Generated by Cython 3.0.11
Yellow lines hint at Python interaction.
Click on a line that starts with a "+" to see the C code that Cython generated for it.
Raw output: cut_finder.c
+001: # distutils: language = c
__pyx_t_7 = __Pyx_PyDict_NewPresized(0); if (unlikely(!__pyx_t_7)) __PYX_ERR(0, 1, __pyx_L1_error) __Pyx_GOTREF(__pyx_t_7); if (PyDict_SetItem(__pyx_d, __pyx_n_s_test, __pyx_t_7) < 0) __PYX_ERR(0, 1, __pyx_L1_error) __Pyx_DECREF(__pyx_t_7); __pyx_t_7 = 0;
002: # cython: boundscheck = False
003: # cython: wraparound = False
004: # cython: profile = False
005:
+006: import numpy as np
__pyx_t_7 = __Pyx_ImportDottedModule(__pyx_n_s_numpy, NULL); if (unlikely(!__pyx_t_7)) __PYX_ERR(0, 6, __pyx_L1_error) __Pyx_GOTREF(__pyx_t_7); if (PyDict_SetItem(__pyx_d, __pyx_n_s_np, __pyx_t_7) < 0) __PYX_ERR(0, 6, __pyx_L1_error) __Pyx_DECREF(__pyx_t_7); __pyx_t_7 = 0;
007: cimport numpy as np
008: cimport cython
009: from cython.parallel import prange
010: from libc.stdlib cimport malloc, free
011:
+012: ctypedef np.int32_t NP_INT_t
typedef __pyx_t_5numpy_int32_t __pyx_t_5d_imm_9splitters_10cut_finder_NP_INT_t;
013: ctypedef np.float64_t NP_FLOAT_t
014:
015: cdef extern from "<math.h>" nogil:
016: const float INFINITY
017:
018: cdef extern from "<limits.h>":
019: const int INT_MIN
020: const int INT_MAX
021:
+022: @cython.boundscheck(False)
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int __pyx_v_col; PyObject *__pyx_r = NULL; /* … */ /* function exit code */ __pyx_L1_error:; __Pyx_XDECREF(__pyx_t_1); __Pyx_AddTraceback("d_imm.splitters.cut_finder.get_all_mistakes_histogram", __pyx_clineno, __pyx_lineno, __pyx_filename); __pyx_r = NULL; __pyx_L0:; __Pyx_XDECREF(__pyx_v_feature_results); __Pyx_XGIVEREF(__pyx_r); __Pyx_RefNannyFinishContext(); return __pyx_r; } /* … */ __pyx_tuple__22 = PyTuple_Pack(12, __pyx_n_s_X, __pyx_n_s_y, __pyx_n_s_centers, __pyx_n_s_valid_centers, __pyx_n_s_valid_cols, __pyx_n_s_histogram, __pyx_n_s_njobs, __pyx_n_s_n, __pyx_n_s_k, __pyx_n_s_d, __pyx_n_s_feature_results, __pyx_n_s_col); if (unlikely(!__pyx_tuple__22)) __PYX_ERR(0, 22, __pyx_L1_error) __Pyx_GOTREF(__pyx_tuple__22); __Pyx_GIVEREF(__pyx_tuple__22); /* … */ __pyx_t_7 = __Pyx_CyFunction_New(&__pyx_mdef_5d_imm_9splitters_10cut_finder_1get_all_mistakes_histogram, 0, __pyx_n_s_get_all_mistakes_histogram, NULL, __pyx_n_s_d_imm_splitters_cut_finder, __pyx_d, ((PyObject *)__pyx_codeobj__23)); 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023: @cython.wraparound(False)
024: def get_all_mistakes_histogram(
025: NP_FLOAT_t[:,:] X, NP_INT_t[:] y, NP_FLOAT_t[:,:] centers,
026: NP_INT_t[:] valid_centers, NP_INT_t[:] valid_cols, list histogram, int njobs
027: ):
028: """
029: Main function to calculate mistakes for all features and thresholds.
030: Returns a list of Python dictionaries with 'feature', 'threshold', and 'mistakes'.
