绘制阿拉斯加和夏威夷的插图（理想情况下为 Mapbox）

Question

有没有办法创建额外的等值线（最好是 Mapbox 等值线，但我会满足于 Plotly 的标准等值线函数）地图并将它们分层在基本等值线之上，以便我可以轻松地显示与阿拉斯加和夏威夷相关的数据美国大陆？

Something like this image

不要相信我现有的代码一定有用，但这是我构建基本地图的方式（删除了我的自定义样式，以便任何人都应该能够生成）。

fig = px.choropleth_mapbox(
    df_mar,
    geojson=puma,
    locations="stpuma",
    color="inter_pct",
    range_color=(0,25),
    color_continuous_scale="Viridis",
    labels={"inter_pct": "Marriage (%)"},
    center={"lat": 37.0902, "lon": -95.7129},
    zoom=4.2,
    opacity=1.0,
    mapbox_style="white-bg"
)
fig.update_layout(
    coloraxis_colorbar=dict(
        bgcolor="rgba(22,33,49,1)",
        title="Marriage,<br>Percent Share",
        titlefont=dict(
            color="rgba(255,255,255,1)"
        ),
        tickfont=dict(
            color="rgba(255,255,255,1)"
        ),
    ),
    margin=dict(
        l=50,
        r=50,
        b=50,
        t=50,
        pad=4
    ),
    paper_bgcolor = "rgba(8,18,23,1)",
    plot_bgcolor = "rgba(8,18,23,1)",
    showlegend = True,
    annotations = [
        dict(
            x=-0.025,
            y=-0.04,
            xref='paper',
            yref='paper',
            text='Source: Census ACS 5 2015-2019',
            showarrow = False,
            font=dict(
                color="rgba(255,255,255,1)"
            ),
            bgcolor="rgba(8,18,23,1)",
        )
    ]
)
fig.update_traces(
    marker_line_width=0,
    below="waterway"
)
fig.show(width=1920, height=1080)

Answer 1

• 可以通过ma​​pbox实现
• 关键概念是修改几何以满足您的布局要求。因此已经完成https://shapely.readthedocs.io/en/stable/manual.html#affine-transformations 移动阿拉斯加和夏威夷
• 还发现 阿拉斯加 几何形状会出现问题，因为它跨越了日期变更线。因此，变换后的几何图形也被剪裁了
• 添加层以表明几何图形已被操纵
• 包括海洋边界以演示如何将其扩展到其他几何形状

import geopandas as gpd
import shapely.geometry
import numpy as np
import plotly.express as px
import requests, io
from pathlib import Path
from zipfile import ZipFile
import urllib
import pandas as pd
from shapely.affinity import affine_transform as T

# US geometry
urls = [
    "https://www2.census.gov/geo/tiger/GENZ2018/shp/cb_2018_us_state_5m.zip",
    "https://maritimeboundaries.noaa.gov/downloads/USMaritimeLimitsAndBoundariesSHP.zip",
]
gdfs = {}
for url in urls:
    f = Path.cwd().joinpath(urllib.parse.urlparse(url).path.split("/")[-1])

    if not f.exists():
        r = requests.get(url, stream=True, headers={"User-Agent": "XY"})
        with open(f, "wb") as fd:
            for chunk in r.iter_content(chunk_size=128):
                fd.write(chunk)
        zfile = ZipFile(f)
        zfile.extractall(f.stem)

    gdfs[f.stem] = gpd.read_file(
        list(f.parent.joinpath(f.stem).glob("*.shp"))[0]
    )  # .to_crs("EPSG:4326")

gdf2 = gdfs["cb_2018_us_state_5m"]
gdf2 = gdf2.set_index("STUSPS", drop=False)
gdf2["color"] = gdf2["STATEFP"].astype(int)


# move alaska and hawaii using affine transform
t = {"AK": [0.6, 0, 0, 0.6, -20, -15], "HI": [3, 0, 0, 3, 385, -42]}
clip = (-179, 15, 0, 150)
gdf3 = gdf2.copy()
gdf3.loc[t.keys(), "geometry"] = gdf3.loc[t.keys(), ["geometry"]].apply(
    lambda g: shapely.ops.clip_by_rect(T(g["geometry"], t[g.name]), *clip), axis=1
)

gdf_m = gdfs["USMaritimeLimitsAndBoundariesSHP"]
gdf_m = gdf_m.dissolve("REGION")
tm = {"Alaska": "AK", "Hawaiian Islands": "HI"}
gdf_m.loc[tm.keys(), "geometry"] = gdf_m.loc[tm.keys(), ["geometry"]].apply(
    lambda g: shapely.ops.clip_by_rect(
        T(g["geometry"], t[tm[g.name]]), *gdf3.loc[tm[g.name]].geometry.bounds
    ),
    axis=1,
)


px.choropleth_mapbox(
    gdf3,
    geojson=gdf3.geometry.__geo_interface__,
    locations=gdf3.index,
    color="color",
    hover_name="NAME",
).update_layout(
    mapbox={
        "style": "carto-positron",
        "center": {"lon": -98, "lat": 33},
        "zoom": 2.5,
        "layers": [
            {
                "source": shapely.geometry.box(
                    *gdf3.loc[box].geometry.bounds
                ).__geo_interface__,
                "type": "fill",
                "color": "blue",
                "opacity": 0.1,
            }
            for box in t.keys()
        ]
        + [
            {
                "source": gdf_m.geometry.__geo_interface__,
                "type": "line",
                "color": "blue",
                "line": {"width": 1},
            }
        ],
    },
    margin={"l": 0, "r": 0, "t": 0, "b": 0},
)