diff options
Diffstat (limited to 'jpa_test/algorithms.py')
| -rw-r--r-- | jpa_test/algorithms.py | 14 |
1 files changed, 2 insertions, 12 deletions
diff --git a/jpa_test/algorithms.py b/jpa_test/algorithms.py index be9caba..2ed015a 100644 --- a/jpa_test/algorithms.py +++ b/jpa_test/algorithms.py @@ -9,8 +9,8 @@ import convex_optimization def greedy_prediction(G, cascades): """ Returns estimated graph from Greedy algorithm in "Learning Epidemic ..." - TODO: write cleaner code? """ + #TODO: This function is deprecated! G_hat = cascade_creation.InfluenceGraph(max_proba=None) G_hat.add_nodes_from(G.nodes()) for node in G_hat.nodes(): @@ -44,9 +44,7 @@ def recovery_l1obj_l2constraint(G, cascades): G_hat.add_nodes_from(G.nodes()) for node in G_hat.nodes(): M, w = cascade_creation.icc_matrixvector_for_node(cascades, node) - M = M.astype("float64") - edges_node = convex_optimization.l1obj_l2constraint(M,w) - print edges_node + p_node, __ = convex_optimization.l1obj_l2constraint(M,w) def correctness_measure(G, G_hat): @@ -73,13 +71,5 @@ def test(): recovery_l1obj_l2constraint(G, A) - G_hat = greedy_prediction(G, A) - fp, fn, gp = correctness_measure(G, G_hat) - print "False Positive: {}".format(len(fp)) - print "False Negative: {}".format(len(fn)) - print "Good Positives: {}".format(len(gp)) - t1 = time.time() - print t1 - t0 - if __name__=="__main__": test() |