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# Author: OMKAR PATHAK
# Created On: 31st July 2017
# Best O(nlog(n)); Average O(nlog(n)); Worst O(nlog(n))
# heap sort algorithm
def sort(List):
heapify(List) # create the heap
end = len(List) - 1
while end > 0:
List[end], List[0] = List[0], List[end]
shiftDown(List, 0, end - 1)
end -= 1
return List
def heapify(List):
''' This function helps to maintain the heap property '''
# start = (len(List) - 2) // 2 (faster execution)
start = len(List) // 2
while start >= 0:
shiftDown(List, start, len(List) - 1)
start -= 1
def shiftDown(List, start, end):
root = start
while root * 2 + 1 <= end:
child = root * 2 + 1
# right child exists and is greater than left child
if child + 1 <= end and List[child] < List[child + 1]:
child += 1
# if child is greater than root(parent), then swap their positions
if child <= end and List[root] < List[child]:
List[root], List[child] = List[child], List[root]
root = child
else:
return
# time complexities
def time_complexities():
return '''Best Case: O(nlogn), Average Case: O(nlogn), Worst Case: O(nlogn)'''
# easily retrieve the source code of the sort function
def get_code():
import inspect
return inspect.getsource(sort)