matplotlib-users Mailing List for matplotlib (Page 14)

Hello All,

I am working with Basemap and loading several shapefiles using checkboxes in python. However, when I uncheck a checkbox I would like a shapefile to be removed and stay with the other shapefiles that are already loaded. I tried reloading and replotting the whole thing when I remove a checkbox but it will remove all the other shapefiles as well. In simpler words, is it possible to remove a shapefile from Basemap after m.readshapefile() has been called?

Thanks in advance

Head over to https://www.euroscipy.org/2015/ for more information.

On 2015/06/30 6:41 AM, Benjamin Root wrote:
> It looks like your X data is one element larger than it needs to be. I
> know pcolor() accepts grids that are (N+1,M+1), and I *think* pcolormesh
> does the same. It will also accept grids that are (N,M) as well, but
> will drop the last row and collumn.

Yes, pcolormesh and pcolor use the same argument parsing and checking. 
They actually *want* N+1, M+1; the *acceptance* of N, M is a matlab-ism 
that is convenient for quick looks, but is also a potential source of error.

The OP has an X dimension of M+2, which indicates an error earlier in 
the OP's code.

Eric

Well, the way those work is essentially overlay one axes object over
another along with some extra fanagiling to link up the shared axis and put
ticks on opposing sides. If your projection is already available as an
axes, then you are good to go that way. However, it sounds what you want is
to have some things follow one transform while others follow another? That
is certainly doable, it is just a question of bookkeeping.

I would check to see if the axis_artist1 toolkit supplies what you need (or
at least some of it).

Ben Root


On Tue, Jun 30, 2015 at 1:20 PM, T J <tj...@gm...> wrote:

> Ok, sounds like I'll have to copy what those do, as I'm not planning on
> working with Cartesian or even curvilinear coordinates.
>
> On Tue, Jun 30, 2015 at 11:36 AM, Benjamin Root <ben...@ou...> wrote:
>
>> twinx()/twiny() I think is your best bet. It isn't a fully generic
>> solution, but I think it addresses most needs.
>>
>> Ben Root
>>
>> On Mon, Jun 29, 2015 at 6:00 PM, T J <tj...@gm...> wrote:
>>
>>> When I read the transformations documentation:
>>>
>>>
>>> http://matplotlib.org/devel/add_new_projection.html#creating-a-new-projection
>>>
>>> it seems like each projection is tied to an Axes instance.  How might I
>>> go about plotting two different projections on the same axes? Let's just
>>> assume that the actual axes each projection draws is exactly same and all
>>> that differs between to the two is how data is mapped to axis coordinates.
>>>
>>>
>>>
>>>
>>> ------------------------------------------------------------------------------
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>>>
>>>
>>
>

Ok, sounds like I'll have to copy what those do, as I'm not planning on
working with Cartesian or even curvilinear coordinates.

On Tue, Jun 30, 2015 at 11:36 AM, Benjamin Root <ben...@ou...> wrote:

> twinx()/twiny() I think is your best bet. It isn't a fully generic
> solution, but I think it addresses most needs.
>
> Ben Root
>
> On Mon, Jun 29, 2015 at 6:00 PM, T J <tj...@gm...> wrote:
>
>> When I read the transformations documentation:
>>
>>
>> http://matplotlib.org/devel/add_new_projection.html#creating-a-new-projection
>>
>> it seems like each projection is tied to an Axes instance.  How might I
>> go about plotting two different projections on the same axes? Let's just
>> assume that the actual axes each projection draws is exactly same and all
>> that differs between to the two is how data is mapped to axis coordinates.
>>
>>
>>
>>
>> ------------------------------------------------------------------------------
>> Don't Limit Your Business. Reach for the Cloud.
>> GigeNET's Cloud Solutions provide you with the tools and support that
>> you need to offload your IT needs and focus on growing your business.
>> Configured For All Businesses. Start Your Cloud Today.
>> https://www.gigenetcloud.com/
>> _______________________________________________
>> Matplotlib-users mailing list
>> Mat...@li...
>> https://lists.sourceforge.net/lists/listinfo/matplotlib-users
>>
>>
>

