diff --git a/sklearn/cluster/k_means_.py b/sklearn/cluster/k_means_.py index 1b87dd2b16cb8..fc55ae3d78917 100644 --- a/sklearn/cluster/k_means_.py +++ b/sklearn/cluster/k_means_.py @@ -94,7 +94,7 @@ def _k_init(X, n_clusters, n_local_trials=None, random_state=None, if x_squared_norms is None: x_squared_norms = _squared_norms(X) closest_dist_sq = euclidean_distances( - centers[0], X, Y_norm_squared=x_squared_norms, squared=True) + centers[0], X, Y_norm_precomputed=x_squared_norms, squared=True) current_pot = closest_dist_sq.sum() # Pick the remaining n_clusters-1 points @@ -106,7 +106,8 @@ def _k_init(X, n_clusters, n_local_trials=None, random_state=None, # Compute distances to center candidates distance_to_candidates = euclidean_distances( - X[candidate_ids], X, Y_norm_squared=x_squared_norms, squared=True) + X[candidate_ids], X, Y_norm_precomputed=x_squared_norms, + squared=True) # Decide which candidate is the best best_candidate = None @@ -415,7 +416,8 @@ def _squared_norms(X): def _labels_inertia_precompute_dense(X, x_squared_norms, centers): n_samples = X.shape[0] k = centers.shape[0] - distances = euclidean_distances(centers, X, x_squared_norms, + distances = euclidean_distances(centers, X, + Y_norm_precomputed=x_squared_norms, squared=True) labels = np.empty(n_samples, dtype=np.int) labels.fill(-1) diff --git a/sklearn/manifold/mds.py b/sklearn/manifold/mds.py index a042cf334364f..b1531e5bc94f7 100644 --- a/sklearn/manifold/mds.py +++ b/sklearn/manifold/mds.py @@ -87,9 +87,10 @@ def _smacof_single(similarities, metric=True, n_components=2, init=None, X = init old_stress = None + dis = np.empty((n_samples, n_samples), dtype=np.float64) for it in range(max_iter): # Compute distance and monotonic regression - dis = euclidean_distances(X) + euclidean_distances(X, out=dis) if metric: disparities = similarities @@ -120,16 +121,16 @@ def _smacof_single(similarities, metric=True, n_components=2, init=None, B[np.arange(len(B)), np.arange(len(B))] += ratio.sum(axis=1) X = 1. / n_samples * np.dot(B, X) - dis = np.sqrt((X ** 2).sum(axis=1)).sum() + dis_sum = np.sqrt((X ** 2).sum(axis=1)).sum() if verbose == 2: print 'it: %d, stress %s' % (it, stress) if old_stress is not None: - if(old_stress - stress / dis) < eps: + if(old_stress - stress / dis_sum) < eps: if verbose: print 'breaking at iteration %d with stress %s' % (it, stress) break - old_stress = stress / dis + old_stress = stress / dis_sum return X, stress diff --git a/sklearn/metrics/_euclidean_fast.c b/sklearn/metrics/_euclidean_fast.c new file mode 100644 index 0000000000000..95526b8248b9d --- /dev/null +++ b/sklearn/metrics/_euclidean_fast.c @@ -0,0 +1,9265 @@ +/* Generated by Cython 0.16 on Thu Oct 4 13:28:58 2012 */ + +#define PY_SSIZE_T_CLEAN +#include "Python.h" +#ifndef Py_PYTHON_H + #error Python headers needed to compile C extensions, please install development version of Python. +#elif PY_VERSION_HEX < 0x02040000 + #error Cython requires Python 2.4+. +#else +#include /* For offsetof */ +#ifndef offsetof +#define offsetof(type, member) ( (size_t) & ((type*)0) -> member ) +#endif + +#if !defined(WIN32) && !defined(MS_WINDOWS) + #ifndef __stdcall + #define __stdcall + #endif + #ifndef __cdecl + #define __cdecl + #endif + #ifndef __fastcall + #define __fastcall + #endif +#endif + +#ifndef DL_IMPORT + #define DL_IMPORT(t) t +#endif +#ifndef DL_EXPORT + #define DL_EXPORT(t) t +#endif + +#ifndef PY_LONG_LONG + #define PY_LONG_LONG LONG_LONG +#endif + +#ifndef Py_HUGE_VAL + #define Py_HUGE_VAL HUGE_VAL +#endif + +#ifdef PYPY_VERSION +#define CYTHON_COMPILING_IN_PYPY 1 +#define CYTHON_COMPILING_IN_CPYTHON 0 +#else +#define CYTHON_COMPILING_IN_PYPY 0 +#define CYTHON_COMPILING_IN_CPYTHON 1 +#endif + +#if CYTHON_COMPILING_IN_PYPY + #define __Pyx_PyCFunction_Call PyObject_Call +#else + #define __Pyx_PyCFunction_Call PyCFunction_Call +#endif + +#if PY_VERSION_HEX < 0x02050000 + typedef int Py_ssize_t; 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+ typedef void (*releasebufferproc)(PyObject *, Py_buffer *); +#endif + +#if PY_MAJOR_VERSION < 3 + #define __Pyx_BUILTIN_MODULE_NAME "__builtin__" + #define __Pyx_PyCode_New(a, k, l, s, f, code, c, n, v, fv, cell, fn, name, fline, lnos) \ + PyCode_New(a, l, s, f, code, c, n, v, fv, cell, fn, name, fline, lnos) +#else + #define __Pyx_BUILTIN_MODULE_NAME "builtins" + #define __Pyx_PyCode_New(a, k, l, s, f, code, c, n, v, fv, cell, fn, name, fline, lnos) \ + PyCode_New(a, k, l, s, f, code, c, n, v, fv, cell, fn, name, fline, lnos) +#endif + +#if PY_MAJOR_VERSION < 3 && PY_MINOR_VERSION < 6 + #define PyUnicode_FromString(s) PyUnicode_Decode(s, strlen(s), "UTF-8", "strict") +#endif + +#if PY_MAJOR_VERSION >= 3 + #define Py_TPFLAGS_CHECKTYPES 0 + #define Py_TPFLAGS_HAVE_INDEX 0 +#endif + +#if (PY_VERSION_HEX < 0x02060000) || (PY_MAJOR_VERSION >= 3) + #define Py_TPFLAGS_HAVE_NEWBUFFER 0 +#endif + + +#if PY_VERSION_HEX > 0x03030000 && defined(PyUnicode_GET_LENGTH) + #define CYTHON_PEP393_ENABLED 1 + #define __Pyx_PyUnicode_GET_LENGTH(u) PyUnicode_GET_LENGTH(u) + #define __Pyx_PyUnicode_READ_CHAR(u, i) PyUnicode_READ_CHAR(u, i) +#else + #define CYTHON_PEP393_ENABLED 0 + #define __Pyx_PyUnicode_GET_LENGTH(u) PyUnicode_GET_SIZE(u) + #define __Pyx_PyUnicode_READ_CHAR(u, i) ((Py_UCS4)(PyUnicode_AS_UNICODE(u)[i])) +#endif + +#if PY_MAJOR_VERSION >= 3 + #define PyBaseString_Type PyUnicode_Type + #define PyStringObject PyUnicodeObject + #define PyString_Type PyUnicode_Type + #define PyString_Check PyUnicode_Check + #define PyString_CheckExact PyUnicode_CheckExact +#endif + +#if PY_VERSION_HEX < 0x02060000 + #define PyBytesObject PyStringObject + #define PyBytes_Type PyString_Type + #define PyBytes_Check PyString_Check + #define PyBytes_CheckExact PyString_CheckExact + #define PyBytes_FromString PyString_FromString + #define PyBytes_FromStringAndSize PyString_FromStringAndSize + #define PyBytes_FromFormat PyString_FromFormat + #define PyBytes_DecodeEscape PyString_DecodeEscape + #define PyBytes_AsString PyString_AsString + #define PyBytes_AsStringAndSize PyString_AsStringAndSize + #define PyBytes_Size PyString_Size + #define PyBytes_AS_STRING PyString_AS_STRING + #define PyBytes_GET_SIZE PyString_GET_SIZE + #define PyBytes_Repr PyString_Repr + #define PyBytes_Concat PyString_Concat + #define PyBytes_ConcatAndDel PyString_ConcatAndDel +#endif + +#if PY_VERSION_HEX < 0x02060000 + #define PySet_Check(obj) PyObject_TypeCheck(obj, &PySet_Type) + #define PyFrozenSet_Check(obj) PyObject_TypeCheck(obj, &PyFrozenSet_Type) +#endif +#ifndef PySet_CheckExact + #define PySet_CheckExact(obj) (Py_TYPE(obj) == &PySet_Type) +#endif + +#define __Pyx_TypeCheck(obj, type) PyObject_TypeCheck(obj, (PyTypeObject *)type) + +#if PY_MAJOR_VERSION >= 3 + #define PyIntObject PyLongObject + #define PyInt_Type PyLong_Type + #define PyInt_Check(op) PyLong_Check(op) + #define PyInt_CheckExact(op) PyLong_CheckExact(op) + #define PyInt_FromString PyLong_FromString + #define PyInt_FromUnicode PyLong_FromUnicode + #define PyInt_FromLong PyLong_FromLong + #define PyInt_FromSize_t PyLong_FromSize_t + #define PyInt_FromSsize_t PyLong_FromSsize_t + #define PyInt_AsLong PyLong_AsLong + #define PyInt_AS_LONG PyLong_AS_LONG + #define PyInt_AsSsize_t PyLong_AsSsize_t + #define PyInt_AsUnsignedLongMask PyLong_AsUnsignedLongMask + #define PyInt_AsUnsignedLongLongMask PyLong_AsUnsignedLongLongMask +#endif + +#if PY_MAJOR_VERSION >= 3 + #define PyBoolObject PyLongObject +#endif + +#if PY_VERSION_HEX < 0x03020000 + typedef long Py_hash_t; + #define __Pyx_PyInt_FromHash_t PyInt_FromLong + #define __Pyx_PyInt_AsHash_t PyInt_AsLong +#else + #define __Pyx_PyInt_FromHash_t PyInt_FromSsize_t + #define __Pyx_PyInt_AsHash_t PyInt_AsSsize_t +#endif + +#if (PY_MAJOR_VERSION < 3) || (PY_VERSION_HEX >= 0x03010300) + #define __Pyx_PySequence_GetSlice(obj, a, b) PySequence_GetSlice(obj, a, b) + #define __Pyx_PySequence_SetSlice(obj, a, b, value) PySequence_SetSlice(obj, a, b, value) + #define __Pyx_PySequence_DelSlice(obj, a, b) PySequence_DelSlice(obj, a, b) +#else + #define __Pyx_PySequence_GetSlice(obj, a, b) (unlikely(!(obj)) ? \ + (PyErr_SetString(PyExc_SystemError, "null argument to internal routine"), (PyObject*)0) : \ + (likely((obj)->ob_type->tp_as_mapping) ? (PySequence_GetSlice(obj, a, b)) : \ + (PyErr_Format(PyExc_TypeError, "'%.200s' object is unsliceable", (obj)->ob_type->tp_name), (PyObject*)0))) + #define __Pyx_PySequence_SetSlice(obj, a, b, value) (unlikely(!