Clearer parameters for graph_to_clique_complex

Co-authored-by: Florian Frantzen <[email protected]>
pyt-team · Jul 8, 2024 · a78cd6a · a78cd6a
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Showing 2 changed files with 16 additions and 14 deletions.
diff --git a/test/transform/test_graph_to_simplicial_complex.py b/test/transform/test_graph_to_simplicial_complex.py
@@ -53,7 +53,7 @@ def test_graph_to_clique_complex(self):
         assert sc[(0,)]["label"] == 5
         assert sc[(0, 1)]["weight"] == 10
 
-        sc = graph_to_clique_complex(G, max_dim=2)
+        sc = graph_to_clique_complex(G, max_rank=1)
 
         assert sc.dim == 1
         assert (0, 2, 3) not in sc
@@ -93,7 +93,7 @@ def test_graph_2_clique_complex(self):
         assert (0, 1, 2) in sc
 
         with pytest.deprecated_call():
-            sc = graph_2_clique_complex(G, max_dim=2)
+            sc = graph_2_clique_complex(G, max_rank=1)
 
         assert sc.dim == 1
         assert (0, 2, 3) not in sc

diff --git a/toponetx/transform/graph_to_simplicial_complex.py b/toponetx/transform/graph_to_simplicial_complex.py
@@ -37,37 +37,39 @@ def graph_to_neighbor_complex(G: nx.Graph) -> SimplicialComplex:
 
 
 def graph_to_clique_complex(
-    G: nx.Graph, max_dim: int | None = None
+    G: nx.Graph, max_rank: int | None = None
 ) -> SimplicialComplex:
     """Get the clique complex of a graph.
 
     Parameters
     ----------
     G : networks.Graph
         Input graph.
-    max_dim : int, optional
-        The max dimension of the cliques in the output clique complex.
+    max_rank : int, optional
+        The maximum rank of the simplices in the output clique complex.
 
     Returns
     -------
     SimplicialComplex
-        The clique simplicial complex of dimension dim of the graph G.
+        The clique simplicial complex of rank `max_rank` of the graph G.
     """
     cliques = nx.enumerate_all_cliques(G)
 
     # `nx.enumerate_all_cliques` returns cliques in ascending order of size. Abort calling the generator once we reach
     # cliques larger than the requested max dimension.
     cliques = takewhile(
-        lambda clique: max_dim is None or len(clique) <= max_dim, cliques
+        lambda clique: max_rank is None or len(clique) <= max_rank + 1, cliques
     )
 
     SC = SimplicialComplex(cliques)
 
     # copy attributes of the input graph
     for node in G.nodes:
         SC[[node]].update(G.nodes[node])
-    for edge in G.edges:
-        SC[edge].update(G.edges[edge])
+    # if the resulting complex has dimension 1 or higher, copy the attributes of the edges
+    if SC.dim >= 1:
+        for edge in G.edges:
+            SC[edge].update(G.edges[edge])
     SC.complex.update(G.graph)
 
     return SC
@@ -101,23 +103,23 @@ def graph_2_neighbor_complex(G) -> SimplicialComplex:
     "`graph_2_clique_complex` is deprecated and will be removed in a future version, use `graph_to_clique_complex` instead."
 )
 def graph_2_clique_complex(
-    G: nx.Graph, max_dim: int | None = None
+    G: nx.Graph, max_rank: int | None = None
 ) -> SimplicialComplex:
     """Get the clique complex of a graph.
 
     Parameters
     ----------
     G : networks.Graph
         Input graph.
-    max_dim : int, optional
-        The max dimension of the cliques in the output clique complex.
+    max_rank : int, optional
+        The maximum rank of the simplices in the output clique complex.
 
     Returns
     -------
     SimplicialComplex
-        The clique simplicial complex of dimension dim of the graph G.
+        The clique simplicial complex of rank `max_rank` of the graph `G`.
     """
-    return graph_to_clique_complex(G, max_dim)
+    return graph_to_clique_complex(G, max_rank)
 
 
 def weighted_graph_to_vietoris_rips_complex(