import random
"""
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
https://en.wikipedia.org/wiki/Quickselect
"""
def _partition(data, pivot):
"""
Three way partition the data into smaller, equal and greater lists,
in relationship to the pivot
:param data: The data to be sorted (a list)
:param pivot: The value to partition the data on
:return: Three list: smaller, equal and greater
"""
less, equal, greater = [], [], []
for element in data:
if element.address < pivot.address:
less.append(element)
elif element.address > pivot.address:
greater.append(element)
else:
equal.append(element)
return less, equal, greater
def quickSelect(list, k):
#k = len(list) // 2 when trying to find the median (index that value would be when list is sorted)
smaller = []
larger = []
pivot = random.randint(0, len(list) - 1)
pivot = list[pivot]
count = 0
smaller, equal, larger =_partition(list, pivot)
count = len(equal)
m = len(smaller)
#k is the pivot
if m <= k < m + count:
return pivot
# must be in smaller
elif m > k:
return quickSelect(smaller, k)
#must be in larger
else:
return quickSelect(larger, k - (m + count))