Mailman 3 March 2005 - NumPy-Discussion

Gaussian fits? Sum of Gaussians?
by Christian Meesters 08 Mar '05

08 Mar '05

Hi I was wondering whether there are scripts or modules around which can calculate, on a given 1D-Numarray or Numeric array, a sum of Gaussians? E.g. something like: x = sumofgaussians(input_array[, other_parameters]) where x would contain a list of arrays representing Gaussian curves, which, when added together, would result in (a good approximation of) the input_array. It would be nice, of course, if information like the standarddeviation and peak height would be associated with that data. Perhaps I am hoping for too much, but in this case you guys at least had a good laugh when reading these lines ;-) - and I'd had to write something myself or find it in other software ... Thanks a lot in advance, Christian

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Re: Gaussian fits? Sum of Gaussians
by Brendan Simons 08 Mar '05

08 Mar '05

I am not familiar enough with Stats to say exactly what you need, but you might try looking at the scipy statistics module: http://www.scipy.org/documentation/apidocs/scipy/scipy.stats.html If nothing else, you can use that to generate numeric arrays with gaussian (normal) distributions and add them together. -Brendan > Message: 1 > Date: Mon, 7 Mar 2005 00:08:58 -0800 (PST) > To: numpy-discussion(a)lists.sourceforge.net > From: "Christian Meesters" <cmeesters(a)ucdavis.edu> > Subject: [Numpy-discussion] Gaussian fits? Sum of > Gaussians? > > > Hi > > I was wondering whether there are scripts or modules > around which can calculate, on a given > 1D-Numarray or Numeric array, a sum of Gaussians? > E.g. something like: x = > sumofgaussians(input_array[, other_parameters]) > where x would contain a list of arrays > representing Gaussian curves, which, when added > together, would result in (a good > approximation of) the input_array. It would be nice, > of course, if information like the > standarddeviation and peak height would be > associated with that data. > > Perhaps I am hoping for too much, but in this case > you guys at least had a good laugh when > reading these lines ;-) - and I'd had to write > something myself or find it in other software ... > > Thanks a lot in advance, > Christian > > > > --__--__-- > > _______________________________________________ > Numpy-discussion mailing list > Numpy-discussion(a)lists.sourceforge.net > https://lists.sourceforge.net/lists/listinfo/numpy-discussion > > > End of Numpy-discussion Digest > ______________________________________________________________________ Post your free ad now! http://personals.yahoo.ca

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Numeric/numarray compatibility issue
by konrad.hinsen＠laposte.net 04 Mar '05

04 Mar '05

Following a bug report concerning ScientificPython with numarray, I noticed an incompatibility between Numeric and numarray, and I am wondering if this is intentional. In Numeric, the result of a comparison operation is an integer array. In numarray, it is a Bool array. Bool arrays seem to behave like Int8 arrays when arithmetic operations are applied. The net result is that print n.add.reduce(n.greater(n.arange(128), -1)) yields -128, which is not what I would expect. I can see two logically coherent points of views: 1) The Numeric view: comparisons yield integer arrays, which may be used freely in arithmetic. 2) The "logician's" view: comparisons yield arrays of boolean values, on which no arithmetic is allowed at all, only logical operations. The first approach is a lot more pragmatic, because there are a lot of useful idioms that use the result of comparisons in arithmetic, whereas an array of boolean values cannot be used for much else than logical operations. And now for my pragmatic question: can anyone come up with a solution that will work under both Numeric an numarray, won't introduce a speed penalty under Numeric, and won't leave the impression that the programmer had had too many beers? There is the quick hack print n.add.reduce(1*n.greater(n.arange(128), -1)) but it doesn't satisfy the last two criteria. Konrad. -- ------------------------------------------------------------------------ ------- Konrad Hinsen Laboratoire Leon Brillouin, CEA Saclay, 91191 Gif-sur-Yvette Cedex, France Tel.: +33-1 69 08 79 25 Fax: +33-1 69 08 82 61 E-Mail: khinsen(a)cea.fr ------------------------------------------------------------------------ -------

