Tried ml3 that allows for multiple parents to infect.

6 files changed, 768 insertions, 632 deletions

diff --git a/experiments/build/temp.macosx-10.6-x86_64-2.7/ml3.o b/experiments/build/temp.macosx-10.6-x86_64-2.7/ml3.o
index b211a49..e928c51 100644
--- a/experiments/build/temp.macosx-10.6-x86_64-2.7/ml3.o
+++ b/experiments/build/temp.macosx-10.6-x86_64-2.7/ml3.o
diff --git a/experiments/ml3.c b/experiments/ml3.c
index 08730d3..12d0e1d 100644
--- a/experiments/ml3.c
+++ b/experiments/ml3.c
@@ -914,18 +914,6 @@ 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 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
-
 #define __Pyx_GetItemInt(o, i, type, is_signed, to_py_func, is_list, wraparound, boundscheck) \
     (__Pyx_fits_Py_ssize_t(i, type, is_signed) ? \
     __Pyx_GetItemInt_Fast(o, (Py_ssize_t)i, is_list, wraparound, boundscheck) : \
@@ -947,6 +935,18 @@ static CYTHON_INLINE PyObject *__Pyx_GetItemInt_Generic(PyObject *o, PyObject* j
 static CYTHON_INLINE PyObject *__Pyx_GetItemInt_Fast(PyObject *o, Py_ssize_t i,
                                                      int is_list, int wraparound, int boundscheck);
 
+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);
 
