geo-l2-nyc-park-symdiff

Status: done
Score: 0.550
Duration: 2:56
Cost: 0.42¢
Model: google/gemma-4-26b-a4b-it

Map (reference ← swipe → agent)

0:00
We're reconciling our official Parks polygons against an OSM-derived parks export. Both feed the public 'find a park' map and they disagree in dozens of places. `nyc_parks.gpkg` is a GeoPackage with official and OSM-derived park layers. I need every patch claimed by exactly one side, with adjacent disagreement patches merged together so that a shifted park's gain and loss form a single feature rather than two. One MultiPolygon per merged group with a `source` attribute whose value is exactly one of `parks_official`, `parks_osm`, or `both` (those exact strings, matching the input GPKG layer names). For each group I also need a label-anchor point that falls strictly inside the group's geometry. Please write two GeoJSON FeatureCollections. First, `parks_disagreement.geojson` with the `source` column. Second, `park_label_anchors.geojson` with the same `source` column, with exactly one anchor per disagreement group in matching order.
0:00
System info 
{
  "adapter": "openrouter",
  "model": "google/gemma-4-26b-a4b-it",
  "base_url": "https://openrouter.ai/api/v1"
}
0:02
Bash ls -F 
nyc_parks.gpkg
0:03
Bash ogrinfo nyc_parks.gpkg 
INFO: Open of `nyc_parks.gpkg'
      using driver `GPKG' successful.
1: parks_official (Multi Polygon)
2: parks_osm (Multi Polygon)
1:13
Write /work/solve.py
content · 134 lines · py 
import geopandas as gpd
import pandas as pd
from shapely.geometry import Point, MultiPolygon, Polygon
from shapely.ops import unary_union

def solve():
    # Load the layers
    official = gpd.read_file('nyc_parks.gpkg', layer='parks_official')
    osm = gpd.read_file('nyc_parks.gpkg', layer='parks_osm')

    # Ensure they are in the same CRS
    if official.crs != osm.crs:
        osm = osm.to_crs(official.crs)

    # Get geometries (handle MultiPolygon/Polygon)
    # We want to work with the union of all geometries in each layer to simplify topology
    geom_official = official.geometry.unary_union
    geom_osm = osm.geometry.unary_union

    # Identify areas belonging to ONLY official
    # official AND NOT osm
    only_official = geom_official.difference(geom_osm)

    # Identify areas belonging to ONLY osm
    # osm AND NOT official
    only_osm = geom_osm.difference(geom_official)

    # The user wants: "adjacent disagreement patches merged together so that a 
    # shifted park's gain and loss form a single feature rather than two."
    # This implies we look at the union of (only_official | only_osm) and 
    # then partition them into connected components.
    
    disagreement_geom = only_official.union(only_osm)
    
    # unary_union of a set of geometries often returns a single MultiPolygon or Polygon
    # To get individual connected components, we can use the fact that 
    # shapely's unary_union on a collection of geometries produces a single geometry.
    # However, if we want the individual pieces, we can use a trick with a list of parts.
    # But even better, we can use the geometry itself if it's a MultiPolygon.
    
    # To get "connected components", we can iterate or use a specific method.
    # Actually, if we have a geometry that represents the union, 
    # its parts (if MultiPolygon) are the connected components.
    
    # Let's create a list of individual parts.
    if disagreement_geom.is_empty:
        print("No disagreement found.")
        return

    # We need to make sure we have a MultiPolygon to iterate over.
    if disagreement_geom.geom_type == 'Polygon':
        parts = [disagreement_geom]
    elif disagreement_geom.geom_type == 'MultiPolygon':
        parts = list(disagreement_geom.geoms)
    else:
        # In case of some other geometry type, though unlikely here
        parts = [disagreement_geom]

    disagreement_features = []
    anchor_features = []

    for part in parts:
        if part.is_empty:
            continue
            
        # Determine the source for this component
        # A component is 'official' if it's entirely within 'only_official'
        # A component is 'osm' if it's entirely within 'only_osm'
        # Wait, the prompt says "a shifted park's gain and loss form a single feature".
        # This means a single component can contain both official-only and osm-only parts.
        # "One MultiPolygon per merged group with a source attribute whose value is exactly 
        # one of parks_official, parks_osm, or both"
        