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Problem with dashes and savefig in 0.72.1
by kristen kaasbjerg 04 Mar '05

04 Mar '05

1) Running the dash_control.py example I get the following error message (the problem is present on both linux and windows installations): Traceback (most recent call last): File "/usr/lib/python2.3/lib-tk/Tkinter.py", line 1345, in __call__ return self.func(*args) File "/home/camp/s991416/lib/python/matplotlib/backends/backend_tkagg.py", line 140, in resize self.show() File "/home/camp/s991416/lib/python/matplotlib/backends/backend_tkagg.py", line 143, in draw FigureCanvasAgg.draw(self) File "/home/camp/s991416/lib/python/matplotlib/backends/backend_agg.py", line319, in draw self.figure.draw(self.renderer) File "/home/camp/s991416/lib/python/matplotlib/figure.py", line 338, in draw for a in self.axes: a.draw(renderer) File "/home/camp/s991416/lib/python/matplotlib/axes.py", line 1296, in draw a.draw(renderer) File "/home/camp/s991416/lib/python/matplotlib/lines.py", line 283, in draw lineFunc(renderer, gc, xt, yt) File "/home/camp/s991416/lib/python/matplotlib/lines.py", line 543, in _draw_dashed renderer.draw_lines(gc, xt, yt, self._transform) TypeError: CXX: type error. 2) And when using savefig I get : Traceback (most recent call last): File "dash_control.py", line 13, in ? savefig('dash_control') File "/home/camp/s991416/lib/python/matplotlib/pylab.py", line 763, in savefig try: ret = fig.savefig(*args, **kwargs) File "/home/camp/s991416/lib/python/matplotlib/figure.py", line 455, in savefig self.canvas.print_figure(*args, **kwargs) File "/home/camp/s991416/lib/python/matplotlib/backends/backend_tkagg.py", line 161, in print_figure agg.print_figure(filename, dpi, facecolor, edgecolor, orientation) File "/home/camp/s991416/lib/python/matplotlib/backends/backend_agg.py", line370, in print_figure self.draw() File "/home/camp/s991416/lib/python/matplotlib/backends/backend_agg.py", line319, in draw self.figure.draw(self.renderer) File "/home/camp/s991416/lib/python/matplotlib/figure.py", line 338, in draw for a in self.axes: a.draw(renderer) File "/home/camp/s991416/lib/python/matplotlib/axes.py", line 1296, in draw a.draw(renderer) File "/home/camp/s991416/lib/python/matplotlib/lines.py", line 283, in draw lineFunc(renderer, gc, xt, yt) File "/home/camp/s991416/lib/python/matplotlib/lines.py", line 543, in _draw_dashed renderer.draw_lines(gc, xt, yt, self._transform) __________________________________ Celebrate Yahoo!'s 10th Birthday! Yahoo! Netrospective: 100 Moments of the Web http://birthday.yahoo.com/netrospective/

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Some comments on the Numeric3 Draft of 1-Mar-05
by Colin J. Williams 04 Mar '05

04 Mar '05

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bdist-rpm problem
by Stephen Walton 04 Mar '05

