matplotlib-users Mailing List for matplotlib (Page 4)

Not quite sure exactly what you need to do, but it sounds like separate
calls to `plot` for each quadrilateral will do the trick.
-paul


On Wed, Feb 5, 2014 at 4:57 PM, Pedro Marcal <ped...@gm...> wrote:

> I don't know how to separately plot the quadrilaterals after plotting each
> of them in a closed loop eg nodes 1,2,3,4,1 the next quad is 3,2,5,6,3 say.
> I use a return to 1,0.0,3 and continue the curve numpy curve X,Y,Z as per
> the example tutorials. I tried inserting a None in between the quads, but
> this raises a python error. Please advise me on how to plot my quads
> without having to trace a sequence of previously plotted sides, eg 1,2,3
> then the second quad.
> Thanks,
> Pedro
>
>
> ------------------------------------------------------------------------------
> Managing the Performance of Cloud-Based Applications
> Take advantage of what the Cloud has to offer - Avoid Common Pitfalls.
> Read the Whitepaper.
>
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> _______________________________________________
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>
>

I don't know how to separately plot the quadrilaterals after plotting each
of them in a closed loop eg nodes 1,2,3,4,1 the next quad is 3,2,5,6,3 say.
I use a return to 1,0.0,3 and continue the curve numpy curve X,Y,Z as per
the example tutorials. I tried inserting a None in between the quads, but
this raises a python error. Please advise me on how to plot my quads
without having to trace a sequence of previously plotted sides, eg 1,2,3
then the second quad.
Thanks,
Pedro

Hello.
EPS files contain titles in them ("%%Title" at the beginning). Is it 
possible to define this title while using "savefig"? By default the file 
name is used. But I use "savefig" with temporary file names (to pass the 
created file to "epstool" to add a preview) which don't mean anything. 
So I want to define the title manually.
Kind regards, Petr.

Hello,

i've made a (filled) contour plot with matplotlib-pyplot. First i use
contour() and after that contourf().
My question: the contour-values on the lines have all different
orientations. Is it possible to align alle values horizontal (linke normal
text)?



Thanks,
Sappy85





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

Hey everyone,

Sorry to posters who may have seen this on the scikit mailing list.  

I started a small project for drawing and manipulating particles on images. 
All of the particles optionally support matplotlib patches on the backend. 
I thought I'd share in case anyone was interested, or if any of the images
might be useful just for the aesthetic appeal on your site.

Here is the page:

https://github.com/hugadams/pyparty

In the "documentation" section, there are several notebooks with various
examples of patch objects used.  

If this is inappropriate for the list, feel free to delete.  

Thanks.



--
View this message in context: http://matplotlib.1069221.n5.nabble.com/small-library-with-matplotlib-patches-backend-crosslist-post-tp42828.html
Sent from the matplotlib - users mailing list archive at Nabble.com.

The solution is following:

uninstall numpy using yum.
build numpy from source and install it.
Build matplotlib from source!

Best


On Mon, Feb 3, 2014 at 3:29 PM, Nemanja Savic <vla...@gm...> wrote:

