Restructure Python code as package
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@ -0,0 +1,11 @@
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"""
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Algorithm for finding a maximum weight matching in general graphs.
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"""
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from .algorithm import (maximum_weight_matching,
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adjust_weights_for_maximum_cardinality_matching,
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MatchingError)
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__all__ = ["maximum_weight_matching",
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"adjust_weights_for_maximum_cardinality_matching",
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"MatchingError"]
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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 UnionFindQueue, PriorityQueue
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def maximum_weight_matching(
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@ -66,10 +66,10 @@ def maximum_weight_matching(
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return []
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# Initialize graph representation.
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graph = _GraphInfo(edges)
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graph = GraphInfo(edges)
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# Initialize the matching algorithm.
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ctx = _MatchingContext(graph)
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ctx = MatchingContext(graph)
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ctx.start()
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# Improve the solution until no further improvement is possible.
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@ -92,7 +92,7 @@ def maximum_weight_matching(
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# there is a bug in the matching algorithm.
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# Verification only works reliably for integer weights.
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if graph.integer_weights:
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_verify_optimum(ctx)
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verify_optimum(ctx)
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return pairs
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@ -277,7 +277,7 @@ def _remove_negative_weight_edges(
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return edges
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class _GraphInfo:
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class GraphInfo:
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"""Representation of the input graph.
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These data remain unchanged while the algorithm runs.
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@ -328,12 +328,12 @@ class _GraphInfo:
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# Each vertex may be labeled "S" (outer) or "T" (inner) or be unlabeled.
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_LABEL_NONE = 0
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_LABEL_S = 1
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_LABEL_T = 2
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LABEL_NONE = 0
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LABEL_S = 1
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LABEL_T = 2
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class _Blossom:
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class Blossom:
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"""Represents a blossom in a partially matched graph.
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A blossom is an odd-length alternating cycle over sub-blossoms.
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@ -361,7 +361,7 @@ class _Blossom:
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#
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# If this is a top-level blossom,
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# "parent = None".
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self.parent: Optional[_NonTrivialBlossom] = None
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self.parent: Optional[NonTrivialBlossom] = None
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# "base_vertex" is the vertex index of the base of the blossom.
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# This is the unique vertex which is contained in the blossom
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@ -374,7 +374,7 @@ class _Blossom:
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# A top-level blossom that is part of an alternating tree,
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# has label S or T. An unlabeled top-level blossom is not part
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# of any alternating tree.
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self.label: int = _LABEL_NONE
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self.label: int = LABEL_NONE
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# A labeled top-level blossoms keeps track of the edge through which
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# it is attached to the alternating tree.
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@ -389,11 +389,11 @@ class _Blossom:
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# "tree_blossoms" is the set of all top-level blossoms that belong
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# to the same alternating tree. The same set instance is shared by
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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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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]"
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self.vertex_set: "UnionFindQueue[Blossom, int]"
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self.vertex_set = UnionFindQueue(self)
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# If this is a top-level unlabeled blossom with an edge to an
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@ -415,7 +415,7 @@ class _Blossom:
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return [self.base_vertex]
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class _NonTrivialBlossom(_Blossom):
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class NonTrivialBlossom(Blossom):
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"""Represents a non-trivial blossom in a partially matched graph.
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A non-trivial blossom is a blossom that contains multiple sub-blossoms
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@ -436,7 +436,7 @@ class _NonTrivialBlossom(_Blossom):
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def __init__(
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self,
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subblossoms: list[_Blossom],
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subblossoms: list[Blossom],
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edges: list[tuple[int, int]]
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) -> None:
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"""Initialize a new blossom."""
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@ -454,7 +454,7 @@ class _NonTrivialBlossom(_Blossom):
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#
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# "subblossoms[0]" is the start and end of the alternating cycle.
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# "subblossoms[0]" contains the base vertex of the blossom.
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self.subblossoms: list[_Blossom] = subblossoms
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self.subblossoms: list[Blossom] = subblossoms
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# "edges" is a list of edges linking the sub-blossoms.
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# Each edge is represented as an ordered pair "(x, y)" where "x"
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@ -491,13 +491,13 @@ class _NonTrivialBlossom(_Blossom):
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"""Return a list of vertex indices contained in the blossom."""
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# Use an explicit stack to avoid deep recursion.
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stack: list[_NonTrivialBlossom] = [self]
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stack: list[NonTrivialBlossom] = [self]
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nodes: list[int] = []
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while stack:
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b = stack.pop()
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for sub in b.subblossoms:
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if isinstance(sub, _NonTrivialBlossom):
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if isinstance(sub, NonTrivialBlossom):
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stack.append(sub)
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else:
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nodes.append(sub.base_vertex)
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@ -505,21 +505,21 @@ class _NonTrivialBlossom(_Blossom):
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return nodes
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class _AlternatingPath(NamedTuple):
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class AlternatingPath(NamedTuple):
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"""Represents a list of edges forming an alternating path or an
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alternating cycle."""
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edges: list[tuple[int, int]]
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is_cycle: bool
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class _MatchingContext:
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class MatchingContext:
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"""Holds all data used by the matching algorithm.
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It contains a partial solution of the matching problem and several
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auxiliary data structures.
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"""
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def __init__(self, graph: _GraphInfo) -> None:
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def __init__(self, graph: GraphInfo) -> None:
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"""Set up the initial state of the matching algorithm."""
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num_vertex = graph.num_vertex
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@ -545,14 +545,14 @@ class _MatchingContext:
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#
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# "trivial_blossom[x]" is the trivial blossom that contains only
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# vertex "x".
