matplotlib-users Mailing List for matplotlib

Try this:

    self.axes.set_yticks([])


________________________________
From: mat...@li... [mailto:mat...@li...] On Behalf Of "Jonathan Hayward, http://JonathansCorner.com"
Sent: Wednesday, August 06, 2008 4:38 PM
To: Matplotlib
Subject: [Matplotlib-users] Yticks off?

I am making a bar chart and want to turn off (visible) yticks. How can I remove, hide, color with white (the background color), etc., the yticks?

Thanks,
--
-- Jonathan Hayward, chr...@gm...<mailto:chr...@gm...>

** To see an award-winning website with stories, essays, artwork,
** games, and a four-dimensional maze, why not visit my home page?
** All of this is waiting for you at http://JonathansCorner.com

++ Would you like to curl up with one of my hardcover books?
++ You can now get my books from http://CJSHayward.com

Zane Selvans wrote:
> Oh, great!  I'm a dunce.  I should really go through and put all the 
> Basemap examples into the Matplotlib cookbook so they come up when I 
> search for them on the web.  Er, when somebody else searches for them 
> on the web... since I'd be familiar with all of them if I put them up!
>
> Is there some reason that many of the example files haven't been 
> updated to import basemap from the new mpl_toolkits.basemap instead of 
> the old matplotlib.toolkits.basemap?  Or maybe my version of the 
> examples (0.99) isn't the most recent?
>
> Zane

Zane:  All the examples do use mpl_toolkits, and have since the name was 
changed.  You must have a very old copy (probably 0.9.9, not 0.99).

-Jeff
>
> On Aug 6, 2008, at 2:15 PM, Jeff Whitaker wrote:
>
>> Zane Selvans wrote:
>>> Has anyone here ever used Basemap to display 
>>> datasets/layers/features  created using the OGR/GDAL libraries 
>>> (http://www.gdal.org/)?  They're  SWIG wrappers, not pure Python, so 
>>> I could see integration maybe being  a pain.  Just curious if there 
>>> was anything out there to build on  already...
>>>
>>> Thanks!
>>>
>>> -- 
>>> Zane Selvans
>>> Amateur Earthling
>>> http://zaneselvans.org
>>> za...@id...
>>> 303/815-6866
>>> PGP Key: 55E0815F
>>>
>>>
>>
>> Zane:  You can use Basemap to plot GIS data you've read in with 
>> ogr/gdal.  There's an example included with basemap (testgdal.py).  
>> I'm not a  gdal user, so I may be missing something - what sort of 
>> integration do you have in mind?
>>
>> -Jeff
>>
>> -- 
>> Jeffrey S. Whitaker         Phone  : (303)497-6313
>> Meteorologist               FAX    : (303)497-6449
>> NOAA/OAR/PSD  R/PSD1        Email  : Jef...@no...
>> 325 Broadway                Office : Skaggs Research Cntr 1D-113
>> Boulder, CO, USA 80303-3328 Web    : http://tinyurl.com/5telg
>>
>
> -- 
> Zane Selvans
> Amateur Earthling
> http://zaneselvans.org
> za...@id...
> 303/815-6866
> PGP Key: 55E0815F
>


-- 
Jeffrey S. Whitaker         Phone  : (303)497-6313
Meteorologist               FAX    : (303)497-6449
NOAA/OAR/PSD  R/PSD1        Email  : Jef...@no...
325 Broadway                Office : Skaggs Research Cntr 1D-113
Boulder, CO, USA 80303-3328 Web    : http://tinyurl.com/5telg

Ewald,

If you look at the following link it may help you get started:

http://code.google.com/p/subplot/source/browse/branches/mzViewer/PyMZViewer/mpl_custom_widget.py

What you need to do is make a ui with designer and then place a widget where ever you'd like.  From there make sure you right click on the widget and select horizontal layout (This is to make sure the widget occupies the GUI fully).  Then right click on the widget and click on "Promote to."  From there what you need to do is select QWidget as the base class name.  Using the example file I pointed to above you would put in "MPL_Widget" for the "Promoted class name" followed by "mpl_custom_widget" in the header file: field.  Click promote and you should be done.  Be sure to place the mpl_custom_widget.py in the directory of your converted ui file (i.e. the one that was created using pyuic4). Now from your main window file (the one that controls adding data to the plot) you simply need to use the name of widget you promoted followed by canvas.ax etc. to manipulate the plot.  For example if your promoted widget name is "plotWidget" you should be able
 to access the mpl API using "self.plotWidget.canvas.ax.plot(x,y,*kwargs)" where x,y, and *kwargs are the appropriate numpy arrays and keyword arguments.

I hope that helps, and let me know if you need anythinge else.

Cheers,

Brian

--ps if you need the toolbar using the latest version of matplotlib you may have to uncomment some of the code and remove some of the arguments that locate the toolbar in the ui.  

