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splits clean into sub function
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@songololo
songololo committed Nov 26, 2024
1 parent e73c210 commit 53bba84
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2 changes: 1 addition & 1 deletion pyproject.toml
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Original file line number Diff line number Diff line change
@@ -1,6 +1,6 @@
[project]
name = "cityseer"
version = '4.16.8'
version = '4.16.9'
description = "Computational tools for network-based pedestrian-scale urban analysis"
readme = "README.md"
requires-python = ">=3.10, <3.14"
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353 changes: 181 additions & 172 deletions pysrc/cityseer/tools/io.py
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Original file line number Diff line number Diff line change
Expand Up @@ -247,6 +247,186 @@ def _extract_gdf(gdf):
return area_gdf


def _auto_clean_network(
G: nx.MultiGraph, geom_wgs: geometry.Polygon, to_crs_code: int, remove_disconnected: int
) -> nx.MultiGraph:
# parks
parks_gdf = ox.features_from_polygon(
geom_wgs,
tags={
"landuse": ["cemetery", "forest"],
"leisure": ["park", "garden", "sports_centre"],
},
)
park_area_gdf = _extract_gdf(parks_gdf)
park_area_gdf = park_area_gdf.to_crs(to_crs_code)
# plazas
plazas_gdf = ox.features_from_polygon(
geom_wgs,
tags={
"highway": ["pedestrian"],
},
)
plaza_area_gdf = _extract_gdf(plazas_gdf)
plaza_area_gdf = plaza_area_gdf.to_crs(to_crs_code)
# parking
parking_gdf = ox.features_from_polygon(
geom_wgs,
tags={
"amenity": ["parking"],
},
)
parking_area_gdf = _extract_gdf(parking_gdf)
parking_area_gdf = parking_area_gdf.to_crs(to_crs_code)
# use STR Tree for performance
parks_buff_str_tree = STRtree(park_area_gdf.buffer(5).geometry.to_list())
plaza_str_tree = STRtree(plaza_area_gdf.geometry.to_list())
parking_str_tree = STRtree(parking_area_gdf.geometry.to_list())
# iter edges to find edges for marking
remove_edges = []
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(),
):
edge_geom = edge_data["geom"]
if "footway" in edge_data["highways"]:
# mark park footways
itx = parks_buff_str_tree.query(edge_geom, predicate="intersects")
if len(itx):
idx = G[start_node_key][end_node_key][edge_key]["highways"].index("footway")
G[start_node_key][end_node_key][edge_key]["highways"][idx] = "footway_green"
# mark plaza footways
else:
itx = plaza_str_tree.query(edge_geom, predicate="intersects")
if len(itx):
idx = G[start_node_key][end_node_key][edge_key]["highways"].index("footway")
G[start_node_key][end_node_key][edge_key]["highways"][idx] = "footway_pedestrian"
# mark green / cemetries etc. service roads
if "service" in edge_data["highways"]:
itx = parks_buff_str_tree.query(edge_geom, predicate="intersects")
if len(itx):
idx = G[start_node_key][end_node_key][edge_key]["highways"].index("service")
G[start_node_key][end_node_key][edge_key]["highways"][idx] = "service_green"
# remove parking service roads
itx = parking_str_tree.query(edge_geom, predicate="intersects")
if len(itx):
remove_edges.append((start_node_key, end_node_key, edge_key))
G.remove_edges_from(remove_edges)
# remove disconnected components
G = graphs.nx_remove_dangling_nodes(G, despine=0, remove_disconnected=remove_disconnected)
# clean by highway types - leave motorway as is
# split only for a given type at a time
for dist, tags, simplify_line_angles in (
(28, ["trunk"], 45),
(24, ["primary"], 45),
(20, ["secondary"], 45),
(16, ["tertiary"], 45),
):
G = graphs.nx_split_opposing_geoms(
G,
buffer_dist=dist,
squash_nodes=True,
centroid_by_itx=True,
osm_hwy_target_tags=tags,
prioritise_by_hwy_tag=True,
simplify_line_angles=simplify_line_angles,
contains_buffer_dist=50,
)
for dist, tags, simplify_line_angles in (
(28, ["trunk"], 95),
(24, ["trunk", "primary"], 95),
(20, ["trunk", "primary", "secondary"], 95),
(16, ["trunk", "primary", "secondary", "tertiary"], 95),
):
G = graphs.nx_consolidate_nodes(
G,
buffer_dist=dist,
crawl=False,
centroid_by_itx=True,
osm_hwy_target_tags=tags,
prioritise_by_hwy_tag=True,
simplify_line_angles=simplify_line_angles,
contains_buffer_dist=50,
)
G = graphs.nx_remove_filler_nodes(G)
# do smaller scale cleaning
tags = [
# "trunk",
# "primary",
# "secondary",
# "tertiary",
"residential",
"service",
"cycleway",
"bridleway",
"pedestrian",
# "steps",
"footway",
"footway_pedestrian", # plazas
"path",
"living_street",
"unclassified",
]
dists = [6, 12]
simplify_angles = 95
#
for dist in dists:
G = graphs.nx_split_opposing_geoms(
G,
buffer_dist=dist,
squash_nodes=True,
centroid_by_itx=True,
osm_hwy_target_tags=tags,
prioritise_by_hwy_tag=True,
simplify_line_angles=simplify_angles,
contains_buffer_dist=50,
)
G = graphs.nx_consolidate_nodes(
G,
buffer_dist=dist,
crawl=True,
centroid_by_itx=True,
osm_hwy_target_tags=tags,
prioritise_by_hwy_tag=True,
simplify_line_angles=simplify_angles,
contains_buffer_dist=50,
)
G = graphs.nx_remove_filler_nodes(G)
# snap gapped endings - don't clean danglers before this
G = graphs.nx_snap_gapped_endings(
G,
buffer_dist=20,
# not main roads
osm_hwy_target_tags=[
"residential",
"service",
"cycleway",
"bridleway",
"pedestrian",
"steps",
"footway",
"footway_pedestrian", # plazas
"path",
"living_street",
"unclassified",
],
)
# snap gapped endings / roaods - don't clean danglers before this
# look for degree 1 dead-ends and link to nearby edges
G = graphs.nx_split_opposing_geoms(
G,
buffer_dist=25,
min_node_degree=1,
max_node_degree=1,
squash_nodes=False,
)
# remove longer danglers
G = graphs.nx_remove_dangling_nodes(G, despine=50)
G = graphs.nx_iron_edges(G)

