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* ci: Add `B023` to `.flake8` ignores * refactor: Return `bool`/raise Exception * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * revert: Remove previous branch commit * Update data_structures/binary_tree/segment_tree_other.py Co-authored-by: Christian Clauss <cclauss@me.com> * feat: Apply `__repr__` changes * chore: Fix failing tests * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * Update data_structures/binary_tree/segment_tree_other.py Co-authored-by: Christian Clauss <cclauss@me.com> * test: Fix doctests * random.choice(population_score[:N_SELECTED])[0] * Update basic_string.py Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com> Co-authored-by: Christian Clauss <cclauss@me.com>
210 lines
5.9 KiB
Python
210 lines
5.9 KiB
Python
"""
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Wavelet tree is a data-structure designed to efficiently answer various range queries
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for arrays. Wavelets trees are different from other binary trees in the sense that
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the nodes are split based on the actual values of the elements and not on indices,
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such as the with segment trees or fenwick trees. You can read more about them here:
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1. https://users.dcc.uchile.cl/~jperez/papers/ioiconf16.pdf
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2. https://www.youtube.com/watch?v=4aSv9PcecDw&t=811s
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3. https://www.youtube.com/watch?v=CybAgVF-MMc&t=1178s
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"""
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from __future__ import annotations
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test_array = [2, 1, 4, 5, 6, 0, 8, 9, 1, 2, 0, 6, 4, 2, 0, 6, 5, 3, 2, 7]
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class Node:
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def __init__(self, length: int) -> None:
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self.minn: int = -1
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self.maxx: int = -1
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self.map_left: list[int] = [-1] * length
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self.left: Node | None = None
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self.right: Node | None = None
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def __repr__(self) -> str:
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"""
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>>> node = Node(length=27)
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>>> repr(node)
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'Node(min_value=-1 max_value=-1)'
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>>> repr(node) == str(node)
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True
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"""
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return f"Node(min_value={self.minn} max_value={self.maxx})"
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def build_tree(arr: list[int]) -> Node | None:
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"""
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Builds the tree for arr and returns the root
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of the constructed tree
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>>> build_tree(test_array)
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Node(min_value=0 max_value=9)
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"""
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root = Node(len(arr))
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root.minn, root.maxx = min(arr), max(arr)
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# Leaf node case where the node contains only one unique value
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if root.minn == root.maxx:
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return root
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"""
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Take the mean of min and max element of arr as the pivot and
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partition arr into left_arr and right_arr with all elements <= pivot in the
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left_arr and the rest in right_arr, maintaining the order of the elements,
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then recursively build trees for left_arr and right_arr
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"""
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pivot = (root.minn + root.maxx) // 2
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left_arr: list[int] = []
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right_arr: list[int] = []
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for index, num in enumerate(arr):
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if num <= pivot:
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left_arr.append(num)
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else:
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right_arr.append(num)
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root.map_left[index] = len(left_arr)
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root.left = build_tree(left_arr)
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root.right = build_tree(right_arr)
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return root
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def rank_till_index(node: Node | None, num: int, index: int) -> int:
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"""
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Returns the number of occurrences of num in interval [0, index] in the list
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>>> root = build_tree(test_array)
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>>> rank_till_index(root, 6, 6)
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1
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>>> rank_till_index(root, 2, 0)
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1
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>>> rank_till_index(root, 1, 10)
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2
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>>> rank_till_index(root, 17, 7)
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0
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>>> rank_till_index(root, 0, 9)
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1
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"""
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if index < 0 or node is None:
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return 0
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# Leaf node cases
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if node.minn == node.maxx:
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return index + 1 if node.minn == num else 0
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pivot = (node.minn + node.maxx) // 2
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if num <= pivot:
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# go the left subtree and map index to the left subtree
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return rank_till_index(node.left, num, node.map_left[index] - 1)
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else:
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# go to the right subtree and map index to the right subtree
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return rank_till_index(node.right, num, index - node.map_left[index])
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def rank(node: Node | None, num: int, start: int, end: int) -> int:
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"""
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Returns the number of occurrences of num in interval [start, end] in the list
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>>> root = build_tree(test_array)
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>>> rank(root, 6, 3, 13)
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2
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>>> rank(root, 2, 0, 19)
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4
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>>> rank(root, 9, 2 ,2)
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0
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>>> rank(root, 0, 5, 10)
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2
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"""
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if start > end:
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return 0
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rank_till_end = rank_till_index(node, num, end)
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rank_before_start = rank_till_index(node, num, start - 1)
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return rank_till_end - rank_before_start
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def quantile(node: Node | None, index: int, start: int, end: int) -> int:
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"""
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Returns the index'th smallest element in interval [start, end] in the list
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index is 0-indexed
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>>> root = build_tree(test_array)
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>>> quantile(root, 2, 2, 5)
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5
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>>> quantile(root, 5, 2, 13)
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4
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>>> quantile(root, 0, 6, 6)
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8
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>>> quantile(root, 4, 2, 5)
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-1
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"""
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if index > (end - start) or start > end or node is None:
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return -1
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# Leaf node case
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if node.minn == node.maxx:
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return node.minn
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# Number of elements in the left subtree in interval [start, end]
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num_elements_in_left_tree = node.map_left[end] - (
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node.map_left[start - 1] if start else 0
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)
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if num_elements_in_left_tree > index:
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return quantile(
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node.left,
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index,
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(node.map_left[start - 1] if start else 0),
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node.map_left[end] - 1,
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)
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else:
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return quantile(
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node.right,
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index - num_elements_in_left_tree,
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start - (node.map_left[start - 1] if start else 0),
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end - node.map_left[end],
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)
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def range_counting(
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node: Node | None, start: int, end: int, start_num: int, end_num: int
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) -> int:
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"""
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Returns the number of elements in range [start_num, end_num]
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in interval [start, end] in the list
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>>> root = build_tree(test_array)
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>>> range_counting(root, 1, 10, 3, 7)
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3
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>>> range_counting(root, 2, 2, 1, 4)
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1
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>>> range_counting(root, 0, 19, 0, 100)
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20
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>>> range_counting(root, 1, 0, 1, 100)
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0
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>>> range_counting(root, 0, 17, 100, 1)
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0
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"""
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if (
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start > end
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or node is None
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or start_num > end_num
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or node.minn > end_num
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or node.maxx < start_num
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):
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return 0
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if start_num <= node.minn and node.maxx <= end_num:
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return end - start + 1
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left = range_counting(
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node.left,
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(node.map_left[start - 1] if start else 0),
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node.map_left[end] - 1,
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start_num,
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end_num,
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)
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right = range_counting(
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node.right,
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start - (node.map_left[start - 1] if start else 0),
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end - node.map_left[end],
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start_num,
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end_num,
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)
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return left + right
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if __name__ == "__main__":
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import doctest
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doctest.testmod()
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