diff options
Diffstat (limited to 'experiments/ml.c')
| -rw-r--r-- | experiments/ml.c | 203 |
1 files changed, 93 insertions, 110 deletions
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); 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{__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]; 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