1065 lines
30 KiB
Python
1065 lines
30 KiB
Python
"""
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Various small and named graphs, together with some compact generators.
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"""
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__all__ = [
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"make_small_graph",
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"LCF_graph",
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"bull_graph",
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"chvatal_graph",
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"cubical_graph",
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"desargues_graph",
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"diamond_graph",
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"dodecahedral_graph",
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"frucht_graph",
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"heawood_graph",
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"hoffman_singleton_graph",
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"house_graph",
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"house_x_graph",
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"icosahedral_graph",
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"krackhardt_kite_graph",
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"moebius_kantor_graph",
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"octahedral_graph",
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"pappus_graph",
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"petersen_graph",
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"sedgewick_maze_graph",
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"tetrahedral_graph",
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"truncated_cube_graph",
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"truncated_tetrahedron_graph",
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"tutte_graph",
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]
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from functools import wraps
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import networkx as nx
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from networkx.generators.classic import (
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empty_graph,
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cycle_graph,
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path_graph,
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complete_graph,
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)
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from networkx.exception import NetworkXError
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def _raise_on_directed(func):
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"""
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A decorator which inspects the `create_using` argument and raises a
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NetworkX exception when `create_using` is a DiGraph (class or instance) for
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graph generators that do not support directed outputs.
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"""
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@wraps(func)
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def wrapper(*args, **kwargs):
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if kwargs.get("create_using") is not None:
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G = nx.empty_graph(create_using=kwargs["create_using"])
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if G.is_directed():
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raise NetworkXError("Directed Graph not supported")
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return func(*args, **kwargs)
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return wrapper
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def make_small_undirected_graph(graph_description, create_using=None):
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"""
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Return a small undirected graph described by graph_description.
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.. deprecated:: 2.7
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make_small_undirected_graph is deprecated and will be removed in
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version 3.0. If "ltype" == "adjacencylist", convert the list to a dict
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and use `from_dict_of_lists`. If "ltype" == "edgelist", use
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`from_edgelist`.
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See make_small_graph.
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"""
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import warnings
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msg = (
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"\n\nmake_small_undirected_graph is deprecated and will be removed in "
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"version 3.0.\n"
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"If `ltype` == 'adjacencylist', convert `xlist` to a dict and use\n"
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"`from_dict_of_lists` instead.\n"
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"If `ltype` == 'edgelist', use `from_edgelist` instead."
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)
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warnings.warn(msg, category=DeprecationWarning, stacklevel=2)
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G = empty_graph(0, create_using)
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if G.is_directed():
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raise NetworkXError("Directed Graph not supported")
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return make_small_graph(graph_description, G)
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def make_small_graph(graph_description, create_using=None):
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"""
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Return the small graph described by graph_description.
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.. deprecated:: 2.7
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make_small_graph is deprecated and will be removed in
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version 3.0. If "ltype" == "adjacencylist", convert the list to a dict
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and use `from_dict_of_lists`. If "ltype" == "edgelist", use
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`from_edgelist`.
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graph_description is a list of the form [ltype,name,n,xlist]
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Here ltype is one of "adjacencylist" or "edgelist",
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name is the name of the graph and n the number of nodes.
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This constructs a graph of n nodes with integer labels 0,..,n-1.
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If ltype="adjacencylist" then xlist is an adjacency list
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with exactly n entries, in with the j'th entry (which can be empty)
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specifies the nodes connected to vertex j.
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e.g. the "square" graph C_4 can be obtained by
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>>> G = nx.make_small_graph(
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... ["adjacencylist", "C_4", 4, [[2, 4], [1, 3], [2, 4], [1, 3]]]
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... )
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or, since we do not need to add edges twice,
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>>> G = nx.make_small_graph(["adjacencylist", "C_4", 4, [[2, 4], [3], [4], []]])
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If ltype="edgelist" then xlist is an edge list
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written as [[v1,w2],[v2,w2],...,[vk,wk]],
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where vj and wj integers in the range 1,..,n
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e.g. the "square" graph C_4 can be obtained by
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>>> G = nx.make_small_graph(
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... ["edgelist", "C_4", 4, [[1, 2], [3, 4], [2, 3], [4, 1]]]
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... )
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Use the create_using argument to choose the graph class/type.
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"""
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import warnings
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msg = (
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"\n\nmake_small_graph is deprecated and will be removed in version 3.0.\n"
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"If `ltype` == 'adjacencylist', convert `xlist` to a dict and use\n"
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"`from_dict_of_lists` instead.\n"
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"If `ltype` == 'edgelist', use `from_edgelist` instead."