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self.trivial_blossom: list[_Blossom] = [_Blossom(x)
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self.trivial_blossom: list[Blossom] = [Blossom(x)
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for x in range(num_vertex)]
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# Non-trivial blossoms may be created and destroyed during
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# the course of the algorithm.
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#
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# Initially there are no non-trivial blossoms.
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self.nontrivial_blossom: set[_NonTrivialBlossom] = set()
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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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# Queue containing unlabeled top-level blossoms that have an edge to
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# an S-blossom. The priority of a blossom is 2 times its least slack
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# to an S blossom, plus 2 times the running sum of delta steps.
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self.delta2_queue: PriorityQueue[_Blossom] = PriorityQueue()
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self.delta2_queue: PriorityQueue[Blossom] = PriorityQueue()
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# Queue containing edges between S-vertices in different top-level
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# blossoms. The priority of an edge is its slack plus 2 times the
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@ -605,7 +605,7 @@ class _MatchingContext:
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# Queue containing top-level non-trivial T-blossoms.
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# The priority of a blossom is its dual plus 2 times the running
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# sum of delta steps.
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self.delta4_queue: PriorityQueue[_NonTrivialBlossom] = PriorityQueue()
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self.delta4_queue: PriorityQueue[NonTrivialBlossom] = PriorityQueue()
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# For each T-vertex or unlabeled vertex "x",
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# "vertex_sedge_queue[x]" is a queue of edges between "x" and any
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(x, y, w) = self.graph.edges[e]
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return self.vertex_dual_2x[x] + self.vertex_dual_2x[y] - 2 * w
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def delta2_add_edge(self, e: int, y: int, by: _Blossom) -> None:
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def delta2_add_edge(self, e: int, y: int, by: Blossom) -> None:
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"""Add edge "e" for delta2 tracking.
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Edge "e" connects an S-vertex to a T-vertex or unlabeled vertex "y".
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# If the blossom is unlabeled and the new edge becomes its least-slack
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# S-edge, insert or update the blossom in the global delta2 queue.
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if by.label == _LABEL_NONE:
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if by.label == LABEL_NONE:
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prio += by.vertex_dual_offset
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if by.delta2_node is None:
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by.delta2_node = self.delta2_queue.insert(prio, by)
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elif prio < by.delta2_node.prio:
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self.delta2_queue.decrease_prio(by.delta2_node, prio)
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def delta2_remove_edge(self, e: int, y: int, by: _Blossom) -> None:
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def delta2_remove_edge(self, e: int, y: int, by: Blossom) -> None:
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"""Remove edge "e" from delta2 tracking.
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This function is called if an S-vertex becomes unlabeled,
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# If necessary, update the priority of "y" in its UnionFindQueue.
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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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if by.label == LABEL_NONE:
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# Update or delete the blossom in the global delta2 queue.
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assert by.delta2_node is not None
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prio = by.vertex_set.min_prio()
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self.delta2_queue.delete(by.delta2_node)
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by.delta2_node = None
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def delta2_enable_blossom(self, blossom: _Blossom) -> None:
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def delta2_enable_blossom(self, blossom: Blossom) -> None:
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"""Enable delta2 tracking for "blossom".
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This function is called when a blossom becomes an unlabeled top-level
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prio += blossom.vertex_dual_offset
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blossom.delta2_node = self.delta2_queue.insert(prio, blossom)
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def delta2_disable_blossom(self, blossom: _Blossom) -> None:
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def delta2_disable_blossom(self, blossom: Blossom) -> None:
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"""Disable delta2 tracking for "blossom".
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The blossom will be removed from the global delta2 queue.
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@ -780,7 +780,7 @@ class _MatchingContext:
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prio = delta2_node.prio
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slack_2x = prio - self.delta_sum_2x
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assert blossom.parent is None
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assert blossom.label == _LABEL_NONE
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assert blossom.label == LABEL_NONE
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x = blossom.vertex_set.min_elem()
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e = self.vertex_sedge_queue[x].find_min().data
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@ -840,7 +840,7 @@ class _MatchingContext:
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(x, y, _w) = self.graph.edges[e]
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bx = self.vertex_set_node[x].find()
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by = self.vertex_set_node[y].find()
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assert (bx.label == _LABEL_S) and (by.label == _LABEL_S)
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assert (bx.label == LABEL_S) and (by.label == LABEL_S)
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if bx is not by:
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slack = delta3_node.prio - self.delta_sum_2x
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return (e, slack)
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# Managing blossom labels:
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#
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def assign_blossom_label_s(self, blossom: _Blossom) -> None:
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def assign_blossom_label_s(self, blossom: Blossom) -> None:
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"""Change an unlabeled top-level blossom into an S-blossom.
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For a blossom with "j" vertices and "k" incident edges,
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@ -870,8 +870,8 @@ class _MatchingContext:
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"""
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assert blossom.parent is None
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assert blossom.label == _LABEL_NONE
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blossom.label = _LABEL_S
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assert blossom.label == LABEL_NONE
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blossom.label = LABEL_S
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# Labeled blossoms must not be in the delta2 queue.
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self.delta2_disable_blossom(blossom)
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# The value of blossom.dual_var must be adjusted accordingly
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# when the blossom changes from unlabeled to S-blossom.
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#
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if isinstance(blossom, _NonTrivialBlossom):
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if isinstance(blossom, NonTrivialBlossom):
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blossom.dual_var -= self.delta_sum_2x
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# Apply pending updates to vertex dual variables and prepare
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# Add the new S-vertices to the scan queue.
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self.scan_queue.extend(vertices)
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def assign_blossom_label_t(self, blossom: _Blossom) -> None:
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def assign_blossom_label_t(self, blossom: Blossom) -> None:
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"""Change an unlabeled top-level blossom into a T-blossom.
