Changed model for spawning. Began fixing underflow error in

prob_success/failure

7 files changed, 579 insertions, 1035 deletions

diff --git a/experiments/build/temp.macosx-10.6-x86_64-2.7/ml.o b/experiments/build/temp.macosx-10.6-x86_64-2.7/ml.o
index 42c7292..6235b48 100644
--- a/experiments/build/temp.macosx-10.6-x86_64-2.7/ml.o
+++ b/experiments/build/temp.macosx-10.6-x86_64-2.7/ml.o
diff --git a/experiments/build_network.py b/experiments/build_network.py
index fd7179f..0756ded 100644
--- a/experiments/build_network.py
+++ b/experiments/build_network.py
@@ -7,7 +7,7 @@ from os.path import splitext
 def build_network(filename):
     victims = {}
     non_victims = {}
-    age = 0.
+    age = 0
     with open(filename) as fh:
         reader = DictReader(fh)
         for row in reader:
@@ -15,7 +15,7 @@ def build_network(filename):
             dist = int(row["dist"])
             w1, w2, w3 = float(row["w1"]), float(row["w2"]), float(row["w3"])
             # if int(float(row["dist"])) > 1:
-                # continue
+            #     continue
             # 'to' is a victim
             if row["t2"] != "NA":
                 dt = int(row["t2"]) - int(row["t1"])
@@ -43,6 +43,7 @@ def build_network(filename):
         if not victims[victim]:
             del victims[victim]
             root_victims[victim] = []
+    print len(root_victims), len(victims), len(non_victims)
     return root_victims, victims, non_victims, age
 
 
@@ -53,5 +54,4 @@ if __name__ == "__main__":
     filename = sys.argv[1]
     root, _ = splitext(filename)
     root_victims, victims, non_victims, age = build_network(filename)
-    print age
     dump((root_victims, victims, non_victims, age), open(root + ".pickle", "w"))
diff --git a/experiments/ml.c b/experiments/ml.c
index 1bc0ddb..b7bbed6 100644
--- a/experiments/ml.c
+++ b/experiments/ml.c
@@ -759,7 +759,7 @@ typedef npy_clongdouble __pyx_t_5numpy_clongdouble_t;
  */
 typedef npy_cdouble __pyx_t_5numpy_complex_t;
 
-/* "ml.pyx":56
+/* "ml.pyx":34
  *     return result
  * 
  * def ml(dict root_victims, dict victims, dict non_victims, DTYPE_t age,             # <<<<<<<<<<<<<<
@@ -773,7 +773,7 @@ struct __pyx_obj_2ml___pyx_scope_struct__ml {
 };
 
 
-/* "ml.pyx":80
+/* "ml.pyx":58
  *                      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))             # <<<<<<<<<<<<<<
@@ -971,7 +971,17 @@ static CYTHON_INLINE int __Pyx_ListComp_Append(PyObject* list, PyObject* x) {
 #endif
 
 #define __Pyx_BufPtrStrided1d(type, buf, i0, s0) (type)((char*)buf + i0 * s0)
-static void __Pyx_RaiseBufferFallbackError(void);
+static double __Pyx__PyObject_AsDouble(PyObject* obj);
+#if CYTHON_COMPILING_IN_PYPY
+#define __Pyx_PyObject_AsDouble(obj) \
+(likely(PyFloat_CheckExact(obj)) ? PyFloat_AS_DOUBLE(obj) : \
+ likely(PyInt_CheckExact(obj)) ? \
+ PyFloat_AsDouble(obj) : __Pyx__PyObject_AsDouble(obj))
+#else
+#define __Pyx_PyObject_AsDouble(obj) \
+((likely(PyFloat_CheckExact(obj))) ? \
+ PyFloat_AS_DOUBLE(obj) : __Pyx__PyObject_AsDouble(obj))
+#endif
 
 static CYTHON_INLINE void __Pyx_ErrRestore(PyObject *type, PyObject *value, PyObject *tb);
 static CYTHON_INLINE void __Pyx_ErrFetch(PyObject **type, PyObject **value, PyObject **tb);
@@ -1050,14 +1060,6 @@ static CYTHON_INLINE int __Pyx_PyInt_As_int(PyObject *);
 
 static CYTHON_INLINE PyObject* __Pyx_PyInt_From_long(long value);
 
-static int __Pyx_Print(PyObject*, PyObject *, int);
-#if CYTHON_COMPILING_IN_PYPY || PY_MAJOR_VERSION >= 3
-static PyObject* __pyx_print = 0;
-static PyObject* __pyx_print_kwargs = 0;
-#endif
-
-static int __Pyx_PrintOne(PyObject* stream, PyObject *o);
-
 #if CYTHON_CCOMPLEX
   #ifdef __cplusplus
     #define __Pyx_CREAL(z) ((z).real())
@@ -1257,7 +1259,7 @@ static PyObject *__pyx_builtin_ValueError;
 static PyObject *__pyx_builtin_range;
 static PyObject *__pyx_builtin_RuntimeError;
 static PyObject *__pyx_pf_2ml_2ml_genexpr(PyObject *__pyx_self); /* proto */
-static PyObject *__pyx_pf_2ml_ml(CYTHON_UNUSED PyObject *__pyx_self, PyObject *__pyx_v_root_victims, PyObject *__pyx_v_victims, PyObject *__pyx_v_non_victims, __pyx_t_2ml_DTYPE_t __pyx_v_age, __pyx_t_2ml_DTYPE_t __pyx_v_alpha, __pyx_t_2ml_DTYPE_t __pyx_v_delta); /* proto */
+static PyObject *__pyx_pf_2ml_ml(CYTHON_UNUSED PyObject *__pyx_self, PyObject *__pyx_v_root_victims, PyObject *__pyx_v_victims, PyObject *__pyx_v_non_victims, CYTHON_UNUSED __pyx_t_2ml_DTYPE_t __pyx_v_age, __pyx_t_2ml_DTYPE_t __pyx_v_alpha, __pyx_t_2ml_DTYPE_t __pyx_v_delta); /* proto */
 static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, Py_buffer *__pyx_v_info, int __pyx_v_flags); /* proto */
 static void __pyx_pf_5numpy_7ndarray_2__releasebuffer__(PyArrayObject *__pyx_v_self, Py_buffer *__pyx_v_info); /* proto */
 static PyObject *__pyx_tp_new_2ml___pyx_scope_struct__ml(PyTypeObject *t, PyObject *a, PyObject *k); /*proto*/
@@ -1288,17 +1290,14 @@ static char __pyx_k_w1[] = "w1";
 static char __pyx_k_w2[] = "w2";
 static char __pyx_k_w3[] = "w3";
 static char __pyx_k_age[] = "age";
-static char __pyx_k_end[] = "end";
+static char __pyx_k_inf[] = "-inf";
 static char __pyx_k_max[] = "max";
 static char __pyx_k_sum[] = "sum";
 static char __pyx_k_args[] = "args";
 static char __pyx_k_beta[] = "beta";
-static char __pyx_k_cums[] = "cums";
 static char __pyx_k_dist[] = "dist";
-static char __pyx_k_file[] = "file";
 static char __pyx_k_main[] = "__main__";
 static char __pyx_k_send[] = "send";
-static char __pyx_k_sort[] = "sort";
 static char __pyx_k_test[] = "__test__";
 static char __pyx_k_DTYPE[] = "DTYPE";
 static char __pyx_k_alpha[] = "alpha";
@@ -1306,16 +1305,15 @@ static char __pyx_k_beta2[] = "beta2";
 static char __pyx_k_close[] = "close";
 static char __pyx_k_delta[] = "delta";
 static char __pyx_k_dtype[] = "dtype";
+static char __pyx_k_max_i[] = "max_i";
 static char __pyx_k_numpy[] = "numpy";
-static char __pyx_k_print[] = "print";
 static char __pyx_k_probs[] = "probs";
 static char __pyx_k_range[] = "range";
 static char __pyx_k_roots[] = "roots";
 static char __pyx_k_throw[] = "throw";
 static char __pyx_k_zeros[] = "zeros";
-static char __pyx_k_cumsum[] = "cumsum";
-static char __pyx_k_format[] = "format";
 static char __pyx_k_import[] = "__import__";
+static char __pyx_k_thresh[] = "thresh";
 static char __pyx_k_xrange[] = "xrange";
 static char __pyx_k_float64[] = "float64";
 static char __pyx_k_genexpr[] = "genexpr";
@@ -1323,6 +1321,7 @@ static char __pyx_k_n_nodes[] = "n_nodes";
 static char __pyx_k_n_roots[] = "n_roots";
 static char __pyx_k_parents[] = "parents";
 static char __pyx_k_victims[] = "victims";
+static char __pyx_k_beta_add[] = "beta_add";
 static char __pyx_k_failures[] = "failures";
 static char __pyx_k_probs_nv[] = "probs_nv";
 static char __pyx_k_enumerate[] = "enumerate";
@@ -1333,6 +1332,7 @@ static char __pyx_k_itervalues[] = "itervalues";
 static char __pyx_k_probs_fail[] = "probs_fail";
 static char __pyx_k_non_victims[] = "non_victims";
 static char __pyx_k_RuntimeError[] = "RuntimeError";
+static char __pyx_k_max_beta_add[] = "max_beta_add";
 static char __pyx_k_root_victims[] = "root_victims";
 static char __pyx_k_ml_locals_genexpr[] = "ml.<locals>.genexpr";
 static char __pyx_k_ndarray_is_not_C_contiguous[] = "ndarray is not C contiguous";
@@ -1340,7 +1340,6 @@ static char __pyx_k_Users_ben_Documents_Cascade_Pro[] = "/Users/ben/Documents/Ca
 static char __pyx_k_unknown_dtype_code_in_numpy_pxd[] = "unknown dtype code in numpy.pxd (%d)";
 static char __pyx_k_Format_string_allocated_too_shor[] = "Format string allocated too short, see comment in numpy.pxd";
 static char __pyx_k_Non_native_byte_order_not_suppor[] = "Non-native byte order not supported";
-static char __pyx_k_alpha_0_delta_1_Everyone_is_a_ro[] = "alpha: {0}, delta: {1}. Everyone is a root";
 static char __pyx_k_ndarray_is_not_Fortran_contiguou[] = "ndarray is not Fortran contiguous";
 static char __pyx_k_Format_string_allocated_too_shor_2[] = "Format string allocated too short.";
 static PyObject *__pyx_n_s_DTYPE;
@@ -1352,31 +1351,29 @@ static PyObject *__pyx_kp_s_Users_ben_Documents_Cascade_Pro;
 static PyObject *__pyx_n_s_ValueError;
 static PyObject *__pyx_n_s_age;
 static PyObject *__pyx_n_s_alpha;
-static PyObject *__pyx_kp_s_alpha_0_delta_1_Everyone_is_a_ro;
 static PyObject *__pyx_n_s_args;
 static PyObject *__pyx_n_s_beta;
 static PyObject *__pyx_n_s_beta2;
+static PyObject *__pyx_n_s_beta_add;
 static PyObject *__pyx_n_s_close;
-static PyObject *__pyx_n_s_cums;
-static PyObject *__pyx_n_s_cumsum;
 static PyObject *__pyx_n_s_delta;
 static PyObject *__pyx_n_s_dist;
 static PyObject *__pyx_n_s_dt;
 static PyObject *__pyx_n_s_dtype;
-static PyObject *__pyx_n_s_end;
 static PyObject *__pyx_n_s_enumerate;
 static PyObject *__pyx_n_s_failures;
-static PyObject *__pyx_n_s_file;
 static PyObject *__pyx_n_s_float64;
-static PyObject *__pyx_n_s_format;
 static PyObject *__pyx_n_s_genexpr;
 static PyObject *__pyx_n_s_i;
 static PyObject *__pyx_n_s_import;
+static PyObject *__pyx_kp_s_inf;
 static PyObject *__pyx_n_s_itervalues;
 static PyObject *__pyx_n_s_l;
 static PyObject *__pyx_n_s_ll;
 static PyObject *__pyx_n_s_main;
 static PyObject *__pyx_n_s_max;
+static PyObject *__pyx_n_s_max_beta_add;
+static PyObject *__pyx_n_s_max_i;
 static PyObject *__pyx_n_s_ml;
 static PyObject *__pyx_n_s_ml_locals_genexpr;
 static PyObject *__pyx_n_s_n_nodes;
@@ -1388,7 +1385,6 @@ static PyObject *__pyx_n_s_non_victims;
 static PyObject *__pyx_n_s_np;
 static PyObject *__pyx_n_s_numpy;
 static PyObject *__pyx_n_s_parents;
-static PyObject *__pyx_n_s_print;
 static PyObject *__pyx_n_s_probs;
 static PyObject *__pyx_n_s_probs_fail;
 static PyObject *__pyx_n_s_probs_nv;
@@ -1396,11 +1392,11 @@ static PyObject *__pyx_n_s_range;
 static PyObject *__pyx_n_s_root_victims;
 static PyObject *__pyx_n_s_roots;
 static PyObject *__pyx_n_s_send;
-static PyObject *__pyx_n_s_sort;
 static PyObject *__pyx_n_s_successes;
 static PyObject *__pyx_n_s_sum;
 static PyObject *__pyx_n_s_t;
 static PyObject *__pyx_n_s_test;
+static PyObject *__pyx_n_s_thresh;
 static PyObject *__pyx_n_s_throw;
 static PyObject *__pyx_kp_u_unknown_dtype_code_in_numpy_pxd;
 static PyObject *__pyx_n_s_victims;
@@ -1410,15 +1406,14 @@ static PyObject *__pyx_n_s_w3;
 static PyObject *__pyx_n_s_xrange;
 static PyObject *__pyx_n_s_zeros;
 static PyObject *__pyx_int_neg_1;
-static PyObject *__pyx_slice_;
+static PyObject *__pyx_tuple_;
 static PyObject *__pyx_tuple__2;
 static PyObject *__pyx_tuple__3;
 static PyObject *__pyx_tuple__4;
 static PyObject *__pyx_tuple__5;
 static PyObject *__pyx_tuple__6;
 static PyObject *__pyx_tuple__7;
-static PyObject *__pyx_tuple__8;
-static PyObject *__pyx_codeobj__9;
+static PyObject *__pyx_codeobj__8;
 
