python - Plotly - 在 Density Mapbox 上添加 Scatter Geo 点和轨迹

Question

我正在尝试添加 Scattergeo跟踪或覆盖在 white-bg 之上密度 map 框以获取通用美国各州轮廓上的热图。
我使用 scattergeo 的原因我想在密度 map 框的顶部绘制一个星形符号，以及唯一通过 add_scattermapbox 接受的符号吗？是一个点。如果您选择 star符号，没有添加符号。
我也知道 p mapbox_styles 可以接受星号的 add_scattermapbox或 density_scattermapbox但目前我无法在试用金额用完后为每个网络负载付费。
是否有一种巧妙的方法可以在 density_mapbox 上添加星号？阴谋？
工作 ScatterGeo

fig = go.Figure(go.Scattergeo())

fig.add_scattergeo(lat = [30, 40]
                      ,lon = [-90, -80]
                      ,hoverinfo = 'none'
                      ,marker_size = 10
                      ,marker_color = 'rgb(65, 105, 225)' # blue
                      ,marker_symbol = 'star'
                      ,showlegend = False
                     )

fig.update_geos(
    visible=False, resolution=110, scope="usa",
    showcountries=True, countrycolor="Black",
    showsubunits=True, subunitcolor="Black"
)

fig.show()

工作密度 Mapbox

d = {'Location': ['Point A', 'Point B'], 'lat': [30, 40], 'long': [-90, -80], 'z': [100,200]}

df = pd.DataFrame(data=d)

fig = px.density_mapbox(df
                        ,lat='lat'
                        ,lon='long'
                        ,z='z'
                        ,hover_name='Location'
                        ,center=dict(lat=38.5, lon=-96)
                        ,range_color = [0, 200]
                        ,zoom=2
                        ,radius=50
                        ,opacity=.5
                        ,mapbox_style='open-street-map')

fig.add_scattermapbox(lat = [30, 40]
                      ,lon = [-90, -80]
                      ,hoverinfo = 'none'
                      ,marker_size = 6
                      ,marker_color = 'rgb(0, 0, 0)'
#                       ,marker_symbol = 'star'
                      ,showlegend = False
                     )

fig.show()

尝试 #1 - 只需设置 marker_symbol = 'star'
取消评论 marker_symbol = 'star' ，这适用于 mapbox 的高级样式, 完全去除散点。

d = {'Location': ['Point A', 'Point B'], 'lat': [30, 40], 'long': [-90, -80], 'z': [100,200]}

df = pd.DataFrame(data=d)

fig = px.density_mapbox(df
                        ,lat='lat'
                        ,lon='long'
                        ,z='z'
                        ,hover_name='Location'
                        ,center=dict(lat=38.5, lon=-96)
                        ,range_color = [0, 200]
                        ,zoom=2
                        ,radius=50
                        ,opacity=.5
                        ,mapbox_style='open-street-map')

fig.add_scattermapbox(lat = [30, 40]
                      ,lon = [-90, -80]
                      ,hoverinfo = 'none'
                      ,marker_size = 6
                      ,marker_color = 'rgb(0, 0, 0)'
                      ,marker_symbol = 'star'
                      ,showlegend = False
                     )

fig.show()

尝试 #2 - 在散点地理顶部添加密度 map 框
添加 density_mapbox在 scattergeo 之上产生相同的地理图，但仅此而已。密度 map 框图例在那里，但没有热图。

d = {'Location': ['Point A', 'Point B'], 'lat': [30, 40], 'long': [-90, -80], 'z': [100,200]}

df = pd.DataFrame(data=d)

fig = go.Figure(go.Scattergeo())

fig.add_scattergeo(lat = [30, 40]
                      ,lon = [-90, -80]
                      ,hoverinfo = 'none'
                      ,marker_size = 10
                      ,marker_color = 'rgb(65, 105, 225)' # blue
                      ,marker_symbol = 'star'
                      ,showlegend = False
                     )

fig.add_densitymapbox(lat=df['lat'],
                     lon=df['long'],
                      z=df['z'],
                      radius=50,
                      opacity=.5
                     )

fig.update_geos(
    visible=False, resolution=110, scope="usa",
    showcountries=True, countrycolor="Black",
    showsubunits=True, subunitcolor="Black"
)

fig.show()

