Mercurial > repos > shellac > sam_consensus_v3
diff env/lib/python3.9/site-packages/networkx/generators/cographs.py @ 0:4f3585e2f14b draft default tip
"planemo upload commit 60cee0fc7c0cda8592644e1aad72851dec82c959"
author | shellac |
---|---|
date | Mon, 22 Mar 2021 18:12:50 +0000 |
parents | |
children |
line wrap: on
line diff
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/env/lib/python3.9/site-packages/networkx/generators/cographs.py Mon Mar 22 18:12:50 2021 +0000 @@ -0,0 +1,66 @@ +r"""Generators for cographs + +A cograph is a graph containing no path on four vertices. +Cographs or $P_4$-free graphs can be obtained from a single vertex +by disjoint union and complementation operations. + +References +---------- +.. [0] D.G. Corneil, H. Lerchs, L.Stewart Burlingham, + "Complement reducible graphs", + Discrete Applied Mathematics, Volume 3, Issue 3, 1981, Pages 163-174, + ISSN 0166-218X. +""" +import networkx as nx +from networkx.utils import py_random_state + +__all__ = ["random_cograph"] + + +@py_random_state(1) +def random_cograph(n, seed=None): + r"""Returns a random cograph with $2 ^ n$ nodes. + + A cograph is a graph containing no path on four vertices. + Cographs or $P_4$-free graphs can be obtained from a single vertex + by disjoint union and complementation operations. + + This generator starts off from a single vertex and performes disjoint + union and full join operations on itself. + The decision on which operation will take place is random. + + Parameters + ---------- + n : int + The order of the cograph. + seed : integer, random_state, or None (default) + Indicator of random number generation state. + See :ref:`Randomness<randomness>`. + + Returns + ------- + G : A random graph containing no path on four vertices. + + See Also + -------- + full_join + union + + References + ---------- + .. [1] D.G. Corneil, H. Lerchs, L.Stewart Burlingham, + "Complement reducible graphs", + Discrete Applied Mathematics, Volume 3, Issue 3, 1981, Pages 163-174, + ISSN 0166-218X. + """ + R = nx.empty_graph(1) + + for i in range(n): + RR = nx.relabel_nodes(R.copy(), lambda x: x + len(R)) + + if seed.randint(0, 1) == 0: + R = nx.full_join(R, RR) + else: + R = nx.disjoint_union(R, RR) + + return R