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Click on a line that starts with a "+" to see the C code that Cython generated for it.
Raw output: _core.c
+001: # cython: boundscheck=False, wraparound=False, cdivision=True, language_level=3
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002: # cython: nonecheck=False, initializedcheck=False
003: """
004: Cython extensions for mfe.realized hot paths.
005:
006: Functions
007: ---------
008: _autocovariance_sum RK kernel inner loop
009: _bpv_sum BPV skip-k inner loop
010: _medvar_triplets MedRV median-of-three per triplet
011: _hy_sweep Hayashi-Yoshida O((N1+N2)log(N1+N2)) estimator
012: _refresh_time_indices Refresh-time index computation
013: """
014:
+015: import numpy as np
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016: cimport numpy as np
017: from numpy cimport ndarray, float64_t, int64_t
018: from libc.math cimport fabs, sqrt, log
019:
020:
021: # ────────────────────────────────────────────────────────────────────────────
022: # 1. Autocovariance (realized kernel inner loop)
023: # ────────────────────────────────────────────────────────────────────────────
024:
+025: def _autocovariance_sum(double[::1] returns, int H):
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026: """gamma[h] = sum_{t=h}^{T-1} r[t]*r[t-h], h=0..H"""
+027: cdef int T = returns.shape[0], h, t
__pyx_v_T = (__pyx_v_returns.shape[0]);
028: cdef double acc
029:
+030: gamma_arr = np.zeros(H + 1, dtype=np.float64)
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+031: cdef double[::1] g = gamma_arr
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033:
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038:
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+043: g[h] = acc
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044:
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046:
047:
048: # ────────────────────────────────────────────────────────────────────────────
049: # 2. BPV sum
050: # ────────────────────────────────────────────────────────────────────────────
051:
+052: def _bpv_sum(double[::1] abs_returns, int skip):
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__Pyx_NumKwargs_FASTCALL(__pyx_kwds) : 0; if (unlikely(__pyx_kwds_len < 0)) __PYX_ERR(0, 52, __pyx_L3_error) if (__pyx_kwds_len > 0) { switch (__pyx_nargs) { case 2: values[1] = __Pyx_ArgRef_FASTCALL(__pyx_args, 1); if (!CYTHON_ASSUME_SAFE_MACROS && unlikely(!values[1])) __PYX_ERR(0, 52, __pyx_L3_error) CYTHON_FALLTHROUGH; case 1: values[0] = __Pyx_ArgRef_FASTCALL(__pyx_args, 0); if (!CYTHON_ASSUME_SAFE_MACROS && unlikely(!values[0])) __PYX_ERR(0, 52, __pyx_L3_error) CYTHON_FALLTHROUGH; case 0: break; default: goto __pyx_L5_argtuple_error; } const Py_ssize_t kwd_pos_args = __pyx_nargs; if (__Pyx_ParseKeywords(__pyx_kwds, __pyx_kwvalues, __pyx_pyargnames, 0, values, kwd_pos_args, __pyx_kwds_len, "_bpv_sum", 0) < (0)) __PYX_ERR(0, 52, __pyx_L3_error) for (Py_ssize_t i = __pyx_nargs; i < 2; i++) { if (unlikely(!values[i])) { __Pyx_RaiseArgtupleInvalid("_bpv_sum", 