61 lines
No EOL
2.5 KiB
Python
61 lines
No EOL
2.5 KiB
Python
import json
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import click
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import pygeohash as pgh
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import pyarrow.parquet as pq
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import geopandas as gpd
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from shapely.geometry import Point, LineString, MultiLineString
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from pyproj import Geod
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import numpy as np
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@click.command()
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@click.argument("latitude", type=float)
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@click.argument("longitude", type=float)
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@click.option("--distance", type=float, default=10, help="Distance threshold in meters for nearby lines.")
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@click.option("--parquet-dir", type=str, default="geohash", help="Directory containing geohash Parquet files.")
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def geohash_lookup(latitude, longitude, distance, parquet_dir):
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"""
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Finds polygons containing the given point and lines within a threshold (in meters).
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"""
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# Compute geohash (precision can be adjusted)
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geohash = pgh.encode(latitude, longitude, precision=4) # Adjust precision as needed
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parquet_file = f"{parquet_dir}/{geohash}.parquet"
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try:
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# Load the Parquet file directly into a GeoDataFrame
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df = gpd.read_parquet(parquet_file)
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except FileNotFoundError:
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click.echo(json.dumps({"error": f"No Parquet file found for geohash {geohash}."}))
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return
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point = Point(longitude, latitude)
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geod = Geod(ellps="WGS84") # Accurate geodetic distance calculations
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found_geometries = []
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# Vectorized distance calculation for LineStrings and MultiLineStrings
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def calculate_min_distance(geom):
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if isinstance(geom, LineString):
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return min(geod.inv(point.x, point.y, p[0], p[1])[2] for p in geom.coords)
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elif isinstance(geom, MultiLineString):
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return min(min(geod.inv(point.x, point.y, p[0], p[1])[2] for p in line.coords) for line in geom.geoms)
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return np.inf
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for row in df.itertuples(index=False):
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geom = row.geometry # Directly use the Shapely geometry object
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metadata = {}
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if isinstance(row.tags, dict):
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metadata = {k: v for k, v in row.tags.items() if v is not None} # Remove empty values
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if geom.contains(point):
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found_geometries.append({"type": "polygon", **metadata})
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elif isinstance(geom, (LineString, MultiLineString)):
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min_distance = calculate_min_distance(geom)
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if min_distance <= distance:
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found_geometries.append({"type": "line" if isinstance(geom, LineString) else "multi_line", **metadata})
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# Output JSON result
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click.echo(json.dumps(found_geometries, indent=2, ensure_ascii=False)) # Ensure proper Unicode display
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if __name__ == "__main__":
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geohash_lookup() |