031: """
+032: cdef int n = X.shape[0]
__pyx_v_n = (__pyx_v_X.shape[0]);
+033: cdef int k = centers.shape[0]
__pyx_v_k = (__pyx_v_centers.shape[0]);
+034: cdef int d = valid_cols.shape[0]
__pyx_v_d = (__pyx_v_valid_cols.shape[0]);
+035: cdef list feature_results = []
__pyx_t_1 = PyList_New(0); if (unlikely(!__pyx_t_1)) __PYX_ERR(0, 35, __pyx_L1_error) __Pyx_GOTREF(__pyx_t_1); __pyx_v_feature_results = ((PyObject*)__pyx_t_1); __pyx_t_1 = 0;
036: cdef int col
037:
+038: if njobs is None or njobs <= 1:
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039: # Iterate over valid columns
+040: for col in range(d):
__pyx_t_4 = __pyx_v_d;
__pyx_t_5 = __pyx_t_4;
for (__pyx_t_6 = 0; __pyx_t_6 < __pyx_t_5; __pyx_t_6+=1) {
__pyx_v_col = __pyx_t_6;
+041: if valid_cols[col] == 1:
__pyx_t_7 = __pyx_v_col;
__pyx_t_2 = ((*((__pyx_t_5d_imm_9splitters_10cut_finder_NP_INT_t *) ( /* dim=0 */ (__pyx_v_valid_cols.data + __pyx_t_7 * __pyx_v_valid_cols.strides[0]) ))) == 1);
if (__pyx_t_2) {
/* … */
}
}
+042: update_col_all_mistakes_histogram_unsorted(
__pyx_f_5d_imm_9splitters_10cut_finder_update_col_all_mistakes_histogram_unsorted(__pyx_v_X, __pyx_v_y, __pyx_v_centers, __pyx_v_valid_centers, __pyx_v_col, __pyx_v_n, __pyx_v_k, __pyx_v_feature_results, ((PyObject*)__pyx_t_1)); if (unlikely(PyErr_Occurred())) __PYX_ERR(0, 42, __pyx_L1_error) __Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0;
043: X, y, centers, valid_centers,
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if (unlikely(__pyx_v_histogram == Py_None)) {
PyErr_SetString(PyExc_TypeError, "'NoneType' object is not subscriptable");
__PYX_ERR(0, 44, __pyx_L1_error)
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__pyx_t_1 = PyList_GET_ITEM(__pyx_v_histogram, __pyx_v_col);
__Pyx_INCREF(__pyx_t_1);
045: )
046: else:
047: # Parallelize the process
+048: for col in prange(d, num_threads=njobs, schedule='dynamic', nogil=True): # Removed nogil=True
/*else*/ {
{
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Py_BLOCK_THREADS
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goto __pyx_L11;
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__pyx_L10_error: {
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__pyx_L11:;
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__pyx_L3:;
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if (__pyx_t_2) {
/* … */
}
goto __pyx_L23;
__pyx_L14_error:;
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goto __pyx_L22;
__pyx_L22:;
#ifdef _OPENMP
#pragma omp critical(__pyx_parallel_lastprivates0)
#endif /* _OPENMP */
{
__pyx_parallel_temp0 = __pyx_v_col;
}
__pyx_L23:;
#ifdef _OPENMP
#pragma omp flush(__pyx_parallel_why)
#endif /* _OPENMP */
}
}
#ifdef _OPENMP
Py_END_ALLOW_THREADS
#else
{
#ifdef WITH_THREAD
PyGILState_STATE __pyx_gilstate_save = __Pyx_PyGILState_Ensure();