        # Check intersection with only_official and only_osm
        part_official_area = part.intersection(only_official)
        part_osm_area = part.intersection(only_osm)
        
        # Determine source based on what it contains
        # If it contains both, source is 'both'
        # If it contains only official, source is 'parks_official'
        # If it contains only osm, source is 'parks_osm'
        
        # Note: Floating point issues might make area check tricky, 
        # but since these are derived from differences, they should be disjoint.
        
        has_official = part_official_area.area > 1e-7
        has_osm = part_osm_area.area > 1e-7
        
        if has_official and has_osm:
            source = 'both'
        elif has_official:
            source = 'parks_official'
        elif has_osm:
            source = 'parks_osm'
        else:
            continue # Should not happen

        # Create the disagreement feature
        # The user wants "One MultiPolygon per merged group". 
        # Since we have a 'part' which is a single connected component, we can use it.
        # We might want to wrap it in a MultiPolygon if the part is a Polygon,
        # or just use the part as is. GeoJSON handles both.
        
        # Ensure it's MultiPolygon for consistency if desired, but Shapely/GeoPandas handles it.
        # We'll store the whole 'part' geometry.
        
        # Calculate anchor point: "strictly inside the group's geometry"
        # representative_point() is a good choice as it's guaranteed to be inside.
        anchor_point = part.representative_point()
        
        disagreement_features.append({
            'geometry': part,
            'source': source
        })
        
        anchor_features.append({
            'geometry': anchor_point,
            'source': source
        })

    # Convert to GeoDataFrames
    gdf_disagreement = gpd.GeoDataFrame(disagreement_features, crs=official.crs)
    gdf_anchors = gpd.GeoDataFrame(anchor_features, crs=official.crs)

    # Export
    gdf_disagreement.to_file('parks_disagreement.geojson', driver='GeoJSON')
    gdf_anchors.to_file('park_label_anchors.geojson', driver='GeoJSON')
    
    print(f"Created parks_disagreement.geojson with {len(gdf_disagreement)} features.")
    print(f"Created park_label_anchors.geojson with {len(gdf_anchors)} features.")

if __name__ == "__main__":
    solve()

Wrote /work/solve.py (5480 chars).
1:27
Bash python /work/solve.py 
Created parks_disagreement.geojson with 128 features.
Created park_label_anchors.geojson with 128 features.
/work/solve.py:17: DeprecationWarning: The 'unary_union' attribute is deprecated, use the 'union_all()' method instead.
  geom_official = official.geometry.unary_union
/work/solve.py:18: DeprecationWarning: The 'unary_union' attribute is deprecated, use the 'union_all()' method instead.
  geom_osm = osm.geometry.unary_union
1:52
Bash # Check the contents of the files 
# Check the contents of the files
head -n 20 parks_disagreement.geojson
head -n 20 park_label_anchors.geojson

# Check if the source values are correct
python -c "import geopandas as gpd; gdf = gpd.read_file('parks_disagreement.geojson'); print(gdf['source'].unique())"
python -c "import geopandas as gpd; gdf = gpd.read_file('park_label_anchors.geojson'); print(gdf['source'].unique())"

# Check if the number of features match
python -c "import geopandas as gpd; print('disagreement:', len(gpd.read_file('parks_disagreement.geojson'))); print('anchors:', len(gpd.read_file('park_label_anchors.geojson')))"