 /* "ml.pyx":9
  * ctypedef np.float_t DTYPE_t
@@ -1476,36 +1471,36 @@ static __pyx_t_2ml_DTYPE_t __pyx_f_2ml_weight_success(int __pyx_v_dist, int __py
   /* "ml.pyx":16
  *     """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) * (1 - exp(-alpha))
+ *     temporal = log(alpha) - alpha * dt
  */
-  __pyx_v_structural = pow(__pyx_v_delta, ((__pyx_t_2ml_DTYPE_t)__pyx_v_dist));
+  __pyx_v_structural = (__pyx_v_dist * log(__pyx_v_delta));
 
   /* "ml.pyx":18
- *     structural = delta ** (dist)
+ *     structural = dist * log(delta)
  *     # structural = plogis(w1,delta) * plogis(w2,delta) * plogis(w3,delta)
- *     temporal = exp(-alpha * dt) * (1 - exp(-alpha))             # <<<<<<<<<<<<<<
- *     result = log(structural * temporal)
- *     return result
+ *     temporal = log(alpha) - alpha * dt             # <<<<<<<<<<<<<<
+ *     # temporal = 1. / (1. + (dt - 1.)/alpha)**0.01 - 1. / (1. + dt/alpha)**0.01
+ *     result = structural + temporal
  */
-  __pyx_v_temporal = (exp(((-__pyx_v_alpha) * __pyx_v_dt)) * (1.0 - exp((-__pyx_v_alpha))));
+  __pyx_v_temporal = (log(__pyx_v_alpha) - (__pyx_v_alpha * __pyx_v_dt));
 
-  /* "ml.pyx":19
- *     # structural = plogis(w1,delta) * plogis(w2,delta) * plogis(w3,delta)
- *     temporal = exp(-alpha * dt) * (1 - exp(-alpha))
- *     result = log(structural * temporal)             # <<<<<<<<<<<<<<
+  /* "ml.pyx":20
+ *     temporal = log(alpha) - alpha * dt
+ *     # temporal = 1. / (1. + (dt - 1.)/alpha)**0.01 - 1. / (1. + dt/alpha)**0.01
+ *     result = structural + temporal             # <<<<<<<<<<<<<<
  *     return result
  * 
  */
-  __pyx_v_result = log((__pyx_v_structural * __pyx_v_temporal));
+  __pyx_v_result = (__pyx_v_structural + __pyx_v_temporal);
 
-  /* "ml.pyx":20
- *     temporal = exp(-alpha * dt) * (1 - exp(-alpha))
- *     result = log(structural * temporal)
+  /* "ml.pyx":21
+ *     # temporal = 1. / (1. + (dt - 1.)/alpha)**0.01 - 1. / (1. + dt/alpha)**0.01
+ *     result = structural + temporal
  *     return result             # <<<<<<<<<<<<<<
  * 
- * 
+ * cdef DTYPE_t weight_failure(int dist, int dt, DTYPE_t alpha, DTYPE_t delta,
  */
   __pyx_r = __pyx_v_result;
   goto __pyx_L0;
@@ -1525,75 +1520,8 @@ static __pyx_t_2ml_DTYPE_t __pyx_f_2ml_weight_success(int __pyx_v_dist, int __py
 }
 
 /* "ml.pyx":23
- * 
- * 
- * cdef DTYPE_t weight_success_power(int dist, int dt, DTYPE_t alpha, DTYPE_t delta,             # <<<<<<<<<<<<<<
- *                                 DTYPE_t w1, DTYPE_t w2, DTYPE_t w3):
- *     """weight for successful infection, power-law time model"""
- */
-
-static __pyx_t_2ml_DTYPE_t __pyx_f_2ml_weight_success_power(int __pyx_v_dist, int __pyx_v_dt, __pyx_t_2ml_DTYPE_t __pyx_v_alpha, __pyx_t_2ml_DTYPE_t __pyx_v_delta, CYTHON_UNUSED __pyx_t_2ml_DTYPE_t __pyx_v_w1, CYTHON_UNUSED __pyx_t_2ml_DTYPE_t __pyx_v_w2, CYTHON_UNUSED __pyx_t_2ml_DTYPE_t __pyx_v_w3) {
-  __pyx_t_2ml_DTYPE_t __pyx_v_structural;
-  __pyx_t_2ml_DTYPE_t __pyx_v_temporal;
-  __pyx_t_2ml_DTYPE_t __pyx_v_result;
-  __pyx_t_2ml_DTYPE_t __pyx_r;
-  __Pyx_RefNannyDeclarations
-  __Pyx_RefNannySetupContext("weight_success_power", 0);
-
-  /* "ml.pyx":27
- *     """weight for successful infection, power-law time model"""
- *     cdef DTYPE_t structural, temporal, result
- *     structural = delta ** (dist)             # <<<<<<<<<<<<<<
- *     # structural = plogis(w1,delta) * plogis(w2,delta) * plogis(w3,delta)
- *     temporal = 1. / (1. + (dt - 1.)/alpha)**0.01 - 1. / (1. + dt/alpha)**0.01
- */
-  __pyx_v_structural = pow(__pyx_v_delta, ((__pyx_t_2ml_DTYPE_t)__pyx_v_dist));
-
-  /* "ml.pyx":29
- *     structural = delta ** (dist)
- *     # structural = plogis(w1,delta) * plogis(w2,delta) * plogis(w3,delta)
- *     temporal = 1. / (1. + (dt - 1.)/alpha)**0.01 - 1. / (1. + dt/alpha)**0.01             # <<<<<<<<<<<<<<
- *     result = log(structural * temporal)
- *     return result
- */
-  __pyx_v_temporal = ((1. / pow(((double)(1. + ((__pyx_v_dt - 1.) / __pyx_v_alpha))), 0.01)) - (1. / pow(((double)(1. + (__pyx_v_dt / __pyx_v_alpha))), 0.01)));
-
-  /* "ml.pyx":30
- *     # structural = plogis(w1,delta) * plogis(w2,delta) * plogis(w3,delta)
- *     temporal = 1. / (1. + (dt - 1.)/alpha)**0.01 - 1. / (1. + dt/alpha)**0.01
- *     result = log(structural * temporal)             # <<<<<<<<<<<<<<
  *     return result
  * 
- */
-  __pyx_v_result = log((__pyx_v_structural * __pyx_v_temporal));
-
-  /* "ml.pyx":31
- *     temporal = 1. / (1. + (dt - 1.)/alpha)**0.01 - 1. / (1. + dt/alpha)**0.01
- *     result = log(structural * temporal)
- *     return result             # <<<<<<<<<<<<<<
- * 
- * 
- */
-  __pyx_r = __pyx_v_result;
-  goto __pyx_L0;
-
-  /* "ml.pyx":23
- * 
- * 
- * cdef DTYPE_t weight_success_power(int dist, int dt, DTYPE_t alpha, DTYPE_t delta,             # <<<<<<<<<<<<<<
- *                                 DTYPE_t w1, DTYPE_t w2, DTYPE_t w3):
- *     """weight for successful infection, power-law time model"""
- */
-
-  /* function exit code */
-  __pyx_L0:;
-  __Pyx_RefNannyFinishContext();
-  return __pyx_r;
-}
-
-/* "ml.pyx":34
- * 
- * 
  * cdef DTYPE_t weight_failure(int dist, int dt, DTYPE_t alpha, DTYPE_t delta,             # <<<<<<<<<<<<<<
  *                             DTYPE_t w1, DTYPE_t w2, DTYPE_t w3):
  *     """weight for failed infection, exponential time model"""
@@ -1607,45 +1535,45 @@ static __pyx_t_2ml_DTYPE_t __pyx_f_2ml_weight_failure(int __pyx_v_dist, int __py
   __Pyx_RefNannyDeclarations
   __Pyx_RefNannySetupContext("weight_failure", 0);
 
-  /* "ml.pyx":38
+  /* "ml.pyx":27
  *     """weight for failed infection, exponential time model"""
  *     cdef DTYPE_t structural, temporal, result
- *     structural = delta ** (dist)             # <<<<<<<<<<<<<<
+ *     structural = delta ** dist             # <<<<<<<<<<<<<<
  *     # structural = plogis(w1,delta) * plogis(w2,delta) * plogis(w3,delta)
  *     temporal = 1. - exp(-alpha * dt)
  */
   __pyx_v_structural = pow(__pyx_v_delta, ((__pyx_t_2ml_DTYPE_t)__pyx_v_dist));
 
-  /* "ml.pyx":40
- *     structural = delta ** (dist)
+  /* "ml.pyx":29
+ *     structural = delta ** dist
  *     # structural = plogis(w1,delta) * plogis(w2,delta) * plogis(w3,delta)
  *     temporal = 1. - exp(-alpha * dt)             # <<<<<<<<<<<<<<
- *     #result = log(1. - structural)
+ *     # temporal = 1.  - 1. / (1. + dt/alpha)**0.01
  *     result = log(1. - structural * temporal)
  */
   __pyx_v_temporal = (1. - exp(((-__pyx_v_alpha) * __pyx_v_dt)));
 
-  /* "ml.pyx":42
+  /* "ml.pyx":31
  *     temporal = 1. - exp(-alpha * dt)
- *     #result = log(1. - structural)
+ *     # temporal = 1.  - 1. / (1. + dt/alpha)**0.01
  *     result = log(1. - structural * temporal)             # <<<<<<<<<<<<<<
  *     return result
  * 
  */
   __pyx_v_result = log((1. - (__pyx_v_structural * __pyx_v_temporal)));
 
