Mailman 3 May 2005 - SciPy-User

weave inline functions recompiling on first run
by Ryan Krauss May 20, 2005

May 20, 2005

I have a function that uses weave inline that recompiles the first time I run a script every time I start ipython, even though I have not changed the script in some time. The first time the script I get the message: repairing catalog by removing key file changed What can cause this? The code is below. Thanks, Ryan def thresh(iterin, value, startind=0, above=1): # ind=-1 stopind=len(iterin) print('In thresh') print('type(value)='+str(type(value))) print('type(iterin[0])='+str(type(iterin[0]))) print('type(startind)='+str(type(startind))) print('type(stopind)='+str(type(stopind))) print('type(above)='+str(type(above))) code=""" #line 21 "rwkdataproc.py" int ind; for(int j=startind;j<stopind;j++){ if(above>0){ if(iterin(j)>=value){ ind=j; break; } } else{ if(iterin(j)<=value){ ind=j; break; } } } return_val = ind; """ N=inline_tools.inline(code,['iterin','value','above','startind','stopind'], compiler='gcc', type_converters = cblitz, verbose = 1) return N

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send me your blurbs
by John Hunter May 20, 2005

May 20, 2005

If you are using python for high performance or scientific computing, could I ask you to send me a blurb (one or two sentences) on what you are using it for and if you have any publications or references related to this work (the refs don't have to be specifically about the python stuff) please include them (extra points for bibtex). I am writing some grant text justifying python in scientific computing and would like to have a range of examples across disciplines to provide. If I could get these today or tomorrow that would be very helpful! Please send these to me off list. Thanks! JDH

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re: [SciPy-user] send me your blurbs
by Brendan Simons May 20, 2005

May 20, 2005

We use scipy to do non-linear curve-fitting of dimensional data, as part of our nuclear fuel inspection business. I don't have any references for you, as all our publications belong to our clients. Brendan -- Brendan Simons, Project Engineer Stern Laboratories, Hamilton Ontario

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Re: send me your blurbs
by Tom Kornack May 20, 2005

May 20, 2005

I use scipy and python in general to efficiently analyze large data sets from an experiment that searches for CPT and Lorentz Violation using an atomic magnetometer. Analysis typically involves lots of fitting, statistics and complex data manipulation. I have found that my python implementation of our analysis routines is more robust for very large datasets compared with similar C code. It's also just about as fast as the C routines, to the surprise of everyone. All my figures are now generated using PyX, which I find quite pleasing. Tom Kornack @Article{Kominis:2003, author = {Iannis K. Kominis and Thomas Whitmore Kornack and Joel C. Allred and Michael Valeriovich Romalis}, title = {A subfemtotesla multichannel atomic magnetometer}, journal = {Nature}, day = 10, month = {April}, year = 2003, volume = 422, number = 6932, pages = {596--599}, url = {http://www.nature.com/cgi-taf/DynaPage.taf?file=/nature/ journal/v422/n6932/abs/nature01484_fs.html} } @Article{Kornack:2002, author = {Thomas Whitmore Kornack and Michael Valeriovich Romalis}, title = {Dynamics of Two Overlapping Spin Ensembles Interacting by Spin Exchange}, journal = PRL, day = 4, month = {December}, year = 2002, volume = 89, number = 25, pages = {253002}, url = {http://link.aps.org/abstract/PRL/v89/e253002} } http://kornack.com Fundamental Symmetries Lab, Princeton University 609-716-7259 (h), 609-933-2186 (m), 609-258-0702 (w), 609-258-1625 (f) Thomas Kornack, 157 North Post Road, Princeton Junction, NJ 08550-5009

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ANN: Veusz-0.6 released
by Jeremy Sanders May 19, 2005

