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-rw-r--r--experiments/build/temp.macosx-10.6-x86_64-2.7/ml.obin302088 -> 299240 bytes
-rw-r--r--experiments/build/temp.macosx-10.6-x86_64-2.7/ml2.obin292208 -> 285440 bytes
-rw-r--r--experiments/build_network.py10
-rw-r--r--experiments/ml.c203
-rw-r--r--experiments/ml.pyx7
-rwxr-xr-xexperiments/ml.sobin108812 -> 108744 bytes
-rw-r--r--experiments/ml2.c642
-rw-r--r--experiments/ml2.pyx9
-rwxr-xr-xexperiments/ml2.sobin104116 -> 103156 bytes
-rw-r--r--experiments/out.log414
-rw-r--r--experiments/process.py10
11 files changed, 720 insertions, 575 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 e626f4c..640d0f3 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
Binary files differ
diff --git a/experiments/build/temp.macosx-10.6-x86_64-2.7/ml2.o b/experiments/build/temp.macosx-10.6-x86_64-2.7/ml2.o
index 62313a2..1489d58 100644
--- a/experiments/build/temp.macosx-10.6-x86_64-2.7/ml2.o
+++ b/experiments/build/temp.macosx-10.6-x86_64-2.7/ml2.o
Binary files differ
diff --git a/experiments/build_network.py b/experiments/build_network.py
index e34db1c..6cb994c 100644
--- a/experiments/build_network.py
+++ b/experiments/build_network.py
@@ -14,8 +14,8 @@ def build_network(filename):
from_, to = int(float(row["from"])), int(float(row["to"]))
dist = int(row["dist"])
w1, w2, w3 = float(row["w1"]), float(row["w2"]), float(row["w3"])
- # if int(float(row["dist"])) > 1:
- # continue
+ if int(float(row["dist"])) > 1:
+ continue
# 'to' is a victim
if row["t2"] != "NA":
dt = int(row["t2"]) - int(row["t1"])
@@ -39,13 +39,13 @@ def build_network(filename):
age += int(row["t1"]) - int(row["spawn1"])
victims[from_] = []
root_victims = {}
- print victims.keys()
+ # print victims.keys()
for victim in victims.keys():
if not victims[victim]:
del victims[victim]
root_victims[victim] = []
- print root_victims.keys()
- print len(root_victims), len(victims), len(non_victims)
+ # print root_victims.keys()
+ # print len(root_victims), len(victims), len(non_victims)
return root_victims, victims, non_victims, age
diff --git a/experiments/ml.c b/experiments/ml.c
index b350aaf..64d4e3a 100644
--- a/experiments/ml.c
+++ b/experiments/ml.c
@@ -983,8 +983,6 @@ static double __Pyx__PyObject_AsDouble(PyObject* obj);
PyFloat_AS_DOUBLE(obj) : __Pyx__PyObject_AsDouble(obj))
#endif
-static CYTHON_INLINE void __Pyx_RaiseUnboundLocalError(const char *varname);
-
static CYTHON_INLINE void __Pyx_ErrRestore(PyObject *type, PyObject *value, PyObject *tb);
static CYTHON_INLINE void __Pyx_ErrFetch(PyObject **type, PyObject **value, PyObject **tb);
@@ -1475,32 +1473,32 @@ 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) * (exp(alpha)-1.)
+ * temporal = log(exp(alpha)-1.) - 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) * (exp(alpha)-1.) # <<<<<<<<<<<<<<
+ * temporal = log(exp(alpha)-1.) - alpha*dt # <<<<<<<<<<<<<<
* # temporal = 1 - exp(-alpha*dt)
* # if exp(-alpha*dt)==0.: print 'UNDERFLOW ERROR'
*/
- __pyx_v_temporal = (exp(((-__pyx_v_alpha) * __pyx_v_dt)) * (exp(__pyx_v_alpha) - 1.));
+ __pyx_v_temporal = (log((exp(__pyx_v_alpha) - 1.)) - (__pyx_v_alpha * __pyx_v_dt));
/* "ml.pyx":22
* # if exp(-alpha*dt)==0.: print 'UNDERFLOW ERROR'
* # temporal = 1. / (1. + (dt - 1.)/alpha)**0.01 - 1. / (1. + dt/alpha)**0.01
- * result = log(structural * temporal) # <<<<<<<<<<<<<<
+ * result = structural + temporal # <<<<<<<<<<<<<<
* # print 'st', structural, temporal
* return result
*/
- __pyx_v_result = log((__pyx_v_structural * __pyx_v_temporal));
+ __pyx_v_result = (__pyx_v_structural + __pyx_v_temporal);
/* "ml.pyx":24
- * result = log(structural * temporal)
+ * result = structural + temporal
* # print 'st', structural, temporal
* return result # <<<<<<<<<<<<<<
*
@@ -1851,14 +1849,14 @@ static PyObject *__pyx_pf_2ml_ml(CYTHON_UNUSED PyObject *__pyx_self, PyObject *_
int __pyx_v_dt;
__pyx_t_2ml_DTYPE_t __pyx_v_beta;
__pyx_t_2ml_DTYPE_t __pyx_v_ll;
+ __pyx_t_2ml_DTYPE_t __pyx_v_beta_add;
+ __pyx_t_2ml_DTYPE_t __pyx_v_max_beta;
+ __pyx_t_2ml_DTYPE_t __pyx_v_max_beta_add;
PyObject *__pyx_v_parents = 0;
PyArrayObject *__pyx_v_probs = 0;
PyArrayObject *__pyx_v_probs_fail = 0;
PyArrayObject *__pyx_v_probs_nv = 0;
- PyObject *__pyx_v_max_beta_add = NULL;
double __pyx_v_thresh;
- PyObject *__pyx_v_beta_add = NULL;
- PyObject *__pyx_v_max_beta = NULL;
int __pyx_v_max_roots;
PyObject *__pyx_v_w1 = NULL;
PyObject *__pyx_v_w2 = NULL;
@@ -1924,7 +1922,7 @@ static PyObject *__pyx_pf_2ml_ml(CYTHON_UNUSED PyObject *__pyx_self, PyObject *_
__pyx_pybuffernd_probs_nv.rcbuffer = &__pyx_pybuffer_probs_nv;
/* "ml.pyx":44
- * DTYPE_t beta, ll
+ * DTYPE_t beta, ll, beta_add, max_beta, max_beta_add
* list parents, failures, successes
* n_roots, n_victims = len(root_victims), len(victims) # <<<<<<<<<<<<<<
* n_nodes = 148152
@@ -2703,16 +2701,13 @@ static PyObject *__pyx_pf_2ml_ml(CYTHON_UNUSED PyObject *__pyx_self, PyObject *_
* for beta in np.arange(0.001, .2, .002):
*/
__pyx_t_27 = __Pyx_PyObject_AsDouble(__pyx_kp_s_inf); if (unlikely(__pyx_t_27 == ((double)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 84; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
- __pyx_t_5 = PyFloat_FromDouble(__pyx_t_27); if (unlikely(!__pyx_t_5)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 84; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
- __Pyx_GOTREF(__pyx_t_5);
- __pyx_v_max_beta_add = __pyx_t_5;
- __pyx_t_5 = 0;
+ __pyx_v_max_beta_add = __pyx_t_27;
/* "ml.pyx":86
* max_beta_add = float('-inf')
* # iterate over all victim nodes to find the optimal threshold
* for beta in np.arange(0.001, .2, .002): # <<<<<<<<<<<<<<
- * thresh = log(beta/(3012*(1.-beta)))
+ * thresh = log(beta/(3012.*(1.-beta)))
* # print 'beta:', beta, 'thresh:', thresh, 'infected:', len(probs[probs>=thresh])
*/
__pyx_t_5 = __Pyx_GetModuleGlobalName(__pyx_n_s_np); if (unlikely(!__pyx_t_5)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 86; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
@@ -2768,18 +2763,18 @@ static PyObject *__pyx_pf_2ml_ml(CYTHON_UNUSED PyObject *__pyx_self, PyObject *_
/* "ml.pyx":87
* # iterate over all victim nodes to find the optimal threshold
* for beta in np.arange(0.001, .2, .002):
- * thresh = log(beta/(3012*(1.-beta))) # <<<<<<<<<<<<<<
+ * thresh = log(beta/(3012.*(1.-beta))) # <<<<<<<<<<<<<<
* # print 'beta:', beta, 'thresh:', thresh, 'infected:', len(probs[probs>=thresh])
* roots = n_roots + len(probs[probs<thresh])
*/
- __pyx_v_thresh = log((__pyx_v_beta / (3012.0 * (1. - __pyx_v_beta))));
+ __pyx_v_thresh = log((__pyx_v_beta / (3012. * (1. - __pyx_v_beta))));
/* "ml.pyx":89
- * thresh = log(beta/(3012*(1.-beta)))
+ * thresh = log(beta/(3012.*(1.-beta)))
* # print 'beta:', beta, 'thresh:', thresh, 'infected:', len(probs[probs>=thresh])
* roots = n_roots + len(probs[probs<thresh]) # <<<<<<<<<<<<<<
*
- * # add probability for realized edges and subtract probability these edges fail
+ * beta_add = 0.
