>>> """
==========
Ribbon Box
==========

"""
... 
... import numpy as np
... 
... from matplotlib import cbook, colors as mcolors
... from matplotlib.image import AxesImage
... import matplotlib.pyplot as plt
... from matplotlib.transforms import Bbox, TransformedBbox, BboxTransformTo
... 
... 
... class RibbonBox:
... 
...     original_image = plt.imread(
...         cbook.get_sample_data("Minduka_Present_Blue_Pack.png"))
...     cut_location = 70
...     b_and_h = original_image[:, :, 2:3]
...     color = original_image[:, :, 2:3] - original_image[:, :, 0:1]
...     alpha = original_image[:, :, 3:4]
...     nx = original_image.shape[1]
... 
...     def __init__(self, color):
...         rgb = mcolors.to_rgba(color)[:3]
...         self.im = np.dstack(
...             [self.b_and_h - self.color * (1 - np.array(rgb)), self.alpha])
... 
...     def get_stretched_image(self, stretch_factor):
...         stretch_factor = max(stretch_factor, 1)
...         ny, nx, nch = self.im.shape
...         ny2 = int(ny*stretch_factor)
...         return np.vstack(
...             [self.im[:self.cut_location],
...              np.broadcast_to(
...                  self.im[self.cut_location], (ny2 - ny, nx, nch)),
...              self.im[self.cut_location:]])
... 
... 
... class RibbonBoxImage(AxesImage):
...     zorder = 1
... 
...     def __init__(self, ax, bbox, color, *, extent=(0, 1, 0, 1), **kwargs):
...         super().__init__(ax, extent=extent, **kwargs)
...         self._bbox = bbox
...         self._ribbonbox = RibbonBox(color)
...         self.set_transform(BboxTransformTo(bbox))
... 
...     def draw(self, renderer, *args, **kwargs):
...         stretch_factor = self._bbox.height / self._bbox.width
... 
...         ny = int(stretch_factor*self._ribbonbox.nx)
...         if self.get_array() is None or self.get_array().shape[0] != ny:
...             arr = self._ribbonbox.get_stretched_image(stretch_factor)
...             self.set_array(arr)
... 
...         super().draw(renderer, *args, **kwargs)
... 
... 
... def main():
...     fig, ax = plt.subplots()
... 
...     years = np.arange(2004, 2009)
...     heights = [7900, 8100, 7900, 6900, 2800]
...     box_colors = [
...         (0.8, 0.2, 0.2),
...         (0.2, 0.8, 0.2),
...         (0.2, 0.2, 0.8),
...         (0.7, 0.5, 0.8),
...         (0.3, 0.8, 0.7),
...     ]
... 
...     for year, h, bc in zip(years, heights, box_colors):
...         bbox0 = Bbox.from_extents(year - 0.4, 0., year + 0.4, h)
...         bbox = TransformedBbox(bbox0, ax.transData)
...         ax.add_artist(RibbonBoxImage(ax, bbox, bc, interpolation="bicubic"))
...         ax.annotate(str(h), (year, h), va="bottom", ha="center")
... 
...     ax.set_xlim(years[0] - 0.5, years[-1] + 0.5)
...     ax.set_ylim(0, 10000)
... 
...     background_gradient = np.zeros((2, 2, 4))
...     background_gradient[:, :, :3] = [1, 1, 0]
...     background_gradient[:, :, 3] = [[0.1, 0.3], [0.3, 0.5]]  # alpha channel
...     ax.imshow(background_gradient, interpolation="bicubic", zorder=0.1,
...               extent=(0, 1, 0, 1), transform=ax.transAxes, aspect="auto")
... 
...     plt.show()
... 
... 
... main()
...