-  /* "ml.pyx":43
- *     #result = log(1. - structural)
+  /* "ml.pyx":32
+ *     # temporal = 1.  - 1. / (1. + dt/alpha)**0.01
  *     result = log(1. - structural * temporal)
  *     return result             # <<<<<<<<<<<<<<
  * 
- * 
+ * def ml(dict root_victims, dict victims, dict non_victims, DTYPE_t age,
  */
   __pyx_r = __pyx_v_result;
   goto __pyx_L0;
 
-  /* "ml.pyx":34
- * 
+  /* "ml.pyx":23
+ *     return result
  * 
  * cdef DTYPE_t weight_failure(int dist, int dt, DTYPE_t alpha, DTYPE_t delta,             # <<<<<<<<<<<<<<
  *                             DTYPE_t w1, DTYPE_t w2, DTYPE_t w3):
@@ -1658,74 +1586,7 @@ static __pyx_t_2ml_DTYPE_t __pyx_f_2ml_weight_failure(int __pyx_v_dist, int __py
   return __pyx_r;
 }
 
-/* "ml.pyx":46
- * 
- * 
- * cdef DTYPE_t weight_failure_power(int dist, int dt, DTYPE_t alpha, DTYPE_t delta,             # <<<<<<<<<<<<<<
- *                                 DTYPE_t w1, DTYPE_t w2, DTYPE_t w3):
- *     """weight for failed infection, power-law time model"""
- */
-
-static __pyx_t_2ml_DTYPE_t __pyx_f_2ml_weight_failure_power(int __pyx_v_dist, int __pyx_v_dt, __pyx_t_2ml_DTYPE_t __pyx_v_alpha, __pyx_t_2ml_DTYPE_t __pyx_v_delta, CYTHON_UNUSED __pyx_t_2ml_DTYPE_t __pyx_v_w1, CYTHON_UNUSED __pyx_t_2ml_DTYPE_t __pyx_v_w2, CYTHON_UNUSED __pyx_t_2ml_DTYPE_t __pyx_v_w3) {
-  __pyx_t_2ml_DTYPE_t __pyx_v_structural;
-  __pyx_t_2ml_DTYPE_t __pyx_v_temporal;
-  __pyx_t_2ml_DTYPE_t __pyx_v_result;
-  __pyx_t_2ml_DTYPE_t __pyx_r;
-  __Pyx_RefNannyDeclarations
-  __Pyx_RefNannySetupContext("weight_failure_power", 0);
-
-  /* "ml.pyx":50
- *     """weight for failed infection, power-law time model"""
- *     cdef DTYPE_t structural, temporal, result
- *     structural = delta ** (dist)             # <<<<<<<<<<<<<<
- *     # structural = plogis(w1,delta) * plogis(w2,delta) * plogis(w3,delta)
- *     temporal = 1.  - 1. / (1. + dt/alpha)**0.01
- */
-  __pyx_v_structural = pow(__pyx_v_delta, ((__pyx_t_2ml_DTYPE_t)__pyx_v_dist));
-
-  /* "ml.pyx":52
- *     structural = delta ** (dist)
- *     # structural = plogis(w1,delta) * plogis(w2,delta) * plogis(w3,delta)
- *     temporal = 1.  - 1. / (1. + dt/alpha)**0.01             # <<<<<<<<<<<<<<
- *     result = log(1. - structural * temporal)
- *     return result
- */
-  __pyx_v_temporal = (1. - (1. / pow(((double)(1. + (__pyx_v_dt / __pyx_v_alpha))), 0.01)));
-
-  /* "ml.pyx":53
- *     # structural = plogis(w1,delta) * plogis(w2,delta) * plogis(w3,delta)
- *     temporal = 1.  - 1. / (1. + dt/alpha)**0.01
- *     result = log(1. - structural * temporal)             # <<<<<<<<<<<<<<
- *     return result
- * 
- */
-  __pyx_v_result = log((1. - (__pyx_v_structural * __pyx_v_temporal)));
-
-  /* "ml.pyx":54
- *     temporal = 1.  - 1. / (1. + dt/alpha)**0.01
- *     result = log(1. - structural * temporal)
- *     return result             # <<<<<<<<<<<<<<
- * 
- * def ml(dict root_victims, dict victims, dict non_victims, DTYPE_t age,
- */
-  __pyx_r = __pyx_v_result;
-  goto __pyx_L0;
-
-  /* "ml.pyx":46
- * 
- * 
- * cdef DTYPE_t weight_failure_power(int dist, int dt, DTYPE_t alpha, DTYPE_t delta,             # <<<<<<<<<<<<<<
- *                                 DTYPE_t w1, DTYPE_t w2, DTYPE_t w3):
- *     """weight for failed infection, power-law time model"""
- */
-
-  /* function exit code */
-  __pyx_L0:;
-  __Pyx_RefNannyFinishContext();
-  return __pyx_r;
-}
-
-/* "ml.pyx":56
+/* "ml.pyx":34
  *     return result
  * 
  * def ml(dict root_victims, dict victims, dict non_victims, DTYPE_t age,             # <<<<<<<<<<<<<<
@@ -1740,7 +1601,7 @@ static PyObject *__pyx_pw_2ml_1ml(PyObject *__pyx_self, PyObject *__pyx_args, Py
   PyObject *__pyx_v_root_victims = 0;
   PyObject *__pyx_v_victims = 0;
   PyObject *__pyx_v_non_victims = 0;
-  __pyx_t_2ml_DTYPE_t __pyx_v_age;
+  CYTHON_UNUSED __pyx_t_2ml_DTYPE_t __pyx_v_age;
   __pyx_t_2ml_DTYPE_t __pyx_v_alpha;
   __pyx_t_2ml_DTYPE_t __pyx_v_delta;
   int __pyx_lineno = 0;
@@ -1773,31 +1634,31 @@ static PyObject *__pyx_pw_2ml_1ml(PyObject *__pyx_self, PyObject *__pyx_args, Py
         case  1:
         if (likely((values[1] = PyDict_GetItem(__pyx_kwds, __pyx_n_s_victims)) != 0)) kw_args--;
         else {
-          __Pyx_RaiseArgtupleInvalid("ml", 1, 6, 6, 1); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 56; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
+          __Pyx_RaiseArgtupleInvalid("ml", 1, 6, 6, 1); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 34; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
         }
         case  2:
         if (likely((values[2] = PyDict_GetItem(__pyx_kwds, __pyx_n_s_non_victims)) != 0)) kw_args--;
         else {
-          __Pyx_RaiseArgtupleInvalid("ml", 1, 6, 6, 2); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 56; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
+          __Pyx_RaiseArgtupleInvalid("ml", 1, 6, 6, 2); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 34; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
         }
         case  3:
         if (likely((values[3] = PyDict_GetItem(__pyx_kwds, __pyx_n_s_age)) != 0)) kw_args--;
         else {
-          __Pyx_RaiseArgtupleInvalid("ml", 1, 6, 6, 3); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 56; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
+          __Pyx_RaiseArgtupleInvalid("ml", 1, 6, 6, 3); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 34; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
         }
         case  4:
         if (likely((values[4] = PyDict_GetItem(__pyx_kwds, __pyx_n_s_alpha)) != 0)) kw_args--;
         else {
-          __Pyx_RaiseArgtupleInvalid("ml", 1, 6, 6, 4); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 56; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
+          __Pyx_RaiseArgtupleInvalid("ml", 1, 6, 6, 4); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 34; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
         }
         case  5:
         if (likely((values[5] = PyDict_GetItem(__pyx_kwds, __pyx_n_s_delta)) != 0)) kw_args--;
         else {
-          __Pyx_RaiseArgtupleInvalid("ml", 1, 6, 6, 5); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 56; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
+          __Pyx_RaiseArgtupleInvalid("ml", 1, 6, 6, 5); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 34; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
         }
       }
       if (unlikely(kw_args > 0)) {
-        if (unlikely(__Pyx_ParseOptionalKeywords(__pyx_kwds, __pyx_pyargnames, 0, values, pos_args, "ml") < 0)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 56; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
+        if (unlikely(__Pyx_ParseOptionalKeywords(__pyx_kwds, __pyx_pyargnames, 0, values, pos_args, "ml") < 0)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 34; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
       }
     } else if (PyTuple_GET_SIZE(__pyx_args) != 6) {
       goto __pyx_L5_argtuple_error;
@@ -1812,21 +1673,21 @@ static PyObject *__pyx_pw_2ml_1ml(PyObject *__pyx_self, PyObject *__pyx_args, Py
     __pyx_v_root_victims = ((PyObject*)values[0]);
     __pyx_v_victims = ((PyObject*)values[1]);
     __pyx_v_non_victims = ((PyObject*)values[2]);
-    __pyx_v_age = __pyx_PyFloat_AsDouble(values[3]); if (unlikely((__pyx_v_age == (npy_double)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 56; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
-    __pyx_v_alpha = __pyx_PyFloat_AsDouble(values[4]); if (unlikely((__pyx_v_alpha == (npy_double)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 57; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
-    __pyx_v_delta = __pyx_PyFloat_AsDouble(values[5]); if (unlikely((__pyx_v_delta == (npy_double)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 57; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
+    __pyx_v_age = __pyx_PyFloat_AsDouble(values[3]); if (unlikely((__pyx_v_age == (npy_double)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 34; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
+    __pyx_v_alpha = __pyx_PyFloat_AsDouble(values[4]); if (unlikely((__pyx_v_alpha == (npy_double)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 35; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
+    __pyx_v_delta = __pyx_PyFloat_AsDouble(values[5]); if (unlikely((__pyx_v_delta == (npy_double)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 35; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
   }
   goto __pyx_L4_argument_unpacking_done;
   __pyx_L5_argtuple_error:;
-  __Pyx_RaiseArgtupleInvalid("ml", 1, 6, 6, PyTuple_GET_SIZE(__pyx_args)); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 56; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
+  __Pyx_RaiseArgtupleInvalid("ml", 1, 6, 6, PyTuple_GET_SIZE(__pyx_args)); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 34; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
   __pyx_L3_error:;
   __Pyx_AddTraceback("ml.ml", __pyx_clineno, __pyx_lineno, __pyx_filename);
   __Pyx_RefNannyFinishContext();
   return NULL;
   __pyx_L4_argument_unpacking_done:;
-  if (unlikely(!__Pyx_ArgTypeTest(((PyObject *)__pyx_v_root_victims), (&PyDict_Type), 1, "root_victims", 1))) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 56; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
-  if (unlikely(!__Pyx_ArgTypeTest(((PyObject *)__pyx_v_victims), (&PyDict_Type), 1, "victims", 1))) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 56; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
-  if (unlikely(!__Pyx_ArgTypeTest(((PyObject *)__pyx_v_non_victims), (&PyDict_Type), 1, "non_victims", 1))) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 56; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
+  if (unlikely(!__Pyx_ArgTypeTest(((PyObject *)__pyx_v_root_victims), (&PyDict_Type), 1, "root_victims", 1))) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 34; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
+  if (unlikely(!__Pyx_ArgTypeTest(((PyObject *)__pyx_v_victims), (&PyDict_Type), 1, "victims", 1))) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 34; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
+  if (unlikely(!__Pyx_ArgTypeTest(((PyObject *)__pyx_v_non_victims), (&PyDict_Type), 1, "non_victims", 1))) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 34; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
   __pyx_r = __pyx_pf_2ml_ml(__pyx_self, __pyx_v_root_victims, __pyx_v_victims, __pyx_v_non_victims, __pyx_v_age, __pyx_v_alpha, __pyx_v_delta);
 
   /* function exit code */
@@ -1839,7 +1700,7 @@ static PyObject *__pyx_pw_2ml_1ml(PyObject *__pyx_self, PyObject *__pyx_args, Py
 }
 static PyObject *__pyx_gb_2ml_2ml_2generator(__pyx_GeneratorObject *__pyx_generator, PyObject *__pyx_sent_value); /* proto */
 
