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193 lines
6.3 KiB
Python
193 lines
6.3 KiB
Python
"""
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Introspective Sort is a hybrid sort (Quick Sort + Heap Sort + Insertion Sort)
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if the size of the list is under 16, use insertion sort
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https://en.wikipedia.org/wiki/Introsort
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"""
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import math
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def insertion_sort(array: list, start: int = 0, end: int = 0) -> list:
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"""
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>>> array = [4, 2, 6, 8, 1, 7, 8, 22, 14, 56, 27, 79, 23, 45, 14, 12]
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>>> insertion_sort(array, 0, len(array))
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[1, 2, 4, 6, 7, 8, 8, 12, 14, 14, 22, 23, 27, 45, 56, 79]
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>>> array = [21, 15, 11, 45, -2, -11, 46]
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>>> insertion_sort(array, 0, len(array))
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[-11, -2, 11, 15, 21, 45, 46]
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>>> array = [-2, 0, 89, 11, 48, 79, 12]
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>>> insertion_sort(array, 0, len(array))
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[-2, 0, 11, 12, 48, 79, 89]
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>>> array = ['a', 'z', 'd', 'p', 'v', 'l', 'o', 'o']
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>>> insertion_sort(array, 0, len(array))
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['a', 'd', 'l', 'o', 'o', 'p', 'v', 'z']
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>>> array = [73.568, 73.56, -45.03, 1.7, 0, 89.45]
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>>> insertion_sort(array, 0, len(array))
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[-45.03, 0, 1.7, 73.56, 73.568, 89.45]
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"""
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end = end or len(array)
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for i in range(start, end):
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temp_index = i
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temp_index_value = array[i]
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while temp_index != start and temp_index_value < array[temp_index - 1]:
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array[temp_index] = array[temp_index - 1]
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temp_index -= 1
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array[temp_index] = temp_index_value
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return array
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def heapify(array: list, index: int, heap_size: int) -> None: # Max Heap
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"""
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>>> array = [4, 2, 6, 8, 1, 7, 8, 22, 14, 56, 27, 79, 23, 45, 14, 12]
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>>> heapify(array, len(array) // 2, len(array))
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"""
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largest = index
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left_index = 2 * index + 1 # Left Node
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right_index = 2 * index + 2 # Right Node
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if left_index < heap_size and array[largest] < array[left_index]:
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largest = left_index
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if right_index < heap_size and array[largest] < array[right_index]:
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largest = right_index
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if largest != index:
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array[index], array[largest] = array[largest], array[index]
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heapify(array, largest, heap_size)
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def heap_sort(array: list) -> list:
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"""
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>>> heap_sort([4, 2, 6, 8, 1, 7, 8, 22, 14, 56, 27, 79, 23, 45, 14, 12])
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[1, 2, 4, 6, 7, 8, 8, 12, 14, 14, 22, 23, 27, 45, 56, 79]
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>>> heap_sort([-2, -11, 0, 0, 0, 87, 45, -69, 78, 12, 10, 103, 89, 52])
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[-69, -11, -2, 0, 0, 0, 10, 12, 45, 52, 78, 87, 89, 103]
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>>> heap_sort(['b', 'd', 'e', 'f', 'g', 'p', 'x', 'z', 'b', 's', 'e', 'u', 'v'])
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['b', 'b', 'd', 'e', 'e', 'f', 'g', 'p', 's', 'u', 'v', 'x', 'z']
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>>> heap_sort([6.2, -45.54, 8465.20, 758.56, -457.0, 0, 1, 2.879, 1.7, 11.7])
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[-457.0, -45.54, 0, 1, 1.7, 2.879, 6.2, 11.7, 758.56, 8465.2]
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"""
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n = len(array)
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for i in range(n // 2, -1, -1):
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heapify(array, i, n)
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for i in range(n - 1, 0, -1):
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array[i], array[0] = array[0], array[i]
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heapify(array, 0, i)
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return array
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def median_of_3(
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array: list, first_index: int, middle_index: int, last_index: int
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) -> int:
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"""
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>>> array = [4, 2, 6, 8, 1, 7, 8, 22, 14, 56, 27, 79, 23, 45, 14, 12]
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>>> median_of_3(array, 0, ((len(array) - 0) // 2) + 1, len(array) - 1)
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12
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>>> array = [13, 2, 6, 8, 1, 7, 8, 22, 14, 56, 27, 79, 23, 45, 14, 12]
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>>> median_of_3(array, 0, ((len(array) - 0) // 2) + 1, len(array) - 1)
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13
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>>> array = [4, 2, 6, 8, 1, 7, 8, 22, 15, 14, 27, 79, 23, 45, 14, 16]
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>>> median_of_3(array, 0, ((len(array) - 0) // 2) + 1, len(array) - 1)
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14