Yeah, this is a long-standing design issue:
https://github.com/matplotlib/matplotlib/issues/1483

There are some changes that are happening that would make it possible for
me to refactor mplot3d in a way that would make this feasible. I could bite
the bullet and just provide a partial workaround to this problem by
providing a get_3d_data() method to each Artist3D subclass. Should be a
fairly easy task for someone at SciPy 2015.

On Tue, Jun 30, 2015 at 11:51 AM, kola <ko...@sp...> wrote:

> Hi,
>
> I am able to use set_3d_properties to set z data for my 3D line. However,
> if
> I want to get the zdata, I cannot find a function like get_zdata or
> get_3d_properites.
>
> Is there anyway to get the zdata associated with the line?
>
> Thanks,
> Kola
>
>
>
> --
> View this message in context:
> http://matplotlib.1069221.n5.nabble.com/get-3d-properties-tp45851.html
> Sent from the matplotlib - users mailing list archive at Nabble.com.
>
>
> ------------------------------------------------------------------------------
> Don't Limit Your Business. Reach for the Cloud.
> GigeNET's Cloud Solutions provide you with the tools and support that
> you need to offload your IT needs and focus on growing your business.
> Configured For All Businesses. Start Your Cloud Today.
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> _______________________________________________
> Matplotlib-users mailing list
> Mat...@li...
> https://lists.sourceforge.net/lists/listinfo/matplotlib-users
>

It looks like your X data is one element larger than it needs to be. I know
pcolor() accepts grids that are (N+1,M+1), and I *think* pcolormesh does
the same. It will also accept grids that are (N,M) as well, but will drop
the last row and collumn.

Given your statement that it sometimes works, I suspect you have a bug in
your code somewhere that is causing your Xs and Ys to not always be exactly
the length you'd expect them to be.

I hope that helps!
Ben Root


On Mon, Jun 29, 2015 at 2:06 PM, Ronquillo, Edgar Nahum <ero...@la...
> wrote:

>  Hello,
>
> I am getting this error when I try calling pcolormesh this way:
>
>
>
> pcolormesh(x, y, data.T, cmap=cmap, vmin=0, vmax=100)
>
>
>
> I am doing the transpose of data so I don’t know what could be causing
> this. By the way, it does work with some images. Any suggestions?
>
>
>
> Thanks in advance
>
>
> ------------------------------------------------------------------------------
> Don't Limit Your Business. Reach for the Cloud.
> GigeNET's Cloud Solutions provide you with the tools and support that
> you need to offload your IT needs and focus on growing your business.
> Configured For All Businesses. Start Your Cloud Today.
> https://www.gigenetcloud.com/
> _______________________________________________
> Matplotlib-users mailing list
> Mat...@li...
> https://lists.sourceforge.net/lists/listinfo/matplotlib-users
>
>

twinx()/twiny() I think is your best bet. It isn't a fully generic
solution, but I think it addresses most needs.

Ben Root

On Mon, Jun 29, 2015 at 6:00 PM, T J <tj...@gm...> wrote:

> When I read the transformations documentation:
>
>
> http://matplotlib.org/devel/add_new_projection.html#creating-a-new-projection
>
> it seems like each projection is tied to an Axes instance.  How might I go
> about plotting two different projections on the same axes? Let's just
> assume that the actual axes each projection draws is exactly same and all
> that differs between to the two is how data is mapped to axis coordinates.
>
>
>
>
> ------------------------------------------------------------------------------
> Don't Limit Your Business. Reach for the Cloud.
> GigeNET's Cloud Solutions provide you with the tools and support that
> you need to offload your IT needs and focus on growing your business.
> Configured For All Businesses. Start Your Cloud Today.
> https://www.gigenetcloud.com/
> _______________________________________________
> Matplotlib-users mailing list
> Mat...@li...
> https://lists.sourceforge.net/lists/listinfo/matplotlib-users
>
>

Hi,

I am able to use set_3d_properties to set z data for my 3D line. However, if
I want to get the zdata, I cannot find a function like get_zdata or
get_3d_properites.