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/* Clean up any temporaries */
__Pyx_XDECREF(__pyx_t_1); __pyx_t_1 = 0;
#ifdef WITH_THREAD
__Pyx_PyGILState_Release(__pyx_gilstate_save);
#endif
#ifndef _OPENMP
}
#endif /* _OPENMP */
}
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if (__pyx_parallel_exc_type) {
/* This may have been overridden by a continue, break or return in another thread. Prefer the error. */
__pyx_parallel_why = 4;
}
if (__pyx_parallel_why) {
__pyx_v_col = __pyx_parallel_temp0;
switch (__pyx_parallel_why) {
case 4:
{
#ifdef WITH_THREAD
PyGILState_STATE __pyx_gilstate_save = __Pyx_PyGILState_Ensure();
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__Pyx_GIVEREF(__pyx_parallel_exc_type);
__Pyx_ErrRestoreWithState(__pyx_parallel_exc_type, __pyx_parallel_exc_value, __pyx_parallel_exc_tb);
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__Pyx_PyGILState_Release(__pyx_gilstate_save);
#endif
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#if ((defined(__APPLE__) || defined(__OSX__)) && (defined(__GNUC__) && (__GNUC__ > 2 || (__GNUC__ == 2 && (__GNUC_MINOR__ > 95)))))
#undef likely
#undef unlikely
#define likely(x) __builtin_expect(!!(x), 1)
#define unlikely(x) __builtin_expect(!!(x), 0)
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{
#ifdef WITH_THREAD
PyGILState_STATE __pyx_gilstate_save = __Pyx_PyGILState_Ensure();
#endif
/*try:*/ {
/* … */
/*finally:*/ {
/*normal exit:*/{
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__Pyx_PyGILState_Release(__pyx_gilstate_save);
#endif
goto __pyx_L21;
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#ifdef WITH_THREAD
__Pyx_PyGILState_Release(__pyx_gilstate_save);
#endif
goto __pyx_L14_error;
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__pyx_L21:;
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+051: update_col_all_mistakes_histogram_unsorted(
__pyx_f_5d_imm_9splitters_10cut_finder_update_col_all_mistakes_histogram_unsorted(__pyx_v_X, __pyx_v_y, __pyx_v_centers, __pyx_v_valid_centers, __pyx_v_col, __pyx_v_n, __pyx_v_k, __pyx_v_feature_results, ((PyObject*)__pyx_t_1)); if (unlikely(PyErr_Occurred())) __PYX_ERR(0, 51, __pyx_L20_error) __Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0; }
052: X, y, centers, valid_centers,
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if (unlikely(__pyx_v_histogram == Py_None)) {
PyErr_SetString(PyExc_TypeError, "'NoneType' object is not subscriptable");
__PYX_ERR(0, 53, __pyx_L20_error)
}
if (!(likely(PyList_CheckExact(PyList_GET_ITEM(__pyx_v_histogram, __pyx_v_col)))||((PyList_GET_ITEM(__pyx_v_histogram, __pyx_v_col)) == Py_None) || __Pyx_RaiseUnexpectedTypeError("list", PyList_GET_ITEM(__pyx_v_histogram, __pyx_v_col)))) __PYX_ERR(0, 53, __pyx_L20_error)
__pyx_t_1 = PyList_GET_ITEM(__pyx_v_histogram, __pyx_v_col);
__Pyx_INCREF(__pyx_t_1);
054: )
