更新
：这是使用Cartopy的新版本，因为底图是EOL。以下是原始答案。
import matplotlib.pyplot as pltimport cartopy.crs as ccrsimg = plt.imread("/tmp/venuscyl4.tif")plt.figure(figsize=(3, 3))ax = plt.axes(projection=ccrs.Orthographic(-10, 45))ax.gridlines(color='black', linestyle='dotted')ax.imshow(img, origin="upper", extent=(-180, 180, -90, 90), transform=ccrs.PlateCarree()) # importantplt.show()多亏了Raphael
Roth的回答，我终于找到了我想要的东西：底图方法warpimage。
这是一个非常小的例子。使用此金星柱形图，并根据菜谱的简单示例：
from mpl_toolkits.basemap import basemapimport matplotlib.pyplot as pltimport numpy as np# set up orthographic map projection with# perspective of satellite looking down at 50N, 100W.# use low resolution coastlines.# don't plot features that are smaller than 1000 square km.bmap = basemap(projection='ortho', lat_0 = 50, lon_0 = -100, resolution = 'l', area_thresh = 1000.)# plot surfacebmap.warpimage(image='venuscyl4.jpg')# draw the edge of the map projection region (the projection limb)bmap.drawmapboundary()# draw lat/lon grid lines every 30 degrees.bmap.drawmeridians(np.arange(0, 360, 30))bmap.drawparallels(np.arange(-90, 90, 30))plt.show()