Is there anyway to get the zdata associated with the line?

Thanks,
Kola



--
View this message in context: http://matplotlib.1069221.n5.nabble.com/get-3d-properties-tp45851.html
Sent from the matplotlib - users mailing list archive at Nabble.com.

When I read the transformations documentation:

http://matplotlib.org/devel/add_new_projection.html#creating-a-new-projection

it seems like each projection is tied to an Axes instance.  How might I go
about plotting two different projections on the same axes? Let's just
assume that the actual axes each projection draws is exactly same and all
that differs between to the two is how data is mapped to axis coordinates.

Hello,
I am getting this error when I try calling pcolormesh this way:

pcolormesh(x, y, data.T, cmap=cmap, vmin=0, vmax=100)

I am doing the transpose of data so I don't know what could be causing this. By the way, it does work with some images. Any suggestions?

Thanks in advance

Also keep in mind that we consider all of the c extensions to be part of
the private api and do not worry so much about breaking them.

Tom

On Thu, Jun 25, 2015, 3:45 PM Benjamin Root <ben...@ou...> wrote:

> _cntr.so has been deprecated (it might take a couple of releases before we
> remove it entirely). _contour.so has a newer, better interface and comes
> with a python wrapper.  Don't know if that is an issue at all for you, just
> noting that is the case.
>
> I might also suggest looking at scikit-image, as I think it has some
> contouring algorithms that might be easier to link to.
>
> Ben Root
>
> On Thu, Jun 25, 2015 at 2:28 PM, Sterling Smith <sm...@fu...>
> wrote:
>
>> The contour finder in matplotlib is more robust than I currently have in
>> a legacy fortran project.  I would like to link to matplotlib’s instead.
>> Has anyone done this before?  Are there any suggestions or pitfalls for
>> proceeding?
>>
>> Thanks,
>> Sterling
>>
>> ------------------------------------------------------------------------------
>> Monitor 25 network devices or servers for free with OpManager!
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>> for fault. Monitor 25 devices for free with no restriction. Download now
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>> _______________________________________________
>> Matplotlib-users mailing list
>> Mat...@li...
>> https://lists.sourceforge.net/lists/listinfo/matplotlib-users
>>
>
>
> ------------------------------------------------------------------------------
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> OpManager is web-based network management software that monitors
> network devices and physical & virtual servers, alerts via email & sms
> for fault. Monitor 25 devices for free with no restriction. Download now
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> https://lists.sourceforge.net/lists/listinfo/matplotlib-users
>

Hi everyone,

I have just released a small plugin for py.test that wraps the image
comparison functionality in matplotlib.testing, for use in other
packages that use py.test as the testing framework instead of nose:

  https://github.com/astrofrog/pytest-mpl

The idea is to make it easy to write a test such as:

    @pytest.mark.mpl_image_compare
    def test_succeeds():
        fig = plt.figure()
        ax = fig.add_subplot(1,1,1)
        ax.plot([1,2,3])
        return fig

which can then be run in three ways:

- Running py.test as usual will simply check the tests run but won't
check whether the figure is correct.

- Running py.test with the --mpl option will make sure that the figure
produced by the test is the same as a reference image

- Running py.test with the --mpl-generate-path option will generate the
reference images from the tests themselves.

There are a number of other options, including ways to pass arguments to
savefig, customizing the image names, or setting the tolerance for the
comparison. All the documentation is contained in the README.md file:

  https://github.com/astrofrog/pytest-mpl/blob/master/README.md

You can install this plugin with:

  pip install pytest-mpl

I would welcome any feedback and/or contributions!

