geo-l1-cairo-multipoint-hull

Status: done
Score: 100
Duration: 1:53
Cost: 0.19¢
Model: google/gemma-4-26b-a4b-it

Map (reference ← swipe → agent)

0:00
I'm putting together the accessibility report for the Metro, and its static maps need to show how far each station's underground box reaches at street level. `cairo_metro_stations.geojson` has each station's street-level entrances. Can you compute the convex hull of each station's entrances and save the result to `cairo_metro_hulls.geojson`, one Polygon per station? Every row must carry `station_name_en` and `station_name_ar`, both non-empty, with the original Arabic strings and diacritics preserved exactly as they appear in the input.
0:00
System info 
{
  "adapter": "openrouter",
  "model": "google/gemma-4-26b-a4b-it",
  "base_url": "https://openrouter.ai/api/v1"
}
0:04
Bash ls -F 
ls -F

cairo_metro_stations.geojson
1:01
Write /work/solve.py
content · 62 lines · py 
import geopandas as gpd

def main():
    # Load the data
    gdf = gpd.read_file('cairo_metro_stations.geojson')
    
    # Check the columns
    print("Columns:", gdf.columns.tolist())
    print("First few rows:")
    print(gdf.head())
    
    # The user wants the convex hull of each station's entrances.
    # Let's check if there's a station identifier to group by.
    # Looking at the prompt, we need to group by station names.
    # Actually, if each row is an entrance, we group by station names.
    # If each row is a station and 'entrances' is a geometry (MultiPoint?), we handle it.
    # Usually, GeoJSON files with multiple entrances per station might be separate rows.
    
    # Let's see the structure.
    
    # Group by station names and compute convex hull
    # We need to keep both station_name_en and station_name_ar.
    # We'll group by both to ensure we get the unique combination.
    
    # To compute convex hull per station:
    # 1. Group by [station_name_en, station_name_ar]
    # 2. Dissolve/Combine geometries
    # 3. Calculate convex hull
    
    # Grouping by both name columns to preserve them. 
    # Note: We must ensure they are non-empty as requested.
    
    # Filter out rows where names are empty or NaN
    gdf = gdf[gdf['station_name_en'].notna() & (gdf['station_name_en'] != '')]
    gdf = gdf[gdf['station_name_ar'].notna() & (gdf['station_name_ar'] != '')]

    # Grouping by station names
    hulls = gdf.dissolve(by=['station_name_en', 'station_name_ar'], aggfunc='sum')
    
    # Wait, 'sum' on geometry might not work or might be weird. 
    # Let's do it properly: combine all geometries for each group, then hull.
    
    grouped = gdf.groupby(['station_name_en', 'station_name_ar'])['geometry'].apply(lambda x: x.unary_union)
    
    # Convert back to GeoDataFrame
    hulls_gdf = gpd.GeoDataFrame(geometry=grouped.values, crs=gdf.crs)
    hulls_gdf['station_name_en'] = grouped.index.get_level_values(0)
    hulls_gdf['station_name_ar'] = grouped.index.get_level_values(1)
    
    # Now compute the convex hull for each geometry
    hulls_gdf['geometry'] = hulls_gdf.geometry.convex_hull
    
    # Reorder columns to be nice
    hulls_gdf = hulls_gdf[['station_name_en', 'station_name_ar', 'geometry']]
    
    # Save to file
    hulls_gdf.to_file('cairo_metro_hulls.geojson', driver='GeoJSON')
    print("Successfully saved cairo_metro_hulls.geojson")

if __name__ == "__main__":
    main()

Wrote /work/solve.py (2461 chars).
1:04
Bash python /work/solve.py 
python /work/solve.py

Columns: ['station_name_en', 'station_name_ar', 'geometry']
First few rows:
    station_name_en  ...                                           geometry
0       Al-Shohadaa  ...  MULTIPOINT ((31.24644 30.06311), (31.24678 30....
1            Attaba  ...  MULTIPOINT ((31.2462 30.05151), (31.2464 30.05...
2  Cairo University  ...  MULTIPOINT ((31.20022 30.02526), (31.20083 30....
3             Dokki  ...  MULTIPOINT ((31.21193 30.03845), (31.21286 30....
4      El Demerdash  ...  MULTIPOINT ((31.27273 30.0791), (31.27284 30.0...

[5 rows x 3 columns]
Successfully saved cairo_metro_hulls.geojson
/work/solve.py:43: DeprecationWarning: The 'unary_union' attribute is deprecated, use the 'union_all()' method instead.
  grouped = gdf.groupby(['station_name_en', 'station_name_ar'])['geometry'].apply(lambda x: x.unary_union)
1:13
Bash head -n 20 cairo_metro_hulls.geojson 
head -n 20 cairo_metro_hulls.geojson