--- On Wed, 8/6/08, Ewald Zietsman <ewa...@gm...> wrote:
From: Ewald Zietsman <ewa...@gm...>
Subject: Re: [Matplotlib-users] Using matplotlib in Qt4/Qt4 Designer
To: clo...@ya...
Date: Wednesday, August 6, 2008, 2:47 PM


Hi,

Sorry for replying only now. Thanks for the link. I'm very new to GUI programming. Can you please explain to me how to promote a mpl widget from a regular widget? In qt3 it was possible to create a mpl widget in the form by telling the form to import your module containing the widget definition (a python class). I'm working with the qwt widgets at the moment and although they're supposed to be fast, they don't seem to be much faster than mpl, unless I'm doing something funny which is possible. I'm not really a programmer, but I like to tinker in order to learn as much as I can so that I can create programs to solve astrophysical  problems/analyse data more efficiently (less time/less code).


Cheers

Ewald
 

On Wed, Aug 6, 2008 at 12:46 AM, B Clowers <clo...@ya...> wrote:
>
> Ewald,
>
> It is very much a work in progress (and poorly named) but you can check out a project of mine:

>
> http://code.google.com/p/subplot/
>
> I created a custom matplotlib widget that you can promote from a regular widget in Designer.  I hope it helps, let me know if you have any questions.  The ui files are also included in the SVN.  One thing to note there was a recent change to the Qt backend that altered the nature of the toolbar so you may want to comment that part out if you are using the latest matplotlib.  If it is a must have I think I'm sure I could update  the code when I find some time (Currently, I'm using v 0.91 I believe).  Good luck.

>
> Cheers,
>
> Brian
>
> --- On Tue, 8/5/08, Ewald Zietsman <ewa...@gm...> wrote:
>
> From: Ewald Zietsman <ewa...@gm...>

> Subject: [Matplotlib-users] Using matplotlib in Qt4/Qt4 Designer
> To: mat...@li...
> Date: Tuesday, August 5, 2008, 10:06 AM

>
> Hi All,
>
> I'd like to use a matplotlib widget in a GUI app I'm working on. I have tried qwt but I know matplotlib a lot better and would like to use it instead. Is there anybody who have done this before? More specifically, does anyone know how to add a matplotlib widget as a custom widget in qt4 designer?

>
> Any help will be greatly appreciated,
>
> Ewald Zietsman
>
> -------------------------------------------------------------------------
> This SF.Net email is sponsored by the Moblin Your Move Developer's

> challenge
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> Grand prize is a trip for two to an Open Source event anywhere in the world
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>
> _______________________________________________
> Matplotlib-users mailing list
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> https://lists.sourceforge.net/lists/listinfo/matplotlib-users

>





      

Oh, great!  I'm a dunce.  I should really go through and put all the  
Basemap examples into the Matplotlib cookbook so they come up when I  
search for them on the web.  Er, when somebody else searches for them  
on the web... since I'd be familiar with all of them if I put them up!

Is there some reason that many of the example files haven't been  
updated to import basemap from the new mpl_toolkits.basemap instead of  
the old matplotlib.toolkits.basemap?  Or maybe my version of the  
examples (0.99) isn't the most recent?

Zane

On Aug 6, 2008, at 2:15 PM, Jeff Whitaker wrote:

> Zane Selvans wrote:
>> Has anyone here ever used Basemap to display datasets/layers/ 
>> features  created using the OGR/GDAL libraries (http://www.gdal.org/)? 
>>   They're  SWIG wrappers, not pure Python, so I could see  
>> integration maybe being  a pain.  Just curious if there was  
>> anything out there to build on  already...
>>
>> Thanks!
>>
>> --
>> Zane Selvans
>> Amateur Earthling
>> http://zaneselvans.org
>> za...@id...
>> 303/815-6866
>> PGP Key: 55E0815F
>>
>>
>
> Zane:  You can use Basemap to plot GIS data you've read in with ogr/ 
> gdal.  There's an example included with basemap (testgdal.py).  I'm  
> not a  gdal user, so I may be missing something - what sort of  
> integration do you have in mind?
>
> -Jeff
>
> -- 
> Jeffrey S. Whitaker         Phone  : (303)497-6313
> Meteorologist               FAX    : (303)497-6449
> NOAA/OAR/PSD  R/PSD1        Email  : Jef...@no...
> 325 Broadway                Office : Skaggs Research Cntr 1D-113
> Boulder, CO, USA 80303-3328 Web    : http://tinyurl.com/5telg
>

--
Zane Selvans
Amateur Earthling
http://zaneselvans.org
za...@id...
303/815-6866
PGP Key: 55E0815F

Hello,
excuse the late reply.

But you may be interested in the timeseries scikit:
http://scipy.org/scipy/scikits/wiki/TimeSeries
http://www.scipy.org/Cookbook/TimeSeries/FAQ

Have success!

Kind regards,
Timmie

-----BEGIN PGP SIGNED MESSAGE-----
Hash: SHA1

Hello everyone,

I've had a heck of a time trying to install matplotlib.  I've tried
installing both from svn and from the pre-built 0.98.3 egg with no
success.  Any tips would be appreciated.

