Implementation of some known cellular automata. Use for academic purposes only. Work in progress ...
See Video.
- models
- Floor field model:
- Different update schemes: sequential, shuffle sequential, reverse sequential.
- visualisation of the cell states.
todo: make a video from the png's- todo: track cells with id for further trajectory analysis.
todo: implement the dynamic floor field- todo: implement the parallel update.
- todo: read geometry from a png file. See read_png.py.
- ASEP model
- the theoretical fundamental diagram can be reproduced, see figure. The size of the system should be reasonably high and the simulation time also.
- todo: implement TASEP
- todo: implement sequential update with all its variants.
- Remarque: There are two implementations of the asep. One it optimized using vector-operations from
numpy(asep_fast.py) and the other implementation is using explicit loops (asep_slow.py). The naming of the two variations is justified when measuring their execution time:
python make_fd.py asep_fast.py: 0:56.71 real, 52.12 user, 4.03 sys
python make_fd.py asep_slow.py: 1:15.42 real, 70.55 user, 4.23 sys
- How to use
run
python one_of_the_scripts -h
to see the options.