在Cartopy地图上显示阿拉斯加和夏威夷

Question

以下代码创建了一个由人口密度阴影化的美国大陆州地图。我想创建一个类似的地图（我的数据实际上不是流行密度，但这是一个简单的示例），除了它还包括阿拉斯加州和夏威夷州。

具体来说，我想让阿拉斯加/夏威夷出现在图中，但要移动使其位于图中显示美国大陆的部分的下方。或类似的东西。

您知道我将如何使用Cartopy创建这样的地图吗？

import matplotlib.pyplot as plt
import cartopy.crs as ccrs
import cartopy.io.shapereader as shpreader

fig = plt.figure()
ax = fig.add_axes([0, 0, 1, 1], projection=ccrs.LambertConformal())

ax.set_extent([-125, -66.5, 20, 50], ccrs.Geodetic())

shapename = 'admin_1_states_provinces_lakes_shp'
states_shp = shpreader.natural_earth(resolution='110m',
                                     category='cultural', name=shapename)

popdensity = {
    'New Jersey':  438.00,
    'Rhode Island':   387.35,
    'Massachusetts':   312.68,
    'Connecticut':    271.40,
    'Maryland':   209.23,
    'New York':    155.18,
    'Delaware':    154.87,
    'Florida':     114.43,
    'Ohio':  107.05,
    'Pennsylvania':  105.80,
    'Illinois':    86.27,
    'California':  83.85,
    'Virginia':    69.03,
    'Michigan':    67.55,
    'Indiana':    65.46,
    'North Carolina':  63.80,
    'Georgia':     54.59,
    'Tennessee':   53.29,
    'New Hampshire':   53.20,
    'South Carolina':  51.45,
    'Louisiana':   39.61,
    'Kentucky':   39.28,
    'Wisconsin':  38.13,
    'Washington':  34.20,
    'Alabama':     33.84,
    'Missouri':    31.36,
    'Texas':   30.75,
    'West Virginia':   29.00,
    'Vermont':     25.41,
    'Minnesota':  23.86,
    'Mississippi':   23.42,
    'Iowa':  20.22,
    'Arkansas':    19.82,
    'Oklahoma':    19.40,
    'Arizona':     17.43,
    'Colorado':    16.01,
    'Maine':  15.95,
    'Oregon':  13.76,
    'Kansas':  12.69,
    'Utah':  10.50,
    'Nebraska':    8.60,
    'Nevada':  7.03,
    'Idaho':   6.04,
    'New Mexico':  5.79,
    'South Dakota':  3.84,
    'North Dakota':  3.59,
    'Montana':     2.39,
    'Wyoming':      1.96}

ax.background_patch.set_visible(False)
ax.outline_patch.set_visible(False)

ax.set_title('State Population Density')

for state in shpreader.Reader(states_shp).records():

    edgecolor = 'black'

    try:
        # use the name of this state to get pop_density
        state_dens = popdensity[ state.attributes['name'] ]
    except:
        state_dens = 0

    # simple scheme to assign color to each state
    if state_dens < 40:
        facecolor = "lightyellow"
    elif state_dens > 200:
        facecolor = "red"
    else:
        facecolor = "pink"

    # `state.geometry` is the polygon to plot
    ax.add_geometries([state.geometry], ccrs.PlateCarree(),
                      facecolor=facecolor, edgecolor=edgecolor)

plt.show()

（当前）创建的图形如下：

Answer 1

将插图插入图作为主地图的一部分进行绘制具有挑战性。您将需要创建一个axes来绘制每个插图，并将其以适当的位置和相对比例放置在figure上。这是您可以试用的工作代码。

import matplotlib.pyplot as plt
import cartopy
import cartopy.crs as ccrs
import cartopy.io.shapereader as shpreader

import shapely.geometry as sgeom

# A function that draws inset map, ++
# ===================================
def add_insetmap(axes_extent, map_extent, state_name, facecolor, edgecolor, geometry):
    # create new axes, set its projection
    use_projection = ccrs.Mercator()     # preserve shape well
    #use_projection = ccrs.PlateCarree()   # large distortion in E-W for Alaska
    geodetic = ccrs.Geodetic(globe=ccrs.Globe(datum='WGS84'))
    sub_ax = plt.axes(axes_extent, projection=use_projection)  # normal units
    sub_ax.set_extent(map_extent, geodetic)  # map extents