My setup is:
Mac Pro PPC G5, OS X 10.5.4
Python 2.5.1 (Apple build)
Numpy 1.2.0.dev5615 -- ran svn update and rebuilt this morning
Scipy 0.7.0.dev4603 -- ran svn update and rebuilt this morning

1. Error with the SourceForge 0.98.3 egg for OS X:
$ easy_install matplotlib-0.98.3-py2.5-macosx-10.3.egg
[snip]
REQUIRED DEPENDENCIES
~                        * numpy 1.1 or later is required; you have
~                        * 1.0.5.dev4673
error: Setup script exited with 1

As far as I know, numpy 1.0.5.dev4673 was never installed on this
machine.  Running python and checking numpy.__version__ gives the
version string listed above (1.2.etc.).  I can't find any other versions
on the system, and I don't know where the egg would be finding this
phantom version.

2. Error building from svn checkout, following the instructions at
http://ipython.scipy.org/moin/MatplotlibOSXBuildNotes:

g++ -arch i386 -arch ppc -isysroot /Developer/SDKs/MacOSX10.4u.sdk -g
- -bundle -undefined dynamic_lookup -arch ppc -arch i386
- -L/usr/local/src/mpl-build/libpng-1.2.29
- -L/usr/local/src/mpl-build/freetype-2.3.7 -arch ppc -arch i386
- -I/usr/local/src/mpl-build/libpng-1.2.29
- -I/usr/local/src/mpl-build/freetype-2.3.7/include
build/temp.macosx-10.3-fat-2.5/src/ft2font.o
build/temp.macosx-10.3-fat-2.5/src/mplutils.o
build/temp.macosx-10.3-fat-2.5/CXX/cxx_extensions.o
build/temp.macosx-10.3-fat-2.5/CXX/cxxsupport.o
build/temp.macosx-10.3-fat-2.5/CXX/IndirectPythonInterface.o
build/temp.macosx-10.3-fat-2.5/CXX/cxxextensions.o -L/usr/local/lib
- -lfreetype -lz -lz -lstdc++ -lm -o
build/lib.macosx-10.3-fat-2.5/matplotlib/ft2font.so
- -Wl,-framework,CoreServices,-framework,ApplicationServices
ld: in /Developer/SDKs/MacOSX10.4u.sdk/usr/local/lib/libPng.dylib, file
is not of required architecture for architecture i386
collect2: ld returned 1 exit status
lipo: can't open input file:
/var/folders/7h/7hHE3mwXHGCNGWujjUd1L++++U2/-Tmp-//ccS3ZBhp.out (No such
file or directory)
error: command 'g++' failed with exit status 1

~From this, it would seem that the build is attempting to use an external
libpng, despite the fact that I built it from source without a problem,
it's located in /usr/local/src/mpl-build/libpng-1.2.29, and:

$ echo $CFLAGS
- -arch ppc -arch i386 -I/usr/local/src/mpl-build/libpng-1.2.29
- -I/usr/local/src/mpl-build/freetype-2.3.7/include
$ echo $LDFLAGS
- -arch ppc -arch i386 -L/usr/local/src/mpl-build/libpng-1.2.29
- -L/usr/local/src/mpl-build/freetype-2.3.7

What am I missing?

Any help would be greatly appreciated...I've played with this all day
and made little progress.

Thanks!

- --
Richard Lawrence
Research Coordinator
Computational Memory Lab
rw...@ps...
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I am making a bar chart and want to turn off (visible) yticks. How can I
remove, hide, color with white (the background color), etc., the yticks?

Thanks,
-- 
-- Jonathan Hayward, chr...@gm...

** To see an award-winning website with stories, essays, artwork,
** games, and a four-dimensional maze, why not visit my home page?
** All of this is waiting for you at http://JonathansCorner.com

++ Would you like to curl up with one of my hardcover books?
++ You can now get my books from http://CJSHayward.com

Zane Selvans wrote:
> Has anyone here ever used Basemap to display datasets/layers/features  
> created using the OGR/GDAL libraries (http://www.gdal.org/)?  They're  
> SWIG wrappers, not pure Python, so I could see integration maybe being  
> a pain.  Just curious if there was anything out there to build on  
> already...
>
> Thanks!
>
> --
> Zane Selvans
> Amateur Earthling
> http://zaneselvans.org
> za...@id...
> 303/815-6866
> PGP Key: 55E0815F
>
>   

Zane:  You can use Basemap to plot GIS data you've read in with 
ogr/gdal.  There's an example included with basemap (testgdal.py).  I'm 
not a  gdal user, so I may be missing something - what sort of 
integration do you have in mind?

-Jeff

-- 
Jeffrey S. Whitaker         Phone  : (303)497-6313
Meteorologist               FAX    : (303)497-6449
NOAA/OAR/PSD  R/PSD1        Email  : Jef...@no...
325 Broadway                Office : Skaggs Research Cntr 1D-113
Boulder, CO, USA 80303-3328 Web    : http://tinyurl.com/5telg

Has anyone here ever used Basemap to display datasets/layers/features  
created using the OGR/GDAL libraries (http://www.gdal.org/)?  They're  
SWIG wrappers, not pure Python, so I could see integration maybe being  
a pain.  Just curious if there was anything out there to build on  
already...

