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PyScripter is a free and open-source Python Integrated Development Environment (IDE) created with the ambition to become competitive in functionality with commercial Windows-based IDEs available for other languages. Being built in a compiled language is rather snappier than some of the other Python IDEs and provides an extensive blend of features that make it a productive Python development Environment. 

PyScripter is a free and open-source Python Integrated Development Environment (IDE) created with the ambition to become competitive in functionality with commercial Windows-based IDEs available for other languages. Being built in a compiled language is rather snappier than some of the other Python IDEs and provides an extensive blend of features that make it a productive Python development Environment.

Your example works as you describe on recent matplotlib versions. I suspect you are using an old one. The preferred way of handling missing points in numpy, and therefore in matplotlib and pylab, however, is via masked arrays.import pylabimport numpy as npfrom numpy import maa = [1,2,3,4,5]b = np.array([6,2,np.nan,1,9])bm = ma.masked_where(np.isnan(b), b)pylab.plot(a,bm)pylab.show()There are many other examples of masked array use in the examples directory of the matplotlib distribution.EricFernando Abilleira wrote:> Dear sourceforge community,> > I come from a Matlab environment so I am used to plotting matrices that > contain NaN elements. This is very useful because in some cases one > doesn't have data for the entire matrix. If one tries plotting the data, > the NaN elements won't be plotted.

Linda is an widely studied distributed computing environment, centered around the notion of a tuple space. A tuple space is a bag (also called a multi-set) of tuples. A tuple is an ordered, typed chunk of data. Tuple spaces exist independently of processes in the system, and the data placed into a tuple space also exist independently. See "Generative communication in Linda" (1985) and "Multiple tuple spaces in Linda" both by David Gelernter for more information on Linda.

I wrote dbtxt because I needed a small, flat database in a python environment that didn't depend upon any external libraries. Most libraries are contaminated with the GPL, and this needed to be OK for commercial distribution without any complications. So that's what we have here - a complete (though small) database system that depends on nothing at all other than the Python language and its internal libraries. The entire database comes in at about 20k bytes (that's right, "k", not hundreds of k or megabytes) and I was able to implement all the functions I needed. So I was happy. Will you be happy? Well, download it and read the docs and see what you think. The download, zipped, is about 13k. Yep. 13k. :-) By all means, if you have a need for the same kind of thing, feel free to make any use of dbtxt you please. I have released it as PD, so you can use it in projects that are commercial, GPL, BSD, PD, private, government... whatever you like. Below you'll find a basic description taken from beginning of the docs; in the archive you'll download there is complete documentation, two sample databases, a test program and the database engine itself.

PyACTS- http://www.pyacts.org -- PyACTS is a collection of Python Modules that are very useful to Parallel Computing in a High Performance Computing environment. This packages incorporates several modules like PyBLACS (allows communication data for Linear Algebra), PyPBLAS (distributed Matrix Operations) and PyScaLAPACK (solve linear systems and get the eigenvalue problems). These libraries are part of PyACTS project that provide interfaces to the ACTS Collection. Also is provided a parrallel interpreter for using this package that implements message-based parallel programming using MPI.

SVGMath is written in pure Python, with neither extension modules nor external dependencies. It runs on any platform where a modern Python environment (version 2.4 or higher) is available. It can be used either as a command-line script for batch-mode file conversion, or as a component to process MathML data in other Python applications.

> Is there a way to find the number of processors on a machine (on linux/ > windows/macos/cygwin) using python code (using the same code/cross > platform code)? From processing <http://cheeseshop.python.org/pypi/processing/0.34> : def cpuCount():     '''     Returns the number of CPUs in the system     '''     if sys.platform == 'win32':         try:             num = int(os.environ['NUMBER_OF_PROCESSORS'])         except (ValueError, KeyError):             pass     elif sys.platform == 'darwin':         try:             num = int(os.popen('sysctl -n hw.ncpu').read())         except ValueError:             pass     else:         try:             num = os.sysconf('SC_NPROCESSORS_ONLN')         except (ValueError, OSError, AttributeError):             pass     if num >= 1:         return num     else:         raise NotImplementedError --

Install using binary installer Download installer from http://ipython.scipy.org/dist/pyreadline-1.3.win32.exe make sure no other readline is installed run installer The configuration file pyreadlineconfig.ini can be copied from Python24/lib/site-packages/pyreadline/configuration to your HOME directory (usually c:/documents and settings/YOURNAME). When using ipython pyreadline is automatically activated. If you want to use pyreadline from the interactive prompt of the python interpreter then you have to include the code in Python24/lib/site-packages/pyreadline/configuration/startup.py in your pythonstartup file or set the PYTHONSTARTUP environment variable to point to that file. Manual can be found in Python24/share/doc/pyreadline