geo-l1-cairo-multipoint-hull

Status: done
Score: 1.000
Duration: 1:14
Cost: 0.27¢
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.
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System info
{
  "adapter": "openrouter",
  "model": "google/gemma-4-26b-a4b-it",
  "base_url": "https://openrouter.ai/api/v1"
}
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Bash ls -F
cairo_metro_stations.geojson
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Write /work/inspect_data.py
content · 9 lines · py
import geopandas as gpd

# Read the input file
gdf = gpd.read_file('cairo_metro_stations.geojson')

# Inspect the first few rows to understand the structure
print(gdf.head())
print(gdf.columns)
Wrote /work/inspect_data.py (194 chars).
0:08
Bash python /work/inspect_data.py
    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]
Index(['station_name_en', 'station_name_ar', 'geometry'], dtype='str')
0:27
Write /work/solve.py
content · 43 lines · py
import geopandas as gpd

def compute_hulls(input_file, output_file):
    # Load the stations GeoDataFrame
    gdf = gpd.read_file(input_file)
    
    # Ensure we are working with a copy to avoid warnings
    hulls_gdf = gdf.copy()
    
    # Compute the convex hull for each geometry
    # Note: convex_hull returns a Polygon or MultiPolygon
    hulls_gdf['geometry'] = gdf['geometry'].convex_hull
    
    # We need to filter for stations where the hull is actually a Polygon 
    # (convex_hull of a single point is a Point, of a line is a LineString)
    # However, the instructions say "one Polygon per station". 
    # Usually, entrances are multiple points.
    # If a station has only 1 entrance or 2 (forming a line), convex_hull 
    # might return a Point or LineString. 
    # Let's check if the requirement implies we only keep Polygons or if we should just compute it.
    # "compute the convex hull of each station's entrances" 
    # Typically, if it's a line/point, it's not a 'box'. 
    # But let's just apply it first.
    
    # The instruction says: "Every row must carry station_name_en and station_name_ar, 
    # both non-empty, with the original Arabic strings and diacritics preserved exactly".
    
    # Filter out rows where station names are empty (if any)
    # Based on the description, we should keep the columns and make sure they are non-empty.
    # Let's assume the input might have empty strings or NaNs.
    hulls_gdf = hulls_gdf[hulls_gdf['station_name_en'].notna() & (hulls_gdf['station_name_en'] != '')]
    hulls_gdf = hulls_gdf[hulls_gdf['station_name_ar'].notna() & (hulls_gdf['station_name_ar'] != '')]

    # Keep only the required columns
    hulls_gdf = hulls_gdf[['station_name_en', 'station_name_ar', 'geometry']]
    
    # Save the result
    hulls_gdf.to_file(output_file, driver='GeoJSON')
    print(f"Successfully saved hulls to {output_file}")

if __name__ == "__main__":
    compute_hulls('cairo_metro_stations.geojson', 'cairo_metro_hulls.geojson')
Wrote /work/solve.py (2009 chars).
0:29
Bash python /work/solve.py
Successfully saved hulls to cairo_metro_hulls.geojson
0:45
Write /work/verify.py
content · 22 lines · py
import geopandas as gpd

# Read the results
gdf_result = gpd.read_file('cairo_metro_hulls.geojson')

print("Summary of geometry types:")
print(gdf_result.geometry.type.value_counts())

print("\nFirst few rows:")
print(gdf_result.head())

# Check if station_name_en and station_name_ar are indeed present and non-empty
print("\nChecking for empty/null names:")
print(f"Null station_name_en: {gdf_result['station_name_en'].isna().sum()}")
print(f"Empty station_name_en: {(gdf_result['station_name_en'] == '').sum()}")
print(f"Null station_name_ar: {gdf_result['station_name_ar'].isna().sum()}")
print(f"Empty station_name_ar: {(gdf_result['station_name_ar'] == '').sum()}")

# Check Arabic characters (should be preserved)
# If we see them correctly in print, it's a good sign, though terminal might differ.
# We'll look at the raw content of the file later if needed.
Wrote /work/verify.py (867 chars).
0:46
Bash python /work/verify.py
Summary of geometry types:
Polygon    20
Name: count, dtype: int64

First few rows:
    station_name_en  ...                                           geometry
0       Al-Shohadaa  ...  POLYGON ((31.24774 30.06154, 31.24678 30.06243...
1            Attaba  ...  POLYGON ((31.2462 30.05151, 31.2464 30.05185, ...
2  Cairo University  ...  POLYGON ((31.20146 30.02515, 31.20022 30.02526...
3             Dokki  ...  POLYGON ((31.21341 30.03758, 31.21193 30.03845...
4      El Demerdash  ...  POLYGON ((31.27382 30.07892, 31.27273 30.0791,...

[5 rows x 3 columns]

Checking for empty/null names:
Null station_name_en: 0
Empty station_name_en: 0
Null station_name_ar: 0
Empty station_name_ar: 0
0:49
Bash 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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Bash rm /work/inspect_data.py /work/solve.py /work/verify.py
(no output)
1:13