return G


def osm_graph_from_poly(
poly_geom: geometry.Polygon,
poly_crs_code: int | str = 4326,
Expand Down Expand Up @@ -376,178 +556,7 @@ def osm_graph_from_poly(
graph_crs = graphs.nx_simple_geoms(graph_crs)
graph_crs = graphs.nx_remove_filler_nodes(graph_crs)
if simplify:
# parks
parks_gdf = ox.features_from_polygon(
geom_wgs,
tags={
"landuse": ["cemetery", "forest"],
"leisure": ["park", "garden", "sports_centre"],
},
)
park_area_gdf = _extract_gdf(parks_gdf)
park_area_gdf = park_area_gdf.to_crs(to_crs_code)
# plazas
plazas_gdf = ox.features_from_polygon(
geom_wgs,
tags={
"highway": ["pedestrian"],
},
)
plaza_area_gdf = _extract_gdf(plazas_gdf)
plaza_area_gdf = plaza_area_gdf.to_crs(to_crs_code)
# parking
parking_gdf = ox.features_from_polygon(
geom_wgs,
tags={
"amenity": ["parking"],
},
)
parking_area_gdf = _extract_gdf(parking_gdf)
parking_area_gdf = parking_area_gdf.to_crs(to_crs_code)
# use STR Tree for performance
parks_buff_str_tree = STRtree(park_area_gdf.buffer(5).geometry.to_list())
plaza_str_tree = STRtree(plaza_area_gdf.geometry.to_list())
parking_str_tree = STRtree(parking_area_gdf.geometry.to_list())
# iter edges to find edges for marking
remove_edges = []
for start_node_key, end_node_key, edge_key, edge_data in tqdm(
graph_crs.edges(keys=True, data=True), total=graph_crs.number_of_edges()
):
edge_geom = edge_data["geom"]
if "footway" in edge_data["highways"]:
# mark park footways
itx = parks_buff_str_tree.query(edge_geom, predicate="intersects")
if len(itx):
idx = graph_crs[start_node_key][end_node_key][edge_key]["highways"].index("footway")
graph_crs[start_node_key][end_node_key][edge_key]["highways"][idx] = "footway_green"
# mark plaza footways
else:
itx = plaza_str_tree.query(edge_geom, predicate="intersects")
if len(itx):
idx = graph_crs[start_node_key][end_node_key][edge_key]["highways"].index("footway")
graph_crs[start_node_key][end_node_key][edge_key]["highways"][idx] = "footway_pedestrian"
# mark green / cemetries etc. service roads
if "service" in edge_data["highways"]:
itx = parks_buff_str_tree.query(edge_geom, predicate="intersects")
if len(itx):
idx = graph_crs[start_node_key][end_node_key][edge_key]["highways"].index("service")
graph_crs[start_node_key][end_node_key][edge_key]["highways"][idx] = "service_green"
# remove parking service roads
itx = parking_str_tree.query(edge_geom, predicate="intersects")
if len(itx):
remove_edges.append((start_node_key, end_node_key, edge_key))
graph_crs.remove_edges_from(remove_edges)
# remove disconnected components
graph_crs = graphs.nx_remove_dangling_nodes(graph_crs, despine=0, remove_disconnected=remove_disconnected)
