, 9, 99, 77, 0] # d = [999, 3, 2, 98, 765, 8, 14, 15, 16, 88, 145, 100] # e = [1, 11, 5, 15, 2, 999, 3, 2, 98, 765, 8, 14, 15, 16, 88, 145, 100, 12, 9, 99, 77, 0] # arr, result = quick_sort_count(x, -1) # print "The overall comparison # is ", result # # arr, result = quick_sort_count(a, -1) # print "The overall comparison # is ", result # arr, result = quick_sort_count(b, -1) # print "The overall comparison # is ", result # arr, result = quick_sort_count(c, -1) # print "The overall comparison # is ", result # arr, result = quick_sort_count(d, -1) # print "The overall comparison # is ", result # arr, result = quick_sort_count(e, -1) # print "The overall comparison # is ", result # Test the quick_sort shuffle(x) print "The original data set is ", x print "The sorted array is ", quick_sort(x) if __name__ == "__main__": test(20) def run_quicksort (arr, index, median): _,result = quick_sort_count(arr, index, median) print result def main (): arr = [] #sent_file = open("D:\Python27\algoQUICKSORT.txt",) sent_file = open("algoQUICKSORT.txt") with sent_file as datafile: for row in datafile: arr.append(int(row)) # Because the quick_sort is in-place sorting, # arr should be duplicated for different pivot choices arr2 = list(arr) arr3 = list(arr) _,result = quick_sort_count(arr, 0) print "Assign the 1st element as pivot:", result _,result = quick_sort_count(arr2, -1) print "Assign the last element as pivot:", result _,result = quick_sort_count(arr3, 0, True) print "Assign the 'median' element as pivot:", result if __name__=="__main__": main()

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