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This function takes time O(log(n)).
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"""
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assert blossom.parent is None
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assert blossom.label == _LABEL_NONE
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blossom.label = _LABEL_T
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assert blossom.label == LABEL_NONE
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blossom.label = LABEL_T
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# Labeled blossoms must not be in the delta2 queue.
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self.delta2_disable_blossom(blossom)
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if isinstance(blossom, _NonTrivialBlossom):
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if isinstance(blossom, NonTrivialBlossom):
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# Adjust for lazy updating of T-blossom dual variables.
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#
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#
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blossom.vertex_dual_offset -= self.delta_sum_2x
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def remove_blossom_label_s(self, blossom: _Blossom) -> None:
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def remove_blossom_label_s(self, blossom: Blossom) -> None:
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"""Change a top-level S-blossom into an unlabeled blossom.
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For a blossom with "j" vertices and "k" incident edges,
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"""
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assert blossom.parent is None
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assert blossom.label == _LABEL_S
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blossom.label = _LABEL_NONE
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assert blossom.label == LABEL_S
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blossom.label = LABEL_NONE
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# Unwind lazy delta updates to the S-blossom dual variable.
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if isinstance(blossom, _NonTrivialBlossom):
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if isinstance(blossom, NonTrivialBlossom):
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blossom.dual_var += self.delta_sum_2x
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assert blossom.vertex_dual_offset == 0
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self.delta3_remove_edge(e)
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by = self.vertex_set_node[y].find()
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if by.label == _LABEL_S:
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if by.label == LABEL_S:
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# Edge "e" connects unlabeled vertex "x" to S-vertex "y".
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# It must be tracked for delta2 via vertex "x".
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self.delta2_add_edge(e, x, blossom)
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# removed now.
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self.delta2_remove_edge(e, y, by)
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def remove_blossom_label_t(self, blossom: _Blossom) -> None:
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def remove_blossom_label_t(self, blossom: Blossom) -> None:
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"""Change a top-level T-blossom into an unlabeled blossom.
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This function takes time O(log(n)).
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"""
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assert blossom.parent is None
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assert blossom.label == _LABEL_T
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blossom.label = _LABEL_NONE
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assert blossom.label == LABEL_T
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blossom.label = LABEL_NONE
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if isinstance(blossom, _NonTrivialBlossom):
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if isinstance(blossom, NonTrivialBlossom):
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# Unlabeled blossoms are not tracked in the delta4 queue.
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assert blossom.delta4_node is not None
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# Enable unlabeled top-level blossom for delta2 tracking.
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self.delta2_enable_blossom(blossom)
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def change_s_blossom_to_subblossom(self, blossom: _Blossom) -> None:
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def change_s_blossom_to_subblossom(self, blossom: Blossom) -> None:
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"""Change a top-level S-blossom into an S-subblossom.
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This function takes time O(1).
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"""
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assert blossom.parent is None
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assert blossom.label == _LABEL_S
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blossom.label = _LABEL_NONE
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assert blossom.label == LABEL_S
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blossom.label = LABEL_NONE
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# Unwind lazy delta updates to the S-blossom dual variable.
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if isinstance(blossom, _NonTrivialBlossom):
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if isinstance(blossom, NonTrivialBlossom):
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blossom.dual_var += self.delta_sum_2x
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#
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# General support routines:
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#
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def reset_blossom_label(self, blossom: _Blossom) -> None:
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def reset_blossom_label(self, blossom: Blossom) -> None:
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"""Remove blossom label."""
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assert blossom.parent is None
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assert blossom.label != _LABEL_NONE
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assert blossom.label != LABEL_NONE
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if blossom.label == _LABEL_S:
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if blossom.label == LABEL_S:
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self.remove_blossom_label_s(blossom)
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else:
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self.remove_blossom_label_t(blossom)
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@ -1072,7 +1072,7 @@ class _MatchingContext:
|
|||
"""TODO -- remove this function, only for debugging"""
|
||||
for blossom in itertools.chain(self.trivial_blossom,
|
||||
self.nontrivial_blossom):
|
||||
if (blossom.parent is None) and (blossom.label != _LABEL_NONE):
|
||||
if (blossom.parent is None) and (blossom.label != LABEL_NONE):
|
||||
assert blossom.tree_blossoms is not None
|
||||
assert blossom in blossom.tree_blossoms
|
||||
if blossom.tree_edge is not None:
|
||||
|
@ -1084,7 +1084,7 @@ class _MatchingContext:
|
|||
assert blossom.tree_edge is None
|
||||
assert blossom.tree_blossoms is None
|
||||
|
||||
def remove_alternating_tree(self, tree_blossoms: set[_Blossom]) -> None:
|
||||
def remove_alternating_tree(self, tree_blossoms: set[Blossom]) -> None:
|
||||
"""Reset the alternating tree consisting of the specified blossoms.
|
||||
|
||||
Marks the blossoms as unlabeled.
|
||||
|
@ -1093,13 +1093,13 @@ class _MatchingContext:
|
|||
This function takes time O((n + m) * log(n)).
|
||||
"""
|
||||
for blossom in tree_blossoms:
|
||||
assert blossom.label != _LABEL_NONE
|
||||
assert blossom.label != LABEL_NONE
|
||||
assert blossom.tree_blossoms is tree_blossoms
|
||||
self.reset_blossom_label(blossom)
|
||||
blossom.tree_edge = None
|
||||
blossom.tree_blossoms = None
|
||||
|
||||
def trace_alternating_paths(self, x: int, y: int) -> _AlternatingPath:
|
||||
def trace_alternating_paths(self, x: int, y: int) -> AlternatingPath:
|
||||
"""Trace back through the alternating trees from vertices "x" and "y".