(obj)) ? \ + (PyErr_SetString(PyExc_SystemError, "null argument to internal routine"), -1) : \ + (likely((obj)->ob_type->tp_as_mapping) ? (PySequence_SetSlice(obj, a, b, value)) : \ + (PyErr_Format(PyExc_TypeError, "'%.200s' object doesn't support slice assignment", (obj)->ob_type->tp_name), -1))) + #define __Pyx_PySequence_DelSlice(obj, a, b) (unlikely(!(obj)) ? \ + (PyErr_SetString(PyExc_SystemError, "null argument to internal routine"), -1) : \ + (likely((obj)->ob_type->tp_as_mapping) ? (PySequence_DelSlice(obj, a, b)) : \ + (PyErr_Format(PyExc_TypeError, "'%.200s' object doesn't support slice deletion", (obj)->ob_type->tp_name), -1))) +#endif + +#if PY_MAJOR_VERSION >= 3 + #define PyMethod_New(func, self, klass) ((self) ? PyMethod_New(func, self) : PyInstanceMethod_New(func)) +#endif + +#if PY_VERSION_HEX < 0x02050000 + #define __Pyx_GetAttrString(o,n) PyObject_GetAttrString((o),((char *)(n))) + #define __Pyx_SetAttrString(o,n,a) PyObject_SetAttrString((o),((char *)(n)),(a)) + #define __Pyx_DelAttrString(o,n) PyObject_DelAttrString((o),((char *)(n))) +#else + #define __Pyx_GetAttrString(o,n) PyObject_GetAttrString((o),(n)) + #define __Pyx_SetAttrString(o,n,a) PyObject_SetAttrString((o),(n),(a)) + #define __Pyx_DelAttrString(o,n) PyObject_DelAttrString((o),(n)) +#endif + +#if PY_VERSION_HEX < 0x02050000 + #define __Pyx_NAMESTR(n) ((char *)(n)) + #define __Pyx_DOCSTR(n) ((char *)(n)) +#else + #define __Pyx_NAMESTR(n) (n) + #define __Pyx_DOCSTR(n) (n) +#endif + +#if PY_MAJOR_VERSION >= 3 + #define __Pyx_PyNumber_Divide(x,y) PyNumber_TrueDivide(x,y) + #define __Pyx_PyNumber_InPlaceDivide(x,y) PyNumber_InPlaceTrueDivide(x,y) +#else + #define __Pyx_PyNumber_Divide(x,y) PyNumber_Divide(x,y) + #define __Pyx_PyNumber_InPlaceDivide(x,y) PyNumber_InPlaceDivide(x,y) +#endif + +#ifndef __PYX_EXTERN_C + #ifdef __cplusplus + #define __PYX_EXTERN_C extern "C" + #else + #define __PYX_EXTERN_C extern + #endif +#endif + +#if defined(WIN32) || defined(MS_WINDOWS) +#define _USE_MATH_DEFINES +#endif +#include +#define __PYX_HAVE__sklearn__metrics___euclidean_fast +#define __PYX_HAVE_API__sklearn__metrics___euclidean_fast +#include "stdio.h" +#include "stdlib.h" +#include "numpy/arrayobject.h" +#include "numpy/ufuncobject.h" +#include "math.h" +#include "cblas.h" +#ifdef _OPENMP +#include +#endif /* _OPENMP */ + +#ifdef PYREX_WITHOUT_ASSERTIONS +#define CYTHON_WITHOUT_ASSERTIONS +#endif + + +/* inline attribute */ +#ifndef CYTHON_INLINE + #if defined(__GNUC__) + #define CYTHON_INLINE __inline__ + #elif defined(_MSC_VER) + #define CYTHON_INLINE __inline + #elif defined (__STDC_VERSION__) && __STDC_VERSION__ >= 199901L + #define CYTHON_INLINE inline + #else + #define CYTHON_INLINE + #endif +#endif + +/* unused attribute */ +#ifndef CYTHON_UNUSED +# if defined(__GNUC__) +# if !(defined(__cplusplus)) || (__GNUC__ > 3 || (__GNUC__ == 3 && __GNUC_MINOR__ >= 4)) +# define CYTHON_UNUSED __attribute__ ((__unused__)) +# else +# define CYTHON_UNUSED +# endif +# elif defined(__ICC) || (defined(__INTEL_COMPILER) && !defined(_MSC_VER)) +# define CYTHON_UNUSED __attribute__ ((__unused__)) +# else +# define CYTHON_UNUSED +# endif +#endif + +typedef struct {PyObject **p; char *s; const long n; const char* encoding; const char is_unicode; const char is_str; const char intern; } __Pyx_StringTabEntry; /*proto*/ + + +/* Type Conversion Predeclarations */ + +#define __Pyx_PyBytes_FromUString(s) PyBytes_FromString((char*)s) +#define __Pyx_PyBytes_AsUString(s) ((unsigned char*) PyBytes_AsString(s)) + +#define __Pyx_Owned_Py_None(b) (Py_INCREF(Py_None), Py_None) +#define __Pyx_PyBool_FromLong(b) ((b) ? 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PyFloat_AS_DOUBLE(x) : PyFloat_AsDouble(x)) +#define __pyx_PyFloat_AsFloat(x) ((float) __pyx_PyFloat_AsDouble(x)) + +#ifdef __GNUC__ + /* Test for GCC > 2.95 */ + #if __GNUC__ > 2 || (__GNUC__ == 2 && (__GNUC_MINOR__ > 95)) + #define likely(x) __builtin_expect(!!(x), 1) + #define unlikely(x) __builtin_expect(!!(x), 0) + #else /* __GNUC__ > 2 ... */ + #define likely(x) (x) + #define unlikely(x) (x) + #endif /* __GNUC__ > 2 ... */ +#else /* __GNUC__ */ + #define likely(x) (x) + #define unlikely(x) (x) +#endif /* __GNUC__ */ + +static PyObject *__pyx_m; +static PyObject *__pyx_b; +static PyObject *__pyx_empty_tuple; +static PyObject *__pyx_empty_bytes; +static int __pyx_lineno; +static int __pyx_clineno = 0; +static const char * __pyx_cfilenm= __FILE__; +static const char *__pyx_filename; + +#if !defined(CYTHON_CCOMPLEX) + #if defined(__cplusplus) + #define CYTHON_CCOMPLEX 1 + #elif defined(_Complex_I) + #define CYTHON_CCOMPLEX 1 + #else + #define CYTHON_CCOMPLEX 0 + #endif +#endif +#if CYTHON_CCOMPLEX + #ifdef __cplusplus + #include + #else + #include + #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[] = { + "_euclidean_fast.pyx", + "numpy.pxd", +}; +#define IS_UNSIGNED(type) (((type) -1) > 0) +struct __Pyx_StructField_; +#define __PYX_BUF_FLAGS_PACKED_STRUCT (1 << 0) +typedef struct { + const char* name; /* for error messages only */ + struct __Pyx_StructField_* fields; + size_t size; /* sizeof(type) */ + size_t arraysize[8]; /* length of array in each dimension */ + int ndim; + char typegroup; /* _R_eal, _C_omplex, Signed _I_nt, _U_nsigned int, _S_truct, _P_ointer, _O_bject */ + 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; + + +/* "numpy.pxd":722 + * # 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; + +/* "numpy.pxd":723 + * + * 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; + +/* "numpy.pxd":724 + * 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; + +/* "numpy.pxd":725 + * 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; + +/* "numpy.pxd":729 + * #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; + +/* "numpy.pxd":730 + * + * 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; + +/* "numpy.pxd":731 + * 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; + +/* "numpy.pxd":732 + * 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; + +/* "numpy.pxd":736 + * #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; + +/* "numpy.pxd":737 + * + * 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; + +/* "numpy.pxd":746 + * # 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; + +/* "numpy.pxd":747 + * # 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; + +/* "numpy.pxd":748 + * 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; + +/* "numpy.pxd":750 + * 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; + +/* "numpy.pxd":751 + * + * ctypedef npy_ulong uint_t + * ctypedef npy_ulonglong ulong_t # <<<<<<<<<<<<<< + * ctypedef npy_ulonglong ulonglong_t + * + */ +typedef npy_ulonglong __pyx_t_5numpy_ulong_t; + +/* "numpy.pxd":752 + * 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; + +/* "numpy.pxd":754 + * ctypedef npy_ulonglong ulonglong_t + * + * ctypedef npy_intp intp_t # <<<<<<<<<<<<<< + * ctypedef npy_uintp uintp_t + * + */ +typedef npy_intp __pyx_t_5numpy_intp_t; + +/* "numpy.pxd":755 + * + * ctypedef npy_intp intp_t + * ctypedef npy_uintp uintp_t # <<<<<<<<<<<<<< + * + * ctypedef npy_double float_t + */ +typedef npy_uintp __pyx_t_5numpy_uintp_t; + +/* "numpy.pxd":757 + * 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; + +/* "numpy.pxd":758 + * + * ctypedef npy_double float_t + * ctypedef npy_double double_t # <<<<<<<<<<<<<< + * ctypedef npy_longdouble longdouble_t + * + */ +typedef npy_double __pyx_t_5numpy_double_t; + +/* "numpy.pxd":759 + * 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/metrics/_euclidean_fast.pyx":14 + * + * cimport cython + * ctypedef np.int32_t INTEGER # <<<<<<<<<<<<<< + * ctypedef np.float64_t DTYPE_t + * + */ +typedef __pyx_t_5numpy_int32_t __pyx_t_7sklearn_7metrics_15_euclidean_fast_INTEGER; + +/* "sklearn/metrics/_euclidean_fast.pyx":15 + * cimport cython + * ctypedef np.int32_t INTEGER + * ctypedef np.float64_t DTYPE_t # <<<<<<<<<<<<<< + * + * cdef extern from "math.h": + */ +typedef __pyx_t_5numpy_float64_t __pyx_t_7sklearn_7metrics_15_euclidean_fast_DTYPE_t; +#if CYTHON_CCOMPLEX + #ifdef __cplusplus + typedef ::std::complex< float > __pyx_t_float_complex; + #else + typedef float _Complex __pyx_t_float_complex; + #endif +#else + typedef struct { float real, imag; } __pyx_t_float_complex; +#endif + +#if CYTHON_CCOMPLEX + #ifdef __cplusplus + typedef ::std::complex< double > __pyx_t_double_complex; + #else + typedef double _Complex __pyx_t_double_complex; + #endif +#else + typedef struct { double real, imag; } __pyx_t_double_complex; 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+ +/* "sklearn/metrics/_euclidean_fast.pyx":30 + * + * + * cdef inline _euclidean_distances(int X_rows, # <<<<<<<<<<<<<< + * int Y_rows, + * np.ndarray[DTYPE_t, ndim=1] X_norm_squared, + */ +struct __pyx_opt_args_7sklearn_7metrics_15_euclidean_fast__euclidean_distances { + int __pyx_n; + int squared; + int sym; +}; +#ifndef CYTHON_REFNANNY + #define CYTHON_REFNANNY 0 +#endif +#if CYTHON_REFNANNY + typedef struct { + void (*INCREF)(void*, PyObject*, int); + void (*DECREF)(void*, PyObject*, int); + void (*GOTREF)(void*, PyObject*, int); + void (*GIVEREF)(void*, PyObject*, int); + void* (*SetupContext)(const char*, int, const char*); + void (*FinishContext)(void**); + } __Pyx_RefNannyAPIStruct; + static __Pyx_RefNannyAPIStruct *__Pyx_RefNanny = NULL; + static __Pyx_RefNannyAPIStruct *__Pyx_RefNannyImportAPI(const char *modname); /*proto*/ + #define __Pyx_RefNannyDeclarations void *__pyx_refnanny = NULL; +#ifdef WITH_THREAD + #define __Pyx_RefNannySetupContext(name, acquire_gil) \ + if (acquire_gil) { \ + PyGILState_STATE __pyx_gilstate_save = PyGILState_Ensure(); 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}} while(0) + #define __Pyx_XGIVEREF(r) do { if((r) != NULL) {__Pyx_GIVEREF(r);}} while(0) +#else + #define __Pyx_RefNannyDeclarations + #define __Pyx_RefNannySetupContext(name, acquire_gil) + #define __Pyx_RefNannyFinishContext() + #define __Pyx_INCREF(r) Py_INCREF(r) + #define __Pyx_DECREF(r) Py_DECREF(r) + #define __Pyx_GOTREF(r) + #define __Pyx_GIVEREF(r) + #define __Pyx_XINCREF(r) Py_XINCREF(r) + #define __Pyx_XDECREF(r) Py_XDECREF(r) + #define __Pyx_XGOTREF(r) + #define __Pyx_XGIVEREF(r) +#endif /* CYTHON_REFNANNY */ +#define __Pyx_CLEAR(r) do { PyObject* tmp = ((PyObject*)(r)); r = NULL; __Pyx_DECREF(tmp);} while(0) +#define __Pyx_XCLEAR(r) do { if((r) != NULL) {PyObject* tmp = ((PyObject*)(r)); r = NULL; __Pyx_DECREF(tmp);}} while(0) + +static PyObject *__Pyx_GetName(PyObject *dict, PyObject *name); /*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); 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+static Py_ssize_t __Pyx_minusones[] = {-1, -1, -1, -1, -1, -1, -1, -1}; + +static PyObject *__Pyx_Import(PyObject *name, PyObject *from_list, long level); /*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(_WIN32) && defined(__cplusplus) && CYTHON_CCOMPLEX + #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 + +static CYTHON_INLINE __pyx_t_float_complex __pyx_t_float_complex_from_parts(float, float); + +#if CYTHON_CCOMPLEX + #define __Pyx_c_eqf(a, b) ((a)==(b)) + #define __Pyx_c_sumf(a, b) ((a)+(b)) + #define __Pyx_c_difff(a, b) ((a)-(b)) + #define __Pyx_c_prodf(a, b) ((a)*(b)) + #define __Pyx_c_quotf(a, b) ((a)/(b)) + #define __Pyx_c_negf(a) (-(a)) + #ifdef __cplusplus + #define __Pyx_c_is_zerof(z) ((z)==(float)0) + #define __Pyx_c_conjf(z) (::std::conj(z)) + #if 1 + #define __Pyx_c_absf(z) (::std::abs(z)) + #define __Pyx_c_powf(a, b) (::std::pow(a, b)) + #endif + #else + #define __Pyx_c_is_zerof(z) ((z)==0) + #define __Pyx_c_conjf(z) (conjf(z)) + #if 1 + #define __Pyx_c_absf(z) (cabsf(z)) + #define __Pyx_c_powf(a, b) (cpowf(a, b)) + #endif + #endif +#else + static CYTHON_INLINE int __Pyx_c_eqf(__pyx_t_float_complex, __pyx_t_float_complex); + static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_sumf(__pyx_t_float_complex, __pyx_t_float_complex); + static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_difff(__pyx_t_float_complex, __pyx_t_float_complex); + static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_prodf(__pyx_t_float_complex, __pyx_t_float_complex); + static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_quotf(__pyx_t_float_complex, __pyx_t_float_complex); + static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_negf(__pyx_t_float_complex); + static CYTHON_INLINE int __Pyx_c_is_zerof(__pyx_t_float_complex); + static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_conjf(__pyx_t_float_complex); + #if 1 + static CYTHON_INLINE float __Pyx_c_absf(__pyx_t_float_complex); + static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_powf(__pyx_t_float_complex, __pyx_t_float_complex); + #endif +#endif + +static CYTHON_INLINE __pyx_t_double_complex __pyx_t_double_complex_from_parts(double, double); + +#if CYTHON_CCOMPLEX + #define __Pyx_c_eq(a, b) ((a)==(b)) + #define __Pyx_c_sum(a, b) ((a)+(b)) + #define __Pyx_c_diff(a, b) ((a)-(b)) + #define __Pyx_c_prod(a, b) ((a)*(b)) + #define __Pyx_c_quot(a, b) ((a)/(b)) + #define __Pyx_c_neg(a) (-(a)) + #ifdef __cplusplus + #define __Pyx_c_is_zero(z) ((z)==(double)0) + #define __Pyx_c_conj(z) (::std::conj(z)) + #if 1 + #define __Pyx_c_abs(z) (::std::abs(z)) + #define __Pyx_c_pow(a, b) (::std::pow(a, b)) + #endif + #else + #define __Pyx_c_is_zero(z) ((z)==0) + #define __Pyx_c_conj(z) (conj(z)) + #if 1 + #define __Pyx_c_abs(z) (cabs(z)) + #define __Pyx_c_pow(a, b) (cpow(a, b)) + #endif + #endif +#else + static CYTHON_INLINE int __Pyx_c_eq(__pyx_t_double_complex, __pyx_t_double_complex); 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+ +static CYTHON_INLINE unsigned int __Pyx_PyInt_AsUnsignedInt(PyObject *); + +static CYTHON_INLINE char __Pyx_PyInt_AsChar(PyObject *); + +static CYTHON_INLINE short __Pyx_PyInt_AsShort(PyObject *); + +static CYTHON_INLINE int __Pyx_PyInt_AsInt(PyObject *); + +static CYTHON_INLINE signed char __Pyx_PyInt_AsSignedChar(PyObject *); + +static CYTHON_INLINE signed short __Pyx_PyInt_AsSignedShort(PyObject *); + +static CYTHON_INLINE signed int __Pyx_PyInt_AsSignedInt(PyObject *); + +static CYTHON_INLINE int __Pyx_PyInt_AsLongDouble(PyObject *); + +static CYTHON_INLINE unsigned long __Pyx_PyInt_AsUnsignedLong(PyObject *); + +static CYTHON_INLINE unsigned PY_LONG_LONG __Pyx_PyInt_AsUnsignedLongLong(PyObject *); + +static CYTHON_INLINE long __Pyx_PyInt_AsLong(PyObject *); + +static CYTHON_INLINE PY_LONG_LONG __Pyx_PyInt_AsLongLong(PyObject *); + +static CYTHON_INLINE signed long __Pyx_PyInt_AsSignedLong(PyObject *); + +static CYTHON_INLINE signed PY_LONG_LONG __Pyx_PyInt_AsSignedLongLong(PyObject *); + +static int __Pyx_check_binary_version(void); + +#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 + +static PyTypeObject *__Pyx_ImportType(const char *module_name, const char *class_name, size_t size, int strict); /*proto*/ + +static PyObject *__Pyx_ImportModule(const char *name); /*proto*/ + +typedef struct { + int code_line; + PyCodeObject* code_object; +} __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); + +static void __Pyx_AddTraceback(const char *funcname, int c_line, + int py_line, const char *filename); 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+ 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 != ')') { + if (isspace(*ts)) + continue; + number = __Pyx_BufFmt_ExpectNumber(&ts); + if (number == -1) return NULL; + if (i < ndim && (size_t) number != ctx->head->field->type->arraysize[i]) + return PyErr_Format(PyExc_ValueError, + "Expected a dimension of size %zu, got %d", + ctx->head->field->type->arraysize[i], number); + if (*ts != ',' && *ts != ')') + return PyErr_Format(PyExc_ValueError, + "Expected a comma in format string, got '%c'", *ts); + if (*ts == ',') ts++; + i++; + } + if (i != ndim) + return PyErr_Format(PyExc_ValueError, "Expected %d dimension(s), got %d", + ctx->head->field->type->ndim, i); + if (!*ts) { + PyErr_SetString(PyExc_ValueError, + "Unexpected end of format string, expected ')'"); + return NULL; + } + ctx->is_valid_array = 1; + ctx->new_count = 1; + *tsp = ++ts; + return Py_None; +} +static const char* __Pyx_BufFmt_CheckString(__Pyx_BufFmt_Context* ctx, const char* ts) { + int got_Z = 0; + while (1) { + switch(*ts) { + case 0: + if (ctx->enc_type != 0 && ctx->head == NULL) { + __Pyx_BufFmt_RaiseExpected(ctx); + return NULL; + } + if (__Pyx_BufFmt_ProcessTypeChunk(ctx) == -1) return NULL; + if (ctx->head != NULL) { + __Pyx_BufFmt_RaiseExpected(ctx); + return NULL; + } + return ts; + case ' ': + case 10: + case 13: + ++ts; + break; + case '<': + if (!