Answer 1

瓦片 map 和图层 map 不能一起工作。因此你不能使用来自 的标记地理 在 map 框

横向思考，可以加自己的 geojson 层到 map 框地块

生成几何。为此提供了两个选项

一个简单的三角形

get_geom(df["long"], df["lat"], marker=None, size=k)

https://labs.mapbox.com/maki-icons/

get_geom(df["long"], df["lat"], marker="star", size=k)哪里记号笔是 MAKI 图标名称。 NB 带孔的图标可以填充——例如警告

将图层添加到 map 框图形布局。这被参数化以生成多个图层以支持不同的缩放级别。更多层，更多开销。

import geopandas as gpd
import pandas as pd
import shapely.geometry
import math
import json
import plotly.express as px
import svgpath2mpl
import requests
import numpy as np

d = {
    "Location": ["Point A", "Point B"],
    "lat": [30, 40],
    "long": [-90, -80],
    "z": [100, 200],
}
df = pd.DataFrame(data=d)

fig = px.density_mapbox(
    df,
    lat="lat",
    lon="long",
    z="z",
    hover_name="Location",
    center=dict(lat=38.5, lon=-96),
    range_color=[0, 200],
    zoom=2,
    radius=50,
    opacity=0.5,
    mapbox_style="open-street-map",
)

# https://stackoverflow.com/questions/23411688/drawing-polygon-with-n-number-of-sides-in-python-3-2
def polygon(sides, radius=1, rotation=0, translation=None):
    one_segment = math.pi * 2 / sides

    points = [(math.sin(one_segment * i + rotation) * radius,
               math.cos(one_segment * i + rotation) * radius,)
              for i in range(sides)]

    if translation:
        points = [[sum(pair) for pair in zip(point, translation)] for point in points]

    return shapely.geometry.Polygon(points)

def makimarker(makiname="star", geo=(0, 0), size=0.1):
    url = f"https://raw.githubusercontent.com/mapbox/maki/main/icons/{makiname}.svg"
    svgpath = pd.read_xml(requests.get(url).text).loc[0, "d"]
    p = svgpath2mpl.parse_path(svgpath).to_polygons()
    # need centroid to adjust marked to be centred on geo location
    c = shapely.affinity.scale(
        shapely.geometry.Polygon(p[0]), xfact=size, yfact=size
    ).centroid
    # centre and place marker
    marker = shapely.geometry.Polygon(
        [[sum(triple) for triple in zip(point, geo, (-c.x, -c.y))] for point in p[0]]
    )
    # finally size geometry
    return shapely.affinity.scale(marker, xfact=size, yfact=size)


def get_geom(long_a: list, lat_a: list, marker=None, size=0.15) -> list:
    if marker:
        geo = [
            makimarker(marker, geo=(long, lat), size=size)
            for long, lat in zip(long_a, lat_a)
        ]
    else:
        geo = [
            polygon(3, translation=(long, lat), radius=size*10)
            for long, lat in zip(long_a, lat_a)
        ]
    return json.loads(gpd.GeoDataFrame(geometry=geo).to_json())

# basing math on this https://wiki.openstreetmap.org/wiki/Zoom_levels
# dict is keyed by size with min/max zoom levels covered by this size
MINZOOM=.1
MAXZOOM=18
LAYERS=7
zoom = 512**np.linspace(math.log(MINZOOM,512), math.log(MAXZOOM, 512), LAYERS)
zoom = {
    (200/(2**(np.percentile(zoom[i:i+2],25)+9))): {"minzoom":zoom[i], "maxzoom":zoom[i+1], "name":i}
    for i in range(LAYERS-1)
}

# add a layers to density plot that are the markers
fig.update_layout(
    mapbox={
        "layers": [
            {
                "source": get_geom(df["long"], df["lat"], marker="star", size=k),
                "type": "fill",
                "color": "blue",
                **zoom[k],
            }
            for k in zoom.keys()
        ]
    },
    margin={"t": 0, "b": 0, "l": 0, "r": 0},
)
fig