@@ -1217,6 +1217,7 @@ static char __pyx_k_sum[] = "sum";
 static char __pyx_k_beta[] = "beta";
 static char __pyx_k_dist[] = "dist";
 static char __pyx_k_main[] = "__main__";
+static char __pyx_k_ones[] = "ones";
 static char __pyx_k_prob[] = "prob";
 static char __pyx_k_test[] = "__test__";
 static char __pyx_k_DTYPE[] = "DTYPE";
@@ -1232,6 +1233,7 @@ static char __pyx_k_seeds[] = "seeds";
 static char __pyx_k_zeros[] = "zeros";
 static char __pyx_k_arange[] = "arange";
 static char __pyx_k_import[] = "__import__";
+static char __pyx_k_isSeed[] = "isSeed";
 static char __pyx_k_thresh[] = "thresh";
 static char __pyx_k_float64[] = "float64";
 static char __pyx_k_n_roots[] = "n_roots";
@@ -1285,6 +1287,7 @@ static PyObject *__pyx_n_s_float64;
 static PyObject *__pyx_n_s_i;
 static PyObject *__pyx_n_s_import;
 static PyObject *__pyx_kp_s_inf;
+static PyObject *__pyx_n_s_isSeed;
 static PyObject *__pyx_n_s_itervalues;
 static PyObject *__pyx_n_s_l;
 static PyObject *__pyx_n_s_ll;
@@ -1301,6 +1304,7 @@ static PyObject *__pyx_n_s_non_seeds;
 static PyObject *__pyx_n_s_non_victims;
 static PyObject *__pyx_n_s_np;
 static PyObject *__pyx_n_s_numpy;
+static PyObject *__pyx_n_s_ones;
 static PyObject *__pyx_n_s_parent_dists;
 static PyObject *__pyx_n_s_parent_dts;
 static PyObject *__pyx_n_s_parents;
@@ -1323,9 +1327,11 @@ 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__1;
 static PyObject *__pyx_float_1_;
-static PyObject *__pyx_float_0_2;
+static PyObject *__pyx_float_0_00001;
+static PyObject *__pyx_float_neg_19_523275053840013;
+static PyObject *__pyx_int_0;
+static PyObject *__pyx_int_1;
 static PyObject *__pyx_tuple_;
 static PyObject *__pyx_tuple__2;
 static PyObject *__pyx_tuple__3;
@@ -1603,17 +1609,20 @@ static PyObject *__pyx_pf_3ml3_ml3(CYTHON_UNUSED PyObject *__pyx_self, PyObject
   PyArrayObject *__pyx_v_probs_fail = 0;
   PyArrayObject *__pyx_v_parent_dists = 0;
   PyArrayObject *__pyx_v_parent_dts = 0;
+  PyArrayObject *__pyx_v_isSeed = 0;
   PyObject *__pyx_v_dists = NULL;
   PyObject *__pyx_v_dts = NULL;
   PyObject *__pyx_v_s = NULL;
   PyObject *__pyx_v_prob = NULL;
-  double __pyx_v_thresh;
+  CYTHON_UNUSED double __pyx_v_thresh;
   PyObject *__pyx_v_seeds = NULL;
   PyObject *__pyx_v_non_seeds = NULL;
   int __pyx_v_max_roots;
   PyObject *__pyx_v_w1 = NULL;
   PyObject *__pyx_v_w2 = NULL;
   PyObject *__pyx_v_w3 = NULL;
+  __Pyx_LocalBuf_ND __pyx_pybuffernd_isSeed;
+  __Pyx_Buffer __pyx_pybuffer_isSeed;
   __Pyx_LocalBuf_ND __pyx_pybuffernd_parent_dists;
   __Pyx_Buffer __pyx_pybuffer_parent_dists;
   __Pyx_LocalBuf_ND __pyx_pybuffernd_parent_dts;
@@ -1634,28 +1643,28 @@ static PyObject *__pyx_pf_3ml3_ml3(CYTHON_UNUSED PyObject *__pyx_self, PyObject
   PyArrayObject *__pyx_t_8 = NULL;
   PyArrayObject *__pyx_t_9 = NULL;
   PyArrayObject *__pyx_t_10 = NULL;
-  int __pyx_t_11;
+  PyArrayObject *__pyx_t_11 = NULL;
   int __pyx_t_12;
   int __pyx_t_13;
-  Py_ssize_t __pyx_t_14;
-  PyObject *__pyx_t_15 = NULL;
+  int __pyx_t_14;
+  Py_ssize_t __pyx_t_15;
   PyObject *__pyx_t_16 = NULL;
   PyObject *__pyx_t_17 = NULL;
   PyObject *__pyx_t_18 = NULL;
   PyObject *__pyx_t_19 = NULL;
   PyObject *__pyx_t_20 = NULL;
-  PyObject *(*__pyx_t_21)(PyObject *);
-  int __pyx_t_22;
-  __pyx_t_3ml3_DTYPE_t __pyx_t_23;
+  PyObject *__pyx_t_21 = NULL;
+  PyObject *(*__pyx_t_22)(PyObject *);
+  int __pyx_t_23;
   __pyx_t_3ml3_DTYPE_t __pyx_t_24;
   __pyx_t_3ml3_DTYPE_t __pyx_t_25;
-  int __pyx_t_26;
-  double __pyx_t_27;
+  __pyx_t_3ml3_DTYPE_t __pyx_t_26;
+  int __pyx_t_27;
   int __pyx_t_28;
   int __pyx_t_29;
   int __pyx_t_30;
   int __pyx_t_31;
-  int __pyx_t_32;
+  double __pyx_t_32;
   PyObject *(*__pyx_t_33)(PyObject *);
   int __pyx_lineno = 0;
   const char *__pyx_filename = NULL;
@@ -1677,6 +1686,10 @@ static PyObject *__pyx_pf_3ml3_ml3(CYTHON_UNUSED PyObject *__pyx_self, PyObject
   __pyx_pybuffer_parent_dts.refcount = 0;
   __pyx_pybuffernd_parent_dts.data = NULL;
   __pyx_pybuffernd_parent_dts.rcbuffer = &__pyx_pybuffer_parent_dts;
+  __pyx_pybuffer_isSeed.pybuffer.buf = NULL;
+  __pyx_pybuffer_isSeed.refcount = 0;
+  __pyx_pybuffernd_isSeed.data = NULL;
+  __pyx_pybuffernd_isSeed.rcbuffer = &__pyx_pybuffer_isSeed;
 
