171 lines
5.7 KiB
Python
171 lines
5.7 KiB
Python
"""
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Algorithms for asteroidal triples and asteroidal numbers in graphs.
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An asteroidal triple in a graph G is a set of three non-adjacent vertices
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u, v and w such that there exist a path between any two of them that avoids
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closed neighborhood of the third. More formally, v_j, v_k belongs to the same
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connected component of G - N[v_i], where N[v_i] denotes the closed neighborhood
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of v_i. A graph which does not contain any asteroidal triples is called
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an AT-free graph. The class of AT-free graphs is a graph class for which
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many NP-complete problems are solvable in polynomial time. Amongst them,
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independent set and coloring.
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"""
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import networkx as nx
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from networkx.utils import not_implemented_for
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__all__ = ["is_at_free", "find_asteroidal_triple"]
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@not_implemented_for("directed")
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@not_implemented_for("multigraph")
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@nx._dispatch
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def find_asteroidal_triple(G):
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r"""Find an asteroidal triple in the given graph.
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An asteroidal triple is a triple of non-adjacent vertices such that
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there exists a path between any two of them which avoids the closed
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neighborhood of the third. It checks all independent triples of vertices
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and whether they are an asteroidal triple or not. This is done with the
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help of a data structure called a component structure.
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A component structure encodes information about which vertices belongs to
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the same connected component when the closed neighborhood of a given vertex
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is removed from the graph. The algorithm used to check is the trivial
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one, outlined in [1]_, which has a runtime of
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:math:`O(|V||\overline{E} + |V||E|)`, where the second term is the
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creation of the component structure.
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Parameters
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----------
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G : NetworkX Graph
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The graph to check whether is AT-free or not
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Returns
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-------
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list or None
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An asteroidal triple is returned as a list of nodes. If no asteroidal
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triple exists, i.e. the graph is AT-free, then None is returned.
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The returned value depends on the certificate parameter. The default
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option is a bool which is True if the graph is AT-free, i.e. the
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given graph contains no asteroidal triples, and False otherwise, i.e.
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if the graph contains at least one asteroidal triple.
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Notes
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-----
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The component structure and the algorithm is described in [1]_. The current
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implementation implements the trivial algorithm for simple graphs.
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References
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----------
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.. [1] Ekkehard Köhler,
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"Recognizing Graphs without asteroidal triples",
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Journal of Discrete Algorithms 2, pages 439-452, 2004.
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https://www.sciencedirect.com/science/article/pii/S157086670400019X
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"""
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V = set(G.nodes)
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if len(V) < 6:
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# An asteroidal triple cannot exist in a graph with 5 or less vertices.
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return None
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component_structure = create_component_structure(G)
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E_complement = set(nx.complement(G).edges)
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for e in E_complement:
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u = e[0]
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v = e[1]
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u_neighborhood = set(G[u]).union([u])
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v_neighborhood = set(G[v]).union([v])
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union_of_neighborhoods = u_neighborhood.union(v_neighborhood)
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for w in V - union_of_neighborhoods:
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# Check for each pair of vertices whether they belong to the
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# same connected component when the closed neighborhood of the
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# third is removed.
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if (
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component_structure[u][v] == component_structure[u][w]
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and component_structure[v][u] == component_structure[v][w]
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and component_structure[w][u] == component_structure[w][v]
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):
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return [u, v, w]
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return None
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@not_implemented_for("directed")
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@not_implemented_for("multigraph")
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@nx._dispatch
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def is_at_free(G):
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"""Check if a graph is AT-free.
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The method uses the `find_asteroidal_triple` method to recognize
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an AT-free graph. If no asteroidal triple is found the graph is
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AT-free and True is returned. If at least one asteroidal triple is
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found the graph is not AT-free and False is returned.
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Parameters
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----------
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G : NetworkX Graph
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The graph to check whether is AT-free or not.
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Returns
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-------
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bool
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True if G is AT-free and False otherwise.
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Examples
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--------
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>>> G = nx.Graph([(0, 1), (0, 2), (1, 2), (1, 3), (1, 4), (4, 5)])
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>>> nx.is_at_free(G)
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True
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>>> G = nx.cycle_graph(6)
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>>> nx.is_at_free(G)
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False
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"""
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return find_asteroidal_triple(G) is None
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@not_implemented_for("directed")
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@not_implemented_for("multigraph")
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@nx._dispatch
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def create_component_structure(G):
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r"""Create component structure for G.
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A *component structure* is an `nxn` array, denoted `c`, where `n` is
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the number of vertices, where each row and column corresponds to a vertex.
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.. math::
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c_{uv} = \begin{cases} 0, if v \in N[u] \\
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k, if v \in component k of G \setminus N[u] \end{cases}
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Where `k` is an arbitrary label for each component. The structure is used
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to simplify the detection of asteroidal triples.
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Parameters
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----------
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G : NetworkX Graph
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Undirected, simple graph.
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Returns
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-------
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component_structure : dictionary
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A dictionary of dictionaries, keyed by pairs of vertices.
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"""
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V = set(G.nodes)
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component_structure = {}
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for v in V:
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label = 0
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closed_neighborhood = set(G[v]).union({v})
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row_dict = {}
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for u in closed_neighborhood:
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row_dict[u] = 0
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G_reduced = G.subgraph(set(G.nodes) - closed_neighborhood)
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for cc in nx.connected_components(G_reduced):
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label += 1
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for u in cc:
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row_dict[u] = label
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component_structure[v] = row_dict
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return component_structure
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