__Pyx_IsLittleEndian()) { + PyErr_SetString(PyExc_ValueError, "Little-endian buffer not supported on big-endian compiler"); + return NULL; + } + ctx->new_packmode = '='; + ++ts; + break; + case '>': + case '!': + if (__Pyx_IsLittleEndian()) { + PyErr_SetString(PyExc_ValueError, "Big-endian buffer not supported on little-endian compiler"); + return NULL; + } + ctx->new_packmode = '='; + ++ts; + break; + case '=': + case '@': + case '^': + ctx->new_packmode = *ts++; + break; + case 'T': /* substruct */ + { + const char* ts_after_sub; + size_t i, struct_count = ctx->new_count; + size_t struct_alignment = ctx->struct_alignment; + ctx->new_count = 1; + ++ts; + if (*ts != '{') { + PyErr_SetString(PyExc_ValueError, "Buffer acquisition: Expected '{' after 'T'"); + return NULL; + } + if (__Pyx_BufFmt_ProcessTypeChunk(ctx) == -1) return NULL; + ctx->enc_type = 0; /* Erase processed last struct element */ + ctx->enc_count = 0; + ctx->struct_alignment = 0; + ++ts; + ts_after_sub = ts; + for (i = 0; i != struct_count; ++i) { + ts_after_sub = __Pyx_BufFmt_CheckString(ctx, ts); + if (!ts_after_sub) return NULL; + } + ts = ts_after_sub; + if (struct_alignment) ctx->struct_alignment = struct_alignment; + } + break; + case '}': /* end of substruct; either repeat or move on */ + { + size_t alignment = ctx->struct_alignment; + ++ts; + if (__Pyx_BufFmt_ProcessTypeChunk(ctx) == -1) return NULL; + ctx->enc_type = 0; /* Erase processed last struct element */ + if (alignment && ctx->fmt_offset % alignment) { + ctx->fmt_offset += alignment - (ctx->fmt_offset % alignment); + } + } + return ts; + case 'x': + if (__Pyx_BufFmt_ProcessTypeChunk(ctx) == -1) return NULL; + ctx->fmt_offset += ctx->new_count; + ctx->new_count = 1; + ctx->enc_count = 0; + ctx->enc_type = 0; + ctx->enc_packmode = ctx->new_packmode; + ++ts; + break; + case 'Z': + got_Z = 1; + ++ts; + if (*ts != 'f' && *ts != 'd' && *ts != 'g') { + __Pyx_BufFmt_RaiseUnexpectedChar('Z'); + return NULL; + } /* fall through */ + case 'c': case 'b': case 'B': case 'h': case 'H': case 'i': case 'I': + case 'l': case 'L': case 'q': case 'Q': + case 'f': case 'd': case 'g': + case 'O': case 's': case 'p': + if (ctx->enc_type == *ts && got_Z == ctx->is_complex && + ctx->enc_packmode == ctx->new_packmode) { + ctx->enc_count += ctx->new_count; + } else { + if (__Pyx_BufFmt_ProcessTypeChunk(ctx) == -1) return NULL; + ctx->enc_count = ctx->new_count; + ctx->enc_packmode = ctx->new_packmode; + ctx->enc_type = *ts; + ctx->is_complex = got_Z; + } + ++ts; + ctx->new_count = 1; + got_Z = 0; + break; + case ':': + ++ts; + while(*ts != ':') ++ts; + ++ts; + break; + case '(': + if (!__pyx_buffmt_parse_array(ctx, &ts)) return NULL; + break; + default: + { + int number = __Pyx_BufFmt_ExpectNumber(&ts); + if (number == -1) return NULL; + ctx->new_count = (size_t)number; + } + } + } +} +static CYTHON_INLINE void __Pyx_ZeroBuffer(Py_buffer* buf) { + buf->buf = NULL; + buf->obj = NULL; + buf->strides = __Pyx_zeros; + buf->shape = __Pyx_zeros; + buf->suboffsets = __Pyx_minusones; +} +static CYTHON_INLINE int __Pyx_GetBufferAndValidate( + Py_buffer* buf, PyObject* obj, __Pyx_TypeInfo* dtype, int flags, + int nd, int cast, __Pyx_BufFmt_StackElem* stack) +{ + if (obj == Py_None || obj == NULL) { + __Pyx_ZeroBuffer(buf); + return 0; + } + buf->buf = NULL; + if (__Pyx_GetBuffer(obj, buf, flags) == -1) goto fail; + if (buf->ndim != nd) { + PyErr_Format(PyExc_ValueError, + "Buffer has wrong number of dimensions (expected %d, got %d)", + nd, buf->ndim); + goto fail; + } + if (!cast) { + __Pyx_BufFmt_Context ctx; + __Pyx_BufFmt_Init(&ctx, stack, dtype); + if (!__Pyx_BufFmt_CheckString(&ctx, buf->format)) goto fail; + } + if ((unsigned)buf->itemsize != dtype->size) { + PyErr_Format(PyExc_ValueError, + "Item size of buffer (%"PY_FORMAT_SIZE_T"d byte%s) does not match size of '%s' (%"PY_FORMAT_SIZE_T"d byte%s)", + buf->itemsize, (buf->itemsize > 1) ? "s" : "", + dtype->name, (Py_ssize_t)dtype->size, (dtype->size > 1) ? "s" : ""); + goto fail; + } + if (buf->suboffsets == NULL) buf->suboffsets = __Pyx_minusones; + return 0; +fail:; + __Pyx_ZeroBuffer(buf); + return -1; +} +static CYTHON_INLINE void __Pyx_SafeReleaseBuffer(Py_buffer* info) { + if (info->buf == NULL) return; + if (info->suboffsets == __Pyx_minusones) info->suboffsets = NULL; + __Pyx_ReleaseBuffer(info); +} + +static void __Pyx_RaiseBufferIndexError(int axis) { + PyErr_Format(PyExc_IndexError, + "Out of bounds on buffer access (axis %d)", axis); +} + +static CYTHON_INLINE void __Pyx_ErrRestore(PyObject *type, PyObject *value, PyObject *tb) { +#if CYTHON_COMPILING_IN_CPYTHON + PyObject *tmp_type, *tmp_value, *tmp_tb; + PyThreadState *tstate = PyThreadState_GET(); + tmp_type = tstate->curexc_type; + tmp_value = tstate->curexc_value; + tmp_tb = tstate->curexc_traceback; + tstate->curexc_type = type; + tstate->curexc_value = value; + tstate->curexc_traceback = tb; + Py_XDECREF(tmp_type); + Py_XDECREF(tmp_value); + Py_XDECREF(tmp_tb); +#else + PyErr_Restore(type, value, tb); +#endif +} +static CYTHON_INLINE void __Pyx_ErrFetch(PyObject **type, PyObject **value, PyObject **tb) { +#if CYTHON_COMPILING_IN_CPYTHON + PyThreadState *tstate = PyThreadState_GET(); + *type = tstate->curexc_type; + *value = tstate->curexc_value; + *tb = tstate->curexc_traceback; + tstate->curexc_type = 0; + tstate->curexc_value = 0; + tstate->curexc_traceback = 0; +#else + PyErr_Fetch(type, value, tb); +#endif +} + +static void __Pyx_RaiseArgtupleInvalid( + const char* func_name, + int exact, + Py_ssize_t num_min, + Py_ssize_t num_max, + Py_ssize_t num_found) +{ + Py_ssize_t num_expected; + const char *more_or_less; + if (num_found < num_min) { + num_expected = num_min; + more_or_less = "at least"; + } else { + num_expected = num_max; + more_or_less = "at most"; + } + if (exact) { + more_or_less = "exactly"; + } + PyErr_Format(PyExc_TypeError, + "%s() takes %s %"PY_FORMAT_SIZE_T"d positional argument%s (%"PY_FORMAT_SIZE_T"d given)", + func_name, more_or_less, num_expected, + (num_expected == 1) ? "" : "s", num_found); +} + +static void __Pyx_RaiseDoubleKeywordsError( + const char* func_name, + PyObject* kw_name) +{ + PyErr_Format(PyExc_TypeError, + #if PY_MAJOR_VERSION >= 3 + "%s() got multiple values for keyword argument '%U'", func_name, kw_name); + #else + "%s() got multiple values for keyword argument '%s'", func_name, + PyString_AS_STRING(kw_name)); + #endif +} + +static int __Pyx_ParseOptionalKeywords( + PyObject *kwds, + PyObject **argnames[], + PyObject *kwds2, + PyObject *values[], + Py_ssize_t num_pos_args, + const char* function_name) +{ + PyObject *key = 0, *value = 0; + Py_ssize_t pos = 0; + PyObject*** name; + PyObject*** first_kw_arg = argnames + num_pos_args; + while (PyDict_Next(kwds, &pos, &key, &value)) { + name = first_kw_arg; + while (*name && (**name != key)) name++; + if (*name) { + values[name-argnames] = value; + } else { + #if PY_MAJOR_VERSION < 3 + if (unlikely(!PyString_CheckExact(key)) && unlikely(!PyString_Check(key))) { + #else + if (unlikely(!PyUnicode_Check(key))) { + #endif + goto invalid_keyword_type; + } else { + for (name = first_kw_arg; *name; name++) { + #if PY_MAJOR_VERSION >= 3 + if (PyUnicode_GET_SIZE(**name) == PyUnicode_GET_SIZE(key) && + PyUnicode_Compare(**name, key) == 0) break; + #else + if (PyString_GET_SIZE(**name) == PyString_GET_SIZE(key) && + _PyString_Eq(**name, key)) break; + #endif + } + if (*name) { + values[name-argnames] = value; + } else { + for (name=argnames; name != first_kw_arg; name++) { + if (**name == key) goto arg_passed_twice; + #if PY_MAJOR_VERSION >= 3 + if (PyUnicode_GET_SIZE(**name) == PyUnicode_GET_SIZE(key) && + PyUnicode_Compare(**name, key) == 0) goto arg_passed_twice; + #else + if (PyString_GET_SIZE(**name) == PyString_GET_SIZE(key) && + _PyString_Eq(**name, key)) goto arg_passed_twice; + #endif + } + if (kwds2) { + if (unlikely(PyDict_SetItem(kwds2, key, value))) goto bad; + } else { + goto invalid_keyword; + } + } + } + } + } + return 0; +arg_passed_twice: + __Pyx_RaiseDoubleKeywordsError(function_name, **name); + goto bad; +invalid_keyword_type: + PyErr_Format(PyExc_TypeError, + "%s() keywords must be strings", function_name); + goto bad; +invalid_keyword: + PyErr_Format(PyExc_TypeError, + #if PY_MAJOR_VERSION < 3 + "%s() got an unexpected keyword argument '%s'", + function_name, PyString_AsString(key)); + #else + "%s() got an unexpected keyword argument '%U'", + function_name, key); + #endif +bad: + return -1; +} + +static int __Pyx_ArgTypeTest(PyObject *obj, PyTypeObject *type, int none_allowed, + const char *name, int exact) +{ + if (!type) { + PyErr_Format(PyExc_SystemError, "Missing type object"); + return 0; + } + if (none_allowed && obj == Py_None) return 1; + else if (exact) { + if (Py_TYPE(obj) == type) return 1; + } + else { + if (PyObject_TypeCheck(obj, type)) return 1; + } + PyErr_Format(PyExc_TypeError, + "Argument '%s' has incorrect type (expected %s, got %s)", + name, type->tp_name, Py_TYPE(obj)->tp_name); + return 0; +} + +#if PY_MAJOR_VERSION < 3 +static void __Pyx_Raise(PyObject *type, PyObject *value, PyObject *tb, + CYTHON_UNUSED PyObject *cause) { + Py_XINCREF(type); + Py_XINCREF(value); + Py_XINCREF(tb); + if (tb == Py_None) { + Py_DECREF(tb); + tb = 0; + } + else if (tb != NULL && !PyTraceBack_Check(tb)) { + PyErr_SetString(PyExc_TypeError, + "raise: arg 3 must be a traceback or None"); + goto raise_error; + } + if (value == NULL) { + value = Py_None; + Py_INCREF(value); + } + #if PY_VERSION_HEX < 0x02050000 + if (!PyClass_Check(type)) + #else + if (!PyType_Check(type)) + #endif + { + if (value != Py_None) { + PyErr_SetString(PyExc_TypeError, + "instance exception may not have a separate value"); + goto raise_error; + } + Py_DECREF(value); + value = type; + #if PY_VERSION_HEX < 0x02050000 + if (PyInstance_Check(type)) { + type = (PyObject*) ((PyInstanceObject*)type)->in_class; + Py_INCREF(type); + } + else { + type = 0; + PyErr_SetString(PyExc_TypeError, + "raise: exception must be an old-style class or instance"); + goto raise_error; + } + #else + type = (PyObject*) Py_TYPE(type); + Py_INCREF(type); + if (!PyType_IsSubtype((PyTypeObject *)type, (PyTypeObject *)PyExc_BaseException)) { + PyErr_SetString(PyExc_TypeError, + "raise: exception class must be a subclass of BaseException"); + goto raise_error; + } + #endif + } + __Pyx_ErrRestore(type, value, tb); + return; +raise_error: + Py_XDECREF(value); + Py_XDECREF(type); + Py_XDECREF(tb); + return; +} +#else /* Python 3+ */ +static void __Pyx_Raise(PyObject *type, PyObject *value, PyObject *tb, PyObject *cause) { + 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)) { + PyErr_SetString(PyExc_TypeError, + "raise: exception class must be a subclass of BaseException"); + goto bad; + } + if (cause) { + PyObject *fixed_cause; + 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; + } + if (!value) { + value = PyObject_CallObject(type, NULL); + } + PyException_SetCause(value, fixed_cause); + } + PyErr_SetObject(type, value); + if (tb) { + PyThreadState *tstate = PyThreadState_GET(); + PyObject* tmp_tb = tstate->curexc_traceback; + if (tb != tmp_tb) { + Py_INCREF(tb); + tstate->curexc_traceback = tb; + Py_XDECREF(tmp_tb); + } + } +bad: + return; +} +#endif + +static CYTHON_INLINE int __Pyx_TypeTest(PyObject *obj, PyTypeObject *type) { + if (unlikely(!type)) { + PyErr_Format(PyExc_SystemError, "Missing type object"); + return 0; + } + if (likely(PyObject_TypeCheck(obj, type))) + return 1; + PyErr_Format(PyExc_TypeError, "Cannot convert %.200s to %.200s", + Py_TYPE(obj)->tp_name, type->tp_name); + return 0; +} + +static void __Pyx_RaiseBufferFallbackError(void) { + PyErr_Format(PyExc_ValueError, + "Buffer acquisition failed on assignment; and then reacquiring the old buffer failed too!"); +} + +static CYTHON_INLINE void __Pyx_RaiseNeedMoreValuesError(Py_ssize_t index) { + PyErr_Format(PyExc_ValueError, + "need more than %"PY_FORMAT_SIZE_T"d value%s to unpack", + index, (index == 1) ? "" : "s"); +} + +static CYTHON_INLINE void __Pyx_RaiseTooManyValuesError(Py_ssize_t expected) { + PyErr_Format(PyExc_ValueError, + "too many values to unpack (expected %"PY_FORMAT_SIZE_T"d)", expected); +} + +static CYTHON_INLINE void __Pyx_RaiseNoneNotIterableError(void) { + PyErr_SetString(PyExc_TypeError, "'NoneType' object is not iterable"); +} + +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); + } +} + +#if PY_MAJOR_VERSION < 3 +static int __Pyx_GetBuffer(PyObject *obj, Py_buffer *view, int flags) { + PyObject *getbuffer_cobj; + + #if PY_VERSION_HEX >= 0x02060000 + if (PyObject_CheckBuffer(obj)) return PyObject_GetBuffer(obj, view, flags); + #endif + + if (PyObject_TypeCheck(obj, __pyx_ptype_5numpy_ndarray)) return __pyx_pw_5numpy_7ndarray_1__getbuffer__(obj, view, flags); + + #if PY_VERSION_HEX < 0x02060000 + if (obj->ob_type->tp_dict && + (getbuffer_cobj = PyMapping_GetItemString(obj->ob_type->tp_dict, + "__pyx_getbuffer"))) { + getbufferproc func; + + #if PY_VERSION_HEX >= 0x02070000 && !(PY_MAJOR_VERSION == 3 && PY_MINOR_VERSION == 0) + func = (getbufferproc) PyCapsule_GetPointer(getbuffer_cobj, "getbuffer(obj, view, flags)"); + #else + func = (getbufferproc) PyCObject_AsVoidPtr(getbuffer_cobj); + #endif + Py_DECREF(getbuffer_cobj); + if (!func) + goto fail; + + return func(obj, view, flags); + } else { + PyErr_Clear(); + } + #endif + + PyErr_Format(PyExc_TypeError, "'%100s' does not have the buffer interface", Py_TYPE(obj)->tp_name); + +#if PY_VERSION_HEX < 0x02060000 +fail: +#endif + + return -1; +} + +static void __Pyx_ReleaseBuffer(Py_buffer *view) { + PyObject *obj = view->obj; + PyObject *releasebuffer_cobj; + + if (!obj) return; + + #if PY_VERSION_HEX >= 0x02060000 + if (PyObject_CheckBuffer(obj)) { + PyBuffer_Release(view); + return; + } + #endif + + if (PyObject_TypeCheck(obj, __pyx_ptype_5numpy_ndarray)) { __pyx_pw_5numpy_7ndarray_3__releasebuffer__(obj, view); return; } + + #if PY_VERSION_HEX < 0x02060000 + if (obj->ob_type->tp_dict && + (releasebuffer_cobj = PyMapping_GetItemString(obj->ob_type->tp_dict, + "__pyx_releasebuffer"))) { + releasebufferproc func; + + #if PY_VERSION_HEX >= 0x02070000 && !(PY_MAJOR_VERSION == 3 && PY_MINOR_VERSION == 0) + func = (releasebufferproc) PyCapsule_GetPointer(releasebuffer_cobj, "releasebuffer(obj, view)"); + #else + func = (releasebufferproc) PyCObject_AsVoidPtr(releasebuffer_cobj); + #endif + + Py_DECREF(releasebuffer_cobj); + + if (!func) + goto fail; + + func(obj, view); + return; + } else { + PyErr_Clear(); + } + #endif + + goto nofail; + +#if PY_VERSION_HEX < 0x02060000 +fail: +#endif + PyErr_WriteUnraisable(obj); + +nofail: + Py_DECREF(obj); + view->obj = NULL; +} + +#endif /* PY_MAJOR_VERSION < 3 */ + + static PyObject *__Pyx_Import(PyObject *name, PyObject *from_list, long level) { + PyObject *py_import = 0; + PyObject *empty_list = 0; + PyObject *module = 0; + PyObject *global_dict = 0; + PyObject *empty_dict = 0; + PyObject *list; + py_import = __Pyx_GetAttrString(__pyx_b, "__import__"); + if (!py_import) + goto bad; + if (from_list) + list = from_list; + else { + empty_list = PyList_New(0); + if (!empty_list) + goto bad; + list = empty_list; + } + global_dict = PyModule_GetDict(__pyx_m); + if (!global_dict) + goto bad; + empty_dict = PyDict_New(); + if (!empty_dict) + goto bad; + #if PY_VERSION_HEX >= 0x02050000 + { + #if PY_MAJOR_VERSION >= 3 + if (level == -1) { + if (strchr(__Pyx_MODULE_NAME, '.')) { + /* try package relative import first */ + 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); + if (!module) { + if (!PyErr_ExceptionMatches(PyExc_ImportError)) + goto bad; + PyErr_Clear(); + } + } + level = 0; /* try absolute import on failure */ + } + #endif + if (!module) { + 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 + if (level>0) { + PyErr_SetString(PyExc_RuntimeError, "Relative import is not supported for Python <=2.4."); + goto bad; + } + module = PyObject_CallFunctionObjArgs(py_import, + name, global_dict, empty_dict, list, NULL); + #endif +bad: + Py_XDECREF(empty_list); + Py_XDECREF(py_import); + Py_XDECREF(empty_dict); + return module; +} + +#if CYTHON_CCOMPLEX + #ifdef __cplusplus + static CYTHON_INLINE __pyx_t_float_complex __pyx_t_float_complex_from_parts(float x, float y) { + return ::std::complex< float >(x, y); + } + #else + static CYTHON_INLINE __pyx_t_float_complex __pyx_t_float_complex_from_parts(float x, float y) { + return x + y*(__pyx_t_float_complex)_Complex_I; + } + #endif +#else + static CYTHON_INLINE __pyx_t_float_complex __pyx_t_float_complex_from_parts(float x, float y) { + __pyx_t_float_complex z; + z.real = x; + z.imag = y; + return z; + } +#endif + +#if CYTHON_CCOMPLEX +#else + static CYTHON_INLINE int __Pyx_c_eqf(__pyx_t_float_complex a, __pyx_t_float_complex b) { + return (a.real == b.real) && (a.imag == b.imag); + } + static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_sumf(__pyx_t_float_complex a, __pyx_t_float_complex b) { + __pyx_t_float_complex z; + z.real = a.real + b.real; + z.imag = a.imag + b.imag; + return z; + } + static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_difff(__pyx_t_float_complex a, __pyx_t_float_complex b) { + __pyx_t_float_complex z; + z.real = a.real - b.real; + z.imag = a.imag - b.imag; + return z; + } + static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_prodf(__pyx_t_float_complex a, __pyx_t_float_complex b) { + __pyx_t_float_complex z; + z.real = a.real * b.real - a.imag * b.imag; + z.imag = a.real * b.imag + a.imag * b.real; + return z; + } + static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_quotf(__pyx_t_float_complex a, __pyx_t_float_complex b) { + __pyx_t_float_complex z; + float denom = b.real * b.real + b.imag * b.imag; + z.real = (a.real * b.real + a.imag * b.imag) / denom; + z.imag = (a.imag * b.real - a.real * b.imag) / denom; + return z; + } + static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_negf(__pyx_t_float_complex a) { + __pyx_t_float_complex z; + z.real = -a.real; + z.imag = -a.imag; + return z; + } + static CYTHON_INLINE int __Pyx_c_is_zerof(__pyx_t_float_complex a) { + return (a.real == 0) && (a.imag == 0); + } + static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_conjf(__pyx_t_float_complex a) { + __pyx_t_float_complex z; + z.real = a.real; + z.imag = -a.imag; + return z; + } + #if 1 + static CYTHON_INLINE float __Pyx_c_absf(__pyx_t_float_complex z) { + #if !defined(HAVE_HYPOT) || defined(_MSC_VER) + return sqrtf(z.real*z.real + z.imag*z.imag); + #else + return hypotf(z.real, z.imag); + #endif + } + static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_powf(__pyx_t_float_complex a, __pyx_t_float_complex b) { + __pyx_t_float_complex z; + float r, lnr, theta, z_r, z_theta; + if (b.imag == 0 && b.real == (int)b.real) { + if (b.real < 0) { + float denom = a.real * a.real + a.imag * a.imag; + a.real = a.real / denom; + a.imag = -a.imag / denom; + b.real = -b.real; + } + switch ((int)b.real) { + case 0: + z.real = 1; + z.imag = 0; + return z; + case 1: + return a; + case 2: + z = __Pyx_c_prodf(a, a); + return __Pyx_c_prodf(a, a); + case 3: + z = __Pyx_c_prodf(a, a); + return __Pyx_c_prodf(z, a); + case 4: + z = __Pyx_c_prodf(a, a); + return __Pyx_c_prodf(z, z); + } + } + if (a.imag == 0) { + if (a.real == 0) { + return a; + } + r = a.real; + theta = 0; + } else { + r = __Pyx_c_absf(a); + theta = atan2f(a.imag, a.real); + } + lnr = logf(r); + z_r = expf(lnr * b.real - theta * b.imag); + z_theta = theta * b.real + lnr * b.imag; + z.real = z_r * cosf(z_theta); + z.imag = z_r * sinf(z_theta); + return z; + } + #endif +#endif + +#if CYTHON_CCOMPLEX + #ifdef __cplusplus + static CYTHON_INLINE __pyx_t_double_complex __pyx_t_double_complex_from_parts(double x, double y) { + return ::std::complex< double >(x, y); + } + #else + static CYTHON_INLINE __pyx_t_double_complex __pyx_t_double_complex_from_parts(double x, double y) { + return x + y*(__pyx_t_double_complex)_Complex_I; + } + #endif +#else + static CYTHON_INLINE __pyx_t_double_complex __pyx_t_double_complex_from_parts(double x, double y) { + __pyx_t_double_complex z; + z.real = x; + z.imag = y; + return z; + } +#endif + +#if CYTHON_CCOMPLEX +#else + static CYTHON_INLINE int __Pyx_c_eq(__pyx_t_double_complex a, __pyx_t_double_complex b) { + return (a.real == b.real) && (a.imag == b.imag); + } + static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_sum(__pyx_t_double_complex a, __pyx_t_double_complex b) { + __pyx_t_double_complex z; + z.real = a.real + b.real; + z.imag = a.imag + b.imag; + return z; + } + static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_diff(__pyx_t_double_complex a, __pyx_t_double_complex b) { + __pyx_t_double_complex z; + z.real = a.real - b.real; + z.imag = a.imag - b.imag; + return z; + } + static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_prod(__pyx_t_double_complex a, __pyx_t_double_complex b) { + __pyx_t_double_complex z; + z.real = a.real * b.real - a.imag * b.imag; + z.imag = a.real * b.imag + a.imag * b.real; + return z; + } + static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_quot(__pyx_t_double_complex a, __pyx_t_double_complex b) { + __pyx_t_double_complex z; + double denom = b.real * b.real + b.imag * b.imag; + z.real = (a.real * b.real + a.imag * b.imag) / denom; + z.imag = (a.imag * b.real - a.real * b.imag) / denom; + return z; + } + static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_neg(__pyx_t_double_complex a) { + __pyx_t_double_complex z; + z.real = -a.real; + z.imag = -a.imag; + return z; + } + static CYTHON_INLINE int __Pyx_c_is_zero(__pyx_t_double_complex a) { + return (a.real == 0) && (a.imag == 0); + } + static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_conj(__pyx_t_double_complex a) { + __pyx_t_double_complex z; + z.real = a.real; + z.imag = -a.imag; + return z; + } + #if 1 + static CYTHON_INLINE double __Pyx_c_abs(__pyx_t_double_complex z) { + #if !defined(HAVE_HYPOT) || defined(_MSC_VER) + return sqrt(z.real*z.real + z.imag*z.imag); + #else + return hypot(z.real, z.imag); + #endif + } + static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_pow(__pyx_t_double_complex a, __pyx_t_double_complex b) { + __pyx_t_double_complex z; + double r, lnr, theta, z_r, z_theta; + if (b.imag == 0 && b.real == (int)b.real) { + if (b.real < 0) { + double denom = a.real * a.real + a.imag * a.imag; + a.real = a.real / denom; + a.imag = -a.imag / denom; + b.real = -b.real; + } + switch ((int)b.real) { + case 0: + z.real = 1; + z.imag = 0; + return z; + case 1: + return a; + case 2: + z = __Pyx_c_prod(a, a); + return __Pyx_c_prod(a, a); + case 3: + z = __Pyx_c_prod(a, a); + return __Pyx_c_prod(z, a); + case 4: + z = __Pyx_c_prod(a, a); + return __Pyx_c_prod(z, z); + } + } + if (a.imag == 0) { + if (a.real == 0) { + return a; + } + r = a.real; + theta = 0; + } else { + r = __Pyx_c_abs(a); + theta = atan2(a.imag, a.real); + } + lnr = log(r); + z_r = exp(lnr * b.real - theta * b.imag); + z_theta = theta * b.real + lnr * b.imag; + z.real = z_r * cos(z_theta); + z.imag = z_r * sin(z_theta); + return z; + } + #endif +#endif + +static CYTHON_INLINE unsigned char __Pyx_PyInt_AsUnsignedChar(PyObject* x) { + const unsigned char neg_one = (unsigned char)-1, const_zero = 0; + const int is_unsigned = neg_one > const_zero; + if (sizeof(unsigned char) < sizeof(long)) { + long val = __Pyx_PyInt_AsLong(x); + if (unlikely(val != (long)(unsigned char)val)) { + if (!unlikely(val == -1 && PyErr_Occurred())) { + PyErr_SetString(PyExc_OverflowError, + (is_unsigned && unlikely(val < 0)) ? + "can't convert negative value to unsigned char" : + "value too large to convert to unsigned char"); + } + return (unsigned char)-1; + } + return (unsigned char)val; + } + return (unsigned char)__Pyx_PyInt_AsUnsignedLong(x); +} + +static CYTHON_INLINE unsigned short __Pyx_PyInt_AsUnsignedShort(PyObject* x) { + const unsigned short neg_one = (unsigned short)-1, const_zero = 0; + const int is_unsigned = neg_one > const_zero; + if (sizeof(unsigned short) < sizeof(long)) { + long val = __Pyx_PyInt_AsLong(x); + if (unlikely(val != (long)(unsigned short)val)) { + if (!unlikely(val == -1 && PyErr_Occurred())) { + PyErr_SetString(PyExc_OverflowError, + (is_unsigned && unlikely(val < 0)) ? + "can't convert negative value to unsigned short" : + "value too large to convert to unsigned short"); + } + return (unsigned short)-1; + } + return (unsigned short)val; + } + return (unsigned short)__Pyx_PyInt_AsUnsignedLong(x); +} + +static CYTHON_INLINE unsigned int __Pyx_PyInt_AsUnsignedInt(PyObject* x) { + const unsigned int neg_one = (unsigned int)-1, const_zero = 0; + const int is_unsigned = neg_one > const_zero; + if (sizeof(unsigned int) < sizeof(long)) { + long val = __Pyx_PyInt_AsLong(x); + if (unlikely(val != (long)(unsigned int)val)) { + if (!unlikely(val == -1 && PyErr_Occurred())) { + PyErr_SetString(PyExc_OverflowError, + (is_unsigned && unlikely(val < 0)) ? + "can't convert negative value to unsigned int" : + "value too large to convert to unsigned