matplotlib-devel Mailing List for matplotlib

On 07/13/2011 10:20 AM, Paul Ivanov wrote:
> Eric Firing, on 2011-07-13 09:54,  wrote:
>> ipython has moved to github for their homepage and documentation, but as
>> far as I can see, github has no facility for hosting downloads; the
>> ipython tarballs are on scipy.org.
>
> They are on scipy, github, and PyPI. Here are the ones for
> matplotlib:
>
> https://github.com/matplotlib/matplotlib/downloads

I don't know how I missed the "Downloads" button on the RHS of 
https://github.com/matplotlib/matplotlib.  It looks like we would need a 
much larger space allocation to include all the binary distributions.


>
>
>> Question: simply abandon v1.0.x-maint without a release?
>
> this makes sense to me. let's just make sure there's nothing
> there that never made it into trunk, but should have.

Fine with me, also.

Eric

Hi,

I will be on vacation with limited email from July 14 to August 7, 2011.

Bonjour,

Je serai en conge du 14 juillet jusqu'au 7 aout, 2011.

Eric Firing, on 2011-07-13 09:54,  wrote:
> ipython has moved to github for their homepage and documentation, but as 
> far as I can see, github has no facility for hosting downloads; the 
> ipython tarballs are on scipy.org.

They are on scipy, github, and PyPI. Here are the ones for
matplotlib:

https://github.com/matplotlib/matplotlib/downloads


> Question: simply abandon v1.0.x-maint without a release?

this makes sense to me. let's just make sure there's nothing
there that never made it into trunk, but should have.

best,
-- 
Paul Ivanov
314 address only used for lists,  off-list direct email at:
http://pirsquared.org | GPG/PGP key id: 0x0F3E28F7 

On Wed, Jul 13, 2011 at 2:54 PM, Eric Firing <ef...@ha...> wrote:

> As I recall, John had time to help in June, but less after that.  I
> don't think we ever reached an agreement as to schedule.  It simply went
> into slide mode.

I am back from my vacation so I have time again.  I figured since I
was leaving and people were making fantastic progress on pull requests
and tickets that it was best to wait.  But I'm available now to help
with the release.

>> Most documentation work that seems to remain are Animation module (and I
>> would love to find out if there is some way to embed a video using
>> sphinx) and the release-related documentation such as "what's new".
>> Also, do we plan to now host the documentation and downloads on github,
>> or are we still sticking with sourceforge for that?
>
> ipython has moved to github for their homepage and documentation, but as
> far as I can see, github has no facility for hosting downloads; the
> ipython tarballs are on scipy.org.

No strong opinions here.  It probably makes sense to move as much
stuff to github as possible now that the issue tracker has been moved,
but the sf download stuff is pretty good now and I haven't
investigated whether github offers equivalents.  Also, our donations
are processed through sf and they are non-negligible.  I found this
old post on github about accepting donations
https://github.com/blog/57-getting-paid-the-open-source-way; not sure
if this is still current.

>> This looks to be a very nice release!
>
> Question: simply abandon v1.0.x-maint without a release?

I would say yes here -- we can leave the branch around for a while in
case there is a reason to cut a release from it, but I don't think it
makes sense to do a release of the branch otherwise.

On 07/13/2011 08:58 AM, Benjamin Root wrote:
> Just wondering if there is any sort of agreement/target for cutting a
> v1.1.0 release?  I think we are very close.  Most of what I see that
> needs to be done are documentation-related (and I want to add a
> can_pan() function to mirror the can_zoom() function).

I think the last chunk of discussion is here:

http://www.mail-archive.com/mat...@li.../msg08276.html

As I recall, John had time to help in June, but less after that.  I 
don't think we ever reached an agreement as to schedule.  It simply went 
into slide mode.

>
> Most documentation work that seems to remain are Animation module (and I
> would love to find out if there is some way to embed a video using
> sphinx) and the release-related documentation such as "what's new".
> Also, do we plan to now host the documentation and downloads on github,
> or are we still sticking with sourceforge for that?

ipython has moved to github for their homepage and documentation, but as 
far as I can see, github has no facility for hosting downloads; the 
ipython tarballs are on scipy.org.

