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I just want to see my figure displayed in a Tkinter window,
without using pylab, with no extras.
No other goals right now.
Is
http://matplotlib.sourceforge.net/examples/embedding_in_tk.py
essentially a *minimal* example of how to do this?
(Aside from the title and toolbar stuff.)
This is a completely naive question.
E.g., choice of backend never implies that we can avoid 
explicitly embedding, as this example illustrates, right?
Thanks,
Alan Isaac
PS What happened to the object oriented "intro" that was 
linked from the Matplotlib page for awhile? Or did I just 
overlook it?

I have image data 2d array with values that spans several decades. It
would be extremely useful for me to be able to plot this data with
imshow using a colorbar/color scale that is logarithmic. In the past I
have just taken the log of the data, but that solution is not really
acceptable for me. Any suggestions would be welcome. Perhaps someone
could give me a idea on how to modify matplotlib to have this
functionality. Thanks.
R Kuehn

Eric Emsellem wrote:
> Hi,
>
> I know this may be a question for scipy or numarray but since 
> matplotlib is using something close to what I wish to have..., here is 
> the question:
>
> - I would like to use some 2D interpolation of a set of x, y, z points 
> (not regularly positioned). If possible I would like to test various 
> interpolation schemes (bilinear, splines, etc), and have a FLAG to 
> tell me if I am trying to EXTRAPOLATE (so that I can control the 
> output). I looked at scipy but this is really bad: as far as I 
> understand the doc mentions that it takes 1D array (what I want), but 
> in fact works on 2D arrays (NOT what I want).... (and it only provides 
> splines)
>
> I know that imshow has this built in with many different options for 
> the visualisation. So how is this done? Is it hard coded in one of the 
> matplotlib routine ? Could not find it there...
>
> thanks for the help
>
> Eric Emsellem
>
Eric: There are a couple of modules in CDAT (http://cdat.sf.net) to do 
this. See
http://rainbow.llnl.gov/software/cdat/support/cdat_utilities/cdat_utilities-3.php
Look for the 'ngmath' module. I've found that ngmath.natgrid works 
quite well. Here's a quick description from the docstring:
"natgrid - a two-dimensional random data interpolation package based on 
Dave Watson's nngridr."
-Jeff
-- 
Jeffrey S. Whitaker Phone : (303)497-6313
Meteorologist FAX : (303)497-6449
NOAA/OAR/CDC R/CDC1 Email : Jef...@no...
325 Broadway Office : Skaggs Research Cntr 1D-124
Boulder, CO, USA 80303-3328 Web : http://tinyurl.com/5telg

Andrew Straw wrote:
> You have at least 2 general approaches: Delaunay triangulation and 
> splines. Straight Delaunay triangulation would be linear interpolation, 
> but can be embellished with fancier interpolation techniques. As far as 
> I know, Delaunay triangulation and associated interpolation routines are 
> not (yet) available in scipy.
I don't think they are. I've been planning to write python wrappers for
Jonathan Shewchuk's triangle code, but if someone wanted to beat me to
it....
http://www-2.cs.cmu.edu/~quake/triangle.html
> Surface splines are available in scipy -- 
> check out bisplrep/bisplev.
Can you do surface splines with irregularly spaced points?
> The
> contour routines are more sophisticated and may be useful to you, but I 
> haven't followed how they work.
I'm pretty sure they require regularly spaced points as well. Or at
least "logically Cartesian" points.
-Chris
-- 
Christopher Barker, Ph.D.
Oceanographer
 		
NOAA/OR&R/HAZMAT (206) 526-6959 voice
7600 Sand Point Way NE (206) 526-6329 fax
Seattle, WA 98115 (206) 526-6317 main reception
Chr...@no...