|
||||
|
||||
If both vertices are part of the same alternating tree, this function
|
||||
|
@ -1119,7 +1119,7 @@ class _MatchingContext:
|
|||
blossoms.
|
||||
"""
|
||||
|
||||
marked_blossoms: list[_Blossom] = []
|
||||
marked_blossoms: list[Blossom] = []
|
||||
|
||||
# "xedges" is a list of edges used while tracing from "x".
|
||||
# "yedges" is a list of edges used while tracing from "y".
|
||||
|
@ -1129,7 +1129,7 @@ class _MatchingContext:
|
|||
|
||||
# "first_common" is the first common ancestor of "x" and "y"
|
||||
# in the alternating tree, or None if there is no common ancestor.
|
||||
first_common: Optional[_Blossom] = None
|
||||
first_common: Optional[Blossom] = None
|
||||
|
||||
# Alternate between tracing the path from "x" and the path from "y".
|
||||
# This ensures that the search time is bounded by the size of the
|
||||
|
@ -1179,14 +1179,14 @@ class _MatchingContext:
|
|||
# Any S-to-S alternating path must have odd length.
|
||||
assert len(path_edges) % 2 == 1
|
||||
|
||||
return _AlternatingPath(edges=path_edges,
|
||||
return AlternatingPath(edges=path_edges,
|
||||
is_cycle=(first_common is not None))
|
||||
|
||||
#
|
||||
# Merge and expand blossoms:
|
||||
#
|
||||
|
||||
def make_blossom(self, path: _AlternatingPath) -> None:
|
||||
def make_blossom(self, path: AlternatingPath) -> None:
|
||||
"""Create a new blossom from an alternating cycle.
|
||||
|
||||
Assign label S to the new blossom.
|
||||
|
@ -1214,21 +1214,21 @@ class _MatchingContext:
|
|||
assert subblossoms[1:] == subblossoms_next[:-1]
|
||||
|
||||
# Blossom must start and end with an S-sub-blossom.
|
||||
assert subblossoms[0].label == _LABEL_S
|
||||
assert subblossoms[0].label == LABEL_S
|
||||
|
||||
# Remove blossom labels.
|
||||
# Mark vertices inside former T-blossoms as S-vertices.
|
||||
for sub in subblossoms:
|
||||
if sub.label == _LABEL_T:
|
||||
if sub.label == LABEL_T:
|
||||
self.remove_blossom_label_t(sub)
|
||||
self.assign_blossom_label_s(sub)
|
||||
self.change_s_blossom_to_subblossom(sub)
|
||||
|
||||
# Create the new blossom object.
|
||||
blossom = _NonTrivialBlossom(subblossoms, path.edges)
|
||||
blossom = NonTrivialBlossom(subblossoms, path.edges)
|
||||
|
||||
# Assign label S to the new blossom.
|
||||
blossom.label = _LABEL_S
|
||||
blossom.label = LABEL_S
|
||||
|
||||
# Prepare for lazy updating of S-blossom dual variable.
|
||||
blossom.dual_var = -self.delta_sum_2x
|
||||
|
@ -1257,9 +1257,9 @@ class _MatchingContext:
|
|||
|
||||
@staticmethod
|
||||
def find_path_through_blossom(
|
||||
blossom: _NonTrivialBlossom,
|
||||
sub: _Blossom
|
||||
) -> tuple[list[_Blossom], list[tuple[int, int]]]:
|
||||
blossom: NonTrivialBlossom,
|
||||
sub: Blossom
|
||||
) -> tuple[list[Blossom], list[tuple[int, int]]]:
|
||||
"""Construct a path with an even number of edges through the
|
||||
specified blossom, from sub-blossom "sub" to the base of "blossom".
|
||||
|
||||
|
@ -1285,14 +1285,14 @@ class _MatchingContext:
|
|||
|
||||
return (nodes, edges)
|
||||
|
||||
def expand_unlabeled_blossom(self, blossom: _NonTrivialBlossom) -> None:
|
||||
def expand_unlabeled_blossom(self, blossom: NonTrivialBlossom) -> None:
|
||||
"""Expand the specified unlabeled blossom.
|
||||
|
||||
This function takes total time O(n * log(n)) per stage.
|
||||
"""
|
||||
|
||||
assert blossom.parent is None
|
||||
assert blossom.label == _LABEL_NONE
|
||||
assert blossom.label == LABEL_NONE
|
||||
|
||||
# Remove blossom from the delta2 queue.
|
||||
self.delta2_disable_blossom(blossom)
|
||||
|
@ -1306,7 +1306,7 @@ class _MatchingContext:
|
|||
|
||||
# Convert sub-blossoms into top-level blossoms.
|
||||
for sub in blossom.subblossoms:
|
||||
assert sub.label == _LABEL_NONE
|
||||
assert sub.label == LABEL_NONE
|
||||
sub.parent = None
|
||||
|
||||
assert sub.vertex_dual_offset == 0
|
||||
|
@ -1320,14 +1320,14 @@ class _MatchingContext:
|
|||
# Delete the expanded blossom.
|
||||
self.nontrivial_blossom.remove(blossom)
|
||||
|
||||
def expand_t_blossom(self, blossom: _NonTrivialBlossom) -> None:
|
||||
def expand_t_blossom(self, blossom: NonTrivialBlossom) -> None:
|
||||
"""Expand the specified T-blossom.
|
||||
|
||||
This function takes total time O(n * log(n) + m) per stage.
