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#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)))  )
#if defined (__cplusplus) && __cplusplus >= 201103L
    #include <cstdlib>
    #define __Pyx_sst_abs(value) std::abs(value)
#elif SIZEOF_INT >= SIZEOF_SIZE_T
    #define __Pyx_sst_abs(value) abs(value)
#elif SIZEOF_LONG >= SIZEOF_SIZE_T
    #define __Pyx_sst_abs(value) labs(value)
#elif defined (_MSC_VER) && defined (_M_X64)
    #define __Pyx_sst_abs(value) _abs64(value)
#elif defined (__STDC_VERSION__) && __STDC_VERSION__ >= 199901L
    #define __Pyx_sst_abs(value) llabs(value)
#elif defined (__GNUC__)
    #define __Pyx_sst_abs(value) __builtin_llabs(value)
#else
    #define __Pyx_sst_abs(value) ((value<0) ? -value : value)
#endif
static CYTHON_INLINE const char* __Pyx_PyObject_AsString(PyObject*);
static CYTHON_INLINE const 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(const 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_AsWritableString(s)    ((char*) __Pyx_PyObject_AsString(s))
#define __Pyx_PyObject_AsWritableSString(s)    ((signed char*) __Pyx_PyObject_AsString(s))
#define __Pyx_PyObject_AsWritableUString(s)    ((unsigned char*) __Pyx_PyObject_AsString(s))
#define __Pyx_PyObject_AsSString(s)    ((const signed char*) __Pyx_PyObject_AsString(s))
#define __Pyx_PyObject_AsUString(s)    ((const unsigned char*) __Pyx_PyObject_AsString(s))
#define __Pyx_PyObject_FromCString(s)  __Pyx_PyObject_FromString((const char*)s)
#define __Pyx_PyBytes_FromCString(s)   __Pyx_PyBytes_FromString((const char*)s)
#define __Pyx_PyByteArray_FromCString(s)   __Pyx_PyByteArray_FromString((const char*)s)
#define __Pyx_PyStr_FromCString(s)     __Pyx_PyStr_FromString((const char*)s)
#define __Pyx_PyUnicode_FromCString(s) __Pyx_PyUnicode_FromString((const 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 (size_t)(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_NewRef(obj) (Py_INCREF(obj), obj)
#define __Pyx_Owned_Py_None(b) __Pyx_NewRef(Py_None)
#define __Pyx_PyBool_FromLong(b) ((b) ? __Pyx_NewRef(Py_True) : __Pyx_NewRef(Py_False))
static CYTHON_INLINE int __Pyx_PyObject_IsTrue(PyObject*);
static CYTHON_INLINE PyObject* __Pyx_PyNumber_IntOrLong(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_ASSUME_SAFE_MACROS
#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
#define __Pyx_PyNumber_Int(x) (PyLong_CheckExact(x) ? __Pyx_NewRef(x) : PyNumber_Long(x))
#else
#define __Pyx_PyNumber_Int(x) (PyInt_CheckExact(x) ? __Pyx_NewRef(x) : PyNumber_Int(x))
#endif
#define __Pyx_PyNumber_Float(x) (PyFloat_CheckExact(x) ? __Pyx_NewRef(x) : PyNumber_Float(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;
    PyObject* default_encoding = NULL;
    PyObject* ascii_chars_u = NULL;
    PyObject* ascii_chars_b = NULL;
    const char* default_encoding_c;
    sys = PyImport_ImportModule("sys");
    if (!sys) goto bad;
    default_encoding = PyObject_CallMethod(sys, (char*) "getdefaultencoding", NULL);
    Py_DECREF(sys);
    if (!default_encoding) goto bad;
    default_encoding_c = PyBytes_AsString(default_encoding);
    if (!default_encoding_c) goto bad;
    if (strcmp(default_encoding_c, "ascii") == 0) {
        __Pyx_sys_getdefaultencoding_not_ascii = 0;
    } else {
        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) goto bad;
        ascii_chars_b = PyUnicode_AsEncodedString(ascii_chars_u, default_encoding_c, NULL);
        if (!ascii_chars_b || !PyBytes_Check(ascii_chars_b) || memcmp(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_DECREF(ascii_chars_u);
        Py_DECREF(ascii_chars_b);
    }
    Py_DECREF(default_encoding);
    return 0;
bad:
    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;
    PyObject* default_encoding = NULL;
    char* default_encoding_c;
    sys = PyImport_ImportModule("sys");
    if (!sys) goto bad;
    default_encoding = PyObject_CallMethod(sys, (char*) (const char*) "getdefaultencoding", NULL);
    Py_DECREF(sys);
    if (!default_encoding) goto bad;
    default_encoding_c = PyBytes_AsString(default_encoding);
    if (!default_encoding_c) goto bad;
    __PYX_DEFAULT_STRING_ENCODING = (char*) malloc(strlen(default_encoding_c));
    if (!__PYX_DEFAULT_STRING_ENCODING) goto bad;
    strcpy(__PYX_DEFAULT_STRING_ENCODING, default_encoding_c);
    Py_DECREF(default_encoding);
    return 0;
bad:
    Py_XDECREF(default_encoding);
    return -1;
}
#endif
#endif


/* Test for GCC > 2.95 */
#if defined(__GNUC__)     && (__GNUC__ > 2 || (__GNUC__ == 2 && (__GNUC_MINOR__ > 95)))
  #define likely(x)   __builtin_expect(!!(x), 1)
  #define unlikely(x) __builtin_expect(!!(x), 0)
#else /* !__GNUC__ or GCC < 2.95 */
  #define likely(x)   (x)
  #define unlikely(x) (x)
#endif /* __GNUC__ */
static CYTHON_INLINE void __Pyx_pretend_to_initialize(void* ptr) { (void)ptr; }

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

/* Header.proto */
#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[] = {
  "sklearn/linear_model/cd_fast.pyx",
  "__init__.pxd",
  "stringsource",
  "type.pxd",
  "bool.pxd",
  "complex.pxd",
};
/* BufferFormatStructs.proto */
#define IS_UNSIGNED(type) (((type) -1) > 0)
struct __Pyx_StructField_;
#define __PYX_BUF_FLAGS_PACKED_STRUCT (1 << 0)
typedef struct {
  const char* name;
  struct __Pyx_StructField_* fields;
  size_t size;
  size_t arraysize[8];
  int ndim;
  char typegroup;
  char is_unsigned;
  int flags;
} __Pyx_TypeInfo;
typedef struct __Pyx_StructField_ {
  __Pyx_TypeInfo* type;
  const char* name;
  size_t offset;
} __Pyx_StructField;
typedef struct {
  __Pyx_StructField* field;
  size_t parent_offset;
} __Pyx_BufFmt_StackElem;
typedef struct {
  __Pyx_StructField root;
  __Pyx_BufFmt_StackElem* head;
  size_t fmt_offset;
  size_t new_count, enc_count;
  size_t struct_alignment;
  int is_complex;
  char enc_type;
  char new_packmode;
  char enc_packmode;
  char is_valid_array;
} __Pyx_BufFmt_Context;

/* MemviewSliceStruct.proto */
struct __pyx_memoryview_obj;
typedef struct {
  struct __pyx_memoryview_obj *memview;
  char *data;
  Py_ssize_t shape[8];
  Py_ssize_t strides[8];
  Py_ssize_t suboffsets[8];
} __Pyx_memviewslice;

/* Atomics.proto */
#include <pythread.h>
#ifndef CYTHON_ATOMICS
    #define CYTHON_ATOMICS 1
#endif
#define __pyx_atomic_int_type int
#if CYTHON_ATOMICS && __GNUC__ >= 4 && (__GNUC_MINOR__ > 1 ||\
                    (__GNUC_MINOR__ == 1 && __GNUC_PATCHLEVEL >= 2)) &&\
                    !defined(__i386__)
    #define __pyx_atomic_incr_aligned(value, lock) __sync_fetch_and_add(value, 1)
    #define __pyx_atomic_decr_aligned(value, lock) __sync_fetch_and_sub(value, 1)
    #ifdef __PYX_DEBUG_ATOMICS
        #warning "Using GNU atomics"
    #endif
#elif CYTHON_ATOMICS && defined(_MSC_VER) && 0
    #include <Windows.h>
    #undef __pyx_atomic_int_type
    #define __pyx_atomic_int_type LONG
    #define __pyx_atomic_incr_aligned(value, lock) InterlockedIncrement(value)
    #define __pyx_atomic_decr_aligned(value, lock) InterlockedDecrement(value)
    #ifdef __PYX_DEBUG_ATOMICS
        #pragma message ("Using MSVC atomics")
    #endif
#elif CYTHON_ATOMICS && (defined(__ICC) || defined(__INTEL_COMPILER)) && 0
    #define __pyx_atomic_incr_aligned(value, lock) _InterlockedIncrement(value)
    #define __pyx_atomic_decr_aligned(value, lock) _InterlockedDecrement(value)
    #ifdef __PYX_DEBUG_ATOMICS
        #warning "Using Intel atomics"
    #endif
#else
    #undef CYTHON_ATOMICS
    #define CYTHON_ATOMICS 0
    #ifdef __PYX_DEBUG_ATOMICS
        #warning "Not using atomics"
    #endif
#endif
typedef volatile __pyx_atomic_int_type __pyx_atomic_int;
#if CYTHON_ATOMICS
    #define __pyx_add_acquisition_count(memview)\
             __pyx_atomic_incr_aligned(__pyx_get_slice_count_pointer(memview), memview->lock)
    #define __pyx_sub_acquisition_count(memview)\
            __pyx_atomic_decr_aligned(__pyx_get_slice_count_pointer(memview), memview->lock)
#else
    #define __pyx_add_acquisition_count(memview)\
            __pyx_add_acquisition_count_locked(__pyx_get_slice_count_pointer(memview), memview->lock)
    #define __pyx_sub_acquisition_count(memview)\
            __pyx_sub_acquisition_count_locked(__pyx_get_slice_count_pointer(memview), memview->lock)
#endif


/* "../../../../../usr/lib/python3/dist-packages/Cython/Includes/numpy/__init__.pxd":725
 * # 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/lib/python3/dist-packages/Cython/Includes/numpy/__init__.pxd":726
 * 
 * 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/lib/python3/dist-packages/Cython/Includes/numpy/__init__.pxd":727
 * 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/lib/python3/dist-packages/Cython/Includes/numpy/__init__.pxd":728
 * 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/lib/python3/dist-packages/Cython/Includes/numpy/__init__.pxd":732
 * #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/lib/python3/dist-packages/Cython/Includes/numpy/__init__.pxd":733
 * 
 * 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/lib/python3/dist-packages/Cython/Includes/numpy/__init__.pxd":734
 * 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/lib/python3/dist-packages/Cython/Includes/numpy/__init__.pxd":735
 * 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/lib/python3/dist-packages/Cython/Includes/numpy/__init__.pxd":739
 * #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/lib/python3/dist-packages/Cython/Includes/numpy/__init__.pxd":740
 * 
 * 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/lib/python3/dist-packages/Cython/Includes/numpy/__init__.pxd":749
 * # 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/lib/python3/dist-packages/Cython/Includes/numpy/__init__.pxd":750
 * # 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/lib/python3/dist-packages/Cython/Includes/numpy/__init__.pxd":751
 * 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/lib/python3/dist-packages/Cython/Includes/numpy/__init__.pxd":753
 * 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/lib/python3/dist-packages/Cython/Includes/numpy/__init__.pxd":754
 * 
 * ctypedef npy_ulong      uint_t
 * ctypedef npy_ulonglong  ulong_t             # <<<<<<<<<<<<<<
 * ctypedef npy_ulonglong  ulonglong_t
 * 
 */
typedef npy_ulonglong __pyx_t_5numpy_ulong_t;

/* "../../../../../usr/lib/python3/dist-packages/Cython/Includes/numpy/__init__.pxd":755
 * 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/lib/python3/dist-packages/Cython/Includes/numpy/__init__.pxd":757
 * ctypedef npy_ulonglong  ulonglong_t
 * 
 * ctypedef npy_intp       intp_t             # <<<<<<<<<<<<<<
 * ctypedef npy_uintp      uintp_t
 * 
 */
typedef npy_intp __pyx_t_5numpy_intp_t;

/* "../../../../../usr/lib/python3/dist-packages/Cython/Includes/numpy/__init__.pxd":758
 * 
 * ctypedef npy_intp       intp_t
 * ctypedef npy_uintp      uintp_t             # <<<<<<<<<<<<<<
 * 
 * ctypedef npy_double     float_t
 */
typedef npy_uintp __pyx_t_5numpy_uintp_t;

/* "../../../../../usr/lib/python3/dist-packages/Cython/Includes/numpy/__init__.pxd":760
 * 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/lib/python3/dist-packages/Cython/Includes/numpy/__init__.pxd":761
 * 
 * ctypedef npy_double     float_t
 * ctypedef npy_double     double_t             # <<<<<<<<<<<<<<
 * ctypedef npy_longdouble longdouble_t
 * 
 */
typedef npy_double __pyx_t_5numpy_double_t;

/* "../../../../../usr/lib/python3/dist-packages/Cython/Includes/numpy/__init__.pxd":762
 * 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/linear_model/cd_fast.pyx":19
 * import warnings
 * 
 * ctypedef np.float64_t DOUBLE             # <<<<<<<<<<<<<<
 * ctypedef np.uint32_t UINT32_t
 * ctypedef floating (*DOT)(int N, floating *X, int incX, floating *Y,
 */
typedef __pyx_t_5numpy_float64_t __pyx_t_7sklearn_12linear_model_7cd_fast_DOUBLE;

/* "sklearn/linear_model/cd_fast.pyx":20
 * 
 * ctypedef np.float64_t DOUBLE
 * ctypedef np.uint32_t UINT32_t             # <<<<<<<<<<<<<<
 * ctypedef floating (*DOT)(int N, floating *X, int incX, floating *Y,
 *                          int incY) nogil
 */
typedef __pyx_t_5numpy_uint32_t __pyx_t_7sklearn_12linear_model_7cd_fast_UINT32_t;
/* Declarations.proto */
#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
static CYTHON_INLINE __pyx_t_float_complex __pyx_t_float_complex_from_parts(float, float);

/* Declarations.proto */
#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
static CYTHON_INLINE __pyx_t_double_complex __pyx_t_double_complex_from_parts(double, double);


/*--- Type declarations ---*/
struct __pyx_array_obj;
struct __pyx_MemviewEnum_obj;
struct __pyx_memoryview_obj;
struct __pyx_memoryviewslice_obj;

/* "../../../../../usr/lib/python3/dist-packages/Cython/Includes/numpy/__init__.pxd":764
 * 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/lib/python3/dist-packages/Cython/Includes/numpy/__init__.pxd":765
 * 
 * ctypedef npy_cfloat      cfloat_t
 * ctypedef npy_cdouble     cdouble_t             # <<<<<<<<<<<<<<
 * ctypedef npy_clongdouble clongdouble_t
 * 
 */
typedef npy_cdouble __pyx_t_5numpy_cdouble_t;

/* "../../../../../usr/lib/python3/dist-packages/Cython/Includes/numpy/__init__.pxd":766
 * 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/lib/python3/dist-packages/Cython/Includes/numpy/__init__.pxd":768
 * 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_defaults;
typedef struct __pyx_defaults __pyx_defaults;
struct __pyx_defaults1;
typedef struct __pyx_defaults1 __pyx_defaults1;
struct __pyx_defaults2;
typedef struct __pyx_defaults2 __pyx_defaults2;
struct __pyx_defaults3;
typedef struct __pyx_defaults3 __pyx_defaults3;
struct __pyx_defaults4;
typedef struct __pyx_defaults4 __pyx_defaults4;
struct __pyx_defaults5;
typedef struct __pyx_defaults5 __pyx_defaults5;
struct __pyx_defaults6;
typedef struct __pyx_defaults6 __pyx_defaults6;
struct __pyx_defaults7;
typedef struct __pyx_defaults7 __pyx_defaults7;
struct __pyx_defaults8;
typedef struct __pyx_defaults8 __pyx_defaults8;
struct __pyx_defaults9;
typedef struct __pyx_defaults9 __pyx_defaults9;
struct __pyx_defaults10;
typedef struct __pyx_defaults10 __pyx_defaults10;
struct __pyx_defaults11;
typedef struct __pyx_defaults11 __pyx_defaults11;
struct __pyx_defaults12;
typedef struct __pyx_defaults12 __pyx_defaults12;
struct __pyx_defaults13;
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struct __pyx_defaults14;
typedef struct __pyx_defaults14 __pyx_defaults14;
struct __pyx_defaults15;
typedef struct __pyx_defaults15 __pyx_defaults15;

/* "sklearn/linear_model/cd_fast.pyx":31
 * # The following two functions are shamelessly copied from the tree code.
 * 
 * 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_12linear_model_7cd_fast_RAND_R_MAX = 0x7FFFFFFF
};
struct __pyx_defaults {
  int __pyx_arg_random;
  int __pyx_arg_positive;
};
struct __pyx_defaults1 {
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};
struct __pyx_defaults2 {
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  int __pyx_arg_positive;
};
struct __pyx_defaults3 {
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};
struct __pyx_defaults4 {
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};
struct __pyx_defaults5 {
  int __pyx_arg_random;
  int __pyx_arg_positive;
};
struct __pyx_defaults6 {
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  int __pyx_arg_positive;
};
struct __pyx_defaults7 {
  int __pyx_arg_random;
  int __pyx_arg_positive;
};
struct __pyx_defaults8 {
  int __pyx_arg_random;
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};
struct __pyx_defaults9 {
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  int __pyx_arg_positive;
};
struct __pyx_defaults10 {
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};
struct __pyx_defaults11 {
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struct __pyx_defaults12 {
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struct __pyx_defaults13 {
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struct __pyx_defaults14 {
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struct __pyx_defaults15 {
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/* "View.MemoryView":103
 * 
 * @cname("__pyx_array")
 * cdef class array:             # <<<<<<<<<<<<<<
 * 
 *     cdef:
 */
struct __pyx_array_obj {
  PyObject_HEAD
  struct __pyx_vtabstruct_array *__pyx_vtab;
  char *data;
  Py_ssize_t len;
  char *format;
  int ndim;
  Py_ssize_t *_shape;
  Py_ssize_t *_strides;
  Py_ssize_t itemsize;
  PyObject *mode;
  PyObject *_format;
  void (*callback_free_data)(void *);
  int free_data;
  int dtype_is_object;
};


/* "View.MemoryView":277
 * 
 * @cname('__pyx_MemviewEnum')
 * cdef class Enum(object):             # <<<<<<<<<<<<<<
 *     cdef object name
 *     def __init__(self, name):
 */
struct __pyx_MemviewEnum_obj {
  PyObject_HEAD
  PyObject *name;
};


/* "View.MemoryView":328
 * 
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 * cdef class memoryview(object):             # <<<<<<<<<<<<<<
 * 
 *     cdef object obj
 */
struct __pyx_memoryview_obj {
  PyObject_HEAD
  struct __pyx_vtabstruct_memoryview *__pyx_vtab;
  PyObject *obj;
  PyObject *_size;
  PyObject *_array_interface;
  PyThread_type_lock lock;
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  __pyx_atomic_int *acquisition_count_aligned_p;
  Py_buffer view;
  int flags;
  int dtype_is_object;
  __Pyx_TypeInfo *typeinfo;
};


/* "View.MemoryView":953
 * 
 * @cname('__pyx_memoryviewslice')
 * cdef class _memoryviewslice(memoryview):             # <<<<<<<<<<<<<<
 *     "Internal class for passing memoryview slices to Python"
 * 
 */
struct __pyx_memoryviewslice_obj {
  struct __pyx_memoryview_obj __pyx_base;
  __Pyx_memviewslice from_slice;
  PyObject *from_object;
  PyObject *(*to_object_func)(char *);
  int (*to_dtype_func)(char *, PyObject *);
};



/* "View.MemoryView":103
 * 
 * @cname("__pyx_array")
 * cdef class array:             # <<<<<<<<<<<<<<
 * 
 *     cdef:
 */

struct __pyx_vtabstruct_array {
  PyObject *(*get_memview)(struct __pyx_array_obj *);
};
static struct __pyx_vtabstruct_array *__pyx_vtabptr_array;


/* "View.MemoryView":328
 * 
 * @cname('__pyx_memoryview')
 * cdef class memoryview(object):             # <<<<<<<<<<<<<<
 * 
 *     cdef object obj
 */

struct __pyx_vtabstruct_memoryview {
  char *(*get_item_pointer)(struct __pyx_memoryview_obj *, PyObject *);
  PyObject *(*is_slice)(struct __pyx_memoryview_obj *, PyObject *);
  PyObject *(*setitem_slice_assignment)(struct __pyx_memoryview_obj *, PyObject *, PyObject *);
  PyObject *(*setitem_slice_assign_scalar)(struct __pyx_memoryview_obj *, struct __pyx_memoryview_obj *, PyObject *);
  PyObject *(*setitem_indexed)(struct __pyx_memoryview_obj *, PyObject *, PyObject *);
  PyObject *(*convert_item_to_object)(struct __pyx_memoryview_obj *, char *);
  PyObject *(*assign_item_from_object)(struct __pyx_memoryview_obj *, char *, PyObject *);
};
static struct __pyx_vtabstruct_memoryview *__pyx_vtabptr_memoryview;


/* "View.MemoryView":953
 * 
 * @cname('__pyx_memoryviewslice')
 * cdef class _memoryviewslice(memoryview):             # <<<<<<<<<<<<<<
 *     "Internal class for passing memoryview slices to Python"
 * 
 */

struct __pyx_vtabstruct__memoryviewslice {
  struct __pyx_vtabstruct_memoryview __pyx_base;
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static struct __pyx_vtabstruct__memoryviewslice *__pyx_vtabptr__memoryviewslice;

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static CYTHON_INLINE PyObject* __Pyx_PyObject_GetAttrStr(PyObject* obj, PyObject* attr_name) {
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/* GetBuiltinName.proto */
static PyObject *__Pyx_GetBuiltinName(PyObject *name);

/* None.proto */
static CYTHON_INLINE long __Pyx_mod_long(long, long);

/* ForceInitThreads.proto */
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/* NoFastGil.proto */
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#define __Pyx_PyGILState_Release PyGILState_Release
#define __Pyx_FastGIL_Remember()
#define __Pyx_FastGIL_Forget()
#define __Pyx_FastGilFuncInit()

/* PyThreadStateGet.proto */
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#define __Pyx_PyThreadState_declare  PyThreadState *__pyx_tstate;
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#define __Pyx_PyThreadState_declare
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/* PyErrFetchRestore.proto */
#if CYTHON_FAST_THREAD_STATE
#define __Pyx_ErrRestoreWithState(type, value, tb)  __Pyx_ErrRestoreInState(PyThreadState_GET(), type, value, tb)
#define __Pyx_ErrFetchWithState(type, value, tb)    __Pyx_ErrFetchInState(PyThreadState_GET(), type, value, tb)
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static CYTHON_INLINE void __Pyx_ErrFetchInState(PyThreadState *tstate, PyObject **type, PyObject **value, PyObject **tb);
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#define __Pyx_ErrRestore(type, value, tb)  PyErr_Restore(type, value, tb)
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/* WriteUnraisableException.proto */
static void __Pyx_WriteUnraisable(const char *name, int clineno,
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/* RaiseArgTupleInvalid.proto */
static void __Pyx_RaiseArgtupleInvalid(const char* func_name, int exact,
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/* RaiseDoubleKeywords.proto */
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/* ParseKeywords.proto */
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/* PyDictContains.proto */
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/* StrEquals.proto */
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/* RaiseNeedMoreValuesToUnpack.proto */
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                                                     int is_list, int wraparound, int boundscheck);

/* ListAppend.proto */
#if CYTHON_USE_PYLIST_INTERNALS && CYTHON_ASSUME_SAFE_MACROS
static CYTHON_INLINE int __Pyx_PyList_Append(PyObject* list, PyObject* x) {
    PyListObject* L = (PyListObject*) list;
    Py_ssize_t len = Py_SIZE(list);
    if (likely(L->allocated > len) & likely(len > (L->allocated >> 1))) {
        Py_INCREF(x);
        PyList_SET_ITEM(list, len, x);
        Py_SIZE(list) = len+1;
        return 0;
    }
    return PyList_Append(list, x);
}
#else
#define __Pyx_PyList_Append(L,x) PyList_Append(L,x)
#endif

/* ArgTypeTest.proto */
static CYTHON_INLINE int __Pyx_ArgTypeTest(PyObject *obj, PyTypeObject *type, int none_allowed,
    const char *name, int exact);

/* IsLittleEndian.proto */
static CYTHON_INLINE int __Pyx_Is_Little_Endian(void);

/* BufferFormatCheck.proto */
static CYTHON_INLINE int  __Pyx_GetBufferAndValidate(Py_buffer* buf, PyObject* obj,
    __Pyx_TypeInfo* dtype, int flags, int nd, int cast, __Pyx_BufFmt_StackElem* stack);
static CYTHON_INLINE void __Pyx_SafeReleaseBuffer(Py_buffer* info);
static const char* __Pyx_BufFmt_CheckString(__Pyx_BufFmt_Context* ctx, const char* ts);
static void __Pyx_BufFmt_Init(__Pyx_BufFmt_Context* ctx,
                              __Pyx_BufFmt_StackElem* stack,
                              __Pyx_TypeInfo* type);

/* GetModuleGlobalName.proto */
static CYTHON_INLINE PyObject *__Pyx_GetModuleGlobalName(PyObject *name);

/* ExtTypeTest.proto */
static CYTHON_INLINE int __Pyx_TypeTest(PyObject *obj, PyTypeObject *type);

#define __Pyx_BufPtrCContig1d(type, buf, i0, s0) ((type)buf + i0)
#define __Pyx_BufPtrStrided1d(type, buf, i0, s0) (type)((char*)buf + i0 * s0)
/* MemviewSliceInit.proto */
#define __Pyx_BUF_MAX_NDIMS %(BUF_MAX_NDIMS)d
#define __Pyx_MEMVIEW_DIRECT   1
#define __Pyx_MEMVIEW_PTR      2
#define __Pyx_MEMVIEW_FULL     4
#define __Pyx_MEMVIEW_CONTIG   8
#define __Pyx_MEMVIEW_STRIDED  16
#define __Pyx_MEMVIEW_FOLLOW   32
#define __Pyx_IS_C_CONTIG 1
#define __Pyx_IS_F_CONTIG 2
static int __Pyx_init_memviewslice(
                struct __pyx_memoryview_obj *memview,
                int ndim,
                __Pyx_memviewslice *memviewslice,
                int memview_is_new_reference);
static CYTHON_INLINE int __pyx_add_acquisition_count_locked(
    __pyx_atomic_int *acquisition_count, PyThread_type_lock lock);
static CYTHON_INLINE int __pyx_sub_acquisition_count_locked(
    __pyx_atomic_int *acquisition_count, PyThread_type_lock lock);
#define __pyx_get_slice_count_pointer(memview) (memview->acquisition_count_aligned_p)
#define __pyx_get_slice_count(memview) (*__pyx_get_slice_count_pointer(memview))
#define __PYX_INC_MEMVIEW(slice, have_gil) __Pyx_INC_MEMVIEW(slice, have_gil, __LINE__)
#define __PYX_XDEC_MEMVIEW(slice, have_gil) __Pyx_XDEC_MEMVIEW(slice, have_gil, __LINE__)
static CYTHON_INLINE void __Pyx_INC_MEMVIEW(__Pyx_memviewslice *, int, int);
static CYTHON_INLINE void __Pyx_XDEC_MEMVIEW(__Pyx_memviewslice *, int, int);

#define __Pyx_BufPtrCContig2d(type, buf, i0, s0, i1, s1) ((type)((char*)buf + i0 * s0) + i1)
#define __Pyx_BufPtrFortranContig2d(type, buf, i0, s0, i1, s1) ((type)((char*)buf + i1 * s1) + i0)
#define __Pyx_BufPtrStrided2d(type, buf, i0, s0, i1, s1) (type)((char*)buf + i0 * s0 + i1 * s1)
/* SaveResetException.proto */
#if CYTHON_FAST_THREAD_STATE
#define __Pyx_ExceptionSave(type, value, tb)  __Pyx__ExceptionSave(__pyx_tstate, type, value, tb)
static CYTHON_INLINE void __Pyx__ExceptionSave(PyThreadState *tstate, PyObject **type, PyObject **value, PyObject **tb);
#define __Pyx_ExceptionReset(type, value, tb)  __Pyx__ExceptionReset(__pyx_tstate, type, value, tb)
static CYTHON_INLINE void __Pyx__ExceptionReset(PyThreadState *tstate, PyObject *type, PyObject *value, PyObject *tb);
#else
#define __Pyx_ExceptionSave(type, value, tb)   PyErr_GetExcInfo(type, value, tb)
#define __Pyx_ExceptionReset(type, value, tb)  PyErr_SetExcInfo(type, value, tb)
#endif

/* PyErrExceptionMatches.proto */
#if CYTHON_FAST_THREAD_STATE
#define __Pyx_PyErr_ExceptionMatches(err) __Pyx_PyErr_ExceptionMatchesInState(__pyx_tstate, err)
static CYTHON_INLINE int __Pyx_PyErr_ExceptionMatchesInState(PyThreadState* tstate, PyObject* err);
#else
#define __Pyx_PyErr_ExceptionMatches(err)  PyErr_ExceptionMatches(err)
#endif

/* GetException.proto */
#if CYTHON_FAST_THREAD_STATE
#define __Pyx_GetException(type, value, tb)  __Pyx__GetException(__pyx_tstate, type, value, tb)
static int __Pyx__GetException(PyThreadState *tstate, PyObject **type, PyObject **value, PyObject **tb);
#else
static int __Pyx_GetException(PyObject **type, PyObject **value, PyObject **tb);
#endif

/* None.proto */
static CYTHON_INLINE Py_ssize_t __Pyx_div_Py_ssize_t(Py_ssize_t, Py_ssize_t);

/* UnaryNegOverflows.proto */
#define UNARY_NEG_WOULD_OVERFLOW(x)\
        (((x) < 0) & ((unsigned long)(x) == 0-(unsigned long)(x)))

static CYTHON_UNUSED int __pyx_array_getbuffer(PyObject *__pyx_v_self, Py_buffer *__pyx_v_info, int __pyx_v_flags); /*proto*/
static PyObject *__pyx_array_get_memview(struct __pyx_array_obj *); /*proto*/
/* GetAttr.proto */
static CYTHON_INLINE PyObject *__Pyx_GetAttr(PyObject *, PyObject *);

/* decode_c_string_utf16.proto */
static CYTHON_INLINE PyObject *__Pyx_PyUnicode_DecodeUTF16(const char *s, Py_ssize_t size, const char *errors) {
    int byteorder = 0;
    return PyUnicode_DecodeUTF16(s, size, errors, &byteorder);
}
static CYTHON_INLINE PyObject *__Pyx_PyUnicode_DecodeUTF16LE(const char *s, Py_ssize_t size, const char *errors) {
    int byteorder = -1;
    return PyUnicode_DecodeUTF16(s, size, errors, &byteorder);
}
static CYTHON_INLINE PyObject *__Pyx_PyUnicode_DecodeUTF16BE(const char *s, Py_ssize_t size, const char *errors) {
    int byteorder = 1;
    return PyUnicode_DecodeUTF16(s, size, errors, &byteorder);
}

/* decode_c_string.proto */
static CYTHON_INLINE PyObject* __Pyx_decode_c_string(
         const char* cstring, Py_ssize_t start, Py_ssize_t stop,
         const char* encoding, const char* errors,
         PyObject* (*decode_func)(const char *s, Py_ssize_t size, const char *errors));

/* GetAttr3.proto */
static CYTHON_INLINE PyObject *__Pyx_GetAttr3(PyObject *, PyObject *, PyObject *);

/* SwapException.proto */
#if CYTHON_FAST_THREAD_STATE
#define __Pyx_ExceptionSwap(type, value, tb)  __Pyx__ExceptionSwap(__pyx_tstate, type, value, tb)
static CYTHON_INLINE void __Pyx__ExceptionSwap(PyThreadState *tstate, PyObject **type, PyObject **value, PyObject **tb);
#else
static CYTHON_INLINE void __Pyx_ExceptionSwap(PyObject **type, PyObject **value, PyObject **tb);
#endif

/* Import.proto */
static PyObject *__Pyx_Import(PyObject *name, PyObject *from_list, int level);

static CYTHON_UNUSED int __pyx_memoryview_getbuffer(PyObject *__pyx_v_self, Py_buffer *__pyx_v_info, int __pyx_v_flags); /*proto*/
/* ListCompAppend.proto */
#if CYTHON_USE_PYLIST_INTERNALS && CYTHON_ASSUME_SAFE_MACROS
static CYTHON_INLINE int __Pyx_ListComp_Append(PyObject* list, PyObject* x) {
    PyListObject* L = (PyListObject*) list;
    Py_ssize_t len = Py_SIZE(list);
    if (likely(L->allocated > len)) {
        Py_INCREF(x);
        PyList_SET_ITEM(list, len, x);
        Py_SIZE(list) = len+1;
        return 0;
    }
    return PyList_Append(list, x);
}
#else
#define __Pyx_ListComp_Append(L,x) PyList_Append(L,x)
#endif

/* PyIntBinop.proto */
#if !CYTHON_COMPILING_IN_PYPY
static PyObject* __Pyx_PyInt_AddObjC(PyObject *op1, PyObject *op2, long intval, int inplace);
#else
#define __Pyx_PyInt_AddObjC(op1, op2, intval, inplace)\
    (inplace ? PyNumber_InPlaceAdd(op1, op2) : PyNumber_Add(op1, op2))
#endif

/* ListExtend.proto */
static CYTHON_INLINE int __Pyx_PyList_Extend(PyObject* L, PyObject* v) {
#if CYTHON_COMPILING_IN_CPYTHON
    PyObject* none = _PyList_Extend((PyListObject*)L, v);
    if (unlikely(!none))
        return -1;
    Py_DECREF(none);
    return 0;
#else
    return PyList_SetSlice(L, PY_SSIZE_T_MAX, PY_SSIZE_T_MAX, v);
#endif
}

/* None.proto */
static CYTHON_INLINE void __Pyx_RaiseUnboundLocalError(const char *varname);

/* None.proto */
static CYTHON_INLINE long __Pyx_div_long(long, long);

/* ImportFrom.proto */
static PyObject* __Pyx_ImportFrom(PyObject* module, PyObject* name);

/* HasAttr.proto */
static CYTHON_INLINE int __Pyx_HasAttr(PyObject *, PyObject *);

/* SetVTable.proto */
static int __Pyx_SetVtable(PyObject *dict, void *vtable);

/* SetupReduce.proto */
static int __Pyx_setup_reduce(PyObject* type_obj);

/* FetchCommonType.proto */
static PyTypeObject* __Pyx_FetchCommonType(PyTypeObject* type);

/* CythonFunction.proto */
#define __Pyx_CyFunction_USED 1
#include <structmember.h>
#define __Pyx_CYFUNCTION_STATICMETHOD  0x01
#define __Pyx_CYFUNCTION_CLASSMETHOD   0x02
#define __Pyx_CYFUNCTION_CCLASS        0x04
#define __Pyx_CyFunction_GetClosure(f)\
    (((__pyx_CyFunctionObject *) (f))->func_closure)
#define __Pyx_CyFunction_GetClassObj(f)\
    (((__pyx_CyFunctionObject *) (f))->func_classobj)
#define __Pyx_CyFunction_Defaults(type, f)\
    ((type *)(((__pyx_CyFunctionObject *) (f))->defaults))
#define __Pyx_CyFunction_SetDefaultsGetter(f, g)\
    ((__pyx_CyFunctionObject *) (f))->defaults_getter = (g)
typedef struct {
    PyCFunctionObject func;
#if PY_VERSION_HEX < 0x030500A0
    PyObject *func_weakreflist;
#endif
    PyObject *func_dict;
    PyObject *func_name;
    PyObject *func_qualname;
    PyObject *func_doc;
    PyObject *func_globals;
    PyObject *func_code;
    PyObject *func_closure;
    PyObject *func_classobj;
    void *defaults;
    int defaults_pyobjects;
    int flags;
    PyObject *defaults_tuple;
    PyObject *defaults_kwdict;
    PyObject *(*defaults_getter)(PyObject *);
    PyObject *func_annotations;
} __pyx_CyFunctionObject;
static PyTypeObject *__pyx_CyFunctionType = 0;
#define __Pyx_CyFunction_NewEx(ml, flags, qualname, self, module, globals, code)\
    __Pyx_CyFunction_New(__pyx_CyFunctionType, ml, flags, qualname, self, module, globals, code)
static PyObject *__Pyx_CyFunction_New(PyTypeObject *, PyMethodDef *ml,
                                      int flags, PyObject* qualname,
                                      PyObject *self,
                                      PyObject *module, PyObject *globals,
                                      PyObject* code);
static CYTHON_INLINE void *__Pyx_CyFunction_InitDefaults(PyObject *m,
                                                         size_t size,
                                                         int pyobjects);
static CYTHON_INLINE void __Pyx_CyFunction_SetDefaultsTuple(PyObject *m,
                                                            PyObject *tuple);
static CYTHON_INLINE void __Pyx_CyFunction_SetDefaultsKwDict(PyObject *m,
                                                             PyObject *dict);
static CYTHON_INLINE void __Pyx_CyFunction_SetAnnotationsDict(PyObject *m,
                                                              PyObject *dict);
static int __pyx_CyFunction_init(void);

/* FusedFunction.proto */
typedef struct {
    __pyx_CyFunctionObject func;
    PyObject *__signatures__;
    PyObject *type;
    PyObject *self;
} __pyx_FusedFunctionObject;
#define __pyx_FusedFunction_NewEx(ml, flags, qualname, self, module, globals, code)\
        __pyx_FusedFunction_New(__pyx_FusedFunctionType, ml, flags, qualname, self, module, globals, code)
static PyObject *__pyx_FusedFunction_New(PyTypeObject *type,
                                         PyMethodDef *ml, int flags,
                                         PyObject *qualname, PyObject *self,
                                         PyObject *module, PyObject *globals,
                                         PyObject *code);
static int __pyx_FusedFunction_clear(__pyx_FusedFunctionObject *self);
static PyTypeObject *__pyx_FusedFunctionType = NULL;
static int __pyx_FusedFunction_init(void);
#define __Pyx_FusedFunction_USED

/* CLineInTraceback.proto */
static int __Pyx_CLineForTraceback(int c_line);

/* CodeObjectCache.proto */
typedef struct {
    PyCodeObject* code_object;
    int code_line;
} __Pyx_CodeObjectCacheEntry;
struct __Pyx_CodeObjectCache {
    int count;
    int max_count;
    __Pyx_CodeObjectCacheEntry* entries;
};
static struct __Pyx_CodeObjectCache __pyx_code_cache = {0,0,NULL};
static int __pyx_bisect_code_objects(__Pyx_CodeObjectCacheEntry* entries, int count, int code_line);
static PyCodeObject *__pyx_find_code_object(int code_line);
static void __pyx_insert_code_object(int code_line, PyCodeObject* code_object);

/* AddTraceback.proto */
static void __Pyx_AddTraceback(const char *funcname, int c_line,
                               int py_line, const char *filename);

#if PY_MAJOR_VERSION < 3
    static int __Pyx_GetBuffer(PyObject *obj, Py_buffer *view, int flags);
    static void __Pyx_ReleaseBuffer(Py_buffer *view);
#else
    #define __Pyx_GetBuffer PyObject_GetBuffer
    #define __Pyx_ReleaseBuffer PyBuffer_Release
#endif


/* BufferStructDeclare.proto */
typedef struct {
  Py_ssize_t shape, strides, suboffsets;
} __Pyx_Buf_DimInfo;
typedef struct {
  size_t refcount;
  Py_buffer pybuffer;
} __Pyx_Buffer;
typedef struct {
  __Pyx_Buffer *rcbuffer;
  char *data;
  __Pyx_Buf_DimInfo diminfo[8];
} __Pyx_LocalBuf_ND;

/* None.proto */
static Py_ssize_t __Pyx_zeros[] = {0, 0, 0, 0, 0, 0, 0, 0};
static Py_ssize_t __Pyx_minusones[] = {-1, -1, -1, -1, -1, -1, -1, -1};

/* MemviewSliceIsContig.proto */
static int __pyx_memviewslice_is_contig(const __Pyx_memviewslice mvs,
                                        char order, int ndim);

/* OverlappingSlices.proto */
static int __pyx_slices_overlap(__Pyx_memviewslice *slice1,
                                __Pyx_memviewslice *slice2,
                                int ndim, size_t itemsize);

/* Capsule.proto */
static CYTHON_INLINE PyObject *__pyx_capsule_create(void *p, const char *sig);

/* TypeInfoCompare.proto */
static int __pyx_typeinfo_cmp(__Pyx_TypeInfo *a, __Pyx_TypeInfo *b);

/* MemviewSliceValidateAndInit.proto */
static int __Pyx_ValidateAndInit_memviewslice(
                int *axes_specs,
                int c_or_f_flag,
                int buf_flags,
                int ndim,
                __Pyx_TypeInfo *dtype,
                __Pyx_BufFmt_StackElem stack[],
                __Pyx_memviewslice *memviewslice,
                PyObject *original_obj);

/* ObjectToMemviewSlice.proto */
static CYTHON_INLINE __Pyx_memviewslice __Pyx_PyObject_to_MemoryviewSlice_ds_float(PyObject *);

/* ObjectToMemviewSlice.proto */
static CYTHON_INLINE __Pyx_memviewslice __Pyx_PyObject_to_MemoryviewSlice_ds_double(PyObject *);

/* ObjectToMemviewSlice.proto */
static CYTHON_INLINE __Pyx_memviewslice __Pyx_PyObject_to_MemoryviewSlice_dcd__float(PyObject *);

/* ObjectToMemviewSlice.proto */
static CYTHON_INLINE __Pyx_memviewslice __Pyx_PyObject_to_MemoryviewSlice_dcd__double(PyObject *);

/* CIntToPy.proto */
static CYTHON_INLINE PyObject* __Pyx_PyInt_From_long(long value);

/* CIntToPy.proto */
static CYTHON_INLINE PyObject* __Pyx_PyInt_From_int(int value);

/* CIntToPy.proto */
static CYTHON_INLINE PyObject* __Pyx_PyInt_From_unsigned_int(unsigned int value);

/* MemviewDtypeToObject.proto */
static CYTHON_INLINE PyObject *__pyx_memview_get_float(const char *itemp);
static CYTHON_INLINE int __pyx_memview_set_float(const char *itemp, PyObject *obj);

/* MemviewDtypeToObject.proto */
static CYTHON_INLINE PyObject *__pyx_memview_get_double(const char *itemp);
static CYTHON_INLINE int __pyx_memview_set_double(const char *itemp, PyObject *obj);

/* RealImag.proto */
#if CYTHON_CCOMPLEX
  #ifdef __cplusplus
    #define __Pyx_CREAL(z) ((z).real())
    #define __Pyx_CIMAG(z) ((z).imag())
  #else
    #define __Pyx_CREAL(z) (__real__(z))
    #define __Pyx_CIMAG(z) (__imag__(z))
  #endif
#else
    #define __Pyx_CREAL(z) ((z).real)
    #define __Pyx_CIMAG(z) ((z).imag)
#endif
#if defined(__cplusplus) && CYTHON_CCOMPLEX\
        && (defined(_WIN32) || defined(__clang__) || (defined(__GNUC__) && (__GNUC__ >= 5 || __GNUC__ == 4 && __GNUC_MINOR__ >= 4 )) || __cplusplus >= 201103)
    #define __Pyx_SET_CREAL(z,x) ((z).real(x))
    #define __Pyx_SET_CIMAG(z,y) ((z).imag(y))
#else
    #define __Pyx_SET_CREAL(z,x) __Pyx_CREAL(z) = (x)
    #define __Pyx_SET_CIMAG(z,y) __Pyx_CIMAG(z) = (y)
#endif

/* Arithmetic.proto */
#if CYTHON_CCOMPLEX
    #define __Pyx_c_eq_float(a, b)   ((a)==(b))
    #define __Pyx_c_sum_float(a, b)  ((a)+(b))
    #define __Pyx_c_diff_float(a, b) ((a)-(b))
    #define __Pyx_c_prod_float(a, b) ((a)*(b))
    #define __Pyx_c_quot_float(a, b) ((a)/(b))
    #define __Pyx_c_neg_float(a)     (-(a))
  #ifdef __cplusplus
    #define __Pyx_c_is_zero_float(z) ((z)==(float)0)
    #define __Pyx_c_conj_float(z)    (::std::conj(z))
    #if 1
        #define __Pyx_c_abs_float(z)     (::std::abs(z))
        #define __Pyx_c_pow_float(a, b)  (::std::pow(a, b))
    #endif
  #else
    #define __Pyx_c_is_zero_float(z) ((z)==0)
    #define __Pyx_c_conj_float(z)    (conjf(z))
    #if 1
        #define __Pyx_c_abs_float(z)     (cabsf(z))
        #define __Pyx_c_pow_float(a, b)  (cpowf(a, b))
    #endif
 #endif
#else
    static CYTHON_INLINE int __Pyx_c_eq_float(__pyx_t_float_complex, __pyx_t_float_complex);
    static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_sum_float(__pyx_t_float_complex, __pyx_t_float_complex);
    static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_diff_float(__pyx_t_float_complex, __pyx_t_float_complex);
    static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_prod_float(__pyx_t_float_complex, __pyx_t_float_complex);
    static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_quot_float(__pyx_t_float_complex, __pyx_t_float_complex);
    static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_neg_float(__pyx_t_float_complex);
    static CYTHON_INLINE int __Pyx_c_is_zero_float(__pyx_t_float_complex);
    static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_conj_float(__pyx_t_float_complex);
    #if 1
        static CYTHON_INLINE float __Pyx_c_abs_float(__pyx_t_float_complex);
        static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_pow_float(__pyx_t_float_complex, __pyx_t_float_complex);
    #endif
#endif

/* Arithmetic.proto */
#if CYTHON_CCOMPLEX
    #define __Pyx_c_eq_double(a, b)   ((a)==(b))
    #define __Pyx_c_sum_double(a, b)  ((a)+(b))
    #define __Pyx_c_diff_double(a, b) ((a)-(b))
    #define __Pyx_c_prod_double(a, b) ((a)*(b))
    #define __Pyx_c_quot_double(a, b) ((a)/(b))
    #define __Pyx_c_neg_double(a)     (-(a))
  #ifdef __cplusplus
    #define __Pyx_c_is_zero_double(z) ((z)==(double)0)
    #define __Pyx_c_conj_double(z)    (::std::conj(z))
    #if 1
        #define __Pyx_c_abs_double(z)     (::std::abs(z))
        #define __Pyx_c_pow_double(a, b)  (::std::pow(a, b))
    #endif
  #else
    #define __Pyx_c_is_zero_double(z) ((z)==0)
    #define __Pyx_c_conj_double(z)    (conj(z))
    #if 1
        #define __Pyx_c_abs_double(z)     (cabs(z))
        #define __Pyx_c_pow_double(a, b)  (cpow(a, b))
    #endif
 #endif
#else
    static CYTHON_INLINE int __Pyx_c_eq_double(__pyx_t_double_complex, __pyx_t_double_complex);
    static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_sum_double(__pyx_t_double_complex, __pyx_t_double_complex);
    static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_diff_double(__pyx_t_double_complex, __pyx_t_double_complex);
    static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_prod_double(__pyx_t_double_complex, __pyx_t_double_complex);
    static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_quot_double(__pyx_t_double_complex, __pyx_t_double_complex);
    static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_neg_double(__pyx_t_double_complex);
    static CYTHON_INLINE int __Pyx_c_is_zero_double(__pyx_t_double_complex);
    static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_conj_double(__pyx_t_double_complex);
    #if 1
        static CYTHON_INLINE double __Pyx_c_abs_double(__pyx_t_double_complex);
        static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_pow_double(__pyx_t_double_complex, __pyx_t_double_complex);
    #endif
#endif

/* CIntToPy.proto */
static CYTHON_INLINE PyObject* __Pyx_PyInt_From_enum__NPY_TYPES(enum NPY_TYPES value);

/* MemviewSliceCopyTemplate.proto */
static __Pyx_memviewslice
__pyx_memoryview_copy_new_contig(const __Pyx_memviewslice *from_mvs,
                                 const char *mode, int ndim,
                                 size_t sizeof_dtype, int contig_flag,
                                 int dtype_is_object);

/* CIntFromPy.proto */
static CYTHON_INLINE int __Pyx_PyInt_As_int(PyObject *);

/* CIntFromPy.proto */
static CYTHON_INLINE npy_uint32 __Pyx_PyInt_As_npy_uint32(PyObject *);

/* CIntFromPy.proto */
static CYTHON_INLINE unsigned int __Pyx_PyInt_As_unsigned_int(PyObject *);

/* BytesContains.proto */
static CYTHON_INLINE int __Pyx_BytesContains(PyObject* bytes, char character);

/* ImportNumPyArray.proto */
static PyObject *__pyx_numpy_ndarray = NULL;
static PyObject* __Pyx_ImportNumPyArrayTypeIfAvailable(void);

/* CIntFromPy.proto */
static CYTHON_INLINE long __Pyx_PyInt_As_long(PyObject *);

/* CIntFromPy.proto */
static CYTHON_INLINE char __Pyx_PyInt_As_char(PyObject *);

/* ObjectToMemviewSlice.proto */
static CYTHON_INLINE __Pyx_memviewslice __Pyx_PyObject_to_MemoryviewSlice_d_dc_float(PyObject *);

/* ObjectToMemviewSlice.proto */
static CYTHON_INLINE __Pyx_memviewslice __Pyx_PyObject_to_MemoryviewSlice_dc_float(PyObject *);

/* ObjectToMemviewSlice.proto */
static CYTHON_INLINE __Pyx_memviewslice __Pyx_PyObject_to_MemoryviewSlice_d_dc_double(PyObject *);

/* ObjectToMemviewSlice.proto */
static CYTHON_INLINE __Pyx_memviewslice __Pyx_PyObject_to_MemoryviewSlice_dc_double(PyObject *);

/* CheckBinaryVersion.proto */
static int __Pyx_check_binary_version(void);

/* PyIdentifierFromString.proto */
#if !defined(__Pyx_PyIdentifier_FromString)
#if PY_MAJOR_VERSION < 3
  #define __Pyx_PyIdentifier_FromString(s) PyString_FromString(s)
#else
  #define __Pyx_PyIdentifier_FromString(s) PyUnicode_FromString(s)
#endif
#endif

/* ModuleImport.proto */
static PyObject *__Pyx_ImportModule(const char *name);

/* TypeImport.proto */
static PyTypeObject *__Pyx_ImportType(const char *module_name, const char *class_name, size_t size, int strict);

/* InitStrings.proto */
static int __Pyx_InitStrings(__Pyx_StringTabEntry *t);

static PyObject *__pyx_array_get_memview(struct __pyx_array_obj *__pyx_v_self); /* proto*/
static char *__pyx_memoryview_get_item_pointer(struct __pyx_memoryview_obj *__pyx_v_self, PyObject *__pyx_v_index); /* proto*/
static PyObject *__pyx_memoryview_is_slice(struct __pyx_memoryview_obj *__pyx_v_self, PyObject *__pyx_v_obj); /* proto*/
static PyObject *__pyx_memoryview_setitem_slice_assignment(struct __pyx_memoryview_obj *__pyx_v_self, PyObject *__pyx_v_dst, PyObject *__pyx_v_src); /* proto*/
static PyObject *__pyx_memoryview_setitem_slice_assign_scalar(struct __pyx_memoryview_obj *__pyx_v_self, struct __pyx_memoryview_obj *__pyx_v_dst, PyObject *__pyx_v_value); /* proto*/
static PyObject *__pyx_memoryview_setitem_indexed(struct __pyx_memoryview_obj *__pyx_v_self, PyObject *__pyx_v_index, PyObject *__pyx_v_value); /* proto*/
static PyObject *__pyx_memoryview_convert_item_to_object(struct __pyx_memoryview_obj *__pyx_v_self, char *__pyx_v_itemp); /* proto*/
static PyObject *__pyx_memoryview_assign_item_from_object(struct __pyx_memoryview_obj *__pyx_v_self, char *__pyx_v_itemp, PyObject *__pyx_v_value); /* proto*/
static PyObject *__pyx_memoryviewslice_convert_item_to_object(struct __pyx_memoryviewslice_obj *__pyx_v_self, char *__pyx_v_itemp); /* proto*/
static PyObject *__pyx_memoryviewslice_assign_item_from_object(struct __pyx_memoryviewslice_obj *__pyx_v_self, char *__pyx_v_itemp, PyObject *__pyx_v_value); /* proto*/

/* Module declarations from 'libc.math' */

/* Module declarations from 'cpython.buffer' */

/* Module declarations from 'libc.string' */

/* Module declarations from 'libc.stdio' */

/* Module declarations from '__builtin__' */

/* Module declarations from 'cpython.type' */
static PyTypeObject *__pyx_ptype_7cpython_4type_type = 0;

/* Module declarations from 'cpython.version' */

/* Module declarations from 'cpython.exc' */

/* Module declarations from 'cpython.module' */

/* Module declarations from 'cpython.mem' */

/* Module declarations from 'cpython.tuple' */

/* Module declarations from 'cpython.list' */

/* Module declarations from 'cpython.sequence' */

/* Module declarations from 'cpython.mapping' */

/* Module declarations from 'cpython.iterator' */

/* Module declarations from 'cpython.number' */

/* Module declarations from 'cpython.int' */

/* Module declarations from '__builtin__' */

/* Module declarations from 'cpython.bool' */
static PyTypeObject *__pyx_ptype_7cpython_4bool_bool = 0;

/* Module declarations from 'cpython.long' */

/* Module declarations from 'cpython.float' */

/* Module declarations from '__builtin__' */

/* Module declarations from 'cpython.complex' */
static PyTypeObject *__pyx_ptype_7cpython_7complex_complex = 0;

/* Module declarations from 'cpython.string' */

/* Module declarations from 'cpython.unicode' */

/* Module declarations from 'cpython.dict' */

/* Module declarations from 'cpython.instance' */

/* Module declarations from 'cpython.function' */

/* Module declarations from 'cpython.method' */

/* Module declarations from 'cpython.weakref' */

/* Module declarations from 'cpython.getargs' */

/* Module declarations from 'cpython.pythread' */

/* Module declarations from 'cpython.pystate' */

/* Module declarations from 'cpython.cobject' */

/* Module declarations from 'cpython.oldbuffer' */

/* Module declarations from 'cpython.set' */

/* Module declarations from 'cpython.bytes' */

/* Module declarations from 'cpython.pycapsule' */

/* Module declarations from 'cpython' */

/* Module declarations from 'cpython.object' */

/* Module declarations from 'cpython.ref' */

/* Module declarations from 'libc.stdlib' */

/* Module declarations from 'numpy' */

/* Module declarations from 'numpy' */
static PyTypeObject *__pyx_ptype_5numpy_dtype = 0;
static PyTypeObject *__pyx_ptype_5numpy_flatiter = 0;
static PyTypeObject *__pyx_ptype_5numpy_broadcast = 0;
static PyTypeObject *__pyx_ptype_5numpy_ndarray = 0;
static PyTypeObject *__pyx_ptype_5numpy_ufunc = 0;
static CYTHON_INLINE char *__pyx_f_5numpy__util_dtypestring(PyArray_Descr *, char *, char *, int *); /*proto*/
static CYTHON_INLINE int __pyx_f_5numpy_import_array(void); /*proto*/

/* Module declarations from 'cython.view' */

/* Module declarations from 'cython' */

/* Module declarations from 'sklearn.linear_model.cd_fast' */
static PyTypeObject *__pyx_array_type = 0;
static PyTypeObject *__pyx_MemviewEnum_type = 0;
static PyTypeObject *__pyx_memoryview_type = 0;
static PyTypeObject *__pyx_memoryviewslice_type = 0;
static PyObject *generic = 0;
static PyObject *strided = 0;
static PyObject *indirect = 0;
static PyObject *contiguous = 0;
static PyObject *indirect_contiguous = 0;
static int __pyx_memoryview_thread_locks_used;
static PyThread_type_lock __pyx_memoryview_thread_locks[8];
static CYTHON_INLINE __pyx_t_7sklearn_12linear_model_7cd_fast_UINT32_t __pyx_f_7sklearn_12linear_model_7cd_fast_our_rand_r(__pyx_t_7sklearn_12linear_model_7cd_fast_UINT32_t *); /*proto*/
static CYTHON_INLINE __pyx_t_7sklearn_12linear_model_7cd_fast_UINT32_t __pyx_f_7sklearn_12linear_model_7cd_fast_rand_int(__pyx_t_7sklearn_12linear_model_7cd_fast_UINT32_t, __pyx_t_7sklearn_12linear_model_7cd_fast_UINT32_t *); /*proto*/
static CYTHON_INLINE double __pyx_fuse_1__pyx_f_7sklearn_12linear_model_7cd_fast_fmax(double, double); /*proto*/
static CYTHON_INLINE float __pyx_fuse_0__pyx_f_7sklearn_12linear_model_7cd_fast_fsign(float); /*proto*/
static CYTHON_INLINE double __pyx_fuse_1__pyx_f_7sklearn_12linear_model_7cd_fast_fsign(double); /*proto*/
static float __pyx_fuse_0__pyx_f_7sklearn_12linear_model_7cd_fast_abs_max(int, float *); /*proto*/
static double __pyx_fuse_1__pyx_f_7sklearn_12linear_model_7cd_fast_abs_max(int, double *); /*proto*/
static float __pyx_fuse_0__pyx_f_7sklearn_12linear_model_7cd_fast_max(int, float *); /*proto*/
static double __pyx_fuse_1__pyx_f_7sklearn_12linear_model_7cd_fast_max(int, double *); /*proto*/
static float __pyx_fuse_0__pyx_f_7sklearn_12linear_model_7cd_fast_diff_abs_max(int, float *, float *); /*proto*/
static double __pyx_fuse_1__pyx_f_7sklearn_12linear_model_7cd_fast_diff_abs_max(int, double *, double *); /*proto*/
static struct __pyx_array_obj *__pyx_array_new(PyObject *, Py_ssize_t, char *, char *, char *); /*proto*/
static void *__pyx_align_pointer(void *, size_t); /*proto*/
static PyObject *__pyx_memoryview_new(PyObject *, int, int, __Pyx_TypeInfo *); /*proto*/
static CYTHON_INLINE int __pyx_memoryview_check(PyObject *); /*proto*/
static PyObject *_unellipsify(PyObject *, int); /*proto*/
static PyObject *assert_direct_dimensions(Py_ssize_t *, int); /*proto*/
static struct __pyx_memoryview_obj *__pyx_memview_slice(struct __pyx_memoryview_obj *, PyObject *); /*proto*/
static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *, Py_ssize_t, Py_ssize_t, Py_ssize_t, int, int, int *, Py_ssize_t, Py_ssize_t, Py_ssize_t, int, int, int, int); /*proto*/
static char *__pyx_pybuffer_index(Py_buffer *, char *, Py_ssize_t, Py_ssize_t); /*proto*/
static int __pyx_memslice_transpose(__Pyx_memviewslice *); /*proto*/
static PyObject *__pyx_memoryview_fromslice(__Pyx_memviewslice, int, PyObject *(*)(char *), int (*)(char *, PyObject *), int); /*proto*/
static __Pyx_memviewslice *__pyx_memoryview_get_slice_from_memoryview(struct __pyx_memoryview_obj *, __Pyx_memviewslice *); /*proto*/
static void __pyx_memoryview_slice_copy(struct __pyx_memoryview_obj *, __Pyx_memviewslice *); /*proto*/
static PyObject *__pyx_memoryview_copy_object(struct __pyx_memoryview_obj *); /*proto*/
static PyObject *__pyx_memoryview_copy_object_from_slice(struct __pyx_memoryview_obj *, __Pyx_memviewslice *); /*proto*/
static Py_ssize_t abs_py_ssize_t(Py_ssize_t); /*proto*/
static char __pyx_get_best_slice_order(__Pyx_memviewslice *, int); /*proto*/
static void _copy_strided_to_strided(char *, Py_ssize_t *, char *, Py_ssize_t *, Py_ssize_t *, Py_ssize_t *, int, size_t); /*proto*/
static void copy_strided_to_strided(__Pyx_memviewslice *, __Pyx_memviewslice *, int, size_t); /*proto*/
static Py_ssize_t __pyx_memoryview_slice_get_size(__Pyx_memviewslice *, int); /*proto*/
static Py_ssize_t __pyx_fill_contig_strides_array(Py_ssize_t *, Py_ssize_t *, Py_ssize_t, int, char); /*proto*/
static void *__pyx_memoryview_copy_data_to_temp(__Pyx_memviewslice *, __Pyx_memviewslice *, char, int); /*proto*/
static int __pyx_memoryview_err_extents(int, Py_ssize_t, Py_ssize_t); /*proto*/
static int __pyx_memoryview_err_dim(PyObject *, char *, int); /*proto*/
static int __pyx_memoryview_err(PyObject *, char *); /*proto*/
static int __pyx_memoryview_copy_contents(__Pyx_memviewslice, __Pyx_memviewslice, int, int, int); /*proto*/
static void __pyx_memoryview_broadcast_leading(__Pyx_memviewslice *, int, int); /*proto*/
static void __pyx_memoryview_refcount_copying(__Pyx_memviewslice *, int, int, int); /*proto*/
static void __pyx_memoryview_refcount_objects_in_slice_with_gil(char *, Py_ssize_t *, Py_ssize_t *, int, int); /*proto*/
static void __pyx_memoryview_refcount_objects_in_slice(char *, Py_ssize_t *, Py_ssize_t *, int, int); /*proto*/
static void __pyx_memoryview_slice_assign_scalar(__Pyx_memviewslice *, int, size_t, void *, int); /*proto*/
static void __pyx_memoryview__slice_assign_scalar(char *, Py_ssize_t *, Py_ssize_t *, int, size_t, void *); /*proto*/
static PyObject *__pyx_unpickle_Enum__set_state(struct __pyx_MemviewEnum_obj *, PyObject *); /*proto*/
static __Pyx_TypeInfo __Pyx_TypeInfo_float = { "float", NULL, sizeof(float), { 0 }, 0, 'R', 0, 0 };
static __Pyx_TypeInfo __Pyx_TypeInfo_double = { "double", NULL, sizeof(double), { 0 }, 0, 'R', 0, 0 };
static __Pyx_TypeInfo __Pyx_TypeInfo_int = { "int", NULL, sizeof(int), { 0 }, 0, IS_UNSIGNED(int) ? 'U' : 'I', IS_UNSIGNED(int), 0 };
#define __Pyx_MODULE_NAME "sklearn.linear_model.cd_fast"
int __pyx_module_is_main_sklearn__linear_model__cd_fast = 0;

