Implement ConcatenableQueue as 2-3 tree
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dc8cdae225
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@ -10,7 +10,7 @@ import math
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from collections.abc import Sequence
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from typing import NamedTuple, Optional
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from .datastruct import UnionFindQueue, PriorityQueue
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from .datastruct import ConcatenableQueue, PriorityQueue
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def maximum_weight_matching(
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@ -391,9 +391,10 @@ class Blossom:
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# all top-level blossoms in the tree.
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self.tree_blossoms: Optional[set[Blossom]] = None
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# Each top-level blossom maintains a union-find datastructure
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# containing all vertices in the blossom.
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self.vertex_set: UnionFindQueue[Blossom, int] = UnionFindQueue(self)
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# Each top-level blossom maintains a concatenable queue containing
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# all vertices in the blossom.
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self.vertex_set: ConcatenableQueue[Blossom, int]
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self.vertex_set = ConcatenableQueue(self)
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# If this is a top-level unlabeled blossom with an edge to an
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# S-blossom, "delta2_node" is the corresponding node in the delta2
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@ -554,7 +555,7 @@ class MatchingContext:
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self.nontrivial_blossom: set[NonTrivialBlossom] = set()
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# "vertex_set_node[x]" represents the vertex "x" inside the
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# union-find datastructure of its top-level blossom.
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# concatenable queue of its top-level blossom.
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#
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# Initially, each vertex belongs to its own trivial top-level blossom.
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self.vertex_set_node = [b.vertex_set.insert(i, math.inf)
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@ -668,7 +669,7 @@ class MatchingContext:
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if not improved:
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return
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# Update the priority of "y" in its UnionFindQueue.
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# Update the priority of "y" in its ConcatenableQueue.
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self.vertex_set_node[y].set_prio(prio)
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# If the blossom is unlabeled and the new edge becomes its least-slack
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@ -701,7 +702,7 @@ class MatchingContext:
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else:
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prio = vertex_sedge_queue.find_min().prio
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# If necessary, update the priority of "y" in its UnionFindQueue.
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# If necessary, update priority of "y" in its ConcatenableQueue.
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if prio > self.vertex_set_node[y].prio:
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self.vertex_set_node[y].set_prio(prio)
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if by.label == LABEL_NONE:
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@ -1235,7 +1236,7 @@ class MatchingContext:
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sub.tree_blossoms = None
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tree_blossoms.remove(sub)
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# Merge union-find structures.
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# Merge concatenable queues.
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blossom.vertex_set.merge([sub.vertex_set for sub in subblossoms])
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@staticmethod
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@ -1280,7 +1281,7 @@ class MatchingContext:
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# Remove blossom from the delta2 queue.
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self.delta2_disable_blossom(blossom)
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# Split union-find structure.
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# Split concatenable queue.
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blossom.vertex_set.split()
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# Prepare to push lazy delta updates down to the sub-blossoms.
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@ -11,11 +11,11 @@ _ElemT = TypeVar("_ElemT")
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_ElemT2 = TypeVar("_ElemT2")
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class UnionFindQueue(Generic[_NameT, _ElemT]):
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"""Combination of disjoint set and priority queue.
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class ConcatenableQueue(Generic[_NameT, _ElemT]):
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"""Priority queue supporting efficient merge and split operations.
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This is a combination of a disjoint set and a priority queue.
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A queue has a "name", which can be any Python object.
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Each element has associated "data", which can be any Python object.
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Each element has a priority.
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@ -27,68 +27,70 @@ class UnionFindQueue(Generic[_NameT, _ElemT]):
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- Merge two or more queues.
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- Undo a previous merge step.
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The implementation is essentially an AVL tree, with minimum-priority
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This data structure is implemented as a 2-3 tree with minimum-priority
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tracking added to it.
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"""
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__slots__ = ("name", "tree", "first_node", "sub_queues")
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class Node(Generic[_NameT2, _ElemT2]):
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"""Node in a UnionFindQueue."""
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class BaseNode(Generic[_NameT2, _ElemT2]):
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"""Node in the 2-3 tree."""
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__slots__ = ("owner", "data", "prio", "min_node", "height",
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"parent", "left", "right")
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__slots__ = ("owner", "min_node", "height", "parent", "childs")
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def __init__(self,
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owner: UnionFindQueue[_NameT2, _ElemT2],
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data: _ElemT2,
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prio: float
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min_node: ConcatenableQueue.Node[_NameT2, _ElemT2],
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height: int
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) -> None:
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"""Initialize a new element.
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"""Initialize a new node."""
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self.owner: Optional[ConcatenableQueue[_NameT2, _ElemT2]] = None
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self.min_node = min_node
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self.height = height
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self.parent: Optional[ConcatenableQueue.BaseNode[_NameT2,
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_ElemT2]]
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self.parent = None
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self.childs: list[ConcatenableQueue.BaseNode[_NameT2, _ElemT2]]
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self.childs = []
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class Node(BaseNode[_NameT2, _ElemT2]):
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"""Leaf node in the 2-3 tree, representing an element in the queue."""
