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Added/Improved doctests for lowest_common_ancestor.py (#12673)
* added doctests to functions in lowest_common_ancestor.py * fixed doctests to be less excessive * Update lowest_common_ancestor.py * Update lowest_common_ancestor.py * Update lowest_common_ancestor.py * Update lowest_common_ancestor.py * Update lowest_common_ancestor.py * Update lowest_common_ancestor.py --------- Co-authored-by: Maxim Smolskiy <mithridatus@mail.ru>
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@ -15,6 +15,8 @@ def swap(a: int, b: int) -> tuple[int, int]:
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(4, 3)
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>>> swap(67, 12)
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(12, 67)
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>>> swap(3,-4)
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(-4, 3)
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"""
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a ^= b
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b ^= a
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@ -25,6 +27,23 @@ def swap(a: int, b: int) -> tuple[int, int]:
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def create_sparse(max_node: int, parent: list[list[int]]) -> list[list[int]]:
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"""
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creating sparse table which saves each nodes 2^i-th parent
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>>> max_node = 6
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>>> parent = [[0, 0, 1, 1, 2, 2, 3]] + [[0] * 7 for _ in range(19)]
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>>> parent = create_sparse(max_node=max_node, parent=parent)
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>>> parent[0]
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[0, 0, 1, 1, 2, 2, 3]
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>>> parent[1]
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[0, 0, 0, 0, 1, 1, 1]
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>>> parent[2]
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[0, 0, 0, 0, 0, 0, 0]
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>>> max_node = 1
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>>> parent = [[0, 0]] + [[0] * 2 for _ in range(19)]
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>>> parent = create_sparse(max_node=max_node, parent=parent)
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>>> parent[0]
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[0, 0]
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>>> parent[1]
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[0, 0]
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"""
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j = 1
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while (1 << j) < max_node:
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@ -38,6 +57,21 @@ def create_sparse(max_node: int, parent: list[list[int]]) -> list[list[int]]:
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def lowest_common_ancestor(
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u: int, v: int, level: list[int], parent: list[list[int]]
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) -> int:
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"""
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Return the lowest common ancestor between u and v
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>>> level = [-1, 0, 1, 1, 2, 2, 2]
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>>> parent = [[0, 0, 1, 1, 2, 2, 3],[0, 0, 0, 0, 1, 1, 1]] + \
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[[0] * 7 for _ in range(17)]
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>>> lowest_common_ancestor(u=4, v=5, level=level, parent=parent)
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2
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>>> lowest_common_ancestor(u=4, v=6, level=level, parent=parent)
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1
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>>> lowest_common_ancestor(u=2, v=3, level=level, parent=parent)
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1
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>>> lowest_common_ancestor(u=6, v=6, level=level, parent=parent)
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6
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"""
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# u must be deeper in the tree than v
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if level[u] < level[v]:
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u, v = swap(u, v)
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@ -68,6 +102,26 @@ def breadth_first_search(
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sets every nodes direct parent
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parent of root node is set to 0
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calculates depth of each node from root node
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>>> level = [-1] * 7
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>>> parent = [[0] * 7 for _ in range(20)]
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>>> graph = {1: [2, 3], 2: [4, 5], 3: [6], 4: [], 5: [], 6: []}
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>>> level, parent = breadth_first_search(
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... level=level, parent=parent, max_node=6, graph=graph, root=1)
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>>> level
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[-1, 0, 1, 1, 2, 2, 2]
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>>> parent[0]
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[0, 0, 1, 1, 2, 2, 3]
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>>> level = [-1] * 2
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>>> parent = [[0] * 2 for _ in range(20)]
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>>> graph = {1: []}
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>>> level, parent = breadth_first_search(
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... level=level, parent=parent, max_node=1, graph=graph, root=1)
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>>> level
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[-1, 0]
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>>> parent[0]
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[0, 0]
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"""
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level[root] = 0
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q: Queue[int] = Queue(maxsize=max_node)
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