Run 4a0b7258

# attempt undefined — model: @cf/zai-org/glm-4.7-flash — exit 0 — rejected — cost 0.00192 — 37812ms
# verifier: FAIL — verifier did not emit JSON; stdout tail: 
# no artifact produced

# attempt undefined — model: @cf/zai-org/glm-4.7-flash — exit 0 — rejected — cost 0.00159 — 50853ms
# verifier: FAIL — output not in WGS84 Munich coords
# artifact: download (582 bytes)
import geopandas as gpd

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

# Diagnosis: Determine the CRS based on coordinate magnitude.
# Large coordinates (millions) indicate a projected CRS.
# Web Mercator (EPSG:3857) covers approximately -20,000,000 to 20,000,000.
if gdf.crs is None:
    # Check if any coordinate is in the millions
    if (gdf['geometry'].x.abs() > 1_000_000).any():
        gdf.crs = 'EPSG:3857'

# Reproject to WGS84 (EPSG:4326)
gdf_wgs84 = gdf.to_crs(epsg=4326)

# Write the output
gdf_wgs84.to_file('output.geojson', driver='GeoJSON')

# attempt undefined — model: @cf/zai-org/glm-4.7-flash — exit 0 — rejected — cost 0.00210 — 80983ms
# verifier: FAIL — verifier did not emit JSON; stdout tail: 
# no artifact produced

# attempt undefined — model: @cf/zai-org/glm-4.7-flash — exit 0 — rejected — cost 0.00190 — 49096ms
# verifier: FAIL — stats.json unreadable
# no artifact produced

# attempt undefined — model: @cf/zai-org/glm-4.7-flash — exit 0 — rejected — cost 0.00190 — 38163ms
# verifier: FAIL — stats.json unreadable
# no artifact produced

# attempt undefined — model: @cf/zai-org/glm-4.7-flash — exit 0 — rejected — cost 0.00192 — 79605ms
# verifier: FAIL — stats.json unreadable
# no artifact produced

# attempt undefined — model: @cf/zai-org/glm-4.7-flash — exit 0 — accepted — cost 0.00127 — 27210ms
# verifier: PASS — 1000m buffers verified
# artifact: download (5935 bytes)
import geopandas as gpd

gdf = gpd.read_file("sites.geojson")
gdf_projected = gdf.to_crs(epsg=3857)
gdf_projected['geometry'] = gdf_projected.buffer(1000)
gdf_final = gdf_projected.to_crs(epsg=4326)
gdf_final.to_file("buffers.geojson", driver="GeoJSON")

# attempt undefined — model: @cf/zai-org/glm-4.7-flash — exit 0 — accepted — cost 0.00150 — 49203ms
# verifier: PASS — 1000m buffers verified
# artifact: download (5903 bytes)
import geopandas as gpd
from pyproj import CRS

# Read the input file
gdf = gpd.read_file("sites.geojson")

# Reproject to a projected CRS (EPSG:3857) to ensure 1000m is calculated correctly
gdf_projected = gdf.to_crs("EPSG:3857")

# Create 1000 metre buffers
gdf_projected['buffer'] = gdf_projected.geometry.buffer(1000)

# Extract the buffer geometries and reproject back to WGS84 (EPSG:4326)
buffers = gdf_projected[['buffer']].copy()
buffers = buffers.set_geometry('buffer')
buffers = buffers.to_crs("EPSG:4326")

# Write the result to the output file
buffers.to_file("buffers.geojson", driver="GeoJSON")

# attempt undefined — model: @cf/moonshotai/kimi-k2.6 — exit 0 — rejected — cost 0.00192 — 47932ms
# verifier: FAIL — verifier did not emit JSON; stdout tail: 
# no artifact produced

# attempt undefined — model: @cf/moonshotai/kimi-k2.6 — exit 1 — rejected — cost 0.00192 — 41471ms
# verifier: FAIL — verifier did not emit JSON; stdout tail: 
# no artifact produced
import geopandas as gpd
from pyproj import CRS

gdf = gpd.read_file('input.geojson')
source_crs = CRS.from_epsg(3857)
target_crs = CRS.from_epsg(4326)
gdf = gdf.set_crs(source

--- stderr ---
  File "/tmp/arena/solution.py", line 7
    gdf = gdf.set_crs(source
                     ^
SyntaxError: '(' was never closed

# attempt undefined — model: @cf/moonshotai/kimi-k2.6 — exit 0 — accepted — cost 0.00142 — 70451ms
# verifier: PASS — CRS reproject to WGS84 verified
# artifact: download (591 bytes)
import geopandas as gpd
from pyproj import CRS

gdf = gpd.read_file('input.geojson')
source_crs = CRS.from_epsg(3857)
target_crs = CRS.from_epsg(4326)
gdf = gdf.set_crs(source_crs, allow_override=True)
gdf = gdf.to_crs(target_crs)
gdf.to_file('output.geojson', driver='GeoJSON')

# attempt undefined — model: @cf/moonshotai/kimi-k2.6 — exit 0 — rejected — cost 0.00190 — 49410ms
# verifier: FAIL — stats.json unreadable
# no artifact produced

# attempt undefined — model: @cf/moonshotai/kimi-k2.6 — exit 0 — rejected — cost 0.00190 — 41332ms
# verifier: FAIL — stats.json unreadable
# no artifact produced

# attempt undefined — model: @cf/moonshotai/kimi-k2.6 — exit 0 — accepted — cost 0.00163 — 77379ms
# verifier: PASS — zonal mean verified by independent recompute
# artifact: download (14 bytes)
import json
import numpy as np
import rasterio
import rasterio.mask

with open("zone.geojson") as f:
    geojson = json.load(f)

if geojson["type"] == "FeatureCollection":
    geometry = geojson["features"][0]["geometry"]
elif geojson["type"] == "Feature":
    geometry = geojson["geometry"]
else:
    geometry = geojson

with rasterio.open("grid.asc") as src:
    nodata = src.nodata
    out_image, _ = rasterio.mask.mask(src, [geometry], crop=True)
    band = out_image[0]

    valid_mask = np.ones(band.shape, dtype=bool)
    if nodata is not None:
        valid_mask &= band != nodata
    valid_mask &= ~np.isnan(band)

    valid_pixels = band[valid_mask]
    mean_value = float(np.mean(valid_pixels)) if valid_pixels.size > 0 else None

with open("stats.json", "w") as f:
    json.dump({"mean": mean_value}, f)

# attempt undefined — model: @cf/moonshotai/kimi-k2.6 — exit 0 — rejected — cost 0.00194 — 48695ms
# verifier: FAIL — verifier did not emit JSON; stdout tail: 
# no artifact produced
import geopandas as gpd

gdf = gpd.read_file('sites.geojson')
gdf = gdf.set_crs(epsg=4326, allow_override=True)
gdf = gdf

# attempt undefined — model: @cf/moonshotai/kimi-k2.6 — exit 0 — accepted — cost 0.00134 — 31421ms
# verifier: PASS — 1000m buffers verified
# artifact: download (5935 bytes)
import geopandas as gpd

gdf = gpd.read_file('sites.geojson')
if gdf.crs is None:
    gdf.set_crs(epsg=4326, inplace=True)
gdf = gdf.to_crs(epsg=3857)
gdf.geometry = gdf.buffer(1000)
gdf = gdf.to_crs(epsg=4326)
gdf.to_file('buffers.geojson', driver='GeoJSON')