|
||||
"""
|
||||
|
||||
assert blossom.parent is None
|
||||
assert blossom.label == _LABEL_T
|
||||
assert blossom.label == LABEL_T
|
||||
assert blossom.delta2_node is None
|
||||
|
||||
# Remove blossom from its alternating tree.
|
||||
|
@ -1391,9 +1391,9 @@ class _MatchingContext:
|
|||
|
||||
def augment_blossom_rec(
|
||||
self,
|
||||
blossom: _NonTrivialBlossom,
|
||||
sub: _Blossom,
|
||||
stack: list[tuple[_NonTrivialBlossom, _Blossom]]
|
||||
blossom: NonTrivialBlossom,
|
||||
sub: Blossom,
|
||||
stack: list[tuple[NonTrivialBlossom, Blossom]]
|
||||
) -> None:
|
||||
"""Augment along an alternating path through the specified blossom,
|
||||
from sub-blossom "sub" to the base vertex of the blossom.
|
||||
|
@ -1430,11 +1430,11 @@ class _MatchingContext:
|
|||
# Augment through the subblossoms touching the edge (x, y).
|
||||
# Nothing needs to be done for trivial subblossoms.
|
||||
bx = path_nodes[p+1]
|
||||
if isinstance(bx, _NonTrivialBlossom):
|
||||
if isinstance(bx, NonTrivialBlossom):
|
||||
stack.append((bx, self.trivial_blossom[x]))
|
||||
|
||||
by = path_nodes[p+2]
|
||||
if isinstance(by, _NonTrivialBlossom):
|
||||
if isinstance(by, NonTrivialBlossom):
|
||||
stack.append((by, self.trivial_blossom[y]))
|
||||
|
||||
# Rotate the subblossom list so the new base ends up in position 0.
|
||||
|
@ -1450,8 +1450,8 @@ class _MatchingContext:
|
|||
|
||||
def augment_blossom(
|
||||
self,
|
||||
blossom: _NonTrivialBlossom,
|
||||
sub: _Blossom
|
||||
blossom: NonTrivialBlossom,
|
||||
sub: Blossom
|
||||
) -> None:
|
||||
"""Augment along an alternating path through the specified blossom,
|
||||
from sub-blossom "sub" to the base vertex of the blossom.
|
||||
|
@ -1486,7 +1486,7 @@ class _MatchingContext:
|
|||
# Augment "blossom" from "sub" to the base vertex.
|
||||
self.augment_blossom_rec(blossom, sub, stack)
|
||||
|
||||
def augment_matching(self, path: _AlternatingPath) -> None:
|
||||
def augment_matching(self, path: AlternatingPath) -> None:
|
||||
"""Augment the matching through the specified augmenting path.
|
||||
|
||||
This function takes time O(n).
|
||||
|
@ -1515,11 +1515,11 @@ class _MatchingContext:
|
|||
# Augment the non-trivial blossoms on either side of this edge.
|
||||
# No action is necessary for trivial blossoms.
|
||||
bx = self.vertex_set_node[x].find()
|
||||
if isinstance(bx, _NonTrivialBlossom):
|
||||
if isinstance(bx, NonTrivialBlossom):
|
||||
self.augment_blossom(bx, self.trivial_blossom[x])
|
||||
|
||||
by = self.vertex_set_node[y].find()
|
||||
if isinstance(by, _NonTrivialBlossom):
|
||||
if isinstance(by, NonTrivialBlossom):
|
||||
self.augment_blossom(by, self.trivial_blossom[y])
|
||||
|
||||
# Pull the edge into the matching.
|
||||
|
@ -1551,7 +1551,7 @@ class _MatchingContext:
|
|||
assert y != -1
|
||||
|
||||
by = self.vertex_set_node[y].find()
|
||||
assert by.label == _LABEL_T
|
||||
assert by.label == LABEL_T
|
||||
assert by.tree_blossoms is not None
|
||||
|
||||
# Attach the blossom that contains "x" to the alternating tree.
|
||||
|
@ -1575,10 +1575,10 @@ class _MatchingContext:
|
|||
|
||||
bx = self.vertex_set_node[x].find()
|
||||
by = self.vertex_set_node[y].find()
|
||||
assert bx.label == _LABEL_S
|
||||
assert bx.label == LABEL_S
|
||||
|
||||
# Expand zero-dual blossoms before assigning label T.
|
||||
while isinstance(by, _NonTrivialBlossom) and (by.dual_var == 0):
|
||||
while isinstance(by, NonTrivialBlossom) and (by.dual_var == 0):
|
||||
self.expand_unlabeled_blossom(by)
|
||||
by = self.vertex_set_node[y].find()
|
||||
|
||||
|
@ -1617,8 +1617,8 @@ class _MatchingContext:
|
|||
bx = self.vertex_set_node[x].find()
|
||||
by = self.vertex_set_node[y].find()
|
||||
|
||||
assert bx.label == _LABEL_S
|
||||
assert by.label == _LABEL_S
|
||||
assert bx.label == LABEL_S
|
||||
assert by.label == LABEL_S
|
||||
assert bx is not by
|
||||
|
||||
# Trace back through the alternating trees from "x" and "y".
|
||||
|
@ -1680,7 +1680,7 @@ class _MatchingContext:
|
|||
|
||||
# Double-check that "x" is an S-vertex.
|
||||
bx = self.vertex_set_node[x].find()
|
||||
assert bx.label == _LABEL_S
|
||||
assert bx.label == LABEL_S
|
||||
|
||||
# Scan the edges that are incident on "x".
|
||||
# This loop runs through O(m) iterations per stage.
|
||||
|
@ -1703,7 +1703,7 @@ class _MatchingContext:
|
|||
if bx is by:
|
||||
continue
|
||||
|
||||
if by.label == _LABEL_S:
|
||||
if by.label == LABEL_S:
|
||||
self.delta3_add_edge(e)
|
||||
else:
|
||||
self.delta2_add_edge(e, y, by)
|
||||
|
@ -1716,7 +1716,7 @@ class _MatchingContext:
|
|||
|
||||
def calc_dual_delta_step(
|
||||
self
|
||||
) -> tuple[int, float, int, Optional[_NonTrivialBlossom]]:
|
||||
) -> tuple[int, float, int, Optional[NonTrivialBlossom]]:
|
||||
"""Calculate a delta step in the dual LPP problem.