*/
__pyx_t_5 = PyFloat_FromDouble(__pyx_v_thresh); if (unlikely(!__pyx_t_5)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 89; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_5);
@@ -2792,84 +2787,89 @@ static PyObject *__pyx_pf_2ml_ml(CYTHON_UNUSED PyObject *__pyx_self, PyObject *_
__Pyx_DECREF(__pyx_t_5); __pyx_t_5 = 0;
__pyx_v_roots = (__pyx_v_n_roots + __pyx_t_1);
- /* "ml.pyx":92
+ /* "ml.pyx":91
+ * roots = n_roots + len(probs[probs<thresh])
*
+ * beta_add = 0. # <<<<<<<<<<<<<<
* # add probability for realized edges and subtract probability these edges fail
- * beta_add = (probs[probs>=thresh]).sum() # <<<<<<<<<<<<<<
+ * beta_add += (probs[probs>=thresh]).sum()
+ */
+ __pyx_v_beta_add = 0.;
+
+ /* "ml.pyx":93
+ * beta_add = 0.
+ * # add probability for realized edges and subtract probability these edges fail
+ * 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)
*/
- __pyx_t_3 = PyFloat_FromDouble(__pyx_v_thresh); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 92; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
- __Pyx_GOTREF(__pyx_t_3);
- __pyx_t_6 = PyObject_RichCompare(((PyObject *)__pyx_v_probs), __pyx_t_3, Py_GE); __Pyx_XGOTREF(__pyx_t_6); if (unlikely(!__pyx_t_6)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 92; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
- __Pyx_DECREF(__pyx_t_3); __pyx_t_3 = 0;
- __pyx_t_3 = PyObject_GetItem(((PyObject *)__pyx_v_probs), __pyx_t_6); if (unlikely(__pyx_t_3 == NULL)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 92; __pyx_clineno = __LINE__; goto __pyx_L1_error;};
- __Pyx_GOTREF(__pyx_t_3);
+ __pyx_t_5 = PyFloat_FromDouble(__pyx_v_beta_add); if (unlikely(!__pyx_t_5)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 93; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
+ __Pyx_GOTREF(__pyx_t_5);
+ __pyx_t_6 = PyFloat_FromDouble(__pyx_v_thresh); if (unlikely(!__pyx_t_6)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 93; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
+ __Pyx_GOTREF(__pyx_t_6);
+ __pyx_t_18 = PyObject_RichCompare(((PyObject *)__pyx_v_probs), __pyx_t_6, Py_GE); __Pyx_XGOTREF(__pyx_t_18); if (unlikely(!__pyx_t_18)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 93; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_DECREF(__pyx_t_6); __pyx_t_6 = 0;
- __pyx_t_6 = __Pyx_PyObject_GetAttrStr(__pyx_t_3, __pyx_n_s_sum); if (unlikely(!__pyx_t_6)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 92; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
+ __pyx_t_6 = PyObject_GetItem(((PyObject *)__pyx_v_probs), __pyx_t_18); if (unlikely(__pyx_t_6 == NULL)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 93; __pyx_clineno = __LINE__; goto __pyx_L1_error;};
__Pyx_GOTREF(__pyx_t_6);
- __Pyx_DECREF(__pyx_t_3); __pyx_t_3 = 0;
- __pyx_t_3 = NULL;
- if (CYTHON_COMPILING_IN_CPYTHON && likely(PyMethod_Check(__pyx_t_6))) {
- __pyx_t_3 = PyMethod_GET_SELF(__pyx_t_6);
- if (likely(__pyx_t_3)) {
- PyObject* function = PyMethod_GET_FUNCTION(__pyx_t_6);
- __Pyx_INCREF(__pyx_t_3);
+ __Pyx_DECREF(__pyx_t_18); __pyx_t_18 = 0;
+ __pyx_t_18 = __Pyx_PyObject_GetAttrStr(__pyx_t_6, __pyx_n_s_sum); if (unlikely(!__pyx_t_18)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 93; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
+ __Pyx_GOTREF(__pyx_t_18);
+ __Pyx_DECREF(__pyx_t_6); __pyx_t_6 = 0;
+ __pyx_t_6 = NULL;
+ if (CYTHON_COMPILING_IN_CPYTHON && likely(PyMethod_Check(__pyx_t_18))) {
+ __pyx_t_6 = PyMethod_GET_SELF(__pyx_t_18);
+ if (likely(__pyx_t_6)) {
+ PyObject* function = PyMethod_GET_FUNCTION(__pyx_t_18);
+ __Pyx_INCREF(__pyx_t_6);
__Pyx_INCREF(function);
- __Pyx_DECREF_SET(__pyx_t_6, function);
+ __Pyx_DECREF_SET(__pyx_t_18, function);
}
}
- if (__pyx_t_3) {
- __pyx_t_5 = __Pyx_PyObject_CallOneArg(__pyx_t_6, __pyx_t_3); if (unlikely(!__pyx_t_5)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 92; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
- __Pyx_DECREF(__pyx_t_3); __pyx_t_3 = 0;
+ if (__pyx_t_6) {
+ __pyx_t_3 = __Pyx_PyObject_CallOneArg(__pyx_t_18, __pyx_t_6); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 93; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
+ __Pyx_DECREF(__pyx_t_6); __pyx_t_6 = 0;
} else {
- __pyx_t_5 = __Pyx_PyObject_CallNoArg(__pyx_t_6); if (unlikely(!__pyx_t_5)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 92; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
+ __pyx_t_3 = __Pyx_PyObject_CallNoArg(__pyx_t_18); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 93; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
}
- __Pyx_GOTREF(__pyx_t_5);
- __Pyx_DECREF(__pyx_t_6); __pyx_t_6 = 0;
- __Pyx_XDECREF_SET(__pyx_v_beta_add, __pyx_t_5);
- __pyx_t_5 = 0;
+ __Pyx_GOTREF(__pyx_t_3);
+ __Pyx_DECREF(__pyx_t_18); __pyx_t_18 = 0;
+ __pyx_t_18 = PyNumber_InPlaceAdd(__pyx_t_5, __pyx_t_3); if (unlikely(!__pyx_t_18)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 93; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
+ __Pyx_GOTREF(__pyx_t_18);
+ __Pyx_DECREF(__pyx_t_5); __pyx_t_5 = 0;
+ __Pyx_DECREF(__pyx_t_3); __pyx_t_3 = 0;
+ __pyx_t_24 = __pyx_PyFloat_AsDouble(__pyx_t_18); if (unlikely((__pyx_t_24 == (npy_double)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 93; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
+ __Pyx_DECREF(__pyx_t_18); __pyx_t_18 = 0;
+ __pyx_v_beta_add = __pyx_t_24;
- /* "ml.pyx":94
- * beta_add = (probs[probs>=thresh]).sum()