Cheers,
Tom

_cntr.so has been deprecated (it might take a couple of releases before we
remove it entirely). _contour.so has a newer, better interface and comes
with a python wrapper.  Don't know if that is an issue at all for you, just
noting that is the case.

I might also suggest looking at scikit-image, as I think it has some
contouring algorithms that might be easier to link to.

Ben Root

On Thu, Jun 25, 2015 at 2:28 PM, Sterling Smith <sm...@fu...>
wrote:

> The contour finder in matplotlib is more robust than I currently have in a
> legacy fortran project.  I would like to link to matplotlib’s instead.  Has
> anyone done this before?  Are there any suggestions or pitfalls for
> proceeding?
>
> Thanks,
> Sterling
>
> ------------------------------------------------------------------------------
> Monitor 25 network devices or servers for free with OpManager!
> OpManager is web-based network management software that monitors
> network devices and physical & virtual servers, alerts via email & sms
> for fault. Monitor 25 devices for free with no restriction. Download now
> http://ad.doubleclick.net/ddm/clk/292181274;119417398;o
> _______________________________________________
> Matplotlib-users mailing list
> Mat...@li...
> https://lists.sourceforge.net/lists/listinfo/matplotlib-users
>

The contour finder in matplotlib is more robust than I currently have in a legacy fortran project.  I would like to link to matplotlib’s instead.  Has anyone done this before?  Are there any suggestions or pitfalls for proceeding?

Thanks,
Sterling

The mplot3d tutorial page, which is the first result when you google
'mplot3d', includes a section on 'Tri-surface plots' and is precisely what
you are looking for.

You certainly do not need to use scipy.  Matplotlib includes its own
Delaunay triangulator, as specified in the 'triangular grids'
documentation, which is the first result when you google 'matplotlib
triangulation'.

Ian


On 25 June 2015 at 12:22, Philipp A. <fly...@we...> wrote:

> hi!
>
> do a delaunay triangulation
> <http://docs.scipy.org/doc/scipy-0.14.0/reference/generated/scipy.spatial.Delaunay.html>
> on them.
>
> also try to do the triangulation only on the xy coordinates and see which
> of both gives the results you like more.
>
> best, p
>
> justonium <jus...@gm...> schrieb am Do., 25. Juni 2015 um
> 05:21 Uhr:
>
>> I have a set of three dimensional coordinates, each of which is on a
>> landscape. I would like to visualize the entire landscape.
>>
>> I've already tried plotting the points in 3D space using Axes3D.scatter,
>> but
>> I just see a bunch of points, and it's hard to visually understand what's
>> going on.
>>
>> Ideally, I would like to view a wireframe plot. In order for this to be
>> drawn, height values will need to be interpolated from the samples that I
>> have, which don't line up with a grid.
>>
>> Another solution might be:
>>
>> For each point, draw a vertical line from it, straight down, to a point
>> below it which has the same x and y coordinates, with 0 as the z
>> coordinate.
>> This might still be difficult to visually understand.
>>
>>
>>
>> --
>> View this message in context:
>> http://matplotlib.1069221.n5.nabble.com/How-can-I-visualize-a-landscape-which-I-have-sample-heights-of-tp45834.html
>> Sent from the matplotlib - users mailing list archive at Nabble.com.
>>
>>
>> ------------------------------------------------------------------------------
>> Monitor 25 network devices or servers for free with OpManager!
>> OpManager is web-based network management software that monitors
>> network devices and physical & virtual servers, alerts via email & sms
>> for fault. Monitor 25 devices for free with no restriction. Download now
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>> _______________________________________________
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>> https://lists.sourceforge.net/lists/listinfo/matplotlib-users
>>
>
>
> ------------------------------------------------------------------------------
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> OpManager is web-based network management software that monitors
> network devices and physical & virtual servers, alerts via email & sms
> for fault. Monitor 25 devices for free with no restriction. Download now
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>
>

Is there any way to do this?  The example here works in Cartesian
coordinates:

http://matplotlib.org/examples/pylab_examples/coords_report.html

but if you change

subplots()

to

subplots(subplot_kw={'polar':True})

Then the millions() function is never even called.