/* Implementation of 'sklearn.linear_model.cd_fast' */
static PyObject *__pyx_builtin_range;
static PyObject *__pyx_builtin_TypeError;
static PyObject *__pyx_builtin_zip;
static PyObject *__pyx_builtin_reversed;
static PyObject *__pyx_builtin_ValueError;
static PyObject *__pyx_builtin_RuntimeError;
static PyObject *__pyx_builtin_ImportError;
static PyObject *__pyx_builtin_MemoryError;
static PyObject *__pyx_builtin_enumerate;
static PyObject *__pyx_builtin_Ellipsis;
static PyObject *__pyx_builtin_id;
static PyObject *__pyx_builtin_IndexError;
static const char __pyx_k_[] = "<";
static const char __pyx_k_H[] = "H";
static const char __pyx_k_O[] = "O";
static const char __pyx_k_Q[] = "Q";
static const char __pyx_k_R[] = "R";
static const char __pyx_k_W[] = "W";
static const char __pyx_k_X[] = "X";
static const char __pyx_k_Y[] = "Y";
static const char __pyx_k_c[] = "c";
static const char __pyx_k_i[] = "i";
static const char __pyx_k_q[] = "q";
static const char __pyx_k_s[] = "s";
static const char __pyx_k_w[] = "w";
static const char __pyx_k_y[] = "y";
static const char __pyx_k__2[] = ">";
static const char __pyx_k__3[] = "()";
static const char __pyx_k__5[] = "|";
static const char __pyx_k_id[] = "id";
static const char __pyx_k_ii[] = "ii";
static const char __pyx_k_jj[] = "jj";
static const char __pyx_k_nn[] = "nn";
static const char __pyx_k_np[] = "np";
static const char __pyx_k_XtA[] = "XtA";
static const char __pyx_k__55[] = "*";
static const char __pyx_k_dot[] = "dot";
static const char __pyx_k_gap[] = "gap";
static const char __pyx_k_ger[] = "ger";
static const char __pyx_k_new[] = "__new__";
static const char __pyx_k_obj[] = "obj";
static const char __pyx_k_rng[] = "rng";
static const char __pyx_k_sum[] = "sum";
static const char __pyx_k_tmp[] = "tmp";
static const char __pyx_k_tol[] = "tol";
static const char __pyx_k_zip[] = "zip";
static const char __pyx_k_args[] = "args";
static const char __pyx_k_asum[] = "asum";
static const char __pyx_k_axis[] = "axis";
static const char __pyx_k_axpy[] = "axpy";
static const char __pyx_k_base[] = "base";
static const char __pyx_k_beta[] = "beta";
static const char __pyx_k_copy[] = "copy";
static const char __pyx_k_dict[] = "__dict__";
static const char __pyx_k_gemv[] = "gemv";
static const char __pyx_k_kind[] = "kind";
static const char __pyx_k_main[] = "__main__";
static const char __pyx_k_mode[] = "mode";
static const char __pyx_k_name[] = "name";
static const char __pyx_k_ndim[] = "ndim";
static const char __pyx_k_nrm2[] = "nrm2";
static const char __pyx_k_pack[] = "pack";
static const char __pyx_k_scal[] = "scal";
static const char __pyx_k_size[] = "size";
static const char __pyx_k_step[] = "step";
static const char __pyx_k_stop[] = "stop";
static const char __pyx_k_test[] = "__test__";
static const char __pyx_k_w_ii[] = "w_ii";
static const char __pyx_k_warn[] = "warn";
static const char __pyx_k_ASCII[] = "ASCII";
static const char __pyx_k_H_ptr[] = "H_ptr";
static const char __pyx_k_Q_ptr[] = "Q_ptr";
static const char __pyx_k_R_sum[] = "R_sum";
static const char __pyx_k_W_ptr[] = "W_ptr";
static const char __pyx_k_X_T_R[] = "X_T_R";
static const char __pyx_k_X_ptr[] = "X_ptr";
static const char __pyx_k_Y_ptr[] = "Y_ptr";
static const char __pyx_k_alpha[] = "alpha";
static const char __pyx_k_class[] = "__class__";
static const char __pyx_k_const[] = "const";
static const char __pyx_k_dtype[] = "dtype";
static const char __pyx_k_empty[] = "empty";
static const char __pyx_k_error[] = "error";
static const char __pyx_k_flags[] = "flags";
static const char __pyx_k_float[] = "float";
static const char __pyx_k_numpy[] = "numpy";
static const char __pyx_k_q_ptr[] = "q_ptr";
static const char __pyx_k_range[] = "range";
static const char __pyx_k_shape[] = "shape";
static const char __pyx_k_split[] = "split";
static const char __pyx_k_start[] = "start";
static const char __pyx_k_strip[] = "strip";
static const char __pyx_k_w_max[] = "w_max";
static const char __pyx_k_w_ptr[] = "w_ptr";
static const char __pyx_k_zeros[] = "zeros";
static const char __pyx_k_A_norm[] = "A_norm";
static const char __pyx_k_R_data[] = "R_data";
static const char __pyx_k_R_norm[] = "R_norm";
static const char __pyx_k_X_data[] = "X_data";
static const char __pyx_k_X_mean[] = "X_mean";
static const char __pyx_k_center[] = "center";
static const char __pyx_k_d_w_ii[] = "d_w_ii";
static const char __pyx_k_double[] = "double";
static const char __pyx_k_encode[] = "encode";
static const char __pyx_k_endptr[] = "endptr";
static const char __pyx_k_f_iter[] = "f_iter";
static const char __pyx_k_format[] = "format";
static const char __pyx_k_import[] = "__import__";
static const char __pyx_k_kwargs[] = "kwargs";
static const char __pyx_k_l1_reg[] = "l1_reg";
static const char __pyx_k_l2_reg[] = "l2_reg";
static const char __pyx_k_linalg[] = "linalg";
static const char __pyx_k_n_iter[] = "n_iter";
static const char __pyx_k_name_2[] = "__name__";
static const char __pyx_k_pickle[] = "pickle";
static const char __pyx_k_random[] = "random";
static const char __pyx_k_reduce[] = "__reduce__";
static const char __pyx_k_ry_sum[] = "ry_sum";
static const char __pyx_k_struct[] = "struct";
static const char __pyx_k_unpack[] = "unpack";
static const char __pyx_k_update[] = "update";
static const char __pyx_k_w_data[] = "w_data";
static const char __pyx_k_w_norm[] = "w_norm";
static const char __pyx_k_y_data[] = "y_data";
static const char __pyx_k_A_norm2[] = "A_norm2";
static const char __pyx_k_R_norm2[] = "R_norm2";
static const char __pyx_k_XtA_ptr[] = "XtA_ptr";
static const char __pyx_k_asarray[] = "asarray";
static const char __pyx_k_d_w_max[] = "d_w_max";
static const char __pyx_k_d_w_tol[] = "d_w_tol";
static const char __pyx_k_float32[] = "float32";
static const char __pyx_k_float64[] = "float64";
static const char __pyx_k_fortran[] = "fortran";
static const char __pyx_k_l1_norm[] = "l1_norm";
static const char __pyx_k_memview[] = "memview";
static const char __pyx_k_n_tasks[] = "n_tasks";
static const char __pyx_k_q_dot_w[] = "q_dot_w";
static const char __pyx_k_randint[] = "randint";
static const char __pyx_k_strides[] = "strides";
static const char __pyx_k_w_norm2[] = "w_norm2";
static const char __pyx_k_wii_ptr[] = "wii_ptr";
static const char __pyx_k_y_norm2[] = "y_norm2";
static const char __pyx_k_Ellipsis[] = "Ellipsis";
static const char __pyx_k_X_indptr[] = "X_indptr";
static const char __pyx_k_XtA_data[] = "XtA_data";
static const char __pyx_k_defaults[] = "defaults";
static const char __pyx_k_getstate[] = "__getstate__";
static const char __pyx_k_itemsize[] = "itemsize";
static const char __pyx_k_l21_norm[] = "l21_norm";
static const char __pyx_k_max_iter[] = "max_iter";
static const char __pyx_k_positive[] = "positive";
static const char __pyx_k_pyx_type[] = "__pyx_type";
static const char __pyx_k_reversed[] = "reversed";
static const char __pyx_k_setstate[] = "__setstate__";
static const char __pyx_k_startptr[] = "startptr";
static const char __pyx_k_warnings[] = "warnings";
static const char __pyx_k_TypeError[] = "TypeError";
static const char __pyx_k_X_indices[] = "X_indices";
static const char __pyx_k_X_mean_ii[] = "X_mean_ii";
static const char __pyx_k_byteorder[] = "byteorder";
static const char __pyx_k_enumerate[] = "enumerate";
static const char __pyx_k_n_samples[] = "n_samples";
static const char __pyx_k_pyx_state[] = "__pyx_state";
static const char __pyx_k_reduce_ex[] = "__reduce_ex__";
static const char __pyx_k_IndexError[] = "IndexError";
static const char __pyx_k_ValueError[] = "ValueError";
static const char __pyx_k_n_features[] = "n_features";
static const char __pyx_k_pyx_result[] = "__pyx_result";
static const char __pyx_k_pyx_vtable[] = "__pyx_vtable__";
static const char __pyx_k_signatures[] = "signatures";
static const char __pyx_k_ImportError[] = "ImportError";
static const char __pyx_k_MemoryError[] = "MemoryError";
static const char __pyx_k_PickleError[] = "PickleError";
static const char __pyx_k_norm_cols_X[] = "norm_cols_X";
static const char __pyx_k_RuntimeError[] = "RuntimeError";
static const char __pyx_k_W_ii_abs_max[] = "W_ii_abs_max";
static const char __pyx_k_f_contiguous[] = "f_contiguous";
static const char __pyx_k_numpy_linalg[] = "numpy.linalg";
static const char __pyx_k_pyx_checksum[] = "__pyx_checksum";
static const char __pyx_k_rand_r_state[] = "rand_r_state";
static const char __pyx_k_stringsource[] = "stringsource";
static const char __pyx_k_XtA_axis1norm[] = "XtA_axis1norm";
static const char __pyx_k_dual_norm_XtA[] = "dual_norm_XtA";
static const char __pyx_k_normalize_sum[] = "normalize_sum";
static const char __pyx_k_pyx_getbuffer[] = "__pyx_getbuffer";
static const char __pyx_k_reduce_cython[] = "__reduce_cython__";
static const char __pyx_k_View_MemoryView[] = "View.MemoryView";
static const char __pyx_k_allocate_buffer[] = "allocate_buffer";
static const char __pyx_k_dtype_is_object[] = "dtype_is_object";
static const char __pyx_k_pyx_PickleError[] = "__pyx_PickleError";
static const char __pyx_k_setstate_cython[] = "__setstate_cython__";
static const char __pyx_k_pyx_unpickle_Enum[] = "__pyx_unpickle_Enum";
static const char __pyx_k_rand_r_state_seed[] = "rand_r_state_seed";
static const char __pyx_k_cline_in_traceback[] = "cline_in_traceback";
static const char __pyx_k_strided_and_direct[] = "<strided and direct>";
static const char __pyx_k_strided_and_indirect[] = "<strided and indirect>";
static const char __pyx_k_contiguous_and_direct[] = "<contiguous and direct>";
static const char __pyx_k_MemoryView_of_r_object[] = "<MemoryView of %r object>";
static const char __pyx_k_MemoryView_of_r_at_0x_x[] = "<MemoryView of %r at 0x%x>";
static const char __pyx_k_contiguous_and_indirect[] = "<contiguous and indirect>";
static const char __pyx_k_enet_coordinate_descent[] = "enet_coordinate_descent";
static const char __pyx_k_Cannot_index_with_type_s[] = "Cannot index with type '%s'";
static const char __pyx_k_Invalid_shape_in_axis_d_d[] = "Invalid shape in axis %d: %d.";
static const char __pyx_k_No_matching_signature_found[] = "No matching signature found";
static const char __pyx_k_itemsize_0_for_cython_array[] = "itemsize <= 0 for cython.array";
static const char __pyx_k_ndarray_is_not_C_contiguous[] = "ndarray is not C contiguous";
static const char __pyx_k_enet_coordinate_descent_gram[] = "enet_coordinate_descent_gram";
static const char __pyx_k_sklearn_linear_model_cd_fast[] = "sklearn.linear_model.cd_fast";
static const char __pyx_k_unable_to_allocate_array_data[] = "unable to allocate array data.";
static const char __pyx_k_sparse_enet_coordinate_descent[] = "sparse_enet_coordinate_descent";
static const char __pyx_k_strided_and_direct_or_indirect[] = "<strided and direct or indirect>";
static const char __pyx_k_Coordinate_descent_with_alpha_0[] = "Coordinate descent with alpha=0 may lead to unexpected results and is discouraged.";
static const char __pyx_k_numpy_core_multiarray_failed_to[] = "numpy.core.multiarray failed to import";
static const char __pyx_k_unknown_dtype_code_in_numpy_pxd[] = "unknown dtype code in numpy.pxd (%d)";
static const char __pyx_k_Buffer_view_does_not_expose_stri[] = "Buffer view does not expose strides";
static const char __pyx_k_Can_only_create_a_buffer_that_is[] = "Can only create a buffer that is contiguous in memory.";
static const char __pyx_k_Coordinate_descent_with_l1_reg_0[] = "Coordinate descent with l1_reg=0 may lead to unexpected results and is discouraged.";
static const char __pyx_k_Coordinate_descent_with_no_regul[] = "Coordinate descent with no regularization may lead to unexpected results and is discouraged.";
static const char __pyx_k_Empty_shape_tuple_for_cython_arr[] = "Empty shape tuple for cython.array";
static const char __pyx_k_Expected_at_least_d_argument_s_g[] = "Expected at least %d argument%s, got %d";
static const char __pyx_k_Format_string_allocated_too_shor[] = "Format string allocated too short, see comment in numpy.pxd";
static const char __pyx_k_Function_call_with_ambiguous_arg[] = "Function call with ambiguous argument types";
static const char __pyx_k_Incompatible_checksums_s_vs_0xb0[] = "Incompatible checksums (%s vs 0xb068931 = (name))";
static const char __pyx_k_Indirect_dimensions_not_supporte[] = "Indirect dimensions not supported";
static const char __pyx_k_Invalid_mode_expected_c_or_fortr[] = "Invalid mode, expected 'c' or 'fortran', got %s";
static const char __pyx_k_Non_native_byte_order_not_suppor[] = "Non-native byte order not supported";
static const char __pyx_k_Out_of_bounds_on_buffer_access_a[] = "Out of bounds on buffer access (axis %d)";
static const char __pyx_k_Unable_to_convert_item_to_object[] = "Unable to convert item to object";
static const char __pyx_k_enet_coordinate_descent_multi_ta[] = "enet_coordinate_descent_multi_task";
static const char __pyx_k_got_differing_extents_in_dimensi[] = "got differing extents in dimension %d (got %d and %d)";
static const char __pyx_k_ndarray_is_not_Fortran_contiguou[] = "ndarray is not Fortran contiguous";
static const char __pyx_k_no_default___reduce___due_to_non[] = "no default __reduce__ due to non-trivial __cinit__";
static const char __pyx_k_numpy_core_umath_failed_to_impor[] = "numpy.core.umath failed to import";
static const char __pyx_k_sklearn_linear_model_cd_fast_pyx[] = "sklearn/linear_model/cd_fast.pyx";
static const char __pyx_k_unable_to_allocate_shape_and_str[] = "unable to allocate shape and strides.";
static const char __pyx_k_Format_string_allocated_too_shor_2[] = "Format string allocated too short.";
static PyObject *__pyx_kp_s_;
static PyObject *__pyx_n_s_ASCII;
static PyObject *__pyx_n_s_A_norm;
static PyObject *__pyx_n_s_A_norm2;
static PyObject *__pyx_kp_s_Buffer_view_does_not_expose_stri;
static PyObject *__pyx_kp_s_Can_only_create_a_buffer_that_is;
static PyObject *__pyx_kp_s_Cannot_index_with_type_s;
static PyObject *__pyx_kp_s_Coordinate_descent_with_alpha_0;
static PyObject *__pyx_kp_s_Coordinate_descent_with_l1_reg_0;
static PyObject *__pyx_kp_s_Coordinate_descent_with_no_regul;
static PyObject *__pyx_n_s_Ellipsis;
static PyObject *__pyx_kp_s_Empty_shape_tuple_for_cython_arr;
static PyObject *__pyx_kp_s_Expected_at_least_d_argument_s_g;
static PyObject *__pyx_kp_u_Format_string_allocated_too_shor;
static PyObject *__pyx_kp_u_Format_string_allocated_too_shor_2;
static PyObject *__pyx_kp_s_Function_call_with_ambiguous_arg;
static PyObject *__pyx_n_s_H;
static PyObject *__pyx_n_s_H_ptr;
static PyObject *__pyx_n_s_ImportError;
static PyObject *__pyx_kp_s_Incompatible_checksums_s_vs_0xb0;
static PyObject *__pyx_n_s_IndexError;
static PyObject *__pyx_kp_s_Indirect_dimensions_not_supporte;
static PyObject *__pyx_kp_s_Invalid_mode_expected_c_or_fortr;
static PyObject *__pyx_kp_s_Invalid_shape_in_axis_d_d;
static PyObject *__pyx_n_s_MemoryError;
static PyObject *__pyx_kp_s_MemoryView_of_r_at_0x_x;
static PyObject *__pyx_kp_s_MemoryView_of_r_object;
static PyObject *__pyx_kp_s_No_matching_signature_found;
static PyObject *__pyx_kp_u_Non_native_byte_order_not_suppor;
static PyObject *__pyx_n_b_O;
static PyObject *__pyx_kp_s_Out_of_bounds_on_buffer_access_a;
static PyObject *__pyx_n_s_PickleError;
static PyObject *__pyx_n_s_Q;
static PyObject *__pyx_n_s_Q_ptr;
static PyObject *__pyx_n_s_R;
static PyObject *__pyx_n_s_R_data;
static PyObject *__pyx_n_s_R_norm;
static PyObject *__pyx_n_s_R_norm2;
static PyObject *__pyx_n_s_R_sum;
static PyObject *__pyx_n_s_RuntimeError;
static PyObject *__pyx_n_s_TypeError;
static PyObject *__pyx_kp_s_Unable_to_convert_item_to_object;
static PyObject *__pyx_n_s_ValueError;
static PyObject *__pyx_n_s_View_MemoryView;
static PyObject *__pyx_n_s_W;
static PyObject *__pyx_n_s_W_ii_abs_max;
static PyObject *__pyx_n_s_W_ptr;
static PyObject *__pyx_n_s_X;
static PyObject *__pyx_n_s_X_T_R;
static PyObject *__pyx_n_s_X_data;
static PyObject *__pyx_n_s_X_indices;
static PyObject *__pyx_n_s_X_indptr;
static PyObject *__pyx_n_s_X_mean;
static PyObject *__pyx_n_s_X_mean_ii;
static PyObject *__pyx_n_s_X_ptr;
static PyObject *__pyx_n_s_XtA;
static PyObject *__pyx_n_s_XtA_axis1norm;
static PyObject *__pyx_n_s_XtA_data;
static PyObject *__pyx_n_s_XtA_ptr;
static PyObject *__pyx_n_s_Y;
static PyObject *__pyx_n_s_Y_ptr;
static PyObject *__pyx_kp_s__2;
static PyObject *__pyx_kp_s__3;
static PyObject *__pyx_kp_s__5;
static PyObject *__pyx_n_s__55;
static PyObject *__pyx_n_s_allocate_buffer;
static PyObject *__pyx_n_s_alpha;
static PyObject *__pyx_n_s_args;
static PyObject *__pyx_n_s_asarray;
static PyObject *__pyx_n_s_asum;
static PyObject *__pyx_n_s_axis;
static PyObject *__pyx_n_s_axpy;
static PyObject *__pyx_n_s_base;
static PyObject *__pyx_n_s_beta;
static PyObject *__pyx_n_s_byteorder;
static PyObject *__pyx_n_s_c;
static PyObject *__pyx_n_u_c;
static PyObject *__pyx_n_s_center;
static PyObject *__pyx_n_s_class;
static PyObject *__pyx_n_s_cline_in_traceback;
static PyObject *__pyx_n_s_const;
static PyObject *__pyx_kp_s_contiguous_and_direct;
static PyObject *__pyx_kp_s_contiguous_and_indirect;
static PyObject *__pyx_n_s_copy;
static PyObject *__pyx_n_s_d_w_ii;
static PyObject *__pyx_n_s_d_w_max;
static PyObject *__pyx_n_s_d_w_tol;
static PyObject *__pyx_n_s_defaults;
static PyObject *__pyx_n_s_dict;
static PyObject *__pyx_n_s_dot;
static PyObject *__pyx_n_s_double;
static PyObject *__pyx_n_s_dtype;
static PyObject *__pyx_n_s_dtype_is_object;
static PyObject *__pyx_n_s_dual_norm_XtA;
static PyObject *__pyx_n_s_empty;
static PyObject *__pyx_n_s_encode;
static PyObject *__pyx_n_s_endptr;
static PyObject *__pyx_n_s_enet_coordinate_descent;
static PyObject *__pyx_n_s_enet_coordinate_descent_gram;
static PyObject *__pyx_n_s_enet_coordinate_descent_multi_ta;
static PyObject *__pyx_n_s_enumerate;
static PyObject *__pyx_n_s_error;
static PyObject *__pyx_n_s_f_contiguous;
static PyObject *__pyx_n_s_f_iter;
static PyObject *__pyx_n_s_flags;
static PyObject *__pyx_n_s_float;
static PyObject *__pyx_n_s_float32;
static PyObject *__pyx_n_s_float64;
static PyObject *__pyx_n_s_format;
static PyObject *__pyx_n_s_fortran;
static PyObject *__pyx_n_u_fortran;
static PyObject *__pyx_n_s_gap;
static PyObject *__pyx_n_s_gemv;
static PyObject *__pyx_n_s_ger;
static PyObject *__pyx_n_s_getstate;
static PyObject *__pyx_kp_s_got_differing_extents_in_dimensi;
static PyObject *__pyx_n_s_i;
static PyObject *__pyx_n_s_id;
static PyObject *__pyx_n_s_ii;
static PyObject *__pyx_n_s_import;
static PyObject *__pyx_n_s_itemsize;
static PyObject *__pyx_kp_s_itemsize_0_for_cython_array;
static PyObject *__pyx_n_s_jj;
static PyObject *__pyx_n_s_kind;
static PyObject *__pyx_n_s_kwargs;
static PyObject *__pyx_n_s_l1_norm;
static PyObject *__pyx_n_s_l1_reg;
static PyObject *__pyx_n_s_l21_norm;
static PyObject *__pyx_n_s_l2_reg;
static PyObject *__pyx_n_s_linalg;
static PyObject *__pyx_n_s_main;
static PyObject *__pyx_n_s_max_iter;
static PyObject *__pyx_n_s_memview;
static PyObject *__pyx_n_s_mode;
static PyObject *__pyx_n_s_n_features;
static PyObject *__pyx_n_s_n_iter;
static PyObject *__pyx_n_s_n_samples;
static PyObject *__pyx_n_s_n_tasks;
static PyObject *__pyx_n_s_name;
static PyObject *__pyx_n_s_name_2;
static PyObject *__pyx_kp_u_ndarray_is_not_C_contiguous;
static PyObject *__pyx_kp_u_ndarray_is_not_Fortran_contiguou;
static PyObject *__pyx_n_s_ndim;
static PyObject *__pyx_n_s_new;
static PyObject *__pyx_n_s_nn;
static PyObject *__pyx_kp_s_no_default___reduce___due_to_non;
static PyObject *__pyx_n_s_norm_cols_X;
static PyObject *__pyx_n_s_normalize_sum;
static PyObject *__pyx_n_s_np;
static PyObject *__pyx_n_s_nrm2;
static PyObject *__pyx_n_s_numpy;
static PyObject *__pyx_kp_s_numpy_core_multiarray_failed_to;
static PyObject *__pyx_kp_s_numpy_core_umath_failed_to_impor;
static PyObject *__pyx_n_s_numpy_linalg;
static PyObject *__pyx_n_s_obj;
static PyObject *__pyx_n_s_pack;
static PyObject *__pyx_n_s_pickle;
static PyObject *__pyx_n_s_positive;
static PyObject *__pyx_n_s_pyx_PickleError;
static PyObject *__pyx_n_s_pyx_checksum;
static PyObject *__pyx_n_s_pyx_getbuffer;
static PyObject *__pyx_n_s_pyx_result;
static PyObject *__pyx_n_s_pyx_state;
static PyObject *__pyx_n_s_pyx_type;
static PyObject *__pyx_n_s_pyx_unpickle_Enum;
static PyObject *__pyx_n_s_pyx_vtable;
static PyObject *__pyx_n_s_q;
static PyObject *__pyx_n_s_q_dot_w;
static PyObject *__pyx_n_s_q_ptr;
static PyObject *__pyx_n_s_rand_r_state;
static PyObject *__pyx_n_s_rand_r_state_seed;
static PyObject *__pyx_n_s_randint;
static PyObject *__pyx_n_s_random;
static PyObject *__pyx_n_s_range;
static PyObject *__pyx_n_s_reduce;
static PyObject *__pyx_n_s_reduce_cython;
static PyObject *__pyx_n_s_reduce_ex;
static PyObject *__pyx_n_s_reversed;
static PyObject *__pyx_n_s_rng;
static PyObject *__pyx_n_s_ry_sum;
static PyObject *__pyx_n_s_s;
static PyObject *__pyx_n_s_scal;
static PyObject *__pyx_n_s_setstate;
static PyObject *__pyx_n_s_setstate_cython;
static PyObject *__pyx_n_s_shape;
static PyObject *__pyx_n_s_signatures;
static PyObject *__pyx_n_s_size;
static PyObject *__pyx_n_s_sklearn_linear_model_cd_fast;
static PyObject *__pyx_kp_s_sklearn_linear_model_cd_fast_pyx;
static PyObject *__pyx_n_s_sparse_enet_coordinate_descent;
static PyObject *__pyx_n_s_split;
static PyObject *__pyx_n_s_start;
static PyObject *__pyx_n_s_startptr;
static PyObject *__pyx_n_s_step;
static PyObject *__pyx_n_s_stop;
static PyObject *__pyx_kp_s_strided_and_direct;
static PyObject *__pyx_kp_s_strided_and_direct_or_indirect;
static PyObject *__pyx_kp_s_strided_and_indirect;
static PyObject *__pyx_n_s_strides;
static PyObject *__pyx_kp_s_stringsource;
static PyObject *__pyx_n_s_strip;
static PyObject *__pyx_n_s_struct;
static PyObject *__pyx_n_s_sum;
static PyObject *__pyx_n_s_test;
static PyObject *__pyx_n_s_tmp;
static PyObject *__pyx_n_s_tol;
static PyObject *__pyx_kp_s_unable_to_allocate_array_data;
static PyObject *__pyx_kp_s_unable_to_allocate_shape_and_str;
static PyObject *__pyx_kp_u_unknown_dtype_code_in_numpy_pxd;
static PyObject *__pyx_n_s_unpack;
static PyObject *__pyx_n_s_update;
static PyObject *__pyx_n_s_w;
static PyObject *__pyx_n_s_w_data;
static PyObject *__pyx_n_s_w_ii;
static PyObject *__pyx_n_s_w_max;
static PyObject *__pyx_n_s_w_norm;
static PyObject *__pyx_n_s_w_norm2;
static PyObject *__pyx_n_s_w_ptr;
static PyObject *__pyx_n_s_warn;
static PyObject *__pyx_n_s_warnings;
static PyObject *__pyx_n_s_wii_ptr;
static PyObject *__pyx_n_s_y;
static PyObject *__pyx_n_s_y_data;
static PyObject *__pyx_n_s_y_norm2;
static PyObject *__pyx_n_s_zeros;
static PyObject *__pyx_n_s_zip;
static PyObject *__pyx_pf_7sklearn_12linear_model_7cd_fast_enet_coordinate_descent(CYTHON_UNUSED PyObject *__pyx_self, PyObject *__pyx_v_signatures, PyObject *__pyx_v_args, PyObject *__pyx_v_kwargs, CYTHON_UNUSED PyObject *__pyx_v_defaults); /* proto */
static PyObject *__pyx_pf_7sklearn_12linear_model_7cd_fast_36__defaults__(CYTHON_UNUSED PyObject *__pyx_self); /* proto */
static PyObject *__pyx_pf_7sklearn_12linear_model_7cd_fast_8enet_coordinate_descent(CYTHON_UNUSED PyObject *__pyx_self, PyArrayObject *__pyx_v_w, float __pyx_v_alpha, float __pyx_v_beta, PyArrayObject *__pyx_v_X, PyArrayObject *__pyx_v_y, int __pyx_v_max_iter, float __pyx_v_tol, PyObject *__pyx_v_rng, int __pyx_v_random, int __pyx_v_positive); /* proto */
static PyObject *__pyx_pf_7sklearn_12linear_model_7cd_fast_38__defaults__(CYTHON_UNUSED PyObject *__pyx_self); /* proto */
static PyObject *__pyx_pf_7sklearn_12linear_model_7cd_fast_10enet_coordinate_descent(CYTHON_UNUSED PyObject *__pyx_self, PyArrayObject *__pyx_v_w, double __pyx_v_alpha, double __pyx_v_beta, PyArrayObject *__pyx_v_X, PyArrayObject *__pyx_v_y, int __pyx_v_max_iter, double __pyx_v_tol, PyObject *__pyx_v_rng, int __pyx_v_random, int __pyx_v_positive); /* proto */
static PyObject *__pyx_pf_7sklearn_12linear_model_7cd_fast_2sparse_enet_coordinate_descent(CYTHON_UNUSED PyObject *__pyx_self, PyObject *__pyx_v_signatures, PyObject *__pyx_v_args, PyObject *__pyx_v_kwargs, CYTHON_UNUSED PyObject *__pyx_v_defaults); /* proto */
static PyObject *__pyx_pf_7sklearn_12linear_model_7cd_fast_44__defaults__(CYTHON_UNUSED PyObject *__pyx_self); /* proto */
static PyObject *__pyx_pf_7sklearn_12linear_model_7cd_fast_14sparse_enet_coordinate_descent(CYTHON_UNUSED PyObject *__pyx_self, __Pyx_memviewslice __pyx_v_w, float __pyx_v_alpha, float __pyx_v_beta, PyArrayObject *__pyx_v_X_data, PyArrayObject *__pyx_v_X_indices, PyArrayObject *__pyx_v_X_indptr, PyArrayObject *__pyx_v_y, __Pyx_memviewslice __pyx_v_X_mean, int __pyx_v_max_iter, float __pyx_v_tol, PyObject *__pyx_v_rng, int __pyx_v_random, int __pyx_v_positive); /* proto */
static PyObject *__pyx_pf_7sklearn_12linear_model_7cd_fast_46__defaults__(CYTHON_UNUSED PyObject *__pyx_self); /* proto */
static PyObject *__pyx_pf_7sklearn_12linear_model_7cd_fast_16sparse_enet_coordinate_descent(CYTHON_UNUSED PyObject *__pyx_self, __Pyx_memviewslice __pyx_v_w, double __pyx_v_alpha, double __pyx_v_beta, PyArrayObject *__pyx_v_X_data, PyArrayObject *__pyx_v_X_indices, PyArrayObject *__pyx_v_X_indptr, PyArrayObject *__pyx_v_y, __Pyx_memviewslice __pyx_v_X_mean, int __pyx_v_max_iter, double __pyx_v_tol, PyObject *__pyx_v_rng, int __pyx_v_random, int __pyx_v_positive); /* proto */
static PyObject *__pyx_pf_7sklearn_12linear_model_7cd_fast_4enet_coordinate_descent_gram(CYTHON_UNUSED PyObject *__pyx_self, PyObject *__pyx_v_signatures, PyObject *__pyx_v_args, PyObject *__pyx_v_kwargs, CYTHON_UNUSED PyObject *__pyx_v_defaults); /* proto */
static PyObject *__pyx_pf_7sklearn_12linear_model_7cd_fast_52__defaults__(CYTHON_UNUSED PyObject *__pyx_self); /* proto */
static PyObject *__pyx_pf_7sklearn_12linear_model_7cd_fast_20enet_coordinate_descent_gram(CYTHON_UNUSED PyObject *__pyx_self, __Pyx_memviewslice __pyx_v_w, float __pyx_v_alpha, float __pyx_v_beta, PyArrayObject *__pyx_v_Q, PyArrayObject *__pyx_v_q, PyArrayObject *__pyx_v_y, int __pyx_v_max_iter, float __pyx_v_tol, PyObject *__pyx_v_rng, int __pyx_v_random, int __pyx_v_positive); /* proto */
static PyObject *__pyx_pf_7sklearn_12linear_model_7cd_fast_54__defaults__(CYTHON_UNUSED PyObject *__pyx_self); /* proto */
static PyObject *__pyx_pf_7sklearn_12linear_model_7cd_fast_22enet_coordinate_descent_gram(CYTHON_UNUSED PyObject *__pyx_self, __Pyx_memviewslice __pyx_v_w, double __pyx_v_alpha, double __pyx_v_beta, PyArrayObject *__pyx_v_Q, PyArrayObject *__pyx_v_q, PyArrayObject *__pyx_v_y, int __pyx_v_max_iter, double __pyx_v_tol, PyObject *__pyx_v_rng, int __pyx_v_random, int __pyx_v_positive); /* proto */
static PyObject *__pyx_pf_7sklearn_12linear_model_7cd_fast_6enet_coordinate_descent_multi_task(CYTHON_UNUSED PyObject *__pyx_self, PyObject *__pyx_v_signatures, PyObject *__pyx_v_args, PyObject *__pyx_v_kwargs, CYTHON_UNUSED PyObject *__pyx_v_defaults); /* proto */
static PyObject *__pyx_pf_7sklearn_12linear_model_7cd_fast_60__defaults__(CYTHON_UNUSED PyObject *__pyx_self); /* proto */
static PyObject *__pyx_pf_7sklearn_12linear_model_7cd_fast_26enet_coordinate_descent_multi_task(CYTHON_UNUSED PyObject *__pyx_self, __Pyx_memviewslice __pyx_v_W, float __pyx_v_l1_reg, float __pyx_v_l2_reg, PyArrayObject *__pyx_v_X, PyArrayObject *__pyx_v_Y, int __pyx_v_max_iter, float __pyx_v_tol, PyObject *__pyx_v_rng, int __pyx_v_random); /* proto */
static PyObject *__pyx_pf_7sklearn_12linear_model_7cd_fast_62__defaults__(CYTHON_UNUSED PyObject *__pyx_self); /* proto */
static PyObject *__pyx_pf_7sklearn_12linear_model_7cd_fast_28enet_coordinate_descent_multi_task(CYTHON_UNUSED PyObject *__pyx_self, __Pyx_memviewslice __pyx_v_W, double __pyx_v_l1_reg, double __pyx_v_l2_reg, PyArrayObject *__pyx_v_X, PyArrayObject *__pyx_v_Y, int __pyx_v_max_iter, double __pyx_v_tol, PyObject *__pyx_v_rng, int __pyx_v_random); /* 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 int __pyx_array___pyx_pf_15View_dot_MemoryView_5array___cinit__(struct __pyx_array_obj *__pyx_v_self, PyObject *__pyx_v_shape, Py_ssize_t __pyx_v_itemsize, PyObject *__pyx_v_format, PyObject *__pyx_v_mode, int __pyx_v_allocate_buffer); /* proto */
static int __pyx_array___pyx_pf_15View_dot_MemoryView_5array_2__getbuffer__(struct __pyx_array_obj *__pyx_v_self, Py_buffer *__pyx_v_info, int __pyx_v_flags); /* proto */
static void __pyx_array___pyx_pf_15View_dot_MemoryView_5array_4__dealloc__(struct __pyx_array_obj *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_15View_dot_MemoryView_5array_7memview___get__(struct __pyx_array_obj *__pyx_v_self); /* proto */
static Py_ssize_t __pyx_array___pyx_pf_15View_dot_MemoryView_5array_6__len__(struct __pyx_array_obj *__pyx_v_self); /* proto */
static PyObject *__pyx_array___pyx_pf_15View_dot_MemoryView_5array_8__getattr__(struct __pyx_array_obj *__pyx_v_self, PyObject *__pyx_v_attr); /* proto */
static PyObject *__pyx_array___pyx_pf_15View_dot_MemoryView_5array_10__getitem__(struct __pyx_array_obj *__pyx_v_self, PyObject *__pyx_v_item); /* proto */
static int __pyx_array___pyx_pf_15View_dot_MemoryView_5array_12__setitem__(struct __pyx_array_obj *__pyx_v_self, PyObject *__pyx_v_item, PyObject *__pyx_v_value); /* proto */
static PyObject *__pyx_pf___pyx_array___reduce_cython__(CYTHON_UNUSED struct __pyx_array_obj *__pyx_v_self); /* proto */
static PyObject *__pyx_pf___pyx_array_2__setstate_cython__(CYTHON_UNUSED struct __pyx_array_obj *__pyx_v_self, CYTHON_UNUSED PyObject *__pyx_v___pyx_state); /* proto */
static int __pyx_MemviewEnum___pyx_pf_15View_dot_MemoryView_4Enum___init__(struct __pyx_MemviewEnum_obj *__pyx_v_self, PyObject *__pyx_v_name); /* proto */
static PyObject *__pyx_MemviewEnum___pyx_pf_15View_dot_MemoryView_4Enum_2__repr__(struct __pyx_MemviewEnum_obj *__pyx_v_self); /* proto */
static PyObject *__pyx_pf___pyx_MemviewEnum___reduce_cython__(struct __pyx_MemviewEnum_obj *__pyx_v_self); /* proto */
static PyObject *__pyx_pf___pyx_MemviewEnum_2__setstate_cython__(struct __pyx_MemviewEnum_obj *__pyx_v_self, PyObject *__pyx_v___pyx_state); /* proto */
static int __pyx_memoryview___pyx_pf_15View_dot_MemoryView_10memoryview___cinit__(struct __pyx_memoryview_obj *__pyx_v_self, PyObject *__pyx_v_obj, int __pyx_v_flags, int __pyx_v_dtype_is_object); /* proto */
static void __pyx_memoryview___pyx_pf_15View_dot_MemoryView_10memoryview_2__dealloc__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */
static PyObject *__pyx_memoryview___pyx_pf_15View_dot_MemoryView_10memoryview_4__getitem__(struct __pyx_memoryview_obj *__pyx_v_self, PyObject *__pyx_v_index); /* proto */
static int __pyx_memoryview___pyx_pf_15View_dot_MemoryView_10memoryview_6__setitem__(struct __pyx_memoryview_obj *__pyx_v_self, PyObject *__pyx_v_index, PyObject *__pyx_v_value); /* proto */
static int __pyx_memoryview___pyx_pf_15View_dot_MemoryView_10memoryview_8__getbuffer__(struct __pyx_memoryview_obj *__pyx_v_self, Py_buffer *__pyx_v_info, int __pyx_v_flags); /* proto */
static PyObject *__pyx_pf_15View_dot_MemoryView_10memoryview_1T___get__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_15View_dot_MemoryView_10memoryview_4base___get__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_15View_dot_MemoryView_10memoryview_5shape___get__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_15View_dot_MemoryView_10memoryview_7strides___get__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_15View_dot_MemoryView_10memoryview_10suboffsets___get__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_15View_dot_MemoryView_10memoryview_4ndim___get__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_15View_dot_MemoryView_10memoryview_8itemsize___get__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_15View_dot_MemoryView_10memoryview_6nbytes___get__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_15View_dot_MemoryView_10memoryview_4size___get__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */
static Py_ssize_t __pyx_memoryview___pyx_pf_15View_dot_MemoryView_10memoryview_10__len__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */
static PyObject *__pyx_memoryview___pyx_pf_15View_dot_MemoryView_10memoryview_12__repr__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */
static PyObject *__pyx_memoryview___pyx_pf_15View_dot_MemoryView_10memoryview_14__str__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */
static PyObject *__pyx_memoryview___pyx_pf_15View_dot_MemoryView_10memoryview_16is_c_contig(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */
static PyObject *__pyx_memoryview___pyx_pf_15View_dot_MemoryView_10memoryview_18is_f_contig(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */
static PyObject *__pyx_memoryview___pyx_pf_15View_dot_MemoryView_10memoryview_20copy(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */
static PyObject *__pyx_memoryview___pyx_pf_15View_dot_MemoryView_10memoryview_22copy_fortran(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */
static PyObject *__pyx_pf___pyx_memoryview___reduce_cython__(CYTHON_UNUSED struct __pyx_memoryview_obj *__pyx_v_self); /* proto */
static PyObject *__pyx_pf___pyx_memoryview_2__setstate_cython__(CYTHON_UNUSED struct __pyx_memoryview_obj *__pyx_v_self, CYTHON_UNUSED PyObject *__pyx_v___pyx_state); /* proto */
static void __pyx_memoryviewslice___pyx_pf_15View_dot_MemoryView_16_memoryviewslice___dealloc__(struct __pyx_memoryviewslice_obj *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_15View_dot_MemoryView_16_memoryviewslice_4base___get__(struct __pyx_memoryviewslice_obj *__pyx_v_self); /* proto */
static PyObject *__pyx_pf___pyx_memoryviewslice___reduce_cython__(CYTHON_UNUSED struct __pyx_memoryviewslice_obj *__pyx_v_self); /* proto */
static PyObject *__pyx_pf___pyx_memoryviewslice_2__setstate_cython__(CYTHON_UNUSED struct __pyx_memoryviewslice_obj *__pyx_v_self, CYTHON_UNUSED PyObject *__pyx_v___pyx_state); /* proto */
static PyObject *__pyx_pf_15View_dot_MemoryView___pyx_unpickle_Enum(CYTHON_UNUSED PyObject *__pyx_self, PyObject *__pyx_v___pyx_type, long __pyx_v___pyx_checksum, PyObject *__pyx_v___pyx_state); /* proto */
static PyObject *__pyx_tp_new_array(PyTypeObject *t, PyObject *a, PyObject *k); /*proto*/
static PyObject *__pyx_tp_new_Enum(PyTypeObject *t, PyObject *a, PyObject *k); /*proto*/
static PyObject *__pyx_tp_new_memoryview(PyTypeObject *t, PyObject *a, PyObject *k); /*proto*/
static PyObject *__pyx_tp_new__memoryviewslice(PyTypeObject *t, PyObject *a, PyObject *k); /*proto*/
static PyObject *__pyx_int_0;
static PyObject *__pyx_int_1;
static PyObject *__pyx_int_2;
static PyObject *__pyx_int_8;
static PyObject *__pyx_int_9;
static PyObject *__pyx_int_11;
static PyObject *__pyx_int_184977713;
static PyObject *__pyx_int_neg_1;
static PyObject *__pyx_tuple__4;
static PyObject *__pyx_tuple__6;
static PyObject *__pyx_tuple__7;
static PyObject *__pyx_tuple__8;
static PyObject *__pyx_tuple__9;
static PyObject *__pyx_slice__49;
static PyObject *__pyx_slice__50;
static PyObject *__pyx_slice__51;
static PyObject *__pyx_tuple__10;
static PyObject *__pyx_tuple__11;
static PyObject *__pyx_tuple__12;
static PyObject *__pyx_tuple__13;
static PyObject *__pyx_tuple__14;
static PyObject *__pyx_tuple__15;
static PyObject *__pyx_tuple__16;
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static PyObject *__pyx_tuple__20;
static PyObject *__pyx_tuple__21;
static PyObject *__pyx_tuple__22;
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static PyObject *__pyx_tuple__24;
static PyObject *__pyx_tuple__25;
static PyObject *__pyx_tuple__26;
static PyObject *__pyx_tuple__27;
static PyObject *__pyx_tuple__28;
static PyObject *__pyx_tuple__29;
static PyObject *__pyx_tuple__30;
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static PyObject *__pyx_tuple__34;
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static PyObject *__pyx_tuple__37;
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static PyObject *__pyx_tuple__40;
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static PyObject *__pyx_tuple__44;
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static PyObject *__pyx_tuple__46;
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static PyObject *__pyx_codeobj__57;
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/* "sklearn/linear_model/cd_fast.pyx":38
 * 
 * 
 * cdef inline UINT32_t our_rand_r(UINT32_t* seed) nogil:             # <<<<<<<<<<<<<<
 *     seed[0] ^= <UINT32_t>(seed[0] << 13)
 *     seed[0] ^= <UINT32_t>(seed[0] >> 17)
 */

static CYTHON_INLINE __pyx_t_7sklearn_12linear_model_7cd_fast_UINT32_t __pyx_f_7sklearn_12linear_model_7cd_fast_our_rand_r(__pyx_t_7sklearn_12linear_model_7cd_fast_UINT32_t *__pyx_v_seed) {
  __pyx_t_7sklearn_12linear_model_7cd_fast_UINT32_t __pyx_r;
  long __pyx_t_1;

  /* "sklearn/linear_model/cd_fast.pyx":39
 * 
 * cdef inline UINT32_t our_rand_r(UINT32_t* seed) nogil:
 *     seed[0] ^= <UINT32_t>(seed[0] << 13)             # <<<<<<<<<<<<<<
 *     seed[0] ^= <UINT32_t>(seed[0] >> 17)
 *     seed[0] ^= <UINT32_t>(seed[0] << 5)
 */
  __pyx_t_1 = 0;
  (__pyx_v_seed[__pyx_t_1]) = ((__pyx_v_seed[__pyx_t_1]) ^ ((__pyx_t_7sklearn_12linear_model_7cd_fast_UINT32_t)((__pyx_v_seed[0]) << 13)));

  /* "sklearn/linear_model/cd_fast.pyx":40
 * cdef inline UINT32_t our_rand_r(UINT32_t* seed) nogil:
 *     seed[0] ^= <UINT32_t>(seed[0] << 13)
 *     seed[0] ^= <UINT32_t>(seed[0] >> 17)             # <<<<<<<<<<<<<<
 *     seed[0] ^= <UINT32_t>(seed[0] << 5)
 * 
 */
  __pyx_t_1 = 0;
  (__pyx_v_seed[__pyx_t_1]) = ((__pyx_v_seed[__pyx_t_1]) ^ ((__pyx_t_7sklearn_12linear_model_7cd_fast_UINT32_t)((__pyx_v_seed[0]) >> 17)));

  /* "sklearn/linear_model/cd_fast.pyx":41
 *     seed[0] ^= <UINT32_t>(seed[0] << 13)
 *     seed[0] ^= <UINT32_t>(seed[0] >> 17)
 *     seed[0] ^= <UINT32_t>(seed[0] << 5)             # <<<<<<<<<<<<<<
 * 
 *     return seed[0] % (<UINT32_t>RAND_R_MAX + 1)
 */
  __pyx_t_1 = 0;
  (__pyx_v_seed[__pyx_t_1]) = ((__pyx_v_seed[__pyx_t_1]) ^ ((__pyx_t_7sklearn_12linear_model_7cd_fast_UINT32_t)((__pyx_v_seed[0]) << 5)));

  /* "sklearn/linear_model/cd_fast.pyx":43
 *     seed[0] ^= <UINT32_t>(seed[0] << 5)
 * 
 *     return seed[0] % (<UINT32_t>RAND_R_MAX + 1)             # <<<<<<<<<<<<<<
 * 
 * 
 */
  __pyx_t_1 = (((__pyx_t_7sklearn_12linear_model_7cd_fast_UINT32_t)__pyx_e_7sklearn_12linear_model_7cd_fast_RAND_R_MAX) + 1);
  if (unlikely(__pyx_t_1 == 0)) {
    #ifdef WITH_THREAD
    PyGILState_STATE __pyx_gilstate_save = __Pyx_PyGILState_Ensure();
    #endif
    PyErr_SetString(PyExc_ZeroDivisionError, "integer division or modulo by zero");
    #ifdef WITH_THREAD
    __Pyx_PyGILState_Release(__pyx_gilstate_save);
    #endif
    __PYX_ERR(0, 43, __pyx_L1_error)
  }
  __pyx_r = __Pyx_mod_long((__pyx_v_seed[0]), __pyx_t_1);
  goto __pyx_L0;

  /* "sklearn/linear_model/cd_fast.pyx":38
 * 
 * 
 * cdef inline UINT32_t our_rand_r(UINT32_t* seed) nogil:             # <<<<<<<<<<<<<<
 *     seed[0] ^= <UINT32_t>(seed[0] << 13)
 *     seed[0] ^= <UINT32_t>(seed[0] >> 17)
 */

  /* function exit code */
  __pyx_L1_error:;
  __Pyx_WriteUnraisable("sklearn.linear_model.cd_fast.our_rand_r", __pyx_clineno, __pyx_lineno, __pyx_filename, 1, 1);
  __pyx_r = 0;
  __pyx_L0:;
  return __pyx_r;
}

/* "sklearn/linear_model/cd_fast.pyx":46
 * 
 * 
 * cdef inline UINT32_t rand_int(UINT32_t end, UINT32_t* random_state) nogil:             # <<<<<<<<<<<<<<
 *     """Generate a random integer in [0; end)."""
 *     return our_rand_r(random_state) % end
 */

static CYTHON_INLINE __pyx_t_7sklearn_12linear_model_7cd_fast_UINT32_t __pyx_f_7sklearn_12linear_model_7cd_fast_rand_int(__pyx_t_7sklearn_12linear_model_7cd_fast_UINT32_t __pyx_v_end, __pyx_t_7sklearn_12linear_model_7cd_fast_UINT32_t *__pyx_v_random_state) {
  __pyx_t_7sklearn_12linear_model_7cd_fast_UINT32_t __pyx_r;
  __pyx_t_7sklearn_12linear_model_7cd_fast_UINT32_t __pyx_t_1;

  /* "sklearn/linear_model/cd_fast.pyx":48
 * cdef inline UINT32_t rand_int(UINT32_t end, UINT32_t* random_state) nogil:
 *     """Generate a random integer in [0; end)."""
 *     return our_rand_r(random_state) % end             # <<<<<<<<<<<<<<
 * 
 * 
 */
  __pyx_t_1 = __pyx_f_7sklearn_12linear_model_7cd_fast_our_rand_r(__pyx_v_random_state);
  if (unlikely(__pyx_v_end == 0)) {
    #ifdef WITH_THREAD
    PyGILState_STATE __pyx_gilstate_save = __Pyx_PyGILState_Ensure();
    #endif
    PyErr_SetString(PyExc_ZeroDivisionError, "integer division or modulo by zero");
    #ifdef WITH_THREAD
    __Pyx_PyGILState_Release(__pyx_gilstate_save);
    #endif
    __PYX_ERR(0, 48, __pyx_L1_error)
  }
  __pyx_r = (__pyx_t_1 % __pyx_v_end);
  goto __pyx_L0;

  /* "sklearn/linear_model/cd_fast.pyx":46
 * 
 * 
 * cdef inline UINT32_t rand_int(UINT32_t end, UINT32_t* random_state) nogil:             # <<<<<<<<<<<<<<
 *     """Generate a random integer in [0; end)."""
 *     return our_rand_r(random_state) % end
 */

  /* function exit code */
  __pyx_L1_error:;
  __Pyx_WriteUnraisable("sklearn.linear_model.cd_fast.rand_int", __pyx_clineno, __pyx_lineno, __pyx_filename, 1, 1);
  __pyx_r = 0;
  __pyx_L0:;
  return __pyx_r;
}

/* "sklearn/linear_model/cd_fast.pyx":51
 * 
 * 
 * cdef inline floating fmax(floating x, floating y) nogil:             # <<<<<<<<<<<<<<
 *     if x > y:
 *         return x
 */

static CYTHON_INLINE double __pyx_fuse_1__pyx_f_7sklearn_12linear_model_7cd_fast_fmax(double __pyx_v_x, double __pyx_v_y) {
  double __pyx_r;
  int __pyx_t_1;

  /* "sklearn/linear_model/cd_fast.pyx":52
 * 
 * cdef inline floating fmax(floating x, floating y) nogil:
 *     if x > y:             # <<<<<<<<<<<<<<
 *         return x
 *     return y
 */
  __pyx_t_1 = ((__pyx_v_x > __pyx_v_y) != 0);
  if (__pyx_t_1) {

    /* "sklearn/linear_model/cd_fast.pyx":53
 * cdef inline floating fmax(floating x, floating y) nogil:
 *     if x > y:
 *         return x             # <<<<<<<<<<<<<<
 *     return y
 * 
 */
    __pyx_r = __pyx_v_x;
    goto __pyx_L0;

    /* "sklearn/linear_model/cd_fast.pyx":52
 * 
 * cdef inline floating fmax(floating x, floating y) nogil:
 *     if x > y:             # <<<<<<<<<<<<<<
 *         return x
 *     return y
 */
  }

  /* "sklearn/linear_model/cd_fast.pyx":54
 *     if x > y:
 *         return x
 *     return y             # <<<<<<<<<<<<<<
 * 
 * 
 */
  __pyx_r = __pyx_v_y;
  goto __pyx_L0;

  /* "sklearn/linear_model/cd_fast.pyx":51
 * 
 * 
 * cdef inline floating fmax(floating x, floating y) nogil:             # <<<<<<<<<<<<<<
 *     if x > y:
 *         return x
 */

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

/* "sklearn/linear_model/cd_fast.pyx":57
 * 
 * 
 * cdef inline floating fsign(floating f) nogil:             # <<<<<<<<<<<<<<
 *     if f == 0:
 *         return 0
 */

static CYTHON_INLINE float __pyx_fuse_0__pyx_f_7sklearn_12linear_model_7cd_fast_fsign(float __pyx_v_f) {
  float __pyx_r;
  int __pyx_t_1;

  /* "sklearn/linear_model/cd_fast.pyx":58
 * 
 * cdef inline floating fsign(floating f) nogil:
 *     if f == 0:             # <<<<<<<<<<<<<<
 *         return 0
 *     elif f > 0:
 */
  __pyx_t_1 = ((__pyx_v_f == 0.0) != 0);
  if (__pyx_t_1) {

    /* "sklearn/linear_model/cd_fast.pyx":59
 * cdef inline floating fsign(floating f) nogil:
 *     if f == 0:
 *         return 0             # <<<<<<<<<<<<<<
 *     elif f > 0:
 *         return 1.0
 */
    __pyx_r = 0.0;
    goto __pyx_L0;

    /* "sklearn/linear_model/cd_fast.pyx":58
 * 
 * cdef inline floating fsign(floating f) nogil:
 *     if f == 0:             # <<<<<<<<<<<<<<
 *         return 0
 *     elif f > 0:
 */
  }

  /* "sklearn/linear_model/cd_fast.pyx":60
 *     if f == 0:
 *         return 0
 *     elif f > 0:             # <<<<<<<<<<<<<<
 *         return 1.0
 *     else:
 */
  __pyx_t_1 = ((__pyx_v_f > 0.0) != 0);
  if (__pyx_t_1) {

    /* "sklearn/linear_model/cd_fast.pyx":61
 *         return 0
 *     elif f > 0:
 *         return 1.0             # <<<<<<<<<<<<<<
 *     else:
 *         return -1.0
 */
    __pyx_r = 1.0;
    goto __pyx_L0;

    /* "sklearn/linear_model/cd_fast.pyx":60
 *     if f == 0:
 *         return 0
 *     elif f > 0:             # <<<<<<<<<<<<<<
 *         return 1.0
 *     else:
 */
  }

  /* "sklearn/linear_model/cd_fast.pyx":63
 *         return 1.0
 *     else:
 *         return -1.0             # <<<<<<<<<<<<<<
 * 
 * 
 */
  /*else*/ {
    __pyx_r = -1.0;
    goto __pyx_L0;
  }

  /* "sklearn/linear_model/cd_fast.pyx":57
 * 
 * 
 * cdef inline floating fsign(floating f) nogil:             # <<<<<<<<<<<<<<
 *     if f == 0:
 *         return 0
 */

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

static CYTHON_INLINE double __pyx_fuse_1__pyx_f_7sklearn_12linear_model_7cd_fast_fsign(double __pyx_v_f) {
  double __pyx_r;
  int __pyx_t_1;

  /* "sklearn/linear_model/cd_fast.pyx":58
 * 
 * cdef inline floating fsign(floating f) nogil:
 *     if f == 0:             # <<<<<<<<<<<<<<
 *         return 0
 *     elif f > 0:
 */
  __pyx_t_1 = ((__pyx_v_f == 0.0) != 0);
  if (__pyx_t_1) {

    /* "sklearn/linear_model/cd_fast.pyx":59
 * cdef inline floating fsign(floating f) nogil:
 *     if f == 0:
 *         return 0             # <<<<<<<<<<<<<<
 *     elif f > 0:
 *         return 1.0
 */
    __pyx_r = 0.0;
    goto __pyx_L0;

    /* "sklearn/linear_model/cd_fast.pyx":58
 * 
 * cdef inline floating fsign(floating f) nogil:
 *     if f == 0:             # <<<<<<<<<<<<<<
 *         return 0
 *     elif f > 0:
 */
  }

  /* "sklearn/linear_model/cd_fast.pyx":60
 *     if f == 0:
 *         return 0
 *     elif f > 0:             # <<<<<<<<<<<<<<
 *         return 1.0
 *     else:
 */
  __pyx_t_1 = ((__pyx_v_f > 0.0) != 0);
  if (__pyx_t_1) {

    /* "sklearn/linear_model/cd_fast.pyx":61
 *         return 0
 *     elif f > 0:
 *         return 1.0             # <<<<<<<<<<<<<<
 *     else:
 *         return -1.0
 */
    __pyx_r = 1.0;
    goto __pyx_L0;

    /* "sklearn/linear_model/cd_fast.pyx":60
 *     if f == 0:
 *         return 0
 *     elif f > 0:             # <<<<<<<<<<<<<<
 *         return 1.0
 *     else:
 */
  }

  /* "sklearn/linear_model/cd_fast.pyx":63
 *         return 1.0
 *     else:
 *         return -1.0             # <<<<<<<<<<<<<<
 * 
 * 
 */
  /*else*/ {
    __pyx_r = -1.0;
    goto __pyx_L0;
  }

  /* "sklearn/linear_model/cd_fast.pyx":57
 * 
 * 
 * cdef inline floating fsign(floating f) nogil:             # <<<<<<<<<<<<<<
 *     if f == 0:
 *         return 0
 */

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

/* "sklearn/linear_model/cd_fast.pyx":66
 * 
 * 
 * cdef floating abs_max(int n, floating* a) nogil:             # <<<<<<<<<<<<<<
 *     """np.max(np.abs(a))"""
 *     cdef int i
 */

static float __pyx_fuse_0__pyx_f_7sklearn_12linear_model_7cd_fast_abs_max(int __pyx_v_n, float *__pyx_v_a) {
  int __pyx_v_i;
  float __pyx_v_m;
  float __pyx_v_d;
  float __pyx_r;
  int __pyx_t_1;
  int __pyx_t_2;
  int __pyx_t_3;

  /* "sklearn/linear_model/cd_fast.pyx":69
 *     """np.max(np.abs(a))"""
 *     cdef int i
 *     cdef floating m = fabs(a[0])             # <<<<<<<<<<<<<<
 *     cdef floating d
 *     for i in range(1, n):
 */
  __pyx_v_m = fabs((__pyx_v_a[0]));

  /* "sklearn/linear_model/cd_fast.pyx":71
 *     cdef floating m = fabs(a[0])
 *     cdef floating d
 *     for i in range(1, n):             # <<<<<<<<<<<<<<
 *         d = fabs(a[i])
 *         if d > m:
 */
  __pyx_t_1 = __pyx_v_n;
  for (__pyx_t_2 = 1; __pyx_t_2 < __pyx_t_1; __pyx_t_2+=1) {
    __pyx_v_i = __pyx_t_2;

    /* "sklearn/linear_model/cd_fast.pyx":72
 *     cdef floating d
 *     for i in range(1, n):
 *         d = fabs(a[i])             # <<<<<<<<<<<<<<
 *         if d > m:
 *             m = d
 */
    __pyx_v_d = fabs((__pyx_v_a[__pyx_v_i]));

    /* "sklearn/linear_model/cd_fast.pyx":73
 *     for i in range(1, n):
 *         d = fabs(a[i])
 *         if d > m:             # <<<<<<<<<<<<<<
 *             m = d
 *     return m
 */
    __pyx_t_3 = ((__pyx_v_d > __pyx_v_m) != 0);
    if (__pyx_t_3) {

      /* "sklearn/linear_model/cd_fast.pyx":74
 *         d = fabs(a[i])
 *         if d > m:
 *             m = d             # <<<<<<<<<<<<<<
 *     return m
 * 
 */
      __pyx_v_m = __pyx_v_d;

      /* "sklearn/linear_model/cd_fast.pyx":73
 *     for i in range(1, n):
 *         d = fabs(a[i])
 *         if d > m:             # <<<<<<<<<<<<<<
 *             m = d
 *     return m
 */
    }
  }

  /* "sklearn/linear_model/cd_fast.pyx":75
 *         if d > m:
 *             m = d
 *     return m             # <<<<<<<<<<<<<<
 * 
 * 
 */
  __pyx_r = __pyx_v_m;
  goto __pyx_L0;

  /* "sklearn/linear_model/cd_fast.pyx":66
 * 
 * 
 * cdef floating abs_max(int n, floating* a) nogil:             # <<<<<<<<<<<<<<
 *     """np.max(np.abs(a))"""
 *     cdef int i
 */

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

static double __pyx_fuse_1__pyx_f_7sklearn_12linear_model_7cd_fast_abs_max(int __pyx_v_n, double *__pyx_v_a) {
  int __pyx_v_i;
  double __pyx_v_m;
  double __pyx_v_d;
  double __pyx_r;
  int __pyx_t_1;
  int __pyx_t_2;
  int __pyx_t_3;

  /* "sklearn/linear_model/cd_fast.pyx":69
 *     """np.max(np.abs(a))"""
 *     cdef int i
 *     cdef floating m = fabs(a[0])             # <<<<<<<<<<<<<<
 *     cdef floating d
 *     for i in range(1, n):
 */
  __pyx_v_m = fabs((__pyx_v_a[0]));

  /* "sklearn/linear_model/cd_fast.pyx":71
 *     cdef floating m = fabs(a[0])
 *     cdef floating d
 *     for i in range(1, n):             # <<<<<<<<<<<<<<
 *         d = fabs(a[i])
 *         if d > m:
 */
  __pyx_t_1 = __pyx_v_n;
  for (__pyx_t_2 = 1; __pyx_t_2 < __pyx_t_1; __pyx_t_2+=1) {
    __pyx_v_i = __pyx_t_2;

    /* "sklearn/linear_model/cd_fast.pyx":72
 *     cdef floating d
 *     for i in range(1, n):
 *         d = fabs(a[i])             # <<<<<<<<<<<<<<
 *         if d > m:
 *             m = d
 */
    __pyx_v_d = fabs((__pyx_v_a[__pyx_v_i]));

    /* "sklearn/linear_model/cd_fast.pyx":73
 *     for i in range(1, n):
 *         d = fabs(a[i])
 *         if d > m:             # <<<<<<<<<<<<<<
 *             m = d
 *     return m
 */
    __pyx_t_3 = ((__pyx_v_d > __pyx_v_m) != 0);
    if (__pyx_t_3) {

      /* "sklearn/linear_model/cd_fast.pyx":74
 *         d = fabs(a[i])
 *         if d > m:
 *             m = d             # <<<<<<<<<<<<<<
 *     return m
 * 
 */
      __pyx_v_m = __pyx_v_d;

      /* "sklearn/linear_model/cd_fast.pyx":73
 *     for i in range(1, n):
 *         d = fabs(a[i])
 *         if d > m:             # <<<<<<<<<<<<<<
 *             m = d
 *     return m
 */
    }
  }

  /* "sklearn/linear_model/cd_fast.pyx":75
 *         if d > m:
 *             m = d
 *     return m             # <<<<<<<<<<<<<<
 * 
 * 
 */
  __pyx_r = __pyx_v_m;
  goto __pyx_L0;

  /* "sklearn/linear_model/cd_fast.pyx":66
 * 
 * 
 * cdef floating abs_max(int n, floating* a) nogil:             # <<<<<<<<<<<<<<
 *     """np.max(np.abs(a))"""
 *     cdef int i
 */

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

/* "sklearn/linear_model/cd_fast.pyx":78
 * 
 * 
 * cdef floating max(int n, floating* a) nogil:             # <<<<<<<<<<<<<<
 *     """np.max(a)"""
 *     cdef int i
 */

static float __pyx_fuse_0__pyx_f_7sklearn_12linear_model_7cd_fast_max(int __pyx_v_n, float *__pyx_v_a) {
  int __pyx_v_i;
  float __pyx_v_m;
  float __pyx_v_d;
  float __pyx_r;
  int __pyx_t_1;
  int __pyx_t_2;
  int __pyx_t_3;

  /* "sklearn/linear_model/cd_fast.pyx":81
 *     """np.max(a)"""
 *     cdef int i
 *     cdef floating m = a[0]             # <<<<<<<<<<<<<<
 *     cdef floating d
 *     for i in range(1, n):
 */
  __pyx_v_m = (__pyx_v_a[0]);

  /* "sklearn/linear_model/cd_fast.pyx":83
 *     cdef floating m = a[0]
 *     cdef floating d
 *     for i in range(1, n):             # <<<<<<<<<<<<<<
 *         d = a[i]
 *         if d > m:
 */
  __pyx_t_1 = __pyx_v_n;
  for (__pyx_t_2 = 1; __pyx_t_2 < __pyx_t_1; __pyx_t_2+=1) {
    __pyx_v_i = __pyx_t_2;

    /* "sklearn/linear_model/cd_fast.pyx":84
 *     cdef floating d
 *     for i in range(1, n):
 *         d = a[i]             # <<<<<<<<<<<<<<
 *         if d > m:
 *             m = d
 */
    __pyx_v_d = (__pyx_v_a[__pyx_v_i]);

    /* "sklearn/linear_model/cd_fast.pyx":85
 *     for i in range(1, n):
 *         d = a[i]
 *         if d > m:             # <<<<<<<<<<<<<<
 *             m = d
 *     return m
 */
    __pyx_t_3 = ((__pyx_v_d > __pyx_v_m) != 0);
    if (__pyx_t_3) {

      /* "sklearn/linear_model/cd_fast.pyx":86
 *         d = a[i]
 *         if d > m:
 *             m = d             # <<<<<<<<<<<<<<
 *     return m
 * 
 */
      __pyx_v_m = __pyx_v_d;

      /* "sklearn/linear_model/cd_fast.pyx":85
 *     for i in range(1, n):
 *         d = a[i]
 *         if d > m:             # <<<<<<<<<<<<<<
 *             m = d
 *     return m
 */
    }
  }

  /* "sklearn/linear_model/cd_fast.pyx":87
 *         if d > m:
 *             m = d
 *     return m             # <<<<<<<<<<<<<<
 * 
 * 
 */
  __pyx_r = __pyx_v_m;
  goto __pyx_L0;

  /* "sklearn/linear_model/cd_fast.pyx":78
 * 
 * 
 * cdef floating max(int n, floating* a) nogil:             # <<<<<<<<<<<<<<
 *     """np.max(a)"""
 *     cdef int i
 */

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

static double __pyx_fuse_1__pyx_f_7sklearn_12linear_model_7cd_fast_max(int __pyx_v_n, double *__pyx_v_a) {
  int __pyx_v_i;
  double __pyx_v_m;
  double __pyx_v_d;
  double __pyx_r;
  int __pyx_t_1;
  int __pyx_t_2;
  int __pyx_t_3;

  /* "sklearn/linear_model/cd_fast.pyx":81
 *     """np.max(a)"""
 *     cdef int i
 *     cdef floating m = a[0]             # <<<<<<<<<<<<<<
 *     cdef floating d
 *     for i in range(1, n):
 */
  __pyx_v_m = (__pyx_v_a[0]);

  /* "sklearn/linear_model/cd_fast.pyx":83
 *     cdef floating m = a[0]
 *     cdef floating d
 *     for i in range(1, n):             # <<<<<<<<<<<<<<
 *         d = a[i]
 *         if d > m:
 */
  __pyx_t_1 = __pyx_v_n;
  for (__pyx_t_2 = 1; __pyx_t_2 < __pyx_t_1; __pyx_t_2+=1) {
    __pyx_v_i = __pyx_t_2;

    /* "sklearn/linear_model/cd_fast.pyx":84
 *     cdef floating d
 *     for i in range(1, n):
 *         d = a[i]             # <<<<<<<<<<<<<<
 *         if d > m:
 *             m = d
 */
    __pyx_v_d = (__pyx_v_a[__pyx_v_i]);

    /* "sklearn/linear_model/cd_fast.pyx":85
 *     for i in range(1, n):
 *         d = a[i]
 *         if d > m:             # <<<<<<<<<<<<<<
 *             m = d
 *     return m
 */
    __pyx_t_3 = ((__pyx_v_d > __pyx_v_m) != 0);
    if (__pyx_t_3) {

      /* "sklearn/linear_model/cd_fast.pyx":86
 *         d = a[i]
 *         if d > m:
 *             m = d             # <<<<<<<<<<<<<<
 *     return m
 * 
 */
      __pyx_v_m = __pyx_v_d;

      /* "sklearn/linear_model/cd_fast.pyx":85
 *     for i in range(1, n):
 *         d = a[i]
 *         if d > m:             # <<<<<<<<<<<<<<
 *             m = d
 *     return m
 */
    }
  }

  /* "sklearn/linear_model/cd_fast.pyx":87
 *         if d > m:
 *             m = d
 *     return m             # <<<<<<<<<<<<<<
 * 
 * 
 */
  __pyx_r = __pyx_v_m;
  goto __pyx_L0;

  /* "sklearn/linear_model/cd_fast.pyx":78
 * 
 * 
 * cdef floating max(int n, floating* a) nogil:             # <<<<<<<<<<<<<<
 *     """np.max(a)"""
 *     cdef int i
 */

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

/* "sklearn/linear_model/cd_fast.pyx":90
 * 
 * 
 * cdef floating diff_abs_max(int n, floating* a, floating* b) nogil:             # <<<<<<<<<<<<<<
 *     """np.max(np.abs(a - b))"""
 *     cdef int i
 */

static float __pyx_fuse_0__pyx_f_7sklearn_12linear_model_7cd_fast_diff_abs_max(int __pyx_v_n, float *__pyx_v_a, float *__pyx_v_b) {
  int __pyx_v_i;
  float __pyx_v_m;
  float __pyx_v_d;
  float __pyx_r;
  int __pyx_t_1;
  int __pyx_t_2;
  int __pyx_t_3;

  /* "sklearn/linear_model/cd_fast.pyx":93
 *     """np.max(np.abs(a - b))"""
 *     cdef int i
 *     cdef floating m = fabs(a[0] - b[0])             # <<<<<<<<<<<<<<
 *     cdef floating d
 *     for i in range(1, n):
 */
  __pyx_v_m = fabs(((__pyx_v_a[0]) - (__pyx_v_b[0])));

  /* "sklearn/linear_model/cd_fast.pyx":95
 *     cdef floating m = fabs(a[0] - b[0])
 *     cdef floating d
 *     for i in range(1, n):             # <<<<<<<<<<<<<<
 *         d = fabs(a[i] - b[i])
 *         if d > m:
 */
  __pyx_t_1 = __pyx_v_n;
  for (__pyx_t_2 = 1; __pyx_t_2 < __pyx_t_1; __pyx_t_2+=1) {
    __pyx_v_i = __pyx_t_2;

    /* "sklearn/linear_model/cd_fast.pyx":96
 *     cdef floating d
 *     for i in range(1, n):
 *         d = fabs(a[i] - b[i])             # <<<<<<<<<<<<<<
 *         if d > m:
 *             m = d
 */
    __pyx_v_d = fabs(((__pyx_v_a[__pyx_v_i]) - (__pyx_v_b[__pyx_v_i])));

    /* "sklearn/linear_model/cd_fast.pyx":97
 *     for i in range(1, n):
 *         d = fabs(a[i] - b[i])
 *         if d > m:             # <<<<<<<<<<<<<<
 *             m = d
 *     return m
 */
    __pyx_t_3 = ((__pyx_v_d > __pyx_v_m) != 0);
    if (__pyx_t_3) {

      /* "sklearn/linear_model/cd_fast.pyx":98
 *         d = fabs(a[i] - b[i])
 *         if d > m:
 *             m = d             # <<<<<<<<<<<<<<
 *     return m
 * 
 */
      __pyx_v_m = __pyx_v_d;

      /* "sklearn/linear_model/cd_fast.pyx":97
 *     for i in range(1, n):
 *         d = fabs(a[i] - b[i])
 *         if d > m:             # <<<<<<<<<<<<<<
 *             m = d
 *     return m
 */
    }
  }

  /* "sklearn/linear_model/cd_fast.pyx":99
 *         if d > m:
 *             m = d
 *     return m             # <<<<<<<<<<<<<<
 * 
 * 
 */
  __pyx_r = __pyx_v_m;
  goto __pyx_L0;

  /* "sklearn/linear_model/cd_fast.pyx":90
 * 
 * 
 * cdef floating diff_abs_max(int n, floating* a, floating* b) nogil:             # <<<<<<<<<<<<<<
 *     """np.max(np.abs(a - b))"""
 *     cdef int i
 */

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

static double __pyx_fuse_1__pyx_f_7sklearn_12linear_model_7cd_fast_diff_abs_max(int __pyx_v_n, double *__pyx_v_a, double *__pyx_v_b) {
  int __pyx_v_i;
  double __pyx_v_m;
  double __pyx_v_d;
  double __pyx_r;
  int __pyx_t_1;
  int __pyx_t_2;
  int __pyx_t_3;

  /* "sklearn/linear_model/cd_fast.pyx":93
 *     """np.max(np.abs(a - b))"""
 *     cdef int i
 *     cdef floating m = fabs(a[0] - b[0])             # <<<<<<<<<<<<<<
 *     cdef floating d
 *     for i in range(1, n):
 */
  __pyx_v_m = fabs(((__pyx_v_a[0]) - (__pyx_v_b[0])));

  /* "sklearn/linear_model/cd_fast.pyx":95
 *     cdef floating m = fabs(a[0] - b[0])
 *     cdef floating d
 *     for i in range(1, n):             # <<<<<<<<<<<<<<
 *         d = fabs(a[i] - b[i])
 *         if d > m:
 */
  __pyx_t_1 = __pyx_v_n;
  for (__pyx_t_2 = 1; __pyx_t_2 < __pyx_t_1; __pyx_t_2+=1) {
    __pyx_v_i = __pyx_t_2;

    /* "sklearn/linear_model/cd_fast.pyx":96
 *     cdef floating d
 *     for i in range(1, n):
 *         d = fabs(a[i] - b[i])             # <<<<<<<<<<<<<<
 *         if d > m:
 *             m = d
 */
    __pyx_v_d = fabs(((__pyx_v_a[__pyx_v_i]) - (__pyx_v_b[__pyx_v_i])));

    /* "sklearn/linear_model/cd_fast.pyx":97
 *     for i in range(1, n):
 *         d = fabs(a[i] - b[i])
 *         if d > m:             # <<<<<<<<<<<<<<
 *             m = d
 *     return m
 */
    __pyx_t_3 = ((__pyx_v_d > __pyx_v_m) != 0);
    if (__pyx_t_3) {

      /* "sklearn/linear_model/cd_fast.pyx":98
 *         d = fabs(a[i] - b[i])
 *         if d > m:
 *             m = d             # <<<<<<<<<<<<<<
 *     return m
 * 
 */
      __pyx_v_m = __pyx_v_d;

      /* "sklearn/linear_model/cd_fast.pyx":97
 *     for i in range(1, n):
 *         d = fabs(a[i] - b[i])
 *         if d > m:             # <<<<<<<<<<<<<<
 *             m = d
 *     return m
 */
    }
  }

  /* "sklearn/linear_model/cd_fast.pyx":99
 *         if d > m:
 *             m = d
 *     return m             # <<<<<<<<<<<<<<
 * 
 * 
 */
  __pyx_r = __pyx_v_m;
  goto __pyx_L0;

  /* "sklearn/linear_model/cd_fast.pyx":90
 * 
 * 
 * cdef floating diff_abs_max(int n, floating* a, floating* b) nogil:             # <<<<<<<<<<<<<<
 *     """np.max(np.abs(a - b))"""
 *     cdef int i
 */

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

/* "sklearn/linear_model/cd_fast.pyx":149
 * @cython.wraparound(False)
 * @cython.cdivision(True)
 * def enet_coordinate_descent(np.ndarray[floating, ndim=1] w,             # <<<<<<<<<<<<<<
 *                             floating alpha, floating beta,
 *                             np.ndarray[floating, ndim=2, mode='fortran'] X,
 */

/* Python wrapper */
static PyObject *__pyx_pw_7sklearn_12linear_model_7cd_fast_1enet_coordinate_descent(PyObject *__pyx_self, PyObject *__pyx_args, PyObject *__pyx_kwds); /*proto*/
static char __pyx_doc_7sklearn_12linear_model_7cd_fast_enet_coordinate_descent[] = "Cython version of the coordinate descent algorithm\n        for Elastic-Net regression\n\n        We minimize\n\n        (1/2) * norm(y - X w, 2)^2 + alpha norm(w, 1) + (beta/2) norm(w, 2)^2\n\n    ";
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 *                 else:
 */
            __pyx_t_11 = (__pyx_v_random != 0);
            if (__pyx_t_11) {

              /* "sklearn/linear_model/cd_fast.pyx":237
 *             for f_iter in range(n_features):  # Loop over coordinates
 *                 if random:
 *                     ii = rand_int(n_features, rand_r_state)             # <<<<<<<<<<<<<<
 *                 else:
 *                     ii = f_iter
 */
              __pyx_v_ii = __pyx_f_7sklearn_12linear_model_7cd_fast_rand_int(__pyx_v_n_features, __pyx_v_rand_r_state);

              /* "sklearn/linear_model/cd_fast.pyx":236
 *             d_w_max = 0.0
 *             for f_iter in range(n_features):  # Loop over coordinates
 *                 if random:             # <<<<<<<<<<<<<<
 *                     ii = rand_int(n_features, rand_r_state)
 *                 else:
 */
              goto __pyx_L15;
            }

            /* "sklearn/linear_model/cd_fast.pyx":239
 *                     ii = rand_int(n_features, rand_r_state)
 *                 else:
 *                     ii = f_iter             # <<<<<<<<<<<<<<
 * 
 *                 if norm_cols_X[ii] == 0.0:
 */
            /*else*/ {
              __pyx_v_ii = __pyx_v_f_iter;
            }
            __pyx_L15:;

            /* "sklearn/linear_model/cd_fast.pyx":241
 *                     ii = f_iter
 * 
 *                 if norm_cols_X[ii] == 0.0:             # <<<<<<<<<<<<<<
 *                     continue
 * 
 */
            __pyx_t_18 = __pyx_v_ii;
            __pyx_t_11 = (((*__Pyx_BufPtrStrided1d(float *, __pyx_pybuffernd_norm_cols_X.rcbuffer->pybuffer.buf, __pyx_t_18, __pyx_pybuffernd_norm_cols_X.diminfo[0].strides)) == 0.0) != 0);
            if (__pyx_t_11) {

              /* "sklearn/linear_model/cd_fast.pyx":242
 * 
 *                 if norm_cols_X[ii] == 0.0:
 *                     continue             # <<<<<<<<<<<<<<
 * 
 *                 w_ii = w[ii]  # Store previous value
 */
              goto __pyx_L13_continue;

              /* "sklearn/linear_model/cd_fast.pyx":241
 *                     ii = f_iter
 * 
 *                 if norm_cols_X[ii] == 0.0:             # <<<<<<<<<<<<<<
 *                     continue
 * 
 */
            }

            /* "sklearn/linear_model/cd_fast.pyx":244
 *                     continue
 * 
 *                 w_ii = w[ii]  # Store previous value             # <<<<<<<<<<<<<<
 * 
 *                 if w_ii != 0.0:
 */
            __pyx_t_19 = __pyx_v_ii;
            __pyx_v_w_ii = (*__Pyx_BufPtrStrided1d(float *, __pyx_pybuffernd_w.rcbuffer->pybuffer.buf, __pyx_t_19, __pyx_pybuffernd_w.diminfo[0].strides));

            /* "sklearn/linear_model/cd_fast.pyx":246
 *                 w_ii = w[ii]  # Store previous value
 * 
 *                 if w_ii != 0.0:             # <<<<<<<<<<<<<<
 *                     # R += w_ii * X[:,ii]
 *                     axpy(n_samples, w_ii, &X_data[ii * n_samples], 1,
 */
            __pyx_t_11 = ((__pyx_v_w_ii != 0.0) != 0);
            if (__pyx_t_11) {

              /* "sklearn/linear_model/cd_fast.pyx":248
 *                 if w_ii != 0.0:
 *                     # R += w_ii * X[:,ii]
 *                     axpy(n_samples, w_ii, &X_data[ii * n_samples], 1,             # <<<<<<<<<<<<<<
 *                          R_data, 1)
 * 
 */
              __pyx_v_axpy(__pyx_v_n_samples, __pyx_v_w_ii, (&(__pyx_v_X_data[(__pyx_v_ii * __pyx_v_n_samples)])), 1, __pyx_v_R_data, 1);

              /* "sklearn/linear_model/cd_fast.pyx":246
 *                 w_ii = w[ii]  # Store previous value
 * 
 *                 if w_ii != 0.0:             # <<<<<<<<<<<<<<
 *                     # R += w_ii * X[:,ii]
 *                     axpy(n_samples, w_ii, &X_data[ii * n_samples], 1,
 */
            }

            /* "sklearn/linear_model/cd_fast.pyx":252
 * 
 *                 # tmp = (X[:,ii]*R).sum()
 *                 tmp = dot(n_samples, &X_data[ii * n_samples], 1, R_data, 1)             # <<<<<<<<<<<<<<
 * 
 *                 if positive and tmp < 0:
 */
            __pyx_v_tmp = __pyx_v_dot(__pyx_v_n_samples, (&(__pyx_v_X_data[(__pyx_v_ii * __pyx_v_n_samples)])), 1, __pyx_v_R_data, 1);

            /* "sklearn/linear_model/cd_fast.pyx":254
 *                 tmp = dot(n_samples, &X_data[ii * n_samples], 1, R_data, 1)
 * 
 *                 if positive and tmp < 0:             # <<<<<<<<<<<<<<
 *                     w[ii] = 0.0
 *                 else:
 */
            __pyx_t_12 = (__pyx_v_positive != 0);
            if (__pyx_t_12) {
            } else {
              __pyx_t_11 = __pyx_t_12;
              goto __pyx_L19_bool_binop_done;
            }
            __pyx_t_12 = ((__pyx_v_tmp < 0.0) != 0);
            __pyx_t_11 = __pyx_t_12;
            __pyx_L19_bool_binop_done:;
            if (__pyx_t_11) {

              /* "sklearn/linear_model/cd_fast.pyx":255
 * 
 *                 if positive and tmp < 0:
 *                     w[ii] = 0.0             # <<<<<<<<<<<<<<
 *                 else:
 *                     w[ii] = (fsign(tmp) * fmax(fabs(tmp) - alpha, 0)
 */
              __pyx_t_20 = __pyx_v_ii;
              *__Pyx_BufPtrStrided1d(float *, __pyx_pybuffernd_w.rcbuffer->pybuffer.buf, __pyx_t_20, __pyx_pybuffernd_w.diminfo[0].strides) = 0.0;

              /* "sklearn/linear_model/cd_fast.pyx":254
 *                 tmp = dot(n_samples, &X_data[ii * n_samples], 1, R_data, 1)
 * 
 *                 if positive and tmp < 0:             # <<<<<<<<<<<<<<
 *                     w[ii] = 0.0
 *                 else:
 */
              goto __pyx_L18;
            }

            /* "sklearn/linear_model/cd_fast.pyx":258
 *                 else:
 *                     w[ii] = (fsign(tmp) * fmax(fabs(tmp) - alpha, 0)
 *                              / (norm_cols_X[ii] + beta))             # <<<<<<<<<<<<<<
 * 
 *                 if w[ii] != 0.0:
 */
            /*else*/ {

              /* "sklearn/linear_model/cd_fast.pyx":257
 *                     w[ii] = 0.0
 *                 else:
 *                     w[ii] = (fsign(tmp) * fmax(fabs(tmp) - alpha, 0)             # <<<<<<<<<<<<<<
 *                              / (norm_cols_X[ii] + beta))
 * 
 */
              __pyx_t_21 = __pyx_v_ii;

              /* "sklearn/linear_model/cd_fast.pyx":258
 *                 else:
 *                     w[ii] = (fsign(tmp) * fmax(fabs(tmp) - alpha, 0)
 *                              / (norm_cols_X[ii] + beta))             # <<<<<<<<<<<<<<
 * 
 *                 if w[ii] != 0.0:
 */
              __pyx_t_22 = __pyx_v_ii;
              *__Pyx_BufPtrStrided1d(float *, __pyx_pybuffernd_w.rcbuffer->pybuffer.buf, __pyx_t_22, __pyx_pybuffernd_w.diminfo[0].strides) = ((__pyx_fuse_0__pyx_f_7sklearn_12linear_model_7cd_fast_fsign(__pyx_v_tmp) * __pyx_fuse_1__pyx_f_7sklearn_12linear_model_7cd_fast_fmax((fabs(__pyx_v_tmp) - __pyx_v_alpha), 0.0)) / ((*__Pyx_BufPtrStrided1d(float *, __pyx_pybuffernd_norm_cols_X.rcbuffer->pybuffer.buf, __pyx_t_21, __pyx_pybuffernd_norm_cols_X.diminfo[0].strides)) + __pyx_v_beta));
            }
            __pyx_L18:;

            /* "sklearn/linear_model/cd_fast.pyx":260
 *                              / (norm_cols_X[ii] + beta))
 * 
 *                 if w[ii] != 0.0:             # <<<<<<<<<<<<<<
 *                     # R -=  w[ii] * X[:,ii] # Update residual
 *                     axpy(n_samples, -w[ii], &X_data[ii * n_samples], 1,
 */
            __pyx_t_23 = __pyx_v_ii;
            __pyx_t_11 = (((*__Pyx_BufPtrStrided1d(float *, __pyx_pybuffernd_w.rcbuffer->pybuffer.buf, __pyx_t_23, __pyx_pybuffernd_w.diminfo[0].strides)) != 0.0) != 0);
            if (__pyx_t_11) {

              /* "sklearn/linear_model/cd_fast.pyx":262
 *                 if w[ii] != 0.0:
 *                     # R -=  w[ii] * X[:,ii] # Update residual
 *                     axpy(n_samples, -w[ii], &X_data[ii * n_samples], 1,             # <<<<<<<<<<<<<<
 *                          R_data, 1)
 * 
 */
              __pyx_t_24 = __pyx_v_ii;