Thanks!

--
Zane Selvans
Amateur Earthling
http://zaneselvans.org
za...@id...
303/815-6866
PGP Key: 55E0815F

I just played with putting contour labels on manually (and interactively).

It works fine by just left clicking on the spot where you want a label.

But how do you end this feature? The doc string says: right click, or
potentially click both mouse buttons together.

Neither works for me on win32, mpl 0.98.3, TkAgg backend, interactive mode.

Does this work for anybody?

Mark

Quick test:
cobj = contour(x,y,z) # x,y,z some arrays
cobj.clabel(manual=True)

Oops, forgot to cc the list...

---------- Forwarded message ----------
From: Anthony Floyd <ant...@gm...>
Date: Wed, Aug 6, 2008 at 12:28 PM
Subject: Re: [Matplotlib-users] Moving legend with mouse?
To: Søren Nielsen <sor...@gm...>


On Fri, Aug 1, 2008 at 6:10 AM, Søren Nielsen
<sor...@gm...> wrote:
>
> I'm using matplotlib 0.98 together with wxpython 2.8.8.0. It would be nice
> to be able to click on the legend and move it with the mouse. Is that
> possible? Is there a simple way to do this? Has anyone tried this or can
> someone point in the direction?
>
> Thanks,
> Soren

Hi Soren,

Sorry for the delay.  This is pretty easy to do if you're using the API.

Our code is pretty ... um, integrated, so I can't provide you with a
detailed step-by-step, but here's the general idea:

- On a FigureCanvas, use mpl_connect to hook into the
'motion_notify_event'.  So, we have
"self.mpl_connect('motion_notify_event', self._onMouseMove)"
- onMouseMove checks to see if we've previously picked the legend and
adds mplEvent.x and mplEvent.y to the original pick location and calls
our self._moveLegend function
- The _moveLegend routine is:

   def _moveLegend(self, x, y, autoDraw=True):

       height = float(self.figure.bbox.height())
       width = float(self.figure.bbox.width())

       dx = x/width
       dy = y/height

       self._legendLocation = (dx, dy)
       self.plot.getLegend().setLocation(self._legendLocation)

       self._legend._loc=(dx,dy)

       if autoDraw:
           self.draw()

Now, you won't need most of this, but the important things here are
the dx,dy calculations and the _legend._loc=(dx,dy) assignment.

It's not a very complete set of instructions, but it might get you
pointed in the right direction.  Legend dragging in this manner works
quite smoothly for us.

Regards,
Anthony.

On Wed, Aug 6, 2008 at 1:28 PM, peter websdell
<fly...@go...> wrote:
> No michael, that is what I was suggesting. Shame it doesn't work.
>
> I'm looking at using Enthoughts Chaco to do it. It's takes a bit more to get
> it doing what I want though, and I don't know if it does alpha transparency
> at all.

I believe chaco uses the same contouring routine as mpl does, though I
haven't verified this recently.

JDH

No michael, that is what I was suggesting. Shame it doesn't work.

I'm looking at using Enthoughts Chaco to do it. It's takes a bit more to get
it doing what I want though, and I don't know if it does alpha transparency
at all.

Thanks for your help.

