sorts.intro_sort

Introspective Sort is a hybrid sort (Quick Sort + Heap Sort + Insertion Sort) if the size of the list is under 16, use insertion sort https://en.wikipedia.org/wiki/Introsort

Attributes

user_input

Functions

heap_sort(→ list)
heapify(→ None)
insertion_sort(→ list)
intro_sort(→ list)
median_of_3(→ int)
partition(→ int)
sort(→ list)

Module Contents

sorts.intro_sort.heap_sort(array: list) → list

>>> heap_sort([4, 2, 6, 8, 1, 7, 8, 22, 14, 56, 27, 79, 23, 45, 14, 12])
[1, 2, 4, 6, 7, 8, 8, 12, 14, 14, 22, 23, 27, 45, 56, 79]
>>> heap_sort([-2, -11, 0, 0, 0, 87, 45, -69, 78, 12, 10, 103, 89, 52])
[-69, -11, -2, 0, 0, 0, 10, 12, 45, 52, 78, 87, 89, 103]
>>> heap_sort(['b', 'd', 'e', 'f', 'g', 'p', 'x', 'z', 'b', 's', 'e', 'u', 'v'])
['b', 'b', 'd', 'e', 'e', 'f', 'g', 'p', 's', 'u', 'v', 'x', 'z']
>>> heap_sort([6.2, -45.54, 8465.20, 758.56, -457.0, 0, 1, 2.879, 1.7, 11.7])
[-457.0, -45.54, 0, 1, 1.7, 2.879, 6.2, 11.7, 758.56, 8465.2]

sorts.intro_sort.heapify(array: list, index: int, heap_size: int) → None

>>> array = [4, 2, 6, 8, 1, 7, 8, 22, 14, 56, 27, 79, 23, 45, 14, 12]
>>> heapify(array, len(array) // 2, len(array))

sorts.intro_sort.insertion_sort(array: list, start: int = 0, end: int = 0) → list

>>> array = [4, 2, 6, 8, 1, 7, 8, 22, 14, 56, 27, 79, 23, 45, 14, 12]
>>> insertion_sort(array, 0, len(array))
[1, 2, 4, 6, 7, 8, 8, 12, 14, 14, 22, 23, 27, 45, 56, 79]
>>> array = [21, 15, 11, 45, -2, -11, 46]
>>> insertion_sort(array, 0, len(array))
[-11, -2, 11, 15, 21, 45, 46]
>>> array = [-2, 0, 89, 11, 48, 79, 12]
>>> insertion_sort(array, 0, len(array))
[-2, 0, 11, 12, 48, 79, 89]
>>> array = ['a', 'z', 'd', 'p', 'v', 'l', 'o', 'o']
>>> insertion_sort(array, 0, len(array))
['a', 'd', 'l', 'o', 'o', 'p', 'v', 'z']
>>> array = [73.568, 73.56, -45.03, 1.7, 0, 89.45]
>>> insertion_sort(array, 0, len(array))
[-45.03, 0, 1.7, 73.56, 73.568, 89.45]

sorts.intro_sort.intro_sort(array: list, start: int, end: int, size_threshold: int, max_depth: int) → list

>>> array = [4, 2, 6, 8, 1, 7, 8, 22, 14, 56, 27, 79, 23, 45, 14, 12]
>>> max_depth = 2 * math.ceil(math.log2(len(array)))
>>> intro_sort(array, 0, len(array), 16, max_depth)
[1, 2, 4, 6, 7, 8, 8, 12, 14, 14, 22, 23, 27, 45, 56, 79]

sorts.intro_sort.median_of_3(array: list, first_index: int, middle_index: int, last_index: int) → int

>>> array = [4, 2, 6, 8, 1, 7, 8, 22, 14, 56, 27, 79, 23, 45, 14, 12]
>>> median_of_3(array, 0, ((len(array) - 0) // 2) + 1, len(array) - 1)
12
>>> array = [13, 2, 6, 8, 1, 7, 8, 22, 14, 56, 27, 79, 23, 45, 14, 12]
>>> median_of_3(array, 0, ((len(array) - 0) // 2) + 1, len(array) - 1)
13
>>> array = [4, 2, 6, 8, 1, 7, 8, 22, 15, 14, 27, 79, 23, 45, 14, 16]
>>> median_of_3(array, 0, ((len(array) - 0) // 2) + 1, len(array) - 1)
14

sorts.intro_sort.partition(array: list, low: int, high: int, pivot: int) → int

>>> array = [4, 2, 6, 8, 1, 7, 8, 22, 14, 56, 27, 79, 23, 45, 14, 12]
>>> partition(array, 0, len(array), 12)
8
>>> array = [21, 15, 11, 45, -2, -11, 46]
>>> partition(array, 0, len(array), 15)
3
>>> array = ['a', 'z', 'd', 'p', 'v', 'l', 'o', 'o']
>>> partition(array, 0, len(array), 'p')
5
>>> array = [6.2, -45.54, 8465.20, 758.56, -457.0, 0, 1, 2.879, 1.7, 11.7]
>>> partition(array, 0, len(array), 2.879)
6

sorts.intro_sort.sort(array: list) → list

Parameters:

collection – some mutable ordered collection with heterogeneous

comparable items inside :return: the same collection ordered by ascending

Examples: >>> sort([4, 2, 6, 8, 1, 7, 8, 22, 14, 56, 27, 79, 23, 45, 14, 12]) [1, 2, 4, 6, 7, 8, 8, 12, 14, 14, 22, 23, 27, 45, 56, 79] >>> sort([-1, -5, -3, -13, -44]) [-44, -13, -5, -3, -1] >>> sort([]) [] >>> sort([5]) [5] >>> sort([-3, 0, -7, 6, 23, -34]) [-34, -7, -3, 0, 6, 23] >>> sort([1.7, 1.0, 3.3, 2.1, 0.3 ]) [0.3, 1.0, 1.7, 2.1, 3.3] >>> sort([‘d’, ‘a’, ‘b’, ‘e’, ‘c’]) [‘a’, ‘b’, ‘c’, ‘d’, ‘e’]

sorts.intro_sort.user_input