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Partial clique complex #200

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merged 9 commits into from
Oct 24, 2022
Merged

Partial clique complex #200

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7cef908
feat: promote only some cliques in flag complex
maximelucas Jun 13, 2022
6484f7a
fix: import
maximelucas Jul 26, 2022
c0cd622
test: added
maximelucas Oct 24, 2022
cd066ab
fix: test
maximelucas Oct 24, 2022
8bc8576
Merge branch 'main' into partial_clique_complex
maximelucas Oct 24, 2022
f096d28
review suggestion
maximelucas Oct 24, 2022
231e186
review suggestion
maximelucas Oct 24, 2022
61c53a6
fix: typo
maximelucas Oct 24, 2022
6ca1bae
minor rewrite
maximelucas Oct 24, 2022
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feat: promote only some cliques in flag complex
  • Loading branch information
@maximelucas
maximelucas committed Jun 13, 2022
commit 7cef9088fe5ad7ff94a776d7f906f2dabc6c639b
29 changes: 22 additions & 7 deletions xgi/generators/classic.py
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Original file line number Diff line number Diff line change
Expand Up @@ -9,6 +9,9 @@

import networkx as nx

from xgi import SimplicialComplex
from ..utils import py_random_state

__all__ = [
"empty_hypergraph",
"empty_simplicial_complex",
Expand Down Expand Up @@ -169,16 +172,22 @@ def star_clique(n_star, n_clique, d_max):
return H


def flag_complex(g, max_order=2, seed=None):
@py_random_state("seed")
def flag_complex(G, max_order=2, ps=None, seed=None):
"""Generate a flag (or clique) complex from a
NetworkX graph by filling all cliques up to dimension max_order.

Parameters
----------
g : Networkx Graph
G : Networkx Graph

max_order : int
maximal dimension of simplices to add to the output simplicial complex
ps: list of float
List of probabilities (between 0 and 1) to create a
hyperedge from a clique, at each order d. For example,
ps[0] is the probability of promoting any 3-node clique (triangle) to
a 3-hyperedge.

Returns
-------
Expand All @@ -191,16 +200,22 @@ def flag_complex(g, max_order=2, seed=None):
"""
# This import needs to happen when this function is called, not when it is
# defined. Otherwise, a circular import error would happen.
from xgi import SimplicialComplex

nodes = g.nodes()
edges = list(g.edges())
nodes = G.nodes()

# compute all triangles to fill
max_cliques = list(nx.find_cliques(g))
max_cliques = list(nx.find_cliques(G))

S = SimplicialComplex()
S.add_nodes_from(nodes)
S.add_simplices_from(max_cliques, max_order=max_order)
if not ps: # promote all cliques
S.add_simplices_from(max_cliques, max_order=max_order)
else: # promote cliques with a given probability
for i, p in enumerate(ps[max_order - 1]):
d = i + 2 # simplex order
cliques_d = [x for x in max_cliques if len(x) == d + 1]
probas = seed.random.random(size=len(cliques_d))
cliques_d_to_add = cliques_d[probas <= p]
S.add_simplices_from(cliques_d_to_add, max_order=max_order)

return S