Flow Network Generation
Flow networks robust against damages are simple model networks described in a series of publications by Kaluza et al.[1, 2, 3]. The C++ code presented in this repository allows for the generation of such networks via a simulated evolution.
Although the code was programmed with a single core in mind, the compiled binary can easily be (and has been) run multiple times in parallel.
In the main directory, you need to edit the
CMakeLists.txt file. If your
libraries are installed in non-standard locations, please adapt lines 8 to 11.
Then run the following commands:
cmake init . make
If everything went smoothly there should now be a
Add the path to your environment variable
LD_LIBRARY_PATH if you want to run
things from here. In bash this can be done by:
You can now run the
simulation binary in the
bin subdirectory which will
print some info to stdout.
If you want to install the
lib subdirectories in a different
location, either edit line 17 of the
CMakeLists.txt file or invoke:
make install -DDESTDIR=/your/favourite/path
When you are ready to move from testing to large-scale computation you should rebuild the project without debugging and text output, follow these commands:
cmake -DDEBUG=OFF . make
The output files are binary and their exact structure depends on your system's architecture (32 or 64 bit).
NB: If you install these libraries from system packages, please make sure to also
dev packages as the headers are needed for compilation.
- Boost/ namely: algorithm, random, graph, filesystem V3, accumulators, pending/queue, program_options
- GNU Scientific Library
|||Kaluza, P., Ipsen, M., Vingron, M. & Mikhailov, A. S. Design and statistical properties of robust functional networks: A model study of biological signal transduction. Physical Review E 75, 15101 (2007).|
|||Kaluza, P. & Mikhailov, A. S. Evolutionary design of functional networks robust against noise. Europhysics Letters 79, 48001 (2007).|
|||Kaluza, P., Vingron, M. & Mikhailov, A. S. Self-correcting networks: function, robustness, and motif distributions in biological signal processing. Chaos 18, 026113 (2008).|