Thanks,
Alex

hi!

do a delaunay triangulation
<http://docs.scipy.org/doc/scipy-0.14.0/reference/generated/scipy.spatial.Delaunay.html>
on them.

also try to do the triangulation only on the xy coordinates and see which
of both gives the results you like more.

best, p

justonium <jus...@gm...> schrieb am Do., 25. Juni 2015 um
05:21 Uhr:

> I have a set of three dimensional coordinates, each of which is on a
> landscape. I would like to visualize the entire landscape.
>
> I've already tried plotting the points in 3D space using Axes3D.scatter,
> but
> I just see a bunch of points, and it's hard to visually understand what's
> going on.
>
> Ideally, I would like to view a wireframe plot. In order for this to be
> drawn, height values will need to be interpolated from the samples that I
> have, which don't line up with a grid.
>
> Another solution might be:
>
> For each point, draw a vertical line from it, straight down, to a point
> below it which has the same x and y coordinates, with 0 as the z
> coordinate.
> This might still be difficult to visually understand.
>
>
>
> --
> View this message in context:
> http://matplotlib.1069221.n5.nabble.com/How-can-I-visualize-a-landscape-which-I-have-sample-heights-of-tp45834.html
> Sent from the matplotlib - users mailing list archive at Nabble.com.
>
>
> ------------------------------------------------------------------------------
> Monitor 25 network devices or servers for free with OpManager!
> OpManager is web-based network management software that monitors
> network devices and physical & virtual servers, alerts via email & sms
> for fault. Monitor 25 devices for free with no restriction. Download now
> http://ad.doubleclick.net/ddm/clk/292181274;119417398;o
> _______________________________________________
> Matplotlib-users mailing list
> Mat...@li...
> https://lists.sourceforge.net/lists/listinfo/matplotlib-users
>

I have a set of three dimensional coordinates, each of which is on a
landscape. I would like to visualize the entire landscape.

I've already tried plotting the points in 3D space using Axes3D.scatter, but
I just see a bunch of points, and it's hard to visually understand what's
going on.

Ideally, I would like to view a wireframe plot. In order for this to be
drawn, height values will need to be interpolated from the samples that I
have, which don't line up with a grid.

Another solution might be:

For each point, draw a vertical line from it, straight down, to a point
below it which has the same x and y coordinates, with 0 as the z coordinate.
This might still be difficult to visually understand.



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Sent from the matplotlib - users mailing list archive at Nabble.com.

Hi Egayer,

Filipe Fernandes spoted a nice result using Simplekml and Basemap.

https://ocefpaf.github.io/python4oceanographers/blog/2014/03/10/gearth/

Cheers,
Arnaldo.


2015-06-10 5:07 GMT-03:00 egayer <eg...@ip...>:

> Hi all,
>
> Is there a way to produce a KML file from matplolib results as R and Matlab
> do ?
>
> - plotKML is a R package http://plotkml.r-forge.r-project.org
> - Matlab has the Google Earth Toolbox.
>
> Both of them allow to plot directly on GE
>
> I' have been digging around and found this old post :"Producing a
> KML-friendly (Google Earth) image" but nothing about how to actually a
> matplolib result as a KML file useable into Google Earth.
>
> I have seen some shape to KML packages, but nothing about raster.
>
> The ultimate goal being to use the "plot, mplot3d, imshow, etc..." to plot
> any python array on GE.
>
> Thanks for your help
> Eric
>
>
>
>
>
> --
> View this message in context:
> http://matplotlib.1069221.n5.nabble.com/Produce-KML-from-Matplolib-tp45759.html
> Sent from the matplotlib - users mailing list archive at Nabble.com.
>
>
> ------------------------------------------------------------------------------
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> Mat...@li...
> https://lists.sourceforge.net/lists/listinfo/matplotlib-users
>

