matplotlib-users Mailing List for matplotlib

On 2015年02月17日 12:24 PM, Luke Lee wrote:
> It's been suggested to on the above tracker to use imshow. However, that
> doesn't address the issue I'm having using PolyCollection.
I don't think this has anything to do with PolyCollection versus Image, 
and I was not suggesting that you use imshow. What I am suggesting is 
that you take my example and make the minimal changes required to 
convert it back to using your PolyCollection; or go the other way. I 
think the key point is the call to the colorbar method.
Eric

I'm trying to control the over and under colors of a color bar with
set_under
and set_over on a ListedColormap object. I do not see the colors change,
but I
do see the arrows added to the color bar.
For example, the following code mostly works but the calls to set_under and
set_over seem to have no effect. I'm trying to use the color bar
documentation
at http://matplotlib.org/examples/api/colorbar_only.html as a guide. Maybe
I'm
doing something wrong or the example is slightly off?
I'm using matplotlib 1.4.0.
You can see examples of the images I'm generating here:
 - https://github.com/matplotlib/matplotlib/issues/4117
It's been suggested to on the above tracker to use imshow. However, that
doesn't address the issue I'm having using PolyCollection. In addition, I'm
not sure how to translate my example below so that it will work with imshow
because I'm trying to plot a 2D slice of a 3D array.
The code in question is below. Sorry for not including re-usable array data
in
the example. My specific case is with a large 3D array that has several
thousands vertices, etc. Again, you can see the image examples here:
 - https://github.com/matplotlib/matplotlib/issues/4117
import numpy
import matplotlib as mpl
import matplotlib.pyplot as plt
from matplotlib.collections import PolyCollection
vertices = numpy.load('vertices.npy')
array = numpy.load('array.npy')
# Take 2d slice out of 3D array
slice_ = array[:, :, 0:1].flatten(order='F')
fig, ax = plt.subplots()
poly = PolyCollection(vertices, array=slice_, edgecolors='black',
linewidth=.25)
cm = mpl.colors.ListedColormap([(1.0, 0.0, 0.0), (.2, .5, .2)])
cm.set_under('0.75')
cm.set_over('DarkViolet')
poly.set_cmap(cm)
bounds = [.1, .4, .6]
norm = mpl.colors.BoundaryNorm(bounds, cm.N)
bounds = [0.0] + bounds + [1.0]
fig.colorbar(poly, ax=ax, orientation='vertical', boundaries=bounds,
norm=norm, extend='both')
ax.add_collection(poly, autolim=True)
ax.autoscale_view()
plt.show()
Thanks,
Luke

Tom and other devs,
Thanks for all the hard work! Looking forward to making the upgrade.
Just curious if there is a detailed roadmap for v2 and beyond. I feel like
there have been some rumors that the get/set architecture will be
deprecated at some point.
Ryan
On Tue, Feb 17, 2015 at 4:30 AM, Nelle Varoquaux <nel...@gm...>
wrote:
> Thanks again Thomas for the release !
> Cheers,
> N
>
> On 17 February 2015 at 06:09, Thomas Caswell <tca...@gm...> wrote:
> > Hello all,
> >
> > We are pleased to announce the release of matplotlib v1.4.3!
> >
> > Wheels, windows binaries and the source tarball are available through
> both
> > source-forge [1] and pypi (via pip). Additionally the source is
> available
> > tarball is available from github [2] and mac-wheels from
> > http://wheels.scikit-image.org/.
> >
> > This is the last planned bug-fix release in the 1.4 series.
> >
> > Many bugs are fixed including:
> >
> > fixing drawing of edge-only markers in AGG
> > fix run-away memory usage when using %inline or saving with a tight
> bounding
> > box with QuadMesh artists
> > improvements to wx and tk gui backends
> >
> > Additionally the webagg and nbagg backends were brought closer to
> > feature parity with the desktop backends with the addition of keyboard
> > and scroll events thanks to Steven Silvester.
> >
> > The next planned release will be based on the 1.4.x series but will
> change
> > the default colors and be tagged as version v2.0. The target release
> date is
> > in the next month or two.
> >
> > The next feature release will be v2.1 targeted for around SciPy in July.
> >
> > Tom
> >
> >
> > [1]
> >
> https://sourceforge.net/projects/matplotlib/files/matplotlib/matplotlib-1.4.3/
> >
> > [2] https://github.com/matplotlib/matplotlib/releases/tag/v1.4.3
> >
> >
> >
> >
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> >
>
>
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Only number 3.
Sydney
On 16/02/2015 18:16, Benjamin Root wrote:
> I am in the final rounds of edits for my book and a question has come 
> up between me and the editors. When should the matplotlib be capitalized?
>
> 1) never
> 2) mostly never (even in the beginning of a sentence), except when 
> used in a title
> 3) usually never, except at the beginning of a sentence and in titles
> 4) capitalize when referring to the project, not capitalized when 
> referring to the package
> 5) usually capitalize like a proper noun except in code examples
>
> Thoughts?
> Ben Root
>
>
> ------------------------------------------------------------------------------
> Download BIRT iHub F-Type - The Free Enterprise-Grade BIRT Server
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>
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-- 
Sydney