055:
+056: return feature_results
__Pyx_XDECREF(__pyx_r); __Pyx_INCREF(__pyx_v_feature_results); __pyx_r = __pyx_v_feature_results; goto __pyx_L0;
057:
058:
059: @cython.boundscheck(False)
060: @cython.wraparound(False)
+061: cdef void update_col_all_mistakes_histogram_unsorted(
static void __pyx_f_5d_imm_9splitters_10cut_finder_update_col_all_mistakes_histogram_unsorted(__Pyx_memviewslice __pyx_v_X, __Pyx_memviewslice __pyx_v_y, __Pyx_memviewslice __pyx_v_centers, __Pyx_memviewslice __pyx_v_valid_centers, int __pyx_v_col, int __pyx_v_n, int __pyx_v_k, PyObject *__pyx_v_feature_results, PyObject *__pyx_v_histogram) {
int __pyx_v_i;
int __pyx_v_ix;
CYTHON_UNUSED int __pyx_v_ic;
int __pyx_v_mistakes;
__pyx_t_5d_imm_9splitters_10cut_finder_NP_FLOAT_t __pyx_v_threshold;
CYTHON_UNUSED __Pyx_memviewslice __pyx_v_centers_order = { 0, 0, { 0 }, { 0 }, { 0 } };
int __pyx_v_num_thresholds;
__pyx_t_5d_imm_9splitters_10cut_finder_NP_FLOAT_t *__pyx_v_combined_thresholds;
__pyx_t_5d_imm_9splitters_10cut_finder_NP_FLOAT_t __pyx_v_max_val;
__pyx_t_5d_imm_9splitters_10cut_finder_NP_FLOAT_t __pyx_v_min_val;
PyObject *__pyx_v_unique_thresholds = NULL;
PyObject *__pyx_v_split = NULL;
PyObject *__pyx_v_sorted_thresholds = NULL;
/* … */
/* function exit code */
goto __pyx_L0;
__pyx_L1_error:;
#ifdef WITH_THREAD
__pyx_gilstate_save = __Pyx_PyGILState_Ensure();
#endif
__Pyx_XDECREF(__pyx_t_7);
__Pyx_XDECREF(__pyx_t_8);
__Pyx_XDECREF(__pyx_t_9);
__Pyx_XDECREF(__pyx_t_10);
__PYX_XCLEAR_MEMVIEW(&__pyx_t_11, 1);
__Pyx_XDECREF(__pyx_t_12);
__PYX_XCLEAR_MEMVIEW(&__pyx_t_14, 1);
__Pyx_AddTraceback("d_imm.splitters.cut_finder.update_col_all_mistakes_histogram_unsorted", __pyx_clineno, __pyx_lineno, __pyx_filename);
#ifdef WITH_THREAD
__Pyx_PyGILState_Release(__pyx_gilstate_save);
#endif
__pyx_L0:;
__PYX_XCLEAR_MEMVIEW(&__pyx_v_centers_order, 0);
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__pyx_gilstate_save = __Pyx_PyGILState_Ensure();
#endif
__Pyx_XDECREF(__pyx_v_unique_thresholds);
__Pyx_XDECREF(__pyx_v_split);
__Pyx_XDECREF(__pyx_v_sorted_thresholds);
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#ifdef WITH_THREAD
__Pyx_PyGILState_Release(__pyx_gilstate_save);
#endif
}
062: NP_FLOAT_t[:,:] X, NP_INT_t[:] y, NP_FLOAT_t[:,:] centers,
063: NP_INT_t[:] valid_centers,
064: int col, int n, int k,
065: list feature_results, list histogram) nogil: # Marked as noexcept
066: """
067: Helper function to calculate mistakes for a single column using histogram-based and center-based thresholds.
068: Appends the results as Python dictionaries to feature_results.
069: """
070: cdef int i
+071: cdef int ix = 0
__pyx_v_ix = 0;
+072: cdef int ic = 0
__pyx_v_ic = 0;
+073: cdef int mistakes = 0
__pyx_v_mistakes = 0;
074: cdef NP_FLOAT_t threshold
075: cdef np.int64_t[:] centers_order
076: cdef int num_thresholds