|
||||
|
||||
This function returns the minimum of the 4 types of delta values,
|
||||
|
@ -1740,7 +1740,7 @@ class _MatchingContext:
|
|||
Tuple (delta_type, delta_2x, delta_edge, delta_blossom).
|
||||
"""
|
||||
delta_edge = -1
|
||||
delta_blossom: Optional[_NonTrivialBlossom] = None
|
||||
delta_blossom: Optional[NonTrivialBlossom] = None
|
||||
|
||||
# Compute delta1: minimum dual variable of any S-vertex.
|
||||
# All unmatched vertices have the same dual value, and this is
|
||||
|
@ -1770,7 +1770,7 @@ class _MatchingContext:
|
|||
# This takes time O(log(n)).
|
||||
if not self.delta4_queue.empty():
|
||||
blossom = self.delta4_queue.find_min().data
|
||||
assert blossom.label == _LABEL_T
|
||||
assert blossom.label == LABEL_T
|
||||
assert blossom.parent is None
|
||||
blossom_dual = blossom.dual_var - self.delta_sum_2x
|
||||
if blossom_dual <= delta_2x:
|
||||
|
@ -1847,7 +1847,7 @@ class _MatchingContext:
|
|||
# Use the edge from S-vertex to unlabeled vertex that got
|
||||
# unlocked through the delta update.
|
||||
(x, y, _w) = self.graph.edges[delta_edge]
|
||||
if self.vertex_set_node[x].find().label != _LABEL_S:
|
||||
if self.vertex_set_node[x].find().label != LABEL_S:
|
||||
(x, y) = (y, x)
|
||||
self.extend_tree_s_to_t(x, y)
|
||||
|
||||
|
@ -1886,9 +1886,9 @@ class _MatchingContext:
|
|||
self.nontrivial_blossom):
|
||||
|
||||
# Remove blossom label.
|
||||
if (blossom.parent is None) and (blossom.label != _LABEL_NONE):
|
||||
if (blossom.parent is None) and (blossom.label != LABEL_NONE):
|
||||
self.reset_blossom_label(blossom)
|
||||
assert blossom.label == _LABEL_NONE
|
||||
assert blossom.label == LABEL_NONE
|
||||
|
||||
# Remove blossom from alternating tree.
|
||||
blossom.tree_edge = None
|
||||
|
@ -1906,8 +1906,8 @@ class _MatchingContext:
|
|||
|
||||
|
||||
def _verify_blossom_edges(
|
||||
ctx: _MatchingContext,
|
||||
blossom: _NonTrivialBlossom,
|
||||
ctx: MatchingContext,
|
||||
blossom: NonTrivialBlossom,
|
||||
edge_slack_2x: list[float]
|
||||
) -> None:
|
||||
"""Descend down the blossom tree to find edges that are contained
|
||||
|
@ -1943,7 +1943,7 @@ def _verify_blossom_edges(
|
|||
path_num_matched: list[int] = [0]
|
||||
|
||||
# Use an explicit stack to avoid deep recursion.
|
||||
stack: list[tuple[_NonTrivialBlossom, int]] = [(blossom, -1)]
|
||||
stack: list[tuple[NonTrivialBlossom, int]] = [(blossom, -1)]
|
||||
|
||||
while stack:
|
||||
(blossom, p) = stack[-1]
|
||||
|
@ -1969,7 +1969,7 @@ def _verify_blossom_edges(
|
|||
|
||||
# Examine the next sub-blossom at the current level.
|
||||
sub = blossom.subblossoms[p]
|
||||
if isinstance(sub, _NonTrivialBlossom):
|
||||
if isinstance(sub, NonTrivialBlossom):
|
||||
# Prepare to descent into the selected sub-blossom and
|
||||
# scan it recursively.
|
||||
stack.append((sub, -1))
|
||||
|
@ -2031,7 +2031,7 @@ def _verify_blossom_edges(
|
|||
stack.pop()
|
||||
|
||||
|
||||
def _verify_optimum(ctx: _MatchingContext) -> None:
|
||||
def verify_optimum(ctx: MatchingContext) -> None:
|
||||
"""Verify that the optimum solution has been found.
|
||||
|
||||
This function takes time O(n**2).
|
|
@ -4,10 +4,12 @@ import math
|
|||
import unittest
|
||||
from unittest.mock import Mock
|
||||
|
||||
import mwmatching
|
||||
from mwmatching import (
|
||||
maximum_weight_matching as mwm,
|
||||
adjust_weights_for_maximum_cardinality_matching as adj)
|
||||
from mwmatching.algorithm import (
|
||||
MatchingError, GraphInfo, Blossom, NonTrivialBlossom, MatchingContext,
|
||||
verify_optimum)
|
||||
|
||||
|
||||
class TestMaximumWeightMatching(unittest.TestCase):
|
||||
|
@ -431,10 +433,10 @@ class TestMaximumCardinalityMatching(unittest.TestCase):
|
|||
|
||||
|
||||
class TestGraphInfo(unittest.TestCase):
|
||||
"""Test _GraphInfo helper class."""
|
||||
"""Test GraphInfo helper class."""
