spatial-filtering
Methods for filtering GeoDataFrames based on spatial relationships like containment and intersection.
- License 许可
- MIT
- 最近更新
- 2026-10-02
- Stars
- ★ 92
- Forks
- 7
01 前言 Front Matter
- name
- spatial-filtering
- description
- Methods for filtering GeoDataFrames based on spatial relationships like containment and intersection.
03 SKILL.md 正文
Spatial Filtering
Overview
Spatial filtering allows you to select features based on their location relative to other features.
Point-in-Polygon
To find points that lie inside a specific polygon:
# Assuming gdf_points and gdf_polygons are GeoDataFrames
# 1. Get a specific polygon geometry
pacific_poly = gdf_polygons[gdf_polygons['Code'] == 'PA'].geometry.unary_union
# 2. Filter points
points_in_pacific = gdf_points[gdf_points.within(pacific_poly)]
Spatial Joins
Alternatively, use sjoin for batch processing:
joined = gpd.sjoin(gdf_points, gdf_polygons, predicate='within')
Attribute-based Spatial Selection
Often you need to combine attribute filters with spatial operations:
# Find boundaries associated with the Pacific plate (PA)
pacific_boundaries = gdf_boundaries[
(gdf_boundaries['PlateA'] == 'PA') | (gdf_boundaries['PlateB'] == 'PA')
]
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invoke this skill when you need to perform database search for travel planning. This skill provides some useful pre-packaged tools to look up accommodations, attractions, cities, driving distance, flights, and restaurants from the bundled dataset.
glm-output
Output-processing guidance for GLM tasks. Especially useful after glm-basics and glm-calibration when you need verifier-matching metrics from output.nc and a final /root/metrics.json.
glm-calibration
Calibration guidance for GLM tasks. Often most effective after glm-basics has clarified the setup; glm-output is the companion skill for exact final metric computation.
glm-basics
A good starting point for GLM calibration tasks. Use to inspect glm3.nml, confirm how GLM runs, and identify the relevant files before moving on to calibration and output evaluation.