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__slots__ = ("data", "prio")
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def __init__(self, data: _ElemT2, prio: float) -> None:
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"""Initialize a new leaf node.
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This method should not be called directly.
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Instead, call UnionFindQueue.insert().
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Instead, call ConcatenableQueue.insert().
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"""
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self.owner: Optional[UnionFindQueue[_NameT2, _ElemT2]] = owner
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super().__init__(min_node=self, height=0)
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self.data = data
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self.prio = prio
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self.min_node = self
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self.height = 1
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self.parent: Optional[UnionFindQueue.Node[_NameT2, _ElemT2]]
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self.left: Optional[UnionFindQueue.Node[_NameT2, _ElemT2]]
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self.right: Optional[UnionFindQueue.Node[_NameT2, _ElemT2]]
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self.parent = None
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self.left = None
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self.right = None
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def find(self) -> _NameT2:
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"""Return the name of the queue that contains this element.
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This function takes time O(log(n)).
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"""
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node = self
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node: ConcatenableQueue.BaseNode[_NameT2, _ElemT2] = self
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while node.parent is not None:
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node = node.parent
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assert node.owner is not None
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return node.owner.name
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def set_prio(self, prio: float) -> None:
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"""Change the priority of this element."""
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"""Change the priority of this element.
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This function takes time O(log(n)).
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"""
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self.prio = prio
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node = self
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while True:
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min_node = node
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if node.left is not None:
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left_min_node = node.left.min_node
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if left_min_node.prio < min_node.prio:
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min_node = left_min_node
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if node.right is not None:
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right_min_node = node.right.min_node
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if right_min_node.prio < min_node.prio:
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min_node = right_min_node
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node = self.parent
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while node is not None:
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min_node = node.childs[0].min_node
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for child in node.childs[1:]:
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if child.min_node.prio < min_node.prio:
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min_node = child.min_node
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node.min_node = min_node
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if node.parent is None:
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break
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node = node.parent
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def __init__(self, name: _NameT) -> None:
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@ -100,9 +102,10 @@ class UnionFindQueue(Generic[_NameT, _ElemT]):
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name: Name to assign to the new queue.
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"""
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self.name = name
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self.tree: Optional[UnionFindQueue.Node[_NameT, _ElemT]] = None
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self.first_node: Optional[UnionFindQueue.Node[_NameT, _ElemT]] = None
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self.sub_queues: list[UnionFindQueue[_NameT, _ElemT]] = []
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self.tree: Optional[ConcatenableQueue.BaseNode[_NameT, _ElemT]] = None
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self.first_node: Optional[ConcatenableQueue.Node[_NameT, _ElemT]]
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self.first_node = None
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self.sub_queues: list[ConcatenableQueue[_NameT, _ElemT]] = []
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def clear(self) -> None:
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"""Remove all elements from the queue.
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@ -120,12 +123,8 @@ class UnionFindQueue(Generic[_NameT, _ElemT]):
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while node is not None:
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node.min_node = None # type: ignore
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prev_node = node
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if node.left is not None:
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node = node.left
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prev_node.left = None
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elif node.right is not None:
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node = node.right
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prev_node.right = None
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if node.childs:
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node = node.childs.pop()
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else:
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node = node.parent
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prev_node.parent = None
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@ -143,10 +142,10 @@ class UnionFindQueue(Generic[_NameT, _ElemT]):
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prio: Initial priority of the new element.
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"""
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assert self.tree is None
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node = UnionFindQueue.Node(self, elem, prio)
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self.tree = node
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self.first_node = node
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return node
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self.tree = ConcatenableQueue.Node(elem, prio)
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self.tree.owner = self
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self.first_node = self.tree
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return self.tree
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def min_prio(self) -> float:
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"""Return the minimum priority of any element in the queue.
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@ -169,7 +168,7 @@ class UnionFindQueue(Generic[_NameT, _ElemT]):
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return node.min_node.data
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def merge(self,
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sub_queues: list[UnionFindQueue[_NameT, _ElemT]]
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sub_queues: list[ConcatenableQueue[_NameT, _ElemT]]
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) -> None:
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"""Merge the specified queues.
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@ -210,7 +209,7 @@ class UnionFindQueue(Generic[_NameT, _ElemT]):
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subtree.owner = None
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# Merge our current tree with the tree from the sub-queue.
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self.tree = self._merge_tree(self.tree, subtree)
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self.tree = self._join(self.tree, subtree)
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# Put the owner pointer in the root node.
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self.tree.owner = self
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@ -252,417 +251,180 @@ class UnionFindQueue(Generic[_NameT, _ElemT]):
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self.sub_queues = []
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@staticmethod
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def _repair_node(node: Node[_NameT, _ElemT]) -> None:
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"""Recalculate the height and min-priority information of the
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specified node.
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"""
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# Repair node height.
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lh = 0 if node.left is None else node.left.height
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rh = 0 if node.right is None else node.right.height
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node.height = 1 + max(lh, rh)
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# Repair min-priority.
