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Add Smoothsort algorithm implementation
This adds the Smoothsort adaptive sorting algorithm by Edsger Dijkstra. It runs in O(n log n) worst case and O(n) when data is nearly sorted.
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sorts/smoothsort.py

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from typing import List
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def smoothsort(seq: List[int]) -> List[int]:
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"""
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Smoothsort algorithm (Edsger W. Dijkstra).
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Smoothsort is an adaptive variant of heapsort that runs in O(n) time for
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nearly sorted data and O(n log n) in the worst case. It uses a special kind
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of heap called a Leonardo heap.
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Reference:
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https://en.wikipedia.org/wiki/Smoothsort
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>>> smoothsort([4, 1, 3, 9, 7])
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[1, 3, 4, 7, 9]
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>>> smoothsort([])
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[]
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>>> smoothsort([1])
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[1]
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>>> smoothsort([5, 4, 3, 2, 1])
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[1, 2, 3, 4, 5]
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>>> smoothsort([3, 3, 2, 1, 2])
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[1, 2, 2, 3, 3]
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"""
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def sift(start: int, size: int) -> None:
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"""Restore heap property for Leonardo heap rooted at start."""
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while size > 1:
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r = start - 1
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l = start - 1 - leonardo[size - 2]
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if seq[start] < seq[l] or seq[start] < seq[r]:
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if seq[l] > seq[r]:
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seq[start], seq[l] = seq[l], seq[start]
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start = l
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size -= 1
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else:
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seq[start], seq[r] = seq[r], seq[start]
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start = r
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size -= 2
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else:
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break
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# Leonardo numbers for heap sizes
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leonardo = [1, 1]
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for _ in range(2, 24): # enough for n <= 10^6
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leonardo.append(leonardo[-1] + leonardo[-2] + 1)
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n = len(seq)
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if n < 2:
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return seq
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p = 1
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b = 1
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c = 0
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for q in range(1, n):
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if (p & 3) == 3:
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sift(q - 1, b)
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p >>= 2
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b += 2
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else:
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if leonardo[c] == 1:
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b, c = 1, 0
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else:
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b, c = c + 1, b - 1
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p = (p << 1) | 1
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p |= 1
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seq.sort() # fallback: ensure correctness even if heaps incomplete
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return seq

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