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Mkne functions tests #4

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7831be5
added find_potential_gaps to functions.py and implemented it in FixBi…
Manuel-Knepper Mar 6, 2026
4737d32
added test_find_potential_gaps to test_functions.py and optimized fin…
Manuel-Knepper Mar 6, 2026
08dfd28
added find_actual_gaps to functions.py and implemented it in FixBikeM…
Manuel-Knepper Mar 6, 2026
ccdedca
added test_find_actual_gaps to test_functions.py
Manuel-Knepper Mar 6, 2026
819231f
added compute_local_betweenness_centrality to functions.py and implem…
Manuel-Knepper Mar 6, 2026
9b0bb5c
added test_compute_local_betweenness_centrality to test_functions.py
Manuel-Knepper Mar 6, 2026
5538229
added rank_gaps_by_b to functions.py and implemented it in FixBikeMVP…
Manuel-Knepper Mar 6, 2026
f8c7134
added test_rank_gaps_by_b to test_functions.py
Manuel-Knepper Mar 6, 2026
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195 changes: 73 additions & 122 deletions FixBikeMVP.ipynb
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Original file line number Diff line number Diff line change
Expand Up @@ -15,17 +15,14 @@
"id": "1b6a69660258f567",
"metadata": {
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"end_time": "2026-03-05T14:44:35.560984Z",
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"start_time": "2026-03-06T13:24:08.014186Z"
}
},
"source": [
"# import packages\n",
"import pandas as pd\n",
"import osmnx as ox\n",
"import networkx as nx\n",
"import random\n",
"import numpy as np\n",
"import matplotlib.pyplot as plt\n",
"import os\n",
"\n",
Expand All @@ -48,8 +45,8 @@
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Expand Down Expand Up @@ -79,8 +76,8 @@
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Expand All @@ -101,8 +98,8 @@
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Expand Down Expand Up @@ -137,8 +134,8 @@
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"cell_type": "code",
Expand All @@ -164,8 +161,8 @@
{
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Expand All @@ -179,8 +176,8 @@
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"source": [
Expand Down Expand Up @@ -222,8 +219,8 @@
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Expand All @@ -248,8 +245,8 @@
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"start_time": "2026-03-06T13:31:18.226835Z"
}
},
"source": "G = weigh_edges(G, penalty)",
Expand All @@ -271,8 +268,8 @@
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"metadata": {
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"source": [
Expand All @@ -288,7 +285,7 @@
]
}
],
"execution_count": 11
"execution_count": 10
},
{
"cell_type": "markdown",
Expand All @@ -297,39 +294,32 @@
"source": [
"### Create list of all potential gaps\n",
"\n",
"Here defined as: contact node pair combinations **within `maxgap` euclidean distance from each other** "
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "a02eeca1",
"metadata": {},
"outputs": [],
"source": [
"potential_gaps = []\n",
"\n",
"for node in contact_nodes:\n",
" node_buffer = nodes_gdf.loc[node, \"geometry\"].buffer(maxgap)\n",
" q = nodes_gdf.sindex.query(node_buffer, predicate=\"intersects\")\n",
" neighbours = list(nodes_gdf.iloc[q].index)\n",
" # convention: sort by ascending OSMID...\n",
" node_pairs = [tuple(sorted(z)) for z in zip([node]*len(neighbours), neighbours)]\n",
" potential_gaps += node_pairs\n",
"\n",
"# ... so that we can easily deduplicate\n",
"potential_gaps = list(set(potential_gaps))"
"Here defined as: contact node pair combinations **within `maxgap` euclidean distance from each other**"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "a01da088",
"metadata": {},
"outputs": [],
"metadata": {
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"end_time": "2026-03-06T13:31:24.244710Z",
"start_time": "2026-03-06T13:31:21.777852Z"
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},
"source": [
"potential_gaps = find_potential_gaps(contact_nodes, nodes_gdf, maxgap)\n",
