Geopandas sjoin统计多边形内点缺失4个的原因排查（AoC Day10）

There are several common reasons why your GeoPandas sjoin result is 4 points short of the correct count (491 vs 495). Here are the most likely culprits and how to debug them:

1. Boundary Point Exclusion #

GeoPandas relies on Shapely for spatial calculations. If you’re using predicate='within' in sjoin, points lying exactly on the polygon’s boundary are not counted—since within requires strict inclusion inside the polygon.

Your reference code might use a different point-in-polygon logic that either:

• Accidentally counts boundary points as interior, or
• Uses a polygon where those 4 points fall strictly inside (not on the edge).

Debug steps:

• Isolate the 4 missing points from your dataset.
• Use Shapely’s point.within(polygon) and point.touches(polygon) to check if they lie on the polygon boundary.

2. Incorrect Polygon Construction #

Advent of Code Day 10’s pipe loop needs precise polygon creation to accurately represent enclosed areas. Common mistakes here include:

• No coordinate offset: The pipe runs along grid lines between cells. If you build the polygon using integer grid positions instead of shifting to cell edges (e.g., adding 0.5 to coordinates), the polygon will cut through cell centers, leaving some points on the boundary.
• Unclosed loop: If your pipe loop doesn’t connect start and end points properly, the polygon will have gaps, excluding points near the break.
• Invalid geometry: Self-intersections or malformed edges in the polygon can make Shapely misinterpret the interior area.

Debug steps:

• Check if your polygon is valid with polygon.is_valid (from Shapely).
• Compare your polygon’s coordinates to the reference code’s polygon (if possible) to spot offsets or missing segments.
• Visualize the polygon alongside the 4 missing points to see if they’re near a gap or edge.

3. Floating Point Precision Errors #

Minor rounding differences between polygon and point coordinates can misclassify points. For example, a point that should be inside might be calculated as lying on the boundary due to precision gaps.

Debug steps:

• Round all coordinates to a consistent decimal place (e.g., 6 digits) before running the spatial join.
• Fix minor geometry issues with Shapely’s buffer(0): fixed_polygon = polygon.buffer(0)

4. Mismatched Spatial Join Predicate #

Double-check the predicate used in sjoin. If your reference code counts points intersecting the polygon (including boundary) but you’re using 'within', you’ll miss boundary points. Conversely, using 'intersects' when you need strictly interior points will count extra points.

Fix:

• For AoC Day10 Part2, you want strictly enclosed points, so use predicate='within'—but only if your polygon is constructed to exclude pipe cells entirely.

Start by visualizing the 4 missing points relative to your polygon. If they’re on the boundary, adjust your polygon construction to shift edges away from cell centers. If they’re near a gap, fix your loop closure or polygon creation logic.

内容的提问来源于stack exchange，提问作者Scott Boston