added default behavior of path lifting

modules/transforms/liftings/graph2hypergraph/path_lifting.py

@@ -12,31 +12,38 @@ class PathLifting(Graph2HypergraphLifting):
 
     def __init__(
         self,
-        source_nodes: list[int],
-        target_nodes: list[int],
-        lengths: list[int],
+        source_nodes: list[int] = None,
+        target_nodes: list[int] = None,
+        lengths: list[int] = None,
         include_smaller_paths=False,
         **kwargs,
     ):
         # guard clauses
-        if len(source_nodes) != len(lengths):
+        if (
+            lengths is not None
+            and source_nodes is not None
+            and len(source_nodes) != len(lengths)
+        ):
             raise ValueError("source_nodes and lengths must have the same length")
         if target_nodes is not None and len(target_nodes) != len(source_nodes):
             raise ValueError(
                 "When target_nodes is not None, it must have the same length"
                 "as source_nodes"
             )
-        if len(source_nodes) == 0:
-            raise ValueError(
-                "source_nodes,target_nodes and lengths must have at least one element"
-            )
 
         super().__init__(**kwargs)
         self.source_nodes = source_nodes
         self.target_nodes = target_nodes
         self.lengths = lengths
         self.include_smaller_paths = include_smaller_paths
 
+    def value_defaults(self, data: torch_geometric.data.Data):
+        """Sets default values for source_nodes and lengths if not provided."""
+        if self.source_nodes is None:
+            self.source_nodes = np.arange(data.num_nodes)
+        if self.lengths is None:
+            self.lengths = [2] * len(self.source_nodes)
+
     def find_hyperedges(self, data: torch_geometric.data.Data):
         """Finds hyperedges from paths between nodes in a graph."""
         G = torch_geometric.utils.convert.to_networkx(data, to_undirected=True)
@@ -68,6 +75,8 @@ def find_hyperedges(self, data: torch_geometric.data.Data):
         return s_hyperedges
 
     def lift_topology(self, data: torch_geometric.data.Data):
+        if self.source_nodes is None or self.lengths is None:
+            self.value_defaults(data)
         s_hyperedges = self.find_hyperedges(data)
         indices = [[], []]
         for edge_id, x in enumerate(s_hyperedges):