/* Generated by Cython 0.20.1 on Thu Jun 19 21:56:01 2014 */

#define PY_SSIZE_T_CLEAN
#ifndef CYTHON_USE_PYLONG_INTERNALS
#ifdef PYLONG_BITS_IN_DIGIT
#define CYTHON_USE_PYLONG_INTERNALS 0
#else
#include "pyconfig.h"
#ifdef PYLONG_BITS_IN_DIGIT
#define CYTHON_USE_PYLONG_INTERNALS 1
#else
#define CYTHON_USE_PYLONG_INTERNALS 0
#endif
#endif
#endif
#include "Python.h"
#ifndef Py_PYTHON_H
    #error Python headers needed to compile C extensions, please install development version of Python.
#elif PY_VERSION_HEX < 0x02040000
    #error Cython requires Python 2.4+.
#else
#define CYTHON_ABI "0_20_1"
#include <stddef.h> /* For offsetof */
#ifndef offsetof
#define offsetof(type, member) ( (size_t) & ((type*)0) -> member )
#endif
#if !defined(WIN32) && !defined(MS_WINDOWS)
  #ifndef __stdcall
    #define __stdcall
  #endif
  #ifndef __cdecl
    #define __cdecl
  #endif
  #ifndef __fastcall
    #define __fastcall
  #endif
#endif
#ifndef DL_IMPORT
  #define DL_IMPORT(t) t
#endif
#ifndef DL_EXPORT
  #define DL_EXPORT(t) t
#endif
#ifndef PY_LONG_LONG
  #define PY_LONG_LONG LONG_LONG
#endif
#ifndef Py_HUGE_VAL
  #define Py_HUGE_VAL HUGE_VAL
#endif
#ifdef PYPY_VERSION
#define CYTHON_COMPILING_IN_PYPY 1
#define CYTHON_COMPILING_IN_CPYTHON 0
#else
#define CYTHON_COMPILING_IN_PYPY 0
#define CYTHON_COMPILING_IN_CPYTHON 1
#endif
#if CYTHON_COMPILING_IN_PYPY
#define Py_OptimizeFlag 0
#endif
#if PY_VERSION_HEX < 0x02050000
  typedef int Py_ssize_t;
  #define PY_SSIZE_T_MAX INT_MAX
  #define PY_SSIZE_T_MIN INT_MIN
  #define PY_FORMAT_SIZE_T ""
  #define CYTHON_FORMAT_SSIZE_T ""
  #define PyInt_FromSsize_t(z) PyInt_FromLong(z)
  #define PyInt_AsSsize_t(o)   __Pyx_PyInt_As_int(o)
  #define PyNumber_Index(o)    ((PyNumber_Check(o) && !PyFloat_Check(o)) ? PyNumber_Int(o) : \
                                (PyErr_Format(PyExc_TypeError, \
                                              "expected index value, got %.200s", Py_TYPE(o)->tp_name), \
                                 (PyObject*)0))
  #define __Pyx_PyIndex_Check(o) (PyNumber_Check(o) && !PyFloat_Check(o) && \
                                  !PyComplex_Check(o))
  #define PyIndex_Check __Pyx_PyIndex_Check
  #define PyErr_WarnEx(category, message, stacklevel) PyErr_Warn(category, message)
  #define __PYX_BUILD_PY_SSIZE_T "i"
#else
  #define __PYX_BUILD_PY_SSIZE_T "n"
  #define CYTHON_FORMAT_SSIZE_T "z"
  #define __Pyx_PyIndex_Check PyIndex_Check
#endif
#if PY_VERSION_HEX < 0x02060000
  #define Py_REFCNT(ob) (((PyObject*)(ob))->ob_refcnt)
  #define Py_TYPE(ob)   (((PyObject*)(ob))->ob_type)
  #define Py_SIZE(ob)   (((PyVarObject*)(ob))->ob_size)
  #define PyVarObject_HEAD_INIT(type, size) \
          PyObject_HEAD_INIT(type) size,
  #define PyType_Modified(t)
  typedef struct {
     void *buf;
     PyObject *obj;
     Py_ssize_t len;
     Py_ssize_t itemsize;
     int readonly;
     int ndim;
     char *format;
     Py_ssize_t *shape;
     Py_ssize_t *strides;
     Py_ssize_t *suboffsets;
     void *internal;
  } Py_buffer;
  #define PyBUF_SIMPLE 0
  #define PyBUF_WRITABLE 0x0001
  #define PyBUF_FORMAT 0x0004
  #define PyBUF_ND 0x0008
  #define PyBUF_STRIDES (0x0010 | PyBUF_ND)
  #define PyBUF_C_CONTIGUOUS (0x0020 | PyBUF_STRIDES)
  #define PyBUF_F_CONTIGUOUS (0x0040 | PyBUF_STRIDES)
  #define PyBUF_ANY_CONTIGUOUS (0x0080 | PyBUF_STRIDES)
  #define PyBUF_INDIRECT (0x0100 | PyBUF_STRIDES)
  #define PyBUF_RECORDS (PyBUF_STRIDES | PyBUF_FORMAT | PyBUF_WRITABLE)
  #define PyBUF_FULL (PyBUF_INDIRECT | PyBUF_FORMAT | PyBUF_WRITABLE)
  typedef int (*getbufferproc)(PyObject *, Py_buffer *, int);
  typedef void (*releasebufferproc)(PyObject *, Py_buffer *);
#endif
#if PY_MAJOR_VERSION < 3
  #define __Pyx_BUILTIN_MODULE_NAME "__builtin__"
  #define __Pyx_PyCode_New(a, k, l, s, f, code, c, n, v, fv, cell, fn, name, fline, lnos) \
          PyCode_New(a+k, l, s, f, code, c, n, v, fv, cell, fn, name, fline, lnos)
  #define __Pyx_DefaultClassType PyClass_Type
#else
  #define __Pyx_BUILTIN_MODULE_NAME "builtins"
  #define __Pyx_PyCode_New(a, k, l, s, f, code, c, n, v, fv, cell, fn, name, fline, lnos) \
          PyCode_New(a, k, l, s, f, code, c, n, v, fv, cell, fn, name, fline, lnos)
  #define __Pyx_DefaultClassType PyType_Type
#endif
#if PY_VERSION_HEX < 0x02060000
  #define PyUnicode_FromString(s) PyUnicode_Decode(s, strlen(s), "UTF-8", "strict")
#endif
#if PY_MAJOR_VERSION >= 3
  #define Py_TPFLAGS_CHECKTYPES 0
  #define Py_TPFLAGS_HAVE_INDEX 0
#endif
#if (PY_VERSION_HEX < 0x02060000) || (PY_MAJOR_VERSION >= 3)
  #define Py_TPFLAGS_HAVE_NEWBUFFER 0
#endif
#if PY_VERSION_HEX < 0x02060000
  #define Py_TPFLAGS_HAVE_VERSION_TAG 0
#endif
#if PY_VERSION_HEX < 0x02060000 && !defined(Py_TPFLAGS_IS_ABSTRACT)
  #define Py_TPFLAGS_IS_ABSTRACT 0
#endif
#if PY_VERSION_HEX < 0x030400a1 && !defined(Py_TPFLAGS_HAVE_FINALIZE)
  #define Py_TPFLAGS_HAVE_FINALIZE 0
#endif
#if PY_VERSION_HEX > 0x03030000 && defined(PyUnicode_KIND)
  #define CYTHON_PEP393_ENABLED 1
  #define __Pyx_PyUnicode_READY(op)       (likely(PyUnicode_IS_READY(op)) ? \
                                              0 : _PyUnicode_Ready((PyObject *)(op)))
  #define __Pyx_PyUnicode_GET_LENGTH(u)   PyUnicode_GET_LENGTH(u)
  #define __Pyx_PyUnicode_READ_CHAR(u, i) PyUnicode_READ_CHAR(u, i)
  #define __Pyx_PyUnicode_KIND(u)         PyUnicode_KIND(u)
  #define __Pyx_PyUnicode_DATA(u)         PyUnicode_DATA(u)
  #define __Pyx_PyUnicode_READ(k, d, i)   PyUnicode_READ(k, d, i)
#else
  #define CYTHON_PEP393_ENABLED 0
  #define __Pyx_PyUnicode_READY(op)       (0)
  #define __Pyx_PyUnicode_GET_LENGTH(u)   PyUnicode_GET_SIZE(u)
  #define __Pyx_PyUnicode_READ_CHAR(u, i) ((Py_UCS4)(PyUnicode_AS_UNICODE(u)[i]))
  #define __Pyx_PyUnicode_KIND(u)         (sizeof(Py_UNICODE))
  #define __Pyx_PyUnicode_DATA(u)         ((void*)PyUnicode_AS_UNICODE(u))
  #define __Pyx_PyUnicode_READ(k, d, i)   ((void)(k), (Py_UCS4)(((Py_UNICODE*)d)[i]))
#endif
#if CYTHON_COMPILING_IN_PYPY
  #define __Pyx_PyUnicode_Concat(a, b)      PyNumber_Add(a, b)
  #define __Pyx_PyUnicode_ConcatSafe(a, b)  PyNumber_Add(a, b)
#else
  #define __Pyx_PyUnicode_Concat(a, b)      PyUnicode_Concat(a, b)
  #define __Pyx_PyUnicode_ConcatSafe(a, b)  ((unlikely((a) == Py_None) || unlikely((b) == Py_None)) ? \
      PyNumber_Add(a, b) : __Pyx_PyUnicode_Concat(a, b))
#endif
#define __Pyx_PyString_FormatSafe(a, b)  ((unlikely((a) == Py_None)) ? PyNumber_Remainder(a, b) : __Pyx_PyString_Format(a, b))
#define __Pyx_PyUnicode_FormatSafe(a, b)  ((unlikely((a) == Py_None)) ? PyNumber_Remainder(a, b) : PyUnicode_Format(a, b))
#if PY_MAJOR_VERSION >= 3
  #define __Pyx_PyString_Format(a, b)  PyUnicode_Format(a, b)
#else
  #define __Pyx_PyString_Format(a, b)  PyString_Format(a, b)
#endif
#if PY_MAJOR_VERSION >= 3
  #define PyBaseString_Type            PyUnicode_Type
  #define PyStringObject               PyUnicodeObject
  #define PyString_Type                PyUnicode_Type
  #define PyString_Check               PyUnicode_Check
  #define PyString_CheckExact          PyUnicode_CheckExact
#endif
#if PY_VERSION_HEX < 0x02060000
  #define PyBytesObject                PyStringObject
  #define PyBytes_Type                 PyString_Type
  #define PyBytes_Check                PyString_Check
  #define PyBytes_CheckExact           PyString_CheckExact
  #define PyBytes_FromString           PyString_FromString
  #define PyBytes_FromStringAndSize    PyString_FromStringAndSize
  #define PyBytes_FromFormat           PyString_FromFormat
  #define PyBytes_DecodeEscape         PyString_DecodeEscape
  #define PyBytes_AsString             PyString_AsString
  #define PyBytes_AsStringAndSize      PyString_AsStringAndSize
  #define PyBytes_Size                 PyString_Size
  #define PyBytes_AS_STRING            PyString_AS_STRING
  #define PyBytes_GET_SIZE             PyString_GET_SIZE
  #define PyBytes_Repr                 PyString_Repr
  #define PyBytes_Concat               PyString_Concat
  #define PyBytes_ConcatAndDel         PyString_ConcatAndDel
#endif
#if PY_MAJOR_VERSION >= 3
  #define __Pyx_PyBaseString_Check(obj) PyUnicode_Check(obj)
  #define __Pyx_PyBaseString_CheckExact(obj) PyUnicode_CheckExact(obj)
#else
  #define __Pyx_PyBaseString_Check(obj) (PyString_CheckExact(obj) || PyUnicode_CheckExact(obj) || \
                                         PyString_Check(obj) || PyUnicode_Check(obj))
  #define __Pyx_PyBaseString_CheckExact(obj) (PyString_CheckExact(obj) || PyUnicode_CheckExact(obj))
#endif
#if PY_VERSION_HEX < 0x02060000
  #define PySet_Check(obj)             PyObject_TypeCheck(obj, &PySet_Type)
  #define PyFrozenSet_Check(obj)       PyObject_TypeCheck(obj, &PyFrozenSet_Type)
#endif
#ifndef PySet_CheckExact
  #define PySet_CheckExact(obj)        (Py_TYPE(obj) == &PySet_Type)
#endif
#define __Pyx_TypeCheck(obj, type) PyObject_TypeCheck(obj, (PyTypeObject *)type)
#if PY_MAJOR_VERSION >= 3
  #define PyIntObject                  PyLongObject
  #define PyInt_Type                   PyLong_Type
  #define PyInt_Check(op)              PyLong_Check(op)
  #define PyInt_CheckExact(op)         PyLong_CheckExact(op)
  #define PyInt_FromString             PyLong_FromString
  #define PyInt_FromUnicode            PyLong_FromUnicode
  #define PyInt_FromLong               PyLong_FromLong
  #define PyInt_FromSize_t             PyLong_FromSize_t
  #define PyInt_FromSsize_t            PyLong_FromSsize_t
  #define PyInt_AsLong                 PyLong_AsLong
  #define PyInt_AS_LONG                PyLong_AS_LONG
  #define PyInt_AsSsize_t              PyLong_AsSsize_t
  #define PyInt_AsUnsignedLongMask     PyLong_AsUnsignedLongMask
  #define PyInt_AsUnsignedLongLongMask PyLong_AsUnsignedLongLongMask
  #define PyNumber_Int                 PyNumber_Long
#endif
#if PY_MAJOR_VERSION >= 3
  #define PyBoolObject                 PyLongObject
#endif
#if PY_VERSION_HEX < 0x030200A4
  typedef long Py_hash_t;
  #define __Pyx_PyInt_FromHash_t PyInt_FromLong
  #define __Pyx_PyInt_AsHash_t   PyInt_AsLong
#else
  #define __Pyx_PyInt_FromHash_t PyInt_FromSsize_t
  #define __Pyx_PyInt_AsHash_t   PyInt_AsSsize_t
#endif
#if (PY_MAJOR_VERSION < 3) || (PY_VERSION_HEX >= 0x03010300)
  #define __Pyx_PySequence_GetSlice(obj, a, b) PySequence_GetSlice(obj, a, b)
  #define __Pyx_PySequence_SetSlice(obj, a, b, value) PySequence_SetSlice(obj, a, b, value)
  #define __Pyx_PySequence_DelSlice(obj, a, b) PySequence_DelSlice(obj, a, b)
#else
  #define __Pyx_PySequence_GetSlice(obj, a, b) (unlikely(!(obj)) ? \
        (PyErr_SetString(PyExc_SystemError, "null argument to internal routine"), (PyObject*)0) : \
        (likely((obj)->ob_type->tp_as_mapping) ? (PySequence_GetSlice(obj, a, b)) : \
            (PyErr_Format(PyExc_TypeError, "'%.200s' object is unsliceable", (obj)->ob_type->tp_name), (PyObject*)0)))
  #define __Pyx_PySequence_SetSlice(obj, a, b, value) (unlikely(!(obj)) ? \
        (PyErr_SetString(PyExc_SystemError, "null argument to internal routine"), -1) : \
        (likely((obj)->ob_type->tp_as_mapping) ? (PySequence_SetSlice(obj, a, b, value)) : \
            (PyErr_Format(PyExc_TypeError, "'%.200s' object doesn't support slice assignment", (obj)->ob_type->tp_name), -1)))
  #define __Pyx_PySequence_DelSlice(obj, a, b) (unlikely(!(obj)) ? \
        (PyErr_SetString(PyExc_SystemError, "null argument to internal routine"), -1) : \
        (likely((obj)->ob_type->tp_as_mapping) ? (PySequence_DelSlice(obj, a, b)) : \
            (PyErr_Format(PyExc_TypeError, "'%.200s' object doesn't support slice deletion", (obj)->ob_type->tp_name), -1)))
#endif
#if PY_MAJOR_VERSION >= 3
  #define PyMethod_New(func, self, klass) ((self) ? PyMethod_New(func, self) : PyInstanceMethod_New(func))
#endif
#if PY_VERSION_HEX < 0x02050000
  #define __Pyx_GetAttrString(o,n)   PyObject_GetAttrString((o),((char *)(n)))
  #define __Pyx_SetAttrString(o,n,a) PyObject_SetAttrString((o),((char *)(n)),(a))
  #define __Pyx_DelAttrString(o,n)   PyObject_DelAttrString((o),((char *)(n)))
#else
  #define __Pyx_GetAttrString(o,n)   PyObject_GetAttrString((o),(n))
  #define __Pyx_SetAttrString(o,n,a) PyObject_SetAttrString((o),(n),(a))
  #define __Pyx_DelAttrString(o,n)   PyObject_DelAttrString((o),(n))
#endif
#if PY_VERSION_HEX < 0x02050000
  #define __Pyx_NAMESTR(n) ((char *)(n))
  #define __Pyx_DOCSTR(n)  ((char *)(n))
#else
  #define __Pyx_NAMESTR(n) (n)
  #define __Pyx_DOCSTR(n)  (n)
#endif
#ifndef CYTHON_INLINE
  #if defined(__GNUC__)
    #define CYTHON_INLINE __inline__
  #elif defined(_MSC_VER)
    #define CYTHON_INLINE __inline
  #elif defined (__STDC_VERSION__) && __STDC_VERSION__ >= 199901L
    #define CYTHON_INLINE inline
  #else
    #define CYTHON_INLINE
  #endif
#endif
#ifndef CYTHON_RESTRICT
  #if defined(__GNUC__)
    #define CYTHON_RESTRICT __restrict__
  #elif defined(_MSC_VER) && _MSC_VER >= 1400
    #define CYTHON_RESTRICT __restrict
  #elif defined (__STDC_VERSION__) && __STDC_VERSION__ >= 199901L
    #define CYTHON_RESTRICT restrict
  #else
    #define CYTHON_RESTRICT
  #endif
#endif
#ifdef NAN
#define __PYX_NAN() ((float) NAN)
#else
static CYTHON_INLINE float __PYX_NAN() {
  /* Initialize NaN. The sign is irrelevant, an exponent with all bits 1 and
   a nonzero mantissa means NaN. If the first bit in the mantissa is 1, it is
   a quiet NaN. */
  float value;
  memset(&value, 0xFF, sizeof(value));
  return value;
}
#endif


#if PY_MAJOR_VERSION >= 3
  #define __Pyx_PyNumber_Divide(x,y)         PyNumber_TrueDivide(x,y)
  #define __Pyx_PyNumber_InPlaceDivide(x,y)  PyNumber_InPlaceTrueDivide(x,y)
#else
  #define __Pyx_PyNumber_Divide(x,y)         PyNumber_Divide(x,y)
  #define __Pyx_PyNumber_InPlaceDivide(x,y)  PyNumber_InPlaceDivide(x,y)
#endif

#ifndef __PYX_EXTERN_C
  #ifdef __cplusplus
    #define __PYX_EXTERN_C extern "C"
  #else
    #define __PYX_EXTERN_C extern
  #endif
#endif

#if defined(WIN32) || defined(MS_WINDOWS)
#define _USE_MATH_DEFINES
#endif
#include <math.h>
#define __PYX_HAVE__sklearn__tree___tree
#define __PYX_HAVE_API__sklearn__tree___tree
#include "string.h"
#include "stdio.h"
#include "stdlib.h"
#include "numpy/arrayobject.h"
#include "numpy/ufuncobject.h"
#include "math.h"
#include "pythread.h"
#ifdef _OPENMP
#include <omp.h>
#endif /* _OPENMP */

#ifdef PYREX_WITHOUT_ASSERTIONS
#define CYTHON_WITHOUT_ASSERTIONS
#endif

#ifndef CYTHON_UNUSED
# if defined(__GNUC__)
#   if !(defined(__cplusplus)) || (__GNUC__ > 3 || (__GNUC__ == 3 && __GNUC_MINOR__ >= 4))
#     define CYTHON_UNUSED __attribute__ ((__unused__))
#   else
#     define CYTHON_UNUSED
#   endif
# elif defined(__ICC) || (defined(__INTEL_COMPILER) && !defined(_MSC_VER))
#   define CYTHON_UNUSED __attribute__ ((__unused__))
# else
#   define CYTHON_UNUSED
# endif
#endif
typedef struct {PyObject **p; char *s; const Py_ssize_t n; const char* encoding;
                const char is_unicode; const char is_str; const char intern; } __Pyx_StringTabEntry; /*proto*/

#define __PYX_DEFAULT_STRING_ENCODING_IS_ASCII 0
#define __PYX_DEFAULT_STRING_ENCODING_IS_DEFAULT 0
#define __PYX_DEFAULT_STRING_ENCODING ""
#define __Pyx_PyObject_FromString __Pyx_PyBytes_FromString
#define __Pyx_PyObject_FromStringAndSize __Pyx_PyBytes_FromStringAndSize
#define __Pyx_fits_Py_ssize_t(v, type, is_signed)  (    \
    (sizeof(type) < sizeof(Py_ssize_t))  ||             \
    (sizeof(type) > sizeof(Py_ssize_t) &&               \
          likely(v < (type)PY_SSIZE_T_MAX ||            \
                 v == (type)PY_SSIZE_T_MAX)  &&         \
          (!is_signed || likely(v > (type)PY_SSIZE_T_MIN ||       \
                                v == (type)PY_SSIZE_T_MIN)))  ||  \
    (sizeof(type) == sizeof(Py_ssize_t) &&              \
          (is_signed || likely(v < (type)PY_SSIZE_T_MAX ||        \
                               v == (type)PY_SSIZE_T_MAX)))  )
static CYTHON_INLINE char* __Pyx_PyObject_AsString(PyObject*);
static CYTHON_INLINE char* __Pyx_PyObject_AsStringAndSize(PyObject*, Py_ssize_t* length);
#define __Pyx_PyByteArray_FromString(s) PyByteArray_FromStringAndSize((const char*)s, strlen((const char*)s))
#define __Pyx_PyByteArray_FromStringAndSize(s, l) PyByteArray_FromStringAndSize((const char*)s, l)
#define __Pyx_PyBytes_FromString        PyBytes_FromString
#define __Pyx_PyBytes_FromStringAndSize PyBytes_FromStringAndSize
static CYTHON_INLINE PyObject* __Pyx_PyUnicode_FromString(char*);
#if PY_MAJOR_VERSION < 3
    #define __Pyx_PyStr_FromString        __Pyx_PyBytes_FromString
    #define __Pyx_PyStr_FromStringAndSize __Pyx_PyBytes_FromStringAndSize
#else
    #define __Pyx_PyStr_FromString        __Pyx_PyUnicode_FromString
    #define __Pyx_PyStr_FromStringAndSize __Pyx_PyUnicode_FromStringAndSize
#endif
#define __Pyx_PyObject_AsSString(s)    ((signed char*) __Pyx_PyObject_AsString(s))
#define __Pyx_PyObject_AsUString(s)    ((unsigned char*) __Pyx_PyObject_AsString(s))
#define __Pyx_PyObject_FromUString(s)  __Pyx_PyObject_FromString((char*)s)
#define __Pyx_PyBytes_FromUString(s)   __Pyx_PyBytes_FromString((char*)s)
#define __Pyx_PyByteArray_FromUString(s)   __Pyx_PyByteArray_FromString((char*)s)
#define __Pyx_PyStr_FromUString(s)     __Pyx_PyStr_FromString((char*)s)
#define __Pyx_PyUnicode_FromUString(s) __Pyx_PyUnicode_FromString((char*)s)
#if PY_MAJOR_VERSION < 3
static CYTHON_INLINE size_t __Pyx_Py_UNICODE_strlen(const Py_UNICODE *u)
{
    const Py_UNICODE *u_end = u;
    while (*u_end++) ;
    return u_end - u - 1;
}
#else
#define __Pyx_Py_UNICODE_strlen Py_UNICODE_strlen
#endif
#define __Pyx_PyUnicode_FromUnicode(u)       PyUnicode_FromUnicode(u, __Pyx_Py_UNICODE_strlen(u))
#define __Pyx_PyUnicode_FromUnicodeAndLength PyUnicode_FromUnicode
#define __Pyx_PyUnicode_AsUnicode            PyUnicode_AsUnicode
#define __Pyx_Owned_Py_None(b) (Py_INCREF(Py_None), Py_None)
#define __Pyx_PyBool_FromLong(b) ((b) ? (Py_INCREF(Py_True), Py_True) : (Py_INCREF(Py_False), Py_False))
static CYTHON_INLINE int __Pyx_PyObject_IsTrue(PyObject*);
static CYTHON_INLINE PyObject* __Pyx_PyNumber_Int(PyObject* x);
static CYTHON_INLINE Py_ssize_t __Pyx_PyIndex_AsSsize_t(PyObject*);
static CYTHON_INLINE PyObject * __Pyx_PyInt_FromSize_t(size_t);
#if CYTHON_COMPILING_IN_CPYTHON
#define __pyx_PyFloat_AsDouble(x) (PyFloat_CheckExact(x) ? PyFloat_AS_DOUBLE(x) : PyFloat_AsDouble(x))
#else
#define __pyx_PyFloat_AsDouble(x) PyFloat_AsDouble(x)
#endif
#define __pyx_PyFloat_AsFloat(x) ((float) __pyx_PyFloat_AsDouble(x))
#if PY_MAJOR_VERSION < 3 && __PYX_DEFAULT_STRING_ENCODING_IS_ASCII
static int __Pyx_sys_getdefaultencoding_not_ascii;
static int __Pyx_init_sys_getdefaultencoding_params(void) {
    PyObject* sys = NULL;
    PyObject* default_encoding = NULL;
    PyObject* ascii_chars_u = NULL;
    PyObject* ascii_chars_b = NULL;
    sys = PyImport_ImportModule("sys");
    if (sys == NULL) goto bad;
    default_encoding = PyObject_CallMethod(sys, (char*) (const char*) "getdefaultencoding", NULL);
    if (default_encoding == NULL) goto bad;
    if (strcmp(PyBytes_AsString(default_encoding), "ascii") == 0) {
        __Pyx_sys_getdefaultencoding_not_ascii = 0;
    } else {
        const char* default_encoding_c = PyBytes_AS_STRING(default_encoding);
        char ascii_chars[128];
        int c;
        for (c = 0; c < 128; c++) {
            ascii_chars[c] = c;
        }
        __Pyx_sys_getdefaultencoding_not_ascii = 1;
        ascii_chars_u = PyUnicode_DecodeASCII(ascii_chars, 128, NULL);
        if (ascii_chars_u == NULL) goto bad;
        ascii_chars_b = PyUnicode_AsEncodedString(ascii_chars_u, default_encoding_c, NULL);
        if (ascii_chars_b == NULL || strncmp(ascii_chars, PyBytes_AS_STRING(ascii_chars_b), 128) != 0) {
            PyErr_Format(
                PyExc_ValueError,
                "This module compiled with c_string_encoding=ascii, but default encoding '%.200s' is not a superset of ascii.",
                default_encoding_c);
            goto bad;
        }
    }
    Py_XDECREF(sys);
    Py_XDECREF(default_encoding);
    Py_XDECREF(ascii_chars_u);
    Py_XDECREF(ascii_chars_b);
    return 0;
bad:
    Py_XDECREF(sys);
    Py_XDECREF(default_encoding);
    Py_XDECREF(ascii_chars_u);
    Py_XDECREF(ascii_chars_b);
    return -1;
}
#endif
#if __PYX_DEFAULT_STRING_ENCODING_IS_DEFAULT && PY_MAJOR_VERSION >= 3
#define __Pyx_PyUnicode_FromStringAndSize(c_str, size) PyUnicode_DecodeUTF8(c_str, size, NULL)
#else
#define __Pyx_PyUnicode_FromStringAndSize(c_str, size) PyUnicode_Decode(c_str, size, __PYX_DEFAULT_STRING_ENCODING, NULL)
#if __PYX_DEFAULT_STRING_ENCODING_IS_DEFAULT
static char* __PYX_DEFAULT_STRING_ENCODING;
static int __Pyx_init_sys_getdefaultencoding_params(void) {
    PyObject* sys = NULL;
    PyObject* default_encoding = NULL;
    char* default_encoding_c;
    sys = PyImport_ImportModule("sys");
    if (sys == NULL) goto bad;
    default_encoding = PyObject_CallMethod(sys, (char*) (const char*) "getdefaultencoding", NULL);
    if (default_encoding == NULL) goto bad;
    default_encoding_c = PyBytes_AS_STRING(default_encoding);
    __PYX_DEFAULT_STRING_ENCODING = (char*) malloc(strlen(default_encoding_c));
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bad:
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    Py_XDECREF(default_encoding);
    return -1;
}
#endif
#endif


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  /* Test for GCC > 2.95 */
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    #define likely(x)   __builtin_expect(!!(x), 1)
    #define unlikely(x) __builtin_expect(!!(x), 0)
  #else /* __GNUC__ > 2 ... */
    #define likely(x)   (x)
    #define unlikely(x) (x)
  #endif /* __GNUC__ > 2 ... */
#else /* __GNUC__ */
  #define likely(x)   (x)
  #define unlikely(x) (x)
#endif /* __GNUC__ */

static PyObject *__pyx_m;
static PyObject *__pyx_d;
static PyObject *__pyx_b;
static PyObject *__pyx_empty_tuple;
static PyObject *__pyx_empty_bytes;
static int __pyx_lineno;
static int __pyx_clineno = 0;
static const char * __pyx_cfilenm= __FILE__;
static const char *__pyx_filename;

#if !defined(CYTHON_CCOMPLEX)
  #if defined(__cplusplus)
    #define CYTHON_CCOMPLEX 1
  #elif defined(_Complex_I)
    #define CYTHON_CCOMPLEX 1
  #else
    #define CYTHON_CCOMPLEX 0
  #endif
#endif
#if CYTHON_CCOMPLEX
  #ifdef __cplusplus
    #include <complex>
  #else
    #include <complex.h>
  #endif
#endif
#if CYTHON_CCOMPLEX && !defined(__cplusplus) && defined(__sun__) && defined(__GNUC__)
  #undef _Complex_I
  #define _Complex_I 1.0fj
#endif


static const char *__pyx_f[] = {
  "_tree.pyx",
  "_tree.pxd",
  "__init__.pxd",
  "type.pxd",
  "bool.pxd",
  "complex.pxd",
  "_utils.pxd",
};
#define IS_UNSIGNED(type) (((type) -1) > 0)
struct __Pyx_StructField_;
#define __PYX_BUF_FLAGS_PACKED_STRUCT (1 << 0)
typedef struct {
  const char* name; /* for error messages only */
  struct __Pyx_StructField_* fields;
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  char is_unsigned;
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} __Pyx_TypeInfo;
typedef struct __Pyx_StructField_ {
  __Pyx_TypeInfo* type;
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typedef struct {
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} __Pyx_BufFmt_Context;


/* "/usr/local/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":723
 * # in Cython to enable them only on the right systems.
 * 
 * ctypedef npy_int8       int8_t             # <<<<<<<<<<<<<<
 * ctypedef npy_int16      int16_t
 * ctypedef npy_int32      int32_t
 */
typedef npy_int8 __pyx_t_5numpy_int8_t;

/* "/usr/local/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":724
 * 
 * ctypedef npy_int8       int8_t
 * ctypedef npy_int16      int16_t             # <<<<<<<<<<<<<<
 * ctypedef npy_int32      int32_t
 * ctypedef npy_int64      int64_t
 */
typedef npy_int16 __pyx_t_5numpy_int16_t;

/* "/usr/local/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":725
 * ctypedef npy_int8       int8_t
 * ctypedef npy_int16      int16_t
 * ctypedef npy_int32      int32_t             # <<<<<<<<<<<<<<
 * ctypedef npy_int64      int64_t
 * #ctypedef npy_int96      int96_t
 */
typedef npy_int32 __pyx_t_5numpy_int32_t;

/* "/usr/local/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":726
 * ctypedef npy_int16      int16_t
 * ctypedef npy_int32      int32_t
 * ctypedef npy_int64      int64_t             # <<<<<<<<<<<<<<
 * #ctypedef npy_int96      int96_t
 * #ctypedef npy_int128     int128_t
 */
typedef npy_int64 __pyx_t_5numpy_int64_t;

/* "/usr/local/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":730
 * #ctypedef npy_int128     int128_t
 * 
 * ctypedef npy_uint8      uint8_t             # <<<<<<<<<<<<<<
 * ctypedef npy_uint16     uint16_t
 * ctypedef npy_uint32     uint32_t
 */
typedef npy_uint8 __pyx_t_5numpy_uint8_t;

/* "/usr/local/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":731
 * 
 * ctypedef npy_uint8      uint8_t
 * ctypedef npy_uint16     uint16_t             # <<<<<<<<<<<<<<
 * ctypedef npy_uint32     uint32_t
 * ctypedef npy_uint64     uint64_t
 */
typedef npy_uint16 __pyx_t_5numpy_uint16_t;

/* "/usr/local/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":732
 * ctypedef npy_uint8      uint8_t
 * ctypedef npy_uint16     uint16_t
 * ctypedef npy_uint32     uint32_t             # <<<<<<<<<<<<<<
 * ctypedef npy_uint64     uint64_t
 * #ctypedef npy_uint96     uint96_t
 */
typedef npy_uint32 __pyx_t_5numpy_uint32_t;

/* "/usr/local/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":733
 * ctypedef npy_uint16     uint16_t
 * ctypedef npy_uint32     uint32_t
 * ctypedef npy_uint64     uint64_t             # <<<<<<<<<<<<<<
 * #ctypedef npy_uint96     uint96_t
 * #ctypedef npy_uint128    uint128_t
 */
typedef npy_uint64 __pyx_t_5numpy_uint64_t;

/* "/usr/local/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":737
 * #ctypedef npy_uint128    uint128_t
 * 
 * ctypedef npy_float32    float32_t             # <<<<<<<<<<<<<<
 * ctypedef npy_float64    float64_t
 * #ctypedef npy_float80    float80_t
 */
typedef npy_float32 __pyx_t_5numpy_float32_t;

/* "/usr/local/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":738
 * 
 * ctypedef npy_float32    float32_t
 * ctypedef npy_float64    float64_t             # <<<<<<<<<<<<<<
 * #ctypedef npy_float80    float80_t
 * #ctypedef npy_float128   float128_t
 */
typedef npy_float64 __pyx_t_5numpy_float64_t;

/* "/usr/local/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":747
 * # The int types are mapped a bit surprising --
 * # numpy.int corresponds to 'l' and numpy.long to 'q'
 * ctypedef npy_long       int_t             # <<<<<<<<<<<<<<
 * ctypedef npy_longlong   long_t
 * ctypedef npy_longlong   longlong_t
 */
typedef npy_long __pyx_t_5numpy_int_t;

/* "/usr/local/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":748
 * # numpy.int corresponds to 'l' and numpy.long to 'q'
 * ctypedef npy_long       int_t
 * ctypedef npy_longlong   long_t             # <<<<<<<<<<<<<<
 * ctypedef npy_longlong   longlong_t
 * 
 */
typedef npy_longlong __pyx_t_5numpy_long_t;

/* "/usr/local/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":749
 * ctypedef npy_long       int_t
 * ctypedef npy_longlong   long_t
 * ctypedef npy_longlong   longlong_t             # <<<<<<<<<<<<<<
 * 
 * ctypedef npy_ulong      uint_t
 */
typedef npy_longlong __pyx_t_5numpy_longlong_t;

/* "/usr/local/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":751
 * ctypedef npy_longlong   longlong_t
 * 
 * ctypedef npy_ulong      uint_t             # <<<<<<<<<<<<<<
 * ctypedef npy_ulonglong  ulong_t
 * ctypedef npy_ulonglong  ulonglong_t
 */
typedef npy_ulong __pyx_t_5numpy_uint_t;

/* "/usr/local/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":752
 * 
 * ctypedef npy_ulong      uint_t
 * ctypedef npy_ulonglong  ulong_t             # <<<<<<<<<<<<<<
 * ctypedef npy_ulonglong  ulonglong_t
 * 
 */
typedef npy_ulonglong __pyx_t_5numpy_ulong_t;

/* "/usr/local/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":753
 * ctypedef npy_ulong      uint_t
 * ctypedef npy_ulonglong  ulong_t
 * ctypedef npy_ulonglong  ulonglong_t             # <<<<<<<<<<<<<<
 * 
 * ctypedef npy_intp       intp_t
 */
typedef npy_ulonglong __pyx_t_5numpy_ulonglong_t;

/* "/usr/local/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":755
 * ctypedef npy_ulonglong  ulonglong_t
 * 
 * ctypedef npy_intp       intp_t             # <<<<<<<<<<<<<<
 * ctypedef npy_uintp      uintp_t
 * 
 */
typedef npy_intp __pyx_t_5numpy_intp_t;

/* "/usr/local/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":756
 * 
 * ctypedef npy_intp       intp_t
 * ctypedef npy_uintp      uintp_t             # <<<<<<<<<<<<<<
 * 
 * ctypedef npy_double     float_t
 */
typedef npy_uintp __pyx_t_5numpy_uintp_t;

/* "/usr/local/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":758
 * ctypedef npy_uintp      uintp_t
 * 
 * ctypedef npy_double     float_t             # <<<<<<<<<<<<<<
 * ctypedef npy_double     double_t
 * ctypedef npy_longdouble longdouble_t
 */
typedef npy_double __pyx_t_5numpy_float_t;

/* "/usr/local/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":759
 * 
 * ctypedef npy_double     float_t
 * ctypedef npy_double     double_t             # <<<<<<<<<<<<<<
 * ctypedef npy_longdouble longdouble_t
 * 
 */
typedef npy_double __pyx_t_5numpy_double_t;

/* "/usr/local/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":760
 * ctypedef npy_double     float_t
 * ctypedef npy_double     double_t
 * ctypedef npy_longdouble longdouble_t             # <<<<<<<<<<<<<<
 * 
 * ctypedef npy_cfloat      cfloat_t
 */
typedef npy_longdouble __pyx_t_5numpy_longdouble_t;

/* "sklearn/tree/_utils.pxd":12
 * cimport numpy as np
 * 
 * ctypedef np.npy_intp SIZE_t              # Type for indices and counters             # <<<<<<<<<<<<<<
 * 
 * 
 */
typedef npy_intp __pyx_t_7sklearn_4tree_6_utils_SIZE_t;

/* "sklearn/tree/_tree.pxd":14
 * cimport numpy as np
 * 
 * ctypedef np.npy_float32 DTYPE_t          # Type of X             # <<<<<<<<<<<<<<
 * ctypedef np.npy_float64 DOUBLE_t         # Type of y, sample_weight
 * ctypedef np.npy_intp SIZE_t              # Type for indices and counters
 */
typedef npy_float32 __pyx_t_7sklearn_4tree_5_tree_DTYPE_t;

/* "sklearn/tree/_tree.pxd":15
 * 
 * ctypedef np.npy_float32 DTYPE_t          # Type of X
 * ctypedef np.npy_float64 DOUBLE_t         # Type of y, sample_weight             # <<<<<<<<<<<<<<
 * ctypedef np.npy_intp SIZE_t              # Type for indices and counters
 * ctypedef np.npy_int32 INT32_t            # Signed 32 bit integer
 */
typedef npy_float64 __pyx_t_7sklearn_4tree_5_tree_DOUBLE_t;

/* "sklearn/tree/_tree.pxd":16
 * ctypedef np.npy_float32 DTYPE_t          # Type of X
 * ctypedef np.npy_float64 DOUBLE_t         # Type of y, sample_weight
 * ctypedef np.npy_intp SIZE_t              # Type for indices and counters             # <<<<<<<<<<<<<<
 * ctypedef np.npy_int32 INT32_t            # Signed 32 bit integer
 * ctypedef np.npy_uint32 UINT32_t          # Unsigned 32 bit integer
 */
typedef npy_intp __pyx_t_7sklearn_4tree_5_tree_SIZE_t;

/* "sklearn/tree/_tree.pxd":17
 * ctypedef np.npy_float64 DOUBLE_t         # Type of y, sample_weight
 * ctypedef np.npy_intp SIZE_t              # Type for indices and counters
 * ctypedef np.npy_int32 INT32_t            # Signed 32 bit integer             # <<<<<<<<<<<<<<
 * ctypedef np.npy_uint32 UINT32_t          # Unsigned 32 bit integer
 * 
 */
typedef npy_int32 __pyx_t_7sklearn_4tree_5_tree_INT32_t;

/* "sklearn/tree/_tree.pxd":18
 * ctypedef np.npy_intp SIZE_t              # Type for indices and counters
 * ctypedef np.npy_int32 INT32_t            # Signed 32 bit integer
 * ctypedef np.npy_uint32 UINT32_t          # Unsigned 32 bit integer             # <<<<<<<<<<<<<<
 * 
 * 
 */
typedef npy_uint32 __pyx_t_7sklearn_4tree_5_tree_UINT32_t;
#if CYTHON_CCOMPLEX
  #ifdef __cplusplus
    typedef ::std::complex< float > __pyx_t_float_complex;
  #else
    typedef float _Complex __pyx_t_float_complex;
  #endif
#else
    typedef struct { float real, imag; } __pyx_t_float_complex;
#endif

#if CYTHON_CCOMPLEX
  #ifdef __cplusplus
    typedef ::std::complex< double > __pyx_t_double_complex;
  #else
    typedef double _Complex __pyx_t_double_complex;
  #endif
#else
    typedef struct { double real, imag; } __pyx_t_double_complex;
#endif


/*--- Type declarations ---*/
struct __pyx_obj_7sklearn_4tree_6_utils_Stack;
struct __pyx_obj_7sklearn_4tree_6_utils_PriorityHeap;
struct __pyx_obj_7sklearn_4tree_5_tree_Criterion;
struct __pyx_obj_7sklearn_4tree_5_tree_Splitter;
struct __pyx_obj_7sklearn_4tree_5_tree_Tree;
struct __pyx_obj_7sklearn_4tree_5_tree_TreeBuilder;
struct __pyx_obj_7sklearn_4tree_5_tree_ClassificationCriterion;
struct __pyx_obj_7sklearn_4tree_5_tree_Entropy;
struct __pyx_obj_7sklearn_4tree_5_tree_Gini;
struct __pyx_obj_7sklearn_4tree_5_tree_RegressionCriterion;
struct __pyx_obj_7sklearn_4tree_5_tree_MSE;
struct __pyx_obj_7sklearn_4tree_5_tree_FriedmanMSE;
struct __pyx_obj_7sklearn_4tree_5_tree_BestSplitter;
struct __pyx_obj_7sklearn_4tree_5_tree_RandomSplitter;
struct __pyx_obj_7sklearn_4tree_5_tree_PresortBestSplitter;
struct __pyx_obj_7sklearn_4tree_5_tree_DepthFirstTreeBuilder;
struct __pyx_obj_7sklearn_4tree_5_tree_BestFirstTreeBuilder;

/* "/usr/local/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":762
 * ctypedef npy_longdouble longdouble_t
 * 
 * ctypedef npy_cfloat      cfloat_t             # <<<<<<<<<<<<<<
 * ctypedef npy_cdouble     cdouble_t
 * ctypedef npy_clongdouble clongdouble_t
 */
typedef npy_cfloat __pyx_t_5numpy_cfloat_t;

/* "/usr/local/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":763
 * 
 * ctypedef npy_cfloat      cfloat_t
 * ctypedef npy_cdouble     cdouble_t             # <<<<<<<<<<<<<<
 * ctypedef npy_clongdouble clongdouble_t
 * 
 */
typedef npy_cdouble __pyx_t_5numpy_cdouble_t;

/* "/usr/local/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":764
 * ctypedef npy_cfloat      cfloat_t
 * ctypedef npy_cdouble     cdouble_t
 * ctypedef npy_clongdouble clongdouble_t             # <<<<<<<<<<<<<<
 * 
 * ctypedef npy_cdouble     complex_t
 */
typedef npy_clongdouble __pyx_t_5numpy_clongdouble_t;

/* "/usr/local/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":766
 * ctypedef npy_clongdouble clongdouble_t
 * 
 * ctypedef npy_cdouble     complex_t             # <<<<<<<<<<<<<<
 * 
 * cdef inline object PyArray_MultiIterNew1(a):
 */
typedef npy_cdouble __pyx_t_5numpy_complex_t;
struct __pyx_t_7sklearn_4tree_6_utils_StackRecord;
struct __pyx_t_7sklearn_4tree_6_utils_PriorityHeapRecord;

/* "sklearn/tree/_utils.pxd":20
 * 
 * # A record on the stack for depth-first tree growing
 * cdef struct StackRecord:             # <<<<<<<<<<<<<<
 *     SIZE_t start
 *     SIZE_t end
 */
struct __pyx_t_7sklearn_4tree_6_utils_StackRecord {
  __pyx_t_7sklearn_4tree_6_utils_SIZE_t start;
  __pyx_t_7sklearn_4tree_6_utils_SIZE_t end;
  __pyx_t_7sklearn_4tree_6_utils_SIZE_t depth;
  __pyx_t_7sklearn_4tree_6_utils_SIZE_t parent;
  int is_left;
  double impurity;
  __pyx_t_7sklearn_4tree_6_utils_SIZE_t n_constant_features;
};

/* "sklearn/tree/_utils.pxd":46
 * 
 * # A record on the frontier for best-first tree growing
 * cdef struct PriorityHeapRecord:             # <<<<<<<<<<<<<<
 *     SIZE_t node_id
 *     SIZE_t start
 */
struct __pyx_t_7sklearn_4tree_6_utils_PriorityHeapRecord {
  __pyx_t_7sklearn_4tree_6_utils_SIZE_t node_id;
  __pyx_t_7sklearn_4tree_6_utils_SIZE_t start;
  __pyx_t_7sklearn_4tree_6_utils_SIZE_t end;
  __pyx_t_7sklearn_4tree_6_utils_SIZE_t pos;
  __pyx_t_7sklearn_4tree_6_utils_SIZE_t depth;
  int is_leaf;
  double impurity;
  double impurity_left;
  double impurity_right;
  double improvement;
};
struct __pyx_t_7sklearn_4tree_5_tree_SplitRecord;
struct __pyx_t_7sklearn_4tree_5_tree_Node;
struct __pyx_opt_args_7sklearn_4tree_5_tree_4Tree__resize_c;
struct __pyx_opt_args_7sklearn_4tree_5_tree_4Tree_compute_feature_importances;
struct __pyx_opt_args_7sklearn_4tree_5_tree_11TreeBuilder_build;
struct __pyx_opt_args_7sklearn_4tree_5_tree_21DepthFirstTreeBuilder_build;
struct __pyx_opt_args_7sklearn_4tree_5_tree_20BestFirstTreeBuilder_build;

/* "sklearn/tree/_tree.pxd":67
 * # =============================================================================
 * 
 * cdef struct SplitRecord:             # <<<<<<<<<<<<<<
 *     # Data to track sample split
 *     SIZE_t feature         # Which feature to split on.
 */
struct __pyx_t_7sklearn_4tree_5_tree_SplitRecord {
  __pyx_t_7sklearn_4tree_5_tree_SIZE_t feature;
  __pyx_t_7sklearn_4tree_5_tree_SIZE_t pos;
  double threshold;
  double improvement;
  double impurity_left;
  double impurity_right;
};

/* "sklearn/tree/_tree.pxd":146
 * # =============================================================================
 * 
 * cdef struct Node:             # <<<<<<<<<<<<<<
 *     # Base storage structure for the nodes in a Tree object
 * 
 */
struct __pyx_t_7sklearn_4tree_5_tree_Node {
  __pyx_t_7sklearn_4tree_5_tree_SIZE_t left_child;
  __pyx_t_7sklearn_4tree_5_tree_SIZE_t right_child;
  __pyx_t_7sklearn_4tree_5_tree_SIZE_t feature;
  __pyx_t_7sklearn_4tree_5_tree_DOUBLE_t threshold;
  __pyx_t_7sklearn_4tree_5_tree_DOUBLE_t impurity;
  __pyx_t_7sklearn_4tree_5_tree_SIZE_t n_node_samples;
  __pyx_t_7sklearn_4tree_5_tree_DOUBLE_t weighted_n_node_samples;
};

/* "sklearn/tree/_tree.pxd":183
 *                           double weighted_n_samples) nogil
 *     cdef void _resize(self, SIZE_t capacity)
 *     cdef int _resize_c(self, SIZE_t capacity=*) nogil             # <<<<<<<<<<<<<<
 * 
 *     cdef np.ndarray _get_value_ndarray(self)
 */
struct __pyx_opt_args_7sklearn_4tree_5_tree_4Tree__resize_c {
  int __pyx_n;
  __pyx_t_7sklearn_4tree_5_tree_SIZE_t capacity;
};

/* "sklearn/tree/_tree.pxd":190
 *     cpdef np.ndarray predict(self, np.ndarray[DTYPE_t, ndim=2] X)
 *     cpdef np.ndarray apply(self, np.ndarray[DTYPE_t, ndim=2] X)
 *     cpdef compute_feature_importances(self, normalize=*)             # <<<<<<<<<<<<<<
 * 
 * 
 */
struct __pyx_opt_args_7sklearn_4tree_5_tree_4Tree_compute_feature_importances {
  int __pyx_n;
  PyObject *normalize;
};

/* "sklearn/tree/_tree.pxd":211
 *     cdef SIZE_t max_depth           # Maximal tree depth
 * 
 *     cpdef build(self, Tree tree, np.ndarray X, np.ndarray y,             # <<<<<<<<<<<<<<
 *                 np.ndarray sample_weight=*)
 */
struct __pyx_opt_args_7sklearn_4tree_5_tree_11TreeBuilder_build {
  int __pyx_n;
  PyArrayObject *sample_weight;
};

/* "sklearn/tree/_tree.pyx":60
 * cdef int IS_NOT_LEFT = 0
 * 
 * cdef enum:             # <<<<<<<<<<<<<<
 *     # Max value for our rand_r replacement (near the bottom).
 *     # We don't use RAND_MAX because it's different across platforms and
 */
enum  {
  __pyx_e_7sklearn_4tree_5_tree_RAND_R_MAX = 0x7FFFFFFF
};

/* "sklearn/tree/_tree.pyx":1774
 *         self.max_depth = max_depth
 * 
 *     cpdef build(self, Tree tree, np.ndarray X, np.ndarray y,             # <<<<<<<<<<<<<<
 *                 np.ndarray sample_weight=None):
 *         """Build a decision tree from the training set (X, y)."""
 */
struct __pyx_opt_args_7sklearn_4tree_5_tree_21DepthFirstTreeBuilder_build {
  int __pyx_n;
  PyArrayObject *sample_weight;
};

/* "sklearn/tree/_tree.pyx":1933
 *         self.max_leaf_nodes = max_leaf_nodes
 * 
 *     cpdef build(self, Tree tree, np.ndarray X, np.ndarray y,             # <<<<<<<<<<<<<<
 *                 np.ndarray sample_weight=None):
 *         """Build a decision tree from the training set (X, y)."""
 */
struct __pyx_opt_args_7sklearn_4tree_5_tree_20BestFirstTreeBuilder_build {
  int __pyx_n;
  PyArrayObject *sample_weight;
};

/* "sklearn/tree/_utils.pxd":29
 *     SIZE_t n_constant_features
 * 
 * cdef class Stack:             # <<<<<<<<<<<<<<
 *     cdef SIZE_t capacity
 *     cdef SIZE_t top
 */
struct __pyx_obj_7sklearn_4tree_6_utils_Stack {
  PyObject_HEAD
  struct __pyx_vtabstruct_7sklearn_4tree_6_utils_Stack *__pyx_vtab;
  __pyx_t_7sklearn_4tree_6_utils_SIZE_t capacity;
  __pyx_t_7sklearn_4tree_6_utils_SIZE_t top;
  struct __pyx_t_7sklearn_4tree_6_utils_StackRecord *stack_;
};


/* "sklearn/tree/_utils.pxd":58
 *     double improvement
 * 
 * cdef class PriorityHeap:             # <<<<<<<<<<<<<<
 *     cdef SIZE_t capacity
 *     cdef SIZE_t heap_ptr
 */
struct __pyx_obj_7sklearn_4tree_6_utils_PriorityHeap {
  PyObject_HEAD
  struct __pyx_vtabstruct_7sklearn_4tree_6_utils_PriorityHeap *__pyx_vtab;
  __pyx_t_7sklearn_4tree_6_utils_SIZE_t capacity;
  __pyx_t_7sklearn_4tree_6_utils_SIZE_t heap_ptr;
  struct __pyx_t_7sklearn_4tree_6_utils_PriorityHeapRecord *heap_;
};


/* "sklearn/tree/_tree.pxd":25
 * # =============================================================================
 * 
 * cdef class Criterion:             # <<<<<<<<<<<<<<
 *     # The criterion computes the impurity of a node and the reduction of
 *     # impurity of a split on that node. It also computes the output statistics
 */
struct __pyx_obj_7sklearn_4tree_5_tree_Criterion {
  PyObject_HEAD
  struct __pyx_vtabstruct_7sklearn_4tree_5_tree_Criterion *__pyx_vtab;
  __pyx_t_7sklearn_4tree_5_tree_DOUBLE_t *y;
  __pyx_t_7sklearn_4tree_5_tree_SIZE_t y_stride;
  __pyx_t_7sklearn_4tree_5_tree_DOUBLE_t *sample_weight;
  __pyx_t_7sklearn_4tree_5_tree_SIZE_t *samples;
  __pyx_t_7sklearn_4tree_5_tree_SIZE_t start;
  __pyx_t_7sklearn_4tree_5_tree_SIZE_t pos;
  __pyx_t_7sklearn_4tree_5_tree_SIZE_t end;
  __pyx_t_7sklearn_4tree_5_tree_SIZE_t n_outputs;
  __pyx_t_7sklearn_4tree_5_tree_SIZE_t n_node_samples;
  double weighted_n_samples;
  double weighted_n_node_samples;
  double weighted_n_left;
  double weighted_n_right;
};


/* "sklearn/tree/_tree.pxd":79
 * 
 * 
 * cdef class Splitter:             # <<<<<<<<<<<<<<
 *     # The splitter searches in the input space for a feature and a threshold
 *     # to split the samples samples[start:end].
 */
struct __pyx_obj_7sklearn_4tree_5_tree_Splitter {
  PyObject_HEAD
  struct __pyx_vtabstruct_7sklearn_4tree_5_tree_Splitter *__pyx_vtab;
  struct __pyx_obj_7sklearn_4tree_5_tree_Criterion *criterion;
  __pyx_t_7sklearn_4tree_5_tree_SIZE_t max_features;
  __pyx_t_7sklearn_4tree_5_tree_SIZE_t min_samples_leaf;
  PyObject *random_state;
  __pyx_t_7sklearn_4tree_5_tree_UINT32_t rand_r_state;
  __pyx_t_7sklearn_4tree_5_tree_SIZE_t *samples;
  __pyx_t_7sklearn_4tree_5_tree_SIZE_t n_samples;
  double weighted_n_samples;
  __pyx_t_7sklearn_4tree_5_tree_SIZE_t *features;
  __pyx_t_7sklearn_4tree_5_tree_SIZE_t *constant_features;
  __pyx_t_7sklearn_4tree_5_tree_SIZE_t n_features;
  __pyx_t_7sklearn_4tree_5_tree_DTYPE_t *feature_values;
  __pyx_t_7sklearn_4tree_5_tree_SIZE_t start;
  __pyx_t_7sklearn_4tree_5_tree_SIZE_t end;
  __pyx_t_7sklearn_4tree_5_tree_DTYPE_t *X;
  __pyx_t_7sklearn_4tree_5_tree_SIZE_t X_sample_stride;
  __pyx_t_7sklearn_4tree_5_tree_SIZE_t X_fx_stride;
  __pyx_t_7sklearn_4tree_5_tree_DOUBLE_t *y;
  __pyx_t_7sklearn_4tree_5_tree_SIZE_t y_stride;
  __pyx_t_7sklearn_4tree_5_tree_DOUBLE_t *sample_weight;
};


/* "sklearn/tree/_tree.pxd":157
 *     DOUBLE_t weighted_n_node_samples     # Weighted number of samples at the node
 * 
 * cdef class Tree:             # <<<<<<<<<<<<<<
 *     # The Tree object is a binary tree structure constructed by the
 *     # TreeBuilder. The tree structure is used for predictions and
 */
struct __pyx_obj_7sklearn_4tree_5_tree_Tree {
  PyObject_HEAD
  struct __pyx_vtabstruct_7sklearn_4tree_5_tree_Tree *__pyx_vtab;
  __pyx_t_7sklearn_4tree_5_tree_SIZE_t n_features;
  __pyx_t_7sklearn_4tree_5_tree_SIZE_t *n_classes;
  __pyx_t_7sklearn_4tree_5_tree_SIZE_t n_outputs;
  __pyx_t_7sklearn_4tree_5_tree_SIZE_t max_n_classes;
  __pyx_t_7sklearn_4tree_5_tree_SIZE_t max_depth;
  __pyx_t_7sklearn_4tree_5_tree_SIZE_t node_count;
  __pyx_t_7sklearn_4tree_5_tree_SIZE_t capacity;
  struct __pyx_t_7sklearn_4tree_5_tree_Node *nodes;
  double *value;
  __pyx_t_7sklearn_4tree_5_tree_SIZE_t value_stride;
};


/* "sklearn/tree/_tree.pxd":197
 * # =============================================================================
 * 
 * cdef class TreeBuilder:             # <<<<<<<<<<<<<<
 *     # The TreeBuilder recursively builds a Tree object from training samples,
 *     # using a Splitter object for splitting internal nodes and assigning
 */
struct __pyx_obj_7sklearn_4tree_5_tree_TreeBuilder {
  PyObject_HEAD
  struct __pyx_vtabstruct_7sklearn_4tree_5_tree_TreeBuilder *__pyx_vtab;
  struct __pyx_obj_7sklearn_4tree_5_tree_Splitter *splitter;
  __pyx_t_7sklearn_4tree_5_tree_SIZE_t min_samples_split;
  __pyx_t_7sklearn_4tree_5_tree_SIZE_t min_samples_leaf;
  __pyx_t_7sklearn_4tree_5_tree_SIZE_t max_depth;
};


/* "sklearn/tree/_tree.pyx":141
 * 
 * 
 * cdef class ClassificationCriterion(Criterion):             # <<<<<<<<<<<<<<
 *     """Abstract criterion for classification."""
 *     cdef SIZE_t* n_classes
 */
struct __pyx_obj_7sklearn_4tree_5_tree_ClassificationCriterion {
  struct __pyx_obj_7sklearn_4tree_5_tree_Criterion __pyx_base;
  __pyx_t_7sklearn_4tree_5_tree_SIZE_t *n_classes;
  __pyx_t_7sklearn_4tree_5_tree_SIZE_t label_count_stride;
  double *label_count_left;
  double *label_count_right;
  double *label_count_total;
};


/* "sklearn/tree/_tree.pyx":359
 * 
 * 
 * cdef class Entropy(ClassificationCriterion):             # <<<<<<<<<<<<<<
 *     """Cross Entropy impurity criteria.
 * 
 */
struct __pyx_obj_7sklearn_4tree_5_tree_Entropy {
  struct __pyx_obj_7sklearn_4tree_5_tree_ClassificationCriterion __pyx_base;
};


/* "sklearn/tree/_tree.pyx":450
 * 
 * 
 * cdef class Gini(ClassificationCriterion):             # <<<<<<<<<<<<<<
 *     """Gini Index impurity criteria.
 * 
 */
struct __pyx_obj_7sklearn_4tree_5_tree_Gini {
  struct __pyx_obj_7sklearn_4tree_5_tree_ClassificationCriterion __pyx_base;
};


/* "sklearn/tree/_tree.pyx":544
 * 
 * 
 * cdef class RegressionCriterion(Criterion):             # <<<<<<<<<<<<<<
 *     """Abstract criterion for regression.
 * 
 */
struct __pyx_obj_7sklearn_4tree_5_tree_RegressionCriterion {
  struct __pyx_obj_7sklearn_4tree_5_tree_Criterion __pyx_base;
  double *mean_left;
  double *mean_right;
  double *mean_total;
  double *sq_sum_left;
  double *sq_sum_right;
  double *sq_sum_total;
  double *var_left;
  double *var_right;
  double *sum_left;
  double *sum_right;
  double *sum_total;
};


/* "sklearn/tree/_tree.pyx":827
 * 
 * 
 * cdef class MSE(RegressionCriterion):             # <<<<<<<<<<<<<<
 *     """Mean squared error impurity criterion.
 * 
 */
struct __pyx_obj_7sklearn_4tree_5_tree_MSE {
  struct __pyx_obj_7sklearn_4tree_5_tree_RegressionCriterion __pyx_base;
};


/* "sklearn/tree/_tree.pyx":868
 * 
 * 
 * cdef class FriedmanMSE(MSE):             # <<<<<<<<<<<<<<
 *     """Mean squared error impurity criterion with improvement score by Friedman
 * 
 */
struct __pyx_obj_7sklearn_4tree_5_tree_FriedmanMSE {
  struct __pyx_obj_7sklearn_4tree_5_tree_MSE __pyx_base;
};


/* "sklearn/tree/_tree.pyx":1028
 * 
 * 
 * cdef class BestSplitter(Splitter):             # <<<<<<<<<<<<<<
 *     """Splitter for finding the best split."""
 *     def __reduce__(self):
 */
struct __pyx_obj_7sklearn_4tree_5_tree_BestSplitter {
  struct __pyx_obj_7sklearn_4tree_5_tree_Splitter __pyx_base;
};


/* "sklearn/tree/_tree.pyx":1319
 * 
 * 
 * cdef class RandomSplitter(Splitter):             # <<<<<<<<<<<<<<
 *     """Splitter for finding the best random split."""
 *     def __reduce__(self):
 */
struct __pyx_obj_7sklearn_4tree_5_tree_RandomSplitter {
  struct __pyx_obj_7sklearn_4tree_5_tree_Splitter __pyx_base;
};


/* "sklearn/tree/_tree.pyx":1514
 * 
 * 
 * cdef class PresortBestSplitter(Splitter):             # <<<<<<<<<<<<<<
 *     """Splitter for finding the best split, using presorting."""
 *     cdef DTYPE_t* X_old
 */
struct __pyx_obj_7sklearn_4tree_5_tree_PresortBestSplitter {
  struct __pyx_obj_7sklearn_4tree_5_tree_Splitter __pyx_base;
  __pyx_t_7sklearn_4tree_5_tree_DTYPE_t *X_old;
  PyArrayObject *X_argsorted;
  __pyx_t_7sklearn_4tree_5_tree_INT32_t *X_argsorted_ptr;
  __pyx_t_7sklearn_4tree_5_tree_SIZE_t X_argsorted_stride;
  __pyx_t_7sklearn_4tree_5_tree_SIZE_t n_total_samples;
  unsigned char *sample_mask;
};


/* "sklearn/tree/_tree.pyx":1764
 * # Depth first builder ---------------------------------------------------------
 * 
 * cdef class DepthFirstTreeBuilder(TreeBuilder):             # <<<<<<<<<<<<<<
 *     """Build a decision tree in depth-first fashion."""
 * 
 */
struct __pyx_obj_7sklearn_4tree_5_tree_DepthFirstTreeBuilder {
  struct __pyx_obj_7sklearn_4tree_5_tree_TreeBuilder __pyx_base;
};


/* "sklearn/tree/_tree.pyx":1914
 * 
 * 
 * cdef class BestFirstTreeBuilder(TreeBuilder):             # <<<<<<<<<<<<<<
 *     """Build a decision tree in best-first fashion.
 * 
 */
struct __pyx_obj_7sklearn_4tree_5_tree_BestFirstTreeBuilder {
  struct __pyx_obj_7sklearn_4tree_5_tree_TreeBuilder __pyx_base;
  __pyx_t_7sklearn_4tree_5_tree_SIZE_t max_leaf_nodes;
};



/* "sklearn/tree/_utils.pxd":29
 *     SIZE_t n_constant_features
 * 
 * cdef class Stack:             # <<<<<<<<<<<<<<
 *     cdef SIZE_t capacity
 *     cdef SIZE_t top
 */

struct __pyx_vtabstruct_7sklearn_4tree_6_utils_Stack {
  int (*is_empty)(struct __pyx_obj_7sklearn_4tree_6_utils_Stack *);
  int (*push)(struct __pyx_obj_7sklearn_4tree_6_utils_Stack *, __pyx_t_7sklearn_4tree_6_utils_SIZE_t, __pyx_t_7sklearn_4tree_6_utils_SIZE_t, __pyx_t_7sklearn_4tree_6_utils_SIZE_t, __pyx_t_7sklearn_4tree_6_utils_SIZE_t, int, double, __pyx_t_7sklearn_4tree_6_utils_SIZE_t);
  int (*pop)(struct __pyx_obj_7sklearn_4tree_6_utils_Stack *, struct __pyx_t_7sklearn_4tree_6_utils_StackRecord *);
};
static struct __pyx_vtabstruct_7sklearn_4tree_6_utils_Stack *__pyx_vtabptr_7sklearn_4tree_6_utils_Stack;


/* "sklearn/tree/_utils.pxd":58
 *     double improvement
 * 
 * cdef class PriorityHeap:             # <<<<<<<<<<<<<<
 *     cdef SIZE_t capacity
 *     cdef SIZE_t heap_ptr
 */

struct __pyx_vtabstruct_7sklearn_4tree_6_utils_PriorityHeap {
  int (*is_empty)(struct __pyx_obj_7sklearn_4tree_6_utils_PriorityHeap *);
  int (*push)(struct __pyx_obj_7sklearn_4tree_6_utils_PriorityHeap *, __pyx_t_7sklearn_4tree_6_utils_SIZE_t, __pyx_t_7sklearn_4tree_6_utils_SIZE_t, __pyx_t_7sklearn_4tree_6_utils_SIZE_t, __pyx_t_7sklearn_4tree_6_utils_SIZE_t, __pyx_t_7sklearn_4tree_6_utils_SIZE_t, int, double, double, double, double);
  int (*pop)(struct __pyx_obj_7sklearn_4tree_6_utils_PriorityHeap *, struct __pyx_t_7sklearn_4tree_6_utils_PriorityHeapRecord *);
};
static struct __pyx_vtabstruct_7sklearn_4tree_6_utils_PriorityHeap *__pyx_vtabptr_7sklearn_4tree_6_utils_PriorityHeap;


/* "sklearn/tree/_tree.pyx":88
 * # =============================================================================
 * 
 * cdef class Criterion:             # <<<<<<<<<<<<<<
 *     """Interface for impurity criteria."""
 * 
 */

struct __pyx_vtabstruct_7sklearn_4tree_5_tree_Criterion {
  void (*init)(struct __pyx_obj_7sklearn_4tree_5_tree_Criterion *, __pyx_t_7sklearn_4tree_5_tree_DOUBLE_t *, __pyx_t_7sklearn_4tree_5_tree_SIZE_t, __pyx_t_7sklearn_4tree_5_tree_DOUBLE_t *, double, __pyx_t_7sklearn_4tree_5_tree_SIZE_t *, __pyx_t_7sklearn_4tree_5_tree_SIZE_t, __pyx_t_7sklearn_4tree_5_tree_SIZE_t);
  void (*reset)(struct __pyx_obj_7sklearn_4tree_5_tree_Criterion *);
  void (*update)(struct __pyx_obj_7sklearn_4tree_5_tree_Criterion *, __pyx_t_7sklearn_4tree_5_tree_SIZE_t);
  double (*node_impurity)(struct __pyx_obj_7sklearn_4tree_5_tree_Criterion *);
  void (*children_impurity)(struct __pyx_obj_7sklearn_4tree_5_tree_Criterion *, double *, double *);
  void (*node_value)(struct __pyx_obj_7sklearn_4tree_5_tree_Criterion *, double *);
  double (*impurity_improvement)(struct __pyx_obj_7sklearn_4tree_5_tree_Criterion *, double);
};
static struct __pyx_vtabstruct_7sklearn_4tree_5_tree_Criterion *__pyx_vtabptr_7sklearn_4tree_5_tree_Criterion;


/* "sklearn/tree/_tree.pyx":914
 * 
 * 
 * cdef class Splitter:             # <<<<<<<<<<<<<<
 *     def __cinit__(self, Criterion criterion, SIZE_t max_features,
 *                   SIZE_t min_samples_leaf, object random_state):
 */

struct __pyx_vtabstruct_7sklearn_4tree_5_tree_Splitter {
  void (*init)(struct __pyx_obj_7sklearn_4tree_5_tree_Splitter *, PyArrayObject *, PyArrayObject *, __pyx_t_7sklearn_4tree_5_tree_DOUBLE_t *);
  void (*node_reset)(struct __pyx_obj_7sklearn_4tree_5_tree_Splitter *, __pyx_t_7sklearn_4tree_5_tree_SIZE_t, __pyx_t_7sklearn_4tree_5_tree_SIZE_t, double *);
  void (*node_split)(struct __pyx_obj_7sklearn_4tree_5_tree_Splitter *, double, struct __pyx_t_7sklearn_4tree_5_tree_SplitRecord *, __pyx_t_7sklearn_4tree_5_tree_SIZE_t *);
  void (*node_value)(struct __pyx_obj_7sklearn_4tree_5_tree_Splitter *, double *);
  double (*node_impurity)(struct __pyx_obj_7sklearn_4tree_5_tree_Splitter *);
};
static struct __pyx_vtabstruct_7sklearn_4tree_5_tree_Splitter *__pyx_vtabptr_7sklearn_4tree_5_tree_Splitter;


/* "sklearn/tree/_tree.pyx":2122
 * # =============================================================================
 * 
 * cdef class Tree:             # <<<<<<<<<<<<<<
 *     """Array-based representation of a binary decision tree.
 * 
 */

struct __pyx_vtabstruct_7sklearn_4tree_5_tree_Tree {
  __pyx_t_7sklearn_4tree_5_tree_SIZE_t (*_add_node)(struct __pyx_obj_7sklearn_4tree_5_tree_Tree *, __pyx_t_7sklearn_4tree_5_tree_SIZE_t, int, int, __pyx_t_7sklearn_4tree_5_tree_SIZE_t, double, double, __pyx_t_7sklearn_4tree_5_tree_SIZE_t, double);
  void (*_resize)(struct __pyx_obj_7sklearn_4tree_5_tree_Tree *, __pyx_t_7sklearn_4tree_5_tree_SIZE_t);
  int (*_resize_c)(struct __pyx_obj_7sklearn_4tree_5_tree_Tree *, struct __pyx_opt_args_7sklearn_4tree_5_tree_4Tree__resize_c *__pyx_optional_args);
  PyArrayObject *(*_get_value_ndarray)(struct __pyx_obj_7sklearn_4tree_5_tree_Tree *);
  PyArrayObject *(*_get_node_ndarray)(struct __pyx_obj_7sklearn_4tree_5_tree_Tree *);
  PyArrayObject *(*predict)(struct __pyx_obj_7sklearn_4tree_5_tree_Tree *, PyArrayObject *, int __pyx_skip_dispatch);
  PyArrayObject *(*apply)(struct __pyx_obj_7sklearn_4tree_5_tree_Tree *, PyArrayObject *, int __pyx_skip_dispatch);
  PyObject *(*compute_feature_importances)(struct __pyx_obj_7sklearn_4tree_5_tree_Tree *, int __pyx_skip_dispatch, struct __pyx_opt_args_7sklearn_4tree_5_tree_4Tree_compute_feature_importances *__pyx_optional_args);
};
static struct __pyx_vtabstruct_7sklearn_4tree_5_tree_Tree *__pyx_vtabptr_7sklearn_4tree_5_tree_Tree;


/* "sklearn/tree/_tree.pyx":1753
 * # Tree builders
 * # =============================================================================
 * cdef class TreeBuilder:             # <<<<<<<<<<<<<<
 *     """Interface for different tree building strategies. """
 * 
 */

struct __pyx_vtabstruct_7sklearn_4tree_5_tree_TreeBuilder {
  PyObject *(*build)(struct __pyx_obj_7sklearn_4tree_5_tree_TreeBuilder *, struct __pyx_obj_7sklearn_4tree_5_tree_Tree *, PyArrayObject *, PyArrayObject *, int __pyx_skip_dispatch, struct __pyx_opt_args_7sklearn_4tree_5_tree_11TreeBuilder_build *__pyx_optional_args);
};
static struct __pyx_vtabstruct_7sklearn_4tree_5_tree_TreeBuilder *__pyx_vtabptr_7sklearn_4tree_5_tree_TreeBuilder;


/* "sklearn/tree/_tree.pyx":141
 * 
 * 
 * cdef class ClassificationCriterion(Criterion):             # <<<<<<<<<<<<<<
 *     """Abstract criterion for classification."""
 *     cdef SIZE_t* n_classes
 */

struct __pyx_vtabstruct_7sklearn_4tree_5_tree_ClassificationCriterion {
  struct __pyx_vtabstruct_7sklearn_4tree_5_tree_Criterion __pyx_base;
};
static struct __pyx_vtabstruct_7sklearn_4tree_5_tree_ClassificationCriterion *__pyx_vtabptr_7sklearn_4tree_5_tree_ClassificationCriterion;


/* "sklearn/tree/_tree.pyx":359
 * 
 * 
 * cdef class Entropy(ClassificationCriterion):             # <<<<<<<<<<<<<<
 *     """Cross Entropy impurity criteria.
 * 
 */

struct __pyx_vtabstruct_7sklearn_4tree_5_tree_Entropy {
  struct __pyx_vtabstruct_7sklearn_4tree_5_tree_ClassificationCriterion __pyx_base;
};
static struct __pyx_vtabstruct_7sklearn_4tree_5_tree_Entropy *__pyx_vtabptr_7sklearn_4tree_5_tree_Entropy;


/* "sklearn/tree/_tree.pyx":450
 * 
 * 
 * cdef class Gini(ClassificationCriterion):             # <<<<<<<<<<<<<<
 *     """Gini Index impurity criteria.
 * 
 */

struct __pyx_vtabstruct_7sklearn_4tree_5_tree_Gini {
  struct __pyx_vtabstruct_7sklearn_4tree_5_tree_ClassificationCriterion __pyx_base;
};
static struct __pyx_vtabstruct_7sklearn_4tree_5_tree_Gini *__pyx_vtabptr_7sklearn_4tree_5_tree_Gini;


/* "sklearn/tree/_tree.pyx":544
 * 
 * 
 * cdef class RegressionCriterion(Criterion):             # <<<<<<<<<<<<<<
 *     """Abstract criterion for regression.
 * 
 */

struct __pyx_vtabstruct_7sklearn_4tree_5_tree_RegressionCriterion {
  struct __pyx_vtabstruct_7sklearn_4tree_5_tree_Criterion __pyx_base;
};
static struct __pyx_vtabstruct_7sklearn_4tree_5_tree_RegressionCriterion *__pyx_vtabptr_7sklearn_4tree_5_tree_RegressionCriterion;


/* "sklearn/tree/_tree.pyx":827
 * 
 * 
 * cdef class MSE(RegressionCriterion):             # <<<<<<<<<<<<<<
 *     """Mean squared error impurity criterion.
 * 
 */

struct __pyx_vtabstruct_7sklearn_4tree_5_tree_MSE {
  struct __pyx_vtabstruct_7sklearn_4tree_5_tree_RegressionCriterion __pyx_base;
};
static struct __pyx_vtabstruct_7sklearn_4tree_5_tree_MSE *__pyx_vtabptr_7sklearn_4tree_5_tree_MSE;


/* "sklearn/tree/_tree.pyx":868
 * 
 * 
 * cdef class FriedmanMSE(MSE):             # <<<<<<<<<<<<<<
 *     """Mean squared error impurity criterion with improvement score by Friedman
 * 
 */

struct __pyx_vtabstruct_7sklearn_4tree_5_tree_FriedmanMSE {
  struct __pyx_vtabstruct_7sklearn_4tree_5_tree_MSE __pyx_base;
};
static struct __pyx_vtabstruct_7sklearn_4tree_5_tree_FriedmanMSE *__pyx_vtabptr_7sklearn_4tree_5_tree_FriedmanMSE;


/* "sklearn/tree/_tree.pyx":1028
 * 
 * 
 * cdef class BestSplitter(Splitter):             # <<<<<<<<<<<<<<
 *     """Splitter for finding the best split."""
 *     def __reduce__(self):
 */

struct __pyx_vtabstruct_7sklearn_4tree_5_tree_BestSplitter {
  struct __pyx_vtabstruct_7sklearn_4tree_5_tree_Splitter __pyx_base;
};
static struct __pyx_vtabstruct_7sklearn_4tree_5_tree_BestSplitter *__pyx_vtabptr_7sklearn_4tree_5_tree_BestSplitter;


/* "sklearn/tree/_tree.pyx":1319
 * 
 * 
 * cdef class RandomSplitter(Splitter):             # <<<<<<<<<<<<<<
 *     """Splitter for finding the best random split."""
 *     def __reduce__(self):
 */

struct __pyx_vtabstruct_7sklearn_4tree_5_tree_RandomSplitter {
  struct __pyx_vtabstruct_7sklearn_4tree_5_tree_Splitter __pyx_base;
};
static struct __pyx_vtabstruct_7sklearn_4tree_5_tree_RandomSplitter *__pyx_vtabptr_7sklearn_4tree_5_tree_RandomSplitter;


/* "sklearn/tree/_tree.pyx":1514
 * 
 * 
 * cdef class PresortBestSplitter(Splitter):             # <<<<<<<<<<<<<<
 *     """Splitter for finding the best split, using presorting."""
 *     cdef DTYPE_t* X_old
 */

struct __pyx_vtabstruct_7sklearn_4tree_5_tree_PresortBestSplitter {
  struct __pyx_vtabstruct_7sklearn_4tree_5_tree_Splitter __pyx_base;
};
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/* "sklearn/tree/_tree.pyx":1764
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 */

struct __pyx_vtabstruct_7sklearn_4tree_5_tree_DepthFirstTreeBuilder {
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/* "sklearn/tree/_tree.pyx":1914
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static PyTypeObject *__pyx_ptype_7sklearn_4tree_5_tree_Gini = 0;
static PyTypeObject *__pyx_ptype_7sklearn_4tree_5_tree_RegressionCriterion = 0;
static PyTypeObject *__pyx_ptype_7sklearn_4tree_5_tree_MSE = 0;
static PyTypeObject *__pyx_ptype_7sklearn_4tree_5_tree_FriedmanMSE = 0;
static PyTypeObject *__pyx_ptype_7sklearn_4tree_5_tree_BestSplitter = 0;
static PyTypeObject *__pyx_ptype_7sklearn_4tree_5_tree_RandomSplitter = 0;
static PyTypeObject *__pyx_ptype_7sklearn_4tree_5_tree_PresortBestSplitter = 0;
static PyTypeObject *__pyx_ptype_7sklearn_4tree_5_tree_DepthFirstTreeBuilder = 0;
static PyTypeObject *__pyx_ptype_7sklearn_4tree_5_tree_BestFirstTreeBuilder = 0;
static double __pyx_v_7sklearn_4tree_5_tree_INFINITY;
static __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_7sklearn_4tree_5_tree__TREE_LEAF;
static __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_7sklearn_4tree_5_tree__TREE_UNDEFINED;
static __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_7sklearn_4tree_5_tree_INITIAL_STACK_SIZE;
static __pyx_t_7sklearn_4tree_5_tree_DTYPE_t __pyx_v_7sklearn_4tree_5_tree_MIN_IMPURITY_SPLIT;
static __pyx_t_7sklearn_4tree_5_tree_DTYPE_t __pyx_v_7sklearn_4tree_5_tree_FEATURE_THRESHOLD;
static int __pyx_v_7sklearn_4tree_5_tree_IS_FIRST;
static int __pyx_v_7sklearn_4tree_5_tree_IS_NOT_FIRST;
static int __pyx_v_7sklearn_4tree_5_tree_IS_LEFT;
static int __pyx_v_7sklearn_4tree_5_tree_IS_NOT_LEFT;
static CYTHON_INLINE void __pyx_f_7sklearn_4tree_5_tree__init_split(struct __pyx_t_7sklearn_4tree_5_tree_SplitRecord *, __pyx_t_7sklearn_4tree_5_tree_SIZE_t); /*proto*/
static CYTHON_INLINE void __pyx_f_7sklearn_4tree_5_tree_sort(__pyx_t_7sklearn_4tree_5_tree_DTYPE_t *, __pyx_t_7sklearn_4tree_5_tree_SIZE_t *, __pyx_t_7sklearn_4tree_5_tree_SIZE_t); /*proto*/
static CYTHON_INLINE void __pyx_f_7sklearn_4tree_5_tree_swap(__pyx_t_7sklearn_4tree_5_tree_DTYPE_t *, __pyx_t_7sklearn_4tree_5_tree_SIZE_t *, __pyx_t_7sklearn_4tree_5_tree_SIZE_t, __pyx_t_7sklearn_4tree_5_tree_SIZE_t); /*proto*/
static CYTHON_INLINE __pyx_t_7sklearn_4tree_5_tree_DTYPE_t __pyx_f_7sklearn_4tree_5_tree_median3(__pyx_t_7sklearn_4tree_5_tree_DTYPE_t *, __pyx_t_7sklearn_4tree_5_tree_SIZE_t); /*proto*/
static void __pyx_f_7sklearn_4tree_5_tree_introsort(__pyx_t_7sklearn_4tree_5_tree_DTYPE_t *, __pyx_t_7sklearn_4tree_5_tree_SIZE_t *, __pyx_t_7sklearn_4tree_5_tree_SIZE_t, int); /*proto*/
static CYTHON_INLINE void __pyx_f_7sklearn_4tree_5_tree_sift_down(__pyx_t_7sklearn_4tree_5_tree_DTYPE_t *, __pyx_t_7sklearn_4tree_5_tree_SIZE_t *, __pyx_t_7sklearn_4tree_5_tree_SIZE_t, __pyx_t_7sklearn_4tree_5_tree_SIZE_t); /*proto*/
static void __pyx_f_7sklearn_4tree_5_tree_heapsort(__pyx_t_7sklearn_4tree_5_tree_DTYPE_t *, __pyx_t_7sklearn_4tree_5_tree_SIZE_t *, __pyx_t_7sklearn_4tree_5_tree_SIZE_t); /*proto*/
static CYTHON_INLINE int __pyx_f_7sklearn_4tree_5_tree__add_to_frontier(struct __pyx_t_7sklearn_4tree_6_utils_PriorityHeapRecord *, struct __pyx_obj_7sklearn_4tree_6_utils_PriorityHeap *); /*proto*/
static CYTHON_INLINE __pyx_t_7sklearn_4tree_5_tree_UINT32_t __pyx_f_7sklearn_4tree_5_tree_our_rand_r(__pyx_t_7sklearn_4tree_5_tree_UINT32_t *); /*proto*/
static CYTHON_INLINE PyArrayObject *__pyx_f_7sklearn_4tree_5_tree_sizet_ptr_to_ndarray(__pyx_t_7sklearn_4tree_5_tree_SIZE_t *, __pyx_t_7sklearn_4tree_5_tree_SIZE_t); /*proto*/
static CYTHON_INLINE __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_f_7sklearn_4tree_5_tree_rand_int(__pyx_t_7sklearn_4tree_5_tree_SIZE_t, __pyx_t_7sklearn_4tree_5_tree_UINT32_t *); /*proto*/
static CYTHON_INLINE double __pyx_f_7sklearn_4tree_5_tree_rand_double(__pyx_t_7sklearn_4tree_5_tree_UINT32_t *); /*proto*/
static CYTHON_INLINE double __pyx_f_7sklearn_4tree_5_tree_log(double); /*proto*/
static __pyx_t_7sklearn_4tree_5_tree_DTYPE_t *__pyx_fuse_0__pyx_f_7sklearn_4tree_5_tree_safe_realloc(__pyx_t_7sklearn_4tree_5_tree_DTYPE_t **, size_t); /*proto*/
static __pyx_t_7sklearn_4tree_5_tree_SIZE_t *__pyx_fuse_1__pyx_f_7sklearn_4tree_5_tree_safe_realloc(__pyx_t_7sklearn_4tree_5_tree_SIZE_t **, size_t); /*proto*/
static unsigned char *__pyx_fuse_2__pyx_f_7sklearn_4tree_5_tree_safe_realloc(unsigned char **, size_t); /*proto*/
static __Pyx_TypeInfo __Pyx_TypeInfo_nn___pyx_t_7sklearn_4tree_5_tree_SIZE_t = { "SIZE_t", NULL, sizeof(__pyx_t_7sklearn_4tree_5_tree_SIZE_t), { 0 }, 0, IS_UNSIGNED(__pyx_t_7sklearn_4tree_5_tree_SIZE_t) ? 'U' : 'I', IS_UNSIGNED(__pyx_t_7sklearn_4tree_5_tree_SIZE_t), 0 };
static __Pyx_TypeInfo __Pyx_TypeInfo_nn___pyx_t_7sklearn_4tree_5_tree_DTYPE_t = { "DTYPE_t", NULL, sizeof(__pyx_t_7sklearn_4tree_5_tree_DTYPE_t), { 0 }, 0, 'R', 0, 0 };
static __Pyx_TypeInfo __Pyx_TypeInfo_nn___pyx_t_7sklearn_4tree_5_tree_DOUBLE_t = { "DOUBLE_t", NULL, sizeof(__pyx_t_7sklearn_4tree_5_tree_DOUBLE_t), { 0 }, 0, 'R', 0, 0 };
static __Pyx_TypeInfo __Pyx_TypeInfo_nn___pyx_t_5numpy_float64_t = { "float64_t", NULL, sizeof(__pyx_t_5numpy_float64_t), { 0 }, 0, 'R', 0, 0 };
#define __Pyx_MODULE_NAME "sklearn.tree._tree"
int __pyx_module_is_main_sklearn__tree___tree = 0;

/* Implementation of 'sklearn.tree._tree' */
static PyObject *__pyx_builtin_range;
static PyObject *__pyx_builtin_MemoryError;
static PyObject *__pyx_builtin_ValueError;
static PyObject *__pyx_builtin_RuntimeError;
static int __pyx_pf_7sklearn_4tree_5_tree_23ClassificationCriterion___cinit__(struct __pyx_obj_7sklearn_4tree_5_tree_ClassificationCriterion *__pyx_v_self, __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_n_outputs, PyArrayObject *__pyx_v_n_classes); /* proto */
static void __pyx_pf_7sklearn_4tree_5_tree_23ClassificationCriterion_2__dealloc__(struct __pyx_obj_7sklearn_4tree_5_tree_ClassificationCriterion *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_7sklearn_4tree_5_tree_23ClassificationCriterion_4__reduce__(struct __pyx_obj_7sklearn_4tree_5_tree_ClassificationCriterion *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_7sklearn_4tree_5_tree_23ClassificationCriterion_6__getstate__(CYTHON_UNUSED struct __pyx_obj_7sklearn_4tree_5_tree_ClassificationCriterion *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_7sklearn_4tree_5_tree_23ClassificationCriterion_8__setstate__(CYTHON_UNUSED struct __pyx_obj_7sklearn_4tree_5_tree_ClassificationCriterion *__pyx_v_self, CYTHON_UNUSED PyObject *__pyx_v_d); /* proto */
static int __pyx_pf_7sklearn_4tree_5_tree_19RegressionCriterion___cinit__(struct __pyx_obj_7sklearn_4tree_5_tree_RegressionCriterion *__pyx_v_self, __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_n_outputs); /* proto */
static void __pyx_pf_7sklearn_4tree_5_tree_19RegressionCriterion_2__dealloc__(struct __pyx_obj_7sklearn_4tree_5_tree_RegressionCriterion *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_7sklearn_4tree_5_tree_19RegressionCriterion_4__reduce__(struct __pyx_obj_7sklearn_4tree_5_tree_RegressionCriterion *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_7sklearn_4tree_5_tree_19RegressionCriterion_6__getstate__(CYTHON_UNUSED struct __pyx_obj_7sklearn_4tree_5_tree_RegressionCriterion *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_7sklearn_4tree_5_tree_19RegressionCriterion_8__setstate__(CYTHON_UNUSED struct __pyx_obj_7sklearn_4tree_5_tree_RegressionCriterion *__pyx_v_self, CYTHON_UNUSED PyObject *__pyx_v_d); /* proto */
static int __pyx_pf_7sklearn_4tree_5_tree_8Splitter___cinit__(struct __pyx_obj_7sklearn_4tree_5_tree_Splitter *__pyx_v_self, struct __pyx_obj_7sklearn_4tree_5_tree_Criterion *__pyx_v_criterion, __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_max_features, __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_min_samples_leaf, PyObject *__pyx_v_random_state); /* proto */
static void __pyx_pf_7sklearn_4tree_5_tree_8Splitter_2__dealloc__(struct __pyx_obj_7sklearn_4tree_5_tree_Splitter *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_7sklearn_4tree_5_tree_8Splitter_4__getstate__(CYTHON_UNUSED struct __pyx_obj_7sklearn_4tree_5_tree_Splitter *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_7sklearn_4tree_5_tree_8Splitter_6__setstate__(CYTHON_UNUSED struct __pyx_obj_7sklearn_4tree_5_tree_Splitter *__pyx_v_self, CYTHON_UNUSED PyObject *__pyx_v_d); /* proto */
static PyObject *__pyx_pf_7sklearn_4tree_5_tree_8Splitter_9criterion___get__(struct __pyx_obj_7sklearn_4tree_5_tree_Splitter *__pyx_v_self); /* proto */
static int __pyx_pf_7sklearn_4tree_5_tree_8Splitter_9criterion_2__set__(struct __pyx_obj_7sklearn_4tree_5_tree_Splitter *__pyx_v_self, PyObject *__pyx_v_value); /* proto */
static int __pyx_pf_7sklearn_4tree_5_tree_8Splitter_9criterion_4__del__(struct __pyx_obj_7sklearn_4tree_5_tree_Splitter *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_7sklearn_4tree_5_tree_8Splitter_12max_features___get__(struct __pyx_obj_7sklearn_4tree_5_tree_Splitter *__pyx_v_self); /* proto */
static int __pyx_pf_7sklearn_4tree_5_tree_8Splitter_12max_features_2__set__(struct __pyx_obj_7sklearn_4tree_5_tree_Splitter *__pyx_v_self, PyObject *__pyx_v_value); /* proto */
static PyObject *__pyx_pf_7sklearn_4tree_5_tree_8Splitter_16min_samples_leaf___get__(struct __pyx_obj_7sklearn_4tree_5_tree_Splitter *__pyx_v_self); /* proto */
static int __pyx_pf_7sklearn_4tree_5_tree_8Splitter_16min_samples_leaf_2__set__(struct __pyx_obj_7sklearn_4tree_5_tree_Splitter *__pyx_v_self, PyObject *__pyx_v_value); /* proto */
static PyObject *__pyx_pf_7sklearn_4tree_5_tree_12BestSplitter___reduce__(struct __pyx_obj_7sklearn_4tree_5_tree_BestSplitter *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_7sklearn_4tree_5_tree_14RandomSplitter___reduce__(struct __pyx_obj_7sklearn_4tree_5_tree_RandomSplitter *__pyx_v_self); /* proto */
static int __pyx_pf_7sklearn_4tree_5_tree_19PresortBestSplitter___cinit__(struct __pyx_obj_7sklearn_4tree_5_tree_PresortBestSplitter *__pyx_v_self, CYTHON_UNUSED struct __pyx_obj_7sklearn_4tree_5_tree_Criterion *__pyx_v_criterion, CYTHON_UNUSED __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_max_features, CYTHON_UNUSED __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_min_samples_leaf, CYTHON_UNUSED PyObject *__pyx_v_random_state); /* proto */
static void __pyx_pf_7sklearn_4tree_5_tree_19PresortBestSplitter_2__dealloc__(struct __pyx_obj_7sklearn_4tree_5_tree_PresortBestSplitter *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_7sklearn_4tree_5_tree_19PresortBestSplitter_4__reduce__(struct __pyx_obj_7sklearn_4tree_5_tree_PresortBestSplitter *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_7sklearn_4tree_5_tree_11TreeBuilder_build(struct __pyx_obj_7sklearn_4tree_5_tree_TreeBuilder *__pyx_v_self, struct __pyx_obj_7sklearn_4tree_5_tree_Tree *__pyx_v_tree, PyArrayObject *__pyx_v_X, PyArrayObject *__pyx_v_y, PyArrayObject *__pyx_v_sample_weight); /* proto */
static int __pyx_pf_7sklearn_4tree_5_tree_21DepthFirstTreeBuilder___cinit__(struct __pyx_obj_7sklearn_4tree_5_tree_DepthFirstTreeBuilder *__pyx_v_self, struct __pyx_obj_7sklearn_4tree_5_tree_Splitter *__pyx_v_splitter, __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_min_samples_split, __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_min_samples_leaf, __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_max_depth); /* proto */
static PyObject *__pyx_pf_7sklearn_4tree_5_tree_21DepthFirstTreeBuilder_2build(struct __pyx_obj_7sklearn_4tree_5_tree_DepthFirstTreeBuilder *__pyx_v_self, struct __pyx_obj_7sklearn_4tree_5_tree_Tree *__pyx_v_tree, PyArrayObject *__pyx_v_X, PyArrayObject *__pyx_v_y, PyArrayObject *__pyx_v_sample_weight); /* proto */
static int __pyx_pf_7sklearn_4tree_5_tree_20BestFirstTreeBuilder___cinit__(struct __pyx_obj_7sklearn_4tree_5_tree_BestFirstTreeBuilder *__pyx_v_self, struct __pyx_obj_7sklearn_4tree_5_tree_Splitter *__pyx_v_splitter, __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_min_samples_split, __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_min_samples_leaf, __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_max_depth, __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_max_leaf_nodes); /* proto */
static PyObject *__pyx_pf_7sklearn_4tree_5_tree_20BestFirstTreeBuilder_2build(struct __pyx_obj_7sklearn_4tree_5_tree_BestFirstTreeBuilder *__pyx_v_self, struct __pyx_obj_7sklearn_4tree_5_tree_Tree *__pyx_v_tree, PyArrayObject *__pyx_v_X, PyArrayObject *__pyx_v_y, PyArrayObject *__pyx_v_sample_weight); /* proto */
static PyObject *__pyx_pf_7sklearn_4tree_5_tree_4Tree_9n_classes___get__(struct __pyx_obj_7sklearn_4tree_5_tree_Tree *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_7sklearn_4tree_5_tree_4Tree_13children_left___get__(struct __pyx_obj_7sklearn_4tree_5_tree_Tree *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_7sklearn_4tree_5_tree_4Tree_14children_right___get__(struct __pyx_obj_7sklearn_4tree_5_tree_Tree *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_7sklearn_4tree_5_tree_4Tree_7feature___get__(struct __pyx_obj_7sklearn_4tree_5_tree_Tree *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_7sklearn_4tree_5_tree_4Tree_9threshold___get__(struct __pyx_obj_7sklearn_4tree_5_tree_Tree *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_7sklearn_4tree_5_tree_4Tree_8impurity___get__(struct __pyx_obj_7sklearn_4tree_5_tree_Tree *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_7sklearn_4tree_5_tree_4Tree_14n_node_samples___get__(struct __pyx_obj_7sklearn_4tree_5_tree_Tree *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_7sklearn_4tree_5_tree_4Tree_23weighted_n_node_samples___get__(struct __pyx_obj_7sklearn_4tree_5_tree_Tree *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_7sklearn_4tree_5_tree_4Tree_5value___get__(struct __pyx_obj_7sklearn_4tree_5_tree_Tree *__pyx_v_self); /* proto */
static int __pyx_pf_7sklearn_4tree_5_tree_4Tree___cinit__(struct __pyx_obj_7sklearn_4tree_5_tree_Tree *__pyx_v_self, int __pyx_v_n_features, PyArrayObject *__pyx_v_n_classes, int __pyx_v_n_outputs); /* proto */
static void __pyx_pf_7sklearn_4tree_5_tree_4Tree_2__dealloc__(struct __pyx_obj_7sklearn_4tree_5_tree_Tree *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_7sklearn_4tree_5_tree_4Tree_4__reduce__(struct __pyx_obj_7sklearn_4tree_5_tree_Tree *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_7sklearn_4tree_5_tree_4Tree_6__getstate__(struct __pyx_obj_7sklearn_4tree_5_tree_Tree *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_7sklearn_4tree_5_tree_4Tree_8__setstate__(struct __pyx_obj_7sklearn_4tree_5_tree_Tree *__pyx_v_self, PyObject *__pyx_v_d); /* proto */
static PyObject *__pyx_pf_7sklearn_4tree_5_tree_4Tree_10predict(struct __pyx_obj_7sklearn_4tree_5_tree_Tree *__pyx_v_self, PyArrayObject *__pyx_v_X); /* proto */
static PyObject *__pyx_pf_7sklearn_4tree_5_tree_4Tree_12apply(struct __pyx_obj_7sklearn_4tree_5_tree_Tree *__pyx_v_self, PyArrayObject *__pyx_v_X); /* proto */
static PyObject *__pyx_pf_7sklearn_4tree_5_tree_4Tree_14compute_feature_importances(struct __pyx_obj_7sklearn_4tree_5_tree_Tree *__pyx_v_self, PyObject *__pyx_v_normalize); /* proto */
static PyObject *__pyx_pf_7sklearn_4tree_5_tree_4Tree_10n_features___get__(struct __pyx_obj_7sklearn_4tree_5_tree_Tree *__pyx_v_self); /* proto */
static int __pyx_pf_7sklearn_4tree_5_tree_4Tree_10n_features_2__set__(struct __pyx_obj_7sklearn_4tree_5_tree_Tree *__pyx_v_self, PyObject *__pyx_v_value); /* proto */
static PyObject *__pyx_pf_7sklearn_4tree_5_tree_4Tree_9n_outputs___get__(struct __pyx_obj_7sklearn_4tree_5_tree_Tree *__pyx_v_self); /* proto */
static int __pyx_pf_7sklearn_4tree_5_tree_4Tree_9n_outputs_2__set__(struct __pyx_obj_7sklearn_4tree_5_tree_Tree *__pyx_v_self, PyObject *__pyx_v_value); /* proto */
static PyObject *__pyx_pf_7sklearn_4tree_5_tree_4Tree_13max_n_classes___get__(struct __pyx_obj_7sklearn_4tree_5_tree_Tree *__pyx_v_self); /* proto */
static int __pyx_pf_7sklearn_4tree_5_tree_4Tree_13max_n_classes_2__set__(struct __pyx_obj_7sklearn_4tree_5_tree_Tree *__pyx_v_self, PyObject *__pyx_v_value); /* proto */
static PyObject *__pyx_pf_7sklearn_4tree_5_tree_4Tree_9max_depth___get__(struct __pyx_obj_7sklearn_4tree_5_tree_Tree *__pyx_v_self); /* proto */
static int __pyx_pf_7sklearn_4tree_5_tree_4Tree_9max_depth_2__set__(struct __pyx_obj_7sklearn_4tree_5_tree_Tree *__pyx_v_self, PyObject *__pyx_v_value); /* proto */
static PyObject *__pyx_pf_7sklearn_4tree_5_tree_4Tree_10node_count___get__(struct __pyx_obj_7sklearn_4tree_5_tree_Tree *__pyx_v_self); /* proto */
static int __pyx_pf_7sklearn_4tree_5_tree_4Tree_10node_count_2__set__(struct __pyx_obj_7sklearn_4tree_5_tree_Tree *__pyx_v_self, PyObject *__pyx_v_value); /* proto */
static PyObject *__pyx_pf_7sklearn_4tree_5_tree_4Tree_8capacity___get__(struct __pyx_obj_7sklearn_4tree_5_tree_Tree *__pyx_v_self); /* proto */
static int __pyx_pf_7sklearn_4tree_5_tree_4Tree_8capacity_2__set__(struct __pyx_obj_7sklearn_4tree_5_tree_Tree *__pyx_v_self, PyObject *__pyx_v_value); /* proto */
static PyObject *__pyx_pf_7sklearn_4tree_5_tree__realloc_test(CYTHON_UNUSED PyObject *__pyx_self); /* proto */
static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, Py_buffer *__pyx_v_info, int __pyx_v_flags); /* proto */
static void __pyx_pf_5numpy_7ndarray_2__releasebuffer__(PyArrayObject *__pyx_v_self, Py_buffer *__pyx_v_info); /* proto */
static PyObject *__pyx_tp_new_7sklearn_4tree_5_tree_Criterion(PyTypeObject *t, PyObject *a, PyObject *k); /*proto*/
static PyObject *__pyx_tp_new_7sklearn_4tree_5_tree_Splitter(PyTypeObject *t, PyObject *a, PyObject *k); /*proto*/
static PyObject *__pyx_tp_new_7sklearn_4tree_5_tree_Tree(PyTypeObject *t, PyObject *a, PyObject *k); /*proto*/
static PyObject *__pyx_tp_new_7sklearn_4tree_5_tree_TreeBuilder(PyTypeObject *t, PyObject *a, PyObject *k); /*proto*/
static PyObject *__pyx_tp_new_7sklearn_4tree_5_tree_ClassificationCriterion(PyTypeObject *t, PyObject *a, PyObject *k); /*proto*/
static PyObject *__pyx_tp_new_7sklearn_4tree_5_tree_Entropy(PyTypeObject *t, PyObject *a, PyObject *k); /*proto*/
static PyObject *__pyx_tp_new_7sklearn_4tree_5_tree_Gini(PyTypeObject *t, PyObject *a, PyObject *k); /*proto*/
static PyObject *__pyx_tp_new_7sklearn_4tree_5_tree_RegressionCriterion(PyTypeObject *t, PyObject *a, PyObject *k); /*proto*/
static PyObject *__pyx_tp_new_7sklearn_4tree_5_tree_MSE(PyTypeObject *t, PyObject *a, PyObject *k); /*proto*/
static PyObject *__pyx_tp_new_7sklearn_4tree_5_tree_FriedmanMSE(PyTypeObject *t, PyObject *a, PyObject *k); /*proto*/
static PyObject *__pyx_tp_new_7sklearn_4tree_5_tree_BestSplitter(PyTypeObject *t, PyObject *a, PyObject *k); /*proto*/
static PyObject *__pyx_tp_new_7sklearn_4tree_5_tree_RandomSplitter(PyTypeObject *t, PyObject *a, PyObject *k); /*proto*/
static PyObject *__pyx_tp_new_7sklearn_4tree_5_tree_PresortBestSplitter(PyTypeObject *t, PyObject *a, PyObject *k); /*proto*/
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/* "sklearn/tree/_tree.pyx":91
 *     """Interface for impurity criteria."""
 * 
 *     cdef void init(self, DOUBLE_t* y, SIZE_t y_stride, DOUBLE_t* sample_weight,             # <<<<<<<<<<<<<<
 *                    double weighted_n_samples, SIZE_t* samples, SIZE_t start,
 *                    SIZE_t end) nogil:
 */

static void __pyx_f_7sklearn_4tree_5_tree_9Criterion_init(CYTHON_UNUSED struct __pyx_obj_7sklearn_4tree_5_tree_Criterion *__pyx_v_self, CYTHON_UNUSED __pyx_t_7sklearn_4tree_5_tree_DOUBLE_t *__pyx_v_y, CYTHON_UNUSED __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_y_stride, CYTHON_UNUSED __pyx_t_7sklearn_4tree_5_tree_DOUBLE_t *__pyx_v_sample_weight, CYTHON_UNUSED double __pyx_v_weighted_n_samples, CYTHON_UNUSED __pyx_t_7sklearn_4tree_5_tree_SIZE_t *__pyx_v_samples, CYTHON_UNUSED __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_start, CYTHON_UNUSED __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_end) {

  /* function exit code */
}

/* "sklearn/tree/_tree.pyx":98
 *         pass
 * 
 *     cdef void reset(self) nogil:             # <<<<<<<<<<<<<<
 *         """Reset the criterion at pos=start."""
 *         pass
 */

static void __pyx_f_7sklearn_4tree_5_tree_9Criterion_reset(CYTHON_UNUSED struct __pyx_obj_7sklearn_4tree_5_tree_Criterion *__pyx_v_self) {

  /* function exit code */
}

/* "sklearn/tree/_tree.pyx":102
 *         pass
 * 
 *     cdef void update(self, SIZE_t new_pos) nogil:             # <<<<<<<<<<<<<<
 *         """Update the collected statistics by moving samples[pos:new_pos] from
 *            the right child to the left child."""
 */

static void __pyx_f_7sklearn_4tree_5_tree_9Criterion_update(CYTHON_UNUSED struct __pyx_obj_7sklearn_4tree_5_tree_Criterion *__pyx_v_self, CYTHON_UNUSED __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_new_pos) {

  /* function exit code */
}

/* "sklearn/tree/_tree.pyx":107
 *         pass
 * 
 *     cdef double node_impurity(self) nogil:             # <<<<<<<<<<<<<<
 *         """Evaluate the impurity of the current node, i.e. the impurity of
 *            samples[start:end]."""
 */

static double __pyx_f_7sklearn_4tree_5_tree_9Criterion_node_impurity(CYTHON_UNUSED struct __pyx_obj_7sklearn_4tree_5_tree_Criterion *__pyx_v_self) {
  double __pyx_r;

  /* function exit code */
  __pyx_r = 0;
  return __pyx_r;
}

/* "sklearn/tree/_tree.pyx":112
 *         pass
 * 
 *     cdef void children_impurity(self, double* impurity_left,             # <<<<<<<<<<<<<<
 *                                 double* impurity_right) nogil:
 *         """Evaluate the impurity in children nodes, i.e. the impurity of
 */

static void __pyx_f_7sklearn_4tree_5_tree_9Criterion_children_impurity(CYTHON_UNUSED struct __pyx_obj_7sklearn_4tree_5_tree_Criterion *__pyx_v_self, CYTHON_UNUSED double *__pyx_v_impurity_left, CYTHON_UNUSED double *__pyx_v_impurity_right) {

  /* function exit code */
}

/* "sklearn/tree/_tree.pyx":118
 *         pass
 * 
 *     cdef void node_value(self, double* dest) nogil:             # <<<<<<<<<<<<<<
 *         """Compute the node value of samples[start:end] into dest."""
 *         pass
 */

static void __pyx_f_7sklearn_4tree_5_tree_9Criterion_node_value(CYTHON_UNUSED struct __pyx_obj_7sklearn_4tree_5_tree_Criterion *__pyx_v_self, CYTHON_UNUSED double *__pyx_v_dest) {

  /* function exit code */
}

/* "sklearn/tree/_tree.pyx":122
 *         pass
 * 
 *     cdef double impurity_improvement(self, double impurity) nogil:             # <<<<<<<<<<<<<<
 *         """Weighted impurity improvement, i.e.
 * 
 */

static double __pyx_f_7sklearn_4tree_5_tree_9Criterion_impurity_improvement(struct __pyx_obj_7sklearn_4tree_5_tree_Criterion *__pyx_v_self, double __pyx_v_impurity) {
  double __pyx_v_impurity_left;
  double __pyx_v_impurity_right;
  double __pyx_r;

  /* "sklearn/tree/_tree.pyx":134
 *         cdef double impurity_right
 * 
 *         self.children_impurity(&impurity_left, &impurity_right)             # <<<<<<<<<<<<<<
 * 
 *         return ((self.weighted_n_node_samples / self.weighted_n_samples) *
 */
  ((struct __pyx_vtabstruct_7sklearn_4tree_5_tree_Criterion *)__pyx_v_self->__pyx_vtab)->children_impurity(__pyx_v_self, (&__pyx_v_impurity_left), (&__pyx_v_impurity_right));

  /* "sklearn/tree/_tree.pyx":136
 *         self.children_impurity(&impurity_left, &impurity_right)
 * 
 *         return ((self.weighted_n_node_samples / self.weighted_n_samples) *             # <<<<<<<<<<<<<<
 *                 (impurity - self.weighted_n_right / self.weighted_n_node_samples * impurity_right
 *                           - self.weighted_n_left / self.weighted_n_node_samples * impurity_left))
 */
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  goto __pyx_L0;

  /* "sklearn/tree/_tree.pyx":122
 *         pass
 * 
 *     cdef double impurity_improvement(self, double impurity) nogil:             # <<<<<<<<<<<<<<
 *         """Weighted impurity improvement, i.e.
 * 
 */

  /* function exit code */
  __pyx_L0:;
  return __pyx_r;
}

/* "sklearn/tree/_tree.pyx":149
 *     cdef double* label_count_total
 * 
 *     def __cinit__(self, SIZE_t n_outputs,             # <<<<<<<<<<<<<<
 *                   np.ndarray[SIZE_t, ndim=1] n_classes):
 *         # Default values
 */

/* Python wrapper */
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 *         self.end = end
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 *         # Initialize label_count_total and weighted_n_node_samples
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 *         cdef SIZE_t i = 0
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 *         for k in range(n_outputs):
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 *     cdef void reset(self) nogil:
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 *     cdef void reset(self) nogil:             # <<<<<<<<<<<<<<
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 *     cdef void reset(self) nogil:
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 * 
 *         self.weighted_n_left = 0.0
 */
  __pyx_t_1 = __pyx_v_self->__pyx_base.start;
  __pyx_v_self->__pyx_base.pos = __pyx_t_1;

  /* "sklearn/tree/_tree.pyx":272
 *         self.pos = self.start
 * 
 *         self.weighted_n_left = 0.0             # <<<<<<<<<<<<<<
 *         self.weighted_n_right = self.weighted_n_node_samples
 * 
 */
  __pyx_v_self->__pyx_base.weighted_n_left = 0.0;

  /* "sklearn/tree/_tree.pyx":273
 * 
 *         self.weighted_n_left = 0.0
 *         self.weighted_n_right = self.weighted_n_node_samples             # <<<<<<<<<<<<<<
 * 
 *         cdef SIZE_t n_outputs = self.n_outputs
 */
  __pyx_t_2 = __pyx_v_self->__pyx_base.weighted_n_node_samples;
  __pyx_v_self->__pyx_base.weighted_n_right = __pyx_t_2;

  /* "sklearn/tree/_tree.pyx":275
 *         self.weighted_n_right = self.weighted_n_node_samples
 * 
 *         cdef SIZE_t n_outputs = self.n_outputs             # <<<<<<<<<<<<<<
 *         cdef SIZE_t* n_classes = self.n_classes
 *         cdef SIZE_t label_count_stride = self.label_count_stride
 */
  __pyx_t_1 = __pyx_v_self->__pyx_base.n_outputs;
  __pyx_v_n_outputs = __pyx_t_1;

  /* "sklearn/tree/_tree.pyx":276
 * 
 *         cdef SIZE_t n_outputs = self.n_outputs
 *         cdef SIZE_t* n_classes = self.n_classes             # <<<<<<<<<<<<<<
 *         cdef SIZE_t label_count_stride = self.label_count_stride
 *         cdef double* label_count_total = self.label_count_total
 */
  __pyx_t_3 = __pyx_v_self->n_classes;
  __pyx_v_n_classes = __pyx_t_3;

  /* "sklearn/tree/_tree.pyx":277
 *         cdef SIZE_t n_outputs = self.n_outputs
 *         cdef SIZE_t* n_classes = self.n_classes
 *         cdef SIZE_t label_count_stride = self.label_count_stride             # <<<<<<<<<<<<<<
 *         cdef double* label_count_total = self.label_count_total
 *         cdef double* label_count_left = self.label_count_left
 */
  __pyx_t_1 = __pyx_v_self->label_count_stride;
  __pyx_v_label_count_stride = __pyx_t_1;

  /* "sklearn/tree/_tree.pyx":278
 *         cdef SIZE_t* n_classes = self.n_classes
 *         cdef SIZE_t label_count_stride = self.label_count_stride
 *         cdef double* label_count_total = self.label_count_total             # <<<<<<<<<<<<<<
 *         cdef double* label_count_left = self.label_count_left
 *         cdef double* label_count_right = self.label_count_right
 */
  __pyx_t_4 = __pyx_v_self->label_count_total;
  __pyx_v_label_count_total = __pyx_t_4;

  /* "sklearn/tree/_tree.pyx":279
 *         cdef SIZE_t label_count_stride = self.label_count_stride
 *         cdef double* label_count_total = self.label_count_total
 *         cdef double* label_count_left = self.label_count_left             # <<<<<<<<<<<<<<
 *         cdef double* label_count_right = self.label_count_right
 * 
 */
  __pyx_t_4 = __pyx_v_self->label_count_left;
  __pyx_v_label_count_left = __pyx_t_4;

  /* "sklearn/tree/_tree.pyx":280
 *         cdef double* label_count_total = self.label_count_total
 *         cdef double* label_count_left = self.label_count_left
 *         cdef double* label_count_right = self.label_count_right             # <<<<<<<<<<<<<<
 * 
 *         cdef SIZE_t k = 0
 */
  __pyx_t_4 = __pyx_v_self->label_count_right;
  __pyx_v_label_count_right = __pyx_t_4;

  /* "sklearn/tree/_tree.pyx":282
 *         cdef double* label_count_right = self.label_count_right
 * 
 *         cdef SIZE_t k = 0             # <<<<<<<<<<<<<<
 * 
 *         for k in range(n_outputs):
 */
  __pyx_v_k = 0;

  /* "sklearn/tree/_tree.pyx":284
 *         cdef SIZE_t k = 0
 * 
 *         for k in range(n_outputs):             # <<<<<<<<<<<<<<
 *             memset(label_count_left, 0, n_classes[k] * sizeof(double))
 *             memcpy(label_count_right, label_count_total,
 */
  __pyx_t_1 = __pyx_v_n_outputs;
  for (__pyx_t_5 = 0; __pyx_t_5 < __pyx_t_1; __pyx_t_5+=1) {
    __pyx_v_k = __pyx_t_5;

    /* "sklearn/tree/_tree.pyx":285
 * 
 *         for k in range(n_outputs):
 *             memset(label_count_left, 0, n_classes[k] * sizeof(double))             # <<<<<<<<<<<<<<
 *             memcpy(label_count_right, label_count_total,
 *                    n_classes[k] * sizeof(double))
 */
    memset(__pyx_v_label_count_left, 0, ((__pyx_v_n_classes[__pyx_v_k]) * (sizeof(double))));

    /* "sklearn/tree/_tree.pyx":286
 *         for k in range(n_outputs):
 *             memset(label_count_left, 0, n_classes[k] * sizeof(double))
 *             memcpy(label_count_right, label_count_total,             # <<<<<<<<<<<<<<
 *                    n_classes[k] * sizeof(double))
 * 
 */
    memcpy(__pyx_v_label_count_right, __pyx_v_label_count_total, ((__pyx_v_n_classes[__pyx_v_k]) * (sizeof(double))));

    /* "sklearn/tree/_tree.pyx":289
 *                    n_classes[k] * sizeof(double))
 * 
 *             label_count_total += label_count_stride             # <<<<<<<<<<<<<<
 *             label_count_left += label_count_stride
 *             label_count_right += label_count_stride
 */
    __pyx_v_label_count_total = (__pyx_v_label_count_total + __pyx_v_label_count_stride);

    /* "sklearn/tree/_tree.pyx":290
 * 
 *             label_count_total += label_count_stride
 *             label_count_left += label_count_stride             # <<<<<<<<<<<<<<
 *             label_count_right += label_count_stride
 * 
 */
    __pyx_v_label_count_left = (__pyx_v_label_count_left + __pyx_v_label_count_stride);

    /* "sklearn/tree/_tree.pyx":291
 *             label_count_total += label_count_stride
 *             label_count_left += label_count_stride
 *             label_count_right += label_count_stride             # <<<<<<<<<<<<<<
 * 
 *     cdef void update(self, SIZE_t new_pos) nogil:
 */
    __pyx_v_label_count_right = (__pyx_v_label_count_right + __pyx_v_label_count_stride);
  }

  /* "sklearn/tree/_tree.pyx":268
 *         self.reset()
 * 
 *     cdef void reset(self) nogil:             # <<<<<<<<<<<<<<
 *         """Reset the criterion at pos=start."""
 *         self.pos = self.start
 */

  /* function exit code */
}

/* "sklearn/tree/_tree.pyx":293
 *             label_count_right += label_count_stride
 * 
 *     cdef void update(self, SIZE_t new_pos) nogil:             # <<<<<<<<<<<<<<
 *         """Update the collected statistics by moving samples[pos:new_pos] from
 *             the right child to the left child."""
 */

static void __pyx_f_7sklearn_4tree_5_tree_23ClassificationCriterion_update(struct __pyx_obj_7sklearn_4tree_5_tree_ClassificationCriterion *__pyx_v_self, __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_new_pos) {
  __pyx_t_7sklearn_4tree_5_tree_DOUBLE_t *__pyx_v_y;
  __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_y_stride;
  __pyx_t_7sklearn_4tree_5_tree_DOUBLE_t *__pyx_v_sample_weight;
  __pyx_t_7sklearn_4tree_5_tree_SIZE_t *__pyx_v_samples;
  __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_pos;
  __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_n_outputs;
  CYTHON_UNUSED __pyx_t_7sklearn_4tree_5_tree_SIZE_t *__pyx_v_n_classes;
  __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_label_count_stride;
  CYTHON_UNUSED double *__pyx_v_label_count_total;
  double *__pyx_v_label_count_left;
  double *__pyx_v_label_count_right;
  __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_i;
  __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_p;
  __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_k;
  __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_label_index;
  __pyx_t_7sklearn_4tree_5_tree_DOUBLE_t __pyx_v_w;
  __pyx_t_7sklearn_4tree_5_tree_DOUBLE_t __pyx_v_diff_w;
  __pyx_t_7sklearn_4tree_5_tree_DOUBLE_t *__pyx_t_1;
  __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_t_2;
  __pyx_t_7sklearn_4tree_5_tree_SIZE_t *__pyx_t_3;
  double *__pyx_t_4;
  __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_t_5;
  int __pyx_t_6;
  __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_t_7;
  __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_t_8;
  __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_t_9;

  /* "sklearn/tree/_tree.pyx":296
 *         """Update the collected statistics by moving samples[pos:new_pos] from
 *             the right child to the left child."""
 *         cdef DOUBLE_t* y = self.y             # <<<<<<<<<<<<<<
 *         cdef SIZE_t y_stride = self.y_stride
 *         cdef DOUBLE_t* sample_weight = self.sample_weight
 */
  __pyx_t_1 = __pyx_v_self->__pyx_base.y;
  __pyx_v_y = __pyx_t_1;

  /* "sklearn/tree/_tree.pyx":297
 *             the right child to the left child."""
 *         cdef DOUBLE_t* y = self.y
 *         cdef SIZE_t y_stride = self.y_stride             # <<<<<<<<<<<<<<
 *         cdef DOUBLE_t* sample_weight = self.sample_weight
 * 
 */
  __pyx_t_2 = __pyx_v_self->__pyx_base.y_stride;
  __pyx_v_y_stride = __pyx_t_2;

  /* "sklearn/tree/_tree.pyx":298
 *         cdef DOUBLE_t* y = self.y
 *         cdef SIZE_t y_stride = self.y_stride
 *         cdef DOUBLE_t* sample_weight = self.sample_weight             # <<<<<<<<<<<<<<
 * 
 *         cdef SIZE_t* samples = self.samples
 */
  __pyx_t_1 = __pyx_v_self->__pyx_base.sample_weight;
  __pyx_v_sample_weight = __pyx_t_1;

  /* "sklearn/tree/_tree.pyx":300
 *         cdef DOUBLE_t* sample_weight = self.sample_weight
 * 
 *         cdef SIZE_t* samples = self.samples             # <<<<<<<<<<<<<<
 *         cdef SIZE_t pos = self.pos
 * 
 */
  __pyx_t_3 = __pyx_v_self->__pyx_base.samples;
  __pyx_v_samples = __pyx_t_3;

  /* "sklearn/tree/_tree.pyx":301
 * 
 *         cdef SIZE_t* samples = self.samples
 *         cdef SIZE_t pos = self.pos             # <<<<<<<<<<<<<<
 * 
 *         cdef SIZE_t n_outputs = self.n_outputs
 */
  __pyx_t_2 = __pyx_v_self->__pyx_base.pos;
  __pyx_v_pos = __pyx_t_2;

  /* "sklearn/tree/_tree.pyx":303
 *         cdef SIZE_t pos = self.pos
 * 
 *         cdef SIZE_t n_outputs = self.n_outputs             # <<<<<<<<<<<<<<
 *         cdef SIZE_t* n_classes = self.n_classes
 *         cdef SIZE_t label_count_stride = self.label_count_stride
 */
  __pyx_t_2 = __pyx_v_self->__pyx_base.n_outputs;
  __pyx_v_n_outputs = __pyx_t_2;

  /* "sklearn/tree/_tree.pyx":304
 * 
 *         cdef SIZE_t n_outputs = self.n_outputs
 *         cdef SIZE_t* n_classes = self.n_classes             # <<<<<<<<<<<<<<
 *         cdef SIZE_t label_count_stride = self.label_count_stride
 *         cdef double* label_count_total = self.label_count_total
 */
  __pyx_t_3 = __pyx_v_self->n_classes;
  __pyx_v_n_classes = __pyx_t_3;

  /* "sklearn/tree/_tree.pyx":305
 *         cdef SIZE_t n_outputs = self.n_outputs
 *         cdef SIZE_t* n_classes = self.n_classes
 *         cdef SIZE_t label_count_stride = self.label_count_stride             # <<<<<<<<<<<<<<
 *         cdef double* label_count_total = self.label_count_total
 *         cdef double* label_count_left = self.label_count_left
 */
  __pyx_t_2 = __pyx_v_self->label_count_stride;
  __pyx_v_label_count_stride = __pyx_t_2;

  /* "sklearn/tree/_tree.pyx":306
 *         cdef SIZE_t* n_classes = self.n_classes
 *         cdef SIZE_t label_count_stride = self.label_count_stride
 *         cdef double* label_count_total = self.label_count_total             # <<<<<<<<<<<<<<
 *         cdef double* label_count_left = self.label_count_left
 *         cdef double* label_count_right = self.label_count_right
 */
  __pyx_t_4 = __pyx_v_self->label_count_total;
  __pyx_v_label_count_total = __pyx_t_4;

  /* "sklearn/tree/_tree.pyx":307
 *         cdef SIZE_t label_count_stride = self.label_count_stride
 *         cdef double* label_count_total = self.label_count_total
 *         cdef double* label_count_left = self.label_count_left             # <<<<<<<<<<<<<<
 *         cdef double* label_count_right = self.label_count_right
 * 
 */
  __pyx_t_4 = __pyx_v_self->label_count_left;
  __pyx_v_label_count_left = __pyx_t_4;

  /* "sklearn/tree/_tree.pyx":308
 *         cdef double* label_count_total = self.label_count_total
 *         cdef double* label_count_left = self.label_count_left
 *         cdef double* label_count_right = self.label_count_right             # <<<<<<<<<<<<<<
 * 
 *         cdef SIZE_t i
 */
  __pyx_t_4 = __pyx_v_self->label_count_right;
  __pyx_v_label_count_right = __pyx_t_4;

  /* "sklearn/tree/_tree.pyx":314
 *         cdef SIZE_t k
 *         cdef SIZE_t label_index
 *         cdef DOUBLE_t w = 1.0             # <<<<<<<<<<<<<<
 *         cdef DOUBLE_t diff_w = 0.0
 * 
 */
  __pyx_v_w = 1.0;

  /* "sklearn/tree/_tree.pyx":315
 *         cdef SIZE_t label_index
 *         cdef DOUBLE_t w = 1.0
 *         cdef DOUBLE_t diff_w = 0.0             # <<<<<<<<<<<<<<
 * 
 *         # Note: We assume start <= pos < new_pos <= end
 */
  __pyx_v_diff_w = 0.0;

  /* "sklearn/tree/_tree.pyx":319
 *         # Note: We assume start <= pos < new_pos <= end
 * 
 *         for p in range(pos, new_pos):             # <<<<<<<<<<<<<<
 *             i = samples[p]
 * 
 */
  __pyx_t_2 = __pyx_v_new_pos;
  for (__pyx_t_5 = __pyx_v_pos; __pyx_t_5 < __pyx_t_2; __pyx_t_5+=1) {
    __pyx_v_p = __pyx_t_5;

    /* "sklearn/tree/_tree.pyx":320
 * 
 *         for p in range(pos, new_pos):
 *             i = samples[p]             # <<<<<<<<<<<<<<
 * 
 *             if sample_weight != NULL:
 */
    __pyx_v_i = (__pyx_v_samples[__pyx_v_p]);

    /* "sklearn/tree/_tree.pyx":322
 *             i = samples[p]
 * 
 *             if sample_weight != NULL:             # <<<<<<<<<<<<<<
 *                 w = sample_weight[i]
 * 
 */
    __pyx_t_6 = ((__pyx_v_sample_weight != NULL) != 0);
    if (__pyx_t_6) {

      /* "sklearn/tree/_tree.pyx":323
 * 
 *             if sample_weight != NULL:
 *                 w = sample_weight[i]             # <<<<<<<<<<<<<<
 * 
 *             for k in range(n_outputs):
 */
      __pyx_v_w = (__pyx_v_sample_weight[__pyx_v_i]);
      goto __pyx_L5;
    }
    __pyx_L5:;

    /* "sklearn/tree/_tree.pyx":325
 *                 w = sample_weight[i]
 * 
 *             for k in range(n_outputs):             # <<<<<<<<<<<<<<
 *                 label_index = (k * label_count_stride +
 *                                <SIZE_t> y[i * y_stride + k])
 */
    __pyx_t_7 = __pyx_v_n_outputs;
    for (__pyx_t_8 = 0; __pyx_t_8 < __pyx_t_7; __pyx_t_8+=1) {
      __pyx_v_k = __pyx_t_8;

      /* "sklearn/tree/_tree.pyx":326
 * 
 *             for k in range(n_outputs):
 *                 label_index = (k * label_count_stride +             # <<<<<<<<<<<<<<
 *                                <SIZE_t> y[i * y_stride + k])
 *                 label_count_left[label_index] += w
 */
      __pyx_v_label_index = ((__pyx_v_k * __pyx_v_label_count_stride) + ((__pyx_t_7sklearn_4tree_5_tree_SIZE_t)(__pyx_v_y[((__pyx_v_i * __pyx_v_y_stride) + __pyx_v_k)])));

      /* "sklearn/tree/_tree.pyx":328
 *                 label_index = (k * label_count_stride +
 *                                <SIZE_t> y[i * y_stride + k])
 *                 label_count_left[label_index] += w             # <<<<<<<<<<<<<<
 *                 label_count_right[label_index] -= w
 * 
 */
      __pyx_t_9 = __pyx_v_label_index;
      (__pyx_v_label_count_left[__pyx_t_9]) = ((__pyx_v_label_count_left[__pyx_t_9]) + __pyx_v_w);

      /* "sklearn/tree/_tree.pyx":329
 *                                <SIZE_t> y[i * y_stride + k])
 *                 label_count_left[label_index] += w
 *                 label_count_right[label_index] -= w             # <<<<<<<<<<<<<<
 * 
 *             diff_w += w
 */
      __pyx_t_9 = __pyx_v_label_index;
      (__pyx_v_label_count_right[__pyx_t_9]) = ((__pyx_v_label_count_right[__pyx_t_9]) - __pyx_v_w);
    }

    /* "sklearn/tree/_tree.pyx":331
 *                 label_count_right[label_index] -= w
 * 
 *             diff_w += w             # <<<<<<<<<<<<<<
 * 
 *         self.weighted_n_left += diff_w
 */
    __pyx_v_diff_w = (__pyx_v_diff_w + __pyx_v_w);
  }

  /* "sklearn/tree/_tree.pyx":333
 *             diff_w += w
 * 
 *         self.weighted_n_left += diff_w             # <<<<<<<<<<<<<<
 *         self.weighted_n_right -= diff_w
 * 
 */
  __pyx_v_self->__pyx_base.weighted_n_left = (__pyx_v_self->__pyx_base.weighted_n_left + __pyx_v_diff_w);

  /* "sklearn/tree/_tree.pyx":334
 * 
 *         self.weighted_n_left += diff_w
 *         self.weighted_n_right -= diff_w             # <<<<<<<<<<<<<<
 * 
 *         self.pos = new_pos
 */
  __pyx_v_self->__pyx_base.weighted_n_right = (__pyx_v_self->__pyx_base.weighted_n_right - __pyx_v_diff_w);

  /* "sklearn/tree/_tree.pyx":336
 *         self.weighted_n_right -= diff_w
 * 
 *         self.pos = new_pos             # <<<<<<<<<<<<<<
 * 
 *     cdef double node_impurity(self) nogil:
 */
  __pyx_v_self->__pyx_base.pos = __pyx_v_new_pos;

  /* "sklearn/tree/_tree.pyx":293
 *             label_count_right += label_count_stride
 * 
 *     cdef void update(self, SIZE_t new_pos) nogil:             # <<<<<<<<<<<<<<
 *         """Update the collected statistics by moving samples[pos:new_pos] from
 *             the right child to the left child."""
 */

  /* function exit code */
}

/* "sklearn/tree/_tree.pyx":338
 *         self.pos = new_pos
 * 
 *     cdef double node_impurity(self) nogil:             # <<<<<<<<<<<<<<
 *         pass
 * 
 */

static double __pyx_f_7sklearn_4tree_5_tree_23ClassificationCriterion_node_impurity(CYTHON_UNUSED struct __pyx_obj_7sklearn_4tree_5_tree_ClassificationCriterion *__pyx_v_self) {
  double __pyx_r;

  /* function exit code */
  __pyx_r = 0;
  return __pyx_r;
}

/* "sklearn/tree/_tree.pyx":341
 *         pass
 * 
 *     cdef void children_impurity(self, double* impurity_left,             # <<<<<<<<<<<<<<
 *                                 double* impurity_right) nogil:
 *         pass
 */

static void __pyx_f_7sklearn_4tree_5_tree_23ClassificationCriterion_children_impurity(CYTHON_UNUSED struct __pyx_obj_7sklearn_4tree_5_tree_ClassificationCriterion *__pyx_v_self, CYTHON_UNUSED double *__pyx_v_impurity_left, CYTHON_UNUSED double *__pyx_v_impurity_right) {

  /* function exit code */
}

/* "sklearn/tree/_tree.pyx":345
 *         pass
 * 
 *     cdef void node_value(self, double* dest) nogil:             # <<<<<<<<<<<<<<
 *         """Compute the node value of samples[start:end] into dest."""
 *         cdef SIZE_t n_outputs = self.n_outputs
 */

static void __pyx_f_7sklearn_4tree_5_tree_23ClassificationCriterion_node_value(struct __pyx_obj_7sklearn_4tree_5_tree_ClassificationCriterion *__pyx_v_self, double *__pyx_v_dest) {
  __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_n_outputs;
  __pyx_t_7sklearn_4tree_5_tree_SIZE_t *__pyx_v_n_classes;
  __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_label_count_stride;
  double *__pyx_v_label_count_total;
  __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_k;
  __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_t_1;
  __pyx_t_7sklearn_4tree_5_tree_SIZE_t *__pyx_t_2;
  double *__pyx_t_3;
  __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_t_4;

  /* "sklearn/tree/_tree.pyx":347
 *     cdef void node_value(self, double* dest) nogil:
 *         """Compute the node value of samples[start:end] into dest."""
 *         cdef SIZE_t n_outputs = self.n_outputs             # <<<<<<<<<<<<<<
 *         cdef SIZE_t* n_classes = self.n_classes
 *         cdef SIZE_t label_count_stride = self.label_count_stride
 */
  __pyx_t_1 = __pyx_v_self->__pyx_base.n_outputs;
  __pyx_v_n_outputs = __pyx_t_1;

  /* "sklearn/tree/_tree.pyx":348
 *         """Compute the node value of samples[start:end] into dest."""
 *         cdef SIZE_t n_outputs = self.n_outputs
 *         cdef SIZE_t* n_classes = self.n_classes             # <<<<<<<<<<<<<<
 *         cdef SIZE_t label_count_stride = self.label_count_stride
 *         cdef double* label_count_total = self.label_count_total
 */
  __pyx_t_2 = __pyx_v_self->n_classes;
  __pyx_v_n_classes = __pyx_t_2;

  /* "sklearn/tree/_tree.pyx":349
 *         cdef SIZE_t n_outputs = self.n_outputs
 *         cdef SIZE_t* n_classes = self.n_classes
 *         cdef SIZE_t label_count_stride = self.label_count_stride             # <<<<<<<<<<<<<<
 *         cdef double* label_count_total = self.label_count_total
 *         cdef SIZE_t k
 */
  __pyx_t_1 = __pyx_v_self->label_count_stride;
  __pyx_v_label_count_stride = __pyx_t_1;

  /* "sklearn/tree/_tree.pyx":350
 *         cdef SIZE_t* n_classes = self.n_classes
 *         cdef SIZE_t label_count_stride = self.label_count_stride
 *         cdef double* label_count_total = self.label_count_total             # <<<<<<<<<<<<<<
 *         cdef SIZE_t k
 * 
 */
  __pyx_t_3 = __pyx_v_self->label_count_total;
  __pyx_v_label_count_total = __pyx_t_3;

  /* "sklearn/tree/_tree.pyx":353
 *         cdef SIZE_t k
 * 
 *         for k in range(n_outputs):             # <<<<<<<<<<<<<<
 *             memcpy(dest, label_count_total, n_classes[k] * sizeof(double))
 *             dest += label_count_stride
 */
  __pyx_t_1 = __pyx_v_n_outputs;
  for (__pyx_t_4 = 0; __pyx_t_4 < __pyx_t_1; __pyx_t_4+=1) {
    __pyx_v_k = __pyx_t_4;

    /* "sklearn/tree/_tree.pyx":354
 * 
 *         for k in range(n_outputs):
 *             memcpy(dest, label_count_total, n_classes[k] * sizeof(double))             # <<<<<<<<<<<<<<
 *             dest += label_count_stride
 *             label_count_total += label_count_stride
 */
    memcpy(__pyx_v_dest, __pyx_v_label_count_total, ((__pyx_v_n_classes[__pyx_v_k]) * (sizeof(double))));

    /* "sklearn/tree/_tree.pyx":355
 *         for k in range(n_outputs):
 *             memcpy(dest, label_count_total, n_classes[k] * sizeof(double))
 *             dest += label_count_stride             # <<<<<<<<<<<<<<
 *             label_count_total += label_count_stride
 * 
 */
    __pyx_v_dest = (__pyx_v_dest + __pyx_v_label_count_stride);

    /* "sklearn/tree/_tree.pyx":356
 *             memcpy(dest, label_count_total, n_classes[k] * sizeof(double))
 *             dest += label_count_stride
 *             label_count_total += label_count_stride             # <<<<<<<<<<<<<<
 * 
 * 
 */
    __pyx_v_label_count_total = (__pyx_v_label_count_total + __pyx_v_label_count_stride);
  }

  /* "sklearn/tree/_tree.pyx":345
 *         pass
 * 
 *     cdef void node_value(self, double* dest) nogil:             # <<<<<<<<<<<<<<
 *         """Compute the node value of samples[start:end] into dest."""
 *         cdef SIZE_t n_outputs = self.n_outputs
 */

  /* function exit code */
}

/* "sklearn/tree/_tree.pyx":373
 *         cross-entropy = - \sum_{k=0}^{K-1} pmk log(pmk)
 *     """
 *     cdef double node_impurity(self) nogil:             # <<<<<<<<<<<<<<
 *         """Evaluate the impurity of the current node, i.e. the impurity of
 *            samples[start:end]."""
 */

static double __pyx_f_7sklearn_4tree_5_tree_7Entropy_node_impurity(struct __pyx_obj_7sklearn_4tree_5_tree_Entropy *__pyx_v_self) {
  double __pyx_v_weighted_n_node_samples;
  __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_n_outputs;
  __pyx_t_7sklearn_4tree_5_tree_SIZE_t *__pyx_v_n_classes;
  __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_label_count_stride;
  double *__pyx_v_label_count_total;
  double __pyx_v_entropy;
  double __pyx_v_total;
  double __pyx_v_tmp;
  __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_k;
  __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_c;
  double __pyx_r;
  double __pyx_t_1;
  __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_t_2;
  __pyx_t_7sklearn_4tree_5_tree_SIZE_t *__pyx_t_3;
  double *__pyx_t_4;
  __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_t_5;
  __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_t_6;
  __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_t_7;
  int __pyx_t_8;

  /* "sklearn/tree/_tree.pyx":376
 *         """Evaluate the impurity of the current node, i.e. the impurity of
 *            samples[start:end]."""
 *         cdef double weighted_n_node_samples = self.weighted_n_node_samples             # <<<<<<<<<<<<<<
 * 
 *         cdef SIZE_t n_outputs = self.n_outputs
 */
  __pyx_t_1 = __pyx_v_self->__pyx_base.__pyx_base.weighted_n_node_samples;
  __pyx_v_weighted_n_node_samples = __pyx_t_1;

  /* "sklearn/tree/_tree.pyx":378
 *         cdef double weighted_n_node_samples = self.weighted_n_node_samples
 * 
 *         cdef SIZE_t n_outputs = self.n_outputs             # <<<<<<<<<<<<<<
 *         cdef SIZE_t* n_classes = self.n_classes
 *         cdef SIZE_t label_count_stride = self.label_count_stride
 */
  __pyx_t_2 = __pyx_v_self->__pyx_base.__pyx_base.n_outputs;
  __pyx_v_n_outputs = __pyx_t_2;

  /* "sklearn/tree/_tree.pyx":379
 * 
 *         cdef SIZE_t n_outputs = self.n_outputs
 *         cdef SIZE_t* n_classes = self.n_classes             # <<<<<<<<<<<<<<
 *         cdef SIZE_t label_count_stride = self.label_count_stride
 *         cdef double* label_count_total = self.label_count_total
 */
  __pyx_t_3 = __pyx_v_self->__pyx_base.n_classes;
  __pyx_v_n_classes = __pyx_t_3;

  /* "sklearn/tree/_tree.pyx":380
 *         cdef SIZE_t n_outputs = self.n_outputs
 *         cdef SIZE_t* n_classes = self.n_classes
 *         cdef SIZE_t label_count_stride = self.label_count_stride             # <<<<<<<<<<<<<<
 *         cdef double* label_count_total = self.label_count_total
 * 
 */
  __pyx_t_2 = __pyx_v_self->__pyx_base.label_count_stride;
  __pyx_v_label_count_stride = __pyx_t_2;

  /* "sklearn/tree/_tree.pyx":381
 *         cdef SIZE_t* n_classes = self.n_classes
 *         cdef SIZE_t label_count_stride = self.label_count_stride
 *         cdef double* label_count_total = self.label_count_total             # <<<<<<<<<<<<<<
 * 
 *         cdef double entropy = 0.0
 */
  __pyx_t_4 = __pyx_v_self->__pyx_base.label_count_total;
  __pyx_v_label_count_total = __pyx_t_4;

  /* "sklearn/tree/_tree.pyx":383
 *         cdef double* label_count_total = self.label_count_total
 * 
 *         cdef double entropy = 0.0             # <<<<<<<<<<<<<<
 *         cdef double total = 0.0
 *         cdef double tmp
 */
  __pyx_v_entropy = 0.0;

  /* "sklearn/tree/_tree.pyx":384
 * 
 *         cdef double entropy = 0.0
 *         cdef double total = 0.0             # <<<<<<<<<<<<<<
 *         cdef double tmp
 *         cdef SIZE_t k
 */
  __pyx_v_total = 0.0;

  /* "sklearn/tree/_tree.pyx":389
 *         cdef SIZE_t c
 * 
 *         for k in range(n_outputs):             # <<<<<<<<<<<<<<
 *             entropy = 0.0
 * 
 */
  __pyx_t_2 = __pyx_v_n_outputs;
  for (__pyx_t_5 = 0; __pyx_t_5 < __pyx_t_2; __pyx_t_5+=1) {
    __pyx_v_k = __pyx_t_5;

    /* "sklearn/tree/_tree.pyx":390
 * 
 *         for k in range(n_outputs):
 *             entropy = 0.0             # <<<<<<<<<<<<<<
 * 
 *             for c in range(n_classes[k]):
 */
    __pyx_v_entropy = 0.0;

    /* "sklearn/tree/_tree.pyx":392
 *             entropy = 0.0
 * 
 *             for c in range(n_classes[k]):             # <<<<<<<<<<<<<<
 *                 tmp = label_count_total[c]
 *                 if tmp > 0.0:
 */
    __pyx_t_6 = (__pyx_v_n_classes[__pyx_v_k]);
    for (__pyx_t_7 = 0; __pyx_t_7 < __pyx_t_6; __pyx_t_7+=1) {
      __pyx_v_c = __pyx_t_7;

      /* "sklearn/tree/_tree.pyx":393
 * 
 *             for c in range(n_classes[k]):
 *                 tmp = label_count_total[c]             # <<<<<<<<<<<<<<
 *                 if tmp > 0.0:
 *                     tmp /= weighted_n_node_samples
 */
      __pyx_v_tmp = (__pyx_v_label_count_total[__pyx_v_c]);

      /* "sklearn/tree/_tree.pyx":394
 *             for c in range(n_classes[k]):
 *                 tmp = label_count_total[c]
 *                 if tmp > 0.0:             # <<<<<<<<<<<<<<
 *                     tmp /= weighted_n_node_samples
 *                     entropy -= tmp * log(tmp)
 */
      __pyx_t_8 = ((__pyx_v_tmp > 0.0) != 0);
      if (__pyx_t_8) {

        /* "sklearn/tree/_tree.pyx":395
 *                 tmp = label_count_total[c]
 *                 if tmp > 0.0:
 *                     tmp /= weighted_n_node_samples             # <<<<<<<<<<<<<<
 *                     entropy -= tmp * log(tmp)
 * 
 */
        __pyx_v_tmp = (__pyx_v_tmp / __pyx_v_weighted_n_node_samples);

        /* "sklearn/tree/_tree.pyx":396
 *                 if tmp > 0.0:
 *                     tmp /= weighted_n_node_samples
 *                     entropy -= tmp * log(tmp)             # <<<<<<<<<<<<<<
 * 
 *             total += entropy
 */
        __pyx_v_entropy = (__pyx_v_entropy - (__pyx_v_tmp * __pyx_f_7sklearn_4tree_5_tree_log(__pyx_v_tmp)));
        goto __pyx_L7;
      }
      __pyx_L7:;
    }

    /* "sklearn/tree/_tree.pyx":398
 *                     entropy -= tmp * log(tmp)
 * 
 *             total += entropy             # <<<<<<<<<<<<<<
 *             label_count_total += label_count_stride
 * 
 */
    __pyx_v_total = (__pyx_v_total + __pyx_v_entropy);

    /* "sklearn/tree/_tree.pyx":399
 * 
 *             total += entropy
 *             label_count_total += label_count_stride             # <<<<<<<<<<<<<<
 * 
 *         return total / n_outputs
 */
    __pyx_v_label_count_total = (__pyx_v_label_count_total + __pyx_v_label_count_stride);
  }

  /* "sklearn/tree/_tree.pyx":401
 *             label_count_total += label_count_stride
 * 
 *         return total / n_outputs             # <<<<<<<<<<<<<<
 * 
 *     cdef void children_impurity(self, double* impurity_left,
 */
  __pyx_r = (__pyx_v_total / __pyx_v_n_outputs);
  goto __pyx_L0;

  /* "sklearn/tree/_tree.pyx":373
 *         cross-entropy = - \sum_{k=0}^{K-1} pmk log(pmk)
 *     """
 *     cdef double node_impurity(self) nogil:             # <<<<<<<<<<<<<<
 *         """Evaluate the impurity of the current node, i.e. the impurity of
 *            samples[start:end]."""
 */

  /* function exit code */
  __pyx_L0:;
  return __pyx_r;
}

/* "sklearn/tree/_tree.pyx":403
 *         return total / n_outputs
 * 
 *     cdef void children_impurity(self, double* impurity_left,             # <<<<<<<<<<<<<<
 *                                 double* impurity_right) nogil:
 *         """Evaluate the impurity in children nodes, i.e. the impurity of the
 */

static void __pyx_f_7sklearn_4tree_5_tree_7Entropy_children_impurity(struct __pyx_obj_7sklearn_4tree_5_tree_Entropy *__pyx_v_self, double *__pyx_v_impurity_left, double *__pyx_v_impurity_right) {
  CYTHON_UNUSED double __pyx_v_weighted_n_node_samples;
  double __pyx_v_weighted_n_left;
  double __pyx_v_weighted_n_right;
  __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_n_outputs;
  __pyx_t_7sklearn_4tree_5_tree_SIZE_t *__pyx_v_n_classes;
  __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_label_count_stride;
  double *__pyx_v_label_count_left;
  double *__pyx_v_label_count_right;
  double __pyx_v_entropy_left;
  double __pyx_v_entropy_right;
  double __pyx_v_total_left;
  double __pyx_v_total_right;
  double __pyx_v_tmp;
  __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_k;
  __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_c;
  double __pyx_t_1;
  __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_t_2;
  __pyx_t_7sklearn_4tree_5_tree_SIZE_t *__pyx_t_3;
  double *__pyx_t_4;
  __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_t_5;
  __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_t_6;
  __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_t_7;
  int __pyx_t_8;

  /* "sklearn/tree/_tree.pyx":408
 *            left child (samples[start:pos]) and the impurity the right child
 *            (samples[pos:end])."""
 *         cdef double weighted_n_node_samples = self.weighted_n_node_samples             # <<<<<<<<<<<<<<
 *         cdef double weighted_n_left = self.weighted_n_left
 *         cdef double weighted_n_right = self.weighted_n_right
 */
  __pyx_t_1 = __pyx_v_self->__pyx_base.__pyx_base.weighted_n_node_samples;
  __pyx_v_weighted_n_node_samples = __pyx_t_1;

  /* "sklearn/tree/_tree.pyx":409
 *            (samples[pos:end])."""
 *         cdef double weighted_n_node_samples = self.weighted_n_node_samples
 *         cdef double weighted_n_left = self.weighted_n_left             # <<<<<<<<<<<<<<
 *         cdef double weighted_n_right = self.weighted_n_right
 * 
 */
  __pyx_t_1 = __pyx_v_self->__pyx_base.__pyx_base.weighted_n_left;
  __pyx_v_weighted_n_left = __pyx_t_1;

  /* "sklearn/tree/_tree.pyx":410
 *         cdef double weighted_n_node_samples = self.weighted_n_node_samples
 *         cdef double weighted_n_left = self.weighted_n_left
 *         cdef double weighted_n_right = self.weighted_n_right             # <<<<<<<<<<<<<<
 * 
 *         cdef SIZE_t n_outputs = self.n_outputs
 */
  __pyx_t_1 = __pyx_v_self->__pyx_base.__pyx_base.weighted_n_right;
  __pyx_v_weighted_n_right = __pyx_t_1;

  /* "sklearn/tree/_tree.pyx":412
 *         cdef double weighted_n_right = self.weighted_n_right
 * 
 *         cdef SIZE_t n_outputs = self.n_outputs             # <<<<<<<<<<<<<<
 *         cdef SIZE_t* n_classes = self.n_classes
 *         cdef SIZE_t label_count_stride = self.label_count_stride
 */
  __pyx_t_2 = __pyx_v_self->__pyx_base.__pyx_base.n_outputs;
  __pyx_v_n_outputs = __pyx_t_2;

  /* "sklearn/tree/_tree.pyx":413
 * 
 *         cdef SIZE_t n_outputs = self.n_outputs
 *         cdef SIZE_t* n_classes = self.n_classes             # <<<<<<<<<<<<<<
 *         cdef SIZE_t label_count_stride = self.label_count_stride
 *         cdef double* label_count_left = self.label_count_left
 */
  __pyx_t_3 = __pyx_v_self->__pyx_base.n_classes;
  __pyx_v_n_classes = __pyx_t_3;

  /* "sklearn/tree/_tree.pyx":414
 *         cdef SIZE_t n_outputs = self.n_outputs
 *         cdef SIZE_t* n_classes = self.n_classes
 *         cdef SIZE_t label_count_stride = self.label_count_stride             # <<<<<<<<<<<<<<
 *         cdef double* label_count_left = self.label_count_left
 *         cdef double* label_count_right = self.label_count_right
 */
  __pyx_t_2 = __pyx_v_self->__pyx_base.label_count_stride;
  __pyx_v_label_count_stride = __pyx_t_2;

  /* "sklearn/tree/_tree.pyx":415
 *         cdef SIZE_t* n_classes = self.n_classes
 *         cdef SIZE_t label_count_stride = self.label_count_stride
 *         cdef double* label_count_left = self.label_count_left             # <<<<<<<<<<<<<<
 *         cdef double* label_count_right = self.label_count_right
 * 
 */
  __pyx_t_4 = __pyx_v_self->__pyx_base.label_count_left;
  __pyx_v_label_count_left = __pyx_t_4;

  /* "sklearn/tree/_tree.pyx":416
 *         cdef SIZE_t label_count_stride = self.label_count_stride
 *         cdef double* label_count_left = self.label_count_left
 *         cdef double* label_count_right = self.label_count_right             # <<<<<<<<<<<<<<
 * 
 *         cdef double entropy_left = 0.0
 */
  __pyx_t_4 = __pyx_v_self->__pyx_base.label_count_right;
  __pyx_v_label_count_right = __pyx_t_4;

  /* "sklearn/tree/_tree.pyx":418
 *         cdef double* label_count_right = self.label_count_right
 * 
 *         cdef double entropy_left = 0.0             # <<<<<<<<<<<<<<
 *         cdef double entropy_right = 0.0
 *         cdef double total_left = 0.0
 */
  __pyx_v_entropy_left = 0.0;

  /* "sklearn/tree/_tree.pyx":419
 * 
 *         cdef double entropy_left = 0.0
 *         cdef double entropy_right = 0.0             # <<<<<<<<<<<<<<
 *         cdef double total_left = 0.0
 *         cdef double total_right = 0.0
 */
  __pyx_v_entropy_right = 0.0;

  /* "sklearn/tree/_tree.pyx":420
 *         cdef double entropy_left = 0.0
 *         cdef double entropy_right = 0.0
 *         cdef double total_left = 0.0             # <<<<<<<<<<<<<<
 *         cdef double total_right = 0.0
 *         cdef double tmp
 */
  __pyx_v_total_left = 0.0;

  /* "sklearn/tree/_tree.pyx":421
 *         cdef double entropy_right = 0.0
 *         cdef double total_left = 0.0
 *         cdef double total_right = 0.0             # <<<<<<<<<<<<<<
 *         cdef double tmp
 *         cdef SIZE_t k
 */
  __pyx_v_total_right = 0.0;

  /* "sklearn/tree/_tree.pyx":426
 *         cdef SIZE_t c
 * 
 *         for k in range(n_outputs):             # <<<<<<<<<<<<<<
 *             entropy_left = 0.0
 *             entropy_right = 0.0
 */
  __pyx_t_2 = __pyx_v_n_outputs;
  for (__pyx_t_5 = 0; __pyx_t_5 < __pyx_t_2; __pyx_t_5+=1) {
    __pyx_v_k = __pyx_t_5;

    /* "sklearn/tree/_tree.pyx":427
 * 
 *         for k in range(n_outputs):
 *             entropy_left = 0.0             # <<<<<<<<<<<<<<
 *             entropy_right = 0.0
 * 
 */
    __pyx_v_entropy_left = 0.0;

    /* "sklearn/tree/_tree.pyx":428
 *         for k in range(n_outputs):
 *             entropy_left = 0.0
 *             entropy_right = 0.0             # <<<<<<<<<<<<<<
 * 
 *             for c in range(n_classes[k]):
 */
    __pyx_v_entropy_right = 0.0;

    /* "sklearn/tree/_tree.pyx":430
 *             entropy_right = 0.0
 * 
 *             for c in range(n_classes[k]):             # <<<<<<<<<<<<<<
 *                 tmp = label_count_left[c]
 *                 if tmp > 0.0:
 */
    __pyx_t_6 = (__pyx_v_n_classes[__pyx_v_k]);
    for (__pyx_t_7 = 0; __pyx_t_7 < __pyx_t_6; __pyx_t_7+=1) {
      __pyx_v_c = __pyx_t_7;

      /* "sklearn/tree/_tree.pyx":431
 * 
 *             for c in range(n_classes[k]):
 *                 tmp = label_count_left[c]             # <<<<<<<<<<<<<<
 *                 if tmp > 0.0:
 *                     tmp /= weighted_n_left
 */
      __pyx_v_tmp = (__pyx_v_label_count_left[__pyx_v_c]);

      /* "sklearn/tree/_tree.pyx":432
 *             for c in range(n_classes[k]):
 *                 tmp = label_count_left[c]
 *                 if tmp > 0.0:             # <<<<<<<<<<<<<<
 *                     tmp /= weighted_n_left
 *                     entropy_left -= tmp * log(tmp)
 */
      __pyx_t_8 = ((__pyx_v_tmp > 0.0) != 0);
      if (__pyx_t_8) {

        /* "sklearn/tree/_tree.pyx":433
 *                 tmp = label_count_left[c]
 *                 if tmp > 0.0:
 *                     tmp /= weighted_n_left             # <<<<<<<<<<<<<<
 *                     entropy_left -= tmp * log(tmp)
 * 
 */
        __pyx_v_tmp = (__pyx_v_tmp / __pyx_v_weighted_n_left);

        /* "sklearn/tree/_tree.pyx":434
 *                 if tmp > 0.0:
 *                     tmp /= weighted_n_left
 *                     entropy_left -= tmp * log(tmp)             # <<<<<<<<<<<<<<
 * 
 *                 tmp = label_count_right[c]
 */
        __pyx_v_entropy_left = (__pyx_v_entropy_left - (__pyx_v_tmp * __pyx_f_7sklearn_4tree_5_tree_log(__pyx_v_tmp)));
        goto __pyx_L7;
      }
      __pyx_L7:;

      /* "sklearn/tree/_tree.pyx":436
 *                     entropy_left -= tmp * log(tmp)
 * 
 *                 tmp = label_count_right[c]             # <<<<<<<<<<<<<<
 *                 if tmp > 0.0:
 *                     tmp /= weighted_n_right
 */
      __pyx_v_tmp = (__pyx_v_label_count_right[__pyx_v_c]);

      /* "sklearn/tree/_tree.pyx":437
 * 
 *                 tmp = label_count_right[c]
 *                 if tmp > 0.0:             # <<<<<<<<<<<<<<
 *                     tmp /= weighted_n_right
 *                     entropy_right -= tmp * log(tmp)
 */
      __pyx_t_8 = ((__pyx_v_tmp > 0.0) != 0);
      if (__pyx_t_8) {

        /* "sklearn/tree/_tree.pyx":438
 *                 tmp = label_count_right[c]
 *                 if tmp > 0.0:
 *                     tmp /= weighted_n_right             # <<<<<<<<<<<<<<
 *                     entropy_right -= tmp * log(tmp)
 * 
 */
        __pyx_v_tmp = (__pyx_v_tmp / __pyx_v_weighted_n_right);

        /* "sklearn/tree/_tree.pyx":439
 *                 if tmp > 0.0:
 *                     tmp /= weighted_n_right
 *                     entropy_right -= tmp * log(tmp)             # <<<<<<<<<<<<<<
 * 
 *             total_left += entropy_left
 */
        __pyx_v_entropy_right = (__pyx_v_entropy_right - (__pyx_v_tmp * __pyx_f_7sklearn_4tree_5_tree_log(__pyx_v_tmp)));
        goto __pyx_L8;
      }
      __pyx_L8:;
    }

    /* "sklearn/tree/_tree.pyx":441
 *                     entropy_right -= tmp * log(tmp)
 * 
 *             total_left += entropy_left             # <<<<<<<<<<<<<<
 *             total_right += entropy_right
 *             label_count_left += label_count_stride
 */
    __pyx_v_total_left = (__pyx_v_total_left + __pyx_v_entropy_left);

    /* "sklearn/tree/_tree.pyx":442
 * 
 *             total_left += entropy_left
 *             total_right += entropy_right             # <<<<<<<<<<<<<<
 *             label_count_left += label_count_stride
 *             label_count_right += label_count_stride
 */
    __pyx_v_total_right = (__pyx_v_total_right + __pyx_v_entropy_right);

    /* "sklearn/tree/_tree.pyx":443
 *             total_left += entropy_left
 *             total_right += entropy_right
 *             label_count_left += label_count_stride             # <<<<<<<<<<<<<<
 *             label_count_right += label_count_stride
 * 
 */
    __pyx_v_label_count_left = (__pyx_v_label_count_left + __pyx_v_label_count_stride);

    /* "sklearn/tree/_tree.pyx":444
 *             total_right += entropy_right
 *             label_count_left += label_count_stride
 *             label_count_right += label_count_stride             # <<<<<<<<<<<<<<
 * 
 *         impurity_left[0] = total_left / n_outputs
 */
    __pyx_v_label_count_right = (__pyx_v_label_count_right + __pyx_v_label_count_stride);
  }

  /* "sklearn/tree/_tree.pyx":446
 *             label_count_right += label_count_stride
 * 
 *         impurity_left[0] = total_left / n_outputs             # <<<<<<<<<<<<<<
 *         impurity_right[0] = total_right / n_outputs
 * 
 */
  (__pyx_v_impurity_left[0]) = (__pyx_v_total_left / __pyx_v_n_outputs);

  /* "sklearn/tree/_tree.pyx":447
 * 
 *         impurity_left[0] = total_left / n_outputs
 *         impurity_right[0] = total_right / n_outputs             # <<<<<<<<<<<<<<
 * 
 * 
 */
  (__pyx_v_impurity_right[0]) = (__pyx_v_total_right / __pyx_v_n_outputs);

  /* "sklearn/tree/_tree.pyx":403
 *         return total / n_outputs
 * 
 *     cdef void children_impurity(self, double* impurity_left,             # <<<<<<<<<<<<<<
 *                                 double* impurity_right) nogil:
 *         """Evaluate the impurity in children nodes, i.e. the impurity of the
 */

  /* function exit code */
}

/* "sklearn/tree/_tree.pyx":465
 *               = 1 - \sum_{k=0}^{K-1} pmk ** 2
 *     """
 *     cdef double node_impurity(self) nogil:             # <<<<<<<<<<<<<<
 *         """Evaluate the impurity of the current node, i.e. the impurity of
 *            samples[start:end]."""
 */

static double __pyx_f_7sklearn_4tree_5_tree_4Gini_node_impurity(struct __pyx_obj_7sklearn_4tree_5_tree_Gini *__pyx_v_self) {
  double __pyx_v_weighted_n_node_samples;
  __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_n_outputs;
  __pyx_t_7sklearn_4tree_5_tree_SIZE_t *__pyx_v_n_classes;
  __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_label_count_stride;
  double *__pyx_v_label_count_total;
  double __pyx_v_gini;
  double __pyx_v_total;
  double __pyx_v_tmp;
  __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_k;
  __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_c;
  double __pyx_r;
  double __pyx_t_1;
  __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_t_2;
  __pyx_t_7sklearn_4tree_5_tree_SIZE_t *__pyx_t_3;
  double *__pyx_t_4;
  __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_t_5;
  __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_t_6;
  __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_t_7;

  /* "sklearn/tree/_tree.pyx":468
 *         """Evaluate the impurity of the current node, i.e. the impurity of
 *            samples[start:end]."""
 *         cdef double weighted_n_node_samples = self.weighted_n_node_samples             # <<<<<<<<<<<<<<
 * 
 *         cdef SIZE_t n_outputs = self.n_outputs
 */
  __pyx_t_1 = __pyx_v_self->__pyx_base.__pyx_base.weighted_n_node_samples;
  __pyx_v_weighted_n_node_samples = __pyx_t_1;

  /* "sklearn/tree/_tree.pyx":470
 *         cdef double weighted_n_node_samples = self.weighted_n_node_samples
 * 
 *         cdef SIZE_t n_outputs = self.n_outputs             # <<<<<<<<<<<<<<
 *         cdef SIZE_t* n_classes = self.n_classes
 *         cdef SIZE_t label_count_stride = self.label_count_stride
 */
  __pyx_t_2 = __pyx_v_self->__pyx_base.__pyx_base.n_outputs;
  __pyx_v_n_outputs = __pyx_t_2;

  /* "sklearn/tree/_tree.pyx":471
 * 
 *         cdef SIZE_t n_outputs = self.n_outputs
 *         cdef SIZE_t* n_classes = self.n_classes             # <<<<<<<<<<<<<<
 *         cdef SIZE_t label_count_stride = self.label_count_stride
 *         cdef double* label_count_total = self.label_count_total
 */
  __pyx_t_3 = __pyx_v_self->__pyx_base.n_classes;
  __pyx_v_n_classes = __pyx_t_3;

  /* "sklearn/tree/_tree.pyx":472
 *         cdef SIZE_t n_outputs = self.n_outputs
 *         cdef SIZE_t* n_classes = self.n_classes
 *         cdef SIZE_t label_count_stride = self.label_count_stride             # <<<<<<<<<<<<<<
 *         cdef double* label_count_total = self.label_count_total
 * 
 */
  __pyx_t_2 = __pyx_v_self->__pyx_base.label_count_stride;
  __pyx_v_label_count_stride = __pyx_t_2;

  /* "sklearn/tree/_tree.pyx":473
 *         cdef SIZE_t* n_classes = self.n_classes
 *         cdef SIZE_t label_count_stride = self.label_count_stride
 *         cdef double* label_count_total = self.label_count_total             # <<<<<<<<<<<<<<
 * 
 *         cdef double gini = 0.0
 */
  __pyx_t_4 = __pyx_v_self->__pyx_base.label_count_total;
  __pyx_v_label_count_total = __pyx_t_4;

  /* "sklearn/tree/_tree.pyx":475
 *         cdef double* label_count_total = self.label_count_total
 * 
 *         cdef double gini = 0.0             # <<<<<<<<<<<<<<
 *         cdef double total = 0.0
 *         cdef double tmp
 */
  __pyx_v_gini = 0.0;

  /* "sklearn/tree/_tree.pyx":476
 * 
 *         cdef double gini = 0.0
 *         cdef double total = 0.0             # <<<<<<<<<<<<<<
 *         cdef double tmp
 *         cdef SIZE_t k
 */
  __pyx_v_total = 0.0;

  /* "sklearn/tree/_tree.pyx":481
 *         cdef SIZE_t c
 * 
 *         for k in range(n_outputs):             # <<<<<<<<<<<<<<
 *             gini = 0.0
 * 
 */
  __pyx_t_2 = __pyx_v_n_outputs;
  for (__pyx_t_5 = 0; __pyx_t_5 < __pyx_t_2; __pyx_t_5+=1) {
    __pyx_v_k = __pyx_t_5;

    /* "sklearn/tree/_tree.pyx":482
 * 
 *         for k in range(n_outputs):
 *             gini = 0.0             # <<<<<<<<<<<<<<
 * 
 *             for c in range(n_classes[k]):
 */
    __pyx_v_gini = 0.0;

    /* "sklearn/tree/_tree.pyx":484
 *             gini = 0.0
 * 
 *             for c in range(n_classes[k]):             # <<<<<<<<<<<<<<
 *                 tmp = label_count_total[c]
 *                 gini += tmp * tmp
 */
    __pyx_t_6 = (__pyx_v_n_classes[__pyx_v_k]);
    for (__pyx_t_7 = 0; __pyx_t_7 < __pyx_t_6; __pyx_t_7+=1) {
      __pyx_v_c = __pyx_t_7;

      /* "sklearn/tree/_tree.pyx":485
 * 
 *             for c in range(n_classes[k]):
 *                 tmp = label_count_total[c]             # <<<<<<<<<<<<<<
 *                 gini += tmp * tmp
 * 
 */
      __pyx_v_tmp = (__pyx_v_label_count_total[__pyx_v_c]);

      /* "sklearn/tree/_tree.pyx":486
 *             for c in range(n_classes[k]):
 *                 tmp = label_count_total[c]
 *                 gini += tmp * tmp             # <<<<<<<<<<<<<<
 * 
 *             gini = 1.0 - gini / (weighted_n_node_samples *
 */
      __pyx_v_gini = (__pyx_v_gini + (__pyx_v_tmp * __pyx_v_tmp));
    }

    /* "sklearn/tree/_tree.pyx":488
 *                 gini += tmp * tmp
 * 
 *             gini = 1.0 - gini / (weighted_n_node_samples *             # <<<<<<<<<<<<<<
 *                                  weighted_n_node_samples)
 * 
 */
    __pyx_v_gini = (1.0 - (__pyx_v_gini / (__pyx_v_weighted_n_node_samples * __pyx_v_weighted_n_node_samples)));

    /* "sklearn/tree/_tree.pyx":491
 *                                  weighted_n_node_samples)
 * 
 *             total += gini             # <<<<<<<<<<<<<<
 *             label_count_total += label_count_stride
 * 
 */
    __pyx_v_total = (__pyx_v_total + __pyx_v_gini);

    /* "sklearn/tree/_tree.pyx":492
 * 
 *             total += gini
 *             label_count_total += label_count_stride             # <<<<<<<<<<<<<<
 * 
 *         return total / n_outputs
 */
    __pyx_v_label_count_total = (__pyx_v_label_count_total + __pyx_v_label_count_stride);
  }

  /* "sklearn/tree/_tree.pyx":494
 *             label_count_total += label_count_stride
 * 
 *         return total / n_outputs             # <<<<<<<<<<<<<<
 * 
 *     cdef void children_impurity(self, double* impurity_left,
 */
  __pyx_r = (__pyx_v_total / __pyx_v_n_outputs);
  goto __pyx_L0;

  /* "sklearn/tree/_tree.pyx":465
 *               = 1 - \sum_{k=0}^{K-1} pmk ** 2
 *     """
 *     cdef double node_impurity(self) nogil:             # <<<<<<<<<<<<<<
 *         """Evaluate the impurity of the current node, i.e. the impurity of
 *            samples[start:end]."""
 */

  /* function exit code */
  __pyx_L0:;
  return __pyx_r;
}

/* "sklearn/tree/_tree.pyx":496
 *         return total / n_outputs
 * 
 *     cdef void children_impurity(self, double* impurity_left,             # <<<<<<<<<<<<<<
 *                                 double* impurity_right) nogil:
 *         """Evaluate the impurity in children nodes, i.e. the impurity of the
 */

static void __pyx_f_7sklearn_4tree_5_tree_4Gini_children_impurity(struct __pyx_obj_7sklearn_4tree_5_tree_Gini *__pyx_v_self, double *__pyx_v_impurity_left, double *__pyx_v_impurity_right) {
  CYTHON_UNUSED double __pyx_v_weighted_n_node_samples;
  double __pyx_v_weighted_n_left;
  double __pyx_v_weighted_n_right;
  __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_n_outputs;
  __pyx_t_7sklearn_4tree_5_tree_SIZE_t *__pyx_v_n_classes;
  __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_label_count_stride;
  double *__pyx_v_label_count_left;
  double *__pyx_v_label_count_right;
  double __pyx_v_gini_left;
  double __pyx_v_gini_right;
  CYTHON_UNUSED double __pyx_v_total;
  double __pyx_v_total_left;
  double __pyx_v_total_right;
  double __pyx_v_tmp;
  __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_k;
  __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_c;
  double __pyx_t_1;
  __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_t_2;
  __pyx_t_7sklearn_4tree_5_tree_SIZE_t *__pyx_t_3;
  double *__pyx_t_4;
  __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_t_5;
  __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_t_6;
  __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_t_7;

  /* "sklearn/tree/_tree.pyx":501
 *            left child (samples[start:pos]) and the impurity the right child
 *            (samples[pos:end])."""
 *         cdef double weighted_n_node_samples = self.weighted_n_node_samples             # <<<<<<<<<<<<<<
 *         cdef double weighted_n_left = self.weighted_n_left
 *         cdef double weighted_n_right = self.weighted_n_right
 */
  __pyx_t_1 = __pyx_v_self->__pyx_base.__pyx_base.weighted_n_node_samples;
  __pyx_v_weighted_n_node_samples = __pyx_t_1;

  /* "sklearn/tree/_tree.pyx":502
 *            (samples[pos:end])."""
 *         cdef double weighted_n_node_samples = self.weighted_n_node_samples
 *         cdef double weighted_n_left = self.weighted_n_left             # <<<<<<<<<<<<<<
 *         cdef double weighted_n_right = self.weighted_n_right
 * 
 */
  __pyx_t_1 = __pyx_v_self->__pyx_base.__pyx_base.weighted_n_left;
  __pyx_v_weighted_n_left = __pyx_t_1;

  /* "sklearn/tree/_tree.pyx":503
 *         cdef double weighted_n_node_samples = self.weighted_n_node_samples
 *         cdef double weighted_n_left = self.weighted_n_left
 *         cdef double weighted_n_right = self.weighted_n_right             # <<<<<<<<<<<<<<
 * 
 *         cdef SIZE_t n_outputs = self.n_outputs
 */
  __pyx_t_1 = __pyx_v_self->__pyx_base.__pyx_base.weighted_n_right;
  __pyx_v_weighted_n_right = __pyx_t_1;

  /* "sklearn/tree/_tree.pyx":505
 *         cdef double weighted_n_right = self.weighted_n_right
 * 
 *         cdef SIZE_t n_outputs = self.n_outputs             # <<<<<<<<<<<<<<
 *         cdef SIZE_t* n_classes = self.n_classes
 *         cdef SIZE_t label_count_stride = self.label_count_stride
 */
  __pyx_t_2 = __pyx_v_self->__pyx_base.__pyx_base.n_outputs;
  __pyx_v_n_outputs = __pyx_t_2;

  /* "sklearn/tree/_tree.pyx":506
 * 
 *         cdef SIZE_t n_outputs = self.n_outputs
 *         cdef SIZE_t* n_classes = self.n_classes             # <<<<<<<<<<<<<<
 *         cdef SIZE_t label_count_stride = self.label_count_stride
 *         cdef double* label_count_left = self.label_count_left
 */
  __pyx_t_3 = __pyx_v_self->__pyx_base.n_classes;
  __pyx_v_n_classes = __pyx_t_3;

  /* "sklearn/tree/_tree.pyx":507
 *         cdef SIZE_t n_outputs = self.n_outputs
 *         cdef SIZE_t* n_classes = self.n_classes
 *         cdef SIZE_t label_count_stride = self.label_count_stride             # <<<<<<<<<<<<<<
 *         cdef double* label_count_left = self.label_count_left
 *         cdef double* label_count_right = self.label_count_right
 */
  __pyx_t_2 = __pyx_v_self->__pyx_base.label_count_stride;
  __pyx_v_label_count_stride = __pyx_t_2;

  /* "sklearn/tree/_tree.pyx":508
 *         cdef SIZE_t* n_classes = self.n_classes
 *         cdef SIZE_t label_count_stride = self.label_count_stride
 *         cdef double* label_count_left = self.label_count_left             # <<<<<<<<<<<<<<
 *         cdef double* label_count_right = self.label_count_right
 * 
 */
  __pyx_t_4 = __pyx_v_self->__pyx_base.label_count_left;
  __pyx_v_label_count_left = __pyx_t_4;

  /* "sklearn/tree/_tree.pyx":509
 *         cdef SIZE_t label_count_stride = self.label_count_stride
 *         cdef double* label_count_left = self.label_count_left
 *         cdef double* label_count_right = self.label_count_right             # <<<<<<<<<<<<<<
 * 
 *         cdef double gini_left = 0.0
 */
  __pyx_t_4 = __pyx_v_self->__pyx_base.label_count_right;
  __pyx_v_label_count_right = __pyx_t_4;

  /* "sklearn/tree/_tree.pyx":511
 *         cdef double* label_count_right = self.label_count_right
 * 
 *         cdef double gini_left = 0.0             # <<<<<<<<<<<<<<
 *         cdef double gini_right = 0.0
 *         cdef double total = 0.0
 */
  __pyx_v_gini_left = 0.0;

  /* "sklearn/tree/_tree.pyx":512
 * 
 *         cdef double gini_left = 0.0
 *         cdef double gini_right = 0.0             # <<<<<<<<<<<<<<
 *         cdef double total = 0.0
 *         cdef double total_left = 0.0
 */
  __pyx_v_gini_right = 0.0;

  /* "sklearn/tree/_tree.pyx":513
 *         cdef double gini_left = 0.0
 *         cdef double gini_right = 0.0
 *         cdef double total = 0.0             # <<<<<<<<<<<<<<
 *         cdef double total_left = 0.0
 *         cdef double total_right = 0.0
 */
  __pyx_v_total = 0.0;

  /* "sklearn/tree/_tree.pyx":514
 *         cdef double gini_right = 0.0
 *         cdef double total = 0.0
 *         cdef double total_left = 0.0             # <<<<<<<<<<<<<<
 *         cdef double total_right = 0.0
 *         cdef double tmp
 */
  __pyx_v_total_left = 0.0;

  /* "sklearn/tree/_tree.pyx":515
 *         cdef double total = 0.0
 *         cdef double total_left = 0.0
 *         cdef double total_right = 0.0             # <<<<<<<<<<<<<<
 *         cdef double tmp
 *         cdef SIZE_t k
 */
  __pyx_v_total_right = 0.0;

  /* "sklearn/tree/_tree.pyx":520
 *         cdef SIZE_t c
 * 
 *         for k in range(n_outputs):             # <<<<<<<<<<<<<<
 *             gini_left = 0.0
 *             gini_right = 0.0
 */
  __pyx_t_2 = __pyx_v_n_outputs;
  for (__pyx_t_5 = 0; __pyx_t_5 < __pyx_t_2; __pyx_t_5+=1) {
    __pyx_v_k = __pyx_t_5;

    /* "sklearn/tree/_tree.pyx":521
 * 
 *         for k in range(n_outputs):
 *             gini_left = 0.0             # <<<<<<<<<<<<<<
 *             gini_right = 0.0
 * 
 */
    __pyx_v_gini_left = 0.0;

    /* "sklearn/tree/_tree.pyx":522
 *         for k in range(n_outputs):
 *             gini_left = 0.0
 *             gini_right = 0.0             # <<<<<<<<<<<<<<
 * 
 *             for c in range(n_classes[k]):
 */
    __pyx_v_gini_right = 0.0;

    /* "sklearn/tree/_tree.pyx":524
 *             gini_right = 0.0
 * 
 *             for c in range(n_classes[k]):             # <<<<<<<<<<<<<<
 *                 tmp = label_count_left[c]
 *                 gini_left += tmp * tmp
 */
    __pyx_t_6 = (__pyx_v_n_classes[__pyx_v_k]);
    for (__pyx_t_7 = 0; __pyx_t_7 < __pyx_t_6; __pyx_t_7+=1) {
      __pyx_v_c = __pyx_t_7;

      /* "sklearn/tree/_tree.pyx":525
 * 
 *             for c in range(n_classes[k]):
 *                 tmp = label_count_left[c]             # <<<<<<<<<<<<<<
 *                 gini_left += tmp * tmp
 *                 tmp = label_count_right[c]
 */
      __pyx_v_tmp = (__pyx_v_label_count_left[__pyx_v_c]);

      /* "sklearn/tree/_tree.pyx":526
 *             for c in range(n_classes[k]):
 *                 tmp = label_count_left[c]
 *                 gini_left += tmp * tmp             # <<<<<<<<<<<<<<
 *                 tmp = label_count_right[c]
 *                 gini_right += tmp * tmp
 */
      __pyx_v_gini_left = (__pyx_v_gini_left + (__pyx_v_tmp * __pyx_v_tmp));

      /* "sklearn/tree/_tree.pyx":527
 *                 tmp = label_count_left[c]
 *                 gini_left += tmp * tmp
 *                 tmp = label_count_right[c]             # <<<<<<<<<<<<<<
 *                 gini_right += tmp * tmp
 * 
 */
      __pyx_v_tmp = (__pyx_v_label_count_right[__pyx_v_c]);

      /* "sklearn/tree/_tree.pyx":528
 *                 gini_left += tmp * tmp
 *                 tmp = label_count_right[c]
 *                 gini_right += tmp * tmp             # <<<<<<<<<<<<<<
 * 
 *             gini_left = 1.0 - gini_left / (weighted_n_left *
 */
      __pyx_v_gini_right = (__pyx_v_gini_right + (__pyx_v_tmp * __pyx_v_tmp));
    }

    /* "sklearn/tree/_tree.pyx":530
 *                 gini_right += tmp * tmp
 * 
 *             gini_left = 1.0 - gini_left / (weighted_n_left *             # <<<<<<<<<<<<<<
 *                                            weighted_n_left)
 *             gini_right = 1.0 - gini_right / (weighted_n_right *
 */
    __pyx_v_gini_left = (1.0 - (__pyx_v_gini_left / (__pyx_v_weighted_n_left * __pyx_v_weighted_n_left)));

    /* "sklearn/tree/_tree.pyx":532
 *             gini_left = 1.0 - gini_left / (weighted_n_left *
 *                                            weighted_n_left)
 *             gini_right = 1.0 - gini_right / (weighted_n_right *             # <<<<<<<<<<<<<<
 *                                              weighted_n_right)
 * 
 */
    __pyx_v_gini_right = (1.0 - (__pyx_v_gini_right / (__pyx_v_weighted_n_right * __pyx_v_weighted_n_right)));

    /* "sklearn/tree/_tree.pyx":535
 *                                              weighted_n_right)
 * 
 *             total_left += gini_left             # <<<<<<<<<<<<<<
 *             total_right += gini_right
 *             label_count_left += label_count_stride
 */
    __pyx_v_total_left = (__pyx_v_total_left + __pyx_v_gini_left);

    /* "sklearn/tree/_tree.pyx":536
 * 
 *             total_left += gini_left
 *             total_right += gini_right             # <<<<<<<<<<<<<<
 *             label_count_left += label_count_stride
 *             label_count_right += label_count_stride
 */
    __pyx_v_total_right = (__pyx_v_total_right + __pyx_v_gini_right);

    /* "sklearn/tree/_tree.pyx":537
 *             total_left += gini_left
 *             total_right += gini_right
 *             label_count_left += label_count_stride             # <<<<<<<<<<<<<<
 *             label_count_right += label_count_stride
 * 
 */
    __pyx_v_label_count_left = (__pyx_v_label_count_left + __pyx_v_label_count_stride);

    /* "sklearn/tree/_tree.pyx":538
 *             total_right += gini_right
 *             label_count_left += label_count_stride
 *             label_count_right += label_count_stride             # <<<<<<<<<<<<<<
 * 
 *         impurity_left[0] = total_left / n_outputs
 */
    __pyx_v_label_count_right = (__pyx_v_label_count_right + __pyx_v_label_count_stride);
  }

  /* "sklearn/tree/_tree.pyx":540
 *             label_count_right += label_count_stride
 * 
 *         impurity_left[0] = total_left / n_outputs             # <<<<<<<<<<<<<<
 *         impurity_right[0] = total_right / n_outputs
 * 
 */
  (__pyx_v_impurity_left[0]) = (__pyx_v_total_left / __pyx_v_n_outputs);

  /* "sklearn/tree/_tree.pyx":541
 * 
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 *         self.samples = NULL
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 *         self.sq_sum_right = NULL
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 *         self.mean_left = <double*> calloc(n_outputs, sizeof(double))
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 *         self.sq_sum_total = <double*> calloc(n_outputs, sizeof(double))
 *         self.var_left = <double*> calloc(n_outputs, sizeof(double))             # <<<<<<<<<<<<<<
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 *         self.var_left = <double*> calloc(n_outputs, sizeof(double))
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 *         if (self.mean_left == NULL or
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 *         cdef double* mean_total = self.mean_total
 *         cdef double* sq_sum_left = self.sq_sum_left
 *         cdef double* sq_sum_right = self.sq_sum_right             # <<<<<<<<<<<<<<
 *         cdef double* sq_sum_total = self.sq_sum_total
 *         cdef double* var_left = self.var_left
 */
  __pyx_t_2 = __pyx_v_self->sq_sum_right;
  __pyx_v_sq_sum_right = __pyx_t_2;

  /* "sklearn/tree/_tree.pyx":667
 *         cdef double* sq_sum_left = self.sq_sum_left
 *         cdef double* sq_sum_right = self.sq_sum_right
 *         cdef double* sq_sum_total = self.sq_sum_total             # <<<<<<<<<<<<<<
 *         cdef double* var_left = self.var_left
 *         cdef double* var_right = self.var_right
 */
  __pyx_t_2 = __pyx_v_self->sq_sum_total;
  __pyx_v_sq_sum_total = __pyx_t_2;

  /* "sklearn/tree/_tree.pyx":668
 *         cdef double* sq_sum_right = self.sq_sum_right
 *         cdef double* sq_sum_total = self.sq_sum_total
 *         cdef double* var_left = self.var_left             # <<<<<<<<<<<<<<
 *         cdef double* var_right = self.var_right
 *         cdef double* sum_left = self.sum_left
 */
  __pyx_t_2 = __pyx_v_self->var_left;
  __pyx_v_var_left = __pyx_t_2;

  /* "sklearn/tree/_tree.pyx":669
 *         cdef double* sq_sum_total = self.sq_sum_total
 *         cdef double* var_left = self.var_left
 *         cdef double* var_right = self.var_right             # <<<<<<<<<<<<<<
 *         cdef double* sum_left = self.sum_left
 *         cdef double* sum_right = self.sum_right
 */
  __pyx_t_2 = __pyx_v_self->var_right;
  __pyx_v_var_right = __pyx_t_2;

  /* "sklearn/tree/_tree.pyx":670
 *         cdef double* var_left = self.var_left
 *         cdef double* var_right = self.var_right
 *         cdef double* sum_left = self.sum_left             # <<<<<<<<<<<<<<
 *         cdef double* sum_right = self.sum_right
 *         cdef double* sum_total = self.sum_total
 */
  __pyx_t_2 = __pyx_v_self->sum_left;
  __pyx_v_sum_left = __pyx_t_2;

  /* "sklearn/tree/_tree.pyx":671
 *         cdef double* var_right = self.var_right
 *         cdef double* sum_left = self.sum_left
 *         cdef double* sum_right = self.sum_right             # <<<<<<<<<<<<<<
 *         cdef double* sum_total = self.sum_total
 * 
 */
  __pyx_t_2 = __pyx_v_self->sum_right;
  __pyx_v_sum_right = __pyx_t_2;

  /* "sklearn/tree/_tree.pyx":672
 *         cdef double* sum_left = self.sum_left
 *         cdef double* sum_right = self.sum_right
 *         cdef double* sum_total = self.sum_total             # <<<<<<<<<<<<<<
 * 
 *         cdef SIZE_t i = 0
 */
  __pyx_t_2 = __pyx_v_self->sum_total;
  __pyx_v_sum_total = __pyx_t_2;

  /* "sklearn/tree/_tree.pyx":674
 *         cdef double* sum_total = self.sum_total
 * 
 *         cdef SIZE_t i = 0             # <<<<<<<<<<<<<<
 *         cdef SIZE_t p = 0
 *         cdef SIZE_t k = 0
 */
  __pyx_v_i = 0;

  /* "sklearn/tree/_tree.pyx":675
 * 
 *         cdef SIZE_t i = 0
 *         cdef SIZE_t p = 0             # <<<<<<<<<<<<<<
 *         cdef SIZE_t k = 0
 *         cdef DOUBLE_t y_ik = 0.0
 */
  __pyx_v_p = 0;

  /* "sklearn/tree/_tree.pyx":676
 *         cdef SIZE_t i = 0
 *         cdef SIZE_t p = 0
 *         cdef SIZE_t k = 0             # <<<<<<<<<<<<<<
 *         cdef DOUBLE_t y_ik = 0.0
 *         cdef DOUBLE_t w_y_ik = 0.0
 */
  __pyx_v_k = 0;

  /* "sklearn/tree/_tree.pyx":677
 *         cdef SIZE_t p = 0
 *         cdef SIZE_t k = 0
 *         cdef DOUBLE_t y_ik = 0.0             # <<<<<<<<<<<<<<
 *         cdef DOUBLE_t w_y_ik = 0.0
 *         cdef DOUBLE_t w = 1.0
 */
  __pyx_v_y_ik = 0.0;

  /* "sklearn/tree/_tree.pyx":678
 *         cdef SIZE_t k = 0
 *         cdef DOUBLE_t y_ik = 0.0
 *         cdef DOUBLE_t w_y_ik = 0.0             # <<<<<<<<<<<<<<
 *         cdef DOUBLE_t w = 1.0
 * 
 */
  __pyx_v_w_y_ik = 0.0;

  /* "sklearn/tree/_tree.pyx":679
 *         cdef DOUBLE_t y_ik = 0.0
 *         cdef DOUBLE_t w_y_ik = 0.0
 *         cdef DOUBLE_t w = 1.0             # <<<<<<<<<<<<<<
 * 
 *         cdef SIZE_t n_bytes = n_outputs * sizeof(double)
 */
  __pyx_v_w = 1.0;

  /* "sklearn/tree/_tree.pyx":681
 *         cdef DOUBLE_t w = 1.0
 * 
 *         cdef SIZE_t n_bytes = n_outputs * sizeof(double)             # <<<<<<<<<<<<<<
 *         memset(mean_left, 0, n_bytes)
 *         memset(mean_right, 0, n_bytes)
 */
  __pyx_v_n_bytes = (__pyx_v_n_outputs * (sizeof(double)));

  /* "sklearn/tree/_tree.pyx":682
 * 
 *         cdef SIZE_t n_bytes = n_outputs * sizeof(double)
 *         memset(mean_left, 0, n_bytes)             # <<<<<<<<<<<<<<
 *         memset(mean_right, 0, n_bytes)
 *         memset(mean_total, 0, n_bytes)
 */
  memset(__pyx_v_mean_left, 0, __pyx_v_n_bytes);

  /* "sklearn/tree/_tree.pyx":683
 *         cdef SIZE_t n_bytes = n_outputs * sizeof(double)
 *         memset(mean_left, 0, n_bytes)
 *         memset(mean_right, 0, n_bytes)             # <<<<<<<<<<<<<<
 *         memset(mean_total, 0, n_bytes)
 *         memset(sq_sum_left, 0, n_bytes)
 */
  memset(__pyx_v_mean_right, 0, __pyx_v_n_bytes);

  /* "sklearn/tree/_tree.pyx":684
 *         memset(mean_left, 0, n_bytes)
 *         memset(mean_right, 0, n_bytes)
 *         memset(mean_total, 0, n_bytes)             # <<<<<<<<<<<<<<
 *         memset(sq_sum_left, 0, n_bytes)
 *         memset(sq_sum_right, 0, n_bytes)
 */
  memset(__pyx_v_mean_total, 0, __pyx_v_n_bytes);

  /* "sklearn/tree/_tree.pyx":685
 *         memset(mean_right, 0, n_bytes)
 *         memset(mean_total, 0, n_bytes)
 *         memset(sq_sum_left, 0, n_bytes)             # <<<<<<<<<<<<<<
 *         memset(sq_sum_right, 0, n_bytes)
 *         memset(sq_sum_total, 0, n_bytes)
 */
  memset(__pyx_v_sq_sum_left, 0, __pyx_v_n_bytes);

  /* "sklearn/tree/_tree.pyx":686
 *         memset(mean_total, 0, n_bytes)
 *         memset(sq_sum_left, 0, n_bytes)
 *         memset(sq_sum_right, 0, n_bytes)             # <<<<<<<<<<<<<<
 *         memset(sq_sum_total, 0, n_bytes)
 *         memset(var_left, 0, n_bytes)
 */
  memset(__pyx_v_sq_sum_right, 0, __pyx_v_n_bytes);

  /* "sklearn/tree/_tree.pyx":687
 *         memset(sq_sum_left, 0, n_bytes)
 *         memset(sq_sum_right, 0, n_bytes)
 *         memset(sq_sum_total, 0, n_bytes)             # <<<<<<<<<<<<<<
 *         memset(var_left, 0, n_bytes)
 *         memset(var_right, 0, n_bytes)
 */
  memset(__pyx_v_sq_sum_total, 0, __pyx_v_n_bytes);

  /* "sklearn/tree/_tree.pyx":688
 *         memset(sq_sum_right, 0, n_bytes)
 *         memset(sq_sum_total, 0, n_bytes)
 *         memset(var_left, 0, n_bytes)             # <<<<<<<<<<<<<<
 *         memset(var_right, 0, n_bytes)
 *         memset(sum_left, 0, n_bytes)
 */
  memset(__pyx_v_var_left, 0, __pyx_v_n_bytes);

  /* "sklearn/tree/_tree.pyx":689
 *         memset(sq_sum_total, 0, n_bytes)
 *         memset(var_left, 0, n_bytes)
 *         memset(var_right, 0, n_bytes)             # <<<<<<<<<<<<<<
 *         memset(sum_left, 0, n_bytes)
 *         memset(sum_right, 0, n_bytes)
 */
  memset(__pyx_v_var_right, 0, __pyx_v_n_bytes);

  /* "sklearn/tree/_tree.pyx":690
 *         memset(var_left, 0, n_bytes)
 *         memset(var_right, 0, n_bytes)
 *         memset(sum_left, 0, n_bytes)             # <<<<<<<<<<<<<<
 *         memset(sum_right, 0, n_bytes)
 *         memset(sum_total, 0, n_bytes)
 */
  memset(__pyx_v_sum_left, 0, __pyx_v_n_bytes);

  /* "sklearn/tree/_tree.pyx":691
 *         memset(var_right, 0, n_bytes)
 *         memset(sum_left, 0, n_bytes)
 *         memset(sum_right, 0, n_bytes)             # <<<<<<<<<<<<<<
 *         memset(sum_total, 0, n_bytes)
 * 
 */
  memset(__pyx_v_sum_right, 0, __pyx_v_n_bytes);

  /* "sklearn/tree/_tree.pyx":692
 *         memset(sum_left, 0, n_bytes)
 *         memset(sum_right, 0, n_bytes)
 *         memset(sum_total, 0, n_bytes)             # <<<<<<<<<<<<<<
 * 
 *         for p in range(start, end):
 */
  memset(__pyx_v_sum_total, 0, __pyx_v_n_bytes);

  /* "sklearn/tree/_tree.pyx":694
 *         memset(sum_total, 0, n_bytes)
 * 
 *         for p in range(start, end):             # <<<<<<<<<<<<<<
 *             i = samples[p]
 * 
 */
  __pyx_t_1 = __pyx_v_end;
  for (__pyx_t_3 = __pyx_v_start; __pyx_t_3 < __pyx_t_1; __pyx_t_3+=1) {
    __pyx_v_p = __pyx_t_3;

    /* "sklearn/tree/_tree.pyx":695
 * 
 *         for p in range(start, end):
 *             i = samples[p]             # <<<<<<<<<<<<<<
 * 
 *             if sample_weight != NULL:
 */
    __pyx_v_i = (__pyx_v_samples[__pyx_v_p]);

    /* "sklearn/tree/_tree.pyx":697
 *             i = samples[p]
 * 
 *             if sample_weight != NULL:             # <<<<<<<<<<<<<<
 *                 w = sample_weight[i]
 * 
 */
    __pyx_t_4 = ((__pyx_v_sample_weight != NULL) != 0);
    if (__pyx_t_4) {

      /* "sklearn/tree/_tree.pyx":698
 * 
 *             if sample_weight != NULL:
 *                 w = sample_weight[i]             # <<<<<<<<<<<<<<
 * 
 *             for k in range(n_outputs):
 */
      __pyx_v_w = (__pyx_v_sample_weight[__pyx_v_i]);
      goto __pyx_L5;
    }
    __pyx_L5:;

    /* "sklearn/tree/_tree.pyx":700
 *                 w = sample_weight[i]
 * 
 *             for k in range(n_outputs):             # <<<<<<<<<<<<<<
 *                 y_ik = y[i * y_stride + k]
 *                 w_y_ik = w * y_ik
 */
    __pyx_t_5 = __pyx_v_n_outputs;
    for (__pyx_t_6 = 0; __pyx_t_6 < __pyx_t_5; __pyx_t_6+=1) {
      __pyx_v_k = __pyx_t_6;

      /* "sklearn/tree/_tree.pyx":701
 * 
 *             for k in range(n_outputs):
 *                 y_ik = y[i * y_stride + k]             # <<<<<<<<<<<<<<
 *                 w_y_ik = w * y_ik
 *                 sum_total[k] += w_y_ik
 */
      __pyx_v_y_ik = (__pyx_v_y[((__pyx_v_i * __pyx_v_y_stride) + __pyx_v_k)]);

      /* "sklearn/tree/_tree.pyx":702
 *             for k in range(n_outputs):
 *                 y_ik = y[i * y_stride + k]
 *                 w_y_ik = w * y_ik             # <<<<<<<<<<<<<<
 *                 sum_total[k] += w_y_ik
 *                 sq_sum_total[k] += w_y_ik * y_ik
 */
      __pyx_v_w_y_ik = (__pyx_v_w * __pyx_v_y_ik);

      /* "sklearn/tree/_tree.pyx":703
 *                 y_ik = y[i * y_stride + k]
 *                 w_y_ik = w * y_ik
 *                 sum_total[k] += w_y_ik             # <<<<<<<<<<<<<<
 *                 sq_sum_total[k] += w_y_ik * y_ik
 * 
 */
      __pyx_t_7 = __pyx_v_k;
      (__pyx_v_sum_total[__pyx_t_7]) = ((__pyx_v_sum_total[__pyx_t_7]) + __pyx_v_w_y_ik);

      /* "sklearn/tree/_tree.pyx":704
 *                 w_y_ik = w * y_ik
 *                 sum_total[k] += w_y_ik
 *                 sq_sum_total[k] += w_y_ik * y_ik             # <<<<<<<<<<<<<<
 * 
 *             weighted_n_node_samples += w
 */
      __pyx_t_7 = __pyx_v_k;
      (__pyx_v_sq_sum_total[__pyx_t_7]) = ((__pyx_v_sq_sum_total[__pyx_t_7]) + (__pyx_v_w_y_ik * __pyx_v_y_ik));
    }

    /* "sklearn/tree/_tree.pyx":706
 *                 sq_sum_total[k] += w_y_ik * y_ik
 * 
 *             weighted_n_node_samples += w             # <<<<<<<<<<<<<<
 * 
 *         self.weighted_n_node_samples = weighted_n_node_samples
 */
    __pyx_v_weighted_n_node_samples = (__pyx_v_weighted_n_node_samples + __pyx_v_w);
  }

  /* "sklearn/tree/_tree.pyx":708
 *             weighted_n_node_samples += w
 * 
 *         self.weighted_n_node_samples = weighted_n_node_samples             # <<<<<<<<<<<<<<
 * 
 *         for k in range(n_outputs):
 */
  __pyx_v_self->__pyx_base.weighted_n_node_samples = __pyx_v_weighted_n_node_samples;

  /* "sklearn/tree/_tree.pyx":710
 *         self.weighted_n_node_samples = weighted_n_node_samples
 * 
 *         for k in range(n_outputs):             # <<<<<<<<<<<<<<
 *             mean_total[k] = sum_total[k] / weighted_n_node_samples
 * 
 */
  __pyx_t_1 = __pyx_v_n_outputs;
  for (__pyx_t_3 = 0; __pyx_t_3 < __pyx_t_1; __pyx_t_3+=1) {
    __pyx_v_k = __pyx_t_3;

    /* "sklearn/tree/_tree.pyx":711
 * 
 *         for k in range(n_outputs):
 *             mean_total[k] = sum_total[k] / weighted_n_node_samples             # <<<<<<<<<<<<<<
 * 
 *         # Reset to pos=start
 */
    (__pyx_v_mean_total[__pyx_v_k]) = ((__pyx_v_sum_total[__pyx_v_k]) / __pyx_v_weighted_n_node_samples);
  }

  /* "sklearn/tree/_tree.pyx":714
 * 
 *         # Reset to pos=start
 *         self.reset()             # <<<<<<<<<<<<<<
 * 
 *     cdef void reset(self) nogil:
 */
  ((struct __pyx_vtabstruct_7sklearn_4tree_5_tree_RegressionCriterion *)__pyx_v_self->__pyx_base.__pyx_vtab)->__pyx_base.reset(((struct __pyx_obj_7sklearn_4tree_5_tree_Criterion *)__pyx_v_self));

  /* "sklearn/tree/_tree.pyx":644
 *         pass
 * 
 *     cdef void init(self, DOUBLE_t* y, SIZE_t y_stride, DOUBLE_t* sample_weight,             # <<<<<<<<<<<<<<
 *                    double weighted_n_samples, SIZE_t* samples, SIZE_t start,
 *                    SIZE_t end) nogil:
 */

  /* function exit code */
}

/* "sklearn/tree/_tree.pyx":716
 *         self.reset()
 * 
 *     cdef void reset(self) nogil:             # <<<<<<<<<<<<<<
 *         """Reset the criterion at pos=start."""
 *         self.pos = self.start
 */

static void __pyx_f_7sklearn_4tree_5_tree_19RegressionCriterion_reset(struct __pyx_obj_7sklearn_4tree_5_tree_RegressionCriterion *__pyx_v_self) {
  __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_n_outputs;
  double *__pyx_v_mean_left;
  double *__pyx_v_mean_right;
  double *__pyx_v_mean_total;
  double *__pyx_v_sq_sum_left;
  double *__pyx_v_sq_sum_right;
  double *__pyx_v_sq_sum_total;
  double *__pyx_v_var_left;
  double *__pyx_v_var_right;
  double __pyx_v_weighted_n_node_samples;
  double *__pyx_v_sum_left;
  double *__pyx_v_sum_right;
  double *__pyx_v_sum_total;
  __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_k;
  __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_t_1;
  double __pyx_t_2;
  double *__pyx_t_3;
  __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_t_4;

  /* "sklearn/tree/_tree.pyx":718
 *     cdef void reset(self) nogil:
 *         """Reset the criterion at pos=start."""
 *         self.pos = self.start             # <<<<<<<<<<<<<<
 * 
 *         self.weighted_n_left = 0.0
 */
  __pyx_t_1 = __pyx_v_self->__pyx_base.start;
  __pyx_v_self->__pyx_base.pos = __pyx_t_1;

  /* "sklearn/tree/_tree.pyx":720
 *         self.pos = self.start
 * 
 *         self.weighted_n_left = 0.0             # <<<<<<<<<<<<<<
 *         self.weighted_n_right = self.weighted_n_node_samples
 * 
 */
  __pyx_v_self->__pyx_base.weighted_n_left = 0.0;

  /* "sklearn/tree/_tree.pyx":721
 * 
 *         self.weighted_n_left = 0.0
 *         self.weighted_n_right = self.weighted_n_node_samples             # <<<<<<<<<<<<<<
 * 
 *         cdef SIZE_t n_outputs = self.n_outputs
 */
  __pyx_t_2 = __pyx_v_self->__pyx_base.weighted_n_node_samples;
  __pyx_v_self->__pyx_base.weighted_n_right = __pyx_t_2;

  /* "sklearn/tree/_tree.pyx":723
 *         self.weighted_n_right = self.weighted_n_node_samples
 * 
 *         cdef SIZE_t n_outputs = self.n_outputs             # <<<<<<<<<<<<<<
 *         cdef double* mean_left = self.mean_left
 *         cdef double* mean_right = self.mean_right
 */
  __pyx_t_1 = __pyx_v_self->__pyx_base.n_outputs;
  __pyx_v_n_outputs = __pyx_t_1;

  /* "sklearn/tree/_tree.pyx":724
 * 
 *         cdef SIZE_t n_outputs = self.n_outputs
 *         cdef double* mean_left = self.mean_left             # <<<<<<<<<<<<<<
 *         cdef double* mean_right = self.mean_right
 *         cdef double* mean_total = self.mean_total
 */
  __pyx_t_3 = __pyx_v_self->mean_left;
  __pyx_v_mean_left = __pyx_t_3;

  /* "sklearn/tree/_tree.pyx":725
 *         cdef SIZE_t n_outputs = self.n_outputs
 *         cdef double* mean_left = self.mean_left
 *         cdef double* mean_right = self.mean_right             # <<<<<<<<<<<<<<
 *         cdef double* mean_total = self.mean_total
 *         cdef double* sq_sum_left = self.sq_sum_left
 */
  __pyx_t_3 = __pyx_v_self->mean_right;
  __pyx_v_mean_right = __pyx_t_3;

  /* "sklearn/tree/_tree.pyx":726
 *         cdef double* mean_left = self.mean_left
 *         cdef double* mean_right = self.mean_right
 *         cdef double* mean_total = self.mean_total             # <<<<<<<<<<<<<<
 *         cdef double* sq_sum_left = self.sq_sum_left
 *         cdef double* sq_sum_right = self.sq_sum_right
 */
  __pyx_t_3 = __pyx_v_self->mean_total;
  __pyx_v_mean_total = __pyx_t_3;

  /* "sklearn/tree/_tree.pyx":727
 *         cdef double* mean_right = self.mean_right
 *         cdef double* mean_total = self.mean_total
 *         cdef double* sq_sum_left = self.sq_sum_left             # <<<<<<<<<<<<<<
 *         cdef double* sq_sum_right = self.sq_sum_right
 *         cdef double* sq_sum_total = self.sq_sum_total
 */
  __pyx_t_3 = __pyx_v_self->sq_sum_left;
  __pyx_v_sq_sum_left = __pyx_t_3;

  /* "sklearn/tree/_tree.pyx":728
 *         cdef double* mean_total = self.mean_total
 *         cdef double* sq_sum_left = self.sq_sum_left
 *         cdef double* sq_sum_right = self.sq_sum_right             # <<<<<<<<<<<<<<
 *         cdef double* sq_sum_total = self.sq_sum_total
 *         cdef double* var_left = self.var_left
 */
  __pyx_t_3 = __pyx_v_self->sq_sum_right;
  __pyx_v_sq_sum_right = __pyx_t_3;

  /* "sklearn/tree/_tree.pyx":729
 *         cdef double* sq_sum_left = self.sq_sum_left
 *         cdef double* sq_sum_right = self.sq_sum_right
 *         cdef double* sq_sum_total = self.sq_sum_total             # <<<<<<<<<<<<<<
 *         cdef double* var_left = self.var_left
 *         cdef double* var_right = self.var_right
 */
  __pyx_t_3 = __pyx_v_self->sq_sum_total;
  __pyx_v_sq_sum_total = __pyx_t_3;

  /* "sklearn/tree/_tree.pyx":730
 *         cdef double* sq_sum_right = self.sq_sum_right
 *         cdef double* sq_sum_total = self.sq_sum_total
 *         cdef double* var_left = self.var_left             # <<<<<<<<<<<<<<
 *         cdef double* var_right = self.var_right
 *         cdef double weighted_n_node_samples = self.weighted_n_node_samples
 */
  __pyx_t_3 = __pyx_v_self->var_left;
  __pyx_v_var_left = __pyx_t_3;

  /* "sklearn/tree/_tree.pyx":731
 *         cdef double* sq_sum_total = self.sq_sum_total
 *         cdef double* var_left = self.var_left
 *         cdef double* var_right = self.var_right             # <<<<<<<<<<<<<<
 *         cdef double weighted_n_node_samples = self.weighted_n_node_samples
 *         cdef double* sum_left = self.sum_left
 */
  __pyx_t_3 = __pyx_v_self->var_right;
  __pyx_v_var_right = __pyx_t_3;

  /* "sklearn/tree/_tree.pyx":732
 *         cdef double* var_left = self.var_left
 *         cdef double* var_right = self.var_right
 *         cdef double weighted_n_node_samples = self.weighted_n_node_samples             # <<<<<<<<<<<<<<
 *         cdef double* sum_left = self.sum_left
 *         cdef double* sum_right = self.sum_right
 */
  __pyx_t_2 = __pyx_v_self->__pyx_base.weighted_n_node_samples;
  __pyx_v_weighted_n_node_samples = __pyx_t_2;

  /* "sklearn/tree/_tree.pyx":733
 *         cdef double* var_right = self.var_right
 *         cdef double weighted_n_node_samples = self.weighted_n_node_samples
 *         cdef double* sum_left = self.sum_left             # <<<<<<<<<<<<<<
 *         cdef double* sum_right = self.sum_right
 *         cdef double* sum_total = self.sum_total
 */
  __pyx_t_3 = __pyx_v_self->sum_left;
  __pyx_v_sum_left = __pyx_t_3;

  /* "sklearn/tree/_tree.pyx":734
 *         cdef double weighted_n_node_samples = self.weighted_n_node_samples
 *         cdef double* sum_left = self.sum_left
 *         cdef double* sum_right = self.sum_right             # <<<<<<<<<<<<<<
 *         cdef double* sum_total = self.sum_total
 * 
 */
  __pyx_t_3 = __pyx_v_self->sum_right;
  __pyx_v_sum_right = __pyx_t_3;

  /* "sklearn/tree/_tree.pyx":735
 *         cdef double* sum_left = self.sum_left
 *         cdef double* sum_right = self.sum_right
 *         cdef double* sum_total = self.sum_total             # <<<<<<<<<<<<<<
 * 
 *         cdef SIZE_t k = 0
 */
  __pyx_t_3 = __pyx_v_self->sum_total;
  __pyx_v_sum_total = __pyx_t_3;

  /* "sklearn/tree/_tree.pyx":737
 *         cdef double* sum_total = self.sum_total
 * 
 *         cdef SIZE_t k = 0             # <<<<<<<<<<<<<<
 * 
 *         for k in range(n_outputs):
 */
  __pyx_v_k = 0;

  /* "sklearn/tree/_tree.pyx":739
 *         cdef SIZE_t k = 0
 * 
 *         for k in range(n_outputs):             # <<<<<<<<<<<<<<
 *             mean_right[k] = mean_total[k]
 *             mean_left[k] = 0.0
 */
  __pyx_t_1 = __pyx_v_n_outputs;
  for (__pyx_t_4 = 0; __pyx_t_4 < __pyx_t_1; __pyx_t_4+=1) {
    __pyx_v_k = __pyx_t_4;

    /* "sklearn/tree/_tree.pyx":740
 * 
 *         for k in range(n_outputs):
 *             mean_right[k] = mean_total[k]             # <<<<<<<<<<<<<<
 *             mean_left[k] = 0.0
 *             sq_sum_right[k] = sq_sum_total[k]
 */
    (__pyx_v_mean_right[__pyx_v_k]) = (__pyx_v_mean_total[__pyx_v_k]);

    /* "sklearn/tree/_tree.pyx":741
 *         for k in range(n_outputs):
 *             mean_right[k] = mean_total[k]
 *             mean_left[k] = 0.0             # <<<<<<<<<<<<<<
 *             sq_sum_right[k] = sq_sum_total[k]
 *             sq_sum_left[k] = 0.0
 */
    (__pyx_v_mean_left[__pyx_v_k]) = 0.0;

    /* "sklearn/tree/_tree.pyx":742
 *             mean_right[k] = mean_total[k]
 *             mean_left[k] = 0.0
 *             sq_sum_right[k] = sq_sum_total[k]             # <<<<<<<<<<<<<<
 *             sq_sum_left[k] = 0.0
 *             var_right[k] = (sq_sum_right[k] / weighted_n_node_samples -
 */
    (__pyx_v_sq_sum_right[__pyx_v_k]) = (__pyx_v_sq_sum_total[__pyx_v_k]);

    /* "sklearn/tree/_tree.pyx":743
 *             mean_left[k] = 0.0
 *             sq_sum_right[k] = sq_sum_total[k]
 *             sq_sum_left[k] = 0.0             # <<<<<<<<<<<<<<
 *             var_right[k] = (sq_sum_right[k] / weighted_n_node_samples -
 *                             mean_right[k] * mean_right[k])
 */
    (__pyx_v_sq_sum_left[__pyx_v_k]) = 0.0;

    /* "sklearn/tree/_tree.pyx":744
 *             sq_sum_right[k] = sq_sum_total[k]
 *             sq_sum_left[k] = 0.0
 *             var_right[k] = (sq_sum_right[k] / weighted_n_node_samples -             # <<<<<<<<<<<<<<
 *                             mean_right[k] * mean_right[k])
 *             var_left[k] = 0.0
 */
    (__pyx_v_var_right[__pyx_v_k]) = (((__pyx_v_sq_sum_right[__pyx_v_k]) / __pyx_v_weighted_n_node_samples) - ((__pyx_v_mean_right[__pyx_v_k]) * (__pyx_v_mean_right[__pyx_v_k])));

    /* "sklearn/tree/_tree.pyx":746
 *             var_right[k] = (sq_sum_right[k] / weighted_n_node_samples -
 *                             mean_right[k] * mean_right[k])
 *             var_left[k] = 0.0             # <<<<<<<<<<<<<<
 *             sum_right[k] = sum_total[k]
 *             sum_left[k] = 0.0
 */
    (__pyx_v_var_left[__pyx_v_k]) = 0.0;

    /* "sklearn/tree/_tree.pyx":747
 *                             mean_right[k] * mean_right[k])
 *             var_left[k] = 0.0
 *             sum_right[k] = sum_total[k]             # <<<<<<<<<<<<<<
 *             sum_left[k] = 0.0
 * 
 */
    (__pyx_v_sum_right[__pyx_v_k]) = (__pyx_v_sum_total[__pyx_v_k]);

    /* "sklearn/tree/_tree.pyx":748
 *             var_left[k] = 0.0
 *             sum_right[k] = sum_total[k]
 *             sum_left[k] = 0.0             # <<<<<<<<<<<<<<
 * 
 *     cdef void update(self, SIZE_t new_pos) nogil:
 */
    (__pyx_v_sum_left[__pyx_v_k]) = 0.0;
  }

  /* "sklearn/tree/_tree.pyx":716
 *         self.reset()
 * 
 *     cdef void reset(self) nogil:             # <<<<<<<<<<<<<<
 *         """Reset the criterion at pos=start."""
 *         self.pos = self.start
 */

  /* function exit code */
}

/* "sklearn/tree/_tree.pyx":750
 *             sum_left[k] = 0.0
 * 
 *     cdef void update(self, SIZE_t new_pos) nogil:             # <<<<<<<<<<<<<<
 *         """Update the collected statistics by moving samples[pos:new_pos] from
 *            the right child to the left child."""
 */

static void __pyx_f_7sklearn_4tree_5_tree_19RegressionCriterion_update(struct __pyx_obj_7sklearn_4tree_5_tree_RegressionCriterion *__pyx_v_self, __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_new_pos) {
  __pyx_t_7sklearn_4tree_5_tree_DOUBLE_t *__pyx_v_y;
  __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_y_stride;
  __pyx_t_7sklearn_4tree_5_tree_DOUBLE_t *__pyx_v_sample_weight;
  __pyx_t_7sklearn_4tree_5_tree_SIZE_t *__pyx_v_samples;
  __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_pos;
  __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_n_outputs;
  double *__pyx_v_mean_left;
  double *__pyx_v_mean_right;
  double *__pyx_v_sq_sum_left;
  double *__pyx_v_sq_sum_right;
  double *__pyx_v_var_left;
  double *__pyx_v_var_right;
  double *__pyx_v_sum_left;
  double *__pyx_v_sum_right;
  double __pyx_v_weighted_n_left;
  double __pyx_v_weighted_n_right;
  __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_i;
  __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_p;
  __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_k;
  __pyx_t_7sklearn_4tree_5_tree_DOUBLE_t __pyx_v_w;
  __pyx_t_7sklearn_4tree_5_tree_DOUBLE_t __pyx_v_diff_w;
  __pyx_t_7sklearn_4tree_5_tree_DOUBLE_t __pyx_v_y_ik;
  __pyx_t_7sklearn_4tree_5_tree_DOUBLE_t __pyx_v_w_y_ik;
  __pyx_t_7sklearn_4tree_5_tree_DOUBLE_t *__pyx_t_1;
  __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_t_2;
  __pyx_t_7sklearn_4tree_5_tree_SIZE_t *__pyx_t_3;
  double *__pyx_t_4;
  double __pyx_t_5;
  __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_t_6;
  int __pyx_t_7;
  __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_t_8;
  __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_t_9;
  __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_t_10;

  /* "sklearn/tree/_tree.pyx":753
 *         """Update the collected statistics by moving samples[pos:new_pos] from
 *            the right child to the left child."""
 *         cdef DOUBLE_t* y = self.y             # <<<<<<<<<<<<<<
 *         cdef SIZE_t y_stride = self.y_stride
 *         cdef DOUBLE_t* sample_weight = self.sample_weight
 */
  __pyx_t_1 = __pyx_v_self->__pyx_base.y;
  __pyx_v_y = __pyx_t_1;

  /* "sklearn/tree/_tree.pyx":754
 *            the right child to the left child."""
 *         cdef DOUBLE_t* y = self.y
 *         cdef SIZE_t y_stride = self.y_stride             # <<<<<<<<<<<<<<
 *         cdef DOUBLE_t* sample_weight = self.sample_weight
 * 
 */
  __pyx_t_2 = __pyx_v_self->__pyx_base.y_stride;
  __pyx_v_y_stride = __pyx_t_2;

  /* "sklearn/tree/_tree.pyx":755
 *         cdef DOUBLE_t* y = self.y
 *         cdef SIZE_t y_stride = self.y_stride
 *         cdef DOUBLE_t* sample_weight = self.sample_weight             # <<<<<<<<<<<<<<
 * 
 *         cdef SIZE_t* samples = self.samples
 */
  __pyx_t_1 = __pyx_v_self->__pyx_base.sample_weight;
  __pyx_v_sample_weight = __pyx_t_1;

  /* "sklearn/tree/_tree.pyx":757
 *         cdef DOUBLE_t* sample_weight = self.sample_weight
 * 
 *         cdef SIZE_t* samples = self.samples             # <<<<<<<<<<<<<<
 *         cdef SIZE_t pos = self.pos
 * 
 */
  __pyx_t_3 = __pyx_v_self->__pyx_base.samples;
  __pyx_v_samples = __pyx_t_3;

  /* "sklearn/tree/_tree.pyx":758
 * 
 *         cdef SIZE_t* samples = self.samples
 *         cdef SIZE_t pos = self.pos             # <<<<<<<<<<<<<<
 * 
 *         cdef SIZE_t n_outputs = self.n_outputs
 */
  __pyx_t_2 = __pyx_v_self->__pyx_base.pos;
  __pyx_v_pos = __pyx_t_2;

  /* "sklearn/tree/_tree.pyx":760
 *         cdef SIZE_t pos = self.pos
 * 
 *         cdef SIZE_t n_outputs = self.n_outputs             # <<<<<<<<<<<<<<
 *         cdef double* mean_left = self.mean_left
 *         cdef double* mean_right = self.mean_right
 */
  __pyx_t_2 = __pyx_v_self->__pyx_base.n_outputs;
  __pyx_v_n_outputs = __pyx_t_2;

  /* "sklearn/tree/_tree.pyx":761
 * 
 *         cdef SIZE_t n_outputs = self.n_outputs
 *         cdef double* mean_left = self.mean_left             # <<<<<<<<<<<<<<
 *         cdef double* mean_right = self.mean_right
 *         cdef double* sq_sum_left = self.sq_sum_left
 */
  __pyx_t_4 = __pyx_v_self->mean_left;
  __pyx_v_mean_left = __pyx_t_4;

  /* "sklearn/tree/_tree.pyx":762
 *         cdef SIZE_t n_outputs = self.n_outputs
 *         cdef double* mean_left = self.mean_left
 *         cdef double* mean_right = self.mean_right             # <<<<<<<<<<<<<<
 *         cdef double* sq_sum_left = self.sq_sum_left
 *         cdef double* sq_sum_right = self.sq_sum_right
 */
  __pyx_t_4 = __pyx_v_self->mean_right;
  __pyx_v_mean_right = __pyx_t_4;

  /* "sklearn/tree/_tree.pyx":763
 *         cdef double* mean_left = self.mean_left
 *         cdef double* mean_right = self.mean_right
 *         cdef double* sq_sum_left = self.sq_sum_left             # <<<<<<<<<<<<<<
 *         cdef double* sq_sum_right = self.sq_sum_right
 *         cdef double* var_left = self.var_left
 */
  __pyx_t_4 = __pyx_v_self->sq_sum_left;
  __pyx_v_sq_sum_left = __pyx_t_4;

  /* "sklearn/tree/_tree.pyx":764
 *         cdef double* mean_right = self.mean_right
 *         cdef double* sq_sum_left = self.sq_sum_left
 *         cdef double* sq_sum_right = self.sq_sum_right             # <<<<<<<<<<<<<<
 *         cdef double* var_left = self.var_left
 *         cdef double* var_right = self.var_right
 */
  __pyx_t_4 = __pyx_v_self->sq_sum_right;
  __pyx_v_sq_sum_right = __pyx_t_4;

  /* "sklearn/tree/_tree.pyx":765
 *         cdef double* sq_sum_left = self.sq_sum_left
 *         cdef double* sq_sum_right = self.sq_sum_right
 *         cdef double* var_left = self.var_left             # <<<<<<<<<<<<<<
 *         cdef double* var_right = self.var_right
 *         cdef double* sum_left = self.sum_left
 */
  __pyx_t_4 = __pyx_v_self->var_left;
  __pyx_v_var_left = __pyx_t_4;

  /* "sklearn/tree/_tree.pyx":766
 *         cdef double* sq_sum_right = self.sq_sum_right
 *         cdef double* var_left = self.var_left
 *         cdef double* var_right = self.var_right             # <<<<<<<<<<<<<<
 *         cdef double* sum_left = self.sum_left
 *         cdef double* sum_right = self.sum_right
 */
  __pyx_t_4 = __pyx_v_self->var_right;
  __pyx_v_var_right = __pyx_t_4;

  /* "sklearn/tree/_tree.pyx":767
 *         cdef double* var_left = self.var_left
 *         cdef double* var_right = self.var_right
 *         cdef double* sum_left = self.sum_left             # <<<<<<<<<<<<<<
 *         cdef double* sum_right = self.sum_right
 * 
 */
  __pyx_t_4 = __pyx_v_self->sum_left;
  __pyx_v_sum_left = __pyx_t_4;

  /* "sklearn/tree/_tree.pyx":768
 *         cdef double* var_right = self.var_right
 *         cdef double* sum_left = self.sum_left
 *         cdef double* sum_right = self.sum_right             # <<<<<<<<<<<<<<
 * 
 *         cdef double weighted_n_left = self.weighted_n_left
 */
  __pyx_t_4 = __pyx_v_self->sum_right;
  __pyx_v_sum_right = __pyx_t_4;

  /* "sklearn/tree/_tree.pyx":770
 *         cdef double* sum_right = self.sum_right
 * 
 *         cdef double weighted_n_left = self.weighted_n_left             # <<<<<<<<<<<<<<
 *         cdef double weighted_n_right = self.weighted_n_right
 * 
 */
  __pyx_t_5 = __pyx_v_self->__pyx_base.weighted_n_left;
  __pyx_v_weighted_n_left = __pyx_t_5;

  /* "sklearn/tree/_tree.pyx":771
 * 
 *         cdef double weighted_n_left = self.weighted_n_left
 *         cdef double weighted_n_right = self.weighted_n_right             # <<<<<<<<<<<<<<
 * 
 *         cdef SIZE_t i
 */
  __pyx_t_5 = __pyx_v_self->__pyx_base.weighted_n_right;
  __pyx_v_weighted_n_right = __pyx_t_5;

  /* "sklearn/tree/_tree.pyx":776
 *         cdef SIZE_t p
 *         cdef SIZE_t k
 *         cdef DOUBLE_t w = 1.0             # <<<<<<<<<<<<<<
 *         cdef DOUBLE_t diff_w = 0.0
 *         cdef DOUBLE_t y_ik, w_y_ik
 */
  __pyx_v_w = 1.0;

  /* "sklearn/tree/_tree.pyx":777
 *         cdef SIZE_t k
 *         cdef DOUBLE_t w = 1.0
 *         cdef DOUBLE_t diff_w = 0.0             # <<<<<<<<<<<<<<
 *         cdef DOUBLE_t y_ik, w_y_ik
 * 
 */
  __pyx_v_diff_w = 0.0;

  /* "sklearn/tree/_tree.pyx":781
 * 
 *         # Note: We assume start <= pos < new_pos <= end
 *         for p in range(pos, new_pos):             # <<<<<<<<<<<<<<
 *             i = samples[p]
 * 
 */
  __pyx_t_2 = __pyx_v_new_pos;
  for (__pyx_t_6 = __pyx_v_pos; __pyx_t_6 < __pyx_t_2; __pyx_t_6+=1) {
    __pyx_v_p = __pyx_t_6;

    /* "sklearn/tree/_tree.pyx":782
 *         # Note: We assume start <= pos < new_pos <= end
 *         for p in range(pos, new_pos):
 *             i = samples[p]             # <<<<<<<<<<<<<<
 * 
 *             if sample_weight != NULL:
 */
    __pyx_v_i = (__pyx_v_samples[__pyx_v_p]);

    /* "sklearn/tree/_tree.pyx":784
 *             i = samples[p]
 * 
 *             if sample_weight != NULL:             # <<<<<<<<<<<<<<
 *                 w = sample_weight[i]
 * 
 */
    __pyx_t_7 = ((__pyx_v_sample_weight != NULL) != 0);
    if (__pyx_t_7) {

      /* "sklearn/tree/_tree.pyx":785
 * 
 *             if sample_weight != NULL:
 *                 w = sample_weight[i]             # <<<<<<<<<<<<<<
 * 
 *             for k in range(n_outputs):
 */
      __pyx_v_w = (__pyx_v_sample_weight[__pyx_v_i]);
      goto __pyx_L5;
    }
    __pyx_L5:;

    /* "sklearn/tree/_tree.pyx":787
 *                 w = sample_weight[i]
 * 
 *             for k in range(n_outputs):             # <<<<<<<<<<<<<<
 *                 y_ik = y[i * y_stride + k]
 *                 w_y_ik = w * y_ik
 */
    __pyx_t_8 = __pyx_v_n_outputs;
    for (__pyx_t_9 = 0; __pyx_t_9 < __pyx_t_8; __pyx_t_9+=1) {
      __pyx_v_k = __pyx_t_9;

      /* "sklearn/tree/_tree.pyx":788
 * 
 *             for k in range(n_outputs):
 *                 y_ik = y[i * y_stride + k]             # <<<<<<<<<<<<<<
 *                 w_y_ik = w * y_ik
 * 
 */
      __pyx_v_y_ik = (__pyx_v_y[((__pyx_v_i * __pyx_v_y_stride) + __pyx_v_k)]);

      /* "sklearn/tree/_tree.pyx":789
 *             for k in range(n_outputs):
 *                 y_ik = y[i * y_stride + k]
 *                 w_y_ik = w * y_ik             # <<<<<<<<<<<<<<
 * 
 *                 sum_left[k] += w_y_ik
 */
      __pyx_v_w_y_ik = (__pyx_v_w * __pyx_v_y_ik);

      /* "sklearn/tree/_tree.pyx":791
 *                 w_y_ik = w * y_ik
 * 
 *                 sum_left[k] += w_y_ik             # <<<<<<<<<<<<<<
 *                 sum_right[k] -= w_y_ik
 * 
 */
      __pyx_t_10 = __pyx_v_k;
      (__pyx_v_sum_left[__pyx_t_10]) = ((__pyx_v_sum_left[__pyx_t_10]) + __pyx_v_w_y_ik);

      /* "sklearn/tree/_tree.pyx":792
 * 
 *                 sum_left[k] += w_y_ik
 *                 sum_right[k] -= w_y_ik             # <<<<<<<<<<<<<<
 * 
 *                 sq_sum_left[k] += w_y_ik * y_ik
 */
      __pyx_t_10 = __pyx_v_k;
      (__pyx_v_sum_right[__pyx_t_10]) = ((__pyx_v_sum_right[__pyx_t_10]) - __pyx_v_w_y_ik);

      /* "sklearn/tree/_tree.pyx":794
 *                 sum_right[k] -= w_y_ik
 * 
 *                 sq_sum_left[k] += w_y_ik * y_ik             # <<<<<<<<<<<<<<
 *                 sq_sum_right[k] -= w_y_ik * y_ik
 * 
 */
      __pyx_t_10 = __pyx_v_k;
      (__pyx_v_sq_sum_left[__pyx_t_10]) = ((__pyx_v_sq_sum_left[__pyx_t_10]) + (__pyx_v_w_y_ik * __pyx_v_y_ik));

      /* "sklearn/tree/_tree.pyx":795
 * 
 *                 sq_sum_left[k] += w_y_ik * y_ik
 *                 sq_sum_right[k] -= w_y_ik * y_ik             # <<<<<<<<<<<<<<
 * 
 *             diff_w += w
 */
      __pyx_t_10 = __pyx_v_k;
      (__pyx_v_sq_sum_right[__pyx_t_10]) = ((__pyx_v_sq_sum_right[__pyx_t_10]) - (__pyx_v_w_y_ik * __pyx_v_y_ik));
    }

    /* "sklearn/tree/_tree.pyx":797
 *                 sq_sum_right[k] -= w_y_ik * y_ik
 * 
 *             diff_w += w             # <<<<<<<<<<<<<<
 * 
 *         weighted_n_left += diff_w
 */
    __pyx_v_diff_w = (__pyx_v_diff_w + __pyx_v_w);
  }

  /* "sklearn/tree/_tree.pyx":799
 *             diff_w += w
 * 
 *         weighted_n_left += diff_w             # <<<<<<<<<<<<<<
 *         weighted_n_right -= diff_w
 * 
 */
  __pyx_v_weighted_n_left = (__pyx_v_weighted_n_left + __pyx_v_diff_w);

  /* "sklearn/tree/_tree.pyx":800
 * 
 *         weighted_n_left += diff_w
 *         weighted_n_right -= diff_w             # <<<<<<<<<<<<<<
 * 
 *         for k in range(n_outputs):
 */
  __pyx_v_weighted_n_right = (__pyx_v_weighted_n_right - __pyx_v_diff_w);

  /* "sklearn/tree/_tree.pyx":802
 *         weighted_n_right -= diff_w
 * 
 *         for k in range(n_outputs):             # <<<<<<<<<<<<<<
 *             mean_left[k] = sum_left[k] / weighted_n_left
 *             mean_right[k] = sum_right[k] / weighted_n_right
 */
  __pyx_t_2 = __pyx_v_n_outputs;
  for (__pyx_t_6 = 0; __pyx_t_6 < __pyx_t_2; __pyx_t_6+=1) {
    __pyx_v_k = __pyx_t_6;

    /* "sklearn/tree/_tree.pyx":803
 * 
 *         for k in range(n_outputs):
 *             mean_left[k] = sum_left[k] / weighted_n_left             # <<<<<<<<<<<<<<
 *             mean_right[k] = sum_right[k] / weighted_n_right
 *             var_left[k] = (sq_sum_left[k] / weighted_n_left -
 */
    (__pyx_v_mean_left[__pyx_v_k]) = ((__pyx_v_sum_left[__pyx_v_k]) / __pyx_v_weighted_n_left);

    /* "sklearn/tree/_tree.pyx":804
 *         for k in range(n_outputs):
 *             mean_left[k] = sum_left[k] / weighted_n_left
 *             mean_right[k] = sum_right[k] / weighted_n_right             # <<<<<<<<<<<<<<
 *             var_left[k] = (sq_sum_left[k] / weighted_n_left -
 *                            mean_left[k] * mean_left[k])
 */
    (__pyx_v_mean_right[__pyx_v_k]) = ((__pyx_v_sum_right[__pyx_v_k]) / __pyx_v_weighted_n_right);

    /* "sklearn/tree/_tree.pyx":805
 *             mean_left[k] = sum_left[k] / weighted_n_left
 *             mean_right[k] = sum_right[k] / weighted_n_right
 *             var_left[k] = (sq_sum_left[k] / weighted_n_left -             # <<<<<<<<<<<<<<
 *                            mean_left[k] * mean_left[k])
 *             var_right[k] = (sq_sum_right[k] / weighted_n_right -
 */
    (__pyx_v_var_left[__pyx_v_k]) = (((__pyx_v_sq_sum_left[__pyx_v_k]) / __pyx_v_weighted_n_left) - ((__pyx_v_mean_left[__pyx_v_k]) * (__pyx_v_mean_left[__pyx_v_k])));

    /* "sklearn/tree/_tree.pyx":807
 *             var_left[k] = (sq_sum_left[k] / weighted_n_left -
 *                            mean_left[k] * mean_left[k])
 *             var_right[k] = (sq_sum_right[k] / weighted_n_right -             # <<<<<<<<<<<<<<
 *                             mean_right[k] * mean_right[k])
 * 
 */
    (__pyx_v_var_right[__pyx_v_k]) = (((__pyx_v_sq_sum_right[__pyx_v_k]) / __pyx_v_weighted_n_right) - ((__pyx_v_mean_right[__pyx_v_k]) * (__pyx_v_mean_right[__pyx_v_k])));
  }

  /* "sklearn/tree/_tree.pyx":810
 *                             mean_right[k] * mean_right[k])
 * 
 *         self.weighted_n_left = weighted_n_left             # <<<<<<<<<<<<<<
 *         self.weighted_n_right = weighted_n_right
 * 
 */
  __pyx_v_self->__pyx_base.weighted_n_left = __pyx_v_weighted_n_left;

  /* "sklearn/tree/_tree.pyx":811
 * 
 *         self.weighted_n_left = weighted_n_left
 *         self.weighted_n_right = weighted_n_right             # <<<<<<<<<<<<<<
 * 
 *         self.pos = new_pos
 */
  __pyx_v_self->__pyx_base.weighted_n_right = __pyx_v_weighted_n_right;

  /* "sklearn/tree/_tree.pyx":813
 *         self.weighted_n_right = weighted_n_right
 * 
 *         self.pos = new_pos             # <<<<<<<<<<<<<<
 * 
 *     cdef double node_impurity(self) nogil:
 */
  __pyx_v_self->__pyx_base.pos = __pyx_v_new_pos;

  /* "sklearn/tree/_tree.pyx":750
 *             sum_left[k] = 0.0
 * 
 *     cdef void update(self, SIZE_t new_pos) nogil:             # <<<<<<<<<<<<<<
 *         """Update the collected statistics by moving samples[pos:new_pos] from
 *            the right child to the left child."""
 */

  /* function exit code */
}

/* "sklearn/tree/_tree.pyx":815
 *         self.pos = new_pos
 * 
 *     cdef double node_impurity(self) nogil:             # <<<<<<<<<<<<<<
 *         pass
 * 
 */

static double __pyx_f_7sklearn_4tree_5_tree_19RegressionCriterion_node_impurity(CYTHON_UNUSED struct __pyx_obj_7sklearn_4tree_5_tree_RegressionCriterion *__pyx_v_self) {
  double __pyx_r;

  /* function exit code */
  __pyx_r = 0;
  return __pyx_r;
}

/* "sklearn/tree/_tree.pyx":818
 *         pass
 * 
 *     cdef void children_impurity(self, double* impurity_left,             # <<<<<<<<<<<<<<
 *                                 double* impurity_right) nogil:
 *         pass
 */

static void __pyx_f_7sklearn_4tree_5_tree_19RegressionCriterion_children_impurity(CYTHON_UNUSED struct __pyx_obj_7sklearn_4tree_5_tree_RegressionCriterion *__pyx_v_self, CYTHON_UNUSED double *__pyx_v_impurity_left, CYTHON_UNUSED double *__pyx_v_impurity_right) {

  /* function exit code */
}

/* "sklearn/tree/_tree.pyx":822
 *         pass
 * 
 *     cdef void node_value(self, double* dest) nogil:             # <<<<<<<<<<<<<<
 *         """Compute the node value of samples[start:end] into dest."""
 *         memcpy(dest, self.mean_total, self.n_outputs * sizeof(double))
 */

static void __pyx_f_7sklearn_4tree_5_tree_19RegressionCriterion_node_value(struct __pyx_obj_7sklearn_4tree_5_tree_RegressionCriterion *__pyx_v_self, double *__pyx_v_dest) {

  /* "sklearn/tree/_tree.pyx":824
 *     cdef void node_value(self, double* dest) nogil:
 *         """Compute the node value of samples[start:end] into dest."""
 *         memcpy(dest, self.mean_total, self.n_outputs * sizeof(double))             # <<<<<<<<<<<<<<
 * 
 * 
 */
  memcpy(__pyx_v_dest, __pyx_v_self->mean_total, (__pyx_v_self->__pyx_base.n_outputs * (sizeof(double))));

  /* "sklearn/tree/_tree.pyx":822
 *         pass
 * 
 *     cdef void node_value(self, double* dest) nogil:             # <<<<<<<<<<<<<<
 *         """Compute the node value of samples[start:end] into dest."""
 *         memcpy(dest, self.mean_total, self.n_outputs * sizeof(double))
 */

  /* function exit code */
}

/* "sklearn/tree/_tree.pyx":832
 *         MSE = var_left + var_right
 *     """
 *     cdef double node_impurity(self) nogil:             # <<<<<<<<<<<<<<
 *         """Evaluate the impurity of the current node, i.e. the impurity of
 *            samples[start:end]."""
 */

static double __pyx_f_7sklearn_4tree_5_tree_3MSE_node_impurity(struct __pyx_obj_7sklearn_4tree_5_tree_MSE *__pyx_v_self) {
  __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_n_outputs;
  double *__pyx_v_sq_sum_total;
  double *__pyx_v_mean_total;
  double __pyx_v_weighted_n_node_samples;
  double __pyx_v_total;
  __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_k;
  double __pyx_r;
  __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_t_1;
  double *__pyx_t_2;
  double __pyx_t_3;
  __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_t_4;

  /* "sklearn/tree/_tree.pyx":835
 *         """Evaluate the impurity of the current node, i.e. the impurity of
 *            samples[start:end]."""
 *         cdef SIZE_t n_outputs = self.n_outputs             # <<<<<<<<<<<<<<
 *         cdef double* sq_sum_total = self.sq_sum_total
 *         cdef double* mean_total = self.mean_total
 */
  __pyx_t_1 = __pyx_v_self->__pyx_base.__pyx_base.n_outputs;
  __pyx_v_n_outputs = __pyx_t_1;

  /* "sklearn/tree/_tree.pyx":836
 *            samples[start:end]."""
 *         cdef SIZE_t n_outputs = self.n_outputs
 *         cdef double* sq_sum_total = self.sq_sum_total             # <<<<<<<<<<<<<<
 *         cdef double* mean_total = self.mean_total
 *         cdef double weighted_n_node_samples = self.weighted_n_node_samples
 */
  __pyx_t_2 = __pyx_v_self->__pyx_base.sq_sum_total;
  __pyx_v_sq_sum_total = __pyx_t_2;

  /* "sklearn/tree/_tree.pyx":837
 *         cdef SIZE_t n_outputs = self.n_outputs
 *         cdef double* sq_sum_total = self.sq_sum_total
 *         cdef double* mean_total = self.mean_total             # <<<<<<<<<<<<<<
 *         cdef double weighted_n_node_samples = self.weighted_n_node_samples
 *         cdef double total = 0.0
 */
  __pyx_t_2 = __pyx_v_self->__pyx_base.mean_total;
  __pyx_v_mean_total = __pyx_t_2;

  /* "sklearn/tree/_tree.pyx":838
 *         cdef double* sq_sum_total = self.sq_sum_total
 *         cdef double* mean_total = self.mean_total
 *         cdef double weighted_n_node_samples = self.weighted_n_node_samples             # <<<<<<<<<<<<<<
 *         cdef double total = 0.0
 *         cdef SIZE_t k
 */
  __pyx_t_3 = __pyx_v_self->__pyx_base.__pyx_base.weighted_n_node_samples;
  __pyx_v_weighted_n_node_samples = __pyx_t_3;

  /* "sklearn/tree/_tree.pyx":839
 *         cdef double* mean_total = self.mean_total
 *         cdef double weighted_n_node_samples = self.weighted_n_node_samples
 *         cdef double total = 0.0             # <<<<<<<<<<<<<<
 *         cdef SIZE_t k
 * 
 */
  __pyx_v_total = 0.0;

  /* "sklearn/tree/_tree.pyx":842
 *         cdef SIZE_t k
 * 
 *         for k in range(n_outputs):             # <<<<<<<<<<<<<<
 *             total += (sq_sum_total[k] / weighted_n_node_samples -
 *                       mean_total[k] * mean_total[k])
 */
  __pyx_t_1 = __pyx_v_n_outputs;
  for (__pyx_t_4 = 0; __pyx_t_4 < __pyx_t_1; __pyx_t_4+=1) {
    __pyx_v_k = __pyx_t_4;

    /* "sklearn/tree/_tree.pyx":843
 * 
 *         for k in range(n_outputs):
 *             total += (sq_sum_total[k] / weighted_n_node_samples -             # <<<<<<<<<<<<<<
 *                       mean_total[k] * mean_total[k])
 * 
 */
    __pyx_v_total = (__pyx_v_total + (((__pyx_v_sq_sum_total[__pyx_v_k]) / __pyx_v_weighted_n_node_samples) - ((__pyx_v_mean_total[__pyx_v_k]) * (__pyx_v_mean_total[__pyx_v_k]))));
  }

  /* "sklearn/tree/_tree.pyx":846
 *                       mean_total[k] * mean_total[k])
 * 
 *         return total / n_outputs             # <<<<<<<<<<<<<<
 * 
 *     cdef void children_impurity(self, double* impurity_left,
 */
  __pyx_r = (__pyx_v_total / __pyx_v_n_outputs);
  goto __pyx_L0;

  /* "sklearn/tree/_tree.pyx":832
 *         MSE = var_left + var_right
 *     """
 *     cdef double node_impurity(self) nogil:             # <<<<<<<<<<<<<<
 *         """Evaluate the impurity of the current node, i.e. the impurity of
 *            samples[start:end]."""
 */

  /* function exit code */
  __pyx_L0:;
  return __pyx_r;
}

/* "sklearn/tree/_tree.pyx":848
 *         return total / n_outputs
 * 
 *     cdef void children_impurity(self, double* impurity_left,             # <<<<<<<<<<<<<<
 *                                 double* impurity_right) nogil:
 *         """Evaluate the impurity in children nodes, i.e. the impurity of the
 */

static void __pyx_f_7sklearn_4tree_5_tree_3MSE_children_impurity(struct __pyx_obj_7sklearn_4tree_5_tree_MSE *__pyx_v_self, double *__pyx_v_impurity_left, double *__pyx_v_impurity_right) {
  __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_n_outputs;
  double *__pyx_v_var_left;
  double *__pyx_v_var_right;
  double __pyx_v_total_left;
  double __pyx_v_total_right;
  __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_k;
  __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_t_1;
  double *__pyx_t_2;
  __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_t_3;

  /* "sklearn/tree/_tree.pyx":853
 *            left child (samples[start:pos]) and the impurity the right child
 *            (samples[pos:end])."""
 *         cdef SIZE_t n_outputs = self.n_outputs             # <<<<<<<<<<<<<<
 *         cdef double* var_left = self.var_left
 *         cdef double* var_right = self.var_right
 */
  __pyx_t_1 = __pyx_v_self->__pyx_base.__pyx_base.n_outputs;
  __pyx_v_n_outputs = __pyx_t_1;

  /* "sklearn/tree/_tree.pyx":854
 *            (samples[pos:end])."""
 *         cdef SIZE_t n_outputs = self.n_outputs
 *         cdef double* var_left = self.var_left             # <<<<<<<<<<<<<<
 *         cdef double* var_right = self.var_right
 *         cdef double total_left = 0.0
 */
  __pyx_t_2 = __pyx_v_self->__pyx_base.var_left;
  __pyx_v_var_left = __pyx_t_2;

  /* "sklearn/tree/_tree.pyx":855
 *         cdef SIZE_t n_outputs = self.n_outputs
 *         cdef double* var_left = self.var_left
 *         cdef double* var_right = self.var_right             # <<<<<<<<<<<<<<
 *         cdef double total_left = 0.0
 *         cdef double total_right = 0.0
 */
  __pyx_t_2 = __pyx_v_self->__pyx_base.var_right;
  __pyx_v_var_right = __pyx_t_2;

  /* "sklearn/tree/_tree.pyx":856
 *         cdef double* var_left = self.var_left
 *         cdef double* var_right = self.var_right
 *         cdef double total_left = 0.0             # <<<<<<<<<<<<<<
 *         cdef double total_right = 0.0
 *         cdef SIZE_t k
 */
  __pyx_v_total_left = 0.0;

  /* "sklearn/tree/_tree.pyx":857
 *         cdef double* var_right = self.var_right
 *         cdef double total_left = 0.0
 *         cdef double total_right = 0.0             # <<<<<<<<<<<<<<
 *         cdef SIZE_t k
 * 
 */
  __pyx_v_total_right = 0.0;

  /* "sklearn/tree/_tree.pyx":860
 *         cdef SIZE_t k
 * 
 *         for k in range(n_outputs):             # <<<<<<<<<<<<<<
 *             total_left += var_left[k]
 *             total_right += var_right[k]
 */
  __pyx_t_1 = __pyx_v_n_outputs;
  for (__pyx_t_3 = 0; __pyx_t_3 < __pyx_t_1; __pyx_t_3+=1) {
    __pyx_v_k = __pyx_t_3;

    /* "sklearn/tree/_tree.pyx":861
 * 
 *         for k in range(n_outputs):
 *             total_left += var_left[k]             # <<<<<<<<<<<<<<
 *             total_right += var_right[k]
 * 
 */
    __pyx_v_total_left = (__pyx_v_total_left + (__pyx_v_var_left[__pyx_v_k]));

    /* "sklearn/tree/_tree.pyx":862
 *         for k in range(n_outputs):
 *             total_left += var_left[k]
 *             total_right += var_right[k]             # <<<<<<<<<<<<<<
 * 
 *         impurity_left[0] = total_left / n_outputs
 */
    __pyx_v_total_right = (__pyx_v_total_right + (__pyx_v_var_right[__pyx_v_k]));
  }

  /* "sklearn/tree/_tree.pyx":864
 *             total_right += var_right[k]
 * 
 *         impurity_left[0] = total_left / n_outputs             # <<<<<<<<<<<<<<
 *         impurity_right[0] = total_right / n_outputs
 * 
 */
  (__pyx_v_impurity_left[0]) = (__pyx_v_total_left / __pyx_v_n_outputs);

  /* "sklearn/tree/_tree.pyx":865
 * 
 *         impurity_left[0] = total_left / n_outputs
 *         impurity_right[0] = total_right / n_outputs             # <<<<<<<<<<<<<<
 * 
 * 
 */
  (__pyx_v_impurity_right[0]) = (__pyx_v_total_right / __pyx_v_n_outputs);

  /* "sklearn/tree/_tree.pyx":848
 *         return total / n_outputs
 * 
 *     cdef void children_impurity(self, double* impurity_left,             # <<<<<<<<<<<<<<
 *                                 double* impurity_right) nogil:
 *         """Evaluate the impurity in children nodes, i.e. the impurity of the
 */

  /* function exit code */
}

/* "sklearn/tree/_tree.pyx":877
 *     """
 * 
 *     cdef double impurity_improvement(self, double impurity) nogil:             # <<<<<<<<<<<<<<
 *         cdef SIZE_t n_outputs = self.n_outputs
 *         cdef SIZE_t k
 */

static double __pyx_f_7sklearn_4tree_5_tree_11FriedmanMSE_impurity_improvement(struct __pyx_obj_7sklearn_4tree_5_tree_FriedmanMSE *__pyx_v_self, CYTHON_UNUSED double __pyx_v_impurity) {
  __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_n_outputs;
  __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_k;
  double *__pyx_v_sum_left;
  double *__pyx_v_sum_right;
  double __pyx_v_total_sum_left;
  double __pyx_v_total_sum_right;
  double __pyx_v_weighted_n_left;
  double __pyx_v_weighted_n_right;
  double __pyx_v_diff;
  double __pyx_r;
  __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_t_1;
  double *__pyx_t_2;
  double __pyx_t_3;

  /* "sklearn/tree/_tree.pyx":878
 * 
 *     cdef double impurity_improvement(self, double impurity) nogil:
 *         cdef SIZE_t n_outputs = self.n_outputs             # <<<<<<<<<<<<<<
 *         cdef SIZE_t k
 *         cdef double* sum_left = self.sum_left
 */
  __pyx_t_1 = __pyx_v_self->__pyx_base.__pyx_base.__pyx_base.n_outputs;
  __pyx_v_n_outputs = __pyx_t_1;

  /* "sklearn/tree/_tree.pyx":880
 *         cdef SIZE_t n_outputs = self.n_outputs
 *         cdef SIZE_t k
 *         cdef double* sum_left = self.sum_left             # <<<<<<<<<<<<<<
 *         cdef double* sum_right = self.sum_right
 *         cdef double total_sum_left = 0.0
 */
  __pyx_t_2 = __pyx_v_self->__pyx_base.__pyx_base.sum_left;
  __pyx_v_sum_left = __pyx_t_2;

  /* "sklearn/tree/_tree.pyx":881
 *         cdef SIZE_t k
 *         cdef double* sum_left = self.sum_left
 *         cdef double* sum_right = self.sum_right             # <<<<<<<<<<<<<<
 *         cdef double total_sum_left = 0.0
 *         cdef double total_sum_right = 0.0
 */
  __pyx_t_2 = __pyx_v_self->__pyx_base.__pyx_base.sum_right;
  __pyx_v_sum_right = __pyx_t_2;

  /* "sklearn/tree/_tree.pyx":882
 *         cdef double* sum_left = self.sum_left
 *         cdef double* sum_right = self.sum_right
 *         cdef double total_sum_left = 0.0             # <<<<<<<<<<<<<<
 *         cdef double total_sum_right = 0.0
 *         cdef double weighted_n_left = self.weighted_n_left
 */
  __pyx_v_total_sum_left = 0.0;

  /* "sklearn/tree/_tree.pyx":883
 *         cdef double* sum_right = self.sum_right
 *         cdef double total_sum_left = 0.0
 *         cdef double total_sum_right = 0.0             # <<<<<<<<<<<<<<
 *         cdef double weighted_n_left = self.weighted_n_left
 *         cdef double weighted_n_right = self.weighted_n_right
 */
  __pyx_v_total_sum_right = 0.0;

  /* "sklearn/tree/_tree.pyx":884
 *         cdef double total_sum_left = 0.0
 *         cdef double total_sum_right = 0.0
 *         cdef double weighted_n_left = self.weighted_n_left             # <<<<<<<<<<<<<<
 *         cdef double weighted_n_right = self.weighted_n_right
 *         cdef double diff = 0.0
 */
  __pyx_t_3 = __pyx_v_self->__pyx_base.__pyx_base.__pyx_base.weighted_n_left;
  __pyx_v_weighted_n_left = __pyx_t_3;

  /* "sklearn/tree/_tree.pyx":885
 *         cdef double total_sum_right = 0.0
 *         cdef double weighted_n_left = self.weighted_n_left
 *         cdef double weighted_n_right = self.weighted_n_right             # <<<<<<<<<<<<<<
 *         cdef double diff = 0.0
 * 
 */
  __pyx_t_3 = __pyx_v_self->__pyx_base.__pyx_base.__pyx_base.weighted_n_right;
  __pyx_v_weighted_n_right = __pyx_t_3;

  /* "sklearn/tree/_tree.pyx":886
 *         cdef double weighted_n_left = self.weighted_n_left
 *         cdef double weighted_n_right = self.weighted_n_right
 *         cdef double diff = 0.0             # <<<<<<<<<<<<<<
 * 
 *         for k from 0 <= k < n_outputs:
 */
  __pyx_v_diff = 0.0;

  /* "sklearn/tree/_tree.pyx":888
 *         cdef double diff = 0.0
 * 
 *         for k from 0 <= k < n_outputs:             # <<<<<<<<<<<<<<
 *             total_sum_left += sum_left[k]
 *             total_sum_right += sum_right[k]
 */
  __pyx_t_1 = __pyx_v_n_outputs;
  for (__pyx_v_k = 0; __pyx_v_k < __pyx_t_1; __pyx_v_k++) {

    /* "sklearn/tree/_tree.pyx":889
 * 
 *         for k from 0 <= k < n_outputs:
 *             total_sum_left += sum_left[k]             # <<<<<<<<<<<<<<
 *             total_sum_right += sum_right[k]
 * 
 */
    __pyx_v_total_sum_left = (__pyx_v_total_sum_left + (__pyx_v_sum_left[__pyx_v_k]));

    /* "sklearn/tree/_tree.pyx":890
 *         for k from 0 <= k < n_outputs:
 *             total_sum_left += sum_left[k]
 *             total_sum_right += sum_right[k]             # <<<<<<<<<<<<<<
 * 
 *         total_sum_left = total_sum_left / n_outputs
 */
    __pyx_v_total_sum_right = (__pyx_v_total_sum_right + (__pyx_v_sum_right[__pyx_v_k]));
  }

  /* "sklearn/tree/_tree.pyx":892
 *             total_sum_right += sum_right[k]
 * 
 *         total_sum_left = total_sum_left / n_outputs             # <<<<<<<<<<<<<<
 *         total_sum_right = total_sum_right / n_outputs
 *         diff = ((total_sum_left / weighted_n_left) -
 */
  __pyx_v_total_sum_left = (__pyx_v_total_sum_left / __pyx_v_n_outputs);

  /* "sklearn/tree/_tree.pyx":893
 * 
 *         total_sum_left = total_sum_left / n_outputs
 *         total_sum_right = total_sum_right / n_outputs             # <<<<<<<<<<<<<<
 *         diff = ((total_sum_left / weighted_n_left) -
 *                 (total_sum_right / weighted_n_right))
 */
  __pyx_v_total_sum_right = (__pyx_v_total_sum_right / __pyx_v_n_outputs);

  /* "sklearn/tree/_tree.pyx":894
 *         total_sum_left = total_sum_left / n_outputs
 *         total_sum_right = total_sum_right / n_outputs
 *         diff = ((total_sum_left / weighted_n_left) -             # <<<<<<<<<<<<<<
 *                 (total_sum_right / weighted_n_right))
 * 
 */
  __pyx_v_diff = ((__pyx_v_total_sum_left / __pyx_v_weighted_n_left) - (__pyx_v_total_sum_right / __pyx_v_weighted_n_right));

  /* "sklearn/tree/_tree.pyx":897
 *                 (total_sum_right / weighted_n_right))
 * 
 *         return (weighted_n_left * weighted_n_right * diff * diff /             # <<<<<<<<<<<<<<
 *                 (weighted_n_left + weighted_n_right))
 * 
 */
  __pyx_r = ((((__pyx_v_weighted_n_left * __pyx_v_weighted_n_right) * __pyx_v_diff) * __pyx_v_diff) / (__pyx_v_weighted_n_left + __pyx_v_weighted_n_right));
  goto __pyx_L0;

  /* "sklearn/tree/_tree.pyx":877
 *     """
 * 
 *     cdef double impurity_improvement(self, double impurity) nogil:             # <<<<<<<<<<<<<<
 *         cdef SIZE_t n_outputs = self.n_outputs
 *         cdef SIZE_t k
 */

  /* function exit code */
  __pyx_L0:;
  return __pyx_r;
}

/* "sklearn/tree/_tree.pyx":905
 * # =============================================================================
 * 
 * cdef inline void _init_split(SplitRecord* self, SIZE_t start_pos) nogil:             # <<<<<<<<<<<<<<
 *     self.impurity_left = INFINITY
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  /* "sklearn/tree/_tree.pyx":1031
 *     """Splitter for finding the best split."""
 *     def __reduce__(self):
 *         return (BestSplitter, (self.criterion,             # <<<<<<<<<<<<<<
 *                                self.max_features,
 *                                self.min_samples_leaf,
 */
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  /* "sklearn/tree/_tree.pyx":1030
 * cdef class BestSplitter(Splitter):
 *     """Splitter for finding the best split."""
 *     def __reduce__(self):             # <<<<<<<<<<<<<<
 *         return (BestSplitter, (self.criterion,
 *                                self.max_features,
 */

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/* "sklearn/tree/_tree.pyx":1036
 *                                self.random_state), self.__getstate__())
 * 
 *     cdef void node_split(self, double impurity, SplitRecord* split,             # <<<<<<<<<<<<<<
 *                          SIZE_t* n_constant_features) nogil:
 *         """Find the best split on node samples[start:end]."""
 */

static void __pyx_f_7sklearn_4tree_5_tree_12BestSplitter_node_split(struct __pyx_obj_7sklearn_4tree_5_tree_BestSplitter *__pyx_v_self, double __pyx_v_impurity, struct __pyx_t_7sklearn_4tree_5_tree_SplitRecord *__pyx_v_split, __pyx_t_7sklearn_4tree_5_tree_SIZE_t *__pyx_v_n_constant_features) {
  __pyx_t_7sklearn_4tree_5_tree_SIZE_t *__pyx_v_samples;
  __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_start;
  __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_end;
  __pyx_t_7sklearn_4tree_5_tree_SIZE_t *__pyx_v_features;
  __pyx_t_7sklearn_4tree_5_tree_SIZE_t *__pyx_v_constant_features;
  __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_n_features;
  __pyx_t_7sklearn_4tree_5_tree_DTYPE_t *__pyx_v_X;
  __pyx_t_7sklearn_4tree_5_tree_DTYPE_t *__pyx_v_Xf;
  __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_X_sample_stride;
  __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_X_fx_stride;
  __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_max_features;
  __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_min_samples_leaf;
  __pyx_t_7sklearn_4tree_5_tree_UINT32_t *__pyx_v_random_state;
  struct __pyx_t_7sklearn_4tree_5_tree_SplitRecord __pyx_v_best;
  struct __pyx_t_7sklearn_4tree_5_tree_SplitRecord __pyx_v_current;
  __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_f_i;
  __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_f_j;
  __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_p;
  __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_tmp;
  __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_n_visited_features;
  __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_n_found_constants;
  __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_n_drawn_constants;
  __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_n_known_constants;
  __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_n_total_constants;
  __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_partition_end;
  __pyx_t_7sklearn_4tree_5_tree_SIZE_t *__pyx_t_1;
  __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_t_2;
  __pyx_t_7sklearn_4tree_5_tree_DTYPE_t *__pyx_t_3;
  int __pyx_t_4;
  int __pyx_t_5;
  int __pyx_t_6;
  int __pyx_t_7;
  __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_t_8;

  /* "sklearn/tree/_tree.pyx":1040
 *         """Find the best split on node samples[start:end]."""
 *         # Find the best split
 *         cdef SIZE_t* samples = self.samples             # <<<<<<<<<<<<<<
 *         cdef SIZE_t start = self.start
 *         cdef SIZE_t end = self.end
 */
  __pyx_t_1 = __pyx_v_self->__pyx_base.samples;
  __pyx_v_samples = __pyx_t_1;

  /* "sklearn/tree/_tree.pyx":1041
 *         # Find the best split
 *         cdef SIZE_t* samples = self.samples
 *         cdef SIZE_t start = self.start             # <<<<<<<<<<<<<<
 *         cdef SIZE_t end = self.end
 * 
 */
  __pyx_t_2 = __pyx_v_self->__pyx_base.start;
  __pyx_v_start = __pyx_t_2;

  /* "sklearn/tree/_tree.pyx":1042
 *         cdef SIZE_t* samples = self.samples
 *         cdef SIZE_t start = self.start
 *         cdef SIZE_t end = self.end             # <<<<<<<<<<<<<<
 * 
 *         cdef SIZE_t* features = self.features
 */
  __pyx_t_2 = __pyx_v_self->__pyx_base.end;
  __pyx_v_end = __pyx_t_2;

  /* "sklearn/tree/_tree.pyx":1044
 *         cdef SIZE_t end = self.end
 * 
 *         cdef SIZE_t* features = self.features             # <<<<<<<<<<<<<<
 *         cdef SIZE_t* constant_features = self.constant_features
 *         cdef SIZE_t n_features = self.n_features
 */
  __pyx_t_1 = __pyx_v_self->__pyx_base.features;
  __pyx_v_features = __pyx_t_1;

  /* "sklearn/tree/_tree.pyx":1045
 * 
 *         cdef SIZE_t* features = self.features
 *         cdef SIZE_t* constant_features = self.constant_features             # <<<<<<<<<<<<<<
 *         cdef SIZE_t n_features = self.n_features
 * 
 */
  __pyx_t_1 = __pyx_v_self->__pyx_base.constant_features;
  __pyx_v_constant_features = __pyx_t_1;

  /* "sklearn/tree/_tree.pyx":1046
 *         cdef SIZE_t* features = self.features
 *         cdef SIZE_t* constant_features = self.constant_features
 *         cdef SIZE_t n_features = self.n_features             # <<<<<<<<<<<<<<
 * 
 *         cdef DTYPE_t* X = self.X
 */
  __pyx_t_2 = __pyx_v_self->__pyx_base.n_features;
  __pyx_v_n_features = __pyx_t_2;

  /* "sklearn/tree/_tree.pyx":1048
 *         cdef SIZE_t n_features = self.n_features
 * 
 *         cdef DTYPE_t* X = self.X             # <<<<<<<<<<<<<<
 *         cdef DTYPE_t* Xf = self.feature_values
 *         cdef SIZE_t X_sample_stride = self.X_sample_stride
 */
  __pyx_t_3 = __pyx_v_self->__pyx_base.X;
  __pyx_v_X = __pyx_t_3;

  /* "sklearn/tree/_tree.pyx":1049
 * 
 *         cdef DTYPE_t* X = self.X
 *         cdef DTYPE_t* Xf = self.feature_values             # <<<<<<<<<<<<<<
 *         cdef SIZE_t X_sample_stride = self.X_sample_stride
 *         cdef SIZE_t X_fx_stride = self.X_fx_stride
 */
  __pyx_t_3 = __pyx_v_self->__pyx_base.feature_values;
  __pyx_v_Xf = __pyx_t_3;

  /* "sklearn/tree/_tree.pyx":1050
 *         cdef DTYPE_t* X = self.X
 *         cdef DTYPE_t* Xf = self.feature_values
 *         cdef SIZE_t X_sample_stride = self.X_sample_stride             # <<<<<<<<<<<<<<
 *         cdef SIZE_t X_fx_stride = self.X_fx_stride
 *         cdef SIZE_t max_features = self.max_features
 */
  __pyx_t_2 = __pyx_v_self->__pyx_base.X_sample_stride;
  __pyx_v_X_sample_stride = __pyx_t_2;

  /* "sklearn/tree/_tree.pyx":1051
 *         cdef DTYPE_t* Xf = self.feature_values
 *         cdef SIZE_t X_sample_stride = self.X_sample_stride
 *         cdef SIZE_t X_fx_stride = self.X_fx_stride             # <<<<<<<<<<<<<<
 *         cdef SIZE_t max_features = self.max_features
 *         cdef SIZE_t min_samples_leaf = self.min_samples_leaf
 */
  __pyx_t_2 = __pyx_v_self->__pyx_base.X_fx_stride;
  __pyx_v_X_fx_stride = __pyx_t_2;

  /* "sklearn/tree/_tree.pyx":1052
 *         cdef SIZE_t X_sample_stride = self.X_sample_stride
 *         cdef SIZE_t X_fx_stride = self.X_fx_stride
 *         cdef SIZE_t max_features = self.max_features             # <<<<<<<<<<<<<<
 *         cdef SIZE_t min_samples_leaf = self.min_samples_leaf
 *         cdef UINT32_t* random_state = &self.rand_r_state
 */
  __pyx_t_2 = __pyx_v_self->__pyx_base.max_features;
  __pyx_v_max_features = __pyx_t_2;

  /* "sklearn/tree/_tree.pyx":1053
 *         cdef SIZE_t X_fx_stride = self.X_fx_stride
 *         cdef SIZE_t max_features = self.max_features
 *         cdef SIZE_t min_samples_leaf = self.min_samples_leaf             # <<<<<<<<<<<<<<
 *         cdef UINT32_t* random_state = &self.rand_r_state
 * 
 */
  __pyx_t_2 = __pyx_v_self->__pyx_base.min_samples_leaf;
  __pyx_v_min_samples_leaf = __pyx_t_2;

  /* "sklearn/tree/_tree.pyx":1054
 *         cdef SIZE_t max_features = self.max_features
 *         cdef SIZE_t min_samples_leaf = self.min_samples_leaf
 *         cdef UINT32_t* random_state = &self.rand_r_state             # <<<<<<<<<<<<<<
 * 
 *         cdef SplitRecord best, current
 */
  __pyx_v_random_state = (&__pyx_v_self->__pyx_base.rand_r_state);

  /* "sklearn/tree/_tree.pyx":1058
 *         cdef SplitRecord best, current
 * 
 *         cdef SIZE_t f_i = n_features             # <<<<<<<<<<<<<<
 *         cdef SIZE_t f_j, p, tmp
 *         cdef SIZE_t n_visited_features = 0
 */
  __pyx_v_f_i = __pyx_v_n_features;

  /* "sklearn/tree/_tree.pyx":1060
 *         cdef SIZE_t f_i = n_features
 *         cdef SIZE_t f_j, p, tmp
 *         cdef SIZE_t n_visited_features = 0             # <<<<<<<<<<<<<<
 *         # Number of features discovered to be constant during the split search
 *         cdef SIZE_t n_found_constants = 0
 */
  __pyx_v_n_visited_features = 0;

  /* "sklearn/tree/_tree.pyx":1062
 *         cdef SIZE_t n_visited_features = 0
 *         # Number of features discovered to be constant during the split search
 *         cdef SIZE_t n_found_constants = 0             # <<<<<<<<<<<<<<
 *         # Number of features known to be constant and drawn without replacement
 *         cdef SIZE_t n_drawn_constants = 0
 */
  __pyx_v_n_found_constants = 0;

  /* "sklearn/tree/_tree.pyx":1064
 *         cdef SIZE_t n_found_constants = 0
 *         # Number of features known to be constant and drawn without replacement
 *         cdef SIZE_t n_drawn_constants = 0             # <<<<<<<<<<<<<<
 *         cdef SIZE_t n_known_constants = n_constant_features[0]
 *         # n_total_constants = n_known_constants + n_found_constants
 */
  __pyx_v_n_drawn_constants = 0;

  /* "sklearn/tree/_tree.pyx":1065
 *         # Number of features known to be constant and drawn without replacement
 *         cdef SIZE_t n_drawn_constants = 0
 *         cdef SIZE_t n_known_constants = n_constant_features[0]             # <<<<<<<<<<<<<<
 *         # n_total_constants = n_known_constants + n_found_constants
 *         cdef SIZE_t n_total_constants = n_known_constants
 */
  __pyx_v_n_known_constants = (__pyx_v_n_constant_features[0]);

  /* "sklearn/tree/_tree.pyx":1067
 *         cdef SIZE_t n_known_constants = n_constant_features[0]
 *         # n_total_constants = n_known_constants + n_found_constants
 *         cdef SIZE_t n_total_constants = n_known_constants             # <<<<<<<<<<<<<<
 *         cdef DTYPE_t current_feature_value
 *         cdef SIZE_t partition_end
 */
  __pyx_v_n_total_constants = __pyx_v_n_known_constants;

  /* "sklearn/tree/_tree.pyx":1071
 *         cdef SIZE_t partition_end
 * 
 *         _init_split(&best, end)             # <<<<<<<<<<<<<<
 * 
 *         # Sample up to max_features without replacement using a
 */
  __pyx_f_7sklearn_4tree_5_tree__init_split((&__pyx_v_best), __pyx_v_end);

  /* "sklearn/tree/_tree.pyx":1082
 *         # newly discovered constant features to spare computation on descendant
 *         # nodes.
 *         while (f_i > n_total_constants and  # Stop early if remaining features             # <<<<<<<<<<<<<<
 *                                             # are constant
 *                 (n_visited_features < max_features or
 */
  while (1) {
    __pyx_t_4 = ((__pyx_v_f_i > __pyx_v_n_total_constants) != 0);
    if (__pyx_t_4) {

      /* "sklearn/tree/_tree.pyx":1084
 *         while (f_i > n_total_constants and  # Stop early if remaining features
 *                                             # are constant
 *                 (n_visited_features < max_features or             # <<<<<<<<<<<<<<
 *                  # At least one drawn features must be non constant
 *                  n_visited_features <= n_found_constants + n_drawn_constants)):
 */
      __pyx_t_5 = ((__pyx_v_n_visited_features < __pyx_v_max_features) != 0);
      if (!__pyx_t_5) {

        /* "sklearn/tree/_tree.pyx":1086
 *                 (n_visited_features < max_features or
 *                  # At least one drawn features must be non constant
 *                  n_visited_features <= n_found_constants + n_drawn_constants)):             # <<<<<<<<<<<<<<
 * 
 *             n_visited_features += 1
 */
        __pyx_t_6 = ((__pyx_v_n_visited_features <= (__pyx_v_n_found_constants + __pyx_v_n_drawn_constants)) != 0);
        __pyx_t_7 = __pyx_t_6;
      } else {
        __pyx_t_7 = __pyx_t_5;
      }
      __pyx_t_5 = __pyx_t_7;
    } else {
      __pyx_t_5 = __pyx_t_4;
    }
    if (!__pyx_t_5) break;

    /* "sklearn/tree/_tree.pyx":1088
 *                  n_visited_features <= n_found_constants + n_drawn_constants)):
 * 
 *             n_visited_features += 1             # <<<<<<<<<<<<<<
 * 
 *             # Loop invariant: elements of features in
 */
    __pyx_v_n_visited_features = (__pyx_v_n_visited_features + 1);

    /* "sklearn/tree/_tree.pyx":1103
 *             # Draw a feature at random
 *             f_j = rand_int(f_i - n_drawn_constants - n_found_constants,
 *                            random_state) + n_drawn_constants             # <<<<<<<<<<<<<<
 * 
 *             if f_j < n_known_constants:
 */
    __pyx_v_f_j = (__pyx_f_7sklearn_4tree_5_tree_rand_int(((__pyx_v_f_i - __pyx_v_n_drawn_constants) - __pyx_v_n_found_constants), __pyx_v_random_state) + __pyx_v_n_drawn_constants);

    /* "sklearn/tree/_tree.pyx":1105
 *                            random_state) + n_drawn_constants
 * 
 *             if f_j < n_known_constants:             # <<<<<<<<<<<<<<
 *                 # f_j in the interval [n_drawn_constants, n_known_constants[
 *                 tmp = features[f_j]
 */
    __pyx_t_5 = ((__pyx_v_f_j < __pyx_v_n_known_constants) != 0);
    if (__pyx_t_5) {

      /* "sklearn/tree/_tree.pyx":1107
 *             if f_j < n_known_constants:
 *                 # f_j in the interval [n_drawn_constants, n_known_constants[
 *                 tmp = features[f_j]             # <<<<<<<<<<<<<<
 *                 features[f_j] = features[n_drawn_constants]
 *                 features[n_drawn_constants] = tmp
 */
      __pyx_v_tmp = (__pyx_v_features[__pyx_v_f_j]);

      /* "sklearn/tree/_tree.pyx":1108
 *                 # f_j in the interval [n_drawn_constants, n_known_constants[
 *                 tmp = features[f_j]
 *                 features[f_j] = features[n_drawn_constants]             # <<<<<<<<<<<<<<
 *                 features[n_drawn_constants] = tmp
 * 
 */
      (__pyx_v_features[__pyx_v_f_j]) = (__pyx_v_features[__pyx_v_n_drawn_constants]);

      /* "sklearn/tree/_tree.pyx":1109
 *                 tmp = features[f_j]
 *                 features[f_j] = features[n_drawn_constants]
 *                 features[n_drawn_constants] = tmp             # <<<<<<<<<<<<<<
 * 
 *                 n_drawn_constants += 1
 */
      (__pyx_v_features[__pyx_v_n_drawn_constants]) = __pyx_v_tmp;

      /* "sklearn/tree/_tree.pyx":1111
 *                 features[n_drawn_constants] = tmp
 * 
 *                 n_drawn_constants += 1             # <<<<<<<<<<<<<<
 * 
 *             else:
 */
      __pyx_v_n_drawn_constants = (__pyx_v_n_drawn_constants + 1);
      goto __pyx_L5;
    }
    /*else*/ {

      /* "sklearn/tree/_tree.pyx":1115
 *             else:
 *                 # f_j in the interval [n_known_constants, f_i - n_found_constants[
 *                 f_j += n_found_constants             # <<<<<<<<<<<<<<
 *                 # f_j in the interval [n_total_constants, f_i[
 * 
 */
      __pyx_v_f_j = (__pyx_v_f_j + __pyx_v_n_found_constants);

      /* "sklearn/tree/_tree.pyx":1118
 *                 # f_j in the interval [n_total_constants, f_i[
 * 
 *                 current.feature = features[f_j]             # <<<<<<<<<<<<<<
 * 
 *                 # Sort samples along that feature; first copy the feature
 */
      __pyx_v_current.feature = (__pyx_v_features[__pyx_v_f_j]);

      /* "sklearn/tree/_tree.pyx":1124
 *                 # Xf[i] == X[samples[i], j], so the sort uses the cache more
 *                 # effectively.
 *                 for p in range(start, end):             # <<<<<<<<<<<<<<
 *                     Xf[p] = X[X_sample_stride * samples[p] +
 *                               X_fx_stride * current.feature]
 */
      __pyx_t_2 = __pyx_v_end;
      for (__pyx_t_8 = __pyx_v_start; __pyx_t_8 < __pyx_t_2; __pyx_t_8+=1) {
        __pyx_v_p = __pyx_t_8;

        /* "sklearn/tree/_tree.pyx":1125
 *                 # effectively.
 *                 for p in range(start, end):
 *                     Xf[p] = X[X_sample_stride * samples[p] +             # <<<<<<<<<<<<<<
 *                               X_fx_stride * current.feature]
 * 
 */
        (__pyx_v_Xf[__pyx_v_p]) = (__pyx_v_X[((__pyx_v_X_sample_stride * (__pyx_v_samples[__pyx_v_p])) + (__pyx_v_X_fx_stride * __pyx_v_current.feature))]);
      }

      /* "sklearn/tree/_tree.pyx":1128
 *                               X_fx_stride * current.feature]
 * 
 *                 sort(Xf + start, samples + start, end - start)             # <<<<<<<<<<<<<<
 * 
 *                 if Xf[end - 1] <= Xf[start] + FEATURE_THRESHOLD:
 */
      __pyx_f_7sklearn_4tree_5_tree_sort((__pyx_v_Xf + __pyx_v_start), (__pyx_v_samples + __pyx_v_start), (__pyx_v_end - __pyx_v_start));

      /* "sklearn/tree/_tree.pyx":1130
 *                 sort(Xf + start, samples + start, end - start)
 * 
 *                 if Xf[end - 1] <= Xf[start] + FEATURE_THRESHOLD:             # <<<<<<<<<<<<<<
 *                     features[f_j] = features[n_total_constants]
 *                     features[n_total_constants] = current.feature
 */
      __pyx_t_5 = (((__pyx_v_Xf[(__pyx_v_end - 1)]) <= ((__pyx_v_Xf[__pyx_v_start]) + __pyx_v_7sklearn_4tree_5_tree_FEATURE_THRESHOLD)) != 0);
      if (__pyx_t_5) {

        /* "sklearn/tree/_tree.pyx":1131
 * 
 *                 if Xf[end - 1] <= Xf[start] + FEATURE_THRESHOLD:
 *                     features[f_j] = features[n_total_constants]             # <<<<<<<<<<<<<<
 *                     features[n_total_constants] = current.feature
 * 
 */
        (__pyx_v_features[__pyx_v_f_j]) = (__pyx_v_features[__pyx_v_n_total_constants]);

        /* "sklearn/tree/_tree.pyx":1132
 *                 if Xf[end - 1] <= Xf[start] + FEATURE_THRESHOLD:
 *                     features[f_j] = features[n_total_constants]
 *                     features[n_total_constants] = current.feature             # <<<<<<<<<<<<<<
 * 
 *                     n_found_constants += 1
 */
        __pyx_t_2 = __pyx_v_current.feature;
        (__pyx_v_features[__pyx_v_n_total_constants]) = __pyx_t_2;

        /* "sklearn/tree/_tree.pyx":1134
 *                     features[n_total_constants] = current.feature
 * 
 *                     n_found_constants += 1             # <<<<<<<<<<<<<<
 *                     n_total_constants += 1
 * 
 */
        __pyx_v_n_found_constants = (__pyx_v_n_found_constants + 1);

        /* "sklearn/tree/_tree.pyx":1135
 * 
 *                     n_found_constants += 1
 *                     n_total_constants += 1             # <<<<<<<<<<<<<<
 * 
 *                 else:
 */
        __pyx_v_n_total_constants = (__pyx_v_n_total_constants + 1);
        goto __pyx_L8;
      }
      /*else*/ {

        /* "sklearn/tree/_tree.pyx":1138
 * 
 *                 else:
 *                     f_i -= 1             # <<<<<<<<<<<<<<
 *                     features[f_i], features[f_j] = features[f_j], features[f_i]
 * 
 */
        __pyx_v_f_i = (__pyx_v_f_i - 1);

        /* "sklearn/tree/_tree.pyx":1139
 *                 else:
 *                     f_i -= 1
 *                     features[f_i], features[f_j] = features[f_j], features[f_i]             # <<<<<<<<<<<<<<
 * 
 *                     # Evaluate all splits
 */
        __pyx_t_2 = (__pyx_v_features[__pyx_v_f_j]);
        __pyx_t_8 = (__pyx_v_features[__pyx_v_f_i]);
        (__pyx_v_features[__pyx_v_f_i]) = __pyx_t_2;
        (__pyx_v_features[__pyx_v_f_j]) = __pyx_t_8;

        /* "sklearn/tree/_tree.pyx":1142
 * 
 *                     # Evaluate all splits
 *                     self.criterion.reset()             # <<<<<<<<<<<<<<
 *                     p = start
 * 
 */
        ((struct __pyx_vtabstruct_7sklearn_4tree_5_tree_Criterion *)__pyx_v_self->__pyx_base.criterion->__pyx_vtab)->reset(__pyx_v_self->__pyx_base.criterion);

        /* "sklearn/tree/_tree.pyx":1143
 *                     # Evaluate all splits
 *                     self.criterion.reset()
 *                     p = start             # <<<<<<<<<<<<<<
 * 
 *                     while p < end:
 */
        __pyx_v_p = __pyx_v_start;

        /* "sklearn/tree/_tree.pyx":1145
 *                     p = start
 * 
 *                     while p < end:             # <<<<<<<<<<<<<<
 *                         while (p + 1 < end and
 *                                Xf[p + 1] <= Xf[p] + FEATURE_THRESHOLD):
 */
        while (1) {
          __pyx_t_5 = ((__pyx_v_p < __pyx_v_end) != 0);
          if (!__pyx_t_5) break;

          /* "sklearn/tree/_tree.pyx":1146
 * 
 *                     while p < end:
 *                         while (p + 1 < end and             # <<<<<<<<<<<<<<
 *                                Xf[p + 1] <= Xf[p] + FEATURE_THRESHOLD):
 *                             p += 1
 */
          while (1) {
            __pyx_t_5 = (((__pyx_v_p + 1) < __pyx_v_end) != 0);
            if (__pyx_t_5) {

              /* "sklearn/tree/_tree.pyx":1147
 *                     while p < end:
 *                         while (p + 1 < end and
 *                                Xf[p + 1] <= Xf[p] + FEATURE_THRESHOLD):             # <<<<<<<<<<<<<<
 *                             p += 1
 * 
 */
              __pyx_t_4 = (((__pyx_v_Xf[(__pyx_v_p + 1)]) <= ((__pyx_v_Xf[__pyx_v_p]) + __pyx_v_7sklearn_4tree_5_tree_FEATURE_THRESHOLD)) != 0);
              __pyx_t_7 = __pyx_t_4;
            } else {
              __pyx_t_7 = __pyx_t_5;
            }
            if (!__pyx_t_7) break;

            /* "sklearn/tree/_tree.pyx":1148
 *                         while (p + 1 < end and
 *                                Xf[p + 1] <= Xf[p] + FEATURE_THRESHOLD):
 *                             p += 1             # <<<<<<<<<<<<<<
 * 
 *                         # (p + 1 >= end) or (X[samples[p + 1], current.feature] >
 */
            __pyx_v_p = (__pyx_v_p + 1);
          }

          /* "sklearn/tree/_tree.pyx":1152
 *                         # (p + 1 >= end) or (X[samples[p + 1], current.feature] >
 *                         #                    X[samples[p], current.feature])
 *                         p += 1             # <<<<<<<<<<<<<<
 *                         # (p >= end) or (X[samples[p], current.feature] >
 *                         #                X[samples[p - 1], current.feature])
 */
          __pyx_v_p = (__pyx_v_p + 1);

          /* "sklearn/tree/_tree.pyx":1156
 *                         #                X[samples[p - 1], current.feature])
 * 
 *                         if p < end:             # <<<<<<<<<<<<<<
 *                             current.pos = p
 * 
 */
          __pyx_t_7 = ((__pyx_v_p < __pyx_v_end) != 0);
          if (__pyx_t_7) {

            /* "sklearn/tree/_tree.pyx":1157
 * 
 *                         if p < end:
 *                             current.pos = p             # <<<<<<<<<<<<<<
 * 
 *                             # Reject if min_samples_leaf is not guaranteed
 */
            __pyx_v_current.pos = __pyx_v_p;

            /* "sklearn/tree/_tree.pyx":1160
 * 
 *                             # Reject if min_samples_leaf is not guaranteed
 *                             if (((current.pos - start) < min_samples_leaf) or             # <<<<<<<<<<<<<<
 *                                     ((end - current.pos) < min_samples_leaf)):
 *                                 continue
 */
            __pyx_t_7 = (((__pyx_v_current.pos - __pyx_v_start) < __pyx_v_min_samples_leaf) != 0);
            if (!__pyx_t_7) {

              /* "sklearn/tree/_tree.pyx":1161
 *                             # Reject if min_samples_leaf is not guaranteed
 *                             if (((current.pos - start) < min_samples_leaf) or
 *                                     ((end - current.pos) < min_samples_leaf)):             # <<<<<<<<<<<<<<
 *                                 continue
 * 
 */
              __pyx_t_5 = (((__pyx_v_end - __pyx_v_current.pos) < __pyx_v_min_samples_leaf) != 0);
              __pyx_t_4 = __pyx_t_5;
            } else {
              __pyx_t_4 = __pyx_t_7;
            }
            if (__pyx_t_4) {

              /* "sklearn/tree/_tree.pyx":1162
 *                             if (((current.pos - start) < min_samples_leaf) or
 *                                     ((end - current.pos) < min_samples_leaf)):
 *                                 continue             # <<<<<<<<<<<<<<
 * 
 *                             self.criterion.update(current.pos)
 */
              goto __pyx_L9_continue;
            }

            /* "sklearn/tree/_tree.pyx":1164
 *                                 continue
 * 
 *                             self.criterion.update(current.pos)             # <<<<<<<<<<<<<<
 *                             current.improvement = self.criterion.impurity_improvement(impurity)
 * 
 */
            ((struct __pyx_vtabstruct_7sklearn_4tree_5_tree_Criterion *)__pyx_v_self->__pyx_base.criterion->__pyx_vtab)->update(__pyx_v_self->__pyx_base.criterion, __pyx_v_current.pos);

            /* "sklearn/tree/_tree.pyx":1165
 * 
 *                             self.criterion.update(current.pos)
 *                             current.improvement = self.criterion.impurity_improvement(impurity)             # <<<<<<<<<<<<<<
 * 
 *                             if current.improvement > best.improvement:
 */
            __pyx_v_current.improvement = ((struct __pyx_vtabstruct_7sklearn_4tree_5_tree_Criterion *)__pyx_v_self->__pyx_base.criterion->__pyx_vtab)->impurity_improvement(__pyx_v_self->__pyx_base.criterion, __pyx_v_impurity);

            /* "sklearn/tree/_tree.pyx":1167
 *                             current.improvement = self.criterion.impurity_improvement(impurity)
 * 
 *                             if current.improvement > best.improvement:             # <<<<<<<<<<<<<<
 *                                 self.criterion.children_impurity(&current.impurity_left,
 *                                                                  &current.impurity_right)
 */
            __pyx_t_4 = ((__pyx_v_current.improvement > __pyx_v_best.improvement) != 0);
            if (__pyx_t_4) {

              /* "sklearn/tree/_tree.pyx":1168
 * 
 *                             if current.improvement > best.improvement:
 *                                 self.criterion.children_impurity(&current.impurity_left,             # <<<<<<<<<<<<<<
 *                                                                  &current.impurity_right)
 *                                 current.threshold = (Xf[p - 1] + Xf[p]) / 2.0
 */
              ((struct __pyx_vtabstruct_7sklearn_4tree_5_tree_Criterion *)__pyx_v_self->__pyx_base.criterion->__pyx_vtab)->children_impurity(__pyx_v_self->__pyx_base.criterion, (&__pyx_v_current.impurity_left), (&__pyx_v_current.impurity_right));

              /* "sklearn/tree/_tree.pyx":1170
 *                                 self.criterion.children_impurity(&current.impurity_left,
 *                                                                  &current.impurity_right)
 *                                 current.threshold = (Xf[p - 1] + Xf[p]) / 2.0             # <<<<<<<<<<<<<<
 * 
 *                                 if current.threshold == Xf[p]:
 */
              __pyx_v_current.threshold = (((__pyx_v_Xf[(__pyx_v_p - 1)]) + (__pyx_v_Xf[__pyx_v_p])) / 2.0);

              /* "sklearn/tree/_tree.pyx":1172
 *                                 current.threshold = (Xf[p - 1] + Xf[p]) / 2.0
 * 
 *                                 if current.threshold == Xf[p]:             # <<<<<<<<<<<<<<
 *                                     current.threshold = Xf[p - 1]
 * 
 */
              __pyx_t_4 = ((__pyx_v_current.threshold == (__pyx_v_Xf[__pyx_v_p])) != 0);
              if (__pyx_t_4) {

                /* "sklearn/tree/_tree.pyx":1173
 * 
 *                                 if current.threshold == Xf[p]:
 *                                     current.threshold = Xf[p - 1]             # <<<<<<<<<<<<<<
 * 
 *                                 best = current  # copy
 */
                __pyx_v_current.threshold = (__pyx_v_Xf[(__pyx_v_p - 1)]);
                goto __pyx_L16;
              }
              __pyx_L16:;

              /* "sklearn/tree/_tree.pyx":1175
 *                                     current.threshold = Xf[p - 1]
 * 
 *                                 best = current  # copy             # <<<<<<<<<<<<<<
 * 
 *         # Reorganize into samples[start:best.pos] + samples[best.pos:end]
 */
              __pyx_v_best = __pyx_v_current;
              goto __pyx_L15;
            }
            __pyx_L15:;
            goto __pyx_L13;
          }
          __pyx_L13:;
          __pyx_L9_continue:;
        }
      }
      __pyx_L8:;
    }
    __pyx_L5:;
  }

  /* "sklearn/tree/_tree.pyx":1178
 * 
 *         # Reorganize into samples[start:best.pos] + samples[best.pos:end]
 *         if best.pos < end:             # <<<<<<<<<<<<<<
 *             partition_end = end
 *             p = start
 */
  __pyx_t_4 = ((__pyx_v_best.pos < __pyx_v_end) != 0);
  if (__pyx_t_4) {

    /* "sklearn/tree/_tree.pyx":1179
 *         # Reorganize into samples[start:best.pos] + samples[best.pos:end]
 *         if best.pos < end:
 *             partition_end = end             # <<<<<<<<<<<<<<
 *             p = start
 * 
 */
    __pyx_v_partition_end = __pyx_v_end;

    /* "sklearn/tree/_tree.pyx":1180
 *         if best.pos < end:
 *             partition_end = end
 *             p = start             # <<<<<<<<<<<<<<
 * 
 *             while p < partition_end:
 */
    __pyx_v_p = __pyx_v_start;

    /* "sklearn/tree/_tree.pyx":1182
 *             p = start
 * 
 *             while p < partition_end:             # <<<<<<<<<<<<<<
 *                 if X[X_sample_stride * samples[p] +
 *                      X_fx_stride * best.feature] <= best.threshold:
 */
    while (1) {
      __pyx_t_4 = ((__pyx_v_p < __pyx_v_partition_end) != 0);
      if (!__pyx_t_4) break;

      /* "sklearn/tree/_tree.pyx":1184
 *             while p < partition_end:
 *                 if X[X_sample_stride * samples[p] +
 *                      X_fx_stride * best.feature] <= best.threshold:             # <<<<<<<<<<<<<<
 *                     p += 1
 * 
 */
      __pyx_t_4 = (((__pyx_v_X[((__pyx_v_X_sample_stride * (__pyx_v_samples[__pyx_v_p])) + (__pyx_v_X_fx_stride * __pyx_v_best.feature))]) <= __pyx_v_best.threshold) != 0);
      if (__pyx_t_4) {

        /* "sklearn/tree/_tree.pyx":1185
 *                 if X[X_sample_stride * samples[p] +
 *                      X_fx_stride * best.feature] <= best.threshold:
 *                     p += 1             # <<<<<<<<<<<<<<
 * 
 *                 else:
 */
        __pyx_v_p = (__pyx_v_p + 1);
        goto __pyx_L20;
      }
      /*else*/ {

        /* "sklearn/tree/_tree.pyx":1188
 * 
 *                 else:
 *                     partition_end -= 1             # <<<<<<<<<<<<<<
 * 
 *                     tmp = samples[partition_end]
 */
        __pyx_v_partition_end = (__pyx_v_partition_end - 1);

        /* "sklearn/tree/_tree.pyx":1190
 *                     partition_end -= 1
 * 
 *                     tmp = samples[partition_end]             # <<<<<<<<<<<<<<
 *                     samples[partition_end] = samples[p]
 *                     samples[p] = tmp
 */
        __pyx_v_tmp = (__pyx_v_samples[__pyx_v_partition_end]);

        /* "sklearn/tree/_tree.pyx":1191
 * 
 *                     tmp = samples[partition_end]
 *                     samples[partition_end] = samples[p]             # <<<<<<<<<<<<<<
 *                     samples[p] = tmp
 * 
 */
        (__pyx_v_samples[__pyx_v_partition_end]) = (__pyx_v_samples[__pyx_v_p]);

        /* "sklearn/tree/_tree.pyx":1192
 *                     tmp = samples[partition_end]
 *                     samples[partition_end] = samples[p]
 *                     samples[p] = tmp             # <<<<<<<<<<<<<<
 * 
 *         # Respect invariant for constant features: the original order of
 */
        (__pyx_v_samples[__pyx_v_p]) = __pyx_v_tmp;
      }
      __pyx_L20:;
    }
    goto __pyx_L17;
  }
  __pyx_L17:;

  /* "sklearn/tree/_tree.pyx":1197
 *         # element in features[:n_known_constants] must be preserved for sibling
 *         # and child nodes
 *         memcpy(features, constant_features, sizeof(SIZE_t) * n_known_constants)             # <<<<<<<<<<<<<<
 * 
 *         # Copy newly found constant features
 */
  memcpy(__pyx_v_features, __pyx_v_constant_features, ((sizeof(__pyx_t_7sklearn_4tree_5_tree_SIZE_t)) * __pyx_v_n_known_constants));

  /* "sklearn/tree/_tree.pyx":1200
 * 
 *         # Copy newly found constant features
 *         memcpy(constant_features + n_known_constants,             # <<<<<<<<<<<<<<
 *                features + n_known_constants,
 *                sizeof(SIZE_t) * n_found_constants)
 */
  memcpy((__pyx_v_constant_features + __pyx_v_n_known_constants), (__pyx_v_features + __pyx_v_n_known_constants), ((sizeof(__pyx_t_7sklearn_4tree_5_tree_SIZE_t)) * __pyx_v_n_found_constants));

  /* "sklearn/tree/_tree.pyx":1205
 * 
 *         # Return values
 *         split[0] = best             # <<<<<<<<<<<<<<
 *         n_constant_features[0] = n_total_constants
 * 
 */
  (__pyx_v_split[0]) = __pyx_v_best;

  /* "sklearn/tree/_tree.pyx":1206
 *         # Return values
 *         split[0] = best
 *         n_constant_features[0] = n_total_constants             # <<<<<<<<<<<<<<
 * 
 * 
 */
  (__pyx_v_n_constant_features[0]) = __pyx_v_n_total_constants;

  /* "sklearn/tree/_tree.pyx":1036
 *                                self.random_state), self.__getstate__())
 * 
 *     cdef void node_split(self, double impurity, SplitRecord* split,             # <<<<<<<<<<<<<<
 *                          SIZE_t* n_constant_features) nogil:
 *         """Find the best split on node samples[start:end]."""
 */

  /* function exit code */
}

/* "sklearn/tree/_tree.pyx":1211
 * # Sort n-element arrays pointed to by Xf and samples, simultaneously,
 * # by the values in Xf. Algorithm: Introsort (Musser, SP&E, 1997).
 * cdef inline void sort(DTYPE_t* Xf, SIZE_t* samples, SIZE_t n) nogil:             # <<<<<<<<<<<<<<
 *     cdef int maxd = 2 * <int>log(n)
 *     introsort(Xf, samples, n, maxd)
 */

static CYTHON_INLINE void __pyx_f_7sklearn_4tree_5_tree_sort(__pyx_t_7sklearn_4tree_5_tree_DTYPE_t *__pyx_v_Xf, __pyx_t_7sklearn_4tree_5_tree_SIZE_t *__pyx_v_samples, __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_n) {
  int __pyx_v_maxd;

  /* "sklearn/tree/_tree.pyx":1212
 * # by the values in Xf. Algorithm: Introsort (Musser, SP&E, 1997).
 * cdef inline void sort(DTYPE_t* Xf, SIZE_t* samples, SIZE_t n) nogil:
 *     cdef int maxd = 2 * <int>log(n)             # <<<<<<<<<<<<<<
 *     introsort(Xf, samples, n, maxd)
 * 
 */
  __pyx_v_maxd = (2 * ((int)__pyx_f_7sklearn_4tree_5_tree_log(__pyx_v_n)));

  /* "sklearn/tree/_tree.pyx":1213
 * cdef inline void sort(DTYPE_t* Xf, SIZE_t* samples, SIZE_t n) nogil:
 *     cdef int maxd = 2 * <int>log(n)
 *     introsort(Xf, samples, n, maxd)             # <<<<<<<<<<<<<<
 * 
 * 
 */
  __pyx_f_7sklearn_4tree_5_tree_introsort(__pyx_v_Xf, __pyx_v_samples, __pyx_v_n, __pyx_v_maxd);

  /* "sklearn/tree/_tree.pyx":1211
 * # Sort n-element arrays pointed to by Xf and samples, simultaneously,
 * # by the values in Xf. Algorithm: Introsort (Musser, SP&E, 1997).
 * cdef inline void sort(DTYPE_t* Xf, SIZE_t* samples, SIZE_t n) nogil:             # <<<<<<<<<<<<<<
 *     cdef int maxd = 2 * <int>log(n)
 *     introsort(Xf, samples, n, maxd)
 */

  /* function exit code */
}

/* "sklearn/tree/_tree.pyx":1216
 * 
 * 
 * cdef inline void swap(DTYPE_t* Xf, SIZE_t* samples, SIZE_t i, SIZE_t j) nogil:             # <<<<<<<<<<<<<<
 *     # Helper for sort
 *     Xf[i], Xf[j] = Xf[j], Xf[i]
 */

static CYTHON_INLINE void __pyx_f_7sklearn_4tree_5_tree_swap(__pyx_t_7sklearn_4tree_5_tree_DTYPE_t *__pyx_v_Xf, __pyx_t_7sklearn_4tree_5_tree_SIZE_t *__pyx_v_samples, __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_i, __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_j) {
  __pyx_t_7sklearn_4tree_5_tree_DTYPE_t __pyx_t_1;
  __pyx_t_7sklearn_4tree_5_tree_DTYPE_t __pyx_t_2;
  __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_t_3;
  __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_t_4;

  /* "sklearn/tree/_tree.pyx":1218
 * cdef inline void swap(DTYPE_t* Xf, SIZE_t* samples, SIZE_t i, SIZE_t j) nogil:
 *     # Helper for sort
 *     Xf[i], Xf[j] = Xf[j], Xf[i]             # <<<<<<<<<<<<<<
 *     samples[i], samples[j] = samples[j], samples[i]
 * 
 */
  __pyx_t_1 = (__pyx_v_Xf[__pyx_v_j]);
  __pyx_t_2 = (__pyx_v_Xf[__pyx_v_i]);
  (__pyx_v_Xf[__pyx_v_i]) = __pyx_t_1;
  (__pyx_v_Xf[__pyx_v_j]) = __pyx_t_2;

  /* "sklearn/tree/_tree.pyx":1219
 *     # Helper for sort
 *     Xf[i], Xf[j] = Xf[j], Xf[i]
 *     samples[i], samples[j] = samples[j], samples[i]             # <<<<<<<<<<<<<<
 * 
 * 
 */
  __pyx_t_3 = (__pyx_v_samples[__pyx_v_j]);
  __pyx_t_4 = (__pyx_v_samples[__pyx_v_i]);
  (__pyx_v_samples[__pyx_v_i]) = __pyx_t_3;
  (__pyx_v_samples[__pyx_v_j]) = __pyx_t_4;

  /* "sklearn/tree/_tree.pyx":1216
 * 
 * 
 * cdef inline void swap(DTYPE_t* Xf, SIZE_t* samples, SIZE_t i, SIZE_t j) nogil:             # <<<<<<<<<<<<<<
 *     # Helper for sort
 *     Xf[i], Xf[j] = Xf[j], Xf[i]
 */

  /* function exit code */
}

/* "sklearn/tree/_tree.pyx":1222
 * 
 * 
 * cdef inline DTYPE_t median3(DTYPE_t* Xf, SIZE_t n) nogil:             # <<<<<<<<<<<<<<
 *     # Median of three pivot selection, after Bentley and McIlroy (1993).
 *     # Engineering a sort function. SP&E. Requires 8/3 comparisons on average.
 */

static CYTHON_INLINE __pyx_t_7sklearn_4tree_5_tree_DTYPE_t __pyx_f_7sklearn_4tree_5_tree_median3(__pyx_t_7sklearn_4tree_5_tree_DTYPE_t *__pyx_v_Xf, __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_n) {
  __pyx_t_7sklearn_4tree_5_tree_DTYPE_t __pyx_v_a;
  __pyx_t_7sklearn_4tree_5_tree_DTYPE_t __pyx_v_b;
  __pyx_t_7sklearn_4tree_5_tree_DTYPE_t __pyx_v_c;
  __pyx_t_7sklearn_4tree_5_tree_DTYPE_t __pyx_r;
  int __pyx_t_1;

  /* "sklearn/tree/_tree.pyx":1225
 *     # Median of three pivot selection, after Bentley and McIlroy (1993).
 *     # Engineering a sort function. SP&E. Requires 8/3 comparisons on average.
 *     cdef DTYPE_t a = Xf[0], b = Xf[n / 2], c = Xf[n - 1]             # <<<<<<<<<<<<<<
 *     if a < b:
 *         if b < c:
 */
  __pyx_v_a = (__pyx_v_Xf[0]);
  __pyx_v_b = (__pyx_v_Xf[(__pyx_v_n / 2)]);
  __pyx_v_c = (__pyx_v_Xf[(__pyx_v_n - 1)]);

  /* "sklearn/tree/_tree.pyx":1226
 *     # Engineering a sort function. SP&E. Requires 8/3 comparisons on average.
 *     cdef DTYPE_t a = Xf[0], b = Xf[n / 2], c = Xf[n - 1]
 *     if a < b:             # <<<<<<<<<<<<<<
 *         if b < c:
 *             return b
 */
  __pyx_t_1 = ((__pyx_v_a < __pyx_v_b) != 0);
  if (__pyx_t_1) {

    /* "sklearn/tree/_tree.pyx":1227
 *     cdef DTYPE_t a = Xf[0], b = Xf[n / 2], c = Xf[n - 1]
 *     if a < b:
 *         if b < c:             # <<<<<<<<<<<<<<
 *             return b
 *         elif a < c:
 */
    __pyx_t_1 = ((__pyx_v_b < __pyx_v_c) != 0);
    if (__pyx_t_1) {

      /* "sklearn/tree/_tree.pyx":1228
 *     if a < b:
 *         if b < c:
 *             return b             # <<<<<<<<<<<<<<
 *         elif a < c:
 *             return c
 */
      __pyx_r = __pyx_v_b;
      goto __pyx_L0;
    }

    /* "sklearn/tree/_tree.pyx":1229
 *         if b < c:
 *             return b
 *         elif a < c:             # <<<<<<<<<<<<<<
 *             return c
 *         else:
 */
    __pyx_t_1 = ((__pyx_v_a < __pyx_v_c) != 0);
    if (__pyx_t_1) {

      /* "sklearn/tree/_tree.pyx":1230
 *             return b
 *         elif a < c:
 *             return c             # <<<<<<<<<<<<<<
 *         else:
 *             return a
 */
      __pyx_r = __pyx_v_c;
      goto __pyx_L0;
    }
    /*else*/ {

      /* "sklearn/tree/_tree.pyx":1232
 *             return c
 *         else:
 *             return a             # <<<<<<<<<<<<<<
 *     elif b < c:
 *         if a < c:
 */
      __pyx_r = __pyx_v_a;
      goto __pyx_L0;
    }
  }

  /* "sklearn/tree/_tree.pyx":1233
 *         else:
 *             return a
 *     elif b < c:             # <<<<<<<<<<<<<<
 *         if a < c:
 *             return a
 */
  __pyx_t_1 = ((__pyx_v_b < __pyx_v_c) != 0);
  if (__pyx_t_1) {

    /* "sklearn/tree/_tree.pyx":1234
 *             return a
 *     elif b < c:
 *         if a < c:             # <<<<<<<<<<<<<<
 *             return a
 *         else:
 */
    __pyx_t_1 = ((__pyx_v_a < __pyx_v_c) != 0);
    if (__pyx_t_1) {

      /* "sklearn/tree/_tree.pyx":1235
 *     elif b < c:
 *         if a < c:
 *             return a             # <<<<<<<<<<<<<<
 *         else:
 *             return c
 */
      __pyx_r = __pyx_v_a;
      goto __pyx_L0;
    }
    /*else*/ {

      /* "sklearn/tree/_tree.pyx":1237
 *             return a
 *         else:
 *             return c             # <<<<<<<<<<<<<<
 *     else:
 *         return b
 */
      __pyx_r = __pyx_v_c;
      goto __pyx_L0;
    }
  }
  /*else*/ {

    /* "sklearn/tree/_tree.pyx":1239
 *             return c
 *     else:
 *         return b             # <<<<<<<<<<<<<<
 * 
 * 
 */
    __pyx_r = __pyx_v_b;
    goto __pyx_L0;
  }

  /* "sklearn/tree/_tree.pyx":1222
 * 
 * 
 * cdef inline DTYPE_t median3(DTYPE_t* Xf, SIZE_t n) nogil:             # <<<<<<<<<<<<<<
 *     # Median of three pivot selection, after Bentley and McIlroy (1993).
 *     # Engineering a sort function. SP&E. Requires 8/3 comparisons on average.
 */

  /* function exit code */
  __pyx_L0:;
  return __pyx_r;
}

/* "sklearn/tree/_tree.pyx":1244
 * # Introsort with median of 3 pivot selection and 3-way partition function
 * # (robust to repeated elements, e.g. lots of zero features).
 * cdef void introsort(DTYPE_t* Xf, SIZE_t *samples, SIZE_t n, int maxd) nogil:             # <<<<<<<<<<<<<<
 *     cdef DTYPE_t pivot
 *     cdef SIZE_t i, l, r
 */

static void __pyx_f_7sklearn_4tree_5_tree_introsort(__pyx_t_7sklearn_4tree_5_tree_DTYPE_t *__pyx_v_Xf, __pyx_t_7sklearn_4tree_5_tree_SIZE_t *__pyx_v_samples, __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_n, int __pyx_v_maxd) {
  __pyx_t_7sklearn_4tree_5_tree_DTYPE_t __pyx_v_pivot;
  __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_i;
  __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_l;
  __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_r;
  int __pyx_t_1;

  /* "sklearn/tree/_tree.pyx":1248
 *     cdef SIZE_t i, l, r
 * 
 *     while n > 1:             # <<<<<<<<<<<<<<
 *         if maxd <= 0:   # max depth limit exceeded ("gone quadratic")
 *             heapsort(Xf, samples, n)
 */
  while (1) {
    __pyx_t_1 = ((__pyx_v_n > 1) != 0);
    if (!__pyx_t_1) break;

    /* "sklearn/tree/_tree.pyx":1249
 * 
 *     while n > 1:
 *         if maxd <= 0:   # max depth limit exceeded ("gone quadratic")             # <<<<<<<<<<<<<<
 *             heapsort(Xf, samples, n)
 *             return
 */
    __pyx_t_1 = ((__pyx_v_maxd <= 0) != 0);
    if (__pyx_t_1) {

      /* "sklearn/tree/_tree.pyx":1250
 *     while n > 1:
 *         if maxd <= 0:   # max depth limit exceeded ("gone quadratic")
 *             heapsort(Xf, samples, n)             # <<<<<<<<<<<<<<
 *             return
 *         maxd -= 1
 */
      __pyx_f_7sklearn_4tree_5_tree_heapsort(__pyx_v_Xf, __pyx_v_samples, __pyx_v_n);

      /* "sklearn/tree/_tree.pyx":1251
 *         if maxd <= 0:   # max depth limit exceeded ("gone quadratic")
 *             heapsort(Xf, samples, n)
 *             return             # <<<<<<<<<<<<<<
 *         maxd -= 1
 * 
 */
      goto __pyx_L0;
    }

    /* "sklearn/tree/_tree.pyx":1252
 *             heapsort(Xf, samples, n)
 *             return
 *         maxd -= 1             # <<<<<<<<<<<<<<
 * 
 *         pivot = median3(Xf, n)
 */
    __pyx_v_maxd = (__pyx_v_maxd - 1);

    /* "sklearn/tree/_tree.pyx":1254
 *         maxd -= 1
 * 
 *         pivot = median3(Xf, n)             # <<<<<<<<<<<<<<
 * 
 *         # Three-way partition.
 */
    __pyx_v_pivot = __pyx_f_7sklearn_4tree_5_tree_median3(__pyx_v_Xf, __pyx_v_n);

    /* "sklearn/tree/_tree.pyx":1257
 * 
 *         # Three-way partition.
 *         i = l = 0             # <<<<<<<<<<<<<<
 *         r = n
 *         while i < r:
 */
    __pyx_v_i = 0;
    __pyx_v_l = 0;

    /* "sklearn/tree/_tree.pyx":1258
 *         # Three-way partition.
 *         i = l = 0
 *         r = n             # <<<<<<<<<<<<<<
 *         while i < r:
 *             if Xf[i] < pivot:
 */
    __pyx_v_r = __pyx_v_n;

    /* "sklearn/tree/_tree.pyx":1259
 *         i = l = 0
 *         r = n
 *         while i < r:             # <<<<<<<<<<<<<<
 *             if Xf[i] < pivot:
 *                 swap(Xf, samples, i, l)
 */
    while (1) {
      __pyx_t_1 = ((__pyx_v_i < __pyx_v_r) != 0);
      if (!__pyx_t_1) break;

      /* "sklearn/tree/_tree.pyx":1260
 *         r = n
 *         while i < r:
 *             if Xf[i] < pivot:             # <<<<<<<<<<<<<<
 *                 swap(Xf, samples, i, l)
 *                 i += 1
 */
      __pyx_t_1 = (((__pyx_v_Xf[__pyx_v_i]) < __pyx_v_pivot) != 0);
      if (__pyx_t_1) {

        /* "sklearn/tree/_tree.pyx":1261
 *         while i < r:
 *             if Xf[i] < pivot:
 *                 swap(Xf, samples, i, l)             # <<<<<<<<<<<<<<
 *                 i += 1
 *                 l += 1
 */
        __pyx_f_7sklearn_4tree_5_tree_swap(__pyx_v_Xf, __pyx_v_samples, __pyx_v_i, __pyx_v_l);

        /* "sklearn/tree/_tree.pyx":1262
 *             if Xf[i] < pivot:
 *                 swap(Xf, samples, i, l)
 *                 i += 1             # <<<<<<<<<<<<<<
 *                 l += 1
 *             elif Xf[i] > pivot:
 */
        __pyx_v_i = (__pyx_v_i + 1);

        /* "sklearn/tree/_tree.pyx":1263
 *                 swap(Xf, samples, i, l)
 *                 i += 1
 *                 l += 1             # <<<<<<<<<<<<<<
 *             elif Xf[i] > pivot:
 *                 r -= 1
 */
        __pyx_v_l = (__pyx_v_l + 1);
        goto __pyx_L8;
      }

      /* "sklearn/tree/_tree.pyx":1264
 *                 i += 1
 *                 l += 1
 *             elif Xf[i] > pivot:             # <<<<<<<<<<<<<<
 *                 r -= 1
 *                 swap(Xf, samples, i, r)
 */
      __pyx_t_1 = (((__pyx_v_Xf[__pyx_v_i]) > __pyx_v_pivot) != 0);
      if (__pyx_t_1) {

        /* "sklearn/tree/_tree.pyx":1265
 *                 l += 1
 *             elif Xf[i] > pivot:
 *                 r -= 1             # <<<<<<<<<<<<<<
 *                 swap(Xf, samples, i, r)
 *             else:
 */
        __pyx_v_r = (__pyx_v_r - 1);

        /* "sklearn/tree/_tree.pyx":1266
 *             elif Xf[i] > pivot:
 *                 r -= 1
 *                 swap(Xf, samples, i, r)             # <<<<<<<<<<<<<<
 *             else:
 *                 i += 1
 */
        __pyx_f_7sklearn_4tree_5_tree_swap(__pyx_v_Xf, __pyx_v_samples, __pyx_v_i, __pyx_v_r);
        goto __pyx_L8;
      }
      /*else*/ {

        /* "sklearn/tree/_tree.pyx":1268
 *                 swap(Xf, samples, i, r)
 *             else:
 *                 i += 1             # <<<<<<<<<<<<<<
 * 
 *         introsort(Xf, samples, l, maxd)
 */
        __pyx_v_i = (__pyx_v_i + 1);
      }
      __pyx_L8:;
    }

    /* "sklearn/tree/_tree.pyx":1270
 *                 i += 1
 * 
 *         introsort(Xf, samples, l, maxd)             # <<<<<<<<<<<<<<
 *         Xf += r
 *         samples += r
 */
    __pyx_f_7sklearn_4tree_5_tree_introsort(__pyx_v_Xf, __pyx_v_samples, __pyx_v_l, __pyx_v_maxd);

    /* "sklearn/tree/_tree.pyx":1271
 * 
 *         introsort(Xf, samples, l, maxd)
 *         Xf += r             # <<<<<<<<<<<<<<
 *         samples += r
 *         n -= r
 */
    __pyx_v_Xf = (__pyx_v_Xf + __pyx_v_r);

    /* "sklearn/tree/_tree.pyx":1272
 *         introsort(Xf, samples, l, maxd)
 *         Xf += r
 *         samples += r             # <<<<<<<<<<<<<<
 *         n -= r
 * 
 */
    __pyx_v_samples = (__pyx_v_samples + __pyx_v_r);

    /* "sklearn/tree/_tree.pyx":1273
 *         Xf += r
 *         samples += r
 *         n -= r             # <<<<<<<<<<<<<<
 * 
 * 
 */
    __pyx_v_n = (__pyx_v_n - __pyx_v_r);
  }

  /* "sklearn/tree/_tree.pyx":1244
 * # Introsort with median of 3 pivot selection and 3-way partition function
 * # (robust to repeated elements, e.g. lots of zero features).
 * cdef void introsort(DTYPE_t* Xf, SIZE_t *samples, SIZE_t n, int maxd) nogil:             # <<<<<<<<<<<<<<
 *     cdef DTYPE_t pivot
 *     cdef SIZE_t i, l, r
 */

  /* function exit code */
  __pyx_L0:;
}

/* "sklearn/tree/_tree.pyx":1276
 * 
 * 
 * cdef inline void sift_down(DTYPE_t* Xf, SIZE_t* samples,             # <<<<<<<<<<<<<<
 *                            SIZE_t start, SIZE_t end) nogil:
 *     # Restore heap order in Xf[start:end] by moving the max element to start.
 */

static CYTHON_INLINE void __pyx_f_7sklearn_4tree_5_tree_sift_down(__pyx_t_7sklearn_4tree_5_tree_DTYPE_t *__pyx_v_Xf, __pyx_t_7sklearn_4tree_5_tree_SIZE_t *__pyx_v_samples, __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_start, __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_end) {
  __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_child;
  __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_maxind;
  __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_root;
  int __pyx_t_1;
  int __pyx_t_2;
  int __pyx_t_3;

  /* "sklearn/tree/_tree.pyx":1281
 *     cdef SIZE_t child, maxind, root
 * 
 *     root = start             # <<<<<<<<<<<<<<
 *     while True:
 *         child = root * 2 + 1
 */
  __pyx_v_root = __pyx_v_start;

  /* "sklearn/tree/_tree.pyx":1282
 * 
 *     root = start
 *     while True:             # <<<<<<<<<<<<<<
 *         child = root * 2 + 1
 * 
 */
  while (1) {

    /* "sklearn/tree/_tree.pyx":1283
 *     root = start
 *     while True:
 *         child = root * 2 + 1             # <<<<<<<<<<<<<<
 * 
 *         # find max of root, left child, right child
 */
    __pyx_v_child = ((__pyx_v_root * 2) + 1);

    /* "sklearn/tree/_tree.pyx":1286
 * 
 *         # find max of root, left child, right child
 *         maxind = root             # <<<<<<<<<<<<<<
 *         if child < end and Xf[maxind] < Xf[child]:
 *             maxind = child
 */
    __pyx_v_maxind = __pyx_v_root;

    /* "sklearn/tree/_tree.pyx":1287
 *         # find max of root, left child, right child
 *         maxind = root
 *         if child < end and Xf[maxind] < Xf[child]:             # <<<<<<<<<<<<<<
 *             maxind = child
 *         if child + 1 < end and Xf[maxind] < Xf[child + 1]:
 */
    __pyx_t_1 = ((__pyx_v_child < __pyx_v_end) != 0);
    if (__pyx_t_1) {
      __pyx_t_2 = (((__pyx_v_Xf[__pyx_v_maxind]) < (__pyx_v_Xf[__pyx_v_child])) != 0);
      __pyx_t_3 = __pyx_t_2;
    } else {
      __pyx_t_3 = __pyx_t_1;
    }
    if (__pyx_t_3) {

      /* "sklearn/tree/_tree.pyx":1288
 *         maxind = root
 *         if child < end and Xf[maxind] < Xf[child]:
 *             maxind = child             # <<<<<<<<<<<<<<
 *         if child + 1 < end and Xf[maxind] < Xf[child + 1]:
 *             maxind = child + 1
 */
      __pyx_v_maxind = __pyx_v_child;
      goto __pyx_L5;
    }
    __pyx_L5:;

    /* "sklearn/tree/_tree.pyx":1289
 *         if child < end and Xf[maxind] < Xf[child]:
 *             maxind = child
 *         if child + 1 < end and Xf[maxind] < Xf[child + 1]:             # <<<<<<<<<<<<<<
 *             maxind = child + 1
 * 
 */
    __pyx_t_3 = (((__pyx_v_child + 1) < __pyx_v_end) != 0);
    if (__pyx_t_3) {
      __pyx_t_1 = (((__pyx_v_Xf[__pyx_v_maxind]) < (__pyx_v_Xf[(__pyx_v_child + 1)])) != 0);
      __pyx_t_2 = __pyx_t_1;
    } else {
      __pyx_t_2 = __pyx_t_3;
    }
    if (__pyx_t_2) {

      /* "sklearn/tree/_tree.pyx":1290
 *             maxind = child
 *         if child + 1 < end and Xf[maxind] < Xf[child + 1]:
 *             maxind = child + 1             # <<<<<<<<<<<<<<
 * 
 *         if maxind == root:
 */
      __pyx_v_maxind = (__pyx_v_child + 1);
      goto __pyx_L6;
    }
    __pyx_L6:;

    /* "sklearn/tree/_tree.pyx":1292
 *             maxind = child + 1
 * 
 *         if maxind == root:             # <<<<<<<<<<<<<<
 *             break
 *         else:
 */
    __pyx_t_2 = ((__pyx_v_maxind == __pyx_v_root) != 0);
    if (__pyx_t_2) {

      /* "sklearn/tree/_tree.pyx":1293
 * 
 *         if maxind == root:
 *             break             # <<<<<<<<<<<<<<
 *         else:
 *             swap(Xf, samples, root, maxind)
 */
      goto __pyx_L4_break;
    }
    /*else*/ {

      /* "sklearn/tree/_tree.pyx":1295
 *             break
 *         else:
 *             swap(Xf, samples, root, maxind)             # <<<<<<<<<<<<<<
 *             root = maxind
 * 
 */
      __pyx_f_7sklearn_4tree_5_tree_swap(__pyx_v_Xf, __pyx_v_samples, __pyx_v_root, __pyx_v_maxind);

      /* "sklearn/tree/_tree.pyx":1296
 *         else:
 *             swap(Xf, samples, root, maxind)
 *             root = maxind             # <<<<<<<<<<<<<<
 * 
 * 
 */
      __pyx_v_root = __pyx_v_maxind;
    }
  }
  __pyx_L4_break:;

  /* "sklearn/tree/_tree.pyx":1276
 * 
 * 
 * cdef inline void sift_down(DTYPE_t* Xf, SIZE_t* samples,             # <<<<<<<<<<<<<<
 *                            SIZE_t start, SIZE_t end) nogil:
 *     # Restore heap order in Xf[start:end] by moving the max element to start.
 */

  /* function exit code */
}

/* "sklearn/tree/_tree.pyx":1299
 * 
 * 
 * cdef void heapsort(DTYPE_t* Xf, SIZE_t* samples, SIZE_t n) nogil:             # <<<<<<<<<<<<<<
 *     cdef SIZE_t start, end
 * 
 */

static void __pyx_f_7sklearn_4tree_5_tree_heapsort(__pyx_t_7sklearn_4tree_5_tree_DTYPE_t *__pyx_v_Xf, __pyx_t_7sklearn_4tree_5_tree_SIZE_t *__pyx_v_samples, __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_n) {
  __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_start;
  __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_end;
  int __pyx_t_1;

  /* "sklearn/tree/_tree.pyx":1303
 * 
 *     # heapify
 *     start = (n - 2) / 2             # <<<<<<<<<<<<<<
 *     end = n
 *     while True:
 */
  __pyx_v_start = ((__pyx_v_n - 2) / 2);

  /* "sklearn/tree/_tree.pyx":1304
 *     # heapify
 *     start = (n - 2) / 2
 *     end = n             # <<<<<<<<<<<<<<
 *     while True:
 *         sift_down(Xf, samples, start, end)
 */
  __pyx_v_end = __pyx_v_n;

  /* "sklearn/tree/_tree.pyx":1305
 *     start = (n - 2) / 2
 *     end = n
 *     while True:             # <<<<<<<<<<<<<<
 *         sift_down(Xf, samples, start, end)
 *         if start == 0:
 */
  while (1) {

    /* "sklearn/tree/_tree.pyx":1306
 *     end = n
 *     while True:
 *         sift_down(Xf, samples, start, end)             # <<<<<<<<<<<<<<
 *         if start == 0:
 *             break
 */
    __pyx_f_7sklearn_4tree_5_tree_sift_down(__pyx_v_Xf, __pyx_v_samples, __pyx_v_start, __pyx_v_end);

    /* "sklearn/tree/_tree.pyx":1307
 *     while True:
 *         sift_down(Xf, samples, start, end)
 *         if start == 0:             # <<<<<<<<<<<<<<
 *             break
 *         start -= 1
 */
    __pyx_t_1 = ((__pyx_v_start == 0) != 0);
    if (__pyx_t_1) {

      /* "sklearn/tree/_tree.pyx":1308
 *         sift_down(Xf, samples, start, end)
 *         if start == 0:
 *             break             # <<<<<<<<<<<<<<
 *         start -= 1
 * 
 */
      goto __pyx_L4_break;
    }

    /* "sklearn/tree/_tree.pyx":1309
 *         if start == 0:
 *             break
 *         start -= 1             # <<<<<<<<<<<<<<
 * 
 *     # sort by shrinking the heap, putting the max element immediately after it
 */
    __pyx_v_start = (__pyx_v_start - 1);
  }
  __pyx_L4_break:;

  /* "sklearn/tree/_tree.pyx":1312
 * 
 *     # sort by shrinking the heap, putting the max element immediately after it
 *     end = n - 1             # <<<<<<<<<<<<<<
 *     while end > 0:
 *         swap(Xf, samples, 0, end)
 */
  __pyx_v_end = (__pyx_v_n - 1);

  /* "sklearn/tree/_tree.pyx":1313
 *     # sort by shrinking the heap, putting the max element immediately after it
 *     end = n - 1
 *     while end > 0:             # <<<<<<<<<<<<<<
 *         swap(Xf, samples, 0, end)
 *         sift_down(Xf, samples, 0, end)
 */
  while (1) {
    __pyx_t_1 = ((__pyx_v_end > 0) != 0);
    if (!__pyx_t_1) break;

    /* "sklearn/tree/_tree.pyx":1314
 *     end = n - 1
 *     while end > 0:
 *         swap(Xf, samples, 0, end)             # <<<<<<<<<<<<<<
 *         sift_down(Xf, samples, 0, end)
 *         end = end - 1
 */
    __pyx_f_7sklearn_4tree_5_tree_swap(__pyx_v_Xf, __pyx_v_samples, 0, __pyx_v_end);

    /* "sklearn/tree/_tree.pyx":1315
 *     while end > 0:
 *         swap(Xf, samples, 0, end)
 *         sift_down(Xf, samples, 0, end)             # <<<<<<<<<<<<<<
 *         end = end - 1
 * 
 */
    __pyx_f_7sklearn_4tree_5_tree_sift_down(__pyx_v_Xf, __pyx_v_samples, 0, __pyx_v_end);

    /* "sklearn/tree/_tree.pyx":1316
 *         swap(Xf, samples, 0, end)
 *         sift_down(Xf, samples, 0, end)
 *         end = end - 1             # <<<<<<<<<<<<<<
 * 
 * 
 */
    __pyx_v_end = (__pyx_v_end - 1);
  }

  /* "sklearn/tree/_tree.pyx":1299
 * 
 * 
 * cdef void heapsort(DTYPE_t* Xf, SIZE_t* samples, SIZE_t n) nogil:             # <<<<<<<<<<<<<<
 *     cdef SIZE_t start, end
 * 
 */

  /* function exit code */
}

/* "sklearn/tree/_tree.pyx":1321
 * cdef class RandomSplitter(Splitter):
 *     """Splitter for finding the best random split."""
 *     def __reduce__(self):             # <<<<<<<<<<<<<<
 *         return (RandomSplitter, (self.criterion,
 *                                  self.max_features,
 */

/* Python wrapper */
static PyObject *__pyx_pw_7sklearn_4tree_5_tree_14RandomSplitter_1__reduce__(PyObject *__pyx_v_self, CYTHON_UNUSED PyObject *unused); /*proto*/
static PyObject *__pyx_pw_7sklearn_4tree_5_tree_14RandomSplitter_1__reduce__(PyObject *__pyx_v_self, CYTHON_UNUSED PyObject *unused) {
  PyObject *__pyx_r = 0;
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  __Pyx_RefNannySetupContext("__reduce__ (wrapper)", 0);
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  /* function exit code */
  __Pyx_RefNannyFinishContext();
  return __pyx_r;
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static PyObject *__pyx_pf_7sklearn_4tree_5_tree_14RandomSplitter___reduce__(struct __pyx_obj_7sklearn_4tree_5_tree_RandomSplitter *__pyx_v_self) {
  PyObject *__pyx_r = NULL;
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 *         """Find the best random split on node samples[start:end]."""
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 *         cdef SIZE_t end = self.end
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 *         cdef SIZE_t start = self.start             # <<<<<<<<<<<<<<
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 *         cdef SIZE_t end = self.end             # <<<<<<<<<<<<<<
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 *         cdef SIZE_t* features = self.features
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 *         cdef SIZE_t X_fx_stride = self.X_fx_stride             # <<<<<<<<<<<<<<
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 *         cdef SIZE_t X_fx_stride = self.X_fx_stride
 *         cdef SIZE_t max_features = self.max_features             # <<<<<<<<<<<<<<
 *         cdef SIZE_t min_samples_leaf = self.min_samples_leaf
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 *         cdef SIZE_t max_features = self.max_features
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 *         cdef SIZE_t min_samples_leaf = self.min_samples_leaf
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 *                 n_drawn_constants += 1             # <<<<<<<<<<<<<<
 * 
 *             else:
 */
      __pyx_v_n_drawn_constants = (__pyx_v_n_drawn_constants + 1);
      goto __pyx_L5;
    }
    /*else*/ {

      /* "sklearn/tree/_tree.pyx":1407
 *             else:
 *                 # f_j in the interval [n_known_constants, f_i - n_found_constants[
 *                 f_j += n_found_constants             # <<<<<<<<<<<<<<
 *                 # f_j in the interval [n_total_constants, f_i[
 * 
 */
      __pyx_v_f_j = (__pyx_v_f_j + __pyx_v_n_found_constants);

      /* "sklearn/tree/_tree.pyx":1410
 *                 # f_j in the interval [n_total_constants, f_i[
 * 
 *                 current.feature = features[f_j]             # <<<<<<<<<<<<<<
 * 
 *                 # Find min, max
 */
      __pyx_v_current.feature = (__pyx_v_features[__pyx_v_f_j]);

      /* "sklearn/tree/_tree.pyx":1413
 * 
 *                 # Find min, max
 *                 min_feature_value = X[X_sample_stride * samples[start] +             # <<<<<<<<<<<<<<
 *                                       X_fx_stride * current.feature]
 *                 max_feature_value = min_feature_value
 */
      __pyx_v_min_feature_value = (__pyx_v_X[((__pyx_v_X_sample_stride * (__pyx_v_samples[__pyx_v_start])) + (__pyx_v_X_fx_stride * __pyx_v_current.feature))]);

      /* "sklearn/tree/_tree.pyx":1415
 *                 min_feature_value = X[X_sample_stride * samples[start] +
 *                                       X_fx_stride * current.feature]
 *                 max_feature_value = min_feature_value             # <<<<<<<<<<<<<<
 *                 Xf[start] = min_feature_value
 * 
 */
      __pyx_v_max_feature_value = __pyx_v_min_feature_value;

      /* "sklearn/tree/_tree.pyx":1416
 *                                       X_fx_stride * current.feature]
 *                 max_feature_value = min_feature_value
 *                 Xf[start] = min_feature_value             # <<<<<<<<<<<<<<
 * 
 *                 for p in range(start + 1, end):
 */
      (__pyx_v_Xf[__pyx_v_start]) = __pyx_v_min_feature_value;

      /* "sklearn/tree/_tree.pyx":1418
 *                 Xf[start] = min_feature_value
 * 
 *                 for p in range(start + 1, end):             # <<<<<<<<<<<<<<
 *                     current_feature_value = X[X_sample_stride * samples[p] +
 *                                               X_fx_stride * current.feature]
 */
      __pyx_t_2 = __pyx_v_end;
      for (__pyx_t_8 = (__pyx_v_start + 1); __pyx_t_8 < __pyx_t_2; __pyx_t_8+=1) {
        __pyx_v_p = __pyx_t_8;

        /* "sklearn/tree/_tree.pyx":1419
 * 
 *                 for p in range(start + 1, end):
 *                     current_feature_value = X[X_sample_stride * samples[p] +             # <<<<<<<<<<<<<<
 *                                               X_fx_stride * current.feature]
 *                     Xf[p] = current_feature_value
 */
        __pyx_v_current_feature_value = (__pyx_v_X[((__pyx_v_X_sample_stride * (__pyx_v_samples[__pyx_v_p])) + (__pyx_v_X_fx_stride * __pyx_v_current.feature))]);

        /* "sklearn/tree/_tree.pyx":1421
 *                     current_feature_value = X[X_sample_stride * samples[p] +
 *                                               X_fx_stride * current.feature]
 *                     Xf[p] = current_feature_value             # <<<<<<<<<<<<<<
 * 
 *                     if current_feature_value < min_feature_value:
 */
        (__pyx_v_Xf[__pyx_v_p]) = __pyx_v_current_feature_value;

        /* "sklearn/tree/_tree.pyx":1423
 *                     Xf[p] = current_feature_value
 * 
 *                     if current_feature_value < min_feature_value:             # <<<<<<<<<<<<<<
 *                         min_feature_value = current_feature_value
 *                     elif current_feature_value > max_feature_value:
 */
        __pyx_t_5 = ((__pyx_v_current_feature_value < __pyx_v_min_feature_value) != 0);
        if (__pyx_t_5) {

          /* "sklearn/tree/_tree.pyx":1424
 * 
 *                     if current_feature_value < min_feature_value:
 *                         min_feature_value = current_feature_value             # <<<<<<<<<<<<<<
 *                     elif current_feature_value > max_feature_value:
 *                         max_feature_value = current_feature_value
 */
          __pyx_v_min_feature_value = __pyx_v_current_feature_value;
          goto __pyx_L8;
        }

        /* "sklearn/tree/_tree.pyx":1425
 *                     if current_feature_value < min_feature_value:
 *                         min_feature_value = current_feature_value
 *                     elif current_feature_value > max_feature_value:             # <<<<<<<<<<<<<<
 *                         max_feature_value = current_feature_value
 * 
 */
        __pyx_t_5 = ((__pyx_v_current_feature_value > __pyx_v_max_feature_value) != 0);
        if (__pyx_t_5) {

          /* "sklearn/tree/_tree.pyx":1426
 *                         min_feature_value = current_feature_value
 *                     elif current_feature_value > max_feature_value:
 *                         max_feature_value = current_feature_value             # <<<<<<<<<<<<<<
 * 
 *                 if max_feature_value <= min_feature_value + FEATURE_THRESHOLD:
 */
          __pyx_v_max_feature_value = __pyx_v_current_feature_value;
          goto __pyx_L8;
        }
        __pyx_L8:;
      }

      /* "sklearn/tree/_tree.pyx":1428
 *                         max_feature_value = current_feature_value
 * 
 *                 if max_feature_value <= min_feature_value + FEATURE_THRESHOLD:             # <<<<<<<<<<<<<<
 *                     features[f_j] = features[n_total_constants]
 *                     features[n_total_constants] = current.feature
 */
      __pyx_t_5 = ((__pyx_v_max_feature_value <= (__pyx_v_min_feature_value + __pyx_v_7sklearn_4tree_5_tree_FEATURE_THRESHOLD)) != 0);
      if (__pyx_t_5) {

        /* "sklearn/tree/_tree.pyx":1429
 * 
 *                 if max_feature_value <= min_feature_value + FEATURE_THRESHOLD:
 *                     features[f_j] = features[n_total_constants]             # <<<<<<<<<<<<<<
 *                     features[n_total_constants] = current.feature
 * 
 */
        (__pyx_v_features[__pyx_v_f_j]) = (__pyx_v_features[__pyx_v_n_total_constants]);

        /* "sklearn/tree/_tree.pyx":1430
 *                 if max_feature_value <= min_feature_value + FEATURE_THRESHOLD:
 *                     features[f_j] = features[n_total_constants]
 *                     features[n_total_constants] = current.feature             # <<<<<<<<<<<<<<
 * 
 *                     n_found_constants += 1
 */
        __pyx_t_2 = __pyx_v_current.feature;
        (__pyx_v_features[__pyx_v_n_total_constants]) = __pyx_t_2;

        /* "sklearn/tree/_tree.pyx":1432
 *                     features[n_total_constants] = current.feature
 * 
 *                     n_found_constants += 1             # <<<<<<<<<<<<<<
 *                     n_total_constants += 1
 * 
 */
        __pyx_v_n_found_constants = (__pyx_v_n_found_constants + 1);

        /* "sklearn/tree/_tree.pyx":1433
 * 
 *                     n_found_constants += 1
 *                     n_total_constants += 1             # <<<<<<<<<<<<<<
 * 
 *                 else:
 */
        __pyx_v_n_total_constants = (__pyx_v_n_total_constants + 1);
        goto __pyx_L9;
      }
      /*else*/ {

        /* "sklearn/tree/_tree.pyx":1436
 * 
 *                 else:
 *                     f_i -= 1             # <<<<<<<<<<<<<<
 *                     features[f_i], features[f_j] = features[f_j], features[f_i]
 * 
 */
        __pyx_v_f_i = (__pyx_v_f_i - 1);

        /* "sklearn/tree/_tree.pyx":1437
 *                 else:
 *                     f_i -= 1
 *                     features[f_i], features[f_j] = features[f_j], features[f_i]             # <<<<<<<<<<<<<<
 * 
 *                     # Draw a random threshold
 */
        __pyx_t_2 = (__pyx_v_features[__pyx_v_f_j]);
        __pyx_t_8 = (__pyx_v_features[__pyx_v_f_i]);
        (__pyx_v_features[__pyx_v_f_i]) = __pyx_t_2;
        (__pyx_v_features[__pyx_v_f_j]) = __pyx_t_8;

        /* "sklearn/tree/_tree.pyx":1440
 * 
 *                     # Draw a random threshold
 *                     current.threshold = (min_feature_value +             # <<<<<<<<<<<<<<
 *                                          rand_double(random_state) *
 *                                          (max_feature_value -
 */
        __pyx_v_current.threshold = (__pyx_v_min_feature_value + (__pyx_f_7sklearn_4tree_5_tree_rand_double(__pyx_v_random_state) * (__pyx_v_max_feature_value - __pyx_v_min_feature_value)));

        /* "sklearn/tree/_tree.pyx":1445
 *                                           min_feature_value))
 * 
 *                     if current.threshold == max_feature_value:             # <<<<<<<<<<<<<<
 *                         current.threshold = min_feature_value
 * 
 */
        __pyx_t_5 = ((__pyx_v_current.threshold == __pyx_v_max_feature_value) != 0);
        if (__pyx_t_5) {

          /* "sklearn/tree/_tree.pyx":1446
 * 
 *                     if current.threshold == max_feature_value:
 *                         current.threshold = min_feature_value             # <<<<<<<<<<<<<<
 * 
 *                     # Partition
 */
          __pyx_v_current.threshold = __pyx_v_min_feature_value;
          goto __pyx_L10;
        }
        __pyx_L10:;

        /* "sklearn/tree/_tree.pyx":1449
 * 
 *                     # Partition
 *                     partition_end = end             # <<<<<<<<<<<<<<
 *                     p = start
 *                     while p < partition_end:
 */
        __pyx_v_partition_end = __pyx_v_end;

        /* "sklearn/tree/_tree.pyx":1450
 *                     # Partition
 *                     partition_end = end
 *                     p = start             # <<<<<<<<<<<<<<
 *                     while p < partition_end:
 *                         current_feature_value = Xf[p]
 */
        __pyx_v_p = __pyx_v_start;

        /* "sklearn/tree/_tree.pyx":1451
 *                     partition_end = end
 *                     p = start
 *                     while p < partition_end:             # <<<<<<<<<<<<<<
 *                         current_feature_value = Xf[p]
 *                         if current_feature_value <= current.threshold:
 */
        while (1) {
          __pyx_t_5 = ((__pyx_v_p < __pyx_v_partition_end) != 0);
          if (!__pyx_t_5) break;

          /* "sklearn/tree/_tree.pyx":1452
 *                     p = start
 *                     while p < partition_end:
 *                         current_feature_value = Xf[p]             # <<<<<<<<<<<<<<
 *                         if current_feature_value <= current.threshold:
 *                             p += 1
 */
          __pyx_v_current_feature_value = (__pyx_v_Xf[__pyx_v_p]);

          /* "sklearn/tree/_tree.pyx":1453
 *                     while p < partition_end:
 *                         current_feature_value = Xf[p]
 *                         if current_feature_value <= current.threshold:             # <<<<<<<<<<<<<<
 *                             p += 1
 *                         else:
 */
          __pyx_t_5 = ((__pyx_v_current_feature_value <= __pyx_v_current.threshold) != 0);
          if (__pyx_t_5) {

            /* "sklearn/tree/_tree.pyx":1454
 *                         current_feature_value = Xf[p]
 *                         if current_feature_value <= current.threshold:
 *                             p += 1             # <<<<<<<<<<<<<<
 *                         else:
 *                             partition_end -= 1
 */
            __pyx_v_p = (__pyx_v_p + 1);
            goto __pyx_L13;
          }
          /*else*/ {

            /* "sklearn/tree/_tree.pyx":1456
 *                             p += 1
 *                         else:
 *                             partition_end -= 1             # <<<<<<<<<<<<<<
 * 
 *                             Xf[p] = Xf[partition_end]
 */
            __pyx_v_partition_end = (__pyx_v_partition_end - 1);

            /* "sklearn/tree/_tree.pyx":1458
 *                             partition_end -= 1
 * 
 *                             Xf[p] = Xf[partition_end]             # <<<<<<<<<<<<<<
 *                             Xf[partition_end] = current_feature_value
 * 
 */
            (__pyx_v_Xf[__pyx_v_p]) = (__pyx_v_Xf[__pyx_v_partition_end]);

            /* "sklearn/tree/_tree.pyx":1459
 * 
 *                             Xf[p] = Xf[partition_end]
 *                             Xf[partition_end] = current_feature_value             # <<<<<<<<<<<<<<
 * 
 *                             tmp = samples[partition_end]
 */
            (__pyx_v_Xf[__pyx_v_partition_end]) = __pyx_v_current_feature_value;

            /* "sklearn/tree/_tree.pyx":1461
 *                             Xf[partition_end] = current_feature_value
 * 
 *                             tmp = samples[partition_end]             # <<<<<<<<<<<<<<
 *                             samples[partition_end] = samples[p]
 *                             samples[p] = tmp
 */
            __pyx_v_tmp = (__pyx_v_samples[__pyx_v_partition_end]);

            /* "sklearn/tree/_tree.pyx":1462
 * 
 *                             tmp = samples[partition_end]
 *                             samples[partition_end] = samples[p]             # <<<<<<<<<<<<<<
 *                             samples[p] = tmp
 * 
 */
            (__pyx_v_samples[__pyx_v_partition_end]) = (__pyx_v_samples[__pyx_v_p]);

            /* "sklearn/tree/_tree.pyx":1463
 *                             tmp = samples[partition_end]
 *                             samples[partition_end] = samples[p]
 *                             samples[p] = tmp             # <<<<<<<<<<<<<<
 * 
 *                     current.pos = partition_end
 */
            (__pyx_v_samples[__pyx_v_p]) = __pyx_v_tmp;
          }
          __pyx_L13:;
        }

        /* "sklearn/tree/_tree.pyx":1465
 *                             samples[p] = tmp
 * 
 *                     current.pos = partition_end             # <<<<<<<<<<<<<<
 * 
 *                     # Reject if min_samples_leaf is not guaranteed
 */
        __pyx_v_current.pos = __pyx_v_partition_end;

        /* "sklearn/tree/_tree.pyx":1468
 * 
 *                     # Reject if min_samples_leaf is not guaranteed
 *                     if (((current.pos - start) < min_samples_leaf) or             # <<<<<<<<<<<<<<
 *                             ((end - current.pos) < min_samples_leaf)):
 *                         continue
 */
        __pyx_t_5 = (((__pyx_v_current.pos - __pyx_v_start) < __pyx_v_min_samples_leaf) != 0);
        if (!__pyx_t_5) {

          /* "sklearn/tree/_tree.pyx":1469
 *                     # Reject if min_samples_leaf is not guaranteed
 *                     if (((current.pos - start) < min_samples_leaf) or
 *                             ((end - current.pos) < min_samples_leaf)):             # <<<<<<<<<<<<<<
 *                         continue
 * 
 */
          __pyx_t_4 = (((__pyx_v_end - __pyx_v_current.pos) < __pyx_v_min_samples_leaf) != 0);
          __pyx_t_7 = __pyx_t_4;
        } else {
          __pyx_t_7 = __pyx_t_5;
        }
        if (__pyx_t_7) {

          /* "sklearn/tree/_tree.pyx":1470
 *                     if (((current.pos - start) < min_samples_leaf) or
 *                             ((end - current.pos) < min_samples_leaf)):
 *                         continue             # <<<<<<<<<<<<<<
 * 
 *                     # Evaluate split
 */
          goto __pyx_L3_continue;
        }

        /* "sklearn/tree/_tree.pyx":1473
 * 
 *                     # Evaluate split
 *                     self.criterion.reset()             # <<<<<<<<<<<<<<
 *                     self.criterion.update(current.pos)
 *                     current.improvement = self.criterion.impurity_improvement(impurity)
 */
        ((struct __pyx_vtabstruct_7sklearn_4tree_5_tree_Criterion *)__pyx_v_self->__pyx_base.criterion->__pyx_vtab)->reset(__pyx_v_self->__pyx_base.criterion);

        /* "sklearn/tree/_tree.pyx":1474
 *                     # Evaluate split
 *                     self.criterion.reset()
 *                     self.criterion.update(current.pos)             # <<<<<<<<<<<<<<
 *                     current.improvement = self.criterion.impurity_improvement(impurity)
 * 
 */
        ((struct __pyx_vtabstruct_7sklearn_4tree_5_tree_Criterion *)__pyx_v_self->__pyx_base.criterion->__pyx_vtab)->update(__pyx_v_self->__pyx_base.criterion, __pyx_v_current.pos);

        /* "sklearn/tree/_tree.pyx":1475
 *                     self.criterion.reset()
 *                     self.criterion.update(current.pos)
 *                     current.improvement = self.criterion.impurity_improvement(impurity)             # <<<<<<<<<<<<<<
 * 
 *                     if current.improvement > best.improvement:
 */
        __pyx_v_current.improvement = ((struct __pyx_vtabstruct_7sklearn_4tree_5_tree_Criterion *)__pyx_v_self->__pyx_base.criterion->__pyx_vtab)->impurity_improvement(__pyx_v_self->__pyx_base.criterion, __pyx_v_impurity);

        /* "sklearn/tree/_tree.pyx":1477
 *                     current.improvement = self.criterion.impurity_improvement(impurity)
 * 
 *                     if current.improvement > best.improvement:             # <<<<<<<<<<<<<<
 *                         self.criterion.children_impurity(&current.impurity_left,
 *                                                          &current.impurity_right)
 */
        __pyx_t_7 = ((__pyx_v_current.improvement > __pyx_v_best.improvement) != 0);
        if (__pyx_t_7) {

          /* "sklearn/tree/_tree.pyx":1478
 * 
 *                     if current.improvement > best.improvement:
 *                         self.criterion.children_impurity(&current.impurity_left,             # <<<<<<<<<<<<<<
 *                                                          &current.impurity_right)
 *                         best = current  # copy
 */
          ((struct __pyx_vtabstruct_7sklearn_4tree_5_tree_Criterion *)__pyx_v_self->__pyx_base.criterion->__pyx_vtab)->children_impurity(__pyx_v_self->__pyx_base.criterion, (&__pyx_v_current.impurity_left), (&__pyx_v_current.impurity_right));

          /* "sklearn/tree/_tree.pyx":1480
 *                         self.criterion.children_impurity(&current.impurity_left,
 *                                                          &current.impurity_right)
 *                         best = current  # copy             # <<<<<<<<<<<<<<
 * 
 *         # Reorganize into samples[start:best.pos] + samples[best.pos:end]
 */
          __pyx_v_best = __pyx_v_current;
          goto __pyx_L15;
        }
        __pyx_L15:;
      }
      __pyx_L9:;
    }
    __pyx_L5:;
    __pyx_L3_continue:;
  }

  /* "sklearn/tree/_tree.pyx":1483
 * 
 *         # Reorganize into samples[start:best.pos] + samples[best.pos:end]
 *         if best.pos < end and current.feature != best.feature:             # <<<<<<<<<<<<<<
 *             partition_end = end
 *             p = start
 */
  __pyx_t_7 = ((__pyx_v_best.pos < __pyx_v_end) != 0);
  if (__pyx_t_7) {
    __pyx_t_5 = ((__pyx_v_current.feature != __pyx_v_best.feature) != 0);
    __pyx_t_4 = __pyx_t_5;
  } else {
    __pyx_t_4 = __pyx_t_7;
  }
  if (__pyx_t_4) {

    /* "sklearn/tree/_tree.pyx":1484
 *         # Reorganize into samples[start:best.pos] + samples[best.pos:end]
 *         if best.pos < end and current.feature != best.feature:
 *             partition_end = end             # <<<<<<<<<<<<<<
 *             p = start
 * 
 */
    __pyx_v_partition_end = __pyx_v_end;

    /* "sklearn/tree/_tree.pyx":1485
 *         if best.pos < end and current.feature != best.feature:
 *             partition_end = end
 *             p = start             # <<<<<<<<<<<<<<
 * 
 *             while p < partition_end:
 */
    __pyx_v_p = __pyx_v_start;

    /* "sklearn/tree/_tree.pyx":1487
 *             p = start
 * 
 *             while p < partition_end:             # <<<<<<<<<<<<<<
 *                 if X[X_sample_stride * samples[p] +
 *                      X_fx_stride * best.feature] <= best.threshold:
 */
    while (1) {
      __pyx_t_4 = ((__pyx_v_p < __pyx_v_partition_end) != 0);
      if (!__pyx_t_4) break;

      /* "sklearn/tree/_tree.pyx":1489
 *             while p < partition_end:
 *                 if X[X_sample_stride * samples[p] +
 *                      X_fx_stride * best.feature] <= best.threshold:             # <<<<<<<<<<<<<<
 *                     p += 1
 * 
 */
      __pyx_t_4 = (((__pyx_v_X[((__pyx_v_X_sample_stride * (__pyx_v_samples[__pyx_v_p])) + (__pyx_v_X_fx_stride * __pyx_v_best.feature))]) <= __pyx_v_best.threshold) != 0);
      if (__pyx_t_4) {

        /* "sklearn/tree/_tree.pyx":1490
 *                 if X[X_sample_stride * samples[p] +
 *                      X_fx_stride * best.feature] <= best.threshold:
 *                     p += 1             # <<<<<<<<<<<<<<
 * 
 *                 else:
 */
        __pyx_v_p = (__pyx_v_p + 1);
        goto __pyx_L19;
      }
      /*else*/ {

        /* "sklearn/tree/_tree.pyx":1493
 * 
 *                 else:
 *                     partition_end -= 1             # <<<<<<<<<<<<<<
 * 
 *                     tmp = samples[partition_end]
 */
        __pyx_v_partition_end = (__pyx_v_partition_end - 1);

        /* "sklearn/tree/_tree.pyx":1495
 *                     partition_end -= 1
 * 
 *                     tmp = samples[partition_end]             # <<<<<<<<<<<<<<
 *                     samples[partition_end] = samples[p]
 *                     samples[p] = tmp
 */
        __pyx_v_tmp = (__pyx_v_samples[__pyx_v_partition_end]);

        /* "sklearn/tree/_tree.pyx":1496
 * 
 *                     tmp = samples[partition_end]
 *                     samples[partition_end] = samples[p]             # <<<<<<<<<<<<<<
 *                     samples[p] = tmp
 * 
 */
        (__pyx_v_samples[__pyx_v_partition_end]) = (__pyx_v_samples[__pyx_v_p]);

        /* "sklearn/tree/_tree.pyx":1497
 *                     tmp = samples[partition_end]
 *                     samples[partition_end] = samples[p]
 *                     samples[p] = tmp             # <<<<<<<<<<<<<<
 * 
 *         # Respect invariant for constant features: the original order of
 */
        (__pyx_v_samples[__pyx_v_p]) = __pyx_v_tmp;
      }
      __pyx_L19:;
    }
    goto __pyx_L16;
  }
  __pyx_L16:;

  /* "sklearn/tree/_tree.pyx":1502
 *         # element in features[:n_known_constants] must be preserved for sibling
 *         # and child nodes
 *         memcpy(features, constant_features, sizeof(SIZE_t) * n_known_constants)             # <<<<<<<<<<<<<<
 * 
 *         # Copy newly found constant features
 */
  memcpy(__pyx_v_features, __pyx_v_constant_features, ((sizeof(__pyx_t_7sklearn_4tree_5_tree_SIZE_t)) * __pyx_v_n_known_constants));

  /* "sklearn/tree/_tree.pyx":1505
 * 
 *         # Copy newly found constant features
 *         memcpy(constant_features + n_known_constants,             # <<<<<<<<<<<<<<
 *                features + n_known_constants,
 *                sizeof(SIZE_t) * n_found_constants)
 */
  memcpy((__pyx_v_constant_features + __pyx_v_n_known_constants), (__pyx_v_features + __pyx_v_n_known_constants), ((sizeof(__pyx_t_7sklearn_4tree_5_tree_SIZE_t)) * __pyx_v_n_found_constants));

  /* "sklearn/tree/_tree.pyx":1510
 * 
 *         # Return values
 *         split[0] = best             # <<<<<<<<<<<<<<
 *         n_constant_features[0] = n_total_constants
 * 
 */
  (__pyx_v_split[0]) = __pyx_v_best;

  /* "sklearn/tree/_tree.pyx":1511
 *         # Return values
 *         split[0] = best
 *         n_constant_features[0] = n_total_constants             # <<<<<<<<<<<<<<
 * 
 * 
 */
  (__pyx_v_n_constant_features[0]) = __pyx_v_n_total_constants;

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 *         cdef unsigned char* sample_mask = self.sample_mask
 */
  __pyx_t_2 = __pyx_v_self->X_argsorted_stride;
  __pyx_v_X_argsorted_stride = __pyx_t_2;

  /* "sklearn/tree/_tree.pyx":1582
 *         cdef INT32_t* X_argsorted = self.X_argsorted_ptr
 *         cdef SIZE_t X_argsorted_stride = self.X_argsorted_stride
 *         cdef SIZE_t n_total_samples = self.n_total_samples             # <<<<<<<<<<<<<<
 *         cdef unsigned char* sample_mask = self.sample_mask
 * 
 */
  __pyx_t_2 = __pyx_v_self->n_total_samples;
  __pyx_v_n_total_samples = __pyx_t_2;

  /* "sklearn/tree/_tree.pyx":1583
 *         cdef SIZE_t X_argsorted_stride = self.X_argsorted_stride
 *         cdef SIZE_t n_total_samples = self.n_total_samples
 *         cdef unsigned char* sample_mask = self.sample_mask             # <<<<<<<<<<<<<<
 * 
 *         cdef SIZE_t max_features = self.max_features
 */
  __pyx_t_5 = __pyx_v_self->sample_mask;
  __pyx_v_sample_mask = __pyx_t_5;

  /* "sklearn/tree/_tree.pyx":1585
 *         cdef unsigned char* sample_mask = self.sample_mask
 * 
 *         cdef SIZE_t max_features = self.max_features             # <<<<<<<<<<<<<<
 *         cdef SIZE_t min_samples_leaf = self.min_samples_leaf
 *         cdef UINT32_t* random_state = &self.rand_r_state
 */
  __pyx_t_2 = __pyx_v_self->__pyx_base.max_features;
  __pyx_v_max_features = __pyx_t_2;

  /* "sklearn/tree/_tree.pyx":1586
 * 
 *         cdef SIZE_t max_features = self.max_features
 *         cdef SIZE_t min_samples_leaf = self.min_samples_leaf             # <<<<<<<<<<<<<<
 *         cdef UINT32_t* random_state = &self.rand_r_state
 * 
 */
  __pyx_t_2 = __pyx_v_self->__pyx_base.min_samples_leaf;
  __pyx_v_min_samples_leaf = __pyx_t_2;

  /* "sklearn/tree/_tree.pyx":1587
 *         cdef SIZE_t max_features = self.max_features
 *         cdef SIZE_t min_samples_leaf = self.min_samples_leaf
 *         cdef UINT32_t* random_state = &self.rand_r_state             # <<<<<<<<<<<<<<
 * 
 *         cdef SplitRecord best, current
 */
  __pyx_v_random_state = (&__pyx_v_self->__pyx_base.rand_r_state);

  /* "sklearn/tree/_tree.pyx":1591
 *         cdef SplitRecord best, current
 * 
 *         cdef SIZE_t f_i = n_features             # <<<<<<<<<<<<<<
 *         cdef SIZE_t f_j, p
 *         # Number of features discovered to be constant during the split search
 */
  __pyx_v_f_i = __pyx_v_n_features;

  /* "sklearn/tree/_tree.pyx":1594
 *         cdef SIZE_t f_j, p
 *         # Number of features discovered to be constant during the split search
 *         cdef SIZE_t n_found_constants = 0             # <<<<<<<<<<<<<<
 *         # Number of features known to be constant and drawn without replacement
 *         cdef SIZE_t n_drawn_constants = 0
 */
  __pyx_v_n_found_constants = 0;

  /* "sklearn/tree/_tree.pyx":1596
 *         cdef SIZE_t n_found_constants = 0
 *         # Number of features known to be constant and drawn without replacement
 *         cdef SIZE_t n_drawn_constants = 0             # <<<<<<<<<<<<<<
 *         cdef SIZE_t n_known_constants = n_constant_features[0]
 *         # n_total_constants = n_known_constants + n_found_constants
 */
  __pyx_v_n_drawn_constants = 0;

  /* "sklearn/tree/_tree.pyx":1597
 *         # Number of features known to be constant and drawn without replacement
 *         cdef SIZE_t n_drawn_constants = 0
 *         cdef SIZE_t n_known_constants = n_constant_features[0]             # <<<<<<<<<<<<<<
 *         # n_total_constants = n_known_constants + n_found_constants
 *         cdef SIZE_t n_total_constants = n_known_constants
 */
  __pyx_v_n_known_constants = (__pyx_v_n_constant_features[0]);

  /* "sklearn/tree/_tree.pyx":1599
 *         cdef SIZE_t n_known_constants = n_constant_features[0]
 *         # n_total_constants = n_known_constants + n_found_constants
 *         cdef SIZE_t n_total_constants = n_known_constants             # <<<<<<<<<<<<<<
 *         cdef SIZE_t n_visited_features = 0
 *         cdef SIZE_t partition_end
 */
  __pyx_v_n_total_constants = __pyx_v_n_known_constants;

  /* "sklearn/tree/_tree.pyx":1600
 *         # n_total_constants = n_known_constants + n_found_constants
 *         cdef SIZE_t n_total_constants = n_known_constants
 *         cdef SIZE_t n_visited_features = 0             # <<<<<<<<<<<<<<
 *         cdef SIZE_t partition_end
 *         cdef SIZE_t i, j
 */
  __pyx_v_n_visited_features = 0;

  /* "sklearn/tree/_tree.pyx":1604
 *         cdef SIZE_t i, j
 * 
 *         _init_split(&best, end)             # <<<<<<<<<<<<<<
 * 
 *         # Set sample mask
 */
  __pyx_f_7sklearn_4tree_5_tree__init_split((&__pyx_v_best), __pyx_v_end);

  /* "sklearn/tree/_tree.pyx":1607
 * 
 *         # Set sample mask
 *         for p in range(start, end):             # <<<<<<<<<<<<<<
 *             sample_mask[samples[p]] = 1
 * 
 */
  __pyx_t_2 = __pyx_v_end;
  for (__pyx_t_6 = __pyx_v_start; __pyx_t_6 < __pyx_t_2; __pyx_t_6+=1) {
    __pyx_v_p = __pyx_t_6;

    /* "sklearn/tree/_tree.pyx":1608
 *         # Set sample mask
 *         for p in range(start, end):
 *             sample_mask[samples[p]] = 1             # <<<<<<<<<<<<<<
 * 
 *         # Sample up to max_features without replacement using a
 */
    (__pyx_v_sample_mask[(__pyx_v_samples[__pyx_v_p])]) = 1;
  }

  /* "sklearn/tree/_tree.pyx":1619
 *         # newly discovered constant features to spare computation on descendant
 *         # nodes.
 *         while (f_i > n_total_constants and  # Stop early if remaining features             # <<<<<<<<<<<<<<
 *                                             # are constant
 *                 (n_visited_features < max_features or
 */
  while (1) {
    __pyx_t_7 = ((__pyx_v_f_i > __pyx_v_n_total_constants) != 0);
    if (__pyx_t_7) {

      /* "sklearn/tree/_tree.pyx":1621
 *         while (f_i > n_total_constants and  # Stop early if remaining features
 *                                             # are constant
 *                 (n_visited_features < max_features or             # <<<<<<<<<<<<<<
 *                  # At least one drawn features must be non constant
 *                  n_visited_features <= n_found_constants + n_drawn_constants)):
 */
      __pyx_t_8 = ((__pyx_v_n_visited_features < __pyx_v_max_features) != 0);
      if (!__pyx_t_8) {

        /* "sklearn/tree/_tree.pyx":1623
 *                 (n_visited_features < max_features or
 *                  # At least one drawn features must be non constant
 *                  n_visited_features <= n_found_constants + n_drawn_constants)):             # <<<<<<<<<<<<<<
 *             n_visited_features += 1
 * 
 */
        __pyx_t_9 = ((__pyx_v_n_visited_features <= (__pyx_v_n_found_constants + __pyx_v_n_drawn_constants)) != 0);
        __pyx_t_10 = __pyx_t_9;
      } else {
        __pyx_t_10 = __pyx_t_8;
      }
      __pyx_t_8 = __pyx_t_10;
    } else {
      __pyx_t_8 = __pyx_t_7;
    }
    if (!__pyx_t_8) break;

    /* "sklearn/tree/_tree.pyx":1624
 *                  # At least one drawn features must be non constant
 *                  n_visited_features <= n_found_constants + n_drawn_constants)):
 *             n_visited_features += 1             # <<<<<<<<<<<<<<
 * 
 *             # Loop invariant: elements of features in
 */
    __pyx_v_n_visited_features = (__pyx_v_n_visited_features + 1);

    /* "sklearn/tree/_tree.pyx":1639
 *             # Draw a feature at random
 *             f_j = rand_int(f_i - n_drawn_constants - n_found_constants,
 *                            random_state) + n_drawn_constants             # <<<<<<<<<<<<<<
 * 
 *             if f_j < n_known_constants:
 */
    __pyx_v_f_j = (__pyx_f_7sklearn_4tree_5_tree_rand_int(((__pyx_v_f_i - __pyx_v_n_drawn_constants) - __pyx_v_n_found_constants), __pyx_v_random_state) + __pyx_v_n_drawn_constants);

    /* "sklearn/tree/_tree.pyx":1641
 *                            random_state) + n_drawn_constants
 * 
 *             if f_j < n_known_constants:             # <<<<<<<<<<<<<<
 *                 # f_j is in [n_drawn_constants, n_known_constants[
 *                 tmp = features[f_j]
 */
    __pyx_t_8 = ((__pyx_v_f_j < __pyx_v_n_known_constants) != 0);
    if (__pyx_t_8) {

      /* "sklearn/tree/_tree.pyx":1643
 *             if f_j < n_known_constants:
 *                 # f_j is in [n_drawn_constants, n_known_constants[
 *                 tmp = features[f_j]             # <<<<<<<<<<<<<<
 *                 features[f_j] = features[n_drawn_constants]
 *                 features[n_drawn_constants] = tmp
 */
      __pyx_v_tmp = (__pyx_v_features[__pyx_v_f_j]);

      /* "sklearn/tree/_tree.pyx":1644
 *                 # f_j is in [n_drawn_constants, n_known_constants[
 *                 tmp = features[f_j]
 *                 features[f_j] = features[n_drawn_constants]             # <<<<<<<<<<<<<<
 *                 features[n_drawn_constants] = tmp
 * 
 */
      (__pyx_v_features[__pyx_v_f_j]) = (__pyx_v_features[__pyx_v_n_drawn_constants]);

      /* "sklearn/tree/_tree.pyx":1645
 *                 tmp = features[f_j]
 *                 features[f_j] = features[n_drawn_constants]
 *                 features[n_drawn_constants] = tmp             # <<<<<<<<<<<<<<
 * 
 *                 n_drawn_constants += 1
 */
      (__pyx_v_features[__pyx_v_n_drawn_constants]) = __pyx_v_tmp;

      /* "sklearn/tree/_tree.pyx":1647
 *                 features[n_drawn_constants] = tmp
 * 
 *                 n_drawn_constants += 1             # <<<<<<<<<<<<<<
 * 
 *             else:
 */
      __pyx_v_n_drawn_constants = (__pyx_v_n_drawn_constants + 1);
      goto __pyx_L7;
    }
    /*else*/ {

      /* "sklearn/tree/_tree.pyx":1651
 *             else:
 *                 # f_j in the interval [n_known_constants, f_i - n_found_constants[
 *                 f_j += n_found_constants             # <<<<<<<<<<<<<<
 *                 # f_j in the interval [n_total_constants, f_i[
 * 
 */
      __pyx_v_f_j = (__pyx_v_f_j + __pyx_v_n_found_constants);

      /* "sklearn/tree/_tree.pyx":1654
 *                 # f_j in the interval [n_total_constants, f_i[
 * 
 *                 current.feature = features[f_j]             # <<<<<<<<<<<<<<
 * 
 *                 # Extract ordering from X_argsorted
 */
      __pyx_v_current.feature = (__pyx_v_features[__pyx_v_f_j]);

      /* "sklearn/tree/_tree.pyx":1657
 * 
 *                 # Extract ordering from X_argsorted
 *                 p = start             # <<<<<<<<<<<<<<
 * 
 *                 for i in range(n_total_samples):
 */
      __pyx_v_p = __pyx_v_start;

      /* "sklearn/tree/_tree.pyx":1659
 *                 p = start
 * 
 *                 for i in range(n_total_samples):             # <<<<<<<<<<<<<<
 *                     j = X_argsorted[X_argsorted_stride * current.feature + i]
 *                     if sample_mask[j] == 1:
 */
      __pyx_t_2 = __pyx_v_n_total_samples;
      for (__pyx_t_6 = 0; __pyx_t_6 < __pyx_t_2; __pyx_t_6+=1) {
        __pyx_v_i = __pyx_t_6;

        /* "sklearn/tree/_tree.pyx":1660
 * 
 *                 for i in range(n_total_samples):
 *                     j = X_argsorted[X_argsorted_stride * current.feature + i]             # <<<<<<<<<<<<<<
 *                     if sample_mask[j] == 1:
 *                         samples[p] = j
 */
        __pyx_v_j = (__pyx_v_X_argsorted[((__pyx_v_X_argsorted_stride * __pyx_v_current.feature) + __pyx_v_i)]);

        /* "sklearn/tree/_tree.pyx":1661
 *                 for i in range(n_total_samples):
 *                     j = X_argsorted[X_argsorted_stride * current.feature + i]
 *                     if sample_mask[j] == 1:             # <<<<<<<<<<<<<<
 *                         samples[p] = j
 *                         Xf[p] = X[X_sample_stride * j +
 */
        __pyx_t_8 = (((__pyx_v_sample_mask[__pyx_v_j]) == 1) != 0);
        if (__pyx_t_8) {

          /* "sklearn/tree/_tree.pyx":1662
 *                     j = X_argsorted[X_argsorted_stride * current.feature + i]
 *                     if sample_mask[j] == 1:
 *                         samples[p] = j             # <<<<<<<<<<<<<<
 *                         Xf[p] = X[X_sample_stride * j +
 *                                   X_fx_stride * current.feature]
 */
          (__pyx_v_samples[__pyx_v_p]) = __pyx_v_j;

          /* "sklearn/tree/_tree.pyx":1663
 *                     if sample_mask[j] == 1:
 *                         samples[p] = j
 *                         Xf[p] = X[X_sample_stride * j +             # <<<<<<<<<<<<<<
 *                                   X_fx_stride * current.feature]
 *                         p += 1
 */
          (__pyx_v_Xf[__pyx_v_p]) = (__pyx_v_X[((__pyx_v_X_sample_stride * __pyx_v_j) + (__pyx_v_X_fx_stride * __pyx_v_current.feature))]);

          /* "sklearn/tree/_tree.pyx":1665
 *                         Xf[p] = X[X_sample_stride * j +
 *                                   X_fx_stride * current.feature]
 *                         p += 1             # <<<<<<<<<<<<<<
 * 
 *                 # Evaluate all splits
 */
          __pyx_v_p = (__pyx_v_p + 1);
          goto __pyx_L10;
        }
        __pyx_L10:;
      }

      /* "sklearn/tree/_tree.pyx":1668
 * 
 *                 # Evaluate all splits
 *                 if Xf[end - 1] <= Xf[start] + FEATURE_THRESHOLD:             # <<<<<<<<<<<<<<
 *                     features[f_j] = features[n_total_constants]
 *                     features[n_total_constants] = current.feature
 */
      __pyx_t_8 = (((__pyx_v_Xf[(__pyx_v_end - 1)]) <= ((__pyx_v_Xf[__pyx_v_start]) + __pyx_v_7sklearn_4tree_5_tree_FEATURE_THRESHOLD)) != 0);
      if (__pyx_t_8) {

        /* "sklearn/tree/_tree.pyx":1669
 *                 # Evaluate all splits
 *                 if Xf[end - 1] <= Xf[start] + FEATURE_THRESHOLD:
 *                     features[f_j] = features[n_total_constants]             # <<<<<<<<<<<<<<
 *                     features[n_total_constants] = current.feature
 * 
 */
        (__pyx_v_features[__pyx_v_f_j]) = (__pyx_v_features[__pyx_v_n_total_constants]);

        /* "sklearn/tree/_tree.pyx":1670
 *                 if Xf[end - 1] <= Xf[start] + FEATURE_THRESHOLD:
 *                     features[f_j] = features[n_total_constants]
 *                     features[n_total_constants] = current.feature             # <<<<<<<<<<<<<<
 * 
 *                     n_found_constants += 1
 */
        __pyx_t_2 = __pyx_v_current.feature;
        (__pyx_v_features[__pyx_v_n_total_constants]) = __pyx_t_2;

        /* "sklearn/tree/_tree.pyx":1672
 *                     features[n_total_constants] = current.feature
 * 
 *                     n_found_constants += 1             # <<<<<<<<<<<<<<
 *                     n_total_constants += 1
 * 
 */
        __pyx_v_n_found_constants = (__pyx_v_n_found_constants + 1);

        /* "sklearn/tree/_tree.pyx":1673
 * 
 *                     n_found_constants += 1
 *                     n_total_constants += 1             # <<<<<<<<<<<<<<
 * 
 *                 else:
 */
        __pyx_v_n_total_constants = (__pyx_v_n_total_constants + 1);
        goto __pyx_L11;
      }
      /*else*/ {

        /* "sklearn/tree/_tree.pyx":1676
 * 
 *                 else:
 *                     f_i -= 1             # <<<<<<<<<<<<<<
 *                     features[f_i], features[f_j] = features[f_j], features[f_i]
 * 
 */
        __pyx_v_f_i = (__pyx_v_f_i - 1);

        /* "sklearn/tree/_tree.pyx":1677
 *                 else:
 *                     f_i -= 1
 *                     features[f_i], features[f_j] = features[f_j], features[f_i]             # <<<<<<<<<<<<<<
 * 
 *                     self.criterion.reset()
 */
        __pyx_t_2 = (__pyx_v_features[__pyx_v_f_j]);
        __pyx_t_6 = (__pyx_v_features[__pyx_v_f_i]);
        (__pyx_v_features[__pyx_v_f_i]) = __pyx_t_2;
        (__pyx_v_features[__pyx_v_f_j]) = __pyx_t_6;

        /* "sklearn/tree/_tree.pyx":1679
 *                     features[f_i], features[f_j] = features[f_j], features[f_i]
 * 
 *                     self.criterion.reset()             # <<<<<<<<<<<<<<
 *                     p = start
 * 
 */
        ((struct __pyx_vtabstruct_7sklearn_4tree_5_tree_Criterion *)__pyx_v_self->__pyx_base.criterion->__pyx_vtab)->reset(__pyx_v_self->__pyx_base.criterion);

        /* "sklearn/tree/_tree.pyx":1680
 * 
 *                     self.criterion.reset()
 *                     p = start             # <<<<<<<<<<<<<<
 * 
 *                     while p < end:
 */
        __pyx_v_p = __pyx_v_start;

        /* "sklearn/tree/_tree.pyx":1682
 *                     p = start
 * 
 *                     while p < end:             # <<<<<<<<<<<<<<
 *                         while (p + 1 < end and
 *                                Xf[p + 1] <= Xf[p] + FEATURE_THRESHOLD):
 */
        while (1) {
          __pyx_t_8 = ((__pyx_v_p < __pyx_v_end) != 0);
          if (!__pyx_t_8) break;

          /* "sklearn/tree/_tree.pyx":1683
 * 
 *                     while p < end:
 *                         while (p + 1 < end and             # <<<<<<<<<<<<<<
 *                                Xf[p + 1] <= Xf[p] + FEATURE_THRESHOLD):
 *                             p += 1
 */
          while (1) {
            __pyx_t_8 = (((__pyx_v_p + 1) < __pyx_v_end) != 0);
            if (__pyx_t_8) {

              /* "sklearn/tree/_tree.pyx":1684
 *                     while p < end:
 *                         while (p + 1 < end and
 *                                Xf[p + 1] <= Xf[p] + FEATURE_THRESHOLD):             # <<<<<<<<<<<<<<
 *                             p += 1
 * 
 */
              __pyx_t_7 = (((__pyx_v_Xf[(__pyx_v_p + 1)]) <= ((__pyx_v_Xf[__pyx_v_p]) + __pyx_v_7sklearn_4tree_5_tree_FEATURE_THRESHOLD)) != 0);
              __pyx_t_10 = __pyx_t_7;
            } else {
              __pyx_t_10 = __pyx_t_8;
            }
            if (!__pyx_t_10) break;

            /* "sklearn/tree/_tree.pyx":1685
 *                         while (p + 1 < end and
 *                                Xf[p + 1] <= Xf[p] + FEATURE_THRESHOLD):
 *                             p += 1             # <<<<<<<<<<<<<<
 * 
 *                         # (p + 1 >= end) or (X[samples[p + 1], current.feature] >
 */
            __pyx_v_p = (__pyx_v_p + 1);
          }

          /* "sklearn/tree/_tree.pyx":1689
 *                         # (p + 1 >= end) or (X[samples[p + 1], current.feature] >
 *                         #                    X[samples[p], current.feature])
 *                         p += 1             # <<<<<<<<<<<<<<
 *                         # (p >= end) or (X[samples[p], current.feature] >
 *                         #                X[samples[p - 1], current.feature])
 */
          __pyx_v_p = (__pyx_v_p + 1);

          /* "sklearn/tree/_tree.pyx":1693
 *                         #                X[samples[p - 1], current.feature])
 * 
 *                         if p < end:             # <<<<<<<<<<<<<<
 *                             current.pos = p
 * 
 */
          __pyx_t_10 = ((__pyx_v_p < __pyx_v_end) != 0);
          if (__pyx_t_10) {

            /* "sklearn/tree/_tree.pyx":1694
 * 
 *                         if p < end:
 *                             current.pos = p             # <<<<<<<<<<<<<<
 * 
 *                             # Reject if min_samples_leaf is not guaranteed
 */
            __pyx_v_current.pos = __pyx_v_p;

            /* "sklearn/tree/_tree.pyx":1697
 * 
 *                             # Reject if min_samples_leaf is not guaranteed
 *                             if (((current.pos - start) < min_samples_leaf) or             # <<<<<<<<<<<<<<
 *                                     ((end - current.pos) < min_samples_leaf)):
 *                                 continue
 */
            __pyx_t_10 = (((__pyx_v_current.pos - __pyx_v_start) < __pyx_v_min_samples_leaf) != 0);
            if (!__pyx_t_10) {

              /* "sklearn/tree/_tree.pyx":1698
 *                             # Reject if min_samples_leaf is not guaranteed
 *                             if (((current.pos - start) < min_samples_leaf) or
 *                                     ((end - current.pos) < min_samples_leaf)):             # <<<<<<<<<<<<<<
 *                                 continue
 * 
 */
              __pyx_t_8 = (((__pyx_v_end - __pyx_v_current.pos) < __pyx_v_min_samples_leaf) != 0);
              __pyx_t_7 = __pyx_t_8;
            } else {
              __pyx_t_7 = __pyx_t_10;
            }
            if (__pyx_t_7) {

              /* "sklearn/tree/_tree.pyx":1699
 *                             if (((current.pos - start) < min_samples_leaf) or
 *                                     ((end - current.pos) < min_samples_leaf)):
 *                                 continue             # <<<<<<<<<<<<<<
 * 
 *                             self.criterion.update(current.pos)
 */
              goto __pyx_L12_continue;
            }

            /* "sklearn/tree/_tree.pyx":1701
 *                                 continue
 * 
 *                             self.criterion.update(current.pos)             # <<<<<<<<<<<<<<
 *                             current.improvement = self.criterion.impurity_improvement(impurity)
 * 
 */
            ((struct __pyx_vtabstruct_7sklearn_4tree_5_tree_Criterion *)__pyx_v_self->__pyx_base.criterion->__pyx_vtab)->update(__pyx_v_self->__pyx_base.criterion, __pyx_v_current.pos);

            /* "sklearn/tree/_tree.pyx":1702
 * 
 *                             self.criterion.update(current.pos)
 *                             current.improvement = self.criterion.impurity_improvement(impurity)             # <<<<<<<<<<<<<<
 * 
 *                             if current.improvement > best.improvement:
 */
            __pyx_v_current.improvement = ((struct __pyx_vtabstruct_7sklearn_4tree_5_tree_Criterion *)__pyx_v_self->__pyx_base.criterion->__pyx_vtab)->impurity_improvement(__pyx_v_self->__pyx_base.criterion, __pyx_v_impurity);

            /* "sklearn/tree/_tree.pyx":1704
 *                             current.improvement = self.criterion.impurity_improvement(impurity)
 * 
 *                             if current.improvement > best.improvement:             # <<<<<<<<<<<<<<
 *                                 self.criterion.children_impurity(&current.impurity_left,
 *                                                                  &current.impurity_right)
 */
            __pyx_t_7 = ((__pyx_v_current.improvement > __pyx_v_best.improvement) != 0);
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 *         if rc == -1:             # <<<<<<<<<<<<<<
 *             # got return code -1 - out-of-memory
 *             raise MemoryError()
 */
  __pyx_t_6 = ((__pyx_v_rc == -1) != 0);
  if (__pyx_t_6) {

    /* "sklearn/tree/_tree.pyx":1837
 *         if rc == -1:
 *             # got return code -1 - out-of-memory
 *             raise MemoryError()             # <<<<<<<<<<<<<<
 * 
 *         with nogil:
 */
    PyErr_NoMemory(); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1837; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
  }

  /* "sklearn/tree/_tree.pyx":1839
 *             raise MemoryError()
 * 
 *         with nogil:             # <<<<<<<<<<<<<<
 *             while not stack.is_empty():
 *                 stack.pop(&stack_record)
 */
  {
      #ifdef WITH_THREAD
      PyThreadState *_save;
      Py_UNBLOCK_THREADS
      #endif
      /*try:*/ {

        /* "sklearn/tree/_tree.pyx":1840
 * 
 *         with nogil:
 *             while not stack.is_empty():             # <<<<<<<<<<<<<<
 *                 stack.pop(&stack_record)
 * 
 */
        while (1) {
          __pyx_t_6 = ((!(((struct __pyx_vtabstruct_7sklearn_4tree_6_utils_Stack *)__pyx_v_stack->__pyx_vtab)->is_empty(__pyx_v_stack) != 0)) != 0);
          if (!__pyx_t_6) break;

          /* "sklearn/tree/_tree.pyx":1841
 *         with nogil:
 *             while not stack.is_empty():
 *                 stack.pop(&stack_record)             # <<<<<<<<<<<<<<
 * 
 *                 start = stack_record.start
 */
          ((struct __pyx_vtabstruct_7sklearn_4tree_6_utils_Stack *)__pyx_v_stack->__pyx_vtab)->pop(__pyx_v_stack, (&__pyx_v_stack_record));

          /* "sklearn/tree/_tree.pyx":1843
 *                 stack.pop(&stack_record)
 * 
 *                 start = stack_record.start             # <<<<<<<<<<<<<<
 *                 end = stack_record.end
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 */
          __pyx_t_9 = __pyx_v_stack_record.start;
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          /* "sklearn/tree/_tree.pyx":1844
 * 
 *                 start = stack_record.start
 *                 end = stack_record.end             # <<<<<<<<<<<<<<
 *                 depth = stack_record.depth
 *                 parent = stack_record.parent
 */
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 *                 start = stack_record.start
 *                 end = stack_record.end
 *                 depth = stack_record.depth             # <<<<<<<<<<<<<<
 *                 parent = stack_record.parent
 *                 is_left = stack_record.is_left
 */
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 *                 depth = stack_record.depth
 *                 parent = stack_record.parent             # <<<<<<<<<<<<<<
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 *                 impurity = stack_record.impurity
 */
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          /* "sklearn/tree/_tree.pyx":1847
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 *                 parent = stack_record.parent
 *                 is_left = stack_record.is_left             # <<<<<<<<<<<<<<
 *                 impurity = stack_record.impurity
 *                 n_constant_features = stack_record.n_constant_features
 */
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 *                 parent = stack_record.parent
 *                 is_left = stack_record.is_left
 *                 impurity = stack_record.impurity             # <<<<<<<<<<<<<<
 *                 n_constant_features = stack_record.n_constant_features
 * 
 */
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          /* "sklearn/tree/_tree.pyx":1849
 *                 is_left = stack_record.is_left
 *                 impurity = stack_record.impurity
 *                 n_constant_features = stack_record.n_constant_features             # <<<<<<<<<<<<<<
 * 
 *                 n_node_samples = end - start
 */
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          /* "sklearn/tree/_tree.pyx":1851
 *                 n_constant_features = stack_record.n_constant_features
 * 
 *                 n_node_samples = end - start             # <<<<<<<<<<<<<<
 *                 is_leaf = ((depth >= max_depth) or
 *                            (n_node_samples < min_samples_split) or
 */
          __pyx_v_n_node_samples = (__pyx_v_end - __pyx_v_start);

          /* "sklearn/tree/_tree.pyx":1852
 * 
 *                 n_node_samples = end - start
 *                 is_leaf = ((depth >= max_depth) or             # <<<<<<<<<<<<<<
 *                            (n_node_samples < min_samples_split) or
 *                            (n_node_samples < 2 * min_samples_leaf))
 */
          __pyx_t_6 = (__pyx_v_depth >= __pyx_v_max_depth);
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            /* "sklearn/tree/_tree.pyx":1853
 *                 n_node_samples = end - start
 *                 is_leaf = ((depth >= max_depth) or
 *                            (n_node_samples < min_samples_split) or             # <<<<<<<<<<<<<<
 *                            (n_node_samples < 2 * min_samples_leaf))
 * 
 */
            __pyx_t_4 = (__pyx_v_n_node_samples < __pyx_v_min_samples_split);
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              /* "sklearn/tree/_tree.pyx":1854
 *                 is_leaf = ((depth >= max_depth) or
 *                            (n_node_samples < min_samples_split) or
 *                            (n_node_samples < 2 * min_samples_leaf))             # <<<<<<<<<<<<<<
 * 
 *                 splitter.node_reset(start, end, &weighted_n_node_samples)
 */
              __pyx_t_7 = (__pyx_v_n_node_samples < (2 * __pyx_v_min_samples_leaf));
              __pyx_t_11 = __pyx_t_7;
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              __pyx_t_11 = __pyx_t_4;
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            __pyx_t_4 = __pyx_t_6;
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          /* "sklearn/tree/_tree.pyx":1856
 *                            (n_node_samples < 2 * min_samples_leaf))
 * 
 *                 splitter.node_reset(start, end, &weighted_n_node_samples)             # <<<<<<<<<<<<<<
 * 
 *                 if first:
 */
          ((struct __pyx_vtabstruct_7sklearn_4tree_5_tree_Splitter *)__pyx_v_splitter->__pyx_vtab)->node_reset(__pyx_v_splitter, __pyx_v_start, __pyx_v_end, (&__pyx_v_weighted_n_node_samples));

          /* "sklearn/tree/_tree.pyx":1858
 *                 splitter.node_reset(start, end, &weighted_n_node_samples)
 * 
 *                 if first:             # <<<<<<<<<<<<<<
 *                     impurity = splitter.node_impurity()
 *                     first = 0
 */
          __pyx_t_4 = (__pyx_v_first != 0);
          if (__pyx_t_4) {

            /* "sklearn/tree/_tree.pyx":1859
 * 
 *                 if first:
 *                     impurity = splitter.node_impurity()             # <<<<<<<<<<<<<<
 *                     first = 0
 * 
 */
            __pyx_v_impurity = ((struct __pyx_vtabstruct_7sklearn_4tree_5_tree_Splitter *)__pyx_v_splitter->__pyx_vtab)->node_impurity(__pyx_v_splitter);

            /* "sklearn/tree/_tree.pyx":1860
 *                 if first:
 *                     impurity = splitter.node_impurity()
 *                     first = 0             # <<<<<<<<<<<<<<
 * 
 *                 is_leaf = is_leaf or (impurity <= MIN_IMPURITY_SPLIT)
 */
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          /* "sklearn/tree/_tree.pyx":1862
 *                     first = 0
 * 
 *                 is_leaf = is_leaf or (impurity <= MIN_IMPURITY_SPLIT)             # <<<<<<<<<<<<<<
 * 
 *                 if not is_leaf:
 */
          if (!__pyx_v_is_leaf) {
            __pyx_t_4 = (__pyx_v_impurity <= __pyx_v_7sklearn_4tree_5_tree_MIN_IMPURITY_SPLIT);
            __pyx_t_6 = __pyx_t_4;
          } else {
            __pyx_t_6 = __pyx_v_is_leaf;
          }
          __pyx_v_is_leaf = __pyx_t_6;

          /* "sklearn/tree/_tree.pyx":1864
 *                 is_leaf = is_leaf or (impurity <= MIN_IMPURITY_SPLIT)
 * 
 *                 if not is_leaf:             # <<<<<<<<<<<<<<
 *                     splitter.node_split(impurity, &split, &n_constant_features)
 *                     is_leaf = is_leaf or (split.pos >= end)
 */
          __pyx_t_6 = ((!(__pyx_v_is_leaf != 0)) != 0);
          if (__pyx_t_6) {

            /* "sklearn/tree/_tree.pyx":1865
 * 
 *                 if not is_leaf:
 *                     splitter.node_split(impurity, &split, &n_constant_features)             # <<<<<<<<<<<<<<
 *                     is_leaf = is_leaf or (split.pos >= end)
 * 
 */
            ((struct __pyx_vtabstruct_7sklearn_4tree_5_tree_Splitter *)__pyx_v_splitter->__pyx_vtab)->node_split(__pyx_v_splitter, __pyx_v_impurity, (&__pyx_v_split), (&__pyx_v_n_constant_features));

            /* "sklearn/tree/_tree.pyx":1866
 *                 if not is_leaf:
 *                     splitter.node_split(impurity, &split, &n_constant_features)
 *                     is_leaf = is_leaf or (split.pos >= end)             # <<<<<<<<<<<<<<
 * 
 *                 node_id = tree._add_node(parent, is_left, is_leaf, split.feature,
 */
            if (!__pyx_v_is_leaf) {
              __pyx_t_6 = (__pyx_v_split.pos >= __pyx_v_end);
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            } else {
              __pyx_t_4 = __pyx_v_is_leaf;
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          /* "sklearn/tree/_tree.pyx":1868
 *                     is_leaf = is_leaf or (split.pos >= end)
 * 
 *                 node_id = tree._add_node(parent, is_left, is_leaf, split.feature,             # <<<<<<<<<<<<<<
 *                                          split.threshold, impurity, n_node_samples,
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 */
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          /* "sklearn/tree/_tree.pyx":1872
 *                                          weighted_n_node_samples)
 * 
 *                 if is_leaf:             # <<<<<<<<<<<<<<
 *                     # Don't store value for internal nodes
 *                     splitter.node_value(tree.value +
 */
          __pyx_t_4 = (__pyx_v_is_leaf != 0);
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            /* "sklearn/tree/_tree.pyx":1874
 *                 if is_leaf:
 *                     # Don't store value for internal nodes
 *                     splitter.node_value(tree.value +             # <<<<<<<<<<<<<<
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 * 
 */
            ((struct __pyx_vtabstruct_7sklearn_4tree_5_tree_Splitter *)__pyx_v_splitter->__pyx_vtab)->node_value(__pyx_v_splitter, (__pyx_v_tree->value + (__pyx_v_node_id * __pyx_v_tree->value_stride)));
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 *                                     split.impurity_right, n_constant_features)
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 */
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            /* "sklearn/tree/_tree.pyx":1881
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 * 
 */
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              /* "sklearn/tree/_tree.pyx":1882
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            /* "sklearn/tree/_tree.pyx":1885
 * 
 *                     # Push left child on stack
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            /* "sklearn/tree/_tree.pyx":1887
 *                     rc = stack.push(start, split.pos, depth + 1, node_id, 1,
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 * 
 */
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              /* "sklearn/tree/_tree.pyx":1888
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 *                     if rc == -1:
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 * 
 *                 if depth > max_depth_seen:
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          /* "sklearn/tree/_tree.pyx":1890
 *                         break
 * 
 *                 if depth > max_depth_seen:             # <<<<<<<<<<<<<<
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 * 
 */
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            /* "sklearn/tree/_tree.pyx":1891
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 * 
 *             if rc >= 0:
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 * 
 *             if rc >= 0:             # <<<<<<<<<<<<<<
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 * 
 */
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          /* "sklearn/tree/_tree.pyx":1894
 * 
 *             if rc >= 0:
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 * 
 *             if rc >= 0:
 */
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 * 
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 */
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 * 
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 *         self.max_depth = max_depth
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 *     cpdef build(self, Tree tree, np.ndarray X, np.ndarray y,             # <<<<<<<<<<<<<<
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 *         # Parameters
 *         cdef Splitter splitter = self.splitter
 *         cdef SIZE_t max_leaf_nodes = self.max_leaf_nodes             # <<<<<<<<<<<<<<
 *         cdef SIZE_t min_samples_leaf = self.min_samples_leaf
 *         cdef SIZE_t min_samples_split = self.min_samples_split
 */
  __pyx_t_8 = __pyx_v_self->max_leaf_nodes;
  __pyx_v_max_leaf_nodes = __pyx_t_8;

  /* "sklearn/tree/_tree.pyx":1955
 *         cdef Splitter splitter = self.splitter
 *         cdef SIZE_t max_leaf_nodes = self.max_leaf_nodes
 *         cdef SIZE_t min_samples_leaf = self.min_samples_leaf             # <<<<<<<<<<<<<<
 *         cdef SIZE_t min_samples_split = self.min_samples_split
 * 
 */
  __pyx_t_8 = __pyx_v_self->__pyx_base.min_samples_leaf;
  __pyx_v_min_samples_leaf = __pyx_t_8;

  /* "sklearn/tree/_tree.pyx":1956
 *         cdef SIZE_t max_leaf_nodes = self.max_leaf_nodes
 *         cdef SIZE_t min_samples_leaf = self.min_samples_leaf
 *         cdef SIZE_t min_samples_split = self.min_samples_split             # <<<<<<<<<<<<<<
 * 
 *         # Recursive partition (without actual recursion)
 */
  __pyx_t_8 = __pyx_v_self->__pyx_base.min_samples_split;
  __pyx_v_min_samples_split = __pyx_t_8;

  /* "sklearn/tree/_tree.pyx":1959
 * 
 *         # Recursive partition (without actual recursion)
 *         splitter.init(X, y, sample_weight_ptr)             # <<<<<<<<<<<<<<
 * 
 *         cdef PriorityHeap frontier = PriorityHeap(INITIAL_STACK_SIZE)
 */
  ((struct __pyx_vtabstruct_7sklearn_4tree_5_tree_Splitter *)__pyx_v_splitter->__pyx_vtab)->init(__pyx_v_splitter, __pyx_v_X, __pyx_v_y, __pyx_v_sample_weight_ptr);

  /* "sklearn/tree/_tree.pyx":1961
 *         splitter.init(X, y, sample_weight_ptr)
 * 
 *         cdef PriorityHeap frontier = PriorityHeap(INITIAL_STACK_SIZE)             # <<<<<<<<<<<<<<
 *         cdef PriorityHeapRecord record
 *         cdef PriorityHeapRecord split_node_left
 */
  __pyx_t_2 = __Pyx_PyInt_From_Py_intptr_t(__pyx_v_7sklearn_4tree_5_tree_INITIAL_STACK_SIZE); if (unlikely(!__pyx_t_2)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1961; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
  __Pyx_GOTREF(__pyx_t_2);
  __pyx_t_3 = PyTuple_New(1); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1961; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
  __Pyx_GOTREF(__pyx_t_3);
  PyTuple_SET_ITEM(__pyx_t_3, 0, __pyx_t_2);
  __Pyx_GIVEREF(__pyx_t_2);
  __pyx_t_2 = 0;
  __pyx_t_2 = __Pyx_PyObject_Call(((PyObject *)((PyObject*)__pyx_ptype_7sklearn_4tree_6_utils_PriorityHeap)), __pyx_t_3, NULL); if (unlikely(!__pyx_t_2)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1961; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
  __Pyx_GOTREF(__pyx_t_2);
  __Pyx_DECREF(__pyx_t_3); __pyx_t_3 = 0;
  __pyx_v_frontier = ((struct __pyx_obj_7sklearn_4tree_6_utils_PriorityHeap *)__pyx_t_2);
  __pyx_t_2 = 0;

  /* "sklearn/tree/_tree.pyx":1966
 *         cdef PriorityHeapRecord split_node_right
 * 
 *         cdef SIZE_t n_node_samples = splitter.n_samples             # <<<<<<<<<<<<<<
 *         cdef int max_split_nodes = max_leaf_nodes - 1
 *         cdef bint is_leaf
 */
  __pyx_t_8 = __pyx_v_splitter->n_samples;
  __pyx_v_n_node_samples = __pyx_t_8;

  /* "sklearn/tree/_tree.pyx":1967
 * 
 *         cdef SIZE_t n_node_samples = splitter.n_samples
 *         cdef int max_split_nodes = max_leaf_nodes - 1             # <<<<<<<<<<<<<<
 *         cdef bint is_leaf
 *         cdef SIZE_t max_depth_seen = -1
 */
  __pyx_v_max_split_nodes = (__pyx_v_max_leaf_nodes - 1);

  /* "sklearn/tree/_tree.pyx":1969
 *         cdef int max_split_nodes = max_leaf_nodes - 1
 *         cdef bint is_leaf
 *         cdef SIZE_t max_depth_seen = -1             # <<<<<<<<<<<<<<
 *         cdef int rc = 0
 *         cdef Node* node
 */
  __pyx_v_max_depth_seen = -1;

  /* "sklearn/tree/_tree.pyx":1970
 *         cdef bint is_leaf
 *         cdef SIZE_t max_depth_seen = -1
 *         cdef int rc = 0             # <<<<<<<<<<<<<<
 *         cdef Node* node
 * 
 */
  __pyx_v_rc = 0;

  /* "sklearn/tree/_tree.pyx":1974
 * 
 *         # Initial capacity
 *         cdef int init_capacity = max_split_nodes + max_leaf_nodes             # <<<<<<<<<<<<<<
 *         tree._resize(init_capacity)
 * 
 */
  __pyx_v_init_capacity = (__pyx_v_max_split_nodes + __pyx_v_max_leaf_nodes);

  /* "sklearn/tree/_tree.pyx":1975
 *         # Initial capacity
 *         cdef int init_capacity = max_split_nodes + max_leaf_nodes
 *         tree._resize(init_capacity)             # <<<<<<<<<<<<<<
 * 
 *         with nogil:
 */
  ((struct __pyx_vtabstruct_7sklearn_4tree_5_tree_Tree *)__pyx_v_tree->__pyx_vtab)->_resize(__pyx_v_tree, __pyx_v_init_capacity);

  /* "sklearn/tree/_tree.pyx":1977
 *         tree._resize(init_capacity)
 * 
 *         with nogil:             # <<<<<<<<<<<<<<
 *             # add root to frontier
 *             rc = self._add_split_node(splitter, tree, 0, n_node_samples,
 */
  {
      #ifdef WITH_THREAD
      PyThreadState *_save;
      Py_UNBLOCK_THREADS
      #endif
      /*try:*/ {

        /* "sklearn/tree/_tree.pyx":1979
 *         with nogil:
 *             # add root to frontier
 *             rc = self._add_split_node(splitter, tree, 0, n_node_samples,             # <<<<<<<<<<<<<<
 *                                       INFINITY, IS_FIRST, IS_LEFT, NULL, 0,
 *                                       &split_node_left)
 */
        __pyx_v_rc = __pyx_f_7sklearn_4tree_5_tree_20BestFirstTreeBuilder__add_split_node(__pyx_v_self, __pyx_v_splitter, __pyx_v_tree, 0, __pyx_v_n_node_samples, __pyx_v_7sklearn_4tree_5_tree_INFINITY, __pyx_v_7sklearn_4tree_5_tree_IS_FIRST, __pyx_v_7sklearn_4tree_5_tree_IS_LEFT, NULL, 0, (&__pyx_v_split_node_left));

        /* "sklearn/tree/_tree.pyx":1982
 *                                       INFINITY, IS_FIRST, IS_LEFT, NULL, 0,
 *                                       &split_node_left)
 *             if rc >= 0:             # <<<<<<<<<<<<<<
 *                 rc = _add_to_frontier(&split_node_left, frontier)
 *         if rc == -1:
 */
        __pyx_t_6 = ((__pyx_v_rc >= 0) != 0);
        if (__pyx_t_6) {

          /* "sklearn/tree/_tree.pyx":1983
 *                                       &split_node_left)
 *             if rc >= 0:
 *                 rc = _add_to_frontier(&split_node_left, frontier)             # <<<<<<<<<<<<<<
 *         if rc == -1:
 *             raise MemoryError()
 */
          __pyx_v_rc = __pyx_f_7sklearn_4tree_5_tree__add_to_frontier((&__pyx_v_split_node_left), __pyx_v_frontier);
          goto __pyx_L10;
        }
        __pyx_L10:;
      }

      /* "sklearn/tree/_tree.pyx":1977
 *         tree._resize(init_capacity)
 * 
 *         with nogil:             # <<<<<<<<<<<<<<
 *             # add root to frontier
 *             rc = self._add_split_node(splitter, tree, 0, n_node_samples,
 */
      /*finally:*/ {
        /*normal exit:*/{
          #ifdef WITH_THREAD
          Py_BLOCK_THREADS
          #endif
          goto __pyx_L9;
        }
        __pyx_L9:;
      }
  }

  /* "sklearn/tree/_tree.pyx":1984
 *             if rc >= 0:
 *                 rc = _add_to_frontier(&split_node_left, frontier)
 *         if rc == -1:             # <<<<<<<<<<<<<<
 *             raise MemoryError()
 * 
 */
  __pyx_t_6 = ((__pyx_v_rc == -1) != 0);
  if (__pyx_t_6) {

    /* "sklearn/tree/_tree.pyx":1985
 *                 rc = _add_to_frontier(&split_node_left, frontier)
 *         if rc == -1:
 *             raise MemoryError()             # <<<<<<<<<<<<<<
 * 
 *         with nogil:
 */
    PyErr_NoMemory(); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1985; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
  }

  /* "sklearn/tree/_tree.pyx":1987
 *             raise MemoryError()
 * 
 *         with nogil:             # <<<<<<<<<<<<<<
 *             while not frontier.is_empty():
 *                 frontier.pop(&record)
 */
  {
      #ifdef WITH_THREAD
      PyThreadState *_save;
      Py_UNBLOCK_THREADS
      #endif
      /*try:*/ {

        /* "sklearn/tree/_tree.pyx":1988
 * 
 *         with nogil:
 *             while not frontier.is_empty():             # <<<<<<<<<<<<<<
 *                 frontier.pop(&record)
 * 
 */
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          __pyx_t_6 = ((!(((struct __pyx_vtabstruct_7sklearn_4tree_6_utils_PriorityHeap *)__pyx_v_frontier->__pyx_vtab)->is_empty(__pyx_v_frontier) != 0)) != 0);
          if (!__pyx_t_6) break;

          /* "sklearn/tree/_tree.pyx":1989
 *         with nogil:
 *             while not frontier.is_empty():
 *                 frontier.pop(&record)             # <<<<<<<<<<<<<<
 * 
 *                 node = &tree.nodes[record.node_id]
 */
          ((struct __pyx_vtabstruct_7sklearn_4tree_6_utils_PriorityHeap *)__pyx_v_frontier->__pyx_vtab)->pop(__pyx_v_frontier, (&__pyx_v_record));

          /* "sklearn/tree/_tree.pyx":1991
 *                 frontier.pop(&record)
 * 
 *                 node = &tree.nodes[record.node_id]             # <<<<<<<<<<<<<<
 *                 is_leaf = (record.is_leaf or max_split_nodes <= 0)
 * 
 */
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          /* "sklearn/tree/_tree.pyx":1992
 * 
 *                 node = &tree.nodes[record.node_id]
 *                 is_leaf = (record.is_leaf or max_split_nodes <= 0)             # <<<<<<<<<<<<<<
 * 
 *                 if is_leaf:
 */
          if (!__pyx_v_record.is_leaf) {
            __pyx_t_6 = (__pyx_v_max_split_nodes <= 0);
            __pyx_t_4 = __pyx_t_6;
          } else {
            __pyx_t_4 = __pyx_v_record.is_leaf;
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          /* "sklearn/tree/_tree.pyx":1994
 *                 is_leaf = (record.is_leaf or max_split_nodes <= 0)
 * 
 *                 if is_leaf:             # <<<<<<<<<<<<<<
 *                     # Node is not expandable; set node as leaf
 *                     node.left_child = _TREE_LEAF
 */
          __pyx_t_4 = (__pyx_v_is_leaf != 0);
          if (__pyx_t_4) {

            /* "sklearn/tree/_tree.pyx":1996
 *                 if is_leaf:
 *                     # Node is not expandable; set node as leaf
 *                     node.left_child = _TREE_LEAF             # <<<<<<<<<<<<<<
 *                     node.right_child = _TREE_LEAF
 *                     node.feature = _TREE_UNDEFINED
 */
            __pyx_v_node->left_child = __pyx_v_7sklearn_4tree_5_tree__TREE_LEAF;

            /* "sklearn/tree/_tree.pyx":1997
 *                     # Node is not expandable; set node as leaf
 *                     node.left_child = _TREE_LEAF
 *                     node.right_child = _TREE_LEAF             # <<<<<<<<<<<<<<
 *                     node.feature = _TREE_UNDEFINED
 *                     node.threshold = _TREE_UNDEFINED
 */
            __pyx_v_node->right_child = __pyx_v_7sklearn_4tree_5_tree__TREE_LEAF;

            /* "sklearn/tree/_tree.pyx":1998
 *                     node.left_child = _TREE_LEAF
 *                     node.right_child = _TREE_LEAF
 *                     node.feature = _TREE_UNDEFINED             # <<<<<<<<<<<<<<
 *                     node.threshold = _TREE_UNDEFINED
 * 
 */
            __pyx_v_node->feature = __pyx_v_7sklearn_4tree_5_tree__TREE_UNDEFINED;

            /* "sklearn/tree/_tree.pyx":1999
 *                     node.right_child = _TREE_LEAF
 *                     node.feature = _TREE_UNDEFINED
 *                     node.threshold = _TREE_UNDEFINED             # <<<<<<<<<<<<<<
 * 
 *                 else:
 */
            __pyx_v_node->threshold = __pyx_v_7sklearn_4tree_5_tree__TREE_UNDEFINED;
            goto __pyx_L17;
          }
          /*else*/ {

            /* "sklearn/tree/_tree.pyx":2005
 * 
 *                     # Decrement number of split nodes available
 *                     max_split_nodes -= 1             # <<<<<<<<<<<<<<
 * 
 *                     # Compute left split node
 */
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            /* "sklearn/tree/_tree.pyx":2008
 * 
 *                     # Compute left split node
 *                     rc = self._add_split_node(splitter, tree,             # <<<<<<<<<<<<<<
 *                                               record.start, record.pos,
 *                                               record.impurity_left,
 */
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            /* "sklearn/tree/_tree.pyx":2014
 *                                               record.depth + 1,
 *                                               &split_node_left)
 *                     if rc == -1:             # <<<<<<<<<<<<<<
 *                         break
 * 
 */
            __pyx_t_4 = ((__pyx_v_rc == -1) != 0);
            if (__pyx_t_4) {

              /* "sklearn/tree/_tree.pyx":2015
 *                                               &split_node_left)
 *                     if rc == -1:
 *                         break             # <<<<<<<<<<<<<<
 * 
 *                     # tree.nodes may have changed
 */
              goto __pyx_L16_break;
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 * 
 *                     # tree.nodes may have changed
 *                     node = &tree.nodes[record.node_id]             # <<<<<<<<<<<<<<
 * 
 *                     # Compute right split node
 */
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            /* "sklearn/tree/_tree.pyx":2021
 * 
 *                     # Compute right split node
 *                     rc = self._add_split_node(splitter, tree, record.pos,             # <<<<<<<<<<<<<<
 *                                               record.end,
 *                                               record.impurity_right,
 */
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 *                                               record.depth + 1,
 *                                               &split_node_right)
 *                     if rc == -1:             # <<<<<<<<<<<<<<
 *                         break
 * 
 */
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              /* "sklearn/tree/_tree.pyx":2028
 *                                               &split_node_right)
 *                     if rc == -1:
 *                         break             # <<<<<<<<<<<<<<
 * 
 *                     # Add nodes to queue
 */
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 * 
 *                     # Add nodes to queue
 *                     rc = _add_to_frontier(&split_node_left, frontier)             # <<<<<<<<<<<<<<
 *                     if rc == -1:
 *                         break
 */
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 *                     # Add nodes to queue
 *                     rc = _add_to_frontier(&split_node_left, frontier)
 *                     if rc == -1:             # <<<<<<<<<<<<<<
 *                         break
 * 
 */
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 *                     rc = _add_to_frontier(&split_node_left, frontier)
 *                     if rc == -1:
 *                         break             # <<<<<<<<<<<<<<
 * 
 *                     rc = _add_to_frontier(&split_node_right, frontier)
 */
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 *                         break
 * 
 *                     rc = _add_to_frontier(&split_node_right, frontier)             # <<<<<<<<<<<<<<
 *                     if rc == -1:
 *                         break
 */
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 * 
 *                     rc = _add_to_frontier(&split_node_right, frontier)
 *                     if rc == -1:             # <<<<<<<<<<<<<<
 *                         break
 * 
 */
            __pyx_t_4 = ((__pyx_v_rc == -1) != 0);
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              /* "sklearn/tree/_tree.pyx":2037
 *                     rc = _add_to_frontier(&split_node_right, frontier)
 *                     if rc == -1:
 *                         break             # <<<<<<<<<<<<<<
 * 
 *                 if record.depth > max_depth_seen:
 */
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          __pyx_L17:;

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 *                         break
 * 
 *                 if record.depth > max_depth_seen:             # <<<<<<<<<<<<<<
 *                     max_depth_seen = record.depth
 * 
 */
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          if (__pyx_t_4) {

            /* "sklearn/tree/_tree.pyx":2040
 * 
 *                 if record.depth > max_depth_seen:
 *                     max_depth_seen = record.depth             # <<<<<<<<<<<<<<
 * 
 *             if rc >= 0:
 */
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 *                     max_depth_seen = record.depth
 * 
 *             if rc >= 0:             # <<<<<<<<<<<<<<
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 * 
 */
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 * 
 *             if rc >= 0:
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 * 
 *             if rc >= 0:
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 * 
 *             if rc >= 0:             # <<<<<<<<<<<<<<
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 * 
 */
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 * 
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 * 
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      /* "sklearn/tree/_tree.pyx":1987
 *             raise MemoryError()
 * 
 *         with nogil:             # <<<<<<<<<<<<<<
 *             while not frontier.is_empty():
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  /* "sklearn/tree/_tree.pyx":2048
 *                 tree.max_depth = max_depth_seen
 * 
 *         if rc == -1:             # <<<<<<<<<<<<<<
 *             raise MemoryError()
 * 
 */
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 * 
 *         if rc == -1:
 *             raise MemoryError()             # <<<<<<<<<<<<<<
 * 
 *     cdef inline int _add_split_node(self, Splitter splitter, Tree tree,
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    PyErr_NoMemory(); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 2049; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
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 *         self.max_leaf_nodes = max_leaf_nodes
 * 
 *     cpdef build(self, Tree tree, np.ndarray X, np.ndarray y,             # <<<<<<<<<<<<<<
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 *     cpdef build(self, Tree tree, np.ndarray X, np.ndarray y,             # <<<<<<<<<<<<<<
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/* "sklearn/tree/_tree.pyx":2051
 *             raise MemoryError()
 * 
 *     cdef inline int _add_split_node(self, Splitter splitter, Tree tree,             # <<<<<<<<<<<<<<
 *                                     SIZE_t start, SIZE_t end, double impurity,
 *                                     bint is_first, bint is_left, Node* parent,
 */

static CYTHON_INLINE int __pyx_f_7sklearn_4tree_5_tree_20BestFirstTreeBuilder__add_split_node(struct __pyx_obj_7sklearn_4tree_5_tree_BestFirstTreeBuilder *__pyx_v_self, struct __pyx_obj_7sklearn_4tree_5_tree_Splitter *__pyx_v_splitter, struct __pyx_obj_7sklearn_4tree_5_tree_Tree *__pyx_v_tree, __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_start, __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_end, double __pyx_v_impurity, int __pyx_v_is_first, int __pyx_v_is_left, struct __pyx_t_7sklearn_4tree_5_tree_Node *__pyx_v_parent, __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_depth, struct __pyx_t_7sklearn_4tree_6_utils_PriorityHeapRecord *__pyx_v_res) {
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  __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_n_constant_features;
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  int __pyx_v_is_leaf;
  int __pyx_r;
  int __pyx_t_1;
  int __pyx_t_2;
  int __pyx_t_3;
  int __pyx_t_4;
  int __pyx_t_5;
  ptrdiff_t __pyx_t_6;
  __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_t_7;
  double __pyx_t_8;

  /* "sklearn/tree/_tree.pyx":2060
 *         cdef SIZE_t node_id
 *         cdef SIZE_t n_node_samples
 *         cdef SIZE_t n_constant_features = 0             # <<<<<<<<<<<<<<
 *         cdef double weighted_n_node_samples
 *         cdef bint is_leaf
 */
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  /* "sklearn/tree/_tree.pyx":2066
 *         cdef double imp_diff
 * 
 *         splitter.node_reset(start, end, &weighted_n_node_samples)             # <<<<<<<<<<<<<<
 * 
 *         if is_first:
 */
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  /* "sklearn/tree/_tree.pyx":2068
 *         splitter.node_reset(start, end, &weighted_n_node_samples)
 * 
 *         if is_first:             # <<<<<<<<<<<<<<
 *             impurity = splitter.node_impurity()
 * 
 */
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    /* "sklearn/tree/_tree.pyx":2069
 * 
 *         if is_first:
 *             impurity = splitter.node_impurity()             # <<<<<<<<<<<<<<
 * 
 *         n_node_samples = end - start
 */
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  /* "sklearn/tree/_tree.pyx":2071
 *             impurity = splitter.node_impurity()
 * 
 *         n_node_samples = end - start             # <<<<<<<<<<<<<<
 *         is_leaf = ((depth > self.max_depth) or
 *                    (n_node_samples < self.min_samples_split) or
 */
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  /* "sklearn/tree/_tree.pyx":2072
 * 
 *         n_node_samples = end - start
 *         is_leaf = ((depth > self.max_depth) or             # <<<<<<<<<<<<<<
 *                    (n_node_samples < self.min_samples_split) or
 *                    (n_node_samples < 2 * self.min_samples_leaf) or
 */
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    /* "sklearn/tree/_tree.pyx":2073
 *         n_node_samples = end - start
 *         is_leaf = ((depth > self.max_depth) or
 *                    (n_node_samples < self.min_samples_split) or             # <<<<<<<<<<<<<<
 *                    (n_node_samples < 2 * self.min_samples_leaf) or
 *                    (impurity <= MIN_IMPURITY_SPLIT))
 */
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      /* "sklearn/tree/_tree.pyx":2074
 *         is_leaf = ((depth > self.max_depth) or
 *                    (n_node_samples < self.min_samples_split) or
 *                    (n_node_samples < 2 * self.min_samples_leaf) or             # <<<<<<<<<<<<<<
 *                    (impurity <= MIN_IMPURITY_SPLIT))
 * 
 */
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      if (!__pyx_t_3) {

        /* "sklearn/tree/_tree.pyx":2075
 *                    (n_node_samples < self.min_samples_split) or
 *                    (n_node_samples < 2 * self.min_samples_leaf) or
 *                    (impurity <= MIN_IMPURITY_SPLIT))             # <<<<<<<<<<<<<<
 * 
 *         if not is_leaf:
 */
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  /* "sklearn/tree/_tree.pyx":2077
 *                    (impurity <= MIN_IMPURITY_SPLIT))
 * 
 *         if not is_leaf:             # <<<<<<<<<<<<<<
 *             splitter.node_split(impurity, &split, &n_constant_features)
 *             is_leaf = is_leaf or (split.pos >= end)
 */
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  if (__pyx_t_2) {

    /* "sklearn/tree/_tree.pyx":2078
 * 
 *         if not is_leaf:
 *             splitter.node_split(impurity, &split, &n_constant_features)             # <<<<<<<<<<<<<<
 *             is_leaf = is_leaf or (split.pos >= end)
 * 
 */
    ((struct __pyx_vtabstruct_7sklearn_4tree_5_tree_Splitter *)__pyx_v_splitter->__pyx_vtab)->node_split(__pyx_v_splitter, __pyx_v_impurity, (&__pyx_v_split), (&__pyx_v_n_constant_features));

    /* "sklearn/tree/_tree.pyx":2079
 *         if not is_leaf:
 *             splitter.node_split(impurity, &split, &n_constant_features)
 *             is_leaf = is_leaf or (split.pos >= end)             # <<<<<<<<<<<<<<
 * 
 *         node_id = tree._add_node(parent - tree.nodes
 */
    if (!__pyx_v_is_leaf) {
      __pyx_t_2 = (__pyx_v_split.pos >= __pyx_v_end);
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    } else {
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    goto __pyx_L4;
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  __pyx_L4:;

  /* "sklearn/tree/_tree.pyx":2082
 * 
 *         node_id = tree._add_node(parent - tree.nodes
 *                                  if parent != NULL             # <<<<<<<<<<<<<<
 *                                  else _TREE_UNDEFINED,
 *                                  is_left, is_leaf,
 */
  if (((__pyx_v_parent != NULL) != 0)) {

    /* "sklearn/tree/_tree.pyx":2081
 *             is_leaf = is_leaf or (split.pos >= end)
 * 
 *         node_id = tree._add_node(parent - tree.nodes             # <<<<<<<<<<<<<<
 *                                  if parent != NULL
 *                                  else _TREE_UNDEFINED,
 */
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  } else {

    /* "sklearn/tree/_tree.pyx":2083
 *         node_id = tree._add_node(parent - tree.nodes
 *                                  if parent != NULL
 *                                  else _TREE_UNDEFINED,             # <<<<<<<<<<<<<<
 *                                  is_left, is_leaf,
 *                                  split.feature, split.threshold, impurity, n_node_samples,
 */
    __pyx_t_6 = __pyx_v_7sklearn_4tree_5_tree__TREE_UNDEFINED;
  }

  /* "sklearn/tree/_tree.pyx":2081
 *             is_leaf = is_leaf or (split.pos >= end)
 * 
 *         node_id = tree._add_node(parent - tree.nodes             # <<<<<<<<<<<<<<
 *                                  if parent != NULL
 *                                  else _TREE_UNDEFINED,
 */
  __pyx_v_node_id = ((struct __pyx_vtabstruct_7sklearn_4tree_5_tree_Tree *)__pyx_v_tree->__pyx_vtab)->_add_node(__pyx_v_tree, __pyx_t_6, __pyx_v_is_left, __pyx_v_is_leaf, __pyx_v_split.feature, __pyx_v_split.threshold, __pyx_v_impurity, __pyx_v_n_node_samples, __pyx_v_weighted_n_node_samples);

  /* "sklearn/tree/_tree.pyx":2087
 *                                  split.feature, split.threshold, impurity, n_node_samples,
 *                                  weighted_n_node_samples)
 *         if node_id == <SIZE_t>(-1):             # <<<<<<<<<<<<<<
 *             return -1
 * 
 */
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  if (__pyx_t_1) {

    /* "sklearn/tree/_tree.pyx":2088
 *                                  weighted_n_node_samples)
 *         if node_id == <SIZE_t>(-1):
 *             return -1             # <<<<<<<<<<<<<<
 * 
 *         # compute values also for split nodes (might become leafs later).
 */
    __pyx_r = -1;
    goto __pyx_L0;
  }

  /* "sklearn/tree/_tree.pyx":2091
 * 
 *         # compute values also for split nodes (might become leafs later).
 *         splitter.node_value(tree.value + node_id * tree.value_stride)             # <<<<<<<<<<<<<<
 * 
 *         res.node_id = node_id
 */
  ((struct __pyx_vtabstruct_7sklearn_4tree_5_tree_Splitter *)__pyx_v_splitter->__pyx_vtab)->node_value(__pyx_v_splitter, (__pyx_v_tree->value + (__pyx_v_node_id * __pyx_v_tree->value_stride)));

  /* "sklearn/tree/_tree.pyx":2093
 *         splitter.node_value(tree.value + node_id * tree.value_stride)
 * 
 *         res.node_id = node_id             # <<<<<<<<<<<<<<
 *         res.start = start
 *         res.end = end
 */
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  /* "sklearn/tree/_tree.pyx":2094
 * 
 *         res.node_id = node_id
 *         res.start = start             # <<<<<<<<<<<<<<
 *         res.end = end
 *         res.depth = depth
 */
  __pyx_v_res->start = __pyx_v_start;

  /* "sklearn/tree/_tree.pyx":2095
 *         res.node_id = node_id
 *         res.start = start
 *         res.end = end             # <<<<<<<<<<<<<<
 *         res.depth = depth
 *         res.impurity = impurity
 */
  __pyx_v_res->end = __pyx_v_end;

  /* "sklearn/tree/_tree.pyx":2096
 *         res.start = start
 *         res.end = end
 *         res.depth = depth             # <<<<<<<<<<<<<<
 *         res.impurity = impurity
 * 
 */
  __pyx_v_res->depth = __pyx_v_depth;

  /* "sklearn/tree/_tree.pyx":2097
 *         res.end = end
 *         res.depth = depth
 *         res.impurity = impurity             # <<<<<<<<<<<<<<
 * 
 *         if not is_leaf:
 */
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  /* "sklearn/tree/_tree.pyx":2099
 *         res.impurity = impurity
 * 
 *         if not is_leaf:             # <<<<<<<<<<<<<<
 *             # is split node
 *             res.pos = split.pos
 */
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  if (__pyx_t_1) {

    /* "sklearn/tree/_tree.pyx":2101
 *         if not is_leaf:
 *             # is split node
 *             res.pos = split.pos             # <<<<<<<<<<<<<<
 *             res.is_leaf = 0
 *             res.improvement = split.improvement
 */
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    /* "sklearn/tree/_tree.pyx":2102
 *             # is split node
 *             res.pos = split.pos
 *             res.is_leaf = 0             # <<<<<<<<<<<<<<
 *             res.improvement = split.improvement
 *             res.impurity_left = split.impurity_left
 */
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    /* "sklearn/tree/_tree.pyx":2103
 *             res.pos = split.pos
 *             res.is_leaf = 0
 *             res.improvement = split.improvement             # <<<<<<<<<<<<<<
 *             res.impurity_left = split.impurity_left
 *             res.impurity_right = split.impurity_right
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 *             res.is_leaf = 0
 *             res.improvement = split.improvement
 *             res.impurity_left = split.impurity_left             # <<<<<<<<<<<<<<
 *             res.impurity_right = split.impurity_right
 * 
 */
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    /* "sklearn/tree/_tree.pyx":2105
 *             res.improvement = split.improvement
 *             res.impurity_left = split.impurity_left
 *             res.impurity_right = split.impurity_right             # <<<<<<<<<<<<<<
 * 
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  /* "sklearn/tree/_tree.pyx":2316
 *         ptr = realloc(self.value,
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    /* "sklearn/tree/_tree.pyx":2317
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 *         # value memory is initialised to 0 to enable classifier argmax
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 */
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    /* "sklearn/tree/_tree.pyx":2322
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 *                    (capacity - self.capacity) * self.value_stride *
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  /* "sklearn/tree/_tree.pyx":2327
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 */
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  /* "sklearn/tree/_tree.pyx":2298
 *     # XXX using (size_t)(-1) is ugly, but SIZE_MAX is not available in C89
 *     # (i.e., older MSVC).
 *     cdef int _resize_c(self, SIZE_t capacity=<SIZE_t>(-1)) nogil:             # <<<<<<<<<<<<<<
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/* "sklearn/tree/_tree.pyx":2333
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static __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_f_7sklearn_4tree_5_tree_4Tree__add_node(struct __pyx_obj_7sklearn_4tree_5_tree_Tree *__pyx_v_self, __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_parent, int __pyx_v_is_left, int __pyx_v_is_leaf, __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_feature, double __pyx_v_threshold, double __pyx_v_impurity, __pyx_t_7sklearn_4tree_5_tree_SIZE_t __pyx_v_n_node_samples, double __pyx_v_weighted_n_node_samples) {
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  /* "sklearn/tree/_tree.pyx":2348
 *                 return <SIZE_t>(-1)
 * 
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static int __pyx_tp_traverse_7sklearn_4tree_5_tree_Splitter(PyObject *o, visitproc v, void *a) {
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static PyObject *__pyx_getprop_7sklearn_4tree_5_tree_8Splitter_max_features(PyObject *o, CYTHON_UNUSED void *x) {
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static int __pyx_setprop_7sklearn_4tree_5_tree_8Splitter_max_features(PyObject *o, PyObject *v, CYTHON_UNUSED void *x) {
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static struct __pyx_vtabstruct_7sklearn_4tree_5_tree_Tree __pyx_vtable_7sklearn_4tree_5_tree_Tree;

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static PyObject *__pyx_getprop_7sklearn_4tree_5_tree_4Tree_n_classes(PyObject *o, CYTHON_UNUSED void *x) {
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static PyObject *__pyx_getprop_7sklearn_4tree_5_tree_4Tree_children_right(PyObject *o, CYTHON_UNUSED void *x) {
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static PyObject *__pyx_getprop_7sklearn_4tree_5_tree_4Tree_feature(PyObject *o, CYTHON_UNUSED void *x) {
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static PyObject *__pyx_getprop_7sklearn_4tree_5_tree_4Tree_impurity(PyObject *o, CYTHON_UNUSED void *x) {
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static PyObject *__pyx_getprop_7sklearn_4tree_5_tree_4Tree_n_features(PyObject *o, CYTHON_UNUSED void *x) {
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static PyObject *__pyx_getprop_7sklearn_4tree_5_tree_4Tree_node_count(PyObject *o, CYTHON_UNUSED void *x) {
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  Py_CLEAR(p->splitter);
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}

static int __pyx_tp_traverse_7sklearn_4tree_5_tree_TreeBuilder(PyObject *o, visitproc v, void *a) {
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}

static int __pyx_tp_clear_7sklearn_4tree_5_tree_TreeBuilder(PyObject *o) {
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static PyMethodDef __pyx_methods_7sklearn_4tree_5_tree_TreeBuilder[] = {
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static PyTypeObject __pyx_type_7sklearn_4tree_5_tree_TreeBuilder = {
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static struct __pyx_vtabstruct_7sklearn_4tree_5_tree_ClassificationCriterion __pyx_vtable_7sklearn_4tree_5_tree_ClassificationCriterion;

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static struct __pyx_vtabstruct_7sklearn_4tree_5_tree_Entropy __pyx_vtable_7sklearn_4tree_5_tree_Entropy;

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  if (unlikely(!o)) return 0;
  p = ((struct __pyx_obj_7sklearn_4tree_5_tree_Entropy *)o);
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}

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static struct __pyx_vtabstruct_7sklearn_4tree_5_tree_Gini __pyx_vtable_7sklearn_4tree_5_tree_Gini;

static PyObject *__pyx_tp_new_7sklearn_4tree_5_tree_Gini(PyTypeObject *t, PyObject *a, PyObject *k) {
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}

static PyTypeObject __pyx_type_7sklearn_4tree_5_tree_Gini = {
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static struct __pyx_vtabstruct_7sklearn_4tree_5_tree_RegressionCriterion __pyx_vtable_7sklearn_4tree_5_tree_RegressionCriterion;

static PyObject *__pyx_tp_new_7sklearn_4tree_5_tree_RegressionCriterion(PyTypeObject *t, PyObject *a, PyObject *k) {
  struct __pyx_obj_7sklearn_4tree_5_tree_RegressionCriterion *p;
  PyObject *o = __pyx_tp_new_7sklearn_4tree_5_tree_Criterion(t, a, k);
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  p = ((struct __pyx_obj_7sklearn_4tree_5_tree_RegressionCriterion *)o);
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}

static void __pyx_tp_dealloc_7sklearn_4tree_5_tree_RegressionCriterion(PyObject *o) {
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    PyErr_Restore(etype, eval, etb);
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  __pyx_tp_dealloc_7sklearn_4tree_5_tree_Criterion(o);
}

static PyMethodDef __pyx_methods_7sklearn_4tree_5_tree_RegressionCriterion[] = {
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static PyTypeObject __pyx_type_7sklearn_4tree_5_tree_RegressionCriterion = {
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static struct __pyx_vtabstruct_7sklearn_4tree_5_tree_MSE __pyx_vtable_7sklearn_4tree_5_tree_MSE;

static PyObject *__pyx_tp_new_7sklearn_4tree_5_tree_MSE(PyTypeObject *t, PyObject *a, PyObject *k) {
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static PyTypeObject __pyx_type_7sklearn_4tree_5_tree_MSE = {
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static struct __pyx_vtabstruct_7sklearn_4tree_5_tree_FriedmanMSE __pyx_vtable_7sklearn_4tree_5_tree_FriedmanMSE;

static PyObject *__pyx_tp_new_7sklearn_4tree_5_tree_FriedmanMSE(PyTypeObject *t, PyObject *a, PyObject *k) {
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static PyTypeObject __pyx_type_7sklearn_4tree_5_tree_FriedmanMSE = {
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static struct __pyx_vtabstruct_7sklearn_4tree_5_tree_BestSplitter __pyx_vtable_7sklearn_4tree_5_tree_BestSplitter;

static PyObject *__pyx_tp_new_7sklearn_4tree_5_tree_BestSplitter(PyTypeObject *t, PyObject *a, PyObject *k) {
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static PyTypeObject __pyx_type_7sklearn_4tree_5_tree_BestSplitter = {
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static struct __pyx_vtabstruct_7sklearn_4tree_5_tree_RandomSplitter __pyx_vtable_7sklearn_4tree_5_tree_RandomSplitter;

static PyObject *__pyx_tp_new_7sklearn_4tree_5_tree_RandomSplitter(PyTypeObject *t, PyObject *a, PyObject *k) {
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}

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static struct __pyx_vtabstruct_7sklearn_4tree_5_tree_PresortBestSplitter __pyx_vtable_7sklearn_4tree_5_tree_PresortBestSplitter;

static PyObject *__pyx_tp_new_7sklearn_4tree_5_tree_PresortBestSplitter(PyTypeObject *t, PyObject *a, PyObject *k) {
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}

static void __pyx_tp_dealloc_7sklearn_4tree_5_tree_PresortBestSplitter(PyObject *o) {
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}

static int __pyx_tp_traverse_7sklearn_4tree_5_tree_PresortBestSplitter(PyObject *o, visitproc v, void *a) {
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static int __pyx_tp_clear_7sklearn_4tree_5_tree_PresortBestSplitter(PyObject *o) {
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  __pyx_vtable_7sklearn_4tree_5_tree_Tree._add_node = (__pyx_t_7sklearn_4tree_5_tree_SIZE_t (*)(struct __pyx_obj_7sklearn_4tree_5_tree_Tree *, __pyx_t_7sklearn_4tree_5_tree_SIZE_t, int, int, __pyx_t_7sklearn_4tree_5_tree_SIZE_t, double, double, __pyx_t_7sklearn_4tree_5_tree_SIZE_t, double))__pyx_f_7sklearn_4tree_5_tree_4Tree__add_node;
  __pyx_vtable_7sklearn_4tree_5_tree_Tree._resize = (void (*)(struct __pyx_obj_7sklearn_4tree_5_tree_Tree *, __pyx_t_7sklearn_4tree_5_tree_SIZE_t))__pyx_f_7sklearn_4tree_5_tree_4Tree__resize;
  __pyx_vtable_7sklearn_4tree_5_tree_Tree._resize_c = (int (*)(struct __pyx_obj_7sklearn_4tree_5_tree_Tree *, struct __pyx_opt_args_7sklearn_4tree_5_tree_4Tree__resize_c *__pyx_optional_args))__pyx_f_7sklearn_4tree_5_tree_4Tree__resize_c;
  __pyx_vtable_7sklearn_4tree_5_tree_Tree._get_value_ndarray = (PyArrayObject *(*)(struct __pyx_obj_7sklearn_4tree_5_tree_Tree *))__pyx_f_7sklearn_4tree_5_tree_4Tree__get_value_ndarray;
  __pyx_vtable_7sklearn_4tree_5_tree_Tree._get_node_ndarray = (PyArrayObject *(*)(struct __pyx_obj_7sklearn_4tree_5_tree_Tree *))__pyx_f_7sklearn_4tree_5_tree_4Tree__get_node_ndarray;
  __pyx_vtable_7sklearn_4tree_5_tree_Tree.predict = (PyArrayObject *(*)(struct __pyx_obj_7sklearn_4tree_5_tree_Tree *, PyArrayObject *, int __pyx_skip_dispatch))__pyx_f_7sklearn_4tree_5_tree_4Tree_predict;
  __pyx_vtable_7sklearn_4tree_5_tree_Tree.apply = (PyArrayObject *(*)(struct __pyx_obj_7sklearn_4tree_5_tree_Tree *, PyArrayObject *, int __pyx_skip_dispatch))__pyx_f_7sklearn_4tree_5_tree_4Tree_apply;
  __pyx_vtable_7sklearn_4tree_5_tree_Tree.compute_feature_importances = (PyObject *(*)(struct __pyx_obj_7sklearn_4tree_5_tree_Tree *, int __pyx_skip_dispatch, struct __pyx_opt_args_7sklearn_4tree_5_tree_4Tree_compute_feature_importances *__pyx_optional_args))__pyx_f_7sklearn_4tree_5_tree_4Tree_compute_feature_importances;
  if (PyType_Ready(&__pyx_type_7sklearn_4tree_5_tree_Tree) < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 2122; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
  __pyx_type_7sklearn_4tree_5_tree_Tree.tp_print = 0;
  if (__Pyx_SetVtable(__pyx_type_7sklearn_4tree_5_tree_Tree.tp_dict, __pyx_vtabptr_7sklearn_4tree_5_tree_Tree) < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 2122; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
  if (__Pyx_SetAttrString(__pyx_m, "Tree", (PyObject *)&__pyx_type_7sklearn_4tree_5_tree_Tree) < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 2122; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
  __pyx_ptype_7sklearn_4tree_5_tree_Tree = &__pyx_type_7sklearn_4tree_5_tree_Tree;
  __pyx_vtabptr_7sklearn_4tree_5_tree_TreeBuilder = &__pyx_vtable_7sklearn_4tree_5_tree_TreeBuilder;
  __pyx_vtable_7sklearn_4tree_5_tree_TreeBuilder.build = (PyObject *(*)(struct __pyx_obj_7sklearn_4tree_5_tree_TreeBuilder *, struct __pyx_obj_7sklearn_4tree_5_tree_Tree *, PyArrayObject *, PyArrayObject *, int __pyx_skip_dispatch, struct __pyx_opt_args_7sklearn_4tree_5_tree_11TreeBuilder_build *__pyx_optional_args))__pyx_f_7sklearn_4tree_5_tree_11TreeBuilder_build;
  if (PyType_Ready(&__pyx_type_7sklearn_4tree_5_tree_TreeBuilder) < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1753; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
  __pyx_type_7sklearn_4tree_5_tree_TreeBuilder.tp_print = 0;
  if (__Pyx_SetVtable(__pyx_type_7sklearn_4tree_5_tree_TreeBuilder.tp_dict, __pyx_vtabptr_7sklearn_4tree_5_tree_TreeBuilder) < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1753; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
  if (__Pyx_SetAttrString(__pyx_m, "TreeBuilder", (PyObject *)&__pyx_type_7sklearn_4tree_5_tree_TreeBuilder) < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1753; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
  __pyx_ptype_7sklearn_4tree_5_tree_TreeBuilder = &__pyx_type_7sklearn_4tree_5_tree_TreeBuilder;
  __pyx_vtabptr_7sklearn_4tree_5_tree_ClassificationCriterion = &__pyx_vtable_7sklearn_4tree_5_tree_ClassificationCriterion;
  __pyx_vtable_7sklearn_4tree_5_tree_ClassificationCriterion.__pyx_base = *__pyx_vtabptr_7sklearn_4tree_5_tree_Criterion;
  __pyx_vtable_7sklearn_4tree_5_tree_ClassificationCriterion.__pyx_base.init = (void (*)(struct __pyx_obj_7sklearn_4tree_5_tree_Criterion *, __pyx_t_7sklearn_4tree_5_tree_DOUBLE_t *, __pyx_t_7sklearn_4tree_5_tree_SIZE_t, __pyx_t_7sklearn_4tree_5_tree_DOUBLE_t *, double, __pyx_t_7sklearn_4tree_5_tree_SIZE_t *, __pyx_t_7sklearn_4tree_5_tree_SIZE_t, __pyx_t_7sklearn_4tree_5_tree_SIZE_t))__pyx_f_7sklearn_4tree_5_tree_23ClassificationCriterion_init;
  __pyx_vtable_7sklearn_4tree_5_tree_ClassificationCriterion.__pyx_base.reset = (void (*)(struct __pyx_obj_7sklearn_4tree_5_tree_Criterion *))__pyx_f_7sklearn_4tree_5_tree_23ClassificationCriterion_reset;
  __pyx_vtable_7sklearn_4tree_5_tree_ClassificationCriterion.__pyx_base.update = (void (*)(struct __pyx_obj_7sklearn_4tree_5_tree_Criterion *, __pyx_t_7sklearn_4tree_5_tree_SIZE_t))__pyx_f_7sklearn_4tree_5_tree_23ClassificationCriterion_update;
  __pyx_vtable_7sklearn_4tree_5_tree_ClassificationCriterion.__pyx_base.node_impurity = (double (*)(struct __pyx_obj_7sklearn_4tree_5_tree_Criterion *))__pyx_f_7sklearn_4tree_5_tree_23ClassificationCriterion_node_impurity;
  __pyx_vtable_7sklearn_4tree_5_tree_ClassificationCriterion.__pyx_base.children_impurity = (void (*)(struct __pyx_obj_7sklearn_4tree_5_tree_Criterion *, double *, double *))__pyx_f_7sklearn_4tree_5_tree_23ClassificationCriterion_children_impurity;
  __pyx_vtable_7sklearn_4tree_5_tree_ClassificationCriterion.__pyx_base.node_value = (void (*)(struct __pyx_obj_7sklearn_4tree_5_tree_Criterion *, double *))__pyx_f_7sklearn_4tree_5_tree_23ClassificationCriterion_node_value;
  __pyx_type_7sklearn_4tree_5_tree_ClassificationCriterion.tp_base = __pyx_ptype_7sklearn_4tree_5_tree_Criterion;
  if (PyType_Ready(&__pyx_type_7sklearn_4tree_5_tree_ClassificationCriterion) < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 141; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
  __pyx_type_7sklearn_4tree_5_tree_ClassificationCriterion.tp_print = 0;
  if (__Pyx_SetVtable(__pyx_type_7sklearn_4tree_5_tree_ClassificationCriterion.tp_dict, __pyx_vtabptr_7sklearn_4tree_5_tree_ClassificationCriterion) < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 141; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
  if (__Pyx_SetAttrString(__pyx_m, "ClassificationCriterion", (PyObject *)&__pyx_type_7sklearn_4tree_5_tree_ClassificationCriterion) < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 141; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
  __pyx_ptype_7sklearn_4tree_5_tree_ClassificationCriterion = &__pyx_type_7sklearn_4tree_5_tree_ClassificationCriterion;
  __pyx_vtabptr_7sklearn_4tree_5_tree_Entropy = &__pyx_vtable_7sklearn_4tree_5_tree_Entropy;
  __pyx_vtable_7sklearn_4tree_5_tree_Entropy.__pyx_base = *__pyx_vtabptr_7sklearn_4tree_5_tree_ClassificationCriterion;
  __pyx_vtable_7sklearn_4tree_5_tree_Entropy.__pyx_base.__pyx_base.node_impurity = (double (*)(struct __pyx_obj_7sklearn_4tree_5_tree_Criterion *))__pyx_f_7sklearn_4tree_5_tree_7Entropy_node_impurity;
  __pyx_vtable_7sklearn_4tree_5_tree_Entropy.__pyx_base.__pyx_base.children_impurity = (void (*)(struct __pyx_obj_7sklearn_4tree_5_tree_Criterion *, double *, double *))__pyx_f_7sklearn_4tree_5_tree_7Entropy_children_impurity;
  __pyx_type_7sklearn_4tree_5_tree_Entropy.tp_base = __pyx_ptype_7sklearn_4tree_5_tree_ClassificationCriterion;
  if (PyType_Ready(&__pyx_type_7sklearn_4tree_5_tree_Entropy) < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 359; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
  __pyx_type_7sklearn_4tree_5_tree_Entropy.tp_print = 0;
  if (__Pyx_SetVtable(__pyx_type_7sklearn_4tree_5_tree_Entropy.tp_dict, __pyx_vtabptr_7sklearn_4tree_5_tree_Entropy) < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 359; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
  if (__Pyx_SetAttrString(__pyx_m, "Entropy", (PyObject *)&__pyx_type_7sklearn_4tree_5_tree_Entropy) < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 359; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
  __pyx_ptype_7sklearn_4tree_5_tree_Entropy = &__pyx_type_7sklearn_4tree_5_tree_Entropy;
  __pyx_vtabptr_7sklearn_4tree_5_tree_Gini = &__pyx_vtable_7sklearn_4tree_5_tree_Gini;
  __pyx_vtable_7sklearn_4tree_5_tree_Gini.__pyx_base = *__pyx_vtabptr_7sklearn_4tree_5_tree_ClassificationCriterion;
  __pyx_vtable_7sklearn_4tree_5_tree_Gini.__pyx_base.__pyx_base.node_impurity = (double (*)(struct __pyx_obj_7sklearn_4tree_5_tree_Criterion *))__pyx_f_7sklearn_4tree_5_tree_4Gini_node_impurity;
  __pyx_vtable_7sklearn_4tree_5_tree_Gini.__pyx_base.__pyx_base.children_impurity = (void (*)(struct __pyx_obj_7sklearn_4tree_5_tree_Criterion *, double *, double *))__pyx_f_7sklearn_4tree_5_tree_4Gini_children_impurity;
  __pyx_type_7sklearn_4tree_5_tree_Gini.tp_base = __pyx_ptype_7sklearn_4tree_5_tree_ClassificationCriterion;
  if (PyType_Ready(&__pyx_type_7sklearn_4tree_5_tree_Gini) < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 450; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
  __pyx_type_7sklearn_4tree_5_tree_Gini.tp_print = 0;
  if (__Pyx_SetVtable(__pyx_type_7sklearn_4tree_5_tree_Gini.tp_dict, __pyx_vtabptr_7sklearn_4tree_5_tree_Gini) < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 450; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
  if (__Pyx_SetAttrString(__pyx_m, "Gini", (PyObject *)&__pyx_type_7sklearn_4tree_5_tree_Gini) < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 450; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
  __pyx_ptype_7sklearn_4tree_5_tree_Gini = &__pyx_type_7sklearn_4tree_5_tree_Gini;
  __pyx_vtabptr_7sklearn_4tree_5_tree_RegressionCriterion = &__pyx_vtable_7sklearn_4tree_5_tree_RegressionCriterion;
  __pyx_vtable_7sklearn_4tree_5_tree_RegressionCriterion.__pyx_base = *__pyx_vtabptr_7sklearn_4tree_5_tree_Criterion;
  __pyx_vtable_7sklearn_4tree_5_tree_RegressionCriterion.__pyx_base.init = (void (*)(struct __pyx_obj_7sklearn_4tree_5_tree_Criterion *, __pyx_t_7sklearn_4tree_5_tree_DOUBLE_t *, __pyx_t_7sklearn_4tree_5_tree_SIZE_t, __pyx_t_7sklearn_4tree_5_tree_DOUBLE_t *, double, __pyx_t_7sklearn_4tree_5_tree_SIZE_t *, __pyx_t_7sklearn_4tree_5_tree_SIZE_t, __pyx_t_7sklearn_4tree_5_tree_SIZE_t))__pyx_f_7sklearn_4tree_5_tree_19RegressionCriterion_init;
  __pyx_vtable_7sklearn_4tree_5_tree_RegressionCriterion.__pyx_base.reset = (void (*)(struct __pyx_obj_7sklearn_4tree_5_tree_Criterion *))__pyx_f_7sklearn_4tree_5_tree_19RegressionCriterion_reset;
  __pyx_vtable_7sklearn_4tree_5_tree_RegressionCriterion.__pyx_base.update = (void (*)(struct __pyx_obj_7sklearn_4tree_5_tree_Criterion *, __pyx_t_7sklearn_4tree_5_tree_SIZE_t))__pyx_f_7sklearn_4tree_5_tree_19RegressionCriterion_update;
  __pyx_vtable_7sklearn_4tree_5_tree_RegressionCriterion.__pyx_base.node_impurity = (double (*)(struct __pyx_obj_7sklearn_4tree_5_tree_Criterion *))__pyx_f_7sklearn_4tree_5_tree_19RegressionCriterion_node_impurity;
  __pyx_vtable_7sklearn_4tree_5_tree_RegressionCriterion.__pyx_base.children_impurity = (void (*)(struct __pyx_obj_7sklearn_4tree_5_tree_Criterion *, double *, double *))__pyx_f_7sklearn_4tree_5_tree_19RegressionCriterion_children_impurity;
  __pyx_vtable_7sklearn_4tree_5_tree_RegressionCriterion.__pyx_base.node_value = (void (*)(struct __pyx_obj_7sklearn_4tree_5_tree_Criterion *, double *))__pyx_f_7sklearn_4tree_5_tree_19RegressionCriterion_node_value;
  __pyx_type_7sklearn_4tree_5_tree_RegressionCriterion.tp_base = __pyx_ptype_7sklearn_4tree_5_tree_Criterion;
  if (PyType_Ready(&__pyx_type_7sklearn_4tree_5_tree_RegressionCriterion) < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 544; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
  __pyx_type_7sklearn_4tree_5_tree_RegressionCriterion.tp_print = 0;
  if (__Pyx_SetVtable(__pyx_type_7sklearn_4tree_5_tree_RegressionCriterion.tp_dict, __pyx_vtabptr_7sklearn_4tree_5_tree_RegressionCriterion) < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 544; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
  if (__Pyx_SetAttrString(__pyx_m, "RegressionCriterion", (PyObject *)&__pyx_type_7sklearn_4tree_5_tree_RegressionCriterion) < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 544; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
  __pyx_ptype_7sklearn_4tree_5_tree_RegressionCriterion = &__pyx_type_7sklearn_4tree_5_tree_RegressionCriterion;
  __pyx_vtabptr_7sklearn_4tree_5_tree_MSE = &__pyx_vtable_7sklearn_4tree_5_tree_MSE;
  __pyx_vtable_7sklearn_4tree_5_tree_MSE.__pyx_base = *__pyx_vtabptr_7sklearn_4tree_5_tree_RegressionCriterion;
  __pyx_vtable_7sklearn_4tree_5_tree_MSE.__pyx_base.__pyx_base.node_impurity = (double (*)(struct __pyx_obj_7sklearn_4tree_5_tree_Criterion *))__pyx_f_7sklearn_4tree_5_tree_3MSE_node_impurity;
  __pyx_vtable_7sklearn_4tree_5_tree_MSE.__pyx_base.__pyx_base.children_impurity = (void (*)(struct __pyx_obj_7sklearn_4tree_5_tree_Criterion *, double *, double *))__pyx_f_7sklearn_4tree_5_tree_3MSE_children_impurity;
  __pyx_type_7sklearn_4tree_5_tree_MSE.tp_base = __pyx_ptype_7sklearn_4tree_5_tree_RegressionCriterion;
  if (PyType_Ready(&__pyx_type_7sklearn_4tree_5_tree_MSE) < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 827; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
  __pyx_type_7sklearn_4tree_5_tree_MSE.tp_print = 0;
  if (__Pyx_SetVtable(__pyx_type_7sklearn_4tree_5_tree_MSE.tp_dict, __pyx_vtabptr_7sklearn_4tree_5_tree_MSE) < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 827; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
  if (__Pyx_SetAttrString(__pyx_m, "MSE", (PyObject *)&__pyx_type_7sklearn_4tree_5_tree_MSE) < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 827; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
  __pyx_ptype_7sklearn_4tree_5_tree_MSE = &__pyx_type_7sklearn_4tree_5_tree_MSE;
  __pyx_vtabptr_7sklearn_4tree_5_tree_FriedmanMSE = &__pyx_vtable_7sklearn_4tree_5_tree_FriedmanMSE;
  __pyx_vtable_7sklearn_4tree_5_tree_FriedmanMSE.__pyx_base = *__pyx_vtabptr_7sklearn_4tree_5_tree_MSE;
  __pyx_vtable_7sklearn_4tree_5_tree_FriedmanMSE.__pyx_base.__pyx_base.__pyx_base.impurity_improvement = (double (*)(struct __pyx_obj_7sklearn_4tree_5_tree_Criterion *, double))__pyx_f_7sklearn_4tree_5_tree_11FriedmanMSE_impurity_improvement;
  __pyx_type_7sklearn_4tree_5_tree_FriedmanMSE.tp_base = __pyx_ptype_7sklearn_4tree_5_tree_MSE;
  if (PyType_Ready(&__pyx_type_7sklearn_4tree_5_tree_FriedmanMSE) < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 868; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
  __pyx_type_7sklearn_4tree_5_tree_FriedmanMSE.tp_print = 0;
  if (__Pyx_SetVtable(__pyx_type_7sklearn_4tree_5_tree_FriedmanMSE.tp_dict, __pyx_vtabptr_7sklearn_4tree_5_tree_FriedmanMSE) < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 868; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
  if (__Pyx_SetAttrString(__pyx_m, "FriedmanMSE", (PyObject *)&__pyx_type_7sklearn_4tree_5_tree_FriedmanMSE) < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 868; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
  __pyx_ptype_7sklearn_4tree_5_tree_FriedmanMSE = &__pyx_type_7sklearn_4tree_5_tree_FriedmanMSE;
  __pyx_vtabptr_7sklearn_4tree_5_tree_BestSplitter = &__pyx_vtable_7sklearn_4tree_5_tree_BestSplitter;
  __pyx_vtable_7sklearn_4tree_5_tree_BestSplitter.__pyx_base = *__pyx_vtabptr_7sklearn_4tree_5_tree_Splitter;
  __pyx_vtable_7sklearn_4tree_5_tree_BestSplitter.__pyx_base.node_split = (void (*)(struct __pyx_obj_7sklearn_4tree_5_tree_Splitter *, double, struct __pyx_t_7sklearn_4tree_5_tree_SplitRecord *, __pyx_t_7sklearn_4tree_5_tree_SIZE_t *))__pyx_f_7sklearn_4tree_5_tree_12BestSplitter_node_split;
  __pyx_type_7sklearn_4tree_5_tree_BestSplitter.tp_base = __pyx_ptype_7sklearn_4tree_5_tree_Splitter;
  if (PyType_Ready(&__pyx_type_7sklearn_4tree_5_tree_BestSplitter) < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1028; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
  __pyx_type_7sklearn_4tree_5_tree_BestSplitter.tp_print = 0;
  if (__Pyx_SetVtable(__pyx_type_7sklearn_4tree_5_tree_BestSplitter.tp_dict, __pyx_vtabptr_7sklearn_4tree_5_tree_BestSplitter) < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1028; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
  if (__Pyx_SetAttrString(__pyx_m, "BestSplitter", (PyObject *)&__pyx_type_7sklearn_4tree_5_tree_BestSplitter) < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1028; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
  __pyx_ptype_7sklearn_4tree_5_tree_BestSplitter = &__pyx_type_7sklearn_4tree_5_tree_BestSplitter;
  __pyx_vtabptr_7sklearn_4tree_5_tree_RandomSplitter = &__pyx_vtable_7sklearn_4tree_5_tree_RandomSplitter;
  __pyx_vtable_7sklearn_4tree_5_tree_RandomSplitter.__pyx_base = *__pyx_vtabptr_7sklearn_4tree_5_tree_Splitter;
  __pyx_vtable_7sklearn_4tree_5_tree_RandomSplitter.__pyx_base.node_split = (void (*)(struct __pyx_obj_7sklearn_4tree_5_tree_Splitter *, double, struct __pyx_t_7sklearn_4tree_5_tree_SplitRecord *, __pyx_t_7sklearn_4tree_5_tree_SIZE_t *))__pyx_f_7sklearn_4tree_5_tree_14RandomSplitter_node_split;
  __pyx_type_7sklearn_4tree_5_tree_RandomSplitter.tp_base = __pyx_ptype_7sklearn_4tree_5_tree_Splitter;
  if (PyType_Ready(&__pyx_type_7sklearn_4tree_5_tree_RandomSplitter) < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1319; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
  __pyx_type_7sklearn_4tree_5_tree_RandomSplitter.tp_print = 0;
  if (__Pyx_SetVtable(__pyx_type_7sklearn_4tree_5_tree_RandomSplitter.tp_dict, __pyx_vtabptr_7sklearn_4tree_5_tree_RandomSplitter) < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1319; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
  if (__Pyx_SetAttrString(__pyx_m, "RandomSplitter", (PyObject *)&__pyx_type_7sklearn_4tree_5_tree_RandomSplitter) < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1319; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
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    PyErr_SetString(PyExc_ImportError, "init sklearn.tree._tree");
  }
  __pyx_L0:;
  __Pyx_RefNannyFinishContext();
  #if PY_MAJOR_VERSION < 3
  return;
  #else
  return __pyx_m;
  #endif
}

/* Runtime support code */
#if CYTHON_REFNANNY
static __Pyx_RefNannyAPIStruct *__Pyx_RefNannyImportAPI(const char *modname) {
    PyObject *m = NULL, *p = NULL;
    void *r = NULL;
    m = PyImport_ImportModule((char *)modname);
    if (!m) goto end;
    p = PyObject_GetAttrString(m, (char *)"RefNannyAPI");
    if (!p) goto end;
    r = PyLong_AsVoidPtr(p);
end:
    Py_XDECREF(p);
    Py_XDECREF(m);
    return (__Pyx_RefNannyAPIStruct *)r;
}
#endif /* CYTHON_REFNANNY */

static PyObject *__Pyx_GetBuiltinName(PyObject *name) {
    PyObject* result = __Pyx_PyObject_GetAttrStr(__pyx_b, name);
    if (unlikely(!result)) {
        PyErr_Format(PyExc_NameError,
#if PY_MAJOR_VERSION >= 3
            "name '%U' is not defined", name);
#else
            "name '%.200s' is not defined", PyString_AS_STRING(name));
#endif
    }
    return result;
}

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)
{
    Py_ssize_t num_expected;
    const char *more_or_less;
    if (num_found < num_min) {
        num_expected = num_min;
        more_or_less = "at least";
    } else {
        num_expected = num_max;
        more_or_less = "at most";
    }
    if (exact) {
        more_or_less = "exactly";
    }
    PyErr_Format(PyExc_TypeError,
                 "%.200s() takes %.8s %" CYTHON_FORMAT_SSIZE_T "d positional argument%.1s (%" CYTHON_FORMAT_SSIZE_T "d given)",
                 func_name, more_or_less, num_expected,
                 (num_expected == 1) ? "" : "s", num_found);
}

static void __Pyx_RaiseDoubleKeywordsError(
    const char* func_name,
    PyObject* kw_name)
{
    PyErr_Format(PyExc_TypeError,
        #if PY_MAJOR_VERSION >= 3
        "%s() got multiple values for keyword argument '%U'", func_name, kw_name);
        #else
        "%s() got multiple values for keyword argument '%s'", func_name,
        PyString_AsString(kw_name));
        #endif
}

static int __Pyx_ParseOptionalKeywords(
    PyObject *kwds,
    PyObject **argnames[],
    PyObject *kwds2,
    PyObject *values[],
    Py_ssize_t num_pos_args,
    const char* function_name)
{
    PyObject *key = 0, *value = 0;
    Py_ssize_t pos = 0;
    PyObject*** name;
    PyObject*** first_kw_arg = argnames + num_pos_args;
    while (PyDict_Next(kwds, &pos, &key, &value)) {
        name = first_kw_arg;
        while (*name && (**name != key)) name++;
        if (*name) {
            values[name-argnames] = value;
            continue;
        }
        name = first_kw_arg;
        #if PY_MAJOR_VERSION < 3
        if (likely(PyString_CheckExact(key)) || likely(PyString_Check(key))) {
            while (*name) {
                if ((CYTHON_COMPILING_IN_PYPY || PyString_GET_SIZE(**name) == PyString_GET_SIZE(key))
                        && _PyString_Eq(**name, key)) {
                    values[name-argnames] = value;
                    break;
                }
                name++;
            }
            if (*name) continue;
            else {
                PyObject*** argname = argnames;
                while (argname != first_kw_arg) {
                    if ((**argname == key) || (
                            (CYTHON_COMPILING_IN_PYPY || PyString_GET_SIZE(**argname) == PyString_GET_SIZE(key))
                             && _PyString_Eq(**argname, key))) {
                        goto arg_passed_twice;
                    }
                    argname++;
                }
            }
        } else
        #endif
        if (likely(PyUnicode_Check(key))) {
            while (*name) {
                int cmp = (**name == key) ? 0 :
                #if !CYTHON_COMPILING_IN_PYPY && PY_MAJOR_VERSION >= 3
                    (PyUnicode_GET_SIZE(**name) != PyUnicode_GET_SIZE(key)) ? 1 :
                #endif
                    PyUnicode_Compare(**name, key);
                if (cmp < 0 && unlikely(PyErr_Occurred())) goto bad;
                if (cmp == 0) {
                    values[name-argnames] = value;
                    break;
                }
                name++;
            }
            if (*name) continue;
            else {
                PyObject*** argname = argnames;
                while (argname != first_kw_arg) {
                    int cmp = (**argname == key) ? 0 :
                    #if !CYTHON_COMPILING_IN_PYPY && PY_MAJOR_VERSION >= 3
                        (PyUnicode_GET_SIZE(**argname) != PyUnicode_GET_SIZE(key)) ? 1 :
                    #endif
                        PyUnicode_Compare(**argname, key);
                    if (cmp < 0 && unlikely(PyErr_Occurred())) goto bad;
                    if (cmp == 0) goto arg_passed_twice;
                    argname++;
                }
            }
        } else
            goto invalid_keyword_type;
        if (kwds2) {
            if (unlikely(PyDict_SetItem(kwds2, key, value))) goto bad;
        } else {
            goto invalid_keyword;
        }
    }
    return 0;
arg_passed_twice:
    __Pyx_RaiseDoubleKeywordsError(function_name, key);
    goto bad;
invalid_keyword_type:
    PyErr_Format(PyExc_TypeError,
        "%.200s() keywords must be strings", function_name);
    goto bad;
invalid_keyword:
    PyErr_Format(PyExc_TypeError,
    #if PY_MAJOR_VERSION < 3
        "%.200s() got an unexpected keyword argument '%.200s'",
        function_name, PyString_AsString(key));
    #else
        "%s() got an unexpected keyword argument '%U'",
        function_name, key);
    #endif
bad:
    return -1;
}

static void __Pyx_RaiseArgumentTypeInvalid(const char* name, PyObject *obj, PyTypeObject *type) {
    PyErr_Format(PyExc_TypeError,
        "Argument '%.200s' has incorrect type (expected %.200s, got %.200s)",
        name, type->tp_name, Py_TYPE(obj)->tp_name);
}
static CYTHON_INLINE int __Pyx_ArgTypeTest(PyObject *obj, PyTypeObject *type, int none_allowed,
    const char *name, int exact)
{
    if (unlikely(!type)) {
        PyErr_SetString(PyExc_SystemError, "Missing type object");
        return 0;
    }
    if (none_allowed && obj == Py_None) return 1;
    else if (exact) {
        if (likely(Py_TYPE(obj) == type)) return 1;
        #if PY_MAJOR_VERSION == 2
        else if ((type == &PyBaseString_Type) && likely(__Pyx_PyBaseString_CheckExact(obj))) return 1;
        #endif
    }
    else {
        if (likely(PyObject_TypeCheck(obj, type))) return 1;
    }
    __Pyx_RaiseArgumentTypeInvalid(name, obj, type);
    return 0;
}

static CYTHON_INLINE int __Pyx_IsLittleEndian(void) {
  unsigned int n = 1;
  return *(unsigned char*)(&n) != 0;
}
static void __Pyx_BufFmt_Init(__Pyx_BufFmt_Context* ctx,
                              __Pyx_BufFmt_StackElem* stack,
                              __Pyx_TypeInfo* type) {
  stack[0].field = &ctx->root;
  stack[0].parent_offset = 0;
  ctx->root.type = type;
  ctx->root.name = "buffer dtype";
  ctx->root.offset = 0;
  ctx->head = stack;
  ctx->head->field = &ctx->root;
  ctx->fmt_offset = 0;
  ctx->head->parent_offset = 0;
  ctx->new_packmode = '@';
  ctx->enc_packmode = '@';
  ctx->new_count = 1;
  ctx->enc_count = 0;
  ctx->enc_type = 0;
  ctx->is_complex = 0;
  ctx->is_valid_array = 0;
  ctx->struct_alignment = 0;
  while (type->typegroup == 'S') {
    ++ctx->head;
    ctx->head->field = type->fields;
    ctx->head->parent_offset = 0;
    type = type->fields->type;
  }
}
static int __Pyx_BufFmt_ParseNumber(const char** ts) {
    int count;
    const char* t = *ts;
    if (*t < '0' || *t > '9') {
      return -1;
    } else {
        count = *t++ - '0';
        while (*t >= '0' && *t < '9') {
            count *= 10;
            count += *t++ - '0';
        }
    }
    *ts = t;
    return count;
}
static int __Pyx_BufFmt_ExpectNumber(const char **ts) {
    int number = __Pyx_BufFmt_ParseNumber(ts);
    if (number == -1) /* First char was not a digit */
        PyErr_Format(PyExc_ValueError,\
                     "Does not understand character buffer dtype format string ('%c')", **ts);
    return number;
}
static void __Pyx_BufFmt_RaiseUnexpectedChar(char ch) {
  PyErr_Format(PyExc_ValueError,
               "Unexpected format string character: '%c'", ch);
}
static const char* __Pyx_BufFmt_DescribeTypeChar(char ch, int is_complex) {
  switch (ch) {
    case 'c': return "'char'";
    case 'b': return "'signed char'";
    case 'B': return "'unsigned char'";
    case 'h': return "'short'";
    case 'H': return "'unsigned short'";
    case 'i': return "'int'";
    case 'I': return "'unsigned int'";
    case 'l': return "'long'";
    case 'L': return "'unsigned long'";
    case 'q': return "'long long'";
    case 'Q': return "'unsigned long long'";
    case 'f': return (is_complex ? "'complex float'" : "'float'");
    case 'd': return (is_complex ? "'complex double'" : "'double'");
    case 'g': return (is_complex ? "'complex long double'" : "'long double'");
    case 'T': return "a struct";
    case 'O': return "Python object";
    case 'P': return "a pointer";
    case 's': case 'p': return "a string";
    case 0: return "end";
    default: return "unparseable format string";
  }
}
static size_t __Pyx_BufFmt_TypeCharToStandardSize(char ch, int is_complex) {
  switch (ch) {
    case '?': case 'c': case 'b': case 'B': case 's': case 'p': return 1;
    case 'h': case 'H': return 2;
    case 'i': case 'I': case 'l': case 'L': return 4;
    case 'q': case 'Q': return 8;
    case 'f': return (is_complex ? 8 : 4);
    case 'd': return (is_complex ? 16 : 8);
    case 'g': {
      PyErr_SetString(PyExc_ValueError, "Python does not define a standard format string size for long double ('g')..");
      return 0;
    }
    case 'O': case 'P': return sizeof(void*);
    default:
      __Pyx_BufFmt_RaiseUnexpectedChar(ch);
      return 0;
    }
}
static size_t __Pyx_BufFmt_TypeCharToNativeSize(char ch, int is_complex) {
  switch (ch) {
    case 'c': case 'b': case 'B': case 's': case 'p': return 1;
    case 'h': case 'H': return sizeof(short);
    case 'i': case 'I': return sizeof(int);
    case 'l': case 'L': return sizeof(long);
    #ifdef HAVE_LONG_LONG
    case 'q': case 'Q': return sizeof(PY_LONG_LONG);
    #endif
    case 'f': return sizeof(float) * (is_complex ? 2 : 1);
    case 'd': return sizeof(double) * (is_complex ? 2 : 1);
    case 'g': return sizeof(long double) * (is_complex ? 2 : 1);
    case 'O': case 'P': return sizeof(void*);
    default: {
      __Pyx_BufFmt_RaiseUnexpectedChar(ch);
      return 0;
    }
  }
}
typedef struct { char c; short x; } __Pyx_st_short;
typedef struct { char c; int x; } __Pyx_st_int;
typedef struct { char c; long x; } __Pyx_st_long;
typedef struct { char c; float x; } __Pyx_st_float;
typedef struct { char c; double x; } __Pyx_st_double;
typedef struct { char c; long double x; } __Pyx_st_longdouble;
typedef struct { char c; void *x; } __Pyx_st_void_p;
#ifdef HAVE_LONG_LONG
typedef struct { char c; PY_LONG_LONG x; } __Pyx_st_longlong;
#endif
static size_t __Pyx_BufFmt_TypeCharToAlignment(char ch, CYTHON_UNUSED int is_complex) {
  switch (ch) {
    case '?': case 'c': case 'b': case 'B': case 's': case 'p': return 1;
    case 'h': case 'H': return sizeof(__Pyx_st_short) - sizeof(short);
    case 'i': case 'I': return sizeof(__Pyx_st_int) - sizeof(int);
    case 'l': case 'L': return sizeof(__Pyx_st_long) - sizeof(long);
#ifdef HAVE_LONG_LONG
    case 'q': case 'Q': return sizeof(__Pyx_st_longlong) - sizeof(PY_LONG_LONG);
#endif
    case 'f': return sizeof(__Pyx_st_float) - sizeof(float);
    case 'd': return sizeof(__Pyx_st_double) - sizeof(double);
    case 'g': return sizeof(__Pyx_st_longdouble) - sizeof(long double);
    case 'P': case 'O': return sizeof(__Pyx_st_void_p) - sizeof(void*);
    default:
      __Pyx_BufFmt_RaiseUnexpectedChar(ch);
      return 0;
    }
}
/* These are for computing the padding at the end of the struct to align
   on the first member of the struct. This will probably the same as above,
   but we don't have any guarantees.
 */
typedef struct { short x; char c; } __Pyx_pad_short;
typedef struct { int x; char c; } __Pyx_pad_int;
typedef struct { long x; char c; } __Pyx_pad_long;
typedef struct { float x; char c; } __Pyx_pad_float;
typedef struct { double x; char c; } __Pyx_pad_double;
typedef struct { long double x; char c; } __Pyx_pad_longdouble;
typedef struct { void *x; char c; } __Pyx_pad_void_p;
#ifdef HAVE_LONG_LONG
typedef struct { PY_LONG_LONG x; char c; } __Pyx_pad_longlong;
#endif
static size_t __Pyx_BufFmt_TypeCharToPadding(char ch, CYTHON_UNUSED int is_complex) {
  switch (ch) {
    case '?': case 'c': case 'b': case 'B': case 's': case 'p': return 1;
    case 'h': case 'H': return sizeof(__Pyx_pad_short) - sizeof(short);
    case 'i': case 'I': return sizeof(__Pyx_pad_int) - sizeof(int);
    case 'l': case 'L': return sizeof(__Pyx_pad_long) - sizeof(long);
#ifdef HAVE_LONG_LONG
    case 'q': case 'Q': return sizeof(__Pyx_pad_longlong) - sizeof(PY_LONG_LONG);
#endif
    case 'f': return sizeof(__Pyx_pad_float) - sizeof(float);
    case 'd': return sizeof(__Pyx_pad_double) - sizeof(double);
    case 'g': return sizeof(__Pyx_pad_longdouble) - sizeof(long double);
    case 'P': case 'O': return sizeof(__Pyx_pad_void_p) - sizeof(void*);
    default:
      __Pyx_BufFmt_RaiseUnexpectedChar(ch);
      return 0;
    }
}
static char __Pyx_BufFmt_TypeCharToGroup(char ch, int is_complex) {
  switch (ch) {
    case 'c':
        return 'H';
    case 'b': case 'h': case 'i':
    case 'l': case 'q': case 's': case 'p':
        return 'I';
    case 'B': case 'H': case 'I': case 'L': case 'Q':
        return 'U';
    case 'f': case 'd': case 'g':
        return (is_complex ? 'C' : 'R');
    case 'O':
        return 'O';
    case 'P':
        return 'P';
    default: {
      __Pyx_BufFmt_RaiseUnexpectedChar(ch);
      return 0;
    }
  }
}
static void __Pyx_BufFmt_RaiseExpected(__Pyx_BufFmt_Context* ctx) {
  if (ctx->head == NULL || ctx->head->field == &ctx->root) {
    const char* expected;
    const char* quote;
    if (ctx->head == NULL) {
      expected = "end";
      quote = "";
    } else {
      expected = ctx->head->field->type->name;
      quote = "'";
    }
    PyErr_Format(PyExc_ValueError,
                 "Buffer dtype mismatch, expected %s%s%s but got %s",
                 quote, expected, quote,
                 __Pyx_BufFmt_DescribeTypeChar(ctx->enc_type, ctx->is_complex));
  } else {
    __Pyx_StructField* field = ctx->head->field;
    __Pyx_StructField* parent = (ctx->head - 1)->field;
    PyErr_Format(PyExc_ValueError,
                 "Buffer dtype mismatch, expected '%s' but got %s in '%s.%s'",
                 field->type->name, __Pyx_BufFmt_DescribeTypeChar(ctx->enc_type, ctx->is_complex),
                 parent->type->name, field->name);
  }
}
static int __Pyx_BufFmt_ProcessTypeChunk(__Pyx_BufFmt_Context* ctx) {
  char group;
  size_t size, offset, arraysize = 1;
  if (ctx->enc_type == 0) return 0;
  if (ctx->head->field->type->arraysize[0]) {
    int i, ndim = 0;
    if (ctx->enc_type == 's' || ctx->enc_type == 'p') {
        ctx->is_valid_array = ctx->head->field->type->ndim == 1;
        ndim = 1;
        if (ctx->enc_count != ctx->head->field->type->arraysize[0]) {
            PyErr_Format(PyExc_ValueError,
                         "Expected a dimension of size %zu, got %zu",
                         ctx->head->field->type->arraysize[0], ctx->enc_count);
            return -1;
        }
    }
    if (!ctx->is_valid_array) {
      PyErr_Format(PyExc_ValueError, "Expected %d dimensions, got %d",
                   ctx->head->field->type->ndim, ndim);
      return -1;
    }
    for (i = 0; i < ctx->head->field->type->ndim; i++) {
      arraysize *= ctx->head->field->type->arraysize[i];
    }
    ctx->is_valid_array = 0;
    ctx->enc_count = 1;
  }
  group = __Pyx_BufFmt_TypeCharToGroup(ctx->enc_type, ctx->is_complex);
  do {
    __Pyx_StructField* field = ctx->head->field;
    __Pyx_TypeInfo* type = field->type;
    if (ctx->enc_packmode == '@' || ctx->enc_packmode == '^') {
      size = __Pyx_BufFmt_TypeCharToNativeSize(ctx->enc_type, ctx->is_complex);
    } else {
      size = __Pyx_BufFmt_TypeCharToStandardSize(ctx->enc_type, ctx->is_complex);
    }
    if (ctx->enc_packmode == '@') {
      size_t align_at = __Pyx_BufFmt_TypeCharToAlignment(ctx->enc_type, ctx->is_complex);
      size_t align_mod_offset;
      if (align_at == 0) return -1;
      align_mod_offset = ctx->fmt_offset % align_at;
      if (align_mod_offset > 0) ctx->fmt_offset += align_at - align_mod_offset;
      if (ctx->struct_alignment == 0)
          ctx->struct_alignment = __Pyx_BufFmt_TypeCharToPadding(ctx->enc_type,
                                                                 ctx->is_complex);
    }
    if (type->size != size || type->typegroup != group) {
      if (type->typegroup == 'C' && type->fields != NULL) {
        size_t parent_offset = ctx->head->parent_offset + field->offset;
        ++ctx->head;
        ctx->head->field = type->fields;
        ctx->head->parent_offset = parent_offset;
        continue;
      }
      if ((type->typegroup == 'H' || group == 'H') && type->size == size) {
      } else {
          __Pyx_BufFmt_RaiseExpected(ctx);
          return -1;
      }
    }
    offset = ctx->head->parent_offset + field->offset;
    if (ctx->fmt_offset != offset) {
      PyErr_Format(PyExc_ValueError,
                   "Buffer dtype mismatch; next field is at offset %" CYTHON_FORMAT_SSIZE_T "d but %" CYTHON_FORMAT_SSIZE_T "d expected",
                   (Py_ssize_t)ctx->fmt_offset, (Py_ssize_t)offset);
      return -1;
    }
    ctx->fmt_offset += size;
    if (arraysize)
      ctx->fmt_offset += (arraysize - 1) * size;
    --ctx->enc_count; /* Consume from buffer string */
    while (1) {
      if (field == &ctx->root) {
        ctx->head = NULL;
        if (ctx->enc_count != 0) {
          __Pyx_BufFmt_RaiseExpected(ctx);
          return -1;
        }
        break; /* breaks both loops as ctx->enc_count == 0 */
      }
      ctx->head->field = ++field;
      if (field->type == NULL) {
        --ctx->head;
        field = ctx->head->field;
        continue;
      } else if (field->type->typegroup == 'S') {
        size_t parent_offset = ctx->head->parent_offset + field->offset;
        if (field->type->fields->type == NULL) continue; /* empty struct */
        field = field->type->fields;
        ++ctx->head;
        ctx->head->field = field;
        ctx->head->parent_offset = parent_offset;
        break;
      } else {
        break;
      }
    }
  } while (ctx->enc_count);
  ctx->enc_type = 0;
  ctx->is_complex = 0;
  return 0;
}
static CYTHON_INLINE PyObject *
__pyx_buffmt_parse_array(__Pyx_BufFmt_Context* ctx, const char** tsp)
{
    const char *ts = *tsp;
    int i = 0, number;
    int ndim = ctx->head->field->type->ndim;
;
    ++ts;
    if (ctx->new_count != 1) {
        PyErr_SetString(PyExc_ValueError,
                        "Cannot handle repeated arrays in format string");
        return NULL;
    }
    if (__Pyx_BufFmt_ProcessTypeChunk(ctx) == -1) return NULL;
    while (*ts && *ts != ')') {
        switch (*ts) {
            case ' ': case '\f': case '\r': case '\n': case '\t': case '\v':  continue;
            default:  break;  /* not a 'break' in the loop */
        }
        number = __Pyx_BufFmt_ExpectNumber(&ts);
        if (number == -1) return NULL;
        if (i < ndim && (size_t) number != ctx->head->field->type->arraysize[i])
            return PyErr_Format(PyExc_ValueError,
                        "Expected a dimension of size %zu, got %d",
                        ctx->head->field->type->arraysize[i], number);
        if (*ts != ',' && *ts != ')')
            return PyErr_Format(PyExc_ValueError,
                                "Expected a comma in format string, got '%c'", *ts);
        if (*ts == ',') ts++;
        i++;
    }
    if (i != ndim)
        return PyErr_Format(PyExc_ValueError, "Expected %d dimension(s), got %d",
                            ctx->head->field->type->ndim, i);
    if (!*ts) {
        PyErr_SetString(PyExc_ValueError,
                        "Unexpected end of format string, expected ')'");
        return NULL;
    }
    ctx->is_valid_array = 1;
    ctx->new_count = 1;
    *tsp = ++ts;
    return Py_None;
}
static const char* __Pyx_BufFmt_CheckString(__Pyx_BufFmt_Context* ctx, const char* ts) {
  int got_Z = 0;
  while (1) {
    switch(*ts) {
      case 0:
        if (ctx->enc_type != 0 && ctx->head == NULL) {
          __Pyx_BufFmt_RaiseExpected(ctx);
          return NULL;
        }
        if (__Pyx_BufFmt_ProcessTypeChunk(ctx) == -1) return NULL;
        if (ctx->head != NULL) {
          __Pyx_BufFmt_RaiseExpected(ctx);
          return NULL;
        }
                return ts;
      case ' ':
      case 10:
      case 13:
        ++ts;
        break;
      case '<':
        if (!__Pyx_IsLittleEndian()) {
          PyErr_SetString(PyExc_ValueError, "Little-endian buffer not supported on big-endian compiler");
          return NULL;
        }
        ctx->new_packmode = '=';
        ++ts;
        break;
      case '>':
      case '!':
        if (__Pyx_IsLittleEndian()) {
          PyErr_SetString(PyExc_ValueError, "Big-endian buffer not supported on little-endian compiler");
          return NULL;
        }
        ctx->new_packmode = '=';
        ++ts;
        break;
      case '=':
      case '@':
      case '^':
        ctx->new_packmode = *ts++;
        break;
      case 'T': /* substruct */
        {
          const char* ts_after_sub;
          size_t i, struct_count = ctx->new_count;
          size_t struct_alignment = ctx->struct_alignment;
          ctx->new_count = 1;
          ++ts;
          if (*ts != '{') {
            PyErr_SetString(PyExc_ValueError, "Buffer acquisition: Expected '{' after 'T'");
            return NULL;
          }
          if (__Pyx_BufFmt_ProcessTypeChunk(ctx) == -1) return NULL;
          ctx->enc_type = 0; /* Erase processed last struct element */
          ctx->enc_count = 0;
          ctx->struct_alignment = 0;
          ++ts;
          ts_after_sub = ts;
          for (i = 0; i != struct_count; ++i) {
            ts_after_sub = __Pyx_BufFmt_CheckString(ctx, ts);
            if (!ts_after_sub) return NULL;
          }
          ts = ts_after_sub;
          if (struct_alignment) ctx->struct_alignment = struct_alignment;
        }
        break;
      case '}': /* end of substruct; either repeat or move on */
        {
          size_t alignment = ctx->struct_alignment;
          ++ts;
          if (__Pyx_BufFmt_ProcessTypeChunk(ctx) == -1) return NULL;
          ctx->enc_type = 0; /* Erase processed last struct element */
          if (alignment && ctx->fmt_offset % alignment) {
            ctx->fmt_offset += alignment - (ctx->fmt_offset % alignment);
          }
        }
        return ts;
      case 'x':
        if (__Pyx_BufFmt_ProcessTypeChunk(ctx) == -1) return NULL;
        ctx->fmt_offset += ctx->new_count;
        ctx->new_count = 1;
        ctx->enc_count = 0;
        ctx->enc_type = 0;
        ctx->enc_packmode = ctx->new_packmode;
        ++ts;
        break;
      case 'Z':
        got_Z = 1;
        ++ts;
        if (*ts != 'f' && *ts != 'd' && *ts != 'g') {
          __Pyx_BufFmt_RaiseUnexpectedChar('Z');
          return NULL;
        }        /* fall through */
      case 'c': case 'b': case 'B': case 'h': case 'H': case 'i': case 'I':
      case 'l': case 'L': case 'q': case 'Q':
      case 'f': case 'd': case 'g':
      case 'O': case 's': case 'p':
        if (ctx->enc_type == *ts && got_Z == ctx->is_complex &&
            ctx->enc_packmode == ctx->new_packmode) {
          ctx->enc_count += ctx->new_count;
        } else {
          if (__Pyx_BufFmt_ProcessTypeChunk(ctx) == -1) return NULL;
          ctx->enc_count = ctx->new_count;
          ctx->enc_packmode = ctx->new_packmode;
          ctx->enc_type = *ts;
          ctx->is_complex = got_Z;
        }
        ++ts;
        ctx->new_count = 1;
        got_Z = 0;
        break;
      case ':':
        ++ts;
        while(*ts != ':') ++ts;
        ++ts;
        break;
      case '(':
        if (!__pyx_buffmt_parse_array(ctx, &ts)) return NULL;
        break;
      default:
        {
          int number = __Pyx_BufFmt_ExpectNumber(&ts);
          if (number == -1) return NULL;
          ctx->new_count = (size_t)number;
        }
    }
  }
}
static CYTHON_INLINE void __Pyx_ZeroBuffer(Py_buffer* buf) {
  buf->buf = NULL;
  buf->obj = NULL;
  buf->strides = __Pyx_zeros;
  buf->shape = __Pyx_zeros;
  buf->suboffsets = __Pyx_minusones;
}
static CYTHON_INLINE int __Pyx_GetBufferAndValidate(
        Py_buffer* buf, PyObject* obj,  __Pyx_TypeInfo* dtype, int flags,
        int nd, int cast, __Pyx_BufFmt_StackElem* stack)
{
  if (obj == Py_None || obj == NULL) {
    __Pyx_ZeroBuffer(buf);
    return 0;
  }
  buf->buf = NULL;
  if (__Pyx_GetBuffer(obj, buf, flags) == -1) goto fail;
  if (buf->ndim != nd) {
    PyErr_Format(PyExc_ValueError,
                 "Buffer has wrong number of dimensions (expected %d, got %d)",
                 nd, buf->ndim);
    goto fail;
  }
  if (!cast) {
    __Pyx_BufFmt_Context ctx;
    __Pyx_BufFmt_Init(&ctx, stack, dtype);
    if (!__Pyx_BufFmt_CheckString(&ctx, buf->format)) goto fail;
  }
  if ((unsigned)buf->itemsize != dtype->size) {
    PyErr_Format(PyExc_ValueError,
      "Item size of buffer (%" CYTHON_FORMAT_SSIZE_T "d byte%s) does not match size of '%s' (%" CYTHON_FORMAT_SSIZE_T "d byte%s)",
      buf->itemsize, (buf->itemsize > 1) ? "s" : "",
      dtype->name, (Py_ssize_t)dtype->size, (dtype->size > 1) ? "s" : "");
    goto fail;
  }
  if (buf->suboffsets == NULL) buf->suboffsets = __Pyx_minusones;
  return 0;
fail:;
  __Pyx_ZeroBuffer(buf);
  return -1;
}
static CYTHON_INLINE void __Pyx_SafeReleaseBuffer(Py_buffer* info) {
  if (info->buf == NULL) return;
  if (info->suboffsets == __Pyx_minusones) info->suboffsets = NULL;
  __Pyx_ReleaseBuffer(info);
}

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 CYTHON_COMPILING_IN_CPYTHON
static CYTHON_INLINE PyObject* __Pyx_PyObject_Call(PyObject *func, PyObject *arg, PyObject *kw) {
    PyObject *result;
    ternaryfunc call = func->ob_type->tp_call;
    if (unlikely(!call))
        return PyObject_Call(func, arg, kw);
#if PY_VERSION_HEX >= 0x02060000
    if (unlikely(Py_EnterRecursiveCall((char*)" while calling a Python object")))
        return NULL;
#endif
    result = (*call)(func, arg, kw);
#if PY_VERSION_HEX >= 0x02060000
    Py_LeaveRecursiveCall();
#endif
    if (unlikely(!result) && unlikely(!PyErr_Occurred())) {
        PyErr_SetString(
            PyExc_SystemError,
            "NULL result without error in PyObject_Call");
    }
    return result;
}
#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 CYTHON_INLINE int __Pyx_TypeTest(PyObject *obj, PyTypeObject *type) {
    if (unlikely(!type)) {
        PyErr_SetString(PyExc_SystemError, "Missing type object");
        return 0;
    }
    if (likely(PyObject_TypeCheck(obj, type)))
        return 1;
    PyErr_Format(PyExc_TypeError, "Cannot convert %.200s to %.200s",
                 Py_TYPE(obj)->tp_name, type->tp_name);
    return 0;
}

static CYTHON_INLINE PyObject *__Pyx_GetModuleGlobalName(PyObject *name) {
    PyObject *result;
#if CYTHON_COMPILING_IN_CPYTHON
    result = PyDict_GetItem(__pyx_d, name);
    if (result) {
        Py_INCREF(result);
    } else {
#else
    result = PyObject_GetItem(__pyx_d, name);
    if (!result) {
        PyErr_Clear();
#endif
        result = __Pyx_GetBuiltinName(name);
    }
    return result;
}

static CYTHON_INLINE PyObject* __Pyx_PyObject_GetSlice(
        PyObject* obj, Py_ssize_t cstart, Py_ssize_t cstop,
        PyObject** _py_start, PyObject** _py_stop, PyObject** _py_slice,
        int has_cstart, int has_cstop, CYTHON_UNUSED int wraparound) {
#if CYTHON_COMPILING_IN_CPYTHON
    PyMappingMethods* mp;
#if PY_MAJOR_VERSION < 3
    PySequenceMethods* ms = Py_TYPE(obj)->tp_as_sequence;
    if (likely(ms && ms->sq_slice)) {
        if (!has_cstart) {
            if (_py_start && (*_py_start != Py_None)) {
                cstart = __Pyx_PyIndex_AsSsize_t(*_py_start);
                if ((cstart == (Py_ssize_t)-1) && PyErr_Occurred()) goto bad;
            } else
                cstart = 0;
        }
        if (!has_cstop) {
            if (_py_stop && (*_py_stop != Py_None)) {
                cstop = __Pyx_PyIndex_AsSsize_t(*_py_stop);
                if ((cstop == (Py_ssize_t)-1) && PyErr_Occurred()) goto bad;
            } else
                cstop = PY_SSIZE_T_MAX;
        }
        if (wraparound && unlikely((cstart < 0) | (cstop < 0)) && likely(ms->sq_length)) {
            Py_ssize_t l = ms->sq_length(obj);
            if (likely(l >= 0)) {
                if (cstop < 0) {
                    cstop += l;
                    if (cstop < 0) cstop = 0;
                }
                if (cstart < 0) {
                    cstart += l;
                    if (cstart < 0) cstart = 0;
                }
            } else {
                if (PyErr_ExceptionMatches(PyExc_OverflowError))
                    PyErr_Clear();
                else
                    goto bad;
            }
        }
        return ms->sq_slice(obj, cstart, cstop);
    }
#endif
    mp = Py_TYPE(obj)->tp_as_mapping;
    if (likely(mp && mp->mp_subscript))
#endif
    {
        PyObject* result;
        PyObject *py_slice, *py_start, *py_stop;
        if (_py_slice) {
            py_slice = *_py_slice;
        } else {
            PyObject* owned_start = NULL;
            PyObject* owned_stop = NULL;
            if (_py_start) {
                py_start = *_py_start;
            } else {
                if (has_cstart) {
                    owned_start = py_start = PyInt_FromSsize_t(cstart);
                    if (unlikely(!py_start)) goto bad;
                } else
                    py_start = Py_None;
            }
            if (_py_stop) {
                py_stop = *_py_stop;
            } else {
                if (has_cstop) {
                    owned_stop = py_stop = PyInt_FromSsize_t(cstop);
                    if (unlikely(!py_stop)) {
                        Py_XDECREF(owned_start);
                        goto bad;
                    }
                } else
                    py_stop = Py_None;
            }
            py_slice = PySlice_New(py_start, py_stop, Py_None);
            Py_XDECREF(owned_start);
            Py_XDECREF(owned_stop);
            if (unlikely(!py_slice)) goto bad;
        }
#if CYTHON_COMPILING_IN_CPYTHON
        result = mp->mp_subscript(obj, py_slice);
#else
        result = PyObject_GetItem(obj, py_slice);
#endif
        if (!_py_slice) {
            Py_DECREF(py_slice);
        }
        return result;
    }
    PyErr_Format(PyExc_TypeError,
        "'%.200s' object is unsliceable", Py_TYPE(obj)->tp_name);
bad:
    return NULL;
}

#if PY_MAJOR_VERSION < 3
static void __Pyx_Raise(PyObject *type, PyObject *value, PyObject *tb,
                        CYTHON_UNUSED PyObject *cause) {
    Py_XINCREF(type);
    if (!value || value == Py_None)
        value = NULL;
    else
        Py_INCREF(value);
    if (!tb || tb == Py_None)
        tb = NULL;
    else {
        Py_INCREF(tb);
        if (!PyTraceBack_Check(tb)) {
            PyErr_SetString(PyExc_TypeError,
                "raise: arg 3 must be a traceback or None");
            goto raise_error;
        }
    }
    #if PY_VERSION_HEX < 0x02050000
    if (PyClass_Check(type)) {
    #else
    if (PyType_Check(type)) {
    #endif
#if CYTHON_COMPILING_IN_PYPY
        if (!value) {
            Py_INCREF(Py_None);
            value = Py_None;
        }
#endif
        PyErr_NormalizeException(&type, &value, &tb);
    } else {
        if (value) {
            PyErr_SetString(PyExc_TypeError,
                "instance exception may not have a separate value");
            goto raise_error;
        }
        value = type;
        #if PY_VERSION_HEX < 0x02050000
        if (PyInstance_Check(type)) {
            type = (PyObject*) ((PyInstanceObject*)type)->in_class;
            Py_INCREF(type);
        } else {
            type = 0;
            PyErr_SetString(PyExc_TypeError,
                "raise: exception must be an old-style class or instance");
            goto raise_error;
        }
        #else
        type = (PyObject*) Py_TYPE(type);
        Py_INCREF(type);
        if (!PyType_IsSubtype((PyTypeObject *)type, (PyTypeObject *)PyExc_BaseException)) {
            PyErr_SetString(PyExc_TypeError,
                "raise: exception class must be a subclass of BaseException");
            goto raise_error;
        }
        #endif
    }
    __Pyx_ErrRestore(type, value, tb);
    return;
raise_error:
    Py_XDECREF(value);
    Py_XDECREF(type);
    Py_XDECREF(tb);
    return;
}
#else /* Python 3+ */
static void __Pyx_Raise(PyObject *type, PyObject *value, PyObject *tb, PyObject *cause) {
    PyObject* owned_instance = NULL;
    if (tb == Py_None) {
        tb = 0;
    } else if (tb && !PyTraceBack_Check(tb)) {
        PyErr_SetString(PyExc_TypeError,
            "raise: arg 3 must be a traceback or None");
        goto bad;
    }
    if (value == Py_None)
        value = 0;
    if (PyExceptionInstance_Check(type)) {
        if (value) {
            PyErr_SetString(PyExc_TypeError,
                "instance exception may not have a separate value");
            goto bad;
        }
        value = type;
        type = (PyObject*) Py_TYPE(value);
    } else if (PyExceptionClass_Check(type)) {
        PyObject *instance_class = NULL;
        if (value && PyExceptionInstance_Check(value)) {
            instance_class = (PyObject*) Py_TYPE(value);
            if (instance_class != type) {
                if (PyObject_IsSubclass(instance_class, type)) {
                    type = instance_class;
                } else {
                    instance_class = NULL;
                }
            }
        }
        if (!instance_class) {
            PyObject *args;
            if (!value)
                args = PyTuple_New(0);
            else if (PyTuple_Check(value)) {
                Py_INCREF(value);
                args = value;
            } else
                args = PyTuple_Pack(1, value);
            if (!args)
                goto bad;
            owned_instance = PyObject_Call(type, args, NULL);
            Py_DECREF(args);
            if (!owned_instance)
                goto bad;
            value = owned_instance;
            if (!PyExceptionInstance_Check(value)) {
                PyErr_Format(PyExc_TypeError,
                             "calling %R should have returned an instance of "
                             "BaseException, not %R",
                             type, Py_TYPE(value));
                goto bad;
            }
        }
    } else {
        PyErr_SetString(PyExc_TypeError,
            "raise: exception class must be a subclass of BaseException");
        goto bad;
    }
#if PY_VERSION_HEX >= 0x03030000
    if (cause) {
#else
    if (cause && cause != Py_None) {
#endif
        PyObject *fixed_cause;
        if (cause == Py_None) {
            fixed_cause = NULL;
        } else if (PyExceptionClass_Check(cause)) {
            fixed_cause = PyObject_CallObject(cause, NULL);
            if (fixed_cause == NULL)
                goto bad;
        } else if (PyExceptionInstance_Check(cause)) {
            fixed_cause = cause;
            Py_INCREF(fixed_cause);
        } else {
            PyErr_SetString(PyExc_TypeError,
                            "exception causes must derive from "
                            "BaseException");
            goto bad;
        }
        PyException_SetCause(value, fixed_cause);
    }
    PyErr_SetObject(type, value);
    if (tb) {
        PyThreadState *tstate = PyThreadState_GET();
        PyObject* tmp_tb = tstate->curexc_traceback;
        if (tb != tmp_tb) {
            Py_INCREF(tb);
            tstate->curexc_traceback = tb;
            Py_XDECREF(tmp_tb);
        }
    }
bad:
    Py_XDECREF(owned_instance);
    return;
}
#endif

static CYTHON_INLINE PyObject *__Pyx_GetItemInt_Generic(PyObject *o, PyObject* j) {
    PyObject *r;
    if (!j) return NULL;
    r = PyObject_GetItem(o, j);
    Py_DECREF(j);
    return r;
}
static CYTHON_INLINE PyObject *__Pyx_GetItemInt_List_Fast(PyObject *o, Py_ssize_t i,
                                                              int wraparound, int boundscheck) {
#if CYTHON_COMPILING_IN_CPYTHON
    if (wraparound & unlikely(i < 0)) i += PyList_GET_SIZE(o);
    if ((!boundscheck) || likely((0 <= i) & (i < PyList_GET_SIZE(o)))) {
        PyObject *r = PyList_GET_ITEM(o, i);
        Py_INCREF(r);
        return r;
    }
    return __Pyx_GetItemInt_Generic(o, PyInt_FromSsize_t(i));
#else
    return PySequence_GetItem(o, i);
#endif
}
static CYTHON_INLINE PyObject *__Pyx_GetItemInt_Tuple_Fast(PyObject *o, Py_ssize_t i,
                                                              int wraparound, int boundscheck) {
#if CYTHON_COMPILING_IN_CPYTHON
    if (wraparound & unlikely(i < 0)) i += PyTuple_GET_SIZE(o);
    if ((!boundscheck) || likely((0 <= i) & (i < PyTuple_GET_SIZE(o)))) {
        PyObject *r = PyTuple_GET_ITEM(o, i);
        Py_INCREF(r);
        return r;
    }
    return __Pyx_GetItemInt_Generic(o, PyInt_FromSsize_t(i));
#else
    return PySequence_GetItem(o, i);
#endif
}
static CYTHON_INLINE PyObject *__Pyx_GetItemInt_Fast(PyObject *o, Py_ssize_t i,
                                                     int is_list, int wraparound, int boundscheck) {
#if CYTHON_COMPILING_IN_CPYTHON
    if (is_list || PyList_CheckExact(o)) {
        Py_ssize_t n = ((!wraparound) | likely(i >= 0)) ? i : i + PyList_GET_SIZE(o);
        if ((!boundscheck) || (likely((n >= 0) & (n < PyList_GET_SIZE(o))))) {
            PyObject *r = PyList_GET_ITEM(o, n);
            Py_INCREF(r);
            return r;
        }
    }
    else if (PyTuple_CheckExact(o)) {
        Py_ssize_t n = ((!wraparound) | likely(i >= 0)) ? i : i + PyTuple_GET_SIZE(o);
        if ((!boundscheck) || likely((n >= 0) & (n < PyTuple_GET_SIZE(o)))) {
            PyObject *r = PyTuple_GET_ITEM(o, n);
            Py_INCREF(r);
            return r;
        }
    } else {
        PySequenceMethods *m = Py_TYPE(o)->tp_as_sequence;
        if (likely(m && m->sq_item)) {
            if (wraparound && unlikely(i < 0) && likely(m->sq_length)) {
                Py_ssize_t l = m->sq_length(o);
                if (likely(l >= 0)) {
                    i += l;
                } else {
                    if (PyErr_ExceptionMatches(PyExc_OverflowError))
                        PyErr_Clear();
                    else
                        return NULL;
                }
            }
            return m->sq_item(o, i);
        }
    }
#else
    if (is_list || PySequence_Check(o)) {
        return PySequence_GetItem(o, i);
    }
#endif
    return __Pyx_GetItemInt_Generic(o, PyInt_FromSsize_t(i));
}

static void __Pyx_RaiseBufferFallbackError(void) {
  PyErr_SetString(PyExc_ValueError,
     "Buffer acquisition failed on assignment; and then reacquiring the old buffer failed too!");
}

static CYTHON_INLINE void __Pyx_RaiseTooManyValuesError(Py_ssize_t expected) {
    PyErr_Format(PyExc_ValueError,
                 "too many values to unpack (expected %" CYTHON_FORMAT_SSIZE_T "d)", expected);
}

static CYTHON_INLINE void __Pyx_RaiseNeedMoreValuesError(Py_ssize_t index) {
    PyErr_Format(PyExc_ValueError,
                 "need more than %" CYTHON_FORMAT_SSIZE_T "d value%.1s to unpack",
                 index, (index == 1) ? "" : "s");
}

static CYTHON_INLINE void __Pyx_RaiseNoneNotIterableError(void) {
    PyErr_SetString(PyExc_TypeError, "'NoneType' object is not iterable");
}

static int __Pyx_SetVtable(PyObject *dict, void *vtable) {
#if PY_VERSION_HEX >= 0x02070000 && !(PY_MAJOR_VERSION==3&&PY_MINOR_VERSION==0)
    PyObject *ob = PyCapsule_New(vtable, 0, 0);
#else
    PyObject *ob = PyCObject_FromVoidPtr(vtable, 0);
#endif
    if (!ob)
        goto bad;
    if (PyDict_SetItem(dict, __pyx_n_s_pyx_vtable, ob) < 0)
        goto bad;
    Py_DECREF(ob);
    return 0;
bad:
    Py_XDECREF(ob);
    return -1;
}

static void* __Pyx_GetVtable(PyObject *dict) {
    void* ptr;
    PyObject *ob = PyObject_GetItem(dict, __pyx_n_s_pyx_vtable);
    if (!ob)
        goto bad;
#if PY_VERSION_HEX >= 0x02070000 && !(PY_MAJOR_VERSION==3&&PY_MINOR_VERSION==0)
    ptr = PyCapsule_GetPointer(ob, 0);
#else
    ptr = PyCObject_AsVoidPtr(ob);
#endif
    if (!ptr && !PyErr_Occurred())
        PyErr_SetString(PyExc_RuntimeError, "invalid vtable found for imported type");
    Py_DECREF(ob);
    return ptr;
bad:
    Py_XDECREF(ob);
    return NULL;
}

static PyObject* __Pyx_ImportFrom(PyObject* module, PyObject* name) {
    PyObject* value = __Pyx_PyObject_GetAttrStr(module, name);
    if (unlikely(!value) && PyErr_ExceptionMatches(PyExc_AttributeError)) {
        PyErr_Format(PyExc_ImportError,
        #if PY_MAJOR_VERSION < 3
            "cannot import name %.230s", PyString_AS_STRING(name));
        #else
            "cannot import name %S", name);
        #endif
    }
    return value;
}

static CYTHON_INLINE PyObject* __Pyx_PyInt_From_Py_intptr_t(Py_intptr_t value) {
    const Py_intptr_t neg_one = (Py_intptr_t) -1, const_zero = 0;
    const int is_unsigned = neg_one > const_zero;
    if (is_unsigned) {
        if (sizeof(Py_intptr_t) < sizeof(long)) {
            return PyInt_FromLong((long) value);
        } else if (sizeof(Py_intptr_t) <= sizeof(unsigned long)) {
            return PyLong_FromUnsignedLong((unsigned long) value);
        } else if (sizeof(Py_intptr_t) <= sizeof(unsigned long long)) {
            return PyLong_FromUnsignedLongLong((unsigned long long) value);
        }
    } else {
        if (sizeof(Py_intptr_t) <= sizeof(long)) {
            return PyInt_FromLong((long) value);
        } else if (sizeof(Py_intptr_t) <= sizeof(long long)) {
            return PyLong_FromLongLong((long long) value);
        }
    }
    {
        int one = 1; int little = (int)*(unsigned char *)&one;
        unsigned char *bytes = (unsigned char *)&value;
        return _PyLong_FromByteArray(bytes, sizeof(Py_intptr_t),
                                     little, !is_unsigned);
    }
}

#define __PYX_VERIFY_RETURN_INT(target_type, func_type, func)             \
    {                                                                     \
        func_type value = func(x);                                        \
        if (sizeof(target_type) < sizeof(func_type)) {                    \
            if (unlikely(value != (func_type) (target_type) value)) {     \
                func_type zero = 0;                                       \
                PyErr_SetString(PyExc_OverflowError,                      \
                    (is_unsigned && unlikely(value < zero)) ?             \
                    "can't convert negative value to " #target_type :     \
                    "value too large to convert to " #target_type);       \
                return (target_type) -1;                                  \
            }                                                             \
        }                                                                 \
        return (target_type) value;                                       \
    }

#if CYTHON_COMPILING_IN_CPYTHON && PY_MAJOR_VERSION >= 3
 #if CYTHON_USE_PYLONG_INTERNALS
  #include "longintrepr.h"
 #endif
#endif
static CYTHON_INLINE Py_intptr_t __Pyx_PyInt_As_Py_intptr_t(PyObject *x) {
    const Py_intptr_t neg_one = (Py_intptr_t) -1, const_zero = 0;
    const int is_unsigned = neg_one > const_zero;
#if PY_MAJOR_VERSION < 3
    if (likely(PyInt_Check(x))) {
        if (sizeof(Py_intptr_t) < sizeof(long)) {
            __PYX_VERIFY_RETURN_INT(Py_intptr_t, long, PyInt_AS_LONG)
        } else {
            long val = PyInt_AS_LONG(x);
            if (is_unsigned && unlikely(val < 0)) {
                PyErr_SetString(PyExc_OverflowError,
                                "can't convert negative value to Py_intptr_t");
                return (Py_intptr_t) -1;
            }
            return (Py_intptr_t) val;
        }
    } else
#endif
    if (likely(PyLong_Check(x))) {
        if (is_unsigned) {
#if CYTHON_COMPILING_IN_CPYTHON && PY_MAJOR_VERSION >= 3
 #if CYTHON_USE_PYLONG_INTERNALS
            if (sizeof(digit) <= sizeof(Py_intptr_t)) {
                switch (Py_SIZE(x)) {
                    case  0: return 0;
                    case  1: return (Py_intptr_t) ((PyLongObject*)x)->ob_digit[0];
                }
            }
 #endif
#endif
            if (unlikely(Py_SIZE(x) < 0)) {
                PyErr_SetString(PyExc_OverflowError,
                                "can't convert negative value to Py_intptr_t");
                return (Py_intptr_t) -1;
            }
            if (sizeof(Py_intptr_t) <= sizeof(unsigned long)) {
                __PYX_VERIFY_RETURN_INT(Py_intptr_t, unsigned long, PyLong_AsUnsignedLong)
            } else if (sizeof(Py_intptr_t) <= sizeof(unsigned long long)) {
                __PYX_VERIFY_RETURN_INT(Py_intptr_t, unsigned long long, PyLong_AsUnsignedLongLong)
            }
        } else {
#if CYTHON_COMPILING_IN_CPYTHON && PY_MAJOR_VERSION >= 3
 #if CYTHON_USE_PYLONG_INTERNALS
            if (sizeof(digit) <= sizeof(Py_intptr_t)) {
                switch (Py_SIZE(x)) {
                    case  0: return 0;
                    case  1: return +(Py_intptr_t) ((PyLongObject*)x)->ob_digit[0];
                    case -1: return -(Py_intptr_t) ((PyLongObject*)x)->ob_digit[0];
                }
            }
 #endif
#endif
            if (sizeof(Py_intptr_t) <= sizeof(long)) {
                __PYX_VERIFY_RETURN_INT(Py_intptr_t, long, PyLong_AsLong)
            } else if (sizeof(Py_intptr_t) <= sizeof(long long)) {
                __PYX_VERIFY_RETURN_INT(Py_intptr_t, long long, PyLong_AsLongLong)
            }
        }
        {
#if CYTHON_COMPILING_IN_PYPY && !defined(_PyLong_AsByteArray)
            PyErr_SetString(PyExc_RuntimeError,
                            "_PyLong_AsByteArray() not available in PyPy, cannot convert large numbers");
#else
            Py_intptr_t val;
            PyObject *v = __Pyx_PyNumber_Int(x);
 #if PY_MAJOR_VERSION < 3
            if (likely(v) && !PyLong_Check(v)) {
                PyObject *tmp = v;
                v = PyNumber_Long(tmp);
                Py_DECREF(tmp);
            }
 #endif
            if (likely(v)) {
                int one = 1; int is_little = (int)*(unsigned char *)&one;
                unsigned char *bytes = (unsigned char *)&val;
                int ret = _PyLong_AsByteArray((PyLongObject *)v,
                                              bytes, sizeof(val),
                                              is_little, !is_unsigned);
                Py_DECREF(v);
                if (likely(!ret))
                    return val;
            }
#endif
            return (Py_intptr_t) -1;
        }
    } else {
        Py_intptr_t val;
        PyObject *tmp = __Pyx_PyNumber_Int(x);
        if (!tmp) return (Py_intptr_t) -1;
        val = __Pyx_PyInt_As_Py_intptr_t(tmp);
        Py_DECREF(tmp);
        return val;
    }
}

static PyObject *__Pyx_Import(PyObject *name, PyObject *from_list, int level) {
    PyObject *empty_list = 0;
    PyObject *module = 0;
    PyObject *global_dict = 0;
    PyObject *empty_dict = 0;
    PyObject *list;
    #if PY_VERSION_HEX < 0x03030000
    PyObject *py_import;
    py_import = __Pyx_PyObject_GetAttrStr(__pyx_b, __pyx_n_s_import);
    if (!py_import)
        goto bad;
    #endif
    if (from_list)
        list = from_list;
    else {
        empty_list = PyList_New(0);
        if (!empty_list)
            goto bad;
        list = empty_list;
    }
    global_dict = PyModule_GetDict(__pyx_m);
    if (!global_dict)
        goto bad;
    empty_dict = PyDict_New();
    if (!empty_dict)
        goto bad;
    #if PY_VERSION_HEX >= 0x02050000
    {
        #if PY_MAJOR_VERSION >= 3
        if (level == -1) {
            if (strchr(__Pyx_MODULE_NAME, '.')) {
                #if PY_VERSION_HEX < 0x03030000
                PyObject *py_level = PyInt_FromLong(1);
                if (!py_level)
                    goto bad;
                module = PyObject_CallFunctionObjArgs(py_import,
                    name, global_dict, empty_dict, list, py_level, NULL);
                Py_DECREF(py_level);
                #else
                module = PyImport_ImportModuleLevelObject(
                    name, global_dict, empty_dict, list, 1);
                #endif
                if (!module) {
                    if (!PyErr_ExceptionMatches(PyExc_ImportError))
                        goto bad;
                    PyErr_Clear();
                }
            }
            level = 0; /* try absolute import on failure */
        }
        #endif
        if (!module) {
            #if PY_VERSION_HEX < 0x03030000
            PyObject *py_level = PyInt_FromLong(level);
            if (!py_level)
                goto bad;
            module = PyObject_CallFunctionObjArgs(py_import,
                name, global_dict, empty_dict, list, py_level, NULL);
            Py_DECREF(py_level);
            #else
            module = PyImport_ImportModuleLevelObject(
                name, global_dict, empty_dict, list, level);
            #endif
        }
    }
    #else
    if (level>0) {
        PyErr_SetString(PyExc_RuntimeError, "Relative import is not supported for Python <=2.4.");
        goto bad;
    }
    module = PyObject_CallFunctionObjArgs(py_import,
        name, global_dict, empty_dict, list, NULL);
    #endif
bad:
    #if PY_VERSION_HEX < 0x03030000
    Py_XDECREF(py_import);
    #endif
    Py_XDECREF(empty_list);
    Py_XDECREF(empty_dict);
    return module;
}

#if PY_MAJOR_VERSION < 3
static int __Pyx_GetBuffer(PyObject *obj, Py_buffer *view, int flags) {
  #if PY_VERSION_HEX >= 0x02060000
    if (PyObject_CheckBuffer(obj)) return PyObject_GetBuffer(obj, view, flags);
  #endif
        if (PyObject_TypeCheck(obj, __pyx_ptype_5numpy_ndarray)) return __pyx_pw_5numpy_7ndarray_1__getbuffer__(obj, view, flags);
  #if PY_VERSION_HEX < 0x02060000
    if (obj->ob_type->tp_dict) {
        PyObject *getbuffer_cobj = PyObject_GetItem(
            obj->ob_type->tp_dict, __pyx_n_s_pyx_getbuffer);
        if (getbuffer_cobj) {
            getbufferproc func = (getbufferproc) PyCObject_AsVoidPtr(getbuffer_cobj);
            Py_DECREF(getbuffer_cobj);
            if (!func)
                goto fail;
            return func(obj, view, flags);
        } else {
            PyErr_Clear();
        }
    }
  #endif
    PyErr_Format(PyExc_TypeError, "'%.200s' does not have the buffer interface", Py_TYPE(obj)->tp_name);
#if PY_VERSION_HEX < 0x02060000
fail:
#endif
    return -1;
}
static void __Pyx_ReleaseBuffer(Py_buffer *view) {
    PyObject *obj = view->obj;
    if (!obj) return;
  #if PY_VERSION_HEX >= 0x02060000
    if (PyObject_CheckBuffer(obj)) {
        PyBuffer_Release(view);
        return;
    }
  #endif
        if (PyObject_TypeCheck(obj, __pyx_ptype_5numpy_ndarray)) { __pyx_pw_5numpy_7ndarray_3__releasebuffer__(obj, view); return; }
  #if PY_VERSION_HEX < 0x02060000
    if (obj->ob_type->tp_dict) {
        PyObject *releasebuffer_cobj = PyObject_GetItem(
            obj->ob_type->tp_dict, __pyx_n_s_pyx_releasebuffer);
        if (releasebuffer_cobj) {
            releasebufferproc func = (releasebufferproc) PyCObject_AsVoidPtr(releasebuffer_cobj);
            Py_DECREF(releasebuffer_cobj);
            if (!func)
                goto fail;
            func(obj, view);
            return;
        } else {
            PyErr_Clear();
        }
    }
  #endif
    goto nofail;
#if PY_VERSION_HEX < 0x02060000
fail:
#endif
    PyErr_WriteUnraisable(obj);
nofail:
    Py_DECREF(obj);
    view->obj = NULL;
}
#endif /*  PY_MAJOR_VERSION < 3 */


        #if CYTHON_COMPILING_IN_CPYTHON && PY_MAJOR_VERSION >= 3
 #if CYTHON_USE_PYLONG_INTERNALS
  #include "longintrepr.h"
 #endif
#endif
static CYTHON_INLINE int __Pyx_PyInt_As_int(PyObject *x) {
    const int neg_one = (int) -1, const_zero = 0;
    const int is_unsigned = neg_one > const_zero;
#if PY_MAJOR_VERSION < 3
    if (likely(PyInt_Check(x))) {
        if (sizeof(int) < sizeof(long)) {
            __PYX_VERIFY_RETURN_INT(int, long, PyInt_AS_LONG)
        } else {
            long val = PyInt_AS_LONG(x);
            if (is_unsigned && unlikely(val < 0)) {
                PyErr_SetString(PyExc_OverflowError,
                                "can't convert negative value to int");
                return (int) -1;
            }
            return (int) val;
        }
    } else
#endif
    if (likely(PyLong_Check(x))) {
        if (is_unsigned) {
#if CYTHON_COMPILING_IN_CPYTHON && PY_MAJOR_VERSION >= 3
 #if CYTHON_USE_PYLONG_INTERNALS
            if (sizeof(digit) <= sizeof(int)) {
                switch (Py_SIZE(x)) {
                    case  0: return 0;
                    case  1: return (int) ((PyLongObject*)x)->ob_digit[0];
                }
            }
 #endif
#endif
            if (unlikely(Py_SIZE(x) < 0)) {
                PyErr_SetString(PyExc_OverflowError,
                                "can't convert negative value to int");
                return (int) -1;
            }
            if (sizeof(int) <= sizeof(unsigned long)) {
                __PYX_VERIFY_RETURN_INT(int, unsigned long, PyLong_AsUnsignedLong)
            } else if (sizeof(int) <= sizeof(unsigned long long)) {
                __PYX_VERIFY_RETURN_INT(int, unsigned long long, PyLong_AsUnsignedLongLong)
            }
        } else {
#if CYTHON_COMPILING_IN_CPYTHON && PY_MAJOR_VERSION >= 3
 #if CYTHON_USE_PYLONG_INTERNALS
            if (sizeof(digit) <= sizeof(int)) {
                switch (Py_SIZE(x)) {
                    case  0: return 0;
                    case  1: return +(int) ((PyLongObject*)x)->ob_digit[0];
                    case -1: return -(int) ((PyLongObject*)x)->ob_digit[0];
                }
            }
 #endif
#endif
            if (sizeof(int) <= sizeof(long)) {
                __PYX_VERIFY_RETURN_INT(int, long, PyLong_AsLong)
            } else if (sizeof(int) <= sizeof(long long)) {
                __PYX_VERIFY_RETURN_INT(int, long long, PyLong_AsLongLong)
            }
        }
        {
#if CYTHON_COMPILING_IN_PYPY && !defined(_PyLong_AsByteArray)
            PyErr_SetString(PyExc_RuntimeError,
                            "_PyLong_AsByteArray() not available in PyPy, cannot convert large numbers");
#else
            int val;
            PyObject *v = __Pyx_PyNumber_Int(x);
 #if PY_MAJOR_VERSION < 3
            if (likely(v) && !PyLong_Check(v)) {
                PyObject *tmp = v;
                v = PyNumber_Long(tmp);
                Py_DECREF(tmp);
            }
 #endif
            if (likely(v)) {
                int one = 1; int is_little = (int)*(unsigned char *)&one;
                unsigned char *bytes = (unsigned char *)&val;
                int ret = _PyLong_AsByteArray((PyLongObject *)v,
                                              bytes, sizeof(val),
                                              is_little, !is_unsigned);
                Py_DECREF(v);
                if (likely(!ret))
                    return val;
            }
#endif
            return (int) -1;
        }
    } else {
        int val;
        PyObject *tmp = __Pyx_PyNumber_Int(x);
        if (!tmp) return (int) -1;
        val = __Pyx_PyInt_As_int(tmp);
        Py_DECREF(tmp);
        return val;
    }
}

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;
    if (is_unsigned) {
        if (sizeof(int) < sizeof(long)) {
            return PyInt_FromLong((long) value);
        } else if (sizeof(int) <= sizeof(unsigned long)) {
            return PyLong_FromUnsignedLong((unsigned long) value);
        } else if (sizeof(int) <= sizeof(unsigned long long)) {
            return PyLong_FromUnsignedLongLong((unsigned long long) value);
        }
    } else {
        if (sizeof(int) <= sizeof(long)) {
            return PyInt_FromLong((long) value);
        } else if (sizeof(int) <= sizeof(long long)) {
            return PyLong_FromLongLong((long long) value);
        }
    }
    {
        int one = 1; int little = (int)*(unsigned char *)&one;
        unsigned char *bytes = (unsigned char *)&value;
        return _PyLong_FromByteArray(bytes, sizeof(int),
                                     little, !is_unsigned);
    }
}

#if CYTHON_COMPILING_IN_CPYTHON && PY_MAJOR_VERSION >= 3
 #if CYTHON_USE_PYLONG_INTERNALS
  #include "longintrepr.h"
 #endif
#endif
static CYTHON_INLINE npy_uint32 __Pyx_PyInt_As_npy_uint32(PyObject *x) {
    const npy_uint32 neg_one = (npy_uint32) -1, const_zero = 0;
    const int is_unsigned = neg_one > const_zero;
#if PY_MAJOR_VERSION < 3
    if (likely(PyInt_Check(x))) {
        if (sizeof(npy_uint32) < sizeof(long)) {
            __PYX_VERIFY_RETURN_INT(npy_uint32, long, PyInt_AS_LONG)
        } else {
            long val = PyInt_AS_LONG(x);
            if (is_unsigned && unlikely(val < 0)) {
                PyErr_SetString(PyExc_OverflowError,
                                "can't convert negative value to npy_uint32");
                return (npy_uint32) -1;
            }
            return (npy_uint32) val;
        }
    } else
#endif
    if (likely(PyLong_Check(x))) {
        if (is_unsigned) {
#if CYTHON_COMPILING_IN_CPYTHON && PY_MAJOR_VERSION >= 3
 #if CYTHON_USE_PYLONG_INTERNALS
            if (sizeof(digit) <= sizeof(npy_uint32)) {
                switch (Py_SIZE(x)) {
                    case  0: return 0;
                    case  1: return (npy_uint32) ((PyLongObject*)x)->ob_digit[0];
                }
            }
 #endif
#endif
            if (unlikely(Py_SIZE(x) < 0)) {
                PyErr_SetString(PyExc_OverflowError,
                                "can't convert negative value to npy_uint32");
                return (npy_uint32) -1;
            }
            if (sizeof(npy_uint32) <= sizeof(unsigned long)) {
                __PYX_VERIFY_RETURN_INT(npy_uint32, unsigned long, PyLong_AsUnsignedLong)
            } else if (sizeof(npy_uint32) <= sizeof(unsigned long long)) {
                __PYX_VERIFY_RETURN_INT(npy_uint32, unsigned long long, PyLong_AsUnsignedLongLong)
            }
        } else {
#if CYTHON_COMPILING_IN_CPYTHON && PY_MAJOR_VERSION >= 3
 #if CYTHON_USE_PYLONG_INTERNALS
            if (sizeof(digit) <= sizeof(npy_uint32)) {
                switch (Py_SIZE(x)) {
                    case  0: return 0;
                    case  1: return +(npy_uint32) ((PyLongObject*)x)->ob_digit[0];
                    case -1: return -(npy_uint32) ((PyLongObject*)x)->ob_digit[0];
                }
            }
 #endif
#endif
            if (sizeof(npy_uint32) <= sizeof(long)) {
                __PYX_VERIFY_RETURN_INT(npy_uint32, long, PyLong_AsLong)
            } else if (sizeof(npy_uint32) <= sizeof(long long)) {
                __PYX_VERIFY_RETURN_INT(npy_uint32, long long, PyLong_AsLongLong)
            }
        }
        {
#if CYTHON_COMPILING_IN_PYPY && !defined(_PyLong_AsByteArray)
            PyErr_SetString(PyExc_RuntimeError,
                            "_PyLong_AsByteArray() not available in PyPy, cannot convert large numbers");
#else
            npy_uint32 val;
            PyObject *v = __Pyx_PyNumber_Int(x);
 #if PY_MAJOR_VERSION < 3
            if (likely(v) && !PyLong_Check(v)) {
                PyObject *tmp = v;
                v = PyNumber_Long(tmp);
                Py_DECREF(tmp);
            }
 #endif
            if (likely(v)) {
                int one = 1; int is_little = (int)*(unsigned char *)&one;
                unsigned char *bytes = (unsigned char *)&val;
                int ret = _PyLong_AsByteArray((PyLongObject *)v,
                                              bytes, sizeof(val),
                                              is_little, !is_unsigned);
                Py_DECREF(v);
                if (likely(!ret))
                    return val;
            }
#endif
            return (npy_uint32) -1;
        }
    } else {
        npy_uint32 val;
        PyObject *tmp = __Pyx_PyNumber_Int(x);
        if (!tmp) return (npy_uint32) -1;
        val = __Pyx_PyInt_As_npy_uint32(tmp);
        Py_DECREF(tmp);
        return val;
    }
}

static CYTHON_INLINE PyObject* __Pyx_PyInt_From_long(long value) {
    const long neg_one = (long) -1, const_zero = 0;
    const int is_unsigned = neg_one > const_zero;
    if (is_unsigned) {
        if (sizeof(long) < sizeof(long)) {
            return PyInt_FromLong((long) value);
        } else if (sizeof(long) <= sizeof(unsigned long)) {
            return PyLong_FromUnsignedLong((unsigned long) value);
        } else if (sizeof(long) <= sizeof(unsigned long long)) {
            return PyLong_FromUnsignedLongLong((unsigned long long) value);
        }
    } else {
        if (sizeof(long) <= sizeof(long)) {
            return PyInt_FromLong((long) value);
        } else if (sizeof(long) <= sizeof(long long)) {
            return PyLong_FromLongLong((long long) value);
        }
    }
    {
        int one = 1; int little = (int)*(unsigned char *)&one;
        unsigned char *bytes = (unsigned char *)&value;
        return _PyLong_FromByteArray(bytes, sizeof(long),
                                     little, !is_unsigned);
    }
}

static CYTHON_INLINE long __Pyx_pow_long(long b, long e) {
    long t = b;
    switch (e) {
        case 3:
            t *= b;
        case 2:
            t *= b;
        case 1:
            return t;
        case 0:
            return 1;
    }
    #if 1
    if (unlikely(e<0)) return 0;
    #endif
    t = 1;
    while (likely(e)) {
        t *= (b * (e&1)) | ((~e)&1);    /* 1 or b */
        b *= b;
        e >>= 1;
    }
    return t;
}

#if CYTHON_CCOMPLEX
  #ifdef __cplusplus
    static CYTHON_INLINE __pyx_t_float_complex __pyx_t_float_complex_from_parts(float x, float y) {
      return ::std::complex< float >(x, y);
    }
  #else
    static CYTHON_INLINE __pyx_t_float_complex __pyx_t_float_complex_from_parts(float x, float y) {
      return x + y*(__pyx_t_float_complex)_Complex_I;
    }
  #endif
#else
    static CYTHON_INLINE __pyx_t_float_complex __pyx_t_float_complex_from_parts(float x, float y) {
      __pyx_t_float_complex z;
      z.real = x;
      z.imag = y;
      return z;
    }
#endif

#if CYTHON_CCOMPLEX
#else
    static CYTHON_INLINE int __Pyx_c_eqf(__pyx_t_float_complex a, __pyx_t_float_complex b) {
       return (a.real == b.real) && (a.imag == b.imag);
    }
    static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_sumf(__pyx_t_float_complex a, __pyx_t_float_complex b) {
        __pyx_t_float_complex z;
        z.real = a.real + b.real;
        z.imag = a.imag + b.imag;
        return z;
    }
    static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_difff(__pyx_t_float_complex a, __pyx_t_float_complex b) {
        __pyx_t_float_complex z;
        z.real = a.real - b.real;
        z.imag = a.imag - b.imag;
        return z;
    }
    static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_prodf(__pyx_t_float_complex a, __pyx_t_float_complex b) {
        __pyx_t_float_complex z;
        z.real = a.real * b.real - a.imag * b.imag;
        z.imag = a.real * b.imag + a.imag * b.real;
        return z;
    }
    static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_quotf(__pyx_t_float_complex a, __pyx_t_float_complex b) {
        __pyx_t_float_complex z;
        float denom = b.real * b.real + b.imag * b.imag;
        z.real = (a.real * b.real + a.imag * b.imag) / denom;
        z.imag = (a.imag * b.real - a.real * b.imag) / denom;
        return z;
    }
    static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_negf(__pyx_t_float_complex a) {
        __pyx_t_float_complex z;
        z.real = -a.real;
        z.imag = -a.imag;
        return z;
    }
    static CYTHON_INLINE int __Pyx_c_is_zerof(__pyx_t_float_complex a) {
       return (a.real == 0) && (a.imag == 0);
    }
    static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_conjf(__pyx_t_float_complex a) {
        __pyx_t_float_complex z;
        z.real =  a.real;
        z.imag = -a.imag;
        return z;
    }
    #if 1
        static CYTHON_INLINE float __Pyx_c_absf(__pyx_t_float_complex z) {
          #if !defined(HAVE_HYPOT) || defined(_MSC_VER)
            return sqrtf(z.real*z.real + z.imag*z.imag);
          #else
            return hypotf(z.real, z.imag);
          #endif
        }
        static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_powf(__pyx_t_float_complex a, __pyx_t_float_complex b) {
            __pyx_t_float_complex z;
            float r, lnr, theta, z_r, z_theta;
            if (b.imag == 0 && b.real == (int)b.real) {
                if (b.real < 0) {
                    float denom = a.real * a.real + a.imag * a.imag;
                    a.real = a.real / denom;
                    a.imag = -a.imag / denom;
                    b.real = -b.real;
                }
                switch ((int)b.real) {
                    case 0:
                        z.real = 1;
                        z.imag = 0;
                        return z;
                    case 1:
                        return a;
                    case 2:
                        z = __Pyx_c_prodf(a, a);
                        return __Pyx_c_prodf(a, a);
                    case 3:
                        z = __Pyx_c_prodf(a, a);
                        return __Pyx_c_prodf(z, a);
                    case 4:
                        z = __Pyx_c_prodf(a, a);
                        return __Pyx_c_prodf(z, z);
                }
            }
            if (a.imag == 0) {
                if (a.real == 0) {
                    return a;
                }
                r = a.real;
                theta = 0;
            } else {
                r = __Pyx_c_absf(a);
                theta = atan2f(a.imag, a.real);
            }
            lnr = logf(r);
            z_r = expf(lnr * b.real - theta * b.imag);
            z_theta = theta * b.real + lnr * b.imag;
            z.real = z_r * cosf(z_theta);
            z.imag = z_r * sinf(z_theta);
            return z;
        }
    #endif
#endif

#if CYTHON_CCOMPLEX
  #ifdef __cplusplus
    static CYTHON_INLINE __pyx_t_double_complex __pyx_t_double_complex_from_parts(double x, double y) {
      return ::std::complex< double >(x, y);
    }
  #else
    static CYTHON_INLINE __pyx_t_double_complex __pyx_t_double_complex_from_parts(double x, double y) {
      return x + y*(__pyx_t_double_complex)_Complex_I;
    }
  #endif
#else
    static CYTHON_INLINE __pyx_t_double_complex __pyx_t_double_complex_from_parts(double x, double y) {
      __pyx_t_double_complex z;
      z.real = x;
      z.imag = y;
      return z;
    }
#endif

#if CYTHON_CCOMPLEX
#else
    static CYTHON_INLINE int __Pyx_c_eq(__pyx_t_double_complex a, __pyx_t_double_complex b) {
       return (a.real == b.real) && (a.imag == b.imag);
    }
    static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_sum(__pyx_t_double_complex a, __pyx_t_double_complex b) {
        __pyx_t_double_complex z;
        z.real = a.real + b.real;
        z.imag = a.imag + b.imag;
        return z;
    }
    static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_diff(__pyx_t_double_complex a, __pyx_t_double_complex b) {
        __pyx_t_double_complex z;
        z.real = a.real - b.real;
        z.imag = a.imag - b.imag;
        return z;
    }
    static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_prod(__pyx_t_double_complex a, __pyx_t_double_complex b) {
        __pyx_t_double_complex z;
        z.real = a.real * b.real - a.imag * b.imag;
        z.imag = a.real * b.imag + a.imag * b.real;
        return z;
    }
    static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_quot(__pyx_t_double_complex a, __pyx_t_double_complex b) {
        __pyx_t_double_complex z;
        double denom = b.real * b.real + b.imag * b.imag;
        z.real = (a.real * b.real + a.imag * b.imag) / denom;
        z.imag = (a.imag * b.real - a.real * b.imag) / denom;
        return z;
    }
    static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_neg(__pyx_t_double_complex a) {
        __pyx_t_double_complex z;
        z.real = -a.real;
        z.imag = -a.imag;
        return z;
    }
    static CYTHON_INLINE int __Pyx_c_is_zero(__pyx_t_double_complex a) {
       return (a.real == 0) && (a.imag == 0);
    }
    static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_conj(__pyx_t_double_complex a) {
        __pyx_t_double_complex z;
        z.real =  a.real;
        z.imag = -a.imag;
        return z;
    }
    #if 1
        static CYTHON_INLINE double __Pyx_c_abs(__pyx_t_double_complex z) {
          #if !defined(HAVE_HYPOT) || defined(_MSC_VER)
            return sqrt(z.real*z.real + z.imag*z.imag);
          #else
            return hypot(z.real, z.imag);
          #endif
        }
        static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_pow(__pyx_t_double_complex a, __pyx_t_double_complex b) {
            __pyx_t_double_complex z;
            double r, lnr, theta, z_r, z_theta;
            if (b.imag == 0 && b.real == (int)b.real) {
                if (b.real < 0) {
                    double denom = a.real * a.real + a.imag * a.imag;
                    a.real = a.real / denom;
                    a.imag = -a.imag / denom;
                    b.real = -b.real;
                }
                switch ((int)b.real) {
                    case 0:
                        z.real = 1;
                        z.imag = 0;
                        return z;
                    case 1:
                        return a;
                    case 2:
                        z = __Pyx_c_prod(a, a);
                        return __Pyx_c_prod(a, a);
                    case 3:
                        z = __Pyx_c_prod(a, a);
                        return __Pyx_c_prod(z, a);
                    case 4:
                        z = __Pyx_c_prod(a, a);
                        return __Pyx_c_prod(z, z);
                }
            }
            if (a.imag == 0) {
                if (a.real == 0) {
                    return a;
                }
                r = a.real;
                theta = 0;
            } else {
                r = __Pyx_c_abs(a);
                theta = atan2(a.imag, a.real);
            }
            lnr = log(r);
            z_r = exp(lnr * b.real - theta * b.imag);
            z_theta = theta * b.real + lnr * b.imag;
            z.real = z_r * cos(z_theta);
            z.imag = z_r * sin(z_theta);
            return z;
        }
    #endif
#endif

#if CYTHON_COMPILING_IN_CPYTHON && PY_MAJOR_VERSION >= 3
 #if CYTHON_USE_PYLONG_INTERNALS
  #include "longintrepr.h"
 #endif
#endif
static CYTHON_INLINE long __Pyx_PyInt_As_long(PyObject *x) {
    const long neg_one = (long) -1, const_zero = 0;
    const int is_unsigned = neg_one > const_zero;
#if PY_MAJOR_VERSION < 3
    if (likely(PyInt_Check(x))) {
        if (sizeof(long) < sizeof(long)) {
            __PYX_VERIFY_RETURN_INT(long, long, PyInt_AS_LONG)
        } else {
            long val = PyInt_AS_LONG(x);
            if (is_unsigned && unlikely(val < 0)) {
                PyErr_SetString(PyExc_OverflowError,
                                "can't convert negative value to long");
                return (long) -1;
            }
            return (long) val;
        }
    } else
#endif
    if (likely(PyLong_Check(x))) {
        if (is_unsigned) {
#if CYTHON_COMPILING_IN_CPYTHON && PY_MAJOR_VERSION >= 3
 #if CYTHON_USE_PYLONG_INTERNALS
            if (sizeof(digit) <= sizeof(long)) {
                switch (Py_SIZE(x)) {
                    case  0: return 0;
                    case  1: return (long) ((PyLongObject*)x)->ob_digit[0];
                }
            }
 #endif
#endif
            if (unlikely(Py_SIZE(x) < 0)) {
                PyErr_SetString(PyExc_OverflowError,
                                "can't convert negative value to long");
                return (long) -1;
            }
            if (sizeof(long) <= sizeof(unsigned long)) {
                __PYX_VERIFY_RETURN_INT(long, unsigned long, PyLong_AsUnsignedLong)
            } else if (sizeof(long) <= sizeof(unsigned long long)) {
                __PYX_VERIFY_RETURN_INT(long, unsigned long long, PyLong_AsUnsignedLongLong)
            }
        } else {
#if CYTHON_COMPILING_IN_CPYTHON && PY_MAJOR_VERSION >= 3
 #if CYTHON_USE_PYLONG_INTERNALS
            if (sizeof(digit) <= sizeof(long)) {
                switch (Py_SIZE(x)) {
                    case  0: return 0;
                    case  1: return +(long) ((PyLongObject*)x)->ob_digit[0];
                    case -1: return -(long) ((PyLongObject*)x)->ob_digit[0];
                }
            }
 #endif
#endif
            if (sizeof(long) <= sizeof(long)) {
                __PYX_VERIFY_RETURN_INT(long, long, PyLong_AsLong)
            } else if (sizeof(long) <= sizeof(long long)) {
                __PYX_VERIFY_RETURN_INT(long, long long, PyLong_AsLongLong)
            }
        }
        {
#if CYTHON_COMPILING_IN_PYPY && !defined(_PyLong_AsByteArray)
            PyErr_SetString(PyExc_RuntimeError,
                            "_PyLong_AsByteArray() not available in PyPy, cannot convert large numbers");
#else
            long val;
            PyObject *v = __Pyx_PyNumber_Int(x);
 #if PY_MAJOR_VERSION < 3
            if (likely(v) && !PyLong_Check(v)) {
                PyObject *tmp = v;
                v = PyNumber_Long(tmp);
                Py_DECREF(tmp);
            }
 #endif
            if (likely(v)) {
                int one = 1; int is_little = (int)*(unsigned char *)&one;
                unsigned char *bytes = (unsigned char *)&val;
                int ret = _PyLong_AsByteArray((PyLongObject *)v,
                                              bytes, sizeof(val),
                                              is_little, !is_unsigned);
                Py_DECREF(v);
                if (likely(!ret))
                    return val;
            }
#endif
            return (long) -1;
        }
    } else {
        long val;
        PyObject *tmp = __Pyx_PyNumber_Int(x);
        if (!tmp) return (long) -1;
        val = __Pyx_PyInt_As_long(tmp);
        Py_DECREF(tmp);
        return val;
    }
}

static int __Pyx_check_binary_version(void) {
    char ctversion[4], rtversion[4];
    PyOS_snprintf(ctversion, 4, "%d.%d", PY_MAJOR_VERSION, PY_MINOR_VERSION);
    PyOS_snprintf(rtversion, 4, "%s", Py_GetVersion());
    if (ctversion[0] != rtversion[0] || ctversion[2] != rtversion[2]) {
        char message[200];
        PyOS_snprintf(message, sizeof(message),
                      "compiletime version %s of module '%.100s' "
                      "does not match runtime version %s",
                      ctversion, __Pyx_MODULE_NAME, rtversion);
        #if PY_VERSION_HEX < 0x02050000
        return PyErr_Warn(NULL, message);
        #else
        return PyErr_WarnEx(NULL, message, 1);
        #endif
    }
    return 0;
}

#ifndef __PYX_HAVE_RT_ImportModule
#define __PYX_HAVE_RT_ImportModule
static PyObject *__Pyx_ImportModule(const char *name) {
    PyObject *py_name = 0;
    PyObject *py_module = 0;
    py_name = __Pyx_PyIdentifier_FromString(name);
    if (!py_name)
        goto bad;
    py_module = PyImport_Import(py_name);
    Py_DECREF(py_name);
    return py_module;
bad:
    Py_XDECREF(py_name);
    return 0;
}
#endif

#ifndef __PYX_HAVE_RT_ImportType
#define __PYX_HAVE_RT_ImportType
static PyTypeObject *__Pyx_ImportType(const char *module_name, const char *class_name,
    size_t size, int strict)
{
    PyObject *py_module = 0;
    PyObject *result = 0;
    PyObject *py_name = 0;
    char warning[200];
    Py_ssize_t basicsize;
#ifdef Py_LIMITED_API
    PyObject *py_basicsize;
#endif
    py_module = __Pyx_ImportModule(module_name);
    if (!py_module)
        goto bad;
    py_name = __Pyx_PyIdentifier_FromString(class_name);
    if (!py_name)
        goto bad;
    result = PyObject_GetAttr(py_module, py_name);
    Py_DECREF(py_name);
    py_name = 0;
    Py_DECREF(py_module);
    py_module = 0;
    if (!result)
        goto bad;
    if (!PyType_Check(result)) {
        PyErr_Format(PyExc_TypeError,
            "%.200s.%.200s is not a type object",
            module_name, class_name);
        goto bad;
    }
#ifndef Py_LIMITED_API
    basicsize = ((PyTypeObject *)result)->tp_basicsize;
#else
    py_basicsize = PyObject_GetAttrString(result, "__basicsize__");
    if (!py_basicsize)
        goto bad;
    basicsize = PyLong_AsSsize_t(py_basicsize);
    Py_DECREF(py_basicsize);
    py_basicsize = 0;
    if (basicsize == (Py_ssize_t)-1 && PyErr_Occurred())
        goto bad;
#endif
    if (!strict && (size_t)basicsize > size) {
        PyOS_snprintf(warning, sizeof(warning),
            "%s.%s size changed, may indicate binary incompatibility",
            module_name, class_name);
        #if PY_VERSION_HEX < 0x02050000
        if (PyErr_Warn(NULL, warning) < 0) goto bad;
        #else
        if (PyErr_WarnEx(NULL, warning, 0) < 0) goto bad;
        #endif
    }
    else if ((size_t)basicsize != size) {
        PyErr_Format(PyExc_ValueError,
            "%.200s.%.200s has the wrong size, try recompiling",
            module_name, class_name);
        goto bad;
    }
    return (PyTypeObject *)result;
bad:
    Py_XDECREF(py_module);
    Py_XDECREF(result);
    return NULL;
}
#endif

static int __pyx_bisect_code_objects(__Pyx_CodeObjectCacheEntry* entries, int count, int code_line) {
    int start = 0, mid = 0, end = count - 1;
    if (end >= 0 && code_line > entries[end].code_line) {
        return count;
    }
    while (start < end) {
        mid = (start + end) / 2;
        if (code_line < entries[mid].code_line) {
            end = mid;
        } else if (code_line > entries[mid].code_line) {
             start = mid + 1;
        } else {
            return mid;
        }
    }
    if (code_line <= entries[mid].code_line) {
        return mid;
    } else {
        return mid + 1;
    }
}
static PyCodeObject *__pyx_find_code_object(int code_line) {
    PyCodeObject* code_object;
    int pos;
    if (unlikely(!code_line) || unlikely(!__pyx_code_cache.entries)) {
        return NULL;
    }
    pos = __pyx_bisect_code_objects(__pyx_code_cache.entries, __pyx_code_cache.count, code_line);
    if (unlikely(pos >= __pyx_code_cache.count) || unlikely(__pyx_code_cache.entries[pos].code_line != code_line)) {
        return NULL;
    }
    code_object = __pyx_code_cache.entries[pos].code_object;
    Py_INCREF(code_object);
    return code_object;
}
static void __pyx_insert_code_object(int code_line, PyCodeObject* code_object) {
    int pos, i;
    __Pyx_CodeObjectCacheEntry* entries = __pyx_code_cache.entries;
    if (unlikely(!code_line)) {
        return;
    }
    if (unlikely(!entries)) {
        entries = (__Pyx_CodeObjectCacheEntry*)PyMem_Malloc(64*sizeof(__Pyx_CodeObjectCacheEntry));
        if (likely(entries)) {
            __pyx_code_cache.entries = entries;
            __pyx_code_cache.max_count = 64;
            __pyx_code_cache.count = 1;
            entries[0].code_line = code_line;
            entries[0].code_object = code_object;
            Py_INCREF(code_object);
        }
        return;
    }
    pos = __pyx_bisect_code_objects(__pyx_code_cache.entries, __pyx_code_cache.count, code_line);
    if ((pos < __pyx_code_cache.count) && unlikely(__pyx_code_cache.entries[pos].code_line == code_line)) {
        PyCodeObject* tmp = entries[pos].code_object;
        entries[pos].code_object = code_object;
        Py_DECREF(tmp);
        return;
    }
    if (__pyx_code_cache.count == __pyx_code_cache.max_count) {
        int new_max = __pyx_code_cache.max_count + 64;
        entries = (__Pyx_CodeObjectCacheEntry*)PyMem_Realloc(
            __pyx_code_cache.entries, new_max*sizeof(__Pyx_CodeObjectCacheEntry));
        if (unlikely(!entries)) {
            return;
        }
        __pyx_code_cache.entries = entries;
        __pyx_code_cache.max_count = new_max;
    }
    for (i=__pyx_code_cache.count; i>pos; i--) {
        entries[i] = entries[i-1];
    }
    entries[pos].code_line = code_line;
    entries[pos].code_object = code_object;
    __pyx_code_cache.count++;
    Py_INCREF(code_object);
}

#include "compile.h"
#include "frameobject.h"
#include "traceback.h"
static PyCodeObject* __Pyx_CreateCodeObjectForTraceback(
            const char *funcname, int c_line,
            int py_line, const char *filename) {
    PyCodeObject *py_code = 0;
    PyObject *py_srcfile = 0;
    PyObject *py_funcname = 0;
    #if PY_MAJOR_VERSION < 3
    py_srcfile = PyString_FromString(filename);
    #else
    py_srcfile = PyUnicode_FromString(filename);
    #endif
    if (!py_srcfile) goto bad;
    if (c_line) {
        #if PY_MAJOR_VERSION < 3
        py_funcname = PyString_FromFormat( "%s (%s:%d)", funcname, __pyx_cfilenm, c_line);
        #else
        py_funcname = PyUnicode_FromFormat( "%s (%s:%d)", funcname, __pyx_cfilenm, c_line);
        #endif
    }
    else {
        #if PY_MAJOR_VERSION < 3
        py_funcname = PyString_FromString(funcname);
        #else
        py_funcname = PyUnicode_FromString(funcname);
        #endif
    }
    if (!py_funcname) goto bad;
    py_code = __Pyx_PyCode_New(
        0,            /*int argcount,*/
        0,            /*int kwonlyargcount,*/
        0,            /*int nlocals,*/
        0,            /*int stacksize,*/
        0,            /*int flags,*/
        __pyx_empty_bytes, /*PyObject *code,*/
        __pyx_empty_tuple, /*PyObject *consts,*/
        __pyx_empty_tuple, /*PyObject *names,*/
        __pyx_empty_tuple, /*PyObject *varnames,*/
        __pyx_empty_tuple, /*PyObject *freevars,*/
        __pyx_empty_tuple, /*PyObject *cellvars,*/
        py_srcfile,   /*PyObject *filename,*/
        py_funcname,  /*PyObject *name,*/
        py_line,      /*int firstlineno,*/
        __pyx_empty_bytes  /*PyObject *lnotab*/
    );
    Py_DECREF(py_srcfile);
    Py_DECREF(py_funcname);
    return py_code;
bad:
    Py_XDECREF(py_srcfile);
    Py_XDECREF(py_funcname);
    return NULL;
}
static void __Pyx_AddTraceback(const char *funcname, int c_line,
                               int py_line, const char *filename) {
    PyCodeObject *py_code = 0;
    PyObject *py_globals = 0;
    PyFrameObject *py_frame = 0;
    py_code = __pyx_find_code_object(c_line ? c_line : py_line);
    if (!py_code) {
        py_code = __Pyx_CreateCodeObjectForTraceback(
            funcname, c_line, py_line, filename);
        if (!py_code) goto bad;
        __pyx_insert_code_object(c_line ? c_line : py_line, py_code);
    }
    py_globals = PyModule_GetDict(__pyx_m);
    if (!py_globals) goto bad;
    py_frame = PyFrame_New(
        PyThreadState_GET(), /*PyThreadState *tstate,*/
        py_code,             /*PyCodeObject *code,*/
        py_globals,          /*PyObject *globals,*/
        0                    /*PyObject *locals*/
    );
    if (!py_frame) goto bad;
    py_frame->f_lineno = py_line;
    PyTraceBack_Here(py_frame);
bad:
    Py_XDECREF(py_code);
    Py_XDECREF(py_frame);
}

static int __Pyx_InitStrings(__Pyx_StringTabEntry *t) {
    while (t->p) {
        #if PY_MAJOR_VERSION < 3
        if (t->is_unicode) {
            *t->p = PyUnicode_DecodeUTF8(t->s, t->n - 1, NULL);
        } else if (t->intern) {
            *t->p = PyString_InternFromString(t->s);
        } else {
            *t->p = PyString_FromStringAndSize(t->s, t->n - 1);
        }
        #else  /* Python 3+ has unicode identifiers */
        if (t->is_unicode | t->is_str) {
            if (t->intern) {
                *t->p = PyUnicode_InternFromString(t->s);
            } else if (t->encoding) {
                *t->p = PyUnicode_Decode(t->s, t->n - 1, t->encoding, NULL);
            } else {
                *t->p = PyUnicode_FromStringAndSize(t->s, t->n - 1);
            }
        } else {
            *t->p = PyBytes_FromStringAndSize(t->s, t->n - 1);
        }
        #endif
        if (!*t->p)
            return -1;
        ++t;
    }
    return 0;
}

static CYTHON_INLINE PyObject* __Pyx_PyUnicode_FromString(char* c_str) {
    return __Pyx_PyUnicode_FromStringAndSize(c_str, strlen(c_str));
}
static CYTHON_INLINE char* __Pyx_PyObject_AsString(PyObject* o) {
    Py_ssize_t ignore;
    return __Pyx_PyObject_AsStringAndSize(o, &ignore);
}
static CYTHON_INLINE char* __Pyx_PyObject_AsStringAndSize(PyObject* o, Py_ssize_t *length) {
#if __PYX_DEFAULT_STRING_ENCODING_IS_ASCII || __PYX_DEFAULT_STRING_ENCODING_IS_DEFAULT
    if (
#if PY_MAJOR_VERSION < 3 && __PYX_DEFAULT_STRING_ENCODING_IS_ASCII
            __Pyx_sys_getdefaultencoding_not_ascii &&
#endif
            PyUnicode_Check(o)) {
#if PY_VERSION_HEX < 0x03030000
        char* defenc_c;
        PyObject* defenc = _PyUnicode_AsDefaultEncodedString(o, NULL);
        if (!defenc) return NULL;
        defenc_c = PyBytes_AS_STRING(defenc);
#if __PYX_DEFAULT_STRING_ENCODING_IS_ASCII
        {
            char* end = defenc_c + PyBytes_GET_SIZE(defenc);
            char* c;
            for (c = defenc_c; c < end; c++) {
                if ((unsigned char) (*c) >= 128) {
                    PyUnicode_AsASCIIString(o);
                    return NULL;
                }
            }
        }
#endif /*__PYX_DEFAULT_STRING_ENCODING_IS_ASCII*/
        *length = PyBytes_GET_SIZE(defenc);
        return defenc_c;
#else /* PY_VERSION_HEX < 0x03030000 */
        if (PyUnicode_READY(o) == -1) return NULL;
#if __PYX_DEFAULT_STRING_ENCODING_IS_ASCII
        if (PyUnicode_IS_ASCII(o)) {
            *length = PyUnicode_GET_DATA_SIZE(o);
            return PyUnicode_AsUTF8(o);
        } else {
            PyUnicode_AsASCIIString(o);
            return NULL;
        }
#else /* __PYX_DEFAULT_STRING_ENCODING_IS_ASCII */
        return PyUnicode_AsUTF8AndSize(o, length);
#endif /* __PYX_DEFAULT_STRING_ENCODING_IS_ASCII */
#endif /* PY_VERSION_HEX < 0x03030000 */
    } else
#endif /* __PYX_DEFAULT_STRING_ENCODING_IS_ASCII  || __PYX_DEFAULT_STRING_ENCODING_IS_DEFAULT */
#if !CYTHON_COMPILING_IN_PYPY
#if PY_VERSION_HEX >= 0x02060000
    if (PyByteArray_Check(o)) {
        *length = PyByteArray_GET_SIZE(o);
        return PyByteArray_AS_STRING(o);
    } else
#endif
#endif
    {
        char* result;
        int r = PyBytes_AsStringAndSize(o, &result, length);
        if (unlikely(r < 0)) {
            return NULL;
        } else {
            return result;
        }
    }
}
static CYTHON_INLINE int __Pyx_PyObject_IsTrue(PyObject* x) {
   int is_true = x == Py_True;
   if (is_true | (x == Py_False) | (x == Py_None)) return is_true;
   else return PyObject_IsTrue(x);
}
static CYTHON_INLINE PyObject* __Pyx_PyNumber_Int(PyObject* x) {
  PyNumberMethods *m;
  const char *name = NULL;
  PyObject *res = NULL;
#if PY_MAJOR_VERSION < 3
  if (PyInt_Check(x) || PyLong_Check(x))
#else
  if (PyLong_Check(x))
#endif
    return Py_INCREF(x), x;
  m = Py_TYPE(x)->tp_as_number;
#if PY_MAJOR_VERSION < 3
  if (m && m->nb_int) {
    name = "int";
    res = PyNumber_Int(x);
  }
  else if (m && m->nb_long) {
    name = "long";
    res = PyNumber_Long(x);
  }
#else
  if (m && m->nb_int) {
    name = "int";
    res = PyNumber_Long(x);
  }
#endif
  if (res) {
#if PY_MAJOR_VERSION < 3
    if (!PyInt_Check(res) && !PyLong_Check(res)) {
#else
    if (!PyLong_Check(res)) {
#endif
      PyErr_Format(PyExc_TypeError,
                   "__%.4s__ returned non-%.4s (type %.200s)",
                   name, name, Py_TYPE(res)->tp_name);
      Py_DECREF(res);
      return NULL;
    }
  }
  else if (!PyErr_Occurred()) {
    PyErr_SetString(PyExc_TypeError,
                    "an integer is required");
  }
  return res;
}
#if CYTHON_COMPILING_IN_CPYTHON && PY_MAJOR_VERSION >= 3
 #if CYTHON_USE_PYLONG_INTERNALS
  #include "longintrepr.h"
 #endif
#endif
static CYTHON_INLINE Py_ssize_t __Pyx_PyIndex_AsSsize_t(PyObject* b) {
  Py_ssize_t ival;
  PyObject *x;
#if PY_MAJOR_VERSION < 3
  if (likely(PyInt_CheckExact(b)))
      return PyInt_AS_LONG(b);
#endif
  if (likely(PyLong_CheckExact(b))) {
    #if CYTHON_COMPILING_IN_CPYTHON && PY_MAJOR_VERSION >= 3
     #if CYTHON_USE_PYLONG_INTERNALS
       switch (Py_SIZE(b)) {
       case -1: return -(sdigit)((PyLongObject*)b)->ob_digit[0];
       case  0: return 0;
       case  1: return ((PyLongObject*)b)->ob_digit[0];
       }
     #endif
    #endif
  #if PY_VERSION_HEX < 0x02060000
    return PyInt_AsSsize_t(b);
  #else
    return PyLong_AsSsize_t(b);
  #endif
  }
  x = PyNumber_Index(b);
  if (!x) return -1;
  ival = PyInt_AsSsize_t(x);
  Py_DECREF(x);
  return ival;
}
static CYTHON_INLINE PyObject * __Pyx_PyInt_FromSize_t(size_t ival) {
#if PY_VERSION_HEX < 0x02050000
   if (ival <= LONG_MAX)
       return PyInt_FromLong((long)ival);
   else {
       unsigned char *bytes = (unsigned char *) &ival;
       int one = 1; int little = (int)*(unsigned char*)&one;
       return _PyLong_FromByteArray(bytes, sizeof(size_t), little, 0);
   }
#else
   return PyInt_FromSize_t(ival);
#endif
}


#endif /* Py_PYTHON_H */