+ /* "ml.pyx":95
+ * 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:
*/
- __pyx_t_5 = PyFloat_FromDouble(((__pyx_v_roots * log(__pyx_v_beta)) + ((__pyx_v_n_nodes - __pyx_v_roots) * log((1. - __pyx_v_beta))))); if (unlikely(!__pyx_t_5)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 94; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
- __Pyx_GOTREF(__pyx_t_5);
- __pyx_t_6 = PyNumber_InPlaceAdd(__pyx_v_beta_add, __pyx_t_5); if (unlikely(!__pyx_t_6)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 94; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
- __Pyx_GOTREF(__pyx_t_6);
- __Pyx_DECREF(__pyx_t_5); __pyx_t_5 = 0;
- __Pyx_DECREF_SET(__pyx_v_beta_add, __pyx_t_6);
- __pyx_t_6 = 0;
+ __pyx_v_beta_add = (__pyx_v_beta_add + ((__pyx_v_roots * log(__pyx_v_beta)) + ((__pyx_v_n_nodes - __pyx_v_roots) * log((1. - __pyx_v_beta)))));
- /* "ml.pyx":96
+ /* "ml.pyx":97
* beta_add += roots * log(beta) + (n_nodes-roots) * log(1. - beta)
*
* if beta_add > max_beta_add: # <<<<<<<<<<<<<<
* max_beta = beta
* max_roots = roots
*/
- __pyx_t_6 = PyObject_RichCompare(__pyx_v_beta_add, __pyx_v_max_beta_add, Py_GT); __Pyx_XGOTREF(__pyx_t_6); if (unlikely(!__pyx_t_6)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 96; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
- __pyx_t_29 = __Pyx_PyObject_IsTrue(__pyx_t_6); if (unlikely(__pyx_t_29 < 0)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 96; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
- __Pyx_DECREF(__pyx_t_6); __pyx_t_6 = 0;
+ __pyx_t_29 = ((__pyx_v_beta_add > __pyx_v_max_beta_add) != 0);
if (__pyx_t_29) {
- /* "ml.pyx":97
+ /* "ml.pyx":98
*
* if beta_add > max_beta_add:
* max_beta = beta # <<<<<<<<<<<<<<
* max_roots = roots
* max_beta_add = beta_add
*/
- __pyx_t_6 = PyFloat_FromDouble(__pyx_v_beta); if (unlikely(!__pyx_t_6)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 97; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
- __Pyx_GOTREF(__pyx_t_6);
- __Pyx_XDECREF_SET(__pyx_v_max_beta, __pyx_t_6);
- __pyx_t_6 = 0;
+ __pyx_v_max_beta = __pyx_v_beta;
- /* "ml.pyx":98
+ /* "ml.pyx":99
* if beta_add > max_beta_add:
* max_beta = beta
* max_roots = roots # <<<<<<<<<<<<<<
@@ -2878,15 +2878,14 @@ static PyObject *__pyx_pf_2ml_ml(CYTHON_UNUSED PyObject *__pyx_self, PyObject *_
*/
__pyx_v_max_roots = __pyx_v_roots;
- /* "ml.pyx":99
+ /* "ml.pyx":100
* max_beta = beta
* max_roots = roots
* max_beta_add = beta_add # <<<<<<<<<<<<<<
* # print 'beta:', max_beta, 'add:', max_beta_add, 'roots:', max_roots
*
*/
- __Pyx_INCREF(__pyx_v_beta_add);
- __Pyx_DECREF_SET(__pyx_v_max_beta_add, __pyx_v_beta_add);
+ __pyx_v_max_beta_add = __pyx_v_beta_add;
goto __pyx_L21;
}
__pyx_L21:;
@@ -2895,29 +2894,22 @@ static PyObject *__pyx_pf_2ml_ml(CYTHON_UNUSED PyObject *__pyx_self, PyObject *_
* max_beta_add = float('-inf')
* # iterate over all victim nodes to find the optimal threshold
* for beta in np.arange(0.001, .2, .002): # <<<<<<<<<<<<<<
- * thresh = log(beta/(3012*(1.-beta)))
+ * thresh = log(beta/(3012.*(1.-beta)))
* # print 'beta:', beta, 'thresh:', thresh, 'infected:', len(probs[probs>=thresh])
*/
}
__Pyx_DECREF(__pyx_t_4); __pyx_t_4 = 0;
- /* "ml.pyx":102
+ /* "ml.pyx":103
* # print 'beta:', max_beta, 'add:', max_beta_add, 'roots:', max_roots
*
* ll += max_beta_add # <<<<<<<<<<<<<<
* roots = max_roots
* beta = max_beta
*/
- __pyx_t_4 = PyFloat_FromDouble(__pyx_v_ll); if (unlikely(!__pyx_t_4)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 102; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
- __Pyx_GOTREF(__pyx_t_4);
- __pyx_t_6 = PyNumber_InPlaceAdd(__pyx_t_4, __pyx_v_max_beta_add); if (unlikely(!__pyx_t_6)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 102; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
- __Pyx_GOTREF(__pyx_t_6);
- __Pyx_DECREF(__pyx_t_4); __pyx_t_4 = 0;
- __pyx_t_24 = __pyx_PyFloat_AsDouble(__pyx_t_6); if (unlikely((__pyx_t_24 == (npy_double)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 102; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
- __Pyx_DECREF(__pyx_t_6); __pyx_t_6 = 0;
- __pyx_v_ll = __pyx_t_24;
+ __pyx_v_ll = (__pyx_v_ll + __pyx_v_max_beta_add);
- /* "ml.pyx":103
+ /* "ml.pyx":104
*
* ll += max_beta_add
* roots = max_roots # <<<<<<<<<<<<<<
@@ -2926,42 +2918,40 @@ static PyObject *__pyx_pf_2ml_ml(CYTHON_UNUSED PyObject *__pyx_self, PyObject *_
*/
__pyx_v_roots = __pyx_v_max_roots;
- /* "ml.pyx":104
+ /* "ml.pyx":105
* ll += max_beta_add
* roots = max_roots
* beta = max_beta # <<<<<<<<<<<<<<
* # print n_nodes, n_roots, n_victims, max_i, roots
* return (beta, roots, ll)
*/
- if (unlikely(!__pyx_v_max_beta)) { __Pyx_RaiseUnboundLocalError("max_beta"); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 104; __pyx_clineno = __LINE__; goto __pyx_L1_error;} }
- __pyx_t_24 = __pyx_PyFloat_AsDouble(__pyx_v_max_beta); if (unlikely((__pyx_t_24 == (npy_double)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 104; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
- __pyx_v_beta = __pyx_t_24;
+ __pyx_v_beta = __pyx_v_max_beta;
- /* "ml.pyx":106
+ /* "ml.pyx":107
* beta = max_beta
* # print n_nodes, n_roots, n_victims, max_i, roots
* return (beta, roots, ll) # <<<<<<<<<<<<<<
*/
__Pyx_XDECREF(__pyx_r);
- __pyx_t_6 = PyFloat_FromDouble(__pyx_v_beta); if (unlikely(!__pyx_t_6)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 106; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