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"""
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if (array[first_index] > array[middle_index]) != (
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array[first_index] > array[last_index]
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):
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return array[first_index]
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elif (array[middle_index] > array[first_index]) != (
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array[middle_index] > array[last_index]
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):
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return array[middle_index]
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else:
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return array[last_index]
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def partition(array: list, low: int, high: int, pivot: int) -> int:
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"""
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>>> array = [4, 2, 6, 8, 1, 7, 8, 22, 14, 56, 27, 79, 23, 45, 14, 12]
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>>> partition(array, 0, len(array), 12)
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8
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>>> array = [21, 15, 11, 45, -2, -11, 46]
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>>> partition(array, 0, len(array), 15)
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3
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>>> array = ['a', 'z', 'd', 'p', 'v', 'l', 'o', 'o']
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>>> partition(array, 0, len(array), 'p')
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5
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>>> array = [6.2, -45.54, 8465.20, 758.56, -457.0, 0, 1, 2.879, 1.7, 11.7]
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>>> partition(array, 0, len(array), 2.879)
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6
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"""
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i = low
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j = high
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while True:
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while array[i] < pivot:
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i += 1
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j -= 1
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while pivot < array[j]:
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j -= 1
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if i >= j:
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return i
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array[i], array[j] = array[j], array[i]
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i += 1
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def sort(array: list) -> list:
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"""
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:param collection: some mutable ordered collection with heterogeneous
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comparable items inside
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:return: the same collection ordered by ascending
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Examples:
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>>> sort([4, 2, 6, 8, 1, 7, 8, 22, 14, 56, 27, 79, 23, 45, 14, 12])
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[1, 2, 4, 6, 7, 8, 8, 12, 14, 14, 22, 23, 27, 45, 56, 79]
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>>> sort([-1, -5, -3, -13, -44])
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[-44, -13, -5, -3, -1]
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>>> sort([])
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[]
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>>> sort([5])
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[5]
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>>> sort([-3, 0, -7, 6, 23, -34])
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[-34, -7, -3, 0, 6, 23]
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>>> sort([1.7, 1.0, 3.3, 2.1, 0.3 ])
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[0.3, 1.0, 1.7, 2.1, 3.3]
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>>> sort(['d', 'a', 'b', 'e', 'c'])
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['a', 'b', 'c', 'd', 'e']
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"""
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if len(array) == 0:
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return array
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max_depth = 2 * math.ceil(math.log2(len(array)))
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size_threshold = 16
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return intro_sort(array, 0, len(array), size_threshold, max_depth)
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def intro_sort(
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array: list, start: int, end: int, size_threshold: int, max_depth: int
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) -> list:
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"""
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>>> array = [4, 2, 6, 8, 1, 7, 8, 22, 14, 56, 27, 79, 23, 45, 14, 12]
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>>> max_depth = 2 * math.ceil(math.log2(len(array)))
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>>> intro_sort(array, 0, len(array), 16, max_depth)
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[1, 2, 4, 6, 7, 8, 8, 12, 14, 14, 22, 23, 27, 45, 56, 79]
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"""
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while end - start > size_threshold:
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if max_depth == 0:
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return heap_sort(array)
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max_depth -= 1
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pivot = median_of_3(array, start, start + ((end - start) // 2) + 1, end - 1)
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p = partition(array, start, end, pivot)
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intro_sort(array, p, end, size_threshold, max_depth)
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end = p
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return insertion_sort(array, start, end)
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if __name__ == "__main__":
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import doctest
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doctest.testmod()
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user_input = input("Enter numbers separated by a comma : ").strip()
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unsorted = [float(item) for item in user_input.split(",")]
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print(f"{sort(unsorted) = }")
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