https://github.com/fabriziocosta/constrActive
this should cover most of the depencencies
pip install structout graphlearn
pip install git+https://github.com/fabriziocosta/EDeN.git --user
- generate a set of random graphs by editing params_graphs in reconstruct.py and running:
python3 reconstruct.py maketasks
# you can inspect the set via
# python3 inspecttasks.py .tasks
# util/rule_rand_graphs.py contains even more options for graph generation
- run the experiments.
Edit params_insta and params_opt to anjust parameters of the instance maker and the optimizer. Then calculate the number of reconstructions that need to be performed. Here we set the number to 1000 because we conduct 50 reconstructions and explore 5 x 4 parameter combinations of the instance maker (see below). During the reconstruction a lot of debug information is displayed.
seq 0 1000 | parallel -j 10 python3 reconstruct.py
- look at reports
edit the report function and look at the result. You see (#success, #iterations used by the 'slowest' attempt)
python3 reconstruct.py report
marks:10 marks:20 marks:25 marks:30 marks:5
neigh:100 (35, 9) (36, 18) (37, 12) (33, 15) (29, 17)
neigh:150 (35, 16) (34, 13) (37, 12) (37, 16) (30, 19)
neigh:25 (31, 12) (32, 17) (32, 17) (33, 19) (25, 18)
neigh:50 (31, 8) (38, 19) (36, 15) (36, 15) (29, 18)
use maketaskschem and reportchem respectively :)
