leaflet获取聚类结果，{"y":115.9057200,"x":29.1660800,"label":0},格式的json文件，写dbscan函数遍历聚类结果，在地图上绘制聚类点。

以下是一个简单的dbscan函数，可以遍历聚类结果并在地图上绘制聚类点。请注意，这个函数假定聚类结果已经按照标签排好序了。

import folium

def dbscan(cluster_results, eps, min_pts, color_map):
    """
    :param cluster_results: 聚类结果，格式为 [{"y":115.9057200,"x":29.1660800,"label":0}, ...]
    :param eps: DBSCAN算法中的半径参数
    :param min_pts: DBSCAN算法中的最小点数参数
    :param color_map: 标签和颜色的映射关系，格式为 {0: 'red', 1: 'blue', ...}
    """
    # 初始化地图
    map_center = [cluster_results[0]['y'], cluster_results[0]['x']]
    m = folium.Map(location=map_center, zoom_start=10)

    # 初始化聚类器
    clusters = {}
    for point in cluster_results:
        label = point['label']
        if label not in clusters:
            clusters[label] = []
        clusters[label].append((point['y'], point['x']))

    # 遍历聚类结果并在地图上绘制聚类点
    for label, points in clusters.items():
        color = color_map[label]
        for point in points:
            folium.CircleMarker(
                location=point,
                radius=5,
                color=color,
                fill=True,
                fill_color=color
            ).add_to(m)

    return m

使用示例：

cluster_results = [
    {"y": 115.9057200, "x": 29.1660800, "label": 0},
    {"y": 115.9057200, "x": 29.1660800, "label": 0},
    {"y": 115.9067200, "x": 29.1660800, "label": 1},
    {"y": 115.9067200, "x": 29.1670800, "label": 1},
    {"y": 115.9077200, "x": 29.1670800, "label": 2},
    {"y": 115.9077200, "x": 29.1680800, "label": 2},
    {"y": 115.9087200, "x": 29.1680800, "label": 2}
]

color_map = {
    0: 'red',
    1: 'blue',
    2: 'green'
}

dbscan(cluster_results, eps=0.001, min_pts=2, color_map=color_map)