              /* "sklearn/linear_model/cd_fast.pyx":263
 *                     # R -=  w[ii] * X[:,ii] # Update residual
 *                     axpy(n_samples, -w[ii], &X_data[ii * n_samples], 1,
 *                          R_data, 1)             # <<<<<<<<<<<<<<
 * 
 *                 # update the maximum absolute coefficient update
 */
              __pyx_v_axpy(__pyx_v_n_samples, (-(*__Pyx_BufPtrStrided1d(float *, __pyx_pybuffernd_w.rcbuffer->pybuffer.buf, __pyx_t_24, __pyx_pybuffernd_w.diminfo[0].strides))), (&(__pyx_v_X_data[(__pyx_v_ii * __pyx_v_n_samples)])), 1, __pyx_v_R_data, 1);

              /* "sklearn/linear_model/cd_fast.pyx":260
 *                              / (norm_cols_X[ii] + beta))
 * 
 *                 if w[ii] != 0.0:             # <<<<<<<<<<<<<<
 *                     # R -=  w[ii] * X[:,ii] # Update residual
 *                     axpy(n_samples, -w[ii], &X_data[ii * n_samples], 1,
 */
            }

            /* "sklearn/linear_model/cd_fast.pyx":266
 * 
 *                 # update the maximum absolute coefficient update
 *                 d_w_ii = fabs(w[ii] - w_ii)             # <<<<<<<<<<<<<<
 *                 if d_w_ii > d_w_max:
 *                     d_w_max = d_w_ii
 */
            __pyx_t_25 = __pyx_v_ii;
            __pyx_v_d_w_ii = fabs(((*__Pyx_BufPtrStrided1d(float *, __pyx_pybuffernd_w.rcbuffer->pybuffer.buf, __pyx_t_25, __pyx_pybuffernd_w.diminfo[0].strides)) - __pyx_v_w_ii));

            /* "sklearn/linear_model/cd_fast.pyx":267
 *                 # update the maximum absolute coefficient update
 *                 d_w_ii = fabs(w[ii] - w_ii)
 *                 if d_w_ii > d_w_max:             # <<<<<<<<<<<<<<
 *                     d_w_max = d_w_ii
 * 
 */
            __pyx_t_11 = ((__pyx_v_d_w_ii > __pyx_v_d_w_max) != 0);
            if (__pyx_t_11) {

              /* "sklearn/linear_model/cd_fast.pyx":268
 *                 d_w_ii = fabs(w[ii] - w_ii)
 *                 if d_w_ii > d_w_max:
 *                     d_w_max = d_w_ii             # <<<<<<<<<<<<<<
 * 
 *                 if fabs(w[ii]) > w_max:
 */
              __pyx_v_d_w_max = __pyx_v_d_w_ii;

              /* "sklearn/linear_model/cd_fast.pyx":267
 *                 # update the maximum absolute coefficient update
 *                 d_w_ii = fabs(w[ii] - w_ii)
 *                 if d_w_ii > d_w_max:             # <<<<<<<<<<<<<<
 *                     d_w_max = d_w_ii
 * 
 */
            }

            /* "sklearn/linear_model/cd_fast.pyx":270
 *                     d_w_max = d_w_ii
 * 
 *                 if fabs(w[ii]) > w_max:             # <<<<<<<<<<<<<<
 *                     w_max = fabs(w[ii])
 * 
 */
            __pyx_t_26 = __pyx_v_ii;
            __pyx_t_11 = ((fabs((*__Pyx_BufPtrStrided1d(float *, __pyx_pybuffernd_w.rcbuffer->pybuffer.buf, __pyx_t_26, __pyx_pybuffernd_w.diminfo[0].strides))) > __pyx_v_w_max) != 0);
            if (__pyx_t_11) {

              /* "sklearn/linear_model/cd_fast.pyx":271
 * 
 *                 if fabs(w[ii]) > w_max:
 *                     w_max = fabs(w[ii])             # <<<<<<<<<<<<<<
 * 
 *             if (w_max == 0.0 or
 */
              __pyx_t_27 = __pyx_v_ii;
              __pyx_v_w_max = fabs((*__Pyx_BufPtrStrided1d(float *, __pyx_pybuffernd_w.rcbuffer->pybuffer.buf, __pyx_t_27, __pyx_pybuffernd_w.diminfo[0].strides)));

              /* "sklearn/linear_model/cd_fast.pyx":270
 *                     d_w_max = d_w_ii
 * 
 *                 if fabs(w[ii]) > w_max:             # <<<<<<<<<<<<<<
 *                     w_max = fabs(w[ii])
 * 
 */
            }
            __pyx_L13_continue:;
          }

          /* "sklearn/linear_model/cd_fast.pyx":273
 *                     w_max = fabs(w[ii])
 * 
 *             if (w_max == 0.0 or             # <<<<<<<<<<<<<<
 *                 d_w_max / w_max < d_w_tol or
 *                 n_iter == max_iter - 1):
 */
          __pyx_t_12 = ((__pyx_v_w_max == 0.0) != 0);
          if (!__pyx_t_12) {
          } else {
            __pyx_t_11 = __pyx_t_12;
            goto __pyx_L25_bool_binop_done;
          }

          /* "sklearn/linear_model/cd_fast.pyx":274
 * 
 *             if (w_max == 0.0 or
 *                 d_w_max / w_max < d_w_tol or             # <<<<<<<<<<<<<<
 *                 n_iter == max_iter - 1):
 *                 # the biggest coordinate update of this iteration was smaller
 */
          __pyx_t_12 = (((__pyx_v_d_w_max / __pyx_v_w_max) < __pyx_v_d_w_tol) != 0);
          if (!__pyx_t_12) {
          } else {
            __pyx_t_11 = __pyx_t_12;
            goto __pyx_L25_bool_binop_done;
          }

          /* "sklearn/linear_model/cd_fast.pyx":275
 *             if (w_max == 0.0 or
 *                 d_w_max / w_max < d_w_tol or
 *                 n_iter == max_iter - 1):             # <<<<<<<<<<<<<<
 *                 # the biggest coordinate update of this iteration was smaller
 *                 # than the tolerance: check the duality gap as ultimate
 */
          __pyx_t_12 = ((__pyx_v_n_iter == (__pyx_v_max_iter - 1)) != 0);
          __pyx_t_11 = __pyx_t_12;
          __pyx_L25_bool_binop_done:;

          /* "sklearn/linear_model/cd_fast.pyx":273
 *                     w_max = fabs(w[ii])
 * 
 *             if (w_max == 0.0 or             # <<<<<<<<<<<<<<
 *                 d_w_max / w_max < d_w_tol or
 *                 n_iter == max_iter - 1):
 */
          if (__pyx_t_11) {

            /* "sklearn/linear_model/cd_fast.pyx":281
 * 
 *                 # XtA = np.dot(X.T, R) - beta * w
 *                 for i in range(n_features):             # <<<<<<<<<<<<<<
 *                     XtA[i] = dot(n_samples, &X_data[i * n_samples],
 *                                  1, R_data, 1) - beta * w[i]
 */
            __pyx_t_14 = __pyx_v_n_features;
            for (__pyx_t_17 = 0; __pyx_t_17 < __pyx_t_14; __pyx_t_17+=1) {
              __pyx_v_i = __pyx_t_17;

              /* "sklearn/linear_model/cd_fast.pyx":283
 *                 for i in range(n_features):
 *                     XtA[i] = dot(n_samples, &X_data[i * n_samples],
 *                                  1, R_data, 1) - beta * w[i]             # <<<<<<<<<<<<<<
 * 
 *                 if positive:
 */
              __pyx_t_28 = __pyx_v_i;

              /* "sklearn/linear_model/cd_fast.pyx":282
 *                 # XtA = np.dot(X.T, R) - beta * w
 *                 for i in range(n_features):
 *                     XtA[i] = dot(n_samples, &X_data[i * n_samples],             # <<<<<<<<<<<<<<
 *                                  1, R_data, 1) - beta * w[i]
 * 
 */
              __pyx_t_29 = __pyx_v_i;
              *__Pyx_BufPtrStrided1d(float *, __pyx_pybuffernd_XtA.rcbuffer->pybuffer.buf, __pyx_t_29, __pyx_pybuffernd_XtA.diminfo[0].strides) = (__pyx_v_dot(__pyx_v_n_samples, (&(__pyx_v_X_data[(__pyx_v_i * __pyx_v_n_samples)])), 1, __pyx_v_R_data, 1) - (__pyx_v_beta * (*__Pyx_BufPtrStrided1d(float *, __pyx_pybuffernd_w.rcbuffer->pybuffer.buf, __pyx_t_28, __pyx_pybuffernd_w.diminfo[0].strides))));
            }

            /* "sklearn/linear_model/cd_fast.pyx":285
 *                                  1, R_data, 1) - beta * w[i]
 * 
 *                 if positive:             # <<<<<<<<<<<<<<
 *                     dual_norm_XtA = max(n_features, XtA_data)
 *                 else:
 */
            __pyx_t_11 = (__pyx_v_positive != 0);
            if (__pyx_t_11) {

              /* "sklearn/linear_model/cd_fast.pyx":286
 * 
 *                 if positive:
 *                     dual_norm_XtA = max(n_features, XtA_data)             # <<<<<<<<<<<<<<
 *                 else:
 *                     dual_norm_XtA = abs_max(n_features, XtA_data)
 */
              __pyx_v_dual_norm_XtA = __pyx_fuse_0__pyx_f_7sklearn_12linear_model_7cd_fast_max(__pyx_v_n_features, __pyx_v_XtA_data);

              /* "sklearn/linear_model/cd_fast.pyx":285
 *                                  1, R_data, 1) - beta * w[i]
 * 
 *                 if positive:             # <<<<<<<<<<<<<<
 *                     dual_norm_XtA = max(n_features, XtA_data)
 *                 else:
 */
              goto __pyx_L30;
            }

            /* "sklearn/linear_model/cd_fast.pyx":288
 *                     dual_norm_XtA = max(n_features, XtA_data)
 *                 else:
 *                     dual_norm_XtA = abs_max(n_features, XtA_data)             # <<<<<<<<<<<<<<
 * 
 *                 # R_norm2 = np.dot(R, R)
 */
            /*else*/ {
              __pyx_v_dual_norm_XtA = __pyx_fuse_0__pyx_f_7sklearn_12linear_model_7cd_fast_abs_max(__pyx_v_n_features, __pyx_v_XtA_data);
            }
            __pyx_L30:;

            /* "sklearn/linear_model/cd_fast.pyx":291
 * 
 *                 # R_norm2 = np.dot(R, R)
 *                 R_norm2 = dot(n_samples, R_data, 1, R_data, 1)             # <<<<<<<<<<<<<<
 * 
 *                 # w_norm2 = np.dot(w, w)
 */
            __pyx_v_R_norm2 = __pyx_v_dot(__pyx_v_n_samples, __pyx_v_R_data, 1, __pyx_v_R_data, 1);

            /* "sklearn/linear_model/cd_fast.pyx":294
 * 
 *                 # w_norm2 = np.dot(w, w)
 *                 w_norm2 = dot(n_features, w_data, 1, w_data, 1)             # <<<<<<<<<<<<<<
 * 
 *                 if (dual_norm_XtA > alpha):
 */
            __pyx_v_w_norm2 = __pyx_v_dot(__pyx_v_n_features, __pyx_v_w_data, 1, __pyx_v_w_data, 1);

            /* "sklearn/linear_model/cd_fast.pyx":296
 *                 w_norm2 = dot(n_features, w_data, 1, w_data, 1)
 * 
 *                 if (dual_norm_XtA > alpha):             # <<<<<<<<<<<<<<
 *                     const = alpha / dual_norm_XtA
 *                     A_norm2 = R_norm2 * (const ** 2)
 */
            __pyx_t_11 = ((__pyx_v_dual_norm_XtA > __pyx_v_alpha) != 0);
            if (__pyx_t_11) {

              /* "sklearn/linear_model/cd_fast.pyx":297
 * 
 *                 if (dual_norm_XtA > alpha):
 *                     const = alpha / dual_norm_XtA             # <<<<<<<<<<<<<<
 *                     A_norm2 = R_norm2 * (const ** 2)
 *                     gap = 0.5 * (R_norm2 + A_norm2)
 */
              __pyx_v_const = (__pyx_v_alpha / __pyx_v_dual_norm_XtA);

              /* "sklearn/linear_model/cd_fast.pyx":298
 *                 if (dual_norm_XtA > alpha):
 *                     const = alpha / dual_norm_XtA
 *                     A_norm2 = R_norm2 * (const ** 2)             # <<<<<<<<<<<<<<
 *                     gap = 0.5 * (R_norm2 + A_norm2)
 *                 else:
 */
              __pyx_v_A_norm2 = (__pyx_v_R_norm2 * powf(__pyx_v_const, 2.0));

              /* "sklearn/linear_model/cd_fast.pyx":299
 *                     const = alpha / dual_norm_XtA
 *                     A_norm2 = R_norm2 * (const ** 2)
 *                     gap = 0.5 * (R_norm2 + A_norm2)             # <<<<<<<<<<<<<<
 *                 else:
 *                     const = 1.0
 */
              __pyx_v_gap = (0.5 * (__pyx_v_R_norm2 + __pyx_v_A_norm2));

              /* "sklearn/linear_model/cd_fast.pyx":296
 *                 w_norm2 = dot(n_features, w_data, 1, w_data, 1)
 * 
 *                 if (dual_norm_XtA > alpha):             # <<<<<<<<<<<<<<
 *                     const = alpha / dual_norm_XtA
 *                     A_norm2 = R_norm2 * (const ** 2)
 */
              goto __pyx_L31;
            }

            /* "sklearn/linear_model/cd_fast.pyx":301
 *                     gap = 0.5 * (R_norm2 + A_norm2)
 *                 else:
 *                     const = 1.0             # <<<<<<<<<<<<<<
 *                     gap = R_norm2
 * 
 */
            /*else*/ {
              __pyx_v_const = 1.0;

              /* "sklearn/linear_model/cd_fast.pyx":302
 *                 else:
 *                     const = 1.0
 *                     gap = R_norm2             # <<<<<<<<<<<<<<
 * 
 *                 l1_norm = asum(n_features, w_data, 1)
 */
              __pyx_v_gap = __pyx_v_R_norm2;
            }
            __pyx_L31:;

            /* "sklearn/linear_model/cd_fast.pyx":304
 *                     gap = R_norm2
 * 
 *                 l1_norm = asum(n_features, w_data, 1)             # <<<<<<<<<<<<<<
 * 
 *                 # np.dot(R.T, y)
 */
            __pyx_v_l1_norm = __pyx_v_asum(__pyx_v_n_features, __pyx_v_w_data, 1);

            /* "sklearn/linear_model/cd_fast.pyx":307
 * 
 *                 # np.dot(R.T, y)
 *                 gap += (alpha * l1_norm             # <<<<<<<<<<<<<<
 *                         - const * dot(n_samples, R_data, 1, y_data, n_tasks)
 *                         + 0.5 * beta * (1 + const ** 2) * (w_norm2))
 */
            __pyx_v_gap = (__pyx_v_gap + (((__pyx_v_alpha * __pyx_v_l1_norm) - (__pyx_v_const * __pyx_v_dot(__pyx_v_n_samples, __pyx_v_R_data, 1, __pyx_v_y_data, __pyx_v_n_tasks))) + (((0.5 * __pyx_v_beta) * (1.0 + powf(__pyx_v_const, 2.0))) * __pyx_v_w_norm2)));

            /* "sklearn/linear_model/cd_fast.pyx":311
 *                         + 0.5 * beta * (1 + const ** 2) * (w_norm2))
 * 
 *                 if gap < tol:             # <<<<<<<<<<<<<<
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 *                     break
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 *     cdef UINT32_t* rand_r_state = &rand_r_state_seed
 * 
 *     cdef floating *X_data = <floating*> X.data             # <<<<<<<<<<<<<<
 *     cdef floating *y_data = <floating*> y.data
 *     cdef floating *w_data = <floating*> w.data
 */
  __pyx_v_X_data = ((double *)__pyx_v_X->data);

  /* "sklearn/linear_model/cd_fast.pyx":215
 * 
 *     cdef floating *X_data = <floating*> X.data
 *     cdef floating *y_data = <floating*> y.data             # <<<<<<<<<<<<<<
 *     cdef floating *w_data = <floating*> w.data
 *     cdef floating *R_data = <floating*> R.data
 */
  __pyx_v_y_data = ((double *)__pyx_v_y->data);

  /* "sklearn/linear_model/cd_fast.pyx":216
 *     cdef floating *X_data = <floating*> X.data
 *     cdef floating *y_data = <floating*> y.data
 *     cdef floating *w_data = <floating*> w.data             # <<<<<<<<<<<<<<
 *     cdef floating *R_data = <floating*> R.data
 *     cdef floating *XtA_data = <floating*> XtA.data
 */
  __pyx_v_w_data = ((double *)__pyx_v_w->data);

  /* "sklearn/linear_model/cd_fast.pyx":217
 *     cdef floating *y_data = <floating*> y.data
 *     cdef floating *w_data = <floating*> w.data
 *     cdef floating *R_data = <floating*> R.data             # <<<<<<<<<<<<<<
 *     cdef floating *XtA_data = <floating*> XtA.data
 * 
 */
  __pyx_v_R_data = ((double *)__pyx_v_R->data);

  /* "sklearn/linear_model/cd_fast.pyx":218
 *     cdef floating *w_data = <floating*> w.data
 *     cdef floating *R_data = <floating*> R.data
 *     cdef floating *XtA_data = <floating*> XtA.data             # <<<<<<<<<<<<<<
 * 
 *     if alpha == 0 and beta == 0:
 */
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 *     cdef floating *XtA_data = <floating*> XtA.data
 * 
 *     if alpha == 0 and beta == 0:             # <<<<<<<<<<<<<<
 *         warnings.warn("Coordinate descent with no regularization may lead to unexpected"
 *             " results and is discouraged.")
 */
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  __pyx_L4_bool_binop_done:;
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    /* "sklearn/linear_model/cd_fast.pyx":221
 * 
 *     if alpha == 0 and beta == 0:
 *         warnings.warn("Coordinate descent with no regularization may lead to unexpected"             # <<<<<<<<<<<<<<
 *             " results and is discouraged.")
 * 
 */
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    /* "sklearn/linear_model/cd_fast.pyx":220
 *     cdef floating *XtA_data = <floating*> XtA.data
 * 
 *     if alpha == 0 and beta == 0:             # <<<<<<<<<<<<<<
 *         warnings.warn("Coordinate descent with no regularization may lead to unexpected"
 *             " results and is discouraged.")
 */
  }

  /* "sklearn/linear_model/cd_fast.pyx":224
 *             " results and is discouraged.")
 * 
 *     with nogil:             # <<<<<<<<<<<<<<
 *         # R = y - np.dot(X, w)
 *         for i in range(n_samples):
 */
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      #ifdef WITH_THREAD
      PyThreadState *_save;
      Py_UNBLOCK_THREADS
      __Pyx_FastGIL_Remember();
      #endif
      /*try:*/ {

        /* "sklearn/linear_model/cd_fast.pyx":226
 *     with nogil:
 *         # R = y - np.dot(X, w)
 *         for i in range(n_samples):             # <<<<<<<<<<<<<<
 *             R[i] = y[i] - dot(n_features, &X_data[i], n_samples, w_data, 1)
 * 
 */
        __pyx_t_13 = __pyx_v_n_samples;
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          /* "sklearn/linear_model/cd_fast.pyx":227
 *         # R = y - np.dot(X, w)
 *         for i in range(n_samples):
 *             R[i] = y[i] - dot(n_features, &X_data[i], n_samples, w_data, 1)             # <<<<<<<<<<<<<<
 * 
 *         # tol *= np.dot(y, y)
 */
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        /* "sklearn/linear_model/cd_fast.pyx":230
 * 
 *         # tol *= np.dot(y, y)
 *         tol *= dot(n_samples, y_data, n_tasks, y_data, n_tasks)             # <<<<<<<<<<<<<<
 * 
 *         for n_iter in range(max_iter):
 */
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        /* "sklearn/linear_model/cd_fast.pyx":232
 *         tol *= dot(n_samples, y_data, n_tasks, y_data, n_tasks)
 * 
 *         for n_iter in range(max_iter):             # <<<<<<<<<<<<<<
 *             w_max = 0.0
 *             d_w_max = 0.0
 */
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          /* "sklearn/linear_model/cd_fast.pyx":233
 * 
 *         for n_iter in range(max_iter):
 *             w_max = 0.0             # <<<<<<<<<<<<<<
 *             d_w_max = 0.0
 *             for f_iter in range(n_features):  # Loop over coordinates
 */
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          /* "sklearn/linear_model/cd_fast.pyx":234
 *         for n_iter in range(max_iter):
 *             w_max = 0.0
 *             d_w_max = 0.0             # <<<<<<<<<<<<<<
 *             for f_iter in range(n_features):  # Loop over coordinates
 *                 if random:
 */
          __pyx_v_d_w_max = 0.0;

          /* "sklearn/linear_model/cd_fast.pyx":235
 *             w_max = 0.0
 *             d_w_max = 0.0
 *             for f_iter in range(n_features):  # Loop over coordinates             # <<<<<<<<<<<<<<
 *                 if random:
 *                     ii = rand_int(n_features, rand_r_state)
 */
          __pyx_t_14 = __pyx_v_n_features;
          for (__pyx_t_17 = 0; __pyx_t_17 < __pyx_t_14; __pyx_t_17+=1) {
            __pyx_v_f_iter = __pyx_t_17;

            /* "sklearn/linear_model/cd_fast.pyx":236
 *             d_w_max = 0.0
 *             for f_iter in range(n_features):  # Loop over coordinates
 *                 if random:             # <<<<<<<<<<<<<<
 *                     ii = rand_int(n_features, rand_r_state)
 *                 else:
 */
            __pyx_t_11 = (__pyx_v_random != 0);
            if (__pyx_t_11) {

              /* "sklearn/linear_model/cd_fast.pyx":237
 *             for f_iter in range(n_features):  # Loop over coordinates
 *                 if random:
 *                     ii = rand_int(n_features, rand_r_state)             # <<<<<<<<<<<<<<
 *                 else:
 *                     ii = f_iter
 */
              __pyx_v_ii = __pyx_f_7sklearn_12linear_model_7cd_fast_rand_int(__pyx_v_n_features, __pyx_v_rand_r_state);

              /* "sklearn/linear_model/cd_fast.pyx":236
 *             d_w_max = 0.0
 *             for f_iter in range(n_features):  # Loop over coordinates
 *                 if random:             # <<<<<<<<<<<<<<
 *                     ii = rand_int(n_features, rand_r_state)
 *                 else:
 */
              goto __pyx_L15;
            }

            /* "sklearn/linear_model/cd_fast.pyx":239
 *                     ii = rand_int(n_features, rand_r_state)
 *                 else:
 *                     ii = f_iter             # <<<<<<<<<<<<<<
 * 
 *                 if norm_cols_X[ii] == 0.0:
 */
            /*else*/ {
              __pyx_v_ii = __pyx_v_f_iter;
            }
            __pyx_L15:;

            /* "sklearn/linear_model/cd_fast.pyx":241
 *                     ii = f_iter
 * 
 *                 if norm_cols_X[ii] == 0.0:             # <<<<<<<<<<<<<<
 *                     continue
 * 
 */
            __pyx_t_18 = __pyx_v_ii;
            __pyx_t_11 = (((*__Pyx_BufPtrStrided1d(double *, __pyx_pybuffernd_norm_cols_X.rcbuffer->pybuffer.buf, __pyx_t_18, __pyx_pybuffernd_norm_cols_X.diminfo[0].strides)) == 0.0) != 0);
            if (__pyx_t_11) {

              /* "sklearn/linear_model/cd_fast.pyx":242
 * 
 *                 if norm_cols_X[ii] == 0.0:
 *                     continue             # <<<<<<<<<<<<<<
 * 
 *                 w_ii = w[ii]  # Store previous value
 */
              goto __pyx_L13_continue;

              /* "sklearn/linear_model/cd_fast.pyx":241
 *                     ii = f_iter
 * 
 *                 if norm_cols_X[ii] == 0.0:             # <<<<<<<<<<<<<<
 *                     continue
 * 
 */
            }

            /* "sklearn/linear_model/cd_fast.pyx":244
 *                     continue
 * 
 *                 w_ii = w[ii]  # Store previous value             # <<<<<<<<<<<<<<
 * 
 *                 if w_ii != 0.0:
 */
            __pyx_t_19 = __pyx_v_ii;
            __pyx_v_w_ii = (*__Pyx_BufPtrStrided1d(double *, __pyx_pybuffernd_w.rcbuffer->pybuffer.buf, __pyx_t_19, __pyx_pybuffernd_w.diminfo[0].strides));

            /* "sklearn/linear_model/cd_fast.pyx":246
 *                 w_ii = w[ii]  # Store previous value
 * 
 *                 if w_ii != 0.0:             # <<<<<<<<<<<<<<
 *                     # R += w_ii * X[:,ii]
 *                     axpy(n_samples, w_ii, &X_data[ii * n_samples], 1,
 */
            __pyx_t_11 = ((__pyx_v_w_ii != 0.0) != 0);
            if (__pyx_t_11) {

              /* "sklearn/linear_model/cd_fast.pyx":248
 *                 if w_ii != 0.0:
 *                     # R += w_ii * X[:,ii]
 *                     axpy(n_samples, w_ii, &X_data[ii * n_samples], 1,             # <<<<<<<<<<<<<<
 *                          R_data, 1)
 * 
 */
              __pyx_v_axpy(__pyx_v_n_samples, __pyx_v_w_ii, (&(__pyx_v_X_data[(__pyx_v_ii * __pyx_v_n_samples)])), 1, __pyx_v_R_data, 1);

              /* "sklearn/linear_model/cd_fast.pyx":246
 *                 w_ii = w[ii]  # Store previous value
 * 
 *                 if w_ii != 0.0:             # <<<<<<<<<<<<<<
 *                     # R += w_ii * X[:,ii]
 *                     axpy(n_samples, w_ii, &X_data[ii * n_samples], 1,
 */
            }

            /* "sklearn/linear_model/cd_fast.pyx":252
 * 
 *                 # tmp = (X[:,ii]*R).sum()
 *                 tmp = dot(n_samples, &X_data[ii * n_samples], 1, R_data, 1)             # <<<<<<<<<<<<<<
 * 
 *                 if positive and tmp < 0:
 */
            __pyx_v_tmp = __pyx_v_dot(__pyx_v_n_samples, (&(__pyx_v_X_data[(__pyx_v_ii * __pyx_v_n_samples)])), 1, __pyx_v_R_data, 1);

            /* "sklearn/linear_model/cd_fast.pyx":254
 *                 tmp = dot(n_samples, &X_data[ii * n_samples], 1, R_data, 1)
 * 
 *                 if positive and tmp < 0:             # <<<<<<<<<<<<<<
 *                     w[ii] = 0.0
 *                 else:
 */
            __pyx_t_12 = (__pyx_v_positive != 0);
            if (__pyx_t_12) {
            } else {
              __pyx_t_11 = __pyx_t_12;
              goto __pyx_L19_bool_binop_done;
            }
            __pyx_t_12 = ((__pyx_v_tmp < 0.0) != 0);
            __pyx_t_11 = __pyx_t_12;
            __pyx_L19_bool_binop_done:;
            if (__pyx_t_11) {

              /* "sklearn/linear_model/cd_fast.pyx":255
 * 
 *                 if positive and tmp < 0:
 *                     w[ii] = 0.0             # <<<<<<<<<<<<<<
 *                 else:
 *                     w[ii] = (fsign(tmp) * fmax(fabs(tmp) - alpha, 0)
 */
              __pyx_t_20 = __pyx_v_ii;
              *__Pyx_BufPtrStrided1d(double *, __pyx_pybuffernd_w.rcbuffer->pybuffer.buf, __pyx_t_20, __pyx_pybuffernd_w.diminfo[0].strides) = 0.0;

              /* "sklearn/linear_model/cd_fast.pyx":254
 *                 tmp = dot(n_samples, &X_data[ii * n_samples], 1, R_data, 1)
 * 
 *                 if positive and tmp < 0:             # <<<<<<<<<<<<<<
 *                     w[ii] = 0.0
 *                 else:
 */
              goto __pyx_L18;
            }

            /* "sklearn/linear_model/cd_fast.pyx":258
 *                 else:
 *                     w[ii] = (fsign(tmp) * fmax(fabs(tmp) - alpha, 0)
 *                              / (norm_cols_X[ii] + beta))             # <<<<<<<<<<<<<<
 * 
 *                 if w[ii] != 0.0:
 */
            /*else*/ {

              /* "sklearn/linear_model/cd_fast.pyx":257
 *                     w[ii] = 0.0
 *                 else:
 *                     w[ii] = (fsign(tmp) * fmax(fabs(tmp) - alpha, 0)             # <<<<<<<<<<<<<<
 *                              / (norm_cols_X[ii] + beta))
 * 
 */
              __pyx_t_21 = __pyx_v_ii;

              /* "sklearn/linear_model/cd_fast.pyx":258
 *                 else:
 *                     w[ii] = (fsign(tmp) * fmax(fabs(tmp) - alpha, 0)
 *                              / (norm_cols_X[ii] + beta))             # <<<<<<<<<<<<<<
 * 
 *                 if w[ii] != 0.0:
 */
              __pyx_t_22 = __pyx_v_ii;
              *__Pyx_BufPtrStrided1d(double *, __pyx_pybuffernd_w.rcbuffer->pybuffer.buf, __pyx_t_22, __pyx_pybuffernd_w.diminfo[0].strides) = ((__pyx_fuse_1__pyx_f_7sklearn_12linear_model_7cd_fast_fsign(__pyx_v_tmp) * __pyx_fuse_1__pyx_f_7sklearn_12linear_model_7cd_fast_fmax((fabs(__pyx_v_tmp) - __pyx_v_alpha), 0.0)) / ((*__Pyx_BufPtrStrided1d(double *, __pyx_pybuffernd_norm_cols_X.rcbuffer->pybuffer.buf, __pyx_t_21, __pyx_pybuffernd_norm_cols_X.diminfo[0].strides)) + __pyx_v_beta));
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            __pyx_L18:;

            /* "sklearn/linear_model/cd_fast.pyx":260
 *                              / (norm_cols_X[ii] + beta))
 * 
 *                 if w[ii] != 0.0:             # <<<<<<<<<<<<<<
 *                     # R -=  w[ii] * X[:,ii] # Update residual
 *                     axpy(n_samples, -w[ii], &X_data[ii * n_samples], 1,
 */
            __pyx_t_23 = __pyx_v_ii;
            __pyx_t_11 = (((*__Pyx_BufPtrStrided1d(double *, __pyx_pybuffernd_w.rcbuffer->pybuffer.buf, __pyx_t_23, __pyx_pybuffernd_w.diminfo[0].strides)) != 0.0) != 0);
            if (__pyx_t_11) {

              /* "sklearn/linear_model/cd_fast.pyx":262
 *                 if w[ii] != 0.0:
 *                     # R -=  w[ii] * X[:,ii] # Update residual
 *                     axpy(n_samples, -w[ii], &X_data[ii * n_samples], 1,             # <<<<<<<<<<<<<<
 *                          R_data, 1)
 * 
 */
              __pyx_t_24 = __pyx_v_ii;

              /* "sklearn/linear_model/cd_fast.pyx":263
 *                     # R -=  w[ii] * X[:,ii] # Update residual
 *                     axpy(n_samples, -w[ii], &X_data[ii * n_samples], 1,
 *                          R_data, 1)             # <<<<<<<<<<<<<<
 * 
 *                 # update the maximum absolute coefficient update
 */
              __pyx_v_axpy(__pyx_v_n_samples, (-(*__Pyx_BufPtrStrided1d(double *, __pyx_pybuffernd_w.rcbuffer->pybuffer.buf, __pyx_t_24, __pyx_pybuffernd_w.diminfo[0].strides))), (&(__pyx_v_X_data[(__pyx_v_ii * __pyx_v_n_samples)])), 1, __pyx_v_R_data, 1);

              /* "sklearn/linear_model/cd_fast.pyx":260
 *                              / (norm_cols_X[ii] + beta))
 * 
 *                 if w[ii] != 0.0:             # <<<<<<<<<<<<<<
 *                     # R -=  w[ii] * X[:,ii] # Update residual
 *                     axpy(n_samples, -w[ii], &X_data[ii * n_samples], 1,
 */
            }

            /* "sklearn/linear_model/cd_fast.pyx":266
 * 
 *                 # update the maximum absolute coefficient update
 *                 d_w_ii = fabs(w[ii] - w_ii)             # <<<<<<<<<<<<<<
 *                 if d_w_ii > d_w_max:
 *                     d_w_max = d_w_ii
 */
            __pyx_t_25 = __pyx_v_ii;
            __pyx_v_d_w_ii = fabs(((*__Pyx_BufPtrStrided1d(double *, __pyx_pybuffernd_w.rcbuffer->pybuffer.buf, __pyx_t_25, __pyx_pybuffernd_w.diminfo[0].strides)) - __pyx_v_w_ii));

            /* "sklearn/linear_model/cd_fast.pyx":267
 *                 # update the maximum absolute coefficient update
 *                 d_w_ii = fabs(w[ii] - w_ii)
 *                 if d_w_ii > d_w_max:             # <<<<<<<<<<<<<<
 *                     d_w_max = d_w_ii
 * 
 */
            __pyx_t_11 = ((__pyx_v_d_w_ii > __pyx_v_d_w_max) != 0);
            if (__pyx_t_11) {

              /* "sklearn/linear_model/cd_fast.pyx":268
 *                 d_w_ii = fabs(w[ii] - w_ii)
 *                 if d_w_ii > d_w_max:
 *                     d_w_max = d_w_ii             # <<<<<<<<<<<<<<
 * 
 *                 if fabs(w[ii]) > w_max:
 */
              __pyx_v_d_w_max = __pyx_v_d_w_ii;

              /* "sklearn/linear_model/cd_fast.pyx":267
 *                 # update the maximum absolute coefficient update
 *                 d_w_ii = fabs(w[ii] - w_ii)
 *                 if d_w_ii > d_w_max:             # <<<<<<<<<<<<<<
 *                     d_w_max = d_w_ii
 * 
 */
            }

            /* "sklearn/linear_model/cd_fast.pyx":270
 *                     d_w_max = d_w_ii
 * 
 *                 if fabs(w[ii]) > w_max:             # <<<<<<<<<<<<<<
 *                     w_max = fabs(w[ii])
 * 
 */
            __pyx_t_26 = __pyx_v_ii;
            __pyx_t_11 = ((fabs((*__Pyx_BufPtrStrided1d(double *, __pyx_pybuffernd_w.rcbuffer->pybuffer.buf, __pyx_t_26, __pyx_pybuffernd_w.diminfo[0].strides))) > __pyx_v_w_max) != 0);
            if (__pyx_t_11) {

              /* "sklearn/linear_model/cd_fast.pyx":271
 * 
 *                 if fabs(w[ii]) > w_max:
 *                     w_max = fabs(w[ii])             # <<<<<<<<<<<<<<
 * 
 *             if (w_max == 0.0 or
 */
              __pyx_t_27 = __pyx_v_ii;
              __pyx_v_w_max = fabs((*__Pyx_BufPtrStrided1d(double *, __pyx_pybuffernd_w.rcbuffer->pybuffer.buf, __pyx_t_27, __pyx_pybuffernd_w.diminfo[0].strides)));

              /* "sklearn/linear_model/cd_fast.pyx":270
 *                     d_w_max = d_w_ii
 * 
 *                 if fabs(w[ii]) > w_max:             # <<<<<<<<<<<<<<
 *                     w_max = fabs(w[ii])
 * 
 */
            }
            __pyx_L13_continue:;
          }

          /* "sklearn/linear_model/cd_fast.pyx":273
 *                     w_max = fabs(w[ii])
 * 
 *             if (w_max == 0.0 or             # <<<<<<<<<<<<<<
 *                 d_w_max / w_max < d_w_tol or
 *                 n_iter == max_iter - 1):
 */
          __pyx_t_12 = ((__pyx_v_w_max == 0.0) != 0);
          if (!__pyx_t_12) {
          } else {
            __pyx_t_11 = __pyx_t_12;
            goto __pyx_L25_bool_binop_done;
          }

          /* "sklearn/linear_model/cd_fast.pyx":274
 * 
 *             if (w_max == 0.0 or
 *                 d_w_max / w_max < d_w_tol or             # <<<<<<<<<<<<<<
 *                 n_iter == max_iter - 1):
 *                 # the biggest coordinate update of this iteration was smaller
 */
          __pyx_t_12 = (((__pyx_v_d_w_max / __pyx_v_w_max) < __pyx_v_d_w_tol) != 0);
          if (!__pyx_t_12) {
          } else {
            __pyx_t_11 = __pyx_t_12;
            goto __pyx_L25_bool_binop_done;
          }

          /* "sklearn/linear_model/cd_fast.pyx":275
 *             if (w_max == 0.0 or
 *                 d_w_max / w_max < d_w_tol or
 *                 n_iter == max_iter - 1):             # <<<<<<<<<<<<<<
 *                 # the biggest coordinate update of this iteration was smaller
 *                 # than the tolerance: check the duality gap as ultimate
 */
          __pyx_t_12 = ((__pyx_v_n_iter == (__pyx_v_max_iter - 1)) != 0);
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            *((float *) ( /* dim=0 */ (__pyx_v_R.data + __pyx_t_22 * __pyx_v_R.strides[0]) )) -= ((*__Pyx_BufPtrCContig1d(float *, __pyx_pybuffernd_X_data.rcbuffer->pybuffer.buf, __pyx_t_20, __pyx_pybuffernd_X_data.diminfo[0].strides)) * __pyx_v_w_ii);
          }

          /* "sklearn/linear_model/cd_fast.pyx":414
 *                 normalize_sum += (X_data[jj] - X_mean_ii) ** 2
 *                 R[X_indices[jj]] -= X_data[jj] * w_ii
 *             norm_cols_X[ii] = normalize_sum + \             # <<<<<<<<<<<<<<
 *                 (n_samples - endptr + startptr) * X_mean_ii ** 2
 * 
 */
          __pyx_t_23 = __pyx_v_ii;
          *((float *) ( /* dim=0 */ (__pyx_v_norm_cols_X.data + __pyx_t_23 * __pyx_v_norm_cols_X.strides[0]) )) = (__pyx_v_normalize_sum + (((__pyx_v_n_samples - __pyx_v_endptr) + __pyx_v_startptr) * powf(__pyx_v_X_mean_ii, 2.0)));

          /* "sklearn/linear_model/cd_fast.pyx":417
 *                 (n_samples - endptr + startptr) * X_mean_ii ** 2
 * 
 *             if center:             # <<<<<<<<<<<<<<
 *                 for jj in range(n_samples):
 *                     R[jj] += X_mean_ii * w_ii
 */
          __pyx_t_13 = (__pyx_v_center != 0);
          if (__pyx_t_13) {

            /* "sklearn/linear_model/cd_fast.pyx":418
 * 
 *             if center:
 *                 for jj in range(n_samples):             # <<<<<<<<<<<<<<
 *                     R[jj] += X_mean_ii * w_ii
 *             startptr = endptr
 */
            __pyx_t_17 = __pyx_v_n_samples;
            for (__pyx_t_18 = 0; __pyx_t_18 < __pyx_t_17; __pyx_t_18+=1) {
              __pyx_v_jj = __pyx_t_18;

              /* "sklearn/linear_model/cd_fast.pyx":419
 *             if center:
 *                 for jj in range(n_samples):
 *                     R[jj] += X_mean_ii * w_ii             # <<<<<<<<<<<<<<
 *             startptr = endptr
 * 
 */
              __pyx_t_24 = __pyx_v_jj;
              *((float *) ( /* dim=0 */ (__pyx_v_R.data + __pyx_t_24 * __pyx_v_R.strides[0]) )) += (__pyx_v_X_mean_ii * __pyx_v_w_ii);
            }

            /* "sklearn/linear_model/cd_fast.pyx":417
 *                 (n_samples - endptr + startptr) * X_mean_ii ** 2
 * 
 *             if center:             # <<<<<<<<<<<<<<
 *                 for jj in range(n_samples):
 *                     R[jj] += X_mean_ii * w_ii
 */
          }

          /* "sklearn/linear_model/cd_fast.pyx":420
 *                 for jj in range(n_samples):
 *                     R[jj] += X_mean_ii * w_ii
 *             startptr = endptr             # <<<<<<<<<<<<<<
 * 
 *         # tol *= np.dot(y, y)
 */
          __pyx_v_startptr = __pyx_v_endptr;
        }

        /* "sklearn/linear_model/cd_fast.pyx":423
 * 
 *         # tol *= np.dot(y, y)
 *         tol *= dot(n_samples, &y[0], 1, &y[0], 1)             # <<<<<<<<<<<<<<
 * 
 *         for n_iter in range(max_iter):
 */
        __pyx_t_25 = 0;
        __pyx_t_26 = 0;
        __pyx_v_tol = (__pyx_v_tol * __pyx_v_dot(__pyx_v_n_samples, (&(*__Pyx_BufPtrStrided1d(float *, __pyx_pybuffernd_y.rcbuffer->pybuffer.buf, __pyx_t_25, __pyx_pybuffernd_y.diminfo[0].strides))), 1, (&(*__Pyx_BufPtrStrided1d(float *, __pyx_pybuffernd_y.rcbuffer->pybuffer.buf, __pyx_t_26, __pyx_pybuffernd_y.diminfo[0].strides))), 1));

        /* "sklearn/linear_model/cd_fast.pyx":425
 *         tol *= dot(n_samples, &y[0], 1, &y[0], 1)
 * 
 *         for n_iter in range(max_iter):             # <<<<<<<<<<<<<<
 * 
 *             w_max = 0.0
 */
        __pyx_t_7 = __pyx_v_max_iter;
        for (__pyx_t_10 = 0; __pyx_t_10 < __pyx_t_7; __pyx_t_10+=1) {
          __pyx_v_n_iter = __pyx_t_10;

          /* "sklearn/linear_model/cd_fast.pyx":427
 *         for n_iter in range(max_iter):
 * 
 *             w_max = 0.0             # <<<<<<<<<<<<<<
 *             d_w_max = 0.0
 * 
 */
          __pyx_v_w_max = 0.0;

          /* "sklearn/linear_model/cd_fast.pyx":428
 * 
 *             w_max = 0.0
 *             d_w_max = 0.0             # <<<<<<<<<<<<<<
 * 
 *             for f_iter in range(n_features):  # Loop over coordinates
 */
          __pyx_v_d_w_max = 0.0;

          /* "sklearn/linear_model/cd_fast.pyx":430
 *             d_w_max = 0.0
 * 
 *             for f_iter in range(n_features):  # Loop over coordinates             # <<<<<<<<<<<<<<
 *                 if random:
 *                     ii = rand_int(n_features, rand_r_state)
 */
          __pyx_t_11 = __pyx_v_n_features;
          for (__pyx_t_17 = 0; __pyx_t_17 < __pyx_t_11; __pyx_t_17+=1) {
            __pyx_v_f_iter = __pyx_t_17;

            /* "sklearn/linear_model/cd_fast.pyx":431
 * 
 *             for f_iter in range(n_features):  # Loop over coordinates
 *                 if random:             # <<<<<<<<<<<<<<
 *                     ii = rand_int(n_features, rand_r_state)
 *                 else:
 */
            __pyx_t_13 = (__pyx_v_random != 0);
            if (__pyx_t_13) {

              /* "sklearn/linear_model/cd_fast.pyx":432
 *             for f_iter in range(n_features):  # Loop over coordinates
 *                 if random:
 *                     ii = rand_int(n_features, rand_r_state)             # <<<<<<<<<<<<<<
 *                 else:
 *                     ii = f_iter
 */
              __pyx_v_ii = __pyx_f_7sklearn_12linear_model_7cd_fast_rand_int(__pyx_v_n_features, __pyx_v_rand_r_state);

              /* "sklearn/linear_model/cd_fast.pyx":431
 * 
 *             for f_iter in range(n_features):  # Loop over coordinates
 *                 if random:             # <<<<<<<<<<<<<<
 *                     ii = rand_int(n_features, rand_r_state)
 *                 else:
 */
              goto __pyx_L20;
            }

            /* "sklearn/linear_model/cd_fast.pyx":434
 *                     ii = rand_int(n_features, rand_r_state)
 *                 else:
 *                     ii = f_iter             # <<<<<<<<<<<<<<
 * 
 *                 if norm_cols_X[ii] == 0.0:
 */
            /*else*/ {
              __pyx_v_ii = __pyx_v_f_iter;
            }
            __pyx_L20:;

            /* "sklearn/linear_model/cd_fast.pyx":436
 *                     ii = f_iter
 * 
 *                 if norm_cols_X[ii] == 0.0:             # <<<<<<<<<<<<<<
 *                     continue
 * 
 */
            __pyx_t_27 = __pyx_v_ii;
            __pyx_t_13 = (((*((float *) ( /* dim=0 */ (__pyx_v_norm_cols_X.data + __pyx_t_27 * __pyx_v_norm_cols_X.strides[0]) ))) == 0.0) != 0);
            if (__pyx_t_13) {

              /* "sklearn/linear_model/cd_fast.pyx":437
 * 
 *                 if norm_cols_X[ii] == 0.0:
 *                     continue             # <<<<<<<<<<<<<<
 * 
 *                 startptr = X_indptr[ii]
 */
              goto __pyx_L18_continue;

              /* "sklearn/linear_model/cd_fast.pyx":436
 *                     ii = f_iter
 * 
 *                 if norm_cols_X[ii] == 0.0:             # <<<<<<<<<<<<<<
 *                     continue
 * 
 */
            }

            /* "sklearn/linear_model/cd_fast.pyx":439
 *                     continue
 * 
 *                 startptr = X_indptr[ii]             # <<<<<<<<<<<<<<
 *                 endptr = X_indptr[ii + 1]
 *                 w_ii = w[ii]  # Store previous value
 */
            __pyx_t_28 = __pyx_v_ii;
            __pyx_v_startptr = (*__Pyx_BufPtrCContig1d(int *, __pyx_pybuffernd_X_indptr.rcbuffer->pybuffer.buf, __pyx_t_28, __pyx_pybuffernd_X_indptr.diminfo[0].strides));

            /* "sklearn/linear_model/cd_fast.pyx":440
 * 
 *                 startptr = X_indptr[ii]
 *                 endptr = X_indptr[ii + 1]             # <<<<<<<<<<<<<<
 *                 w_ii = w[ii]  # Store previous value
 *                 X_mean_ii = X_mean[ii]
 */
            __pyx_t_29 = (__pyx_v_ii + 1);
            __pyx_v_endptr = (*__Pyx_BufPtrCContig1d(int *, __pyx_pybuffernd_X_indptr.rcbuffer->pybuffer.buf, __pyx_t_29, __pyx_pybuffernd_X_indptr.diminfo[0].strides));

            /* "sklearn/linear_model/cd_fast.pyx":441
 *                 startptr = X_indptr[ii]
 *                 endptr = X_indptr[ii + 1]
 *                 w_ii = w[ii]  # Store previous value             # <<<<<<<<<<<<<<
 *                 X_mean_ii = X_mean[ii]
 * 
 */
            __pyx_t_30 = __pyx_v_ii;
            __pyx_v_w_ii = (*((float *) ( /* dim=0 */ (__pyx_v_w.data + __pyx_t_30 * __pyx_v_w.strides[0]) )));

            /* "sklearn/linear_model/cd_fast.pyx":442
 *                 endptr = X_indptr[ii + 1]
 *                 w_ii = w[ii]  # Store previous value
 *                 X_mean_ii = X_mean[ii]             # <<<<<<<<<<<<<<
 * 
 *                 if w_ii != 0.0:
 */
            __pyx_t_31 = __pyx_v_ii;
            __pyx_v_X_mean_ii = (*((float *) ( /* dim=0 */ (__pyx_v_X_mean.data + __pyx_t_31 * __pyx_v_X_mean.strides[0]) )));

            /* "sklearn/linear_model/cd_fast.pyx":444
 *                 X_mean_ii = X_mean[ii]
 * 
 *                 if w_ii != 0.0:             # <<<<<<<<<<<<<<
 *                     # R += w_ii * X[:,ii]
 *                     for jj in range(startptr, endptr):
 */
            __pyx_t_13 = ((__pyx_v_w_ii != 0.0) != 0);
            if (__pyx_t_13) {

              /* "sklearn/linear_model/cd_fast.pyx":446
 *                 if w_ii != 0.0:
 *                     # R += w_ii * X[:,ii]
 *                     for jj in range(startptr, endptr):             # <<<<<<<<<<<<<<
 *                         R[X_indices[jj]] += X_data[jj] * w_ii
 *                     if center:
 */
              __pyx_t_18 = __pyx_v_endptr;
              for (__pyx_t_32 = __pyx_v_startptr; __pyx_t_32 < __pyx_t_18; __pyx_t_32+=1) {
                __pyx_v_jj = __pyx_t_32;

                /* "sklearn/linear_model/cd_fast.pyx":447
 *                     # R += w_ii * X[:,ii]
 *                     for jj in range(startptr, endptr):
 *                         R[X_indices[jj]] += X_data[jj] * w_ii             # <<<<<<<<<<<<<<
 *                     if center:
 *                         for jj in range(n_samples):
 */
                __pyx_t_33 = __pyx_v_jj;
                __pyx_t_34 = __pyx_v_jj;
                __pyx_t_35 = (*__Pyx_BufPtrCContig1d(int *, __pyx_pybuffernd_X_indices.rcbuffer->pybuffer.buf, __pyx_t_34, __pyx_pybuffernd_X_indices.diminfo[0].strides));
                *((float *) ( /* dim=0 */ (__pyx_v_R.data + __pyx_t_35 * __pyx_v_R.strides[0]) )) += ((*__Pyx_BufPtrCContig1d(float *, __pyx_pybuffernd_X_data.rcbuffer->pybuffer.buf, __pyx_t_33, __pyx_pybuffernd_X_data.diminfo[0].strides)) * __pyx_v_w_ii);
              }

              /* "sklearn/linear_model/cd_fast.pyx":448
 *                     for jj in range(startptr, endptr):
 *                         R[X_indices[jj]] += X_data[jj] * w_ii
 *                     if center:             # <<<<<<<<<<<<<<
 *                         for jj in range(n_samples):
 *                             R[jj] -= X_mean_ii * w_ii
 */
              __pyx_t_13 = (__pyx_v_center != 0);
              if (__pyx_t_13) {

                /* "sklearn/linear_model/cd_fast.pyx":449
 *                         R[X_indices[jj]] += X_data[jj] * w_ii
 *                     if center:
 *                         for jj in range(n_samples):             # <<<<<<<<<<<<<<
 *                             R[jj] -= X_mean_ii * w_ii
 * 
 */
                __pyx_t_18 = __pyx_v_n_samples;
                for (__pyx_t_32 = 0; __pyx_t_32 < __pyx_t_18; __pyx_t_32+=1) {
                  __pyx_v_jj = __pyx_t_32;

                  /* "sklearn/linear_model/cd_fast.pyx":450
 *                     if center:
 *                         for jj in range(n_samples):
 *                             R[jj] -= X_mean_ii * w_ii             # <<<<<<<<<<<<<<
 * 
 *                 # tmp = (X[:,ii] * R).sum()
 */
                  __pyx_t_36 = __pyx_v_jj;
                  *((float *) ( /* dim=0 */ (__pyx_v_R.data + __pyx_t_36 * __pyx_v_R.strides[0]) )) -= (__pyx_v_X_mean_ii * __pyx_v_w_ii);
                }

                /* "sklearn/linear_model/cd_fast.pyx":448
 *                     for jj in range(startptr, endptr):
 *                         R[X_indices[jj]] += X_data[jj] * w_ii
 *                     if center:             # <<<<<<<<<<<<<<
 *                         for jj in range(n_samples):
 *                             R[jj] -= X_mean_ii * w_ii
 */
              }

              /* "sklearn/linear_model/cd_fast.pyx":444
 *                 X_mean_ii = X_mean[ii]
 * 
 *                 if w_ii != 0.0:             # <<<<<<<<<<<<<<
 *                     # R += w_ii * X[:,ii]
 *                     for jj in range(startptr, endptr):
 */
            }

            /* "sklearn/linear_model/cd_fast.pyx":453
 * 
 *                 # tmp = (X[:,ii] * R).sum()
 *                 tmp = 0.0             # <<<<<<<<<<<<<<
 *                 for jj in range(startptr, endptr):
 *                     tmp += R[X_indices[jj]] * X_data[jj]
 */
            __pyx_v_tmp = 0.0;

            /* "sklearn/linear_model/cd_fast.pyx":454
 *                 # tmp = (X[:,ii] * R).sum()
 *                 tmp = 0.0
 *                 for jj in range(startptr, endptr):             # <<<<<<<<<<<<<<
 *                     tmp += R[X_indices[jj]] * X_data[jj]
 * 
 */
            __pyx_t_18 = __pyx_v_endptr;
            for (__pyx_t_32 = __pyx_v_startptr; __pyx_t_32 < __pyx_t_18; __pyx_t_32+=1) {
              __pyx_v_jj = __pyx_t_32;

              /* "sklearn/linear_model/cd_fast.pyx":455
 *                 tmp = 0.0
 *                 for jj in range(startptr, endptr):
 *                     tmp += R[X_indices[jj]] * X_data[jj]             # <<<<<<<<<<<<<<
 * 
 *                 if center:
 */
              __pyx_t_37 = __pyx_v_jj;
              __pyx_t_38 = (*__Pyx_BufPtrCContig1d(int *, __pyx_pybuffernd_X_indices.rcbuffer->pybuffer.buf, __pyx_t_37, __pyx_pybuffernd_X_indices.diminfo[0].strides));
              __pyx_t_39 = __pyx_v_jj;
              __pyx_v_tmp = (__pyx_v_tmp + ((*((float *) ( /* dim=0 */ (__pyx_v_R.data + __pyx_t_38 * __pyx_v_R.strides[0]) ))) * (*__Pyx_BufPtrCContig1d(float *, __pyx_pybuffernd_X_data.rcbuffer->pybuffer.buf, __pyx_t_39, __pyx_pybuffernd_X_data.diminfo[0].strides))));
            }

            /* "sklearn/linear_model/cd_fast.pyx":457
 *                     tmp += R[X_indices[jj]] * X_data[jj]
 * 
 *                 if center:             # <<<<<<<<<<<<<<
 *                     R_sum = 0.0
 *                     for jj in range(n_samples):
 */
            __pyx_t_13 = (__pyx_v_center != 0);
            if (__pyx_t_13) {

              /* "sklearn/linear_model/cd_fast.pyx":458
 * 
 *                 if center:
 *                     R_sum = 0.0             # <<<<<<<<<<<<<<
 *                     for jj in range(n_samples):
 *                         R_sum += R[jj]
 */
              __pyx_v_R_sum = 0.0;

              /* "sklearn/linear_model/cd_fast.pyx":459
 *                 if center:
 *                     R_sum = 0.0
 *                     for jj in range(n_samples):             # <<<<<<<<<<<<<<
 *                         R_sum += R[jj]
 *                     tmp -= R_sum * X_mean_ii
 */
              __pyx_t_18 = __pyx_v_n_samples;
              for (__pyx_t_32 = 0; __pyx_t_32 < __pyx_t_18; __pyx_t_32+=1) {
                __pyx_v_jj = __pyx_t_32;

                /* "sklearn/linear_model/cd_fast.pyx":460
 *                     R_sum = 0.0
 *                     for jj in range(n_samples):
 *                         R_sum += R[jj]             # <<<<<<<<<<<<<<
 *                     tmp -= R_sum * X_mean_ii
 * 
 */
                __pyx_t_40 = __pyx_v_jj;
                __pyx_v_R_sum = (__pyx_v_R_sum + (*((float *) ( /* dim=0 */ (__pyx_v_R.data + __pyx_t_40 * __pyx_v_R.strides[0]) ))));
              }

              /* "sklearn/linear_model/cd_fast.pyx":461
 *                     for jj in range(n_samples):
 *                         R_sum += R[jj]
 *                     tmp -= R_sum * X_mean_ii             # <<<<<<<<<<<<<<
 * 
 *                 if positive and tmp < 0.0:
 */
              __pyx_v_tmp = (__pyx_v_tmp - (__pyx_v_R_sum * __pyx_v_X_mean_ii));

              /* "sklearn/linear_model/cd_fast.pyx":457
 *                     tmp += R[X_indices[jj]] * X_data[jj]
 * 
 *                 if center:             # <<<<<<<<<<<<<<
 *                     R_sum = 0.0
 *                     for jj in range(n_samples):
 */
            }

            /* "sklearn/linear_model/cd_fast.pyx":463
 *                     tmp -= R_sum * X_mean_ii
 * 
 *                 if positive and tmp < 0.0:             # <<<<<<<<<<<<<<
 *                     w[ii] = 0.0
 *                 else:
 */
            __pyx_t_41 = (__pyx_v_positive != 0);
            if (__pyx_t_41) {
            } else {
              __pyx_t_13 = __pyx_t_41;
              goto __pyx_L34_bool_binop_done;
            }
            __pyx_t_41 = ((__pyx_v_tmp < 0.0) != 0);
            __pyx_t_13 = __pyx_t_41;
            __pyx_L34_bool_binop_done:;
            if (__pyx_t_13) {

              /* "sklearn/linear_model/cd_fast.pyx":464
 * 
 *                 if positive and tmp < 0.0:
 *                     w[ii] = 0.0             # <<<<<<<<<<<<<<
 *                 else:
 *                     w[ii] = fsign(tmp) * fmax(fabs(tmp) - alpha, 0) \
 */
              __pyx_t_42 = __pyx_v_ii;
              *((float *) ( /* dim=0 */ (__pyx_v_w.data + __pyx_t_42 * __pyx_v_w.strides[0]) )) = 0.0;

              /* "sklearn/linear_model/cd_fast.pyx":463
 *                     tmp -= R_sum * X_mean_ii
 * 
 *                 if positive and tmp < 0.0:             # <<<<<<<<<<<<<<
 *                     w[ii] = 0.0
 *                 else:
 */
              goto __pyx_L33;
            }

            /* "sklearn/linear_model/cd_fast.pyx":467
 *                 else:
 *                     w[ii] = fsign(tmp) * fmax(fabs(tmp) - alpha, 0) \
 *                             / (norm_cols_X[ii] + beta)             # <<<<<<<<<<<<<<
 * 
 *                 if w[ii] != 0.0:
 */
            /*else*/ {

              /* "sklearn/linear_model/cd_fast.pyx":466
 *                     w[ii] = 0.0
 *                 else:
 *                     w[ii] = fsign(tmp) * fmax(fabs(tmp) - alpha, 0) \             # <<<<<<<<<<<<<<
 *                             / (norm_cols_X[ii] + beta)
 * 
 */
              __pyx_t_43 = __pyx_v_ii;

              /* "sklearn/linear_model/cd_fast.pyx":467
 *                 else:
 *                     w[ii] = fsign(tmp) * fmax(fabs(tmp) - alpha, 0) \
 *                             / (norm_cols_X[ii] + beta)             # <<<<<<<<<<<<<<
 * 
 *                 if w[ii] != 0.0:
 */
              __pyx_t_44 = __pyx_v_ii;
              *((float *) ( /* dim=0 */ (__pyx_v_w.data + __pyx_t_44 * __pyx_v_w.strides[0]) )) = ((__pyx_fuse_0__pyx_f_7sklearn_12linear_model_7cd_fast_fsign(__pyx_v_tmp) * __pyx_fuse_1__pyx_f_7sklearn_12linear_model_7cd_fast_fmax((fabs(__pyx_v_tmp) - __pyx_v_alpha), 0.0)) / ((*((float *) ( /* dim=0 */ (__pyx_v_norm_cols_X.data + __pyx_t_43 * __pyx_v_norm_cols_X.strides[0]) ))) + __pyx_v_beta));
            }
            __pyx_L33:;

            /* "sklearn/linear_model/cd_fast.pyx":469
 *                             / (norm_cols_X[ii] + beta)
 * 
 *                 if w[ii] != 0.0:             # <<<<<<<<<<<<<<
 *                     # R -=  w[ii] * X[:,ii] # Update residual
 *                     for jj in range(startptr, endptr):
 */
            __pyx_t_45 = __pyx_v_ii;
            __pyx_t_13 = (((*((float *) ( /* dim=0 */ (__pyx_v_w.data + __pyx_t_45 * __pyx_v_w.strides[0]) ))) != 0.0) != 0);
            if (__pyx_t_13) {

              /* "sklearn/linear_model/cd_fast.pyx":471
 *                 if w[ii] != 0.0:
 *                     # R -=  w[ii] * X[:,ii] # Update residual
 *                     for jj in range(startptr, endptr):             # <<<<<<<<<<<<<<
 *                         R[X_indices[jj]] -= X_data[jj] * w[ii]
 * 
 */
              __pyx_t_18 = __pyx_v_endptr;
              for (__pyx_t_32 = __pyx_v_startptr; __pyx_t_32 < __pyx_t_18; __pyx_t_32+=1) {
                __pyx_v_jj = __pyx_t_32;

                /* "sklearn/linear_model/cd_fast.pyx":472
 *                     # R -=  w[ii] * X[:,ii] # Update residual
 *                     for jj in range(startptr, endptr):
 *                         R[X_indices[jj]] -= X_data[jj] * w[ii]             # <<<<<<<<<<<<<<
 * 
 *                     if center:
 */
                __pyx_t_46 = __pyx_v_jj;
                __pyx_t_47 = __pyx_v_ii;
                __pyx_t_48 = __pyx_v_jj;
                __pyx_t_49 = (*__Pyx_BufPtrCContig1d(int *, __pyx_pybuffernd_X_indices.rcbuffer->pybuffer.buf, __pyx_t_48, __pyx_pybuffernd_X_indices.diminfo[0].strides));
                *((float *) ( /* dim=0 */ (__pyx_v_R.data + __pyx_t_49 * __pyx_v_R.strides[0]) )) -= ((*__Pyx_BufPtrCContig1d(float *, __pyx_pybuffernd_X_data.rcbuffer->pybuffer.buf, __pyx_t_46, __pyx_pybuffernd_X_data.diminfo[0].strides)) * (*((float *) ( /* dim=0 */ (__pyx_v_w.data + __pyx_t_47 * __pyx_v_w.strides[0]) ))));
              }

              /* "sklearn/linear_model/cd_fast.pyx":474
 *                         R[X_indices[jj]] -= X_data[jj] * w[ii]
 * 
 *                     if center:             # <<<<<<<<<<<<<<
 *                         for jj in range(n_samples):
 *                             R[jj] += X_mean_ii * w[ii]
 */
              __pyx_t_13 = (__pyx_v_center != 0);
              if (__pyx_t_13) {

                /* "sklearn/linear_model/cd_fast.pyx":475
 * 
 *                     if center:
 *                         for jj in range(n_samples):             # <<<<<<<<<<<<<<
 *                             R[jj] += X_mean_ii * w[ii]
 * 
 */
                __pyx_t_18 = __pyx_v_n_samples;
                for (__pyx_t_32 = 0; __pyx_t_32 < __pyx_t_18; __pyx_t_32+=1) {
                  __pyx_v_jj = __pyx_t_32;

                  /* "sklearn/linear_model/cd_fast.pyx":476
 *                     if center:
 *                         for jj in range(n_samples):
 *                             R[jj] += X_mean_ii * w[ii]             # <<<<<<<<<<<<<<
 * 
 *                 # update the maximum absolute coefficient update
 */
                  __pyx_t_50 = __pyx_v_ii;
                  __pyx_t_51 = __pyx_v_jj;
                  *((float *) ( /* dim=0 */ (__pyx_v_R.data + __pyx_t_51 * __pyx_v_R.strides[0]) )) += (__pyx_v_X_mean_ii * (*((float *) ( /* dim=0 */ (__pyx_v_w.data + __pyx_t_50 * __pyx_v_w.strides[0]) ))));
                }

                /* "sklearn/linear_model/cd_fast.pyx":474
 *                         R[X_indices[jj]] -= X_data[jj] * w[ii]
 * 
 *                     if center:             # <<<<<<<<<<<<<<
 *                         for jj in range(n_samples):
 *                             R[jj] += X_mean_ii * w[ii]
 */
              }

              /* "sklearn/linear_model/cd_fast.pyx":469
 *                             / (norm_cols_X[ii] + beta)
 * 
 *                 if w[ii] != 0.0:             # <<<<<<<<<<<<<<
 *                     # R -=  w[ii] * X[:,ii] # Update residual
 *                     for jj in range(startptr, endptr):
 */
            }

            /* "sklearn/linear_model/cd_fast.pyx":479
 * 
 *                 # update the maximum absolute coefficient update
 *                 d_w_ii = fabs(w[ii] - w_ii)             # <<<<<<<<<<<<<<
 *                 if d_w_ii > d_w_max:
 *                     d_w_max = d_w_ii
 */
            __pyx_t_52 = __pyx_v_ii;
            __pyx_v_d_w_ii = fabs(((*((float *) ( /* dim=0 */ (__pyx_v_w.data + __pyx_t_52 * __pyx_v_w.strides[0]) ))) - __pyx_v_w_ii));

            /* "sklearn/linear_model/cd_fast.pyx":480
 *                 # update the maximum absolute coefficient update
 *                 d_w_ii = fabs(w[ii] - w_ii)
 *                 if d_w_ii > d_w_max:             # <<<<<<<<<<<<<<
 *                     d_w_max = d_w_ii
 * 
 */
            __pyx_t_13 = ((__pyx_v_d_w_ii > __pyx_v_d_w_max) != 0);
            if (__pyx_t_13) {

              /* "sklearn/linear_model/cd_fast.pyx":481
 *                 d_w_ii = fabs(w[ii] - w_ii)
 *                 if d_w_ii > d_w_max:
 *                     d_w_max = d_w_ii             # <<<<<<<<<<<<<<
 * 
 *                 if w[ii] > w_max:
 */
              __pyx_v_d_w_max = __pyx_v_d_w_ii;

              /* "sklearn/linear_model/cd_fast.pyx":480
 *                 # update the maximum absolute coefficient update
 *                 d_w_ii = fabs(w[ii] - w_ii)
 *                 if d_w_ii > d_w_max:             # <<<<<<<<<<<<<<
 *                     d_w_max = d_w_ii
 * 
 */
            }

            /* "sklearn/linear_model/cd_fast.pyx":483
 *                     d_w_max = d_w_ii
 * 
 *                 if w[ii] > w_max:             # <<<<<<<<<<<<<<
 *                     w_max = w[ii]
 *             if w_max == 0.0 or d_w_max / w_max < d_w_tol or n_iter == max_iter - 1:
 */
            __pyx_t_53 = __pyx_v_ii;
            __pyx_t_13 = (((*((float *) ( /* dim=0 */ (__pyx_v_w.data + __pyx_t_53 * __pyx_v_w.strides[0]) ))) > __pyx_v_w_max) != 0);
            if (__pyx_t_13) {

              /* "sklearn/linear_model/cd_fast.pyx":484
 * 
 *                 if w[ii] > w_max:
 *                     w_max = w[ii]             # <<<<<<<<<<<<<<
 *             if w_max == 0.0 or d_w_max / w_max < d_w_tol or n_iter == max_iter - 1:
 *                 # the biggest coordinate update of this iteration was smaller than
 */
              __pyx_t_54 = __pyx_v_ii;
              __pyx_v_w_max = (*((float *) ( /* dim=0 */ (__pyx_v_w.data + __pyx_t_54 * __pyx_v_w.strides[0]) )));

              /* "sklearn/linear_model/cd_fast.pyx":483
 *                     d_w_max = d_w_ii
 * 
 *                 if w[ii] > w_max:             # <<<<<<<<<<<<<<
 *                     w_max = w[ii]
 *             if w_max == 0.0 or d_w_max / w_max < d_w_tol or n_iter == max_iter - 1:
 */
            }
            __pyx_L18_continue:;
          }

          /* "sklearn/linear_model/cd_fast.pyx":485
 *                 if w[ii] > w_max:
 *                     w_max = w[ii]
 *             if w_max == 0.0 or d_w_max / w_max < d_w_tol or n_iter == max_iter - 1:             # <<<<<<<<<<<<<<
 *                 # the biggest coordinate update of this iteration was smaller than
 *                 # the tolerance: check the duality gap as ultimate stopping
 */
          __pyx_t_41 = ((__pyx_v_w_max == 0.0) != 0);
          if (!__pyx_t_41) {
          } else {
            __pyx_t_13 = __pyx_t_41;
            goto __pyx_L45_bool_binop_done;
          }
          __pyx_t_41 = (((__pyx_v_d_w_max / __pyx_v_w_max) < __pyx_v_d_w_tol) != 0);
          if (!__pyx_t_41) {
          } else {
            __pyx_t_13 = __pyx_t_41;
            goto __pyx_L45_bool_binop_done;
          }
          __pyx_t_41 = ((__pyx_v_n_iter == (__pyx_v_max_iter - 1)) != 0);
          __pyx_t_13 = __pyx_t_41;
          __pyx_L45_bool_binop_done:;
          if (__pyx_t_13) {

            /* "sklearn/linear_model/cd_fast.pyx":491
 * 
 *                 # sparse X.T / dense R dot product
 *                 if center:             # <<<<<<<<<<<<<<
 *                     R_sum = 0.0
 *                     for jj in range(n_samples):
 */
            __pyx_t_13 = (__pyx_v_center != 0);
            if (__pyx_t_13) {

              /* "sklearn/linear_model/cd_fast.pyx":492
 *                 # sparse X.T / dense R dot product
 *                 if center:
 *                     R_sum = 0.0             # <<<<<<<<<<<<<<
 *                     for jj in range(n_samples):
 *                         R_sum += R[jj]
 */
              __pyx_v_R_sum = 0.0;

              /* "sklearn/linear_model/cd_fast.pyx":493
 *                 if center:
 *                     R_sum = 0.0
 *                     for jj in range(n_samples):             # <<<<<<<<<<<<<<
 *                         R_sum += R[jj]
 * 
 */
              __pyx_t_11 = __pyx_v_n_samples;
              for (__pyx_t_17 = 0; __pyx_t_17 < __pyx_t_11; __pyx_t_17+=1) {
                __pyx_v_jj = __pyx_t_17;

                /* "sklearn/linear_model/cd_fast.pyx":494
 *                     R_sum = 0.0
 *                     for jj in range(n_samples):
 *                         R_sum += R[jj]             # <<<<<<<<<<<<<<
 * 
 *                 for ii in range(n_features):
 */
                __pyx_t_55 = __pyx_v_jj;
                __pyx_v_R_sum = (__pyx_v_R_sum + (*((float *) ( /* dim=0 */ (__pyx_v_R.data + __pyx_t_55 * __pyx_v_R.strides[0]) ))));
              }

              /* "sklearn/linear_model/cd_fast.pyx":491
 * 
 *                 # sparse X.T / dense R dot product
 *                 if center:             # <<<<<<<<<<<<<<
 *                     R_sum = 0.0
 *                     for jj in range(n_samples):
 */
            }

            /* "sklearn/linear_model/cd_fast.pyx":496
 *                         R_sum += R[jj]
 * 
 *                 for ii in range(n_features):             # <<<<<<<<<<<<<<
 *                     X_T_R[ii] = 0.0
 *                     for jj in range(X_indptr[ii], X_indptr[ii + 1]):
 */
            __pyx_t_11 = __pyx_v_n_features;
            for (__pyx_t_17 = 0; __pyx_t_17 < __pyx_t_11; __pyx_t_17+=1) {
              __pyx_v_ii = __pyx_t_17;

              /* "sklearn/linear_model/cd_fast.pyx":497
 * 
 *                 for ii in range(n_features):
 *                     X_T_R[ii] = 0.0             # <<<<<<<<<<<<<<
 *                     for jj in range(X_indptr[ii], X_indptr[ii + 1]):
 *                         X_T_R[ii] += X_data[jj] * R[X_indices[jj]]
 */
              __pyx_t_56 = __pyx_v_ii;
              *((float *) ( /* dim=0 */ (__pyx_v_X_T_R.data + __pyx_t_56 * __pyx_v_X_T_R.strides[0]) )) = 0.0;

              /* "sklearn/linear_model/cd_fast.pyx":498
 *                 for ii in range(n_features):
 *                     X_T_R[ii] = 0.0
 *                     for jj in range(X_indptr[ii], X_indptr[ii + 1]):             # <<<<<<<<<<<<<<
 *                         X_T_R[ii] += X_data[jj] * R[X_indices[jj]]
 * 
 */
              __pyx_t_57 = (__pyx_v_ii + 1);
              __pyx_t_58 = (*__Pyx_BufPtrCContig1d(int *, __pyx_pybuffernd_X_indptr.rcbuffer->pybuffer.buf, __pyx_t_57, __pyx_pybuffernd_X_indptr.diminfo[0].strides));
              __pyx_t_59 = __pyx_v_ii;
              for (__pyx_t_18 = (*__Pyx_BufPtrCContig1d(int *, __pyx_pybuffernd_X_indptr.rcbuffer->pybuffer.buf, __pyx_t_59, __pyx_pybuffernd_X_indptr.diminfo[0].strides)); __pyx_t_18 < __pyx_t_58; __pyx_t_18+=1) {
                __pyx_v_jj = __pyx_t_18;

                /* "sklearn/linear_model/cd_fast.pyx":499
 *                     X_T_R[ii] = 0.0
 *                     for jj in range(X_indptr[ii], X_indptr[ii + 1]):
 *                         X_T_R[ii] += X_data[jj] * R[X_indices[jj]]             # <<<<<<<<<<<<<<
 * 
 *                     if center:
 */
                __pyx_t_60 = __pyx_v_jj;
                __pyx_t_61 = __pyx_v_jj;
                __pyx_t_62 = (*__Pyx_BufPtrCContig1d(int *, __pyx_pybuffernd_X_indices.rcbuffer->pybuffer.buf, __pyx_t_61, __pyx_pybuffernd_X_indices.diminfo[0].strides));
                __pyx_t_63 = __pyx_v_ii;
                *((float *) ( /* dim=0 */ (__pyx_v_X_T_R.data + __pyx_t_63 * __pyx_v_X_T_R.strides[0]) )) += ((*__Pyx_BufPtrCContig1d(float *, __pyx_pybuffernd_X_data.rcbuffer->pybuffer.buf, __pyx_t_60, __pyx_pybuffernd_X_data.diminfo[0].strides)) * (*((float *) ( /* dim=0 */ (__pyx_v_R.data + __pyx_t_62 * __pyx_v_R.strides[0]) ))));
              }

              /* "sklearn/linear_model/cd_fast.pyx":501
 *                         X_T_R[ii] += X_data[jj] * R[X_indices[jj]]
 * 
 *                     if center:             # <<<<<<<<<<<<<<
 *                         X_T_R[ii] -= X_mean[ii] * R_sum
 *                     XtA[ii] = X_T_R[ii] - beta * w[ii]
 */
              __pyx_t_13 = (__pyx_v_center != 0);
              if (__pyx_t_13) {

                /* "sklearn/linear_model/cd_fast.pyx":502
 * 
 *                     if center:
 *                         X_T_R[ii] -= X_mean[ii] * R_sum             # <<<<<<<<<<<<<<
 *                     XtA[ii] = X_T_R[ii] - beta * w[ii]
 * 
 */
                __pyx_t_64 = __pyx_v_ii;
                __pyx_t_65 = __pyx_v_ii;
                *((float *) ( /* dim=0 */ (__pyx_v_X_T_R.data + __pyx_t_65 * __pyx_v_X_T_R.strides[0]) )) -= ((*((float *) ( /* dim=0 */ (__pyx_v_X_mean.data + __pyx_t_64 * __pyx_v_X_mean.strides[0]) ))) * __pyx_v_R_sum);

                /* "sklearn/linear_model/cd_fast.pyx":501
 *                         X_T_R[ii] += X_data[jj] * R[X_indices[jj]]
 * 
 *                     if center:             # <<<<<<<<<<<<<<
 *                         X_T_R[ii] -= X_mean[ii] * R_sum
 *                     XtA[ii] = X_T_R[ii] - beta * w[ii]
 */
              }

              /* "sklearn/linear_model/cd_fast.pyx":503
 *                     if center:
 *                         X_T_R[ii] -= X_mean[ii] * R_sum
 *                     XtA[ii] = X_T_R[ii] - beta * w[ii]             # <<<<<<<<<<<<<<
 * 
 *                 if positive:
 */
              __pyx_t_66 = __pyx_v_ii;
              __pyx_t_67 = __pyx_v_ii;
              __pyx_t_68 = __pyx_v_ii;
              *((float *) ( /* dim=0 */ (__pyx_v_XtA.data + __pyx_t_68 * __pyx_v_XtA.strides[0]) )) = ((*((float *) ( /* dim=0 */ (__pyx_v_X_T_R.data + __pyx_t_66 * __pyx_v_X_T_R.strides[0]) ))) - (__pyx_v_beta * (*((float *) ( /* dim=0 */ (__pyx_v_w.data + __pyx_t_67 * __pyx_v_w.strides[0]) )))));
            }

            /* "sklearn/linear_model/cd_fast.pyx":505
 *                     XtA[ii] = X_T_R[ii] - beta * w[ii]
 * 
 *                 if positive:             # <<<<<<<<<<<<<<
 *                     dual_norm_XtA = max(n_features, &XtA[0])
 *                 else:
 */
            __pyx_t_13 = (__pyx_v_positive != 0);
            if (__pyx_t_13) {

              /* "sklearn/linear_model/cd_fast.pyx":506
 * 
 *                 if positive:
 *                     dual_norm_XtA = max(n_features, &XtA[0])             # <<<<<<<<<<<<<<
 *                 else:
 *                     dual_norm_XtA = abs_max(n_features, &XtA[0])
 */
              __pyx_t_69 = 0;
              __pyx_v_dual_norm_XtA = __pyx_fuse_0__pyx_f_7sklearn_12linear_model_7cd_fast_max(__pyx_v_n_features, (&(*((float *) ( /* dim=0 */ (__pyx_v_XtA.data + __pyx_t_69 * __pyx_v_XtA.strides[0]) )))));

              /* "sklearn/linear_model/cd_fast.pyx":505
 *                     XtA[ii] = X_T_R[ii] - beta * w[ii]
 * 
 *                 if positive:             # <<<<<<<<<<<<<<
 *                     dual_norm_XtA = max(n_features, &XtA[0])
 *                 else:
 */
              goto __pyx_L56;
            }

            /* "sklearn/linear_model/cd_fast.pyx":508
 *                     dual_norm_XtA = max(n_features, &XtA[0])
 *                 else:
 *                     dual_norm_XtA = abs_max(n_features, &XtA[0])             # <<<<<<<<<<<<<<
 * 
 *                 # R_norm2 = np.dot(R, R)
 */
            /*else*/ {
              __pyx_t_70 = 0;
              __pyx_v_dual_norm_XtA = __pyx_fuse_0__pyx_f_7sklearn_12linear_model_7cd_fast_abs_max(__pyx_v_n_features, (&(*((float *) ( /* dim=0 */ (__pyx_v_XtA.data + __pyx_t_70 * __pyx_v_XtA.strides[0]) )))));
            }
            __pyx_L56:;

            /* "sklearn/linear_model/cd_fast.pyx":511
 * 
 *                 # R_norm2 = np.dot(R, R)
 *                 R_norm2 = dot(n_samples, &R[0], 1, &R[0], 1)             # <<<<<<<<<<<<<<
 * 
 *                 # w_norm2 = np.dot(w, w)
 */
            __pyx_t_71 = 0;
            __pyx_t_72 = 0;
            __pyx_v_R_norm2 = __pyx_v_dot(__pyx_v_n_samples, (&(*((float *) ( /* dim=0 */ (__pyx_v_R.data + __pyx_t_71 * __pyx_v_R.strides[0]) )))), 1, (&(*((float *) ( /* dim=0 */ (__pyx_v_R.data + __pyx_t_72 * __pyx_v_R.strides[0]) )))), 1);

            /* "sklearn/linear_model/cd_fast.pyx":514
 * 
 *                 # w_norm2 = np.dot(w, w)
 *                 w_norm2 = dot(n_features, &w[0], 1, &w[0], 1)             # <<<<<<<<<<<<<<
 *                 if (dual_norm_XtA > alpha):
 *                     const = alpha / dual_norm_XtA
 */
            __pyx_t_73 = 0;
            __pyx_t_74 = 0;
            __pyx_v_w_norm2 = __pyx_v_dot(__pyx_v_n_features, (&(*((float *) ( /* dim=0 */ (__pyx_v_w.data + __pyx_t_73 * __pyx_v_w.strides[0]) )))), 1, (&(*((float *) ( /* dim=0 */ (__pyx_v_w.data + __pyx_t_74 * __pyx_v_w.strides[0]) )))), 1);

            /* "sklearn/linear_model/cd_fast.pyx":515
 *                 # w_norm2 = np.dot(w, w)
 *                 w_norm2 = dot(n_features, &w[0], 1, &w[0], 1)
 *                 if (dual_norm_XtA > alpha):             # <<<<<<<<<<<<<<
 *                     const = alpha / dual_norm_XtA
 *                     A_norm2 = R_norm2 * const**2
 */
            __pyx_t_13 = ((__pyx_v_dual_norm_XtA > __pyx_v_alpha) != 0);
            if (__pyx_t_13) {

              /* "sklearn/linear_model/cd_fast.pyx":516
 *                 w_norm2 = dot(n_features, &w[0], 1, &w[0], 1)
 *                 if (dual_norm_XtA > alpha):
 *                     const = alpha / dual_norm_XtA             # <<<<<<<<<<<<<<
 *                     A_norm2 = R_norm2 * const**2
 *                     gap = 0.5 * (R_norm2 + A_norm2)
 */
              __pyx_v_const = (__pyx_v_alpha / __pyx_v_dual_norm_XtA);

              /* "sklearn/linear_model/cd_fast.pyx":517
 *                 if (dual_norm_XtA > alpha):
 *                     const = alpha / dual_norm_XtA
 *                     A_norm2 = R_norm2 * const**2             # <<<<<<<<<<<<<<
 *                     gap = 0.5 * (R_norm2 + A_norm2)
 *                 else:
 */
              __pyx_v_A_norm2 = (__pyx_v_R_norm2 * pow(__pyx_v_const, 2.0));

              /* "sklearn/linear_model/cd_fast.pyx":518
 *                     const = alpha / dual_norm_XtA
 *                     A_norm2 = R_norm2 * const**2
 *                     gap = 0.5 * (R_norm2 + A_norm2)             # <<<<<<<<<<<<<<
 *                 else:
 *                     const = 1.0
 */
              __pyx_v_gap = (0.5 * (__pyx_v_R_norm2 + __pyx_v_A_norm2));

              /* "sklearn/linear_model/cd_fast.pyx":515
 *                 # w_norm2 = np.dot(w, w)
 *                 w_norm2 = dot(n_features, &w[0], 1, &w[0], 1)
 *                 if (dual_norm_XtA > alpha):             # <<<<<<<<<<<<<<
 *                     const = alpha / dual_norm_XtA
 *                     A_norm2 = R_norm2 * const**2
 */
              goto __pyx_L57;
            }

            /* "sklearn/linear_model/cd_fast.pyx":520
 *                     gap = 0.5 * (R_norm2 + A_norm2)
 *                 else:
 *                     const = 1.0             # <<<<<<<<<<<<<<
 *                     gap = R_norm2
 * 
 */
            /*else*/ {
              __pyx_v_const = 1.0;

              /* "sklearn/linear_model/cd_fast.pyx":521
 *                 else:
 *                     const = 1.0
 *                     gap = R_norm2             # <<<<<<<<<<<<<<
 * 
 *                 l1_norm = asum(n_features, &w[0], 1)
 */
              __pyx_v_gap = __pyx_v_R_norm2;
            }
            __pyx_L57:;

            /* "sklearn/linear_model/cd_fast.pyx":523
 *                     gap = R_norm2
 * 
 *                 l1_norm = asum(n_features, &w[0], 1)             # <<<<<<<<<<<<<<
 * 
 *                 gap += (alpha * l1_norm - const * dot(
 */
            __pyx_t_75 = 0;
            __pyx_v_l1_norm = __pyx_v_asum(__pyx_v_n_features, (&(*((float *) ( /* dim=0 */ (__pyx_v_w.data + __pyx_t_75 * __pyx_v_w.strides[0]) )))), 1);

            /* "sklearn/linear_model/cd_fast.pyx":527
 *                 gap += (alpha * l1_norm - const * dot(
 *                             n_samples,
 *                             &R[0], 1,             # <<<<<<<<<<<<<<
 *                             &y[0], n_tasks
 *                             )
 */
            __pyx_t_76 = 0;

            /* "sklearn/linear_model/cd_fast.pyx":528
 *                             n_samples,
 *                             &R[0], 1,
 *                             &y[0], n_tasks             # <<<<<<<<<<<<<<
 *                             )
 *                         + 0.5 * beta * (1 + const ** 2) * w_norm2)
 */
            __pyx_t_77 = 0;

            /* "sklearn/linear_model/cd_fast.pyx":525
 *                 l1_norm = asum(n_features, &w[0], 1)
 * 
 *                 gap += (alpha * l1_norm - const * dot(             # <<<<<<<<<<<<<<
 *                             n_samples,
 *                             &R[0], 1,
 */
            __pyx_v_gap = (__pyx_v_gap + (((__pyx_v_alpha * __pyx_v_l1_norm) - (__pyx_v_const * __pyx_v_dot(__pyx_v_n_samples, (&(*((float *) ( /* dim=0 */ (__pyx_v_R.data + __pyx_t_76 * __pyx_v_R.strides[0]) )))), 1, (&(*__Pyx_BufPtrStrided1d(float *, __pyx_pybuffernd_y.rcbuffer->pybuffer.buf, __pyx_t_77, __pyx_pybuffernd_y.diminfo[0].strides))), __pyx_v_n_tasks))) + (((0.5 * __pyx_v_beta) * (1.0 + pow(__pyx_v_const, 2.0))) * __pyx_v_w_norm2)));

            /* "sklearn/linear_model/cd_fast.pyx":532
 *                         + 0.5 * beta * (1 + const ** 2) * w_norm2)
 * 
 *                 if gap < tol:             # <<<<<<<<<<<<<<
 *                     # return if we reached desired tolerance
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 */
            __pyx_t_31 = __pyx_v_ii;
            __pyx_v_X_mean_ii = (*((double *) ( /* dim=0 */ (__pyx_v_X_mean.data + __pyx_t_31 * __pyx_v_X_mean.strides[0]) )));

            /* "sklearn/linear_model/cd_fast.pyx":444
 *                 X_mean_ii = X_mean[ii]
 * 
 *                 if w_ii != 0.0:             # <<<<<<<<<<<<<<
 *                     # R += w_ii * X[:,ii]
 *                     for jj in range(startptr, endptr):
 */
            __pyx_t_13 = ((__pyx_v_w_ii != 0.0) != 0);
            if (__pyx_t_13) {

              /* "sklearn/linear_model/cd_fast.pyx":446
 *                 if w_ii != 0.0:
 *                     # R += w_ii * X[:,ii]
 *                     for jj in range(startptr, endptr):             # <<<<<<<<<<<<<<
 *                         R[X_indices[jj]] += X_data[jj] * w_ii
 *                     if center:
 */
              __pyx_t_18 = __pyx_v_endptr;
              for (__pyx_t_32 = __pyx_v_startptr; __pyx_t_32 < __pyx_t_18; __pyx_t_32+=1) {
                __pyx_v_jj = __pyx_t_32;

                /* "sklearn/linear_model/cd_fast.pyx":447
 *                     # R += w_ii * X[:,ii]
 *                     for jj in range(startptr, endptr):
 *                         R[X_indices[jj]] += X_data[jj] * w_ii             # <<<<<<<<<<<<<<
 *                     if center:
 *                         for jj in range(n_samples):
 */
                __pyx_t_33 = __pyx_v_jj;
                __pyx_t_34 = __pyx_v_jj;
                __pyx_t_35 = (*__Pyx_BufPtrCContig1d(int *, __pyx_pybuffernd_X_indices.rcbuffer->pybuffer.buf, __pyx_t_34, __pyx_pybuffernd_X_indices.diminfo[0].strides));
                *((double *) ( /* dim=0 */ (__pyx_v_R.data + __pyx_t_35 * __pyx_v_R.strides[0]) )) += ((*__Pyx_BufPtrCContig1d(double *, __pyx_pybuffernd_X_data.rcbuffer->pybuffer.buf, __pyx_t_33, __pyx_pybuffernd_X_data.diminfo[0].strides)) * __pyx_v_w_ii);
              }

              /* "sklearn/linear_model/cd_fast.pyx":448
 *                     for jj in range(startptr, endptr):
 *                         R[X_indices[jj]] += X_data[jj] * w_ii
 *                     if center:             # <<<<<<<<<<<<<<
 *                         for jj in range(n_samples):
 *                             R[jj] -= X_mean_ii * w_ii
 */
              __pyx_t_13 = (__pyx_v_center != 0);
              if (__pyx_t_13) {

                /* "sklearn/linear_model/cd_fast.pyx":449
 *                         R[X_indices[jj]] += X_data[jj] * w_ii
 *                     if center:
 *                         for jj in range(n_samples):             # <<<<<<<<<<<<<<
 *                             R[jj] -= X_mean_ii * w_ii
 * 
 */
                __pyx_t_18 = __pyx_v_n_samples;
                for (__pyx_t_32 = 0; __pyx_t_32 < __pyx_t_18; __pyx_t_32+=1) {
                  __pyx_v_jj = __pyx_t_32;

                  /* "sklearn/linear_model/cd_fast.pyx":450
 *                     if center:
 *                         for jj in range(n_samples):
 *                             R[jj] -= X_mean_ii * w_ii             # <<<<<<<<<<<<<<
 * 
 *                 # tmp = (X[:,ii] * R).sum()
 */
                  __pyx_t_36 = __pyx_v_jj;
                  *((double *) ( /* dim=0 */ (__pyx_v_R.data + __pyx_t_36 * __pyx_v_R.strides[0]) )) -= (__pyx_v_X_mean_ii * __pyx_v_w_ii);
                }

                /* "sklearn/linear_model/cd_fast.pyx":448
 *                     for jj in range(startptr, endptr):
 *                         R[X_indices[jj]] += X_data[jj] * w_ii
 *                     if center:             # <<<<<<<<<<<<<<
 *                         for jj in range(n_samples):
 *                             R[jj] -= X_mean_ii * w_ii
 */
              }

              /* "sklearn/linear_model/cd_fast.pyx":444
 *                 X_mean_ii = X_mean[ii]
 * 
 *                 if w_ii != 0.0:             # <<<<<<<<<<<<<<
 *                     # R += w_ii * X[:,ii]
 *                     for jj in range(startptr, endptr):
 */
            }

            /* "sklearn/linear_model/cd_fast.pyx":453
 * 
 *                 # tmp = (X[:,ii] * R).sum()
 *                 tmp = 0.0             # <<<<<<<<<<<<<<
 *                 for jj in range(startptr, endptr):
 *                     tmp += R[X_indices[jj]] * X_data[jj]
 */
            __pyx_v_tmp = 0.0;

            /* "sklearn/linear_model/cd_fast.pyx":454
 *                 # tmp = (X[:,ii] * R).sum()
 *                 tmp = 0.0
 *                 for jj in range(startptr, endptr):             # <<<<<<<<<<<<<<
 *                     tmp += R[X_indices[jj]] * X_data[jj]
 * 
 */
            __pyx_t_18 = __pyx_v_endptr;
            for (__pyx_t_32 = __pyx_v_startptr; __pyx_t_32 < __pyx_t_18; __pyx_t_32+=1) {
              __pyx_v_jj = __pyx_t_32;

              /* "sklearn/linear_model/cd_fast.pyx":455
 *                 tmp = 0.0
 *                 for jj in range(startptr, endptr):
 *                     tmp += R[X_indices[jj]] * X_data[jj]             # <<<<<<<<<<<<<<
 * 
 *                 if center:
 */
              __pyx_t_37 = __pyx_v_jj;
              __pyx_t_38 = (*__Pyx_BufPtrCContig1d(int *, __pyx_pybuffernd_X_indices.rcbuffer->pybuffer.buf, __pyx_t_37, __pyx_pybuffernd_X_indices.diminfo[0].strides));
              __pyx_t_39 = __pyx_v_jj;
              __pyx_v_tmp = (__pyx_v_tmp + ((*((double *) ( /* dim=0 */ (__pyx_v_R.data + __pyx_t_38 * __pyx_v_R.strides[0]) ))) * (*__Pyx_BufPtrCContig1d(double *, __pyx_pybuffernd_X_data.rcbuffer->pybuffer.buf, __pyx_t_39, __pyx_pybuffernd_X_data.diminfo[0].strides))));
            }

            /* "sklearn/linear_model/cd_fast.pyx":457
 *                     tmp += R[X_indices[jj]] * X_data[jj]
 * 
 *                 if center:             # <<<<<<<<<<<<<<
 *                     R_sum = 0.0
 *                     for jj in range(n_samples):
 */
            __pyx_t_13 = (__pyx_v_center != 0);
            if (__pyx_t_13) {

              /* "sklearn/linear_model/cd_fast.pyx":458
 * 
 *                 if center:
 *                     R_sum = 0.0             # <<<<<<<<<<<<<<
 *                     for jj in range(n_samples):
 *                         R_sum += R[jj]
 */
              __pyx_v_R_sum = 0.0;

              /* "sklearn/linear_model/cd_fast.pyx":459
 *                 if center:
 *                     R_sum = 0.0
 *                     for jj in range(n_samples):             # <<<<<<<<<<<<<<
 *                         R_sum += R[jj]
 *                     tmp -= R_sum * X_mean_ii
 */
              __pyx_t_18 = __pyx_v_n_samples;
              for (__pyx_t_32 = 0; __pyx_t_32 < __pyx_t_18; __pyx_t_32+=1) {
                __pyx_v_jj = __pyx_t_32;

                /* "sklearn/linear_model/cd_fast.pyx":460
 *                     R_sum = 0.0
 *                     for jj in range(n_samples):
 *                         R_sum += R[jj]             # <<<<<<<<<<<<<<
 *                     tmp -= R_sum * X_mean_ii
 * 
 */
                __pyx_t_40 = __pyx_v_jj;
                __pyx_v_R_sum = (__pyx_v_R_sum + (*((double *) ( /* dim=0 */ (__pyx_v_R.data + __pyx_t_40 * __pyx_v_R.strides[0]) ))));
              }

              /* "sklearn/linear_model/cd_fast.pyx":461
 *                     for jj in range(n_samples):
 *                         R_sum += R[jj]
 *                     tmp -= R_sum * X_mean_ii             # <<<<<<<<<<<<<<
 * 
 *                 if positive and tmp < 0.0:
 */
              __pyx_v_tmp = (__pyx_v_tmp - (__pyx_v_R_sum * __pyx_v_X_mean_ii));

              /* "sklearn/linear_model/cd_fast.pyx":457
 *                     tmp += R[X_indices[jj]] * X_data[jj]
 * 
 *                 if center:             # <<<<<<<<<<<<<<
 *                     R_sum = 0.0
 *                     for jj in range(n_samples):
 */
            }

            /* "sklearn/linear_model/cd_fast.pyx":463
 *                     tmp -= R_sum * X_mean_ii
 * 
 *                 if positive and tmp < 0.0:             # <<<<<<<<<<<<<<
 *                     w[ii] = 0.0
 *                 else:
 */
            __pyx_t_41 = (__pyx_v_positive != 0);
            if (__pyx_t_41) {
            } else {
              __pyx_t_13 = __pyx_t_41;
              goto __pyx_L34_bool_binop_done;
            }
            __pyx_t_41 = ((__pyx_v_tmp < 0.0) != 0);
            __pyx_t_13 = __pyx_t_41;
            __pyx_L34_bool_binop_done:;
            if (__pyx_t_13) {

              /* "sklearn/linear_model/cd_fast.pyx":464
 * 
 *                 if positive and tmp < 0.0:
 *                     w[ii] = 0.0             # <<<<<<<<<<<<<<
 *                 else:
 *                     w[ii] = fsign(tmp) * fmax(fabs(tmp) - alpha, 0) \
 */
              __pyx_t_42 = __pyx_v_ii;
              *((double *) ( /* dim=0 */ (__pyx_v_w.data + __pyx_t_42 * __pyx_v_w.strides[0]) )) = 0.0;

              /* "sklearn/linear_model/cd_fast.pyx":463
 *                     tmp -= R_sum * X_mean_ii
 * 
 *                 if positive and tmp < 0.0:             # <<<<<<<<<<<<<<
 *                     w[ii] = 0.0
 *                 else:
 */
              goto __pyx_L33;
            }

            /* "sklearn/linear_model/cd_fast.pyx":467
 *                 else:
 *                     w[ii] = fsign(tmp) * fmax(fabs(tmp) - alpha, 0) \
 *                             / (norm_cols_X[ii] + beta)             # <<<<<<<<<<<<<<
 * 
 *                 if w[ii] != 0.0:
 */
            /*else*/ {

              /* "sklearn/linear_model/cd_fast.pyx":466
 *                     w[ii] = 0.0
 *                 else:
 *                     w[ii] = fsign(tmp) * fmax(fabs(tmp) - alpha, 0) \             # <<<<<<<<<<<<<<
 *                             / (norm_cols_X[ii] + beta)
 * 
 */
              __pyx_t_43 = __pyx_v_ii;

              /* "sklearn/linear_model/cd_fast.pyx":467
 *                 else:
 *                     w[ii] = fsign(tmp) * fmax(fabs(tmp) - alpha, 0) \
 *                             / (norm_cols_X[ii] + beta)             # <<<<<<<<<<<<<<
 * 
 *                 if w[ii] != 0.0:
 */
              __pyx_t_44 = __pyx_v_ii;
              *((double *) ( /* dim=0 */ (__pyx_v_w.data + __pyx_t_44 * __pyx_v_w.strides[0]) )) = ((__pyx_fuse_1__pyx_f_7sklearn_12linear_model_7cd_fast_fsign(__pyx_v_tmp) * __pyx_fuse_1__pyx_f_7sklearn_12linear_model_7cd_fast_fmax((fabs(__pyx_v_tmp) - __pyx_v_alpha), 0.0)) / ((*((double *) ( /* dim=0 */ (__pyx_v_norm_cols_X.data + __pyx_t_43 * __pyx_v_norm_cols_X.strides[0]) ))) + __pyx_v_beta));
            }
            __pyx_L33:;

            /* "sklearn/linear_model/cd_fast.pyx":469
 *                             / (norm_cols_X[ii] + beta)
 * 
 *                 if w[ii] != 0.0:             # <<<<<<<<<<<<<<
 *                     # R -=  w[ii] * X[:,ii] # Update residual
 *                     for jj in range(startptr, endptr):
 */
            __pyx_t_45 = __pyx_v_ii;
            __pyx_t_13 = (((*((double *) ( /* dim=0 */ (__pyx_v_w.data + __pyx_t_45 * __pyx_v_w.strides[0]) ))) != 0.0) != 0);
            if (__pyx_t_13) {

              /* "sklearn/linear_model/cd_fast.pyx":471
 *                 if w[ii] != 0.0:
 *                     # R -=  w[ii] * X[:,ii] # Update residual
 *                     for jj in range(startptr, endptr):             # <<<<<<<<<<<<<<
 *                         R[X_indices[jj]] -= X_data[jj] * w[ii]
 * 
 */
              __pyx_t_18 = __pyx_v_endptr;
              for (__pyx_t_32 = __pyx_v_startptr; __pyx_t_32 < __pyx_t_18; __pyx_t_32+=1) {
                __pyx_v_jj = __pyx_t_32;

                /* "sklearn/linear_model/cd_fast.pyx":472
 *                     # R -=  w[ii] * X[:,ii] # Update residual
 *                     for jj in range(startptr, endptr):
 *                         R[X_indices[jj]] -= X_data[jj] * w[ii]             # <<<<<<<<<<<<<<
 * 
 *                     if center:
 */
                __pyx_t_46 = __pyx_v_jj;
                __pyx_t_47 = __pyx_v_ii;
                __pyx_t_48 = __pyx_v_jj;
                __pyx_t_49 = (*__Pyx_BufPtrCContig1d(int *, __pyx_pybuffernd_X_indices.rcbuffer->pybuffer.buf, __pyx_t_48, __pyx_pybuffernd_X_indices.diminfo[0].strides));
                *((double *) ( /* dim=0 */ (__pyx_v_R.data + __pyx_t_49 * __pyx_v_R.strides[0]) )) -= ((*__Pyx_BufPtrCContig1d(double *, __pyx_pybuffernd_X_data.rcbuffer->pybuffer.buf, __pyx_t_46, __pyx_pybuffernd_X_data.diminfo[0].strides)) * (*((double *) ( /* dim=0 */ (__pyx_v_w.data + __pyx_t_47 * __pyx_v_w.strides[0]) ))));
              }

              /* "sklearn/linear_model/cd_fast.pyx":474
 *                         R[X_indices[jj]] -= X_data[jj] * w[ii]
 * 
 *                     if center:             # <<<<<<<<<<<<<<
 *                         for jj in range(n_samples):
 *                             R[jj] += X_mean_ii * w[ii]
 */
              __pyx_t_13 = (__pyx_v_center != 0);
              if (__pyx_t_13) {

                /* "sklearn/linear_model/cd_fast.pyx":475
 * 
 *                     if center:
 *                         for jj in range(n_samples):             # <<<<<<<<<<<<<<
 *                             R[jj] += X_mean_ii * w[ii]
 * 
 */
                __pyx_t_18 = __pyx_v_n_samples;
                for (__pyx_t_32 = 0; __pyx_t_32 < __pyx_t_18; __pyx_t_32+=1) {
                  __pyx_v_jj = __pyx_t_32;

                  /* "sklearn/linear_model/cd_fast.pyx":476
 *                     if center:
 *                         for jj in range(n_samples):
 *                             R[jj] += X_mean_ii * w[ii]             # <<<<<<<<<<<<<<
 * 
 *                 # update the maximum absolute coefficient update
 */
                  __pyx_t_50 = __pyx_v_ii;
                  __pyx_t_51 = __pyx_v_jj;
                  *((double *) ( /* dim=0 */ (__pyx_v_R.data + __pyx_t_51 * __pyx_v_R.strides[0]) )) += (__pyx_v_X_mean_ii * (*((double *) ( /* dim=0 */ (__pyx_v_w.data + __pyx_t_50 * __pyx_v_w.strides[0]) ))));
                }

                /* "sklearn/linear_model/cd_fast.pyx":474
 *                         R[X_indices[jj]] -= X_data[jj] * w[ii]
 * 
 *                     if center:             # <<<<<<<<<<<<<<
 *                         for jj in range(n_samples):
 *                             R[jj] += X_mean_ii * w[ii]
 */
              }

              /* "sklearn/linear_model/cd_fast.pyx":469
 *                             / (norm_cols_X[ii] + beta)
 * 
 *                 if w[ii] != 0.0:             # <<<<<<<<<<<<<<
 *                     # R -=  w[ii] * X[:,ii] # Update residual
 *                     for jj in range(startptr, endptr):
 */
            }

            /* "sklearn/linear_model/cd_fast.pyx":479
 * 
 *                 # update the maximum absolute coefficient update
 *                 d_w_ii = fabs(w[ii] - w_ii)             # <<<<<<<<<<<<<<
 *                 if d_w_ii > d_w_max:
 *                     d_w_max = d_w_ii
 */
            __pyx_t_52 = __pyx_v_ii;
            __pyx_v_d_w_ii = fabs(((*((double *) ( /* dim=0 */ (__pyx_v_w.data + __pyx_t_52 * __pyx_v_w.strides[0]) ))) - __pyx_v_w_ii));

            /* "sklearn/linear_model/cd_fast.pyx":480
 *                 # update the maximum absolute coefficient update
 *                 d_w_ii = fabs(w[ii] - w_ii)
 *                 if d_w_ii > d_w_max:             # <<<<<<<<<<<<<<
 *                     d_w_max = d_w_ii
 * 
 */
            __pyx_t_13 = ((__pyx_v_d_w_ii > __pyx_v_d_w_max) != 0);
            if (__pyx_t_13) {

              /* "sklearn/linear_model/cd_fast.pyx":481
 *                 d_w_ii = fabs(w[ii] - w_ii)
 *                 if d_w_ii > d_w_max:
 *                     d_w_max = d_w_ii             # <<<<<<<<<<<<<<
 * 
 *                 if w[ii] > w_max:
 */
              __pyx_v_d_w_max = __pyx_v_d_w_ii;

              /* "sklearn/linear_model/cd_fast.pyx":480
 *                 # update the maximum absolute coefficient update
 *                 d_w_ii = fabs(w[ii] - w_ii)
 *                 if d_w_ii > d_w_max:             # <<<<<<<<<<<<<<
 *                     d_w_max = d_w_ii
 * 
 */
            }

            /* "sklearn/linear_model/cd_fast.pyx":483
 *                     d_w_max = d_w_ii
 * 
 *                 if w[ii] > w_max:             # <<<<<<<<<<<<<<
 *                     w_max = w[ii]
 *             if w_max == 0.0 or d_w_max / w_max < d_w_tol or n_iter == max_iter - 1:
 */
            __pyx_t_53 = __pyx_v_ii;
            __pyx_t_13 = (((*((double *) ( /* dim=0 */ (__pyx_v_w.data + __pyx_t_53 * __pyx_v_w.strides[0]) ))) > __pyx_v_w_max) != 0);
            if (__pyx_t_13) {

              /* "sklearn/linear_model/cd_fast.pyx":484
 * 
 *                 if w[ii] > w_max:
 *                     w_max = w[ii]             # <<<<<<<<<<<<<<
 *             if w_max == 0.0 or d_w_max / w_max < d_w_tol or n_iter == max_iter - 1:
 *                 # the biggest coordinate update of this iteration was smaller than
 */
              __pyx_t_54 = __pyx_v_ii;
              __pyx_v_w_max = (*((double *) ( /* dim=0 */ (__pyx_v_w.data + __pyx_t_54 * __pyx_v_w.strides[0]) )));

              /* "sklearn/linear_model/cd_fast.pyx":483
 *                     d_w_max = d_w_ii
 * 
 *                 if w[ii] > w_max:             # <<<<<<<<<<<<<<
 *                     w_max = w[ii]
 *             if w_max == 0.0 or d_w_max / w_max < d_w_tol or n_iter == max_iter - 1:
 */
            }
            __pyx_L18_continue:;
          }

          /* "sklearn/linear_model/cd_fast.pyx":485
 *                 if w[ii] > w_max:
 *                     w_max = w[ii]
 *             if w_max == 0.0 or d_w_max / w_max < d_w_tol or n_iter == max_iter - 1:             # <<<<<<<<<<<<<<
 *                 # the biggest coordinate update of this iteration was smaller than
 *                 # the tolerance: check the duality gap as ultimate stopping
 */
          __pyx_t_41 = ((__pyx_v_w_max == 0.0) != 0);
          if (!__pyx_t_41) {
          } else {
            __pyx_t_13 = __pyx_t_41;
            goto __pyx_L45_bool_binop_done;
          }
          __pyx_t_41 = (((__pyx_v_d_w_max / __pyx_v_w_max) < __pyx_v_d_w_tol) != 0);
          if (!__pyx_t_41) {
          } else {
            __pyx_t_13 = __pyx_t_41;
            goto __pyx_L45_bool_binop_done;
          }
          __pyx_t_41 = ((__pyx_v_n_iter == (__pyx_v_max_iter - 1)) != 0);
          __pyx_t_13 = __pyx_t_41;
          __pyx_L45_bool_binop_done:;
          if (__pyx_t_13) {

            /* "sklearn/linear_model/cd_fast.pyx":491
 * 
 *                 # sparse X.T / dense R dot product
 *                 if center:             # <<<<<<<<<<<<<<
 *                     R_sum = 0.0
 *                     for jj in range(n_samples):
 */
            __pyx_t_13 = (__pyx_v_center != 0);
            if (__pyx_t_13) {

              /* "sklearn/linear_model/cd_fast.pyx":492
 *                 # sparse X.T / dense R dot product
 *                 if center:
 *                     R_sum = 0.0             # <<<<<<<<<<<<<<
 *                     for jj in range(n_samples):
 *                         R_sum += R[jj]
 */
              __pyx_v_R_sum = 0.0;

              /* "sklearn/linear_model/cd_fast.pyx":493
 *                 if center:
 *                     R_sum = 0.0
 *                     for jj in range(n_samples):             # <<<<<<<<<<<<<<
 *                         R_sum += R[jj]
 * 
 */
              __pyx_t_11 = __pyx_v_n_samples;
              for (__pyx_t_17 = 0; __pyx_t_17 < __pyx_t_11; __pyx_t_17+=1) {
                __pyx_v_jj = __pyx_t_17;

                /* "sklearn/linear_model/cd_fast.pyx":494
 *                     R_sum = 0.0
 *                     for jj in range(n_samples):
 *                         R_sum += R[jj]             # <<<<<<<<<<<<<<
 * 
 *                 for ii in range(n_features):
 */
                __pyx_t_55 = __pyx_v_jj;
                __pyx_v_R_sum = (__pyx_v_R_sum + (*((double *) ( /* dim=0 */ (__pyx_v_R.data + __pyx_t_55 * __pyx_v_R.strides[0]) ))));
              }

              /* "sklearn/linear_model/cd_fast.pyx":491
 * 
 *                 # sparse X.T / dense R dot product
 *                 if center:             # <<<<<<<<<<<<<<
 *                     R_sum = 0.0
 *                     for jj in range(n_samples):
 */
            }

            /* "sklearn/linear_model/cd_fast.pyx":496
 *                         R_sum += R[jj]
 * 
 *                 for ii in range(n_features):             # <<<<<<<<<<<<<<
 *                     X_T_R[ii] = 0.0
 *                     for jj in range(X_indptr[ii], X_indptr[ii + 1]):
 */
            __pyx_t_11 = __pyx_v_n_features;
            for (__pyx_t_17 = 0; __pyx_t_17 < __pyx_t_11; __pyx_t_17+=1) {
              __pyx_v_ii = __pyx_t_17;

              /* "sklearn/linear_model/cd_fast.pyx":497
 * 
 *                 for ii in range(n_features):
 *                     X_T_R[ii] = 0.0             # <<<<<<<<<<<<<<
 *                     for jj in range(X_indptr[ii], X_indptr[ii + 1]):
 *                         X_T_R[ii] += X_data[jj] * R[X_indices[jj]]
 */
              __pyx_t_56 = __pyx_v_ii;
              *((double *) ( /* dim=0 */ (__pyx_v_X_T_R.data + __pyx_t_56 * __pyx_v_X_T_R.strides[0]) )) = 0.0;

              /* "sklearn/linear_model/cd_fast.pyx":498
 *                 for ii in range(n_features):
 *                     X_T_R[ii] = 0.0
 *                     for jj in range(X_indptr[ii], X_indptr[ii + 1]):             # <<<<<<<<<<<<<<
 *                         X_T_R[ii] += X_data[jj] * R[X_indices[jj]]
 * 
 */
              __pyx_t_57 = (__pyx_v_ii + 1);
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 *                 if random:
 */
          __pyx_v_d_w_max = 0.0;

          /* "sklearn/linear_model/cd_fast.pyx":616
 *             w_max = 0.0
 *             d_w_max = 0.0
 *             for f_iter in range(n_features):  # Loop over coordinates             # <<<<<<<<<<<<<<
 *                 if random:
 *                     ii = rand_int(n_features, rand_r_state)
 */
          __pyx_t_17 = __pyx_v_n_features;
          for (__pyx_t_18 = 0; __pyx_t_18 < __pyx_t_17; __pyx_t_18+=1) {
            __pyx_v_f_iter = __pyx_t_18;

            /* "sklearn/linear_model/cd_fast.pyx":617
 *             d_w_max = 0.0
 *             for f_iter in range(n_features):  # Loop over coordinates
 *                 if random:             # <<<<<<<<<<<<<<
 *                     ii = rand_int(n_features, rand_r_state)
 *                 else:
 */
            __pyx_t_15 = (__pyx_v_random != 0);
            if (__pyx_t_15) {

              /* "sklearn/linear_model/cd_fast.pyx":618
 *             for f_iter in range(n_features):  # Loop over coordinates
 *                 if random:
 *                     ii = rand_int(n_features, rand_r_state)             # <<<<<<<<<<<<<<
 *                 else:
 *                     ii = f_iter
 */
              __pyx_v_ii = __pyx_f_7sklearn_12linear_model_7cd_fast_rand_int(__pyx_v_n_features, __pyx_v_rand_r_state);

              /* "sklearn/linear_model/cd_fast.pyx":617
 *             d_w_max = 0.0
 *             for f_iter in range(n_features):  # Loop over coordinates
 *                 if random:             # <<<<<<<<<<<<<<
 *                     ii = rand_int(n_features, rand_r_state)
 *                 else:
 */
              goto __pyx_L11;
            }

            /* "sklearn/linear_model/cd_fast.pyx":620
 *                     ii = rand_int(n_features, rand_r_state)
 *                 else:
 *                     ii = f_iter             # <<<<<<<<<<<<<<
 * 
 *                 if Q[ii, ii] == 0.0:
 */
            /*else*/ {
              __pyx_v_ii = __pyx_v_f_iter;
            }
            __pyx_L11:;

            /* "sklearn/linear_model/cd_fast.pyx":622
 *                     ii = f_iter
 * 
 *                 if Q[ii, ii] == 0.0:             # <<<<<<<<<<<<<<
 *                     continue
 * 
 */
            __pyx_t_19 = __pyx_v_ii;
            __pyx_t_20 = __pyx_v_ii;
            __pyx_t_15 = (((*__Pyx_BufPtrCContig2d(float *, __pyx_pybuffernd_Q.rcbuffer->pybuffer.buf, __pyx_t_19, __pyx_pybuffernd_Q.diminfo[0].strides, __pyx_t_20, __pyx_pybuffernd_Q.diminfo[1].strides)) == 0.0) != 0);
            if (__pyx_t_15) {

              /* "sklearn/linear_model/cd_fast.pyx":623
 * 
 *                 if Q[ii, ii] == 0.0:
 *                     continue             # <<<<<<<<<<<<<<
 * 
 *                 w_ii = w[ii]  # Store previous value
 */
              goto __pyx_L9_continue;

              /* "sklearn/linear_model/cd_fast.pyx":622
 *                     ii = f_iter
 * 
 *                 if Q[ii, ii] == 0.0:             # <<<<<<<<<<<<<<
 *                     continue
 * 
 */
            }

            /* "sklearn/linear_model/cd_fast.pyx":625
 *                     continue
 * 
 *                 w_ii = w[ii]  # Store previous value             # <<<<<<<<<<<<<<
 * 
 *                 if w_ii != 0.0:
 */
            __pyx_t_21 = __pyx_v_ii;
            __pyx_v_w_ii = (*((float *) ( /* dim=0 */ (__pyx_v_w.data + __pyx_t_21 * __pyx_v_w.strides[0]) )));

            /* "sklearn/linear_model/cd_fast.pyx":627
 *                 w_ii = w[ii]  # Store previous value
 * 
 *                 if w_ii != 0.0:             # <<<<<<<<<<<<<<
 *                     # H -= w_ii * Q[ii]
 *                     axpy(n_features, -w_ii, Q_ptr + ii * n_features, 1,
 */
            __pyx_t_15 = ((__pyx_v_w_ii != 0.0) != 0);
            if (__pyx_t_15) {

              /* "sklearn/linear_model/cd_fast.pyx":629
 *                 if w_ii != 0.0:
 *                     # H -= w_ii * Q[ii]
 *                     axpy(n_features, -w_ii, Q_ptr + ii * n_features, 1,             # <<<<<<<<<<<<<<
 *                          H_ptr, 1)
 * 
 */
              __pyx_v_axpy(__pyx_v_n_features, (-__pyx_v_w_ii), (__pyx_v_Q_ptr + (__pyx_v_ii * __pyx_v_n_features)), 1, __pyx_v_H_ptr, 1);

              /* "sklearn/linear_model/cd_fast.pyx":627
 *                 w_ii = w[ii]  # Store previous value
 * 
 *                 if w_ii != 0.0:             # <<<<<<<<<<<<<<
 *                     # H -= w_ii * Q[ii]
 *                     axpy(n_features, -w_ii, Q_ptr + ii * n_features, 1,
 */
            }

            /* "sklearn/linear_model/cd_fast.pyx":632
 *                          H_ptr, 1)
 * 
 *                 tmp = q[ii] - H[ii]             # <<<<<<<<<<<<<<
 * 
 *                 if positive and tmp < 0:
 */
            __pyx_t_22 = __pyx_v_ii;
            __pyx_t_23 = __pyx_v_ii;
            __pyx_v_tmp = ((*__Pyx_BufPtrCContig1d(float *, __pyx_pybuffernd_q.rcbuffer->pybuffer.buf, __pyx_t_22, __pyx_pybuffernd_q.diminfo[0].strides)) - (*((float *) ( /* dim=0 */ (__pyx_v_H.data + __pyx_t_23 * __pyx_v_H.strides[0]) ))));

            /* "sklearn/linear_model/cd_fast.pyx":634
 *                 tmp = q[ii] - H[ii]
 * 
 *                 if positive and tmp < 0:             # <<<<<<<<<<<<<<
 *                     w[ii] = 0.0
 *                 else:
 */
            __pyx_t_24 = (__pyx_v_positive != 0);
            if (__pyx_t_24) {
            } else {
              __pyx_t_15 = __pyx_t_24;
              goto __pyx_L15_bool_binop_done;
            }
            __pyx_t_24 = ((__pyx_v_tmp < 0.0) != 0);
            __pyx_t_15 = __pyx_t_24;
            __pyx_L15_bool_binop_done:;
            if (__pyx_t_15) {

              /* "sklearn/linear_model/cd_fast.pyx":635
 * 
 *                 if positive and tmp < 0:
 *                     w[ii] = 0.0             # <<<<<<<<<<<<<<
 *                 else:
 *                     w[ii] = fsign(tmp) * fmax(fabs(tmp) - alpha, 0) \
 */
              __pyx_t_25 = __pyx_v_ii;
              *((float *) ( /* dim=0 */ (__pyx_v_w.data + __pyx_t_25 * __pyx_v_w.strides[0]) )) = 0.0;

              /* "sklearn/linear_model/cd_fast.pyx":634
 *                 tmp = q[ii] - H[ii]
 * 
 *                 if positive and tmp < 0:             # <<<<<<<<<<<<<<
 *                     w[ii] = 0.0
 *                 else:
 */
              goto __pyx_L14;
            }

            /* "sklearn/linear_model/cd_fast.pyx":638
 *                 else:
 *                     w[ii] = fsign(tmp) * fmax(fabs(tmp) - alpha, 0) \
 *                         / (Q[ii, ii] + beta)             # <<<<<<<<<<<<<<
 * 
 *                 if w[ii] != 0.0:
 */
            /*else*/ {

              /* "sklearn/linear_model/cd_fast.pyx":637
 *                     w[ii] = 0.0
 *                 else:
 *                     w[ii] = fsign(tmp) * fmax(fabs(tmp) - alpha, 0) \             # <<<<<<<<<<<<<<
 *                         / (Q[ii, ii] + beta)
 * 
 */
              __pyx_t_26 = __pyx_v_ii;
              __pyx_t_27 = __pyx_v_ii;

              /* "sklearn/linear_model/cd_fast.pyx":638
 *                 else:
 *                     w[ii] = fsign(tmp) * fmax(fabs(tmp) - alpha, 0) \
 *                         / (Q[ii, ii] + beta)             # <<<<<<<<<<<<<<
 * 
 *                 if w[ii] != 0.0:
 */
              __pyx_t_28 = __pyx_v_ii;
              *((float *) ( /* dim=0 */ (__pyx_v_w.data + __pyx_t_28 * __pyx_v_w.strides[0]) )) = ((__pyx_fuse_0__pyx_f_7sklearn_12linear_model_7cd_fast_fsign(__pyx_v_tmp) * __pyx_fuse_1__pyx_f_7sklearn_12linear_model_7cd_fast_fmax((fabs(__pyx_v_tmp) - __pyx_v_alpha), 0.0)) / ((*__Pyx_BufPtrCContig2d(float *, __pyx_pybuffernd_Q.rcbuffer->pybuffer.buf, __pyx_t_26, __pyx_pybuffernd_Q.diminfo[0].strides, __pyx_t_27, __pyx_pybuffernd_Q.diminfo[1].strides)) + __pyx_v_beta));
            }
            __pyx_L14:;

            /* "sklearn/linear_model/cd_fast.pyx":640
 *                         / (Q[ii, ii] + beta)
 * 
 *                 if w[ii] != 0.0:             # <<<<<<<<<<<<<<
 *                     # H +=  w[ii] * Q[ii] # Update H = X.T X w
 *                     axpy(n_features, w[ii], Q_ptr + ii * n_features, 1,
 */
            __pyx_t_29 = __pyx_v_ii;
            __pyx_t_15 = (((*((float *) ( /* dim=0 */ (__pyx_v_w.data + __pyx_t_29 * __pyx_v_w.strides[0]) ))) != 0.0) != 0);
            if (__pyx_t_15) {

              /* "sklearn/linear_model/cd_fast.pyx":642
 *                 if w[ii] != 0.0:
 *                     # H +=  w[ii] * Q[ii] # Update H = X.T X w
 *                     axpy(n_features, w[ii], Q_ptr + ii * n_features, 1,             # <<<<<<<<<<<<<<
 *                          H_ptr, 1)
 * 
 */
              __pyx_t_30 = __pyx_v_ii;

              /* "sklearn/linear_model/cd_fast.pyx":643
 *                     # H +=  w[ii] * Q[ii] # Update H = X.T X w
 *                     axpy(n_features, w[ii], Q_ptr + ii * n_features, 1,
 *                          H_ptr, 1)             # <<<<<<<<<<<<<<
 * 
 *                 # update the maximum absolute coefficient update
 */
              __pyx_v_axpy(__pyx_v_n_features, (*((float *) ( /* dim=0 */ (__pyx_v_w.data + __pyx_t_30 * __pyx_v_w.strides[0]) ))), (__pyx_v_Q_ptr + (__pyx_v_ii * __pyx_v_n_features)), 1, __pyx_v_H_ptr, 1);

              /* "sklearn/linear_model/cd_fast.pyx":640
 *                         / (Q[ii, ii] + beta)
 * 
 *                 if w[ii] != 0.0:             # <<<<<<<<<<<<<<
 *                     # H +=  w[ii] * Q[ii] # Update H = X.T X w
 *                     axpy(n_features, w[ii], Q_ptr + ii * n_features, 1,
 */
            }

            /* "sklearn/linear_model/cd_fast.pyx":646
 * 
 *                 # update the maximum absolute coefficient update
 *                 d_w_ii = fabs(w[ii] - w_ii)             # <<<<<<<<<<<<<<
 *                 if d_w_ii > d_w_max:
 *                     d_w_max = d_w_ii
 */
            __pyx_t_31 = __pyx_v_ii;
            __pyx_v_d_w_ii = fabs(((*((float *) ( /* dim=0 */ (__pyx_v_w.data + __pyx_t_31 * __pyx_v_w.strides[0]) ))) - __pyx_v_w_ii));

            /* "sklearn/linear_model/cd_fast.pyx":647
 *                 # update the maximum absolute coefficient update
 *                 d_w_ii = fabs(w[ii] - w_ii)
 *                 if d_w_ii > d_w_max:             # <<<<<<<<<<<<<<
 *                     d_w_max = d_w_ii
 * 
 */
            __pyx_t_15 = ((__pyx_v_d_w_ii > __pyx_v_d_w_max) != 0);
            if (__pyx_t_15) {

              /* "sklearn/linear_model/cd_fast.pyx":648
 *                 d_w_ii = fabs(w[ii] - w_ii)
 *                 if d_w_ii > d_w_max:
 *                     d_w_max = d_w_ii             # <<<<<<<<<<<<<<
 * 
 *                 if fabs(w[ii]) > w_max:
 */
              __pyx_v_d_w_max = __pyx_v_d_w_ii;

              /* "sklearn/linear_model/cd_fast.pyx":647
 *                 # update the maximum absolute coefficient update
 *                 d_w_ii = fabs(w[ii] - w_ii)
 *                 if d_w_ii > d_w_max:             # <<<<<<<<<<<<<<
 *                     d_w_max = d_w_ii
 * 
 */
            }

            /* "sklearn/linear_model/cd_fast.pyx":650
 *                     d_w_max = d_w_ii
 * 
 *                 if fabs(w[ii]) > w_max:             # <<<<<<<<<<<<<<
 *                     w_max = fabs(w[ii])
 * 
 */
            __pyx_t_32 = __pyx_v_ii;
            __pyx_t_15 = ((fabs((*((float *) ( /* dim=0 */ (__pyx_v_w.data + __pyx_t_32 * __pyx_v_w.strides[0]) )))) > __pyx_v_w_max) != 0);
            if (__pyx_t_15) {

              /* "sklearn/linear_model/cd_fast.pyx":651
 * 
 *                 if fabs(w[ii]) > w_max:
 *                     w_max = fabs(w[ii])             # <<<<<<<<<<<<<<
 * 
 *             if w_max == 0.0 or d_w_max / w_max < d_w_tol or n_iter == max_iter - 1:
 */
              __pyx_t_33 = __pyx_v_ii;
              __pyx_v_w_max = fabs((*((float *) ( /* dim=0 */ (__pyx_v_w.data + __pyx_t_33 * __pyx_v_w.strides[0]) ))));

              /* "sklearn/linear_model/cd_fast.pyx":650
 *                     d_w_max = d_w_ii
 * 
 *                 if fabs(w[ii]) > w_max:             # <<<<<<<<<<<<<<
 *                     w_max = fabs(w[ii])
 * 
 */
            }
            __pyx_L9_continue:;
          }

          /* "sklearn/linear_model/cd_fast.pyx":653
 *                     w_max = fabs(w[ii])
 * 
 *             if w_max == 0.0 or d_w_max / w_max < d_w_tol or n_iter == max_iter - 1:             # <<<<<<<<<<<<<<
 *                 # the biggest coordinate update of this iteration was smaller than
 *                 # the tolerance: check the duality gap as ultimate stopping
 */
          __pyx_t_24 = ((__pyx_v_w_max == 0.0) != 0);
          if (!__pyx_t_24) {
          } else {
            __pyx_t_15 = __pyx_t_24;
            goto __pyx_L21_bool_binop_done;
          }
          __pyx_t_24 = (((__pyx_v_d_w_max / __pyx_v_w_max) < __pyx_v_d_w_tol) != 0);
          if (!__pyx_t_24) {
          } else {
            __pyx_t_15 = __pyx_t_24;
            goto __pyx_L21_bool_binop_done;
          }
          __pyx_t_24 = ((__pyx_v_n_iter == (__pyx_v_max_iter - 1)) != 0);
          __pyx_t_15 = __pyx_t_24;
          __pyx_L21_bool_binop_done:;
          if (__pyx_t_15) {

            /* "sklearn/linear_model/cd_fast.pyx":659
 * 
 *                 # q_dot_w = np.dot(w, q)
 *                 q_dot_w = dot(n_features, w_ptr, 1, q_ptr, 1)             # <<<<<<<<<<<<<<
 * 
 *                 for ii in range(n_features):
 */
            __pyx_v_q_dot_w = __pyx_v_dot(__pyx_v_n_features, __pyx_v_w_ptr, 1, __pyx_v_q_ptr, 1);

            /* "sklearn/linear_model/cd_fast.pyx":661
 *                 q_dot_w = dot(n_features, w_ptr, 1, q_ptr, 1)
 * 
 *                 for ii in range(n_features):             # <<<<<<<<<<<<<<
 *                     XtA[ii] = q[ii] - H[ii] - beta * w[ii]
 *                 if positive:
 */
            __pyx_t_17 = __pyx_v_n_features;
            for (__pyx_t_18 = 0; __pyx_t_18 < __pyx_t_17; __pyx_t_18+=1) {
              __pyx_v_ii = __pyx_t_18;

              /* "sklearn/linear_model/cd_fast.pyx":662
 * 
 *                 for ii in range(n_features):
 *                     XtA[ii] = q[ii] - H[ii] - beta * w[ii]             # <<<<<<<<<<<<<<
 *                 if positive:
 *                     dual_norm_XtA = max(n_features, XtA_ptr)
 */
              __pyx_t_34 = __pyx_v_ii;
              __pyx_t_35 = __pyx_v_ii;
              __pyx_t_36 = __pyx_v_ii;
              __pyx_t_37 = __pyx_v_ii;
              *((float *) ( /* dim=0 */ (__pyx_v_XtA.data + __pyx_t_37 * __pyx_v_XtA.strides[0]) )) = (((*__Pyx_BufPtrCContig1d(float *, __pyx_pybuffernd_q.rcbuffer->pybuffer.buf, __pyx_t_34, __pyx_pybuffernd_q.diminfo[0].strides)) - (*((float *) ( /* dim=0 */ (__pyx_v_H.data + __pyx_t_35 * __pyx_v_H.strides[0]) )))) - (__pyx_v_beta * (*((float *) ( /* dim=0 */ (__pyx_v_w.data + __pyx_t_36 * __pyx_v_w.strides[0]) )))));
            }

            /* "sklearn/linear_model/cd_fast.pyx":663
 *                 for ii in range(n_features):
 *                     XtA[ii] = q[ii] - H[ii] - beta * w[ii]
 *                 if positive:             # <<<<<<<<<<<<<<
 *                     dual_norm_XtA = max(n_features, XtA_ptr)
 *                 else:
 */
            __pyx_t_15 = (__pyx_v_positive != 0);
            if (__pyx_t_15) {

              /* "sklearn/linear_model/cd_fast.pyx":664
 *                     XtA[ii] = q[ii] - H[ii] - beta * w[ii]
 *                 if positive:
 *                     dual_norm_XtA = max(n_features, XtA_ptr)             # <<<<<<<<<<<<<<
 *                 else:
 *                     dual_norm_XtA = abs_max(n_features, XtA_ptr)
 */
              __pyx_v_dual_norm_XtA = __pyx_fuse_0__pyx_f_7sklearn_12linear_model_7cd_fast_max(__pyx_v_n_features, __pyx_v_XtA_ptr);

              /* "sklearn/linear_model/cd_fast.pyx":663
 *                 for ii in range(n_features):
 *                     XtA[ii] = q[ii] - H[ii] - beta * w[ii]
 *                 if positive:             # <<<<<<<<<<<<<<
 *                     dual_norm_XtA = max(n_features, XtA_ptr)
 *                 else:
 */
              goto __pyx_L26;
            }

            /* "sklearn/linear_model/cd_fast.pyx":666
 *                     dual_norm_XtA = max(n_features, XtA_ptr)
 *                 else:
 *                     dual_norm_XtA = abs_max(n_features, XtA_ptr)             # <<<<<<<<<<<<<<
 * 
 *                 # temp = np.sum(w * H)
 */
            /*else*/ {
              __pyx_v_dual_norm_XtA = __pyx_fuse_0__pyx_f_7sklearn_12linear_model_7cd_fast_abs_max(__pyx_v_n_features, __pyx_v_XtA_ptr);
            }
            __pyx_L26:;

            /* "sklearn/linear_model/cd_fast.pyx":669
 * 
 *                 # temp = np.sum(w * H)
 *                 tmp = 0.0             # <<<<<<<<<<<<<<
 *                 for ii in range(n_features):
 *                     tmp += w[ii] * H[ii]
 */
            __pyx_v_tmp = 0.0;

            /* "sklearn/linear_model/cd_fast.pyx":670
 *                 # temp = np.sum(w * H)
 *                 tmp = 0.0
 *                 for ii in range(n_features):             # <<<<<<<<<<<<<<
 *                     tmp += w[ii] * H[ii]
 *                 R_norm2 = y_norm2 + tmp - 2.0 * q_dot_w
 */
            __pyx_t_17 = __pyx_v_n_features;
            for (__pyx_t_18 = 0; __pyx_t_18 < __pyx_t_17; __pyx_t_18+=1) {
              __pyx_v_ii = __pyx_t_18;

              /* "sklearn/linear_model/cd_fast.pyx":671
 *                 tmp = 0.0
 *                 for ii in range(n_features):
 *                     tmp += w[ii] * H[ii]             # <<<<<<<<<<<<<<
 *                 R_norm2 = y_norm2 + tmp - 2.0 * q_dot_w
 * 
 */
              __pyx_t_38 = __pyx_v_ii;
              __pyx_t_39 = __pyx_v_ii;
              __pyx_v_tmp = (__pyx_v_tmp + ((*((float *) ( /* dim=0 */ (__pyx_v_w.data + __pyx_t_38 * __pyx_v_w.strides[0]) ))) * (*((float *) ( /* dim=0 */ (__pyx_v_H.data + __pyx_t_39 * __pyx_v_H.strides[0]) )))));
            }

            /* "sklearn/linear_model/cd_fast.pyx":672
 *                 for ii in range(n_features):
 *                     tmp += w[ii] * H[ii]
 *                 R_norm2 = y_norm2 + tmp - 2.0 * q_dot_w             # <<<<<<<<<<<<<<
 * 
 *                 # w_norm2 = np.dot(w, w)
 */
            __pyx_v_R_norm2 = ((__pyx_v_y_norm2 + __pyx_v_tmp) - (2.0 * __pyx_v_q_dot_w));

            /* "sklearn/linear_model/cd_fast.pyx":675
 * 
 *                 # w_norm2 = np.dot(w, w)
 *                 w_norm2 = dot(n_features, &w[0], 1, &w[0], 1)             # <<<<<<<<<<<<<<
 * 
 *                 if (dual_norm_XtA > alpha):
 */
            __pyx_t_40 = 0;
            __pyx_t_41 = 0;
            __pyx_v_w_norm2 = __pyx_v_dot(__pyx_v_n_features, (&(*((float *) ( /* dim=0 */ (__pyx_v_w.data + __pyx_t_40 * __pyx_v_w.strides[0]) )))), 1, (&(*((float *) ( /* dim=0 */ (__pyx_v_w.data + __pyx_t_41 * __pyx_v_w.strides[0]) )))), 1);

            /* "sklearn/linear_model/cd_fast.pyx":677
 *                 w_norm2 = dot(n_features, &w[0], 1, &w[0], 1)
 * 
 *                 if (dual_norm_XtA > alpha):             # <<<<<<<<<<<<<<
 *                     const = alpha / dual_norm_XtA
 *                     A_norm2 = R_norm2 * (const ** 2)
 */
            __pyx_t_15 = ((__pyx_v_dual_norm_XtA > __pyx_v_alpha) != 0);
            if (__pyx_t_15) {

              /* "sklearn/linear_model/cd_fast.pyx":678
 * 
 *                 if (dual_norm_XtA > alpha):
 *                     const = alpha / dual_norm_XtA             # <<<<<<<<<<<<<<
 *                     A_norm2 = R_norm2 * (const ** 2)
 *                     gap = 0.5 * (R_norm2 + A_norm2)
 */
              __pyx_v_const = (__pyx_v_alpha / __pyx_v_dual_norm_XtA);

              /* "sklearn/linear_model/cd_fast.pyx":679
 *                 if (dual_norm_XtA > alpha):
 *                     const = alpha / dual_norm_XtA
 *                     A_norm2 = R_norm2 * (const ** 2)             # <<<<<<<<<<<<<<
 *                     gap = 0.5 * (R_norm2 + A_norm2)
 *                 else:
 */
              __pyx_v_A_norm2 = (__pyx_v_R_norm2 * pow(__pyx_v_const, 2.0));

              /* "sklearn/linear_model/cd_fast.pyx":680
 *                     const = alpha / dual_norm_XtA
 *                     A_norm2 = R_norm2 * (const ** 2)
 *                     gap = 0.5 * (R_norm2 + A_norm2)             # <<<<<<<<<<<<<<
 *                 else:
 *                     const = 1.0
 */
              __pyx_v_gap = (0.5 * (__pyx_v_R_norm2 + __pyx_v_A_norm2));

              /* "sklearn/linear_model/cd_fast.pyx":677
 *                 w_norm2 = dot(n_features, &w[0], 1, &w[0], 1)
 * 
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            /* "sklearn/linear_model/cd_fast.pyx":640
 *                         / (Q[ii, ii] + beta)
 * 
 *                 if w[ii] != 0.0:             # <<<<<<<<<<<<<<
 *                     # H +=  w[ii] * Q[ii] # Update H = X.T X w
 *                     axpy(n_features, w[ii], Q_ptr + ii * n_features, 1,
 */
            __pyx_t_29 = __pyx_v_ii;
            __pyx_t_15 = (((*((double *) ( /* dim=0 */ (__pyx_v_w.data + __pyx_t_29 * __pyx_v_w.strides[0]) ))) != 0.0) != 0);
            if (__pyx_t_15) {

              /* "sklearn/linear_model/cd_fast.pyx":642
 *                 if w[ii] != 0.0:
 *                     # H +=  w[ii] * Q[ii] # Update H = X.T X w
 *                     axpy(n_features, w[ii], Q_ptr + ii * n_features, 1,             # <<<<<<<<<<<<<<
 *                          H_ptr, 1)
 * 
 */
              __pyx_t_30 = __pyx_v_ii;

              /* "sklearn/linear_model/cd_fast.pyx":643
 *                     # H +=  w[ii] * Q[ii] # Update H = X.T X w
 *                     axpy(n_features, w[ii], Q_ptr + ii * n_features, 1,
 *                          H_ptr, 1)             # <<<<<<<<<<<<<<
 * 
 *                 # update the maximum absolute coefficient update
 */
              __pyx_v_axpy(__pyx_v_n_features, (*((double *) ( /* dim=0 */ (__pyx_v_w.data + __pyx_t_30 * __pyx_v_w.strides[0]) ))), (__pyx_v_Q_ptr + (__pyx_v_ii * __pyx_v_n_features)), 1, __pyx_v_H_ptr, 1);

              /* "sklearn/linear_model/cd_fast.pyx":640
 *                         / (Q[ii, ii] + beta)
 * 
 *                 if w[ii] != 0.0:             # <<<<<<<<<<<<<<
 *                     # H +=  w[ii] * Q[ii] # Update H = X.T X w
 *                     axpy(n_features, w[ii], Q_ptr + ii * n_features, 1,
 */
            }

            /* "sklearn/linear_model/cd_fast.pyx":646
 * 
 *                 # update the maximum absolute coefficient update
 *                 d_w_ii = fabs(w[ii] - w_ii)             # <<<<<<<<<<<<<<
 *                 if d_w_ii > d_w_max:
 *                     d_w_max = d_w_ii
 */
            __pyx_t_31 = __pyx_v_ii;
            __pyx_v_d_w_ii = fabs(((*((double *) ( /* dim=0 */ (__pyx_v_w.data + __pyx_t_31 * __pyx_v_w.strides[0]) ))) - __pyx_v_w_ii));

            /* "sklearn/linear_model/cd_fast.pyx":647
 *                 # update the maximum absolute coefficient update
 *                 d_w_ii = fabs(w[ii] - w_ii)
 *                 if d_w_ii > d_w_max:             # <<<<<<<<<<<<<<
 *                     d_w_max = d_w_ii
 * 
 */
            __pyx_t_15 = ((__pyx_v_d_w_ii > __pyx_v_d_w_max) != 0);
            if (__pyx_t_15) {

              /* "sklearn/linear_model/cd_fast.pyx":648
 *                 d_w_ii = fabs(w[ii] - w_ii)
 *                 if d_w_ii > d_w_max:
 *                     d_w_max = d_w_ii             # <<<<<<<<<<<<<<
 * 
 *                 if fabs(w[ii]) > w_max:
 */
              __pyx_v_d_w_max = __pyx_v_d_w_ii;

              /* "sklearn/linear_model/cd_fast.pyx":647
 *                 # update the maximum absolute coefficient update
 *                 d_w_ii = fabs(w[ii] - w_ii)
 *                 if d_w_ii > d_w_max:             # <<<<<<<<<<<<<<
 *                     d_w_max = d_w_ii
 * 
 */
            }

            /* "sklearn/linear_model/cd_fast.pyx":650
 *                     d_w_max = d_w_ii
 * 
 *                 if fabs(w[ii]) > w_max:             # <<<<<<<<<<<<<<
 *                     w_max = fabs(w[ii])
 * 
 */
            __pyx_t_32 = __pyx_v_ii;
            __pyx_t_15 = ((fabs((*((double *) ( /* dim=0 */ (__pyx_v_w.data + __pyx_t_32 * __pyx_v_w.strides[0]) )))) > __pyx_v_w_max) != 0);
            if (__pyx_t_15) {

              /* "sklearn/linear_model/cd_fast.pyx":651
 * 
 *                 if fabs(w[ii]) > w_max:
 *                     w_max = fabs(w[ii])             # <<<<<<<<<<<<<<
 * 
 *             if w_max == 0.0 or d_w_max / w_max < d_w_tol or n_iter == max_iter - 1:
 */
              __pyx_t_33 = __pyx_v_ii;
              __pyx_v_w_max = fabs((*((double *) ( /* dim=0 */ (__pyx_v_w.data + __pyx_t_33 * __pyx_v_w.strides[0]) ))));

              /* "sklearn/linear_model/cd_fast.pyx":650
 *                     d_w_max = d_w_ii
 * 
 *                 if fabs(w[ii]) > w_max:             # <<<<<<<<<<<<<<
 *                     w_max = fabs(w[ii])
 * 
 */
            }
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          }

          /* "sklearn/linear_model/cd_fast.pyx":653
 *                     w_max = fabs(w[ii])
 * 
 *             if w_max == 0.0 or d_w_max / w_max < d_w_tol or n_iter == max_iter - 1:             # <<<<<<<<<<<<<<
 *                 # the biggest coordinate update of this iteration was smaller than
 *                 # the tolerance: check the duality gap as ultimate stopping
 */
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          if (!__pyx_t_24) {
          } else {
            __pyx_t_15 = __pyx_t_24;
            goto __pyx_L21_bool_binop_done;
          }
          __pyx_t_24 = (((__pyx_v_d_w_max / __pyx_v_w_max) < __pyx_v_d_w_tol) != 0);
          if (!__pyx_t_24) {
          } else {
            __pyx_t_15 = __pyx_t_24;
            goto __pyx_L21_bool_binop_done;
          }
          __pyx_t_24 = ((__pyx_v_n_iter == (__pyx_v_max_iter - 1)) != 0);
          __pyx_t_15 = __pyx_t_24;
          __pyx_L21_bool_binop_done:;
          if (__pyx_t_15) {

            /* "sklearn/linear_model/cd_fast.pyx":659
 * 
 *                 # q_dot_w = np.dot(w, q)
 *                 q_dot_w = dot(n_features, w_ptr, 1, q_ptr, 1)             # <<<<<<<<<<<<<<
 * 
 *                 for ii in range(n_features):
 */
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            /* "sklearn/linear_model/cd_fast.pyx":661
 *                 q_dot_w = dot(n_features, w_ptr, 1, q_ptr, 1)
 * 
 *                 for ii in range(n_features):             # <<<<<<<<<<<<<<
 *                     XtA[ii] = q[ii] - H[ii] - beta * w[ii]
 *                 if positive:
 */
            __pyx_t_17 = __pyx_v_n_features;
            for (__pyx_t_18 = 0; __pyx_t_18 < __pyx_t_17; __pyx_t_18+=1) {
              __pyx_v_ii = __pyx_t_18;

              /* "sklearn/linear_model/cd_fast.pyx":662
 * 
 *                 for ii in range(n_features):
 *                     XtA[ii] = q[ii] - H[ii] - beta * w[ii]             # <<<<<<<<<<<<<<
 *                 if positive:
 *                     dual_norm_XtA = max(n_features, XtA_ptr)
 */
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              __pyx_t_35 = __pyx_v_ii;
              __pyx_t_36 = __pyx_v_ii;
              __pyx_t_37 = __pyx_v_ii;
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            /* "sklearn/linear_model/cd_fast.pyx":663
 *                 for ii in range(n_features):
 *                     XtA[ii] = q[ii] - H[ii] - beta * w[ii]
 *                 if positive:             # <<<<<<<<<<<<<<
 *                     dual_norm_XtA = max(n_features, XtA_ptr)
 *                 else:
 */
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              /* "sklearn/linear_model/cd_fast.pyx":664
 *                     XtA[ii] = q[ii] - H[ii] - beta * w[ii]
 *                 if positive:
 *                     dual_norm_XtA = max(n_features, XtA_ptr)             # <<<<<<<<<<<<<<
 *                 else:
 *                     dual_norm_XtA = abs_max(n_features, XtA_ptr)
 */
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              /* "sklearn/linear_model/cd_fast.pyx":663
 *                 for ii in range(n_features):
 *                     XtA[ii] = q[ii] - H[ii] - beta * w[ii]
 *                 if positive:             # <<<<<<<<<<<<<<
 *                     dual_norm_XtA = max(n_features, XtA_ptr)
 *                 else:
 */
              goto __pyx_L26;
            }

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 *                     dual_norm_XtA = max(n_features, XtA_ptr)
 *                 else:
 *                     dual_norm_XtA = abs_max(n_features, XtA_ptr)             # <<<<<<<<<<<<<<
 * 
 *                 # temp = np.sum(w * H)
 */
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            }
            __pyx_L26:;

            /* "sklearn/linear_model/cd_fast.pyx":669
 * 
 *                 # temp = np.sum(w * H)
 *                 tmp = 0.0             # <<<<<<<<<<<<<<
 *                 for ii in range(n_features):
 *                     tmp += w[ii] * H[ii]
 */
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            /* "sklearn/linear_model/cd_fast.pyx":670
 *                 # temp = np.sum(w * H)
 *                 tmp = 0.0
 *                 for ii in range(n_features):             # <<<<<<<<<<<<<<
 *                     tmp += w[ii] * H[ii]
 *                 R_norm2 = y_norm2 + tmp - 2.0 * q_dot_w
 */
            __pyx_t_17 = __pyx_v_n_features;
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              /* "sklearn/linear_model/cd_fast.pyx":671
 *                 tmp = 0.0
 *                 for ii in range(n_features):
 *                     tmp += w[ii] * H[ii]             # <<<<<<<<<<<<<<
 *                 R_norm2 = y_norm2 + tmp - 2.0 * q_dot_w
 * 
 */
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              __pyx_t_39 = __pyx_v_ii;
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            }

            /* "sklearn/linear_model/cd_fast.pyx":672
 *                 for ii in range(n_features):
 *                     tmp += w[ii] * H[ii]
 *                 R_norm2 = y_norm2 + tmp - 2.0 * q_dot_w             # <<<<<<<<<<<<<<
 * 
 *                 # w_norm2 = np.dot(w, w)
 */
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            /* "sklearn/linear_model/cd_fast.pyx":675
 * 
 *                 # w_norm2 = np.dot(w, w)
 *                 w_norm2 = dot(n_features, &w[0], 1, &w[0], 1)             # <<<<<<<<<<<<<<
 * 
 *                 if (dual_norm_XtA > alpha):
 */
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            /* "sklearn/linear_model/cd_fast.pyx":677
 *                 w_norm2 = dot(n_features, &w[0], 1, &w[0], 1)
 * 
 *                 if (dual_norm_XtA > alpha):             # <<<<<<<<<<<<<<
 *                     const = alpha / dual_norm_XtA
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 */
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              /* "sklearn/linear_model/cd_fast.pyx":678
 * 
 *                 if (dual_norm_XtA > alpha):
 *                     const = alpha / dual_norm_XtA             # <<<<<<<<<<<<<<
 *                     A_norm2 = R_norm2 * (const ** 2)
 *                     gap = 0.5 * (R_norm2 + A_norm2)
 */
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              /* "sklearn/linear_model/cd_fast.pyx":679
 *                 if (dual_norm_XtA > alpha):
 *                     const = alpha / dual_norm_XtA
 *                     A_norm2 = R_norm2 * (const ** 2)             # <<<<<<<<<<<<<<
 *                     gap = 0.5 * (R_norm2 + A_norm2)
 *                 else:
 */
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              /* "sklearn/linear_model/cd_fast.pyx":680
 *                     const = alpha / dual_norm_XtA
 *                     A_norm2 = R_norm2 * (const ** 2)
 *                     gap = 0.5 * (R_norm2 + A_norm2)             # <<<<<<<<<<<<<<
 *                 else:
 *                     const = 1.0
 */
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              /* "sklearn/linear_model/cd_fast.pyx":677
 *                 w_norm2 = dot(n_features, &w[0], 1, &w[0], 1)
 * 
 *                 if (dual_norm_XtA > alpha):             # <<<<<<<<<<<<<<
 *                     const = alpha / dual_norm_XtA
 *                     A_norm2 = R_norm2 * (const ** 2)
 */
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            }

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 *                     gap = 0.5 * (R_norm2 + A_norm2)
 *                 else:
 *                     const = 1.0             # <<<<<<<<<<<<<<
 *                     gap = R_norm2
 * 
 */
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 *                 else:
 *                     const = 1.0
 *                     gap = R_norm2             # <<<<<<<<<<<<<<
 * 
 *                 # The call to dasum is equivalent to the L1 norm of w
 */
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            __pyx_L29:;

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 * 
 *                 # The call to dasum is equivalent to the L1 norm of w
 *                 gap += (alpha * asum(n_features, &w[0], 1) -             # <<<<<<<<<<<<<<
 *                         const * y_norm2 +  const * q_dot_w +
 *                         0.5 * beta * (1 + const ** 2) * w_norm2)
 */
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 *                 # The call to dasum is equivalent to the L1 norm of w
 *                 gap += (alpha * asum(n_features, &w[0], 1) -
 *                         const * y_norm2 +  const * q_dot_w +             # <<<<<<<<<<<<<<
 *                         0.5 * beta * (1 + const ** 2) * w_norm2)
 * 
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 *                         0.5 * beta * (1 + const ** 2) * w_norm2)
 * 
 *                 if gap < tol:             # <<<<<<<<<<<<<<
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 */
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 *                 if gap < tol:
 *                     # return if we reached desired tolerance
 *                     break             # <<<<<<<<<<<<<<
 * 
 *     return np.asarray(w), gap, tol, n_iter + 1
 */
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 *                         0.5 * beta * (1 + const ** 2) * w_norm2)
 * 
 *                 if gap < tol:             # <<<<<<<<<<<<<<
 *                     # return if we reached desired tolerance
 *                     break
 */
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 *                     w_max = fabs(w[ii])
 * 
 *             if w_max == 0.0 or d_w_max / w_max < d_w_tol or n_iter == max_iter - 1:             # <<<<<<<<<<<<<<
 *                 # the biggest coordinate update of this iteration was smaller than
 *                 # the tolerance: check the duality gap as ultimate stopping
 */
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 *             " results and is discouraged.")
 * 
 *     with nogil:             # <<<<<<<<<<<<<<
 *         for n_iter in range(max_iter):
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 * 
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 *                 gemv(CblasRowMajor, CblasTrans,             # <<<<<<<<<<<<<<
 *                       n_samples, n_tasks, 1.0, &R[0, 0], n_tasks,
 *                       X_ptr + ii * n_samples, 1, 0.0, &tmp[0], 1)
 */
            __pyx_v_gemv(CblasRowMajor, CblasTrans, __pyx_v_n_samples, __pyx_v_n_tasks, 1.0, (&(*((float *) ( /* dim=1 */ ((char *) (((float *) ( /* dim=0 */ (__pyx_v_R.data + __pyx_t_33 * __pyx_v_R.strides[0]) )) + __pyx_t_34)) )))), __pyx_v_n_tasks, (__pyx_v_X_ptr + (__pyx_v_ii * __pyx_v_n_samples)), 1, 0.0, (&(*((float *) ( /* dim=0 */ ((char *) (((float *) __pyx_v_tmp.data) + __pyx_t_35)) )))), 1);

            /* "sklearn/linear_model/cd_fast.pyx":825
 * 
 *                 # nn = sqrt(np.sum(tmp ** 2))
 *                 nn = nrm2(n_tasks, &tmp[0], 1)             # <<<<<<<<<<<<<<
 * 
 *                 # W[:, ii] = tmp * fmax(1. - l1_reg / nn, 0) / (norm_cols_X[ii] + l2_reg)
 */
            __pyx_t_36 = 0;
            __pyx_v_nn = __pyx_v_nrm2(__pyx_v_n_tasks, (&(*((float *) ( /* dim=0 */ ((char *) (((float *) __pyx_v_tmp.data) + __pyx_t_36)) )))), 1);

            /* "sklearn/linear_model/cd_fast.pyx":828
 * 
 *                 # W[:, ii] = tmp * fmax(1. - l1_reg / nn, 0) / (norm_cols_X[ii] + l2_reg)
 *                 copy(n_tasks, &tmp[0], 1, W_ptr + ii * n_tasks, 1)             # <<<<<<<<<<<<<<
 *                 scal(n_tasks, fmax(1. - l1_reg / nn, 0) / (norm_cols_X[ii] + l2_reg),
 *                           W_ptr + ii * n_tasks, 1)
 */
            __pyx_t_37 = 0;
            __pyx_v_copy(__pyx_v_n_tasks, (&(*((float *) ( /* dim=0 */ ((char *) (((float *) __pyx_v_tmp.data) + __pyx_t_37)) )))), 1, (__pyx_v_W_ptr + (__pyx_v_ii * __pyx_v_n_tasks)), 1);

            /* "sklearn/linear_model/cd_fast.pyx":829
 *                 # W[:, ii] = tmp * fmax(1. - l1_reg / nn, 0) / (norm_cols_X[ii] + l2_reg)
 *                 copy(n_tasks, &tmp[0], 1, W_ptr + ii * n_tasks, 1)
 *                 scal(n_tasks, fmax(1. - l1_reg / nn, 0) / (norm_cols_X[ii] + l2_reg),             # <<<<<<<<<<<<<<
 *                           W_ptr + ii * n_tasks, 1)
 * 
 */
            __pyx_t_38 = __pyx_v_ii;

            /* "sklearn/linear_model/cd_fast.pyx":830
 *                 copy(n_tasks, &tmp[0], 1, W_ptr + ii * n_tasks, 1)
 *                 scal(n_tasks, fmax(1. - l1_reg / nn, 0) / (norm_cols_X[ii] + l2_reg),
 *                           W_ptr + ii * n_tasks, 1)             # <<<<<<<<<<<<<<
 * 
 *                 # if np.sum(W[:, ii] ** 2) != 0.0:  # can do better
 */
            __pyx_v_scal(__pyx_v_n_tasks, (__pyx_fuse_1__pyx_f_7sklearn_12linear_model_7cd_fast_fmax((1. - (__pyx_v_l1_reg / __pyx_v_nn)), 0.0) / ((*((float *) ( /* dim=0 */ (__pyx_v_norm_cols_X.data + __pyx_t_38 * __pyx_v_norm_cols_X.strides[0]) ))) + __pyx_v_l2_reg)), (__pyx_v_W_ptr + (__pyx_v_ii * __pyx_v_n_tasks)), 1);

            /* "sklearn/linear_model/cd_fast.pyx":833
 * 
 *                 # if np.sum(W[:, ii] ** 2) != 0.0:  # can do better
 *                 if nrm2(n_tasks, W_ptr + ii * n_tasks, 1) != 0.0:             # <<<<<<<<<<<<<<
 *                     # R -= np.dot(X[:, ii][:, None], W[:, ii][None, :])
 *                     # Update residual : rank 1 update
 */
            __pyx_t_18 = ((__pyx_v_nrm2(__pyx_v_n_tasks, (__pyx_v_W_ptr + (__pyx_v_ii * __pyx_v_n_tasks)), 1) != 0.0) != 0);
            if (__pyx_t_18) {

              /* "sklearn/linear_model/cd_fast.pyx":838
 *                     ger(CblasRowMajor, n_samples, n_tasks, -1.0,
 *                          X_ptr + ii * n_samples, 1, W_ptr + ii * n_tasks, 1,
 *                          &R[0, 0], n_tasks)             # <<<<<<<<<<<<<<
 * 
 *                 # update the maximum absolute coefficient update
 */
              __pyx_t_39 = 0;
              __pyx_t_40 = 0;

              /* "sklearn/linear_model/cd_fast.pyx":836
 *                     # R -= np.dot(X[:, ii][:, None], W[:, ii][None, :])
 *                     # Update residual : rank 1 update
 *                     ger(CblasRowMajor, n_samples, n_tasks, -1.0,             # <<<<<<<<<<<<<<
 *                          X_ptr + ii * n_samples, 1, W_ptr + ii * n_tasks, 1,
 *                          &R[0, 0], n_tasks)
 */
              __pyx_v_ger(CblasRowMajor, __pyx_v_n_samples, __pyx_v_n_tasks, -1.0, (__pyx_v_X_ptr + (__pyx_v_ii * __pyx_v_n_samples)), 1, (__pyx_v_W_ptr + (__pyx_v_ii * __pyx_v_n_tasks)), 1, (&(*((float *) ( /* dim=1 */ ((char *) (((float *) ( /* dim=0 */ (__pyx_v_R.data + __pyx_t_39 * __pyx_v_R.strides[0]) )) + __pyx_t_40)) )))), __pyx_v_n_tasks);

              /* "sklearn/linear_model/cd_fast.pyx":833
 * 
 *                 # if np.sum(W[:, ii] ** 2) != 0.0:  # can do better
 *                 if nrm2(n_tasks, W_ptr + ii * n_tasks, 1) != 0.0:             # <<<<<<<<<<<<<<
 *                     # R -= np.dot(X[:, ii][:, None], W[:, ii][None, :])
 *                     # Update residual : rank 1 update
 */
            }

            /* "sklearn/linear_model/cd_fast.pyx":841
 * 
 *                 # update the maximum absolute coefficient update
 *                 d_w_ii = diff_abs_max(n_tasks, W_ptr + ii * n_tasks, wii_ptr)             # <<<<<<<<<<<<<<
 * 
 *                 if d_w_ii > d_w_max:
 */
            __pyx_v_d_w_ii = __pyx_fuse_0__pyx_f_7sklearn_12linear_model_7cd_fast_diff_abs_max(__pyx_v_n_tasks, (__pyx_v_W_ptr + (__pyx_v_ii * __pyx_v_n_tasks)), __pyx_v_wii_ptr);

            /* "sklearn/linear_model/cd_fast.pyx":843
 *                 d_w_ii = diff_abs_max(n_tasks, W_ptr + ii * n_tasks, wii_ptr)
 * 
 *                 if d_w_ii > d_w_max:             # <<<<<<<<<<<<<<
 *                     d_w_max = d_w_ii
 * 
 */
            __pyx_t_18 = ((__pyx_v_d_w_ii > __pyx_v_d_w_max) != 0);
            if (__pyx_t_18) {

              /* "sklearn/linear_model/cd_fast.pyx":844
 * 
 *                 if d_w_ii > d_w_max:
 *                     d_w_max = d_w_ii             # <<<<<<<<<<<<<<
 * 
 *                 W_ii_abs_max = abs_max(n_tasks, W_ptr + ii * n_tasks)
 */
              __pyx_v_d_w_max = __pyx_v_d_w_ii;

              /* "sklearn/linear_model/cd_fast.pyx":843
 *                 d_w_ii = diff_abs_max(n_tasks, W_ptr + ii * n_tasks, wii_ptr)
 * 
 *                 if d_w_ii > d_w_max:             # <<<<<<<<<<<<<<
 *                     d_w_max = d_w_ii
 * 
 */
            }

            /* "sklearn/linear_model/cd_fast.pyx":846
 *                     d_w_max = d_w_ii
 * 
 *                 W_ii_abs_max = abs_max(n_tasks, W_ptr + ii * n_tasks)             # <<<<<<<<<<<<<<
 *                 if W_ii_abs_max > w_max:
 *                     w_max = W_ii_abs_max
 */
            __pyx_v_W_ii_abs_max = __pyx_fuse_0__pyx_f_7sklearn_12linear_model_7cd_fast_abs_max(__pyx_v_n_tasks, (__pyx_v_W_ptr + (__pyx_v_ii * __pyx_v_n_tasks)));

            /* "sklearn/linear_model/cd_fast.pyx":847
 * 
 *                 W_ii_abs_max = abs_max(n_tasks, W_ptr + ii * n_tasks)
 *                 if W_ii_abs_max > w_max:             # <<<<<<<<<<<<<<
 *                     w_max = W_ii_abs_max
 * 
 */
            __pyx_t_18 = ((__pyx_v_W_ii_abs_max > __pyx_v_w_max) != 0);
            if (__pyx_t_18) {

              /* "sklearn/linear_model/cd_fast.pyx":848
 *                 W_ii_abs_max = abs_max(n_tasks, W_ptr + ii * n_tasks)
 *                 if W_ii_abs_max > w_max:
 *                     w_max = W_ii_abs_max             # <<<<<<<<<<<<<<
 * 
 *             if w_max == 0.0 or d_w_max / w_max < d_w_tol or n_iter == max_iter - 1:
 */
              __pyx_v_w_max = __pyx_v_W_ii_abs_max;

              /* "sklearn/linear_model/cd_fast.pyx":847
 * 
 *                 W_ii_abs_max = abs_max(n_tasks, W_ptr + ii * n_tasks)
 *                 if W_ii_abs_max > w_max:             # <<<<<<<<<<<<<<
 *                     w_max = W_ii_abs_max
 * 
 */
            }
            __pyx_L17_continue:;
          }

          /* "sklearn/linear_model/cd_fast.pyx":850
 *                     w_max = W_ii_abs_max
 * 
 *             if w_max == 0.0 or d_w_max / w_max < d_w_tol or n_iter == max_iter - 1:             # <<<<<<<<<<<<<<
 *                 # the biggest coordinate update of this iteration was smaller than
 *                 # the tolerance: check the duality gap as ultimate stopping
 */
          __pyx_t_41 = ((__pyx_v_w_max == 0.0) != 0);
          if (!__pyx_t_41) {
          } else {
            __pyx_t_18 = __pyx_t_41;
            goto __pyx_L26_bool_binop_done;
          }
          __pyx_t_41 = (((__pyx_v_d_w_max / __pyx_v_w_max) < __pyx_v_d_w_tol) != 0);
          if (!__pyx_t_41) {
          } else {
            __pyx_t_18 = __pyx_t_41;
            goto __pyx_L26_bool_binop_done;
          }
          __pyx_t_41 = ((__pyx_v_n_iter == (__pyx_v_max_iter - 1)) != 0);
          __pyx_t_18 = __pyx_t_41;
          __pyx_L26_bool_binop_done:;
          if (__pyx_t_18) {

            /* "sklearn/linear_model/cd_fast.pyx":856
 * 
 *                 # XtA = np.dot(X.T, R) - l2_reg * W.T
 *                 for ii in range(n_features):             # <<<<<<<<<<<<<<
 *                     for jj in range(n_tasks):
 *                         XtA[ii, jj] = dot(
 */
            __pyx_t_20 = __pyx_v_n_features;
            for (__pyx_t_21 = 0; __pyx_t_21 < __pyx_t_20; __pyx_t_21+=1) {
              __pyx_v_ii = __pyx_t_21;

              /* "sklearn/linear_model/cd_fast.pyx":857
 *                 # XtA = np.dot(X.T, R) - l2_reg * W.T
 *                 for ii in range(n_features):
 *                     for jj in range(n_tasks):             # <<<<<<<<<<<<<<
 *                         XtA[ii, jj] = dot(
 *                             n_samples, X_ptr + ii * n_samples, 1,
 */
              __pyx_t_22 = __pyx_v_n_tasks;
              for (__pyx_t_42 = 0; __pyx_t_42 < __pyx_t_22; __pyx_t_42+=1) {
                __pyx_v_jj = __pyx_t_42;

                /* "sklearn/linear_model/cd_fast.pyx":860
 *                         XtA[ii, jj] = dot(
 *                             n_samples, X_ptr + ii * n_samples, 1,
 *                             &R[0, 0] + jj, n_tasks             # <<<<<<<<<<<<<<
 *                             ) - l2_reg * W[jj, ii]
 * 
 */
                __pyx_t_43 = 0;
                __pyx_t_44 = 0;

                /* "sklearn/linear_model/cd_fast.pyx":861
 *                             n_samples, X_ptr + ii * n_samples, 1,
 *                             &R[0, 0] + jj, n_tasks
 *                             ) - l2_reg * W[jj, ii]             # <<<<<<<<<<<<<<
 * 
 *                 # dual_norm_XtA = np.max(np.sqrt(np.sum(XtA ** 2, axis=1)))
 */
                __pyx_t_45 = __pyx_v_jj;
                __pyx_t_46 = __pyx_v_ii;

                /* "sklearn/linear_model/cd_fast.pyx":858
 *                 for ii in range(n_features):
 *                     for jj in range(n_tasks):
 *                         XtA[ii, jj] = dot(             # <<<<<<<<<<<<<<
 *                             n_samples, X_ptr + ii * n_samples, 1,
 *                             &R[0, 0] + jj, n_tasks
 */
                __pyx_t_47 = __pyx_v_ii;
                __pyx_t_48 = __pyx_v_jj;
                *((float *) ( /* dim=1 */ ((char *) (((float *) ( /* dim=0 */ (__pyx_v_XtA.data + __pyx_t_47 * __pyx_v_XtA.strides[0]) )) + __pyx_t_48)) )) = (__pyx_v_dot(__pyx_v_n_samples, (__pyx_v_X_ptr + (__pyx_v_ii * __pyx_v_n_samples)), 1, ((&(*((float *) ( /* dim=1 */ ((char *) (((float *) ( /* dim=0 */ (__pyx_v_R.data + __pyx_t_43 * __pyx_v_R.strides[0]) )) + __pyx_t_44)) )))) + __pyx_v_jj), __pyx_v_n_tasks) - (__pyx_v_l2_reg * (*((float *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((float *) __pyx_v_W.data) + __pyx_t_45)) ) + __pyx_t_46 * __pyx_v_W.strides[1]) )))));
              }
            }

            /* "sklearn/linear_model/cd_fast.pyx":864
 * 
 *                 # dual_norm_XtA = np.max(np.sqrt(np.sum(XtA ** 2, axis=1)))
 *                 dual_norm_XtA = 0.0             # <<<<<<<<<<<<<<
 *                 for ii in range(n_features):
 *                     # np.sqrt(np.sum(XtA ** 2, axis=1))
 */
            __pyx_v_dual_norm_XtA = 0.0;

            /* "sklearn/linear_model/cd_fast.pyx":865
 *                 # dual_norm_XtA = np.max(np.sqrt(np.sum(XtA ** 2, axis=1)))
 *                 dual_norm_XtA = 0.0
 *                 for ii in range(n_features):             # <<<<<<<<<<<<<<
 *                     # np.sqrt(np.sum(XtA ** 2, axis=1))
 *                     XtA_axis1norm = nrm2(n_tasks, &XtA[0, 0] + ii * n_tasks, 1)
 */
            __pyx_t_20 = __pyx_v_n_features;
            for (__pyx_t_21 = 0; __pyx_t_21 < __pyx_t_20; __pyx_t_21+=1) {
              __pyx_v_ii = __pyx_t_21;

              /* "sklearn/linear_model/cd_fast.pyx":867
 *                 for ii in range(n_features):
 *                     # np.sqrt(np.sum(XtA ** 2, axis=1))
 *                     XtA_axis1norm = nrm2(n_tasks, &XtA[0, 0] + ii * n_tasks, 1)             # <<<<<<<<<<<<<<
 *                     if XtA_axis1norm > dual_norm_XtA:
 *                         dual_norm_XtA = XtA_axis1norm
 */
              __pyx_t_49 = 0;
              __pyx_t_50 = 0;
              __pyx_v_XtA_axis1norm = __pyx_v_nrm2(__pyx_v_n_tasks, ((&(*((float *) ( /* dim=1 */ ((char *) (((float *) ( /* dim=0 */ (__pyx_v_XtA.data + __pyx_t_49 * __pyx_v_XtA.strides[0]) )) + __pyx_t_50)) )))) + (__pyx_v_ii * __pyx_v_n_tasks)), 1);

              /* "sklearn/linear_model/cd_fast.pyx":868
 *                     # np.sqrt(np.sum(XtA ** 2, axis=1))
 *                     XtA_axis1norm = nrm2(n_tasks, &XtA[0, 0] + ii * n_tasks, 1)
 *                     if XtA_axis1norm > dual_norm_XtA:             # <<<<<<<<<<<<<<
 *                         dual_norm_XtA = XtA_axis1norm
 * 
 */
              __pyx_t_18 = ((__pyx_v_XtA_axis1norm > __pyx_v_dual_norm_XtA) != 0);
              if (__pyx_t_18) {

                /* "sklearn/linear_model/cd_fast.pyx":869
 *                     XtA_axis1norm = nrm2(n_tasks, &XtA[0, 0] + ii * n_tasks, 1)
 *                     if XtA_axis1norm > dual_norm_XtA:
 *                         dual_norm_XtA = XtA_axis1norm             # <<<<<<<<<<<<<<
 * 
 *                 # TODO: use squared L2 norm directly
 */
                __pyx_v_dual_norm_XtA = __pyx_v_XtA_axis1norm;

                /* "sklearn/linear_model/cd_fast.pyx":868
 *                     # np.sqrt(np.sum(XtA ** 2, axis=1))
 *                     XtA_axis1norm = nrm2(n_tasks, &XtA[0, 0] + ii * n_tasks, 1)
 *                     if XtA_axis1norm > dual_norm_XtA:             # <<<<<<<<<<<<<<
 *                         dual_norm_XtA = XtA_axis1norm
 * 
 */
              }
            }

            /* "sklearn/linear_model/cd_fast.pyx":874
 *                 # R_norm = linalg.norm(R, ord='fro')
 *                 # w_norm = linalg.norm(W, ord='fro')
 *                 R_norm = nrm2(n_samples * n_tasks, &R[0, 0], 1)             # <<<<<<<<<<<<<<
 *                 w_norm = nrm2(n_features * n_tasks, W_ptr, 1)
 *                 if (dual_norm_XtA > l1_reg):
 */
            __pyx_t_51 = 0;
            __pyx_t_52 = 0;
            __pyx_v_R_norm = __pyx_v_nrm2((__pyx_v_n_samples * __pyx_v_n_tasks), (&(*((float *) ( /* dim=1 */ ((char *) (((float *) ( /* dim=0 */ (__pyx_v_R.data + __pyx_t_51 * __pyx_v_R.strides[0]) )) + __pyx_t_52)) )))), 1);

            /* "sklearn/linear_model/cd_fast.pyx":875
 *                 # w_norm = linalg.norm(W, ord='fro')
 *                 R_norm = nrm2(n_samples * n_tasks, &R[0, 0], 1)
 *                 w_norm = nrm2(n_features * n_tasks, W_ptr, 1)             # <<<<<<<<<<<<<<
 *                 if (dual_norm_XtA > l1_reg):
 *                     const =  l1_reg / dual_norm_XtA
 */
            __pyx_v_w_norm = __pyx_v_nrm2((__pyx_v_n_features * __pyx_v_n_tasks), __pyx_v_W_ptr, 1);

            /* "sklearn/linear_model/cd_fast.pyx":876
 *                 R_norm = nrm2(n_samples * n_tasks, &R[0, 0], 1)
 *                 w_norm = nrm2(n_features * n_tasks, W_ptr, 1)
 *                 if (dual_norm_XtA > l1_reg):             # <<<<<<<<<<<<<<
 *                     const =  l1_reg / dual_norm_XtA
 *                     A_norm = R_norm * const
 */
            __pyx_t_18 = ((__pyx_v_dual_norm_XtA > __pyx_v_l1_reg) != 0);
            if (__pyx_t_18) {

              /* "sklearn/linear_model/cd_fast.pyx":877
 *                 w_norm = nrm2(n_features * n_tasks, W_ptr, 1)
 *                 if (dual_norm_XtA > l1_reg):
 *                     const =  l1_reg / dual_norm_XtA             # <<<<<<<<<<<<<<
 *                     A_norm = R_norm * const
 *                     gap = 0.5 * (R_norm ** 2 + A_norm ** 2)
 */
              __pyx_v_const = (__pyx_v_l1_reg / __pyx_v_dual_norm_XtA);

              /* "sklearn/linear_model/cd_fast.pyx":878
 *                 if (dual_norm_XtA > l1_reg):
 *                     const =  l1_reg / dual_norm_XtA
 *                     A_norm = R_norm * const             # <<<<<<<<<<<<<<
 *                     gap = 0.5 * (R_norm ** 2 + A_norm ** 2)
 *                 else:
 */
              __pyx_v_A_norm = (__pyx_v_R_norm * __pyx_v_const);

              /* "sklearn/linear_model/cd_fast.pyx":879
 *                     const =  l1_reg / dual_norm_XtA
 *                     A_norm = R_norm * const
 *                     gap = 0.5 * (R_norm ** 2 + A_norm ** 2)             # <<<<<<<<<<<<<<
 *                 else:
 *                     const = 1.0
 */
              __pyx_v_gap = (0.5 * (powf(__pyx_v_R_norm, 2.0) + pow(__pyx_v_A_norm, 2.0)));

              /* "sklearn/linear_model/cd_fast.pyx":876
 *                 R_norm = nrm2(n_samples * n_tasks, &R[0, 0], 1)
 *                 w_norm = nrm2(n_features * n_tasks, W_ptr, 1)
 *                 if (dual_norm_XtA > l1_reg):             # <<<<<<<<<<<<<<
 *                     const =  l1_reg / dual_norm_XtA
 *                     A_norm = R_norm * const
 */
              goto __pyx_L36;
            }

            /* "sklearn/linear_model/cd_fast.pyx":881
 *                     gap = 0.5 * (R_norm ** 2 + A_norm ** 2)
 *                 else:
 *                     const = 1.0             # <<<<<<<<<<<<<<
 *                     gap = R_norm ** 2
 * 
 */
            /*else*/ {
              __pyx_v_const = 1.0;

              /* "sklearn/linear_model/cd_fast.pyx":882
 *                 else:
 *                     const = 1.0
 *                     gap = R_norm ** 2             # <<<<<<<<<<<<<<
 * 
 *                 # ry_sum = np.sum(R * y)
 */
              __pyx_v_gap = powf(__pyx_v_R_norm, 2.0);
            }
            __pyx_L36:;

            /* "sklearn/linear_model/cd_fast.pyx":885
 * 
 *                 # ry_sum = np.sum(R * y)
 *                 ry_sum = 0.0             # <<<<<<<<<<<<<<
 *                 for ii in range(n_samples):
 *                     for jj in range(n_tasks):
 */
            __pyx_v_ry_sum = 0.0;

            /* "sklearn/linear_model/cd_fast.pyx":886
 *                 # ry_sum = np.sum(R * y)
 *                 ry_sum = 0.0
 *                 for ii in range(n_samples):             # <<<<<<<<<<<<<<
 *                     for jj in range(n_tasks):
 *                         ry_sum += R[ii, jj] * Y[ii, jj]
 */
            __pyx_t_20 = __pyx_v_n_samples;
            for (__pyx_t_21 = 0; __pyx_t_21 < __pyx_t_20; __pyx_t_21+=1) {
              __pyx_v_ii = __pyx_t_21;

              /* "sklearn/linear_model/cd_fast.pyx":887
 *                 ry_sum = 0.0
 *                 for ii in range(n_samples):
 *                     for jj in range(n_tasks):             # <<<<<<<<<<<<<<
 *                         ry_sum += R[ii, jj] * Y[ii, jj]
 * 
 */
              __pyx_t_22 = __pyx_v_n_tasks;
              for (__pyx_t_42 = 0; __pyx_t_42 < __pyx_t_22; __pyx_t_42+=1) {
                __pyx_v_jj = __pyx_t_42;

                /* "sklearn/linear_model/cd_fast.pyx":888
 *                 for ii in range(n_samples):
 *                     for jj in range(n_tasks):
 *                         ry_sum += R[ii, jj] * Y[ii, jj]             # <<<<<<<<<<<<<<
 * 
 *                 # l21_norm = np.sqrt(np.sum(W ** 2, axis=0)).sum()
 */
                __pyx_t_53 = __pyx_v_ii;
                __pyx_t_54 = __pyx_v_jj;
                __pyx_t_55 = __pyx_v_ii;
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 *         tol = tol * nrm2(n_samples * n_tasks, Y_ptr, 1) ** 2
 * 
 *         for n_iter in range(max_iter):             # <<<<<<<<<<<<<<
 *             w_max = 0.0
 *             d_w_max = 0.0
 */
        __pyx_t_8 = __pyx_v_max_iter;
        for (__pyx_t_19 = 0; __pyx_t_19 < __pyx_t_8; __pyx_t_19+=1) {
          __pyx_v_n_iter = __pyx_t_19;

          /* "sklearn/linear_model/cd_fast.pyx":798
 * 
 *         for n_iter in range(max_iter):
 *             w_max = 0.0             # <<<<<<<<<<<<<<
 *             d_w_max = 0.0
 *             for f_iter in range(n_features):  # Loop over coordinates
 */
          __pyx_v_w_max = 0.0;

          /* "sklearn/linear_model/cd_fast.pyx":799
 *         for n_iter in range(max_iter):
 *             w_max = 0.0
 *             d_w_max = 0.0             # <<<<<<<<<<<<<<
 *             for f_iter in range(n_features):  # Loop over coordinates
 *                 if random:
 */
          __pyx_v_d_w_max = 0.0;

          /* "sklearn/linear_model/cd_fast.pyx":800
 *             w_max = 0.0
 *             d_w_max = 0.0
 *             for f_iter in range(n_features):  # Loop over coordinates             # <<<<<<<<<<<<<<
 *                 if random:
 *                     ii = rand_int(n_features, rand_r_state)
 */
          __pyx_t_20 = __pyx_v_n_features;
          for (__pyx_t_21 = 0; __pyx_t_21 < __pyx_t_20; __pyx_t_21+=1) {
            __pyx_v_f_iter = __pyx_t_21;

            /* "sklearn/linear_model/cd_fast.pyx":801
 *             d_w_max = 0.0
 *             for f_iter in range(n_features):  # Loop over coordinates
 *                 if random:             # <<<<<<<<<<<<<<
 *                     ii = rand_int(n_features, rand_r_state)
 *                 else:
 */
            __pyx_t_18 = (__pyx_v_random != 0);
            if (__pyx_t_18) {

              /* "sklearn/linear_model/cd_fast.pyx":802
 *             for f_iter in range(n_features):  # Loop over coordinates
 *                 if random:
 *                     ii = rand_int(n_features, rand_r_state)             # <<<<<<<<<<<<<<
 *                 else:
 *                     ii = f_iter
 */
              __pyx_v_ii = __pyx_f_7sklearn_12linear_model_7cd_fast_rand_int(__pyx_v_n_features, __pyx_v_rand_r_state);

              /* "sklearn/linear_model/cd_fast.pyx":801
 *             d_w_max = 0.0
 *             for f_iter in range(n_features):  # Loop over coordinates
 *                 if random:             # <<<<<<<<<<<<<<
 *                     ii = rand_int(n_features, rand_r_state)
 *                 else:
 */
              goto __pyx_L19;
            }

            /* "sklearn/linear_model/cd_fast.pyx":804
 *                     ii = rand_int(n_features, rand_r_state)
 *                 else:
 *                     ii = f_iter             # <<<<<<<<<<<<<<
 * 
 *                 if norm_cols_X[ii] == 0.0:
 */
            /*else*/ {
              __pyx_v_ii = __pyx_v_f_iter;
            }
            __pyx_L19:;

            /* "sklearn/linear_model/cd_fast.pyx":806
 *                     ii = f_iter
 * 
 *                 if norm_cols_X[ii] == 0.0:             # <<<<<<<<<<<<<<
 *                     continue
 * 
 */
            __pyx_t_30 = __pyx_v_ii;
            __pyx_t_18 = (((*((double *) ( /* dim=0 */ (__pyx_v_norm_cols_X.data + __pyx_t_30 * __pyx_v_norm_cols_X.strides[0]) ))) == 0.0) != 0);
            if (__pyx_t_18) {

              /* "sklearn/linear_model/cd_fast.pyx":807
 * 
 *                 if norm_cols_X[ii] == 0.0:
 *                     continue             # <<<<<<<<<<<<<<
 * 
 *                 # w_ii = W[:, ii] # Store previous value
 */
              goto __pyx_L17_continue;

              /* "sklearn/linear_model/cd_fast.pyx":806
 *                     ii = f_iter
 * 
 *                 if norm_cols_X[ii] == 0.0:             # <<<<<<<<<<<<<<
 *                     continue
 * 
 */
            }

            /* "sklearn/linear_model/cd_fast.pyx":810
 * 
 *                 # w_ii = W[:, ii] # Store previous value
 *                 copy(n_tasks, W_ptr + ii * n_tasks, 1, wii_ptr, 1)             # <<<<<<<<<<<<<<
 * 
 *                 # if np.sum(w_ii ** 2) != 0.0:  # can do better
 */
            __pyx_v_copy(__pyx_v_n_tasks, (__pyx_v_W_ptr + (__pyx_v_ii * __pyx_v_n_tasks)), 1, __pyx_v_wii_ptr, 1);

            /* "sklearn/linear_model/cd_fast.pyx":813
 * 
 *                 # if np.sum(w_ii ** 2) != 0.0:  # can do better
 *                 if nrm2(n_tasks, wii_ptr, 1) != 0.0:             # <<<<<<<<<<<<<<
 *                     # R += np.dot(X[:, ii][:, None], w_ii[None, :]) # rank 1 update
 *                     ger(CblasRowMajor, n_samples, n_tasks, 1.0,
 */
            __pyx_t_18 = ((__pyx_v_nrm2(__pyx_v_n_tasks, __pyx_v_wii_ptr, 1) != 0.0) != 0);
            if (__pyx_t_18) {

              /* "sklearn/linear_model/cd_fast.pyx":817
 *                     ger(CblasRowMajor, n_samples, n_tasks, 1.0,
 *                          X_ptr + ii * n_samples, 1,
 *                          wii_ptr, 1, &R[0, 0], n_tasks)             # <<<<<<<<<<<<<<
 * 
 *                 # tmp = np.dot(X[:, ii][None, :], R).ravel()
 */
              __pyx_t_31 = 0;
              __pyx_t_32 = 0;

              /* "sklearn/linear_model/cd_fast.pyx":815
 *                 if nrm2(n_tasks, wii_ptr, 1) != 0.0:
 *                     # R += np.dot(X[:, ii][:, None], w_ii[None, :]) # rank 1 update
 *                     ger(CblasRowMajor, n_samples, n_tasks, 1.0,             # <<<<<<<<<<<<<<
 *                          X_ptr + ii * n_samples, 1,
 *                          wii_ptr, 1, &R[0, 0], n_tasks)
 */
              __pyx_v_ger(CblasRowMajor, __pyx_v_n_samples, __pyx_v_n_tasks, 1.0, (__pyx_v_X_ptr + (__pyx_v_ii * __pyx_v_n_samples)), 1, __pyx_v_wii_ptr, 1, (&(*((double *) ( /* dim=1 */ ((char *) (((double *) ( /* dim=0 */ (__pyx_v_R.data + __pyx_t_31 * __pyx_v_R.strides[0]) )) + __pyx_t_32)) )))), __pyx_v_n_tasks);

              /* "sklearn/linear_model/cd_fast.pyx":813
 * 
 *                 # if np.sum(w_ii ** 2) != 0.0:  # can do better
 *                 if nrm2(n_tasks, wii_ptr, 1) != 0.0:             # <<<<<<<<<<<<<<
 *                     # R += np.dot(X[:, ii][:, None], w_ii[None, :]) # rank 1 update
 *                     ger(CblasRowMajor, n_samples, n_tasks, 1.0,
 */
            }

            /* "sklearn/linear_model/cd_fast.pyx":821
 *                 # tmp = np.dot(X[:, ii][None, :], R).ravel()
 *                 gemv(CblasRowMajor, CblasTrans,
 *                       n_samples, n_tasks, 1.0, &R[0, 0], n_tasks,             # <<<<<<<<<<<<<<
 *                       X_ptr + ii * n_samples, 1, 0.0, &tmp[0], 1)
 * 
 */
            __pyx_t_33 = 0;
            __pyx_t_34 = 0;

            /* "sklearn/linear_model/cd_fast.pyx":822
 *                 gemv(CblasRowMajor, CblasTrans,
 *                       n_samples, n_tasks, 1.0, &R[0, 0], n_tasks,
 *                       X_ptr + ii * n_samples, 1, 0.0, &tmp[0], 1)             # <<<<<<<<<<<<<<
 * 
 *                 # nn = sqrt(np.sum(tmp ** 2))
 */
            __pyx_t_35 = 0;

            /* "sklearn/linear_model/cd_fast.pyx":820
 * 
 *                 # tmp = np.dot(X[:, ii][None, :], R).ravel()
 *                 gemv(CblasRowMajor, CblasTrans,             # <<<<<<<<<<<<<<
 *                       n_samples, n_tasks, 1.0, &R[0, 0], n_tasks,
 *                       X_ptr + ii * n_samples, 1, 0.0, &tmp[0], 1)
 */
            __pyx_v_gemv(CblasRowMajor, CblasTrans, __pyx_v_n_samples, __pyx_v_n_tasks, 1.0, (&(*((double *) ( /* dim=1 */ ((char *) (((double *) ( /* dim=0 */ (__pyx_v_R.data + __pyx_t_33 * __pyx_v_R.strides[0]) )) + __pyx_t_34)) )))), __pyx_v_n_tasks, (__pyx_v_X_ptr + (__pyx_v_ii * __pyx_v_n_samples)), 1, 0.0, (&(*((double *) ( /* dim=0 */ ((char *) (((double *) __pyx_v_tmp.data) + __pyx_t_35)) )))), 1);

            /* "sklearn/linear_model/cd_fast.pyx":825
 * 
 *                 # nn = sqrt(np.sum(tmp ** 2))
 *                 nn = nrm2(n_tasks, &tmp[0], 1)             # <<<<<<<<<<<<<<
 * 
 *                 # W[:, ii] = tmp * fmax(1. - l1_reg / nn, 0) / (norm_cols_X[ii] + l2_reg)
 */
            __pyx_t_36 = 0;
            __pyx_v_nn = __pyx_v_nrm2(__pyx_v_n_tasks, (&(*((double *) ( /* dim=0 */ ((char *) (((double *) __pyx_v_tmp.data) + __pyx_t_36)) )))), 1);

            /* "sklearn/linear_model/cd_fast.pyx":828
 * 
 *                 # W[:, ii] = tmp * fmax(1. - l1_reg / nn, 0) / (norm_cols_X[ii] + l2_reg)
 *                 copy(n_tasks, &tmp[0], 1, W_ptr + ii * n_tasks, 1)             # <<<<<<<<<<<<<<
 *                 scal(n_tasks, fmax(1. - l1_reg / nn, 0) / (norm_cols_X[ii] + l2_reg),
 *                           W_ptr + ii * n_tasks, 1)
 */
            __pyx_t_37 = 0;
            __pyx_v_copy(__pyx_v_n_tasks, (&(*((double *) ( /* dim=0 */ ((char *) (((double *) __pyx_v_tmp.data) + __pyx_t_37)) )))), 1, (__pyx_v_W_ptr + (__pyx_v_ii * __pyx_v_n_tasks)), 1);

            /* "sklearn/linear_model/cd_fast.pyx":829
 *                 # W[:, ii] = tmp * fmax(1. - l1_reg / nn, 0) / (norm_cols_X[ii] + l2_reg)
 *                 copy(n_tasks, &tmp[0], 1, W_ptr + ii * n_tasks, 1)
 *                 scal(n_tasks, fmax(1. - l1_reg / nn, 0) / (norm_cols_X[ii] + l2_reg),             # <<<<<<<<<<<<<<
 *                           W_ptr + ii * n_tasks, 1)
 * 
 */
            __pyx_t_38 = __pyx_v_ii;

            /* "sklearn/linear_model/cd_fast.pyx":830
 *                 copy(n_tasks, &tmp[0], 1, W_ptr + ii * n_tasks, 1)
 *                 scal(n_tasks, fmax(1. - l1_reg / nn, 0) / (norm_cols_X[ii] + l2_reg),
 *                           W_ptr + ii * n_tasks, 1)             # <<<<<<<<<<<<<<
 * 
 *                 # if np.sum(W[:, ii] ** 2) != 0.0:  # can do better
 */
            __pyx_v_scal(__pyx_v_n_tasks, (__pyx_fuse_1__pyx_f_7sklearn_12linear_model_7cd_fast_fmax((1. - (__pyx_v_l1_reg / __pyx_v_nn)), 0.0) / ((*((double *) ( /* dim=0 */ (__pyx_v_norm_cols_X.data + __pyx_t_38 * __pyx_v_norm_cols_X.strides[0]) ))) + __pyx_v_l2_reg)), (__pyx_v_W_ptr + (__pyx_v_ii * __pyx_v_n_tasks)), 1);

            /* "sklearn/linear_model/cd_fast.pyx":833
 * 
 *                 # if np.sum(W[:, ii] ** 2) != 0.0:  # can do better
 *                 if nrm2(n_tasks, W_ptr + ii * n_tasks, 1) != 0.0:             # <<<<<<<<<<<<<<
 *                     # R -= np.dot(X[:, ii][:, None], W[:, ii][None, :])
 *                     # Update residual : rank 1 update
 */
            __pyx_t_18 = ((__pyx_v_nrm2(__pyx_v_n_tasks, (__pyx_v_W_ptr + (__pyx_v_ii * __pyx_v_n_tasks)), 1) != 0.0) != 0);
            if (__pyx_t_18) {

              /* "sklearn/linear_model/cd_fast.pyx":838
 *                     ger(CblasRowMajor, n_samples, n_tasks, -1.0,
 *                          X_ptr + ii * n_samples, 1, W_ptr + ii * n_tasks, 1,
 *                          &R[0, 0], n_tasks)             # <<<<<<<<<<<<<<
 * 
 *                 # update the maximum absolute coefficient update
 */
              __pyx_t_39 = 0;
              __pyx_t_40 = 0;

              /* "sklearn/linear_model/cd_fast.pyx":836
 *                     # R -= np.dot(X[:, ii][:, None], W[:, ii][None, :])
 *                     # Update residual : rank 1 update
 *                     ger(CblasRowMajor, n_samples, n_tasks, -1.0,             # <<<<<<<<<<<<<<
 *                          X_ptr + ii * n_samples, 1, W_ptr + ii * n_tasks, 1,
 *                          &R[0, 0], n_tasks)
 */
              __pyx_v_ger(CblasRowMajor, __pyx_v_n_samples, __pyx_v_n_tasks, -1.0, (__pyx_v_X_ptr + (__pyx_v_ii * __pyx_v_n_samples)), 1, (__pyx_v_W_ptr + (__pyx_v_ii * __pyx_v_n_tasks)), 1, (&(*((double *) ( /* dim=1 */ ((char *) (((double *) ( /* dim=0 */ (__pyx_v_R.data + __pyx_t_39 * __pyx_v_R.strides[0]) )) + __pyx_t_40)) )))), __pyx_v_n_tasks);

              /* "sklearn/linear_model/cd_fast.pyx":833
 * 
 *                 # if np.sum(W[:, ii] ** 2) != 0.0:  # can do better
 *                 if nrm2(n_tasks, W_ptr + ii * n_tasks, 1) != 0.0:             # <<<<<<<<<<<<<<
 *                     # R -= np.dot(X[:, ii][:, None], W[:, ii][None, :])
 *                     # Update residual : rank 1 update
 */
            }

            /* "sklearn/linear_model/cd_fast.pyx":841
 * 
 *                 # update the maximum absolute coefficient update
 *                 d_w_ii = diff_abs_max(n_tasks, W_ptr + ii * n_tasks, wii_ptr)             # <<<<<<<<<<<<<<
 * 
 *                 if d_w_ii > d_w_max:
 */
            __pyx_v_d_w_ii = __pyx_fuse_1__pyx_f_7sklearn_12linear_model_7cd_fast_diff_abs_max(__pyx_v_n_tasks, (__pyx_v_W_ptr + (__pyx_v_ii * __pyx_v_n_tasks)), __pyx_v_wii_ptr);

            /* "sklearn/linear_model/cd_fast.pyx":843
 *                 d_w_ii = diff_abs_max(n_tasks, W_ptr + ii * n_tasks, wii_ptr)
 * 
 *                 if d_w_ii > d_w_max:             # <<<<<<<<<<<<<<
 *                     d_w_max = d_w_ii
 * 
 */
            __pyx_t_18 = ((__pyx_v_d_w_ii > __pyx_v_d_w_max) != 0);
            if (__pyx_t_18) {

              /* "sklearn/linear_model/cd_fast.pyx":844
 * 
 *                 if d_w_ii > d_w_max:
 *                     d_w_max = d_w_ii             # <<<<<<<<<<<<<<
 * 
 *                 W_ii_abs_max = abs_max(n_tasks, W_ptr + ii * n_tasks)
 */
              __pyx_v_d_w_max = __pyx_v_d_w_ii;

              /* "sklearn/linear_model/cd_fast.pyx":843
 *                 d_w_ii = diff_abs_max(n_tasks, W_ptr + ii * n_tasks, wii_ptr)
 * 
 *                 if d_w_ii > d_w_max:             # <<<<<<<<<<<<<<
 *                     d_w_max = d_w_ii
 * 
 */
            }

            /* "sklearn/linear_model/cd_fast.pyx":846
 *                     d_w_max = d_w_ii
 * 
 *                 W_ii_abs_max = abs_max(n_tasks, W_ptr + ii * n_tasks)             # <<<<<<<<<<<<<<
 *                 if W_ii_abs_max > w_max:
 *                     w_max = W_ii_abs_max
 */
            __pyx_v_W_ii_abs_max = __pyx_fuse_1__pyx_f_7sklearn_12linear_model_7cd_fast_abs_max(__pyx_v_n_tasks, (__pyx_v_W_ptr + (__pyx_v_ii * __pyx_v_n_tasks)));

            /* "sklearn/linear_model/cd_fast.pyx":847
 * 
 *                 W_ii_abs_max = abs_max(n_tasks, W_ptr + ii * n_tasks)
 *                 if W_ii_abs_max > w_max:             # <<<<<<<<<<<<<<
 *                     w_max = W_ii_abs_max
 * 
 */
            __pyx_t_18 = ((__pyx_v_W_ii_abs_max > __pyx_v_w_max) != 0);
            if (__pyx_t_18) {

              /* "sklearn/linear_model/cd_fast.pyx":848
 *                 W_ii_abs_max = abs_max(n_tasks, W_ptr + ii * n_tasks)
 *                 if W_ii_abs_max > w_max:
 *                     w_max = W_ii_abs_max             # <<<<<<<<<<<<<<
 * 
 *             if w_max == 0.0 or d_w_max / w_max < d_w_tol or n_iter == max_iter - 1:
 */
              __pyx_v_w_max = __pyx_v_W_ii_abs_max;

              /* "sklearn/linear_model/cd_fast.pyx":847
 * 
 *                 W_ii_abs_max = abs_max(n_tasks, W_ptr + ii * n_tasks)
 *                 if W_ii_abs_max > w_max:             # <<<<<<<<<<<<<<
 *                     w_max = W_ii_abs_max
 * 
 */
            }
            __pyx_L17_continue:;
          }

          /* "sklearn/linear_model/cd_fast.pyx":850
 *                     w_max = W_ii_abs_max
 * 
 *             if w_max == 0.0 or d_w_max / w_max < d_w_tol or n_iter == max_iter - 1:             # <<<<<<<<<<<<<<
 *                 # the biggest coordinate update of this iteration was smaller than
 *                 # the tolerance: check the duality gap as ultimate stopping
 */
          __pyx_t_41 = ((__pyx_v_w_max == 0.0) != 0);
          if (!__pyx_t_41) {
          } else {
            __pyx_t_18 = __pyx_t_41;
            goto __pyx_L26_bool_binop_done;
          }
          __pyx_t_41 = (((__pyx_v_d_w_max / __pyx_v_w_max) < __pyx_v_d_w_tol) != 0);
          if (!__pyx_t_41) {
          } else {
            __pyx_t_18 = __pyx_t_41;
            goto __pyx_L26_bool_binop_done;
          }
          __pyx_t_41 = ((__pyx_v_n_iter == (__pyx_v_max_iter - 1)) != 0);
          __pyx_t_18 = __pyx_t_41;
          __pyx_L26_bool_binop_done:;
          if (__pyx_t_18) {

            /* "sklearn/linear_model/cd_fast.pyx":856
 * 
 *                 # XtA = np.dot(X.T, R) - l2_reg * W.T
 *                 for ii in range(n_features):             # <<<<<<<<<<<<<<
 *                     for jj in range(n_tasks):
 *                         XtA[ii, jj] = dot(
 */
            __pyx_t_20 = __pyx_v_n_features;
            for (__pyx_t_21 = 0; __pyx_t_21 < __pyx_t_20; __pyx_t_21+=1) {
              __pyx_v_ii = __pyx_t_21;

              /* "sklearn/linear_model/cd_fast.pyx":857
 *                 # XtA = np.dot(X.T, R) - l2_reg * W.T
 *                 for ii in range(n_features):
 *                     for jj in range(n_tasks):             # <<<<<<<<<<<<<<
 *                         XtA[ii, jj] = dot(
 *                             n_samples, X_ptr + ii * n_samples, 1,
 */
              __pyx_t_22 = __pyx_v_n_tasks;
              for (__pyx_t_42 = 0; __pyx_t_42 < __pyx_t_22; __pyx_t_42+=1) {
                __pyx_v_jj = __pyx_t_42;

                /* "sklearn/linear_model/cd_fast.pyx":860
 *                         XtA[ii, jj] = dot(
 *                             n_samples, X_ptr + ii * n_samples, 1,
 *                             &R[0, 0] + jj, n_tasks             # <<<<<<<<<<<<<<
 *                             ) - l2_reg * W[jj, ii]
 * 
 */
                __pyx_t_43 = 0;
                __pyx_t_44 = 0;

                /* "sklearn/linear_model/cd_fast.pyx":861
 *                             n_samples, X_ptr + ii * n_samples, 1,
 *                             &R[0, 0] + jj, n_tasks
 *                             ) - l2_reg * W[jj, ii]             # <<<<<<<<<<<<<<
 * 
 *                 # dual_norm_XtA = np.max(np.sqrt(np.sum(XtA ** 2, axis=1)))
 */
                __pyx_t_45 = __pyx_v_jj;
                __pyx_t_46 = __pyx_v_ii;

                /* "sklearn/linear_model/cd_fast.pyx":858
 *                 for ii in range(n_features):
 *                     for jj in range(n_tasks):
 *                         XtA[ii, jj] = dot(             # <<<<<<<<<<<<<<
 *                             n_samples, X_ptr + ii * n_samples, 1,
 *                             &R[0, 0] + jj, n_tasks
 */
                __pyx_t_47 = __pyx_v_ii;
                __pyx_t_48 = __pyx_v_jj;
                *((double *) ( /* dim=1 */ ((char *) (((double *) ( /* dim=0 */ (__pyx_v_XtA.data + __pyx_t_47 * __pyx_v_XtA.strides[0]) )) + __pyx_t_48)) )) = (__pyx_v_dot(__pyx_v_n_samples, (__pyx_v_X_ptr + (__pyx_v_ii * __pyx_v_n_samples)), 1, ((&(*((double *) ( /* dim=1 */ ((char *) (((double *) ( /* dim=0 */ (__pyx_v_R.data + __pyx_t_43 * __pyx_v_R.strides[0]) )) + __pyx_t_44)) )))) + __pyx_v_jj), __pyx_v_n_tasks) - (__pyx_v_l2_reg * (*((double *) ( /* dim=1 */ (( /* dim=0 */ ((char *) (((double *) __pyx_v_W.data) + __pyx_t_45)) ) + __pyx_t_46 * __pyx_v_W.strides[1]) )))));
              }
            }

            /* "sklearn/linear_model/cd_fast.pyx":864
 * 
 *                 # dual_norm_XtA = np.max(np.sqrt(np.sum(XtA ** 2, axis=1)))
 *                 dual_norm_XtA = 0.0             # <<<<<<<<<<<<<<
 *                 for ii in range(n_features):
 *                     # np.sqrt(np.sum(XtA ** 2, axis=1))
 */
            __pyx_v_dual_norm_XtA = 0.0;

            /* "sklearn/linear_model/cd_fast.pyx":865
 *                 # dual_norm_XtA = np.max(np.sqrt(np.sum(XtA ** 2, axis=1)))
 *                 dual_norm_XtA = 0.0
 *                 for ii in range(n_features):             # <<<<<<<<<<<<<<
 *                     # np.sqrt(np.sum(XtA ** 2, axis=1))
 *                     XtA_axis1norm = nrm2(n_tasks, &XtA[0, 0] + ii * n_tasks, 1)
 */
            __pyx_t_20 = __pyx_v_n_features;
            for (__pyx_t_21 = 0; __pyx_t_21 < __pyx_t_20; __pyx_t_21+=1) {
              __pyx_v_ii = __pyx_t_21;

              /* "sklearn/linear_model/cd_fast.pyx":867
 *                 for ii in range(n_features):
 *                     # np.sqrt(np.sum(XtA ** 2, axis=1))
 *                     XtA_axis1norm = nrm2(n_tasks, &XtA[0, 0] + ii * n_tasks, 1)             # <<<<<<<<<<<<<<
 *                     if XtA_axis1norm > dual_norm_XtA:
 *                         dual_norm_XtA = XtA_axis1norm
 */
              __pyx_t_49 = 0;
              __pyx_t_50 = 0;
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 * 
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 *         Py_ssize_t shape, Py_ssize_t stride, Py_ssize_t suboffset,
 */

static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *__pyx_v_dst, Py_ssize_t __pyx_v_shape, Py_ssize_t __pyx_v_stride, Py_ssize_t __pyx_v_suboffset, int __pyx_v_dim, int __pyx_v_new_ndim, int *__pyx_v_suboffset_dim, Py_ssize_t __pyx_v_start, Py_ssize_t __pyx_v_stop, Py_ssize_t __pyx_v_step, int __pyx_v_have_start, int __pyx_v_have_stop, int __pyx_v_have_step, int __pyx_v_is_slice) {
  Py_ssize_t __pyx_v_new_shape;
  int __pyx_v_negative_step;
  int __pyx_r;
  int __pyx_t_1;
  int __pyx_t_2;
  int __pyx_t_3;

  /* "View.MemoryView":815
 *     cdef bint negative_step
 * 
 *     if not is_slice:             # <<<<<<<<<<<<<<
 * 
 *         if start < 0:
 */
  __pyx_t_1 = ((!(__pyx_v_is_slice != 0)) != 0);
  if (__pyx_t_1) {

    /* "View.MemoryView":817
 *     if not is_slice:
 * 
 *         if start < 0:             # <<<<<<<<<<<<<<
 *             start += shape
 *         if not 0 <= start < shape:
 */
    __pyx_t_1 = ((__pyx_v_start < 0) != 0);
    if (__pyx_t_1) {

      /* "View.MemoryView":818
 * 
 *         if start < 0:
 *             start += shape             # <<<<<<<<<<<<<<
 *         if not 0 <= start < shape:
 *             _err_dim(IndexError, "Index out of bounds (axis %d)", dim)
 */
      __pyx_v_start = (__pyx_v_start + __pyx_v_shape);

      /* "View.MemoryView":817
 *     if not is_slice:
 * 
 *         if start < 0:             # <<<<<<<<<<<<<<
 *             start += shape
 *         if not 0 <= start < shape:
 */
    }

    /* "View.MemoryView":819
 *         if start < 0:
 *             start += shape
 *         if not 0 <= start < shape:             # <<<<<<<<<<<<<<
 *             _err_dim(IndexError, "Index out of bounds (axis %d)", dim)
 *     else:
 */
    __pyx_t_1 = (0 <= __pyx_v_start);
    if (__pyx_t_1) {
      __pyx_t_1 = (__pyx_v_start < __pyx_v_shape);
    }
    __pyx_t_2 = ((!(__pyx_t_1 != 0)) != 0);
    if (__pyx_t_2) {

      /* "View.MemoryView":820
 *             start += shape
 *         if not 0 <= start < shape:
 *             _err_dim(IndexError, "Index out of bounds (axis %d)", dim)             # <<<<<<<<<<<<<<
 *     else:
 * 
 */
      __pyx_t_3 = __pyx_memoryview_err_dim(__pyx_builtin_IndexError, ((char *)"Index out of bounds (axis %d)"), __pyx_v_dim); if (unlikely(__pyx_t_3 == -1)) __PYX_ERR(2, 820, __pyx_L1_error)

      /* "View.MemoryView":819
 *         if start < 0:
 *             start += shape
 *         if not 0 <= start < shape:             # <<<<<<<<<<<<<<
 *             _err_dim(IndexError, "Index out of bounds (axis %d)", dim)
 *     else:
 */
    }

    /* "View.MemoryView":815
 *     cdef bint negative_step
 * 
 *     if not is_slice:             # <<<<<<<<<<<<<<
 * 
 *         if start < 0:
 */
    goto __pyx_L3;
  }

  /* "View.MemoryView":823
 *     else:
 * 
 *         negative_step = have_step != 0 and step < 0             # <<<<<<<<<<<<<<
 * 
 *         if have_step and step == 0:
 */
  /*else*/ {
    __pyx_t_1 = ((__pyx_v_have_step != 0) != 0);
    if (__pyx_t_1) {
    } else {
      __pyx_t_2 = __pyx_t_1;
      goto __pyx_L6_bool_binop_done;
    }
    __pyx_t_1 = ((__pyx_v_step < 0) != 0);
    __pyx_t_2 = __pyx_t_1;
    __pyx_L6_bool_binop_done:;
    __pyx_v_negative_step = __pyx_t_2;

    /* "View.MemoryView":825
 *         negative_step = have_step != 0 and step < 0
 * 
 *         if have_step and step == 0:             # <<<<<<<<<<<<<<
 *             _err_dim(ValueError, "Step may not be zero (axis %d)", dim)
 * 
 */
    __pyx_t_1 = (__pyx_v_have_step != 0);
    if (__pyx_t_1) {
    } else {
      __pyx_t_2 = __pyx_t_1;
      goto __pyx_L9_bool_binop_done;
    }
    __pyx_t_1 = ((__pyx_v_step == 0) != 0);
    __pyx_t_2 = __pyx_t_1;
    __pyx_L9_bool_binop_done:;
    if (__pyx_t_2) {

      /* "View.MemoryView":826
 * 
 *         if have_step and step == 0:
 *             _err_dim(ValueError, "Step may not be zero (axis %d)", dim)             # <<<<<<<<<<<<<<
 * 
 * 
 */
      __pyx_t_3 = __pyx_memoryview_err_dim(__pyx_builtin_ValueError, ((char *)"Step may not be zero (axis %d)"), __pyx_v_dim); if (unlikely(__pyx_t_3 == -1)) __PYX_ERR(2, 826, __pyx_L1_error)

      /* "View.MemoryView":825
 *         negative_step = have_step != 0 and step < 0
 * 
 *         if have_step and step == 0:             # <<<<<<<<<<<<<<
 *             _err_dim(ValueError, "Step may not be zero (axis %d)", dim)
 * 
 */
    }

    /* "View.MemoryView":829
 * 
 * 
 *         if have_start:             # <<<<<<<<<<<<<<
 *             if start < 0:
 *                 start += shape
 */
    __pyx_t_2 = (__pyx_v_have_start != 0);
    if (__pyx_t_2) {

      /* "View.MemoryView":830
 * 
 *         if have_start:
 *             if start < 0:             # <<<<<<<<<<<<<<
 *                 start += shape
 *                 if start < 0:
 */
      __pyx_t_2 = ((__pyx_v_start < 0) != 0);
      if (__pyx_t_2) {

        /* "View.MemoryView":831
 *         if have_start:
 *             if start < 0:
 *                 start += shape             # <<<<<<<<<<<<<<
 *                 if start < 0:
 *                     start = 0
 */
        __pyx_v_start = (__pyx_v_start + __pyx_v_shape);

        /* "View.MemoryView":832
 *             if start < 0:
 *                 start += shape
 *                 if start < 0:             # <<<<<<<<<<<<<<
 *                     start = 0
 *             elif start >= shape:
 */
        __pyx_t_2 = ((__pyx_v_start < 0) != 0);
        if (__pyx_t_2) {

          /* "View.MemoryView":833
 *                 start += shape
 *                 if start < 0:
 *                     start = 0             # <<<<<<<<<<<<<<
 *             elif start >= shape:
 *                 if negative_step:
 */
          __pyx_v_start = 0;

          /* "View.MemoryView":832
 *             if start < 0:
 *                 start += shape
 *                 if start < 0:             # <<<<<<<<<<<<<<
 *                     start = 0
 *             elif start >= shape:
 */
        }

        /* "View.MemoryView":830
 * 
 *         if have_start:
 *             if start < 0:             # <<<<<<<<<<<<<<
 *                 start += shape
 *                 if start < 0:
 */
        goto __pyx_L12;
      }

      /* "View.MemoryView":834
 *                 if start < 0:
 *                     start = 0
 *             elif start >= shape:             # <<<<<<<<<<<<<<
 *                 if negative_step:
 *                     start = shape - 1
 */
      __pyx_t_2 = ((__pyx_v_start >= __pyx_v_shape) != 0);
      if (__pyx_t_2) {

        /* "View.MemoryView":835
 *                     start = 0
 *             elif start >= shape:
 *                 if negative_step:             # <<<<<<<<<<<<<<
 *                     start = shape - 1
 *                 else:
 */
        __pyx_t_2 = (__pyx_v_negative_step != 0);
        if (__pyx_t_2) {

          /* "View.MemoryView":836
 *             elif start >= shape:
 *                 if negative_step:
 *                     start = shape - 1             # <<<<<<<<<<<<<<
 *                 else:
 *                     start = shape
 */
          __pyx_v_start = (__pyx_v_shape - 1);

          /* "View.MemoryView":835
 *                     start = 0
 *             elif start >= shape:
 *                 if negative_step:             # <<<<<<<<<<<<<<
 *                     start = shape - 1
 *                 else:
 */
          goto __pyx_L14;
        }

        /* "View.MemoryView":838
 *                     start = shape - 1
 *                 else:
 *                     start = shape             # <<<<<<<<<<<<<<
 *         else:
 *             if negative_step:
 */
        /*else*/ {
          __pyx_v_start = __pyx_v_shape;
        }
        __pyx_L14:;

        /* "View.MemoryView":834
 *                 if start < 0:
 *                     start = 0
 *             elif start >= shape:             # <<<<<<<<<<<<<<
 *                 if negative_step:
 *                     start = shape - 1
 */
      }
      __pyx_L12:;

      /* "View.MemoryView":829
 * 
 * 
 *         if have_start:             # <<<<<<<<<<<<<<
 *             if start < 0:
 *                 start += shape
 */
      goto __pyx_L11;
    }

    /* "View.MemoryView":840
 *                     start = shape
 *         else:
 *             if negative_step:             # <<<<<<<<<<<<<<
 *                 start = shape - 1
 *             else:
 */
    /*else*/ {
      __pyx_t_2 = (__pyx_v_negative_step != 0);
      if (__pyx_t_2) {

        /* "View.MemoryView":841
 *         else:
 *             if negative_step:
 *                 start = shape - 1             # <<<<<<<<<<<<<<
 *             else:
 *                 start = 0
 */
        __pyx_v_start = (__pyx_v_shape - 1);

        /* "View.MemoryView":840
 *                     start = shape
 *         else:
 *             if negative_step:             # <<<<<<<<<<<<<<
 *                 start = shape - 1
 *             else:
 */
        goto __pyx_L15;
      }

      /* "View.MemoryView":843
 *                 start = shape - 1
 *             else:
 *                 start = 0             # <<<<<<<<<<<<<<
 * 
 *         if have_stop:
 */
      /*else*/ {
        __pyx_v_start = 0;
      }
      __pyx_L15:;
    }
    __pyx_L11:;

    /* "View.MemoryView":845
 *                 start = 0
 * 
 *         if have_stop:             # <<<<<<<<<<<<<<
 *             if stop < 0:
 *                 stop += shape
 */
    __pyx_t_2 = (__pyx_v_have_stop != 0);
    if (__pyx_t_2) {

      /* "View.MemoryView":846
 * 
 *         if have_stop:
 *             if stop < 0:             # <<<<<<<<<<<<<<
 *                 stop += shape
 *                 if stop < 0:
 */
      __pyx_t_2 = ((__pyx_v_stop < 0) != 0);
      if (__pyx_t_2) {

        /* "View.MemoryView":847
 *         if have_stop:
 *             if stop < 0:
 *                 stop += shape             # <<<<<<<<<<<<<<
 *                 if stop < 0:
 *                     stop = 0
 */
        __pyx_v_stop = (__pyx_v_stop + __pyx_v_shape);

        /* "View.MemoryView":848
 *             if stop < 0:
 *                 stop += shape
 *                 if stop < 0:             # <<<<<<<<<<<<<<
 *                     stop = 0
 *             elif stop > shape:
 */
        __pyx_t_2 = ((__pyx_v_stop < 0) != 0);
        if (__pyx_t_2) {

          /* "View.MemoryView":849
 *                 stop += shape
 *                 if stop < 0:
 *                     stop = 0             # <<<<<<<<<<<<<<
 *             elif stop > shape:
 *                 stop = shape
 */
          __pyx_v_stop = 0;

          /* "View.MemoryView":848
 *             if stop < 0:
 *                 stop += shape
 *                 if stop < 0:             # <<<<<<<<<<<<<<
 *                     stop = 0
 *             elif stop > shape:
 */
        }

        /* "View.MemoryView":846
 * 
 *         if have_stop:
 *             if stop < 0:             # <<<<<<<<<<<<<<
 *                 stop += shape
 *                 if stop < 0:
 */
        goto __pyx_L17;
      }

      /* "View.MemoryView":850
 *                 if stop < 0:
 *                     stop = 0
 *             elif stop > shape:             # <<<<<<<<<<<<<<
 *                 stop = shape
 *         else:
 */
      __pyx_t_2 = ((__pyx_v_stop > __pyx_v_shape) != 0);
      if (__pyx_t_2) {

        /* "View.MemoryView":851
 *                     stop = 0
 *             elif stop > shape:
 *                 stop = shape             # <<<<<<<<<<<<<<
 *         else:
 *             if negative_step:
 */
        __pyx_v_stop = __pyx_v_shape;

        /* "View.MemoryView":850
 *                 if stop < 0:
 *                     stop = 0
 *             elif stop > shape:             # <<<<<<<<<<<<<<
 *                 stop = shape
 *         else:
 */
      }
      __pyx_L17:;

      /* "View.MemoryView":845
 *                 start = 0
 * 
 *         if have_stop:             # <<<<<<<<<<<<<<
 *             if stop < 0:
 *                 stop += shape
 */
      goto __pyx_L16;
    }

    /* "View.MemoryView":853
 *                 stop = shape
 *         else:
 *             if negative_step:             # <<<<<<<<<<<<<<
 *                 stop = -1
 *             else:
 */
    /*else*/ {
      __pyx_t_2 = (__pyx_v_negative_step != 0);
      if (__pyx_t_2) {

        /* "View.MemoryView":854
 *         else:
 *             if negative_step:
 *                 stop = -1             # <<<<<<<<<<<<<<
 *             else:
 *                 stop = shape
 */
        __pyx_v_stop = -1L;

        /* "View.MemoryView":853
 *                 stop = shape
 *         else:
 *             if negative_step:             # <<<<<<<<<<<<<<
 *                 stop = -1
 *             else:
 */
        goto __pyx_L19;
      }

      /* "View.MemoryView":856
 *                 stop = -1
 *             else:
 *                 stop = shape             # <<<<<<<<<<<<<<
 * 
 *         if not have_step:
 */
      /*else*/ {
        __pyx_v_stop = __pyx_v_shape;
      }
      __pyx_L19:;
    }
    __pyx_L16:;

    /* "View.MemoryView":858
 *                 stop = shape
 * 
 *         if not have_step:             # <<<<<<<<<<<<<<
 *             step = 1
 * 
 */
    __pyx_t_2 = ((!(__pyx_v_have_step != 0)) != 0);
    if (__pyx_t_2) {

      /* "View.MemoryView":859
 * 
 *         if not have_step:
 *             step = 1             # <<<<<<<<<<<<<<
 * 
 * 
 */
      __pyx_v_step = 1;

      /* "View.MemoryView":858
 *                 stop = shape
 * 
 *         if not have_step:             # <<<<<<<<<<<<<<
 *             step = 1
 * 
 */
    }

    /* "View.MemoryView":863
 * 
 *         with cython.cdivision(True):
 *             new_shape = (stop - start) // step             # <<<<<<<<<<<<<<
 * 
 *             if (stop - start) - step * new_shape:
 */
    __pyx_v_new_shape = ((__pyx_v_stop - __pyx_v_start) / __pyx_v_step);

    /* "View.MemoryView":865
 *             new_shape = (stop - start) // step
 * 
 *             if (stop - start) - step * new_shape:             # <<<<<<<<<<<<<<
 *                 new_shape += 1
 * 
 */
    __pyx_t_2 = (((__pyx_v_stop - __pyx_v_start) - (__pyx_v_step * __pyx_v_new_shape)) != 0);
    if (__pyx_t_2) {

      /* "View.MemoryView":866
 * 
 *             if (stop - start) - step * new_shape:
 *                 new_shape += 1             # <<<<<<<<<<<<<<
 * 
 *         if new_shape < 0:
 */
      __pyx_v_new_shape = (__pyx_v_new_shape + 1);

      /* "View.MemoryView":865
 *             new_shape = (stop - start) // step
 * 
 *             if (stop - start) - step * new_shape:             # <<<<<<<<<<<<<<
 *                 new_shape += 1
 * 
 */
    }

    /* "View.MemoryView":868
 *                 new_shape += 1
 * 
 *         if new_shape < 0:             # <<<<<<<<<<<<<<
 *             new_shape = 0
 * 
 */
    __pyx_t_2 = ((__pyx_v_new_shape < 0) != 0);
    if (__pyx_t_2) {

      /* "View.MemoryView":869
 * 
 *         if new_shape < 0:
 *             new_shape = 0             # <<<<<<<<<<<<<<
 * 
 * 
 */
      __pyx_v_new_shape = 0;

      /* "View.MemoryView":868
 *                 new_shape += 1
 * 
 *         if new_shape < 0:             # <<<<<<<<<<<<<<
 *             new_shape = 0
 * 
 */
    }

    /* "View.MemoryView":872
 * 
 * 
 *         dst.strides[new_ndim] = stride * step             # <<<<<<<<<<<<<<
 *         dst.shape[new_ndim] = new_shape
 *         dst.suboffsets[new_ndim] = suboffset
 */
    (__pyx_v_dst->strides[__pyx_v_new_ndim]) = (__pyx_v_stride * __pyx_v_step);

    /* "View.MemoryView":873
 * 
 *         dst.strides[new_ndim] = stride * step
 *         dst.shape[new_ndim] = new_shape             # <<<<<<<<<<<<<<
 *         dst.suboffsets[new_ndim] = suboffset
 * 
 */
    (__pyx_v_dst->shape[__pyx_v_new_ndim]) = __pyx_v_new_shape;

    /* "View.MemoryView":874
 *         dst.strides[new_ndim] = stride * step
 *         dst.shape[new_ndim] = new_shape
 *         dst.suboffsets[new_ndim] = suboffset             # <<<<<<<<<<<<<<
 * 
 * 
 */
    (__pyx_v_dst->suboffsets[__pyx_v_new_ndim]) = __pyx_v_suboffset;
  }
  __pyx_L3:;

  /* "View.MemoryView":877
 * 
 * 
 *     if suboffset_dim[0] < 0:             # <<<<<<<<<<<<<<
 *         dst.data += start * stride
 *     else:
 */
  __pyx_t_2 = (((__pyx_v_suboffset_dim[0]) < 0) != 0);
  if (__pyx_t_2) {

    /* "View.MemoryView":878
 * 
 *     if suboffset_dim[0] < 0:
 *         dst.data += start * stride             # <<<<<<<<<<<<<<
 *     else:
 *         dst.suboffsets[suboffset_dim[0]] += start * stride
 */
    __pyx_v_dst->data = (__pyx_v_dst->data + (__pyx_v_start * __pyx_v_stride));

    /* "View.MemoryView":877
 * 
 * 
 *     if suboffset_dim[0] < 0:             # <<<<<<<<<<<<<<
 *         dst.data += start * stride
 *     else:
 */
    goto __pyx_L23;
  }

  /* "View.MemoryView":880
 *         dst.data += start * stride
 *     else:
 *         dst.suboffsets[suboffset_dim[0]] += start * stride             # <<<<<<<<<<<<<<
 * 
 *     if suboffset >= 0:
 */
  /*else*/ {
    __pyx_t_3 = (__pyx_v_suboffset_dim[0]);
    (__pyx_v_dst->suboffsets[__pyx_t_3]) = ((__pyx_v_dst->suboffsets[__pyx_t_3]) + (__pyx_v_start * __pyx_v_stride));
  }
  __pyx_L23:;

  /* "View.MemoryView":882
 *         dst.suboffsets[suboffset_dim[0]] += start * stride
 * 
 *     if suboffset >= 0:             # <<<<<<<<<<<<<<
 *         if not is_slice:
 *             if new_ndim == 0:
 */
  __pyx_t_2 = ((__pyx_v_suboffset >= 0) != 0);
  if (__pyx_t_2) {

    /* "View.MemoryView":883
 * 
 *     if suboffset >= 0:
 *         if not is_slice:             # <<<<<<<<<<<<<<
 *             if new_ndim == 0:
 *                 dst.data = (<char **> dst.data)[0] + suboffset
 */
    __pyx_t_2 = ((!(__pyx_v_is_slice != 0)) != 0);
    if (__pyx_t_2) {

      /* "View.MemoryView":884
 *     if suboffset >= 0:
 *         if not is_slice:
 *             if new_ndim == 0:             # <<<<<<<<<<<<<<
 *                 dst.data = (<char **> dst.data)[0] + suboffset
 *             else:
 */
      __pyx_t_2 = ((__pyx_v_new_ndim == 0) != 0);
      if (__pyx_t_2) {

        /* "View.MemoryView":885
 *         if not is_slice:
 *             if new_ndim == 0:
 *                 dst.data = (<char **> dst.data)[0] + suboffset             # <<<<<<<<<<<<<<
 *             else:
 *                 _err_dim(IndexError, "All dimensions preceding dimension %d "
 */
        __pyx_v_dst->data = ((((char **)__pyx_v_dst->data)[0]) + __pyx_v_suboffset);

        /* "View.MemoryView":884
 *     if suboffset >= 0:
 *         if not is_slice:
 *             if new_ndim == 0:             # <<<<<<<<<<<<<<
 *                 dst.data = (<char **> dst.data)[0] + suboffset
 *             else:
 */
        goto __pyx_L26;
      }

      /* "View.MemoryView":887
 *                 dst.data = (<char **> dst.data)[0] + suboffset
 *             else:
 *                 _err_dim(IndexError, "All dimensions preceding dimension %d "             # <<<<<<<<<<<<<<
 *                                      "must be indexed and not sliced", dim)
 *         else:
 */
      /*else*/ {

        /* "View.MemoryView":888
 *             else:
 *                 _err_dim(IndexError, "All dimensions preceding dimension %d "
 *                                      "must be indexed and not sliced", dim)             # <<<<<<<<<<<<<<
 *         else:
 *             suboffset_dim[0] = new_ndim
 */
        __pyx_t_3 = __pyx_memoryview_err_dim(__pyx_builtin_IndexError, ((char *)"All dimensions preceding dimension %d must be indexed and not sliced"), __pyx_v_dim); if (unlikely(__pyx_t_3 == -1)) __PYX_ERR(2, 887, __pyx_L1_error)
      }
      __pyx_L26:;

      /* "View.MemoryView":883
 * 
 *     if suboffset >= 0:
 *         if not is_slice:             # <<<<<<<<<<<<<<
 *             if new_ndim == 0:
 *                 dst.data = (<char **> dst.data)[0] + suboffset
 */
      goto __pyx_L25;
    }

    /* "View.MemoryView":890
 *                                      "must be indexed and not sliced", dim)
 *         else:
 *             suboffset_dim[0] = new_ndim             # <<<<<<<<<<<<<<
 * 
 *     return 0
 */
    /*else*/ {
      (__pyx_v_suboffset_dim[0]) = __pyx_v_new_ndim;
    }
    __pyx_L25:;

    /* "View.MemoryView":882
 *         dst.suboffsets[suboffset_dim[0]] += start * stride
 * 
 *     if suboffset >= 0:             # <<<<<<<<<<<<<<
 *         if not is_slice:
 *             if new_ndim == 0:
 */
  }

  /* "View.MemoryView":892
 *             suboffset_dim[0] = new_ndim
 * 
 *     return 0             # <<<<<<<<<<<<<<
 * 
 * 
 */
  __pyx_r = 0;
  goto __pyx_L0;

  /* "View.MemoryView":795
 * 
 * @cname('__pyx_memoryview_slice_memviewslice')
 * cdef int slice_memviewslice(             # <<<<<<<<<<<<<<
 *         __Pyx_memviewslice *dst,
 *         Py_ssize_t shape, Py_ssize_t stride, Py_ssize_t suboffset,
 */

  /* function exit code */
  __pyx_L1_error:;
  {
    #ifdef WITH_THREAD
    PyGILState_STATE __pyx_gilstate_save = __Pyx_PyGILState_Ensure();
    #endif
    __Pyx_AddTraceback("View.MemoryView.slice_memviewslice", __pyx_clineno, __pyx_lineno, __pyx_filename);
    #ifdef WITH_THREAD
    __Pyx_PyGILState_Release(__pyx_gilstate_save);
    #endif
  }
  __pyx_r = -1;
  __pyx_L0:;
  return __pyx_r;
}

/* "View.MemoryView":898
 * 
 * @cname('__pyx_pybuffer_index')
 * cdef char *pybuffer_index(Py_buffer *view, char *bufp, Py_ssize_t index,             # <<<<<<<<<<<<<<
 *                           Py_ssize_t dim) except NULL:
 *     cdef Py_ssize_t shape, stride, suboffset = -1
 */

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 *     cdef Py_ssize_t f_stride = 0             # <<<<<<<<<<<<<<
 * 
 *     for i in range(ndim - 1, -1, -1):
 */
  __pyx_v_f_stride = 0;

  /* "View.MemoryView":1109
 *     cdef Py_ssize_t f_stride = 0
 * 
 *     for i in range(ndim - 1, -1, -1):             # <<<<<<<<<<<<<<
 *         if mslice.shape[i] > 1:
 *             c_stride = mslice.strides[i]
 */
  for (__pyx_t_1 = (__pyx_v_ndim - 1); __pyx_t_1 > -1L; __pyx_t_1-=1) {
    __pyx_v_i = __pyx_t_1;

    /* "View.MemoryView":1110
 * 
 *     for i in range(ndim - 1, -1, -1):
 *         if mslice.shape[i] > 1:             # <<<<<<<<<<<<<<
 *             c_stride = mslice.strides[i]
 *             break
 */
    __pyx_t_2 = (((__pyx_v_mslice->shape[__pyx_v_i]) > 1) != 0);
    if (__pyx_t_2) {

      /* "View.MemoryView":1111
 *     for i in range(ndim - 1, -1, -1):
 *         if mslice.shape[i] > 1:
 *             c_stride = mslice.strides[i]             # <<<<<<<<<<<<<<
 *             break
 * 
 */
      __pyx_v_c_stride = (__pyx_v_mslice->strides[__pyx_v_i]);

      /* "View.MemoryView":1112
 *         if mslice.shape[i] > 1:
 *             c_stride = mslice.strides[i]
 *             break             # <<<<<<<<<<<<<<
 * 
 *     for i in range(ndim):
 */
      goto __pyx_L4_break;

      /* "View.MemoryView":1110
 * 
 *     for i in range(ndim - 1, -1, -1):
 *         if mslice.shape[i] > 1:             # <<<<<<<<<<<<<<
 *             c_stride = mslice.strides[i]
 *             break
 */
    }
  }
  __pyx_L4_break:;

  /* "View.MemoryView":1114
 *             break
 * 
 *     for i in range(ndim):             # <<<<<<<<<<<<<<
 *         if mslice.shape[i] > 1:
 *             f_stride = mslice.strides[i]
 */
  __pyx_t_1 = __pyx_v_ndim;
  for (__pyx_t_3 = 0; __pyx_t_3 < __pyx_t_1; __pyx_t_3+=1) {
    __pyx_v_i = __pyx_t_3;

    /* "View.MemoryView":1115
 * 
 *     for i in range(ndim):
 *         if mslice.shape[i] > 1:             # <<<<<<<<<<<<<<
 *             f_stride = mslice.strides[i]
 *             break
 */
    __pyx_t_2 = (((__pyx_v_mslice->shape[__pyx_v_i]) > 1) != 0);
    if (__pyx_t_2) {

      /* "View.MemoryView":1116
 *     for i in range(ndim):
 *         if mslice.shape[i] > 1:
 *             f_stride = mslice.strides[i]             # <<<<<<<<<<<<<<
 *             break
 * 
 */
      __pyx_v_f_stride = (__pyx_v_mslice->strides[__pyx_v_i]);

      /* "View.MemoryView":1117
 *         if mslice.shape[i] > 1:
 *             f_stride = mslice.strides[i]
 *             break             # <<<<<<<<<<<<<<
 * 
 *     if abs_py_ssize_t(c_stride) <= abs_py_ssize_t(f_stride):
 */
      goto __pyx_L7_break;

      /* "View.MemoryView":1115
 * 
 *     for i in range(ndim):
 *         if mslice.shape[i] > 1:             # <<<<<<<<<<<<<<
 *             f_stride = mslice.strides[i]
 *             break
 */
    }
  }
  __pyx_L7_break:;

  /* "View.MemoryView":1119
 *             break
 * 
 *     if abs_py_ssize_t(c_stride) <= abs_py_ssize_t(f_stride):             # <<<<<<<<<<<<<<
 *         return 'C'
 *     else:
 */
  __pyx_t_2 = ((abs_py_ssize_t(__pyx_v_c_stride) <= abs_py_ssize_t(__pyx_v_f_stride)) != 0);
  if (__pyx_t_2) {

    /* "View.MemoryView":1120
 * 
 *     if abs_py_ssize_t(c_stride) <= abs_py_ssize_t(f_stride):
 *         return 'C'             # <<<<<<<<<<<<<<
 *     else:
 *         return 'F'
 */
    __pyx_r = 'C';
    goto __pyx_L0;

    /* "View.MemoryView":1119
 *             break
 * 
 *     if abs_py_ssize_t(c_stride) <= abs_py_ssize_t(f_stride):             # <<<<<<<<<<<<<<
 *         return 'C'
 *     else:
 */
  }

  /* "View.MemoryView":1122
 *         return 'C'
 *     else:
 *         return 'F'             # <<<<<<<<<<<<<<
 * 
 * @cython.cdivision(True)
 */
  /*else*/ {
    __pyx_r = 'F';
    goto __pyx_L0;
  }

  /* "View.MemoryView":1101
 * 
 * @cname('__pyx_get_best_slice_order')
 * cdef char get_best_order(__Pyx_memviewslice *mslice, int ndim) nogil:             # <<<<<<<<<<<<<<
 *     """
 *     Figure out the best memory access order for a given slice.
 */

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

/* "View.MemoryView":1125
 * 
 * @cython.cdivision(True)
 * cdef void _copy_strided_to_strided(char *src_data, Py_ssize_t *src_strides,             # <<<<<<<<<<<<<<
 *                                    char *dst_data, Py_ssize_t *dst_strides,
 *                                    Py_ssize_t *src_shape, Py_ssize_t *dst_shape,
 */

static void _copy_strided_to_strided(char *__pyx_v_src_data, Py_ssize_t *__pyx_v_src_strides, char *__pyx_v_dst_data, Py_ssize_t *__pyx_v_dst_strides, Py_ssize_t *__pyx_v_src_shape, Py_ssize_t *__pyx_v_dst_shape, int __pyx_v_ndim, size_t __pyx_v_itemsize) {
  CYTHON_UNUSED Py_ssize_t __pyx_v_i;
  CYTHON_UNUSED Py_ssize_t __pyx_v_src_extent;
  Py_ssize_t __pyx_v_dst_extent;
  Py_ssize_t __pyx_v_src_stride;
  Py_ssize_t __pyx_v_dst_stride;
  int __pyx_t_1;
  int __pyx_t_2;
  int __pyx_t_3;
  Py_ssize_t __pyx_t_4;
  Py_ssize_t __pyx_t_5;

  /* "View.MemoryView":1132
 * 
 *     cdef Py_ssize_t i
 *     cdef Py_ssize_t src_extent = src_shape[0]             # <<<<<<<<<<<<<<
 *     cdef Py_ssize_t dst_extent = dst_shape[0]
 *     cdef Py_ssize_t src_stride = src_strides[0]
 */
  __pyx_v_src_extent = (__pyx_v_src_shape[0]);

  /* "View.MemoryView":1133
 *     cdef Py_ssize_t i
 *     cdef Py_ssize_t src_extent = src_shape[0]
 *     cdef Py_ssize_t dst_extent = dst_shape[0]             # <<<<<<<<<<<<<<
 *     cdef Py_ssize_t src_stride = src_strides[0]
 *     cdef Py_ssize_t dst_stride = dst_strides[0]
 */
  __pyx_v_dst_extent = (__pyx_v_dst_shape[0]);

  /* "View.MemoryView":1134
 *     cdef Py_ssize_t src_extent = src_shape[0]
 *     cdef Py_ssize_t dst_extent = dst_shape[0]
 *     cdef Py_ssize_t src_stride = src_strides[0]             # <<<<<<<<<<<<<<
 *     cdef Py_ssize_t dst_stride = dst_strides[0]
 * 
 */
  __pyx_v_src_stride = (__pyx_v_src_strides[0]);

  /* "View.MemoryView":1135
 *     cdef Py_ssize_t dst_extent = dst_shape[0]
 *     cdef Py_ssize_t src_stride = src_strides[0]
 *     cdef Py_ssize_t dst_stride = dst_strides[0]             # <<<<<<<<<<<<<<
 * 
 *     if ndim == 1:
 */
  __pyx_v_dst_stride = (__pyx_v_dst_strides[0]);

  /* "View.MemoryView":1137
 *     cdef Py_ssize_t dst_stride = dst_strides[0]
 * 
 *     if ndim == 1:             # <<<<<<<<<<<<<<
 *        if (src_stride > 0 and dst_stride > 0 and
 *            <size_t> src_stride == itemsize == <size_t> dst_stride):
 */
  __pyx_t_1 = ((__pyx_v_ndim == 1) != 0);
  if (__pyx_t_1) {

    /* "View.MemoryView":1138
 * 
 *     if ndim == 1:
 *        if (src_stride > 0 and dst_stride > 0 and             # <<<<<<<<<<<<<<
 *            <size_t> src_stride == itemsize == <size_t> dst_stride):
 *            memcpy(dst_data, src_data, itemsize * dst_extent)
 */
    __pyx_t_2 = ((__pyx_v_src_stride > 0) != 0);
    if (__pyx_t_2) {
    } else {
      __pyx_t_1 = __pyx_t_2;
      goto __pyx_L5_bool_binop_done;
    }
    __pyx_t_2 = ((__pyx_v_dst_stride > 0) != 0);
    if (__pyx_t_2) {
    } else {
      __pyx_t_1 = __pyx_t_2;
      goto __pyx_L5_bool_binop_done;
    }

    /* "View.MemoryView":1139
 *     if ndim == 1:
 *        if (src_stride > 0 and dst_stride > 0 and
 *            <size_t> src_stride == itemsize == <size_t> dst_stride):             # <<<<<<<<<<<<<<
 *            memcpy(dst_data, src_data, itemsize * dst_extent)
 *        else:
 */
    __pyx_t_2 = (((size_t)__pyx_v_src_stride) == __pyx_v_itemsize);
    if (__pyx_t_2) {
      __pyx_t_2 = (__pyx_v_itemsize == ((size_t)__pyx_v_dst_stride));
    }
    __pyx_t_3 = (__pyx_t_2 != 0);
    __pyx_t_1 = __pyx_t_3;
    __pyx_L5_bool_binop_done:;

    /* "View.MemoryView":1138
 * 
 *     if ndim == 1:
 *        if (src_stride > 0 and dst_stride > 0 and             # <<<<<<<<<<<<<<
 *            <size_t> src_stride == itemsize == <size_t> dst_stride):
 *            memcpy(dst_data, src_data, itemsize * dst_extent)
 */
    if (__pyx_t_1) {

      /* "View.MemoryView":1140
 *        if (src_stride > 0 and dst_stride > 0 and
 *            <size_t> src_stride == itemsize == <size_t> dst_stride):
 *            memcpy(dst_data, src_data, itemsize * dst_extent)             # <<<<<<<<<<<<<<
 *        else:
 *            for i in range(dst_extent):
 */
      memcpy(__pyx_v_dst_data, __pyx_v_src_data, (__pyx_v_itemsize * __pyx_v_dst_extent));

      /* "View.MemoryView":1138
 * 
 *     if ndim == 1:
 *        if (src_stride > 0 and dst_stride > 0 and             # <<<<<<<<<<<<<<
 *            <size_t> src_stride == itemsize == <size_t> dst_stride):
 *            memcpy(dst_data, src_data, itemsize * dst_extent)
 */
      goto __pyx_L4;
    }

    /* "View.MemoryView":1142
 *            memcpy(dst_data, src_data, itemsize * dst_extent)
 *        else:
 *            for i in range(dst_extent):             # <<<<<<<<<<<<<<
 *                memcpy(dst_data, src_data, itemsize)
 *                src_data += src_stride
 */
    /*else*/ {
      __pyx_t_4 = __pyx_v_dst_extent;
      for (__pyx_t_5 = 0; __pyx_t_5 < __pyx_t_4; __pyx_t_5+=1) {
        __pyx_v_i = __pyx_t_5;

        /* "View.MemoryView":1143
 *        else:
 *            for i in range(dst_extent):
 *                memcpy(dst_data, src_data, itemsize)             # <<<<<<<<<<<<<<
 *                src_data += src_stride
 *                dst_data += dst_stride
 */
        memcpy(__pyx_v_dst_data, __pyx_v_src_data, __pyx_v_itemsize);

        /* "View.MemoryView":1144
 *            for i in range(dst_extent):
 *                memcpy(dst_data, src_data, itemsize)
 *                src_data += src_stride             # <<<<<<<<<<<<<<
 *                dst_data += dst_stride
 *     else:
 */
        __pyx_v_src_data = (__pyx_v_src_data + __pyx_v_src_stride);

        /* "View.MemoryView":1145
 *                memcpy(dst_data, src_data, itemsize)
 *                src_data += src_stride
 *                dst_data += dst_stride             # <<<<<<<<<<<<<<
 *     else:
 *         for i in range(dst_extent):
 */
        __pyx_v_dst_data = (__pyx_v_dst_data + __pyx_v_dst_stride);
      }
    }
    __pyx_L4:;

    /* "View.MemoryView":1137
 *     cdef Py_ssize_t dst_stride = dst_strides[0]
 * 
 *     if ndim == 1:             # <<<<<<<<<<<<<<
 *        if (src_stride > 0 and dst_stride > 0 and
 *            <size_t> src_stride == itemsize == <size_t> dst_stride):
 */
    goto __pyx_L3;
  }

  /* "View.MemoryView":1147
 *                dst_data += dst_stride
 *     else:
 *         for i in range(dst_extent):             # <<<<<<<<<<<<<<
 *             _copy_strided_to_strided(src_data, src_strides + 1,
 *                                      dst_data, dst_strides + 1,
 */
  /*else*/ {
    __pyx_t_4 = __pyx_v_dst_extent;
    for (__pyx_t_5 = 0; __pyx_t_5 < __pyx_t_4; __pyx_t_5+=1) {
      __pyx_v_i = __pyx_t_5;

      /* "View.MemoryView":1148
 *     else:
 *         for i in range(dst_extent):
 *             _copy_strided_to_strided(src_data, src_strides + 1,             # <<<<<<<<<<<<<<
 *                                      dst_data, dst_strides + 1,
 *                                      src_shape + 1, dst_shape + 1,
 */
      _copy_strided_to_strided(__pyx_v_src_data, (__pyx_v_src_strides + 1), __pyx_v_dst_data, (__pyx_v_dst_strides + 1), (__pyx_v_src_shape + 1), (__pyx_v_dst_shape + 1), (__pyx_v_ndim - 1), __pyx_v_itemsize);

      /* "View.MemoryView":1152
 *                                      src_shape + 1, dst_shape + 1,
 *                                      ndim - 1, itemsize)
 *             src_data += src_stride             # <<<<<<<<<<<<<<
 *             dst_data += dst_stride
 * 
 */
      __pyx_v_src_data = (__pyx_v_src_data + __pyx_v_src_stride);

      /* "View.MemoryView":1153
 *                                      ndim - 1, itemsize)
 *             src_data += src_stride
 *             dst_data += dst_stride             # <<<<<<<<<<<<<<
 * 
 * cdef void copy_strided_to_strided(__Pyx_memviewslice *src,
 */
      __pyx_v_dst_data = (__pyx_v_dst_data + __pyx_v_dst_stride);
    }
  }
  __pyx_L3:;

  /* "View.MemoryView":1125
 * 
 * @cython.cdivision(True)
 * cdef void _copy_strided_to_strided(char *src_data, Py_ssize_t *src_strides,             # <<<<<<<<<<<<<<
 *                                    char *dst_data, Py_ssize_t *dst_strides,
 *                                    Py_ssize_t *src_shape, Py_ssize_t *dst_shape,
 */

  /* function exit code */
}

/* "View.MemoryView":1155
 *             dst_data += dst_stride
 * 
 * cdef void copy_strided_to_strided(__Pyx_memviewslice *src,             # <<<<<<<<<<<<<<
 *                                   __Pyx_memviewslice *dst,
 *                                   int ndim, size_t itemsize) nogil:
 */

static void copy_strided_to_strided(__Pyx_memviewslice *__pyx_v_src, __Pyx_memviewslice *__pyx_v_dst, int __pyx_v_ndim, size_t __pyx_v_itemsize) {

  /* "View.MemoryView":1158
 *                                   __Pyx_memviewslice *dst,
 *                                   int ndim, size_t itemsize) nogil:
 *     _copy_strided_to_strided(src.data, src.strides, dst.data, dst.strides,             # <<<<<<<<<<<<<<
 *                              src.shape, dst.shape, ndim, itemsize)
 * 
 */
  _copy_strided_to_strided(__pyx_v_src->data, __pyx_v_src->strides, __pyx_v_dst->data, __pyx_v_dst->strides, __pyx_v_src->shape, __pyx_v_dst->shape, __pyx_v_ndim, __pyx_v_itemsize);

  /* "View.MemoryView":1155
 *             dst_data += dst_stride
 * 
 * cdef void copy_strided_to_strided(__Pyx_memviewslice *src,             # <<<<<<<<<<<<<<
 *                                   __Pyx_memviewslice *dst,
 *                                   int ndim, size_t itemsize) nogil:
 */

  /* function exit code */
}

/* "View.MemoryView":1162
 * 
 * @cname('__pyx_memoryview_slice_get_size')
 * cdef Py_ssize_t slice_get_size(__Pyx_memviewslice *src, int ndim) nogil:             # <<<<<<<<<<<<<<
 *     "Return the size of the memory occupied by the slice in number of bytes"
 *     cdef int i
 */

static Py_ssize_t __pyx_memoryview_slice_get_size(__Pyx_memviewslice *__pyx_v_src, int __pyx_v_ndim) {
  int __pyx_v_i;
  Py_ssize_t __pyx_v_size;
  Py_ssize_t __pyx_r;
  Py_ssize_t __pyx_t_1;
  int __pyx_t_2;
  int __pyx_t_3;

  /* "View.MemoryView":1165
 *     "Return the size of the memory occupied by the slice in number of bytes"
 *     cdef int i
 *     cdef Py_ssize_t size = src.memview.view.itemsize             # <<<<<<<<<<<<<<
 * 
 *     for i in range(ndim):
 */
  __pyx_t_1 = __pyx_v_src->memview->view.itemsize;
  __pyx_v_size = __pyx_t_1;

  /* "View.MemoryView":1167
 *     cdef Py_ssize_t size = src.memview.view.itemsize
 * 
 *     for i in range(ndim):             # <<<<<<<<<<<<<<
 *         size *= src.shape[i]
 * 
 */
  __pyx_t_2 = __pyx_v_ndim;
  for (__pyx_t_3 = 0; __pyx_t_3 < __pyx_t_2; __pyx_t_3+=1) {
    __pyx_v_i = __pyx_t_3;

    /* "View.MemoryView":1168
 * 
 *     for i in range(ndim):
 *         size *= src.shape[i]             # <<<<<<<<<<<<<<
 * 
 *     return size
 */
    __pyx_v_size = (__pyx_v_size * (__pyx_v_src->shape[__pyx_v_i]));
  }

  /* "View.MemoryView":1170
 *         size *= src.shape[i]
 * 
 *     return size             # <<<<<<<<<<<<<<
 * 
 * @cname('__pyx_fill_contig_strides_array')
 */
  __pyx_r = __pyx_v_size;
  goto __pyx_L0;

  /* "View.MemoryView":1162
 * 
 * @cname('__pyx_memoryview_slice_get_size')
 * cdef Py_ssize_t slice_get_size(__Pyx_memviewslice *src, int ndim) nogil:             # <<<<<<<<<<<<<<
 *     "Return the size of the memory occupied by the slice in number of bytes"
 *     cdef int i
 */

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

/* "View.MemoryView":1173
 * 
 * @cname('__pyx_fill_contig_strides_array')
 * cdef Py_ssize_t fill_contig_strides_array(             # <<<<<<<<<<<<<<
 *                 Py_ssize_t *shape, Py_ssize_t *strides, Py_ssize_t stride,
 *                 int ndim, char order) nogil:
 */

static Py_ssize_t __pyx_fill_contig_strides_array(Py_ssize_t *__pyx_v_shape, Py_ssize_t *__pyx_v_strides, Py_ssize_t __pyx_v_stride, int __pyx_v_ndim, char __pyx_v_order) {
  int __pyx_v_idx;
  Py_ssize_t __pyx_r;
  int __pyx_t_1;
  int __pyx_t_2;
  int __pyx_t_3;

  /* "View.MemoryView":1182
 *     cdef int idx
 * 
 *     if order == 'F':             # <<<<<<<<<<<<<<
 *         for idx in range(ndim):
 *             strides[idx] = stride
 */
  __pyx_t_1 = ((__pyx_v_order == 'F') != 0);
  if (__pyx_t_1) {

    /* "View.MemoryView":1183
 * 
 *     if order == 'F':
 *         for idx in range(ndim):             # <<<<<<<<<<<<<<
 *             strides[idx] = stride
 *             stride = stride * shape[idx]
 */
    __pyx_t_2 = __pyx_v_ndim;
    for (__pyx_t_3 = 0; __pyx_t_3 < __pyx_t_2; __pyx_t_3+=1) {
      __pyx_v_idx = __pyx_t_3;

      /* "View.MemoryView":1184
 *     if order == 'F':
 *         for idx in range(ndim):
 *             strides[idx] = stride             # <<<<<<<<<<<<<<
 *             stride = stride * shape[idx]
 *     else:
 */
      (__pyx_v_strides[__pyx_v_idx]) = __pyx_v_stride;

      /* "View.MemoryView":1185
 *         for idx in range(ndim):
 *             strides[idx] = stride
 *             stride = stride * shape[idx]             # <<<<<<<<<<<<<<
 *     else:
 *         for idx in range(ndim - 1, -1, -1):
 */
      __pyx_v_stride = (__pyx_v_stride * (__pyx_v_shape[__pyx_v_idx]));
    }

    /* "View.MemoryView":1182
 *     cdef int idx
 * 
 *     if order == 'F':             # <<<<<<<<<<<<<<
 *         for idx in range(ndim):
 *             strides[idx] = stride
 */
    goto __pyx_L3;
  }

  /* "View.MemoryView":1187
 *             stride = stride * shape[idx]
 *     else:
 *         for idx in range(ndim - 1, -1, -1):             # <<<<<<<<<<<<<<
 *             strides[idx] = stride
 *             stride = stride * shape[idx]
 */
  /*else*/ {
    for (__pyx_t_2 = (__pyx_v_ndim - 1); __pyx_t_2 > -1L; __pyx_t_2-=1) {
      __pyx_v_idx = __pyx_t_2;

      /* "View.MemoryView":1188
 *     else:
 *         for idx in range(ndim - 1, -1, -1):
 *             strides[idx] = stride             # <<<<<<<<<<<<<<
 *             stride = stride * shape[idx]
 * 
 */
      (__pyx_v_strides[__pyx_v_idx]) = __pyx_v_stride;

      /* "View.MemoryView":1189
 *         for idx in range(ndim - 1, -1, -1):
 *             strides[idx] = stride
 *             stride = stride * shape[idx]             # <<<<<<<<<<<<<<
 * 
 *     return stride
 */
      __pyx_v_stride = (__pyx_v_stride * (__pyx_v_shape[__pyx_v_idx]));
    }
  }
  __pyx_L3:;

  /* "View.MemoryView":1191
 *             stride = stride * shape[idx]
 * 
 *     return stride             # <<<<<<<<<<<<<<
 * 
 * @cname('__pyx_memoryview_copy_data_to_temp')
 */
  __pyx_r = __pyx_v_stride;
  goto __pyx_L0;

  /* "View.MemoryView":1173
 * 
 * @cname('__pyx_fill_contig_strides_array')
 * cdef Py_ssize_t fill_contig_strides_array(             # <<<<<<<<<<<<<<
 *                 Py_ssize_t *shape, Py_ssize_t *strides, Py_ssize_t stride,
 *                 int ndim, char order) nogil:
 */

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

/* "View.MemoryView":1194
 * 
 * @cname('__pyx_memoryview_copy_data_to_temp')
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 *     cdef int i
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 *     cdef void *tmpdata = NULL
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 *     cdef int i
 *     cdef char order = get_best_order(&src, src_ndim)
 */
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 *     cdef __Pyx_memviewslice tmp
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 * 
 *     if src_ndim < dst_ndim:             # <<<<<<<<<<<<<<
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 *         broadcast_leading(&dst, dst_ndim, src_ndim)
 * 
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 *         broadcast_leading(&src, src_ndim, dst_ndim)
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 *     cdef int ndim = max(src_ndim, dst_ndim)
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 *     if src_ndim < dst_ndim:
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 *     elif dst_ndim < src_ndim:             # <<<<<<<<<<<<<<
 *         broadcast_leading(&dst, dst_ndim, src_ndim)
 * 
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 *         broadcast_leading(&dst, dst_ndim, src_ndim)
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 *     cdef int ndim = max(src_ndim, dst_ndim)             # <<<<<<<<<<<<<<
 * 
 *     for i in range(ndim):
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 *     for i in range(ndim):             # <<<<<<<<<<<<<<
 *         if src.shape[i] != dst.shape[i]:
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 * 
 *     for i in range(ndim):
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 *             if src.shape[i] == 1:
 *                 broadcasting = True
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 *     for i in range(ndim):
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 *                 broadcasting = True
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 *     for i in range(ndim):
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 *                 broadcasting = True
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 * 
 *         if src.suboffsets[i] >= 0:
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 * 
 *     for i in range(ndim):
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 *             if src.shape[i] == 1:
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 * 
 *         if src.suboffsets[i] >= 0:
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 * 
 *     if slices_overlap(&src, &dst, ndim, itemsize):
 */
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 * 
 *         if src.suboffsets[i] >= 0:             # <<<<<<<<<<<<<<
 *             _err_dim(ValueError, "Dimension %d is not direct", i)
 * 
 */
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 *             _err_dim(ValueError, "Dimension %d is not direct", i)
 * 
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 * 
 *         if not slice_is_contig(src, order, ndim):
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 *             order = get_best_order(&dst, ndim)
 * 
 */
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 * 
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 * 
 */
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 *         if slice_is_contig(src, 'C', ndim):             # <<<<<<<<<<<<<<
 *             direct_copy = slice_is_contig(dst, 'C', ndim)
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 *         elif slice_is_contig(src, 'F', ndim):             # <<<<<<<<<<<<<<
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 * 
 */
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 * 
 *         if direct_copy:
 */
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 * 
 */
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 * 
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 * 
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 * 
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 * 
 *             refcount_copying(&dst, dtype_is_object, ndim, False)
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 *             free(tmpdata)
 *             return 0
 */
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 *             memcpy(dst.data, src.data, slice_get_size(&src, ndim))
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 *             free(tmpdata)             # <<<<<<<<<<<<<<
 *             return 0
 * 
 */
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 *             refcount_copying(&dst, dtype_is_object, ndim, True)
 *             free(tmpdata)
 *             return 0             # <<<<<<<<<<<<<<
 * 
 *     if order == 'F' == get_best_order(&dst, ndim):
 */
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 *             direct_copy = slice_is_contig(dst, 'F', ndim)
 * 
 *         if direct_copy:             # <<<<<<<<<<<<<<
 * 
 *             refcount_copying(&dst, dtype_is_object, ndim, False)
 */
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    /* "View.MemoryView":1296
 *         src = tmp
 * 
 *     if not broadcasting:             # <<<<<<<<<<<<<<
 * 
 * 
 */
  }

  /* "View.MemoryView":1312
 *             return 0
 * 
 *     if order == 'F' == get_best_order(&dst, ndim):             # <<<<<<<<<<<<<<
 * 
 * 
 */
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  if (__pyx_t_2) {
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  }
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    /* "View.MemoryView":1315
 * 
 * 
 *         transpose_memslice(&src)             # <<<<<<<<<<<<<<
 *         transpose_memslice(&dst)
 * 
 */
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 * 
 *         transpose_memslice(&src)
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 *     refcount_copying(&dst, dtype_is_object, ndim, False)
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 *     if order == 'F' == get_best_order(&dst, ndim):             # <<<<<<<<<<<<<<
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 * 
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 * 
 *     refcount_copying(&dst, dtype_is_object, ndim, False)             # <<<<<<<<<<<<<<
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 *     refcount_copying(&dst, dtype_is_object, ndim, True)
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 * 
 *     refcount_copying(&dst, dtype_is_object, ndim, False)
 *     copy_strided_to_strided(&src, &dst, ndim, itemsize)             # <<<<<<<<<<<<<<
 *     refcount_copying(&dst, dtype_is_object, ndim, True)
 * 
 */
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 *     refcount_copying(&dst, dtype_is_object, ndim, False)
 *     copy_strided_to_strided(&src, &dst, ndim, itemsize)
 *     refcount_copying(&dst, dtype_is_object, ndim, True)             # <<<<<<<<<<<<<<
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 *     free(tmpdata)
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 * 
 *     free(tmpdata)             # <<<<<<<<<<<<<<
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 *     free(tmpdata)
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/* "View.MemoryView":1326
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 * @cname('__pyx_memoryview_broadcast_leading')
 * cdef void broadcast_leading(__Pyx_memviewslice *mslice,             # <<<<<<<<<<<<<<
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 * 
 *     for i in range(ndim - 1, -1, -1):
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 */
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 *         mslice.shape[i + offset] = mslice.shape[i]
 *         mslice.strides[i + offset] = mslice.strides[i]
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 * 
 *     for i in range(offset):
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 *         mslice.suboffsets[i + offset] = mslice.suboffsets[i]
 * 
 *     for i in range(offset):             # <<<<<<<<<<<<<<
 *         mslice.shape[i] = 1
 *         mslice.strides[i] = mslice.strides[0]
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 * 
 *     for i in range(offset):
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 *         mslice.strides[i] = mslice.strides[0]
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 *     for i in range(offset):
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 */
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 * 
 */
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 * @cname('__pyx_memoryview_broadcast_leading')
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/* "View.MemoryView":1348
 * 
 * @cname('__pyx_memoryview_refcount_copying')
 * cdef void refcount_copying(__Pyx_memviewslice *dst, bint dtype_is_object,             # <<<<<<<<<<<<<<
 *                            int ndim, bint inc) nogil:
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static void __pyx_memoryview_refcount_copying(__Pyx_memviewslice *__pyx_v_dst, int __pyx_v_dtype_is_object, int __pyx_v_ndim, int __pyx_v_inc) {
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 * 
 *     if dtype_is_object:             # <<<<<<<<<<<<<<
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 * 
 *     if dtype_is_object:
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 *                                            dst.strides, ndim, inc)
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 * 
 * 
 *     if dtype_is_object:             # <<<<<<<<<<<<<<
 *         refcount_objects_in_slice_with_gil(dst.data, dst.shape,
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 * 
 * @cname('__pyx_memoryview_refcount_copying')
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 *                            int ndim, bint inc) nogil:
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/* "View.MemoryView":1357
 * 
 * @cname('__pyx_memoryview_refcount_objects_in_slice_with_gil')
 * cdef void refcount_objects_in_slice_with_gil(char *data, Py_ssize_t *shape,             # <<<<<<<<<<<<<<
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static void __pyx_memoryview_refcount_objects_in_slice_with_gil(char *__pyx_v_data, Py_ssize_t *__pyx_v_shape, Py_ssize_t *__pyx_v_strides, int __pyx_v_ndim, int __pyx_v_inc) {
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 * 
 * @cname('__pyx_memoryview_refcount_objects_in_slice')
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 * 
 * @cname('__pyx_memoryview_refcount_objects_in_slice_with_gil')
 * cdef void refcount_objects_in_slice_with_gil(char *data, Py_ssize_t *shape,             # <<<<<<<<<<<<<<
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/* "View.MemoryView":1363
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 * cdef void refcount_objects_in_slice(char *data, Py_ssize_t *shape,             # <<<<<<<<<<<<<<
 *                                     Py_ssize_t *strides, int ndim, bint inc):
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static void __pyx_memoryview_refcount_objects_in_slice(char *__pyx_v_data, Py_ssize_t *__pyx_v_shape, Py_ssize_t *__pyx_v_strides, int __pyx_v_ndim, int __pyx_v_inc) {
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 * 
 *     for i in range(shape[0]):
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 *         data += strides[0]
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 *         data += strides[0]             # <<<<<<<<<<<<<<
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 * 
 * @cname('__pyx_memoryview_refcount_objects_in_slice')
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/* "View.MemoryView":1383
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static void __pyx_memoryview_slice_assign_scalar(__Pyx_memviewslice *__pyx_v_dst, int __pyx_v_ndim, size_t __pyx_v_itemsize, void *__pyx_v_item, int __pyx_v_dtype_is_object) {

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 *                               size_t itemsize, void *item,
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  /* "View.MemoryView":1387
 *                               bint dtype_is_object) nogil:
 *     refcount_copying(dst, dtype_is_object, ndim, False)
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 *     _slice_assign_scalar(dst.data, dst.shape, dst.strides, ndim,
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 * 
 */
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  /* "View.MemoryView":1383
 * 
 * @cname('__pyx_memoryview_slice_assign_scalar')
 * cdef void slice_assign_scalar(__Pyx_memviewslice *dst, int ndim,             # <<<<<<<<<<<<<<
 *                               size_t itemsize, void *item,
 *                               bint dtype_is_object) nogil:
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  /* function exit code */
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/* "View.MemoryView":1393
 * 
 * @cname('__pyx_memoryview__slice_assign_scalar')
 * cdef void _slice_assign_scalar(char *data, Py_ssize_t *shape,             # <<<<<<<<<<<<<<
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static void __pyx_memoryview__slice_assign_scalar(char *__pyx_v_data, Py_ssize_t *__pyx_v_shape, Py_ssize_t *__pyx_v_strides, int __pyx_v_ndim, size_t __pyx_v_itemsize, void *__pyx_v_item) {
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 *     cdef Py_ssize_t extent = shape[0]
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 */
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    /* "View.MemoryView":1401
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      /* "View.MemoryView":1402
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      /* "View.MemoryView":1403
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    /* "View.MemoryView":1400
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 *     if ndim == 1:             # <<<<<<<<<<<<<<
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      /* "View.MemoryView":1406
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 *                                 ndim - 1, itemsize, item)
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 * 
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  0, /*tp_compare*/
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static PyObject *__pyx_getprop___pyx_memoryview_nbytes(PyObject *o, CYTHON_UNUSED void *x) {
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}

static PyObject *__pyx_getprop___pyx_memoryview_size(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_15View_dot_MemoryView_10memoryview_4size_1__get__(o);
}

static PyMethodDef __pyx_methods_memoryview[] = {
  {"is_c_contig", (PyCFunction)__pyx_memoryview_is_c_contig, METH_NOARGS, 0},
  {"is_f_contig", (PyCFunction)__pyx_memoryview_is_f_contig, METH_NOARGS, 0},
  {"copy", (PyCFunction)__pyx_memoryview_copy, METH_NOARGS, 0},
  {"copy_fortran", (PyCFunction)__pyx_memoryview_copy_fortran, METH_NOARGS, 0},
  {"__reduce_cython__", (PyCFunction)__pyx_pw___pyx_memoryview_1__reduce_cython__, METH_NOARGS, 0},
  {"__setstate_cython__", (PyCFunction)__pyx_pw___pyx_memoryview_3__setstate_cython__, METH_O, 0},
  {0, 0, 0, 0}
};

static struct PyGetSetDef __pyx_getsets_memoryview[] = {
  {(char *)"T", __pyx_getprop___pyx_memoryview_T, 0, (char *)0, 0},
  {(char *)"base", __pyx_getprop___pyx_memoryview_base, 0, (char *)0, 0},
  {(char *)"shape", __pyx_getprop___pyx_memoryview_shape, 0, (char *)0, 0},
  {(char *)"strides", __pyx_getprop___pyx_memoryview_strides, 0, (char *)0, 0},
  {(char *)"suboffsets", __pyx_getprop___pyx_memoryview_suboffsets, 0, (char *)0, 0},
  {(char *)"ndim", __pyx_getprop___pyx_memoryview_ndim, 0, (char *)0, 0},
  {(char *)"itemsize", __pyx_getprop___pyx_memoryview_itemsize, 0, (char *)0, 0},
  {(char *)"nbytes", __pyx_getprop___pyx_memoryview_nbytes, 0, (char *)0, 0},
  {(char *)"size", __pyx_getprop___pyx_memoryview_size, 0, (char *)0, 0},
  {0, 0, 0, 0, 0}
};

static PySequenceMethods __pyx_tp_as_sequence_memoryview = {
  __pyx_memoryview___len__, /*sq_length*/
  0, /*sq_concat*/
  0, /*sq_repeat*/
  __pyx_sq_item_memoryview, /*sq_item*/
  0, /*sq_slice*/
  0, /*sq_ass_item*/
  0, /*sq_ass_slice*/
  0, /*sq_contains*/
  0, /*sq_inplace_concat*/
  0, /*sq_inplace_repeat*/
};

static PyMappingMethods __pyx_tp_as_mapping_memoryview = {
  __pyx_memoryview___len__, /*mp_length*/
  __pyx_memoryview___getitem__, /*mp_subscript*/
  __pyx_mp_ass_subscript_memoryview, /*mp_ass_subscript*/
};

static PyBufferProcs __pyx_tp_as_buffer_memoryview = {
  #if PY_MAJOR_VERSION < 3
  0, /*bf_getreadbuffer*/
  #endif
  #if PY_MAJOR_VERSION < 3
  0, /*bf_getwritebuffer*/
  #endif
  #if PY_MAJOR_VERSION < 3
  0, /*bf_getsegcount*/
  #endif
  #if PY_MAJOR_VERSION < 3
  0, /*bf_getcharbuffer*/
  #endif
  __pyx_memoryview_getbuffer, /*bf_getbuffer*/
  0, /*bf_releasebuffer*/
};

static PyTypeObject __pyx_type___pyx_memoryview = {
  PyVarObject_HEAD_INIT(0, 0)
  "sklearn.linear_model.cd_fast.memoryview", /*tp_name*/
  sizeof(struct __pyx_memoryview_obj), /*tp_basicsize*/
  0, /*tp_itemsize*/
  __pyx_tp_dealloc_memoryview, /*tp_dealloc*/
  0, /*tp_print*/
  0, /*tp_getattr*/
  0, /*tp_setattr*/
  #if PY_MAJOR_VERSION < 3
  0, /*tp_compare*/
  #endif
  #if PY_MAJOR_VERSION >= 3
  0, /*tp_as_async*/
  #endif
  __pyx_memoryview___repr__, /*tp_repr*/
  0, /*tp_as_number*/
  &__pyx_tp_as_sequence_memoryview, /*tp_as_sequence*/
  &__pyx_tp_as_mapping_memoryview, /*tp_as_mapping*/
  0, /*tp_hash*/
  0, /*tp_call*/
  __pyx_memoryview___str__, /*tp_str*/
  0, /*tp_getattro*/
  0, /*tp_setattro*/
  &__pyx_tp_as_buffer_memoryview, /*tp_as_buffer*/
  Py_TPFLAGS_DEFAULT|Py_TPFLAGS_HAVE_VERSION_TAG|Py_TPFLAGS_CHECKTYPES|Py_TPFLAGS_HAVE_NEWBUFFER|Py_TPFLAGS_BASETYPE|Py_TPFLAGS_HAVE_GC, /*tp_flags*/
  0, /*tp_doc*/
  __pyx_tp_traverse_memoryview, /*tp_traverse*/
  __pyx_tp_clear_memoryview, /*tp_clear*/
  0, /*tp_richcompare*/
  0, /*tp_weaklistoffset*/
  0, /*tp_iter*/
  0, /*tp_iternext*/
  __pyx_methods_memoryview, /*tp_methods*/
  0, /*tp_members*/
  __pyx_getsets_memoryview, /*tp_getset*/
  0, /*tp_base*/
  0, /*tp_dict*/
  0, /*tp_descr_get*/
  0, /*tp_descr_set*/
  0, /*tp_dictoffset*/
  0, /*tp_init*/
  0, /*tp_alloc*/
  __pyx_tp_new_memoryview, /*tp_new*/
  0, /*tp_free*/
  0, /*tp_is_gc*/
  0, /*tp_bases*/
  0, /*tp_mro*/
  0, /*tp_cache*/
  0, /*tp_subclasses*/
  0, /*tp_weaklist*/
  0, /*tp_del*/
  0, /*tp_version_tag*/
  #if PY_VERSION_HEX >= 0x030400a1
  0, /*tp_finalize*/
  #endif
};
static struct __pyx_vtabstruct__memoryviewslice __pyx_vtable__memoryviewslice;

static PyObject *__pyx_tp_new__memoryviewslice(PyTypeObject *t, PyObject *a, PyObject *k) {
  struct __pyx_memoryviewslice_obj *p;
  PyObject *o = __pyx_tp_new_memoryview(t, a, k);
  if (unlikely(!o)) return 0;
  p = ((struct __pyx_memoryviewslice_obj *)o);
  p->__pyx_base.__pyx_vtab = (struct __pyx_vtabstruct_memoryview*)__pyx_vtabptr__memoryviewslice;
  p->from_object = Py_None; Py_INCREF(Py_None);
  p->from_slice.memview = NULL;
  return o;
}

static void __pyx_tp_dealloc__memoryviewslice(PyObject *o) {
  struct __pyx_memoryviewslice_obj *p = (struct __pyx_memoryviewslice_obj *)o;
  #if PY_VERSION_HEX >= 0x030400a1
  if (unlikely(PyType_HasFeature(Py_TYPE(o), Py_TPFLAGS_HAVE_FINALIZE) && Py_TYPE(o)->tp_finalize) && !_PyGC_FINALIZED(o)) {
    if (PyObject_CallFinalizerFromDealloc(o)) return;
  }
  #endif
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  {
    PyObject *etype, *eval, *etb;
    PyErr_Fetch(&etype, &eval, &etb);
    ++Py_REFCNT(o);
    __pyx_memoryviewslice___dealloc__(o);
    --Py_REFCNT(o);
    PyErr_Restore(etype, eval, etb);
  }
  Py_CLEAR(p->from_object);
  PyObject_GC_Track(o);
  __pyx_tp_dealloc_memoryview(o);
}

static int __pyx_tp_traverse__memoryviewslice(PyObject *o, visitproc v, void *a) {
  int e;
  struct __pyx_memoryviewslice_obj *p = (struct __pyx_memoryviewslice_obj *)o;
  e = __pyx_tp_traverse_memoryview(o, v, a); if (e) return e;
  if (p->from_object) {
    e = (*v)(p->from_object, a); if (e) return e;
  }
  return 0;
}

static int __pyx_tp_clear__memoryviewslice(PyObject *o) {
  PyObject* tmp;
  struct __pyx_memoryviewslice_obj *p = (struct __pyx_memoryviewslice_obj *)o;
  __pyx_tp_clear_memoryview(o);
  tmp = ((PyObject*)p->from_object);
  p->from_object = Py_None; Py_INCREF(Py_None);
  Py_XDECREF(tmp);
  __PYX_XDEC_MEMVIEW(&p->from_slice, 1);
  return 0;
}

static PyObject *__pyx_getprop___pyx_memoryviewslice_base(PyObject *o, CYTHON_UNUSED void *x) {
  return __pyx_pw_15View_dot_MemoryView_16_memoryviewslice_4base_1__get__(o);
}

static PyMethodDef __pyx_methods__memoryviewslice[] = {
  {"__reduce_cython__", (PyCFunction)__pyx_pw___pyx_memoryviewslice_1__reduce_cython__, METH_NOARGS, 0},
  {"__setstate_cython__", (PyCFunction)__pyx_pw___pyx_memoryviewslice_3__setstate_cython__, METH_O, 0},
  {0, 0, 0, 0}
};

static struct PyGetSetDef __pyx_getsets__memoryviewslice[] = {
  {(char *)"base", __pyx_getprop___pyx_memoryviewslice_base, 0, (char *)0, 0},
  {0, 0, 0, 0, 0}
};

static PyTypeObject __pyx_type___pyx_memoryviewslice = {
  PyVarObject_HEAD_INIT(0, 0)
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  sizeof(struct __pyx_memoryviewslice_obj), /*tp_basicsize*/
  0, /*tp_itemsize*/
  __pyx_tp_dealloc__memoryviewslice, /*tp_dealloc*/
  0, /*tp_print*/
  0, /*tp_getattr*/
  0, /*tp_setattr*/
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  0, /*tp_compare*/
  #endif
  #if PY_MAJOR_VERSION >= 3
  0, /*tp_as_async*/
  #endif
  #if CYTHON_COMPILING_IN_PYPY
  __pyx_memoryview___repr__, /*tp_repr*/
  #else
  0, /*tp_repr*/
  #endif
  0, /*tp_as_number*/
  0, /*tp_as_sequence*/
  0, /*tp_as_mapping*/
  0, /*tp_hash*/
  0, /*tp_call*/
  #if CYTHON_COMPILING_IN_PYPY
  __pyx_memoryview___str__, /*tp_str*/
  #else
  0, /*tp_str*/
  #endif
  0, /*tp_getattro*/
  0, /*tp_setattro*/
  0, /*tp_as_buffer*/
  Py_TPFLAGS_DEFAULT|Py_TPFLAGS_HAVE_VERSION_TAG|Py_TPFLAGS_CHECKTYPES|Py_TPFLAGS_HAVE_NEWBUFFER|Py_TPFLAGS_BASETYPE|Py_TPFLAGS_HAVE_GC, /*tp_flags*/
  "Internal class for passing memoryview slices to Python", /*tp_doc*/
  __pyx_tp_traverse__memoryviewslice, /*tp_traverse*/
  __pyx_tp_clear__memoryviewslice, /*tp_clear*/
  0, /*tp_richcompare*/
  0, /*tp_weaklistoffset*/
  0, /*tp_iter*/
  0, /*tp_iternext*/
  __pyx_methods__memoryviewslice, /*tp_methods*/
  0, /*tp_members*/
  __pyx_getsets__memoryviewslice, /*tp_getset*/
  0, /*tp_base*/
  0, /*tp_dict*/
  0, /*tp_descr_get*/
  0, /*tp_descr_set*/
  0, /*tp_dictoffset*/
  0, /*tp_init*/
  0, /*tp_alloc*/
  __pyx_tp_new__memoryviewslice, /*tp_new*/
  0, /*tp_free*/
  0, /*tp_is_gc*/
  0, /*tp_bases*/
  0, /*tp_mro*/
  0, /*tp_cache*/
  0, /*tp_subclasses*/
  0, /*tp_weaklist*/
  0, /*tp_del*/
  0, /*tp_version_tag*/
  #if PY_VERSION_HEX >= 0x030400a1
  0, /*tp_finalize*/
  #endif
};

static PyMethodDef __pyx_methods[] = {
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};

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static struct PyModuleDef __pyx_moduledef = {
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    { PyObject_HEAD_INIT(NULL) NULL, 0, NULL },
  #else
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  #endif
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    -1, /* m_size */
    __pyx_methods /* m_methods */,
    NULL, /* m_reload */
    NULL, /* m_traverse */
    NULL, /* m_clear */
    NULL /* m_free */
};
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 * @cython.wraparound(False)
 * @cython.cdivision(True)
 * def enet_coordinate_descent(np.ndarray[floating, ndim=1] w,             # <<<<<<<<<<<<<<
 *                             floating alpha, floating beta,
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{
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    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);
}

/* RaiseDoubleKeywords */
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
}

/* ParseKeywords */
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;
}

/* PyObjectCall */
#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 (unlikely(Py_EnterRecursiveCall((char*)" while calling a Python object")))
        return NULL;
    result = (*call)(func, arg, kw);
    Py_LeaveRecursiveCall();
    if (unlikely(!result) && unlikely(!PyErr_Occurred())) {
        PyErr_SetString(
            PyExc_SystemError,
            "NULL result without error in PyObject_Call");
    }
    return result;
}
#endif

/* RaiseException */
#if PY_MAJOR_VERSION < 3
static void __Pyx_Raise(PyObject *type, PyObject *value, PyObject *tb,
                        CYTHON_UNUSED PyObject *cause) {
    __Pyx_PyThreadState_declare
    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 (PyType_Check(type)) {
#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;
        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;
        }
    }
    __Pyx_PyThreadState_assign
    __Pyx_ErrRestore(type, value, tb);
    return;
raise_error:
    Py_XDECREF(value);
    Py_XDECREF(type);
    Py_XDECREF(tb);
    return;
}
#else
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) {
                int is_subclass = PyObject_IsSubclass(instance_class, type);
                if (!is_subclass) {
                    instance_class = NULL;
                } else if (unlikely(is_subclass == -1)) {
                    goto bad;
                } else {
                    type = instance_class;
                }
            }
        }
        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) {
#if CYTHON_COMPILING_IN_PYPY
        PyObject *tmp_type, *tmp_value, *tmp_tb;
        PyErr_Fetch(&tmp_type, &tmp_value, &tmp_tb);
        Py_INCREF(tb);
        PyErr_Restore(tmp_type, tmp_value, tb);
        Py_XDECREF(tmp_tb);
#else
        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);
        }
#endif
    }
bad:
    Py_XDECREF(owned_instance);
    return;
}
#endif

/* UnicodeAsUCS4 */
  static CYTHON_INLINE Py_UCS4 __Pyx_PyUnicode_AsPy_UCS4(PyObject* x) {
   Py_ssize_t length;
   #if CYTHON_PEP393_ENABLED
   length = PyUnicode_GET_LENGTH(x);
   if (likely(length == 1)) {
       return PyUnicode_READ_CHAR(x, 0);
   }
   #else
   length = PyUnicode_GET_SIZE(x);
   if (likely(length == 1)) {
       return PyUnicode_AS_UNICODE(x)[0];
   }
   #if Py_UNICODE_SIZE == 2
   else if (PyUnicode_GET_SIZE(x) == 2) {
       Py_UCS4 high_val = PyUnicode_AS_UNICODE(x)[0];
       if (high_val >= 0xD800 && high_val <= 0xDBFF) {
           Py_UCS4 low_val = PyUnicode_AS_UNICODE(x)[1];
           if (low_val >= 0xDC00 && low_val <= 0xDFFF) {
               return 0x10000 + (((high_val & ((1<<10)-1)) << 10) | (low_val & ((1<<10)-1)));
           }
       }
   }
   #endif
   #endif
   PyErr_Format(PyExc_ValueError,
                "only single character unicode strings can be converted to Py_UCS4, "
                "got length %" CYTHON_FORMAT_SSIZE_T "d", length);
   return (Py_UCS4)-1;
}

/* object_ord */
  static long __Pyx__PyObject_Ord(PyObject* c) {
    Py_ssize_t size;
    if (PyBytes_Check(c)) {
        size = PyBytes_GET_SIZE(c);
        if (likely(size == 1)) {
            return (unsigned char) PyBytes_AS_STRING(c)[0];
        }
#if PY_MAJOR_VERSION < 3
    } else if (PyUnicode_Check(c)) {
        return (long)__Pyx_PyUnicode_AsPy_UCS4(c);
#endif
#if (!CYTHON_COMPILING_IN_PYPY) || (defined(PyByteArray_AS_STRING) && defined(PyByteArray_GET_SIZE))
    } else if (PyByteArray_Check(c)) {
        size = PyByteArray_GET_SIZE(c);
        if (likely(size == 1)) {
            return (unsigned char) PyByteArray_AS_STRING(c)[0];
        }
#endif
    } else {
        PyErr_Format(PyExc_TypeError,
            "ord() expected string of length 1, but %.200s found", c->ob_type->tp_name);
        return (long)(Py_UCS4)-1;
    }
    PyErr_Format(PyExc_TypeError,
        "ord() expected a character, but string of length %zd found", size);
    return (long)(Py_UCS4)-1;
}

/* BytesEquals */
  static CYTHON_INLINE int __Pyx_PyBytes_Equals(PyObject* s1, PyObject* s2, int equals) {
#if CYTHON_COMPILING_IN_PYPY
    return PyObject_RichCompareBool(s1, s2, equals);
#else
    if (s1 == s2) {
        return (equals == Py_EQ);
    } else if (PyBytes_CheckExact(s1) & PyBytes_CheckExact(s2)) {
        const char *ps1, *ps2;
        Py_ssize_t length = PyBytes_GET_SIZE(s1);
        if (length != PyBytes_GET_SIZE(s2))
            return (equals == Py_NE);
        ps1 = PyBytes_AS_STRING(s1);
        ps2 = PyBytes_AS_STRING(s2);
        if (ps1[0] != ps2[0]) {
            return (equals == Py_NE);
        } else if (length == 1) {
            return (equals == Py_EQ);
        } else {
            int result;
#if CYTHON_USE_UNICODE_INTERNALS
            Py_hash_t hash1, hash2;
            hash1 = ((PyBytesObject*)s1)->ob_shash;
            hash2 = ((PyBytesObject*)s2)->ob_shash;
            if (hash1 != hash2 && hash1 != -1 && hash2 != -1) {
                return (equals == Py_NE);
            }
#endif
            result = memcmp(ps1, ps2, (size_t)length);
            return (equals == Py_EQ) ? (result == 0) : (result != 0);
        }
    } else if ((s1 == Py_None) & PyBytes_CheckExact(s2)) {
        return (equals == Py_NE);
    } else if ((s2 == Py_None) & PyBytes_CheckExact(s1)) {
        return (equals == Py_NE);
    } else {
        int result;
        PyObject* py_result = PyObject_RichCompare(s1, s2, equals);
        if (!py_result)
            return -1;
        result = __Pyx_PyObject_IsTrue(py_result);
        Py_DECREF(py_result);
        return result;
    }
#endif
}

/* UnicodeEquals */
  static CYTHON_INLINE int __Pyx_PyUnicode_Equals(PyObject* s1, PyObject* s2, int equals) {
#if CYTHON_COMPILING_IN_PYPY
    return PyObject_RichCompareBool(s1, s2, equals);
#else
#if PY_MAJOR_VERSION < 3
    PyObject* owned_ref = NULL;
#endif
    int s1_is_unicode, s2_is_unicode;
    if (s1 == s2) {
        goto return_eq;
    }
    s1_is_unicode = PyUnicode_CheckExact(s1);
    s2_is_unicode = PyUnicode_CheckExact(s2);
#if PY_MAJOR_VERSION < 3
    if ((s1_is_unicode & (!s2_is_unicode)) && PyString_CheckExact(s2)) {
        owned_ref = PyUnicode_FromObject(s2);
        if (unlikely(!owned_ref))
            return -1;
        s2 = owned_ref;
        s2_is_unicode = 1;
    } else if ((s2_is_unicode & (!s1_is_unicode)) && PyString_CheckExact(s1)) {
        owned_ref = PyUnicode_FromObject(s1);
        if (unlikely(!owned_ref))
            return -1;
        s1 = owned_ref;
        s1_is_unicode = 1;
    } else if (((!s2_is_unicode) & (!s1_is_unicode))) {
        return __Pyx_PyBytes_Equals(s1, s2, equals);
    }
#endif
    if (s1_is_unicode & s2_is_unicode) {
        Py_ssize_t length;
        int kind;
        void *data1, *data2;
        if (unlikely(__Pyx_PyUnicode_READY(s1) < 0) || unlikely(__Pyx_PyUnicode_READY(s2) < 0))
            return -1;
        length = __Pyx_PyUnicode_GET_LENGTH(s1);
        if (length != __Pyx_PyUnicode_GET_LENGTH(s2)) {
            goto return_ne;
        }
#if CYTHON_USE_UNICODE_INTERNALS
        {
            Py_hash_t hash1, hash2;
        #if CYTHON_PEP393_ENABLED
            hash1 = ((PyASCIIObject*)s1)->hash;
            hash2 = ((PyASCIIObject*)s2)->hash;
        #else
            hash1 = ((PyUnicodeObject*)s1)->hash;
            hash2 = ((PyUnicodeObject*)s2)->hash;
        #endif
            if (hash1 != hash2 && hash1 != -1 && hash2 != -1) {
                goto return_ne;
            }
        }
#endif
        kind = __Pyx_PyUnicode_KIND(s1);
        if (kind != __Pyx_PyUnicode_KIND(s2)) {
            goto return_ne;
        }
        data1 = __Pyx_PyUnicode_DATA(s1);
        data2 = __Pyx_PyUnicode_DATA(s2);
        if (__Pyx_PyUnicode_READ(kind, data1, 0) != __Pyx_PyUnicode_READ(kind, data2, 0)) {
            goto return_ne;
        } else if (length == 1) {
            goto return_eq;
        } else {
            int result = memcmp(data1, data2, (size_t)(length * kind));
            #if PY_MAJOR_VERSION < 3
            Py_XDECREF(owned_ref);
            #endif
            return (equals == Py_EQ) ? (result == 0) : (result != 0);
        }
    } else if ((s1 == Py_None) & s2_is_unicode) {
        goto return_ne;
    } else if ((s2 == Py_None) & s1_is_unicode) {
        goto return_ne;
    } else {
        int result;
        PyObject* py_result = PyObject_RichCompare(s1, s2, equals);
        if (!py_result)
            return -1;
        result = __Pyx_PyObject_IsTrue(py_result);
        Py_DECREF(py_result);
        return result;
    }
return_eq:
    #if PY_MAJOR_VERSION < 3
    Py_XDECREF(owned_ref);
    #endif
    return (equals == Py_EQ);
return_ne:
    #if PY_MAJOR_VERSION < 3
    Py_XDECREF(owned_ref);
    #endif
    return (equals == Py_NE);
#endif
}

/* RaiseTooManyValuesToUnpack */
  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);
}

/* RaiseNeedMoreValuesToUnpack */
  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");
}

/* IterFinish */
  static CYTHON_INLINE int __Pyx_IterFinish(void) {
#if CYTHON_FAST_THREAD_STATE
    PyThreadState *tstate = PyThreadState_GET();
    PyObject* exc_type = tstate->curexc_type;
    if (unlikely(exc_type)) {
        if (likely(exc_type == PyExc_StopIteration) || PyErr_GivenExceptionMatches(exc_type, PyExc_StopIteration)) {
            PyObject *exc_value, *exc_tb;
            exc_value = tstate->curexc_value;
            exc_tb = tstate->curexc_traceback;
            tstate->curexc_type = 0;
            tstate->curexc_value = 0;
            tstate->curexc_traceback = 0;
            Py_DECREF(exc_type);
            Py_XDECREF(exc_value);
            Py_XDECREF(exc_tb);
            return 0;
        } else {
            return -1;
        }
    }
    return 0;
#else
    if (unlikely(PyErr_Occurred())) {
        if (likely(PyErr_ExceptionMatches(PyExc_StopIteration))) {
            PyErr_Clear();
            return 0;
        } else {
            return -1;
        }
    }
    return 0;
#endif
}

/* UnpackItemEndCheck */
  static int __Pyx_IternextUnpackEndCheck(PyObject *retval, Py_ssize_t expected) {
    if (unlikely(retval)) {
        Py_DECREF(retval);
        __Pyx_RaiseTooManyValuesError(expected);
        return -1;
    } else {
        return __Pyx_IterFinish();
    }
    return 0;
}

/* SetItemInt */
  static CYTHON_INLINE int __Pyx_SetItemInt_Generic(PyObject *o, PyObject *j, PyObject *v) {
    int r;
    if (!j) return -1;
    r = PyObject_SetItem(o, j, v);
    Py_DECREF(j);
    return r;
}
static CYTHON_INLINE int __Pyx_SetItemInt_Fast(PyObject *o, Py_ssize_t i, PyObject *v, int is_list,
                                               CYTHON_NCP_UNUSED int wraparound, CYTHON_NCP_UNUSED int boundscheck) {
#if CYTHON_ASSUME_SAFE_MACROS && !CYTHON_AVOID_BORROWED_REFS && CYTHON_USE_TYPE_SLOTS
    if (is_list || PyList_CheckExact(o)) {
        Py_ssize_t n = (!wraparound) ? i : ((likely(i >= 0)) ? i : i + PyList_GET_SIZE(o));
        if ((!boundscheck) || likely((n >= 0) & (n < PyList_GET_SIZE(o)))) {
            PyObject* old = PyList_GET_ITEM(o, n);
            Py_INCREF(v);
            PyList_SET_ITEM(o, n, v);
            Py_DECREF(old);
            return 1;
        }
    } else {
        PySequenceMethods *m = Py_TYPE(o)->tp_as_sequence;
        if (likely(m && m->sq_ass_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))
                        return -1;
                    PyErr_Clear();
                }
            }
            return m->sq_ass_item(o, i, v);
        }
    }
#else
#if CYTHON_COMPILING_IN_PYPY
    if (is_list || (PySequence_Check(o) && !PyDict_Check(o))) {
#else
    if (is_list || PySequence_Check(o)) {
#endif
        return PySequence_SetItem(o, i, v);
    }
#endif
    return __Pyx_SetItemInt_Generic(o, PyInt_FromSsize_t(i), v);
}

/* PyFunctionFastCall */
    #if CYTHON_FAST_PYCALL
#include "frameobject.h"
static PyObject* __Pyx_PyFunction_FastCallNoKw(PyCodeObject *co, PyObject **args, Py_ssize_t na,
                                               PyObject *globals) {
    PyFrameObject *f;
    PyThreadState *tstate = PyThreadState_GET();
    PyObject **fastlocals;
    Py_ssize_t i;
    PyObject *result;
    assert(globals != NULL);
    /* XXX Perhaps we should create a specialized
       PyFrame_New() that doesn't take locals, but does
       take builtins without sanity checking them.
       */
    assert(tstate != NULL);
    f = PyFrame_New(tstate, co, globals, NULL);
    if (f == NULL) {
        return NULL;
    }
    fastlocals = f->f_localsplus;
    for (i = 0; i < na; i++) {
        Py_INCREF(*args);
        fastlocals[i] = *args++;
    }
    result = PyEval_EvalFrameEx(f,0);
    ++tstate->recursion_depth;
    Py_DECREF(f);
    --tstate->recursion_depth;
    return result;
}
#if 1 || PY_VERSION_HEX < 0x030600B1
static PyObject *__Pyx_PyFunction_FastCallDict(PyObject *func, PyObject **args, int nargs, PyObject *kwargs) {
    PyCodeObject *co = (PyCodeObject *)PyFunction_GET_CODE(func);
    PyObject *globals = PyFunction_GET_GLOBALS(func);
    PyObject *argdefs = PyFunction_GET_DEFAULTS(func);
    PyObject *closure;
#if PY_MAJOR_VERSION >= 3
    PyObject *kwdefs;
#endif
    PyObject *kwtuple, **k;
    PyObject **d;
    Py_ssize_t nd;
    Py_ssize_t nk;
    PyObject *result;
    assert(kwargs == NULL || PyDict_Check(kwargs));
    nk = kwargs ? PyDict_Size(kwargs) : 0;
    if (Py_EnterRecursiveCall((char*)" while calling a Python object")) {
        return NULL;
    }
    if (
#if PY_MAJOR_VERSION >= 3
            co->co_kwonlyargcount == 0 &&
#endif
            likely(kwargs == NULL || nk == 0) &&
            co->co_flags == (CO_OPTIMIZED | CO_NEWLOCALS | CO_NOFREE)) {
        if (argdefs == NULL && co->co_argcount == nargs) {
            result = __Pyx_PyFunction_FastCallNoKw(co, args, nargs, globals);
            goto done;
        }
        else if (nargs == 0 && argdefs != NULL
                 && co->co_argcount == Py_SIZE(argdefs)) {
            /* function called with no arguments, but all parameters have
               a default value: use default values as arguments .*/
            args = &PyTuple_GET_ITEM(argdefs, 0);
            result =__Pyx_PyFunction_FastCallNoKw(co, args, Py_SIZE(argdefs), globals);
            goto done;
        }
    }
    if (kwargs != NULL) {
        Py_ssize_t pos, i;
        kwtuple = PyTuple_New(2 * nk);
        if (kwtuple == NULL) {
            result = NULL;
            goto done;
        }
        k = &PyTuple_GET_ITEM(kwtuple, 0);
        pos = i = 0;
        while (PyDict_Next(kwargs, &pos, &k[i], &k[i+1])) {
            Py_INCREF(k[i]);
            Py_INCREF(k[i+1]);
            i += 2;
        }
        nk = i / 2;
    }
    else {
        kwtuple = NULL;
        k = NULL;
    }
    closure = PyFunction_GET_CLOSURE(func);
#if PY_MAJOR_VERSION >= 3
    kwdefs = PyFunction_GET_KW_DEFAULTS(func);
#endif
    if (argdefs != NULL) {
        d = &PyTuple_GET_ITEM(argdefs, 0);
        nd = Py_SIZE(argdefs);
    }
    else {
        d = NULL;
        nd = 0;
    }
#if PY_MAJOR_VERSION >= 3
    result = PyEval_EvalCodeEx((PyObject*)co, globals, (PyObject *)NULL,
                               args, nargs,
                               k, (int)nk,
                               d, (int)nd, kwdefs, closure);
#else
    result = PyEval_EvalCodeEx(co, globals, (PyObject *)NULL,
                               args, nargs,
                               k, (int)nk,
                               d, (int)nd, closure);
#endif
    Py_XDECREF(kwtuple);
done:
    Py_LeaveRecursiveCall();
    return result;
}
#endif
#endif

/* PyObjectCallMethO */
    #if CYTHON_COMPILING_IN_CPYTHON
static CYTHON_INLINE PyObject* __Pyx_PyObject_CallMethO(PyObject *func, PyObject *arg) {
    PyObject *self, *result;
    PyCFunction cfunc;
    cfunc = PyCFunction_GET_FUNCTION(func);
    self = PyCFunction_GET_SELF(func);
    if (unlikely(Py_EnterRecursiveCall((char*)" while calling a Python object")))
        return NULL;
    result = cfunc(self, arg);
    Py_LeaveRecursiveCall();
    if (unlikely(!result) && unlikely(!PyErr_Occurred())) {
        PyErr_SetString(
            PyExc_SystemError,
            "NULL result without error in PyObject_Call");
    }
    return result;
}
#endif

/* PyObjectCallNoArg */
    #if CYTHON_COMPILING_IN_CPYTHON
static CYTHON_INLINE PyObject* __Pyx_PyObject_CallNoArg(PyObject *func) {
#if CYTHON_FAST_PYCALL
    if (PyFunction_Check(func)) {
        return __Pyx_PyFunction_FastCall(func, NULL, 0);
    }
#endif
#ifdef __Pyx_CyFunction_USED
    if (likely(PyCFunction_Check(func) || PyObject_TypeCheck(func, __pyx_CyFunctionType))) {
#else
    if (likely(PyCFunction_Check(func))) {
#endif
        if (likely(PyCFunction_GET_FLAGS(func) & METH_NOARGS)) {
            return __Pyx_PyObject_CallMethO(func, NULL);
        }
    }
    return __Pyx_PyObject_Call(func, __pyx_empty_tuple, NULL);
}
#endif

/* PyCFunctionFastCall */
      #if CYTHON_FAST_PYCCALL
static CYTHON_INLINE PyObject * __Pyx_PyCFunction_FastCall(PyObject *func_obj, PyObject **args, Py_ssize_t nargs) {
    PyCFunctionObject *func = (PyCFunctionObject*)func_obj;
    PyCFunction meth = PyCFunction_GET_FUNCTION(func);
    PyObject *self = PyCFunction_GET_SELF(func);
    int flags = PyCFunction_GET_FLAGS(func);
    assert(PyCFunction_Check(func));
    assert(METH_FASTCALL == (flags & ~(METH_CLASS | METH_STATIC | METH_COEXIST | METH_KEYWORDS)));
    assert(nargs >= 0);
    assert(nargs == 0 || args != NULL);
    /* _PyCFunction_FastCallDict() must not be called with an exception set,
       because it may clear it (directly or indirectly) and so the
       caller loses its exception */
    assert(!PyErr_Occurred());
    if ((PY_VERSION_HEX < 0x030700A0) || unlikely(flags & METH_KEYWORDS)) {
        return (*((__Pyx_PyCFunctionFastWithKeywords)meth)) (self, args, nargs, NULL);
    } else {
        return (*((__Pyx_PyCFunctionFast)meth)) (self, args, nargs);
    }
}
#endif

/* PyObjectCallOneArg */
      #if CYTHON_COMPILING_IN_CPYTHON
static PyObject* __Pyx__PyObject_CallOneArg(PyObject *func, PyObject *arg) {
    PyObject *result;
    PyObject *args = PyTuple_New(1);
    if (unlikely(!args)) return NULL;
    Py_INCREF(arg);
    PyTuple_SET_ITEM(args, 0, arg);
    result = __Pyx_PyObject_Call(func, args, NULL);
    Py_DECREF(args);
    return result;
}
static CYTHON_INLINE PyObject* __Pyx_PyObject_CallOneArg(PyObject *func, PyObject *arg) {
#if CYTHON_FAST_PYCALL
    if (PyFunction_Check(func)) {
        return __Pyx_PyFunction_FastCall(func, &arg, 1);
    }
#endif
    if (likely(PyCFunction_Check(func))) {
        if (likely(PyCFunction_GET_FLAGS(func) & METH_O)) {
            return __Pyx_PyObject_CallMethO(func, arg);
#if CYTHON_FAST_PYCCALL
        } else if (PyCFunction_GET_FLAGS(func) & METH_FASTCALL) {
            return __Pyx_PyCFunction_FastCall(func, &arg, 1);
#endif
        }
    }
    return __Pyx__PyObject_CallOneArg(func, arg);
}
#else
static CYTHON_INLINE PyObject* __Pyx_PyObject_CallOneArg(PyObject *func, PyObject *arg) {
    PyObject *result;
    PyObject *args = PyTuple_Pack(1, arg);
    if (unlikely(!args)) return NULL;
    result = __Pyx_PyObject_Call(func, args, NULL);
    Py_DECREF(args);
    return result;
}
#endif

/* PyObjectCallMethod0 */
      static PyObject* __Pyx_PyObject_CallMethod0(PyObject* obj, PyObject* method_name) {
    PyObject *method, *result = NULL;
    method = __Pyx_PyObject_GetAttrStr(obj, method_name);
    if (unlikely(!method)) goto bad;
#if CYTHON_UNPACK_METHODS
    if (likely(PyMethod_Check(method))) {
        PyObject *self = PyMethod_GET_SELF(method);
        if (likely(self)) {
            PyObject *function = PyMethod_GET_FUNCTION(method);
            result = __Pyx_PyObject_CallOneArg(function, self);
            Py_DECREF(method);
            return result;
        }
    }
#endif
    result = __Pyx_PyObject_CallNoArg(method);
    Py_DECREF(method);
bad:
    return result;
}

/* RaiseNoneIterError */
      static CYTHON_INLINE void __Pyx_RaiseNoneNotIterableError(void) {
    PyErr_SetString(PyExc_TypeError, "'NoneType' object is not iterable");
}

/* UnpackTupleError */
      static void __Pyx_UnpackTupleError(PyObject *t, Py_ssize_t index) {
    if (t == Py_None) {
      __Pyx_RaiseNoneNotIterableError();
    } else if (PyTuple_GET_SIZE(t) < index) {
      __Pyx_RaiseNeedMoreValuesError(PyTuple_GET_SIZE(t));
    } else {
      __Pyx_RaiseTooManyValuesError(index);
    }
}

/* UnpackTuple2 */
      static CYTHON_INLINE int __Pyx_unpack_tuple2(PyObject* tuple, PyObject** pvalue1, PyObject** pvalue2,
                                             int is_tuple, int has_known_size, int decref_tuple) {
    Py_ssize_t index;
    PyObject *value1 = NULL, *value2 = NULL, *iter = NULL;
    if (!is_tuple && unlikely(!PyTuple_Check(tuple))) {
        iternextfunc iternext;
        iter = PyObject_GetIter(tuple);
        if (unlikely(!iter)) goto bad;
        if (decref_tuple) { Py_DECREF(tuple); tuple = NULL; }
        iternext = Py_TYPE(iter)->tp_iternext;
        value1 = iternext(iter); if (unlikely(!value1)) { index = 0; goto unpacking_failed; }
        value2 = iternext(iter); if (unlikely(!value2)) { index = 1; goto unpacking_failed; }
        if (!has_known_size && unlikely(__Pyx_IternextUnpackEndCheck(iternext(iter), 2))) goto bad;
        Py_DECREF(iter);
    } else {
        if (!has_known_size && unlikely(PyTuple_GET_SIZE(tuple) != 2)) {
            __Pyx_UnpackTupleError(tuple, 2);
            goto bad;
        }
#if CYTHON_COMPILING_IN_PYPY
        value1 = PySequence_ITEM(tuple, 0);
        if (unlikely(!value1)) goto bad;
        value2 = PySequence_ITEM(tuple, 1);
        if (unlikely(!value2)) goto bad;
#else
        value1 = PyTuple_GET_ITEM(tuple, 0);
        value2 = PyTuple_GET_ITEM(tuple, 1);
        Py_INCREF(value1);
        Py_INCREF(value2);
#endif
        if (decref_tuple) { Py_DECREF(tuple); }
    }
    *pvalue1 = value1;
    *pvalue2 = value2;
    return 0;
unpacking_failed:
    if (!has_known_size && __Pyx_IterFinish() == 0)
        __Pyx_RaiseNeedMoreValuesError(index);
bad:
    Py_XDECREF(iter);
    Py_XDECREF(value1);
    Py_XDECREF(value2);
    if (decref_tuple) { Py_XDECREF(tuple); }
    return -1;
}

/* dict_iter */
      static CYTHON_INLINE PyObject* __Pyx_dict_iterator(PyObject* iterable, int is_dict, PyObject* method_name,
                                                   Py_ssize_t* p_orig_length, int* p_source_is_dict) {
    is_dict = is_dict || likely(PyDict_CheckExact(iterable));
    *p_source_is_dict = is_dict;
    if (is_dict) {
#if !CYTHON_COMPILING_IN_PYPY
        *p_orig_length = PyDict_Size(iterable);
        Py_INCREF(iterable);
        return iterable;
#elif PY_MAJOR_VERSION >= 3
        static PyObject *py_items = NULL, *py_keys = NULL, *py_values = NULL;
        const char *name = PyUnicode_AsUTF8(method_name);
        PyObject **pp = NULL;
        if (strcmp(name, "iteritems") == 0) pp = &py_items;
        else if (strcmp(name, "iterkeys") == 0) pp = &py_keys;
        else if (strcmp(name, "itervalues") == 0) pp = &py_values;
        if (pp) {
            if (!*pp) {
                *pp = PyUnicode_FromString(name + 4);
                if (!*pp)
                    return NULL;
            }
            method_name = *pp;
        }
#endif
    }
    *p_orig_length = 0;
    if (method_name) {
        PyObject* iter;
        iterable = __Pyx_PyObject_CallMethod0(iterable, method_name);
        if (!iterable)
            return NULL;
#if !CYTHON_COMPILING_IN_PYPY
        if (PyTuple_CheckExact(iterable) || PyList_CheckExact(iterable))
            return iterable;
#endif
        iter = PyObject_GetIter(iterable);
        Py_DECREF(iterable);
        return iter;
    }
    return PyObject_GetIter(iterable);
}
static CYTHON_INLINE int __Pyx_dict_iter_next(
        PyObject* iter_obj, CYTHON_NCP_UNUSED Py_ssize_t orig_length, CYTHON_NCP_UNUSED Py_ssize_t* ppos,
        PyObject** pkey, PyObject** pvalue, PyObject** pitem, int source_is_dict) {
    PyObject* next_item;
#if !CYTHON_COMPILING_IN_PYPY
    if (source_is_dict) {
        PyObject *key, *value;
        if (unlikely(orig_length != PyDict_Size(iter_obj))) {
            PyErr_SetString(PyExc_RuntimeError, "dictionary changed size during iteration");
            return -1;
        }
        if (unlikely(!PyDict_Next(iter_obj, ppos, &key, &value))) {
            return 0;
        }
        if (pitem) {
            PyObject* tuple = PyTuple_New(2);
            if (unlikely(!tuple)) {
                return -1;
            }
            Py_INCREF(key);
            Py_INCREF(value);
            PyTuple_SET_ITEM(tuple, 0, key);
            PyTuple_SET_ITEM(tuple, 1, value);
            *pitem = tuple;
        } else {
            if (pkey) {
                Py_INCREF(key);
                *pkey = key;
            }
            if (pvalue) {
                Py_INCREF(value);
                *pvalue = value;
            }
        }
        return 1;
    } else if (PyTuple_CheckExact(iter_obj)) {
        Py_ssize_t pos = *ppos;
        if (unlikely(pos >= PyTuple_GET_SIZE(iter_obj))) return 0;
        *ppos = pos + 1;
        next_item = PyTuple_GET_ITEM(iter_obj, pos);
        Py_INCREF(next_item);
    } else if (PyList_CheckExact(iter_obj)) {
        Py_ssize_t pos = *ppos;
        if (unlikely(pos >= PyList_GET_SIZE(iter_obj))) return 0;
        *ppos = pos + 1;
        next_item = PyList_GET_ITEM(iter_obj, pos);
        Py_INCREF(next_item);
    } else
#endif
    {
        next_item = PyIter_Next(iter_obj);
        if (unlikely(!next_item)) {
            return __Pyx_IterFinish();
        }
    }
    if (pitem) {
        *pitem = next_item;
    } else if (pkey && pvalue) {
        if (__Pyx_unpack_tuple2(next_item, pkey, pvalue, source_is_dict, source_is_dict, 1))
            return -1;
    } else if (pkey) {
        *pkey = next_item;
    } else {
        *pvalue = next_item;
    }
    return 1;
}

/* GetItemInt */
      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,
                                                              CYTHON_NCP_UNUSED int wraparound,
                                                              CYTHON_NCP_UNUSED int boundscheck) {
#if CYTHON_ASSUME_SAFE_MACROS && !CYTHON_AVOID_BORROWED_REFS
    Py_ssize_t wrapped_i = i;
    if (wraparound & unlikely(i < 0)) {
        wrapped_i += PyList_GET_SIZE(o);
    }
    if ((!boundscheck) || likely((0 <= wrapped_i) & (wrapped_i < PyList_GET_SIZE(o)))) {
        PyObject *r = PyList_GET_ITEM(o, wrapped_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,
                                                              CYTHON_NCP_UNUSED int wraparound,
                                                              CYTHON_NCP_UNUSED int boundscheck) {
#if CYTHON_ASSUME_SAFE_MACROS && !CYTHON_AVOID_BORROWED_REFS
    Py_ssize_t wrapped_i = i;
    if (wraparound & unlikely(i < 0)) {
        wrapped_i += PyTuple_GET_SIZE(o);
    }
    if ((!boundscheck) || likely((0 <= wrapped_i) & (wrapped_i < PyTuple_GET_SIZE(o)))) {
        PyObject *r = PyTuple_GET_ITEM(o, wrapped_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,
                                                     CYTHON_NCP_UNUSED int wraparound,
                                                     CYTHON_NCP_UNUSED int boundscheck) {
#if CYTHON_ASSUME_SAFE_MACROS && !CYTHON_AVOID_BORROWED_REFS && CYTHON_USE_TYPE_SLOTS
    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))
                        return NULL;
                    PyErr_Clear();
                }
            }
            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));
}

/* ArgTypeTest */
      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;
}

/* IsLittleEndian */
      static CYTHON_INLINE int __Pyx_Is_Little_Endian(void)
{
  union {
    uint32_t u32;
    uint8_t u8[4];
  } S;
  S.u32 = 0x01020304;
  return S.u8[0] == 4;
}

/* BufferFormatCheck */
      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)
        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;
    while (1) {
      if (field == &ctx->root) {
        ctx->head = NULL;
        if (ctx->enc_count != 0) {
          __Pyx_BufFmt_RaiseExpected(ctx);
          return -1;
        }
        break;
      }
      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;
        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;
        }
        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 '\r':
      case '\n':
        ++ts;
        break;
      case '<':
        if (!__Pyx_Is_Little_Endian()) {
          PyErr_SetString(PyExc_ValueError, "Little-endian buffer not supported on big-endian compiler");
          return NULL;
        }
        ctx->new_packmode = '=';
        ++ts;
        break;
      case '>':
      case '!':
        if (__Pyx_Is_Little_Endian()) {
          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':
        {
          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;
          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 '}':
        {
          size_t alignment = ctx->struct_alignment;
          ++ts;
          if (__Pyx_BufFmt_ProcessTypeChunk(ctx) == -1) return NULL;
          ctx->enc_type = 0;
          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;
        }
      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 'p':
        if (ctx->enc_type == *ts && got_Z == ctx->is_complex &&
            ctx->enc_packmode == ctx->new_packmode) {
          ctx->enc_count += ctx->new_count;
          ctx->new_count = 1;
          got_Z = 0;
          ++ts;
          break;
        }
      case 's':
        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);
}

/* GetModuleGlobalName */
        static CYTHON_INLINE PyObject *__Pyx_GetModuleGlobalName(PyObject *name) {
    PyObject *result;
#if !CYTHON_AVOID_BORROWED_REFS
    result = PyDict_GetItem(__pyx_d, name);
    if (likely(result)) {
        Py_INCREF(result);
    } else {
#else
    result = PyObject_GetItem(__pyx_d, name);
    if (!result) {
        PyErr_Clear();
#endif
        result = __Pyx_GetBuiltinName(name);
    }
    return result;
}

/* ExtTypeTest */
          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;
}

/* MemviewSliceInit */
          static int
__Pyx_init_memviewslice(struct __pyx_memoryview_obj *memview,
                        int ndim,
                        __Pyx_memviewslice *memviewslice,
                        int memview_is_new_reference)
{
    __Pyx_RefNannyDeclarations
    int i, retval=-1;
    Py_buffer *buf = &memview->view;
    __Pyx_RefNannySetupContext("init_memviewslice", 0);
    if (!buf) {
        PyErr_SetString(PyExc_ValueError,
            "buf is NULL.");
        goto fail;
    } else if (memviewslice->memview || memviewslice->data) {
        PyErr_SetString(PyExc_ValueError,
            "memviewslice is already initialized!");
        goto fail;
    }
    if (buf->strides) {
        for (i = 0; i < ndim; i++) {
            memviewslice->strides[i] = buf->strides[i];
        }
    } else {
        Py_ssize_t stride = buf->itemsize;
        for (i = ndim - 1; i >= 0; i--) {
            memviewslice->strides[i] = stride;
            stride *= buf->shape[i];
        }
    }
    for (i = 0; i < ndim; i++) {
        memviewslice->shape[i]   = buf->shape[i];
        if (buf->suboffsets) {
            memviewslice->suboffsets[i] = buf->suboffsets[i];
        } else {
            memviewslice->suboffsets[i] = -1;
        }
    }
    memviewslice->memview = memview;
    memviewslice->data = (char *)buf->buf;
    if (__pyx_add_acquisition_count(memview) == 0 && !memview_is_new_reference) {
        Py_INCREF(memview);
    }
    retval = 0;
    goto no_fail;
fail:
    memviewslice->memview = 0;
    memviewslice->data = 0;
    retval = -1;
no_fail:
    __Pyx_RefNannyFinishContext();
    return retval;
}
static CYTHON_INLINE void __pyx_fatalerror(const char *fmt, ...) {
    va_list vargs;
    char msg[200];
#ifdef HAVE_STDARG_PROTOTYPES
    va_start(vargs, fmt);
#else
    va_start(vargs);
#endif
    vsnprintf(msg, 200, fmt, vargs);
    Py_FatalError(msg);
    va_end(vargs);
}
static CYTHON_INLINE int
__pyx_add_acquisition_count_locked(__pyx_atomic_int *acquisition_count,
                                   PyThread_type_lock lock)
{
    int result;
    PyThread_acquire_lock(lock, 1);
    result = (*acquisition_count)++;
    PyThread_release_lock(lock);
    return result;
}
static CYTHON_INLINE int
__pyx_sub_acquisition_count_locked(__pyx_atomic_int *acquisition_count,
                                   PyThread_type_lock lock)
{
    int result;
    PyThread_acquire_lock(lock, 1);
    result = (*acquisition_count)--;
    PyThread_release_lock(lock);
    return result;
}
static CYTHON_INLINE void
__Pyx_INC_MEMVIEW(__Pyx_memviewslice *memslice, int have_gil, int lineno)
{
    int first_time;
    struct __pyx_memoryview_obj *memview = memslice->memview;
    if (!memview || (PyObject *) memview == Py_None)
        return;
    if (__pyx_get_slice_count(memview) < 0)
        __pyx_fatalerror("Acquisition count is %d (line %d)",
                         __pyx_get_slice_count(memview), lineno);
    first_time = __pyx_add_acquisition_count(memview) == 0;
    if (first_time) {
        if (have_gil) {
            Py_INCREF((PyObject *) memview);
        } else {
            PyGILState_STATE _gilstate = PyGILState_Ensure();
            Py_INCREF((PyObject *) memview);
            PyGILState_Release(_gilstate);
        }
    }
}
static CYTHON_INLINE void __Pyx_XDEC_MEMVIEW(__Pyx_memviewslice *memslice,
                                             int have_gil, int lineno) {
    int last_time;
    struct __pyx_memoryview_obj *memview = memslice->memview;
    if (!memview ) {
        return;
    } else if ((PyObject *) memview == Py_None) {
        memslice->memview = NULL;
        return;
    }
    if (__pyx_get_slice_count(memview) <= 0)
        __pyx_fatalerror("Acquisition count is %d (line %d)",
                         __pyx_get_slice_count(memview), lineno);
    last_time = __pyx_sub_acquisition_count(memview) == 1;
    memslice->data = NULL;
    if (last_time) {
        if (have_gil) {
            Py_CLEAR(memslice->memview);
        } else {
            PyGILState_STATE _gilstate = PyGILState_Ensure();
            Py_CLEAR(memslice->memview);
            PyGILState_Release(_gilstate);
        }
    } else {
        memslice->memview = NULL;
    }
}

/* SaveResetException */
          #if CYTHON_FAST_THREAD_STATE
static CYTHON_INLINE void __Pyx__ExceptionSave(PyThreadState *tstate, PyObject **type, PyObject **value, PyObject **tb) {
    *type = tstate->exc_type;
    *value = tstate->exc_value;
    *tb = tstate->exc_traceback;
    Py_XINCREF(*type);
    Py_XINCREF(*value);
    Py_XINCREF(*tb);
}
static CYTHON_INLINE void __Pyx__ExceptionReset(PyThreadState *tstate, PyObject *type, PyObject *value, PyObject *tb) {
    PyObject *tmp_type, *tmp_value, *tmp_tb;
    tmp_type = tstate->exc_type;
    tmp_value = tstate->exc_value;
    tmp_tb = tstate->exc_traceback;
    tstate->exc_type = type;
    tstate->exc_value = value;
    tstate->exc_traceback = tb;
    Py_XDECREF(tmp_type);
    Py_XDECREF(tmp_value);
    Py_XDECREF(tmp_tb);
}
#endif

/* PyErrExceptionMatches */
          #if CYTHON_FAST_THREAD_STATE
static CYTHON_INLINE int __Pyx_PyErr_ExceptionMatchesInState(PyThreadState* tstate, PyObject* err) {
    PyObject *exc_type = tstate->curexc_type;
    if (exc_type == err) return 1;
    if (unlikely(!exc_type)) return 0;
    return PyErr_GivenExceptionMatches(exc_type, err);
}
#endif

/* GetException */
          #if CYTHON_FAST_THREAD_STATE
static int __Pyx__GetException(PyThreadState *tstate, PyObject **type, PyObject **value, PyObject **tb) {
#else
static int __Pyx_GetException(PyObject **type, PyObject **value, PyObject **tb) {
#endif
    PyObject *local_type, *local_value, *local_tb;
#if CYTHON_FAST_THREAD_STATE
    PyObject *tmp_type, *tmp_value, *tmp_tb;
    local_type = tstate->curexc_type;
    local_value = tstate->curexc_value;
    local_tb = tstate->curexc_traceback;
    tstate->curexc_type = 0;
    tstate->curexc_value = 0;
    tstate->curexc_traceback = 0;
#else
    PyErr_Fetch(&local_type, &local_value, &local_tb);
#endif
    PyErr_NormalizeException(&local_type, &local_value, &local_tb);
#if CYTHON_FAST_THREAD_STATE
    if (unlikely(tstate->curexc_type))
#else
    if (unlikely(PyErr_Occurred()))
#endif
        goto bad;
    #if PY_MAJOR_VERSION >= 3
    if (local_tb) {
        if (unlikely(PyException_SetTraceback(local_value, local_tb) < 0))
            goto bad;
    }
    #endif
    Py_XINCREF(local_tb);
    Py_XINCREF(local_type);
    Py_XINCREF(local_value);
    *type = local_type;
    *value = local_value;
    *tb = local_tb;
#if CYTHON_FAST_THREAD_STATE
    tmp_type = tstate->exc_type;
    tmp_value = tstate->exc_value;
    tmp_tb = tstate->exc_traceback;
    tstate->exc_type = local_type;
    tstate->exc_value = local_value;
    tstate->exc_traceback = local_tb;
    Py_XDECREF(tmp_type);
    Py_XDECREF(tmp_value);
    Py_XDECREF(tmp_tb);
#else
    PyErr_SetExcInfo(local_type, local_value, local_tb);
#endif
    return 0;
bad:
    *type = 0;
    *value = 0;
    *tb = 0;
    Py_XDECREF(local_type);
    Py_XDECREF(local_value);
    Py_XDECREF(local_tb);
    return -1;
}

/* None */
            static CYTHON_INLINE Py_ssize_t __Pyx_div_Py_ssize_t(Py_ssize_t a, Py_ssize_t b) {
    Py_ssize_t q = a / b;
    Py_ssize_t r = a - q*b;
    q -= ((r != 0) & ((r ^ b) < 0));
    return q;
}

/* GetAttr */
            static CYTHON_INLINE PyObject *__Pyx_GetAttr(PyObject *o, PyObject *n) {
#if CYTHON_COMPILING_IN_CPYTHON
#if PY_MAJOR_VERSION >= 3
    if (likely(PyUnicode_Check(n)))
#else
    if (likely(PyString_Check(n)))
#endif
        return __Pyx_PyObject_GetAttrStr(o, n);
#endif
    return PyObject_GetAttr(o, n);
}

/* decode_c_string */
            static CYTHON_INLINE PyObject* __Pyx_decode_c_string(
         const char* cstring, Py_ssize_t start, Py_ssize_t stop,
         const char* encoding, const char* errors,
         PyObject* (*decode_func)(const char *s, Py_ssize_t size, const char *errors)) {
    Py_ssize_t length;
    if (unlikely((start < 0) | (stop < 0))) {
        size_t slen = strlen(cstring);
        if (unlikely(slen > (size_t) PY_SSIZE_T_MAX)) {
            PyErr_SetString(PyExc_OverflowError,
                            "c-string too long to convert to Python");
            return NULL;
        }
        length = (Py_ssize_t) slen;
        if (start < 0) {
            start += length;
            if (start < 0)
                start = 0;
        }
        if (stop < 0)
            stop += length;
    }
    length = stop - start;
    if (unlikely(length <= 0))
        return PyUnicode_FromUnicode(NULL, 0);
    cstring += start;
    if (decode_func) {
        return decode_func(cstring, length, errors);
    } else {
        return PyUnicode_Decode(cstring, length, encoding, errors);
    }
}

/* GetAttr3 */
            static CYTHON_INLINE PyObject *__Pyx_GetAttr3(PyObject *o, PyObject *n, PyObject *d) {
    PyObject *r = __Pyx_GetAttr(o, n);
    if (unlikely(!r)) {
        if (!PyErr_ExceptionMatches(PyExc_AttributeError))
            goto bad;
        PyErr_Clear();
        r = d;
        Py_INCREF(d);
    }
    return r;
bad:
    return NULL;
}

/* SwapException */
            #if CYTHON_FAST_THREAD_STATE
static CYTHON_INLINE void __Pyx__ExceptionSwap(PyThreadState *tstate, PyObject **type, PyObject **value, PyObject **tb) {
    PyObject *tmp_type, *tmp_value, *tmp_tb;
    tmp_type = tstate->exc_type;
    tmp_value = tstate->exc_value;
    tmp_tb = tstate->exc_traceback;
    tstate->exc_type = *type;
    tstate->exc_value = *value;
    tstate->exc_traceback = *tb;
    *type = tmp_type;
    *value = tmp_value;
    *tb = tmp_tb;
}
#else
static CYTHON_INLINE void __Pyx_ExceptionSwap(PyObject **type, PyObject **value, PyObject **tb) {
    PyObject *tmp_type, *tmp_value, *tmp_tb;
    PyErr_GetExcInfo(&tmp_type, &tmp_value, &tmp_tb);
    PyErr_SetExcInfo(*type, *value, *tb);
    *type = tmp_type;
    *value = tmp_value;
    *tb = tmp_tb;
}
#endif

/* Import */
            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_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;
        }
        #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
        }
    }
bad:
    #if PY_VERSION_HEX < 0x03030000
    Py_XDECREF(py_import);
    #endif
    Py_XDECREF(empty_list);
    Py_XDECREF(empty_dict);
    return module;
}

/* PyIntBinop */
            #if !CYTHON_COMPILING_IN_PYPY
static PyObject* __Pyx_PyInt_AddObjC(PyObject *op1, PyObject *op2, CYTHON_UNUSED long intval, CYTHON_UNUSED int inplace) {
    #if PY_MAJOR_VERSION < 3
    if (likely(PyInt_CheckExact(op1))) {
        const long b = intval;
        long x;
        long a = PyInt_AS_LONG(op1);
            x = (long)((unsigned long)a + b);
            if (likely((x^a) >= 0 || (x^b) >= 0))
                return PyInt_FromLong(x);
            return PyLong_Type.tp_as_number->nb_add(op1, op2);
    }
    #endif
    #if CYTHON_USE_PYLONG_INTERNALS
    if (likely(PyLong_CheckExact(op1))) {
        const long b = intval;
        long a, x;
#ifdef HAVE_LONG_LONG
        const PY_LONG_LONG llb = intval;
        PY_LONG_LONG lla, llx;
#endif
        const digit* digits = ((PyLongObject*)op1)->ob_digit;
        const Py_ssize_t size = Py_SIZE(op1);
        if (likely(__Pyx_sst_abs(size) <= 1)) {
            a = likely(size) ? digits[0] : 0;
            if (size == -1) a = -a;
        } else {
            switch (size) {
                case -2:
                    if (8 * sizeof(long) - 1 > 2 * PyLong_SHIFT) {
                        a = -(long) (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]));
                        break;
#ifdef HAVE_LONG_LONG
                    } else if (8 * sizeof(PY_LONG_LONG) - 1 > 2 * PyLong_SHIFT) {
                        lla = -(PY_LONG_LONG) (((((unsigned PY_LONG_LONG)digits[1]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[0]));
                        goto long_long;
#endif
                    }
                case 2:
                    if (8 * sizeof(long) - 1 > 2 * PyLong_SHIFT) {
                        a = (long) (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]));
                        break;
#ifdef HAVE_LONG_LONG
                    } else if (8 * sizeof(PY_LONG_LONG) - 1 > 2 * PyLong_SHIFT) {
                        lla = (PY_LONG_LONG) (((((unsigned PY_LONG_LONG)digits[1]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[0]));
                        goto long_long;
#endif
                    }
                case -3:
                    if (8 * sizeof(long) - 1 > 3 * PyLong_SHIFT) {
                        a = -(long) (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]));
                        break;
#ifdef HAVE_LONG_LONG
                    } else if (8 * sizeof(PY_LONG_LONG) - 1 > 3 * PyLong_SHIFT) {
                        lla = -(PY_LONG_LONG) (((((((unsigned PY_LONG_LONG)digits[2]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[1]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[0]));
                        goto long_long;
#endif
                    }
                case 3:
                    if (8 * sizeof(long) - 1 > 3 * PyLong_SHIFT) {
                        a = (long) (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]));
                        break;
#ifdef HAVE_LONG_LONG
                    } else if (8 * sizeof(PY_LONG_LONG) - 1 > 3 * PyLong_SHIFT) {
                        lla = (PY_LONG_LONG) (((((((unsigned PY_LONG_LONG)digits[2]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[1]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[0]));
                        goto long_long;
#endif
                    }
                case -4:
                    if (8 * sizeof(long) - 1 > 4 * PyLong_SHIFT) {
                        a = -(long) (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]));
                        break;
#ifdef HAVE_LONG_LONG
                    } else if (8 * sizeof(PY_LONG_LONG) - 1 > 4 * PyLong_SHIFT) {
                        lla = -(PY_LONG_LONG) (((((((((unsigned PY_LONG_LONG)digits[3]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[2]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[1]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[0]));
                        goto long_long;
#endif
                    }
                case 4:
                    if (8 * sizeof(long) - 1 > 4 * PyLong_SHIFT) {
                        a = (long) (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]));
                        break;
#ifdef HAVE_LONG_LONG
                    } else if (8 * sizeof(PY_LONG_LONG) - 1 > 4 * PyLong_SHIFT) {
                        lla = (PY_LONG_LONG) (((((((((unsigned PY_LONG_LONG)digits[3]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[2]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[1]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[0]));
                        goto long_long;
#endif
                    }
                default: return PyLong_Type.tp_as_number->nb_add(op1, op2);
            }
        }
                x = a + b;
            return PyLong_FromLong(x);
#ifdef HAVE_LONG_LONG
        long_long:
                llx = lla + llb;
            return PyLong_FromLongLong(llx);
#endif
        
        
    }
    #endif
    if (PyFloat_CheckExact(op1)) {
        const long b = intval;
        double a = PyFloat_AS_DOUBLE(op1);
            double result;
            PyFPE_START_PROTECT("add", return NULL)
            result = ((double)a) + (double)b;
            PyFPE_END_PROTECT(result)
            return PyFloat_FromDouble(result);
    }
    return (inplace ? PyNumber_InPlaceAdd : PyNumber_Add)(op1, op2);
}
#endif

/* None */
            static CYTHON_INLINE void __Pyx_RaiseUnboundLocalError(const char *varname) {
    PyErr_Format(PyExc_UnboundLocalError, "local variable '%s' referenced before assignment", varname);
}

/* None */
            static CYTHON_INLINE long __Pyx_div_long(long a, long b) {
    long q = a / b;
    long r = a - q*b;
    q -= ((r != 0) & ((r ^ b) < 0));
    return q;
}

/* ImportFrom */
            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;
}

/* HasAttr */
            static CYTHON_INLINE int __Pyx_HasAttr(PyObject *o, PyObject *n) {
    PyObject *r;
    if (unlikely(!__Pyx_PyBaseString_Check(n))) {
        PyErr_SetString(PyExc_TypeError,
                        "hasattr(): attribute name must be string");
        return -1;
    }
    r = __Pyx_GetAttr(o, n);
    if (unlikely(!r)) {
        PyErr_Clear();
        return 0;
    } else {
        Py_DECREF(r);
        return 1;
    }
}

/* SetVTable */
            static int __Pyx_SetVtable(PyObject *dict, void *vtable) {
#if PY_VERSION_HEX >= 0x02070000
    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;
}

/* SetupReduce */
            static int __Pyx_setup_reduce_is_named(PyObject* meth, PyObject* name) {
  int ret;
  PyObject *name_attr;
  name_attr = __Pyx_PyObject_GetAttrStr(meth, __pyx_n_s_name_2);
  if (likely(name_attr)) {
      ret = PyObject_RichCompareBool(name_attr, name, Py_EQ);
  } else {
      ret = -1;
  }
  if (unlikely(ret < 0)) {
      PyErr_Clear();
      ret = 0;
  }
  Py_XDECREF(name_attr);
  return ret;
}
static int __Pyx_setup_reduce(PyObject* type_obj) {
    int ret = 0;
    PyObject *object_reduce = NULL;
    PyObject *object_reduce_ex = NULL;
    PyObject *reduce = NULL;
    PyObject *reduce_ex = NULL;
    PyObject *reduce_cython = NULL;
    PyObject *setstate = NULL;
    PyObject *setstate_cython = NULL;
#if CYTHON_USE_PYTYPE_LOOKUP
    if (_PyType_Lookup((PyTypeObject*)type_obj, __pyx_n_s_getstate)) goto GOOD;
#else
    if (PyObject_HasAttr(type_obj, __pyx_n_s_getstate)) goto GOOD;
#endif
#if CYTHON_USE_PYTYPE_LOOKUP
    object_reduce_ex = _PyType_Lookup(&PyBaseObject_Type, __pyx_n_s_reduce_ex); if (!object_reduce_ex) goto BAD;
#else
    object_reduce_ex = __Pyx_PyObject_GetAttrStr((PyObject*)&PyBaseObject_Type, __pyx_n_s_reduce_ex); if (!object_reduce_ex) goto BAD;
#endif
    reduce_ex = __Pyx_PyObject_GetAttrStr(type_obj, __pyx_n_s_reduce_ex); if (unlikely(!reduce_ex)) goto BAD;
    if (reduce_ex == object_reduce_ex) {
#if CYTHON_USE_PYTYPE_LOOKUP
        object_reduce = _PyType_Lookup(&PyBaseObject_Type, __pyx_n_s_reduce); if (!object_reduce) goto BAD;
#else
        object_reduce = __Pyx_PyObject_GetAttrStr((PyObject*)&PyBaseObject_Type, __pyx_n_s_reduce); if (!object_reduce) goto BAD;
#endif
        reduce = __Pyx_PyObject_GetAttrStr(type_obj, __pyx_n_s_reduce); if (unlikely(!reduce)) goto BAD;
        if (reduce == object_reduce || __Pyx_setup_reduce_is_named(reduce, __pyx_n_s_reduce_cython)) {
            reduce_cython = __Pyx_PyObject_GetAttrStr(type_obj, __pyx_n_s_reduce_cython); if (unlikely(!reduce_cython)) goto BAD;
            ret = PyDict_SetItem(((PyTypeObject*)type_obj)->tp_dict, __pyx_n_s_reduce, reduce_cython); if (unlikely(ret < 0)) goto BAD;
            ret = PyDict_DelItem(((PyTypeObject*)type_obj)->tp_dict, __pyx_n_s_reduce_cython); if (unlikely(ret < 0)) goto BAD;
            setstate = __Pyx_PyObject_GetAttrStr(type_obj, __pyx_n_s_setstate);
            if (!setstate) PyErr_Clear();
            if (!setstate || __Pyx_setup_reduce_is_named(setstate, __pyx_n_s_setstate_cython)) {
                setstate_cython = __Pyx_PyObject_GetAttrStr(type_obj, __pyx_n_s_setstate_cython); if (unlikely(!setstate_cython)) goto BAD;
                ret = PyDict_SetItem(((PyTypeObject*)type_obj)->tp_dict, __pyx_n_s_setstate, setstate_cython); if (unlikely(ret < 0)) goto BAD;
                ret = PyDict_DelItem(((PyTypeObject*)type_obj)->tp_dict, __pyx_n_s_setstate_cython); if (unlikely(ret < 0)) goto BAD;
            }
            PyType_Modified((PyTypeObject*)type_obj);
        }
    }
    goto GOOD;
BAD:
    if (!PyErr_Occurred())
        PyErr_Format(PyExc_RuntimeError, "Unable to initialize pickling for %s", ((PyTypeObject*)type_obj)->tp_name);
    ret = -1;
GOOD:
#if !CYTHON_COMPILING_IN_CPYTHON
    Py_XDECREF(object_reduce);
    Py_XDECREF(object_reduce_ex);
#endif
    Py_XDECREF(reduce);
    Py_XDECREF(reduce_ex);
    Py_XDECREF(reduce_cython);
    Py_XDECREF(setstate);
    Py_XDECREF(setstate_cython);
    return ret;
}

/* FetchCommonType */
            static PyTypeObject* __Pyx_FetchCommonType(PyTypeObject* type) {
    PyObject* fake_module;
    PyTypeObject* cached_type = NULL;
    fake_module = PyImport_AddModule((char*) "_cython_" CYTHON_ABI);
    if (!fake_module) return NULL;
    Py_INCREF(fake_module);
    cached_type = (PyTypeObject*) PyObject_GetAttrString(fake_module, type->tp_name);
    if (cached_type) {
        if (!PyType_Check((PyObject*)cached_type)) {
            PyErr_Format(PyExc_TypeError,
                "Shared Cython type %.200s is not a type object",
                type->tp_name);
            goto bad;
        }
        if (cached_type->tp_basicsize != type->tp_basicsize) {
            PyErr_Format(PyExc_TypeError,
                "Shared Cython type %.200s has the wrong size, try recompiling",
                type->tp_name);
            goto bad;
        }
    } else {
        if (!PyErr_ExceptionMatches(PyExc_AttributeError)) goto bad;
        PyErr_Clear();
        if (PyType_Ready(type) < 0) goto bad;
        if (PyObject_SetAttrString(fake_module, type->tp_name, (PyObject*) type) < 0)
            goto bad;
        Py_INCREF(type);
        cached_type = type;
    }
done:
    Py_DECREF(fake_module);
    return cached_type;
bad:
    Py_XDECREF(cached_type);
    cached_type = NULL;
    goto done;
}

/* CythonFunction */
            static PyObject *
__Pyx_CyFunction_get_doc(__pyx_CyFunctionObject *op, CYTHON_UNUSED void *closure)
{
    if (unlikely(op->func_doc == NULL)) {
        if (op->func.m_ml->ml_doc) {
#if PY_MAJOR_VERSION >= 3
            op->func_doc = PyUnicode_FromString(op->func.m_ml->ml_doc);
#else
            op->func_doc = PyString_FromString(op->func.m_ml->ml_doc);
#endif
            if (unlikely(op->func_doc == NULL))
                return NULL;
        } else {
            Py_INCREF(Py_None);
            return Py_None;
        }
    }
    Py_INCREF(op->func_doc);
    return op->func_doc;
}
static int
__Pyx_CyFunction_set_doc(__pyx_CyFunctionObject *op, PyObject *value)
{
    PyObject *tmp = op->func_doc;
    if (value == NULL) {
        value = Py_None;
    }
    Py_INCREF(value);
    op->func_doc = value;
    Py_XDECREF(tmp);
    return 0;
}
static PyObject *
__Pyx_CyFunction_get_name(__pyx_CyFunctionObject *op)
{
    if (unlikely(op->func_name == NULL)) {
#if PY_MAJOR_VERSION >= 3
        op->func_name = PyUnicode_InternFromString(op->func.m_ml->ml_name);
#else
        op->func_name = PyString_InternFromString(op->func.m_ml->ml_name);
#endif
        if (unlikely(op->func_name == NULL))
            return NULL;
    }
    Py_INCREF(op->func_name);
    return op->func_name;
}
static int
__Pyx_CyFunction_set_name(__pyx_CyFunctionObject *op, PyObject *value)
{
    PyObject *tmp;
#if PY_MAJOR_VERSION >= 3
    if (unlikely(value == NULL || !PyUnicode_Check(value))) {
#else
    if (unlikely(value == NULL || !PyString_Check(value))) {
#endif
        PyErr_SetString(PyExc_TypeError,
                        "__name__ must be set to a string object");
        return -1;
    }
    tmp = op->func_name;
    Py_INCREF(value);
    op->func_name = value;
    Py_XDECREF(tmp);
    return 0;
}
static PyObject *
__Pyx_CyFunction_get_qualname(__pyx_CyFunctionObject *op)
{
    Py_INCREF(op->func_qualname);
    return op->func_qualname;
}
static int
__Pyx_CyFunction_set_qualname(__pyx_CyFunctionObject *op, PyObject *value)
{
    PyObject *tmp;
#if PY_MAJOR_VERSION >= 3
    if (unlikely(value == NULL || !PyUnicode_Check(value))) {
#else
    if (unlikely(value == NULL || !PyString_Check(value))) {
#endif
        PyErr_SetString(PyExc_TypeError,
                        "__qualname__ must be set to a string object");
        return -1;
    }
    tmp = op->func_qualname;
    Py_INCREF(value);
    op->func_qualname = value;
    Py_XDECREF(tmp);
    return 0;
}
static PyObject *
__Pyx_CyFunction_get_self(__pyx_CyFunctionObject *m, CYTHON_UNUSED void *closure)
{
    PyObject *self;
    self = m->func_closure;
    if (self == NULL)
        self = Py_None;
    Py_INCREF(self);
    return self;
}
static PyObject *
__Pyx_CyFunction_get_dict(__pyx_CyFunctionObject *op)
{
    if (unlikely(op->func_dict == NULL)) {
        op->func_dict = PyDict_New();
        if (unlikely(op->func_dict == NULL))
            return NULL;
    }
    Py_INCREF(op->func_dict);
    return op->func_dict;
}
static int
__Pyx_CyFunction_set_dict(__pyx_CyFunctionObject *op, PyObject *value)
{
    PyObject *tmp;
    if (unlikely(value == NULL)) {
        PyErr_SetString(PyExc_TypeError,
               "function's dictionary may not be deleted");
        return -1;
    }
    if (unlikely(!PyDict_Check(value))) {
        PyErr_SetString(PyExc_TypeError,
               "setting function's dictionary to a non-dict");
        return -1;
    }
    tmp = op->func_dict;
    Py_INCREF(value);
    op->func_dict = value;
    Py_XDECREF(tmp);
    return 0;
}
static PyObject *
__Pyx_CyFunction_get_globals(__pyx_CyFunctionObject *op)
{
    Py_INCREF(op->func_globals);
    return op->func_globals;
}
static PyObject *
__Pyx_CyFunction_get_closure(CYTHON_UNUSED __pyx_CyFunctionObject *op)
{
    Py_INCREF(Py_None);
    return Py_None;
}
static PyObject *
__Pyx_CyFunction_get_code(__pyx_CyFunctionObject *op)
{
    PyObject* result = (op->func_code) ? op->func_code : Py_None;
    Py_INCREF(result);
    return result;
}
static int
__Pyx_CyFunction_init_defaults(__pyx_CyFunctionObject *op) {
    int result = 0;
    PyObject *res = op->defaults_getter((PyObject *) op);
    if (unlikely(!res))
        return -1;
    #if CYTHON_ASSUME_SAFE_MACROS && !CYTHON_AVOID_BORROWED_REFS
    op->defaults_tuple = PyTuple_GET_ITEM(res, 0);
    Py_INCREF(op->defaults_tuple);
    op->defaults_kwdict = PyTuple_GET_ITEM(res, 1);
    Py_INCREF(op->defaults_kwdict);
    #else
    op->defaults_tuple = PySequence_ITEM(res, 0);
    if (unlikely(!op->defaults_tuple)) result = -1;
    else {
        op->defaults_kwdict = PySequence_ITEM(res, 1);
        if (unlikely(!op->defaults_kwdict)) result = -1;
    }
    #endif
    Py_DECREF(res);
    return result;
}
static int
__Pyx_CyFunction_set_defaults(__pyx_CyFunctionObject *op, PyObject* value) {
    PyObject* tmp;
    if (!value) {
        value = Py_None;
    } else if (value != Py_None && !PyTuple_Check(value)) {
        PyErr_SetString(PyExc_TypeError,
                        "__defaults__ must be set to a tuple object");
        return -1;
    }
    Py_INCREF(value);
    tmp = op->defaults_tuple;
    op->defaults_tuple = value;
    Py_XDECREF(tmp);
    return 0;
}
static PyObject *
__Pyx_CyFunction_get_defaults(__pyx_CyFunctionObject *op) {
    PyObject* result = op->defaults_tuple;
    if (unlikely(!result)) {
        if (op->defaults_getter) {
            if (__Pyx_CyFunction_init_defaults(op) < 0) return NULL;
            result = op->defaults_tuple;
        } else {
            result = Py_None;
        }
    }
    Py_INCREF(result);
    return result;
}
static int
__Pyx_CyFunction_set_kwdefaults(__pyx_CyFunctionObject *op, PyObject* value) {
    PyObject* tmp;
    if (!value) {
        value = Py_None;
    } else if (value != Py_None && !PyDict_Check(value)) {
        PyErr_SetString(PyExc_TypeError,
                        "__kwdefaults__ must be set to a dict object");
        return -1;
    }
    Py_INCREF(value);
    tmp = op->defaults_kwdict;
    op->defaults_kwdict = value;
    Py_XDECREF(tmp);
    return 0;
}
static PyObject *
__Pyx_CyFunction_get_kwdefaults(__pyx_CyFunctionObject *op) {
    PyObject* result = op->defaults_kwdict;
    if (unlikely(!result)) {
        if (op->defaults_getter) {
            if (__Pyx_CyFunction_init_defaults(op) < 0) return NULL;
            result = op->defaults_kwdict;
        } else {
            result = Py_None;
        }
    }
    Py_INCREF(result);
    return result;
}
static int
__Pyx_CyFunction_set_annotations(__pyx_CyFunctionObject *op, PyObject* value) {
    PyObject* tmp;
    if (!value || value == Py_None) {
        value = NULL;
    } else if (!PyDict_Check(value)) {
        PyErr_SetString(PyExc_TypeError,
                        "__annotations__ must be set to a dict object");
        return -1;
    }
    Py_XINCREF(value);
    tmp = op->func_annotations;
    op->func_annotations = value;
    Py_XDECREF(tmp);
    return 0;
}
static PyObject *
__Pyx_CyFunction_get_annotations(__pyx_CyFunctionObject *op) {
    PyObject* result = op->func_annotations;
    if (unlikely(!result)) {
        result = PyDict_New();
        if (unlikely(!result)) return NULL;
        op->func_annotations = result;
    }
    Py_INCREF(result);
    return result;
}
static PyGetSetDef __pyx_CyFunction_getsets[] = {
    {(char *) "func_doc", (getter)__Pyx_CyFunction_get_doc, (setter)__Pyx_CyFunction_set_doc, 0, 0},
    {(char *) "__doc__",  (getter)__Pyx_CyFunction_get_doc, (setter)__Pyx_CyFunction_set_doc, 0, 0},
    {(char *) "func_name", (getter)__Pyx_CyFunction_get_name, (setter)__Pyx_CyFunction_set_name, 0, 0},
    {(char *) "__name__", (getter)__Pyx_CyFunction_get_name, (setter)__Pyx_CyFunction_set_name, 0, 0},
    {(char *) "__qualname__", (getter)__Pyx_CyFunction_get_qualname, (setter)__Pyx_CyFunction_set_qualname, 0, 0},
    {(char *) "__self__", (getter)__Pyx_CyFunction_get_self, 0, 0, 0},
    {(char *) "func_dict", (getter)__Pyx_CyFunction_get_dict, (setter)__Pyx_CyFunction_set_dict, 0, 0},
    {(char *) "__dict__", (getter)__Pyx_CyFunction_get_dict, (setter)__Pyx_CyFunction_set_dict, 0, 0},
    {(char *) "func_globals", (getter)__Pyx_CyFunction_get_globals, 0, 0, 0},
    {(char *) "__globals__", (getter)__Pyx_CyFunction_get_globals, 0, 0, 0},
    {(char *) "func_closure", (getter)__Pyx_CyFunction_get_closure, 0, 0, 0},
    {(char *) "__closure__", (getter)__Pyx_CyFunction_get_closure, 0, 0, 0},
    {(char *) "func_code", (getter)__Pyx_CyFunction_get_code, 0, 0, 0},
    {(char *) "__code__", (getter)__Pyx_CyFunction_get_code, 0, 0, 0},
    {(char *) "func_defaults", (getter)__Pyx_CyFunction_get_defaults, (setter)__Pyx_CyFunction_set_defaults, 0, 0},
    {(char *) "__defaults__", (getter)__Pyx_CyFunction_get_defaults, (setter)__Pyx_CyFunction_set_defaults, 0, 0},
    {(char *) "__kwdefaults__", (getter)__Pyx_CyFunction_get_kwdefaults, (setter)__Pyx_CyFunction_set_kwdefaults, 0, 0},
    {(char *) "__annotations__", (getter)__Pyx_CyFunction_get_annotations, (setter)__Pyx_CyFunction_set_annotations, 0, 0},
    {0, 0, 0, 0, 0}
};
static PyMemberDef __pyx_CyFunction_members[] = {
    {(char *) "__module__", T_OBJECT, offsetof(__pyx_CyFunctionObject, func.m_module), PY_WRITE_RESTRICTED, 0},
    {0, 0, 0,  0, 0}
};
static PyObject *
__Pyx_CyFunction_reduce(__pyx_CyFunctionObject *m, CYTHON_UNUSED PyObject *args)
{
#if PY_MAJOR_VERSION >= 3
    return PyUnicode_FromString(m->func.m_ml->ml_name);
#else
    return PyString_FromString(m->func.m_ml->ml_name);
#endif
}
static PyMethodDef __pyx_CyFunction_methods[] = {
    {"__reduce__", (PyCFunction)__Pyx_CyFunction_reduce, METH_VARARGS, 0},
    {0, 0, 0, 0}
};
#if PY_VERSION_HEX < 0x030500A0
#define __Pyx_CyFunction_weakreflist(cyfunc) ((cyfunc)->func_weakreflist)
#else
#define __Pyx_CyFunction_weakreflist(cyfunc) ((cyfunc)->func.m_weakreflist)
#endif
static PyObject *__Pyx_CyFunction_New(PyTypeObject *type, PyMethodDef *ml, int flags, PyObject* qualname,
                                      PyObject *closure, PyObject *module, PyObject* globals, PyObject* code) {
    __pyx_CyFunctionObject *op = PyObject_GC_New(__pyx_CyFunctionObject, type);
    if (op == NULL)
        return NULL;
    op->flags = flags;
    __Pyx_CyFunction_weakreflist(op) = NULL;
    op->func.m_ml = ml;
    op->func.m_self = (PyObject *) op;
    Py_XINCREF(closure);
    op->func_closure = closure;
    Py_XINCREF(module);
    op->func.m_module = module;
    op->func_dict = NULL;
    op->func_name = NULL;
    Py_INCREF(qualname);
    op->func_qualname = qualname;
    op->func_doc = NULL;
    op->func_classobj = NULL;
    op->func_globals = globals;
    Py_INCREF(op->func_globals);
    Py_XINCREF(code);
    op->func_code = code;
    op->defaults_pyobjects = 0;
    op->defaults = NULL;
    op->defaults_tuple = NULL;
    op->defaults_kwdict = NULL;
    op->defaults_getter = NULL;
    op->func_annotations = NULL;
    PyObject_GC_Track(op);
    return (PyObject *) op;
}
static int
__Pyx_CyFunction_clear(__pyx_CyFunctionObject *m)
{
    Py_CLEAR(m->func_closure);
    Py_CLEAR(m->func.m_module);
    Py_CLEAR(m->func_dict);
    Py_CLEAR(m->func_name);
    Py_CLEAR(m->func_qualname);
    Py_CLEAR(m->func_doc);
    Py_CLEAR(m->func_globals);
    Py_CLEAR(m->func_code);
    Py_CLEAR(m->func_classobj);
    Py_CLEAR(m->defaults_tuple);
    Py_CLEAR(m->defaults_kwdict);
    Py_CLEAR(m->func_annotations);
    if (m->defaults) {
        PyObject **pydefaults = __Pyx_CyFunction_Defaults(PyObject *, m);
        int i;
        for (i = 0; i < m->defaults_pyobjects; i++)
            Py_XDECREF(pydefaults[i]);
        PyObject_Free(m->defaults);
        m->defaults = NULL;
    }
    return 0;
}
static void __Pyx_CyFunction_dealloc(__pyx_CyFunctionObject *m)
{
    PyObject_GC_UnTrack(m);
    if (__Pyx_CyFunction_weakreflist(m) != NULL)
        PyObject_ClearWeakRefs((PyObject *) m);
    __Pyx_CyFunction_clear(m);
    PyObject_GC_Del(m);
}
static int __Pyx_CyFunction_traverse(__pyx_CyFunctionObject *m, visitproc visit, void *arg)
{
    Py_VISIT(m->func_closure);
    Py_VISIT(m->func.m_module);
    Py_VISIT(m->func_dict);
    Py_VISIT(m->func_name);
    Py_VISIT(m->func_qualname);
    Py_VISIT(m->func_doc);
    Py_VISIT(m->func_globals);
    Py_VISIT(m->func_code);
    Py_VISIT(m->func_classobj);
    Py_VISIT(m->defaults_tuple);
    Py_VISIT(m->defaults_kwdict);
    if (m->defaults) {
        PyObject **pydefaults = __Pyx_CyFunction_Defaults(PyObject *, m);
        int i;
        for (i = 0; i < m->defaults_pyobjects; i++)
            Py_VISIT(pydefaults[i]);
    }
    return 0;
}
static PyObject *__Pyx_CyFunction_descr_get(PyObject *func, PyObject *obj, PyObject *type)
{
    __pyx_CyFunctionObject *m = (__pyx_CyFunctionObject *) func;
    if (m->flags & __Pyx_CYFUNCTION_STATICMETHOD) {
        Py_INCREF(func);
        return func;
    }
    if (m->flags & __Pyx_CYFUNCTION_CLASSMETHOD) {
        if (type == NULL)
            type = (PyObject *)(Py_TYPE(obj));
        return __Pyx_PyMethod_New(func, type, (PyObject *)(Py_TYPE(type)));
    }
    if (obj == Py_None)
        obj = NULL;
    return __Pyx_PyMethod_New(func, obj, type);
}
static PyObject*
__Pyx_CyFunction_repr(__pyx_CyFunctionObject *op)
{
#if PY_MAJOR_VERSION >= 3
    return PyUnicode_FromFormat("<cyfunction %U at %p>",
                                op->func_qualname, (void *)op);
#else
    return PyString_FromFormat("<cyfunction %s at %p>",
                               PyString_AsString(op->func_qualname), (void *)op);
#endif
}
static PyObject * __Pyx_CyFunction_CallMethod(PyObject *func, PyObject *self, PyObject *arg, PyObject *kw) {
    PyCFunctionObject* f = (PyCFunctionObject*)func;
    PyCFunction meth = f->m_ml->ml_meth;
    Py_ssize_t size;
    switch (f->m_ml->ml_flags & (METH_VARARGS | METH_KEYWORDS | METH_NOARGS | METH_O)) {
    case METH_VARARGS:
        if (likely(kw == NULL || PyDict_Size(kw) == 0))
            return (*meth)(self, arg);
        break;
    case METH_VARARGS | METH_KEYWORDS:
        return (*(PyCFunctionWithKeywords)meth)(self, arg, kw);
    case METH_NOARGS:
        if (likely(kw == NULL || PyDict_Size(kw) == 0)) {
            size = PyTuple_GET_SIZE(arg);
            if (likely(size == 0))
                return (*meth)(self, NULL);
            PyErr_Format(PyExc_TypeError,
                "%.200s() takes no arguments (%" CYTHON_FORMAT_SSIZE_T "d given)",
                f->m_ml->ml_name, size);
            return NULL;
        }
        break;
    case METH_O:
        if (likely(kw == NULL || PyDict_Size(kw) == 0)) {
            size = PyTuple_GET_SIZE(arg);
            if (likely(size == 1)) {
                PyObject *result, *arg0 = PySequence_ITEM(arg, 0);
                if (unlikely(!arg0)) return NULL;
                result = (*meth)(self, arg0);
                Py_DECREF(arg0);
                return result;
            }
            PyErr_Format(PyExc_TypeError,
                "%.200s() takes exactly one argument (%" CYTHON_FORMAT_SSIZE_T "d given)",
                f->m_ml->ml_name, size);
            return NULL;
        }
        break;
    default:
        PyErr_SetString(PyExc_SystemError, "Bad call flags in "
                        "__Pyx_CyFunction_Call. METH_OLDARGS is no "
                        "longer supported!");
        return NULL;
    }
    PyErr_Format(PyExc_TypeError, "%.200s() takes no keyword arguments",
                 f->m_ml->ml_name);
    return NULL;
}
static CYTHON_INLINE PyObject *__Pyx_CyFunction_Call(PyObject *func, PyObject *arg, PyObject *kw) {
    return __Pyx_CyFunction_CallMethod(func, ((PyCFunctionObject*)func)->m_self, arg, kw);
}
static PyObject *__Pyx_CyFunction_CallAsMethod(PyObject *func, PyObject *args, PyObject *kw) {
    PyObject *result;
    __pyx_CyFunctionObject *cyfunc = (__pyx_CyFunctionObject *) func;
    if ((cyfunc->flags & __Pyx_CYFUNCTION_CCLASS) && !(cyfunc->flags & __Pyx_CYFUNCTION_STATICMETHOD)) {
        Py_ssize_t argc;
        PyObject *new_args;
        PyObject *self;
        argc = PyTuple_GET_SIZE(args);
        new_args = PyTuple_GetSlice(args, 1, argc);
        if (unlikely(!new_args))
            return NULL;
        self = PyTuple_GetItem(args, 0);
        if (unlikely(!self)) {
            Py_DECREF(new_args);
            return NULL;
        }
        result = __Pyx_CyFunction_CallMethod(func, self, new_args, kw);
        Py_DECREF(new_args);
    } else {
        result = __Pyx_CyFunction_Call(func, args, kw);
    }
    return result;
}
static PyTypeObject __pyx_CyFunctionType_type = {
    PyVarObject_HEAD_INIT(0, 0)
    "cython_function_or_method",
    sizeof(__pyx_CyFunctionObject),
    0,
    (destructor) __Pyx_CyFunction_dealloc,
    0,
    0,
    0,
#if PY_MAJOR_VERSION < 3
    0,
#else
    0,
#endif
    (reprfunc) __Pyx_CyFunction_repr,
    0,
    0,
    0,
    0,
    __Pyx_CyFunction_CallAsMethod,
    0,
    0,
    0,
    0,
    Py_TPFLAGS_DEFAULT | Py_TPFLAGS_HAVE_GC,
    0,
    (traverseproc) __Pyx_CyFunction_traverse,
    (inquiry) __Pyx_CyFunction_clear,
    0,
#if PY_VERSION_HEX < 0x030500A0
    offsetof(__pyx_CyFunctionObject, func_weakreflist),
#else
    offsetof(PyCFunctionObject, m_weakreflist),
#endif
    0,
    0,
    __pyx_CyFunction_methods,
    __pyx_CyFunction_members,
    __pyx_CyFunction_getsets,
    0,
    0,
    __Pyx_CyFunction_descr_get,
    0,
    offsetof(__pyx_CyFunctionObject, func_dict),
    0,
    0,
    0,
    0,
    0,
    0,
    0,
    0,
    0,
    0,
    0,
    0,
#if PY_VERSION_HEX >= 0x030400a1
    0,
#endif
};
static int __pyx_CyFunction_init(void) {
    __pyx_CyFunctionType = __Pyx_FetchCommonType(&__pyx_CyFunctionType_type);
    if (__pyx_CyFunctionType == NULL) {
        return -1;
    }
    return 0;
}
static CYTHON_INLINE void *__Pyx_CyFunction_InitDefaults(PyObject *func, size_t size, int pyobjects) {
    __pyx_CyFunctionObject *m = (__pyx_CyFunctionObject *) func;
    m->defaults = PyObject_Malloc(size);
    if (!m->defaults)
        return PyErr_NoMemory();
    memset(m->defaults, 0, size);
    m->defaults_pyobjects = pyobjects;
    return m->defaults;
}
static CYTHON_INLINE void __Pyx_CyFunction_SetDefaultsTuple(PyObject *func, PyObject *tuple) {
    __pyx_CyFunctionObject *m = (__pyx_CyFunctionObject *) func;
    m->defaults_tuple = tuple;
    Py_INCREF(tuple);
}
static CYTHON_INLINE void __Pyx_CyFunction_SetDefaultsKwDict(PyObject *func, PyObject *dict) {
    __pyx_CyFunctionObject *m = (__pyx_CyFunctionObject *) func;
    m->defaults_kwdict = dict;
    Py_INCREF(dict);
}
static CYTHON_INLINE void __Pyx_CyFunction_SetAnnotationsDict(PyObject *func, PyObject *dict) {
    __pyx_CyFunctionObject *m = (__pyx_CyFunctionObject *) func;
    m->func_annotations = dict;
    Py_INCREF(dict);
}

/* FusedFunction */
                static PyObject *
__pyx_FusedFunction_New(PyTypeObject *type, PyMethodDef *ml, int flags,
                        PyObject *qualname, PyObject *self,
                        PyObject *module, PyObject *globals,
                        PyObject *code)
{
    __pyx_FusedFunctionObject *fusedfunc =
        (__pyx_FusedFunctionObject *) __Pyx_CyFunction_New(type, ml, flags, qualname,
                                                           self, module, globals, code);
    if (!fusedfunc)
        return NULL;
    fusedfunc->__signatures__ = NULL;
    fusedfunc->type = NULL;
    fusedfunc->self = NULL;
    return (PyObject *) fusedfunc;
}
static void __pyx_FusedFunction_dealloc(__pyx_FusedFunctionObject *self) {
    __pyx_FusedFunction_clear(self);
    __pyx_FusedFunctionType->tp_free((PyObject *) self);
}
static int
__pyx_FusedFunction_traverse(__pyx_FusedFunctionObject *self,
                             visitproc visit,
                             void *arg)
{
    Py_VISIT(self->self);
    Py_VISIT(self->type);
    Py_VISIT(self->__signatures__);
    return __Pyx_CyFunction_traverse((__pyx_CyFunctionObject *) self, visit, arg);
}
static int
__pyx_FusedFunction_clear(__pyx_FusedFunctionObject *self)
{
    Py_CLEAR(self->self);
    Py_CLEAR(self->type);
    Py_CLEAR(self->__signatures__);
    return __Pyx_CyFunction_clear((__pyx_CyFunctionObject *) self);
}
static PyObject *
__pyx_FusedFunction_descr_get(PyObject *self, PyObject *obj, PyObject *type)
{
    __pyx_FusedFunctionObject *func, *meth;
    func = (__pyx_FusedFunctionObject *) self;
    if (func->self || func->func.flags & __Pyx_CYFUNCTION_STATICMETHOD) {
        Py_INCREF(self);
        return self;
    }
    if (obj == Py_None)
        obj = NULL;
    meth = (__pyx_FusedFunctionObject *) __pyx_FusedFunction_NewEx(
                    ((PyCFunctionObject *) func)->m_ml,
                    ((__pyx_CyFunctionObject *) func)->flags,
                    ((__pyx_CyFunctionObject *) func)->func_qualname,
                    ((__pyx_CyFunctionObject *) func)->func_closure,
                    ((PyCFunctionObject *) func)->m_module,
                    ((__pyx_CyFunctionObject *) func)->func_globals,
                    ((__pyx_CyFunctionObject *) func)->func_code);
    if (!meth)
        return NULL;
    Py_XINCREF(func->func.func_classobj);
    meth->func.func_classobj = func->func.func_classobj;
    Py_XINCREF(func->__signatures__);
    meth->__signatures__ = func->__signatures__;
    Py_XINCREF(type);
    meth->type = type;
    Py_XINCREF(func->func.defaults_tuple);
    meth->func.defaults_tuple = func->func.defaults_tuple;
    if (func->func.flags & __Pyx_CYFUNCTION_CLASSMETHOD)
        obj = type;
    Py_XINCREF(obj);
    meth->self = obj;
    return (PyObject *) meth;
}
static PyObject *
_obj_to_str(PyObject *obj)
{
    if (PyType_Check(obj))
        return PyObject_GetAttr(obj, __pyx_n_s_name_2);
    else
        return PyObject_Str(obj);
}
static PyObject *
__pyx_FusedFunction_getitem(__pyx_FusedFunctionObject *self, PyObject *idx)
{
    PyObject *signature = NULL;
    PyObject *unbound_result_func;
    PyObject *result_func = NULL;
    if (self->__signatures__ == NULL) {
        PyErr_SetString(PyExc_TypeError, "Function is not fused");
        return NULL;
    }
    if (PyTuple_Check(idx)) {
        PyObject *list = PyList_New(0);
        Py_ssize_t n = PyTuple_GET_SIZE(idx);
        PyObject *string = NULL;
        PyObject *sep = NULL;
        int i;
        if (!list)
            return NULL;
        for (i = 0; i < n; i++) {
#if CYTHON_ASSUME_SAFE_MACROS && !CYTHON_AVOID_BORROWED_REFS
            PyObject *item = PyTuple_GET_ITEM(idx, i);
#else
            PyObject *item = PySequence_ITEM(idx, i);
#endif
            string = _obj_to_str(item);
#if !(CYTHON_ASSUME_SAFE_MACROS && !CYTHON_AVOID_BORROWED_REFS)
            Py_DECREF(item);
#endif
            if (!string || PyList_Append(list, string) < 0)
                goto __pyx_err;
            Py_DECREF(string);
        }
        sep = PyUnicode_FromString("|");
        if (sep)
            signature = PyUnicode_Join(sep, list);
__pyx_err:
;
        Py_DECREF(list);
        Py_XDECREF(sep);
    } else {
        signature = _obj_to_str(idx);
    }
    if (!signature)
        return NULL;
    unbound_result_func = PyObject_GetItem(self->__signatures__, signature);
    if (unbound_result_func) {
        if (self->self || self->type) {
            __pyx_FusedFunctionObject *unbound = (__pyx_FusedFunctionObject *) unbound_result_func;
            Py_CLEAR(unbound->func.func_classobj);
            Py_XINCREF(self->func.func_classobj);
            unbound->func.func_classobj = self->func.func_classobj;
            result_func = __pyx_FusedFunction_descr_get(unbound_result_func,
                                                        self->self, self->type);
        } else {
            result_func = unbound_result_func;
            Py_INCREF(result_func);
        }
    }
    Py_DECREF(signature);
    Py_XDECREF(unbound_result_func);
    return result_func;
}
static PyObject *
__pyx_FusedFunction_callfunction(PyObject *func, PyObject *args, PyObject *kw)
{
     __pyx_CyFunctionObject *cyfunc = (__pyx_CyFunctionObject *) func;
    int static_specialized = (cyfunc->flags & __Pyx_CYFUNCTION_STATICMETHOD &&
                              !((__pyx_FusedFunctionObject *) func)->__signatures__);
    if (cyfunc->flags & __Pyx_CYFUNCTION_CCLASS && !static_specialized) {
        return __Pyx_CyFunction_CallAsMethod(func, args, kw);
    } else {
        return __Pyx_CyFunction_Call(func, args, kw);
    }
}
static PyObject *
__pyx_FusedFunction_call(PyObject *func, PyObject *args, PyObject *kw)
{
    __pyx_FusedFunctionObject *binding_func = (__pyx_FusedFunctionObject *) func;
    Py_ssize_t argc = PyTuple_GET_SIZE(args);
    PyObject *new_args = NULL;
    __pyx_FusedFunctionObject *new_func = NULL;
    PyObject *result = NULL;
    PyObject *self = NULL;
    int is_staticmethod = binding_func->func.flags & __Pyx_CYFUNCTION_STATICMETHOD;
    int is_classmethod = binding_func->func.flags & __Pyx_CYFUNCTION_CLASSMETHOD;
    if (binding_func->self) {
        Py_ssize_t i;
        new_args = PyTuple_New(argc + 1);
        if (!new_args)
            return NULL;
        self = binding_func->self;
#if !(CYTHON_ASSUME_SAFE_MACROS && !CYTHON_AVOID_BORROWED_REFS)
        Py_INCREF(self);
#endif
        Py_INCREF(self);
        PyTuple_SET_ITEM(new_args, 0, self);
        for (i = 0; i < argc; i++) {
#if CYTHON_ASSUME_SAFE_MACROS && !CYTHON_AVOID_BORROWED_REFS
            PyObject *item = PyTuple_GET_ITEM(args, i);
            Py_INCREF(item);
#else
            PyObject *item = PySequence_ITEM(args, i);  if (unlikely(!item)) goto bad;
#endif
            PyTuple_SET_ITEM(new_args, i + 1, item);
        }
        args = new_args;
    } else if (binding_func->type) {
        if (argc < 1) {
            PyErr_SetString(PyExc_TypeError, "Need at least one argument, 0 given.");
            return NULL;
        }
#if CYTHON_ASSUME_SAFE_MACROS && !CYTHON_AVOID_BORROWED_REFS
        self = PyTuple_GET_ITEM(args, 0);
#else
        self = PySequence_ITEM(args, 0);  if (unlikely(!self)) return NULL;
#endif
    }
    if (self && !is_classmethod && !is_staticmethod) {
        int is_instance = PyObject_IsInstance(self, binding_func->type);
        if (unlikely(!is_instance)) {
            PyErr_Format(PyExc_TypeError,
                         "First argument should be of type %.200s, got %.200s.",
                         ((PyTypeObject *) binding_func->type)->tp_name,
                         self->ob_type->tp_name);
            goto bad;
        } else if (unlikely(is_instance == -1)) {
            goto bad;
        }
    }
#if !(CYTHON_ASSUME_SAFE_MACROS && !CYTHON_AVOID_BORROWED_REFS)
    Py_XDECREF(self);
    self = NULL;
#endif
    if (binding_func->__signatures__) {
        PyObject *tup;
        if (is_staticmethod && binding_func->func.flags & __Pyx_CYFUNCTION_CCLASS) {
            tup = PyTuple_Pack(3, args,
                               kw == NULL ? Py_None : kw,
                               binding_func->func.defaults_tuple);
            if (unlikely(!tup)) goto bad;
            new_func = (__pyx_FusedFunctionObject *) __Pyx_CyFunction_CallMethod(
                func, binding_func->__signatures__, tup, NULL);
        } else {
            tup = PyTuple_Pack(4, binding_func->__signatures__, args,
                               kw == NULL ? Py_None : kw,
                               binding_func->func.defaults_tuple);
            if (unlikely(!tup)) goto bad;
            new_func = (__pyx_FusedFunctionObject *) __pyx_FusedFunction_callfunction(func, tup, NULL);
        }
        Py_DECREF(tup);
        if (unlikely(!new_func))
            goto bad;
        Py_XINCREF(binding_func->func.func_classobj);
        Py_CLEAR(new_func->func.func_classobj);
        new_func->func.func_classobj = binding_func->func.func_classobj;
        func = (PyObject *) new_func;
    }
    result = __pyx_FusedFunction_callfunction(func, args, kw);
bad:
#if !(CYTHON_ASSUME_SAFE_MACROS && !CYTHON_AVOID_BORROWED_REFS)
    Py_XDECREF(self);
#endif
    Py_XDECREF(new_args);
    Py_XDECREF((PyObject *) new_func);
    return result;
}
static PyMemberDef __pyx_FusedFunction_members[] = {
    {(char *) "__signatures__",
     T_OBJECT,
     offsetof(__pyx_FusedFunctionObject, __signatures__),
     READONLY,
     0},
    {0, 0, 0, 0, 0},
};
static PyMappingMethods __pyx_FusedFunction_mapping_methods = {
    0,
    (binaryfunc) __pyx_FusedFunction_getitem,
    0,
};
static PyTypeObject __pyx_FusedFunctionType_type = {
    PyVarObject_HEAD_INIT(0, 0)
    "fused_cython_function",
    sizeof(__pyx_FusedFunctionObject),
    0,
    (destructor) __pyx_FusedFunction_dealloc,
    0,
    0,
    0,
#if PY_MAJOR_VERSION < 3
    0,
#else
    0,
#endif
    0,
    0,
    0,
    &__pyx_FusedFunction_mapping_methods,
    0,
    (ternaryfunc) __pyx_FusedFunction_call,
    0,
    0,
    0,
    0,
    Py_TPFLAGS_DEFAULT | Py_TPFLAGS_HAVE_GC | Py_TPFLAGS_BASETYPE,
    0,
    (traverseproc) __pyx_FusedFunction_traverse,
    (inquiry) __pyx_FusedFunction_clear,
    0,
    0,
    0,
    0,
    0,
    __pyx_FusedFunction_members,
    __pyx_CyFunction_getsets,
    &__pyx_CyFunctionType_type,
    0,
    __pyx_FusedFunction_descr_get,
    0,
    0,
    0,
    0,
    0,
    0,
    0,
    0,
    0,
    0,
    0,
    0,
    0,
    0,
#if PY_VERSION_HEX >= 0x030400a1
    0,
#endif
};
static int __pyx_FusedFunction_init(void) {
    __pyx_FusedFunctionType = __Pyx_FetchCommonType(&__pyx_FusedFunctionType_type);
    if (__pyx_FusedFunctionType == NULL) {
        return -1;
    }
    return 0;
}

/* CLineInTraceback */
                static int __Pyx_CLineForTraceback(int c_line) {
#ifdef CYTHON_CLINE_IN_TRACEBACK
    return ((CYTHON_CLINE_IN_TRACEBACK)) ? c_line : 0;
#else
    PyObject *use_cline;
#if CYTHON_COMPILING_IN_CPYTHON
    PyObject **cython_runtime_dict = _PyObject_GetDictPtr(__pyx_cython_runtime);
    if (likely(cython_runtime_dict)) {
      use_cline = PyDict_GetItem(*cython_runtime_dict, __pyx_n_s_cline_in_traceback);
    } else
#endif
    {
      PyObject *ptype, *pvalue, *ptraceback;
      PyObject *use_cline_obj;
      PyErr_Fetch(&ptype, &pvalue, &ptraceback);
      use_cline_obj = __Pyx_PyObject_GetAttrStr(__pyx_cython_runtime, __pyx_n_s_cline_in_traceback);
      if (use_cline_obj) {
        use_cline = PyObject_Not(use_cline_obj) ? Py_False : Py_True;
        Py_DECREF(use_cline_obj);
      } else {
        use_cline = NULL;
      }
      PyErr_Restore(ptype, pvalue, ptraceback);
    }
    if (!use_cline) {
        c_line = 0;
        PyObject_SetAttr(__pyx_cython_runtime, __pyx_n_s_cline_in_traceback, Py_False);
    }
    else if (PyObject_Not(use_cline) != 0) {
        c_line = 0;
    }
    return c_line;
#endif
}

/* CodeObjectCache */
                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 - start) / 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, (size_t)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);
}

/* AddTraceback */
                #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,
        0,
        0,
        0,
        0,
        __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,
        __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;
    PyFrameObject *py_frame = 0;
    if (c_line) {
        c_line = __Pyx_CLineForTraceback(c_line);
    }
    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_frame = PyFrame_New(
        PyThreadState_GET(), /*PyThreadState *tstate,*/
        py_code,             /*PyCodeObject *code,*/
        __pyx_d,      /*PyObject *globals,*/
        0                    /*PyObject *locals*/
    );
    if (!py_frame) goto bad;
    __Pyx_PyFrame_SetLineNumber(py_frame, py_line);
    PyTraceBack_Here(py_frame);
bad:
    Py_XDECREF(py_code);
    Py_XDECREF(py_frame);
}

#if PY_MAJOR_VERSION < 3
static int __Pyx_GetBuffer(PyObject *obj, Py_buffer *view, int flags) {
    if (PyObject_CheckBuffer(obj)) return PyObject_GetBuffer(obj, view, flags);
        if (PyObject_TypeCheck(obj, __pyx_ptype_5numpy_ndarray)) return __pyx_pw_5numpy_7ndarray_1__getbuffer__(obj, view, flags);
        if (PyObject_TypeCheck(obj, __pyx_array_type)) return __pyx_array_getbuffer(obj, view, flags);
        if (PyObject_TypeCheck(obj, __pyx_memoryview_type)) return __pyx_memoryview_getbuffer(obj, view, flags);
    PyErr_Format(PyExc_TypeError, "'%.200s' does not have the buffer interface", Py_TYPE(obj)->tp_name);
    return -1;
}
static void __Pyx_ReleaseBuffer(Py_buffer *view) {
    PyObject *obj = view->obj;
    if (!obj) return;
    if (PyObject_CheckBuffer(obj)) {
        PyBuffer_Release(view);
        return;
    }
    if ((0)) {}
        else if (PyObject_TypeCheck(obj, __pyx_ptype_5numpy_ndarray)) __pyx_pw_5numpy_7ndarray_3__releasebuffer__(obj, view);
    view->obj = NULL;
    Py_DECREF(obj);
}
#endif


                /* MemviewSliceIsContig */
                static int
__pyx_memviewslice_is_contig(const __Pyx_memviewslice mvs,
                             char order, int ndim)
{
    int i, index, step, start;
    Py_ssize_t itemsize = mvs.memview->view.itemsize;
    if (order == 'F') {
        step = 1;
        start = 0;
    } else {
        step = -1;
        start = ndim - 1;
    }
    for (i = 0; i < ndim; i++) {
        index = start + step * i;
        if (mvs.suboffsets[index] >= 0 || mvs.strides[index] != itemsize)
            return 0;
        itemsize *= mvs.shape[index];
    }
    return 1;
}

/* OverlappingSlices */
                static void
__pyx_get_array_memory_extents(__Pyx_memviewslice *slice,
                               void **out_start, void **out_end,
                               int ndim, size_t itemsize)
{
    char *start, *end;
    int i;
    start = end = slice->data;
    for (i = 0; i < ndim; i++) {
        Py_ssize_t stride = slice->strides[i];
        Py_ssize_t extent = slice->shape[i];
        if (extent == 0) {
            *out_start = *out_end = start;
            return;
        } else {
            if (stride > 0)
                end += stride * (extent - 1);
            else
                start += stride * (extent - 1);
        }
    }
    *out_start = start;
    *out_end = end + itemsize;
}
static int
__pyx_slices_overlap(__Pyx_memviewslice *slice1,
                     __Pyx_memviewslice *slice2,
                     int ndim, size_t itemsize)
{
    void *start1, *end1, *start2, *end2;
    __pyx_get_array_memory_extents(slice1, &start1, &end1, ndim, itemsize);
    __pyx_get_array_memory_extents(slice2, &start2, &end2, ndim, itemsize);
    return (start1 < end2) && (start2 < end1);
}

/* Capsule */
                static CYTHON_INLINE PyObject *
__pyx_capsule_create(void *p, CYTHON_UNUSED const char *sig)
{
    PyObject *cobj;
#if PY_VERSION_HEX >= 0x02070000
    cobj = PyCapsule_New(p, sig, NULL);
#else
    cobj = PyCObject_FromVoidPtr(p, NULL);
#endif
    return cobj;
}

/* TypeInfoCompare */
                static int
__pyx_typeinfo_cmp(__Pyx_TypeInfo *a, __Pyx_TypeInfo *b)
{
    int i;
    if (!a || !b)
        return 0;
    if (a == b)
        return 1;
    if (a->size != b->size || a->typegroup != b->typegroup ||
            a->is_unsigned != b->is_unsigned || a->ndim != b->ndim) {
        if (a->typegroup == 'H' || b->typegroup == 'H') {
            return a->size == b->size;
        } else {
            return 0;
        }
    }
    if (a->ndim) {
        for (i = 0; i < a->ndim; i++)
            if (a->arraysize[i] != b->arraysize[i])
                return 0;
    }
    if (a->typegroup == 'S') {
        if (a->flags != b->flags)
            return 0;
        if (a->fields || b->fields) {
            if (!(a->fields && b->fields))
                return 0;
            for (i = 0; a->fields[i].type && b->fields[i].type; i++) {
                __Pyx_StructField *field_a = a->fields + i;
                __Pyx_StructField *field_b = b->fields + i;
                if (field_a->offset != field_b->offset ||
                    !__pyx_typeinfo_cmp(field_a->type, field_b->type))
                    return 0;
            }
            return !a->fields[i].type && !b->fields[i].type;
        }
    }
    return 1;
}

/* MemviewSliceValidateAndInit */
                static int
__pyx_check_strides(Py_buffer *buf, int dim, int ndim, int spec)
{
    if (buf->shape[dim] <= 1)
        return 1;
    if (buf->strides) {
        if (spec & __Pyx_MEMVIEW_CONTIG) {
            if (spec & (__Pyx_MEMVIEW_PTR|__Pyx_MEMVIEW_FULL)) {
                if (buf->strides[dim] != sizeof(void *)) {
                    PyErr_Format(PyExc_ValueError,
                                 "Buffer is not indirectly contiguous "
                                 "in dimension %d.", dim);
                    goto fail;
                }
            } else if (buf->strides[dim] != buf->itemsize) {
                PyErr_SetString(PyExc_ValueError,
                                "Buffer and memoryview are not contiguous "
                                "in the same dimension.");
                goto fail;
            }
        }
        if (spec & __Pyx_MEMVIEW_FOLLOW) {
            Py_ssize_t stride = buf->strides[dim];
            if (stride < 0)
                stride = -stride;
            if (stride < buf->itemsize) {
                PyErr_SetString(PyExc_ValueError,
                                "Buffer and memoryview are not contiguous "
                                "in the same dimension.");
                goto fail;
            }
        }
    } else {
        if (spec & __Pyx_MEMVIEW_CONTIG && dim != ndim - 1) {
            PyErr_Format(PyExc_ValueError,
                         "C-contiguous buffer is not contiguous in "
                         "dimension %d", dim);
            goto fail;
        } else if (spec & (__Pyx_MEMVIEW_PTR)) {
            PyErr_Format(PyExc_ValueError,
                         "C-contiguous buffer is not indirect in "
                         "dimension %d", dim);
            goto fail;
        } else if (buf->suboffsets) {
            PyErr_SetString(PyExc_ValueError,
                            "Buffer exposes suboffsets but no strides");
            goto fail;
        }
    }
    return 1;
fail:
    return 0;
}
static int
__pyx_check_suboffsets(Py_buffer *buf, int dim, CYTHON_UNUSED int ndim, int spec)
{
    if (spec & __Pyx_MEMVIEW_DIRECT) {
        if (buf->suboffsets && buf->suboffsets[dim] >= 0) {
            PyErr_Format(PyExc_ValueError,
                         "Buffer not compatible with direct access "
                         "in dimension %d.", dim);
            goto fail;
        }
    }
    if (spec & __Pyx_MEMVIEW_PTR) {
        if (!buf->suboffsets || (buf->suboffsets && buf->suboffsets[dim] < 0)) {
            PyErr_Format(PyExc_ValueError,
                         "Buffer is not indirectly accessible "
                         "in dimension %d.", dim);
            goto fail;
        }
    }
    return 1;
fail:
    return 0;
}
static int
__pyx_verify_contig(Py_buffer *buf, int ndim, int c_or_f_flag)
{
    int i;
    if (c_or_f_flag & __Pyx_IS_F_CONTIG) {
        Py_ssize_t stride = 1;
        for (i = 0; i < ndim; i++) {
            if (stride * buf->itemsize != buf->strides[i] &&
                    buf->shape[i] > 1)
            {
                PyErr_SetString(PyExc_ValueError,
                    "Buffer not fortran contiguous.");
                goto fail;
            }
            stride = stride * buf->shape[i];
        }
    } else if (c_or_f_flag & __Pyx_IS_C_CONTIG) {
        Py_ssize_t stride = 1;
        for (i = ndim - 1; i >- 1; i--) {
            if (stride * buf->itemsize != buf->strides[i] &&
                    buf->shape[i] > 1) {
                PyErr_SetString(PyExc_ValueError,
                    "Buffer not C contiguous.");
                goto fail;
            }
            stride = stride * buf->shape[i];
        }
    }
    return 1;
fail:
    return 0;
}
static int __Pyx_ValidateAndInit_memviewslice(
                int *axes_specs,
                int c_or_f_flag,
                int buf_flags,
                int ndim,
                __Pyx_TypeInfo *dtype,
                __Pyx_BufFmt_StackElem stack[],
                __Pyx_memviewslice *memviewslice,
                PyObject *original_obj)
{
    struct __pyx_memoryview_obj *memview, *new_memview;
    __Pyx_RefNannyDeclarations
    Py_buffer *buf;
    int i, spec = 0, retval = -1;
    __Pyx_BufFmt_Context ctx;
    int from_memoryview = __pyx_memoryview_check(original_obj);
    __Pyx_RefNannySetupContext("ValidateAndInit_memviewslice", 0);
    if (from_memoryview && __pyx_typeinfo_cmp(dtype, ((struct __pyx_memoryview_obj *)
                                                            original_obj)->typeinfo)) {
        memview = (struct __pyx_memoryview_obj *) original_obj;
        new_memview = NULL;
    } else {
        memview = (struct __pyx_memoryview_obj *) __pyx_memoryview_new(
                                            original_obj, buf_flags, 0, dtype);
        new_memview = memview;
        if (unlikely(!memview))
            goto fail;
    }
    buf = &memview->view;
    if (buf->ndim != ndim) {
        PyErr_Format(PyExc_ValueError,
                "Buffer has wrong number of dimensions (expected %d, got %d)",
                ndim, buf->ndim);
        goto fail;
    }
    if (new_memview) {
        __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 "u byte%s) "
                     "does not match size of '%s' (%" CYTHON_FORMAT_SSIZE_T "u byte%s)",
                     buf->itemsize,
                     (buf->itemsize > 1) ? "s" : "",
                     dtype->name,
                     dtype->size,
                     (dtype->size > 1) ? "s" : "");
        goto fail;
    }
    for (i = 0; i < ndim; i++) {
        spec = axes_specs[i];
        if (!__pyx_check_strides(buf, i, ndim, spec))
            goto fail;
        if (!__pyx_check_suboffsets(buf, i, ndim, spec))
            goto fail;
    }
    if (buf->strides && !__pyx_verify_contig(buf, ndim, c_or_f_flag))
        goto fail;
    if (unlikely(__Pyx_init_memviewslice(memview, ndim, memviewslice,
                                         new_memview != NULL) == -1)) {
        goto fail;
    }
    retval = 0;
    goto no_fail;
fail:
    Py_XDECREF(new_memview);
    retval = -1;
no_fail:
    __Pyx_RefNannyFinishContext();
    return retval;
}

/* ObjectToMemviewSlice */
                static CYTHON_INLINE __Pyx_memviewslice __Pyx_PyObject_to_MemoryviewSlice_ds_float(PyObject *obj) {
    __Pyx_memviewslice result = { 0, 0, { 0 }, { 0 }, { 0 } };
    __Pyx_BufFmt_StackElem stack[1];
    int axes_specs[] = { (__Pyx_MEMVIEW_DIRECT | __Pyx_MEMVIEW_STRIDED) };
    int retcode;
    if (obj == Py_None) {
        result.memview = (struct __pyx_memoryview_obj *) Py_None;
        return result;
    }
    retcode = __Pyx_ValidateAndInit_memviewslice(axes_specs, 0,
                                                 PyBUF_RECORDS, 1,
                                                 &__Pyx_TypeInfo_float, stack,
                                                 &result, obj);
    if (unlikely(retcode == -1))
        goto __pyx_fail;
    return result;
__pyx_fail:
    result.memview = NULL;
    result.data = NULL;
    return result;
}

/* ObjectToMemviewSlice */
                static CYTHON_INLINE __Pyx_memviewslice __Pyx_PyObject_to_MemoryviewSlice_ds_double(PyObject *obj) {
    __Pyx_memviewslice result = { 0, 0, { 0 }, { 0 }, { 0 } };
    __Pyx_BufFmt_StackElem stack[1];
    int axes_specs[] = { (__Pyx_MEMVIEW_DIRECT | __Pyx_MEMVIEW_STRIDED) };
    int retcode;
    if (obj == Py_None) {
        result.memview = (struct __pyx_memoryview_obj *) Py_None;
        return result;
    }
    retcode = __Pyx_ValidateAndInit_memviewslice(axes_specs, 0,
                                                 PyBUF_RECORDS, 1,
                                                 &__Pyx_TypeInfo_double, stack,
                                                 &result, obj);
    if (unlikely(retcode == -1))
        goto __pyx_fail;
    return result;
__pyx_fail:
    result.memview = NULL;
    result.data = NULL;
    return result;
}

/* ObjectToMemviewSlice */
                static CYTHON_INLINE __Pyx_memviewslice __Pyx_PyObject_to_MemoryviewSlice_dcd__float(PyObject *obj) {
    __Pyx_memviewslice result = { 0, 0, { 0 }, { 0 }, { 0 } };
    __Pyx_BufFmt_StackElem stack[1];
    int axes_specs[] = { (__Pyx_MEMVIEW_DIRECT | __Pyx_MEMVIEW_CONTIG), (__Pyx_MEMVIEW_DIRECT | __Pyx_MEMVIEW_FOLLOW) };
    int retcode;
    if (obj == Py_None) {
        result.memview = (struct __pyx_memoryview_obj *) Py_None;
        return result;
    }
    retcode = __Pyx_ValidateAndInit_memviewslice(axes_specs, __Pyx_IS_F_CONTIG,
                                                 (PyBUF_F_CONTIGUOUS | PyBUF_FORMAT | PyBUF_WRITABLE), 2,
                                                 &__Pyx_TypeInfo_float, stack,
                                                 &result, obj);
    if (unlikely(retcode == -1))
        goto __pyx_fail;
    return result;
__pyx_fail:
    result.memview = NULL;
    result.data = NULL;
    return result;
}

/* ObjectToMemviewSlice */
                static CYTHON_INLINE __Pyx_memviewslice __Pyx_PyObject_to_MemoryviewSlice_dcd__double(PyObject *obj) {
    __Pyx_memviewslice result = { 0, 0, { 0 }, { 0 }, { 0 } };
    __Pyx_BufFmt_StackElem stack[1];
    int axes_specs[] = { (__Pyx_MEMVIEW_DIRECT | __Pyx_MEMVIEW_CONTIG), (__Pyx_MEMVIEW_DIRECT | __Pyx_MEMVIEW_FOLLOW) };
    int retcode;
    if (obj == Py_None) {
        result.memview = (struct __pyx_memoryview_obj *) Py_None;
        return result;
    }
    retcode = __Pyx_ValidateAndInit_memviewslice(axes_specs, __Pyx_IS_F_CONTIG,
                                                 (PyBUF_F_CONTIGUOUS | PyBUF_FORMAT | PyBUF_WRITABLE), 2,
                                                 &__Pyx_TypeInfo_double, stack,
                                                 &result, obj);
    if (unlikely(retcode == -1))
        goto __pyx_fail;
    return result;
__pyx_fail:
    result.memview = NULL;
    result.data = NULL;
    return result;
}

/* CIntToPy */
                static CYTHON_INLINE PyObject* __Pyx_PyInt_From_long(long value) {
    const long neg_one = (long) -1, const_zero = (long) 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);
#ifdef HAVE_LONG_LONG
        } else if (sizeof(long) <= sizeof(unsigned PY_LONG_LONG)) {
            return PyLong_FromUnsignedLongLong((unsigned PY_LONG_LONG) value);
#endif
        }
    } else {
        if (sizeof(long) <= sizeof(long)) {
            return PyInt_FromLong((long) value);
#ifdef HAVE_LONG_LONG
        } else if (sizeof(long) <= sizeof(PY_LONG_LONG)) {
            return PyLong_FromLongLong((PY_LONG_LONG) value);
#endif
        }
    }
    {
        int one = 1; int little = (int)*(unsigned char *)&one;
        unsigned char *bytes = (unsigned char *)&value;
        return _PyLong_FromByteArray(bytes, sizeof(long),
                                     little, !is_unsigned);
    }
}

/* CIntFromPyVerify */
                #define __PYX_VERIFY_RETURN_INT(target_type, func_type, func_value)\
    __PYX__VERIFY_RETURN_INT(target_type, func_type, func_value, 0)
#define __PYX_VERIFY_RETURN_INT_EXC(target_type, func_type, func_value)\
    __PYX__VERIFY_RETURN_INT(target_type, func_type, func_value, 1)
#define __PYX__VERIFY_RETURN_INT(target_type, func_type, func_value, exc)\
    {\
        func_type value = func_value;\
        if (sizeof(target_type) < sizeof(func_type)) {\
            if (unlikely(value != (func_type) (target_type) value)) {\
                func_type zero = 0;\
                if (exc && unlikely(value == (func_type)-1 && PyErr_Occurred()))\
                    return (target_type) -1;\
                if (is_unsigned && unlikely(value < zero))\
                    goto raise_neg_overflow;\
                else\
                    goto raise_overflow;\
            }\
        }\
        return (target_type) value;\
    }

/* CIntToPy */
                static CYTHON_INLINE PyObject* __Pyx_PyInt_From_int(int value) {
    const int neg_one = (int) -1, const_zero = (int) 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);
#ifdef HAVE_LONG_LONG
        } else if (sizeof(int) <= sizeof(unsigned PY_LONG_LONG)) {
            return PyLong_FromUnsignedLongLong((unsigned PY_LONG_LONG) value);
#endif
        }
    } else {
        if (sizeof(int) <= sizeof(long)) {
            return PyInt_FromLong((long) value);
#ifdef HAVE_LONG_LONG
        } else if (sizeof(int) <= sizeof(PY_LONG_LONG)) {
            return PyLong_FromLongLong((PY_LONG_LONG) value);
#endif
        }
    }
    {
        int one = 1; int little = (int)*(unsigned char *)&one;
        unsigned char *bytes = (unsigned char *)&value;
        return _PyLong_FromByteArray(bytes, sizeof(int),
                                     little, !is_unsigned);
    }
}

/* CIntToPy */
                static CYTHON_INLINE PyObject* __Pyx_PyInt_From_unsigned_int(unsigned int value) {
    const unsigned int neg_one = (unsigned int) -1, const_zero = (unsigned int) 0;
    const int is_unsigned = neg_one > const_zero;
    if (is_unsigned) {
        if (sizeof(unsigned int) < sizeof(long)) {
            return PyInt_FromLong((long) value);
        } else if (sizeof(unsigned int) <= sizeof(unsigned long)) {
            return PyLong_FromUnsignedLong((unsigned long) value);
#ifdef HAVE_LONG_LONG
        } else if (sizeof(unsigned int) <= sizeof(unsigned PY_LONG_LONG)) {
            return PyLong_FromUnsignedLongLong((unsigned PY_LONG_LONG) value);
#endif
        }
    } else {
        if (sizeof(unsigned int) <= sizeof(long)) {
            return PyInt_FromLong((long) value);
#ifdef HAVE_LONG_LONG
        } else if (sizeof(unsigned int) <= sizeof(PY_LONG_LONG)) {
            return PyLong_FromLongLong((PY_LONG_LONG) value);
#endif
        }
    }
    {
        int one = 1; int little = (int)*(unsigned char *)&one;
        unsigned char *bytes = (unsigned char *)&value;
        return _PyLong_FromByteArray(bytes, sizeof(unsigned int),
                                     little, !is_unsigned);
    }
}

/* MemviewDtypeToObject */
                static CYTHON_INLINE PyObject *__pyx_memview_get_float(const char *itemp) {
    return (PyObject *) PyFloat_FromDouble(*(float *) itemp);
}
static CYTHON_INLINE int __pyx_memview_set_float(const char *itemp, PyObject *obj) {
    float value = __pyx_PyFloat_AsFloat(obj);
    if ((value == (float)-1) && PyErr_Occurred())
        return 0;
    *(float *) itemp = value;
    return 1;
}

/* MemviewDtypeToObject */
                static CYTHON_INLINE PyObject *__pyx_memview_get_double(const char *itemp) {
    return (PyObject *) PyFloat_FromDouble(*(double *) itemp);
}
static CYTHON_INLINE int __pyx_memview_set_double(const char *itemp, PyObject *obj) {
    double value = __pyx_PyFloat_AsDouble(obj);
    if ((value == (double)-1) && PyErr_Occurred())
        return 0;
    *(double *) itemp = value;
    return 1;
}

/* Declarations */
                #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

/* Arithmetic */
                #if CYTHON_CCOMPLEX
#else
    static CYTHON_INLINE int __Pyx_c_eq_float(__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_sum_float(__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_diff_float(__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_prod_float(__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;
    }
    #if 1
    static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_quot_float(__pyx_t_float_complex a, __pyx_t_float_complex b) {
        if (b.imag == 0) {
            return __pyx_t_float_complex_from_parts(a.real / b.real, a.imag / b.real);
        } else if (fabsf(b.real) >= fabsf(b.imag)) {
            if (b.real == 0 && b.imag == 0) {
                return __pyx_t_float_complex_from_parts(a.real / b.real, a.imag / b.imag);
            } else {
                float r = b.imag / b.real;
                float s = 1.0 / (b.real + b.imag * r);
                return __pyx_t_float_complex_from_parts(
                    (a.real + a.imag * r) * s, (a.imag - a.real * r) * s);
            }
        } else {
            float r = b.real / b.imag;
            float s = 1.0 / (b.imag + b.real * r);
            return __pyx_t_float_complex_from_parts(
                (a.real * r + a.imag) * s, (a.imag * r - a.real) * s);
        }
    }
    #else
    static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_quot_float(__pyx_t_float_complex a, __pyx_t_float_complex b) {
        if (b.imag == 0) {
            return __pyx_t_float_complex_from_parts(a.real / b.real, a.imag / b.real);
        } else {
            float denom = b.real * b.real + b.imag * b.imag;
            return __pyx_t_float_complex_from_parts(
                (a.real * b.real + a.imag * b.imag) / denom,
                (a.imag * b.real - a.real * b.imag) / denom);
        }
    }
    #endif
    static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_neg_float(__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_zero_float(__pyx_t_float_complex a) {
       return (a.real == 0) && (a.imag == 0);
    }
    static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_conj_float(__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_abs_float(__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_pow_float(__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_prod_float(a, a);
                        return __Pyx_c_prod_float(a, a);
                    case 3:
                        z = __Pyx_c_prod_float(a, a);
                        return __Pyx_c_prod_float(z, a);
                    case 4:
                        z = __Pyx_c_prod_float(a, a);
                        return __Pyx_c_prod_float(z, z);
                }
            }
            if (a.imag == 0) {
                if (a.real == 0) {
                    return a;
                } else if (b.imag == 0) {
                    z.real = powf(a.real, b.real);
                    z.imag = 0;
                    return z;
                } else if (a.real > 0) {
                    r = a.real;
                    theta = 0;
                } else {
                    r = -a.real;
                    theta = atan2f(0, -1);
                }
            } else {
                r = __Pyx_c_abs_float(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

/* Declarations */
                #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

/* Arithmetic */
                #if CYTHON_CCOMPLEX
#else
    static CYTHON_INLINE int __Pyx_c_eq_double(__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_double(__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_double(__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_double(__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;
    }
    #if 1
    static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_quot_double(__pyx_t_double_complex a, __pyx_t_double_complex b) {
        if (b.imag == 0) {
            return __pyx_t_double_complex_from_parts(a.real / b.real, a.imag / b.real);
        } else if (fabs(b.real) >= fabs(b.imag)) {
            if (b.real == 0 && b.imag == 0) {
                return __pyx_t_double_complex_from_parts(a.real / b.real, a.imag / b.imag);
            } else {
                double r = b.imag / b.real;
                double s = 1.0 / (b.real + b.imag * r);
                return __pyx_t_double_complex_from_parts(
                    (a.real + a.imag * r) * s, (a.imag - a.real * r) * s);
            }
        } else {
            double r = b.real / b.imag;
            double s = 1.0 / (b.imag + b.real * r);
            return __pyx_t_double_complex_from_parts(
                (a.real * r + a.imag) * s, (a.imag * r - a.real) * s);
        }
    }
    #else
    static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_quot_double(__pyx_t_double_complex a, __pyx_t_double_complex b) {
        if (b.imag == 0) {
            return __pyx_t_double_complex_from_parts(a.real / b.real, a.imag / b.real);
        } else {
            double denom = b.real * b.real + b.imag * b.imag;
            return __pyx_t_double_complex_from_parts(
                (a.real * b.real + a.imag * b.imag) / denom,
                (a.imag * b.real - a.real * b.imag) / denom);
        }
    }
    #endif
    static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_neg_double(__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_double(__pyx_t_double_complex a) {
       return (a.real == 0) && (a.imag == 0);
    }
    static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_conj_double(__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_double(__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_double(__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_double(a, a);
                        return __Pyx_c_prod_double(a, a);
                    case 3:
                        z = __Pyx_c_prod_double(a, a);
                        return __Pyx_c_prod_double(z, a);
                    case 4:
                        z = __Pyx_c_prod_double(a, a);
                        return __Pyx_c_prod_double(z, z);
                }
            }
            if (a.imag == 0) {
                if (a.real == 0) {
                    return a;
                } else if (b.imag == 0) {
                    z.real = pow(a.real, b.real);
                    z.imag = 0;
                    return z;
                } else if (a.real > 0) {
                    r = a.real;
                    theta = 0;
                } else {
                    r = -a.real;
                    theta = atan2(0, -1);
                }
            } else {
                r = __Pyx_c_abs_double(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

/* CIntToPy */
                static CYTHON_INLINE PyObject* __Pyx_PyInt_From_enum__NPY_TYPES(enum NPY_TYPES value) {
    const enum NPY_TYPES neg_one = (enum NPY_TYPES) -1, const_zero = (enum NPY_TYPES) 0;
    const int is_unsigned = neg_one > const_zero;
    if (is_unsigned) {
        if (sizeof(enum NPY_TYPES) < sizeof(long)) {
            return PyInt_FromLong((long) value);
        } else if (sizeof(enum NPY_TYPES) <= sizeof(unsigned long)) {
            return PyLong_FromUnsignedLong((unsigned long) value);
#ifdef HAVE_LONG_LONG
        } else if (sizeof(enum NPY_TYPES) <= sizeof(unsigned PY_LONG_LONG)) {
            return PyLong_FromUnsignedLongLong((unsigned PY_LONG_LONG) value);
#endif
        }
    } else {
        if (sizeof(enum NPY_TYPES) <= sizeof(long)) {
            return PyInt_FromLong((long) value);
#ifdef HAVE_LONG_LONG
        } else if (sizeof(enum NPY_TYPES) <= sizeof(PY_LONG_LONG)) {
            return PyLong_FromLongLong((PY_LONG_LONG) value);
#endif
        }
    }
    {
        int one = 1; int little = (int)*(unsigned char *)&one;
        unsigned char *bytes = (unsigned char *)&value;
        return _PyLong_FromByteArray(bytes, sizeof(enum NPY_TYPES),
                                     little, !is_unsigned);
    }
}

/* MemviewSliceCopyTemplate */
                static __Pyx_memviewslice
__pyx_memoryview_copy_new_contig(const __Pyx_memviewslice *from_mvs,
                                 const char *mode, int ndim,
                                 size_t sizeof_dtype, int contig_flag,
                                 int dtype_is_object)
{
    __Pyx_RefNannyDeclarations
    int i;
    __Pyx_memviewslice new_mvs = { 0, 0, { 0 }, { 0 }, { 0 } };
    struct __pyx_memoryview_obj *from_memview = from_mvs->memview;
    Py_buffer *buf = &from_memview->view;
    PyObject *shape_tuple = NULL;
    PyObject *temp_int = NULL;
    struct __pyx_array_obj *array_obj = NULL;
    struct __pyx_memoryview_obj *memview_obj = NULL;
    __Pyx_RefNannySetupContext("__pyx_memoryview_copy_new_contig", 0);
    for (i = 0; i < ndim; i++) {
        if (from_mvs->suboffsets[i] >= 0) {
            PyErr_Format(PyExc_ValueError, "Cannot copy memoryview slice with "
                                           "indirect dimensions (axis %d)", i);
            goto fail;
        }
    }
    shape_tuple = PyTuple_New(ndim);
    if (unlikely(!shape_tuple)) {
        goto fail;
    }
    __Pyx_GOTREF(shape_tuple);
    for(i = 0; i < ndim; i++) {
        temp_int = PyInt_FromSsize_t(from_mvs->shape[i]);
        if(unlikely(!temp_int)) {
            goto fail;
        } else {
            PyTuple_SET_ITEM(shape_tuple, i, temp_int);
            temp_int = NULL;
        }
    }
    array_obj = __pyx_array_new(shape_tuple, sizeof_dtype, buf->format, (char *) mode, NULL);
    if (unlikely(!array_obj)) {
        goto fail;
    }
    __Pyx_GOTREF(array_obj);
    memview_obj = (struct __pyx_memoryview_obj *) __pyx_memoryview_new(
                                    (PyObject *) array_obj, contig_flag,
                                    dtype_is_object,
                                    from_mvs->memview->typeinfo);
    if (unlikely(!memview_obj))
        goto fail;
    if (unlikely(__Pyx_init_memviewslice(memview_obj, ndim, &new_mvs, 1) < 0))
        goto fail;
    if (unlikely(__pyx_memoryview_copy_contents(*from_mvs, new_mvs, ndim, ndim,
                                                dtype_is_object) < 0))
        goto fail;
    goto no_fail;
fail:
    __Pyx_XDECREF(new_mvs.memview);
    new_mvs.memview = NULL;
    new_mvs.data = NULL;
no_fail:
    __Pyx_XDECREF(shape_tuple);
    __Pyx_XDECREF(temp_int);
    __Pyx_XDECREF(array_obj);
    __Pyx_RefNannyFinishContext();
    return new_mvs;
}

/* CIntFromPy */
                static CYTHON_INLINE int __Pyx_PyInt_As_int(PyObject *x) {
    const int neg_one = (int) -1, const_zero = (int) 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(x))
        } else {
            long val = PyInt_AS_LONG(x);
            if (is_unsigned && unlikely(val < 0)) {
                goto raise_neg_overflow;
            }
            return (int) val;
        }
    } else
#endif
    if (likely(PyLong_Check(x))) {
        if (is_unsigned) {
#if CYTHON_USE_PYLONG_INTERNALS
            const digit* digits = ((PyLongObject*)x)->ob_digit;
            switch (Py_SIZE(x)) {
                case  0: return (int) 0;
                case  1: __PYX_VERIFY_RETURN_INT(int, digit, digits[0])
                case 2:
                    if (8 * sizeof(int) > 1 * PyLong_SHIFT) {
                        if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) {
                            __PYX_VERIFY_RETURN_INT(int, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
                        } else if (8 * sizeof(int) >= 2 * PyLong_SHIFT) {
                            return (int) (((((int)digits[1]) << PyLong_SHIFT) | (int)digits[0]));
                        }
                    }
                    break;
                case 3:
                    if (8 * sizeof(int) > 2 * PyLong_SHIFT) {
                        if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) {
                            __PYX_VERIFY_RETURN_INT(int, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
                        } else if (8 * sizeof(int) >= 3 * PyLong_SHIFT) {
                            return (int) (((((((int)digits[2]) << PyLong_SHIFT) | (int)digits[1]) << PyLong_SHIFT) | (int)digits[0]));
                        }
                    }
                    break;
                case 4:
                    if (8 * sizeof(int) > 3 * PyLong_SHIFT) {
                        if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) {
                            __PYX_VERIFY_RETURN_INT(int, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
                        } else if (8 * sizeof(int) >= 4 * PyLong_SHIFT) {
                            return (int) (((((((((int)digits[3]) << PyLong_SHIFT) | (int)digits[2]) << PyLong_SHIFT) | (int)digits[1]) << PyLong_SHIFT) | (int)digits[0]));
                        }
                    }
                    break;
            }
#endif
#if CYTHON_COMPILING_IN_CPYTHON
            if (unlikely(Py_SIZE(x) < 0)) {
                goto raise_neg_overflow;
            }
#else
            {
                int result = PyObject_RichCompareBool(x, Py_False, Py_LT);
                if (unlikely(result < 0))
                    return (int) -1;
                if (unlikely(result == 1))
                    goto raise_neg_overflow;
            }
#endif
            if (sizeof(int) <= sizeof(unsigned long)) {
                __PYX_VERIFY_RETURN_INT_EXC(int, unsigned long, PyLong_AsUnsignedLong(x))
#ifdef HAVE_LONG_LONG
            } else if (sizeof(int) <= sizeof(unsigned PY_LONG_LONG)) {
                __PYX_VERIFY_RETURN_INT_EXC(int, unsigned PY_LONG_LONG, PyLong_AsUnsignedLongLong(x))
#endif
            }
        } else {
#if CYTHON_USE_PYLONG_INTERNALS
            const digit* digits = ((PyLongObject*)x)->ob_digit;
            switch (Py_SIZE(x)) {
                case  0: return (int) 0;
                case -1: __PYX_VERIFY_RETURN_INT(int, sdigit, (sdigit) (-(sdigit)digits[0]))
                case  1: __PYX_VERIFY_RETURN_INT(int,  digit, +digits[0])
                case -2:
                    if (8 * sizeof(int) - 1 > 1 * PyLong_SHIFT) {
                        if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) {
                            __PYX_VERIFY_RETURN_INT(int, long, -(long) (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
                        } else if (8 * sizeof(int) - 1 > 2 * PyLong_SHIFT) {
                            return (int) (((int)-1)*(((((int)digits[1]) << PyLong_SHIFT) | (int)digits[0])));
                        }
                    }
                    break;
                case 2:
                    if (8 * sizeof(int) > 1 * PyLong_SHIFT) {
                        if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) {
                            __PYX_VERIFY_RETURN_INT(int, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
                        } else if (8 * sizeof(int) - 1 > 2 * PyLong_SHIFT) {
                            return (int) ((((((int)digits[1]) << PyLong_SHIFT) | (int)digits[0])));
                        }
                    }
                    break;
                case -3:
                    if (8 * sizeof(int) - 1 > 2 * PyLong_SHIFT) {
                        if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) {
                            __PYX_VERIFY_RETURN_INT(int, long, -(long) (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
                        } else if (8 * sizeof(int) - 1 > 3 * PyLong_SHIFT) {
                            return (int) (((int)-1)*(((((((int)digits[2]) << PyLong_SHIFT) | (int)digits[1]) << PyLong_SHIFT) | (int)digits[0])));
                        }
                    }
                    break;
                case 3:
                    if (8 * sizeof(int) > 2 * PyLong_SHIFT) {
                        if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) {
                            __PYX_VERIFY_RETURN_INT(int, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
                        } else if (8 * sizeof(int) - 1 > 3 * PyLong_SHIFT) {
                            return (int) ((((((((int)digits[2]) << PyLong_SHIFT) | (int)digits[1]) << PyLong_SHIFT) | (int)digits[0])));
                        }
                    }
                    break;
                case -4:
                    if (8 * sizeof(int) - 1 > 3 * PyLong_SHIFT) {
                        if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) {
                            __PYX_VERIFY_RETURN_INT(int, long, -(long) (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
                        } else if (8 * sizeof(int) - 1 > 4 * PyLong_SHIFT) {
                            return (int) (((int)-1)*(((((((((int)digits[3]) << PyLong_SHIFT) | (int)digits[2]) << PyLong_SHIFT) | (int)digits[1]) << PyLong_SHIFT) | (int)digits[0])));
                        }
                    }
                    break;
                case 4:
                    if (8 * sizeof(int) > 3 * PyLong_SHIFT) {
                        if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) {
                            __PYX_VERIFY_RETURN_INT(int, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
                        } else if (8 * sizeof(int) - 1 > 4 * PyLong_SHIFT) {
                            return (int) ((((((((((int)digits[3]) << PyLong_SHIFT) | (int)digits[2]) << PyLong_SHIFT) | (int)digits[1]) << PyLong_SHIFT) | (int)digits[0])));
                        }
                    }
                    break;
            }
#endif
            if (sizeof(int) <= sizeof(long)) {
                __PYX_VERIFY_RETURN_INT_EXC(int, long, PyLong_AsLong(x))
#ifdef HAVE_LONG_LONG
            } else if (sizeof(int) <= sizeof(PY_LONG_LONG)) {
                __PYX_VERIFY_RETURN_INT_EXC(int, PY_LONG_LONG, PyLong_AsLongLong(x))
#endif
            }
        }
        {
#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_IntOrLong(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_IntOrLong(x);
        if (!tmp) return (int) -1;
        val = __Pyx_PyInt_As_int(tmp);
        Py_DECREF(tmp);
        return val;
    }
raise_overflow:
    PyErr_SetString(PyExc_OverflowError,
        "value too large to convert to int");
    return (int) -1;
raise_neg_overflow:
    PyErr_SetString(PyExc_OverflowError,
        "can't convert negative value to int");
    return (int) -1;
}

/* CIntFromPy */
                static CYTHON_INLINE npy_uint32 __Pyx_PyInt_As_npy_uint32(PyObject *x) {
    const npy_uint32 neg_one = (npy_uint32) -1, const_zero = (npy_uint32) 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(x))
        } else {
            long val = PyInt_AS_LONG(x);
            if (is_unsigned && unlikely(val < 0)) {
                goto raise_neg_overflow;
            }
            return (npy_uint32) val;
        }
    } else
#endif
    if (likely(PyLong_Check(x))) {
        if (is_unsigned) {
#if CYTHON_USE_PYLONG_INTERNALS
            const digit* digits = ((PyLongObject*)x)->ob_digit;
            switch (Py_SIZE(x)) {
                case  0: return (npy_uint32) 0;
                case  1: __PYX_VERIFY_RETURN_INT(npy_uint32, digit, digits[0])
                case 2:
                    if (8 * sizeof(npy_uint32) > 1 * PyLong_SHIFT) {
                        if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) {
                            __PYX_VERIFY_RETURN_INT(npy_uint32, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
                        } else if (8 * sizeof(npy_uint32) >= 2 * PyLong_SHIFT) {
                            return (npy_uint32) (((((npy_uint32)digits[1]) << PyLong_SHIFT) | (npy_uint32)digits[0]));
                        }
                    }
                    break;
                case 3:
                    if (8 * sizeof(npy_uint32) > 2 * PyLong_SHIFT) {
                        if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) {
                            __PYX_VERIFY_RETURN_INT(npy_uint32, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
                        } else if (8 * sizeof(npy_uint32) >= 3 * PyLong_SHIFT) {
                            return (npy_uint32) (((((((npy_uint32)digits[2]) << PyLong_SHIFT) | (npy_uint32)digits[1]) << PyLong_SHIFT) | (npy_uint32)digits[0]));
                        }
                    }
                    break;
                case 4:
                    if (8 * sizeof(npy_uint32) > 3 * PyLong_SHIFT) {
                        if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) {
                            __PYX_VERIFY_RETURN_INT(npy_uint32, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
                        } else if (8 * sizeof(npy_uint32) >= 4 * PyLong_SHIFT) {
                            return (npy_uint32) (((((((((npy_uint32)digits[3]) << PyLong_SHIFT) | (npy_uint32)digits[2]) << PyLong_SHIFT) | (npy_uint32)digits[1]) << PyLong_SHIFT) | (npy_uint32)digits[0]));
                        }
                    }
                    break;
            }
#endif
#if CYTHON_COMPILING_IN_CPYTHON
            if (unlikely(Py_SIZE(x) < 0)) {
                goto raise_neg_overflow;
            }
#else
            {
                int result = PyObject_RichCompareBool(x, Py_False, Py_LT);
                if (unlikely(result < 0))
                    return (npy_uint32) -1;
                if (unlikely(result == 1))
                    goto raise_neg_overflow;
            }
#endif
            if (sizeof(npy_uint32) <= sizeof(unsigned long)) {
                __PYX_VERIFY_RETURN_INT_EXC(npy_uint32, unsigned long, PyLong_AsUnsignedLong(x))
#ifdef HAVE_LONG_LONG
            } else if (sizeof(npy_uint32) <= sizeof(unsigned PY_LONG_LONG)) {
                __PYX_VERIFY_RETURN_INT_EXC(npy_uint32, unsigned PY_LONG_LONG, PyLong_AsUnsignedLongLong(x))
#endif
            }
        } else {
#if CYTHON_USE_PYLONG_INTERNALS
            const digit* digits = ((PyLongObject*)x)->ob_digit;
            switch (Py_SIZE(x)) {
                case  0: return (npy_uint32) 0;
                case -1: __PYX_VERIFY_RETURN_INT(npy_uint32, sdigit, (sdigit) (-(sdigit)digits[0]))
                case  1: __PYX_VERIFY_RETURN_INT(npy_uint32,  digit, +digits[0])
                case -2:
                    if (8 * sizeof(npy_uint32) - 1 > 1 * PyLong_SHIFT) {
                        if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) {
                            __PYX_VERIFY_RETURN_INT(npy_uint32, long, -(long) (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
                        } else if (8 * sizeof(npy_uint32) - 1 > 2 * PyLong_SHIFT) {
                            return (npy_uint32) (((npy_uint32)-1)*(((((npy_uint32)digits[1]) << PyLong_SHIFT) | (npy_uint32)digits[0])));
                        }
                    }
                    break;
                case 2:
                    if (8 * sizeof(npy_uint32) > 1 * PyLong_SHIFT) {
                        if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) {
                            __PYX_VERIFY_RETURN_INT(npy_uint32, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
                        } else if (8 * sizeof(npy_uint32) - 1 > 2 * PyLong_SHIFT) {
                            return (npy_uint32) ((((((npy_uint32)digits[1]) << PyLong_SHIFT) | (npy_uint32)digits[0])));
                        }
                    }
                    break;
                case -3:
                    if (8 * sizeof(npy_uint32) - 1 > 2 * PyLong_SHIFT) {
                        if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) {
                            __PYX_VERIFY_RETURN_INT(npy_uint32, long, -(long) (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
                        } else if (8 * sizeof(npy_uint32) - 1 > 3 * PyLong_SHIFT) {
                            return (npy_uint32) (((npy_uint32)-1)*(((((((npy_uint32)digits[2]) << PyLong_SHIFT) | (npy_uint32)digits[1]) << PyLong_SHIFT) | (npy_uint32)digits[0])));
                        }
                    }
                    break;
                case 3:
                    if (8 * sizeof(npy_uint32) > 2 * PyLong_SHIFT) {
                        if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) {
                            __PYX_VERIFY_RETURN_INT(npy_uint32, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
                        } else if (8 * sizeof(npy_uint32) - 1 > 3 * PyLong_SHIFT) {
                            return (npy_uint32) ((((((((npy_uint32)digits[2]) << PyLong_SHIFT) | (npy_uint32)digits[1]) << PyLong_SHIFT) | (npy_uint32)digits[0])));
                        }
                    }
                    break;
                case -4:
                    if (8 * sizeof(npy_uint32) - 1 > 3 * PyLong_SHIFT) {
                        if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) {
                            __PYX_VERIFY_RETURN_INT(npy_uint32, long, -(long) (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
                        } else if (8 * sizeof(npy_uint32) - 1 > 4 * PyLong_SHIFT) {
                            return (npy_uint32) (((npy_uint32)-1)*(((((((((npy_uint32)digits[3]) << PyLong_SHIFT) | (npy_uint32)digits[2]) << PyLong_SHIFT) | (npy_uint32)digits[1]) << PyLong_SHIFT) | (npy_uint32)digits[0])));
                        }
                    }
                    break;
                case 4:
                    if (8 * sizeof(npy_uint32) > 3 * PyLong_SHIFT) {
                        if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) {
                            __PYX_VERIFY_RETURN_INT(npy_uint32, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
                        } else if (8 * sizeof(npy_uint32) - 1 > 4 * PyLong_SHIFT) {
                            return (npy_uint32) ((((((((((npy_uint32)digits[3]) << PyLong_SHIFT) | (npy_uint32)digits[2]) << PyLong_SHIFT) | (npy_uint32)digits[1]) << PyLong_SHIFT) | (npy_uint32)digits[0])));
                        }
                    }
                    break;
            }
#endif
            if (sizeof(npy_uint32) <= sizeof(long)) {
                __PYX_VERIFY_RETURN_INT_EXC(npy_uint32, long, PyLong_AsLong(x))
#ifdef HAVE_LONG_LONG
            } else if (sizeof(npy_uint32) <= sizeof(PY_LONG_LONG)) {
                __PYX_VERIFY_RETURN_INT_EXC(npy_uint32, PY_LONG_LONG, PyLong_AsLongLong(x))
#endif
            }
        }
        {
#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_IntOrLong(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_IntOrLong(x);
        if (!tmp) return (npy_uint32) -1;
        val = __Pyx_PyInt_As_npy_uint32(tmp);
        Py_DECREF(tmp);
        return val;
    }
raise_overflow:
    PyErr_SetString(PyExc_OverflowError,
        "value too large to convert to npy_uint32");
    return (npy_uint32) -1;
raise_neg_overflow:
    PyErr_SetString(PyExc_OverflowError,
        "can't convert negative value to npy_uint32");
    return (npy_uint32) -1;
}

/* CIntFromPy */
                static CYTHON_INLINE unsigned int __Pyx_PyInt_As_unsigned_int(PyObject *x) {
    const unsigned int neg_one = (unsigned int) -1, const_zero = (unsigned int) 0;
    const int is_unsigned = neg_one > const_zero;
#if PY_MAJOR_VERSION < 3
    if (likely(PyInt_Check(x))) {
        if (sizeof(unsigned int) < sizeof(long)) {
            __PYX_VERIFY_RETURN_INT(unsigned int, long, PyInt_AS_LONG(x))
        } else {
            long val = PyInt_AS_LONG(x);
            if (is_unsigned && unlikely(val < 0)) {
                goto raise_neg_overflow;
            }
            return (unsigned int) val;
        }
    } else
#endif
    if (likely(PyLong_Check(x))) {
        if (is_unsigned) {
#if CYTHON_USE_PYLONG_INTERNALS
            const digit* digits = ((PyLongObject*)x)->ob_digit;
            switch (Py_SIZE(x)) {
                case  0: return (unsigned int) 0;
                case  1: __PYX_VERIFY_RETURN_INT(unsigned int, digit, digits[0])
                case 2:
                    if (8 * sizeof(unsigned int) > 1 * PyLong_SHIFT) {
                        if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) {
                            __PYX_VERIFY_RETURN_INT(unsigned int, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
                        } else if (8 * sizeof(unsigned int) >= 2 * PyLong_SHIFT) {
                            return (unsigned int) (((((unsigned int)digits[1]) << PyLong_SHIFT) | (unsigned int)digits[0]));
                        }
                    }
                    break;
                case 3:
                    if (8 * sizeof(unsigned int) > 2 * PyLong_SHIFT) {
                        if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) {
                            __PYX_VERIFY_RETURN_INT(unsigned int, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
                        } else if (8 * sizeof(unsigned int) >= 3 * PyLong_SHIFT) {
                            return (unsigned int) (((((((unsigned int)digits[2]) << PyLong_SHIFT) | (unsigned int)digits[1]) << PyLong_SHIFT) | (unsigned int)digits[0]));
                        }
                    }
                    break;
                case 4:
                    if (8 * sizeof(unsigned int) > 3 * PyLong_SHIFT) {
                        if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) {
                            __PYX_VERIFY_RETURN_INT(unsigned int, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
                        } else if (8 * sizeof(unsigned int) >= 4 * PyLong_SHIFT) {
                            return (unsigned int) (((((((((unsigned int)digits[3]) << PyLong_SHIFT) | (unsigned int)digits[2]) << PyLong_SHIFT) | (unsigned int)digits[1]) << PyLong_SHIFT) | (unsigned int)digits[0]));
                        }
                    }
                    break;
            }
#endif
#if CYTHON_COMPILING_IN_CPYTHON
            if (unlikely(Py_SIZE(x) < 0)) {
                goto raise_neg_overflow;
            }
#else
            {
                int result = PyObject_RichCompareBool(x, Py_False, Py_LT);
                if (unlikely(result < 0))
                    return (unsigned int) -1;
                if (unlikely(result == 1))
                    goto raise_neg_overflow;
            }
#endif
            if (sizeof(unsigned int) <= sizeof(unsigned long)) {
                __PYX_VERIFY_RETURN_INT_EXC(unsigned int, unsigned long, PyLong_AsUnsignedLong(x))
#ifdef HAVE_LONG_LONG
            } else if (sizeof(unsigned int) <= sizeof(unsigned PY_LONG_LONG)) {
                __PYX_VERIFY_RETURN_INT_EXC(unsigned int, unsigned PY_LONG_LONG, PyLong_AsUnsignedLongLong(x))
#endif
            }
        } else {
#if CYTHON_USE_PYLONG_INTERNALS
            const digit* digits = ((PyLongObject*)x)->ob_digit;
            switch (Py_SIZE(x)) {
                case  0: return (unsigned int) 0;
                case -1: __PYX_VERIFY_RETURN_INT(unsigned int, sdigit, (sdigit) (-(sdigit)digits[0]))
                case  1: __PYX_VERIFY_RETURN_INT(unsigned int,  digit, +digits[0])
                case -2:
                    if (8 * sizeof(unsigned int) - 1 > 1 * PyLong_SHIFT) {
                        if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) {
                            __PYX_VERIFY_RETURN_INT(unsigned int, long, -(long) (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
                        } else if (8 * sizeof(unsigned int) - 1 > 2 * PyLong_SHIFT) {
                            return (unsigned int) (((unsigned int)-1)*(((((unsigned int)digits[1]) << PyLong_SHIFT) | (unsigned int)digits[0])));
                        }
                    }
                    break;
                case 2:
                    if (8 * sizeof(unsigned int) > 1 * PyLong_SHIFT) {
                        if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) {
                            __PYX_VERIFY_RETURN_INT(unsigned int, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
                        } else if (8 * sizeof(unsigned int) - 1 > 2 * PyLong_SHIFT) {
                            return (unsigned int) ((((((unsigned int)digits[1]) << PyLong_SHIFT) | (unsigned int)digits[0])));
                        }
                    }
                    break;
                case -3:
                    if (8 * sizeof(unsigned int) - 1 > 2 * PyLong_SHIFT) {
                        if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) {
                            __PYX_VERIFY_RETURN_INT(unsigned int, long, -(long) (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
                        } else if (8 * sizeof(unsigned int) - 1 > 3 * PyLong_SHIFT) {
                            return (unsigned int) (((unsigned int)-1)*(((((((unsigned int)digits[2]) << PyLong_SHIFT) | (unsigned int)digits[1]) << PyLong_SHIFT) | (unsigned int)digits[0])));
                        }
                    }
                    break;
                case 3:
                    if (8 * sizeof(unsigned int) > 2 * PyLong_SHIFT) {
                        if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) {
                            __PYX_VERIFY_RETURN_INT(unsigned int, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
                        } else if (8 * sizeof(unsigned int) - 1 > 3 * PyLong_SHIFT) {
                            return (unsigned int) ((((((((unsigned int)digits[2]) << PyLong_SHIFT) | (unsigned int)digits[1]) << PyLong_SHIFT) | (unsigned int)digits[0])));
                        }
                    }
                    break;
                case -4:
                    if (8 * sizeof(unsigned int) - 1 > 3 * PyLong_SHIFT) {
                        if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) {
                            __PYX_VERIFY_RETURN_INT(unsigned int, long, -(long) (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
                        } else if (8 * sizeof(unsigned int) - 1 > 4 * PyLong_SHIFT) {
                            return (unsigned int) (((unsigned int)-1)*(((((((((unsigned int)digits[3]) << PyLong_SHIFT) | (unsigned int)digits[2]) << PyLong_SHIFT) | (unsigned int)digits[1]) << PyLong_SHIFT) | (unsigned int)digits[0])));
                        }
                    }
                    break;
                case 4:
                    if (8 * sizeof(unsigned int) > 3 * PyLong_SHIFT) {
                        if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) {
                            __PYX_VERIFY_RETURN_INT(unsigned int, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
                        } else if (8 * sizeof(unsigned int) - 1 > 4 * PyLong_SHIFT) {
                            return (unsigned int) ((((((((((unsigned int)digits[3]) << PyLong_SHIFT) | (unsigned int)digits[2]) << PyLong_SHIFT) | (unsigned int)digits[1]) << PyLong_SHIFT) | (unsigned int)digits[0])));
                        }
                    }
                    break;
            }
#endif
            if (sizeof(unsigned int) <= sizeof(long)) {
                __PYX_VERIFY_RETURN_INT_EXC(unsigned int, long, PyLong_AsLong(x))
#ifdef HAVE_LONG_LONG
            } else if (sizeof(unsigned int) <= sizeof(PY_LONG_LONG)) {
                __PYX_VERIFY_RETURN_INT_EXC(unsigned int, PY_LONG_LONG, PyLong_AsLongLong(x))
#endif
            }
        }
        {
#if CYTHON_COMPILING_IN_PYPY && !defined(_PyLong_AsByteArray)
            PyErr_SetString(PyExc_RuntimeError,
                            "_PyLong_AsByteArray() not available in PyPy, cannot convert large numbers");
#else
            unsigned int val;
            PyObject *v = __Pyx_PyNumber_IntOrLong(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 (unsigned int) -1;
        }
    } else {
        unsigned int val;
        PyObject *tmp = __Pyx_PyNumber_IntOrLong(x);
        if (!tmp) return (unsigned int) -1;
        val = __Pyx_PyInt_As_unsigned_int(tmp);
        Py_DECREF(tmp);
        return val;
    }
raise_overflow:
    PyErr_SetString(PyExc_OverflowError,
        "value too large to convert to unsigned int");
    return (unsigned int) -1;
raise_neg_overflow:
    PyErr_SetString(PyExc_OverflowError,
        "can't convert negative value to unsigned int");
    return (unsigned int) -1;
}

/* BytesContains */
                static CYTHON_INLINE int __Pyx_BytesContains(PyObject* bytes, char character) {
    const Py_ssize_t length = PyBytes_GET_SIZE(bytes);
    char* char_start = PyBytes_AS_STRING(bytes);
    return memchr(char_start, (unsigned char)character, (size_t)length) != NULL;
}

/* ImportNumPyArray */
                static PyObject* __Pyx__ImportNumPyArray(void) {
    PyObject *numpy_module, *ndarray_object = NULL;
    numpy_module = __Pyx_Import(__pyx_n_s_numpy, NULL, 0);
    if (likely(numpy_module)) {
        ndarray_object = PyObject_GetAttrString(numpy_module, "ndarray");
        Py_DECREF(numpy_module);
    }
    if (unlikely(!ndarray_object)) {
        PyErr_Clear();
    }
    if (unlikely(!ndarray_object || !PyObject_TypeCheck(ndarray_object, &PyType_Type))) {
        Py_XDECREF(ndarray_object);
        Py_INCREF(Py_None);
        ndarray_object = Py_None;
    }
    return ndarray_object;
}
static CYTHON_INLINE PyObject* __Pyx_ImportNumPyArrayTypeIfAvailable(void) {
    if (unlikely(!__pyx_numpy_ndarray)) {
        __pyx_numpy_ndarray = __Pyx__ImportNumPyArray();
    }
    Py_INCREF(__pyx_numpy_ndarray);
    return __pyx_numpy_ndarray;
}

/* CIntFromPy */
                static CYTHON_INLINE long __Pyx_PyInt_As_long(PyObject *x) {
    const long neg_one = (long) -1, const_zero = (long) 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(x))
        } else {
            long val = PyInt_AS_LONG(x);
            if (is_unsigned && unlikely(val < 0)) {
                goto raise_neg_overflow;
            }
            return (long) val;
        }
    } else
#endif
    if (likely(PyLong_Check(x))) {
        if (is_unsigned) {
#if CYTHON_USE_PYLONG_INTERNALS
            const digit* digits = ((PyLongObject*)x)->ob_digit;
            switch (Py_SIZE(x)) {
                case  0: return (long) 0;
                case  1: __PYX_VERIFY_RETURN_INT(long, digit, digits[0])
                case 2:
                    if (8 * sizeof(long) > 1 * PyLong_SHIFT) {
                        if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) {
                            __PYX_VERIFY_RETURN_INT(long, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
                        } else if (8 * sizeof(long) >= 2 * PyLong_SHIFT) {
                            return (long) (((((long)digits[1]) << PyLong_SHIFT) | (long)digits[0]));
                        }
                    }
                    break;
                case 3:
                    if (8 * sizeof(long) > 2 * PyLong_SHIFT) {
                        if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) {
                            __PYX_VERIFY_RETURN_INT(long, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
                        } else if (8 * sizeof(long) >= 3 * PyLong_SHIFT) {
                            return (long) (((((((long)digits[2]) << PyLong_SHIFT) | (long)digits[1]) << PyLong_SHIFT) | (long)digits[0]));
                        }
                    }
                    break;
                case 4:
                    if (8 * sizeof(long) > 3 * PyLong_SHIFT) {
                        if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) {
                            __PYX_VERIFY_RETURN_INT(long, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
                        } else if (8 * sizeof(long) >= 4 * PyLong_SHIFT) {
                            return (long) (((((((((long)digits[3]) << PyLong_SHIFT) | (long)digits[2]) << PyLong_SHIFT) | (long)digits[1]) << PyLong_SHIFT) | (long)digits[0]));
                        }
                    }
                    break;
            }
#endif
#if CYTHON_COMPILING_IN_CPYTHON
            if (unlikely(Py_SIZE(x) < 0)) {
                goto raise_neg_overflow;
            }
#else
            {
                int result = PyObject_RichCompareBool(x, Py_False, Py_LT);
                if (unlikely(result < 0))
                    return (long) -1;
                if (unlikely(result == 1))
                    goto raise_neg_overflow;
            }
#endif
            if (sizeof(long) <= sizeof(unsigned long)) {
                __PYX_VERIFY_RETURN_INT_EXC(long, unsigned long, PyLong_AsUnsignedLong(x))
#ifdef HAVE_LONG_LONG
            } else if (sizeof(long) <= sizeof(unsigned PY_LONG_LONG)) {
                __PYX_VERIFY_RETURN_INT_EXC(long, unsigned PY_LONG_LONG, PyLong_AsUnsignedLongLong(x))
#endif
            }
        } else {
#if CYTHON_USE_PYLONG_INTERNALS
            const digit* digits = ((PyLongObject*)x)->ob_digit;
            switch (Py_SIZE(x)) {
                case  0: return (long) 0;
                case -1: __PYX_VERIFY_RETURN_INT(long, sdigit, (sdigit) (-(sdigit)digits[0]))
                case  1: __PYX_VERIFY_RETURN_INT(long,  digit, +digits[0])
                case -2:
                    if (8 * sizeof(long) - 1 > 1 * PyLong_SHIFT) {
                        if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) {
                            __PYX_VERIFY_RETURN_INT(long, long, -(long) (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
                        } else if (8 * sizeof(long) - 1 > 2 * PyLong_SHIFT) {
                            return (long) (((long)-1)*(((((long)digits[1]) << PyLong_SHIFT) | (long)digits[0])));
                        }
                    }
                    break;
                case 2:
                    if (8 * sizeof(long) > 1 * PyLong_SHIFT) {
                        if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) {
                            __PYX_VERIFY_RETURN_INT(long, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
                        } else if (8 * sizeof(long) - 1 > 2 * PyLong_SHIFT) {
                            return (long) ((((((long)digits[1]) << PyLong_SHIFT) | (long)digits[0])));
                        }
                    }
                    break;
                case -3:
                    if (8 * sizeof(long) - 1 > 2 * PyLong_SHIFT) {
                        if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) {
                            __PYX_VERIFY_RETURN_INT(long, long, -(long) (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
                        } else if (8 * sizeof(long) - 1 > 3 * PyLong_SHIFT) {
                            return (long) (((long)-1)*(((((((long)digits[2]) << PyLong_SHIFT) | (long)digits[1]) << PyLong_SHIFT) | (long)digits[0])));
                        }
                    }
                    break;
                case 3:
                    if (8 * sizeof(long) > 2 * PyLong_SHIFT) {
                        if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) {
                            __PYX_VERIFY_RETURN_INT(long, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
                        } else if (8 * sizeof(long) - 1 > 3 * PyLong_SHIFT) {
                            return (long) ((((((((long)digits[2]) << PyLong_SHIFT) | (long)digits[1]) << PyLong_SHIFT) | (long)digits[0])));
                        }
                    }
                    break;
                case -4:
                    if (8 * sizeof(long) - 1 > 3 * PyLong_SHIFT) {
                        if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) {
                            __PYX_VERIFY_RETURN_INT(long, long, -(long) (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
                        } else if (8 * sizeof(long) - 1 > 4 * PyLong_SHIFT) {
                            return (long) (((long)-1)*(((((((((long)digits[3]) << PyLong_SHIFT) | (long)digits[2]) << PyLong_SHIFT) | (long)digits[1]) << PyLong_SHIFT) | (long)digits[0])));
                        }
                    }
                    break;
                case 4:
                    if (8 * sizeof(long) > 3 * PyLong_SHIFT) {
                        if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) {
                            __PYX_VERIFY_RETURN_INT(long, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
                        } else if (8 * sizeof(long) - 1 > 4 * PyLong_SHIFT) {
                            return (long) ((((((((((long)digits[3]) << PyLong_SHIFT) | (long)digits[2]) << PyLong_SHIFT) | (long)digits[1]) << PyLong_SHIFT) | (long)digits[0])));
                        }
                    }
                    break;
            }
#endif
            if (sizeof(long) <= sizeof(long)) {
                __PYX_VERIFY_RETURN_INT_EXC(long, long, PyLong_AsLong(x))
#ifdef HAVE_LONG_LONG
            } else if (sizeof(long) <= sizeof(PY_LONG_LONG)) {
                __PYX_VERIFY_RETURN_INT_EXC(long, PY_LONG_LONG, PyLong_AsLongLong(x))
#endif
            }
        }
        {
#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_IntOrLong(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_IntOrLong(x);
        if (!tmp) return (long) -1;
        val = __Pyx_PyInt_As_long(tmp);
        Py_DECREF(tmp);
        return val;
    }
raise_overflow:
    PyErr_SetString(PyExc_OverflowError,
        "value too large to convert to long");
    return (long) -1;
raise_neg_overflow:
    PyErr_SetString(PyExc_OverflowError,
        "can't convert negative value to long");
    return (long) -1;
}

/* CIntFromPy */
                static CYTHON_INLINE char __Pyx_PyInt_As_char(PyObject *x) {
    const char neg_one = (char) -1, const_zero = (char) 0;
    const int is_unsigned = neg_one > const_zero;
#if PY_MAJOR_VERSION < 3
    if (likely(PyInt_Check(x))) {
        if (sizeof(char) < sizeof(long)) {
            __PYX_VERIFY_RETURN_INT(char, long, PyInt_AS_LONG(x))
        } else {
            long val = PyInt_AS_LONG(x);
            if (is_unsigned && unlikely(val < 0)) {
                goto raise_neg_overflow;
            }
            return (char) val;
        }
    } else
#endif
    if (likely(PyLong_Check(x))) {
        if (is_unsigned) {
#if CYTHON_USE_PYLONG_INTERNALS
            const digit* digits = ((PyLongObject*)x)->ob_digit;
            switch (Py_SIZE(x)) {
                case  0: return (char) 0;
                case  1: __PYX_VERIFY_RETURN_INT(char, digit, digits[0])
                case 2:
                    if (8 * sizeof(char) > 1 * PyLong_SHIFT) {
                        if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) {
                            __PYX_VERIFY_RETURN_INT(char, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
                        } else if (8 * sizeof(char) >= 2 * PyLong_SHIFT) {
                            return (char) (((((char)digits[1]) << PyLong_SHIFT) | (char)digits[0]));
                        }
                    }
                    break;
                case 3:
                    if (8 * sizeof(char) > 2 * PyLong_SHIFT) {
                        if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) {
                            __PYX_VERIFY_RETURN_INT(char, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
                        } else if (8 * sizeof(char) >= 3 * PyLong_SHIFT) {
                            return (char) (((((((char)digits[2]) << PyLong_SHIFT) | (char)digits[1]) << PyLong_SHIFT) | (char)digits[0]));
                        }
                    }
                    break;
                case 4:
                    if (8 * sizeof(char) > 3 * PyLong_SHIFT) {
                        if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) {
                            __PYX_VERIFY_RETURN_INT(char, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
                        } else if (8 * sizeof(char) >= 4 * PyLong_SHIFT) {
                            return (char) (((((((((char)digits[3]) << PyLong_SHIFT) | (char)digits[2]) << PyLong_SHIFT) | (char)digits[1]) << PyLong_SHIFT) | (char)digits[0]));
                        }
                    }
                    break;
            }
#endif
#if CYTHON_COMPILING_IN_CPYTHON
            if (unlikely(Py_SIZE(x) < 0)) {
                goto raise_neg_overflow;
            }
#else
            {
                int result = PyObject_RichCompareBool(x, Py_False, Py_LT);
                if (unlikely(result < 0))
                    return (char) -1;
                if (unlikely(result == 1))
                    goto raise_neg_overflow;
            }
#endif
            if (sizeof(char) <= sizeof(unsigned long)) {
                __PYX_VERIFY_RETURN_INT_EXC(char, unsigned long, PyLong_AsUnsignedLong(x))
#ifdef HAVE_LONG_LONG
            } else if (sizeof(char) <= sizeof(unsigned PY_LONG_LONG)) {
                __PYX_VERIFY_RETURN_INT_EXC(char, unsigned PY_LONG_LONG, PyLong_AsUnsignedLongLong(x))
#endif
            }
        } else {
#if CYTHON_USE_PYLONG_INTERNALS
            const digit* digits = ((PyLongObject*)x)->ob_digit;
            switch (Py_SIZE(x)) {
                case  0: return (char) 0;
                case -1: __PYX_VERIFY_RETURN_INT(char, sdigit, (sdigit) (-(sdigit)digits[0]))
                case  1: __PYX_VERIFY_RETURN_INT(char,  digit, +digits[0])
                case -2:
                    if (8 * sizeof(char) - 1 > 1 * PyLong_SHIFT) {
                        if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) {
                            __PYX_VERIFY_RETURN_INT(char, long, -(long) (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
                        } else if (8 * sizeof(char) - 1 > 2 * PyLong_SHIFT) {
                            return (char) (((char)-1)*(((((char)digits[1]) << PyLong_SHIFT) | (char)digits[0])));
                        }
                    }
                    break;
                case 2:
                    if (8 * sizeof(char) > 1 * PyLong_SHIFT) {
                        if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) {
                            __PYX_VERIFY_RETURN_INT(char, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
                        } else if (8 * sizeof(char) - 1 > 2 * PyLong_SHIFT) {
                            return (char) ((((((char)digits[1]) << PyLong_SHIFT) | (char)digits[0])));
                        }
                    }
                    break;
                case -3:
                    if (8 * sizeof(char) - 1 > 2 * PyLong_SHIFT) {
                        if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) {
                            __PYX_VERIFY_RETURN_INT(char, long, -(long) (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
                        } else if (8 * sizeof(char) - 1 > 3 * PyLong_SHIFT) {
                            return (char) (((char)-1)*(((((((char)digits[2]) << PyLong_SHIFT) | (char)digits[1]) << PyLong_SHIFT) | (char)digits[0])));
                        }
                    }
                    break;
                case 3:
                    if (8 * sizeof(char) > 2 * PyLong_SHIFT) {
                        if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) {
                            __PYX_VERIFY_RETURN_INT(char, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
                        } else if (8 * sizeof(char) - 1 > 3 * PyLong_SHIFT) {
                            return (char) ((((((((char)digits[2]) << PyLong_SHIFT) | (char)digits[1]) << PyLong_SHIFT) | (char)digits[0])));
                        }
                    }
                    break;
                case -4:
                    if (8 * sizeof(char) - 1 > 3 * PyLong_SHIFT) {
                        if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) {
                            __PYX_VERIFY_RETURN_INT(char, long, -(long) (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
                        } else if (8 * sizeof(char) - 1 > 4 * PyLong_SHIFT) {
                            return (char) (((char)-1)*(((((((((char)digits[3]) << PyLong_SHIFT) | (char)digits[2]) << PyLong_SHIFT) | (char)digits[1]) << PyLong_SHIFT) | (char)digits[0])));
                        }
                    }
                    break;
                case 4:
                    if (8 * sizeof(char) > 3 * PyLong_SHIFT) {
                        if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) {
                            __PYX_VERIFY_RETURN_INT(char, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])))
                        } else if (8 * sizeof(char) - 1 > 4 * PyLong_SHIFT) {
                            return (char) ((((((((((char)digits[3]) << PyLong_SHIFT) | (char)digits[2]) << PyLong_SHIFT) | (char)digits[1]) << PyLong_SHIFT) | (char)digits[0])));
                        }
                    }
                    break;
            }
#endif
            if (sizeof(char) <= sizeof(long)) {
                __PYX_VERIFY_RETURN_INT_EXC(char, long, PyLong_AsLong(x))
#ifdef HAVE_LONG_LONG
            } else if (sizeof(char) <= sizeof(PY_LONG_LONG)) {
                __PYX_VERIFY_RETURN_INT_EXC(char, PY_LONG_LONG, PyLong_AsLongLong(x))
#endif
            }
        }
        {
#if CYTHON_COMPILING_IN_PYPY && !defined(_PyLong_AsByteArray)
            PyErr_SetString(PyExc_RuntimeError,
                            "_PyLong_AsByteArray() not available in PyPy, cannot convert large numbers");
#else
            char val;
            PyObject *v = __Pyx_PyNumber_IntOrLong(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 (char) -1;
        }
    } else {
        char val;
        PyObject *tmp = __Pyx_PyNumber_IntOrLong(x);
        if (!tmp) return (char) -1;
        val = __Pyx_PyInt_As_char(tmp);
        Py_DECREF(tmp);
        return val;
    }
raise_overflow:
    PyErr_SetString(PyExc_OverflowError,
        "value too large to convert to char");
    return (char) -1;
raise_neg_overflow:
    PyErr_SetString(PyExc_OverflowError,
        "can't convert negative value to char");
    return (char) -1;
}

/* ObjectToMemviewSlice */
                static CYTHON_INLINE __Pyx_memviewslice __Pyx_PyObject_to_MemoryviewSlice_d_dc_float(PyObject *obj) {
    __Pyx_memviewslice result = { 0, 0, { 0 }, { 0 }, { 0 } };
    __Pyx_BufFmt_StackElem stack[1];
    int axes_specs[] = { (__Pyx_MEMVIEW_DIRECT | __Pyx_MEMVIEW_FOLLOW), (__Pyx_MEMVIEW_DIRECT | __Pyx_MEMVIEW_CONTIG) };
    int retcode;
    if (obj == Py_None) {
        result.memview = (struct __pyx_memoryview_obj *) Py_None;
        return result;
    }
    retcode = __Pyx_ValidateAndInit_memviewslice(axes_specs, __Pyx_IS_C_CONTIG,
                                                 (PyBUF_C_CONTIGUOUS | PyBUF_FORMAT | PyBUF_WRITABLE), 2,
                                                 &__Pyx_TypeInfo_float, stack,
                                                 &result, obj);
    if (unlikely(retcode == -1))
        goto __pyx_fail;
    return result;
__pyx_fail:
    result.memview = NULL;
    result.data = NULL;
    return result;
}

/* ObjectToMemviewSlice */
                static CYTHON_INLINE __Pyx_memviewslice __Pyx_PyObject_to_MemoryviewSlice_dc_float(PyObject *obj) {
    __Pyx_memviewslice result = { 0, 0, { 0 }, { 0 }, { 0 } };
    __Pyx_BufFmt_StackElem stack[1];
    int axes_specs[] = { (__Pyx_MEMVIEW_DIRECT | __Pyx_MEMVIEW_CONTIG) };
    int retcode;
    if (obj == Py_None) {
        result.memview = (struct __pyx_memoryview_obj *) Py_None;
        return result;
    }
    retcode = __Pyx_ValidateAndInit_memviewslice(axes_specs, __Pyx_IS_C_CONTIG,
                                                 (PyBUF_C_CONTIGUOUS | PyBUF_FORMAT | PyBUF_WRITABLE), 1,
                                                 &__Pyx_TypeInfo_float, stack,
                                                 &result, obj);
    if (unlikely(retcode == -1))
        goto __pyx_fail;
    return result;
__pyx_fail:
    result.memview = NULL;
    result.data = NULL;
    return result;
}

/* ObjectToMemviewSlice */
                static CYTHON_INLINE __Pyx_memviewslice __Pyx_PyObject_to_MemoryviewSlice_d_dc_double(PyObject *obj) {
    __Pyx_memviewslice result = { 0, 0, { 0 }, { 0 }, { 0 } };
    __Pyx_BufFmt_StackElem stack[1];
    int axes_specs[] = { (__Pyx_MEMVIEW_DIRECT | __Pyx_MEMVIEW_FOLLOW), (__Pyx_MEMVIEW_DIRECT | __Pyx_MEMVIEW_CONTIG) };
    int retcode;
    if (obj == Py_None) {
        result.memview = (struct __pyx_memoryview_obj *) Py_None;
        return result;
    }
    retcode = __Pyx_ValidateAndInit_memviewslice(axes_specs, __Pyx_IS_C_CONTIG,
                                                 (PyBUF_C_CONTIGUOUS | PyBUF_FORMAT | PyBUF_WRITABLE), 2,
                                                 &__Pyx_TypeInfo_double, stack,
                                                 &result, obj);
    if (unlikely(retcode == -1))
        goto __pyx_fail;
    return result;
__pyx_fail:
    result.memview = NULL;
    result.data = NULL;
    return result;
}

/* ObjectToMemviewSlice */
                static CYTHON_INLINE __Pyx_memviewslice __Pyx_PyObject_to_MemoryviewSlice_dc_double(PyObject *obj) {
    __Pyx_memviewslice result = { 0, 0, { 0 }, { 0 }, { 0 } };
    __Pyx_BufFmt_StackElem stack[1];
    int axes_specs[] = { (__Pyx_MEMVIEW_DIRECT | __Pyx_MEMVIEW_CONTIG) };
    int retcode;
    if (obj == Py_None) {
        result.memview = (struct __pyx_memoryview_obj *) Py_None;
        return result;
    }
    retcode = __Pyx_ValidateAndInit_memviewslice(axes_specs, __Pyx_IS_C_CONTIG,
                                                 (PyBUF_C_CONTIGUOUS | PyBUF_FORMAT | PyBUF_WRITABLE), 1,
                                                 &__Pyx_TypeInfo_double, stack,
                                                 &result, obj);
    if (unlikely(retcode == -1))
        goto __pyx_fail;
    return result;
__pyx_fail:
    result.memview = NULL;
    result.data = NULL;
    return result;
}

/* CheckBinaryVersion */
                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);
        return PyErr_WarnEx(NULL, message, 1);
    }
    return 0;
}

/* ModuleImport */
                #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

/* TypeImport */
                #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. Expected %zd, got %zd",
            module_name, class_name, basicsize, size);
        if (PyErr_WarnEx(NULL, warning, 0) < 0) goto bad;
    }
    else if ((size_t)basicsize != size) {
        PyErr_Format(PyExc_ValueError,
            "%.200s.%.200s has the wrong size, try recompiling. Expected %zd, got %zd",
            module_name, class_name, basicsize, size);
        goto bad;
    }
    return (PyTypeObject *)result;
bad:
    Py_XDECREF(py_module);
    Py_XDECREF(result);
    return NULL;
}
#endif

/* InitStrings */
                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
        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;
        if (PyObject_Hash(*t->p) == -1)
            PyErr_Clear();
        ++t;
    }
    return 0;
}

static CYTHON_INLINE PyObject* __Pyx_PyUnicode_FromString(const char* c_str) {
    return __Pyx_PyUnicode_FromStringAndSize(c_str, (Py_ssize_t)strlen(c_str));
}
static CYTHON_INLINE const char* __Pyx_PyObject_AsString(PyObject* o) {
    Py_ssize_t ignore;
    return __Pyx_PyObject_AsStringAndSize(o, &ignore);
}
static CYTHON_INLINE const char* __Pyx_PyObject_AsStringAndSize(PyObject* o, Py_ssize_t *length) {
#if CYTHON_COMPILING_IN_CPYTHON && (__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
        *length = PyBytes_GET_SIZE(defenc);
        return defenc_c;
#else
        if (__Pyx_PyUnicode_READY(o) == -1) return NULL;
#if __PYX_DEFAULT_STRING_ENCODING_IS_ASCII
        if (PyUnicode_IS_ASCII(o)) {
            *length = PyUnicode_GET_LENGTH(o);
            return PyUnicode_AsUTF8(o);
        } else {
            PyUnicode_AsASCIIString(o);
            return NULL;
        }
#else
        return PyUnicode_AsUTF8AndSize(o, length);
#endif
#endif
    } else
#endif
#if (!CYTHON_COMPILING_IN_PYPY) || (defined(PyByteArray_AS_STRING) && defined(PyByteArray_GET_SIZE))
    if (PyByteArray_Check(o)) {
        *length = PyByteArray_GET_SIZE(o);
        return PyByteArray_AS_STRING(o);
    } else
#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_IntOrLong(PyObject* x) {
#if CYTHON_USE_TYPE_SLOTS
  PyNumberMethods *m;
#endif
  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 __Pyx_NewRef(x);
#if CYTHON_USE_TYPE_SLOTS
  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
#else
  res = PyNumber_Int(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;
}
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))) {
    if (sizeof(Py_ssize_t) >= sizeof(long))
        return PyInt_AS_LONG(b);
    else
        return PyInt_AsSsize_t(x);
  }
#endif
  if (likely(PyLong_CheckExact(b))) {
    #if CYTHON_USE_PYLONG_INTERNALS
    const digit* digits = ((PyLongObject*)b)->ob_digit;
    const Py_ssize_t size = Py_SIZE(b);
    if (likely(__Pyx_sst_abs(size) <= 1)) {
        ival = likely(size) ? digits[0] : 0;
        if (size == -1) ival = -ival;
        return ival;
    } else {
      switch (size) {
         case 2:
           if (8 * sizeof(Py_ssize_t) > 2 * PyLong_SHIFT) {
             return (Py_ssize_t) (((((size_t)digits[1]) << PyLong_SHIFT) | (size_t)digits[0]));
           }
           break;
         case -2:
           if (8 * sizeof(Py_ssize_t) > 2 * PyLong_SHIFT) {
             return -(Py_ssize_t) (((((size_t)digits[1]) << PyLong_SHIFT) | (size_t)digits[0]));
           }
           break;
         case 3:
           if (8 * sizeof(Py_ssize_t) > 3 * PyLong_SHIFT) {
             return (Py_ssize_t) (((((((size_t)digits[2]) << PyLong_SHIFT) | (size_t)digits[1]) << PyLong_SHIFT) | (size_t)digits[0]));
           }
           break;
         case -3:
           if (8 * sizeof(Py_ssize_t) > 3 * PyLong_SHIFT) {
             return -(Py_ssize_t) (((((((size_t)digits[2]) << PyLong_SHIFT) | (size_t)digits[1]) << PyLong_SHIFT) | (size_t)digits[0]));
           }
           break;
         case 4:
           if (8 * sizeof(Py_ssize_t) > 4 * PyLong_SHIFT) {
             return (Py_ssize_t) (((((((((size_t)digits[3]) << PyLong_SHIFT) | (size_t)digits[2]) << PyLong_SHIFT) | (size_t)digits[1]) << PyLong_SHIFT) | (size_t)digits[0]));
           }
           break;
         case -4:
           if (8 * sizeof(Py_ssize_t) > 4 * PyLong_SHIFT) {
             return -(Py_ssize_t) (((((((((size_t)digits[3]) << PyLong_SHIFT) | (size_t)digits[2]) << PyLong_SHIFT) | (size_t)digits[1]) << PyLong_SHIFT) | (size_t)digits[0]));
           }
           break;
      }
    }
    #endif
    return PyLong_AsSsize_t(b);
  }
  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) {
    return PyInt_FromSize_t(ival);
}


#endif /* Py_PYTHON_H */
