More tests with ml2 to find optimal results

1 files changed, 5 insertions, 4 deletions

diff --git a/experiments/ml2.pyx b/experiments/ml2.pyx
index 9edc7e6..8974106 100644
--- a/experiments/ml2.pyx
+++ b/experiments/ml2.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
 
@@ -59,6 +59,7 @@ def ml2(dict root_victims, dict victims, dict non_victims, DTYPE_t age,
                      for (dist, dt, w1, w2, w3) in parents]
         # find parent that maximizes log(p) - log(\tilde{p})
         probs[i] = max(s - failures[l] for l, s in enumerate(successes)) 
+        probs_data[i] = 
 
     # loop through non-victims
     for i, parents in enumerate(non_victims.itervalues()):