> Hi all guys, I am back to the same issue again. At the moment I am not
> able to reazlize where does matplotlib configure script find that my
> version of numpy is 1.4.1?
>
>
> On Tue, Nov 12, 2013 at 4:20 PM, Nemanja Savic <vla...@gm...> wrote:
>
>> I see. But is there any other way to cope with this x server problem and
>> multiple figures plotting?
>>
>>
>> On Tue, Nov 12, 2013 at 3:21 PM, Benjamin Root <ben...@ou...> wrote:
>>
>>>
>>>
>>>
>>> On Tue, Nov 12, 2013 at 7:37 AM, Nemanja Savic <vla...@gm...>wrote:
>>>
>>>> Hi all guys,
>>>>
>>>> I am using RHEL6 and I am ploting figures throughout my project, so I
>>>> wanted some workaroung blocking show() function call. I have found few
>>>> solutions that use multiprocessing, so finally i finished with this:
>>>>
>>>> pool.map(plot_graph, c)
>>>>
>>>> and
>>>>
>>>> def plot_graph(*args):
>>>>     plt.figure(args[0][2])
>>>>     plt.bar(args[0][1][:-1], args[0][0], width=1)
>>>>     plt.show()
>>>>
>>>> But when I have more than one figure the following error occures:
>>>>
>>>>
>>>> /usr/lib64/python2.6/site-packages/matplotlib/backends/backend_gtk.py:621:
>>>> DeprecationWarning: Use the new widget gtk.Tooltip
>>>>   self.tooltips = gtk.Tooltips()
>>>> /usr/lib64/python2.6/site-packages/matplotlib/backends/backend_gtk.py:621:
>>>> DeprecationWarning: Use the new widget gtk.Tooltip
>>>>   self.tooltips = gtk.Tooltips()
>>>> [xcb] Unknown sequence number while processing queue
>>>> [xcb] Most likely this is a multi-threaded client and XInitThreads has
>>>> not been called
>>>> [xcb] Aborting, sorry about that.
>>>> python: xcb_io.c:273: poll_for_event: Assertion
>>>> `!xcb_xlib_threads_sequence_lost' failed.
>>>> runner.py: Fatal IO error 0 (Success) on X server :0.0.
>>>>
>>>> Since my version of matplolib doesnt support blocking = false solution,
>>>> I wanted to install new version. For that I installed new version of numpy
>>>> but when i run python setup.py build in matplolib foldet i get following:
>>>>
>>>> Edit setup.cfg to change the build options
>>>>
>>>> BUILDING MATPLOTLIB
>>>>             matplotlib: yes [1.3.1]
>>>>                 python: yes [2.6.6 (r266:84292, May 27 2013, 05:35:12)
>>>> [GCC
>>>>                         4.4.7 20120313 (Red Hat 4.4.7-3)]]
>>>>               platform: yes [linux2]
>>>>
>>>> REQUIRED DEPENDENCIES AND EXTENSIONS
>>>>                  numpy: yes [version 1.8.0]
>>>>               dateutil: yes [using dateutil version 1.4.1]
>>>>                tornado: yes [tornado was not found. It is required for
>>>> the
>>>>                         WebAgg backend. pip/easy_install may attempt to
>>>>                         install it after matplotlib.]
>>>>              pyparsing: yes [pyparsing was not found. It is required for
>>>>                         mathtext support. pip/easy_install may attempt
>>>> to
>>>>                         install it after matplotlib.]
>>>>                  pycxx: yes [Couldn't import.  Using local copy.]
>>>>                 libagg: yes [pkg-config information for 'libagg' could
>>>> not
