convex_optimization first draft

1 files changed, 27 insertions, 2 deletions

diff --git a/jpa_test/cascade_creation.py b/jpa_test/cascade_creation.py
index 80054a7..2b53963 100644
--- a/jpa_test/cascade_creation.py
+++ b/jpa_test/cascade_creation.py
@@ -55,6 +55,8 @@ class Cascade(list):
         for t, infected_set in izip(xrange(len(self)), self):
             if infected_set[node]:
                 infected_times.append(t)
+        if not infected_times:
+            infected_times.append(None)
         return infected_times
 
     def candidate_infectors(self, node):
@@ -68,6 +70,27 @@ class Cascade(list):
         return candidate_infectors
 
 
+def icc_matrixvector_for_node(cascades, node):
+    """
+    for the ICC model:
+    Returns M, w in matrix form where rows of M are i = t + k.T
+    Excludes all (t,k) after node infection time; w = 1_{infected}
+    """
+    w = []
+    M = []
+    for cascade in cascades:
+        t_i = cascade.infection_time(node)[0]
+        if t_i > 0 or t_i is None:
+            indicator = np.zeros(len(cascade))
+            if t_i > 0:
+                indicator[-1] = 1
+            w.append(indicator)
+            M.append(np.array(cascade[:t_i]))
+    M = np.vstack(M)
+    w = np.hstack(w)
+    return M, w
+
+
 def icc_cascade(G, p_init):
     """
     Returns boolean vectors for one cascade
@@ -78,7 +101,7 @@ def icc_cascade(G, p_init):
     active = np.random.rand(G.number_of_nodes()) < p_init
     susceptible = susceptible - active
     cascade = Cascade()
-    while active.any() and susceptible.any():
+    while active.any():
         cascade.append(active)
         active = np.exp(np.dot(G.logmat, active)) \
                     < np.random.rand(G.number_of_nodes())
@@ -102,7 +125,9 @@ def test():
     G.erdos_init(n = 100, p = 1)
     import time
     t0 = time.time()
-    print len(icc_cascade(G, p_init=.1))
+    A = generate_cascades(G, .1, 10)
+    M, w = icc_matrixvector_for_node(A, 0)
+    print w
     t1 = time.time()
     print t1 - t0