Pete

2008/8/6 Michael Droettboom <md...@st...>

> It doesn't seem to matter whether the filled contours are drawn with edges
> or not -- the cuts are still visible because they're caused by over-drawing
> of the fill.  (You can set linewidth=0 to try this.)  But maybe I
> misunderstand your question.
>
> Cheers,
> Mike
>
>
> kippertoffee wrote:
>
>> Thank you for your reply Michael.
>>
>> Is it possible to make the lines in the contourf plot completely
>> transparent
>> using an alpha setting? That would make a reasonable workaround as I
>> intend
>> to overlay black contours anyway.
>>
>>  I've had a look at the source but it is way beyond me; I am a mere
>> dabbler.
>>
>> Cheers,
>> Pete.
>>
>>
>> Michael Droettboom-3 wrote:
>>
>>
>>> This is a known issue with the contouring code.  It's borrowed from an
>>> earlier plotting package called GIST, and assumes that the renderer can not
>>> handle compound polygons (for example, donut-shaped, with both an inner and
>>> outer edge).  So instead, it draws "cuts" that go from the inner to the
>>> outer edge.  When anti-aliasing is turned on, there is a slight overlap or
>>> "drawing twice" along this edge which creates what looks like a line.
>>>  Unfortunately, this can't be remedied by plotting the contour fills and
>>> then plotting the contour edges over top (as is done is contourf_demo.py).
>>>
>>> As of matplotlib 0.98.x, matplotlib itself can handle compound paths, so
>>> we no longer need the cuts.  I've made a few attempts at updating the
>>> contouring code to avoid them, but got nowhere.  The contouring code is very
>>> opaque, almost magical code, and most who've dared to go in have barely made
>>> it out alive... ;)  That said, a fresh pair of eyes may have what it
>>> takes...
>>>
>>> As for a workaround, you could render your contour as opaque, save that
>>> out as an image and read it back in.  The code to do that won't be pretty,
>>> but it just might work.
>>>
>>> Cheers,
>>> Mike
>>>
>>> kippertoffee wrote:
>>>
>>>
>>>> Hello,
>>>>
>>>> I am attempting to overlay a filled contour over a custom image.
>>>>
>>>> I have managed to get something basic working, but i have encountered a
>>>> problem:
>>>>
>>>> When the contourf plot is set to semi-transparent there are visible
>>>> lines
>>>> joining the bottom of the plot and the filled contour edges. I have
>>>> attached
>>>> an image of the plot.
>>>>
>>>> http://img232.imageshack.us/my.php?image=spambs6.png spam.png
>>>> The code i have used is below; please bear in mind I am not a
>>>> programmer,
>>>> so
>>>> if the code seems botched, that's because it is.
>>>>
>>>> ###############################
>>>>
>>>> import matplotlib.pyplot as plt
>>>> from pylab import *
>>>> try:
>>>>    import Image
>>>> except ImportError, exc:
>>>>    raise SystemExit("PIL must be installed to run this example")
>>>>
>>>> lena = Image.open('lena.jpg')
>>>> dpi = rcParams['figure.dpi']
>>>> figsize = lena.size[0]/dpi, lena.size[1]/dpi
>>>>
>>>> fig = plt.figure(figsize=figsize)
>>>> #fig.patch.set_alpha(0.5)
>>>> ax = fig.add_subplot(111)
>>>> #ax.patch.set_alpha(0.5)
>>>>
>>>> ax.imshow(lena, origin='lower')
>>>>
>>>> ax.contourf(z2,[10,15,20,25,30,35,40,45,50,55,60,65],alpha=0.7)
>>>> show()
>>>> ############################
>>>>
>>>>
>>>> Can anyone help me with this problem?
>>>>
>>>> Thanks for reading,
>>>> Pete.
>>>>
>>>>
>>>
>>>
>>>
>>
>>
>>
>
> --
> Michael Droettboom
> Science Software Branch
> Operations and Engineering Division
> Space Telescope Science Institute
> Operated by AURA for NASA
>
>

It doesn't seem to matter whether the filled contours are drawn with 
edges or not -- the cuts are still visible because they're caused by 
over-drawing of the fill.  (You can set linewidth=0 to try this.)  But 
maybe I misunderstand your question.

Cheers,
Mike

kippertoffee wrote:
> Thank you for your reply Michael.
>
> Is it possible to make the lines in the contourf plot completely transparent
> using an alpha setting? That would make a reasonable workaround as I intend
> to overlay black contours anyway.
>
>  I've had a look at the source but it is way beyond me; I am a mere dabbler.
>
> Cheers,
> Pete.
>
>
> Michael Droettboom-3 wrote:
>   
>> This is a known issue with the contouring code.  It's borrowed from an 
>> earlier plotting package called GIST, and assumes that the renderer can 
>> not handle compound polygons (for example, donut-shaped, with both an 
>> inner and outer edge).  So instead, it draws "cuts" that go from the 
>> inner to the outer edge.  When anti-aliasing is turned on, there is a 
>> slight overlap or "drawing twice" along this edge which creates what 
>> looks like a line.  Unfortunately, this can't be remedied by plotting 
>> the contour fills and then plotting the contour edges over top (as is 
>> done is contourf_demo.py).
>>
>> As of matplotlib 0.98.x, matplotlib itself can handle compound paths, so 
>> we no longer need the cuts.  I've made a few attempts at updating the 
>> contouring code to avoid them, but got nowhere.  The contouring code is 
>> very opaque, almost magical code, and most who've dared to go in have 
>> barely made it out alive... ;)  That said, a fresh pair of eyes may have 
>> what it takes...
>>
>> As for a workaround, you could render your contour as opaque, save that 
>> out as an image and read it back in.  The code to do that won't be 
>> pretty, but it just might work.
>>
>> Cheers,
>> Mike
>>
>> kippertoffee wrote:
>>     
>>> Hello,
>>>
>>> I am attempting to overlay a filled contour over a custom image.
>>>
>>> I have managed to get something basic working, but i have encountered a
>>> problem:
>>>
>>> When the contourf plot is set to semi-transparent there are visible lines
>>> joining the bottom of the plot and the filled contour edges. I have
>>> attached
>>> an image of the plot.
>>>
>>> http://img232.imageshack.us/my.php?image=spambs6.png spam.png 
>>>
>>> The code i have used is below; please bear in mind I am not a programmer,
>>> so
>>> if the code seems botched, that's because it is.
>>>
>>> ###############################
>>>
>>> import matplotlib.pyplot as plt
>>> from pylab import *
>>> try:
>>>     import Image
>>> except ImportError, exc:
>>>     raise SystemExit("PIL must be installed to run this example")
>>>
>>> lena = Image.open('lena.jpg')
>>> dpi = rcParams['figure.dpi']
>>> figsize = lena.size[0]/dpi, lena.size[1]/dpi
>>>
>>> fig = plt.figure(figsize=figsize)
>>> #fig.patch.set_alpha(0.5)
>>> ax = fig.add_subplot(111)
>>> #ax.patch.set_alpha(0.5)
>>>
>>> ax.imshow(lena, origin='lower')
>>>
>>> ax.contourf(z2,[10,15,20,25,30,35,40,45,50,55,60,65],alpha=0.7)
>>> show()
>>> ############################
>>>
>>>
>>> Can anyone help me with this problem?
>>>
>>> Thanks for reading,
>>> Pete.
>>>       
>>
>>     
>
>   