-/* "ml.pyx":80
+/* "ml.pyx":58
  *                      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))             # <<<<<<<<<<<<<<
@@ -1865,7 +1726,7 @@ static PyObject *__pyx_pf_2ml_2ml_genexpr(PyObject *__pyx_self) {
   __Pyx_INCREF(((PyObject *)__pyx_cur_scope->__pyx_outer_scope));
   __Pyx_GIVEREF(__pyx_cur_scope->__pyx_outer_scope);
   {
-    __pyx_GeneratorObject *gen = __Pyx_Generator_New((__pyx_generator_body_t) __pyx_gb_2ml_2ml_2generator, (PyObject *) __pyx_cur_scope, __pyx_n_s_genexpr, __pyx_n_s_ml_locals_genexpr); if (unlikely(!gen)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 80; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
+    __pyx_GeneratorObject *gen = __Pyx_Generator_New((__pyx_generator_body_t) __pyx_gb_2ml_2ml_2generator, (PyObject *) __pyx_cur_scope, __pyx_n_s_genexpr, __pyx_n_s_ml_locals_genexpr); if (unlikely(!gen)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 58; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
     __Pyx_DECREF(__pyx_cur_scope);
     __Pyx_RefNannyFinishContext();
     return (PyObject *) gen;
@@ -1903,16 +1764,16 @@ static PyObject *__pyx_gb_2ml_2ml_2generator(__pyx_GeneratorObject *__pyx_genera
     return NULL;
   }
   __pyx_L3_first_run:;
-  if (unlikely(!__pyx_sent_value)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 80; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
+  if (unlikely(!__pyx_sent_value)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 58; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
   __pyx_t_1 = 0;
-  if (unlikely(!__pyx_cur_scope->__pyx_outer_scope->__pyx_v_successes)) { __Pyx_RaiseClosureNameError("successes"); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 80; __pyx_clineno = __LINE__; goto __pyx_L1_error;} }
+  if (unlikely(!__pyx_cur_scope->__pyx_outer_scope->__pyx_v_successes)) { __Pyx_RaiseClosureNameError("successes"); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 58; __pyx_clineno = __LINE__; goto __pyx_L1_error;} }
   __pyx_t_2 = __pyx_cur_scope->__pyx_outer_scope->__pyx_v_successes; __Pyx_INCREF(__pyx_t_2); __pyx_t_3 = 0;
   for (;;) {
     if (__pyx_t_3 >= PyList_GET_SIZE(__pyx_t_2)) break;
     #if CYTHON_COMPILING_IN_CPYTHON
-    __pyx_t_4 = PyList_GET_ITEM(__pyx_t_2, __pyx_t_3); __Pyx_INCREF(__pyx_t_4); __pyx_t_3++; if (unlikely(0 < 0)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 80; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
+    __pyx_t_4 = PyList_GET_ITEM(__pyx_t_2, __pyx_t_3); __Pyx_INCREF(__pyx_t_4); __pyx_t_3++; if (unlikely(0 < 0)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 58; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
     #else
-    __pyx_t_4 = PySequence_ITEM(__pyx_t_2, __pyx_t_3); __pyx_t_3++; if (unlikely(!__pyx_t_4)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 80; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
+    __pyx_t_4 = PySequence_ITEM(__pyx_t_2, __pyx_t_3); __pyx_t_3++; if (unlikely(!__pyx_t_4)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 58; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
     #endif
     __Pyx_XGOTREF(__pyx_cur_scope->__pyx_v_s);
     __Pyx_XDECREF_SET(__pyx_cur_scope->__pyx_v_s, __pyx_t_4);
@@ -1920,14 +1781,14 @@ static PyObject *__pyx_gb_2ml_2ml_2generator(__pyx_GeneratorObject *__pyx_genera
     __pyx_t_4 = 0;
     __pyx_cur_scope->__pyx_v_l = __pyx_t_1;
     __pyx_t_1 = (__pyx_t_1 + 1);
-    if (unlikely(!__pyx_cur_scope->__pyx_outer_scope->__pyx_v_failures)) { __Pyx_RaiseClosureNameError("failures"); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 80; __pyx_clineno = __LINE__; goto __pyx_L1_error;} }
+    if (unlikely(!__pyx_cur_scope->__pyx_outer_scope->__pyx_v_failures)) { __Pyx_RaiseClosureNameError("failures"); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 58; __pyx_clineno = __LINE__; goto __pyx_L1_error;} }
     if (unlikely(__pyx_cur_scope->__pyx_outer_scope->__pyx_v_failures == Py_None)) {
       PyErr_SetString(PyExc_TypeError, "'NoneType' object is not subscriptable");
-      {__pyx_filename = __pyx_f[0]; __pyx_lineno = 80; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
+      {__pyx_filename = __pyx_f[0]; __pyx_lineno = 58; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
     }
-    __pyx_t_4 = __Pyx_GetItemInt_List(__pyx_cur_scope->__pyx_outer_scope->__pyx_v_failures, __pyx_cur_scope->__pyx_v_l, Py_ssize_t, 1, PyInt_FromSsize_t, 1, 1, 0); if (unlikely(__pyx_t_4 == NULL)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 80; __pyx_clineno = __LINE__; goto __pyx_L1_error;};
+    __pyx_t_4 = __Pyx_GetItemInt_List(__pyx_cur_scope->__pyx_outer_scope->__pyx_v_failures, __pyx_cur_scope->__pyx_v_l, Py_ssize_t, 1, PyInt_FromSsize_t, 1, 1, 0); if (unlikely(__pyx_t_4 == NULL)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 58; __pyx_clineno = __LINE__; goto __pyx_L1_error;};
     __Pyx_GOTREF(__pyx_t_4);
-    __pyx_t_5 = PyNumber_Subtract(__pyx_cur_scope->__pyx_v_s, __pyx_t_4); if (unlikely(!__pyx_t_5)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 80; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
+    __pyx_t_5 = PyNumber_Subtract(__pyx_cur_scope->__pyx_v_s, __pyx_t_4); if (unlikely(!__pyx_t_5)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 58; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
     __Pyx_GOTREF(__pyx_t_5);
     __Pyx_DECREF(__pyx_t_4); __pyx_t_4 = 0;
     __pyx_r = __pyx_t_5;
@@ -1947,7 +1808,7 @@ static PyObject *__pyx_gb_2ml_2ml_2generator(__pyx_GeneratorObject *__pyx_genera
     __pyx_cur_scope->__pyx_t_1 = 0;
     __Pyx_XGOTREF(__pyx_t_2);
     __pyx_t_3 = __pyx_cur_scope->__pyx_t_2;
-    if (unlikely(!__pyx_sent_value)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 80; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
+    if (unlikely(!__pyx_sent_value)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 58; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
   }
   __Pyx_DECREF(__pyx_t_2); __pyx_t_2 = 0;
 
@@ -1967,7 +1828,7 @@ static PyObject *__pyx_gb_2ml_2ml_2generator(__pyx_GeneratorObject *__pyx_genera
   return NULL;
 }
 
-/* "ml.pyx":56
+/* "ml.pyx":34
  *     return result
  * 
  * def ml(dict root_victims, dict victims, dict non_victims, DTYPE_t age,             # <<<<<<<<<<<<<<
@@ -1975,11 +1836,11 @@ static PyObject *__pyx_gb_2ml_2ml_2generator(__pyx_GeneratorObject *__pyx_genera
  *     cdef:
  */
 
-static PyObject *__pyx_pf_2ml_ml(CYTHON_UNUSED PyObject *__pyx_self, PyObject *__pyx_v_root_victims, PyObject *__pyx_v_victims, PyObject *__pyx_v_non_victims, __pyx_t_2ml_DTYPE_t __pyx_v_age, __pyx_t_2ml_DTYPE_t __pyx_v_alpha, __pyx_t_2ml_DTYPE_t __pyx_v_delta) {
+static PyObject *__pyx_pf_2ml_ml(CYTHON_UNUSED PyObject *__pyx_self, PyObject *__pyx_v_root_victims, PyObject *__pyx_v_victims, PyObject *__pyx_v_non_victims, CYTHON_UNUSED __pyx_t_2ml_DTYPE_t __pyx_v_age, __pyx_t_2ml_DTYPE_t __pyx_v_alpha, __pyx_t_2ml_DTYPE_t __pyx_v_delta) {
   struct __pyx_obj_2ml___pyx_scope_struct__ml *__pyx_cur_scope;
   int __pyx_v_n_roots;
   int __pyx_v_n_victims;
-  CYTHON_UNUSED int __pyx_v_n_nodes;
+  int __pyx_v_n_nodes;
   int __pyx_v_roots;
   int __pyx_v_i;
   int __pyx_v_dist;
@@ -1990,12 +1851,13 @@ static PyObject *__pyx_pf_2ml_ml(CYTHON_UNUSED PyObject *__pyx_self, PyObject *_
   PyArrayObject *__pyx_v_probs = 0;
   PyArrayObject *__pyx_v_probs_fail = 0;
   PyArrayObject *__pyx_v_probs_nv = 0;
-  PyArrayObject *__pyx_v_cums = 0;
+  PyObject *__pyx_v_max_i = NULL;
+  PyObject *__pyx_v_max_beta_add = NULL;
+  double __pyx_v_thresh;
+  PyObject *__pyx_v_beta_add = NULL;
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-  PyObject *__pyx_t_29 = NULL;
-  PyArrayObject *__pyx_t_30 = NULL;
-  int __pyx_t_31;
+  double __pyx_t_27;
+  long __pyx_t_28;
+  int __pyx_t_29;
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   const char *__pyx_filename = NULL;
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-  /* "ml.pyx":62
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-    {__pyx_filename = __pyx_f[0]; __pyx_lineno = 62; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
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-    {__pyx_filename = __pyx_f[0]; __pyx_lineno = 62; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
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+  __pyx_t_6 = __Pyx_GetModuleGlobalName(__pyx_n_s_DTYPE); if (unlikely(!__pyx_t_6)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 43; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
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+  if (!(likely(((__pyx_t_6) == Py_None) || likely(__Pyx_TypeTest(__pyx_t_6, __pyx_ptype_5numpy_ndarray))))) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 43; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
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-      {__pyx_filename = __pyx_f[0]; __pyx_lineno = 65; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
+      {__pyx_filename = __pyx_f[0]; __pyx_lineno = 43; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
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-  /* "ml.pyx":66
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  * 
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+  __pyx_t_6 = __Pyx_GetModuleGlobalName(__pyx_n_s_np); if (unlikely(!__pyx_t_6)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 44; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
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+  __pyx_t_3 = __Pyx_PyObject_GetAttrStr(__pyx_t_6, __pyx_n_s_zeros); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 44; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
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-      {__pyx_filename = __pyx_f[0]; __pyx_lineno = 66; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
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+  __pyx_t_3 = __Pyx_GetModuleGlobalName(__pyx_n_s_DTYPE); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 45; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
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-  if (PyDict_SetItem(__pyx_t_4, __pyx_n_s_dtype, __pyx_t_3) < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 67; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
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+  __pyx_t_3 = __Pyx_PyObject_Call(__pyx_t_6, __pyx_t_5, __pyx_t_4); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 45; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
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+  if (!(likely(((__pyx_t_3) == Py_None) || likely(__Pyx_TypeTest(__pyx_t_3, __pyx_ptype_5numpy_ndarray))))) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 45; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
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-      {__pyx_filename = __pyx_f[0]; __pyx_lineno = 67; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
+      {__pyx_filename = __pyx_f[0]; __pyx_lineno = 45; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
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   __pyx_v_probs_nv = ((PyArrayObject *)__pyx_t_3);
   __pyx_t_3 = 0;
 
