Overlay/Fill 个国家/地区边界图片位于

Question

有没有办法使用自定义库用类似于 R 解决方案的图像填充国家/地区 here:

我有一个解决方案，其中填充了面部颜色，例如下面的意大利是蓝色的。但是，我想添加意大利国旗。 Python 中有没有什么方法（我搜索后没有找到太多）或者需要像 QGIS 这样的东西：

#create a map where I can load images in to fill the countries
import cartopy
import cartopy.crs as ccrs
import matplotlib.pyplot as plt
import cartopy.io.shapereader as shpreader

flag = "italy.png" #this is a locally saved png.

plt.figure(figsize=(15, 15)) #size of plot
ax = plt.axes(projection=cartopy.crs.TransverseMercator(25))
ax.add_feature(cartopy.feature.BORDERS, linestyle='-', alpha=1)
ax.coastlines(resolution='110m') #simplifies the border lines
ax.add_feature(cartopy.feature.OCEAN, facecolor="#40e0d0") #colour of ocean
# ax.gridlines() #adds global grid lines
ax.set_extent ((-7.5, 50, 34, 69), cartopy.crs.PlateCarree()) #makes it european


shpfilename = shpreader.natural_earth(resolution='110m',
                                      category='cultural',
                                      name='admin_0_countries')

for country in shpreader.Reader(shpfilename).records():
    if country.attributes['NAME_LONG'] == "Italy":
        ax.add_geometries(country.geometry, ccrs.PlateCarree(),
                          facecolor="blue",
                          #no attribute like this img= "fd",

                          label=country.attributes['NAME_LONG'])

plt.show()

任何帮助，非常感谢！

Answer 1

这是一个演示代码，可以满足您的需要。事实上，cartopy logo就是用这种技术来创作的。

import cartopy
import cartopy.crs as ccrs
import matplotlib.pyplot as plt
import cartopy.io.shapereader as shpreader
import matplotlib.patches as mpatches
import numpy as np

imdat1 = plt.imread('flag-of-italy.jpg', format='jpg') # use your flag

plt.figure(figsize=(8, 8))
ax = plt.axes(projection=cartopy.crs.TransverseMercator(25))
ax.add_feature(cartopy.feature.BORDERS, linestyle='-', alpha=1)
ax.coastlines(resolution='110m')
ax.add_feature(cartopy.feature.OCEAN, facecolor="#40e0d0")
# ax.gridlines() #adds global grid lines
ax.set_extent ((-7.5, 50, 24, 69), cartopy.crs.PlateCarree())

shpfilename = shpreader.natural_earth(resolution='110m',
                                      category='cultural',
                                      name='admin_0_countries')

italy_ctry = None  #use this to grab italy's

for country in shpreader.Reader(shpfilename).records():
    if country.attributes['NAME_LONG'] == "Italy":
        italy_ctry = country
        ax.add_geometries(country.geometry, ccrs.PlateCarree(),
                          facecolor="none",
                          alpha=0.7,
                          zorder=2,
                          label=country.attributes['NAME_LONG'])

# create mpatch from `italy` geometry
cg = italy_ctry.geometry
cg2 = cg.simplify(0.02)

if cg2.geometryType()=='MultiPolygon':
    # if == `Polygon`, dont need to loop
    for ea in cg2.geoms:
        cg2xy = ea.exterior.xy  # tuple of (x,y)
        xys = []
        for ea in zip(cg2xy[0], cg2xy[1]):
            #print(ea[0],ea[1])
            xys.append([ea[0],ea[1]])

        # add a patch
        poly = mpatches.Polygon(xys, closed=True, ec='r', \
                                lw=2, fc='yellow', \
                                transform=ccrs.PlateCarree(), \
                                alpha=0.5, zorder=30)

        plate_carree_transform = ccrs.PlateCarree()._as_mpl_transform(ax)

        xtent1 = (6.519950, 17.122259, 35.783370, 47.962952)
        imdat2 = ax.imshow(imdat1, origin='upper', extent=xtent1, \
            transform=ccrs.PlateCarree(), \
            zorder=15, alpha=.9)

        ##imdat2 = ax.stock_img()  #for testing
        imdat2.set_clip_path(mpatches.Path(xys), transform=plate_carree_transform) 
    pass

plt.show()

样例图（因使用的标志而异）：

Overlay/Fill 个国家/地区边界图片位于

Overlay/Fill country boundaries with image in

python

matplotlib

geospatial

matplotlib-basemap

cartopy