1, 2, 2, i); __PYX_ERR(0, 52, __pyx_L3_error) } } } else if (unlikely(__pyx_nargs != 2)) { goto __pyx_L5_argtuple_error; } else { values[0] = __Pyx_ArgRef_FASTCALL(__pyx_args, 0); if (!CYTHON_ASSUME_SAFE_MACROS && unlikely(!values[0])) __PYX_ERR(0, 52, __pyx_L3_error) values[1] = __Pyx_ArgRef_FASTCALL(__pyx_args, 1); if (!CYTHON_ASSUME_SAFE_MACROS && unlikely(!values[1])) __PYX_ERR(0, 52, __pyx_L3_error) } __pyx_v_abs_returns = __Pyx_PyObject_to_MemoryviewSlice_dc_double(values[0], PyBUF_WRITABLE); if (unlikely(!__pyx_v_abs_returns.memview)) __PYX_ERR(0, 52, __pyx_L3_error) __pyx_v_skip = __Pyx_PyLong_As_int(values[1]); if (unlikely((__pyx_v_skip == (int)-1) && PyErr_Occurred())) __PYX_ERR(0, 52, __pyx_L3_error) } goto __pyx_L6_skip; __pyx_L5_argtuple_error:; __Pyx_RaiseArgtupleInvalid("_bpv_sum", 1, 2, 2, __pyx_nargs); __PYX_ERR(0, 52, __pyx_L3_error) __pyx_L6_skip:; goto __pyx_L4_argument_unpacking_done; __pyx_L3_error:; for (Py_ssize_t __pyx_temp=0; __pyx_temp < (Py_ssize_t)(sizeof(values)/sizeof(values[0])); ++__pyx_temp) { Py_XDECREF(values[__pyx_temp]); } __PYX_XCLEAR_MEMVIEW(&__pyx_v_abs_returns, 1); __Pyx_AddTraceback("mfe.realized._core._bpv_sum", __pyx_clineno, __pyx_lineno, __pyx_filename); __Pyx_RefNannyFinishContext(); return NULL; __pyx_L4_argument_unpacking_done:; __pyx_r = __pyx_pf_3mfe_8realized_5_core_2_bpv_sum(__pyx_self, __pyx_v_abs_returns, __pyx_v_skip); int __pyx_lineno = 0; const char *__pyx_filename = NULL; int __pyx_clineno = 0; /* function exit code */ for (Py_ssize_t __pyx_temp=0; __pyx_temp < (Py_ssize_t)(sizeof(values)/sizeof(values[0])); ++__pyx_temp) { Py_XDECREF(values[__pyx_temp]); } __PYX_XCLEAR_MEMVIEW(&__pyx_v_abs_returns, 1); __Pyx_RefNannyFinishContext(); return __pyx_r; } static PyObject *__pyx_pf_3mfe_8realized_5_core_2_bpv_sum(CYTHON_UNUSED PyObject *__pyx_self, __Pyx_memviewslice __pyx_v_abs_returns, int __pyx_v_skip) { int __pyx_v_T; int __pyx_v_t; int __pyx_v_gap; double __pyx_v_acc; __Pyx_memviewslice __pyx_v_a = { 0, 0, { 0 }, { 0 }, { 0 } }; PyObject *__pyx_r = NULL; /* … */ /* function exit code */ __pyx_L1_error:; __Pyx_XDECREF(__pyx_t_6); __Pyx_AddTraceback("mfe.realized._core._bpv_sum", __pyx_clineno, __pyx_lineno, __pyx_filename); __pyx_r = NULL; __pyx_L0:; __PYX_XCLEAR_MEMVIEW(&__pyx_v_a, 1); __Pyx_XGIVEREF(__pyx_r); __Pyx_RefNannyFinishContext(); return __pyx_r; } /* … */ __pyx_t_4 = __Pyx_CyFunction_New(&__pyx_mdef_3mfe_8realized_5_core_3_bpv_sum, 0, __pyx_mstate_global->__pyx_n_u_bpv_sum, NULL, __pyx_mstate_global->__pyx_n_u_mfe_realized__core, __pyx_mstate_global->__pyx_d, ((PyObject *)__pyx_mstate_global->__pyx_codeobj_tab[4])); if (unlikely(!__pyx_t_4)) __PYX_ERR(0, 52, __pyx_L1_error) __Pyx_GOTREF(__pyx_t_4); #if CYTHON_COMPILING_IN_CPYTHON && PY_VERSION_HEX >= 0x030E0000 PyUnstable_Object_EnableDeferredRefcount(__pyx_t_4); #endif if (PyDict_SetItem(__pyx_mstate_global->__pyx_d, __pyx_mstate_global->__pyx_n_u_bpv_sum, __pyx_t_4) < (0)) __PYX_ERR(0, 52, __pyx_L1_error) __Pyx_DECREF(__pyx_t_4); __pyx_t_4 = 0;
