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b6c3fa8992
* fix endless loop bug, divide 0 bug and update description fix an endless bug, for example, if collection = [10,30,40,45,50,66,77,93], item = 67. fix divide 0 bug, when right=left it is not OK to point = left + ((item - sorted_collection[left]) * (right - left)) // (sorted_collection[right] - sorted_collection[left]) update 'sorted' to 'ascending sorted' in description to avoid confusion * delete swap files * delete 'address' and add input validation
49 lines
1.5 KiB
Python
49 lines
1.5 KiB
Python
import random
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"""
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A python implementation of the quick select algorithm, which is efficient for calculating the value that would appear in the index of a list if it would be sorted, even if it is not already sorted
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https://en.wikipedia.org/wiki/Quickselect
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"""
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def _partition(data, pivot):
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"""
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Three way partition the data into smaller, equal and greater lists,
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in relationship to the pivot
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:param data: The data to be sorted (a list)
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:param pivot: The value to partition the data on
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:return: Three list: smaller, equal and greater
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"""
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less, equal, greater = [], [], []
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for element in data:
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if element < pivot:
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less.append(element)
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elif element > pivot:
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greater.append(element)
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else:
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equal.append(element)
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return less, equal, greater
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def quickSelect(list, k):
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#k = len(list) // 2 when trying to find the median (index that value would be when list is sorted)
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#invalid input
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if k>=len(list) or k<0:
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return None
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smaller = []
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larger = []
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pivot = random.randint(0, len(list) - 1)
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pivot = list[pivot]
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count = 0
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smaller, equal, larger =_partition(list, pivot)
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count = len(equal)
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m = len(smaller)
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#k is the pivot
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if m <= k < m + count:
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return pivot
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# must be in smaller
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elif m > k:
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return quickSelect(smaller, k)
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#must be in larger
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else:
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return quickSelect(larger, k - (m + count)) |