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On 2015/06/23 10:39 AM, Eric Firing wrote:
> I would like to be able to publish plots that are updated as data are
> received by the server.  I don't actually want any of the toolbar
> interactivity--I just want the updated plot to appear in the browser
> automatically.  I suspect this can all be done quite easily using the
> webagg backend, but I have not yet figured it out by looking at the
> embedding_in_webagg.py example and the backend_webagg* code.  I expect
> that stripping out the toolbar is straightforward, but what I don't
> understand is how to achieve the dynamic updates, preferably without
> using the animation framework, which I think would add unnecessary
> complexity.
>
> Are there any other examples floating around that would help?
>
> Thanks.
>
> Eric

To answer my own question, in case anyone else is interested, here is a 
block of code that can be substituted for the corresponding elements of 
the embedding_in_webagg.py example.  The whole block goes at the bottom.

-------------------------------------------------
def create_figure():
     fig = Figure()
     ax = fig.add_subplot(1,1,1)
     ax.set_xlim(0, 1)
     ax.set_ylim(0, 1)
     line, = ax.plot([], [], 'r-')
     return fig, line

if __name__ == "__main__":
     figure, line = create_figure()
     application = MyApplication(figure)

     http_server = tornado.httpserver.HTTPServer(application)
     http_server.listen(8080)

     print("http://127.0.0.1:8080/")
     print("Press Ctrl+C to quit")

     def update2():
         line.set_data(np.random.rand(2, 25))
         figure.canvas.draw_idle()

     io_loop = tornado.ioloop.IOLoop.instance()
     cb = tornado.ioloop.PeriodicCallback(update2, 1000)
     cb.start()

     io_loop.start()
----------------------------------------------------------

Instead of the using the PeriodicCallback I will probably be using 
ZMQStream.on_recv() to register a callback on a socket, but that doesn't 
change the basic structure.

Eric

I would like to be able to publish plots that are updated as data are 
received by the server.  I don't actually want any of the toolbar 
interactivity--I just want the updated plot to appear in the browser 
automatically.  I suspect this can all be done quite easily using the 
webagg backend, but I have not yet figured it out by looking at the 
embedding_in_webagg.py example and the backend_webagg* code.  I expect 
that stripping out the toolbar is straightforward, but what I don't 
understand is how to achieve the dynamic updates, preferably without 
using the animation framework, which I think would add unnecessary 
complexity.

Are there any other examples floating around that would help?

Thanks.

Eric

One thing you can do which may work is to partition your plots 'by hand'.

It is not super elegant, but might get you the desired behavior.  As long
as the number of partitions is low it shouldn't hurt performance _too_ much.

def z_jitter_plot(ax, x, y, partitions=10, **kwargs):
    labels = np.random.randint(0, partitions, len(y))
    z_levels = 1 + np.random.rand(partitions)
    lns = []
    for n, z in enumerate(z_levels):
        ln = ax.plot(x[labels==n], y[labels==n], zorder=z, **kwargs)
        lns.extend(ln)

    return lns


fig, ax = plt.subplots()
N = 2500
all_lns = []
for j, c in enumerate('rgbk'):
    x = np.linspace(0, 1, N)
    y = np.random.randn(N)
    lns = z_jitter_plot(ax, x, y, partitions=100, color=c, ls='',
markersize=52, marker='o')
    all_lns.extend(lns)

Throwing in `alpha=.5` might also help a bit.

You will have to manage the color cycle your self here as this plots many
lines (each of which wants to advance the color cycle) per data set.

