Fix: Remove some slow jaccard features (#108)

hcga/features/jaccard_similarity.py

@@ -82,16 +82,6 @@ def degree_assortativity_coeff(graph):
     return nx.degree_assortativity_coefficient(jaccard_similarity(graph))
 
 
-def graph_clique_number(graph):
-    """graph_clique_number"""
-    return max(len(c) for c in nx.clique.find_cliques(jaccard_similarity(graph)))
-
-
-def num_max_cliques(graph):
-    """num_max_cliques"""
-    return sum(1 for _ in nx.clique.find_cliques(jaccard_similarity(graph)))
-
-
 def transitivity(graph):
     """transitivity"""
     return nx.transitivity(jaccard_similarity(graph))
@@ -117,16 +107,6 @@ def global_efficiency(graph):
     return nx.global_efficiency(jaccard_similarity(graph))
 
 
-def node_connectivity(graph):
-    """node_connectivity"""
-    return nx.node_connectivity(jaccard_similarity(graph))
-
-
-def edge_connectivity(graph):
-    """edge_connectivity"""
-    return nx.edge_connectivity(jaccard_similarity(graph))
-
-
 class JaccardSimilarity(FeatureClass):
     """Jaccard Similarity class."""
 
@@ -164,7 +144,6 @@ def compute_features(self):
             "Diameter of Jaccard similarity graph",
             InterpretabilityScore(5),
         )
-
         self.add_feature(
             "radius",
             radius,
@@ -180,21 +159,6 @@ def compute_features(self):
             InterpretabilityScore(4),
         )
 
-        # Cliques
-        self.add_feature(
-            "graph_clique_number",
-            graph_clique_number,
-            "The size of the largest clique in the Jaccard similarity graph",
-            InterpretabilityScore(3),
-        )
-
-        self.add_feature(
-            "num_max_cliques",
-            num_max_cliques,
-            "The number of maximal cliques in the Jaccard similarity graph",
-            InterpretabilityScore(3),
-        )
-
         # Clustering
         self.add_feature(
             "transitivity",
@@ -232,18 +196,3 @@ def compute_features(self):
             "The global efficiency",
             InterpretabilityScore(4),
         )
-
-        # Node connectivity
-        self.add_feature(
-            "node_connectivity",
-            node_connectivity,
-            "Node connectivity",
-            InterpretabilityScore(4),
-        )
-
-        self.add_feature(
-            "edge_connectivity",
-            edge_connectivity,
-            "Edge connectivity",
-            InterpretabilityScore(4),
-        )

hcga/graph.py

@@ -282,7 +282,7 @@ def convert_graph(  # pylint: disable=too-many-branches
         label = [label]
 
     if isinstance(graph, nx.Graph):
-        A = nx.to_scipy_sparse_matrix(graph, weight="weight", format="coo")
+        A = nx.to_scipy_sparse_array(graph, weight="weight", format="coo")
 
         if not node_features:
             try: