Mailman 3 September 2000 - NumPy-Discussion

Numeric addition: put
by Paul F. Dubois 17 Sep '00

17 Sep '00

In the CVS sources there is now a new function "put". "put" is roughly the opposite of "take" put(x, indices, values) is roughly x.flat[j] = values[j] for all j in indices The fine print will appear in the manuals shortly.

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Survey available on lapack_lite question
by Paul F. Dubois 14 Sep '00

14 Sep '00

I have started a survey on sourceforge which asks the question, should lapack_lite and the modules that depend upon it be moved to the optional Packages section. Pros: this would move these modules out of a privleged position into equality with other "application" packages. Their presence in the core is unnecessary. The compilation problems, as yet unsolved, with lapack_lite vs. alternate implementations, break the installation of the core even for people who are not using the facilities. Cons: It would require extra effort to install the Numerical distribution from source and get back to the current status quo. Some people would be confused at the changes. Note: If we did it "right", and made these things into packages instead of modules that install into Numeric, changes to scripts would be required, but that is not being proposed here. My vision of this change is that they would still install directly into Numeric, and would be included in all "prebuilt" distributions.

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Da Blas
by Paul F. Dubois 14 Sep '00

14 Sep '00

Well, I certainly didn't mean to flame anyone in particular, so I'm sorry that Frank was offended. I suppose I got irritated when I tried to solve one problem and simply created one that was harder to solve. I don't think any of us quite appreciated how bad the situation is. No good deed goes unpunished. I tried yesterday to help someone internally with an SGI system. They had two new wrinkles on this: a. They had their own blas but not their own lapack, in /usr/lib. Well, I had allowed for that in my second version, but of course the imprecision of the -L stuff makes it possible to get the wrong one that way. b. I did get the /usr/lib version of the blas, and boy was it the wrong one, since apparently there are two binary modes on an SGI and it was not -n32 like Python expected. Neither was the lapack_lite one. I had to edit the Makefile. That problem could be avoided using distutils to do the compile. The solution was to edit setup.py to remove /usr/lib from the search list. The problem with simply using the desired library as a binary instead of a library is that you would load all of it. I do not know how much control you can get with the -l -L paradigm, especially in a portable way.

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NumPy built distributions >
by Michel Sanner 13 Sep '00

13 Sep '00

Hello, We have a download site for Python module (which I meant to make public .. just didn't have time yet). It enables downloading precompiled Python interpreters (my users are no wanting to have to compile the interpreter) and a large number of Python extensions including Numeric for the following platforms: sgi IRIX5 sgi IRIX6 sun SunOS5 Dec Alpha Linux feel free to give it a shot ! http://www.scripps.edu/~sanner/Python and scroll down to Downloads Any feed back is welcome ! -Michel -- ----------------------------------------------------------------------- >>>>>>>>>> AREA CODE CHANGE <<<<<<<<< we are now 858 !!!!!!! Michel F. Sanner Ph.D. The Scripps Research Institute Assistant Professor Department of Molecular Biology 10550 North Torrey Pines Road Tel. (858) 784-2341 La Jolla, CA 92037 Fax. (858) 784-2860 sanner(a)scripps.edu http://www.scripps.edu/sanner -----------------------------------------------------------------------

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Sourceforge down time scheduled -- heads up
by Paul F. Dubois 13 Sep '00

13 Sep '00

-----Original Message----- From: noreply(a)sourceforge.net [mailto:noreply@sourceforge.net] Sent: Tuesday, September 12, 2000 6:18 PM To: noreply(a)sourceforge.net Subject: SourceForge: Important Site News Dear SourceForge User, As the Director of SourceForge, I want to thank you in making SourceForge the most successful Open Source Development Site in the World. We just surpassed 60,000 registered users and 8,800 open source projects. We have a lot of exciting things planned for SourceForge in the coming months. These include faster servers, improved connectivity, mirrored servers, and the addition of more hardware platforms to our compile farm (including Sparc, PowerPC, Alpha, and more). Did I mention additional storage? The new servers that we will be adding to the site will increase the total storage on SourceForge by an additional 6 terabytes. In 10 days we will begin the first phase of our new hardware build out. This phase involves moving the primary site to our new location in Fremont, California. This move will take place on Friday night (Sept 22nd) at 10pm and continue to 8am Saturday morning (Pacific Standard Time). During this time the site will be off-line as we make the physical change. I know many of you use Sourceforge as your primary development environment, so I want to apologize in advance for the inconvenience of this downtime. If you have any concerns about this, please feel free to email me. I will write you again as this date nears, with a reminder and an update. Thank you again for using SourceForge.net -- Patrick McGovern Director of SourceForge.net Pat(a)sourceforge.net --------------------- This email was sent from sourceforge.net. To change your email receipt preferences, please visit the site and edit your account via the "Account Maintenance" link. Direct any questions to admin(a)sourceforge.net, or reply to this email.