I do this in python/matplotlib using hardy's multiquadric 
interpolation.... I've posted here before promising to attach some code, 
but haven't done so yet, since really need to clean things up a little. 
Will try to get it done on my 10 hour flight tonight... and post within 
the next few days...
Cheers,
Peter
Eric Emsellem wrote:
> Hi
> thanks for the input, however scipy interpolation scheme is on a 
> regular grid.
>
> The positions I have are not even on an ORTHOGONAL grid: they are 
> randomly distributed!
> So I have a set of x,y random positions with Z values and I wish to 
> know the interpolated value
> at a new position xnew, ynew...
>
> It seems that this does not exist in scipy. Someone pointed out 
> Scientific Python but this again does not work
> (using irregular but orthogonal grids)...
>
> This would be pretty bad if I cannot do this in python!!!
>
> Any help welcome!
>
> Cheers
> Eric
>
> Eric Emsellem wrote:
>
>> Hi,
>>
>> I know this may be a question for scipy or numarray but since 
>> matplotlib is using something close to what I wish to have..., here 
>> is the question:
>>
>> - I would like to use some 2D interpolation of a set of x, y, z 
>> points (not regularly positioned). If possible I would like to test 
>> various interpolation schemes (bilinear, splines, etc), and have a 
>> FLAG to tell me if I am trying to EXTRAPOLATE (so that I can control 
>> the output). I looked at scipy but this is really bad: as far as I 
>> understand the doc mentions that it takes 1D array (what I want), but 
>> in fact works on 2D arrays (NOT what I want).... (and it only 
>> provides splines)
>>
>> I know that imshow has this built in with many different options for 
>> the visualisation. So how is this done? Is it hard coded in one of 
>> the matplotlib routine ? Could not find it there...
>>
>> thanks for the help
>>
>> Eric Emsellem
>>
>> On Jul 19, 2005, at 2:17 AM, Eric Emsellem wrote:
>>
>> > - I would like to use some 2D interpolation of a set of x, y, z 
>> points > (not regularly positioned). If possible I would like to test 
>> various > interpolation schemes (bilinear, splines, etc), and have a 
>> FLAG to > tell me if I am trying to EXTRAPOLATE (so that I can 
>> control the > output). I looked at scipy but this is really bad: as 
>> far as I > understand the doc mentions that it takes 1D array (what I 
>> want), but > in fact works on 2D arrays (NOT what I want).... (and it 
>> only provides > splines)
>>
>> You have at least 2 general approaches: Delaunay triangulation and 
>> splines. Straight Delaunay triangulation would be linear 
>> interpolation, but can be embellished with fancier interpolation 
>> techniques. As far as I know, Delaunay triangulation and associated 
>> interpolation routines are not (yet) available in scipy. Surface 
>> splines are available in scipy -- check out bisplrep/bisplev.
>>
>> As far as a FLAG to tell if you want to EXTRAPOLATE, I don"t know. 
>> They may not be in ALL CAPS, either, so read the fine print. :)
>>
>> > I know that imshow has this built in with many different options 
>> for > the visualisation. So how is this done? Is it hard coded in one 
>> of the > matplotlib routine ? Could not find it there...
>>
>> I don"t think imshow does anything as fancy as what you suggest. The 
>> contour routines are more sophisticated and may be useful to you, but 
>> I haven"t followed how they work.
>>
>> 
>>
>
-- 
Peter Groszkowski Gemini Observatory
Tel: +1 808 9742509 670 N. A'ohoku Place
Fax: +1 808 9359235 Hilo, Hawai'i 96720, USA 