    # add basic land, coastlines of the map
    # you may comment out if you don't need them
    sub_ax.add_feature(cartopy.feature.LAND)
    sub_ax.coastlines()

    sub_ax.set_title(state_name)

    # add map `geometry` here
    sub_ax.add_geometries([geometry], ccrs.PlateCarree(), \
                          facecolor=facecolor, edgecolor=edgecolor)
    # +++ more features can be added here +++

    # plot box around the map
    extent_box = sgeom.box(map_extent[0], map_extent[2], map_extent[1], map_extent[3])
    sub_ax.add_geometries([extent_box], ccrs.PlateCarree(), color='none', linewidth=0.05)


fig = plt.figure()
ax = fig.add_axes([0, 0, 1, 1], projection=ccrs.LambertConformal())

ax.set_extent([-125, -66.5, 20, 50], ccrs.Geodetic())

shapename = 'admin_1_states_provinces_lakes_shp'
states_shp = shpreader.natural_earth(resolution='110m',
                                     category='cultural', name=shapename)

popdensity = {
    'New Jersey':  438.00,
    'Rhode Island':   387.35,
    'Massachusetts':   312.68,
    'Connecticut':    271.40,
    'Maryland':   209.23,
    'New York':    155.18,
    'Delaware':    154.87,
    'Florida':     114.43,
    'Ohio':  107.05,
    'Pennsylvania':  105.80,
    'Illinois':    86.27,
    'California':  83.85,
    'Virginia':    69.03,
    'Michigan':    67.55,
    'Indiana':    65.46,
    'North Carolina':  63.80,
    'Georgia':     54.59,
    'Tennessee':   53.29,
    'New Hampshire':   53.20,
    'South Carolina':  51.45,
    'Louisiana':   39.61,
    'Kentucky':   39.28,
    'Wisconsin':  38.13,
    'Washington':  34.20,
    'Alabama':     33.84,
    'Missouri':    31.36,
    'Texas':   30.75,
    'West Virginia':   29.00,
    'Vermont':     25.41,
    'Minnesota':  23.86,
    'Mississippi':   23.42,
    'Iowa':  20.22,
    'Arkansas':    19.82,
    'Oklahoma':    19.40,
    'Arizona':     17.43,
    'Colorado':    16.01,
    'Maine':  15.95,
    'Oregon':  13.76,
    'Kansas':  12.69,
    'Utah':  10.50,
    'Nebraska':    8.60,
    'Nevada':  7.03,
    'Idaho':   6.04,
    'New Mexico':  5.79,
    'South Dakota':  3.84,
    'North Dakota':  3.59,
    'Montana':     2.39,
    'Wyoming':      1.96}

ax.background_patch.set_visible(False)
ax.outline_patch.set_visible(False)

ax.set_title('State Population Density')

for state in shpreader.Reader(states_shp).records():


    edgecolor = 'black'

    try:
        # use the name of this state to get pop_density
        state_dens = popdensity[ state.attributes['name'] ]
    except:
        state_dens = 0

    # simple scheme to assign color to each state
    if state_dens < 40:
        facecolor = "lightyellow"
    elif state_dens > 200:
        facecolor = "red"
    else:
        facecolor = "pink"

    # special handling for the 2 states
    # ---------------------------------
    if state.attributes['name'] in ("Alaska", "Hawaii"):
        # print("state.attributes['name']:", state.attributes['name'])

        state_name = state.attributes['name']

        # prep map settings
        # experiment with the numbers in both `_extents` for your best results
        if state_name == "Alaska":
            # (1) Alaska
            map_extent = (-178, -135, 46, 73)    # degrees: (lonmin,lonmax,latmin,latmax)
            axes_extent = (0.04, 0.06, 0.29, 0.275) # axes units: 0 to 1, (LLx,LLy,width,height)

        if state_name == "Hawaii":
            # (2) Hawii
            map_extent = (-162, -152, 15, 25)
            axes_extent = (0.27, 0.06, 0.15, 0.15)

        # add inset maps
        add_insetmap(axes_extent, map_extent, state_name, \
                     facecolor, \
                     edgecolor, \
                     state.geometry)

    # the other (conterminous) states go here
    else:
        # `state.geometry` is the polygon to plot
        ax.add_geometries([state.geometry], ccrs.PlateCarree(),
                          facecolor=facecolor, edgecolor=edgecolor)

plt.show()

输出图将是：