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Simplify demo_ribbon_box.py. #11197

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Merged
merged 1 commit into from
May 9, 2018
Merged

Simplify demo_ribbon_box.py. #11197

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92 changes: 25 additions & 67 deletions 92 examples/misc/demo_ribbon_box.py
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Original file line number Diff line number Diff line change
Expand Up @@ -4,98 +4,60 @@
===============

"""
import matplotlib.pyplot as plt

import numpy as np
from matplotlib.image import BboxImage

from matplotlib._png import read_png
import matplotlib.colors
from matplotlib.cbook import get_sample_data
from matplotlib import cbook, colors as mcolors
from matplotlib.image import BboxImage
import matplotlib.pyplot as plt


class RibbonBox(object):
class RibbonBox:

original_image = read_png(get_sample_data("Minduka_Present_Blue_Pack.png",
asfileobj=False))
original_image = plt.imread(
cbook.get_sample_data("Minduka_Present_Blue_Pack.png"))
cut_location = 70
b_and_h = original_image[:, :, 2]
color = original_image[:, :, 2] - original_image[:, :, 0]
alpha = original_image[:, :, 3]
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 = matplotlib.colors.to_rgba(color)[:3]

im = np.empty(self.original_image.shape,
self.original_image.dtype)

im[:, :, :3] = self.b_and_h[:, :, np.newaxis]
im[:, :, :3] -= self.color[:, :, np.newaxis] * (1 - np.array(rgb))
im[:, :, 3] = self.alpha

self.im = im
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)

stretched_image = np.empty((ny2, nx, nch),
self.im.dtype)
cut = self.im[self.cut_location, :, :]
stretched_image[:, :, :] = cut
stretched_image[:self.cut_location, :, :] = \
self.im[:self.cut_location, :, :]
stretched_image[-(ny - self.cut_location):, :, :] = \
self.im[-(ny - self.cut_location):, :, :]

self._cached_im = stretched_image
return stretched_image
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(BboxImage):
zorder = 1

def __init__(self, bbox, color,
cmap=None,
norm=None,
interpolation=None,
origin=None,
filternorm=1,
filterrad=4.0,
resample=False,
**kwargs
):

BboxImage.__init__(self, bbox,
cmap=cmap,
norm=norm,
interpolation=interpolation,
origin=origin,
filternorm=filternorm,
filterrad=filterrad,
resample=resample,
**kwargs
)

def __init__(self, bbox, color, **kwargs):
super().__init__(bbox, **kwargs)
self._ribbonbox = RibbonBox(color)
self._cached_ny = None

def draw(self, renderer, *args, **kwargs):

bbox = self.get_window_extent(renderer)
stretch_factor = bbox.height / bbox.width

ny = int(stretch_factor*self._ribbonbox.nx)
if self._cached_ny != ny:
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)
self._cached_ny = ny

BboxImage.draw(self, renderer, *args, **kwargs)
super().draw(renderer, *args, **kwargs)


if 1:
if True:
from matplotlib.transforms import Bbox, TransformedBbox
from matplotlib.ticker import ScalarFormatter

Expand Down Expand Up @@ -126,11 +88,8 @@ def draw(self, renderer, *args, **kwargs):
ax.annotate(r"%d" % (int(h/100.)*100),
(year, h), va="bottom", ha="center")

patch_gradient = BboxImage(ax.bbox,
interpolation="bicubic",
zorder=0.1,
)
gradient = np.zeros((2, 2, 4), dtype=float)
patch_gradient = BboxImage(ax.bbox, interpolation="bicubic", zorder=0.1)
gradient = np.zeros((2, 2, 4))
gradient[:, :, :3] = [1, 1, 0.]
gradient[:, :, 3] = [[0.1, 0.3], [0.3, 0.5]] # alpha channel
patch_gradient.set_array(gradient)
Expand All @@ -139,5 +98,4 @@ def draw(self, renderer, *args, **kwargs):
ax.set_xlim(years[0] - 0.5, years[-1] + 0.5)
ax.set_ylim(0, 10000)

fig.savefig('ribbon_box.png')
plt.show()
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