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NumPy built distributions
by Goodger, David 12 Sep '00

12 Sep '00

ATTN: Numeric Python project administrators There is a lot of interest in NumPy out there. Every time a new version of Numeric or Python comes out, people are interested in obtaining built distributions. Many of us are not able to build from source; without a repository of built distributions I'm afraid that many people will give up. The MacOS community is lucky that Jack Jansen, who maintains the MacPython distribution, also includes a built NumPy with his installers. Other OSes are not so lucky. Robin Becker (robin(a)jessikat.fsnet.co.uk) has built NumPy for Win32 many times and emails copies to those who request them. Unfortunately for him, but fortunately for NumPy, the demand is getting too high for this method of distribution. It would be great if these built distributions were available for all, with minimal overhead to developers/packagers. Would it be possible to add Robin's installers to the FTP site? How should he (or I, if he's not able) go about this? David Goodger Systems Administrator, Advanced Systems Automation Tooling Systems Inc., Automation Systems Division direct: (519) 653-4483 ext. 7121 fax: (519) 650-6695 e-mail: dgoodger(a)atsautomation.com goodger(a)users.sourceforge.net >From NumPy's Open Discussion forum (http://sourceforge.net/forum/forum.php?forum_id=3847): By: rgbecker ( Robin Becker ) Numeric-16.0 win32 builds [ reply ] 2000-Sep-09 03:57 I have built and zipped binaries for Numeric-16.0 for Python-1.5.2/1.6b1/2.0b1 I am fed up with sending these binaries to people individually. Is there an FTP location I could use on the sourceforge site?

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ANNOUNCEMENT: Fortran to Python Interface Generator, 2nd Rel.
by Pearu Peterson 12 Sep '00

12 Sep '00

FPIG - Fortran to Python Interface Generator I am pleased to announce the second public release of f2py (version 2.264): http://cens.ioc.ee/projects/f2py2e/ f2py is a command line tool for binding Python and Fortran codes. It scans Fortran 77/90/95 codes and generates a Python C/API module that makes it possible to call Fortran routines from Python. No Fortran or C expertise is required for using this tool. Features include: *** All basic Fortran types are supported: integer[ | *1 | *2 | *4 | *8 ], logical[ | *1 | *2 | *4 | *8 ], character[ | *(*) | *1 | *2 | *3 | ... ] real[ | *4 | *8 | *16 ], double precision, complex[ | *8 | *16 | *32 ] *** Multi-dimensional arrays of (almost) all basic types. Dimension specifications: <dim> | <start>:<end> | * | : *** Supported attributes: intent([ in | inout | out | hide | in,out | inout,out ]) dimension(<dimspec>) depend([<names>]) check([<C-booleanexpr>]) note(<LaTeX text>) optional, required, external *** Calling Fortran 77/90/95 subroutines and functions. Also Fortran 90/95 module routines. Internal initialization of optional arguments. *** Accessing COMMON blocks from Python. Accessing Fortran 90/95 module data coming soon. *** Call-back functions: calling Python functions from Fortran with very flexible hooks. *** In Python, arguments of the interfaced functions may be of different type - necessary type conversations are done internally in C level. *** Automatically generates documentation (__doc__,LaTeX) for interface functions. *** Automatically generates signature files --- user has full control over the interface constructions. Automatically detects the signatures of call-back functions, solves argument dependencies, etc. *** Automatically generates Makefile for compiling Fortran and C codes and linking them to a shared module. Many compilers are supported: gcc, Compaq Fortran, VAST/f90 Fortran, Absoft F77/F90, MIPSpro 7 Compilers, etc. Platforms: Intel/Alpha Linux, HP-UX, IRIX64. *** Complete User's Guide in various formats (html,ps,pdf,dvi). *** f2py users list is available for support, feedback, etc. More information about f2py, see http://cens.ioc.ee/projects/f2py2e/ f2py is released under the LGPL license. Sincerely, Pearu Peterson <pearu(a)ioc.ee> September 12, 2000 <P><A HREF="http://cens.ioc.ee/projects/f2py2e/">f2py 2.264</A> - The Fortran to Python Interface Generator (12-Sep-00)

