使用 Colomap 绘制线串 - Geopandas 和 Folium

Plotting Linestrings with a Colomap - Geopandas and Folium

我有一个包含 ~500 线串的 geopandas 数据框和一个名为 total 的列,其中包含一个介于 0 和 1 之间的数字。

我想在 folium 地图上绘制线串,其颜色取决于 total 的值。因此,我定义了一个颜色图如下:

colormap = cm.LinearColormap(colors=['lightblue','blue'])

我正在使用以下代码绘制所有内容:

m = folium.Map(zoom_start=10, tiles='CartoDB positron')

for _, r in gdf.iterrows():
    geo_j = gpd.GeoSeries(r['geometry']).to_json()
    geo_j = folium.GeoJson(data=geo_j,
                           style_function=lambda x:
                                      {'lineColor':colormap(r['total']),
                                       'color': colormap(r['total']),
                                       'fill':True,
                                       'opacity': 1, 
                                       'fillColor': colormap(r['total'])})
    geo_j.add_to(m)

我尝试了线条颜色、颜色、填充颜色、不透明度等的所有组合,但即使 colormap(r['total'] 工作正常(总是检索到不同的 rgb),所有的线条总是用相同的颜色绘制:

有人能帮忙吗?

import requests
import geopandas as gpd
import plotly.graph_objects as go
import itertools
import numpy as np
import pandas as pd
import shapely.geometry

# get geometry of london underground stations
gdf = gpd.GeoDataFrame.from_features(
    requests.get(
        "https://raw.githubusercontent.com/oobrien/vis/master/tube/data/tfl_stations.json"
    ).json()
)

# limit to zone 1 and stations that have larger number of lines going through them
gdf = (
    gdf.loc[gdf["zone"].isin(["1", "2"]) & gdf["lines"].apply(len).gt(2)]
    .reset_index(drop=True)
    .rename(columns={"id": "tfl_id", "name": "id"})
)

# wanna join all valid combinations of stations...
combis = np.array(list(itertools.combinations(gdf.index, 2)))

# generate dataframe of all combinations of stations
gdf_c = (
    gdf.loc[combis[:, 0], ["geometry", "id"]]
    .assign(right=combis[:, 1])
    .merge(
        gdf.loc[:, ["geometry", "id"]],
        left_on="right",
        right_index=True,
        suffixes=("_start_station", "_end_station"),
    )
)

# generate linestrings between stations
gdf = gpd.GeoDataFrame(
    geometry=gdf_c.select_dtypes("geometry").apply(shapely.geometry.LineString, axis=1),
    data=gdf_c,
    crs="EPSG:4326",
)
gdf["total"] = np.random.uniform(0, 1, len(gdf))

# now use explore that uses folium
gdf.explore("total", cmap="Blues", tiles="CartoDB positron")