From 6379b73a79f070c823e887447d6a391fcc5e9401 Mon Sep 17 00:00:00 2001 From: Manuel-Knepper Date: Fri, 14 Aug 2026 09:56:39 +0200 Subject: [PATCH 1/2] added import for bike network --- LinkBikeNet_MVP.ipynb | 653 +++++++++++++++++++++++++++++++++++-- linkbikenet/functions.py | 36 ++ linkbikenet/linkbikenet.py | 24 +- 3 files changed, 678 insertions(+), 35 deletions(-) diff --git a/LinkBikeNet_MVP.ipynb b/LinkBikeNet_MVP.ipynb index e344ada..370e006 100644 --- a/LinkBikeNet_MVP.ipynb +++ b/LinkBikeNet_MVP.ipynb @@ -7,7 +7,12 @@ "id": "53fb68da3433feed" }, { - "metadata": {}, + "metadata": { + "ExecuteTime": { + "end_time": "2026-08-14T07:12:15.483106Z", + "start_time": "2026-08-14T07:12:13.924401Z" + } + }, "cell_type": "code", "source": [ "# imports\n", @@ -20,22 +25,51 @@ ], "id": "e36d2da0a6b91022", "outputs": [], - "execution_count": null + "execution_count": 1 }, { - "metadata": {}, + "metadata": { + "ExecuteTime": { + "end_time": "2026-08-14T07:12:16.132974Z", + "start_time": "2026-08-14T07:12:16.115155Z" + } + }, "cell_type": "code", "source": [ "# config\n", - "city_name = 'Budapest'\n", - "ox.settings.useful_tags_way = [\"highway\", \"cycleway\", \"cycleway:right\", \"cycleway:left\", \"cycleway:both\", \"cyclestreet\"]" + "city_name = 'Tirana'\n", + "ox.settings.useful_tags_way = [\"highway\", \"cycleway\", \"cycleway:right\", \"cycleway:left\", \"cycleway:both\", \"cyclestreet\"]\n", + "import_files={'bike_network':\"./tirana_al.gpkg\"}\n", + "proj_crs=\"3857\"" ], "id": "614776afbd56a6ef", "outputs": [], - "execution_count": null + "execution_count": 2 }, { - "metadata": {}, + "metadata": { + "ExecuteTime": { + "end_time": "2026-08-14T07:12:17.195663Z", + "start_time": "2026-08-14T07:12:16.996834Z" + } + }, + "cell_type": "code", + "source": [ + "h = import_bike_network(import_files['bike_network'])\n", + "h = ox.project_graph(h, to_crs=proj_crs)\n", + "h = nx.Graph(h)" + ], + "id": "4c0364c42c6fd40f", + "outputs": [], + "execution_count": 3 + }, + { + "metadata": { + "ExecuteTime": { + "end_time": "2026-08-14T07:12:29.582859Z", + "start_time": "2026-08-14T07:12:18.045278Z" + } + }, "cell_type": "code", "source": [ "# fetch street network from OSM\n", @@ -49,16 +83,35 @@ "ox.plot_graph(g);" ], "id": "44efda017a66aba5", - "outputs": [], - "execution_count": null + "outputs": [ + { + "data": { + "text/plain": [ + "
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" + }, + "metadata": {}, + "output_type": "display_data", + "jetTransient": { + "display_id": null + } + } + ], + "execution_count": 4 }, { - "metadata": {}, + "metadata": { + "ExecuteTime": { + "end_time": "2026-08-14T07:12:35.125333Z", + "start_time": "2026-08-14T07:12:33.993835Z" + } + }, "cell_type": "code", "source": "g = ox.project_graph(g, to_crs=\"3857\")", "id": "d9ceb1ea7ac8a753", "outputs": [], - "execution_count": null + "execution_count": 5 }, { "metadata": {}, @@ -67,12 +120,17 @@ "id": "f800a2ddf842b29a" }, { - "metadata": {}, + "metadata": { + "ExecuteTime": { + "end_time": "2026-08-14T07:12:36.211729Z", + "start_time": "2026-08-14T07:12:36.095058Z" + } + }, "cell_type": "code", "source": "g = map_edges_to_bike_infrastructure(g)", "id": "3161e72cc886c716", "outputs": [], - "execution_count": null + "execution_count": 6 }, { "metadata": {}, @@ -81,7 +139,12 @@ "id": "24edbcdf1a30042b" }, { - "metadata": {}, + "metadata": { + "ExecuteTime": { + "end_time": "2026-08-14T07:12:48.214012Z", + "start_time": "2026-08-14T07:12:37.267756Z" + } + }, "cell_type": "code", "source": [ "# finding parallel edges and dropping them\n", @@ -90,10 +153,15 @@ ], "id": "736c43fa7495d973", "outputs": [], - "execution_count": null + "execution_count": 7 }, { - "metadata": {}, + "metadata": { + "ExecuteTime": { + "end_time": "2026-08-14T07:13:08.048239Z", + "start_time": "2026-08-14T07:13:07.799679Z" + } + }, "cell_type": "code", "source": [ "# Capital-G: the Graph() object we will be working with from now on\n", @@ -101,7 +169,7 @@ ], "id": "63fce5acd06b8ad1", "outputs": [], - "execution_count": null + "execution_count": 8 }, { "metadata": {}, @@ -110,7 +178,12 @@ "id": "8d170498268cac6c" }, { - "metadata": {}, + "metadata": { + "ExecuteTime": { + "end_time": "2026-08-14T07:13:09.255921Z", + "start_time": "2026-08-14T07:13:09.218439Z" + } + }, "cell_type": "code", "source": [ "edges = [\n", @@ -119,38 +192,93 @@ " if data.get(\"pbi\") == 1\n", "]\n", "\n", - "H = G.edge_subgraph(edges).copy()" + "if import_files['bike_network'] is not None:\n", + " H = h.copy()\n", + "else:\n", + " H = G.edge_subgraph(edges).copy()" ], "id": "b37fec62eac9b875", "outputs": [], - "execution_count": null + "execution_count": 9 }, { - "metadata": {}, + "metadata": { + "ExecuteTime": { + "end_time": "2026-08-14T07:13:11.401975Z", + "start_time": "2026-08-14T07:13:11.358570Z" + } + }, "cell_type": "code", "source": "wcc = [H.subgraph(c).copy() for c in sorted(nx.connected_components(H), key=lambda c: sum([l[-1] for l in H.subgraph(c).copy().edges.data('length')]), reverse=True)]", "id": "3c4f7e3fccdcfdab", "outputs": [], - "execution_count": null + "execution_count": 10 }, { - "metadata": {}, + "metadata": { + "ExecuteTime": { + "end_time": "2026-08-14T07:13:12.428076Z", + "start_time": "2026-08-14T07:13:12.418637Z" + } + }, + "cell_type": "code", + "source": [ + "# Nodes belonging to the original largest component\n", + "main_component = set(wcc[0])\n", + "\n", + "# Mark all edges in the original largest component as step 0\n", + "for u, v in H.subgraph(main_component).edges():\n", + " H[u][v][\"lcc_step\"] = 0" + ], + "id": "34545b984c4499f7", + "outputs": [], + "execution_count": 11 + }, + { + "metadata": { + "ExecuteTime": { + "end_time": "2026-08-14T07:13:23.975824Z", + "start_time": "2026-08-14T07:13:13.347485Z" + } + }, "cell_type": "code", "source": [ "to_iterate = len(wcc) -1\n", "closest_pairs = []\n", + "step = 1\n", "for i in range(to_iterate):\n", - " wcc = [H.subgraph(c).copy() for c in sorted(nx.connected_components(H), key=lambda c: sum([l[-1] for l in H.subgraph(c).copy().edges.data('length')]), reverse=True)]\n", + " wcc = [H.subgraph(c).copy() for c in sorted(nx.connected_components(H), key=lambda c: sum(\n", + " [l[-1] for l in H.subgraph(c).copy().edges.data('length')]), reverse=True)]\n", " pair = pair_between_largest_components(wcc)\n", + " # Determine which components contain u and v\n", + " component_u = next(c for c in wcc if pair[0] in c)\n", + " component_v = next(c for c in wcc if pair[1] in c)\n", + " u_in_main = pair[0] in main_component\n", + " v_in_main = pair[1] in main_component\n", " closest_pairs.append(pair)\n", - " H.add_edge(pair[0], pair[1], length=0)" + " H.add_edge(pair[0], pair[1], length=0, lcc_step=None)\n", + " if u_in_main and not v_in_main:\n", + " mark_joined_component(H, component_v, step)\n", + " main_component.update(component_v)\n", + " H[pair[0]][pair[1]][\"lcc_step\"] = step\n", + "\n", + " elif v_in_main and not u_in_main:\n", + " mark_joined_component(H, component_u, step)\n", + " main_component.update(component_u)\n", + " H[pair[0]][pair[1]][\"lcc_step\"] = step\n", + " step += 1" ], "id": "4e01176474c927ad", "outputs": [], - "execution_count": null + "execution_count": 12 }, { - "metadata": {}, + "metadata": { + "ExecuteTime": { + "end_time": "2026-08-14T07:13:29.982280Z", + "start_time": "2026-08-14T07:13:29.914074Z" + } + }, "cell_type": "code", "source": [ "# find paths between nodes\n", @@ -164,15 +292,478 @@ ], "id": "22bf8b71ab94ad53", "outputs": [], - "execution_count": null + "execution_count": 13 }, { - "metadata": {}, + "metadata": { + "ExecuteTime": { + "end_time": "2026-08-14T07:46:18.469640Z", + "start_time": "2026-08-14T07:46:18.198316Z" + } + }, "cell_type": "code", - "source": "edges_gdf = graph_edges_to_gdf(G)", + "source": [ + "H.remove_edges_from(closest_pairs)\n", + "edges_pbi_gdf = graph_edges_to_gdf(H)\n", + "edges_gdf = graph_edges_to_gdf(G)" + ], "id": "5e190540745efa98", "outputs": [], - "execution_count": null + "execution_count": 28 + }, + { + "metadata": { + "ExecuteTime": { + "end_time": "2026-08-14T07:51:07.330786Z", + "start_time": "2026-08-14T07:51:07.302764Z" + } + }, + "cell_type": "code", + "source": "edges_pbi_gdf.set_crs(epsg=4326, allow_override=True, inplace=True)", + "id": "f6e33b52d205e44d", + "outputs": [ + { + "data": { + "text/plain": [ + " access bridge footway highway junction lanes \\\n", + "u v 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"... ... \n", + "12104386197 12103394999 40 \n", + "12103420503 12104395903 36 \n", + "6297599068 6297599071 158 \n", + "12141005253 12141005257 267 \n", + "10922895977 12173793268 80 \n", + "\n", + "[1243 rows x 19 columns]" + ], + "text/html": [ + "
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accessbridgefootwayhighwayjunctionlanesmaxspeednameonewaysegregatedtunnelcycleway:leftcycleway:rightosmidlengthfromtogeometrylcc_step
uv
154930214652332064living_streetRruga Mihal Popiyes319244528.314154930214652332064LINESTRING (19.8069 41.32001, 19.80672 41.31979)0
15461424living_streetRruga Mustafa Qosjayes404224734.1441549302115461424LINESTRING (19.80656 41.32018, 19.8069 41.32001)0
1843574832living_streetRruga Mustafa Qosjayes404224738.110154930211843574832LINESTRING (19.8069 41.32001, 19.8072 41.31985...0
46523320641458037101living_streetRruga Mihal Popiyes31924454.08846523320641458037101LINESTRING (19.80672 41.31979, 19.80669 41.31976)0
4652332059cyclewayno67153008592.60946523320644652332059LINESTRING (19.80672 41.31979, 19.80647 41.319...0
...............................................................
1210438619712103394999cycleway1306941968532.2021210438619712103394999LINESTRING (19.85635 41.33304, 19.8556 41.3331...40
1210342050312104395903cycleway1306941972558.4011210342050312104395903LINESTRING (19.84991 41.33347, 19.84994 41.333...36
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1243 rows × 19 columns

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" + ] + }, + "execution_count": 42, + "metadata": {}, + "output_type": "execute_result" + } + ], + "execution_count": 42 + }, + { + "metadata": { + "ExecuteTime": { + "end_time": "2026-08-14T07:45:51.068887Z", + "start_time": "2026-08-14T07:45:51.007784Z" + } + }, + "cell_type": "code", + "source": "edges_pbi_gdf.to_crs(epsg=4326, inplace=True)", + "id": "bb46c58c1c4e6338", + "outputs": [], + "execution_count": 26 + }, + { + "metadata": { + "ExecuteTime": { + "end_time": "2026-08-14T07:51:30.103958Z", + "start_time": "2026-08-14T07:51:30.033648Z" + } + }, + "cell_type": "code", + "source": "edges_pbi_gdf.to_file(\"test_tirana_existing_network\", driver=\"GeoJSON\", RFC7946=\"YES\")", + "id": "d361510cf9bea633", + "outputs": [], + "execution_count": 44 }, { "metadata": {}, diff --git a/linkbikenet/functions.py b/linkbikenet/functions.py index d6bccd8..4075124 100644 --- a/linkbikenet/functions.py +++ b/linkbikenet/functions.py @@ -49,6 +49,42 @@ def import_network(street_network, import_path=settings.import_path): return g +def import_bike_network(bike_network, import_path=settings.import_path): + """Import and project a street network from gpkg file + + For all edges between a pair of nodes u