updates auto clean defaults

pyproject.toml

@@ -1,6 +1,6 @@
 [project]
 name = "cityseer"
-version = '4.17.0'
+version = '4.17.1'
 description = "Computational tools for network-based pedestrian-scale urban analysis"
 readme = "README.md"
 requires-python = ">=3.10, <3.14"

pysrc/cityseer/tools/graphs.py

@@ -562,7 +562,7 @@ def nx_iron_edges(
     nx_multigraph: MultiGraph,
     simplify_by_max_angle: int = 120,
     min_self_loop_length: int = 100,
-    max_foot_tunnel_length: int = 50,
+    max_foot_tunnel_length: int = 100,
 ) -> MultiGraph:
     """
     Simplifies edges.
@@ -577,7 +577,7 @@ def nx_iron_edges(
     min_self_loop_length: int
         Maximum self loop length to permit for a given edge.
     max_foot_tunnel_length: int
-        Maximum tunnel length to permit for non motorised edges.
+        Maximum tunnel length to permit for non motorised edges. Default of 100m.
 
     Returns
     -------
@@ -646,15 +646,15 @@ def nx_iron_edges(
         "tertiary",
         "tertiary_link",
         "residential",
-        "living_street",
+        # "living_street",  # intentional - e.g. barcelona
         # "service",  # intentional
     ]
 )
 
 
 def nx_deduplicate_edges(
     nx_multigraph: MultiGraph,
-    dissolve_distance: int = 12,
+    dissolve_distance: int = 20,
     max_ang_diff: int = 20,
 ) -> MultiGraph:
     """
@@ -670,7 +670,7 @@ def nx_deduplicate_edges(
         A `networkX` `MultiGraph` in a projected coordinate system, containing `x` and `y` node attributes, and `geom`
         edge attributes containing `LineString` geoms.
     dissolve_distance: int
-        A distance to use when searching for adjacent edges. 12m by default.
+        A distance to use when searching for adjacent edges. 20m by default.
     max_ang_diff: int
          Only count a nearby adjacent edge as duplicitous if the angular difference between edges is less than
          `max_ang_diff`. 20 degrees by default.

pysrc/cityseer/tools/io.py

@@ -257,7 +257,7 @@ def _auto_clean_network(
     green_service_roads: bool = False,
 ) -> nx.MultiGraph:
     # deduplicate by hierarchy
-    G = graphs.nx_deduplicate_edges(G)
+    G = graphs.nx_deduplicate_edges(G, dissolve_distance=20, max_ang_diff=20)
     # parks
     parks_gdf = ox.features_from_polygon(
         geom_wgs,
@@ -295,6 +295,7 @@ def _auto_clean_network(
     for start_node_key, end_node_key, edge_key, edge_data in tqdm(  # type: ignore
         G.edges(keys=True, data=True),  # type: ignore
         total=G.number_of_edges(),
+        disable=config.QUIET_MODE,
     ):
         edge_geom = edge_data["geom"]
         if "footway" in edge_data["highways"]:
@@ -475,7 +476,7 @@ def _auto_clean_network(
         )
     G = graphs.nx_remove_filler_nodes(G)
     G = graphs.nx_merge_parallel_edges(G, merge_edges_by_midline=True, contains_buffer_dist=50)
-    G = graphs.nx_iron_edges(G, min_self_loop_length=100, max_foot_tunnel_length=50)
+    G = graphs.nx_iron_edges(G, min_self_loop_length=100, max_foot_tunnel_length=100)
     # do this last to clean up any orphaned sub components
     G = graphs.nx_remove_dangling_nodes(G, despine=25)
 
@@ -708,6 +709,8 @@ def get_merged_nd_keys(_idx: int) -> tuple[str, str]:
                             levels = tags["level"].split(":")
                         elif ";" in tags["level"]:
                             levels = tags["level"].split(";")
+                        elif "," in tags["level"]:
+                            levels = tags["level"].split(",")
                         else:
                             levels = [tags["level"]]
                         levels = [int(round(float(level))) for level in levels]