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)
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warnings.warn(msg, category=DeprecationWarning, stacklevel=2)
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if graph_description[0] not in ("adjacencylist", "edgelist"):
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raise NetworkXError("ltype must be either adjacencylist or edgelist")
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ltype = graph_description[0]
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name = graph_description[1]
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n = graph_description[2]
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G = empty_graph(n, create_using)
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nodes = G.nodes()
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if ltype == "adjacencylist":
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adjlist = graph_description[3]
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if len(adjlist) != n:
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raise NetworkXError("invalid graph_description")
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G.add_edges_from([(u - 1, v) for v in nodes for u in adjlist[v]])
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elif ltype == "edgelist":
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edgelist = graph_description[3]
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for e in edgelist:
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v1 = e[0] - 1
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v2 = e[1] - 1
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if v1 < 0 or v1 > n - 1 or v2 < 0 or v2 > n - 1:
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raise NetworkXError("invalid graph_description")
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else:
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G.add_edge(v1, v2)
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G.name = name
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return G
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def LCF_graph(n, shift_list, repeats, create_using=None):
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"""
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Return the cubic graph specified in LCF notation.
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LCF notation (LCF=Lederberg-Coxeter-Fruchte) is a compressed
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notation used in the generation of various cubic Hamiltonian
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graphs of high symmetry. See, for example, dodecahedral_graph,
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desargues_graph, heawood_graph and pappus_graph below.
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n (number of nodes)
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The starting graph is the n-cycle with nodes 0,...,n-1.
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(The null graph is returned if n < 0.)
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shift_list = [s1,s2,..,sk], a list of integer shifts mod n,
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repeats
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integer specifying the number of times that shifts in shift_list
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are successively applied to each v_current in the n-cycle
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to generate an edge between v_current and v_current+shift mod n.
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For v1 cycling through the n-cycle a total of k*repeats
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with shift cycling through shiftlist repeats times connect
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v1 with v1+shift mod n
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The utility graph $K_{3,3}$
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>>> G = nx.LCF_graph(6, [3, -3], 3)
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The Heawood graph
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>>> G = nx.LCF_graph(14, [5, -5], 7)
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See http://mathworld.wolfram.com/LCFNotation.html for a description
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and references.
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"""
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if n <= 0:
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return empty_graph(0, create_using)
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# start with the n-cycle
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G = cycle_graph(n, create_using)
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if G.is_directed():
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raise NetworkXError("Directed Graph not supported")
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G.name = "LCF_graph"
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nodes = sorted(list(G))
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n_extra_edges = repeats * len(shift_list)
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# edges are added n_extra_edges times
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# (not all of these need be new)
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if n_extra_edges < 1:
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return G
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for i in range(n_extra_edges):
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shift = shift_list[i % len(shift_list)] # cycle through shift_list
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v1 = nodes[i % n] # cycle repeatedly through nodes
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v2 = nodes[(i + shift) % n]
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G.add_edge(v1, v2)
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return G
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# -------------------------------------------------------------------------------
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# Various small and named graphs
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# -------------------------------------------------------------------------------
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@_raise_on_directed
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def bull_graph(create_using=None):
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"""
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Returns the Bull Graph
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The Bull Graph has 5 nodes and 5 edges. It is a planar undirected
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graph in the form of a triangle with two disjoint pendant edges [1]_
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The name comes from the triangle and pendant edges representing
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respectively the body and legs of a bull.
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Parameters
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----------
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create_using : NetworkX graph constructor, optional (default=nx.Graph)
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Graph type to create. If graph instance, then cleared before populated.
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Returns
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-------
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G : networkx Graph
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A bull graph with 5 nodes
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References
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----------
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.. [1] https://en.wikipedia.org/wiki/Bull_graph.
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"""
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G = nx.from_dict_of_lists(
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{0: [1, 2], 1: [0, 2, 3], 2: [0, 1, 4], 3: [1], 4: [2]},
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create_using=create_using,
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)
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G.name = "Bull Graph"
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return G
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@_raise_on_directed
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def chvatal_graph(create_using=None):
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"""
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Returns the Chvátal Graph
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The Chvátal Graph is an undirected graph with 12 nodes and 24 edges [1]_.
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It has 370 distinct (directed) Hamiltonian cycles, giving a unique generalized
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LCF notation of order 4, two of order 6 , and 43 of order 1 [2]_.
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Parameters
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----------
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create_using : NetworkX graph constructor, optional (default=nx.Graph)
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Graph type to create. If graph instance, then cleared before populated.