077: cdef NP_FLOAT_t *combined_thresholds
078: cdef NP_FLOAT_t max_val
079: cdef NP_FLOAT_t min_val
080:
081: # Find the maximum and minimum valid center values
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__pyx_v_max_val = (-INFINITY);
+083: min_val = INFINITY
__pyx_v_min_val = INFINITY;
084:
+085: for i in range(k):
__pyx_t_1 = __pyx_v_k;
__pyx_t_2 = __pyx_t_1;
for (__pyx_t_3 = 0; __pyx_t_3 < __pyx_t_2; __pyx_t_3+=1) {
__pyx_v_i = __pyx_t_3;
+086: if valid_centers[i] == 1:
__pyx_t_4 = __pyx_v_i;
__pyx_t_5 = ((*((__pyx_t_5d_imm_9splitters_10cut_finder_NP_INT_t *) ( /* dim=0 */ (__pyx_v_valid_centers.data + __pyx_t_4 * __pyx_v_valid_centers.strides[0]) ))) == 1);
if (__pyx_t_5) {
/* … */
}
}
+087: if centers[i, col] > max_val:
__pyx_t_4 = __pyx_v_i;
__pyx_t_6 = __pyx_v_col;
__pyx_t_5 = ((*((__pyx_t_5d_imm_9splitters_10cut_finder_NP_FLOAT_t *) ( /* dim=1 */ (( /* dim=0 */ (__pyx_v_centers.data + __pyx_t_4 * __pyx_v_centers.strides[0]) ) + __pyx_t_6 * __pyx_v_centers.strides[1]) ))) > __pyx_v_max_val);
if (__pyx_t_5) {
/* … */
}
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__pyx_t_6 = __pyx_v_i;
__pyx_t_4 = __pyx_v_col;
__pyx_v_max_val = (*((__pyx_t_5d_imm_9splitters_10cut_finder_NP_FLOAT_t *) ( /* dim=1 */ (( /* dim=0 */ (__pyx_v_centers.data + __pyx_t_6 * __pyx_v_centers.strides[0]) ) + __pyx_t_4 * __pyx_v_centers.strides[1]) )));
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__pyx_t_4 = __pyx_v_i;
__pyx_t_6 = __pyx_v_col;
__pyx_t_5 = ((*((__pyx_t_5d_imm_9splitters_10cut_finder_NP_FLOAT_t *) ( /* dim=1 */ (( /* dim=0 */ (__pyx_v_centers.data + __pyx_t_4 * __pyx_v_centers.strides[0]) ) + __pyx_t_6 * __pyx_v_centers.strides[1]) ))) < __pyx_v_min_val);
if (__pyx_t_5) {
/* … */
}
+090: min_val = centers[i, col]
__pyx_t_6 = __pyx_v_i;
__pyx_t_4 = __pyx_v_col;
__pyx_v_min_val = (*((__pyx_t_5d_imm_9splitters_10cut_finder_NP_FLOAT_t *) ( /* dim=1 */ (( /* dim=0 */ (__pyx_v_centers.data + __pyx_t_6 * __pyx_v_centers.strides[0]) ) + __pyx_t_4 * __pyx_v_centers.strides[1]) )));
091:
092: # Sorting and threshold combination
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{
#ifdef WITH_THREAD
PyGILState_STATE __pyx_gilstate_save = __Pyx_PyGILState_Ensure();
#endif
/*try:*/ {
/* … */
/*finally:*/ {
/*normal exit:*/{
#ifdef WITH_THREAD
__Pyx_PyGILState_Release(__pyx_gilstate_save);
#endif
goto __pyx_L10;
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__pyx_L9_error: {
#ifdef WITH_THREAD
__Pyx_PyGILState_Release(__pyx_gilstate_save);
#endif
goto __pyx_L1_error;
}
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095:
096: # Combine histogram-based and center-based thresholds
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__pyx_t_7 = PySet_New(0); if (unlikely(!__pyx_t_7)) __PYX_ERR(0, 97, __pyx_L9_error) __Pyx_GOTREF(__pyx_t_7); __pyx_v_unique_thresholds = ((PyObject*)__pyx_t_7); __pyx_t_7 = 0;
