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| author | jeanpouget-abadie <jean.pougetabadie@gmail.com> | 2015-02-03 20:34:05 -0500 |
|---|---|---|
| committer | jeanpouget-abadie <jean.pougetabadie@gmail.com> | 2015-02-03 20:34:05 -0500 |
| commit | af2ac731db5077a802e3ec2924f210cc9fdbe5c6 (patch) | |
| tree | 9d9f2bcef77ebb2522a7e058245dc4f863c8381e /src/make_plots.py | |
| parent | a9acec30743687fdaf1df291b51b346bca7cf5a7 (diff) | |
| download | cascades-af2ac731db5077a802e3ec2924f210cc9fdbe5c6.tar.gz | |
more changes
Diffstat (limited to 'src/make_plots.py')
| -rw-r--r-- | src/make_plots.py | 18 |
1 files changed, 2 insertions, 16 deletions
diff --git a/src/make_plots.py b/src/make_plots.py index 201e375..947bf57 100644 --- a/src/make_plots.py +++ b/src/make_plots.py @@ -44,20 +44,6 @@ def watts_strogatz(n_cascades, lbda, passed_function): algorithms.correctness_measure(G, G_hat, print_values=True) -# def test(): -# """ -# unit test -# """ -# G = cascade_creation.InfluenceGraph(max_proba=1, min_proba=.2) -# G.erdos_init(n=50, p=.2) -# A = cascade_creation.generate_cascades(G, p_init=.1, n_cascades=1000) -# G_hat = algorithms.recovery_passed_function(G, A, -# passed_function=convex_optimization.sparse_recovery, -# floor_cstt=.1, lbda=.001, n_cascades=1000) -# algorithms.correctness_measure(G, G_hat, print_values=True) - - if __name__=="__main__": - watts_strogatz(n_cascades=3000, lbda=.002, passed_function= - convex_optimization.sparse_recovery) - #algorithms.greedy_prediction)
\ No newline at end of file + watts_strogatz(n_cascades=500, lbda=.002, passed_function= + convex_optimization.sparse_recovery)
\ No newline at end of file |
