Feature/Multiedges for temporal graphs

src/pathpyG/io/netzschleuder.py

@@ -172,7 +172,7 @@ def read_netzschleuder_graph(
 
                         # construct graph and assign edge attributes
                         if timestamps:
-                            g = df_to_temporal_graph(df=edges, is_undirected=not is_directed, num_nodes=num_nodes)
+                            g = df_to_temporal_graph(df=edges, is_undirected=not is_directed, multiedges=multiedges, num_nodes=num_nodes)
                         else:
                             g = df_to_graph(df=edges, multiedges=multiedges, is_undirected=not is_directed, num_nodes=num_nodes)
 

src/pathpyG/io/pandas.py

@@ -281,7 +281,7 @@ def add_edge_attributes(df: pd.DataFrame, g: Graph, time_attr: str | None = None
 
 
 def df_to_temporal_graph(
-    df: pd.DataFrame, is_undirected: bool = False, timestamp_format="%Y-%m-%d %H:%M:%S", time_rescale=1, num_nodes: int | None = None
+    df: pd.DataFrame, is_undirected: bool = False, multiedges: bool = False, timestamp_format="%Y-%m-%d %H:%M:%S", time_rescale=1, num_nodes: int | None = None
 ) -> TemporalGraph:
     """Reads a temporal graph from a pandas data frame.
 
@@ -352,6 +352,9 @@ def df_to_temporal_graph(
             f"Found {df['t'].dtype} instead."
         )
 
+    if not multiedges:
+        df = df.drop_duplicates(subset=["v", "w", "t"])
+
     mapping = IndexMap(node_ids=np.unique(df[["v", "w"]].values))
     data = Data(
         edge_index=mapping.to_idxs(df[["v", "w"]].values.T),

tests/io/test_netzschleuder.py

@@ -116,7 +116,7 @@ def test_read_netzschleuder_graph():
 def test_read_netzschleuder_graph_temporal():
     """Test the read_netzschleuder_graph() function for timestamped data."""
 
-    g = read_netzschleuder_graph(name="email_company", time_attr="time")
+    g = read_netzschleuder_graph(name="email_company", time_attr="time", multiedges=True)
     assert isinstance(g, TemporalGraph)
     assert g.n == 167
     assert g.m == 82927