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min_node = node
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if node.left is not None:
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left_min_node = node.left.min_node
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if left_min_node.prio < min_node.prio:
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min_node = left_min_node
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if node.right is not None:
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right_min_node = node.right.min_node
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if right_min_node.prio < min_node.prio:
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min_node = right_min_node
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def _repair_node(node: BaseNode[_NameT, _ElemT]) -> None:
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"""Repair min_prio attribute of an internal node."""
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min_node = node.childs[0].min_node
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for child in node.childs[1:]:
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if child.min_node.prio < min_node.prio:
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min_node = child.min_node
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node.min_node = min_node
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def _rotate_left(self,
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node: Node[_NameT, _ElemT]
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) -> Node[_NameT, _ElemT]:
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"""Rotate the specified subtree to the left.
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Return the new root node of the subtree.
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"""
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#
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# N C
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# / \ / \
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# A C ---> N D
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# / \ / \
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# B D A B
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#
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parent = node.parent
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new_top = node.right
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assert new_top is not None
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node.right = new_top.left
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if node.right is not None:
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node.right.parent = node
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new_top.left = node
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new_top.parent = parent
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node.parent = new_top
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if parent is not None:
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if parent.left is node:
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parent.left = new_top
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elif parent.right is node:
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parent.right = new_top
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self._repair_node(node)
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self._repair_node(new_top)
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return new_top
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def _rotate_right(self,
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node: Node[_NameT, _ElemT]
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) -> Node[_NameT, _ElemT]:
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"""Rotate the specified node to the right.
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Return the new root node of the subtree.
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"""
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#
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# N A
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# / \ / \
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# A D ---> B N
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# / \ / \
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# B C C D
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#
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parent = node.parent
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new_top = node.left
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assert new_top is not None
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node.left = new_top.right
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if node.left is not None:
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node.left.parent = node
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new_top.right = node
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new_top.parent = parent
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node.parent = new_top
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if parent is not None:
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if parent.left is node:
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parent.left = new_top
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elif parent.right is node:
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parent.right = new_top
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self._repair_node(node)
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self._repair_node(new_top)
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return new_top
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def _rebalance_up(self,
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node: Node[_NameT, _ElemT]
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) -> Node[_NameT, _ElemT]:
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"""Repair and rebalance the specified node and its ancestors.
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Return the root node of the rebalanced tree.
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"""
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# Walk up to the root of the tree.
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while True:
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lh = 0 if node.left is None else node.left.height
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rh = 0 if node.right is None else node.right.height
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if lh > rh + 1:
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# This node is left-heavy. Rotate right to rebalance.
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#
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# N L
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# / \ / \
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# L \ / N
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# / \ \ ---> / / \
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# A B \ A B \
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# \ \
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# R R
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#
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lchild = node.left
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assert lchild is not None
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if ((lchild.right is not None)
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and ((lchild.left is None)
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or (lchild.right.height > lchild.left.height))):
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# Double rotation.
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lchild = self._rotate_left(lchild)
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node = self._rotate_right(node)
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elif lh + 1 < rh:
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# This node is right-heavy. Rotate left to rebalance.
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#
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# N R
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# / \ / \
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# / R N \
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# / / \ ---> / \ \
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# / A B / A B
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# / /
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# L L
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#
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rchild = node.right
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assert rchild is not None
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if ((rchild.left is not None)
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and ((rchild.right is None)
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or (rchild.left.height > rchild.right.height))):
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# Double rotation.
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rchild = self._rotate_right(rchild)
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node = self._rotate_left(node)
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else:
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# No rotation. Must still repair node though.
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self._repair_node(node)
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if node.parent is None:
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break
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# Continue rebalancing at the parent.
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node = node.parent
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# Return new root node.
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@staticmethod
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def _new_internal_node(ltree: BaseNode[_NameT, _ElemT],
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rtree: BaseNode[_NameT, _ElemT]
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) -> BaseNode[_NameT, _ElemT]:
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"""Create a new internal node with 2 child nodes."""
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assert ltree.height == rtree.height
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height = ltree.height + 1
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if ltree.min_node.prio <= rtree.min_node.prio:
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min_node = ltree.min_node
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else:
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min_node = rtree.min_node
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node = ConcatenableQueue.BaseNode(min_node, height)
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node.childs = [ltree, rtree]
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ltree.parent = node
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rtree.parent = node
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return node
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def _join_right(self,
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ltree: Node[_NameT, _ElemT],
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node: Node[_NameT, _ElemT],
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rtree: Optional[Node[_NameT, _ElemT]]
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) -> Node[_NameT, _ElemT]:
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"""Join a left subtree, middle node and right subtree together.
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ltree: BaseNode[_NameT, _ElemT],
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rtree: BaseNode[_NameT, _ElemT]
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) -> BaseNode[_NameT, _ElemT]:
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"""Join two trees together.
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The left subtree must be higher than the right subtree.
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The initial left subtree must be higher than the right subtree.