{
"type": "FeatureCollection",
"name": "cairo_metro_hulls",
"crs": { "type": "name", "properties": { "name": "urn:ogc:def:crs:OGC:1.3:CRS84" } },
"features": [
{ "type": "Feature", "properties": { "station_name_en": "Al-Shohadaa", "station_name_ar": "الشهداء" }, "geometry": { "type": "Polygon", "coordinates": [ [ [ 31.247736, 30.061538 ], [ 31.246778, 30.062428 ], [ 31.246441, 30.063109 ], [ 31.246859, 30.063158 ], [ 31.247931, 30.062636 ], [ 31.247736, 30.061538 ] ] ] } },
{ "type": "Feature", "properties": { "station_name_en": "Attaba", "station_name_ar": "العتبة" }, "geometry": { "type": "Polygon", "coordinates": [ [ [ 31.246196, 30.051508 ], [ 31.246396, 30.051849 ], [ 31.246936, 30.052384 ], [ 31.247559, 30.052018 ], [ 31.246196, 30.051508 ] ] ] } },
{ "type": "Feature", "properties": { "station_name_en": "Cairo University", "station_name_ar": "جامعة القاهرة" }, "geometry": { "type": "Polygon", "coordinates": [ [ [ 31.201463, 30.025147 ], [ 31.200216, 30.025256 ], [ 31.200826, 30.026512 ], [ 31.20167, 30.026648 ], [ 31.201463, 30.025147 ] ] ] } },
{ "type": "Feature", "properties": { "station_name_en": "Dokki", "station_name_ar": "الدقي" }, "geometry": { "type": "Polygon", "coordinates": [ [ [ 31.213408, 30.037575 ], [ 31.211926, 30.038446 ], [ 31.213071, 30.039014 ], [ 31.213408, 30.037575 ] ] ] } },
{ "type": "Feature", "properties": { "station_name_en": "El Demerdash", "station_name_ar": "الدمرداش" }, "geometry": { "type": "Polygon", "coordinates": [ [ [ 31.273817, 30.078925 ], [ 31.272726, 30.079096 ], [ 31.272841, 30.079167 ], [ 31.274032, 30.079479 ], [ 31.273817, 30.078925 ] ] ] } },
{ "type": "Feature", "properties": { "station_name_en": "El Malek El Saleh", "station_name_ar": "الملك الصالح" }, "geometry": { "type": "Polygon", "coordinates": [ [ [ 31.234504, 30.017367 ], [ 31.233473, 30.018682 ], [ 31.233442, 30.019095 ], [ 31.234545, 30.017379 ], [ 31.234504, 30.017367 ] ] ] } },
{ "type": "Feature", "properties": { "station_name_en": "El-Marg", "station_name_ar": "المرج" }, "geometry": { "type": "Polygon", "coordinates": [ [ [ 31.334217, 30.146468 ], [ 31.334253, 30.146538 ], [ 31.334782, 30.146493 ], [ 31.334217, 30.146468 ] ] ] } },
{ "type": "Feature", "properties": { "station_name_en": "Ghamra", "station_name_ar": "غمرة" }, "geometry": { "type": "Polygon", "coordinates": [ [ [ 31.263197, 30.068259 ], [ 31.263164, 30.068985 ], [ 31.264394, 30.068864 ], [ 31.263197, 30.068259 ] ] ] } },
{ "type": "Feature", "properties": { "station_name_en": "Hadayek El-Zaitoun", "station_name_ar": "حدائق الزيتون" }, "geometry": { "type": "Polygon", "coordinates": [ [ [ 31.307789, 30.122103 ], [ 31.3063, 30.122913 ], [ 31.30776, 30.123157 ], [ 31.307849, 30.12264 ], [ 31.307789, 30.122103 ] ] ] } },
{ "type": "Feature", "properties": { "station_name_en": "Helmeyet El-Zaitoun", "station_name_ar": "حلمية الزيتون" }, "geometry": { "type": "Polygon", "coordinates": [ [ [ 31.302815, 30.111791 ], [ 31.302031, 30.11224 ], [ 31.303183, 30.111908 ], [ 31.302815, 30.111791 ] ] ] } },
{ "type": "Feature", "properties": { "station_name_en": "Helwan", "station_name_ar": "حلوان" }, "geometry": { "type": "Polygon", "coordinates": [ [ [ 31.333401, 29.847533 ], [ 31.333518, 29.84856 ], [ 31.33383, 29.849118 ], [ 31.33423, 29.849025 ], [ 31.333401, 29.847533 ] ] ] } },
{ "type": "Feature", "properties": { "station_name_en": "Maadi", "station_name_ar": "المعادي" }, "geometry": { "type": "Polygon", "coordinates": [ [ [ 31.25825, 29.959814 ], [ 31.25776, 29.95986 ], [ 31.256977, 29.960391 ], [ 31.256996, 29.961004 ], [ 31.258343, 29.961018 ], [ 31.25825, 29.959814 ] ] ] } },
{ "type": "Feature", "properties": { "station_name_en": "Manshiet El-Sadr", "station_name_ar": "منشية الصدر" }, "geometry": { "type": "Polygon", "coordinates": [ [ [ 31.287036, 30.078534 ], [ 31.286919, 30.07915 ], [ 31.287853, 30.078947 ], [ 31.287036, 30.078534 ] ] ] } },
{ "type": "Feature", "properties": { "station_name_en": "Mar Girgis", "station_name_ar": "مار جرجس" }, "geometry": { "type": "Polygon", "coordinates": [ [ [ 31.229596, 30.005582 ], [ 31.230357, 30.006424 ], [ 31.230863, 30.006943 ], [ 31.229596, 30.005582 ] ] ] } },
{ "type": "Feature", "properties": { "station_name_en": "Mohamed Naguib", "station_name_ar": "محمد نجيب" }, "geometry": { "type": "Polygon", "coordinates": [ [ [ 31.246011, 30.042638 ], [ 31.245937, 30.043448 ], [ 31.246112, 30.043492 ], [ 31.246072, 30.042795 ], [ 31.246011, 30.042638 ] ] ] } },
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