Implementation of some known cellular automata. Use for academic purposes only. Work in progress ...

See Video.

• models

1. Floor field model:

• Different update schemes: sequential, shuffle sequential, reverse sequential.
• visualisation of the cell states.
• done: 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.

2. 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.