PyCX Project

screenshots

 

PyCX 0.31 Now Available!

WPyCX 0.31 -- a Python 3.3 port of PyCX -- is also available! (updated on 10/3/2013)

The PyCX Project aims to develop an online repository of simple, crude, yet easy-to-understand Python sample codes for dynamic complex systems simulations, including iterative maps, cellular automata, dynamical networks and agent-based models.

Download PyCX files
Project Summary on SourceForge.net

Current Version: PyCX-0.31.zip (updated on 9/14/2013)
Codes are tested with Python 2.7.6, NumPy 1.8.0, SciPy 0.13.2, matplotlib 1.2.1 and NetworkX 1.8.1.


Note to Enthought Canopy users (updated on 3/12/2014)
* To run PyCX's dynamic simulations on Enthought Canopy, please do the following:

1. Go to "Edit" -> "Preferences" -> "Python" tab.
2. Uncheck the "Use PyLab" checkbox and click "OK".
3. Choose "Run" -> "Restart kernel".
4. Run your code and enjoy.
(5. To re-run your code, make sure to restart kernel so no PyLab is running beforehand.)

We thank Alex Hill (https://github.com/CloudUK) for bringing this problem to our attention.

What's new in version 0.31?
* The graphics backend has been changed from Tix to ttk so that Mac users can run it without installing Tix.

What's new in version 0.3?
* Przemyslaw Szufel & Bogumil Kaminski at the Warsaw School of Economics made a substantial improvement to the "pycxsimulator.py"
GUI module, implementing interactive control of model and visualization parameters.
* Several new sample simulation codes were added.
* PyCX is now distributed under the FreeBSD license (see LICENSE.txt).
For more details, read the "README.txt" (can be found at the bottom of this page)

What You Should Do

1. Install Python 2.7, NumPy, SciPy, matplotlib and NetworkX.

2. Download a PyCX sample code of your interest from here.

3. Run it.

4. Read it.

5. Change it as you like.

 

PyCX Tutorial at ECAL 2013 (Slides)

Paper on PyCX published in Complex Adaptive Systems Modeling (open access)

 

Copyright 2011-2014 by Hiroki Sayama <sayama@binghamton.edu>