Added ml3, where we don’t consider edges from victims to non-victims.

Also playing around with only allowing most likely parent to try and
infect. Still working to see if some variant produces good results that
allow us to determine seeds/non-seeds.

1 files changed, 82 insertions, 110 deletions

diff --git a/experiments/ml.c b/experiments/ml.c
index 64d4e3a..77f9840 100644
--- a/experiments/ml.c
+++ b/experiments/ml.c
@@ -1252,8 +1252,8 @@ int __pyx_module_is_main_ml = 0;
 
 /* Implementation of 'ml' */
 static PyObject *__pyx_builtin_enumerate;
-static PyObject *__pyx_builtin_sum;
 static PyObject *__pyx_builtin_max;
+static PyObject *__pyx_builtin_sum;
 static PyObject *__pyx_builtin_ValueError;
 static PyObject *__pyx_builtin_range;
 static PyObject *__pyx_builtin_RuntimeError;
@@ -1404,9 +1404,9 @@ static PyObject *__pyx_n_s_w1;
 static PyObject *__pyx_n_s_w2;
 static PyObject *__pyx_n_s_w3;
 static PyObject *__pyx_n_s_zeros;
-static PyObject *__pyx_float__2;
-static PyObject *__pyx_float__002;
-static PyObject *__pyx_float_0_001;
+static PyObject *__pyx_float_1_;
+static PyObject *__pyx_float__05;
+static PyObject *__pyx_float_0_09;
 static PyObject *__pyx_tuple_;
 static PyObject *__pyx_tuple__2;
 static PyObject *__pyx_tuple__3;
@@ -1842,7 +1842,7 @@ static PyObject *__pyx_pf_2ml_ml(CYTHON_UNUSED PyObject *__pyx_self, PyObject *_
   struct __pyx_obj_2ml___pyx_scope_struct__ml *__pyx_cur_scope;
   int __pyx_v_n_roots;
   int __pyx_v_n_victims;
-  int __pyx_v_n_nodes;
+  CYTHON_UNUSED int __pyx_v_n_nodes;
   int __pyx_v_roots;
   int __pyx_v_i;
   int __pyx_v_dist;
@@ -2121,7 +2121,7 @@ static PyObject *__pyx_pf_2ml_ml(CYTHON_UNUSED PyObject *__pyx_self, PyObject *_
  *         # likely parent infects it
  *         failures = [weight_failure(dist, dt, alpha, delta, w1, w2, w3)             # <<<<<<<<<<<<<<
  *                     for (dist, dt, w1, w2, w3) in parents]
- *         probs_fail[i] = sum(failures)
+ *         probs_fail[i] = max(failures)
  */
     __pyx_t_4 = PyList_New(0); if (unlikely(!__pyx_t_4)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 56; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
     __Pyx_GOTREF(__pyx_t_4);
@@ -2130,7 +2130,7 @@ static PyObject *__pyx_pf_2ml_ml(CYTHON_UNUSED PyObject *__pyx_self, PyObject *_
  *         # likely parent infects it
  *         failures = [weight_failure(dist, dt, alpha, delta, w1, w2, w3)
  *                     for (dist, dt, w1, w2, w3) in parents]             # <<<<<<<<<<<<<<
- *         probs_fail[i] = sum(failures)
+ *         probs_fail[i] = max(failures)
  *         successes = [weight_success(dist, dt, alpha, delta, w1, w2, w3)
  */
     if (unlikely(__pyx_v_parents == Py_None)) {