- __Pyx_GOTREF(__pyx_t_6);
- __pyx_t_4 = __Pyx_PyInt_From_int(__pyx_v_roots); if (unlikely(!__pyx_t_4)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 106; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
+ __pyx_t_4 = PyFloat_FromDouble(__pyx_v_beta); if (unlikely(!__pyx_t_4)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 107; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_4);
- __pyx_t_5 = PyFloat_FromDouble(__pyx_v_ll); if (unlikely(!__pyx_t_5)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 106; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
- __Pyx_GOTREF(__pyx_t_5);
- __pyx_t_3 = PyTuple_New(3); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 106; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
+ __pyx_t_18 = __Pyx_PyInt_From_int(__pyx_v_roots); if (unlikely(!__pyx_t_18)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 107; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
+ __Pyx_GOTREF(__pyx_t_18);
+ __pyx_t_3 = PyFloat_FromDouble(__pyx_v_ll); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 107; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_3);
- PyTuple_SET_ITEM(__pyx_t_3, 0, __pyx_t_6);
- __Pyx_GIVEREF(__pyx_t_6);
- PyTuple_SET_ITEM(__pyx_t_3, 1, __pyx_t_4);
+ __pyx_t_5 = PyTuple_New(3); if (unlikely(!__pyx_t_5)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 107; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
+ __Pyx_GOTREF(__pyx_t_5);
+ PyTuple_SET_ITEM(__pyx_t_5, 0, __pyx_t_4);
__Pyx_GIVEREF(__pyx_t_4);
- PyTuple_SET_ITEM(__pyx_t_3, 2, __pyx_t_5);
- __Pyx_GIVEREF(__pyx_t_5);
- __pyx_t_6 = 0;
+ PyTuple_SET_ITEM(__pyx_t_5, 1, __pyx_t_18);
+ __Pyx_GIVEREF(__pyx_t_18);
+ PyTuple_SET_ITEM(__pyx_t_5, 2, __pyx_t_3);
+ __Pyx_GIVEREF(__pyx_t_3);
__pyx_t_4 = 0;
- __pyx_t_5 = 0;
- __pyx_r = __pyx_t_3;
+ __pyx_t_18 = 0;
__pyx_t_3 = 0;
+ __pyx_r = __pyx_t_5;
+ __pyx_t_5 = 0;
goto __pyx_L0;
/* "ml.pyx":38
@@ -3002,9 +2992,6 @@ static PyObject *__pyx_pf_2ml_ml(CYTHON_UNUSED PyObject *__pyx_self, PyObject *_
__Pyx_XDECREF((PyObject *)__pyx_v_probs);
__Pyx_XDECREF((PyObject *)__pyx_v_probs_fail);
__Pyx_XDECREF((PyObject *)__pyx_v_probs_nv);
- __Pyx_XDECREF(__pyx_v_max_beta_add);
- __Pyx_XDECREF(__pyx_v_beta_add);
- __Pyx_XDECREF(__pyx_v_max_beta);
__Pyx_XDECREF(__pyx_v_w1);
__Pyx_XDECREF(__pyx_v_w2);
__Pyx_XDECREF(__pyx_v_w3);
@@ -5351,7 +5338,7 @@ static int __Pyx_InitCachedConstants(void) {
* max_beta_add = float('-inf')
* # iterate over all victim nodes to find the optimal threshold
* for beta in np.arange(0.001, .2, .002): # <<<<<<<<<<<<<<
- * thresh = log(beta/(3012*(1.-beta)))
+ * thresh = log(beta/(3012.*(1.-beta)))
* # print 'beta:', beta, 'thresh:', thresh, 'infected:', len(probs[probs>=thresh])
*/
__pyx_tuple_ = PyTuple_Pack(3, __pyx_float_0_001, __pyx_float__2, __pyx_float__002); if (unlikely(!__pyx_tuple_)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 86; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
@@ -5431,7 +5418,7 @@ static int __Pyx_InitCachedConstants(void) {
* DTYPE_t alpha, DTYPE_t delta):
* cdef:
*/
- __pyx_tuple__8 = 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_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_beta_add, __pyx_n_s_thresh, __pyx_n_s_beta_add, __pyx_n_s_max_beta, __pyx_n_s_max_roots, __pyx_n_s_w1, __pyx_n_s_w2, __pyx_n_s_w3, __pyx_n_s_genexpr, __pyx_n_s_genexpr); if (unlikely(!__pyx_tuple__8)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 38; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
+ __pyx_tuple__8 = 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_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_probs_nv, __pyx_n_s_thresh, __pyx_n_s_max_roots, __pyx_n_s_w1, __pyx_n_s_w2, __pyx_n_s_w3, __pyx_n_s_genexpr, __pyx_n_s_genexpr); if (unlikely(!__pyx_tuple__8)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 38; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_tuple__8);
__Pyx_GIVEREF(__pyx_tuple__8);
__pyx_codeobj__9 = (PyObject*)__Pyx_PyCode_New(6, 0, 33, 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_ml, 38, __pyx_empty_bytes); if (unlikely(!__pyx_codeobj__9)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 38; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
@@ -6843,10 +6830,6 @@ bad:
return (double)-1;
}
-static CYTHON_INLINE void __Pyx_RaiseUnboundLocalError(const char *varname) {
- PyErr_Format(PyExc_UnboundLocalError, "local variable '%s' referenced before assignment", varname);
-}
-
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/ml.pyx b/experiments/ml.pyx
index 53e614b..5016347 100644
--- a/experiments/ml.pyx
+++ b/experiments/ml.pyx
@@ -39,7 +39,7 @@ def ml(dict root_victims, dict victims, dict non_victims, DTYPE_t age,
DTYPE_t alpha, DTYPE_t delta):
cdef:
int n_roots, n_victims, n_nodes, roots, i, dist, dt, t, l
- DTYPE_t beta, ll
+ DTYPE_t beta, ll, beta_add, max_beta, max_beta_add
list parents, failures, successes
n_roots, n_victims = len(root_victims), len(victims)
n_nodes = 148152
@@ -84,12 +84,13 @@ def ml(dict root_victims, dict victims, dict non_victims, DTYPE_t age,
max_beta_add = float('-inf')
# iterate over all victim nodes to find the optimal threshold
for beta in np.arange(0.001, .2, .002):
- thresh = log(beta/(3012*(1.-beta)))
+ thresh = log(beta/(3012.*(1.-beta)))
# print 'beta:', beta, 'thresh:', thresh, 'infected:', len(probs[probs>=thresh])
roots = n_roots + len(probs[probs<thresh])
+ beta_add = 0.