053: """sum_{t=skip+1}^{T-1} |r[t]| * |r[t-skip-1]|"""
+054: cdef int T = abs_returns.shape[0], t, gap = skip + 1
__pyx_v_T = (__pyx_v_abs_returns.shape[0]); __pyx_v_gap = (__pyx_v_skip + 1);
+055: cdef double acc = 0.0
__pyx_v_acc = 0.0;
+056: cdef double[::1] a = abs_returns
__PYX_INC_MEMVIEW(&__pyx_v_abs_returns, 1); __pyx_v_a = __pyx_v_abs_returns;
+057: for t in range(gap, T):
__pyx_t_1 = __pyx_v_T;
__pyx_t_2 = __pyx_t_1;
for (__pyx_t_3 = __pyx_v_gap; __pyx_t_3 < __pyx_t_2; __pyx_t_3+=1) {
__pyx_v_t = __pyx_t_3;
+058: acc += a[t] * a[t - gap]
__pyx_t_4 = __pyx_v_t;
__pyx_t_5 = (__pyx_v_t - __pyx_v_gap);
__pyx_v_acc = (__pyx_v_acc + ((*((double *) ( /* dim=0 */ ((char *) (((double *) __pyx_v_a.data) + __pyx_t_4)) ))) * (*((double *) ( /* dim=0 */ ((char *) (((double *) __pyx_v_a.data) + __pyx_t_5)) )))));
}
+059: return acc
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060:
061:
062: # ────────────────────────────────────────────────────────────────────────────
063: # 3. MedRV triplet sum
064: # ────────────────────────────────────────────────────────────────────────────
065:
+066: cdef inline double _median3(double a, double b, double c) nogil:
static CYTHON_INLINE double __pyx_f_3mfe_8realized_5_core__median3(double __pyx_v_a, double __pyx_v_b, double __pyx_v_c) {
double __pyx_r;
/* … */
/* function exit code */
__pyx_L0:;
return __pyx_r;
}
067: """Branchless median of three values."""
+068: if a > b:
__pyx_t_1 = (__pyx_v_a > __pyx_v_b);
if (__pyx_t_1) {
/* … */
}
+069: a, b = b, a
__pyx_t_2 = __pyx_v_b;
__pyx_t_3 = __pyx_v_a;
__pyx_v_a = __pyx_t_2;
__pyx_v_b = __pyx_t_3;
+070: if b > c:
__pyx_t_1 = (__pyx_v_b > __pyx_v_c);
if (__pyx_t_1) {
/* … */
}
+071: b, c = c, b
__pyx_t_3 = __pyx_v_c;
__pyx_t_2 = __pyx_v_b;
__pyx_v_b = __pyx_t_3;
__pyx_v_c = __pyx_t_2;
+072: if a > b:
__pyx_t_1 = (__pyx_v_a > __pyx_v_b);
if (__pyx_t_1) {
/* … */
}
+073: b = a
__pyx_v_b = __pyx_v_a;
+074: return b
{
__pyx_r = __pyx_v_b;
}
goto __pyx_L0;
075:
+076: def _medvar_triplets(double[::1] abs_returns):
/* Python wrapper */ static PyObject *__pyx_pw_3mfe_8realized_5_core_5_medvar_triplets(PyObject *__pyx_self, #if CYTHON_VECTORCALL PyObject *const *__pyx_args, Py_ssize_t __pyx_nargs, PyObject *__pyx_kwds #else PyObject *__pyx_args, PyObject *__pyx_kwds #endif ); /*proto*/ PyDoc_STRVAR(__pyx_doc_3mfe_8realized_5_core_4_medvar_triplets, "sum_{t=1}^{T-2} median(|r[t-1]|, |r[t]|, |r[t+1]|)^2"); static PyMethodDef __pyx_mdef_3mfe_8realized_5_core_5_medvar_triplets = {"_medvar_triplets", (PyCFunction)(void(*)(void))(__Pyx_PyCFunction_FastCallWithKeywords)__pyx_pw_3mfe_8realized_5_core_5_medvar_triplets, __Pyx_METH_FASTCALL|METH_KEYWORDS, __pyx_doc_3mfe_8realized_5_core_4_medvar_triplets}; static PyObject *__pyx_pw_3mfe_8realized_5_core_5_medvar_triplets(PyObject *__pyx_self, #if CYTHON_VECTORCALL PyObject *const *__pyx_args, Py_ssize_t __pyx_nargs, PyObject *__pyx_kwds #else PyObject *__pyx_args, PyObject *__pyx_kwds #endif ) { __Pyx_memviewslice __pyx_v_abs_returns = { 0, 0, { 0 }, { 0 }, { 0 } }; #if !CYTHON_VECTORCALL CYTHON_UNUSED Py_ssize_t __pyx_nargs; #endif CYTHON_UNUSED PyObject *const *__pyx_kwvalues; PyObject *__pyx_r = 0; __Pyx_RefNannyDeclarations __Pyx_RefNannySetupContext("_medvar_triplets (wrapper)", 0); #if !CYTHON_VECTORCALL #if CYTHON_ASSUME_SAFE_SIZE __pyx_nargs = PyTuple_GET_SIZE(__pyx_args); #else __pyx_nargs = PyTuple_Size(__pyx_args); if (unlikely(__pyx_nargs < 0)) return NULL; #endif #endif __pyx_kwvalues = __Pyx_KwValues_FASTCALL(__pyx_args, __pyx_nargs); { PyObject ** const __pyx_pyargnames[] = {&__pyx_mstate_global->__pyx_n_u_abs_returns,0}; PyObject* values[1] = {0}; const Py_ssize_t __pyx_kwds_len = (__pyx_kwds) ? __Pyx_NumKwargs_FASTCALL(__pyx_kwds) : 0; if (unlikely(__pyx_kwds_len < 0)) __PYX_ERR(0, 76, __pyx_L3_error) if (__pyx_kwds_len > 0) { switch (__pyx_nargs) { case 1: values[0] = __Pyx_ArgRef_FASTCALL(__pyx_args, 0); if (!CYTHON_ASSUME_SAFE_MACROS && unlikely(!values[0])) __PYX_ERR(0, 76, __pyx_L3_error) CYTHON_FALLTHROUGH; case 0: break; default: goto __pyx_L5_argtuple_error; } const Py_ssize_t kwd_pos_args = __pyx_nargs; if (__Pyx_ParseKeywords(__pyx_kwds, __pyx_kwvalues, __pyx_pyargnames, 0, values, kwd_pos_args, __pyx_kwds_len, "_medvar_triplets", 0) < (0)) __PYX_ERR(0, 76, __pyx_L3_error) for (Py_ssize_t i = __pyx_nargs; i < 1; i++) { if (unlikely(!values[i])) { __Pyx_RaiseArgtupleInvalid("_medvar_triplets", 1, 1, 1, i); __PYX_ERR(0, 76, __pyx_L3_error) } } } else if (unlikely(__pyx_nargs != 1)) { goto __pyx_L5_argtuple_error; } else { values[0] = __Pyx_ArgRef_FASTCALL(__pyx_args, 0); if (!CYTHON_ASSUME_SAFE_MACROS && unlikely(!values[0])) __PYX_ERR(0, 76, __pyx_L3_error) } __pyx_v_abs_returns = __Pyx_PyObject_to_MemoryviewSlice_dc_double(values[0], PyBUF_WRITABLE); if (unlikely(!__pyx_v_abs_returns.memview)) __PYX_ERR(0, 76, __pyx_L3_error) } goto __pyx_L6_skip; __pyx_L5_argtuple_error:; __Pyx_RaiseArgtupleInvalid("_medvar_triplets", 1, 1, 1, __pyx_nargs); __PYX_ERR(0, 76, __pyx_L3_error) __pyx_L6_skip:; goto __pyx_L4_argument_unpacking_done; __pyx_L3_error:; for (Py_ssize_t __pyx_temp=0; __pyx_temp < (Py_ssize_t)(sizeof(values)/sizeof(values[0])); ++__pyx_temp) { Py_XDECREF(values[__pyx_temp]); } __PYX_XCLEAR_MEMVIEW(&__pyx_v_abs_returns, 1); __Pyx_AddTraceback("mfe.realized._core._medvar_triplets", __pyx_clineno, __pyx_lineno, __pyx_filename); __Pyx_RefNannyFinishContext(); return NULL; __pyx_L4_argument_unpacking_done:; __pyx_r = __pyx_pf_3mfe_8realized_5_core_4_medvar_triplets(__pyx_self, __pyx_v_abs_returns); int __pyx_lineno = 0; const char *__pyx_filename = NULL; int __pyx_clineno = 0; /* function exit code */ for (Py_ssize_t __pyx_temp=0; __pyx_temp < (Py_ssize_t)(sizeof(values)/sizeof(values[0])); ++__pyx_temp) { Py_XDECREF(values[__pyx_temp]); } __PYX_XCLEAR_MEMVIEW(&__pyx_v_abs_returns, 1); __Pyx_RefNannyFinishContext(); return __pyx_r; } static PyObject *__pyx_pf_3mfe_8realized_5_core_4_medvar_triplets(CYTHON_UNUSED PyObject *__pyx_self, __Pyx_memviewslice __pyx_v_abs_returns) { int __pyx_v_T; int __pyx_v_t; double __pyx_v_med; double __pyx_v_acc; __Pyx_memviewslice __pyx_v_a = { 0, 0, { 0 }, { 0 }, { 0 } }; PyObject *__pyx_r = NULL; /* … */ /* function exit code */ __pyx_L1_error:; __Pyx_XDECREF(__pyx_t_8); __Pyx_AddTraceback("mfe.realized._core._medvar_triplets", __pyx_clineno, __pyx_lineno, __pyx_filename); __pyx_r = NULL; __pyx_L0:; __PYX_XCLEAR_MEMVIEW(&__pyx_v_a, 1); __Pyx_XGIVEREF(__pyx_r); __Pyx_RefNannyFinishContext(); return __pyx_r; } /* … */ __pyx_t_4 = __Pyx_CyFunction_New(&__pyx_mdef_3mfe_8realized_5_core_5_medvar_triplets, 0, __pyx_mstate_global->__pyx_n_u_medvar_triplets, NULL, __pyx_mstate_global->__pyx_n_u_mfe_realized__core, __pyx_mstate_global->__pyx_d, ((PyObject *)__pyx_mstate_global->__pyx_codeobj_tab[5])); if (unlikely(!__pyx_t_4)) __PYX_ERR(0, 76, __pyx_L1_error) __Pyx_GOTREF(__pyx_t_4); #if CYTHON_COMPILING_IN_CPYTHON && PY_VERSION_HEX >= 0x030E0000 PyUnstable_Object_EnableDeferredRefcount(__pyx_t_4); #endif if (PyDict_SetItem(__pyx_mstate_global->__pyx_d, __pyx_mstate_global->__pyx_n_u_medvar_triplets, __pyx_t_4) < (0)) __PYX_ERR(0, 76, __pyx_L1_error) __Pyx_DECREF(__pyx_t_4); __pyx_t_4 = 0;
077: """sum_{t=1}^{T-2} median(|r[t-1]|, |r[t]|, |r[t+1]|)^2"""
+078: cdef int T = abs_returns.shape[0], t
__pyx_v_T = (__pyx_v_abs_returns.shape[0]);
+079: cdef double med, acc = 0.0
__pyx_v_acc = 0.0;
+080: cdef double[::1] a = abs_returns
__PYX_INC_MEMVIEW(&__pyx_v_abs_returns, 1); __pyx_v_a = __pyx_v_abs_returns;
+081: for t in range(1, T - 1):
__pyx_t_1 = (__pyx_v_T - 1);
__pyx_t_2 = __pyx_t_1;
for (__pyx_t_3 = 1; __pyx_t_3 < __pyx_t_2; __pyx_t_3+=1) {
__pyx_v_t = __pyx_t_3;
+082: med = _median3(a[t - 1], a[t], a[t + 1])
__pyx_t_4 = (__pyx_v_t - 1);
__pyx_t_5 = __pyx_v_t;
__pyx_t_6 = (__pyx_v_t + 1);
__pyx_t_7 = __pyx_f_3mfe_8realized_5_core__median3((*((double *) ( /* dim=0 */ ((char *) (((double *) __pyx_v_a.data) + __pyx_t_4)) ))), (*((double *) ( /* dim=0 */ ((char *) (((double *) __pyx_v_a.data) + __pyx_t_5)) ))), (*((double *) ( /* dim=0 */ ((char *) (((double *) __pyx_v_a.data) + __pyx_t_6)) )))); if (unlikely(__pyx_t_7 == ((double)-1) && PyErr_Occurred())) __PYX_ERR(0, 82, __pyx_L1_error)
__pyx_v_med = __pyx_t_7;
+083: acc += med * med
__pyx_v_acc = (__pyx_v_acc + (__pyx_v_med * __pyx_v_med)); }
+084: return acc
__pyx_t_8 = PyFloat_FromDouble(__pyx_v_acc); if (unlikely(!__pyx_t_8)) __PYX_ERR(0, 84, __pyx_L1_error) __Pyx_GOTREF(__pyx_t_8); { PyObject *__pyx_temp; { __pyx_temp = __pyx_r; __pyx_r = __pyx_t_8; } __Pyx_XDECREF(__pyx_temp); } __pyx_t_8 = 0; goto __pyx_L0;
085:
086:
087: # ────────────────────────────────────────────────────────────────────────────
088: # 4. Hayashi-Yoshida sweep-line O((N1+N2)*k) where k = avg open r1 count
089: # ────────────────────────────────────────────────────────────────────────────
090:
+091: def _hy_sweep(
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092: double[::1] r1, double[::1] a1, double[::1] b1,
093: double[::1] r2, double[::1] a2, double[::1] b2,
094: ):
095: """
096: Hayashi-Yoshida estimator via event sweep with swap-remove open-list.