>>>>                         be found. Using local copy.]
>>>>               freetype: yes [version 9.22.3]
>>>>                    png: yes [version 1.2.49]
>>>>
>>>> OPTIONAL SUBPACKAGES
>>>>            sample_data: yes [installing]
>>>>               toolkits: yes [installing]
>>>>                  tests: yes [nose 0.11.1 or later is required to run the
>>>>                         matplotlib test suite]
>>>>
>>>> OPTIONAL BACKEND EXTENSIONS
>>>>                 macosx: no  [Mac OS-X only]
>>>>                 qt4agg: yes [installing, Qt: 4.6.2, PyQt4: 4.6.2]
>>>>                gtk3agg: no  [Requires pygobject to be installed.]
>>>>              gtk3cairo: no  [Requires pygobject to be installed.]
>>>>                 gtkagg: yes [installing, Gtk: 2.18.9 pygtk: 2.16.0]
>>>>                  tkagg: yes [installing, version 73770]
>>>>                  wxagg: yes [installing, version 2.8.12.0]
>>>>                    gtk: yes [installing, Gtk: 2.18.9 pygtk: 2.16.0]
>>>>                    agg: yes [installing]
>>>>                  cairo: yes [installing, version 1.8.6]
>>>>              windowing: no  [Microsoft Windows only]
>>>>
>>>> OPTIONAL LATEX DEPENDENCIES
>>>>                 dvipng: yes [version 1.14]
>>>>            ghostscript: yes [version 8.70]
>>>>                  latex: yes [version 3.1415926]
>>>>                pdftops: no
>>>>
>>>> Traceback (most recent call last):
>>>>   File "setup.py", line 268, in <module>
>>>>     **extra_args
>>>>   File "/usr/lib64/python2.6/distutils/core.py", line 113, in setup
>>>>     _setup_distribution = dist = klass(attrs)
>>>>   File "build/bdist.linux-x86_64/egg/setuptools/dist.py", line 221, in
>>>> __init__
>>>>   File "build/bdist.linux-x86_64/egg/setuptools/dist.py", line 245, in
>>>> fetch_build_eggs
>>>>   File "build/bdist.linux-x86_64/egg/pkg_resources.py", line 592, in
>>>> resolve
>>>>     plugin_projects.sort()  # scan project names in alphabetic order
>>>> pkg_resources.VersionConflict: (numpy 1.4.1
>>>> (/usr/lib64/python2.6/site-packages), Requirement.parse('numpy>=1.5'))
>>>>
>>>> When I run python and check numpy version it is indeed 1.8.0, but
>>>> matplotlib buils script somehow founded older one.
>>>>
>>>>
>>>> I would be really happy if somebody can help me overcome problem with
>>>> many figures.
>>>>
>>>> Best and cheers
>>>>
>>>>
>>> The issue is rather complex, and it is a very difficult one to solve on
>>> our end. What is happening is that in order to build matplotlib from
>>> source, you need to compile against the numpy headers at build-time.
>>> Unfortunately, python packaging being what it is, there is difficulty in
>>> making sure that the version of numpy that will be installed is the version
>>> used for the build. You seem to have numpy installed both at the system
>>> level and possibly at the user level. If possible, I would try removing
>>> numpy from your system level (and that likely means removing any other
>>> installed package that depends on it, and reinstalling via source).
>>>
>>> Ben Root
>>>
>>
>>
>>
>> --
>> Nemanja Savić
>>
>
>
>
> --
> Nemanja Savić
>