-- 
Michael Droettboom
Science Software Branch
Operations and Engineering Division
Space Telescope Science Institute
Operated by AURA for NASA

Thank you for your reply Michael.

Is it possible to make the lines in the contourf plot completely transparent
using an alpha setting? That would make a reasonable workaround as I intend
to overlay black contours anyway.

 I've had a look at the source but it is way beyond me; I am a mere dabbler.

Cheers,
Pete.


Michael Droettboom-3 wrote:
> 
> This is a known issue with the contouring code.  It's borrowed from an 
> earlier plotting package called GIST, and assumes that the renderer can 
> not handle compound polygons (for example, donut-shaped, with both an 
> inner and outer edge).  So instead, it draws "cuts" that go from the 
> inner to the outer edge.  When anti-aliasing is turned on, there is a 
> slight overlap or "drawing twice" along this edge which creates what 
> looks like a line.  Unfortunately, this can't be remedied by plotting 
> the contour fills and then plotting the contour edges over top (as is 
> done is contourf_demo.py).
> 
> As of matplotlib 0.98.x, matplotlib itself can handle compound paths, so 
> we no longer need the cuts.  I've made a few attempts at updating the 
> contouring code to avoid them, but got nowhere.  The contouring code is 
> very opaque, almost magical code, and most who've dared to go in have 
> barely made it out alive... ;)  That said, a fresh pair of eyes may have 
> what it takes...
> 
> As for a workaround, you could render your contour as opaque, save that 
> out as an image and read it back in.  The code to do that won't be 
> pretty, but it just might work.
> 
> Cheers,
> Mike
> 
> kippertoffee wrote:
>> Hello,
>>
>> I am attempting to overlay a filled contour over a custom image.
>>
>> I have managed to get something basic working, but i have encountered a
>> problem:
>>
>> When the contourf plot is set to semi-transparent there are visible lines
>> joining the bottom of the plot and the filled contour edges. I have
>> attached
>> an image of the plot.
>>
>> http://img232.imageshack.us/my.php?image=spambs6.png spam.png 
>>
>> The code i have used is below; please bear in mind I am not a programmer,
>> so
>> if the code seems botched, that's because it is.
>>
>> ###############################
>>
>> import matplotlib.pyplot as plt
>> from pylab import *
>> try:
>>     import Image
>> except ImportError, exc:
>>     raise SystemExit("PIL must be installed to run this example")
>>
>> lena = Image.open('lena.jpg')
>> dpi = rcParams['figure.dpi']
>> figsize = lena.size[0]/dpi, lena.size[1]/dpi
>>
>> fig = plt.figure(figsize=figsize)
>> #fig.patch.set_alpha(0.5)
>> ax = fig.add_subplot(111)
>> #ax.patch.set_alpha(0.5)
>>
>> ax.imshow(lena, origin='lower')
>>
>> ax.contourf(z2,[10,15,20,25,30,35,40,45,50,55,60,65],alpha=0.7)
>> show()
>> ############################
>>
>>
>> Can anyone help me with this problem?
>>
>> Thanks for reading,
>> Pete.
> 
> 
> 

-- 
View this message in context: http://www.nabble.com/Filled-contour-transparency-issue-tp18850187p18856313.html
Sent from the matplotlib - users mailing list archive at Nabble.com.

On Wednesday 06 August 2008 09:24:18 Michael Droettboom wrote:

>   (I don't know if the
> new masked arrays have a C API we could use -- the old ones apparently
> didn't.)

They don't. I thought about it before, but decided to forget about it until I 
could find a job where I could learn C and focus exclusively on that for a 
few months. Unlikely anytime soon.

On Tuesday 05 August 2008 22:25:30 Mark Bakker wrote:
> Can we do the same? I am sure we can (not sure we want, as Google has been
> somewhat difficult to people writing scripts to manipulate images from
> google maps).

