# Copyright Cartopy Contributors
#
# This file is part of Cartopy and is released under the LGPL license.
# See COPYING and COPYING.LESSER in the root of the repository for full
# licensing details.

import matplotlib.pyplot as plt
import pytest

import cartopy.crs as ccrs
from cartopy.tests.mpl import MPL_VERSION, ImageTesting


class ExampleImageTesting(ImageTesting):
    """Subclasses ImageTesting to nullify the plt.show commands."""
    def __call__(self, test_func):
        fn = ImageTesting.__call__(self, test_func)

        def new_fn(*args, **kwargs):
            try:
                show = plt.show
                plt.show = lambda *args, **kwargs: None
                r = fn(*args, **kwargs)
            finally:
                plt.show = show
            return r

        new_fn.__name__ = fn.__name__
        return new_fn


@pytest.mark.natural_earth
@ExampleImageTesting(['global_map'])
def test_global_map():
    fig = plt.figure(figsize=(10, 5))
    ax = fig.add_subplot(1, 1, 1, projection=ccrs.Robinson())

    # make the map global rather than have it zoom in to
    # the extents of any plotted data
    ax.set_global()

    ax.stock_img()
    ax.coastlines()

    ax.plot(-0.08, 51.53, 'o', transform=ccrs.PlateCarree())
    ax.plot([-0.08, 132], [51.53, 43.17], transform=ccrs.PlateCarree())
    ax.plot([-0.08, 132], [51.53, 43.17], transform=ccrs.Geodetic())


contour_image = 'contour_label' if MPL_VERSION < '3.4' else 'contour_label_3.4'
@pytest.mark.natural_earth
@ExampleImageTesting([contour_image], tolerance=0)
def test_contour_label():
    from cartopy.tests.mpl.test_caching import sample_data
    fig = plt.figure()

    # Setup a global EckertIII map with faint coastlines.
    ax = fig.add_subplot(1, 1, 1, projection=ccrs.EckertIII())
    ax.set_global()
    ax.coastlines('110m', alpha=0.1)

    # Use the waves example to provide some sample data, but make it
    # more dependent on y for more interesting contours.
    x, y, z = sample_data((20, 40))
    z = z * -1.5 * y

    # Add colourful filled contours.
    filled_c = ax.contourf(x, y, z, transform=ccrs.PlateCarree())

    # And black line contours.
    line_c = ax.contour(x, y, z, levels=filled_c.levels,
                        colors=['black'],
                        transform=ccrs.PlateCarree())

    # Uncomment to make the line contours invisible.
    # plt.setp(line_c.collections, visible=False)

    # Add a colorbar for the filled contour.
    fig.colorbar(filled_c, orientation='horizontal')

    # Use the line contours to place contour labels.
    ax.clabel(
        line_c,  # Typically best results when labelling line contours.
        colors=['black'],
        manual=False,  # Automatic placement vs manual placement.
        inline=True,  # Cut the line where the label will be placed.
        fmt=' {:.0f} '.format,  # Labes as integers, with some extra space.
    )