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Returns
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-------
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G : networkx Graph
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The Chvátal graph with 12 nodes and 24 edges
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References
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----------
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.. [1] https://en.wikipedia.org/wiki/Chv%C3%A1tal_graph
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.. [2] https://mathworld.wolfram.com/ChvatalGraph.html
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"""
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G = nx.from_dict_of_lists(
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{
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0: [1, 4, 6, 9],
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1: [2, 5, 7],
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2: [3, 6, 8],
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3: [4, 7, 9],
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4: [5, 8],
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5: [10, 11],
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6: [10, 11],
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7: [8, 11],
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8: [10],
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9: [10, 11],
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},
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create_using=create_using,
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)
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G.name = "Chvatal Graph"
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return G
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@_raise_on_directed
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def cubical_graph(create_using=None):
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"""
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Returns the 3-regular Platonic Cubical Graph
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||
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The skeleton of the cube (the nodes and edges) form a graph, with 8
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nodes, and 12 edges. It is a special case of the hypercube graph.
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It is one of 5 Platonic graphs, each a skeleton of its
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Platonic solid [1]_.
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Such graphs arise in parallel processing in computers.
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||
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Parameters
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||
----------
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||
create_using : NetworkX graph constructor, optional (default=nx.Graph)
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||
Graph type to create. If graph instance, then cleared before populated.
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||
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Returns
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||
-------
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G : networkx Graph
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||
A cubical graph with 8 nodes and 12 edges
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References
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----------
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.. [1] https://en.wikipedia.org/wiki/Cube#Cubical_graph
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"""
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G = nx.from_dict_of_lists(
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{
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0: [1, 3, 4],
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1: [0, 2, 7],
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2: [1, 3, 6],
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3: [0, 2, 5],
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4: [0, 5, 7],
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5: [3, 4, 6],
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6: [2, 5, 7],
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7: [1, 4, 6],
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},
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create_using=create_using,
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)
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G.name = ("Platonic Cubical Graph",)
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return G
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||
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||
def desargues_graph(create_using=None):
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||
"""
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Returns the Desargues Graph
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||
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The Desargues Graph is a non-planar, distance-transitive cubic graph
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||
with 20 nodes and 30 edges [1]_.
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It is a symmetric graph. It can be represented in LCF notation
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as [5,-5,9,-9]^5 [2]_.
|
||
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Parameters
|
||
----------
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||
create_using : NetworkX graph constructor, optional (default=nx.Graph)
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||
Graph type to create. If graph instance, then cleared before populated.
|
||
|
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Returns
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||
-------
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G : networkx Graph
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||
Desargues Graph with 20 nodes and 30 edges
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||
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References
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||
----------
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.. [1] https://en.wikipedia.org/wiki/Desargues_graph
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.. [2] https://mathworld.wolfram.com/DesarguesGraph.html
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||
"""
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G = LCF_graph(20, [5, -5, 9, -9], 5, create_using)
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G.name = "Desargues Graph"
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return G
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||
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||
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@_raise_on_directed
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||
def diamond_graph(create_using=None):
|
||
"""
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||
Returns the Diamond graph
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||
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||
The Diamond Graph is planar undirected graph with 4 nodes and 5 edges.
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||
It is also sometimes known as the double triangle graph or kite graph [1]_.
|
||
|
||
Parameters
|
||
----------
|
||
create_using : NetworkX graph constructor, optional (default=nx.Graph)
|
||
Graph type to create. If graph instance, then cleared before populated.
|
||
|
||
Returns
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||
-------
|
||
G : networkx Graph
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||
Diamond Graph with 4 nodes and 5 edges
|
||
|
||
References
|
||
----------
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||
.. [1] https://mathworld.wolfram.com/DiamondGraph.html
|
||
"""
|
||
G = nx.from_dict_of_lists(
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||
{0: [1, 2], 1: [0, 2, 3], 2: [0, 1, 3], 3: [1, 2]}, create_using=create_using
|
||
)
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||
G.name = "Diamond Graph"
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||
return G
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||
|
||
|
||
def dodecahedral_graph(create_using=None):
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||
"""
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||
Returns the Platonic Dodecahedral graph.
|
||
|
||
The dodecahedral graph has 20 nodes and 30 edges. The skeleton of the
|
||
dodecahedron forms a graph. It is one of 5 Platonic graphs [1]_.
|
||
It can be described in LCF notation as:
|
||
``[10, 7, 4, -4, -7, 10, -4, 7, -7, 4]^2`` [2]_.
|
||
|
||
Parameters
|
||
----------
|
||
create_using : NetworkX graph constructor, optional (default=nx.Graph)
|
||
Graph type to create. If graph instance, then cleared before populated.
