Mailman 3 July 2002 - NumPy-Discussion

[ANNOUNCE] Pyfort 8.0
by Paul F Dubois 18 Jul '02

18 Jul '02

Pyfort 8.0 has been released at SourceForge (sf.net/projects/pyfortran) Version 8 This version contains a new facility for making and installing projects. Old compile lines will still work, but will produce an equivalent .pfp file that you could use in the future. Included is a Tkinter-based GUI editor for the project files. However, the format of the files is simple and they could be edited with a text editor as well. There is improved support for installing Pyfort and the modules it creates in a location other than inside Python. See README. This version does change the installation location for an extension. Therefore, you should remove the files of any previous installation from your Python. Yes, this is annoying. That is why we are doing it, so that we can have an "uninstall" command. A new "windows" subdirectory has been added, containing an example of how to use Pyfort on Windows with Visual Fortran. Thanks to Reinhold Niesner. Testing of, and advice about, this are needed from Windows users. The pyfort script itself is also now installed as a .bat script for win32. Support for Mac OSX (Darwin) added.

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Optimization advice
by John Eikenberry 16 Jul '02

16 Jul '02

I'm working on an influence map [1] for game civil [2]. I have a working version, but as a real numeric newbie I thought I'd bounce it off the people here before calling it done. I'm basically looking for an easy to understand but fast influence spreading algorithm. I've read that this algorithm is similar to those used to predict fire spreading or heat transfer in metal if that helps. The attached code is setup for a hex based map and the functions to take this into accounts (shift_hex_up,shift_hex_down) are probably the most naive. The others being only slight modifications of those in the life.py example. Its not really commented but its short and hopefully should be readily understandable. I've only included the base influence map class and its associated functions. If you'd like a version you can run, I can send you a .tgz setup to run in place (for *nix systems). Thanks in advance for any advice or opinions. [1] An influence map is used commonly in strategic war games. It is a simple means of capturing the areas on the game map that one side is strong vs the other side. Read the first post in this thread for a good description: http://www.gameai.com/influ.thread.html [2] Civil is a cross-platform, turn-based, networked strategy game, developed using Python, PyGame and SDL--allowing players to take part in scenarios set during the American Civil war. http://civil.sourceforge.net/ -- John Eikenberry [jae(a)zhar.net - http://zhar.net] ______________________________________________________________ "They who can give up essential liberty to purchase a little temporary safety, deserve neither liberty nor safety." --B. Franklin

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Caution -- // not standard
by Paul Dubois 08 Jul '02

08 Jul '02

I have run into several cases of this on different open-source projects, the latest being an incorrect change in Numeric's arrayobject.c: the use of // to start a comment. Many contributors who work only with Linux have come to believe that this works with other C compilers, which is not true. This construct comes from C++. Please avoid this construct when contributing changes or patches to Numeric.

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Scientific Python 2.4
by Konrad Hinsen 01 Jul '02

01 Jul '02

Scientific Python 2.4 --------------------- Scientific Python is a module library for scientific computing. In this collection you will find modules that cover basic geometry (vectors, tensors, transformations, vector and tensor fields), quaternions, automatic derivatives, (linear) interpolation, polynomials, elementary statistics, nonlinear least-squares fits, unit calculations and conversions, Fortran-compatible data formatting, 3D visualization via VRML, two Tk widgets for simple line plots and 3D wireframe models. Scientific Python also contains Python interfaces to the netCDF library (implementing a portable binary format for large arrays) and the Message Passing Interface, the most widely used communications library for parallel computers. Version 2.4 of Scientific Python has just been released. In addition to numerous small improvents and bug fixes, it contains - the high-level parallelization module Scientific.BSP - an interface to the parallelization library BSPlib (see www.bsp-worldwide.org for details) - autoregressive models for time series in Scientific.Signals.Models The BSP parallelization module was designed to facilitate development and testing of parallel programs. Its main features are: - communication can handle almost any Python object - deadlocks are impossible by design - possibility to implement distributed data classes that can be used transparently by parallel applications - an interactive parallel interpreter that can be used inside Emacs (and perhaps other Python development environments) in order to provide an interactive parallel programming environment - parallel programs run as serial monoprocessor code on any Python installation with no changes and usually negligeable loss of performance - no need to maintain a separate serial version A tutorial on BSP programming with Python is available at the Web site and included in the distribution. For more information and for downloading, see http://dirac.cnrs-orleans.fr/ScientificPython or http://starship.python.net/crew/hinsen/scientific.html -- ------------------------------------------------------------------------------- Konrad Hinsen | E-Mail: hinsen(a)cnrs-orleans.fr Centre de Biophysique Moleculaire (CNRS) | Tel.: +33-2.38.25.56.24 Rue Charles Sadron | Fax: +33-2.38.63.15.17 45071 Orleans Cedex 2 | Deutsch/Esperanto/English/ France | Nederlands/Francais -------------------------------------------------------------------------------

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