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Return the root node of the joined tree.
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"""
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lh = ltree.height
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rh = 0 if rtree is None else rtree.height
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assert lh > rh + 1
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# Descend down the right spine of "ltree".
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# Stop at a node with compatible height, then insert "node"
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# and attach "rtree".
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#
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# ltree
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# / \
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# X
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# / \
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# X <-- cur
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# / \
|
||||
# node
|
||||
# / \
|
||||
# X rtree
|
||||
#
|
||||
# Descend down the right spine of the left tree until we
|
||||
# reach a node just above the right tree.
|
||||
node = ltree
|
||||
while node.height > rtree.height + 1:
|
||||
node = node.childs[-1]
|
||||
|
||||
# Descend to a point with compatible height.
|
||||
cur = ltree
|
||||
while (cur.right is not None) and (cur.right.height > rh + 1):
|
||||
cur = cur.right
|
||||
assert node.height == rtree.height + 1
|
||||
|
||||
# Insert "node" and "rtree".
|
||||
node.left = cur.right
|
||||
node.right = rtree
|
||||
if node.left is not None:
|
||||
node.left.parent = node
|
||||
if rtree is not None:
|
||||
rtree.parent = node
|
||||
cur.right = node
|
||||
node.parent = cur
|
||||
|
||||
# A double rotation may be necessary.
|
||||
if (cur.left is None) or (cur.left.height <= rh):
|
||||
node = self._rotate_right(node)
|
||||
cur = self._rotate_left(cur)
|
||||
else:
|
||||
# Find a node in the left tree to insert the right tree as child.
|
||||
while len(node.childs) == 3:
|
||||
# This node already has 3 childs so we can not add the right tree.
|
||||
# Rearrange into 2 nodes with 2 childs each, then solve it
|
||||
# at the parent level.
|
||||
#
|
||||
# N N R'
|
||||
# / | \ / \ / \
|
||||
# / | \ ---> / \ / \
|
||||
# A B C R A B C R
|
||||
#
|
||||
child = node.childs.pop()
|
||||
self._repair_node(node)
|
||||
self._repair_node(cur)
|
||||
rtree = self._new_internal_node(child, rtree)
|
||||
if node.parent is None:
|
||||
# Create a new root node.
|
||||
return self._new_internal_node(node, rtree)
|
||||
node = node.parent
|
||||
|
||||
# Ascend from "cur" to the root of the tree.
|
||||
# Repair and/or rotate as needed.
|
||||
while cur.parent is not None:
|
||||
cur = cur.parent
|
||||
assert cur.left is not None
|
||||
assert cur.right is not None
|
||||
# Insert the right tree as child of this node.
|
||||
assert len(node.childs) < 3
|
||||
node.childs.append(rtree)
|
||||
rtree.parent = node
|
||||
|
||||
if cur.left.height + 1 < cur.right.height:
|
||||
cur = self._rotate_left(cur)
|
||||
else:
|
||||
self._repair_node(cur)
|
||||
# Repair min-prio pointers of ancestors.
|
||||
while True:
|
||||
self._repair_node(node)
|
||||
if node.parent is None:
|
||||
break
|
||||
node = node.parent
|
||||
|
||||
return cur
|
||||
return node
|
||||
|
||||
def _join_left(self,
|
||||
ltree: Optional[Node[_NameT, _ElemT]],
|
||||
node: Node[_NameT, _ElemT],
|
||||
rtree: Node[_NameT, _ElemT]
|
||||
) -> Node[_NameT, _ElemT]:
|
||||
"""Join a left subtree, middle node and right subtree together.
|
||||
ltree: BaseNode[_NameT, _ElemT],
|
||||
rtree: BaseNode[_NameT, _ElemT]
|
||||
) -> BaseNode[_NameT, _ElemT]:
|
||||
"""Join two trees together.
|
||||
|
||||
The right subtree must be higher than the left subtree.
|
||||
The initial left subtree must be lower than the right subtree.
|
||||
|
||||
Return the root node of the joined tree.
|
||||
"""
|
||||
lh = 0 if ltree is None else ltree.height
|
||||
rh = rtree.height
|
||||
assert lh + 1 < rh
|
||||
|
||||
# Descend down the left spine of "rtree".
|
||||
# Stop at a node with compatible height, then insert "node"
|
||||
# and attach "ltree".
|
||||
#
|
||||
# rtree
|
||||
# / \
|
||||
# X
|
||||
# / \
|
||||
# cur --> X
|
||||
# / \
|
||||
# node
|
||||
# / \
|
||||
# ltree X
|
||||
#
|
||||
# Descend down the left spine of the right tree until we
|
||||
# reach a node just above the left tree.
|
||||
node = rtree
|
||||
while node.height > ltree.height + 1:
|
||||
node = node.childs[0]
|
||||
|
||||
# Descend to a point with compatible height.
|
||||
cur = rtree
|
||||
while (cur.left is not None) and (cur.left.height > lh + 1):
