Squared model

1 files changed, 13 insertions, 11 deletions

diff --git a/hawkes_experiments/cause.py b/hawkes_experiments/cause.py
index 800f699..711e34a 100644
--- a/hawkes_experiments/cause.py
+++ b/hawkes_experiments/cause.py
@@ -30,12 +30,13 @@ def cause(lamb, alpha, mu):
                 fatal_droots += 1
             continue
         background_rate = lamb * (1 + 0.43 * sin(0.0172 * t1 + 4.36))
-        parents = sorted([(n2, t2, alpha / d * mu * exp(-mu * (t1 - t2)), d)
+        parents = sorted([(n2, t2, alpha / d ** 2 * mu * exp(-mu * (t1 - t2)), d)
                           for (n2, t2, d) in s], reverse=True,
                          key=lambda x: x[2])
         parent_rate = sum(e[2] for e in parents)
-        # if sum(e[2] for e in prl[:1]) > br:
-        #    G.add_edge((n1, t1), tuple(prl[0][:2]))
+        # if parents[0][2] > background_rate:
+        #     G.add_edge(tuple(parents[0][:2]), (n1, t1),
+        #                weight=parents[0][3])
         if background_rate > parent_rate:
             roots += 1
             if (n1, t1) in fatals:
@@ -56,9 +57,9 @@ def analyze_graph(G):
     print "cascades: {0}, min: {1}, max: {2}, mean: {3}, median: {4}".format(
         len(csizes),  np.min(csizes), np.max(csizes), np.mean(csizes),
         np.median(csizes))
-    # counts = Counter(l)
-    # w = writer(open("components_dist.csv", "w"))
-    # w.writerows(counts.most_common())
+    counts = Counter(csizes)
+    w = writer(open("components_dist.csv", "w"))
+    w.writerows(counts.most_common())
     edges = list(G.edges_iter(data=True))
     print "edges: {0}".format(len(edges))
     times = [e[1][1] - e[0][1] for e in edges]
@@ -68,14 +69,15 @@ def analyze_graph(G):
     print "distances, min: {0}, max: {1}, mean: {2}, median: {3}".format(
         np.min(distances), np.max(distances), np.mean(distances),
         np.median(distances))
-    # e = writer(open("edges.csv", "w"))
-    # e.writerows(edges)
+    e = writer(open("edges.csv", "w"))
+    e.writerows((e[0][0], e[0][1], e[1][0], e[1][1], e[2]["weight"])
+                for e in edges)
 
 
 if __name__ == "__main__":
-    nodes, edges, events, event_edges = load(open("data-dist1.pickle", "rb"))
-    lamb, alpha, mu = 1.86602117779e-05, 0.0433473674726, 0.00109325510695
-    # lamb, alpha, mu = 1.87717287808e-05, 5.12006113875e+14, 4.20918377797e-20
+    nodes, edges, events, event_edges = load(open("data-all.pickle", "rb"))
+    lamb, alpha, mu = 1.18909761267e-05, 0.00781529533133, 0.00373882477787
+    print "mu: {0}, alpha: {1}, beta: {2}".format(lamb, alpha, mu)
     (droots, roots, infections, fatal_droots,
      fatal_roots, fatal_infections, G) = cause(lamb, alpha, mu)
     r = "events: {0}, droots: {1}, roots: {2}, infections: {3}, "\