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From: Alan G Isaac <aisaac@am...>  20050719 22:12:16

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? 
From: Woodrow Smith <rekuehn@gm...>  20050719 21:51:56

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 
From: Jeff Whitaker <jswhit@fa...>  20050719 21:17:56

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_utilities3.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 twodimensional random data interpolation package based on Dave Watson's nngridr." Jeff  Jeffrey S. Whitaker Phone : (303)4976313 Meteorologist FAX : (303)4976449 NOAA/OAR/CDC R/CDC1 Email : Jeffrey.S.Whitaker@... 325 Broadway Office : Skaggs Research Cntr 1D124 Boulder, CO, USA 803033328 Web : http://tinyurl.com/5telg 
From: Chris Barker <Chris.B<arker@no...>  20050719 20:48:25

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://www2.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) 5266959 voice 7600 Sand Point Way NE (206) 5266329 fax Seattle, WA 98115 (206) 5266317 main reception Chris.Barker@... 
From: Peter Groszkowski <pgroszko@ge...>  20050719 18:08:41

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 
From: Eric Emsellem <emsellem@ob...>  20050719 16:46:01

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 emsellem@... 9 av. CharlesAndre tel: +33 4 78 86 83 84 69561 SaintGenis Laval Cedex fax: +33 4 78 86 83 86 France http://wwwobs.univlyon1.fr/eric.emsellem =============================================================== 
From: Ted Drain <ted.drain@jp...>  20050719 16:26:07

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 
From: Andrew Straw <strawman@as...>  20050719 15:59:10

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. 
From: Eric Emsellem <emsellem@ob...>  20050719 09:18:50

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 emsellem@... 9 av. CharlesAndre tel: +33 4 78 86 83 84 69561 SaintGenis Laval Cedex fax: +33 4 78 86 83 86 France http://wwwobs.univlyon1.fr/eric.emsellem =============================================================== 
From: Mark Engelhardt <marke@st...>  20050719 05:48:27

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_valmin_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/sitepackages/matplotlib/pylab.py", line 1737, in clabel ret = gca().clabel(*args, **kwargs) File "/sw/lib/python2.4/sitepackages/matplotlib/axes.py", line 1245, in clabel return self._contourLabeler.clabel(*args, **kwargs) File "/sw/lib/python2.4/sitepackages/matplotlib/contour.py", line 186, in clabel self.inline_labels(levels, contours, colors, fslist, fmt) File "/sw/lib/python2.4/sitepackages/matplotlib/contour.py", line 399, in inline_labels x,y, rotation, ind = self.locate_label(slc, lw) File "/sw/lib/python2.4/sitepackages/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. 
From: Matt Newville <newville@ca...>  20050719 03:38:54

> 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 
From: Steve Chaplin <stevech1097@ya...>  20050719 02:57:09

> On Fri, 20050715 at 20:28 0700, > matplotlibusersrequest@... 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 nonversion 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 
From: Dev Gorur <dgorur@gm...>  20050719 00:30:56

Hello, I found the following post on matplotlibusers. 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 oneline 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@...> Re: Using color in fill =20 20050106 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 01 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 nonpublic 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) 8594114 > 333 Ravenswood Avenue G273 > Menlo Park, CA 94025 email: leger@... > > >  > The SF.Net email is sponsored by: Beat the postholiday blues > Get a FREE limited edition SourceForge.net tshirt from ThinkGeek. > It"s fun and FREE  well, almost....http://www.thinkgeek.com/sfshirt > _______________________________________________ > Matplotlibusers mailing list > Matplotlibusers@... > https://lists.sourceforge.net/lists/listinfo/matplotlibusers 