from matplotlib import rcParams
from matplotlib.testing.decorators import image_comparison
import matplotlib.pyplot as plt
import matplotlib.path as mpath
import matplotlib.patches as mpatches
from matplotlib.ticker import FuncFormatter
import numpy as np

@image_comparison(baseline_images=['bbox_inches_tight'], remove_text=True,
                  savefig_kwarg=dict(bbox_inches='tight'), tol=15)
def test_bbox_inches_tight():
    "Test that a figure saved using bbox_inches'tight' is clipped right"
    data = [[  66386,  174296,   75131,  577908,   32015],
            [  58230,  381139,   78045,   99308,  160454],
            [  89135,   80552,  152558,  497981,  603535],
            [  78415,   81858,  150656,  193263,   69638],
            [ 139361,  331509,  343164,  781380,   52269]]

    colLabels = rowLabels = [''] * 5

    rows = len(data)
    ind = np.arange(len(colLabels)) + 0.3  # the x locations for the groups
    cellText = []
    width = 0.4     # the width of the bars
    yoff = np.array([0.0] * len(colLabels))
    # the bottom values for stacked bar chart
    fig, ax = plt.subplots(1,1)
    for row in range(rows):
        plt.bar(ind, data[row], width, bottom=yoff)
        yoff = yoff + data[row]
        cellText.append([''])
    plt.xticks([])
    plt.legend([''] * 5, loc = (1.2, 0.2))
    # Add a table at the bottom of the axes
    cellText.reverse()
    the_table = plt.table(cellText=cellText,
                          rowLabels=rowLabels,
                          colLabels=colLabels, loc='bottom')


@image_comparison(baseline_images=['bbox_inches_tight_suptile_legend'],
                  remove_text=False, savefig_kwarg={'bbox_inches': 'tight'})
def test_bbox_inches_tight_suptile_legend():
    plt.plot(list(range(10)), label='a straight line')
    plt.legend(bbox_to_anchor=(0.9, 1), loc=2, )
    plt.title('Axis title')
    plt.suptitle('Figure title')

    # put an extra long y tick on to see that the bbox is accounted for
    def y_formatter(y, pos):
        if int(y) == 4:
            return 'The number 4'
        else:
            return str(y)
    plt.gca().yaxis.set_major_formatter(FuncFormatter(y_formatter))

    plt.xlabel('X axis')


@image_comparison(baseline_images=['bbox_inches_tight_clipping'],
                  remove_text=True, savefig_kwarg={'bbox_inches': 'tight'})
def test_bbox_inches_tight_clipping():
    # tests bbox clipping on scatter points, and path clipping on a patch
    # to generate an appropriately tight bbox
    plt.scatter(list(range(10)), list(range(10)))
    ax = plt.gca()
    ax.set_xlim([0, 5])
    ax.set_ylim([0, 5])

    # make a massive rectangle and clip it with a path
    patch = mpatches.Rectangle([-50, -50], 100, 100,
                           transform=ax.transData,
                           facecolor='blue', alpha=0.5)

    path = mpath.Path.unit_regular_star(5).deepcopy()
    path.vertices *= 0.25
    patch.set_clip_path(path, transform=ax.transAxes)
    plt.gcf().artists.append(patch)


if __name__ == '__main__':
    import nose
    nose.runmodule(argv=['-s', '--with-doctest'], exit=False)