|
||
|
||
Returns
|
||
-------
|
||
G : networkx Graph
|
||
Dodecahedral Graph with 20 nodes and 30 edges
|
||
|
||
References
|
||
----------
|
||
.. [1] https://en.wikipedia.org/wiki/Regular_dodecahedron#Dodecahedral_graph
|
||
.. [2] https://mathworld.wolfram.com/DodecahedralGraph.html
|
||
|
||
"""
|
||
G = LCF_graph(20, [10, 7, 4, -4, -7, 10, -4, 7, -7, 4], 2, create_using)
|
||
G.name = "Dodecahedral Graph"
|
||
return G
|
||
|
||
|
||
def frucht_graph(create_using=None):
|
||
"""
|
||
Returns the Frucht Graph.
|
||
|
||
The Frucht Graph is the smallest cubical graph whose
|
||
automorphism group consists only of the identity element [1]_.
|
||
It has 12 nodes and 18 edges and no nontrivial symmetries.
|
||
It is planar and Hamiltonian [2]_.
|
||
|
||
Parameters
|
||
----------
|
||
create_using : NetworkX graph constructor, optional (default=nx.Graph)
|
||
Graph type to create. If graph instance, then cleared before populated.
|
||
|
||
Returns
|
||
-------
|
||
G : networkx Graph
|
||
Frucht Graph with 12 nodes and 18 edges
|
||
|
||
References
|
||
----------
|
||
.. [1] https://en.wikipedia.org/wiki/Frucht_graph
|
||
.. [2] https://mathworld.wolfram.com/FruchtGraph.html
|
||
|
||
"""
|
||
G = cycle_graph(7, create_using)
|
||
G.add_edges_from(
|
||
[
|
||
[0, 7],
|
||
[1, 7],
|
||
[2, 8],
|
||
[3, 9],
|
||
[4, 9],
|
||
[5, 10],
|
||
[6, 10],
|
||
[7, 11],
|
||
[8, 11],
|
||
[8, 9],
|
||
[10, 11],
|
||
]
|
||
)
|
||
|
||
G.name = "Frucht Graph"
|
||
return G
|
||
|
||
|
||
def heawood_graph(create_using=None):
|
||
"""
|
||
Returns the Heawood Graph, a (3,6) cage.
|
||
|
||
The Heawood Graph is an undirected graph with 14 nodes and 21 edges,
|
||
named after Percy John Heawood [1]_.
|
||
It is cubic symmetric, nonplanar, Hamiltonian, and can be represented
|
||
in LCF notation as ``[5,-5]^7`` [2]_.
|
||
It is the unique (3,6)-cage: the regular cubic graph of girth 6 with
|
||
minimal number of vertices [3]_.
|
||
|
||
Parameters
|
||
----------
|
||
create_using : NetworkX graph constructor, optional (default=nx.Graph)
|
||
Graph type to create. If graph instance, then cleared before populated.
|
||
|
||
Returns
|
||
-------
|
||
G : networkx Graph
|
||
Heawood Graph with 14 nodes and 21 edges
|
||
|
||
References
|
||
----------
|
||
.. [1] https://en.wikipedia.org/wiki/Heawood_graph
|
||
.. [2] https://mathworld.wolfram.com/HeawoodGraph.html
|
||
.. [3] https://www.win.tue.nl/~aeb/graphs/Heawood.html
|
||
|
||
"""
|
||
G = LCF_graph(14, [5, -5], 7, create_using)
|
||
G.name = "Heawood Graph"
|
||
return G
|
||
|
||
|
||
def hoffman_singleton_graph():
|
||
"""
|
||
Returns the Hoffman-Singleton Graph.
|
||
|
||
The Hoffman–Singleton graph is a symmetrical undirected graph
|
||
with 50 nodes and 175 edges.
|
||
All indices lie in ``Z % 5``: that is, the integers mod 5 [1]_.
|
||
It is the only regular graph of vertex degree 7, diameter 2, and girth 5.
|
||
It is the unique (7,5)-cage graph and Moore graph, and contains many
|
||
copies of the Petersen graph [2]_.
|
||
|
||
Returns
|
||
-------
|
||
G : networkx Graph
|
||
Hoffman–Singleton Graph with 50 nodes and 175 edges
|
||
|
||
Notes
|
||
-----
|
||
Constructed from pentagon and pentagram as follows: Take five pentagons $P_h$
|
||
and five pentagrams $Q_i$ . Join vertex $j$ of $P_h$ to vertex $h·i+j$ of $Q_i$ [3]_.
