"""
Displaying data on an eccentric ellipse
---------------------------------------

This example demonstrates plotting data on an eccentric ellipse. The data
plotted is a topography map of the asteroid Vesta. The map is actually an
image, which is defined on an equirectangluar projection relative to an
ellipse with a semi-major axis of 285 km and a semi-minor axis of 229 km.
The image is reprojected on-the-fly onto a geostationary projection with
matching eccentricity.

"""
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()