# add probability for realized edges and subtract probability these edges fail
- beta_add = (probs[probs>=thresh]).sum()
+ 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)
diff --git a/experiments/ml.so b/experiments/ml.so
index 167b2df..ba113c4 100755
--- a/experiments/ml.so
+++ b/experiments/ml.so
Binary files differ
diff --git a/experiments/ml2.c b/experiments/ml2.c
index fe1b1f6..af1134b 100644
--- a/experiments/ml2.c
+++ b/experiments/ml2.c
@@ -773,7 +773,7 @@ struct __pyx_obj_3ml2___pyx_scope_struct__ml2 {
};
-/* "ml2.pyx":62
+/* "ml2.pyx":61
* 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)) # <<<<<<<<<<<<<<
@@ -871,13 +871,6 @@ static CYTHON_INLINE PyObject* __Pyx_PyObject_GetAttrStr(PyObject* obj, PyObject
static PyObject *__Pyx_GetBuiltinName(PyObject *name);
-static CYTHON_INLINE void __Pyx_ErrRestore(PyObject *type, PyObject *value, PyObject *tb);
-static CYTHON_INLINE void __Pyx_ErrFetch(PyObject **type, PyObject **value, PyObject **tb);
-
-static void __Pyx_WriteUnraisable(const char *name, int clineno,
- int lineno, const char *filename,
- int full_traceback);
-
static void __Pyx_RaiseArgtupleInvalid(const char* func_name, int exact,
Py_ssize_t num_min, Py_ssize_t num_max, Py_ssize_t num_found);
@@ -978,6 +971,9 @@ 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 CYTHON_INLINE void __Pyx_ErrRestore(PyObject *type, PyObject *value, PyObject *tb);
+static CYTHON_INLINE void __Pyx_ErrFetch(PyObject **type, PyObject **value, PyObject **tb);
+
static void __Pyx_Raise(PyObject *type, PyObject *value, PyObject *tb, PyObject *cause);
#if PY_MAJOR_VERSION >= 3
@@ -1046,14 +1042,6 @@ static Py_ssize_t __Pyx_minusones[] = {-1, -1, -1, -1, -1, -1, -1, -1};
static PyObject *__Pyx_Import(PyObject *name, PyObject *from_list, int level);
-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);
-
static CYTHON_INLINE PyObject* __Pyx_PyInt_From_int(int value);
static CYTHON_INLINE int __Pyx_PyInt_As_int(PyObject *);
@@ -1288,14 +1276,12 @@ 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_max[] = "max";
static char __pyx_k_ml2[] = "ml2";
static char __pyx_k_sum[] = "sum";
static char __pyx_k_args[] = "args";
static char __pyx_k_beta[] = "beta";
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_test[] = "__test__";
@@ -1305,7 +1291,6 @@ static char __pyx_k_close[] = "close";
static char __pyx_k_delta[] = "delta";
static char __pyx_k_dtype[] = "dtype";
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";
@@ -1314,7 +1299,6 @@ static char __pyx_k_zeros[] = "zeros";
static char __pyx_k_import[] = "__import__";
static char __pyx_k_float64[] = "float64";
static char __pyx_k_genexpr[] = "genexpr";
-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";
@@ -1329,7 +1313,6 @@ 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_root_victims[] = "root_victims";
-static char __pyx_k_UNDERFLOW_ERROR[] = "UNDERFLOW ERROR";
static char __pyx_k_ml2_locals_genexpr[] = "ml2.<locals>.genexpr";
static char __pyx_k_ndarray_is_not_C_contiguous[] = "ndarray is not C contiguous";
static char __pyx_k_Users_ben_Documents_Cascade_Pro[] = "/Users/ben/Documents/Cascade Project/criminal_cascades/experiments/ml2.pyx";
@@ -1343,7 +1326,6 @@ static PyObject *__pyx_kp_u_Format_string_allocated_too_shor;
static PyObject *__pyx_kp_u_Format_string_allocated_too_shor_2;
static PyObject *__pyx_kp_u_Non_native_byte_order_not_suppor;
static PyObject *__pyx_n_s_RuntimeError;
-static PyObject *__pyx_kp_s_UNDERFLOW_ERROR;
static PyObject *__pyx_kp_s_Users_ben_Documents_Cascade_Pro;
static PyObject *__pyx_n_s_ValueError;
static PyObject *__pyx_n_s_age;
@@ -1355,10 +1337,8 @@ 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_genexpr;
static PyObject *__pyx_n_s_i;
@@ -1370,7 +1350,6 @@ static PyObject *__pyx_n_s_main;
static PyObject *__pyx_n_s_max;
static PyObject *__pyx_n_s_ml2;
static PyObject *__pyx_n_s_ml2_locals_genexpr;
-static PyObject *__pyx_n_s_n_nodes;
static PyObject *__pyx_n_s_n_roots;
static PyObject *__pyx_n_s_n_victims;
static PyObject *__pyx_kp_u_ndarray_is_not_C_contiguous;
@@ -1379,7 +1358,6 @@ 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;
@@ -1458,55 +1436,37 @@ static __pyx_t_3ml2_DTYPE_t __pyx_f_3ml2_weight_success(int __pyx_v_dist, int __
__pyx_t_3ml2_DTYPE_t __pyx_v_result;
__pyx_t_3ml2_DTYPE_t __pyx_r;
__Pyx_RefNannyDeclarations
- int __pyx_t_1;
- int __pyx_lineno = 0;
- const char *__pyx_filename = NULL;
- int __pyx_clineno = 0;
__Pyx_RefNannySetupContext("weight_success", 0);
/* "ml2.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) * (exp(alpha)-1.)
+ * temporal = log(exp(alpha)-1.) - alpha*dt
*/
- __pyx_v_structural = pow(__pyx_v_delta, ((__pyx_t_3ml2_DTYPE_t)__pyx_v_dist));
+ __pyx_v_structural = (__pyx_v_dist * log(__pyx_v_delta));
/* "ml2.pyx":18
- * structural = delta ** dist
+ * structural = dist * log(delta)
* # structural = plogis(w1,delta) * plogis(w2,delta) * plogis(w3,delta)
- * temporal = exp(-alpha*dt) * (exp(alpha)-1.) # <<<<<<<<<<<<<<
+ * temporal = log(exp(alpha)-1.) - alpha*dt # <<<<<<<<<<<<<<
* # temporal = 1 - exp(-alpha*dt)
- * if exp(-alpha*dt)==0.: print 'UNDERFLOW ERROR'
+ * # if exp(-alpha*dt)==0.: print 'UNDERFLOW ERROR'
*/
- __pyx_v_temporal = (exp(((-__pyx_v_alpha) * __pyx_v_dt)) * (exp(__pyx_v_alpha) - 1.));
-
- /* "ml2.pyx":20
- * temporal = exp(-alpha*dt) * (exp(alpha)-1.)