I tried doing something similar to this a while ago. You can use gdal to point 
to your tile of interest (e.g., 
http://khm3.google.com/kh?v=30&hl=en&t=tqsrsstr), which is a JPG (or PNG, 
can't remember), and then plot the RGB using imshow(). Difficulty is how to 
get the tile (it is documented somewhere, but I don't know how to do it). 
This is some sample code that seems to work, and hopefully gets the ball 
rolling :)

import osgeo.gdal as gdal

g = gdal.Open ("http://khm3.google.com/kh?v=30&hl=en&t=tqsrsstr")
R = g.GetRasterBand(1).ReadAsArray()
G =g.GetRasterBand(2).ReadAsArray()
B =g.GetRasterBand(3).ReadAsArray()
RGB = np.array((256,256,3)) # Clearly, there must be a better way of doing 
this!
RGB[:,:,0] = R
RGB[:,:,1] = G
RGB[:,:,2] = B

[...]


-- 
NERC Centre for Terrestrial Carbon Dynamics,
Department of Geography, University College London
Gower Street, London WC1E 6BT, UK

Eric Firing wrote:
> John Hunter wrote:
>   
>> On Tue, Aug 5, 2008 at 3:46 PM, Mark Bakker <ma...@gm...> wrote:
>>
>>     
>>> But if I replace the Inf by a nan: y[2] = np.nan, then it plots fine.
>>>
>>> I know, I know, I can do this with masked arrays, but it cannot be that hard
>>> to make this work correctly, and wouldn't that be much nicer? Desirable?
>>>       
>> The question is: what should happen with inf?  Do you know what matlab does?
>>     
>
> Matlab ignores it, same as with a nan.
>
> This needs a bit of thought and checking.  Mike went to some trouble, I 
> believe, to make nans work without running everything through masked 
> arrays--whether this is actually *faster* than doing an initial masking 
> operation when needed and then using masked arrays everywhere internally 
> when bad values are present, I don't know.  
It definitely was faster at the time I implemented it (particularly as 
the arrays get larger).  The difference is that masked arrays must be 
handled in Python, and converted to regular arrays before passing on to 
the Agg backend by performing a compress (which implies a memcpy) and 
inserting MOVETO codes in the appropriate place.  (I don't know if the 
new masked arrays have a C API we could use -- the old ones apparently 
didn't.) 

With the Agg backend, NaNs are all handled in C code -- the iterator 
over the array just skips over them, so there's no memory copy.  (The 
other backends still use Python, so the difference is probably a wash.)
> It is possible that 
> everything could be made to work with infs simply by changing all 
> "isnan(x)" to "~isfinite(x)", which has the advantage of being slightly 
> faster (surprisingly) as well as more general.
>   
As long as we can do the equivalent in C, that seems fine.  _path.cpp's get_path_extents is probably the most important place to be updated -- it currently doesn't even support NaNs.  And then, of course, we'll need to update the "isnan" stuff in agg_py_path_iterator.h

Cheers,
Mike


-- 
Michael Droettboom
Science Software Branch
Operations and Engineering Division
Space Telescope Science Institute
Operated by AURA for NASA

This is a known issue with the contouring code.  It's borrowed from an 
earlier plotting package called GIST, and assumes that the renderer can 
not handle compound polygons (for example, donut-shaped, with both an 
inner and outer edge).  So instead, it draws "cuts" that go from the 
inner to the outer edge.  When anti-aliasing is turned on, there is a 
slight overlap or "drawing twice" along this edge which creates what 
looks like a line.  Unfortunately, this can't be remedied by plotting 
the contour fills and then plotting the contour edges over top (as is 
done is contourf_demo.py).

As of matplotlib 0.98.x, matplotlib itself can handle compound paths, so 
we no longer need the cuts.  I've made a few attempts at updating the 
contouring code to avoid them, but got nowhere.  The contouring code is 
very opaque, almost magical code, and most who've dared to go in have 
barely made it out alive... ;)  That said, a fresh pair of eyes may have 
what it takes...

As for a workaround, you could render your contour as opaque, save that 
out as an image and read it back in.  The code to do that won't be 
pretty, but it just might work.

Cheers,
Mike

kippertoffee wrote:
> Hello,
>
> I am attempting to overlay a filled contour over a custom image.
>
> I have managed to get something basic working, but i have encountered a
> problem:
>
> When the contourf plot is set to semi-transparent there are visible lines
> joining the bottom of the plot and the filled contour edges. I have attached
> an image of the plot.
>
> http://img232.imageshack.us/my.php?image=spambs6.png spam.png 
>
> The code i have used is below; please bear in mind I am not a programmer, so
> if the code seems botched, that's because it is.
>
> ###############################
>
> import matplotlib.pyplot as plt
> from pylab import *
> try:
>     import Image
> except ImportError, exc:
>     raise SystemExit("PIL must be installed to run this example")
>
> lena = Image.open('lena.jpg')
> dpi = rcParams['figure.dpi']
> figsize = lena.size[0]/dpi, lena.size[1]/dpi
>
> fig = plt.figure(figsize=figsize)
> #fig.patch.set_alpha(0.5)
> ax = fig.add_subplot(111)
> #ax.patch.set_alpha(0.5)
>
> ax.imshow(lena, origin='lower')
>
> ax.contourf(z2,[10,15,20,25,30,35,40,45,50,55,60,65],alpha=0.7)
> show()
> ############################
>
>
> Can anyone help me with this problem?
>
> Thanks for reading,
> Pete.
>   

-- 
Michael Droettboom
Science Software Branch
Operations and Engineering Division
Space Telescope Science Institute
Operated by AURA for NASA

On Tue, 5 Aug 2008, John Hunter apparently wrote:
> Although intuitively I think of inf as very different from nan, my 
> default is to go with matlab like behavior in the absence 
> of compelling a argument otherwise.

gnuplot also ignores them.
(I am not arguing this is the correct behavior;
just providing a data point.)