097:
098: Correctness: when r2[t] opens, we add r2[t] to ALL currently-open r1
099: accumulators. This correctly handles r2 intervals that both open and
100: close while r1[s] is active.
101:
102: Complexity: O((N1+N2)*log(N1+N2)) for sort + O((N1+N2)*k_open) for sweep,
103: where k_open = max simultaneous open r1 intervals.
104: For typical HFT data (intervals << trading day) k_open ~ O(1).
105:
106: The open_list uses swap-remove for O(1) deletion.
107: """
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137: # Compact open-list for O(1) swap-remove
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+141: cdef int[::1] open_pos = open_pos_arr
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+142: is_open_arr = np.zeros(N1, dtype=np.int32)
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+143: cdef int[::1] is_open = is_open_arr
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144:
+145: cdef double total = 0.0, rv2, active_r2_sum = 0.0
__pyx_v_total = 0.0; __pyx_v_active_r2_sum = 0.0;
146: cdef int last_pos, last_idx
147:
+148: for ev in range(n_events):
__pyx_t_10 = __pyx_v_n_events;
__pyx_t_11 = __pyx_t_10;
for (__pyx_t_12 = 0; __pyx_t_12 < __pyx_t_11; __pyx_t_12+=1) {
__pyx_v_ev = __pyx_t_12;
+149: idx = ev_idx[ord_v[ev]]
__pyx_t_13 = __pyx_v_ev;
__pyx_t_16 = (*((__pyx_t_5numpy_int64_t *) ( /* dim=0 */ ((char *) (((__pyx_t_5numpy_int64_t *) __pyx_v_ord_v.data) + __pyx_t_13)) )));
__pyx_v_idx = (*((int *) ( /* dim=0 */ ((char *) (((int *) __pyx_v_ev_idx.data) + __pyx_t_16)) )));
+150: etype = ev_type[ord_v[ev]]
__pyx_t_13 = __pyx_v_ev;
__pyx_t_16 = (*((__pyx_t_5numpy_int64_t *) ( /* dim=0 */ ((char *) (((__pyx_t_5numpy_int64_t *) __pyx_v_ord_v.data) + __pyx_t_13)) )));
__pyx_v_etype = (*((int *) ( /* dim=0 */ ((char *) (((int *) __pyx_v_ev_type.data) + __pyx_t_16)) )));
151:
+152: if etype == 0:
switch (__pyx_v_etype) {
case 0:
/* … */
break;
case 1:
153: # r2[idx] opens: (1) track active sum; (2) add to all open r1
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__pyx_t_13 = __pyx_v_idx;
__pyx_v_rv2 = (*((double *) ( /* dim=0 */ ((char *) (((double *) __pyx_v_r2.data) + __pyx_t_13)) )));
+155: active_r2_sum += rv2
__pyx_v_active_r2_sum = (__pyx_v_active_r2_sum + __pyx_v_rv2);
+156: for j in range(n_open):
__pyx_t_17 = __pyx_v_n_open;
__pyx_t_18 = __pyx_t_17;
for (__pyx_t_19 = 0; __pyx_t_19 < __pyx_t_18; __pyx_t_19+=1) {
__pyx_v_j = __pyx_t_19;
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__pyx_t_13 = __pyx_v_j;
__pyx_t_14 = (*((int *) ( /* dim=0 */ ((char *) (((int *) __pyx_v_open_list.data) + __pyx_t_13)) )));
*((double *) ( /* dim=0 */ ((char *) (((double *) __pyx_v_r1_accum.data) + __pyx_t_14)) )) += __pyx_v_rv2;
}
158:
+159: elif etype == 1:
break;
case 2:
160: # r1[idx] opens: seed accumulator with r2 already active, then add to open list
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__pyx_t_13 = __pyx_v_idx;