Tom

On Tue, Jun 23, 2015 at 2:16 PM Benjamin Root <ben...@ou...> wrote:

> Right, when zorder is not explicitly specified, all the artists of the
> same type get the same default zorder (I think 2, but I can't remember). We
> then use a stable sort to determine the draw order, so two artists with the
> same zorder are drawn in the order that they were created (the exception
> being mplot3d, because it mucks about with zorders to achieve the 3d
> effect).
>
> Ben Root
>
> On Tue, Jun 23, 2015 at 1:53 PM, Jody Klymak <jk...@uv...> wrote:
>
>>
>> For my backend (nbagg), the order of the data determines the order of
>> drawing.  So in the following, the third diamond covers the first two in
>> the first plot, but the first diamond covers them all in the second plot.
>> Perhaps not as elegant as a matrix zorder, but can achieve the effect you
>> are after.
>>
>> Cheers,   Jody
>>
>> fig, ax = plt.subplots(2,1)
>> x = np.arange(3)
>> y = 0.*x
>> ax[0].plot(x,y,'d',markersize=52)
>> ax[0].set_xlim(-10.,10.)
>> ax[1].plot(x[[2,1,0]],y[[2,1,0]],'d',markersize=52)
>> ax[1].set_xlim(-10.,10.)
>>
>>
>> On Jun 23, 2015, at  9:44 AM, Benjamin Root <ben...@ou...> wrote:
>>
>> I see what you are getting at. The issue is that artists are first sorted
>> by the zorder and then drawn one at a time. The draw for a collection
>> artist is an at-once operation, it can't (currently) be split out and
>> interspersed with the draws from another artist. This is one of the major
>> limitations for mplot3d, as it would be nice to compose a 3d scene properly
>> so that everything is logically consistent.
>>
>> I have actually been working on some changes that would allow one to sort
>> the draws of individual elements of a collection, but I still haven't
>> figured out a way to "break out" the elements with other collection
>> elements in a way that doesn't break the current design or introduce major
>> performance penalties. Maybe I'll figure something out during SciPy2015.
>>
>> Cheers!
>> Ben Root
>>
>>
>> On Tue, Jun 23, 2015 at 5:44 AM, Simon Walker <
>> s.r...@go...> wrote:
>>
>>> When multiple datasets are plotted on the same axis, the points overlay
>>> each other making it hard to see the points under the most recent ones. One
>>> way to avoid this is to give each point a random zorder, randomising its
>>> position in the z axis. This way, points from the first dataset may overly
>>> points from the last dataset.
>>>
>>> This could be achieved nicely if the zorder keyword took an array so the
>>> random zorder values per point can be pre-computed, but currently it only
>>> accepts a single number for the whole dataset. Would this be a useful
>>> feature for others to have? How difficult would it be to implement?
>>>
>>> Thanks,
>>>
>>> Simon Walker
>>>
>>> ------------------------------------------------------------------------------
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>>
>>
>> ------------------------------------------------------------------------------
>> Monitor 25 network devices or servers for free with OpManager!
>> OpManager is web-based network management software that monitors
>> network devices and physical & virtual servers, alerts via email & sms
>> for fault. Monitor 25 devices for free with no restriction. Download now
>>
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>>
>> ------------------------------------------------------------------------------
>> Monitor 25 network devices or servers for free with OpManager!
>> OpManager is web-based network management software that monitors
>> network devices and physical & virtual servers, alerts via email & sms
>> for fault. Monitor 25 devices for free with no restriction. Download now
>> http://ad.doubleclick.net/ddm/clk/292181274;119417398;o
>> _______________________________________________
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>
> ------------------------------------------------------------------------------
> Monitor 25 network devices or servers for free with OpManager!
> OpManager is web-based network management software that monitors
> network devices and physical & virtual servers, alerts via email & sms
> for fault. Monitor 25 devices for free with no restriction. Download now
> http://ad.doubleclick.net/ddm/clk/292181274;119417398;o
> _______________________________________________
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>