寻找一种快速查找多边形点的方法属于使用Shapely

我有一组~36,000个多边形,代表该国的一个分区(〜县).我的python脚本收到很多点:pointId,经度,纬度.

对于每个点,我想发回pointId,polygonId.对于每个点,循环到所有多边形并使用myPoint.within(myPolygon)是非常低效的.

我认为匀称库提供了一种更好的方法来准备多边形,以便找到一个点的多边形成为树路径(国家,地区,子区域......)

到目前为止,这是我的代码:

import sys
import os
import json
import time
import string
import uuid

py_id = str(uuid.uuid4())

sys.stderr.write(py_id + '\n')
sys.stderr.write('point_in_polygon.py V131130a.\n')
sys.stderr.flush()

from shapely.geometry import Point
from shapely.geometry import Polygon
import sys
import json
import string
import uuid
import time

jsonpath='.\cantons.json'
jsonfile = json.loads(open(jsonpath).read())

def find(id, obj):
    results = []

    def _find_values(id, obj):
        try:
            for key, value in obj.iteritems():
                if key == id:
                    results.append(value)
                elif not isinstance(value, basestring):
                    _find_values(id, value)
        except AttributeError:
            pass

        try:
            for item in obj:
                if not isinstance(item, basestring):
                    _find_values(id, item)
        except TypeError:
            pass

    if not isinstance(obj, basestring):
        _find_values(id, obj)
    return results


#1-Load polygons from json  
r=find('rings',jsonfile)
len_r = len(r)

#2-Load attributes from json
a=find('attributes',jsonfile)

def insidePolygon(point,json):
        x=0
    while x < len_r :
            y=0
            while y < len(r[x]) :
        p=Polygon(r[x][y])
        if(point.within(p)):
            return a[y]['OBJECTID'],a[y]['NAME_5']
        y=y+1
        x=x+1
    return None,None


while True:
    line = sys.stdin.readline()
    if not line:
        break
    try:
        args, tobedropped = string.split(line, "\n", 2)

        #input: vehicleId, longitude, latitude
        vehicleId, longitude, latitude = string.split(args, "\t")

        point = Point(float(longitude), float(latitude))
        cantonId,cantonName = insidePolygon(point,r)

        #output: vehicleId, cantonId, cantonName
        # vehicleId will be 0 if not found
        # vehicleId will be < 0 in case of an exception
        if (cantonId == None):
            print "\t".join(["0", "", ""])
        else:
            print "\t".join([str(vehicleId), str(cantonId), str(cantonName)])

    except ValueError:
        print "\t".join(["-1", "", ""])
        sys.stderr.write(py_id + '\n')
        sys.stderr.write('ValueError in Python script\n')
        sys.stderr.write(line)
        sys.stderr.flush()
    except:
        sys.stderr.write(py_id + '\n')
        sys.stderr.write('Exception in Python script\n')
        sys.stderr.write(str(sys.exc_info()[0]) + '\n')
        sys.stderr.flush()
        print "\t".join(["-2", "", ""])

Mike T.. 6

使用Rtree(示例)作为R树索引:(1)索引36k多边形的边界(在读取jsonfile之后执行此操作),然后(2)非常快速地找到每个多边形的交叉边界框到您感兴趣的点.然后,(3)对于来自Rtree的交叉边界框,使用形状来使用,例如point.within(p)进行实际的多边形点分析.你应该看到这种技术有很大的性能提升.