|
||||
cur = cur.left
|
||||
assert node.height == ltree.height + 1
|
||||
|
||||
# Insert "node" and "ltree".
|
||||
node.left = ltree
|
||||
node.right = cur.left
|
||||
if ltree is not None:
|
||||
ltree.parent = node
|
||||
if node.right is not None:
|
||||
node.right.parent = node
|
||||
cur.left = node
|
||||
node.parent = cur
|
||||
|
||||
# A double rotation may be necessary.
|
||||
if (cur.right is None) or (cur.right.height <= lh):
|
||||
node = self._rotate_left(node)
|
||||
cur = self._rotate_right(cur)
|
||||
else:
|
||||
# Find a node in the right tree to insert the left tree as child.
|
||||
while len(node.childs) == 3:
|
||||
# This node already has 3 childs so we can not add the left tree.
|
||||
# Rearrange into 2 nodes with 2 childs each, then solve it
|
||||
# at the parent level.
|
||||
#
|
||||
# N L' N
|
||||
# / | \ / \ / \
|
||||
# / | \ ---> / \ / \
|
||||
# L A B C L A B C
|
||||
#
|
||||
child = node.childs.pop(0)
|
||||
self._repair_node(node)
|
||||
self._repair_node(cur)
|
||||
ltree = self._new_internal_node(ltree, child)
|
||||
if node.parent is None:
|
||||
# Create a new root node.
|
||||
return self._new_internal_node(ltree, node)
|
||||
node = node.parent
|
||||
|
||||
# Ascend from "cur" to the root of the tree.
|
||||
# Repair and/or rotate as needed.
|
||||
while cur.parent is not None:
|
||||
cur = cur.parent
|
||||
assert cur.left is not None
|
||||
assert cur.right is not None
|
||||
# Insert the left tree as child of this node.
|
||||
assert len(node.childs) < 3
|
||||
node.childs.insert(0, ltree)
|
||||
ltree.parent = node
|
||||
|
||||
if cur.left.height > cur.right.height + 1:
|
||||
cur = self._rotate_right(cur)
|
||||
else:
|
||||
self._repair_node(cur)
|
||||
# Repair min-prio pointers of ancestors.
|
||||
while True:
|
||||
self._repair_node(node)
|
||||
if node.parent is None:
|
||||
break
|
||||
node = node.parent
|
||||
|
||||
return cur
|
||||
return node
|
||||
|
||||
def _join(self,
|
||||
ltree: Optional[Node[_NameT, _ElemT]],
|
||||
node: Node[_NameT, _ElemT],
|
||||
rtree: Optional[Node[_NameT, _ElemT]]
|
||||
) -> Node[_NameT, _ElemT]:
|
||||
"""Join a left subtree, middle node and right subtree together.
|
||||
ltree: BaseNode[_NameT, _ElemT],
|
||||
rtree: BaseNode[_NameT, _ElemT]
|
||||
) -> BaseNode[_NameT, _ElemT]:
|
||||
"""Join two trees together.
|
||||
|
||||
The left or right subtree may initially be a child of the middle
|
||||
node; such links will be broken as needed.
|
||||
|
||||
The left and right subtrees must be consistent, AVL-balanced trees.
|
||||
Parent pointers of the subtrees are ignored.
|
||||
|
||||
The middle node is considered as a single node.
|
||||
Its parent and child pointers are ignored.
|
||||
The left and right subtree must be consistent 2-3 trees.
|
||||
Initial parent pointers of these subtrees are ignored.
|
||||
|
||||
Return the root node of the joined tree.
|
||||
"""
|
||||
lh = 0 if ltree is None else ltree.height
|
||||
rh = 0 if rtree is None else rtree.height
|
||||
|
||||
if lh > rh + 1:
|
||||
assert ltree is not None
|
||||
ltree.parent = None
|
||||
return self._join_right(ltree, node, rtree)
|
||||
elif lh + 1 < rh:
|
||||
assert rtree is not None
|
||||
rtree.parent = None
|
||||
return self._join_left(ltree, node, rtree)
|
||||
if ltree.height > rtree.height:
|
||||
return self._join_right(ltree, rtree)
|
||||
elif ltree.height < rtree.height:
|
||||
return self._join_left(ltree, rtree)
|
||||
else:
|
||||
# Subtree heights are compatible. Just join them.
|
||||
#
|
||||
# node
|
||||
# / \
|
||||
# ltree rtree
|
||||
# / \ / \
|
||||
#
|
||||
node.parent = None
|
||||
node.left = ltree
|
||||
if ltree is not None:
|
||||
ltree.parent = node
|
||||
node.right = rtree
|
||||
if rtree is not None:
|
||||
rtree.parent = node
|
||||
self._repair_node(node)
|
||||
return node
|
||||
|
||||
def _merge_tree(self,
|
||||
ltree: Node[_NameT, _ElemT],
|
||||
rtree: Node[_NameT, _ElemT]
|
||||
) -> Node[_NameT, _ElemT]:
|
||||
"""Merge two trees.
|
||||
|
||||
Return the root node of the merged tree.