Hi
thanks for the input, however scipy interpolation scheme is on a regular 
grid.
The positions I have are not even on an ORTHOGONAL grid: they are 
randomly distributed!
So I have a set of x,y random positions with Z values and I wish to know 
the interpolated value
at a new position xnew, ynew...
It seems that this does not exist in scipy. Someone pointed out 
Scientific Python but this again does not work
(using irregular but orthogonal grids)...
This would be pretty bad if I cannot do this in python!!!
Any help welcome!
Cheers
Eric
Eric Emsellem wrote:
> Hi,
>
> I know this may be a question for scipy or numarray but since 
> matplotlib is using something close to what I wish to have..., here is 
> the question:
>
> - I would like to use some 2D interpolation of a set of x, y, z points 
> (not regularly positioned). If possible I would like to test various 
> interpolation schemes (bilinear, splines, etc), and have a FLAG to 
> tell me if I am trying to EXTRAPOLATE (so that I can control the 
> output). I looked at scipy but this is really bad: as far as I 
> understand the doc mentions that it takes 1D array (what I want), but 
> in fact works on 2D arrays (NOT what I want).... (and it only provides 
> splines)
>
> I know that imshow has this built in with many different options for 
> the visualisation. So how is this done? Is it hard coded in one of the 
> matplotlib routine ? Could not find it there...
>
> thanks for the help
>
> Eric Emsellem
>
>On Jul 19, 2005, at 2:17 AM, Eric Emsellem wrote:
> 
> > - I would like to use some 2D interpolation of a set of x, y, z points 
> > (not regularly positioned). If possible I would like to test various 
> > interpolation schemes (bilinear, splines, etc), and have a FLAG to 
> > tell me if I am trying to EXTRAPOLATE (so that I can control the 
> > output). I looked at scipy but this is really bad: as far as I 
> > understand the doc mentions that it takes 1D array (what I want), but 
> > in fact works on 2D arrays (NOT what I want).... (and it only provides 
> > splines)
> 
> You have at least 2 general approaches: Delaunay triangulation and 
> splines. Straight Delaunay triangulation would be linear interpolation, 
> but can be embellished with fancier interpolation techniques. As far 
> as I know, Delaunay triangulation and associated interpolation routines 
> are not (yet) available in scipy. Surface splines are available in 
> scipy -- check out bisplrep/bisplev.
> 
> As far as a FLAG to tell if you want to EXTRAPOLATE, I don"t know. 
> They may not be in ALL CAPS, either, so read the fine print. :)
> 
> > I know that imshow has this built in with many different options for 
> > the visualisation. So how is this done? Is it hard coded in one of the 
> > matplotlib routine ? Could not find it there...
> 
> I don"t think imshow does anything as fancy as what you suggest. The 
> contour routines are more sophisticated and may be useful to you, but I 
> haven"t followed how they work.
> 
> 
>
-- 
===============================================================
Observatoire de Lyon ems...@ob...
9 av. Charles-Andre tel: +33 4 78 86 83 84
69561 Saint-Genis Laval Cedex fax: +33 4 78 86 83 86
France http://www-obs.univ-lyon1.fr/eric.emsellem
===============================================================

We have several users that routinely plot data sets that "wrap" around an 
axis. For example:
- An angle data set that is angle as a function of time. The y axis would 
be from 0 to 360.
- Any quantity that is a function of hour of the data. The X axis would go 
from 0 to 24.
In both of these cases they want to create a line plot but they don't want 
to have the extra line that shoots across the plot when the data 
wraps. For example, assume you have the angle data set like this:
import pylab as p
x = [ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9 ]
y = []
for i in x:
 y.append( ( 23 + 75*i ) % 360 )
p.plot( x, y )
p.ylim( [ 0, 360 ] )
p.show()
It would be nice if this data could somehow be automatically transformed to 
wrap correctly. Ideally, two extra points are inserted for every 
"wrapping" that are linearly interpolated to fall directly on the axis 
bounds. So the correct plot would look like this (this is terrible way to 
generate it but at least you can see what it should look like):
x1 = [ 0, 1, 2, 3, 4, 4.507 ]
x2 = [ 4.507, 5, 6, 7, 8, 9 ]
y1, y2 = [], []
for i in x1:
 y1.append( ( 23 + 75*i ) )
for i in x2:
 y2.append( ( 23 + 75*i ) %360 )
p.plot( x1, y1 )
p.plot( x2, y2 )
p.ylim( [ 0, 360 ] )
p.show()
In ideal world it would be nice if this could be done automatically. Of 
course this does require some hueristic checking to decide if a point is 
actually crossing the wrap around value or actually moving away from the 
previous point. Does anyone have any thoughts on this or has anyone set up 
something like this before?
Ted