|
||
|
||
References
|
||
----------
|
||
.. [1] https://blogs.ams.org/visualinsight/2016/02/01/hoffman-singleton-graph/
|
||
.. [2] https://mathworld.wolfram.com/Hoffman-SingletonGraph.html
|
||
.. [3] https://en.wikipedia.org/wiki/Hoffman%E2%80%93Singleton_graph
|
||
|
||
"""
|
||
G = nx.Graph()
|
||
for i in range(5):
|
||
for j in range(5):
|
||
G.add_edge(("pentagon", i, j), ("pentagon", i, (j - 1) % 5))
|
||
G.add_edge(("pentagon", i, j), ("pentagon", i, (j + 1) % 5))
|
||
G.add_edge(("pentagram", i, j), ("pentagram", i, (j - 2) % 5))
|
||
G.add_edge(("pentagram", i, j), ("pentagram", i, (j + 2) % 5))
|
||
for k in range(5):
|
||
G.add_edge(("pentagon", i, j), ("pentagram", k, (i * k + j) % 5))
|
||
G = nx.convert_node_labels_to_integers(G)
|
||
G.name = "Hoffman-Singleton Graph"
|
||
return G
|
||
|
||
|
||
@_raise_on_directed
|
||
def house_graph(create_using=None):
|
||
"""
|
||
Returns the House graph (square with triangle on top)
|
||
|
||
The house graph is a simple undirected graph with
|
||
5 nodes and 6 edges [1]_.
|
||
|
||
Parameters
|
||
----------
|
||
create_using : NetworkX graph constructor, optional (default=nx.Graph)
|
||
Graph type to create. If graph instance, then cleared before populated.
|
||
|
||
Returns
|
||
-------
|
||
G : networkx Graph
|
||
House graph in the form of a square with a triangle on top
|
||
|
||
References
|
||
----------
|
||
.. [1] https://mathworld.wolfram.com/HouseGraph.html
|
||
"""
|
||
G = nx.from_dict_of_lists(
|
||
{0: [1, 2], 1: [0, 3], 2: [0, 3, 4], 3: [1, 2, 4], 4: [2, 3]},
|
||
create_using=create_using,
|
||
)
|
||
G.name = "House Graph"
|
||
return G
|
||
|
||
|
||
@_raise_on_directed
|
||
def house_x_graph(create_using=None):
|
||
"""
|
||
Returns the House graph with a cross inside the house square.
|
||
|
||
The House X-graph is the House graph plus the two edges connecting diagonally
|
||
opposite vertices of the square base. It is also one of the two graphs
|
||
obtained by removing two edges from the pentatope graph [1]_.
|
||
|
||
Parameters
|
||
----------
|
||
create_using : NetworkX graph constructor, optional (default=nx.Graph)
|
||
Graph type to create. If graph instance, then cleared before populated.
|
||
|
||
Returns
|
||
-------
|
||
G : networkx Graph
|
||
House graph with diagonal vertices connected
|
||
|
||
References
|
||
----------
|
||
.. [1] https://mathworld.wolfram.com/HouseGraph.html
|
||
"""
|
||
G = house_graph(create_using)
|
||
G.add_edges_from([(0, 3), (1, 2)])
|
||
G.name = "House-with-X-inside Graph"
|
||
return G
|
||
|
||
|
||
@_raise_on_directed
|
||
def icosahedral_graph(create_using=None):
|
||
"""
|
||
Returns the Platonic Icosahedral graph.
|
||
|
||
The icosahedral graph has 12 nodes and 30 edges. It is a Platonic graph
|
||
whose nodes have the connectivity of the icosahedron. It is undirected,
|
||
regular and Hamiltonian [1]_.
|
||
|
||
Parameters
|
||
----------
|
||
create_using : NetworkX graph constructor, optional (default=nx.Graph)
|
||
Graph type to create. If graph instance, then cleared before populated.
|
||
|
||
Returns
|
||
-------
|
||
G : networkx Graph
|
||
Icosahedral graph with 12 nodes and 30 edges.
|
||
|
||
References
|
||
----------
|
||
.. [1] https://mathworld.wolfram.com/IcosahedralGraph.html
|
||
"""
|
||
G = nx.from_dict_of_lists(
|
||
{
|
||
0: [1, 5, 7, 8, 11],
|
||
1: [2, 5, 6, 8],
|
||
2: [3, 6, 8, 9],
|
||
3: [4, 6, 9, 10],
|
||
4: [5, 6, 10, 11],
|
||
5: [6, 11],
|
||
7: [8, 9, 10, 11],
|
||
8: [9],
|
||
9: [10],
|
||
10: [11],
|
||
},
|
||
create_using=create_using,
|
||
)
|
||
G.name = "Platonic Icosahedral Graph"
|
||
return G
|
||
|
||
|
||
@_raise_on_directed
|
||
def krackhardt_kite_graph(create_using=None):
|
||
"""
|
||
Returns the Krackhardt Kite Social Network.
|
||
|
||
A 10 actor social network introduced by David Krackhardt
|
||
to illustrate different centrality measures [1]_.
|
||
|
||
Parameters
|
||
----------
|
||
create_using : NetworkX graph constructor, optional (default=nx.Graph)
|
||
Graph type to create. If graph instance, then cleared before populated.