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Univariate and multivariate density estimation using Python
by Jon Saenz 12 Sep '00

12 Sep '00

Hello, all. I am announcing a C extension module which computes univariate and multivariate probability density functions by means of a kernel-based approach. The module includes functions to perform the estimation using the following kernels: * One-dimensional data: Epanechnikov Biweight Triangular * 2 or 3-dimensional data: Epanechnikov Multivariate gaussian For multivariate data, there is the optional feature of scaling each axis by means of a matrix. This approach allows the definition of Fukunaga-type estimators. The functions in the module are used as follows: import KPDF # edata and gdata must be numpy arrays of shapes (N,) and (E,) # while h is a scalar # pdf1 is a numpy array which holds the PDF evaluated at points # gdata with experimental data in edata. pdf1.shape=(E,) pdf1=KPDF.UPDFEpanechnikov(edata,gdata,h) # For multivariate estimation, edata and gdata must be numpy arrays of # shapes (N,2|3) and (E,2|3) while h is a scalar # pdf2 is a numpy array which holds the PDF evaluated at points # gdata with experimental data in edata. pdf2.shape=(E,) pdf2=KPDF.MPDFEpanechnikov(e2data,g2data,h) # For Fukunaga-type estimators, Sm1 must be a numpy array 2x2(3x3) # and holds the covariance matrix. sqrtdetS is the square root of the # determinant pdf2=KPDF.MPDFEpanechnikov(e2data,g2data,h,Sm1,sqrtdetS) There is not a lot of documentation in the module, but I have a serious commitment of preparing it soon. It can be downloaded from: http://starship.python.net/crew/jsaenz/KPDF.tar.gz Feedback of interested users will be greatly appreciated. Regards. Jon Saenz. | Tfno: +34 946012470 Depto. Fisica Aplicada II | Fax: +34 944648500 Facultad de Ciencias. \\ Universidad del Pais Vasco \\ Apdo. 644 \\ 48080 - Bilbao \\ SPAIN

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Row/Column delete
by Oliver Hofmann 12 Sep '00

12 Sep '00

'lo everyone! Been fiddling around with NumPy lately, trying to use it for some simple clustering algorithms. Those require constant merging or rows and columns. Since the arrays are static in size I've been looking at the FAQ and doku for a function that helps with this, but have been unable to find any. What I am doing right now is: Set up a new matrix with one less row or column (zeros()), then copy all the rows/columns but the one I'd like to delete to the new matrix. However, this requires setting up a second matrix for each delete action. A combined row/column delete requires two copy actions, making it even slower. Is there a better/faster way to do this? Ie, parse through the old matrix and copy individual positions instead of rows/columns? Any help would be appreciated! Oliver Hofmann -- Oliver Hofmann - University of Cologne - Department of Biochemistry o.hofmann(a)smail.uni-koeln.de - setar(a)gmx.de - connla(a)thewell.com "It's too bad she won't live. But then, who does?" <Gaff, Blade Runner>

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ANNOUNCE (Numeric): Some RPMS and a GIST interface I use regularly.
by Travis Oliphant 11 Sep '00

11 Sep '00

Just letting interested people know that I've made RPM's of the Python interface to all of Lapack originally written by Doug Heisterkamp and modified by Konrad Hinsen (Konrad, you may have already made these --- please let me know if you have). (Under Numerical Python RPMS at) http://oliphant.netpedia.net Also, I've released a module I use regularly for interactive plotting with Gist. It makes it much more "MATLAB" like: from Mplot import * mplot(x,y,'r-',x2,y2,'b:') legend(['Line1',Line2']) # will prompt you for a place to put it. title("Title") xlabel("some label") ylabel("other label") You can also do subplots with the module using gist.plsys to change between subplots. I use it everyday and thought others might be interested in it. It's not well documented at this point, though. Needed files: http://oliphant.netpedia.net/packages/Mplot.py http://oliphant.netpedia.net/packages/write_style.py The latter file allows one to construct a gist style file from a Python nested dictionary which is needed for changing the color and style of the axis system. -Travis

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