Thanks again Thomas for the release !
Cheers,
N
On 17 February 2015 at 06:09, Thomas Caswell <tca...@gm...> wrote:
> Hello all,
>
> We are pleased to announce the release of matplotlib v1.4.3!
>
> Wheels, windows binaries and the source tarball are available through both
> source-forge [1] and pypi (via pip). Additionally the source is available
> tarball is available from github [2] and mac-wheels from
> http://wheels.scikit-image.org/.
>
> This is the last planned bug-fix release in the 1.4 series.
>
> Many bugs are fixed including:
>
> fixing drawing of edge-only markers in AGG
> fix run-away memory usage when using %inline or saving with a tight bounding
> box with QuadMesh artists
> improvements to wx and tk gui backends
>
> Additionally the webagg and nbagg backends were brought closer to
> feature parity with the desktop backends with the addition of keyboard
> and scroll events thanks to Steven Silvester.
>
> The next planned release will be based on the 1.4.x series but will change
> the default colors and be tagged as version v2.0. The target release date is
> in the next month or two.
>
> The next feature release will be v2.1 targeted for around SciPy in July.
>
> Tom
>
>
> [1]
> https://sourceforge.net/projects/matplotlib/files/matplotlib/matplotlib-1.4.3/
>
> [2] https://github.com/matplotlib/matplotlib/releases/tag/v1.4.3
>
>
>
> ------------------------------------------------------------------------------
> Download BIRT iHub F-Type - The Free Enterprise-Grade BIRT Server
> from Actuate! Instantly Supercharge Your Business Reports and Dashboards
> with Interactivity, Sharing, Native Excel Exports, App Integration & more
> Get technology previously reserved for billion-dollar corporations, FREE
> http://pubads.g.doubleclick.net/gampad/clk?id=190641631&iu=/4140/ostg.clktrk
> _______________________________________________
> Matplotlib-devel mailing list
> Mat...@li...
> https://lists.sourceforge.net/lists/listinfo/matplotlib-devel
>

Hello all,
We are pleased to announce the release of matplotlib v1.4.3!
Wheels, windows binaries and the source tarball are available through both
source-forge [1] and pypi (via pip). Additionally the source is available
tarball is available from github [2] and mac-wheels from
http://wheels.scikit-image.org/.
This is the last planned bug-fix release in the 1.4 series.
Many bugs are fixed including:
 - fixing drawing of edge-only markers in AGG
 - fix run-away memory usage when using %inline or saving with a tight
 bounding box with QuadMesh artists
 - improvements to wx and tk gui backends
Additionally the webagg and nbagg backends were brought closer to
feature parity with the desktop backends with the addition of keyboard
and scroll events thanks to Steven Silvester.
The next planned release will be based on the 1.4.x series but will change
the default colors and be tagged as version v2.0. The target release date
is in the next month or two.
The next feature release will be v2.1 targeted for around SciPy in July.
Tom
[1]
https://sourceforge.net/projects/matplotlib/files/matplotlib/matplotlib-1.4.3/
[2] https://github.com/matplotlib/matplotlib/releases/tag/v1.4.3