|
||
|
||
Returns
|
||
-------
|
||
G : networkx Graph
|
||
Krackhardt Kite graph with 10 nodes and 18 edges
|
||
|
||
Notes
|
||
-----
|
||
The traditional labeling is:
|
||
Andre=1, Beverley=2, Carol=3, Diane=4,
|
||
Ed=5, Fernando=6, Garth=7, Heather=8, Ike=9, Jane=10.
|
||
|
||
References
|
||
----------
|
||
.. [1] Krackhardt, David. "Assessing the Political Landscape: Structure,
|
||
Cognition, and Power in Organizations". Administrative Science Quarterly.
|
||
35 (2): 342–369. doi:10.2307/2393394. JSTOR 2393394. June 1990.
|
||
|
||
"""
|
||
G = nx.from_dict_of_lists(
|
||
{
|
||
0: [1, 2, 3, 5],
|
||
1: [0, 3, 4, 6],
|
||
2: [0, 3, 5],
|
||
3: [0, 1, 2, 4, 5, 6],
|
||
4: [1, 3, 6],
|
||
5: [0, 2, 3, 6, 7],
|
||
6: [1, 3, 4, 5, 7],
|
||
7: [5, 6, 8],
|
||
8: [7, 9],
|
||
9: [8],
|
||
},
|
||
create_using=create_using,
|
||
)
|
||
G.name = "Krackhardt Kite Social Network"
|
||
return G
|
||
|
||
|
||
def moebius_kantor_graph(create_using=None):
|
||
"""
|
||
Returns the Moebius-Kantor graph.
|
||
|
||
The Möbius-Kantor graph is the cubic symmetric graph on 16 nodes.
|
||
Its LCF notation is [5,-5]^8, and it is isomorphic to the generalized
|
||
Petersen graph [1]_.
|
||
|
||
Parameters
|
||
----------
|
||
create_using : NetworkX graph constructor, optional (default=nx.Graph)
|
||
Graph type to create. If graph instance, then cleared before populated.
|
||
|
||
Returns
|
||
-------
|
||
G : networkx Graph
|
||
Moebius-Kantor graph
|
||
|
||
References
|
||
----------
|
||
.. [1] https://en.wikipedia.org/wiki/M%C3%B6bius%E2%80%93Kantor_graph
|
||
|
||
"""
|
||
G = LCF_graph(16, [5, -5], 8, create_using)
|
||
G.name = "Moebius-Kantor Graph"
|
||
return G
|
||
|
||
|
||
@_raise_on_directed
|
||
def octahedral_graph(create_using=None):
|
||
"""
|
||
Returns the Platonic Octahedral graph.
|
||
|
||
The octahedral graph is the 6-node 12-edge Platonic graph having the
|
||
connectivity of the octahedron [1]_. If 6 couples go to a party,
|
||
and each person shakes hands with every person except his or her partner,
|
||
then this graph describes the set of handshakes that take place;
|
||
for this reason it is also called the cocktail party graph [2]_.
|
||
|
||
Parameters
|
||
----------
|
||
create_using : NetworkX graph constructor, optional (default=nx.Graph)
|
||
Graph type to create. If graph instance, then cleared before populated.
|
||
|
||
Returns
|
||
-------
|
||
G : networkx Graph
|
||
Octahedral graph
|
||
|
||
References
|
||
----------
|
||
.. [1] https://mathworld.wolfram.com/OctahedralGraph.html
|
||
.. [2] https://en.wikipedia.org/wiki/Tur%C3%A1n_graph#Special_cases
|
||
|
||
"""
|
||
G = nx.from_dict_of_lists(
|
||
{0: [1, 2, 3, 4], 1: [2, 3, 5], 2: [4, 5], 3: [4, 5], 4: [5]},
|
||
create_using=create_using,
|
||
)
|
||
G.name = "Platonic Octahedral Graph"
|
||
return G
|
||
|
||
|
||
def pappus_graph():
|
||
"""
|
||
Returns the Pappus graph.
|
||
|
||
The Pappus graph is a cubic symmetric distance-regular graph with 18 nodes
|
||
and 27 edges. It is Hamiltonian and can be represented in LCF notation as
|
||
[5,7,-7,7,-7,-5]^3 [1]_.
|
||
|
||
Returns
|
||
-------
|
||
G : networkx Graph
|
||
Pappus graph
|
||
|
||
References
|
||
----------
|
||
.. [1] https://en.wikipedia.org/wiki/Pappus_graph
|
||
"""
|
||
G = LCF_graph(18, [5, 7, -7, 7, -7, -5], 3)
|
||
G.name = "Pappus Graph"
|
||
return G
|
||
|
||
|
||
@_raise_on_directed
|
||
def petersen_graph(create_using=None):
|
||
"""
|
||
Returns the Petersen graph.