-- 
Nemanja Savić

Hi all guys, I am back to the same issue again. At the moment I am not able
to reazlize where does matplotlib configure script find that my version of
numpy is 1.4.1?


On Tue, Nov 12, 2013 at 4:20 PM, Nemanja Savic <vla...@gm...> wrote:

> I see. But is there any other way to cope with this x server problem and
> multiple figures plotting?
>
>
> On Tue, Nov 12, 2013 at 3:21 PM, Benjamin Root <ben...@ou...> wrote:
>
>>
>>
>>
>> On Tue, Nov 12, 2013 at 7:37 AM, Nemanja Savic <vla...@gm...>wrote:
>>
>>> Hi all guys,
>>>
>>> I am using RHEL6 and I am ploting figures throughout my project, so I
>>> wanted some workaroung blocking show() function call. I have found few
>>> solutions that use multiprocessing, so finally i finished with this:
>>>
>>> pool.map(plot_graph, c)
>>>
>>> and
>>>
>>> def plot_graph(*args):
>>>     plt.figure(args[0][2])
>>>     plt.bar(args[0][1][:-1], args[0][0], width=1)
>>>     plt.show()
>>>
>>> But when I have more than one figure the following error occures:
>>>
>>>
>>> /usr/lib64/python2.6/site-packages/matplotlib/backends/backend_gtk.py:621:
>>> DeprecationWarning: Use the new widget gtk.Tooltip
>>>   self.tooltips = gtk.Tooltips()
>>> /usr/lib64/python2.6/site-packages/matplotlib/backends/backend_gtk.py:621:
>>> DeprecationWarning: Use the new widget gtk.Tooltip
>>>   self.tooltips = gtk.Tooltips()
>>> [xcb] Unknown sequence number while processing queue
>>> [xcb] Most likely this is a multi-threaded client and XInitThreads has
>>> not been called
>>> [xcb] Aborting, sorry about that.
>>> python: xcb_io.c:273: poll_for_event: Assertion
>>> `!xcb_xlib_threads_sequence_lost' failed.
>>> runner.py: Fatal IO error 0 (Success) on X server :0.0.
>>>
>>> Since my version of matplolib doesnt support blocking = false solution,
>>> I wanted to install new version. For that I installed new version of numpy
>>> but when i run python setup.py build in matplolib foldet i get following:
>>>
>>> Edit setup.cfg to change the build options
>>>
>>> BUILDING MATPLOTLIB
>>>             matplotlib: yes [1.3.1]
>>>                 python: yes [2.6.6 (r266:84292, May 27 2013, 05:35:12)
>>> [GCC
>>>                         4.4.7 20120313 (Red Hat 4.4.7-3)]]
>>>               platform: yes [linux2]
>>>
>>> REQUIRED DEPENDENCIES AND EXTENSIONS
>>>                  numpy: yes [version 1.8.0]
>>>               dateutil: yes [using dateutil version 1.4.1]
>>>                tornado: yes [tornado was not found. It is required for
>>> the
>>>                         WebAgg backend. pip/easy_install may attempt to
>>>                         install it after matplotlib.]
>>>              pyparsing: yes [pyparsing was not found. It is required for
>>>                         mathtext support. pip/easy_install may attempt to
>>>                         install it after matplotlib.]
>>>                  pycxx: yes [Couldn't import.  Using local copy.]
>>>                 libagg: yes [pkg-config information for 'libagg' could
>>> not
>>>                         be found. Using local copy.]
>>>               freetype: yes [version 9.22.3]
>>>                    png: yes [version 1.2.49]
>>>
>>> OPTIONAL SUBPACKAGES
>>>            sample_data: yes [installing]
>>>               toolkits: yes [installing]
>>>                  tests: yes [nose 0.11.1 or later is required to run the
>>>                         matplotlib test suite]
>>>
>>> OPTIONAL BACKEND EXTENSIONS
>>>                 macosx: no  [Mac OS-X only]
>>>                 qt4agg: yes [installing, Qt: 4.6.2, PyQt4: 4.6.2]
>>>                gtk3agg: no  [Requires pygobject to be installed.]
>>>              gtk3cairo: no  [Requires pygobject to be installed.]
>>>                 gtkagg: yes [installing, Gtk: 2.18.9 pygtk: 2.16.0]
>>>                  tkagg: yes [installing, version 73770]
>>>                  wxagg: yes [installing, version 2.8.12.0]
>>>                    gtk: yes [installing, Gtk: 2.18.9 pygtk: 2.16.0]
>>>                    agg: yes [installing]
>>>                  cairo: yes [installing, version 1.8.6]
>>>              windowing: no  [Microsoft Windows only]
>>>
>>> OPTIONAL LATEX DEPENDENCIES
>>>                 dvipng: yes [version 1.14]
>>>            ghostscript: yes [version 8.70]
>>>                  latex: yes [version 3.1415926]
>>>                pdftops: no
>>>
>>> Traceback (most recent call last):
>>>   File "setup.py", line 268, in <module>
>>>     **extra_args
>>>   File "/usr/lib64/python2.6/distutils/core.py", line 113, in setup
>>>     _setup_distribution = dist = klass(attrs)
>>>   File "build/bdist.linux-x86_64/egg/setuptools/dist.py", line 221, in
>>> __init__
>>>   File "build/bdist.linux-x86_64/egg/setuptools/dist.py", line 245, in
>>> fetch_build_eggs
>>>   File "build/bdist.linux-x86_64/egg/pkg_resources.py", line 592, in
>>> resolve
>>>     plugin_projects.sort()  # scan project names in alphabetic order
>>> pkg_resources.VersionConflict: (numpy 1.4.1
>>> (/usr/lib64/python2.6/site-packages), Requirement.parse('numpy>=1.5'))
>>>
>>> When I run python and check numpy version it is indeed 1.8.0, but
>>> matplotlib buils script somehow founded older one.
>>>
>>>
>>> I would be really happy if somebody can help me overcome problem with
>>> many figures.
>>>
>>> Best and cheers
>>>
>>>
>> The issue is rather complex, and it is a very difficult one to solve on
>> our end. What is happening is that in order to build matplotlib from
>> source, you need to compile against the numpy headers at build-time.
>> Unfortunately, python packaging being what it is, there is difficulty in
>> making sure that the version of numpy that will be installed is the version
>> used for the build. You seem to have numpy installed both at the system
>> level and possibly at the user level. If possible, I would try removing
>> numpy from your system level (and that likely means removing any other
>> installed package that depends on it, and reinstalling via source).
>>
>> Ben Root
>>
>
>
>
> --
> Nemanja Savić
>



