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mdboommdboom
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Merge pull request #1150 from leejjoon/fix-image-shift
the affine matrix is calculated in the display coordinate for interpolation='none'
2 parents ed7db9b + 67eb71d commit 2e5a38a

4 files changed

Lines changed: 228 additions & 6 deletions

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‎lib/matplotlib/image.py‎

Lines changed: 7 additions & 6 deletions
Original file line numberDiff line numberDiff line change
@@ -25,7 +25,7 @@
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# the image namespace:
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from matplotlib._image import *
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28-
from matplotlib.transforms import BboxBase, Bbox
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from matplotlib.transforms import BboxBase, Bbox, IdentityTransform
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import matplotlib.transforms as mtransforms
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@@ -270,8 +270,8 @@ def _draw_unsampled_image(self, renderer, gc):
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# firs, convert the image extent to the ic
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x_llc, x_trc, y_llc, y_trc = self.get_extent()
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273-
xy = trans.transform_non_affine(np.array([(x_llc, y_llc),
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(x_trc, y_trc)]))
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xy = trans.transform(np.array([(x_llc, y_llc),
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(x_trc, y_trc)]))
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_xx1, _yy1 = xy[0]
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_xx2, _yy2 = xy[1]
@@ -283,15 +283,16 @@ def _draw_unsampled_image(self, renderer, gc):
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if self._image_skew_coordinate:
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# skew the image when required.
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x_lrc, y_lrc = self._image_skew_coordinate
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xy2 = trans.transform_non_affine(np.array([(x_lrc, y_lrc)]))
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xy2 = trans.transform(np.array([(x_lrc, y_lrc)]))
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_xx3, _yy3 = xy2[0]
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tr_rotate_skew = self._get_rotate_and_skew_transform(_xx1, _yy1,
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_xx2, _yy2,
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_xx3, _yy3)
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trans_ic_to_canvas = tr_rotate_skew+trans.get_affine()
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trans_ic_to_canvas = tr_rotate_skew
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else:
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trans_ic_to_canvas = trans.get_affine()
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trans_ic_to_canvas = IdentityTransform()
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# Now, viewLim in the ic. It can be rotated and can be
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# skewed. Make it big enough.

‎lib/matplotlib/tests/baseline_images/test_image/image_shift.pdf‎

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‎lib/matplotlib/tests/baseline_images/test_image/image_shift.svg‎

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‎lib/matplotlib/tests/test_image.py‎

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Original file line numberDiff line numberDiff line change
@@ -160,6 +160,21 @@ def test_no_interpolation_origin():
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ax = fig.add_subplot(212)
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ax.imshow(np.arange(100).reshape((2, 50)), interpolation='none')
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@image_comparison(baseline_images=['image_shift'], remove_text=True,
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extensions=['pdf', 'svg'])
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def test_image_shift():
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from matplotlib.colors import LogNorm
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imgData = [[1.0/(x) + 1.0/(y) for x in range(1,100)] for y in range(1,100)]
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tMin=734717.945208
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tMax=734717.946366
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fig = plt.figure()
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ax = fig.add_subplot(111)
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ax.imshow(imgData, norm=LogNorm(), interpolation='none',
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extent=(tMin, tMax, 1, 100))
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ax.set_aspect('auto')
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if __name__=='__main__':
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import nose
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nose.runmodule(argv=['-s','--with-doctest'], exit=False)

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