On Jul 19, 2005, at 2:17 AM, Eric Emsellem wrote:
> - I would like to use some 2D interpolation of a set of x, y, z points 
> (not regularly positioned). If possible I would like to test various 
> interpolation schemes (bilinear, splines, etc), and have a FLAG to 
> tell me if I am trying to EXTRAPOLATE (so that I can control the 
> output). I looked at scipy but this is really bad: as far as I 
> understand the doc mentions that it takes 1D array (what I want), but 
> in fact works on 2D arrays (NOT what I want).... (and it only provides 
> splines)
You have at least 2 general approaches: Delaunay triangulation and 
splines. Straight Delaunay triangulation would be linear interpolation, 
but can be embellished with fancier interpolation techniques. As far 
as I know, Delaunay triangulation and associated interpolation routines 
are not (yet) available in scipy. Surface splines are available in 
scipy -- check out bisplrep/bisplev.
As far as a FLAG to tell if you want to EXTRAPOLATE, I don't know. 
They may not be in ALL CAPS, either, so read the fine print. :)
> I know that imshow has this built in with many different options for 
> the visualisation. So how is this done? Is it hard coded in one of the 
> matplotlib routine ? Could not find it there...
I don't think imshow does anything as fancy as what you suggest. The 
contour routines are more sophisticated and may be useful to you, but I 
haven't followed how they work.

Hi,
I know this may be a question for scipy or numarray but since matplotlib 
is using something close to what I wish to have..., here is the question:
- I would like to use some 2D interpolation of a set of x, y, z points 
(not regularly positioned). If possible I would like to test various 
interpolation schemes (bilinear, splines, etc), and have a FLAG to tell 
me if I am trying to EXTRAPOLATE (so that I can control the output). I 
looked at scipy but this is really bad: as far as I understand the doc 
mentions that it takes 1D array (what I want), but in fact works on 2D 
arrays (NOT what I want).... (and it only provides splines)
I know that imshow has this built in with many different options for the 
visualisation. So how is this done? Is it hard coded in one of the 
matplotlib routine ? Could not find it there...
thanks for the help
Eric Emsellem
-- 
===============================================================
Observatoire de Lyon ems...@ob...
9 av. Charles-Andre tel: +33 4 78 86 83 84
69561 Saint-Genis Laval Cedex fax: +33 4 78 86 83 86
France http://www-obs.univ-lyon1.fr/eric.emsellem
===============================================================

I am trying to contour some data plots, and am running into an 
exception (it's a divide by zero problem, but I don't see how it's 
coming about). I read in a 3D grid then plot 2D slices of it. The 
program works for about 5 slices, then throws the exception. My 
relevant code is:
 figure()
 im = imshow(gridslice, interpolation='bicubic', origin='lower',\
 cmap=cm.hot, extent=dims, vmin = min_val, vmax = max_val, 
alpha=1)
 levels, colls = contour(gridslice, \
 arange(min_val,max_val, (max_val-min_val)/5),\
 origin='lower', linewidths=3, alpha = 1, extent=dims)
 clabel(colls, levels, inline=1, fmt='%1.2f', fontsize=12)
Traceback (most recent call last):
 File "./dx_slice_contours.py", line 64, in ?
 MakeContours('1_my_var.dx')
 File "./dx_slice_contours.py", line 56, in MakeContours
 clabel(colls, levels, inline=1, fmt='%1.2f', fontsize=12)
 File "/sw/lib/python2.4/site-packages/matplotlib/pylab.py", line 
1737, in clabel
 ret = gca().clabel(*args, **kwargs)
 File "/sw/lib/python2.4/site-packages/matplotlib/axes.py", line 
1245, in clabel
 return self._contourLabeler.clabel(*args, **kwargs)
 File "/sw/lib/python2.4/site-packages/matplotlib/contour.py", line 
186, in clabel
 self.inline_labels(levels, contours, colors, fslist, fmt)
 File "/sw/lib/python2.4/site-packages/matplotlib/contour.py", line 
399, in inline_labels
 x,y, rotation, ind = self.locate_label(slc, lw)
 File "/sw/lib/python2.4/site-packages/matplotlib/contour.py", line 
370, in locate_label
 dist = add.reduce(([(abs(s)[i]/L[i]) for i in range(xsize)]),-1)
OverflowError: math range error
I know that abs(s)[i] = is an array of zeros, L[i] = 0, and xsize = 1 
at this point.