and v there must be one edge with key 0. + + Parameters + ---------- + bike_network : str + The street network will be loaded from this file. Must be a gpkg file in unprojected crs EPSG:4326 with layers nodes and edges, with the structure that a osmnx street network g has after saving its undirected version via ox.io.save_graph_geopackage(). For example: + >>> g = ox.graph_from_place("Barcelona", network_type='all_public', simplify=False, retain_all=True) + >>> g = nx.MultiGraph(ox.convert.to_digraph(g)) + >>> ox.io.save_graph_geopackage(g, "Barcelona_streets.gpkg") + import_path : str, default settings.import_path + Path to import files. + + Returns + ------- + h: networkx.Graph + graph of the bike network + """ + + nodes = gpd.read_file(import_path+bike_network, layer='nodes') + edges = gpd.read_file(import_path+bike_network, layer='edges') + + # Set indices as required by osmnx.convert.graph_from_gdfs + # See: https://osmnx.readthedocs.io/en/stable/user-reference.html#osmnx.utils_graph.graph_from_gdfs + nodes = nodes.set_index(['osmid']) + edges = edges.set_index(['u', 'v', 'key']) + + h = ox.convert.graph_from_gdfs(nodes, edges) + + #city_boundary_gdf = gpd.GeoDataFrame(gpd.GeoSeries(nodes.union_all().convex_hull), geometry=0, crs=nodes.crs) # We do this before the projection of nodes below + # To do: To be super-correct, the hull should be buffered by settings.seed_point_snap_distance (in degrees due to being unprojected) + + return h + def map_edges_to_bike_infrastructure(g): """ map if edges in graph have bike infrastructure as specified in config.py diff --git a/linkbikenet/linkbikenet.py b/linkbikenet/linkbikenet.py index 7d5301b..8372914 100644 --- a/linkbikenet/linkbikenet.py +++ b/linkbikenet/linkbikenet.py @@ -40,6 +40,8 @@ def linkbikenet( >>> g = ox.graph_from_place("Barcelona", network_type='all_public', simplify=False, retain_all=True) >>> g = nx.MultiGraph(ox.convert.to_digraph(g)) >>> ox.io.save_graph_geopackage(g, "Barcelona_streets.gpkg"). + "bike_network" : str | None, default None + If not set to None, the existing bike network is loaded from this file. Must be a gpkg file in unprojected crs EPSG:4326 with layers nodes and edges, with the structure that an undirected osmnx bike network has after saved via ox.io.save_graph_geopackage(). Returns ------- gdf: geopandas.GeoDataFrame @@ -61,6 +63,11 @@ def linkbikenet( # Prepare special case import_files. Turn it into a defaultdict where missing keys are None. import_files = defaultdict(lambda: None, import_files) + if import_files['bike_network'] is not None: + print("Importing bike network..") + h = import_bike_network(import_files['bike_network']) + h = ox.project_graph(h, to_crs=proj_crs) + h = nx.Graph(h) if import_files['street_network'] is not None: print("Importing street network..") @@ -104,7 +111,10 @@ def linkbikenet( if data.get("pbi") == 1 ] - H = G.edge_subgraph(edges).copy() + if import_files['bike_network'] is not None: + H = h.copy() + else: + H = G.edge_subgraph(edges).copy() # computing all weakly connected components to find out how many there are. This informs the amount of loops later wcc = [H.subgraph(c).copy() for c in sorted(nx.connected_components(H), key=lambda c: sum( @@ -214,7 +224,10 @@ def linkbikenet( gdf['ordering'] = gdf.index # reset Graph - H = G.edge_subgraph(edges).copy() + if import_files['bike_network'] is not None: + H = h.copy() + else: + H = G.edge_subgraph(edges).copy() # calculating connectivity metrics print("Calculating connectivity metrics...") @@ -238,7 +251,10 @@ def linkbikenet( # Back to unprojected (potentially). No more calculations after here. gdf.to_crs(epsg=4326, inplace=True) - edges_pbi_gdf.to_crs(epsg=4326, inplace=True) + if