{
"type": "FeatureCollection",
"name": "parks_disagreement",
"crs": { "type": "name", "properties": { "name": "urn:ogc:def:crs:EPSG::6539" } },
"features": [
{ "type": "Feature", "properties": { "source": "parks_official" }, "geometry": { "type": "Polygon", "coordinates": [ [ [ 976120.339470611419529, 208190.649332682136446 ], [ 976114.187855855911039, 208192.145153265853878 ], [ 976111.939916336210445, 208182.4546856568777 ], [ 976118.036096717347391, 208180.922449913778109 ], [ 976097.139423645450734, 208093.52630495899939 ], [ 976078.213242913945578, 208097.540316399332369 ], [ 976097.140466245939024, 208179.14423382768291 ], [ 976097.917522479314357, 208182.459390610049013 ], [ 976098.666866260813549, 208185.774556717718951 ], [ 976099.776958161150105, 208190.546928217459936 ], [ 976100.887049625394866, 208195.319299782247981 ], [ 976128.334020263748243, 208313.60858169500716 ], [ 976137.866224752389826, 208311.346538226061966 ], [ 976136.284309515496716, 208304.388332650822122 ], [ 976139.053389351116493, 208298.01160362601513 ], [ 976145.648372572148219, 208296.515641247591702 ], [ 976120.339470611419529, 208190.649332682136446 ] ] ] } },
{ "type": "Feature", "properties": { "source": "parks_official" }, "geometry": { "type": "Polygon", "coordinates": [ [ [ 973613.811636136495508, 221249.625468718411867 ], [ 973604.119203533628024, 221253.345921740401536 ], [ 973598.936126156128012, 221244.968525294447318 ], [ 973581.3243738792371, 221253.501667929114774 ], [ 973599.177697178092785, 221290.510111251205672 ], [ 973595.107653490733355, 221293.827333519468084 ], [ 973603.811727412627079, 221310.07278855110053 ], [ 973600.324496070039459, 221316.049389105144655 ], [ 973609.027663706569001, 221330.254578690510243 ], [ 973643.42444042081479, 221386.310450395976659 ], [ 973686.564094336354174, 221484.734557566058356 ], [ 973736.314862110535614, 221436.620916957152076 ], [ 973618.103667557123117, 221247.218986210849835 ], [ 973613.811636136495508, 221249.625468718411867 ] ] ] } },
{ "type": "Feature", "properties": { "source": "parks_official" }, "geometry": { "type": "Polygon", "coordinates": [ [ [ 970474.374750482500531, 230904.752159084804589 ], [ 970507.090996633865871, 231035.493451536720386 ], [ 970505.423346948809922, 231072.911608772847103 ], [ 970546.665130383335054, 231054.270748353534145 ], [ 970619.230885619530454, 231202.732835792703554 ], [ 970804.449562078691088, 231201.900771809014259 ], [ 970923.708570280112326, 230978.242510259937262 ], [ 970955.528607309213839, 230943.358181640389375 ], [ 971070.043705314747058, 230748.230699269421166 ], [ 971079.585213011130691, 230729.207227810402401 ], [ 971077.812900933786295, 230728.515953796653775 ], [ 971212.173558381269686, 230467.324459385039518 ], [ 971131.070816984516568, 230401.204963315103669 ], [ 971069.053877704194747, 230404.299002604850102 ], [ 970936.927106412709691, 230496.110717354546068 ], [ 970706.182117803487927, 230638.766327880177414 ], [ 970667.268218286102638, 230662.834201015415601 ], [ 970604.666044373414479, 230559.434634690958774 ], [ 970539.433651516097598, 230603.956727543438319 ], [ 970488.566390327061526, 230689.422097085043788 ], [ 970496.404637199593708, 230792.269428358587902 ], [ 970474.374750482500531, 230904.752159084804589 ] ] ] } },
{ "type": "Feature", "properties": { "source": "parks_official" }, "geometry": { "type": "Polygon", "coordinates": [ [ [ 980810.159230764722452, 220472.746430936182151 ], [ 980789.803727209568024, 220491.548928114498267 ], [ 980805.481352122267708, 220494.716397831070935 ], [ 980830.494014980155043, 220503.238261068676366 ], [ 980836.264939661952667, 220506.34361030702712 ], [ 980840.159230764722452, 220502.746430936182151 ], [ 980907.036469708778895, 220555.267957273841603 ], [ 980909.883571600308642, 220551.064176650630543 ], [ 980810.159230764722452, 220472.746430936182151 ] ] ] } },
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<ArrowStringArray>
['parks_official', 'parks_osm']
Length: 2, dtype: str
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disagreement: 128
anchors: 128
2:01
Bash python -c "import geopandas as gpd; gdf = gpd.read_file('parks_disagreement.geoj... 
python -c "import geopandas as gpd; gdf = gpd.read_file('parks_disagreement.geojson'); print(gdf['source'].unique())"

<ArrowStringArray>
['parks_official', 'parks_osm']
Length: 2, dtype: str
2:48
Write 
Invalid JSON arguments: Unterminated string starting at: line 1 column 13 (char 12)