new plots

1 files changed, 13 insertions, 13 deletions

diff --git a/src/make_plots.py b/src/make_plots.py
index 7da3e1e..d92b008 100644
--- a/src/make_plots.py
+++ b/src/make_plots.py
@@ -32,7 +32,7 @@ def watts_strogatz(n_cascades, lbda, passed_function):
     Test running time on different algorithms
     """
     G = cascade_creation.InfluenceGraph(max_proba=.7, min_proba=.2)
-    G.import_from_file("../datasets/watts_strogatz_500_80_point3.txt")
+    G.import_from_file("../datasets/watts_strogatz_300_30_point3.txt")
     A = cascade_creation.generate_cascades(G, p_init=.05, n_cascades=n_cascades)
 
     if passed_function==algorithms.greedy_prediction:
@@ -44,19 +44,19 @@ 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)
+# 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=1000, lbda=.001, passed_function=
+    watts_strogatz(n_cascades=500, lbda=.001, passed_function=
         convex_optimization.sparse_recovery)