import_files['bike_network'] is not None: + edges_pbi_gdf.set_crs(epsg=4326, allow_override=True, inplace=True) + else: + edges_pbi_gdf.to_crs(epsg=4326, inplace=True) # Generate export data filename if export_data: @@ -259,7 +275,7 @@ def linkbikenet( city_boundary.to_crs(epsg=4326, inplace=True) if export_file_format == "geojson": gdf.to_file(settings.export_path + export_data_filename, driver="GeoJSON", RFC7946="YES") - edges_pbi_gdf.to_file(settings.export_path + slugify(city_string) + connection_strategy + "-existing_bike_network.geojson", driver="GeoJSON", RFC7946="YES") + edges_pbi_gdf.to_file(settings.export_path + slugify(city_string) + "-" + connection_strategy + "-existing_bike_network.geojson", driver="GeoJSON", RFC7946="YES") city_boundary.to_file(settings.export_path + slugify(city_string) + "-city_boundary.geojson", driver="GeoJSON", RFC7946="YES") elif export_file_format == "gpkg": gdf.to_file(settings.export_path + export_data_filename, driver="GPKG", layer="Identified links") From 6eff2376fca1c4cc61dd4f084c612f2b1df5d7fd Mon Sep 17 00:00:00 2001 From: Manuel-Knepper Date: Fri, 14 Aug 2026 10:40:47 +0200 Subject: [PATCH 2/2] add row to show initial state of network, change file export name --- linkbikenet/linkbikenet.py | 28 +++++++++++++++++++++++++--- 1 file changed, 25 insertions(+), 3 deletions(-) diff --git a/linkbikenet/linkbikenet.py b/linkbikenet/linkbikenet.py index 8372914..e3c45e7 100644 --- a/linkbikenet/linkbikenet.py +++ b/linkbikenet/linkbikenet.py @@ -221,8 +221,6 @@ def linkbikenet( df['edge_list'] = df.nodelist.apply(lambda x: get_correct_edgetuples(edges_gdf, x)) gdf = create_gdf_with_geoms(df, edges_gdf) - gdf['ordering'] = gdf.index - # reset Graph if import_files['bike_network'] is not None: H = h.copy() @@ -234,6 +232,7 @@ def linkbikenet( network_lengths = [] lcc_lengths = [] edge_lengths = gdf['geometry'].length + initial_network_length, initial_lcc_length = calculate_network_statistics(H) for i in range(len(gdf)): H.add_edge(closest_pairs[i][0], closest_pairs[i][1], length=edge_lengths[i]) @@ -244,9 +243,32 @@ def linkbikenet( gdf['network_length'] = network_lengths gdf['lcc_length'] = lcc_lengths + # add initial row to represent state of network before links are added + initial_row = { + "nodelist": None, + "edge_list": None, + "geometry": None, + "network_length": initial_network_length, + "lcc_length": initial_lcc_length, + } + # Turn it into a one-row GeoDataFrame + initial_gdf = gpd.GeoDataFrame( + [initial_row], + geometry="geometry", + crs=gdf.crs + ) + + # Put step 0 at the beginning + gdf = pd.concat( + [initial_gdf, gdf], + ignore_index=True + ) + gdf['lcc_share'] = gdf['lcc_length'] / gdf['network_length'] gdf['lcc_gain'] = gdf['lcc_length'].diff().fillna(0) + gdf['ordering'] = gdf.index + #edges_pbi_gdf = edges_gdf[edges_gdf["pbi"] == 1] # Back to unprojected (potentially). No more calculations after here. @@ -275,7 +297,7 @@ def linkbikenet( city_boundary.to_crs(epsg=4326, inplace=True) if export_file_format == "geojson": gdf.to_file(settings.export_path + export_data_filename, driver="GeoJSON", RFC7946="YES") - edges_pbi_gdf.to_file(settings.export_path + slugify(city_string) + "-" + connection_strategy + "-existing_bike_network.geojson", driver="GeoJSON", RFC7946="YES") + edges_pbi_gdf.to_file(settings.export_path + slugify(city_string) + "-linkbikenet-" + connection_strategy + "-existing_bike_network.geojson", driver="GeoJSON", RFC7946="YES") city_boundary.to_file(settings.export_path + slugify(city_string) + "-city_boundary.geojson", driver="GeoJSON", RFC7946="YES") elif export_file_format == "gpkg": gdf.to_file(settings.export_path + export_data_filename, driver="GPKG", layer="Identified links")