   /* "ml3.pyx":33
  *         DTYPE_t beta, ll, beta_add, max_beta, max_beta_add
@@ -1791,7 +1804,7 @@ static PyObject *__pyx_pf_3ml3_ml3(CYTHON_UNUSED PyObject *__pyx_self, PyObject
  *         np.ndarray[DTYPE_t] probs_fail = np.zeros(n_victims, dtype=DTYPE)
  *         np.ndarray[DTYPE_t] parent_dists = np.zeros(n_victims, dtype=DTYPE)             # <<<<<<<<<<<<<<
  *         np.ndarray[DTYPE_t] parent_dts = np.zeros(n_victims, dtype=DTYPE)
- * 
+ *         np.ndarray[DTYPE_t] isSeed = np.ones(n_victims, dtype=DTYPE)
  */
   __pyx_t_4 = __Pyx_GetModuleGlobalName(__pyx_n_s_np); if (unlikely(!__pyx_t_4)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 37; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
   __Pyx_GOTREF(__pyx_t_4);
@@ -1834,8 +1847,8 @@ static PyObject *__pyx_pf_3ml3_ml3(CYTHON_UNUSED PyObject *__pyx_self, PyObject
  *         np.ndarray[DTYPE_t] probs_fail = np.zeros(n_victims, dtype=DTYPE)
  *         np.ndarray[DTYPE_t] parent_dists = np.zeros(n_victims, dtype=DTYPE)
  *         np.ndarray[DTYPE_t] parent_dts = np.zeros(n_victims, dtype=DTYPE)             # <<<<<<<<<<<<<<
+ *         np.ndarray[DTYPE_t] isSeed = np.ones(n_victims, dtype=DTYPE)
  * 
- *     # loop through victims
  */
   __pyx_t_3 = __Pyx_GetModuleGlobalName(__pyx_n_s_np); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 38; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
   __Pyx_GOTREF(__pyx_t_3);
@@ -1874,46 +1887,90 @@ static PyObject *__pyx_pf_3ml3_ml3(CYTHON_UNUSED PyObject *__pyx_self, PyObject
   __pyx_v_parent_dts = ((PyArrayObject *)__pyx_t_6);
   __pyx_t_6 = 0;
 