-- 
Nemanja Savić

On 2/3/2014 1:36 AM, Eric Firing wrote:
> The default of not including the
> head in the length is puzzling, to say the least.


And again, it does not match the behavior of Arrow.
So perhaps the current behavior could be changed?
(E.g., after a period of requiring `length_includes_head`,
which I'll bet practically all users are already
setting, because of the puzzling default.)

Also, am I wrong that the default head_width and head_length
are buggy (i.e., not set in proportion to the `width`,
as the documentation requires)?

Thanks,
Alan

PS Thanks for 'none'; I'd forgotten. Also, quiver is somewhat
useful (good arrows), but lacks easy control over individual
arrow properties.

On 2014/02/02 7:45 PM, Alan G Isaac wrote:
> Last question about this for now ...
>
> Yet another issue with `arrow`: the
> docs say a dashed linestyle is supported
> http://matplotlib.org/api/pyplot_api.html#matplotlib.pyplot.arrow
> but really it is not: the *edge* is dashed rather than the tail!
>
> Maybe I'm missing the intended usage here.  But
> I'm starting to think Matplotlib could use a "SimpleArrow".
> The tail would just be a line.
> The head would just be  a filled triangle.
> The default would be length_includes_head=True.
>
> Alan Isaac
>

Alan,

I think you are raising good points. (The default of not including the 
head in the length is puzzling, to say the least.) Actually making a 
*good* simple arrow is not as simple as it might seem, but it can be 
done.  The main difficulty is the need to use a mix of coordinates and 
transforms to handle varying axes sizes and aspect ratios.  In any case, 
I think you have pointed to one of many areas where mpl's present design 
and user interface could be improved.  It's all a matter of volunteer 
labor to make such improvements--with the added difficulty of needing to 
maintain backward compatibility over fairly long periods.

For your immediate needs, might quiver work better?  It's interface is 
also rather complex because of the use cases it covers.

If you are using the arrows for annotation rather than as 
representations of vectors, then of course the annotate() function is 
appropriate.

Eric

On 2014/02/02 6:52 PM, Alan G Isaac wrote:
> Also, despite setting `edgecolor=None`, the edge is still stroked.

I suspect you need edgecolor='none'.  In general, specifying a color as 
the string 'none' means "don't draw it".

Last question about this for now ...

Yet another issue with `arrow`: the
docs say a dashed linestyle is supported
http://matplotlib.org/api/pyplot_api.html#matplotlib.pyplot.arrow
but really it is not: the *edge* is dashed rather than the tail!

Maybe I'm missing the intended usage here.  But
I'm starting to think Matplotlib could use a "SimpleArrow".
The tail would just be a line.
The head would just be  a filled triangle.
The default would be length_includes_head=True.