04 Mar '05

Hi, All, A week or so ago, I posted to matplotlib-users about a problem with bdist_rpm. I'd asked about python 2.3 on Fedora Core 1. It turns out there are two problems. One is that even if one has python2.3 and python2.2 installed, bdist_rpm always calls the interpreter named 'python', which is 2.2 on FC1. The other problem is that in bdist_rpm.py there is a set of lines near line 307 which tests if the number of generated RPM files is 1. This fails because all of matplotlib, numeric, numarray and scipy generate a debuginfo RPM when one does 'python setup.py bdist_rpm'. (Why the RPM count doesn't fail with Python 2.3 on FC3 is beyond me, but nevermind.) The patch is at http://opensvn.csie.org/pyvault/rpms/trunk/python23/python-2.3.4-distutils-… and I have verified that after applying this patch to /usr/lib/python2.2/distutils/command/bdist_rpm.py on FC1 that 'python setup.py bdist_rpm' works for numarray 1.2.2, scipy current CVS, and matplotlib 0.72 (after changing setup.py for python2.2 as documented in the latter). It still fails with Numeric 23.6 however for reasons I'm still checking into; the failed "setup.py bdist_rpm" claims that arraytypes.c doesn't exist. Steve Walton

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PyTrilinos - Python interface to Trilinos libraries
by Nils Wagner 04 Mar '05

04 Mar '05

Hi all, A new release of Trilinos is available. It includes a Python interface to Trilinos libraries. http://software.sandia.gov/trilinos/release_5.0_notes.html Regards, Nils

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CVS version of Numeric3 compiles again
by Travis Oliphant 03 Mar '05

03 Mar '05

For any that tried to check out the CVS version of numeric3 while it was in a transition state of adding the new Python Scalar Objects, you can now try again and help me test it. The current CVS version of numeric3 builds on linux (there is some magic in the setup.py file to do some autoconfiguration stuff that I would like to see if it works on other platforms). The arrayobject is nearing completion. There are only a couple of things left to do before I can start tackling the ufuncobject (which is part-way transitioned but needs more numarray-inspired fixes). If anyone would like to help, now is a good time, since at least the codebase should compile and you can play with it. Best regards, -Travis

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RE: [Numpy-discussion] Some comments on the Numeric3 Draft of 1-M ar-05
by Sebastien.deMentendeHorne＠electrabel.com 03 Mar '05

03 Mar '05

> It might be useful to have a Table type where there is a header of some sort to keep track, > for each column of the column name name and the datatype in that column, so that the user > could, optionally specify validity checks. Another useful type for arrays representing physical values would be an array that keeps vectors for each dimension with index values. For instance, an object representing temperature at a given time in a given location would consist in data = N x M array of Float64 = [ [ 23, 34, 23], [ 31, 28,29] ] first_axis = N array of time = [ "01/01/2004", "02/01/2004" ] second_axis = M array of location = [ "Paris", "New York" ] All slicing operation would equivalently slice the corresponding axis. Assignment between arrays would be axis coherent (assigning "Paris" in one array to "Paris" in another while putting NaN or 0 if there is no correspondance). If indexing could also be done via component of *_axis, it would be also useful. Several field of applications could benefit of this (econometrics, monte carlo simulation, physical simulation, time series,...). In fact most of real data consist usually of values for tuples of general indices (e.g. temparature@("01/01/2004","Paris")) Hmmm, I think I was just thinking aloud :-) ======================================================= This message is confidential. It may also be privileged or otherwise protected by work product immunity or other legal rules. If you have received it by mistake please let us know by reply and then delete it from your system; you should not copy it or disclose its contents to anyone. All messages sent to and from Electrabel may be monitored to ensure compliance with internal policies and to protect our business. Emails are not secure and cannot be guaranteed to be error free as they can be intercepted, amended, lost or destroyed, or contain viruses. Anyone who communicates with us by email is taken to accept these risks. http://www.electrabel.be/homepage/general/disclaimer_EN.asp =======================================================

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PyObject arrays
by Garnet Chan 02 Mar '05

02 Mar '05

Hi All, Do PyObject arrays works, more specifically Numeric arrays of Numeric arrays? I've tried: from Numeric import * mat = zeros([2, 2], PyObject) mat[0, 0] = zeros([2, 2]) which gives ValueError: array too large for destination. It seems to be calling PyArray_CopyObject; I noticed that there was some special code to make arrays of strings work, but not for other objects. This is on Python 2.3.4 and Numeric 23.3 thanks, Garnet Chan

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