-  /* "ml.pyx":70
+  /* "ml.pyx":48
  * 
  *     # loop through victims
  *     for i, parents in enumerate(victims.itervalues()):             # <<<<<<<<<<<<<<
@@ -2244,9 +2095,9 @@ static PyObject *__pyx_pf_2ml_ml(CYTHON_UNUSED PyObject *__pyx_self, PyObject *_
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     PyErr_Format(PyExc_AttributeError, "'NoneType' object has no attribute '%s'", "itervalues");
-    {__pyx_filename = __pyx_f[0]; __pyx_lineno = 70; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
+    {__pyx_filename = __pyx_f[0]; __pyx_lineno = 48; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
   }
-  __pyx_t_4 = __Pyx_dict_iterator(__pyx_v_victims, 1, __pyx_n_s_itervalues, (&__pyx_t_1), (&__pyx_t_11)); if (unlikely(!__pyx_t_4)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 70; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
+  __pyx_t_4 = __Pyx_dict_iterator(__pyx_v_victims, 1, __pyx_n_s_itervalues, (&__pyx_t_1), (&__pyx_t_11)); if (unlikely(!__pyx_t_4)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 48; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
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   __Pyx_XDECREF(__pyx_t_3);
   __pyx_t_3 = __pyx_t_4;
@@ -2254,25 +2105,25 @@ static PyObject *__pyx_pf_2ml_ml(CYTHON_UNUSED PyObject *__pyx_self, PyObject *_
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-    if (unlikely(__pyx_t_12 == -1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 70; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
+    if (unlikely(__pyx_t_12 == -1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 48; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
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-    if (!(likely(PyList_CheckExact(__pyx_t_4))||((__pyx_t_4) == Py_None)||(PyErr_Format(PyExc_TypeError, "Expected %.16s, got %.200s", "list", Py_TYPE(__pyx_t_4)->tp_name), 0))) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 70; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
+    if (!(likely(PyList_CheckExact(__pyx_t_4))||((__pyx_t_4) == Py_None)||(PyErr_Format(PyExc_TypeError, "Expected %.16s, got %.200s", "list", Py_TYPE(__pyx_t_4)->tp_name), 0))) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 48; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
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-    /* "ml.pyx":74
+    /* "ml.pyx":52
  *         # fail to infect it, also computes the probability that its most
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  *         failures = [weight_failure(dist, dt, alpha, delta, w1, w2, w3)             # <<<<<<<<<<<<<<
  *                     for (dist, dt, w1, w2, w3) in parents]
  *         probs_fail[i] = sum(failures)
  */
-    __pyx_t_4 = PyList_New(0); if (unlikely(!__pyx_t_4)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 74; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
+    __pyx_t_4 = PyList_New(0); if (unlikely(!__pyx_t_4)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 52; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
     __Pyx_GOTREF(__pyx_t_4);
 
-    /* "ml.pyx":75
+    /* "ml.pyx":53
  *         # likely parent infects it
  *         failures = [weight_failure(dist, dt, alpha, delta, w1, w2, w3)
  *                     for (dist, dt, w1, w2, w3) in parents]             # <<<<<<<<<<<<<<
@@ -2281,15 +2132,15 @@ static PyObject *__pyx_pf_2ml_ml(CYTHON_UNUSED PyObject *__pyx_self, PyObject *_
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     if (unlikely(__pyx_v_parents == Py_None)) {
       PyErr_SetString(PyExc_TypeError, "'NoneType' object is not iterable");
-      {__pyx_filename = __pyx_f[0]; __pyx_lineno = 75; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
+      {__pyx_filename = __pyx_f[0]; __pyx_lineno = 53; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
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+      __pyx_t_6 = PyList_GET_ITEM(__pyx_t_5, __pyx_t_13); __Pyx_INCREF(__pyx_t_6); __pyx_t_13++; if (unlikely(0 < 0)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 53; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
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-      __pyx_t_6 = PySequence_ITEM(__pyx_t_5, __pyx_t_13); __pyx_t_13++; if (unlikely(!__pyx_t_6)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 75; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
+      __pyx_t_6 = PySequence_ITEM(__pyx_t_5, __pyx_t_13); __pyx_t_13++; if (unlikely(!__pyx_t_6)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 53; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
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@@ -2301,7 +2152,7 @@ static PyObject *__pyx_pf_2ml_ml(CYTHON_UNUSED PyObject *__pyx_self, PyObject *_
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-          {__pyx_filename = __pyx_f[0]; __pyx_lineno = 75; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
+          {__pyx_filename = __pyx_f[0]; __pyx_lineno = 53; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
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@@ -2327,7 +2178,7 @@ static PyObject *__pyx_pf_2ml_ml(CYTHON_UNUSED PyObject *__pyx_self, PyObject *_
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           for (i=0; i < 5; i++) {
-            PyObject* item = PySequence_ITEM(sequence, i); if (unlikely(!item)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 75; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
+            PyObject* item = PySequence_ITEM(sequence, i); if (unlikely(!item)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 53; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
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@@ -2337,7 +2188,7 @@ static PyObject *__pyx_pf_2ml_ml(CYTHON_UNUSED PyObject *__pyx_self, PyObject *_
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-        __pyx_t_19 = PyObject_GetIter(__pyx_t_6); if (unlikely(!__pyx_t_19)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 75; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
+        __pyx_t_19 = PyObject_GetIter(__pyx_t_6); if (unlikely(!__pyx_t_19)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 53; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
         __Pyx_GOTREF(__pyx_t_19);
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@@ -2346,7 +2197,7 @@ static PyObject *__pyx_pf_2ml_ml(CYTHON_UNUSED PyObject *__pyx_self, PyObject *_
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-        if (__Pyx_IternextUnpackEndCheck(__pyx_t_20(__pyx_t_19), 5) < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 75; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
+        if (__Pyx_IternextUnpackEndCheck(__pyx_t_20(__pyx_t_19), 5) < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 53; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
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@@ -2354,12 +2205,12 @@ static PyObject *__pyx_pf_2ml_ml(CYTHON_UNUSED PyObject *__pyx_self, PyObject *_
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-        {__pyx_filename = __pyx_f[0]; __pyx_lineno = 75; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
+        {__pyx_filename = __pyx_f[0]; __pyx_lineno = 53; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
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+      __pyx_t_12 = __Pyx_PyInt_As_int(__pyx_t_14); if (unlikely((__pyx_t_12 == (int)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 53; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
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+      __pyx_t_21 = __Pyx_PyInt_As_int(__pyx_t_15); if (unlikely((__pyx_t_21 == (int)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 53; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
       __Pyx_DECREF(__pyx_t_15); __pyx_t_15 = 0;
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       __pyx_v_dt = __pyx_t_21;
@@ -2370,22 +2221,22 @@ static PyObject *__pyx_pf_2ml_ml(CYTHON_UNUSED PyObject *__pyx_self, PyObject *_
       __Pyx_XDECREF_SET(__pyx_v_w3, __pyx_t_18);
       __pyx_t_18 = 0;
 
-      /* "ml.pyx":74
+      /* "ml.pyx":52
  *         # fail to infect it, also computes the probability that its most
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-      __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 = 74; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
-      __pyx_t_24 = __pyx_PyFloat_AsDouble(__pyx_v_w3); if (unlikely((__pyx_t_24 == (npy_double)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 74; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
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+      __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 = 52; __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 = 52; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
+      __pyx_t_24 = __pyx_PyFloat_AsDouble(__pyx_v_w3); if (unlikely((__pyx_t_24 == (npy_double)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 52; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
+      __pyx_t_6 = PyFloat_FromDouble(__pyx_f_2ml_weight_failure(__pyx_v_dist, __pyx_v_dt, __pyx_v_alpha, __pyx_v_delta, __pyx_t_22, __pyx_t_23, __pyx_t_24)); if (unlikely(!__pyx_t_6)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 52; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
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-      if (unlikely(__Pyx_ListComp_Append(__pyx_t_4, (PyObject*)__pyx_t_6))) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 74; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
+      if (unlikely(__Pyx_ListComp_Append(__pyx_t_4, (PyObject*)__pyx_t_6))) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 52; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
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-      /* "ml.pyx":75
+      /* "ml.pyx":53
  *         # likely parent infects it
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@@ -2399,38 +2250,38 @@ static PyObject *__pyx_pf_2ml_ml(CYTHON_UNUSED PyObject *__pyx_self, PyObject *_
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-    /* "ml.pyx":76
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+    __pyx_t_4 = PyTuple_New(1); if (unlikely(!__pyx_t_4)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 54; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
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+    __pyx_t_5 = PyList_New(0); if (unlikely(!__pyx_t_5)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 55; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
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-    /* "ml.pyx":78
+    /* "ml.pyx":56
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@@ -2439,15 +2290,15 @@ static PyObject *__pyx_pf_2ml_ml(CYTHON_UNUSED PyObject *__pyx_self, PyObject *_
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-      {__pyx_filename = __pyx_f[0]; __pyx_lineno = 78; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
+      {__pyx_filename = __pyx_f[0]; __pyx_lineno = 56; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
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+      __pyx_t_6 = PyList_GET_ITEM(__pyx_t_4, __pyx_t_13); __Pyx_INCREF(__pyx_t_6); __pyx_t_13++; if (unlikely(0 < 0)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 56; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
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+      __pyx_t_6 = PySequence_ITEM(__pyx_t_4, __pyx_t_13); __pyx_t_13++; if (unlikely(!__pyx_t_6)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 56; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
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-          {__pyx_filename = __pyx_f[0]; __pyx_lineno = 78; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
+          {__pyx_filename = __pyx_f[0]; __pyx_lineno = 56; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
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@@ -2485,7 +2336,7 @@ static PyObject *__pyx_pf_2ml_ml(CYTHON_UNUSED PyObject *__pyx_self, PyObject *_
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+            PyObject* item = PySequence_ITEM(sequence, i); if (unlikely(!item)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 56; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
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@@ -2495,7 +2346,7 @@ static PyObject *__pyx_pf_2ml_ml(CYTHON_UNUSED PyObject *__pyx_self, PyObject *_
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+        __pyx_t_19 = PyObject_GetIter(__pyx_t_6); if (unlikely(!__pyx_t_19)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 56; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
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@@ -2504,7 +2355,7 @@ static PyObject *__pyx_pf_2ml_ml(CYTHON_UNUSED PyObject *__pyx_self, PyObject *_
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+        if (__Pyx_IternextUnpackEndCheck(__pyx_t_20(__pyx_t_19), 5) < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 56; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
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-        {__pyx_filename = __pyx_f[0]; __pyx_lineno = 78; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
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+      __pyx_t_12 = __Pyx_PyInt_As_int(__pyx_t_18); if (unlikely((__pyx_t_12 == (int)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 56; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
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@@ -2528,22 +2379,22 @@ static PyObject *__pyx_pf_2ml_ml(CYTHON_UNUSED PyObject *__pyx_self, PyObject *_
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-      /* "ml.pyx":77
+      /* "ml.pyx":55
  *                     for (dist, dt, w1, w2, w3) in parents]
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-      __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 = 77; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
-      __pyx_t_22 = __pyx_PyFloat_AsDouble(__pyx_v_w3); if (unlikely((__pyx_t_22 == (npy_double)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 77; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
-      __pyx_t_6 = PyFloat_FromDouble(__pyx_f_2ml_weight_success(__pyx_v_dist, __pyx_v_dt, __pyx_v_alpha, __pyx_v_delta, __pyx_t_24, __pyx_t_23, __pyx_t_22)); if (unlikely(!__pyx_t_6)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 77; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
+      __pyx_t_24 = __pyx_PyFloat_AsDouble(__pyx_v_w1); if (unlikely((__pyx_t_24 == (npy_double)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 55; __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 = 55; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
+      __pyx_t_22 = __pyx_PyFloat_AsDouble(__pyx_v_w3); if (unlikely((__pyx_t_22 == (npy_double)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 55; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
+      __pyx_t_6 = PyFloat_FromDouble(__pyx_f_2ml_weight_success(__pyx_v_dist, __pyx_v_dt, __pyx_v_alpha, __pyx_v_delta, __pyx_t_24, __pyx_t_23, __pyx_t_22)); if (unlikely(!__pyx_t_6)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 55; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
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-      if (unlikely(__Pyx_ListComp_Append(__pyx_t_5, (PyObject*)__pyx_t_6))) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 77; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
+      if (unlikely(__Pyx_ListComp_Append(__pyx_t_5, (PyObject*)__pyx_t_6))) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 55; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
       __Pyx_DECREF(__pyx_t_6); __pyx_t_6 = 0;
 