|
||||
"""
|
||||
|
||||
# Find the left-most node of the right tree.
|
||||
split_node = rtree
|
||||
while split_node.left is not None:
|
||||
split_node = split_node.left
|
||||
|
||||
# Delete the split_node from its tree.
|
||||
parent = split_node.parent
|
||||
if split_node.right is not None:
|
||||
split_node.right.parent = parent
|
||||
if parent is None:
|
||||
rtree_new = split_node.right
|
||||
else:
|
||||
# Repair and rebalance the ancestors of split_node.
|
||||
parent.left = split_node.right
|
||||
rtree_new = self._rebalance_up(parent)
|
||||
|
||||
# Join the two trees via the split_node.
|
||||
return self._join(ltree, split_node, rtree_new)
|
||||
return self._new_internal_node(ltree, rtree)
|
||||
|
||||
def _split_tree(self,
|
||||
split_node: Node[_NameT, _ElemT]
|
||||
) -> tuple[Node[_NameT, _ElemT], Node[_NameT, _ElemT]]:
|
||||
split_node: BaseNode[_NameT, _ElemT]
|
||||
) -> tuple[BaseNode[_NameT, _ElemT],
|
||||
BaseNode[_NameT, _ElemT]]:
|
||||
"""Split a tree on a specified node.
|
||||
|
||||
Two new trees will be constructed.
|
||||
All nodes to the left of "split_node" will go to the left tree.
|
||||
All nodes to the right of "split_node", and "split_node" itself,
|
||||
Leaf nodes to the left of "split_node" will go to the left tree.
|
||||
Leaf nodes to the right of "split_node", and "split_node" itself,
|
||||
will go to the right tree.
|
||||
|
||||
Return tuple (ltree, rtree),
|
||||
where ltree contains all nodes left of the split-node,
|
||||
rtree contains the split-nodes and all nodes to its right.
|
||||
Return tuple (ltree, rtree).
|
||||
"""
|
||||
|
||||
# Assign the descendants of "split_node" to the appropriate trees
|
||||
# and detach them from "split_node".
|
||||
ltree = split_node.left
|
||||
rtree = split_node.right
|
||||
|
||||
split_node.left = None
|
||||
split_node.right = None
|
||||
if ltree is not None:
|
||||
ltree.parent = None
|
||||
if rtree is not None:
|
||||
rtree.parent = None
|
||||
|
||||
# Detach "split_node" from its parent (if any).
|
||||
# Detach "split_node" from its parent.
|
||||
# Assign it to the right tree.
|
||||
parent = split_node.parent
|
||||
split_node.parent = None
|
||||
|
||||
# Assign "split_node" to the right tree.
|
||||
rtree = self._join(None, split_node, rtree)
|
||||
# The left tree is initially empty.
|
||||
# The right tree initially contains only "split_node".
|
||||
ltree: Optional[ConcatenableQueue.BaseNode[_NameT, _ElemT]] = None
|
||||
rtree = split_node
|
||||
|
||||
# Walk up to the root of the tree.
|
||||
# On the way up, detach each node from its parent and join it,
|
||||
# and its descendants, to the appropriate tree.
|
||||
# On the way up, detach each node from its parent and join its
|
||||
# child nodes to the appropriate tree.
|
||||
node = split_node
|
||||
while parent is not None:
|
||||
|
||||
|
|
@ -674,16 +436,53 @@ class UnionFindQueue(Generic[_NameT, _ElemT]):
|
|||
# Detach "node" from its parent.
|
||||
node.parent = None
|
||||
|
||||
if node.left is child:
|
||||
# "split_node" was located in the left subtree of "node".
|
||||
# This implies that "node" must be joined to the right tree.
|
||||
rtree = self._join(rtree, node, node.right)
|
||||
if len(node.childs) == 3:
|
||||
if node.childs[0] is child:
|
||||
# "node" has 3 child nodes.
|
||||
# Its left subtree has already been split.
|
||||
# Turn it into a 2-node and join it to the right tree.
|
||||
node.childs.pop(0)
|
||||
self._repair_node(node)
|
||||
rtree = self._join(rtree, node)
|
||||
elif node.childs[2] is child:
|
||||
# "node" has 3 child nodes.
|
||||
# Its right subtree has already been split.
|
||||
# Turn it into a 2-node and join it to the left tree.
|
||||
node.childs.pop()
|
||||
self._repair_node(node)
|
||||
if ltree is None:
|
||||
ltree = node
|
||||
else:
|
||||
ltree = self._join(node, ltree)
|
||||
else:
|
||||
# "node has 3 child nodes.
|
||||
# Its middle subtree has already been split.
|
||||
# Join its left child to the left tree, and its right
|
||||
# child to the right tree, then delete "node".
|
||||
node.childs[0].parent = None
|
||||
node.childs[2].parent = None
|
||||
if ltree is None:
|
||||
ltree = node.childs[0]
|
||||
else:
|
||||
ltree = self._join(node.childs[0], ltree)
|
||||
rtree = self._join(rtree, node.childs[2])
|
||||
|
||||
elif node.childs[0] is child:
|
||||
# "node" has 2 child nodes.
|
||||
# Its left subtree has already been split.
|
||||
# Join its right child to the right tree, then delete "node".
|
||||
node.childs[1].parent = None
|
||||
rtree = self._join(rtree, node.childs[1])
|
||||
|
||||
else:
|
||||
# "split_node" was located in the right subtree of "node".
|
||||
# This implies that "node" must be joined to the right tree.
|
||||
assert node.right is child
|
||||
ltree = self._join(node.left, node, ltree)
|
||||
# "node" has 2 child nodes.
|
||||
# Its right subtree has already been split.
|
||||
# Join its left child to the left tree, then delete "node".
|
||||
node.childs[0].parent = None
|
||||
if ltree is None:
|
||||
ltree = node.childs[0]
|
||||
else:
|
||||
ltree = self._join(node.childs[0], ltree)
|
||||
|
||||
assert ltree is not None
|
||||
return (ltree, rtree)
|
||||
|
|
|
|||
|
|
@ -3,11 +3,11 @@
|
|||
import random
|
||||
import unittest
|
||||
|
||||
from mwmatching.datastruct import UnionFindQueue, PriorityQueue
|
||||
from mwmatching.datastruct import ConcatenableQueue, PriorityQueue
|
||||
|
||||
|
||||
class TestUnionFindQueue(unittest.TestCase):
|
||||
"""Test UnionFindQueue."""
|
||||
class TestConcatenableQueue(unittest.TestCase):
|
||||
"""Test ConcatenableQueue."""
|
||||
|
||||
def _check_tree(self, queue):
|
||||
"""Check tree balancing rules and priority info."""
|
||||
|
|
@ -20,40 +20,33 @@ class TestUnionFindQueue(unittest.TestCase):
|
|||
|
||||
node = nodes.pop()
|
||||
|
||||
if node.left is not None:
|
||||
self.assertIs(node.left.parent, node)
|
||||
nodes.append(node.left)
|
||||
|
||||
if node.right is not None:
|
||||
self.assertIs(node.right.parent, node)
|
||||
nodes.append(node.right)
|
||||
|
||||
if node is not queue.tree:
|
||||
self.assertIsNone(node.owner)
|
||||
|
||||
lh = 0 if node.left is None else node.left.height
|
||||
rh = 0 if node.right is None else node.right.height
|
||||
self.assertEqual(node.height, 1 + max(lh, rh))
|
||||
|
||||
self.assertLessEqual(lh, rh + 1)
|
||||
self.assertLessEqual(rh, lh + 1)
|
||||
|
||||
best_node = {node}
|
||||
best_prio = node.prio
|
||||
for child in (node.left, node.right):
|
||||
if child is not None:
|
||||
if child.min_node.prio < best_prio:
|
||||
best_prio = child.min_node.prio
|
||||
if node.height == 0:
|
||||
self.assertEqual(len(node.childs), 0)
|
||||
self.assertIs(node.min_node, node)
|
||||
else:
|
||||
self.assertIn(len(node.childs), (2, 3))
|
||||
best_node = set()
|
||||
best_prio = None
|
||||
for child in node.childs:
|
||||
self.assertIs(child.parent, node)
|
||||
self.assertEqual(child.height, node.height - 1)
|
||||
nodes.append(child)
|
||||
if ((best_prio is None)
|
||||
or (child.min_node.prio < best_prio)):
|
||||
best_node = {child.min_node}
|
||||
best_prio = child.min_node.prio
|
||||
elif child.min_node.prio == best_prio:
|
||||
best_node.add(child.min_node)
|
||||
|
||||
self.assertEqual(node.min_node.prio, best_prio)
|
||||
self.assertIn(node.min_node, best_node)
|
||||
self.assertEqual(node.min_node.prio, best_prio)
|
||||
self.assertIn(node.min_node, best_node)
|
||||
|
||||
def test_single(self):
|
||||
"""Single element."""
|
||||
q = UnionFindQueue("Q")
|
||||
q = ConcatenableQueue("Q")
|
||||
|
||||
with self.assertRaises(Exception):
|
||||
q.min_prio()
|
||||
|
|
@ -62,7 +55,7 @@ class TestUnionFindQueue(unittest.TestCase):
|
|||
q.min_elem()
|
||||
|
||||
n = q.insert("a", 4)
|
||||
self.assertIsInstance(n, UnionFindQueue.Node)
|
||||
self.assertIsInstance(n, ConcatenableQueue.Node)
|
||||
|
||||
self._check_tree(q)
|
||||
|
||||
|
|
@ -84,22 +77,22 @@ class TestUnionFindQueue(unittest.TestCase):
|
|||
|
||||
def test_simple(self):
|
||||
"""Simple test, 5 elements."""