-  /* "ml3.pyx":41
+  /* "ml3.pyx":39
+ *         np.ndarray[DTYPE_t] parent_dists = np.zeros(n_victims, dtype=DTYPE)
+ *         np.ndarray[DTYPE_t] parent_dts = np.zeros(n_victims, dtype=DTYPE)
+ *         np.ndarray[DTYPE_t] isSeed = np.ones(n_victims, dtype=DTYPE)             # <<<<<<<<<<<<<<
+ * 
+ *     # loop through victims
+ */
+  __pyx_t_6 = __Pyx_GetModuleGlobalName(__pyx_n_s_np); if (unlikely(!__pyx_t_6)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 39; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
+  __Pyx_GOTREF(__pyx_t_6);
+  __pyx_t_3 = __Pyx_PyObject_GetAttrStr(__pyx_t_6, __pyx_n_s_ones); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 39; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
+  __Pyx_GOTREF(__pyx_t_3);
+  __Pyx_DECREF(__pyx_t_6); __pyx_t_6 = 0;
+  __pyx_t_6 = __Pyx_PyInt_From_int(__pyx_v_n_victims); if (unlikely(!__pyx_t_6)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 39; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
+  __Pyx_GOTREF(__pyx_t_6);
+  __pyx_t_5 = PyTuple_New(1); if (unlikely(!__pyx_t_5)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 39; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
+  __Pyx_GOTREF(__pyx_t_5);
+  PyTuple_SET_ITEM(__pyx_t_5, 0, __pyx_t_6);
+  __Pyx_GIVEREF(__pyx_t_6);
+  __pyx_t_6 = 0;
+  __pyx_t_6 = PyDict_New(); if (unlikely(!__pyx_t_6)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 39; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
+  __Pyx_GOTREF(__pyx_t_6);
+  __pyx_t_4 = __Pyx_GetModuleGlobalName(__pyx_n_s_DTYPE); if (unlikely(!__pyx_t_4)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 39; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
+  __Pyx_GOTREF(__pyx_t_4);
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+  __Pyx_DECREF(__pyx_t_4); __pyx_t_4 = 0;
+  __pyx_t_4 = __Pyx_PyObject_Call(__pyx_t_3, __pyx_t_5, __pyx_t_6); if (unlikely(!__pyx_t_4)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 39; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
+  __Pyx_GOTREF(__pyx_t_4);
+  __Pyx_DECREF(__pyx_t_3); __pyx_t_3 = 0;
+  __Pyx_DECREF(__pyx_t_5); __pyx_t_5 = 0;
+  __Pyx_DECREF(__pyx_t_6); __pyx_t_6 = 0;
+  if (!(likely(((__pyx_t_4) == Py_None) || likely(__Pyx_TypeTest(__pyx_t_4, __pyx_ptype_5numpy_ndarray))))) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 39; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
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+      __pyx_v_isSeed = ((PyArrayObject *)Py_None); __Pyx_INCREF(Py_None); __pyx_pybuffernd_isSeed.rcbuffer->pybuffer.buf = NULL;
+      {__pyx_filename = __pyx_f[0]; __pyx_lineno = 39; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
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+    }
+  }
+  __pyx_t_11 = 0;
+  __pyx_v_isSeed = ((PyArrayObject *)__pyx_t_4);
+  __pyx_t_4 = 0;
+
+  /* "ml3.pyx":42
  * 
  *     # loop through victims
  *     for i, parents in enumerate(victims.itervalues()):             # <<<<<<<<<<<<<<
  *         # for each victim node i, compute the probability that all its parents
  *         # fail to infect it, also computes the probability that its most
  */
-  __pyx_t_11 = 0;
+  __pyx_t_12 = 0;
   __pyx_t_2 = 0;
   if (unlikely(__pyx_v_victims == Py_None)) {
     PyErr_Format(PyExc_AttributeError, "'NoneType' object has no attribute '%s'", "itervalues");
-    {__pyx_filename = __pyx_f[0]; __pyx_lineno = 41; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
+    {__pyx_filename = __pyx_f[0]; __pyx_lineno = 42; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
   }
-  __pyx_t_3 = __Pyx_dict_iterator(__pyx_v_victims, 1, __pyx_n_s_itervalues, (&__pyx_t_1), (&__pyx_t_12)); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 41; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
-  __Pyx_GOTREF(__pyx_t_3);
-  __Pyx_XDECREF(__pyx_t_6);
-  __pyx_t_6 = __pyx_t_3;
-  __pyx_t_3 = 0;
+  __pyx_t_6 = __Pyx_dict_iterator(__pyx_v_victims, 1, __pyx_n_s_itervalues, (&__pyx_t_1), (&__pyx_t_13)); if (unlikely(!__pyx_t_6)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 42; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
+  __Pyx_GOTREF(__pyx_t_6);
+  __Pyx_XDECREF(__pyx_t_4);
+  __pyx_t_4 = __pyx_t_6;
+  __pyx_t_6 = 0;
   while (1) {
-    __pyx_t_13 = __Pyx_dict_iter_next(__pyx_t_6, __pyx_t_1, &__pyx_t_2, NULL, &__pyx_t_3, NULL, __pyx_t_12);
-    if (unlikely(__pyx_t_13 == 0)) break;
-    if (unlikely(__pyx_t_13 == -1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 41; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
-    __Pyx_GOTREF(__pyx_t_3);
-    if (!(likely(PyList_CheckExact(__pyx_t_3))||((__pyx_t_3) == Py_None)||(PyErr_Format(PyExc_TypeError, "Expected %.16s, got %.200s", "list", Py_TYPE(__pyx_t_3)->tp_name), 0))) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 41; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
-    __Pyx_XDECREF_SET(__pyx_v_parents, ((PyObject*)__pyx_t_3));
-    __pyx_t_3 = 0;
-    __pyx_v_i = __pyx_t_11;
-    __pyx_t_11 = (__pyx_t_11 + 1);
+    __pyx_t_14 = __Pyx_dict_iter_next(__pyx_t_4, __pyx_t_1, &__pyx_t_2, NULL, &__pyx_t_6, NULL, __pyx_t_13);
+    if (unlikely(__pyx_t_14 == 0)) break;
+    if (unlikely(__pyx_t_14 == -1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 42; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
+    __Pyx_GOTREF(__pyx_t_6);
+    if (!(likely(PyList_CheckExact(__pyx_t_6))||((__pyx_t_6) == Py_None)||(PyErr_Format(PyExc_TypeError, "Expected %.16s, got %.200s", "list", Py_TYPE(__pyx_t_6)->tp_name), 0))) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 42; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
+    __Pyx_XDECREF_SET(__pyx_v_parents, ((PyObject*)__pyx_t_6));
+    __pyx_t_6 = 0;
+    __pyx_v_i = __pyx_t_12;
+    __pyx_t_12 = (__pyx_t_12 + 1);
 
-    /* "ml3.pyx":45
+    /* "ml3.pyx":46
  *         # fail to infect it, also computes the probability that its most
  *         # 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)
  */
-    __pyx_t_3 = PyList_New(0); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 45; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
-    __Pyx_GOTREF(__pyx_t_3);
+    __pyx_t_6 = PyList_New(0); if (unlikely(!__pyx_t_6)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 46; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
+    __Pyx_GOTREF(__pyx_t_6);
 
