Exploring the limits of HRG for network modeling

16Nov16 |toy.py reading cindy rules fails in g.sample Walk throug the parsing it might do the thing

09Jan16 |New sampler (in david.py) that should use much much less memory.

To print the the Tree: in tree_decomposition, line 202 (new_visit) To print the Prod Rules: in tree_decomposition, line 299 (add_to_prod_rules)

• karate_chop.py Working script used for development
• tw_karate_chop.py working script used to generate visuals

HRG offers two methods of generating graphs:

1. Exact Generation
2. Stochastic Genration
   • There is also Probabilistic HRG

• To switch to the dev version of networkx, make PYTHONPATH /home/username/local/python/lib/python2.7/site-packages/

• http://stackoverflow.com/questions/24364770/random-sampling-from-a-list-based-on-a-distribution
• On Assorativity
  • Newman, Phys. Rev. E 67, 026126 (2003).
• Learning Bayesian Networks from Data | Nir Friedman Daphne Koller

29Jun17 | got phrg, cl, and kp working on small grpahs 29Jun17 | Next: work on larger graphs 02Jul17 | Begin Time experiments and large datasets 04Jul17 | Use the nu metrics to do stats 04Jul17 | working on net stats 04Jul17 | nu_metrix.py pami.py, need to reconsider the CDF 05Jul17 | Working on ECDF merging each result on x " 05Jul17 | Working on ECDF merging each result on x 05Jul17 | Workin on generating dat for large datasets 05Jul17 | ECDF http://ars.els-cdn.com/content/image/1-s2.0-S1877750315300259-gr7.jpg 17Jul17 | ToDo: run both Probs and Rods" 17Jul17 | ToDo: run both Probs and Rods

16Nov16 |toy.py reading cindy rules fails in g.sample Walk throug the parsing it might do the thing

09Jan16 |New sampler (in david.py) that should use much much less memory.

To print the the Tree: in tree_decomposition, line 202 (new_visit) To print the Prod Rules: in tree_decomposition, line 299 (add_to_prod_rules)

• karate_chop.py Working script used for development
• tw_karate_chop.py working script used to generate visuals

HRG offers two methods of generating graphs:

1. Exact Generation
2. Stochastic Genration
   • There is also Probabilistic HRG

• To switch to the dev version of networkx, make PYTHONPATH /home/username/local/python/lib/python2.7/site-packages/

• http://stackoverflow.com/questions/24364770/random-sampling-from-a-list-based-on-a-distribution
• On Assorativity
  • Newman, Phys. Rev. E 67, 026126 (2003).
• Learning Bayesian Networks from Data | Nir Friedman Daphne Koller

29Jun17 | got phrg, cl, and kp working on small grpahs 29Jun17 | Next: work on larger graphs 02Jul17 | Begin Time experiments and large datasets 04Jul17 | Use the nu metrics to do stats 04Jul17 | working on net stats 04Jul17 | nu_metrix.py pami.py, need to reconsider the CDF 05Jul17 | Working on ECDF merging each result on x " 05Jul17 | Working on ECDF merging each result on x 05Jul17 | Workin on generating dat for large datasets 05Jul17 | ECDF http://ars.els-cdn.com/content/image/1-s2.0-S1877750315300259-gr7.jpg 17Jul17 | ToDo: run both Probs and Rods" 17Jul17 | ToDo: run both Probs and Rods 25Jul17 | gcd taking for ever 31Aug17 | remote login \ Push URL: git@github.com:abitofalchemy/hrg_nets.git 31Aug17 | working dir: saguinag@dsg1:/data/saguinag/hrg_nets$ 01Sep17 | working on exact hrg to save graphs 03Sep17 | set max loops taking a long time! 05Sep17 | got cl_kron_synth.py working to gen pickle files to be used with pgd 05Sep17 | todo: summarize the macro files for synth graphs 07Sep17 | 5546444797 Sep 5 10:18 Results/amazon0312_clgms.pickle, 644108189 Sep 6 09:29 Results/amazon0312_hstars.pickle 15Sep17 | todo: add a ret_val and return overall 15Sep17 | todo: in net_metrics 15Sep17 | fast exact phrg and net metrics can do faster clust 16Sep17 | got fast exact phrg working