|
||||
|
||||
def test_empty(self):
|
||||
graph = mwmatching._GraphInfo([])
|
||||
graph = GraphInfo([])
|
||||
self.assertEqual(graph.num_vertex, 0)
|
||||
self.assertEqual(graph.edges, [])
|
||||
self.assertEqual(graph.adjacent_edges, [])
|
||||
|
@ -449,8 +451,8 @@ class TestVerificationFail(unittest.TestCase):
|
|||
vertex_mate,
|
||||
vertex_dual_2x,
|
||||
nontrivial_blossom):
|
||||
ctx = Mock(spec=mwmatching._MatchingContext)
|
||||
ctx.graph = mwmatching._GraphInfo(edges)
|
||||
ctx = Mock(spec=MatchingContext)
|
||||
ctx.graph = GraphInfo(edges)
|
||||
ctx.vertex_mate = vertex_mate
|
||||
ctx.vertex_dual_2x = vertex_dual_2x
|
||||
ctx.nontrivial_blossom = nontrivial_blossom
|
||||
|
@ -463,7 +465,7 @@ class TestVerificationFail(unittest.TestCase):
|
|||
vertex_mate=[-1, 2, 1],
|
||||
vertex_dual_2x=[0, 20, 2],
|
||||
nontrivial_blossom=[])
|
||||
mwmatching._verify_optimum(ctx)
|
||||
verify_optimum(ctx)
|
||||
|
||||
def test_asymmetric_matching(self):
|
||||
edges = [(0,1,10), (1,2,11)]
|
||||
|
@ -472,8 +474,8 @@ class TestVerificationFail(unittest.TestCase):
|
|||
vertex_mate=[-1, 2, 0],
|
||||
vertex_dual_2x=[0, 20, 2],
|
||||
nontrivial_blossom=[])
|
||||
with self.assertRaises(mwmatching.MatchingError):
|
||||
mwmatching._verify_optimum(ctx)
|
||||
with self.assertRaises(MatchingError):
|
||||
verify_optimum(ctx)
|
||||
|
||||
def test_nonexistent_matched_edge(self):
|
||||
edges = [(0,1,10), (1,2,11)]
|
||||
|
@ -482,8 +484,8 @@ class TestVerificationFail(unittest.TestCase):
|
|||
vertex_mate=[2, -1, 0],
|
||||
vertex_dual_2x=[11, 11, 11],
|
||||
nontrivial_blossom=[])
|
||||
with self.assertRaises(mwmatching.MatchingError):
|
||||
mwmatching._verify_optimum(ctx)
|
||||
with self.assertRaises(MatchingError):
|
||||
verify_optimum(ctx)
|
||||
|
||||
def test_negative_vertex_dual(self):
|
||||
edges = [(0,1,10), (1,2,11)]
|
||||
|
@ -492,8 +494,8 @@ class TestVerificationFail(unittest.TestCase):
|
|||
vertex_mate=[-1, 2, 1],
|
||||
vertex_dual_2x=[-2, 22, 0],
|
||||
nontrivial_blossom=[])
|
||||
with self.assertRaises(mwmatching.MatchingError):
|
||||
mwmatching._verify_optimum(ctx)
|
||||
with self.assertRaises(MatchingError):
|
||||
verify_optimum(ctx)
|
||||
|
||||
def test_unmatched_nonzero_dual(self):
|
||||
edges = [(0,1,10), (1,2,11)]
|
||||
|
@ -502,8 +504,8 @@ class TestVerificationFail(unittest.TestCase):
|
|||
vertex_mate=[-1, 2, 1],
|
||||
vertex_dual_2x=[9, 11, 11],
|
||||
nontrivial_blossom=[])
|
||||
with self.assertRaises(mwmatching.MatchingError):
|
||||
mwmatching._verify_optimum(ctx)
|
||||
with self.assertRaises(MatchingError):
|
||||
verify_optimum(ctx)
|
||||
|
||||
def test_negative_edge_slack(self):
|
||||
edges = [(0,1,10), (1,2,11)]
|
||||
|
@ -512,8 +514,8 @@ class TestVerificationFail(unittest.TestCase):
|
|||
vertex_mate=[-1, 2, 1],
|
||||
vertex_dual_2x=[0, 11, 11],
|
||||
nontrivial_blossom=[])
|
||||
with self.assertRaises(mwmatching.MatchingError):
|
||||
mwmatching._verify_optimum(ctx)
|
||||
with self.assertRaises(MatchingError):
|
||||
verify_optimum(ctx)
|
||||
|
||||
def test_matched_edge_slack(self):
|
||||
edges = [(0,1,10), (1,2,11)]
|
||||
|
@ -522,8 +524,8 @@ class TestVerificationFail(unittest.TestCase):
|
|||
vertex_mate=[-1, 2, 1],
|
||||
vertex_dual_2x=[0, 20, 11],
|
||||
nontrivial_blossom=[])
|
||||
with self.assertRaises(mwmatching.MatchingError):
|
||||
mwmatching._verify_optimum(ctx)
|
||||
with self.assertRaises(MatchingError):
|
||||
verify_optimum(ctx)
|
||||
|
||||
def test_negative_blossom_dual(self):
|
||||
#
|
||||
|
@ -532,11 +534,8 @@ class TestVerificationFail(unittest.TestCase):
|
|||
# \----8-----/
|
||||
#
|
||||
edges = [(0,1,7), (0,2,8), (1,2,9), (2,3,6)]
|
||||
blossom = mwmatching._NonTrivialBlossom(
|
||||
subblossoms=[
|
||||
mwmatching._Blossom(0),
|
||||
mwmatching._Blossom(1),
|
||||
mwmatching._Blossom(2)],
|
||||
blossom = NonTrivialBlossom(
|
||||
subblossoms=[Blossom(0), Blossom(1), Blossom(2)],
|
||||
edges=[0,2,1])
|
||||
for sub in blossom.subblossoms:
|
||||
sub.parent = blossom