# clean by highway types - leave motorway as is
# split only for a given type at a time
for dist, tags, simplify_line_angles in (
(28, ["trunk"], 45),
(24, ["primary"], 45),
(20, ["secondary"], 45),
(16, ["tertiary"], 45),
):
graph_crs = graphs.nx_split_opposing_geoms(
graph_crs,
buffer_dist=dist,
squash_nodes=True,
centroid_by_itx=True,
osm_hwy_target_tags=tags,
prioritise_by_hwy_tag=True,
simplify_line_angles=simplify_line_angles,
contains_buffer_dist=50,
)
for dist, tags, simplify_line_angles in (
(28, ["trunk"], 95),
(24, ["trunk", "primary"], 95),
(20, ["trunk", "primary", "secondary"], 95),
(16, ["trunk", "primary", "secondary", "tertiary"], 95),
):
graph_crs = graphs.nx_consolidate_nodes(
graph_crs,
buffer_dist=dist,
crawl=False,
centroid_by_itx=True,
osm_hwy_target_tags=tags,
prioritise_by_hwy_tag=True,
simplify_line_angles=simplify_line_angles,
contains_buffer_dist=50,
)
graph_crs = graphs.nx_remove_filler_nodes(graph_crs)
# do smaller scale cleaning
tags = [
# "trunk",
# "primary",
# "secondary",
# "tertiary",
"residential",
"service",
"cycleway",
"bridleway",
"pedestrian",
# "steps",
"footway",
"footway_pedestrian", # plazas
"path",
"living_street",
"unclassified",
]
dists = [6, 12]
simplify_angles = 95
#
for dist in dists:
graph_crs = graphs.nx_split_opposing_geoms(
graph_crs,
buffer_dist=dist,
squash_nodes=True,
centroid_by_itx=True,
osm_hwy_target_tags=tags,
prioritise_by_hwy_tag=True,
simplify_line_angles=simplify_angles,
contains_buffer_dist=50,
)
graph_crs = graphs.nx_consolidate_nodes(
graph_crs,
buffer_dist=dist,
crawl=True,
centroid_by_itx=True,
osm_hwy_target_tags=tags,
prioritise_by_hwy_tag=True,
simplify_line_angles=simplify_angles,
contains_buffer_dist=50,
)
graph_crs = graphs.nx_remove_filler_nodes(graph_crs)
# snap gapped endings - don't clean danglers before this
graph_crs = graphs.nx_snap_gapped_endings(
graph_crs,
buffer_dist=20,
# not main roads
osm_hwy_target_tags=[
"residential",
"service",
"cycleway",
"bridleway",
"pedestrian",
"steps",
"footway",
"footway_pedestrian", # plazas
"path",
"living_street",
"unclassified",
],
)
# snap gapped endings / roaods - don't clean danglers before this
# look for degree 1 dead-ends and link to nearby edges
graph_crs = graphs.nx_split_opposing_geoms(
graph_crs,
buffer_dist=25,
min_node_degree=1,
max_node_degree=1,
squash_nodes=False,
)
# remove longer danglers
graph_crs = graphs.nx_remove_dangling_nodes(graph_crs, despine=50)
graph_crs = graphs.nx_iron_edges(graph_crs)
graph_crs = _auto_clean_network(graph_crs, geom_wgs, int(to_crs_code), remove_disconnected)

return graph_crs

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