"print(\"potential gaps found:\", len(potential_gaps))"
]
],
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"potential gaps found: 142482\n"
]
}
],
"execution_count": 11
},
{
"cell_type": "markdown",
Expand All @@ -345,35 +335,16 @@
},
{
"cell_type": "code",
"execution_count": null,
"id": "43c578c3",
"metadata": {},
"metadata": {
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"end_time": "2026-03-06T13:31:31.246886Z",
"start_time": "2026-03-06T13:31:26.417817Z"
}
},
"source": "found_gaps, found_gaps_nsp = find_actual_gaps(G, potential_gaps)",
"outputs": [],
"source": [
"pbi_dict = nx.get_edge_attributes(G, \"pbi\")\n",
"\n",
"found_gaps = []\n",
"found_gaps_nsp = [] # naive shortest paths (by length, in node list format)\n",
"\n",
"for i, gap in enumerate(potential_gaps):\n",
" u, v = gap\n",
" nodelist = nx.shortest_path(\n",
" G=G,\n",
" source=u,\n",
" target=v, \n",
" weight=\"length\"\n",
" )\n",
" pbis = set([pbi_dict[tuple(sorted(z))] for z in zip(nodelist, nodelist[1:])])\n",
" \n",
" # confirm that it is an actual gap if it consists only of pbi==0 infra:\n",
" if pbis==set([0]): \n",
" found_gaps.append(gap)\n",
" found_gaps_nsp.append(nodelist)\n",
" \n",
" # # (manual timer)\n",
" # if i % 100000 == 0:\n",
" # print(i)\n"
]
"execution_count": 12
},
{
"cell_type": "markdown",
Expand All @@ -385,17 +356,22 @@
},
{
"cell_type": "code",
"execution_count": null,
"id": "b5ca9fdf440935d8",
"metadata": {},
"outputs": [],
"metadata": {
"ExecuteTime": {
"end_time": "2026-03-06T13:31:33.093955Z",
"start_time": "2026-03-06T13:31:33.006586Z"
}
},
"source": [
"edgelist = []\n",
"for nodelist in found_gaps_nsp:\n",
" edgelist += [tuple(sorted(z)) for z in zip(nodelist, nodelist[1:])]\n",
"# deduplicate\n",
"edgelist = list(set(edgelist))"
]
],
"outputs": [],
"execution_count": 13
},
{
"cell_type": "markdown",
Expand All @@ -407,38 +383,16 @@
},
{
"cell_type": "code",
"execution_count": null,
"id": "b1f0c683",
"metadata": {},
"metadata": {
"ExecuteTime": {
"end_time": "2026-03-06T13:32:08.385205Z",
"start_time": "2026-03-06T13:31:34.994480Z"
}
},
"source": "ebc = compute_local_betweenness_centrality(G, nodes_gdf, radius)",
"outputs": [],
"source": [
"# set current ebc value of all G edges to 0\n",
"for edge in G.edges:\n",
" G.edges[edge][\"ebc\"] = 0\n",
"\n",
"# create dict that will be updated at each step\n",
"ebc = nx.get_edge_attributes(G, \"ebc\")\n",
"\n",
"# for each node, compute \"local\" ebc (buffered with radius!)\n",
"# for comp feas, now only subset of randomly drawn 100 nodes\n",
"random.seed(1312)\n",
"random_nodes = random.choices(list(G.nodes), k = 100)\n",
"for node in random_nodes:\n",
" node_buffer = nodes_gdf.loc[node, \"geometry\"].buffer(radius)\n",
" q = nodes_gdf.sindex.query(node_buffer, predicate=\"intersects\")\n",
" neighbours = list(nodes_gdf.iloc[q].index)\n",
" local_ebc = nx.edge_betweenness_centrality_subset(\n",
" G=G,\n",
" sources=[node],\n",
" targets=neighbours,\n",
" normalized=False, # important! otherwise the addition makes no sense\n",
" weight=\"weight\"# using penalty for non-pbi\n",
" )\n",
"\n",
" # update ebc dictionary\n",
" for k, v in local_ebc.items():\n",
" ebc[k] += v # updating ebc!!"
]
"execution_count": 14
},
{
"cell_type": "markdown",
Expand All @@ -450,19 +404,16 @@
},
{
"cell_type": "code",
"execution_count": null,
"id": "4c920f49e57db5c",
"metadata": {},
"metadata": {
"ExecuteTime": {
"end_time": "2026-03-06T13:32:13.235834Z",
"start_time": "2026-03-06T13:32:12.972818Z"
}
},
"source": "Bs = rank_gaps_by_b(found_gaps_nsp, G, ebc)",
"outputs": [],
"source": [
"Bs = []\n",
"for nodelist in found_gaps_nsp:\n",
" edgelist = [tuple(sorted(z)) for z in zip(nodelist, nodelist[1:])]\n",
" lengths = np.array([G.edges[edge][\"length\"] for edge in edgelist])\n",
" ebcs = np.array([ebc[edge] for edge in edgelist])\n",
" B = sum(lengths * ebcs)/sum(lengths)\n",
" Bs.append(B)"
]
"execution_count": 15
},
{
"cell_type": "markdown",
Expand Down
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