- * # temporal = 1 - exp(-alpha*dt)
- * if exp(-alpha*dt)==0.: print 'UNDERFLOW ERROR' # <<<<<<<<<<<<<<
- * # temporal = 1. / (1. + (dt - 1.)/alpha)**0.01 - 1. / (1. + dt/alpha)**0.01
- * result = log(structural * temporal)
- */
- __pyx_t_1 = ((exp(((-__pyx_v_alpha) * __pyx_v_dt)) == 0.) != 0);
- if (__pyx_t_1) {
- if (__Pyx_PrintOne(0, __pyx_kp_s_UNDERFLOW_ERROR) < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 20; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
- goto __pyx_L3;
- }
- __pyx_L3:;
+ __pyx_v_temporal = (log((exp(__pyx_v_alpha) - 1.)) - (__pyx_v_alpha * __pyx_v_dt));
/* "ml2.pyx":22
- * if exp(-alpha*dt)==0.: print 'UNDERFLOW ERROR'
+ * # if exp(-alpha*dt)==0.: print 'UNDERFLOW ERROR'
* # temporal = 1. / (1. + (dt - 1.)/alpha)**0.01 - 1. / (1. + dt/alpha)**0.01
- * result = log(structural * temporal) # <<<<<<<<<<<<<<
+ * result = structural + temporal # <<<<<<<<<<<<<<
* # print 'st', structural, temporal
* return result
*/
- __pyx_v_result = log((__pyx_v_structural * __pyx_v_temporal));
+ __pyx_v_result = (__pyx_v_structural + __pyx_v_temporal);
/* "ml2.pyx":24
- * result = log(structural * temporal)
+ * result = structural + temporal
* # print 'st', structural, temporal
* return result # <<<<<<<<<<<<<<
*
@@ -1524,9 +1484,6 @@ static __pyx_t_3ml2_DTYPE_t __pyx_f_3ml2_weight_success(int __pyx_v_dist, int __
*/
/* function exit code */
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-/* "ml2.pyx":62
+/* "ml2.pyx":61
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__Pyx_GIVEREF(__pyx_cur_scope->__pyx_outer_scope);
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return NULL;
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- if (unlikely(!__pyx_sent_value)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 62; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
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__pyx_cur_scope->__pyx_v_l = __pyx_t_1;
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- {__pyx_filename = __pyx_f[0]; __pyx_lineno = 62; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
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struct __pyx_obj_3ml2___pyx_scope_struct__ml2 *__pyx_cur_scope;
int __pyx_v_n_roots;
int __pyx_v_n_victims;
- CYTHON_UNUSED int __pyx_v_n_nodes;
int __pyx_v_roots;
int __pyx_v_i;
int __pyx_v_dist;
@@ -1928,8 +1884,8 @@ static PyObject *__pyx_pf_3ml2_ml2(CYTHON_UNUSED PyObject *__pyx_self, PyObject
* DTYPE_t beta, ll
* list parents, failures, successes
* n_roots, n_victims = len(root_victims), len(victims) # <<<<<<<<<<<<<<
- * n_nodes = 100
* cdef:
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*/
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PyErr_SetString(PyExc_TypeError, "object of type 'NoneType' has no len()");
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__pyx_v_n_roots = __pyx_t_1;
__pyx_v_n_victims = __pyx_t_2;
- /* "ml2.pyx":45
- * list parents, failures, successes
+ /* "ml2.pyx":46
* n_roots, n_victims = len(root_victims), len(victims)
- * n_nodes = 100 # <<<<<<<<<<<<<<
- * cdef:
- * np.ndarray[DTYPE_t] probs = np.zeros(n_victims, dtype=DTYPE)
- */
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- /* "ml2.pyx":47
- * n_nodes = 100
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* np.ndarray[DTYPE_t] probs_fail = np.zeros(n_victims, dtype=DTYPE)
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+ __pyx_t_3 = __Pyx_GetModuleGlobalName(__pyx_n_s_np); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 46; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
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+ __pyx_t_4 = __Pyx_PyObject_GetAttrStr(__pyx_t_3, __pyx_n_s_zeros); if (unlikely(!__pyx_t_4)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 46; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_4);
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+ __pyx_t_3 = __Pyx_PyInt_From_int(__pyx_v_n_victims); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 46; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
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PyTuple_SET_ITEM(__pyx_t_5, 0, __pyx_t_3);
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+ __pyx_t_3 = PyDict_New(); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 46; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
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+ __pyx_t_6 = __Pyx_PyObject_Call(__pyx_t_4, __pyx_t_5, __pyx_t_3); if (unlikely(!__pyx_t_6)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 46; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
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__pyx_v_probs_nv = ((PyArrayObject *)Py_None); __Pyx_INCREF(Py_None); __pyx_pybuffernd_probs_nv.rcbuffer->pybuffer.buf = NULL;
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__pyx_v_probs_nv = ((PyArrayObject *)__pyx_t_3);
__pyx_t_3 = 0;
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*
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PyErr_Format(PyExc_AttributeError, "'NoneType' object has no attribute '%s'", "itervalues");
- {__pyx_filename = __pyx_f[0]; __pyx_lineno = 52; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
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}
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+ __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 = 51; __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 = 51; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
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__pyx_t_4 = 0;
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+ /* "ml2.pyx":55
* # fail to infect it, also computes the probability that its most
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*/
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+ __pyx_t_4 = PyList_New(0); if (unlikely(!__pyx_t_4)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 55; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_4);
- /* "ml2.pyx":57
+ /* "ml2.pyx":56
* # likely parent infects it
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PyErr_SetString(PyExc_TypeError, "'NoneType' object is not iterable");
- {__pyx_filename = __pyx_f[0]; __pyx_lineno = 57; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
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for (i=0; i < 5; i++) {
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* # fail to infect it, also computes the probability that its most
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if (unlikely(__pyx_v_non_victims == Py_None)) {
PyErr_Format(PyExc_AttributeError, "'NoneType' object has no attribute '%s'", "itervalues");
- {__pyx_filename = __pyx_f[0]; __pyx_lineno = 65; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
+ {__pyx_filename = __pyx_f[0]; __pyx_lineno = 64; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
}
- __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 = 65; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
+ __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 = 64; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_5);
__Pyx_XDECREF(__pyx_t_3);
__pyx_t_3 = __pyx_t_5;
@@ -2460,25 +2407,25 @@ static PyObject *__pyx_pf_3ml2_ml2(CYTHON_UNUSED PyObject *__pyx_self, PyObject
while (1) {