> I searched backend_wx.py and backend_wxagg.py to find wx.__version__ but
> did not find it. So does that mean the wx backend does not need to use
> version checking?
backend_wx.py uses the new wx namespace, which only works with
wx version 2.4 and higher. This block in backend_wx.py: 
try:
 import wx
 backend_version = wx.VERSION_STRING
except:
 print >>sys.stderr, '...'
 sys.exit()
is therefore an effective version filter. I suppose we could
eventually _use_ the value in backend_version.
--Matt

> On Fri, 2005年07月15日 at 20:28 -0700,
> mat...@li... wrote:
> > I'm not familiar with pygtk.require(), but if it's anything like
> > 
> > wxversion.select()
> > 
> > Don't Get Rid of It!
> > 
> > No matter how hard we all try, packages are not totally backward 
> > compatible. Having a dependency without any version info in it is the 
> > road to hard to identify bugs. If matplotlib has been tested only with 
> > certain versions of pygtk, it's quite reasonable that folks get an error 
> > message if they try to run it with other versions. To do otherwise would 
> > be like having a dynamically linked app with non-version dynamic libs.
> > 
> > That being said, perhaps pygtk.require(), or the way it is being used, 
> > is not very well suited to this task. With wxversion, the select call 
> > must be made before any imports of wx. Thus, it should only be called in 
> > __main__. If you have a module (like matplotlib) that has been tested 
> > against certain versions, you should test for the version by checking 
> > wx.__version__, rather than calling wxversion.select(). The exception to 
> > this might be pylab for interactive use, where it is acting as the first 
> > importer of wx.
> > 
> > So, my suggestion is that if pygtk.require() is causing more trouble 
> > than it's worth, then figure out how to use it differently, rather than 
> > scrapping it all together.
> > 
> > -Chris
We already check the pygtk version by using gtk.pygtk_version.
pygtk.require() is more of a migration tool to help people move from
pygtk 1.0 to 2.0 when they still have both versions installed on the
same machine, and for some reason pygtk 1.0 is given preference in
sys.path.
I searched backend_wx.py and backend_wxagg.py to find wx.__version__ but
did not find it. So does that mean the wx backend does not need to use
version checking?
Steve
Send instant messages to your online friends http://au.messenger.yahoo.com 

Hello,
I found the following post on matplotlib-users. However, post reading
the 'docstring', I'm still unable to figure it out. I don't know how
to call the __call__ function in LinearSegmentedColormap in colors.py.
Could someone please help me out? All I need is a one-line command
that tells me how to give this beast a number between 0 and 1 and get
an rgb tuple.
Regards,
Dev
--------------------------------------------------------------
From: Perry Greenfield <perry@st...>
Re: Using color in fill =20
2005年01月06日 12:01
 Yes, colormaps are callable so you can call the colormap with either a=20
 scalar value or an
 array of values and what will be returned is a tuple of rgba values or=20
 an array (shape
 =3D 4, nelements). See the docstring on __call__ for=20
 LinearSegmentedColormap in colors.py
=20
 Perry
=20
 On Jan 6, 2005, at 3:18 PM, Carol Leger wrote:
=20
 > I am using fill to make filled polygons. I want to fill the polygons=20
 > with colors that reflect data values, similar to what imshow does.
 >
 > Is there a way to extract the rgb tuples from a Colormap? This could=20
 > be an array of N tuples, each tuple containing 3 0-1 floats that=20
 > describe the color or three separate arrays, one each for red, green=20
 > and blue.
 >
 > I made the mistake of using some non-public attributes of the class=20
 > colorMap to accomplish this in a previous version of matplotlib. That=
=20
 > was a mistake since Colormap._red_lut, Colormap._green_lut and=20
 > Colormap._blue_lut no longer exist.
 >
 > Once I have the array of tuples, I can determine which one I want and=20
 > create a hex string using rgb2hex to get a color suitable for use with=
=20
 > fill.
 >
 > I need the flexability to make the same plot using several different=20
 > color maps.
 > --=20
 > Ms. Carol A. Leger
 > SRI International=09=09=09Phone: (650) 859-4114
 > 333 Ravenswood Avenue G-273
 > Menlo Park, CA 94025 e-mail: leger@sr...
 >
 >
 > -------------------------------------------------------
 > The SF.Net email is sponsored by: Beat the post-holiday blues
 > Get a FREE limited edition SourceForge.net t-shirt from ThinkGeek.
 > It"s fun and FREE -- well, almost....http://www.thinkgeek.com/sfshirt
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