@@ -2229,7 +2229,7 @@ static PyObject *__pyx_pf_2ml_ml(CYTHON_UNUSED PyObject *__pyx_self, PyObject *_
  *         # likely parent infects it
  *         failures = [weight_failure(dist, dt, alpha, delta, w1, w2, w3)             # <<<<<<<<<<<<<<
  *                     for (dist, dt, w1, w2, w3) in parents]
- *         probs_fail[i] = sum(failures)
+ *         probs_fail[i] = max(failures)
  */
       __pyx_t_22 = __pyx_PyFloat_AsDouble(__pyx_v_w1); if (unlikely((__pyx_t_22 == (npy_double)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 56; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
       __pyx_t_23 = __pyx_PyFloat_AsDouble(__pyx_v_w2); if (unlikely((__pyx_t_23 == (npy_double)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 56; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
@@ -2243,7 +2243,7 @@ static PyObject *__pyx_pf_2ml_ml(CYTHON_UNUSED PyObject *__pyx_self, PyObject *_
  *         # likely parent infects it
  *         failures = [weight_failure(dist, dt, alpha, delta, w1, w2, w3)
  *                     for (dist, dt, w1, w2, w3) in parents]             # <<<<<<<<<<<<<<
- *         probs_fail[i] = sum(failures)
+ *         probs_fail[i] = max(failures)
  *         successes = [weight_success(dist, dt, alpha, delta, w1, w2, w3)
  */
     }
@@ -2256,7 +2256,7 @@ static PyObject *__pyx_pf_2ml_ml(CYTHON_UNUSED PyObject *__pyx_self, PyObject *_
     /* "ml.pyx":58
  *         failures = [weight_failure(dist, dt, alpha, delta, w1, w2, w3)
  *                     for (dist, dt, w1, w2, w3) in parents]
- *         probs_fail[i] = sum(failures)             # <<<<<<<<<<<<<<
+ *         probs_fail[i] = max(failures)             # <<<<<<<<<<<<<<
  *         successes = [weight_success(dist, dt, alpha, delta, w1, w2, w3)
  *                      for (dist, dt, w1, w2, w3) in parents]
  */
@@ -2265,7 +2265,7 @@ static PyObject *__pyx_pf_2ml_ml(CYTHON_UNUSED PyObject *__pyx_self, PyObject *_
     __Pyx_INCREF(__pyx_cur_scope->__pyx_v_failures);
     PyTuple_SET_ITEM(__pyx_t_4, 0, __pyx_cur_scope->__pyx_v_failures);
     __Pyx_GIVEREF(__pyx_cur_scope->__pyx_v_failures);
-    __pyx_t_5 = __Pyx_PyObject_Call(__pyx_builtin_sum, __pyx_t_4, NULL); if (unlikely(!__pyx_t_5)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 58; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
+    __pyx_t_5 = __Pyx_PyObject_Call(__pyx_builtin_max, __pyx_t_4, NULL); if (unlikely(!__pyx_t_5)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 58; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
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     __Pyx_DECREF(__pyx_t_4); __pyx_t_4 = 0;
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@@ -2276,7 +2276,7 @@ static PyObject *__pyx_pf_2ml_ml(CYTHON_UNUSED PyObject *__pyx_self, PyObject *_
 