*((double *) ( /* dim=0 */ ((char *) (((double *) __pyx_v_r1_accum.data) + __pyx_t_13)) )) = __pyx_v_active_r2_sum;
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__pyx_t_13 = __pyx_v_idx;
*((int *) ( /* dim=0 */ ((char *) (((int *) __pyx_v_open_pos.data) + __pyx_t_13)) )) = __pyx_v_n_open;
+163: open_list[n_open] = idx
__pyx_t_13 = __pyx_v_n_open;
*((int *) ( /* dim=0 */ ((char *) (((int *) __pyx_v_open_list.data) + __pyx_t_13)) )) = __pyx_v_idx;
+164: is_open[idx] = 1
__pyx_t_13 = __pyx_v_idx;
*((int *) ( /* dim=0 */ ((char *) (((int *) __pyx_v_is_open.data) + __pyx_t_13)) )) = 1;
+165: n_open += 1
__pyx_v_n_open = (__pyx_v_n_open + 1);
166:
+167: elif etype == 2:
break;
default:
168: # r1[idx] closes: finalize, swap-remove from open list
+169: if is_open[idx]:
__pyx_t_13 = __pyx_v_idx;
__pyx_t_20 = ((*((int *) ( /* dim=0 */ ((char *) (((int *) __pyx_v_is_open.data) + __pyx_t_13)) ))) != 0);
if (__pyx_t_20) {
/* … */
}
+170: total += r1[idx] * r1_accum[idx]
__pyx_t_13 = __pyx_v_idx;
__pyx_t_14 = __pyx_v_idx;
__pyx_v_total = (__pyx_v_total + ((*((double *) ( /* dim=0 */ ((char *) (((double *) __pyx_v_r1.data) + __pyx_t_13)) ))) * (*((double *) ( /* dim=0 */ ((char *) (((double *) __pyx_v_r1_accum.data) + __pyx_t_14)) )))));
+171: last_pos = n_open - 1
__pyx_v_last_pos = (__pyx_v_n_open - 1);
+172: last_idx = open_list[last_pos]
__pyx_t_14 = __pyx_v_last_pos;
__pyx_v_last_idx = (*((int *) ( /* dim=0 */ ((char *) (((int *) __pyx_v_open_list.data) + __pyx_t_14)) )));
+173: open_list[open_pos[idx]] = last_idx
__pyx_t_14 = __pyx_v_idx;
__pyx_t_13 = (*((int *) ( /* dim=0 */ ((char *) (((int *) __pyx_v_open_pos.data) + __pyx_t_14)) )));
*((int *) ( /* dim=0 */ ((char *) (((int *) __pyx_v_open_list.data) + __pyx_t_13)) )) = __pyx_v_last_idx;
+174: open_pos[last_idx] = open_pos[idx]
__pyx_t_14 = __pyx_v_idx;
__pyx_t_13 = __pyx_v_last_idx;
*((int *) ( /* dim=0 */ ((char *) (((int *) __pyx_v_open_pos.data) + __pyx_t_13)) )) = (*((int *) ( /* dim=0 */ ((char *) (((int *) __pyx_v_open_pos.data) + __pyx_t_14)) )));
+175: n_open -= 1
__pyx_v_n_open = (__pyx_v_n_open - 1);
+176: is_open[idx] = 0
__pyx_t_14 = __pyx_v_idx;
*((int *) ( /* dim=0 */ ((char *) (((int *) __pyx_v_is_open.data) + __pyx_t_14)) )) = 0;
177:
178: else:
179: # r2[idx] closes: update active sum only (r1 accumulators already got rv2 on open)
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__pyx_t_14 = __pyx_v_idx;
__pyx_v_active_r2_sum = (__pyx_v_active_r2_sum - (*((double *) ( /* dim=0 */ ((char *) (((double *) __pyx_v_r2.data) + __pyx_t_14)) ))));
break;
}
}
181:
+182: return total
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183:
184:
185: # ────────────────────────────────────────────────────────────────────────────
186: # 5. Refresh-time index computation
187: # ────────────────────────────────────────────────────────────────────────────
188:
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