-    /* "ml3.pyx":46
+    /* "ml3.pyx":47
  *         # likely parent infects it
  *         failures = [weight_failure(dist, dt, alpha, delta, w1, w2, w3)
  *                     for (dist, dt, w1, w2, w3) in parents]             # <<<<<<<<<<<<<<
@@ -1922,18 +1979,18 @@ static PyObject *__pyx_pf_3ml3_ml3(CYTHON_UNUSED PyObject *__pyx_self, PyObject
  */
     if (unlikely(__pyx_v_parents == Py_None)) {
       PyErr_SetString(PyExc_TypeError, "'NoneType' object is not iterable");
-      {__pyx_filename = __pyx_f[0]; __pyx_lineno = 46; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
+      {__pyx_filename = __pyx_f[0]; __pyx_lineno = 47; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
     }
-    __pyx_t_5 = __pyx_v_parents; __Pyx_INCREF(__pyx_t_5); __pyx_t_14 = 0;
+    __pyx_t_5 = __pyx_v_parents; __Pyx_INCREF(__pyx_t_5); __pyx_t_15 = 0;
     for (;;) {
-      if (__pyx_t_14 >= PyList_GET_SIZE(__pyx_t_5)) break;
+      if (__pyx_t_15 >= PyList_GET_SIZE(__pyx_t_5)) break;
       #if CYTHON_COMPILING_IN_CPYTHON
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-    __Pyx_DECREF(__pyx_t_16); __pyx_t_16 = 0;
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  *             max_roots = roots
  */
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@@ -2818,12 +2863,12 @@ static PyObject *__pyx_pf_3ml3_ml3(CYTHON_UNUSED PyObject *__pyx_self, PyObject
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-    /* "ml3.pyx":69
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- *         seeds = probs<thresh
+ *         seeds = isSeed==1
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   goto __pyx_L2;
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   __Pyx_XDECREF((PyObject *)__pyx_v_parent_dists);
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+  __pyx_builtin_enumerate = __Pyx_GetBuiltinName(__pyx_n_s_enumerate); if (!__pyx_builtin_enumerate) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 42; __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 = 48; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
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  *     # iterate over all victim nodes to find the optimal threshold
- *     for beta in np.arange(0.2, 1., .1):             # <<<<<<<<<<<<<<
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- *         seeds = probs<thresh
+ *         seeds = isSeed==1
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+  __pyx_tuple_ = PyTuple_Pack(3, __pyx_float_0_00001, __pyx_float_1_, __pyx_float_1_); if (unlikely(!__pyx_tuple_)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 71; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
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+  __pyx_tuple__8 = PyTuple_Pack(38, __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_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_beta_add, __pyx_n_s_max_beta, __pyx_n_s_max_beta_add, __pyx_n_s_parents, __pyx_n_s_failures, __pyx_n_s_successes, __pyx_n_s_probs, __pyx_n_s_probs_fail, __pyx_n_s_parent_dists, __pyx_n_s_parent_dts, __pyx_n_s_isSeed, __pyx_n_s_dists, __pyx_n_s_dts, __pyx_n_s_s, __pyx_n_s_prob, __pyx_n_s_thresh, __pyx_n_s_seeds, __pyx_n_s_non_seeds, __pyx_n_s_max_roots, __pyx_n_s_w1, __pyx_n_s_w2, __pyx_n_s_w3); if (unlikely(!__pyx_tuple__8)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 27; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
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+  __pyx_codeobj__9 = (PyObject*)__Pyx_PyCode_New(6, 0, 38, 0, 0, __pyx_empty_bytes, __pyx_empty_tuple, __pyx_empty_tuple, __pyx_tuple__8, __pyx_empty_tuple, __pyx_empty_tuple, __pyx_kp_s_Users_ben_Documents_Cascade_Pro, __pyx_n_s_ml3, 27, __pyx_empty_bytes); if (unlikely(!__pyx_codeobj__9)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 27; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
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@@ -5140,9 +5190,11 @@ static int __Pyx_InitCachedConstants(void) {
 
 static int __Pyx_InitGlobals(void) {
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+  __pyx_float_0_00001 = PyFloat_FromDouble(0.00001); if (unlikely(!__pyx_float_0_00001)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
+  __pyx_float_neg_19_523275053840013 = PyFloat_FromDouble(-19.523275053840013); if (unlikely(!__pyx_float_neg_19_523275053840013)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
+  __pyx_int_0 = PyInt_FromLong(0); if (unlikely(!__pyx_int_0)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
+  __pyx_int_1 = PyInt_FromLong(1); if (unlikely(!__pyx_int_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
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-static double __Pyx__PyObject_AsDouble(PyObject* obj) {
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-        if (likely(float_value) && unlikely(!PyFloat_Check(float_value))) {
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-                "__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);
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-        float_value = PyFloat_FromString(obj, 0);
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-    } 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;
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-
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     return __Pyx_GetItemInt_Generic(o, PyInt_FromSsize_t(i));
 }
 