     /* "ml.pyx":59
  *                     for (dist, dt, w1, w2, w3) in parents]
- *         probs_fail[i] = sum(failures)
+ *         probs_fail[i] = max(failures)
  *         successes = [weight_success(dist, dt, alpha, delta, w1, w2, w3)             # <<<<<<<<<<<<<<
  *                      for (dist, dt, w1, w2, w3) in parents]
  *         # find parent that maximizes log(p) - log(\tilde{p})
@@ -2285,7 +2285,7 @@ static PyObject *__pyx_pf_2ml_ml(CYTHON_UNUSED PyObject *__pyx_self, PyObject *_
     __Pyx_GOTREF(__pyx_t_5);
 
     /* "ml.pyx":60
- *         probs_fail[i] = sum(failures)
+ *         probs_fail[i] = max(failures)
  *         successes = [weight_success(dist, dt, alpha, delta, w1, w2, w3)
  *                      for (dist, dt, w1, w2, w3) in parents]             # <<<<<<<<<<<<<<
  *         # find parent that maximizes log(p) - log(\tilde{p})
@@ -2384,7 +2384,7 @@ static PyObject *__pyx_pf_2ml_ml(CYTHON_UNUSED PyObject *__pyx_self, PyObject *_
 
       /* "ml.pyx":59
  *                     for (dist, dt, w1, w2, w3) in parents]
- *         probs_fail[i] = sum(failures)
+ *         probs_fail[i] = max(failures)
  *         successes = [weight_success(dist, dt, alpha, delta, w1, w2, w3)             # <<<<<<<<<<<<<<
  *                      for (dist, dt, w1, w2, w3) in parents]
  *         # find parent that maximizes log(p) - log(\tilde{p})
@@ -2398,7 +2398,7 @@ static PyObject *__pyx_pf_2ml_ml(CYTHON_UNUSED PyObject *__pyx_self, PyObject *_
       __Pyx_DECREF(__pyx_t_6); __pyx_t_6 = 0;
 
       /* "ml.pyx":60
- *         probs_fail[i] = sum(failures)
+ *         probs_fail[i] = max(failures)
  *         successes = [weight_success(dist, dt, alpha, delta, w1, w2, w3)
  *                      for (dist, dt, w1, w2, w3) in parents]             # <<<<<<<<<<<<<<
  *         # find parent that maximizes log(p) - log(\tilde{p})
@@ -2629,7 +2629,7 @@ static PyObject *__pyx_pf_2ml_ml(CYTHON_UNUSED PyObject *__pyx_self, PyObject *_
  *     # cdef:
  *     #     np.ndarray[DTYPE_t] cums = probs.cumsum()
  *     ll =  probs_fail.sum() # add probability that all edges to victims fail             # <<<<<<<<<<<<<<
- *     ll += probs_nv.sum() # add probability that all edges to non_victims fail
+ *     # ll += probs_nv.sum() # add probability that all edges to non_victims fail
  * 
  */
   __pyx_t_4 = __Pyx_PyObject_GetAttrStr(((PyObject *)__pyx_v_probs_fail), __pyx_n_s_sum); if (unlikely(!__pyx_t_4)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 80; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
@@ -2656,49 +2656,12 @@ static PyObject *__pyx_pf_2ml_ml(CYTHON_UNUSED PyObject *__pyx_self, PyObject *_
   __Pyx_DECREF(__pyx_t_3); __pyx_t_3 = 0;
   __pyx_v_ll = __pyx_t_24;
 