-      /* "ml.pyx":78
+      /* "ml.pyx":56
  *         probs_fail[i] = sum(failures)
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@@ -2557,24 +2408,24 @@ static PyObject *__pyx_pf_2ml_ml(CYTHON_UNUSED PyObject *__pyx_self, PyObject *_
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-    /* "ml.pyx":80
+    /* "ml.pyx":58
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+    __pyx_t_5 = __pyx_pf_2ml_2ml_genexpr(((PyObject*)__pyx_cur_scope)); 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_t_4 = PyTuple_New(1); if (unlikely(!__pyx_t_4)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 58; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
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+    __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_t_22 = __pyx_PyFloat_AsDouble(__pyx_t_5); if (unlikely((__pyx_t_22 == (npy_double)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 58; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
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@@ -2582,7 +2433,7 @@ static PyObject *__pyx_pf_2ml_ml(CYTHON_UNUSED PyObject *__pyx_self, PyObject *_
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-  /* "ml.pyx":83
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-    {__pyx_filename = __pyx_f[0]; __pyx_lineno = 83; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
+    {__pyx_filename = __pyx_f[0]; __pyx_lineno = 61; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
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+  __pyx_t_5 = __Pyx_dict_iterator(__pyx_v_non_victims, 1, __pyx_n_s_itervalues, (&__pyx_t_2), (&__pyx_t_11)); if (unlikely(!__pyx_t_5)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 61; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
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@@ -2603,25 +2454,25 @@ static PyObject *__pyx_pf_2ml_ml(CYTHON_UNUSED PyObject *__pyx_self, PyObject *_
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+    if (!(likely(PyList_CheckExact(__pyx_t_5))||((__pyx_t_5) == Py_None)||(PyErr_Format(PyExc_TypeError, "Expected %.16s, got %.200s", "list", Py_TYPE(__pyx_t_5)->tp_name), 0))) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 61; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
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-      {__pyx_filename = __pyx_f[0]; __pyx_lineno = 87; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
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-    } else {__pyx_pybuffernd_cums.diminfo[0].strides = __pyx_pybuffernd_cums.rcbuffer->pybuffer.strides[0]; __pyx_pybuffernd_cums.diminfo[0].shape = __pyx_pybuffernd_cums.rcbuffer->pybuffer.shape[0];
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-  }
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-  __pyx_v_cums = ((PyArrayObject *)__pyx_t_3);
-  __pyx_t_3 = 0;
-
-  /* "ml.pyx":94
- *     cdef:
- *         np.ndarray[DTYPE_t] cums = probs.cumsum()
- *     ll =  probs_fail.sum()             # <<<<<<<<<<<<<<
- *     ll += probs_nv.sum()
+  /* "ml.pyx":72
+ *     # 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
  * 
  */
-  __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 = 94; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
+  __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 = 72; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
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@@ -2884,27 +2642,27 @@ static PyObject *__pyx_pf_2ml_ml(CYTHON_UNUSED PyObject *__pyx_self, PyObject *_
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   }
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+    __pyx_t_3 = __Pyx_PyObject_CallNoArg(__pyx_t_4); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 72; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
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+  __pyx_t_24 = __pyx_PyFloat_AsDouble(__pyx_t_3); if (unlikely((__pyx_t_24 == (npy_double)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 72; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
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- *         np.ndarray[DTYPE_t] cums = probs.cumsum()
- *     ll =  probs_fail.sum()
- *     ll += probs_nv.sum()             # <<<<<<<<<<<<<<
+  /* "ml.pyx":73
+ *     #     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             # <<<<<<<<<<<<<<
  * 
- *     for i in xrange(n_victims - 1, 0, -1):
+ *     max_i = -1
  */
-  __pyx_t_3 = PyFloat_FromDouble(__pyx_v_ll); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 95; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
+  __pyx_t_3 = PyFloat_FromDouble(__pyx_v_ll); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 73; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
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+  __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 = 73; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
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@@ -2917,261 +2675,233 @@ static PyObject *__pyx_pf_2ml_ml(CYTHON_UNUSED PyObject *__pyx_self, PyObject *_
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+  __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 = 73; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
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-  /* "ml.pyx":97
- *     ll += probs_nv.sum()
+  /* "ml.pyx":75
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  * 
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- *         # iterate over all victim nodes to find the optimal threshold
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+ *     max_i = -1             # <<<<<<<<<<<<<<
+ *     max_beta_add = float('-inf')
+ *     # iterate over all victim nodes to find the optimal threshold
  */
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-    __pyx_v_i = __pyx_t_10;
+  __Pyx_INCREF(__pyx_int_neg_1);
+  __pyx_v_max_i = __pyx_int_neg_1;
 
-    /* "ml.pyx":99
- *     for i in xrange(n_victims - 1, 0, -1):
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- *         beta = 1. / (1. + exp(-probs[i]))#exp(probs[i])#
- *         if beta > float(roots) / age:
+  /* "ml.pyx":76
+ * 
+ *     max_i = -1
+ *     max_beta_add = float('-inf')             # <<<<<<<<<<<<<<
+ *     # iterate over all victim nodes to find the optimal threshold
+ *     for i in xrange(0, n_victims+1, 1):
  */
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+  __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 = 76; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
+  __pyx_t_5 = PyFloat_FromDouble(__pyx_t_27); if (unlikely(!__pyx_t_5)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 76; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
+  __Pyx_GOTREF(__pyx_t_5);
+  __pyx_v_max_beta_add = __pyx_t_5;
+  __pyx_t_5 = 0;
 
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- *         if beta > float(roots) / age:
- *             break
+  /* "ml.pyx":78
+ *     max_beta_add = float('-inf')
+ *     # iterate over all victim nodes to find the optimal threshold
+ *     for i in xrange(0, n_victims+1, 1):             # <<<<<<<<<<<<<<
+ *         roots = n_roots + n_victims - i
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  */
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+  __pyx_t_28 = (__pyx_v_n_victims + 1);
+  for (__pyx_t_10 = 0; __pyx_t_10 < __pyx_t_28; __pyx_t_10+=1) {
+    __pyx_v_i = __pyx_t_10;
 
-    /* "ml.pyx":101
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- *         if beta > float(roots) / age:             # <<<<<<<<<<<<<<
- *             break
- *     else:
+    /* "ml.pyx":79
+ *     # iterate over all victim nodes to find the optimal threshold
+ *     for i in xrange(0, n_victims+1, 1):
+ *         roots = n_roots + n_victims - i             # <<<<<<<<<<<<<<
+ *         beta = float(roots)/float(n_nodes)
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  */
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- *             break             # <<<<<<<<<<<<<<
- *     else:
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+    /* "ml.pyx":80
+ *     for i in xrange(0, n_victims+1, 1):
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+ * 
  */
-      goto __pyx_L20_break;
-    }
-  }
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- *         roots = n_victims + n_roots
- *         i = -1
+    /* "ml.pyx":81
+ *         roots = n_roots + n_victims - i
+ *         beta = float(roots)/float(n_nodes)
+ *         thresh = log(beta/(1.-beta))             # <<<<<<<<<<<<<<
+ * 
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+ */
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+    /* "ml.pyx":84
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+ *         beta_add = (probs[probs>thresh]).sum()             # <<<<<<<<<<<<<<
+ *         # add probability for the seeds and non-seeds
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- *         i = -1
- *     beta = float(roots) / age
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- *         roots = n_victims + n_roots
- *         i = -1             # <<<<<<<<<<<<<<
- *     beta = float(roots) / age
- *     for i in xrange(n_victims - 1, 0, -1):
- */
-    __pyx_v_i = -1;
-  }
-  __pyx_L20_break:;
+    __Pyx_DECREF(__pyx_t_3); __pyx_t_3 = 0;
+    __Pyx_XDECREF_SET(__pyx_v_beta_add, __pyx_t_5);
+    __pyx_t_5 = 0;
 
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- *         i = -1
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- *     for i in xrange(n_victims - 1, 0, -1):
- *         if probs[i] >= log(beta/(1.- beta)):
+    /* "ml.pyx":86
+ *         beta_add = (probs[probs>thresh]).sum()
+ *         # add probability for the seeds and non-seeds
+ *         beta_add += roots * log(beta) + (n_nodes-roots) * log(1 - beta)             # <<<<<<<<<<<<<<
+ * 
+ *         if beta_add > max_beta_add:
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   {&__pyx_n_s_import, __pyx_k_import, sizeof(__pyx_k_import), 0, 0, 1, 1},
+  {&__pyx_kp_s_inf, __pyx_k_inf, sizeof(__pyx_k_inf), 0, 0, 1, 0},
   {&__pyx_n_s_itervalues, __pyx_k_itervalues, sizeof(__pyx_k_itervalues), 0, 0, 1, 1},
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   {&__pyx_n_s_main, __pyx_k_main, sizeof(__pyx_k_main), 0, 0, 1, 1},
   {&__pyx_n_s_max, __pyx_k_max, sizeof(__pyx_k_max), 0, 0, 1, 1},
+  {&__pyx_n_s_max_beta_add, __pyx_k_max_beta_add, sizeof(__pyx_k_max_beta_add), 0, 0, 1, 1},
+  {&__pyx_n_s_max_i, __pyx_k_max_i, sizeof(__pyx_k_max_i), 0, 0, 1, 1},
   {&__pyx_n_s_ml, __pyx_k_ml, sizeof(__pyx_k_ml), 0, 0, 1, 1},
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   {&__pyx_n_s_parents, __pyx_k_parents, sizeof(__pyx_k_parents), 0, 0, 1, 1},
-  {&__pyx_n_s_print, __pyx_k_print, sizeof(__pyx_k_print), 0, 0, 1, 1},
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   {&__pyx_n_s_send, __pyx_k_send, sizeof(__pyx_k_send), 0, 0, 1, 1},
-  {&__pyx_n_s_sort, __pyx_k_sort, sizeof(__pyx_k_sort), 0, 0, 1, 1},
   {&__pyx_n_s_successes, __pyx_k_successes, sizeof(__pyx_k_successes), 0, 0, 1, 1},
   {&__pyx_n_s_sum, __pyx_k_sum, sizeof(__pyx_k_sum), 0, 0, 1, 1},
   {&__pyx_n_s_t, __pyx_k_t, sizeof(__pyx_k_t), 0, 0, 1, 1},
   {&__pyx_n_s_test, __pyx_k_test, sizeof(__pyx_k_test), 0, 0, 1, 1},
+  {&__pyx_n_s_thresh, __pyx_k_thresh, sizeof(__pyx_k_thresh), 0, 0, 1, 1},
   {&__pyx_n_s_throw, __pyx_k_throw, sizeof(__pyx_k_throw), 0, 0, 1, 1},
   {&__pyx_kp_u_unknown_dtype_code_in_numpy_pxd, __pyx_k_unknown_dtype_code_in_numpy_pxd, sizeof(__pyx_k_unknown_dtype_code_in_numpy_pxd), 0, 1, 0, 0},
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 };
 static int __Pyx_InitCachedBuiltins(void) {
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-  __pyx_builtin_sum = __Pyx_GetBuiltinName(__pyx_n_s_sum); if (!__pyx_builtin_sum) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 76; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
-  __pyx_builtin_max = __Pyx_GetBuiltinName(__pyx_n_s_max); if (!__pyx_builtin_max) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 80; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
+  __pyx_builtin_enumerate = __Pyx_GetBuiltinName(__pyx_n_s_enumerate); if (!__pyx_builtin_enumerate) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 48; __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 = 54; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
+  __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;}
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+  __pyx_builtin_xrange = __Pyx_GetBuiltinName(__pyx_n_s_range); if (!__pyx_builtin_xrange) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 78; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
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-  __pyx_builtin_xrange = __Pyx_GetBuiltinName(__pyx_n_s_xrange); if (!__pyx_builtin_xrange) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 97; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
+  __pyx_builtin_xrange = __Pyx_GetBuiltinName(__pyx_n_s_xrange); if (!__pyx_builtin_xrange) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 78; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
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-  __Pyx_GIVEREF(__pyx_slice_);
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-  __Pyx_GOTREF(__pyx_tuple__2);
-  __Pyx_GIVEREF(__pyx_tuple__2);
+  __pyx_tuple_ = PyTuple_Pack(1, __pyx_kp_u_ndarray_is_not_C_contiguous); if (unlikely(!__pyx_tuple_)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 218; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
+  __Pyx_GOTREF(__pyx_tuple_);
+  __Pyx_GIVEREF(__pyx_tuple_);
 
