python - DBSCAN 返回部分簇

Question

我正在尝试在这里实现 DBSCAN 的代码:http://en.wikipedia.org/wiki/DBSCAN

我感到困惑的部分是

expandCluster(P, NeighborPts, C, eps, MinPts) 将 P 添加到集群 C 对于 NeighborPts 中的每个点 P' 如果 P' 没有被访问过 将 P' 标记为已访问 NeighborPts' = 区域查询(P', eps) 如果 sizeof(NeighborPts') >= MinPts NeighborPts = NeighborPts 与 NeighborPts' 相连 如果 P' 还不是任何集群的成员 将P'添加到集群C

我的代码如下。照原样，它当前返回部分簇，其中一个点应该是密度连接的，即使它不在紧邻 eps 邻域中。我的代码仅返回每个点的前几个邻居。

import numpy 
import time 
from math import radians, cos, sin, asin, sqrt
import re, math


def haversine(lon1, lat1, lon2, lat2):
    """
    Calculate the great circle distance between two points 
    on the earth (specified in decimal degrees) returned as kilometers 
    """
    # convert decimal degrees to radians 
    lon1, lat1, lon2, lat2 = map(radians, [lon1, lat1, lon2, lat2])
    # haversine formula 
    dlon = lon2 - lon1 
    dlat = lat2 - lat1 
    a = sin(dlat/2)**2 + cos(lat1) * cos(lat2) * sin(dlon/2)**2
    c = 2 * asin(sqrt(a)) 
    km = 6367 * c
    return km



def ST_DBSCAN(points,max_distance,MinPts):
    global visited
    visited = []
    noise = []
    cluster_id = 0
    clusters = []
    in_cluster = []
    for p in points: 
        if p not in visited:
            # neighbor_points = []
            visited.append(p)
            NeighborPts = regionQuery(p,points,max_distance)
            if len(NeighborPts) < MinPts:
                noise.append(p)
            else:
                cluster_id = cluster_id + 1
                g = expandCluster(p,NeighborPts,max_distance,MinPts,in_cluster)
                clusters.append(g)
    return clusters

#return len(NeighborPts)

def expandCluster(p,NeighborPts,max_distance,MinPts,in_cluster):
    in_cluster.append(p[0])
    cluster = []
    cluster.append(p[0])
    for point in NeighborPts:
        if point not in visited:
            visited.append(point)
            new_neighbors = regionQuery(point,points,max_distance)
            if len(new_neighbors) >= MinPts: 
                new_neighbors.append(NeighborPts)
            if point[0] not in in_cluster:
                 in_cluster.append(point[0])
                 cluster.append(point[0])             
    return  cluster




def regionQuery(p,points,max_distance):
    neighbor_points = []
    for j in points:
        if j != p:
           # print 'P is %s and j is %s' % (p[0],j[0])
            dist = haversine(p[1],p[2],j[1],j[2])
            if dist <= max_distance:
                neighbor_points.append(j)
    neighbor_points.append(p) 
    return neighbor_points   

我有下面的一个子集。点 1 和点 5 应相距 10.76 公里，因此它们不应出现在初始查询中，但它们应包含在同一簇中，因为点 5 通过点 3 进行密度连接。

pointList = [[1,36.4686,2.8289], 
[2,36.4706,2.8589], 
[3,36.4726,2.8889],
[4,36.4746,2.9189],
[5,36.4766,2.9489], 
[6,36.4786,2.9789],
[7,36.4806,3.0089], 
[8,36.4826,3.0389], 
[9,36.4846,3.0689], 
[10,36.4866,3.0989]]

points= pointList

g = ST_DBSCAN(points,10,3)

Answer 1

您的 expandCluster 函数忘记了新的邻居。

您的设置更新已交换。