-  /* "ml.pyx":81
- *     #     np.ndarray[DTYPE_t] cums = probs.cumsum()
- *     ll =  probs_fail.sum() # add probability that all edges to victims fail
- *     ll += probs_nv.sum() # add probability that all edges to non_victims fail             # <<<<<<<<<<<<<<
- * 
- *     # print 'probs', probs
- */
-  __pyx_t_3 = PyFloat_FromDouble(__pyx_v_ll); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 81; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
-  __Pyx_GOTREF(__pyx_t_3);
-  __pyx_t_5 = __Pyx_PyObject_GetAttrStr(((PyObject *)__pyx_v_probs_nv), __pyx_n_s_sum); if (unlikely(!__pyx_t_5)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 81; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
-  __Pyx_GOTREF(__pyx_t_5);
-  __pyx_t_6 = NULL;
-  if (CYTHON_COMPILING_IN_CPYTHON && likely(PyMethod_Check(__pyx_t_5))) {
-    __pyx_t_6 = PyMethod_GET_SELF(__pyx_t_5);
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-    __pyx_t_4 = __Pyx_PyObject_CallNoArg(__pyx_t_5); if (unlikely(!__pyx_t_4)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 81; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
-  }
-  __Pyx_GOTREF(__pyx_t_4);
-  __Pyx_DECREF(__pyx_t_5); __pyx_t_5 = 0;
-  __pyx_t_5 = PyNumber_InPlaceAdd(__pyx_t_3, __pyx_t_4); if (unlikely(!__pyx_t_5)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 81; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
-  __Pyx_GOTREF(__pyx_t_5);
-  __Pyx_DECREF(__pyx_t_3); __pyx_t_3 = 0;
-  __Pyx_DECREF(__pyx_t_4); __pyx_t_4 = 0;
-  __pyx_t_24 = __pyx_PyFloat_AsDouble(__pyx_t_5); if (unlikely((__pyx_t_24 == (npy_double)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 81; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
-  __Pyx_DECREF(__pyx_t_5); __pyx_t_5 = 0;
-  __pyx_v_ll = __pyx_t_24;
-
   /* "ml.pyx":84
  * 
  *     # print 'probs', probs
  *     max_beta_add = float('-inf')             # <<<<<<<<<<<<<<
  *     # iterate over all victim nodes to find the optimal threshold
- *     for beta in np.arange(0.001, .2, .002):
+ *     for beta in np.arange(0.09, 1., .05):
  */
   __pyx_t_27 = __Pyx_PyObject_AsDouble(__pyx_kp_s_inf); if (unlikely(__pyx_t_27 == ((double)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 84; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
   __pyx_v_max_beta_add = __pyx_t_27;
@@ -2706,47 +2669,47 @@ static PyObject *__pyx_pf_2ml_ml(CYTHON_UNUSED PyObject *__pyx_self, PyObject *_
   /* "ml.pyx":86
  *     max_beta_add = float('-inf')
  *     # iterate over all victim nodes to find the optimal threshold
- *     for beta in np.arange(0.001, .2, .002):             # <<<<<<<<<<<<<<
+ *     for beta in np.arange(0.09, 1., .05):             # <<<<<<<<<<<<<<
  *         thresh = log(beta/(3012.*(1.-beta)))
  *         # print 'beta:', beta, 'thresh:', thresh, 'infected:', len(probs[probs>=thresh])
  */
-  __pyx_t_5 = __Pyx_GetModuleGlobalName(__pyx_n_s_np); if (unlikely(!__pyx_t_5)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 86; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
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-  __Pyx_GOTREF(__pyx_t_5);
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-  __Pyx_DECREF(__pyx_t_5); __pyx_t_5 = 0;
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+        __pyx_t_3 = PySequence_ITEM(__pyx_t_4, __pyx_t_2); __pyx_t_2++; if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 86; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
         #endif
       }
     } else {
-      __pyx_t_5 = __pyx_t_28(__pyx_t_4);
-      if (unlikely(!__pyx_t_5)) {
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+      if (unlikely(!__pyx_t_3)) {
         PyObject* exc_type = PyErr_Occurred();
         if (exc_type) {
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@@ -2754,15 +2717,15 @@ static PyObject *__pyx_pf_2ml_ml(CYTHON_UNUSED PyObject *__pyx_self, PyObject *_
         }
         break;
       }
-      __Pyx_GOTREF(__pyx_t_5);
+      __Pyx_GOTREF(__pyx_t_3);
     }
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-    __Pyx_DECREF(__pyx_t_5); __pyx_t_5 = 0;
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+    __Pyx_DECREF(__pyx_t_3); __pyx_t_3 = 0;
     __pyx_v_beta = __pyx_t_24;
 