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if (unlikely(__pyx_v_histogram == Py_None)) {
PyErr_SetString(PyExc_TypeError, "'NoneType' object is not iterable");
__PYX_ERR(0, 98, __pyx_L9_error)
}
__pyx_t_7 = __pyx_v_histogram; __Pyx_INCREF(__pyx_t_7);
__pyx_t_15 = 0;
for (;;) {
{
Py_ssize_t __pyx_temp = __Pyx_PyList_GET_SIZE(__pyx_t_7);
#if !CYTHON_ASSUME_SAFE_MACROS
if (unlikely((__pyx_temp < 0))) __PYX_ERR(0, 98, __pyx_L9_error)
#endif
if (__pyx_t_15 >= __pyx_temp) break;
}
#if CYTHON_ASSUME_SAFE_MACROS && !CYTHON_AVOID_BORROWED_REFS
__pyx_t_10 = PyList_GET_ITEM(__pyx_t_7, __pyx_t_15); __Pyx_INCREF(__pyx_t_10); __pyx_t_15++; if (unlikely((0 < 0))) __PYX_ERR(0, 98, __pyx_L9_error)
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__Pyx_XDECREF_SET(__pyx_v_split, __pyx_t_10);
__pyx_t_10 = 0;
/* … */
}
__Pyx_DECREF(__pyx_t_7); __pyx_t_7 = 0;
+099: if min_val <= split.threshold < max_val:
__pyx_t_10 = PyFloat_FromDouble(__pyx_v_min_val); if (unlikely(!__pyx_t_10)) __PYX_ERR(0, 99, __pyx_L9_error) __Pyx_GOTREF(__pyx_t_10); __pyx_t_8 = __Pyx_PyObject_GetAttrStr(__pyx_v_split, __pyx_n_s_threshold); if (unlikely(!__pyx_t_8)) __PYX_ERR(0, 99, __pyx_L9_error) __Pyx_GOTREF(__pyx_t_8); __pyx_t_9 = PyObject_RichCompare(__pyx_t_10, __pyx_t_8, Py_LE); __Pyx_XGOTREF(__pyx_t_9); if (unlikely(!__pyx_t_9)) __PYX_ERR(0, 99, __pyx_L9_error) if (__Pyx_PyObject_IsTrue(__pyx_t_9)) { __Pyx_DECREF(__pyx_t_9); __pyx_t_12 = PyFloat_FromDouble(__pyx_v_max_val); if (unlikely(!__pyx_t_12)) __PYX_ERR(0, 99, __pyx_L9_error) __Pyx_GOTREF(__pyx_t_12); __pyx_t_9 = PyObject_RichCompare(__pyx_t_8, __pyx_t_12, Py_LT); __Pyx_XGOTREF(__pyx_t_9); if (unlikely(!__pyx_t_9)) __PYX_ERR(0, 99, __pyx_L9_error) __Pyx_DECREF(__pyx_t_12); __pyx_t_12 = 0; } __Pyx_DECREF(__pyx_t_10); __pyx_t_10 = 0; __Pyx_DECREF(__pyx_t_8); __pyx_t_8 = 0; __pyx_t_5 = __Pyx_PyObject_IsTrue(__pyx_t_9); if (unlikely((__pyx_t_5 < 0))) __PYX_ERR(0, 99, __pyx_L9_error) __Pyx_DECREF(__pyx_t_9); __pyx_t_9 = 0; if (__pyx_t_5) { /* … */ }
+100: unique_thresholds.add(split.threshold)
__pyx_t_9 = __Pyx_PyObject_GetAttrStr(__pyx_v_split, __pyx_n_s_threshold); if (unlikely(!__pyx_t_9)) __PYX_ERR(0, 100, __pyx_L9_error) __Pyx_GOTREF(__pyx_t_9); __pyx_t_16 = PySet_Add(__pyx_v_unique_thresholds, __pyx_t_9); if (unlikely(__pyx_t_16 == ((int)-1))) __PYX_ERR(0, 100, __pyx_L9_error) __Pyx_DECREF(__pyx_t_9); __pyx_t_9 = 0;
101:
+102: for i in range(k):
__pyx_t_1 = __pyx_v_k;
__pyx_t_2 = __pyx_t_1;
for (__pyx_t_3 = 0; __pyx_t_3 < __pyx_t_2; __pyx_t_3+=1) {
__pyx_v_i = __pyx_t_3;
+103: if valid_centers[i] == 1 and centers[i, col]!=max_val:
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__pyx_t_17 = ((*((__pyx_t_5d_imm_9splitters_10cut_finder_NP_INT_t *) ( /* dim=0 */ (__pyx_v_valid_centers.data + __pyx_t_4 * __pyx_v_valid_centers.strides[0]) ))) == 1);