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-  __Pyx_GOTREF(__pyx_tuple__3);
-  __Pyx_GIVEREF(__pyx_tuple__3);
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-  __Pyx_GOTREF(__pyx_tuple__4);
-  __Pyx_GIVEREF(__pyx_tuple__4);
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-  __Pyx_GOTREF(__pyx_tuple__5);
-  __Pyx_GIVEREF(__pyx_tuple__5);
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@@ -5624,9 +5340,9 @@ static int __Pyx_InitCachedConstants(void) {
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-  __Pyx_GOTREF(__pyx_tuple__6);
-  __Pyx_GIVEREF(__pyx_tuple__6);
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+  __Pyx_GIVEREF(__pyx_tuple__5);
 
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-  __Pyx_GIVEREF(__pyx_tuple__7);
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-  /* "ml.pyx":56
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+  __pyx_tuple__7 = PyTuple_Pack(33, __pyx_n_s_root_victims, __pyx_n_s_victims, __pyx_n_s_non_victims, __pyx_n_s_age, __pyx_n_s_alpha, __pyx_n_s_delta, __pyx_n_s_n_roots, __pyx_n_s_n_victims, __pyx_n_s_n_nodes, __pyx_n_s_roots, __pyx_n_s_i, __pyx_n_s_dist, __pyx_n_s_dt, __pyx_n_s_t, __pyx_n_s_l, __pyx_n_s_beta, __pyx_n_s_ll, __pyx_n_s_beta2, __pyx_n_s_parents, __pyx_n_s_failures, __pyx_n_s_successes, __pyx_n_s_probs, __pyx_n_s_probs_fail, __pyx_n_s_probs_nv, __pyx_n_s_max_i, __pyx_n_s_max_beta_add, __pyx_n_s_thresh, __pyx_n_s_beta_add, __pyx_n_s_w1, __pyx_n_s_w2, __pyx_n_s_w3, __pyx_n_s_genexpr, __pyx_n_s_genexpr); if (unlikely(!__pyx_tuple__7)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 34; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
+  __Pyx_GOTREF(__pyx_tuple__7);
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+  __pyx_codeobj__8 = (PyObject*)__Pyx_PyCode_New(6, 0, 33, 0, 0, __pyx_empty_bytes, __pyx_empty_tuple, __pyx_empty_tuple, __pyx_tuple__7, __pyx_empty_tuple, __pyx_empty_tuple, __pyx_kp_s_Users_ben_Documents_Cascade_Pro, __pyx_n_s_ml, 34, __pyx_empty_bytes); if (unlikely(!__pyx_codeobj__8)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 34; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
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@@ -5746,10 +5462,10 @@ PyMODINIT_FUNC PyInit_ml(void)
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   /*--- Function export code ---*/
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+  if (PyType_Ready(&__pyx_type_2ml___pyx_scope_struct__ml) < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 34; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
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@@ -5795,16 +5511,16 @@ PyMODINIT_FUNC PyInit_ml(void)
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-  /* "ml.pyx":56
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  *     cdef:
  */
-  __pyx_t_2 = PyCFunction_NewEx(&__pyx_mdef_2ml_1ml, NULL, __pyx_n_s_ml); if (unlikely(!__pyx_t_2)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 56; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
+  __pyx_t_2 = PyCFunction_NewEx(&__pyx_mdef_2ml_1ml, NULL, __pyx_n_s_ml); if (unlikely(!__pyx_t_2)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 34; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
   __Pyx_GOTREF(__pyx_t_2);
-  if (PyDict_SetItem(__pyx_d, __pyx_n_s_ml, __pyx_t_2) < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 56; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
+  if (PyDict_SetItem(__pyx_d, __pyx_n_s_ml, __pyx_t_2) < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 34; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
   __Pyx_DECREF(__pyx_t_2); __pyx_t_2 = 0;
 
   /* "ml.pyx":1
@@ -7017,9 +6733,43 @@ static CYTHON_INLINE int __Pyx_dict_iter_next(PyObject* iter_obj, Py_ssize_t ori
     return 1;
 }
 
-static void __Pyx_RaiseBufferFallbackError(void) {
-  PyErr_SetString(PyExc_ValueError,
-     "Buffer acquisition failed on assignment; and then reacquiring the old buffer failed too!");
+static double __Pyx__PyObject_AsDouble(PyObject* obj) {
+    PyObject* float_value;
+#if CYTHON_COMPILING_IN_PYPY
+    float_value = PyNumber_Float(obj);
+#else
+    PyNumberMethods *nb = Py_TYPE(obj)->tp_as_number;
+    if (likely(nb) && likely(nb->nb_float)) {
+        float_value = nb->nb_float(obj);
+        if (likely(float_value) && unlikely(!PyFloat_Check(float_value))) {
+            PyErr_Format(PyExc_TypeError,
+                "__float__ returned non-float (type %.200s)",
+                Py_TYPE(float_value)->tp_name);
+            Py_DECREF(float_value);
+            goto bad;
+        }
+    } else if (PyUnicode_CheckExact(obj) || PyBytes_CheckExact(obj)) {
+#if PY_MAJOR_VERSION >= 3
+        float_value = PyFloat_FromString(obj);
+#else
+        float_value = PyFloat_FromString(obj, 0);
+#endif
+    } else {
+        PyObject* args = PyTuple_New(1);
+        if (unlikely(!args)) goto bad;
+        PyTuple_SET_ITEM(args, 0, obj);
+        float_value = PyObject_Call((PyObject*)&PyFloat_Type, args, 0);
+        PyTuple_SET_ITEM(args, 0, 0);
+        Py_DECREF(args);
+    }
+#endif
+    if (likely(float_value)) {
+        double value = PyFloat_AS_DOUBLE(float_value);
+        Py_DECREF(float_value);
+        return value;
+    }
+bad:
+    return (double)-1;
 }
 
 static CYTHON_INLINE void __Pyx_ErrRestore(PyObject *type, PyObject *value, PyObject *tb) {
@@ -7631,147 +7381,6 @@ static CYTHON_INLINE PyObject* __Pyx_PyInt_From_long(long value) {
     }
 }
 
-#if !CYTHON_COMPILING_IN_PYPY && PY_MAJOR_VERSION < 3
-static PyObject *__Pyx_GetStdout(void) {
-    PyObject *f = PySys_GetObject((char *)"stdout");
-    if (!f) {
-        PyErr_SetString(PyExc_RuntimeError, "lost sys.stdout");
-    }
-    return f;
-}
-static int __Pyx_Print(PyObject* f, PyObject *arg_tuple, int newline) {
-    int i;
-    if (!f) {
-        if (!(f = __Pyx_GetStdout()))
-            return -1;
-    }
-    Py_INCREF(f);
-    for (i=0; i < PyTuple_GET_SIZE(arg_tuple); i++) {
-        PyObject* v;
-        if (PyFile_SoftSpace(f, 1)) {
-            if (PyFile_WriteString(" ", f) < 0)
-                goto error;
-        }
-        v = PyTuple_GET_ITEM(arg_tuple, i);
-        if (PyFile_WriteObject(v, f, Py_PRINT_RAW) < 0)
-            goto error;
-        if (PyString_Check(v)) {
-            char *s = PyString_AsString(v);
-            Py_ssize_t len = PyString_Size(v);
-            if (len > 0) {
-                switch (s[len-1]) {
-                    case ' ': break;
-                    case '\f': case '\r': case '\n': case '\t': case '\v':
-                        PyFile_SoftSpace(f, 0);
-                        break;
-                    default:  break;
-                }
-            }
-        }
-    }
-    if (newline) {
-        if (PyFile_WriteString("\n", f) < 0)
-            goto error;
-        PyFile_SoftSpace(f, 0);
-    }
-    Py_DECREF(f);
-    return 0;
-error:
-    Py_DECREF(f);
-    return -1;
-}
-#else
-static int __Pyx_Print(PyObject* stream, PyObject *arg_tuple, int newline) {
-    PyObject* kwargs = 0;
-    PyObject* result = 0;
-    PyObject* end_string;
-    if (unlikely(!__pyx_print)) {
-        __pyx_print = PyObject_GetAttr(__pyx_b, __pyx_n_s_print);
-        if (!__pyx_print)
-            return -1;
-    }
-    if (stream) {
-        kwargs = PyDict_New();
-        if (unlikely(!kwargs))
-            return -1;
-        if (unlikely(PyDict_SetItem(kwargs, __pyx_n_s_file, stream) < 0))
-            goto bad;
-        if (!newline) {
-            end_string = PyUnicode_FromStringAndSize(" ", 1);
-            if (unlikely(!end_string))
-                goto bad;
-            if (PyDict_SetItem(kwargs, __pyx_n_s_end, end_string) < 0) {
-                Py_DECREF(end_string);
-                goto bad;
-            }
-            Py_DECREF(end_string);
-        }
-    } else if (!newline) {
-        if (unlikely(!__pyx_print_kwargs)) {
-            __pyx_print_kwargs = PyDict_New();
-            if (unlikely(!__pyx_print_kwargs))
-                return -1;
-            end_string = PyUnicode_FromStringAndSize(" ", 1);
-            if (unlikely(!end_string))
-                return -1;
-            if (PyDict_SetItem(__pyx_print_kwargs, __pyx_n_s_end, end_string) < 0) {
-                Py_DECREF(end_string);
-                return -1;
-            }
-            Py_DECREF(end_string);
-        }
-        kwargs = __pyx_print_kwargs;
-    }
-    result = PyObject_Call(__pyx_print, arg_tuple, kwargs);
-    if (unlikely(kwargs) && (kwargs != __pyx_print_kwargs))
-        Py_DECREF(kwargs);
-    if (!result)
-        return -1;
-    Py_DECREF(result);
-    return 0;
-bad:
-    if (kwargs != __pyx_print_kwargs)
-        Py_XDECREF(kwargs);
-    return -1;
-}
-#endif
-
-#if !CYTHON_COMPILING_IN_PYPY && PY_MAJOR_VERSION < 3
-static int __Pyx_PrintOne(PyObject* f, PyObject *o) {
-    if (!f) {
-        if (!(f = __Pyx_GetStdout()))
-            return -1;
-    }
-    Py_INCREF(f);
-    if (PyFile_SoftSpace(f, 0)) {
-        if (PyFile_WriteString(" ", f) < 0)
-            goto error;
-    }
-    if (PyFile_WriteObject(o, f, Py_PRINT_RAW) < 0)
-        goto error;
-    if (PyFile_WriteString("\n", f) < 0)
-        goto error;
-    Py_DECREF(f);
-    return 0;
-error:
-    Py_DECREF(f);
-    return -1;
-    /* the line below is just to avoid C compiler
-     * warnings about unused functions */
-    return __Pyx_Print(f, NULL, 0);
-}
-#else
-static int __Pyx_PrintOne(PyObject* stream, PyObject *o) {
-    int res;
-    PyObject* arg_tuple = PyTuple_Pack(1, o);
-    if (unlikely(!arg_tuple))
-        return -1;
-    res = __Pyx_Print(stream, arg_tuple, 1);
-    Py_DECREF(arg_tuple);
-    return res;
-}
-#endif
-
 #if CYTHON_CCOMPLEX
   #ifdef __cplusplus
     static CYTHON_INLINE __pyx_t_float_complex __pyx_t_float_complex_from_parts(float x, float y) {
diff --git a/experiments/ml.pyx b/experiments/ml.pyx
index 9a786db..8dfea70 100644
--- a/experiments/ml.pyx
+++ b/experiments/ml.pyx
@@ -13,43 +13,21 @@ 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) * (1 - exp(-alpha))
-    result = log(structural * temporal)
+    temporal = log(alpha) - alpha * dt
+    # temporal = 1. / (1. + (dt - 1.)/alpha)**0.01 - 1. / (1. + dt/alpha)**0.01
+    result = structural + temporal
     return result
 
