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PGF Backend: Support interpolation='none' #6792

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Merged
merged 4 commits into from
Aug 27, 2016
Merged

PGF Backend: Support interpolation='none' #6792

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468a977
PGF backend: skip drawing of empty images
f0k Jul 18, 2016
4bcb38f
PGF backend: support affine image transformations
f0k Jul 18, 2016
d931283
Add more transforms to affine image transform demo
f0k Jul 18, 2016
0eb17a4
RendererBase: improve draw_image() docstring
f0k Jul 20, 2016
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Add more transforms to affine image transform demo
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@f0k
f0k committed Aug 16, 2016
commit d931283c9adf082dc9c6ae74a9e9609f6dd306f9
49 changes: 30 additions & 19 deletions examples/api/demo_affine_image.py
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Original file line number Diff line number Diff line change
@@ -1,11 +1,10 @@
"""
For the backends that supports draw_image with optional affine
For the backends that support draw_image with optional affine
transform (e.g., agg, ps backend), the image of the output should
have its boundary matches the red rectangles.
have its boundary match the dashed yellow rectangle.
"""

import numpy as np
import matplotlib.cm as cm
import matplotlib.mlab as mlab
import matplotlib.pyplot as plt
import matplotlib.transforms as mtransforms
Expand All @@ -21,25 +20,37 @@ def get_image():
return Z


if 1:
def do_plot(ax, Z, transform):
im = ax.imshow(Z, interpolation='none',
origin='lower',
extent=[-2, 4, -3, 2], clip_on=True)

# image rotation
trans_data = transform + ax.transData
im.set_transform(trans_data)

fig, ax1 = plt.subplots(1, 1)
Z = get_image()
im1 = ax1.imshow(Z, interpolation='none',
origin='lower',
extent=[-2, 4, -3, 2], clip_on=True)
# display intended extent of the image
x1, x2, y1, y2 = im.get_extent()
ax.plot([x1, x2, x2, x1, x1], [y1, y1, y2, y2, y1], "y--",
transform=trans_data)
ax.set_xlim(-5, 5)
ax.set_ylim(-4, 4)

trans_data2 = mtransforms.Affine2D().rotate_deg(30) + ax1.transData
im1.set_transform(trans_data2)

# display intended extent of the image
x1, x2, y1, y2 = im1.get_extent()
x3, y3 = x2, y1
# prepare image and figure
fig, ((ax1, ax2), (ax3, ax4)) = plt.subplots(2, 2)
Z = get_image()

# image rotation
do_plot(ax1, Z, mtransforms.Affine2D().rotate_deg(30))

# image skew
do_plot(ax2, Z, mtransforms.Affine2D().skew_deg(30, 15))

# scale and reflection
do_plot(ax3, Z, mtransforms.Affine2D().scale(-1, .5))

ax1.plot([x1, x2, x2, x1, x1], [y1, y1, y2, y2, y1], "--",
transform=trans_data2)
# everything and a translation
do_plot(ax4, Z, mtransforms.Affine2D().
rotate_deg(30).skew_deg(30, 15).scale(-1, .5).translate(.5, -1))

ax1.set_xlim(-3, 5)
ax1.set_ylim(-4, 4)
plt.show()