|
||
|
||
The Peterson graph is a cubic, undirected graph with 10 nodes and 15 edges [1]_.
|
||
Julius Petersen constructed the graph as the smallest counterexample
|
||
against the claim that a connected bridgeless cubic graph
|
||
has an edge colouring with three colours [2]_.
|
||
|
||
Parameters
|
||
----------
|
||
create_using : NetworkX graph constructor, optional (default=nx.Graph)
|
||
Graph type to create. If graph instance, then cleared before populated.
|
||
|
||
Returns
|
||
-------
|
||
G : networkx Graph
|
||
Petersen graph
|
||
|
||
References
|
||
----------
|
||
.. [1] https://en.wikipedia.org/wiki/Petersen_graph
|
||
.. [2] https://www.win.tue.nl/~aeb/drg/graphs/Petersen.html
|
||
"""
|
||
G = nx.from_dict_of_lists(
|
||
{
|
||
0: [1, 4, 5],
|
||
1: [0, 2, 6],
|
||
2: [1, 3, 7],
|
||
3: [2, 4, 8],
|
||
4: [3, 0, 9],
|
||
5: [0, 7, 8],
|
||
6: [1, 8, 9],
|
||
7: [2, 5, 9],
|
||
8: [3, 5, 6],
|
||
9: [4, 6, 7],
|
||
},
|
||
create_using=create_using,
|
||
)
|
||
G.name = "Petersen Graph"
|
||
return G
|
||
|
||
|
||
def sedgewick_maze_graph(create_using=None):
|
||
"""
|
||
Return a small maze with a cycle.
|
||
|
||
This is the maze used in Sedgewick, 3rd Edition, Part 5, Graph
|
||
Algorithms, Chapter 18, e.g. Figure 18.2 and following [1]_.
|
||
Nodes are numbered 0,..,7
|
||
|
||
Parameters
|
||
----------
|
||
create_using : NetworkX graph constructor, optional (default=nx.Graph)
|
||
Graph type to create. If graph instance, then cleared before populated.
|
||
|
||
Returns
|
||
-------
|
||
G : networkx Graph
|
||
Small maze with a cycle
|
||
|
||
References
|
||
----------
|
||
.. [1] Figure 18.2, Chapter 18, Graph Algorithms (3rd Ed), Sedgewick
|
||
"""
|
||
G = empty_graph(0, create_using)
|
||
G.add_nodes_from(range(8))
|
||
G.add_edges_from([[0, 2], [0, 7], [0, 5]])
|
||
G.add_edges_from([[1, 7], [2, 6]])
|
||
G.add_edges_from([[3, 4], [3, 5]])
|
||
G.add_edges_from([[4, 5], [4, 7], [4, 6]])
|
||
G.name = "Sedgewick Maze"
|
||
return G
|
||
|
||
|
||
def tetrahedral_graph(create_using=None):
|
||
"""
|
||
Returns the 3-regular Platonic Tetrahedral graph.
|
||
|
||
Tetrahedral graph has 4 nodes and 6 edges. It is a
|
||
special case of the complete graph, K4, and wheel graph, W4.
|
||
It is one of the 5 platonic graphs [1]_.
|
||
|
||
Parameters
|
||
----------
|
||
create_using : NetworkX graph constructor, optional (default=nx.Graph)
|
||
Graph type to create. If graph instance, then cleared before populated.
|
||
|
||
Returns
|
||
-------
|
||
G : networkx Graph
|
||
Tetrahedral Grpah
|
||
|
||
References
|
||
----------
|
||
.. [1] https://en.wikipedia.org/wiki/Tetrahedron#Tetrahedral_graph
|
||
|
||
"""
|
||
G = complete_graph(4, create_using)
|
||
G.name = "Platonic Tetrahedral graph"
|
||
return G
|
||
|
||
|
||
@_raise_on_directed
|
||
def truncated_cube_graph(create_using=None):
|
||
"""
|
||
Returns the skeleton of the truncated cube.
|
||
|
||
The truncated cube is an Archimedean solid with 14 regular
|
||
faces (6 octagonal and 8 triangular), 36 edges and 24 nodes [1]_.
|
||
The truncated cube is created by truncating (cutting off) the tips
|
||
of the cube one third of the way into each edge [2]_.
|
||
|
||
Parameters
|
||
----------
|
||
create_using : NetworkX graph constructor, optional (default=nx.Graph)
|
||
Graph type to create. If graph instance, then cleared before populated.