>
> This looks to be a very nice release!

Question: simply abandon v1.0.x-maint without a release?

Eric

> Ben Root
>

Just wondering if there is any sort of agreement/target for cutting a v1.1.0
release?  I think we are very close.  Most of what I see that needs to be
done are documentation-related (and I want to add a can_pan() function to
mirror the can_zoom() function).

Most documentation work that seems to remain are Animation module (and I
would love to find out if there is some way to embed a video using sphinx)
and the release-related documentation such as "what's new".  Also, do we
plan to now host the documentation and downloads on github, or are we still
sticking with sourceforge for that?

This looks to be a very nice release!
Ben Root

I'm starting to get a better sense of the code now.  One of the features 
of the current implementation is that images are resampled before going 
into the output of the vector backends, so that we can a) control file 
size and b) control the interpolation algorithm used.  It looks like 
that separation is maintained with this approach, only difference is 
that images can be both prerotated as well as prescaled now.  Is that 
correct?  (I must admit, I've work on bits and pieces of the image code 
at the edges, but I don't understand it in great detail).

It looks like overriding "draw_unsampled_image" is the wrong thing to do 
here, though.  The purpose of that function is to draw an image in a 
vector backend without any resampling at all -- and here you seem to be 
adding that.  It also only gets called when interpolation is "none" or 
"nearest", so your helpful changes currently don't work with other forms 
of interpolation.  I think we need to either add a function 
"_draw_sampled_image", or modify make_image so it returns an offset with 
the new location to draw the image (because rotation may cause the 
bounds of the image to be shifted).

This is great work, and is looking to be fairly significant.  Would you 
be able to set up a personal git fork and branch for you work?  It would 
make it easier for the rest of us to evaluate what you have done and 
kick the tires a bit.  The outline of how to do this is here:

http://matplotlib.sourceforge.net/devel/gitwash/index.html

Cheers,
Mike

On 07/12/2011 06:01 AM, Martin Teichmann wrote:
> Dear List,
> dear Michael,
>
>> Looks good.  Does matplotlib still pass all regression tests with this
>> change?
> It does pass all regression tests that were passed with the git version
> I started with. (There were 10 failures which are still there).
>
> In the meantime, I also wrote a class that already uses my extension.
> With it, you can plot rotated or sheared images with all backends.
> (There were some quirks to get sheard images on some backends,
> see examples/api/demo_affine_image.py, but it worked on some backends
> only).
>
> While writing it, I found some inconsistencies in matplotlib:
>
> - bounding boxes are not correctly transformed. BboxBase.tranformed only
> transformes the outer points of a bounding box, if you rotate it, this will give
> wrong results for several angles. I wrote a function that should be correct for
> all affine transformations:
>
> def transform_bbox(bbox, trans):
>      x0, y0, x1, y1 = bbox.extents
>      tx0, ty0 = trans.transform([x0, y0])
>      tx1, ty1 = trans.transform([x1, y1])
>      tx2, ty2 = trans.transform([x1, y0])
>      tx3, ty3 = trans.transform([x0, y1])
>      return Bbox.from_extents(min(tx0, tx1, tx2, tx3), min(ty0, ty1, ty2, ty3),
>          max(tx0, tx1, tx2, tx3), max(ty0, ty1, ty2, ty3))
>
> - The other inconsistency is that within matplotlib, extents are
> defined different:
> in imshow,  the parameter extent expects the order (left, right, bottom, top),
> while BboxBase.extents is (left, bottom, right, top). This should be changed in
> the future, maybe the move to python 3 is a good time for that?
>
> But now to my code to draw images. It's a new class inheriting AxesImage,
> but is supposed to once replace AxesImage, as it is compatible.
>
> I'm re-writing _draw_unsampled_image, to actually draw a sampled image.
> Thats only because make_image, the method to be rewritten for a sampled
> image, is not flexible enough (the caller draws the image, but there is no way
> for make_image to tell where that image is to be put). In the future,
> the methods
> should be renamed (it's a private method, so that's no problem).
>
> class ShearImage(AxesImage):
>      def _check_unsampled_image(self, _):
>          return True
>
>      def _draw_unsampled_image(self, renderer, gc):
>          """
>          actually, draw sampled image. This method is more flexible than
>          make_image
>          """
>          mag = renderer.get_image_magnification()
>          trans = Affine2D().scale(mag, mag) + self.get_transform() + \
>              self.axes.transData.get_affine()
>          bbox = self.axes.bbox
>          viewLim = transform_bbox(bbox, trans.inverted())
>
>          im, xmin, ymin, dxintv, dyintv, sx, sy = \
>              self._get_unsampled_image(self._A, self.get_extent(), viewLim)
>
>          if im is None: return # I'm not if this check is required. -JJL
>          im.set_interpolation(self._interpd[self._interpolation])
>          im.set_resample(self._resample)
>
>          fc = self.axes.patch.get_facecolor()
>          bg = mcolors.colorConverter.to_rgba(fc, 0)
>          im.set_bg( *bg)
>     # uncomment the following line to see the extent to which the image
>     # is drawn
>     #     im.set_bg(0, 0, 0, 100)
>          numrows, numcols = im.get_size()
>
>          ex = self.get_extent()
>          tex = Bbox.from_extents([ex[0], ex[2], ex[1], ex[3]])
>          tex = transform_bbox(tex, trans)
>          if tex.xmin<  bbox.xmin:
>              left = bbox.xmin
>              tx = 0
>          else:
>              left = tex.xmin
>              tx = tex.xmin - bbox.xmin
>          if tex.ymin<  bbox.ymin:
>              bottom = bbox.ymin
>              ty = 0
>          else:
>              bottom = tex.ymin
>              ty = tex.ymin - bbox.ymin
>          trans = Affine2D().scale(dxintv / numcols,
>                  dyintv / numrows).translate(xmin, ymin) + \
>                  trans + \
>                  Affine2D().translate(-bbox.xmin - tx, -bbox.ymin - ty)
>          im.set_matrix(*trans.get_matrix()[:2, :].T.ravel())
>
>          width = min(tex.xmax, bbox.xmax) - left
>          height = min(tex.ymax, bbox.ymax) - bottom
>          if width<= 0 or height<= 0:
>              return
>          im.resize(width * mag, height * mag,
>              norm=self._filternorm, radius=self._filterrad)
>
>          im._url = self.get_url()
>
>          renderer.draw_image(gc, left, bottom, im)
>
> Last but not least, a little script to test the above. It shows a rotated
> image. You can scale and move the image nicely. If you uncomment the
> line mentioned above in ShearImage code, you can see where the
> image is actually drawn, and you will see that only the necessary parts
> are drawn if the image is smaller than the entire axes.
> The test script follows:
>
> from pylab import *
> ax = axes()
> im = ShearImage(ax)
> im.set_data(fromfunction(lambda x, y: sin(x + y ** 2), (100, 100)))
> im.set_extent(im.get_extent())
> transform = Affine2D().rotate_deg(30)
> im.set_transform(transform)
> ax.images.append(im)
> show()
>
> Greetings
>
> Martin
>
> ------------------------------------------------------------------------------
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On Tue, Jul 12, 2011 at 7:01 PM, Martin Teichmann
<mar...@mb...> wrote:
> (There were some quirks to get sheard images on some backends,
> see examples/api/demo_affine_image.py, but it worked on some backends
> only).

I didn't have time to go through your code carefully, but my
understanding is that you rely on Agg to get a transformed image
(resampled image) and provide that image to backends, right? Note that
when interpolation mode is "none", resampling should be prohibited.
There is a good reason why we implemented the "none" interpolation
mode even though this is not supported for some backends. Overriding
this behavior (which I guess is the case of you current ShearImage
implementation. Please correct me if I'm wrong) won't be acceptable.
Please makes sure that resampling of images only happens when the
interpolation mode is not "none".

Regards,

-JJ