-
-cdef DTYPE_t weight_success_power(int dist, int dt, DTYPE_t alpha, DTYPE_t delta,
-                                DTYPE_t w1, DTYPE_t w2, DTYPE_t w3):
-    """weight for successful infection, power-law time model"""
-    cdef DTYPE_t structural, temporal, result
-    structural = delta ** (dist)
-    # structural = plogis(w1,delta) * plogis(w2,delta) * plogis(w3,delta)
-    temporal = 1. / (1. + (dt - 1.)/alpha)**0.01 - 1. / (1. + dt/alpha)**0.01
-    result = log(structural * temporal)
-    return result
-
-
 cdef DTYPE_t weight_failure(int dist, int dt, DTYPE_t alpha, DTYPE_t delta,
                             DTYPE_t w1, DTYPE_t w2, DTYPE_t w3):
     """weight for failed infection, exponential time model"""
     cdef DTYPE_t structural, temporal, result
-    structural = delta ** (dist)
+    structural = delta ** dist
     # structural = plogis(w1,delta) * plogis(w2,delta) * plogis(w3,delta)
     temporal = 1. - exp(-alpha * dt)
-    #result = log(1. - structural)
-    result = log(1. - structural * temporal)
-    return result
-
-
-cdef DTYPE_t weight_failure_power(int dist, int dt, DTYPE_t alpha, DTYPE_t delta,
-                                DTYPE_t w1, DTYPE_t w2, DTYPE_t w3):
-    """weight for failed infection, power-law time model"""
-    cdef DTYPE_t structural, temporal, result
-    structural = delta ** (dist)
-    # structural = plogis(w1,delta) * plogis(w2,delta) * plogis(w3,delta)
-    temporal = 1.  - 1. / (1. + dt/alpha)**0.01
+    # temporal = 1.  - 1. / (1. + dt/alpha)**0.01
     result = log(1. - structural * temporal)
     return result
 
@@ -60,7 +38,7 @@ def ml(dict root_victims, dict victims, dict non_victims, DTYPE_t age,
         DTYPE_t beta, ll, beta2
         list parents, failures, successes
     n_roots, n_victims = len(root_victims), len(victims)
-    n_nodes = n_roots + n_victims + len(non_victims)
+    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)
@@ -88,29 +66,31 @@ def ml(dict root_victims, dict victims, dict non_victims, DTYPE_t age,
         probs_nv[i] = sum(failures)
 
     # calculate log likelihood
-    probs.sort(); probs = probs[::-1] # sort probs in descending order
-    cdef:
-        np.ndarray[DTYPE_t] cums = probs.cumsum()
-    ll =  probs_fail.sum()
-    ll += probs_nv.sum()
+    # probs.sort(); probs = probs[::-1] # sort probs in descending order
+    # 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
+
+    max_i = -1
+    max_beta_add = float('-inf')
+    # iterate over all victim nodes to find the optimal threshold
+    for i in xrange(0, n_victims+1, 1):
+        roots = n_roots + n_victims - i
+        beta = float(roots)/float(n_nodes)
+        thresh = log(beta/(1.-beta))
+
+        # add probability for realized edges and subtract probability these edges fail
+        beta_add = (probs[probs>thresh]).sum()
+        print len(probs[probs>thresh])
+        # add probability for the seeds and non-seeds
+        beta_add += roots * log(beta) + (n_nodes-roots) * log(1 - beta)
+
+        if beta_add > max_beta_add:
+            max_i = i
+            max_beta_add = beta_add
 
-    for i in xrange(n_victims - 1, 0, -1):
-        # iterate over all victim nodes to find the optimal threshold
-        roots = n_roots + n_victims - 1 - i
-        beta = 1. / (1. + exp(-probs[i]))#exp(probs[i])#
-        if beta > float(roots) / age:
-            break
-    else:
-        print "alpha: {0}, delta: {1}. Everyone is a root".format(alpha, delta)
-        roots = n_victims + n_roots
-        i = -1
-    beta = float(roots) / age
-    for i in xrange(n_victims - 1, 0, -1):
-        if probs[i] >= log(beta/(1.- beta)):
-            break
-    ll += age * log(1 - beta)
-    if i >= 0:
-        ll += cums[i]
-    if roots > 0:
-        ll += roots * log(beta) - roots * log(1 - beta)
+    ll += max_beta_add
+    roots = n_roots + n_victims - max_i
+    # print n_nodes, n_roots, n_victims, max_i, roots
     return (beta, roots, ll)
diff --git a/experiments/ml.so b/experiments/ml.so
index 6708b62..687e6fc 100755
--- a/experiments/ml.so
+++ b/experiments/ml.so
diff --git a/experiments/out.log b/experiments/out.log
index 21d7647..7651bb5 100644
--- a/experiments/out.log
+++ b/experiments/out.log
@@ -1,100 +1,50 @@
-1.0	0.01	0.000699524364831	11152	-93563.2077417
-1.0	0.11	0.000687104545585	10954	-126108.954721
-1.0	0.21	0.000637864353118	10169	-225778.622068
-1.0	0.31	0.000615784674457	9817	-438982.304589
-1.0	0.41	0.000594645891194	9480	-820866.792264
-0.0196078431373	0.01	0.000701217976547	11179	-93581.7583087
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-0.0196078431373	0.31	0.0002813904502	4486	-432882.181737
-0.0196078431373	0.41	0.000184478224262	2941	-805629.546036
-0.00990099009901	0.01	0.000701217976547	11179	-93561.2440915
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-0.00497512437811	0.11	0.000701217976547	11179	-124007.285557
-0.00497512437811	0.21	0.000621869131361	9914	-217270.221781
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-0.00110987791343	0.01	0.000701217976547	11179	-93197.8868346
-0.00110987791343	0.11	0.000701217976547	11179	-115073.784274
-0.00110987791343	0.21	0.000701217976547	11179	-182167.315678
-0.00110987791343	0.31	0.000701217976547	11179	-324812.065112
-0.00110987791343	0.41	0.000701217976547	11179	-577557.436029
-0.00105152471083	0.01	0.000701217976547	11179	-93179.8329341
-0.00105152471083	0.11	0.000701217976547	11179	-114561.733755
-0.00105152471083	0.21	0.000701217976547	11179	-180134.424545
-0.00105152471083	0.31	0.000701217976547	11179	-319513.784174
-0.00105152471083	0.41	0.000701217976547	11179	-566356.987655
+inf	0.01	0.00728306064042	1079	nan
+inf	0.11	0.00728306064042	1079	nan
+inf	0.21	0.00728306064042	1079	nan
+inf	0.31	0.00728306064042	1079	nan
+inf	0.41	0.00728306064042	1079	nan
+0.01	0.01	0.00728306064042	1079	-7632.33888826
+0.01	0.11	0.00728306064042	1079	-41145.4085812
+0.01	0.21	0.00728306064042	1079	-143816.774349
+0.01	0.31	0.00728306064042	1079	-362824.427206
+0.01	0.41	0.00728306064042	1079	-753873.18328
+0.005	0.01	0.00728306064042	1079	-7578.26678869
+0.005	0.11	0.00728306064042	1079	-39671.6480412
+0.005	0.21	0.00728306064042	1079	-138032.49228
+0.005	0.31	0.00728306064042	1079	-347783.849869
+0.005	0.41	0.00728306064042	1079	-721985.508852
+0.00333333333333	0.01	0.00728306064042	1079	-7522.44276229
+0.00333333333333	0.11	0.00728306064042	1079	-38127.923151
+0.00333333333333	0.21	0.00728306064042	1079	-131943.601486
+0.00333333333333	0.31	0.00728306064042	1079	-331924.789171
+0.00333333333333	0.41	0.00728306064042	1079	-688355.043571
+0.0025	0.01	0.00728306064042	1079	-7467.51417822
+0.0025	0.11	0.00728306064042	1079	-36599.8359599
+0.0025	0.21	0.00728306064042	1079	-125903.505379
+0.0025	0.31	0.00728306064042	1079	-316183.068106
+0.0025	0.41	0.00728306064042	1079	-654979.438431
+0.002	0.01	0.00728306064042	1079	-7414.70185168
+0.002	0.11	0.00728306064042	1079	-35125.3347484
+0.002	0.21	0.00728306064042	1079	-120067.848333
+0.002	0.31	0.00728306064042	1079	-300970.34788
+0.002	0.41	0.00728306064042	1079	-622737.297292
+0.00166666666667	0.01	0.00728306064042	1079	-7364.63045747
+0.00166666666667	0.11	0.00728306064042	1079	-33723.8769361
+0.00166666666667	0.21	0.00728306064042	1079	-114516.615274
+0.00166666666667	0.31	0.00728306064042	1079	-286498.257545
+0.00166666666667	0.41	0.00728306064042	1079	-592079.644373
+0.00142857142857	0.01	0.00728306064042	1079	-7317.59743719
+0.00142857142857	0.11	0.00728306064042	1079	-32405.1880251
+0.00142857142857	0.21	0.00728306064042	1079	-109290.356131
+0.00142857142857	0.31	0.00728306064042	1079	-272874.512749
+0.00142857142857	0.41	0.00728306064042	1079	-563235.857483
+0.00125	0.01	0.00728306064042	1079	-7273.68766807
+0.00125	0.11	0.00728306064042	1079	-31172.6518115
+0.00125	0.21	0.00728306064042	1079	-104403.890399
+0.00125	0.31	0.00728306064042	1079	-260138.956484
+0.00125	0.41	0.00728306064042	1079	-536290.339785
+0.00111111111111	0.01	0.00728306064042	1079	-7232.84785268
+0.00111111111111	0.11	0.00728306064042	1079	-30025.4645403
+0.00111111111111	0.21	0.00728306064042	1079	-99854.9698943
+0.00111111111111	0.31	0.00728306064042	1079	-248286.311147
+0.00111111111111	0.41	0.00728306064042	1079	-511230.928521
diff --git a/experiments/process.py b/experiments/process.py
index 8ebe953..68c3507 100644
--- a/experiments/process.py
+++ b/experiments/process.py
@@ -11,11 +11,16 @@ if __name__ == "__main__":
         sys.exit("usage: {0} <file>".format(sys.argv[0]))
 
     root_victims, victims, non_victims, age = load(open(sys.argv[1]))
-    alphas = 1. / np.arange(1., 1000., 50.)  # parameter of the time component
+    alphas = 1. / np.arange(0., 1000., 100.)  # parameter of the time component
     deltas = np.arange(0.01, 0.5, 0.1)  # parameter of the structural component
     with open("out.log", "w") as fh:
         for alpha, delta in product(alphas, deltas):
             beta, roots, ll = ml(root_victims, victims, non_victims, age, alpha, delta)
-            print "\t".join(map(str, [1/alpha, delta, beta, roots, ll, exp(ll)]))
+            print "\t".join(map(str, [1/alpha, delta, beta, roots, ll]))
             fh.write("\t".join(map(str, [alpha, delta, beta, roots, ll])) + "\n")
             fh.flush()
+
+    # alpha = 100.
+    # delta = 0.2
+    # beta, roots, ll = ml(root_victims, victims, non_victims, age, alpha, delta)
+    # print "\t".join(map(str, [1./alpha, delta, beta, roots, ll]))
\ No newline at end of file