|
||
|
||
Returns
|
||
-------
|
||
G : networkx Graph
|
||
Skeleton of the truncated cube
|
||
|
||
References
|
||
----------
|
||
.. [1] https://en.wikipedia.org/wiki/Truncated_cube
|
||
.. [2] https://www.coolmath.com/reference/polyhedra-truncated-cube
|
||
|
||
"""
|
||
G = nx.from_dict_of_lists(
|
||
{
|
||
0: [1, 2, 4],
|
||
1: [11, 14],
|
||
2: [3, 4],
|
||
3: [6, 8],
|
||
4: [5],
|
||
5: [16, 18],
|
||
6: [7, 8],
|
||
7: [10, 12],
|
||
8: [9],
|
||
9: [17, 20],
|
||
10: [11, 12],
|
||
11: [14],
|
||
12: [13],
|
||
13: [21, 22],
|
||
14: [15],
|
||
15: [19, 23],
|
||
16: [17, 18],
|
||
17: [20],
|
||
18: [19],
|
||
19: [23],
|
||
20: [21],
|
||
21: [22],
|
||
22: [23],
|
||
},
|
||
create_using=create_using,
|
||
)
|
||
G.name = "Truncated Cube Graph"
|
||
return G
|
||
|
||
|
||
def truncated_tetrahedron_graph(create_using=None):
|
||
"""
|
||
Returns the skeleton of the truncated Platonic tetrahedron.
|
||
|
||
The truncated tetrahedron is an Archimedean solid with 4 regular hexagonal faces,
|
||
4 equilateral triangle faces, 12 nodes and 18 edges. It can be constructed by truncating
|
||
all 4 vertices of a regular tetrahedron at one third of the original edge length [1]_.
|
||
|
||
Parameters
|
||
----------
|
||
create_using : NetworkX graph constructor, optional (default=nx.Graph)
|
||
Graph type to create. If graph instance, then cleared before populated.
|
||
|
||
Returns
|
||
-------
|
||
G : networkx Graph
|
||
Skeleton of the truncated tetrahedron
|
||
|
||
References
|
||
----------
|
||
.. [1] https://en.wikipedia.org/wiki/Truncated_tetrahedron
|
||
|
||
"""
|
||
G = path_graph(12, create_using)
|
||
G.add_edges_from([(0, 2), (0, 9), (1, 6), (3, 11), (4, 11), (5, 7), (8, 10)])
|
||
G.name = "Truncated Tetrahedron Graph"
|
||
return G
|
||
|
||
|
||
@_raise_on_directed
|
||
def tutte_graph(create_using=None):
|
||
"""
|
||
Returns the Tutte graph.
|
||
|
||
The Tutte graph is a cubic polyhedral, non-Hamiltonian graph. It has
|
||
46 nodes and 69 edges.
|
||
It is a counterexample to Tait's conjecture that every 3-regular polyhedron
|
||
has a Hamiltonian cycle.
|
||
It can be realized geometrically from a tetrahedron by multiply truncating
|
||
three of its vertices [1]_.
|
||
|
||
Parameters
|
||
----------
|
||
create_using : NetworkX graph constructor, optional (default=nx.Graph)
|
||
Graph type to create. If graph instance, then cleared before populated.
|
||
|
||
Returns
|
||
-------
|
||
G : networkx Graph
|
||
Tutte graph
|
||
|
||
References
|
||
----------
|
||
.. [1] https://en.wikipedia.org/wiki/Tutte_graph
|
||
"""
|
||
G = nx.from_dict_of_lists(
|
||
{
|
||
0: [1, 2, 3],
|
||
1: [4, 26],
|
||
2: [10, 11],
|
||
3: [18, 19],
|
||
4: [5, 33],
|
||
5: [6, 29],
|
||
6: [7, 27],
|
||
7: [8, 14],
|
||
8: [9, 38],
|
||
9: [10, 37],
|
||
10: [39],
|
||
11: [12, 39],
|
||
12: [13, 35],
|
||
13: [14, 15],
|
||
14: [34],
|
||
15: [16, 22],
|
||
16: [17, 44],
|
||
17: [18, 43],
|
||
18: [45],
|
||
19: [20, 45],
|
||
20: [21, 41],
|
||
21: [22, 23],
|
||
22: [40],
|
||
23: [24, 27],
|
||
24: [25, 32],
|
||
25: [26, 31],
|
||
26: [33],
|
||
27: [28],
|
||
28: [29, 32],
|
||
29: [30],
|
||
30: [31, 33],
|
||
31: [32],
|
||
34: [35, 38],
|
||
35: [36],
|
||
36: [37, 39],
|
||
37: [38],
|
||
40: [41, 44],
|
||
41: [42],
|
||
42: [43, 45],
|
||
43: [44],
|
||
},
|
||
create_using=create_using,
|
||
)
|
||
G.name = "Tutte's Graph"
|
||
return G
|