May 19, 2005

SciPy users may be interested in the new feature of embedding Veusz in other Python programs. Veusz runs in its own thread, so that the other Python program can continue to run. Veusz 0.6 --------- Velvet Ember Under Sky Zenith ----------------------------- http://home.gna.org/veusz/ Veusz is Copyright (C) 2003-2005 Jeremy Sanders <jeremy(a)jeremysanders.net> Licenced under the GPL (version 2 or greater) Veusz is a scientific plotting package written in Python (currently 100% Python). It uses PyQt for display and user-interfaces, and numarray for handling the numeric data. Veusz is designed to produce publication-ready Postscript output. Veusz provides a GUI, command line and scripting interface (based on Python) to its plotting facilities. The plots are built using an object-based system to provide a consistent interface. Changes from 0.5: Please refer to ChangeLog for all the changes. Highlights include: * Major UI enhancements - much faster to control now, more dialogs * Veusz can be embedded within other non-PyQt Python programs. Its plots can be updated at any time from the embedding program using the command line interface. * Dialogs for manipulating datasets using expressions, and direct editing * Multiple documents can be opened simultaneously * Lots of bug fixes (e.g. log axes improvement, rotation of labels) * Unicode support in plots Features of package: * X-Y plots (with errorbars) * Stepped plots (for histograms) * Line plots * Function plots * Fitting functions to data * Stacked plots and arrays of plots * Plot keys * Plot labels * LaTeX-like formatting for text * EPS output * Simple data importing * Scripting interface * Save/Load plots * Dataset manipulation * Embed Veusz within other programs To be done: * Contour plots * Images * UI improvements * Import filters (for qdp and other plotting packages, fits, csv) Requirements: Python (probably 2.3 or greater required) http://www.python.org/ Qt (free edition) http://www.trolltech.com/products/qt/ PyQt (SIP is required to be installed first) http://www.riverbankcomputing.co.uk/pyqt/ http://www.riverbankcomputing.co.uk/sip/ numarray http://www.stsci.edu/resources/software_hardware/numarray Microsoft Core Fonts (recommended) http://corefonts.sourceforge.net/ For documentation on using Veusz, see the "Documents" directory. The manual is in pdf, html and text format (generated from docbook). If you enjoy using Veusz, I would love to hear from you. Please join the mailing lists at https://gna.org/mail/?group=veusz to discuss new features or if you'd like to contribute code. The newest code can always be found in CVS. If non GPL projects are interested in using Veusz code, please contact me. I am happy to consider relicencing code for other free projects, if I am legally allowed to do so. Cheers Jeremy

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scipy Microsoft Windows installer for Python 2.4?
by Jim Vickroy May 19, 2005

May 19, 2005

Hello scipy users, Could someone tell me when/if a MS Windows installer for scipy and Python 2.4 will be available? A search of past postings revealed a similar question posted 2005-Feb. Thanks, -- jv

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strange behavior in RandomArray.randint()
by Tom Denniston May 19, 2005

May 19, 2005

I am running under python 1.4 and windows XP. I get the following results in my python interpretter: -------------------------------------------- n=0 import RandomArray while 1: arr = RandomArray.randint(0, 2509, 252) for x in arr: if x>2508: raise "Found number greater than 2508: " + str(x) + " on iteration " + str(n) n=n+1 Traceback (most recent call last): File "<pyshell#43>", line 5, in -toplevel- raise "Found number greater than 2508: " + str(x) + " on iteration " + str(n) Found number greater than 2508: 2509 on iteration 91719 ------------------------------------------- Even though the Numeric reference (see below) on RandomArray class claims that the number is strictly less than the max. Does anyone know what might cause this problem. Does SciPy have an alternative approach to generating uniform random numbers that is more reliable? randint(minimum, maximum, shape=ReturnFloat) The randint() function returns an array of the specified shape and containing random (standard) integers greater than or equal to minimum and strictly less than maximum . If no shape is specified, a single number is returned. (exerpt from http://www.pfdubois.com/numpy/html2/numpy-19.html#pgfId-303108)

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Matrix docs?
by Skip Montanaro May 19, 2005