Cheers,
Alan Isaac

A little follow-up.
When I use keyword argument inline=False, it doesn't remove the lines
without a label.

So it seems that when using inline=True the unlabeled contours get a white
box, but no label (because it doesn't fit) which essentially removes the
entire contour.

Mark

On Wed, Aug 6, 2008 at 2:27 PM, Mark Bakker <ma...@gm...> wrote:

> Hello list -
>
> There seems to be a bug in labeling contour lines.
> When I call clabel, it removes all contours that are not labeled (because
> the label doesn't fit on the section of contour, I presume).
> This seems like a bug to me (or a really odd feature).
>
> Easy example:
>
> >>> x,y = meshgrid( linspace(-10,10,50), linspace(-10,10,50) )
> >>> z = log(x**2 + y**2)
> >>> cobj = contour(x,y,z)
> >>> cobj.clabel()
> <a list of 8 text.Text objects>
> >>> draw()
>
> And now all contours without a label are gone. On my machine it draws
> labels on contours from 1 through 5, and erases the contours in the middle
> of the plot with values -2, -1, and 0.
>
> Mark
>
>

Hello,

I am attempting to overlay a filled contour over a custom image.

I have managed to get something basic working, but i have encountered a
problem:

When the contourf plot is set to semi-transparent there are visible lines
joining the bottom of the plot and the filled contour edges. I have attached
an image of the plot.

http://img232.imageshack.us/my.php?image=spambs6.png spam.png 

The code i have used is below; please bear in mind I am not a programmer, so
if the code seems botched, that's because it is.

###############################

import matplotlib.pyplot as plt
from pylab import *
try:
    import Image
except ImportError, exc:
    raise SystemExit("PIL must be installed to run this example")

lena = Image.open('lena.jpg')
dpi = rcParams['figure.dpi']
figsize = lena.size[0]/dpi, lena.size[1]/dpi

fig = plt.figure(figsize=figsize)
#fig.patch.set_alpha(0.5)
ax = fig.add_subplot(111)
#ax.patch.set_alpha(0.5)

ax.imshow(lena, origin='lower')

ax.contourf(z2,[10,15,20,25,30,35,40,45,50,55,60,65],alpha=0.7)
show()
############################


Can anyone help me with this problem?

Thanks for reading,
Pete.
-- 
View this message in context: http://www.nabble.com/Filled-contour-transparency-issue-tp18850187p18850187.html
Sent from the matplotlib - users mailing list archive at Nabble.com.

Hello list -

There seems to be a bug in labeling contour lines.
When I call clabel, it removes all contours that are not labeled (because
the label doesn't fit on the section of contour, I presume).
This seems like a bug to me (or a really odd feature).

Easy example:

>>> x,y = meshgrid( linspace(-10,10,50), linspace(-10,10,50) )
>>> z = log(x**2 + y**2)
>>> cobj = contour(x,y,z)
>>> cobj.clabel()
<a list of 8 text.Text objects>
>>> draw()

And now all contours without a label are gone. On my machine it draws labels
on contours from 1 through 5, and erases the contours in the middle of the
plot with values -2, -1, and 0.

Mark

Never mind, I found it.
The solution is:

cobj = contour(x,y,z)

cobj.clabel(manual=True)

How nice!

Mark

On Wed, Aug 6, 2008 at 10:05 AM, Mark Bakker <ma...@gm...> wrote:

> Hello list -
>
> I read that in 0.98.3 we can manually select contour label locations!
>
> I searched around, but couldn't find any instructions.
>
> Can anybody point me in the right direction?
>
> Thanks, Mark
>

Mark Bakker wrote:
> Can we set the markerspacing in mpl?
> 
> If I do
> 
> plot( linspace(0,10,100), 'o' )

You can try the following approach: First plot the line and then plot 
the markers separately (and set colors).

x = linspace(0,10,100)
y = x
plot(x, y, '-')
plot(x[::10], y[::10], linestyle='', marker='o')

Manuel

> I get 100 markers. What if I want to plot every tenth marker? Or better
> even, what if I want to have a certain spacing between markers.
> 
> I know how to work around this, of course (just plot every tenth point), but
> I was looking for a keyword argument or so. I thought that would exist and
> be useful.
> 
> Sorry to flood the list with questions this week.
> 
> Mark
> 
> 
> 
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