有没有办法优化shapely.geometry.shape.contains(a_point)调用的速度? [英] Is there way to optimize speed of shapely.geometry.shape.contains(a_point) call?

问题描述

我们正在使用 shapely 库来检查存储在某些禁区中的随机点是否存在形状文件.

We are using a shapely library to check that some random point is not in some prohibited areas stored in a shape file.

with fiona.open(path) as source:
    geometry = get_exclusive_item(source[0])
geom = shapely.geometry.shape(geometry['geometry'])

def check(lat, lng):
    point = shapely.geometry.Point(lng, lat)
    return not geom.contains(point)  

但是最近的通话geom.contains(point)大约需要一秒钟才能完成.还有其他适用于python的更快的库，还是我们可以通过某种方式优化形状文件以获得更快的速度?

But the latest call geom.contains(point) takes about a second to complete. Is there any other faster libraries for python, or could we optimize a shape files somehow to get better speed?

推荐答案

感谢@iant点使用空间索引.

Thank for the @iant point to use a spatial indexes.

我的shapefile是一个具有很多点的MultiPoligon，这使得.contains()真的很慢.

My shapefile was a single MultiPoligon with a lot of points, makes .contains() are really slow.

我通过将其分成较小的形状并使用Rtree索引解决了该问题.

I solved the issue by splitting it into smaller shapes and use Rtree index.

1. 要分割shapefile，我使用了QGIS，如此处所述- https://gis.stackexchange.com/a/23694/65569

此处介绍如何在python中使用RTree的核心思想- https://gis.stackexchange.com/a/144764/65569

The core idea how to use RTree in python is here - https://gis.stackexchange.com/a/144764/65569

总共使我对.contains()查找的速度提高了1000倍！

In total this gaves me 1000x speed-up for .contains() lookups!

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