__pyx_t_12 = __Pyx_dict_iter_next(__pyx_t_3, __pyx_t_2, &__pyx_t_1, NULL, &__pyx_t_5, NULL, __pyx_t_11);
if (unlikely(__pyx_t_12 == 0)) break;
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__Pyx_GOTREF(__pyx_t_5);
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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 = 64; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_XDECREF_SET(__pyx_v_parents, ((PyObject*)__pyx_t_5));
__pyx_t_5 = 0;
__pyx_v_i = __pyx_t_10;
__pyx_t_10 = (__pyx_t_10 + 1);
- /* "ml2.pyx":68
+ /* "ml2.pyx":67
* # for each non victim node, compute the probability that all its
* # parents fail to infect it
* failures = [weight_failure(dist, dt, alpha, delta, w1, w2, w3) # <<<<<<<<<<<<<<
* for (dist, dt, w1, w2, w3) in parents]
* probs_nv[i] = sum(failures)
*/
- __pyx_t_5 = PyList_New(0); if (unlikely(!__pyx_t_5)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 68; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
+ __pyx_t_5 = PyList_New(0); if (unlikely(!__pyx_t_5)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 67; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_5);
- /* "ml2.pyx":69
+ /* "ml2.pyx":68
* # parents fail to infect it
* failures = [weight_failure(dist, dt, alpha, delta, w1, w2, w3)
* for (dist, dt, w1, w2, w3) in parents] # <<<<<<<<<<<<<<
@@ -2487,15 +2434,15 @@ static PyObject *__pyx_pf_3ml2_ml2(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 = 69; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
+ {__pyx_filename = __pyx_f[0]; __pyx_lineno = 68; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
}
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for (;;) {
if (__pyx_t_13 >= PyList_GET_SIZE(__pyx_t_4)) break;
#if CYTHON_COMPILING_IN_CPYTHON
- __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 = 69; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
+ __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 = 68; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
#else
- __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 = 69; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
+ __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 = 68; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
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if ((likely(PyTuple_CheckExact(__pyx_t_6))) || (PyList_CheckExact(__pyx_t_6))) {
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@@ -2507,7 +2454,7 @@ static PyObject *__pyx_pf_3ml2_ml2(CYTHON_UNUSED PyObject *__pyx_self, PyObject
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if (size > 5) __Pyx_RaiseTooManyValuesError(5);
else if (size >= 0) __Pyx_RaiseNeedMoreValuesError(size);
- {__pyx_filename = __pyx_f[0]; __pyx_lineno = 69; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
+ {__pyx_filename = __pyx_f[0]; __pyx_lineno = 68; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
}
#if CYTHON_COMPILING_IN_CPYTHON
if (likely(PyTuple_CheckExact(sequence))) {
@@ -2533,7 +2480,7 @@ static PyObject *__pyx_pf_3ml2_ml2(CYTHON_UNUSED PyObject *__pyx_self, PyObject
Py_ssize_t i;
PyObject** temps[5] = {&__pyx_t_14,&__pyx_t_15,&__pyx_t_16,&__pyx_t_17,&__pyx_t_18};
for (i=0; i < 5; i++) {
- PyObject* item = PySequence_ITEM(sequence, i); if (unlikely(!item)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 69; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
+ PyObject* item = PySequence_ITEM(sequence, i); if (unlikely(!item)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 68; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(item);
*(temps[i]) = item;
}
@@ -2543,7 +2490,7 @@ static PyObject *__pyx_pf_3ml2_ml2(CYTHON_UNUSED PyObject *__pyx_self, PyObject
} else {
Py_ssize_t index = -1;
PyObject** temps[5] = {&__pyx_t_14,&__pyx_t_15,&__pyx_t_16,&__pyx_t_17,&__pyx_t_18};
- __pyx_t_19 = PyObject_GetIter(__pyx_t_6); if (unlikely(!__pyx_t_19)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 69; __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 = 68; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_19);
__Pyx_DECREF(__pyx_t_6); __pyx_t_6 = 0;
__pyx_t_20 = Py_TYPE(__pyx_t_19)->tp_iternext;
@@ -2552,7 +2499,7 @@ static PyObject *__pyx_pf_3ml2_ml2(CYTHON_UNUSED PyObject *__pyx_self, PyObject
__Pyx_GOTREF(item);
*(temps[index]) = item;
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- if (__Pyx_IternextUnpackEndCheck(__pyx_t_20(__pyx_t_19), 5) < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 69; __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 = 68; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__pyx_t_20 = NULL;
__Pyx_DECREF(__pyx_t_19); __pyx_t_19 = 0;
goto __pyx_L18_unpacking_done;
@@ -2560,12 +2507,12 @@ static PyObject *__pyx_pf_3ml2_ml2(CYTHON_UNUSED PyObject *__pyx_self, PyObject
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__pyx_t_20 = NULL;
if (__Pyx_IterFinish() == 0) __Pyx_RaiseNeedMoreValuesError(index);
- {__pyx_filename = __pyx_f[0]; __pyx_lineno = 69; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
+ {__pyx_filename = __pyx_f[0]; __pyx_lineno = 68; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__pyx_L18_unpacking_done:;
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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 = 68; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_DECREF(__pyx_t_14); __pyx_t_14 = 0;
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__Pyx_DECREF(__pyx_t_15); __pyx_t_15 = 0;
__pyx_v_dist = __pyx_t_12;
__pyx_v_dt = __pyx_t_26;
@@ -2576,22 +2523,22 @@ static PyObject *__pyx_pf_3ml2_ml2(CYTHON_UNUSED PyObject *__pyx_self, PyObject
__Pyx_XDECREF_SET(__pyx_v_w3, __pyx_t_18);
__pyx_t_18 = 0;
- /* "ml2.pyx":68
+ /* "ml2.pyx":67
* # for each non victim node, compute the probability that all its
* # parents fail to infect it
* failures = [weight_failure(dist, dt, alpha, delta, w1, w2, w3) # <<<<<<<<<<<<<<
* for (dist, dt, w1, w2, w3) in parents]
* probs_nv[i] = sum(failures)
*/
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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 = 67; __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 = 67; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
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- /* "ml2.pyx":69
+ /* "ml2.pyx":68
* # parents fail to infect it
* failures = [weight_failure(dist, dt, alpha, delta, w1, w2, w3)
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@@ -2605,22 +2552,22 @@ static PyObject *__pyx_pf_3ml2_ml2(CYTHON_UNUSED PyObject *__pyx_self, PyObject
__Pyx_GIVEREF(__pyx_t_5);
__pyx_t_5 = 0;
- /* "ml2.pyx":70
+ /* "ml2.pyx":69
* failures = [weight_failure(dist, dt, alpha, delta, w1, w2, w3)
* for (dist, dt, w1, w2, w3) in parents]
* probs_nv[i] = sum(failures) # <<<<<<<<<<<<<<
*
* # print successes
*/
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+ __pyx_t_5 = PyTuple_New(1); if (unlikely(!__pyx_t_5)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 69; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_5);
__Pyx_INCREF(__pyx_cur_scope->__pyx_v_failures);
PyTuple_SET_ITEM(__pyx_t_5, 0, __pyx_cur_scope->__pyx_v_failures);
__Pyx_GIVEREF(__pyx_cur_scope->__pyx_v_failures);
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+ __pyx_t_4 = __Pyx_PyObject_Call(__pyx_builtin_sum, __pyx_t_5, NULL); if (unlikely(!__pyx_t_4)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 69; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_4);
