added new model, ml2, which assumes all victims are infected by someone

else (unless they are root victims)

1 files changed, 7 insertions, 7 deletions

diff --git a/experiments/ml.pyx b/experiments/ml.pyx
index e1ce4cf..53e614b 100644
--- a/experiments/ml.pyx
+++ b/experiments/ml.pyx
@@ -13,13 +13,13 @@ cdef DTYPE_t weight_success(int dist, int dt, DTYPE_t alpha, DTYPE_t delta,
                             DTYPE_t w1, DTYPE_t w2, DTYPE_t w3):
     """weight for successful infection, exponential time model"""
     cdef DTYPE_t structural, temporal, result
-    structural = delta ** dist
+    structural = dist * log(delta)
     # structural = plogis(w1,delta) * plogis(w2,delta) * plogis(w3,delta)
-    temporal = exp(-alpha*dt) * (exp(alpha)-1.)
+    temporal = log(exp(alpha)-1.) - alpha*dt
     # temporal = 1 - exp(-alpha*dt)
-    if exp(-alpha*dt)==0.: print 'UNDERFLOW ERROR'
+    # if exp(-alpha*dt)==0.: print 'UNDERFLOW ERROR'
     # temporal = 1. / (1. + (dt - 1.)/alpha)**0.01 - 1. / (1. + dt/alpha)**0.01
-    result = log(structural * temporal)
+    result = structural + temporal
     # print 'st', structural, temporal
     return result
 
@@ -42,7 +42,7 @@ def ml(dict root_victims, dict victims, dict non_victims, DTYPE_t age,
         DTYPE_t beta, ll
         list parents, failures, successes
     n_roots, n_victims = len(root_victims), len(victims)
-    n_nodes = 100
+    n_nodes = 148152
     cdef:
         np.ndarray[DTYPE_t] probs = np.zeros(n_victims, dtype=DTYPE)
         np.ndarray[DTYPE_t] probs_fail = np.zeros(n_victims, dtype=DTYPE)
@@ -83,8 +83,8 @@ def ml(dict root_victims, dict victims, dict non_victims, DTYPE_t age,
     # print 'probs', probs
     max_beta_add = float('-inf')
     # iterate over all victim nodes to find the optimal threshold
-    for beta in [0.13]:#np.arange(0.001, .2, .002):
-        thresh = log(beta/(1.-beta))
+    for beta in np.arange(0.001, .2, .002):
+        thresh = log(beta/(3012*(1.-beta)))
         # print 'beta:', beta, 'thresh:', thresh, 'infected:', len(probs[probs>=thresh])
         roots = n_roots + len(probs[probs<thresh])