     /* "ml.pyx":87
  *     # iterate over all victim nodes to find the optimal threshold
- *     for beta in np.arange(0.001, .2, .002):
+ *     for beta in np.arange(0.09, 1., .05):
  *         thresh = log(beta/(3012.*(1.-beta)))             # <<<<<<<<<<<<<<
  *         # print 'beta:', beta, 'thresh:', thresh, 'infected:', len(probs[probs>=thresh])
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@@ -2776,15 +2739,15 @@ static PyObject *__pyx_pf_2ml_ml(CYTHON_UNUSED PyObject *__pyx_self, PyObject *_
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  */
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@@ -2801,10 +2764,10 @@ static PyObject *__pyx_pf_2ml_ml(CYTHON_UNUSED PyObject *__pyx_self, PyObject *_
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  *         # add probability for the seeds and non-seeds
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+ *         beta_add += roots * log(beta) + len(probs[probs>=thresh]) * log(1. - beta)
  */
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-    __Pyx_GOTREF(__pyx_t_5);
+    __pyx_t_3 = PyFloat_FromDouble(__pyx_v_beta_add); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 93; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
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@@ -2826,17 +2789,17 @@ static PyObject *__pyx_pf_2ml_ml(CYTHON_UNUSED PyObject *__pyx_self, PyObject *_
       }
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-    __Pyx_GOTREF(__pyx_t_3);
+    __Pyx_GOTREF(__pyx_t_5);
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+    __pyx_t_18 = PyNumber_InPlaceAdd(__pyx_t_3, __pyx_t_5); if (unlikely(!__pyx_t_18)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 93; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
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-    __Pyx_DECREF(__pyx_t_5); __pyx_t_5 = 0;
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@@ -2844,14 +2807,23 @@ static PyObject *__pyx_pf_2ml_ml(CYTHON_UNUSED PyObject *__pyx_self, PyObject *_
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  *         # add probability for the seeds and non-seeds
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+ *         beta_add += roots * log(beta) + len(probs[probs>=thresh]) * log(1. - beta)             # <<<<<<<<<<<<<<
  * 
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+    __pyx_t_18 = PyFloat_FromDouble(__pyx_v_thresh); if (unlikely(!__pyx_t_18)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 95; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
+    __Pyx_GOTREF(__pyx_t_18);
+    __pyx_t_5 = PyObject_RichCompare(((PyObject *)__pyx_v_probs), __pyx_t_18, Py_GE); __Pyx_XGOTREF(__pyx_t_5); if (unlikely(!__pyx_t_5)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 95; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
+    __Pyx_DECREF(__pyx_t_18); __pyx_t_18 = 0;
+    __pyx_t_18 = PyObject_GetItem(((PyObject *)__pyx_v_probs), __pyx_t_5); if (unlikely(__pyx_t_18 == NULL)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 95; __pyx_clineno = __LINE__; goto __pyx_L1_error;};
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+    __Pyx_DECREF(__pyx_t_5); __pyx_t_5 = 0;
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+    __Pyx_DECREF(__pyx_t_18); __pyx_t_18 = 0;
+    __pyx_v_beta_add = (__pyx_v_beta_add + ((__pyx_v_roots * log(__pyx_v_beta)) + (__pyx_t_1 * log((1. - __pyx_v_beta)))));
 
     /* "ml.pyx":97
- *         beta_add += roots * log(beta) + (n_nodes-roots) * log(1. - beta)
+ *         beta_add += roots * log(beta) + len(probs[probs>=thresh]) * log(1. - beta)
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@@ -2893,7 +2865,7 @@ static PyObject *__pyx_pf_2ml_ml(CYTHON_UNUSED PyObject *__pyx_self, PyObject *_
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  *         # print 'beta:', beta, 'thresh:', thresh, 'infected:', len(probs[probs>=thresh])
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-  PyTuple_SET_ITEM(__pyx_t_5, 1, __pyx_t_18);
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-  PyTuple_SET_ITEM(__pyx_t_5, 2, __pyx_t_3);
-  __Pyx_GIVEREF(__pyx_t_3);
+  PyTuple_SET_ITEM(__pyx_t_3, 2, __pyx_t_5);
+  __Pyx_GIVEREF(__pyx_t_5);
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   __pyx_t_18 = 0;
-  __pyx_t_3 = 0;
-  __pyx_r = __pyx_t_5;
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@@ -5320,8 +5292,8 @@ static __Pyx_StringTabEntry __pyx_string_tab[] = {
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+  __pyx_builtin_max = __Pyx_GetBuiltinName(__pyx_n_s_max); if (!__pyx_builtin_max) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 58; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
+  __pyx_builtin_sum = __Pyx_GetBuiltinName(__pyx_n_s_sum); if (!__pyx_builtin_sum) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 70; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
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@@ -5337,11 +5309,11 @@ static int __Pyx_InitCachedConstants(void) {
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@@ -5431,9 +5403,9 @@ static int __Pyx_InitCachedConstants(void) {
 
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