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}
__Pyx_DECREF(__pyx_t_3); __pyx_t_3 = 0;
- /* "ml2.pyx":80
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* # cdef:
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* ll += probs.sum() # add probability for realized edges and subtract probability these edges fail
*/
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__Pyx_GOTREF(__pyx_t_3);
__Pyx_DECREF(__pyx_t_4); __pyx_t_4 = 0;
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{&__pyx_n_s_enumerate, __pyx_k_enumerate, sizeof(__pyx_k_enumerate), 0, 0, 1, 1},
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{&__pyx_n_s_ml2_locals_genexpr, __pyx_k_ml2_locals_genexpr, sizeof(__pyx_k_ml2_locals_genexpr), 0, 0, 1, 1},
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{&__pyx_n_s_probs, __pyx_k_probs, sizeof(__pyx_k_probs), 0, 0, 1, 1},
{&__pyx_n_s_probs_fail, __pyx_k_probs_fail, sizeof(__pyx_k_probs_fail), 0, 0, 1, 1},
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__pyx_ptype_3ml2___pyx_scope_struct_1_genexpr = &__pyx_type_3ml2___pyx_scope_struct_1_genexpr;
/*--- Type import code ---*/
@@ -5459,64 +5401,6 @@ static PyObject *__Pyx_GetBuiltinName(PyObject *name) {
return result;
}
-static CYTHON_INLINE void __Pyx_ErrRestore(PyObject *type, PyObject *value, PyObject *tb) {
-#if CYTHON_COMPILING_IN_CPYTHON
- PyObject *tmp_type, *tmp_value, *tmp_tb;
- PyThreadState *tstate = PyThreadState_GET();
- tmp_type = tstate->curexc_type;
- tmp_value = tstate->curexc_value;
- tmp_tb = tstate->curexc_traceback;
- tstate->curexc_type = type;
- tstate->curexc_value = value;
- tstate->curexc_traceback = tb;
- Py_XDECREF(tmp_type);
- Py_XDECREF(tmp_value);
- Py_XDECREF(tmp_tb);
-#else
- PyErr_Restore(type, value, tb);
-#endif
-}
-static CYTHON_INLINE void __Pyx_ErrFetch(PyObject **type, PyObject **value, PyObject **tb) {
-#if CYTHON_COMPILING_IN_CPYTHON
- PyThreadState *tstate = PyThreadState_GET();
- *type = tstate->curexc_type;
- *value = tstate->curexc_value;
- *tb = tstate->curexc_traceback;
- tstate->curexc_type = 0;
- tstate->curexc_value = 0;
- tstate->curexc_traceback = 0;
-#else
- PyErr_Fetch(type, value, tb);
-#endif
-}
-
-static void __Pyx_WriteUnraisable(const char *name, CYTHON_UNUSED int clineno,
- CYTHON_UNUSED int lineno, CYTHON_UNUSED const char *filename,
- int full_traceback) {
- PyObject *old_exc, *old_val, *old_tb;
- PyObject *ctx;
- __Pyx_ErrFetch(&old_exc, &old_val, &old_tb);
- if (full_traceback) {
- Py_XINCREF(old_exc);
- Py_XINCREF(old_val);
- Py_XINCREF(old_tb);
- __Pyx_ErrRestore(old_exc, old_val, old_tb);
- PyErr_PrintEx(1);
- }
- #if PY_MAJOR_VERSION < 3
- ctx = PyString_FromString(name);
- #else
- ctx = PyUnicode_FromString(name);
- #endif
- __Pyx_ErrRestore(old_exc, old_val, old_tb);
- if (!ctx) {
- PyErr_WriteUnraisable(Py_None);
- } else {
- PyErr_WriteUnraisable(ctx);
- Py_DECREF(ctx);
- }
-}
-
static void __Pyx_RaiseArgtupleInvalid(
const char* func_name,
int exact,
@@ -6656,6 +6540,37 @@ static CYTHON_INLINE int __Pyx_dict_iter_next(PyObject* iter_obj, Py_ssize_t ori
return 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;
+ PyThreadState *tstate = PyThreadState_GET();
+ tmp_type = tstate->curexc_type;
+ tmp_value = tstate->curexc_value;
+ tmp_tb = tstate->curexc_traceback;
+ tstate->curexc_type = type;
+ tstate->curexc_value = value;
+ tstate->curexc_traceback = tb;
+ Py_XDECREF(tmp_type);
+ Py_XDECREF(tmp_value);
+ Py_XDECREF(tmp_tb);
+#else
+ PyErr_Restore(type, value, tb);
+#endif
+}
+static CYTHON_INLINE void __Pyx_ErrFetch(PyObject **type, PyObject **value, PyObject **tb) {
+#if CYTHON_COMPILING_IN_CPYTHON
+ PyThreadState *tstate = PyThreadState_GET();
+ *type = tstate->curexc_type;
+ *value = tstate->curexc_value;
+ *tb = tstate->curexc_traceback;
+ tstate->curexc_type = 0;
+ tstate->curexc_value = 0;
+ tstate->curexc_traceback = 0;
+#else
+ PyErr_Fetch(type, value, tb);
+#endif
+}
+
#if PY_MAJOR_VERSION < 3
static void __Pyx_Raise(PyObject *type, PyObject *value, PyObject *tb,
CYTHON_UNUSED PyObject *cause) {
@@ -7066,147 +6981,6 @@ bad:
return module;
}
-#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
-
static CYTHON_INLINE PyObject* __Pyx_PyInt_From_int(int value) {
const int neg_one = (int) -1, const_zero = 0;
const int is_unsigned = neg_one > const_zero;
diff --git a/experiments/ml2.pyx b/experiments/ml2.pyx
index 9edc7e6..8974106 100644
--- a/experiments/ml2.pyx
+++ b/experiments/ml2.pyx
@@ -13,13 +13,13 @@ cdef DTYPE_t weight_success(int dist, int dt, DTYPE_t alpha, DTYPE_t delta,
DTYPE_t w1, DTYPE_t w2, DTYPE_t w3):
"""weight for successful infection, exponential time model"""
cdef DTYPE_t structural, temporal, result
- structural = delta ** dist
+ structural = dist * log(delta)
# structural = plogis(w1,delta) * plogis(w2,delta) * plogis(w3,delta)
- temporal = exp(-alpha*dt) * (exp(alpha)-1.)
+ temporal = log(exp(alpha)-1.) - alpha*dt
# temporal = 1 - exp(-alpha*dt)
- if exp(-alpha*dt)==0.: print 'UNDERFLOW ERROR'
+ # if exp(-alpha*dt)==0.: print 'UNDERFLOW ERROR'
# temporal = 1. / (1. + (dt - 1.)/alpha)**0.01 - 1. / (1. + dt/alpha)**0.01
- result = log(structural * temporal)
+ result = structural + temporal
# print 'st', structural, temporal
return result
@@ -59,6 +59,7 @@ def ml2(dict root_victims, dict victims, dict non_victims, DTYPE_t age,
for (dist, dt, w1, w2, w3) in parents]
# find parent that maximizes log(p) - log(\tilde{p})
probs[i] = max(s - failures[l] for l, s in enumerate(successes))
+ probs_data[i] =
# loop through non-victims
for i, parents in enumerate(non_victims.itervalues()):
diff --git a/experiments/ml2.so b/experiments/ml2.so
index b8dc4b6..af3b3f9 100755
--- a/experiments/ml2.so
+++ b/experiments/ml2.so
Binary files differ
diff --git a/experiments/out.log b/experiments/out.log
index faa96dd..3af5280 100644
--- a/experiments/out.log
+++ b/experiments/out.log
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+0.1 0.0615848211066 0.0 6465 -254454.526891
+0.1 0.1 0.0 6465 -256829.328482
diff --git a/experiments/process.py b/experiments/process.py
index d01b3fd..330a49e 100644
--- a/experiments/process.py
+++ b/experiments/process.py
@@ -12,13 +12,13 @@ if __name__ == "__main__":
sys.exit("usage: {0} <file>".format(sys.argv[0]))
root_victims, victims, non_victims, age = load(open(sys.argv[1]))
- alphas = np.arange(10., 30., 3.) # parameter of the time component
- # alphas = np.logspace(0,2,num=10)
- # deltas = np.arange(0.005, 0.5, 0.005) # parameter of the structural component
- deltas = np.logspace(-4,-2,num=5)
+ # alphas = np.arange(5e-4, 3e-3, 1e-4) # parameter of the time component
+ alphas = np.logspace(-5,-1,num=20)
+ # deltas = np.arange(0.03, 0.1, 0.005) # parameter of the structural component
+ deltas = np.logspace(-5,-1,num=20)
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)
+ beta, roots, ll = ml2(root_victims, victims, non_victims, age, alpha, delta)
print "\t".join(map(str, [alpha, delta, beta, roots, ll]))
fh.write("\t".join(map(str, [alpha, delta, beta, roots, ll])) + "\n")
fh.flush()
generated by cgit v1.2.3-70-g09d2 (git 2.52.0) at 2025-12-21 18:09:02 +0000