May 19, 2005

I'm the "Python guy" at work, not a scientific programmer. I'm trying to help our researchers start using Python and SciPy (they are used to R, Matlab and SPlus). We're all having trouble finding useful documentation for extremely basic stuff. There's a mat() function that returns a Matrix object, but I can't find any documentation on this Matrix object. The only example I have of mat() usage is in the SciPy tutorial and it appears to use some weird string form as input: mat('[1 3 5; 2 5 1; 2 3 8]') I thought, "surely there must be some way to create a Matrix from a list of lists?" The obvious experiment works: mat([[1, 3, 5], [2, 5, 1], [2, 3, 8]]) but it seems odd to me that this isn't the form shown in the tutorial. My feeble attempts to find something come up empty: http://oliphant.ee.byu.edu:81/scipy_base/mat http://www.scipy.org/documentation/apidocs/scipy/scipy.linalg.matfuncs.html >>> info(mat) Matrix(data, typecode=None, copy=1, savespace=0) None I eventually stumbled on the NumPy docs. It has an array, and I then noticed that the scipy package exports an array() function, which at first glance seems to be about the same as mat(). What's the difference between mat() and array()? Is there some more cohesive documentation? Thanks, -- Skip Montanaro skip(a)pobox.com

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Tutorial on advanced slicing with the DCT
by Travis Oliphant May 19, 2005

May 19, 2005

I just checked in a module implementing the Discrete Cosine Transform into the image library of scipy. The main reason I'm advertising on the scipy users list is that it shows an example of using slices to accomplish generic indexing. The DCT can be implemented using the FFT on a specifically sliced version of the sequence. Basically the DCT can be implemented using an FFT of xtilde where xtilde[:N/2] = x[::2] xtilde[N/2:] = x[N::-2] But, I wanted to do this kind of slicing on an arbitrary axis. So, if the user-provided axis was -2 I wanted the first of these to be: xtilde[...,:N/2,:] = x[...,:N/2,:] or if axis=0 this should be xtilde[:N/2,...] = x[:N/2,...] In order to do that I used a tuple of slice objects on each side xtilde[slice0] = xtilde[slice1] where slice0 is a tuple of slice objects with slice?[axis] set to the correct slicing behavior. slice objects can be contructed using sl = slice(arg1, arg2, arg3) where x[sl] will act equivalently to x[arg1:arg2:arg3] I thought that the solution provided a good example for how to do these sorts of things. If others have even better solutions, please let me know. Best regards, -Travis O.

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import error on OS X 10.4
by Benjamin McBride May 18, 2005

May 18, 2005

I'm having a problems getting scipy to run on OS X Tiger. I've tried 0.3.2 as well as CVS sources, but get the same error when trying to import scipy. Has anyone had success building scipy on Tiger? Any help would be appreciated, Ben McBride Numeric Version 23.8 10:17 PM:Numeric-23.8:509$ python Python 2.3.5 (#1, Mar 20 2005, 20:38:20) [GCC 3.3 20030304 (Apple Computer, Inc. build 1809)] on darwin Type "help", "copyright", "credits" or "license" for more information. >>> import scipy Traceback (most recent call last): File "<stdin>", line 1, in ? File "/System/Library/Frameworks/Python.framework/Versions/2.3/lib/ python2.3/site-packages/scipy/__init__.py", line 11, in ? from scipy_base import * File "/System/Library/Frameworks/Python.framework/Versions/2.3/lib/ python2.3/site-packages/scipy_base/__init__.py", line 5, in ? import numerix File "/System/Library/Frameworks/Python.framework/Versions/2.3/lib/ python2.3/site-packages/scipy_base/numerix.py", line 59, in ? from _nc_imports import * File "/System/Library/Frameworks/Python.framework/Versions/2.3/lib/ python2.3/site-packages/scipy_base/_nc_imports.py", line 10, in ? from fastumath import alter_numeric, restore_numeric ImportError: cannot import name alter_numeric

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