Alan Isaac

On 2/2/2014 11:13 PM, Alan G Isaac wrote:
> A follow-on question: the `arrow` method of an axes
> has `length_includes_head` default to False.  Why?
> This seems very unfriendly behavior for an "arrow".
> It also conflicts with the behavior of an `Arrow`.

One more follow-on question:
the documented behavior of head_width and head_length is:
http://matplotlib.org/api/axes_api.html

head_width: float or None (default: 3*width)   total width of the full arrow head
head_length: float or None (default: 1.5 * head_width)   length of arrow head

But I believe that does not match the behavior I am seeing.  E.g., the following
produces two completely different arrow heads.

fig, ax = plt.subplots(1,1)
ax.set_aspect('equal')
w=0.01
ax.arrow(0,0,1,1, width=w,head_width=3*w,head_length=1.5*3*w, facecolor='red',edgecolor=None,length_includes_head=True)
ax.arrow(0,1,1,-1, width=w, facecolor='k',edgecolor='red',length_includes_head=True)

Am I missing something?

Also, despite setting `edgecolor=None`, the edge is still stroked.

Alan Isaac

A follow-on question: the `arrow` method of an axes
has `length_includes_head` default to False.  Why?
This seems very unfriendly behavior for an "arrow".
It also conflicts with the behavior of an `Arrow`.

Thanks,
Alan Isaac

I just want to draw a few vectors of different colors.
In Mathematica I would use Arrow:
http://reference.wolfram.com/mathematica/ref/Arrow.html

In Matplotlib I cannot find an easy way.  Here's the best
I came up with so far.

import matplotlib.pyplot as plt
from matplotlib.patches import Arrow
fig, ax = plt.subplots(1,1)
ax.set_aspect('equal')
ax.add_artist( Arrow(0,0,1,1, width=0.1, facecolor='red',edgecolor=None) )
ax.add_artist( Arrow(0,1,1,-1, width=0.01, facecolor='k',edgecolor=None) )

Things that seem wrong with the interface:
- takes 4 numbers instead of a list of points
- head length and width is not determined by the line width
- edge drawing cannot (?) be turned off

The head drawing issue is particularly serious.

So, have I overlooked an easy way to do what I want?

One other question: am I supposed to use `add_patch` or
`add_artist`, and why?

Thanks,
Alan Isaac

Is it legend(loc='auto') or legend(loc='best')?  I always used the latter.  I think that http://matplotlib.org/api/legend_api.html supports me here.

-Sterling


On Jan 31, 2014, at 8:31AM, Benjamin Root wrote:

> I would also like to point out that you can specify "auto" for a location, and matplotlib will attempt to find a good location for you (within the plot area). It isn't perfect, but it can be useful.
> 
> Cheers!
> Ben Root
> 
> 
> On Fri, Jan 31, 2014 at 7:02 AM, Skip Montanaro <sk...@po...> wrote:
> > 1. PNG file of figure without legend.
> > 2. PNG file of legend only.
> >
> > The end user would import both images into another tool (e.g. microsoft
> > power point) and arrange figure and legend interactively for the final
> > product.
> 
> As someone pointed out to me not long ago, you can call
> 
>     my_legend.draggable(True)
> 
> then drag the legend where you want (in normal pointer mode). Then you
> just need to save the figure and not worry about fiddling with it
> later.
> 
> Skip Montanaro
> 
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> _______________________________________________
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> Mat...@li...
> https://lists.sourceforge.net/lists/listinfo/matplotlib-users
> 
> ------------------------------------------------------------------------------
> WatchGuard Dimension instantly turns raw network data into actionable 
> security intelligence. It gives you real-time visual feedback on key
> security issues and trends.  Skip the complicated setup - simply import
> a virtual appliance and go from zero to informed in seconds.
> http://pubads.g.doubleclick.net/gampad/clk?id=123612991&iu=/4140/ostg.clktrk_______________________________________________
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