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__pyx_L18_bool_binop_done:;
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/* … */
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__pyx_t_4 = __pyx_v_col;
__pyx_t_7 = PyFloat_FromDouble((*((__pyx_t_5d_imm_9splitters_10cut_finder_NP_FLOAT_t *) ( /* dim=1 */ (( /* dim=0 */ (__pyx_v_centers.data + __pyx_t_6 * __pyx_v_centers.strides[0]) ) + __pyx_t_4 * __pyx_v_centers.strides[1]) )))); if (unlikely(!__pyx_t_7)) __PYX_ERR(0, 104, __pyx_L9_error)
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__Pyx_DECREF(__pyx_t_7); __pyx_t_7 = 0;
105:
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107:
+108: num_thresholds = len(sorted_thresholds)
__pyx_t_15 = __Pyx_PyList_GET_SIZE(__pyx_v_sorted_thresholds); if (unlikely(__pyx_t_15 == ((Py_ssize_t)-1))) __PYX_ERR(0, 108, __pyx_L9_error) __pyx_v_num_thresholds = __pyx_t_15;
+109: combined_thresholds = <NP_FLOAT_t *> malloc(num_thresholds * sizeof(NP_FLOAT_t))
__pyx_v_combined_thresholds = ((__pyx_t_5d_imm_9splitters_10cut_finder_NP_FLOAT_t *)malloc((__pyx_v_num_thresholds * (sizeof(__pyx_t_5d_imm_9splitters_10cut_finder_NP_FLOAT_t)))));
110:
+111: for i in range(num_thresholds):
__pyx_t_1 = __pyx_v_num_thresholds;
__pyx_t_2 = __pyx_t_1;
for (__pyx_t_3 = 0; __pyx_t_3 < __pyx_t_2; __pyx_t_3+=1) {
__pyx_v_i = __pyx_t_3;
+112: combined_thresholds[i] = sorted_thresholds[i]
__pyx_t_18 = __pyx_PyFloat_AsDouble(PyList_GET_ITEM(__pyx_v_sorted_thresholds, __pyx_v_i)); if (unlikely((__pyx_t_18 == ((npy_float64)-1)) && PyErr_Occurred())) __PYX_ERR(0, 112, __pyx_L9_error) (__pyx_v_combined_thresholds[__pyx_v_i]) = __pyx_t_18; } }
113:
114: # Process each threshold
+115: for i in range(num_thresholds):
__pyx_t_1 = __pyx_v_num_thresholds;
__pyx_t_2 = __pyx_t_1;
for (__pyx_t_3 = 0; __pyx_t_3 < __pyx_t_2; __pyx_t_3+=1) {
__pyx_v_i = __pyx_t_3;
+116: mistakes = 0
__pyx_v_mistakes = 0;
+117: ix = 0
__pyx_v_ix = 0;
+118: threshold = combined_thresholds[i]
__pyx_v_threshold = (__pyx_v_combined_thresholds[__pyx_v_i]);
119:
120: # Count mistakes
+121: while ix < n:
while (1) {
__pyx_t_5 = (__pyx_v_ix < __pyx_v_n);
if (!__pyx_t_5) break;
+122: if X[ix, col] <= threshold:
__pyx_t_4 = __pyx_v_ix;
__pyx_t_6 = __pyx_v_col;
__pyx_t_5 = ((*((__pyx_t_5d_imm_9splitters_10cut_finder_NP_FLOAT_t *) ( /* dim=1 */ (( /* dim=0 */ (__pyx_v_X.data + __pyx_t_4 * __pyx_v_X.strides[0]) ) + __pyx_t_6 * __pyx_v_X.strides[1]) ))) <= __pyx_v_threshold);
if (__pyx_t_5) {
/* … */
goto __pyx_L26;
}
+123: if centers[y[ix], col] > threshold:
__pyx_t_6 = __pyx_v_ix;
__pyx_t_4 = (*((__pyx_t_5d_imm_9splitters_10cut_finder_NP_INT_t *) ( /* dim=0 */ (__pyx_v_y.data + __pyx_t_6 * __pyx_v_y.strides[0]) )));
__pyx_t_19 = __pyx_v_col;
__pyx_t_5 = ((*((__pyx_t_5d_imm_9splitters_10cut_finder_NP_FLOAT_t *) ( /* dim=1 */ (( /* dim=0 */ (__pyx_v_centers.data + __pyx_t_4 * __pyx_v_centers.strides[0]) ) + __pyx_t_19 * __pyx_v_centers.strides[1]) ))) > __pyx_v_threshold);
if (__pyx_t_5) {