|
||||
|
@ -546,8 +545,8 @@ class TestVerificationFail(unittest.TestCase):
|
|||
vertex_mate=[1, 0, 3, 2],
|
||||
vertex_dual_2x=[4, 6, 8, 4],
|
||||
nontrivial_blossom=[blossom])
|
||||
with self.assertRaises(mwmatching.MatchingError):
|
||||
mwmatching._verify_optimum(ctx)
|
||||
with self.assertRaises(MatchingError):
|
||||
verify_optimum(ctx)
|
||||
|
||||
def test_blossom_not_full(self):
|
||||
#
|
||||
|
@ -560,11 +559,8 @@ class TestVerificationFail(unittest.TestCase):
|
|||
# \----2-----/
|
||||
#
|
||||
edges = [(0,1,7), (0,2,2), (1,2,5), (0,3,8), (1,4,8)]
|
||||
blossom = mwmatching._NonTrivialBlossom(
|
||||
subblossoms=[
|
||||
mwmatching._Blossom(0),
|
||||
mwmatching._Blossom(1),
|
||||
mwmatching._Blossom(2)],
|
||||
blossom = NonTrivialBlossom(
|
||||
subblossoms=[Blossom(0), Blossom(1), Blossom(2)],
|
||||
edges=[0,2,1])
|
||||
for sub in blossom.subblossoms:
|
||||
sub.parent = blossom
|
||||
|
@ -574,8 +570,8 @@ class TestVerificationFail(unittest.TestCase):
|
|||
vertex_mate=[3, 4, -1, 0, 1],
|
||||
vertex_dual_2x=[4, 10, 0, 12, 6],
|
||||
nontrivial_blossom=[blossom])
|
||||
with self.assertRaises(mwmatching.MatchingError):
|
||||
mwmatching._verify_optimum(ctx)
|
||||
with self.assertRaises(MatchingError):
|
||||
verify_optimum(ctx)
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
|
@ -3,7 +3,7 @@
|
|||
import random
|
||||
import unittest
|
||||
|
||||
from datastruct import UnionFindQueue, PriorityQueue
|
||||
from mwmatching.datastruct import UnionFindQueue, PriorityQueue
|
||||
|
||||
|
||||
class TestUnionFindQueue(unittest.TestCase):
|
|
@ -4,7 +4,7 @@ set -e
|
|||
|
||||
echo
|
||||
echo "Running pycodestyle"
|
||||
pycodestyle python/mwmatching.py python/datastruct.py tests
|
||||
pycodestyle python/mwmatching python/run_matching.py tests
|
||||
|
||||
echo
|
||||
echo "Running mypy"
|
||||
|
@ -12,20 +12,15 @@ mypy --disallow-incomplete-defs python tests
|
|||
|
||||
echo
|
||||
echo "Running pylint"
|
||||
pylint --ignore=test_mwmatching.py python tests || [ $(($? & 3)) -eq 0 ]
|
||||
pylint --ignore=test_algorithm.py python tests/*.py tests/generate/*.py || [ $(($? & 3)) -eq 0 ]
|
||||
|
||||
echo
|
||||
echo "Running test_mwmatching.py"
|
||||
python3 python/test_mwmatching.py
|
||||
|
||||
echo
|
||||
echo "Running test_datastruct.py"
|
||||
python3 python/test_datastruct.py
|
||||
echo "Running unit tests"
|
||||
python3 -m unittest discover -t python -s python/tests
|
||||
|
||||
echo
|
||||
echo "Checking test coverage"
|
||||
coverage erase
|
||||
coverage run --branch python/test_datastruct.py
|
||||
coverage run -a --branch python/test_mwmatching.py
|
||||
coverage run --branch -m unittest discover -t python -s python/tests
|
||||
coverage report -m
|
||||
|
||||
|
|
|
@ -19,13 +19,12 @@ count_delta_step = [0]
|
|||
|
||||
def patch_matching_code() -> None:
|
||||
"""Patch the matching code to count events."""
|
||||
# pylint: disable=import-outside-toplevel,protected-access
|
||||
# pylint: disable=import-outside-toplevel
|
||||
|
||||
import mwmatching
|
||||
from mwmatching.algorithm import MatchingContext
|
||||
|
||||
orig_make_blossom = mwmatching._MatchingContext.make_blossom
|
||||
orig_calc_dual_delta_step = (
|
||||
mwmatching._MatchingContext.calc_dual_delta_step)
|
||||
orig_make_blossom = MatchingContext.make_blossom
|
||||
orig_calc_dual_delta_step = MatchingContext.calc_dual_delta_step
|
||||
|
||||
def stub_make_blossom(*args: Any, **kwargs: Any) -> Any:
|
||||
count_make_blossom[0] += 1
|
||||
|
@ -36,9 +35,8 @@ def patch_matching_code() -> None:
|
|||
ret = orig_calc_dual_delta_step(*args, **kwargs)
|
||||
return ret
|
||||
|
||||
mwmatching._MatchingContext.make_blossom = ( # type: ignore
|
||||
stub_make_blossom)
|
||||
mwmatching._MatchingContext.calc_dual_delta_step = ( # type: ignore
|
||||
MatchingContext.make_blossom = stub_make_blossom # type: ignore
|
||||
MatchingContext.calc_dual_delta_step = ( # type: ignore
|
||||
stub_calc_dual_delta_step)
|
||||
|
||||
|
||||
|
|
Loading…
Reference in New Issue