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Merged
merged 4 commits into from
Aug 20, 2012
Merged

External transform api #1090

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5df279d
Support for transform in contour, and an external _as_mpl_transform api.
pelson Mar 2, 2012
7d6fced
Added test for pre-transforming some plot types.
pelson Mar 2, 2012
6ad4e85
updated boilerplate
pelson Aug 15, 2012
456a723
Wrapped lines over 80 chars.
pelson Aug 17, 2012
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Wrapped lines over 80 chars.
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@pelson
pelson committed Aug 17, 2012
commit 456a72332352e4890b6f1323e6b7dfa3da4808fe
3 changes: 2 additions & 1 deletion lib/matplotlib/artist.py
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Expand Up @@ -234,7 +234,8 @@ def get_transform(self):
"""
if self._transform is None:
self._transform = IdentityTransform()
elif not isinstance(self._transform, Transform) and hasattr(self._transform, '_as_mpl_transform'):
elif (not isinstance(self._transform, Transform)
and hasattr(self._transform, '_as_mpl_transform')):
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Is there any point in checking for the _as_mpl_transform attribute? If it is not None, and it is not a Transform, and it can't be made into one, shouldn't it just raise an exception? Or is the idea that something not inheriting from Transform can still function as if it did?

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The idea was simply to not break anything else that was already passing something fruity. I think it might just get down to the point where the transform_path etc. methods are called and blow up if they don't exist on the thing in self._transform, though I am not entirely sure.

I'm not too fussed either way, but I am happy to be less generous and just try calling the _as_mpl_transform method, and if it doesn't exist, oh well... what is your preference?

self._transform = self._transform._as_mpl_transform(self.axes)
return self._transform

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3 changes: 2 additions & 1 deletion lib/matplotlib/collections.py
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Expand Up @@ -158,7 +158,8 @@ def get_transforms(self):

def get_offset_transform(self):
t = self._transOffset
if not isinstance(t, transforms.Transform) and hasattr(t, '_as_mpl_transform'):
if (not isinstance(t, transforms.Transform)
and hasattr(t, '_as_mpl_transform')):
t = t._as_mpl_transform(self.axes)
return t

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9 changes: 7 additions & 2 deletions lib/matplotlib/streamplot.py
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Expand Up @@ -138,10 +138,15 @@ def streamplot(axes, x, y, u, v, density=1, linewidth=None, color=None,
line_colors.extend(color_values)
arrow_kw['color'] = cmap(norm(color_values[n]))

p = patches.FancyArrowPatch(arrow_tail, arrow_head, transform=transform, **arrow_kw)
p = patches.FancyArrowPatch(arrow_tail,
arrow_head,
transform=transform,
**arrow_kw)
axes.add_patch(p)

lc = mcollections.LineCollection(streamlines, transform=transform, **line_kw)
lc = mcollections.LineCollection(streamlines,
transform=transform,
**line_kw)
if use_multicolor_lines:
lc.set_array(np.asarray(line_colors))
lc.set_cmap(cmap)
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10 changes: 7 additions & 3 deletions lib/matplotlib/tests/test_transforms.py
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Expand Up @@ -66,7 +66,8 @@ def _as_mpl_transform(self, axes):
ax.set_xlim(0, 100)
ax.set_ylim(0, 100)
# assert that the top transform of the line is the scale transform.
np.testing.assert_allclose(line.get_transform()._a.get_matrix(), mtrans.Affine2D().scale(10).get_matrix())
np.testing.assert_allclose(line.get_transform()._a.get_matrix(),
mtrans.Affine2D().scale(10).get_matrix())


@image_comparison(baseline_images=['pre_transform_data'])
Expand All @@ -78,10 +79,13 @@ def test_pre_transform_plotting():

ax.contourf(np.arange(48).reshape(6, 8), transform=times10 + ax.transData)

ax.pcolormesh(np.linspace(0, 4, 7), np.linspace(5.5, 8, 9), np.arange(48).reshape(6, 8),
ax.pcolormesh(np.linspace(0, 4, 7),
np.linspace(5.5, 8, 9),
np.arange(48).reshape(6, 8),
transform=times10 + ax.transData)

ax.scatter(np.linspace(0, 10), np.linspace(10, 0), transform=times10 + ax.transData)
ax.scatter(np.linspace(0, 10), np.linspace(10, 0),
transform=times10 + ax.transData)


x = np.linspace(8, 10, 20)
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