/* … */
}
+124: mistakes += 1
__pyx_v_mistakes = (__pyx_v_mistakes + 1);
125: else:
+126: if centers[y[ix], col] <= threshold:
/*else*/ {
__pyx_t_6 = __pyx_v_ix;
__pyx_t_19 = (*((__pyx_t_5d_imm_9splitters_10cut_finder_NP_INT_t *) ( /* dim=0 */ (__pyx_v_y.data + __pyx_t_6 * __pyx_v_y.strides[0]) )));
__pyx_t_4 = __pyx_v_col;
__pyx_t_5 = ((*((__pyx_t_5d_imm_9splitters_10cut_finder_NP_FLOAT_t *) ( /* dim=1 */ (( /* dim=0 */ (__pyx_v_centers.data + __pyx_t_19 * __pyx_v_centers.strides[0]) ) + __pyx_t_4 * __pyx_v_centers.strides[1]) ))) <= __pyx_v_threshold);
if (__pyx_t_5) {
/* … */
}
}
__pyx_L26:;
+127: mistakes += 1
__pyx_v_mistakes = (__pyx_v_mistakes + 1);
+128: ix += 1
__pyx_v_ix = (__pyx_v_ix + 1);
}
129:
130: # Store result
+131: with gil:
{
#ifdef WITH_THREAD
PyGILState_STATE __pyx_gilstate_save = __Pyx_PyGILState_Ensure();
#endif
/*try:*/ {
/* … */
/*finally:*/ {
/*normal exit:*/{
#ifdef WITH_THREAD
__Pyx_PyGILState_Release(__pyx_gilstate_save);
#endif
goto __pyx_L33;
}
__pyx_L32_error: {
#ifdef WITH_THREAD
__Pyx_PyGILState_Release(__pyx_gilstate_save);
#endif
goto __pyx_L1_error;
}
__pyx_L33:;
}
}
}
+132: feature_results.append({
if (unlikely(__pyx_v_feature_results == Py_None)) {
PyErr_Format(PyExc_AttributeError, "'NoneType' object has no attribute '%.30s'", "append");
__PYX_ERR(0, 132, __pyx_L32_error)
}
/* … */
__pyx_t_16 = __Pyx_PyList_Append(__pyx_v_feature_results, __pyx_t_7); if (unlikely(__pyx_t_16 == ((int)-1))) __PYX_ERR(0, 132, __pyx_L32_error)
__Pyx_DECREF(__pyx_t_7); __pyx_t_7 = 0;
}
+133: 'feature': col,
__pyx_t_7 = __Pyx_PyDict_NewPresized(3); if (unlikely(!__pyx_t_7)) __PYX_ERR(0, 133, __pyx_L32_error) __Pyx_GOTREF(__pyx_t_7); __pyx_t_9 = __Pyx_PyInt_From_int(__pyx_v_col); if (unlikely(!__pyx_t_9)) __PYX_ERR(0, 133, __pyx_L32_error) __Pyx_GOTREF(__pyx_t_9); if (PyDict_SetItem(__pyx_t_7, __pyx_n_s_feature, __pyx_t_9) < 0) __PYX_ERR(0, 133, __pyx_L32_error) __Pyx_DECREF(__pyx_t_9); __pyx_t_9 = 0;
+134: 'threshold': threshold,
__pyx_t_9 = PyFloat_FromDouble(__pyx_v_threshold); if (unlikely(!__pyx_t_9)) __PYX_ERR(0, 134, __pyx_L32_error) __Pyx_GOTREF(__pyx_t_9); if (PyDict_SetItem(__pyx_t_7, __pyx_n_s_threshold, __pyx_t_9) < 0) __PYX_ERR(0, 133, __pyx_L32_error) __Pyx_DECREF(__pyx_t_9); __pyx_t_9 = 0;
+135: 'mistakes': mistakes
__pyx_t_9 = __Pyx_PyInt_From_int(__pyx_v_mistakes); if (unlikely(!__pyx_t_9)) __PYX_ERR(0, 135, __pyx_L32_error) __Pyx_GOTREF(__pyx_t_9); if (PyDict_SetItem(__pyx_t_7, __pyx_n_s_mistakes, __pyx_t_9) < 0) __PYX_ERR(0, 133, __pyx_L32_error) __Pyx_DECREF(__pyx_t_9); __pyx_t_9 = 0;
136: })
137:
+138: free(combined_thresholds)
free(__pyx_v_combined_thresholds);