|
||||
q1 = UnionFindQueue("A")
|
||||
q1 = ConcatenableQueue("A")
|
||||
n1 = q1.insert("a", 5)
|
||||
|
||||
q2 = UnionFindQueue("B")
|
||||
q2 = ConcatenableQueue("B")
|
||||
n2 = q2.insert("b", 6)
|
||||
|
||||
q3 = UnionFindQueue("C")
|
||||
q3 = ConcatenableQueue("C")
|
||||
n3 = q3.insert("c", 7)
|
||||
|
||||
q4 = UnionFindQueue("D")
|
||||
q4 = ConcatenableQueue("D")
|
||||
n4 = q4.insert("d", 4)
|
||||
|
||||
q5 = UnionFindQueue("E")
|
||||
q5 = ConcatenableQueue("E")
|
||||
n5 = q5.insert("e", 3)
|
||||
|
||||
q345 = UnionFindQueue("P")
|
||||
q345 = ConcatenableQueue("P")
|
||||
q345.merge([q3, q4, q5])
|
||||
self._check_tree(q345)
|
||||
|
||||
|
|
@ -120,7 +113,7 @@ class TestUnionFindQueue(unittest.TestCase):
|
|||
self.assertEqual(q345.min_prio(), 4)
|
||||
self.assertEqual(q345.min_elem(), "d")
|
||||
|
||||
q12 = UnionFindQueue("Q")
|
||||
q12 = ConcatenableQueue("Q")
|
||||
q12.merge([q1, q2])
|
||||
self._check_tree(q12)
|
||||
|
||||
|
|
@ -129,7 +122,7 @@ class TestUnionFindQueue(unittest.TestCase):
|
|||
self.assertEqual(q12.min_prio(), 5)
|
||||
self.assertEqual(q12.min_elem(), "a")
|
||||
|
||||
q12345 = UnionFindQueue("R")
|
||||
q12345 = ConcatenableQueue("R")
|
||||
q12345.merge([q12, q345])
|
||||
self._check_tree(q12345)
|
||||
|
||||
|
|
@ -201,30 +194,30 @@ class TestUnionFindQueue(unittest.TestCase):
|
|||
queues = []
|
||||
nodes = []
|
||||
for i in range(14):
|
||||
q = UnionFindQueue(chr(ord("A") + i))
|
||||
q = ConcatenableQueue(chr(ord("A") + i))
|
||||
n = q.insert(chr(ord("a") + i), prios[i])
|
||||
queues.append(q)
|
||||
nodes.append(n)
|
||||
|
||||
q = UnionFindQueue("AB")
|
||||
q = ConcatenableQueue("AB")
|
||||
q.merge(queues[0:2])
|
||||
queues.append(q)
|
||||
self._check_tree(q)
|
||||
self.assertEqual(q.min_prio(), min(prios[0:2]))
|
||||
|
||||
q = UnionFindQueue("CDE")
|
||||
q = ConcatenableQueue("CDE")
|
||||
q.merge(queues[2:5])
|
||||
queues.append(q)
|
||||
self._check_tree(q)
|
||||
self.assertEqual(q.min_prio(), min(prios[2:5]))
|
||||
|
||||
q = UnionFindQueue("FGHI")
|
||||
q = ConcatenableQueue("FGHI")
|
||||
q.merge(queues[5:9])
|
||||
queues.append(q)
|
||||
self._check_tree(q)
|
||||
self.assertEqual(q.min_prio(), min(prios[5:9]))
|
||||
|
||||
q = UnionFindQueue("JKLMN")
|
||||
q = ConcatenableQueue("JKLMN")
|
||||
q.merge(queues[9:14])
|
||||
queues.append(q)
|
||||
self._check_tree(q)
|
||||
|
|
@ -239,7 +232,7 @@ class TestUnionFindQueue(unittest.TestCase):
|
|||
for i in range(9, 14):
|
||||
self.assertEqual(nodes[i].find(), "JKLMN")
|
||||
|
||||
q = UnionFindQueue("ALL")
|
||||
q = ConcatenableQueue("ALL")
|
||||
q.merge(queues[14:18])
|
||||
queues.append(q)
|
||||
self._check_tree(q)
|
||||
|
|
@ -298,7 +291,7 @@ class TestUnionFindQueue(unittest.TestCase):
|
|||
|
||||
for i in range(4000):
|
||||
name = f"q{i}"
|
||||
q = UnionFindQueue(name)
|
||||
q = ConcatenableQueue(name)
|
||||
p = rng.random()
|
||||
n = q.insert(f"n{i}", p)
|
||||
nodes.append(n)
|
||||
|
|
@ -326,7 +319,7 @@ class TestUnionFindQueue(unittest.TestCase):
|
|||
subs = rng.sample(sorted(live_queues), k)
|
||||
|
||||
name = f"Q{i}"
|
||||
q = UnionFindQueue(name)
|
||||
q = ConcatenableQueue(name)
|
||||
q.merge([queues[nn] for nn in subs])
|
||||
self._check_tree(q)
|
||||
queues[name] = q
|
||||
|
|
|
|||
Loading…
Reference in New Issue