点概括

# coding:utf-8
import numpy as np
import geopandas as gpd
from shapely.geometry import Point, LineString
from scipy import spatial


class pointAbstract():

    def __init__(self, pnts, method="keep", near=150):
        # 空间点概括
        # 将near范围内的点聚合成 1 个
        # pnts:[[lng,lat], ……]

        self.pnts = pnts
        self.method = method
        self.near = near

    def step(self):
        pps = [Point(_) for _ in self.pnts]
        gps = gpd.GeoDataFrame({"geometry": pps}, crs=4326)
        gps_ = gps.to_crs(4527)
        gps_["cds"] = gps_.geometry.apply(lambda x: (np.array(x)[0], np.array(x)[1]))
        pps_ = gps_.cds.values.tolist()
        dm = spatial.distance.cdist(pps_, pps_, metric='euclidean')
        tu = np.triu(dm, k=1)
        td = np.tril(np.ones_like(dm), k=0)
        tx = tu - td
        idx, idy = np.where((tx > -1) & (tx < self.near))
        mark = [[x, y] for x, y in zip(idx, idy)]  # 需要处理的 点对

        _mark = set(list(range(len(self.pnts)))) - set(sum(mark, []))
        if self.method == "keep":
            keep = [np.random.choice(_) for _ in mark]
            print(keep)
            keep.extend(_mark)
            res = [self.pnts[_] for _ in set(keep)]

        elif self.method == "move":
            res = [self.pnts[_] for _ in _mark]
            nps = [[(self.pnts[i][0] + self.pnts[j][0]) / 2, (self.pnts[i][1] + self.pnts[j][1]) / 2] for i, j in mark]
            res = res + nps

        return res

    def ptsAbstract(self, maxiter=300):

        count = 0
        while 1:
            N = len(self.pnts)
            self.pnts = self.step()
            M = len(self.pnts)

            count = count+1 if count