Making layouts/auto.py work for directed graphs

graspologic/layouts/auto.py

@@ -16,6 +16,7 @@
 from ..preprocessing import cut_edges_by_weight, histogram_edge_weight
 from .classes import NodePosition
 from .nooverlap import remove_overlaps
+from ..utils import symmetrize, largest_connected_component
 
 logger = logging.getLogger(__name__)
 
@@ -200,11 +201,6 @@ def layout_umap(
     return lcc_graph, positions
 
 
-def _largest_connected_component(graph: nx.Graph) -> nx.Graph:
-    largest_component = max(nx.connected_components(graph), key=len)
-    return graph.subgraph(largest_component).copy()
-
-
 def _approximate_prune(graph: nx.Graph, max_edges_to_keep: int = 1000000):
     num_edges = len(graph.edges())
     logger.info(f"num edges: {num_edges}")
@@ -233,7 +229,7 @@ def _node2vec_for_layout(
     random_seed: Optional[int] = None,
 ) -> Tuple[nx.Graph, np.ndarray, np.ndarray]:
     graph = _approximate_prune(graph, max_edges)
-    graph = _largest_connected_component(graph)
+    graph = largest_connected_component(graph)
 
     start = time.time()
     tensors, labels = node2vec_embed(
@@ -260,7 +256,14 @@ def _node_positions_from(
     sizes = _compute_sizes(degree)
     covered_area = _covered_size(sizes)
     scaled_points = _scale_points(down_projection_2d, covered_area)
-    partitions = leiden(graph, random_seed=random_seed)
+    if isinstance(graph, nx.DiGraph):
+        temp_graph = symmetrize(graph)
+        logger.warning(
+            "Directed graph converted to undirected graph for community detection"
+        )
+        partitions = leiden(temp_graph, random_seed=random_seed)
+    else:
+        partitions = leiden(graph, random_seed=random_seed)
     positions = [
         NodePosition(
             node_id=key,