将数据复制到同心椭圆上

此示例演示在同心椭圆上绘制数据。绘制的数据是小行星Vesta的地形图。该地图实际上是一张图像，其定义在相对于半长轴为285公里、半短轴为229公里的椭圆的等矩形投影上。该图像被实时重新投影到具有匹配的同心圆投影上。

Traceback (most recent call last):
  File "/pb1/repo/cartopy/examples/miscellanea/eccentric_ellipse.py", line 72, in <module>
    main()
    ~~~~^^
  File "/pb1/repo/cartopy/examples/miscellanea/eccentric_ellipse.py", line 60, in main
    img, globe, crs, extent = vesta_image()
                              ~~~~~~~~~~~^^
  File "/pb1/repo/cartopy/examples/miscellanea/eccentric_ellipse.py", line 41, in vesta_image
    img_handle = BytesIO(urlopen(url).read())
                         ~~~~~~~^^^^^
  File "/usr/lib/python3.13/urllib/request.py", line 189, in urlopen
    return opener.open(url, data, timeout)
           ~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^
  File "/usr/lib/python3.13/urllib/request.py", line 489, in open
    response = self._open(req, data)
  File "/usr/lib/python3.13/urllib/request.py", line 506, in _open
    result = self._call_chain(self.handle_open, protocol, protocol +
                              '_open', req)
  File "/usr/lib/python3.13/urllib/request.py", line 466, in _call_chain
    result = func(*args)
  File "/usr/lib/python3.13/urllib/request.py", line 1367, in https_open
    return self.do_open(http.client.HTTPSConnection, req,
           ~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                        context=self._context)
                        ^^^^^^^^^^^^^^^^^^^^^^
  File "/usr/lib/python3.13/urllib/request.py", line 1322, in do_open
    raise URLError(err)
urllib.error.URLError: <urlopen error [Errno 110] Connection timed out>

from io import BytesIO
from urllib.request import urlopen

import matplotlib.pyplot as plt
import numpy as np
from PIL import Image

import cartopy.crs as ccrs


def vesta_image():
    """
    Return an image of Vesta's topography.

    Image credit: NASA/JPL-Caltech/UCLA/MPS/DLR/IDA/PSI

    Returns
    -------
    img : numpy array
        The pixels of the image in a numpy array.
    img_proj : cartopy CRS
        The rectangular coordinate system of the image.
    img_extent : tuple of floats
        The extent of the image ``(x0, y0, x1, y1)`` referenced in
        the ``img_proj`` coordinate system.

    """
    url = 'https://photojournal.jpl.nasa.gov/jpeg/PIA17037.jpg'
    img_handle = BytesIO(urlopen(url).read())
    raw_image = Image.open(img_handle)
    # The image is extremely high-resolution, which takes a long time to
    # plot. Sub-sampling reduces the time taken to plot while not
    # significantly altering the integrity of the result.
    smaller_image = raw_image.resize([raw_image.size[0] // 10,
                                      raw_image.size[1] // 10])
    img = np.asarray(smaller_image)
    # We define the semimajor and semiminor axes, but must also tell the
    # globe not to use the WGS84 ellipse, which is its default behaviour.
    img_globe = ccrs.Globe(semimajor_axis=285000., semiminor_axis=229000.,
                           ellipse=None)
    img_proj = ccrs.PlateCarree(globe=img_globe)
    img_extent = (-180, 180,
                  -90, 90)
    return img, img_globe, img_proj, img_extent


def main():
    img, globe, crs, extent = vesta_image()
    projection = ccrs.Geostationary(globe=globe)

    fig = plt.figure()
    ax = fig.add_subplot(1, 1, 1, projection=projection)
    ax.imshow(img, transform=crs, extent=extent)
    fig.text(.075, .012, "Image credit: NASA/JPL-Caltech/UCLA/MPS/DLR/IDA/PSI",
             bbox={'facecolor': 'w', 'edgecolor': 'k'})
    plt.show()


if __name__ == '__main__':
    main()