+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);
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+            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) {
 #if CYTHON_COMPILING_IN_CPYTHON
     PyObject *tmp_type, *tmp_value, *tmp_tb;
diff --git a/experiments/ml3.pyx b/experiments/ml3.pyx
index 49b24cf..faeda92 100644
--- a/experiments/ml3.pyx
+++ b/experiments/ml3.pyx
@@ -36,6 +36,7 @@ def ml3(dict root_victims, dict victims, dict non_victims, DTYPE_t age,
         np.ndarray[DTYPE_t] probs_fail = np.zeros(n_victims, dtype=DTYPE)
         np.ndarray[DTYPE_t] parent_dists = np.zeros(n_victims, dtype=DTYPE)
         np.ndarray[DTYPE_t] parent_dts = np.zeros(n_victims, dtype=DTYPE)
+        np.ndarray[DTYPE_t] isSeed = np.ones(n_victims, dtype=DTYPE)
 
     # loop through victims
     for i, parents in enumerate(victims.itervalues()):
@@ -51,25 +52,26 @@ def ml3(dict root_victims, dict victims, dict non_victims, DTYPE_t age,
         dts = [dt for (dist, dt, w1, w2, w3) in parents]
         # find parent that maximizes log(p) - log(\tilde{p})
         # probs[i] = max(s - failures[l] for l, s in enumerate(successes)) 
-        probs[i] = float("-inf")
+        # probs[i] = 0.
         for l, s in enumerate(successes):
             prob = s - failures[l]
-            if prob > probs[i]:
-                probs[i] = prob
+            if prob > -19.523275053840013:
+                isSeed[i] = 0
+                probs[i] += prob
                 parent_dists[i] = dists[l]
                 parent_dts[i] = dts[l]
                 # probs_fail[i] = failures[l]
 
     # calculate log likelihood
-    ll =  probs_fail.sum() # add probability that all edges to all victims fail
+    ll = probs_fail.sum() # add probability that all edges to all victims fail
 
     # print 'probs', probs
     max_beta_add = float('-inf')
     # iterate over all victim nodes to find the optimal threshold
-    for beta in np.arange(0.2, 1., .1):
+    for beta in np.arange(0.00001, 1., 1.):
         thresh = log(beta/(3012.*(1.-beta)))
-        seeds = probs<thresh
-        non_seeds = probs>=thresh
+        seeds = isSeed==1
+        non_seeds = isSeed==0
         roots = n_roots + sum(seeds)
 
         beta_add = 0.
diff --git a/experiments/ml3.so b/experiments/ml3.so
index ff3bf05..2dd1f2d 100755
--- a/experiments/ml3.so
+++ b/experiments/ml3.so
diff --git a/experiments/out.log b/experiments/out.log
index eb2c025..dbc6e69 100644
--- a/experiments/out.log
+++ b/experiments/out.log
@@ -1,100 +1,180 @@
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diff --git a/experiments/process.py b/experiments/process.py
index 8201dea..9ea2e81 100644
--- a/experiments/process.py
+++ b/experiments/process.py
@@ -6,17 +6,19 @@ import numpy as np
 from cPickle import load
 from itertools import product
 from math import exp
+import time
 
 
 if __name__ == "__main__":
+    time.sleep(3)
     if len(sys.argv) < 2:
         sys.exit("usage: {0} <file>".format(sys.argv[0]))
     root_victims, victims, non_victims, age = load(open(sys.argv[1]))
     
     # alphas = np.arange(1e-3, 1e-2, 8e-4)  # parameter of the time component
-    alphas = np.logspace(-3,-.1,num=10)
+    alphas = np.logspace(-3,0,num=15)
     # deltas = np.arange(0.001, 0.3, 0.008)  # parameter of the structural component
-    deltas = np.logspace(-2,-.1,num=10)
+    deltas = np.logspace(-4,-1.7,num=15)
     with open("out.log", "w") as fh:
         for alpha, delta in product(alphas, deltas):
             beta, roots, ll = ml3(root_victims, victims, non_victims, age, alpha, delta)