int"); + } + return (unsigned int)-1; + } + return (unsigned int)val; + } + return (unsigned int)__Pyx_PyInt_AsUnsignedLong(x); +} + +static CYTHON_INLINE char __Pyx_PyInt_AsChar(PyObject* x) { + const char neg_one = (char)-1, const_zero = 0; + const int is_unsigned = neg_one > const_zero; + if (sizeof(char) < sizeof(long)) { + long val = __Pyx_PyInt_AsLong(x); + if (unlikely(val != (long)(char)val)) { + if (!unlikely(val == -1 && PyErr_Occurred())) { + PyErr_SetString(PyExc_OverflowError, + (is_unsigned && unlikely(val < 0)) ? + "can't convert negative value to char" : + "value too large to convert to char"); + } + return (char)-1; + } + return (char)val; + } + return (char)__Pyx_PyInt_AsLong(x); +} + +static CYTHON_INLINE short __Pyx_PyInt_AsShort(PyObject* x) { + const short neg_one = (short)-1, const_zero = 0; + const int is_unsigned = neg_one > const_zero; + if (sizeof(short) < sizeof(long)) { + long val = __Pyx_PyInt_AsLong(x); + if (unlikely(val != (long)(short)val)) { + if (!unlikely(val == -1 && PyErr_Occurred())) { + PyErr_SetString(PyExc_OverflowError, + (is_unsigned && unlikely(val < 0)) ? + "can't convert negative value to short" : + "value too large to convert to short"); + } + return (short)-1; + } + return (short)val; + } + return (short)__Pyx_PyInt_AsLong(x); +} + +static CYTHON_INLINE int __Pyx_PyInt_AsInt(PyObject* x) { + const int neg_one = (int)-1, const_zero = 0; + const int is_unsigned = neg_one > const_zero; + if (sizeof(int) < sizeof(long)) { + long val = __Pyx_PyInt_AsLong(x); + if (unlikely(val != (long)(int)val)) { + if (!unlikely(val == -1 && PyErr_Occurred())) { + PyErr_SetString(PyExc_OverflowError, + (is_unsigned && unlikely(val < 0)) ? + "can't convert negative value to int" : + "value too large to convert to int"); + } + return (int)-1; + } + return (int)val; + } + return (int)__Pyx_PyInt_AsLong(x); +} + +static CYTHON_INLINE signed char __Pyx_PyInt_AsSignedChar(PyObject* x) { + const signed char neg_one = (signed char)-1, const_zero = 0; + const int is_unsigned = neg_one > const_zero; + if (sizeof(signed char) < sizeof(long)) { + long val = __Pyx_PyInt_AsLong(x); + if (unlikely(val != (long)(signed char)val)) { + if (!unlikely(val == -1 && PyErr_Occurred())) { + PyErr_SetString(PyExc_OverflowError, + (is_unsigned && unlikely(val < 0)) ? + "can't convert negative value to signed char" : + "value too large to convert to signed char"); + } + return (signed char)-1; + } + return (signed char)val; + } + return (signed char)__Pyx_PyInt_AsSignedLong(x); +} + +static CYTHON_INLINE signed short __Pyx_PyInt_AsSignedShort(PyObject* x) { + const signed short neg_one = (signed short)-1, const_zero = 0; + const int is_unsigned = neg_one > const_zero; + if (sizeof(signed short) < sizeof(long)) { + long val = __Pyx_PyInt_AsLong(x); + if (unlikely(val != (long)(signed short)val)) { + if (!unlikely(val == -1 && PyErr_Occurred())) { + PyErr_SetString(PyExc_OverflowError, + (is_unsigned && unlikely(val < 0)) ? + "can't convert negative value to signed short" : + "value too large to convert to signed short"); + } + return (signed short)-1; + } + return (signed short)val; + } + return (signed short)__Pyx_PyInt_AsSignedLong(x); +} + +static CYTHON_INLINE signed int __Pyx_PyInt_AsSignedInt(PyObject* x) { + const signed int neg_one = (signed int)-1, const_zero = 0; + const int is_unsigned = neg_one > const_zero; + if (sizeof(signed int) < sizeof(long)) { + long val = __Pyx_PyInt_AsLong(x); + if (unlikely(val != (long)(signed int)val)) { + if (!unlikely(val == -1 && PyErr_Occurred())) { + PyErr_SetString(PyExc_OverflowError, + (is_unsigned && unlikely(val < 0)) ? + "can't convert negative value to signed int" : + "value too large to convert to signed int"); + } + return (signed int)-1; + } + return (signed int)val; + } + return (signed int)__Pyx_PyInt_AsSignedLong(x); +} + +static CYTHON_INLINE int __Pyx_PyInt_AsLongDouble(PyObject* x) { + const int neg_one = (int)-1, const_zero = 0; + const int is_unsigned = neg_one > const_zero; + if (sizeof(int) < sizeof(long)) { + long val = __Pyx_PyInt_AsLong(x); + if (unlikely(val != (long)(int)val)) { + if (!unlikely(val == -1 && PyErr_Occurred())) { + PyErr_SetString(PyExc_OverflowError, + (is_unsigned && unlikely(val < 0)) ? + "can't convert negative value to int" : + "value too large to convert to int"); + } + return (int)-1; + } + return (int)val; + } + return (int)__Pyx_PyInt_AsLong(x); +} + +static CYTHON_INLINE unsigned long __Pyx_PyInt_AsUnsignedLong(PyObject* x) { + const unsigned long neg_one = (unsigned long)-1, const_zero = 0; + const int is_unsigned = neg_one > const_zero; +#if PY_VERSION_HEX < 0x03000000 + if (likely(PyInt_Check(x))) { + long val = PyInt_AS_LONG(x); + if (is_unsigned && unlikely(val < 0)) { + PyErr_SetString(PyExc_OverflowError, + "can't convert negative value to unsigned long"); + return (unsigned long)-1; + } + return (unsigned long)val; + } else +#endif + if (likely(PyLong_Check(x))) { + if (is_unsigned) { + if (unlikely(Py_SIZE(x) < 0)) { + PyErr_SetString(PyExc_OverflowError, + "can't convert negative value to unsigned long"); + return (unsigned long)-1; + } + return (unsigned long)PyLong_AsUnsignedLong(x); + } else { + return (unsigned long)PyLong_AsLong(x); + } + } else { + unsigned long val; + PyObject *tmp = __Pyx_PyNumber_Int(x); + if (!tmp) return (unsigned long)-1; + val = __Pyx_PyInt_AsUnsignedLong(tmp); + Py_DECREF(tmp); + return val; + } +} + +static CYTHON_INLINE unsigned PY_LONG_LONG __Pyx_PyInt_AsUnsignedLongLong(PyObject* x) { + const unsigned PY_LONG_LONG neg_one = (unsigned PY_LONG_LONG)-1, const_zero = 0; + const int is_unsigned = neg_one > const_zero; +#if PY_VERSION_HEX < 0x03000000 + if (likely(PyInt_Check(x))) { + long val = PyInt_AS_LONG(x); + if (is_unsigned && unlikely(val < 0)) { + PyErr_SetString(PyExc_OverflowError, + "can't convert negative value to unsigned PY_LONG_LONG"); + return (unsigned PY_LONG_LONG)-1; + } + return (unsigned PY_LONG_LONG)val; + } else +#endif + if (likely(PyLong_Check(x))) { + if (is_unsigned) { + if (unlikely(Py_SIZE(x) < 0)) { + PyErr_SetString(PyExc_OverflowError, + "can't convert negative value to unsigned PY_LONG_LONG"); + return (unsigned PY_LONG_LONG)-1; + } + return (unsigned PY_LONG_LONG)PyLong_AsUnsignedLongLong(x); + } else { + return (unsigned PY_LONG_LONG)PyLong_AsLongLong(x); + } + } else { + unsigned PY_LONG_LONG val; + PyObject *tmp = __Pyx_PyNumber_Int(x); + if (!tmp) return (unsigned PY_LONG_LONG)-1; + val = __Pyx_PyInt_AsUnsignedLongLong(tmp); + Py_DECREF(tmp); + return val; + } +} + +static CYTHON_INLINE long __Pyx_PyInt_AsLong(PyObject* x) { + const long neg_one = (long)-1, const_zero = 0; + const int is_unsigned = neg_one > const_zero; +#if PY_VERSION_HEX < 0x03000000 + if (likely(PyInt_Check(x))) { + long val = PyInt_AS_LONG(x); + if (is_unsigned && unlikely(val < 0)) { + PyErr_SetString(PyExc_OverflowError, + "can't convert negative value to long"); + return (long)-1; + } + return (long)val; + } else +#endif + if (likely(PyLong_Check(x))) { + if (is_unsigned) { + if (unlikely(Py_SIZE(x) < 0)) { + PyErr_SetString(PyExc_OverflowError, + "can't convert negative value to long"); + return (long)-1; + } + return (long)PyLong_AsUnsignedLong(x); + } else { + return (long)PyLong_AsLong(x); + } + } else { + long val; + PyObject *tmp = __Pyx_PyNumber_Int(x); + if (!tmp) return (long)-1; + val = __Pyx_PyInt_AsLong(tmp); + Py_DECREF(tmp); + return val; + } +} + +static CYTHON_INLINE PY_LONG_LONG __Pyx_PyInt_AsLongLong(PyObject* x) { + const PY_LONG_LONG neg_one = (PY_LONG_LONG)-1, const_zero = 0; + const int is_unsigned = neg_one > const_zero; +#if PY_VERSION_HEX < 0x03000000 + if (likely(PyInt_Check(x))) { + long val = PyInt_AS_LONG(x); + if (is_unsigned && unlikely(val < 0)) { + PyErr_SetString(PyExc_OverflowError, + "can't convert negative value to PY_LONG_LONG"); + return (PY_LONG_LONG)-1; + } + return (PY_LONG_LONG)val; + } else +#endif + if (likely(PyLong_Check(x))) { + if (is_unsigned) { + if (unlikely(Py_SIZE(x) < 0)) { + PyErr_SetString(PyExc_OverflowError, + "can't convert negative value to PY_LONG_LONG"); + return (PY_LONG_LONG)-1; + } + return (PY_LONG_LONG)PyLong_AsUnsignedLongLong(x); + } else { + return (PY_LONG_LONG)PyLong_AsLongLong(x); + } + } else { + PY_LONG_LONG val; + PyObject *tmp = __Pyx_PyNumber_Int(x); + if (!tmp) return (PY_LONG_LONG)-1; + val = __Pyx_PyInt_AsLongLong(tmp); + Py_DECREF(tmp); + return val; + } +} + +static CYTHON_INLINE signed long __Pyx_PyInt_AsSignedLong(PyObject* x) { + const signed long neg_one = (signed long)-1, const_zero = 0; + const int is_unsigned = neg_one > const_zero; +#if PY_VERSION_HEX < 0x03000000 + if (likely(PyInt_Check(x))) { + long val = PyInt_AS_LONG(x); + if (is_unsigned && unlikely(val < 0)) { + PyErr_SetString(PyExc_OverflowError, + "can't convert negative value to signed long"); + return (signed long)-1; + } + return (signed long)val; + } else +#endif + if (likely(PyLong_Check(x))) { + if (is_unsigned) { + if (unlikely(Py_SIZE(x) < 0)) { + PyErr_SetString(PyExc_OverflowError, + "can't convert negative value to signed long"); + return (signed long)-1; + } + return (signed long)PyLong_AsUnsignedLong(x); + } else { + return (signed long)PyLong_AsLong(x); + } + } else { + signed long val; + PyObject *tmp = __Pyx_PyNumber_Int(x); + if (!tmp) return (signed long)-1; + val = __Pyx_PyInt_AsSignedLong(tmp); + Py_DECREF(tmp); + return val; + } +} + +static CYTHON_INLINE signed PY_LONG_LONG __Pyx_PyInt_AsSignedLongLong(PyObject* x) { + const signed PY_LONG_LONG neg_one = (signed PY_LONG_LONG)-1, const_zero = 0; + const int is_unsigned = neg_one > const_zero; +#if PY_VERSION_HEX < 0x03000000 + if (likely(PyInt_Check(x))) { + long val = PyInt_AS_LONG(x); + if (is_unsigned && unlikely(val < 0)) { + PyErr_SetString(PyExc_OverflowError, + "can't convert negative value to signed PY_LONG_LONG"); + return (signed PY_LONG_LONG)-1; + } + return (signed PY_LONG_LONG)val; + } else +#endif + if (likely(PyLong_Check(x))) { + if (is_unsigned) { + if (unlikely(Py_SIZE(x) < 0)) { + PyErr_SetString(PyExc_OverflowError, + "can't convert negative value to signed PY_LONG_LONG"); + return (signed PY_LONG_LONG)-1; + } + return (signed PY_LONG_LONG)PyLong_AsUnsignedLongLong(x); + } else { + return (signed PY_LONG_LONG)PyLong_AsLongLong(x); + } + } else { + signed PY_LONG_LONG val; + PyObject *tmp = __Pyx_PyNumber_Int(x); + if (!tmp) return (signed PY_LONG_LONG)-1; + val = __Pyx_PyInt_AsSignedLongLong(tmp); + Py_DECREF(tmp); + return val; + } +} + +static int __Pyx_check_binary_version(void) { + char ctversion[4], rtversion[4]; + PyOS_snprintf(ctversion, 4, "%d.%d", PY_MAJOR_VERSION, PY_MINOR_VERSION); + PyOS_snprintf(rtversion, 4, "%s", Py_GetVersion()); + if (ctversion[0] != rtversion[0] || ctversion[2] != rtversion[2]) { + char message[200]; + PyOS_snprintf(message, sizeof(message), + "compiletime version %s of module '%.100s' " + "does not match runtime version %s", + ctversion, __Pyx_MODULE_NAME, rtversion); + #if PY_VERSION_HEX < 0x02050000 + return PyErr_Warn(NULL, message); + #else + return PyErr_WarnEx(NULL, message, 1); + #endif + } + return 0; +} + +#ifndef __PYX_HAVE_RT_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_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, + "%s.%s is not a type object", + module_name, class_name); + goto bad; + } + if (!strict && (size_t)((PyTypeObject *)result)->tp_basicsize > size) { + PyOS_snprintf(warning, sizeof(warning), + "%s.%s size changed, may indicate binary incompatibility", + module_name, class_name); + #if PY_VERSION_HEX < 0x02050000 + if (PyErr_Warn(NULL, warning) < 0) goto bad; + #else + if (PyErr_WarnEx(NULL, warning, 0) < 0) goto bad; + #endif + } + else if ((size_t)((PyTypeObject *)result)->tp_basicsize != size) { + PyErr_Format(PyExc_ValueError, + "%s.%s has the wrong size, try recompiling", + module_name, class_name); + goto bad; + } + return (PyTypeObject *)result; +bad: + Py_XDECREF(py_module); + Py_XDECREF(result); + return NULL; +} +#endif + +#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 + +static int __pyx_bisect_code_objects(__Pyx_CodeObjectCacheEntry* entries, int count, int code_line) { + int start = 0, mid = 0, end = count - 1; + if (end >= 0 && code_line > entries[end].code_line) { + return count; + } + while (start < end) { + mid = (start + end) / 2; + if (code_line < entries[mid].code_line) { + end = mid; + } else if (code_line > entries[mid].code_line) { + start = mid + 1; + } else { + return mid; + } + } + if (code_line <= entries[mid].code_line) { + return mid; + } else { + return mid + 1; + } +} +static PyCodeObject *__pyx_find_code_object(int code_line) { + PyCodeObject* code_object; + int pos; + if (unlikely(!code_line) || unlikely(!__pyx_code_cache.entries)) { + return NULL; + } + pos = __pyx_bisect_code_objects(__pyx_code_cache.entries, __pyx_code_cache.count, code_line); + if (unlikely(pos >= __pyx_code_cache.count) || unlikely(__pyx_code_cache.entries[pos].code_line != code_line)) { + return NULL; + } + code_object = __pyx_code_cache.entries[pos].code_object; + Py_INCREF(code_object); + return code_object; +} +static void __pyx_insert_code_object(int code_line, PyCodeObject* code_object) { + int pos, i; + __Pyx_CodeObjectCacheEntry* entries = __pyx_code_cache.entries; + if (unlikely(!code_line)) { + return; + } + if (unlikely(!entries)) { + entries = (__Pyx_CodeObjectCacheEntry*)PyMem_Malloc(64*sizeof(__Pyx_CodeObjectCacheEntry)); + if (likely(entries)) { + __pyx_code_cache.entries = entries; + __pyx_code_cache.max_count = 64; + __pyx_code_cache.count = 1; + entries[0].code_line = code_line; + entries[0].code_object = code_object; + Py_INCREF(code_object); + } + return; + } + pos = __pyx_bisect_code_objects(__pyx_code_cache.entries, __pyx_code_cache.count, code_line); + if ((pos < __pyx_code_cache.count) && unlikely(__pyx_code_cache.entries[pos].code_line == code_line)) { + PyCodeObject* tmp = entries[pos].code_object; + entries[pos].code_object = code_object; + Py_DECREF(tmp); + return; + } + if (__pyx_code_cache.count == __pyx_code_cache.max_count) { + int new_max = __pyx_code_cache.max_count + 64; + entries = (__Pyx_CodeObjectCacheEntry*)PyMem_Realloc( + __pyx_code_cache.entries, new_max*sizeof(__Pyx_CodeObjectCacheEntry)); + if (unlikely(!entries)) { + return; + } + __pyx_code_cache.entries = entries; + __pyx_code_cache.max_count = new_max; + } + for (i=__pyx_code_cache.count; i>pos; i--) { + entries[i] = entries[i-1]; + } + entries[pos].code_line = code_line; + entries[pos].code_object = code_object; + __pyx_code_cache.count++; + Py_INCREF(code_object); +} + +#include "compile.h" +#include "frameobject.h" +#include "traceback.h" +static PyCodeObject* __Pyx_CreateCodeObjectForTraceback( + const char *funcname, int c_line, + int py_line, const char *filename) { + PyCodeObject *py_code = 0; + PyObject *py_srcfile = 0; + PyObject *py_funcname = 0; + #if PY_MAJOR_VERSION < 3 + py_srcfile = PyString_FromString(filename); + #else + py_srcfile = PyUnicode_FromString(filename); + #endif + if (!py_srcfile) goto bad; + if (c_line) { + #if PY_MAJOR_VERSION < 3 + py_funcname = PyString_FromFormat( "%s (%s:%d)", funcname, __pyx_cfilenm, c_line); + #else + py_funcname = PyUnicode_FromFormat( "%s (%s:%d)", funcname, __pyx_cfilenm, c_line); + #endif + } + else { + #if PY_MAJOR_VERSION < 3 + py_funcname = PyString_FromString(funcname); + #else + py_funcname = PyUnicode_FromString(funcname); + #endif + } + if (!py_funcname) goto bad; + py_code = __Pyx_PyCode_New( + 0, /*int argcount,*/ + 0, /*int kwonlyargcount,*/ + 0, /*int nlocals,*/ + 0, /*int stacksize,*/ + 0, /*int flags,*/ + __pyx_empty_bytes, /*PyObject *code,*/ + __pyx_empty_tuple, /*PyObject *consts,*/ + __pyx_empty_tuple, /*PyObject *names,*/ + __pyx_empty_tuple, /*PyObject *varnames,*/ + __pyx_empty_tuple, /*PyObject *freevars,*/ + __pyx_empty_tuple, /*PyObject *cellvars,*/ + py_srcfile, /*PyObject *filename,*/ + py_funcname, /*PyObject *name,*/ + py_line, /*int firstlineno,*/ + __pyx_empty_bytes /*PyObject *lnotab*/ + ); + Py_DECREF(py_srcfile); + Py_DECREF(py_funcname); + return py_code; +bad: + Py_XDECREF(py_srcfile); + Py_XDECREF(py_funcname); + return NULL; +} +static void __Pyx_AddTraceback(const char *funcname, int c_line, + int py_line, const char *filename) { + PyCodeObject *py_code = 0; + PyObject *py_globals = 0; + PyFrameObject *py_frame = 0; + py_code = __pyx_find_code_object(c_line ? c_line : py_line); + if (!py_code) { + py_code = __Pyx_CreateCodeObjectForTraceback( + funcname, c_line, py_line, filename); + if (!py_code) goto bad; + __pyx_insert_code_object(c_line ? c_line : py_line, py_code); + } + py_globals = PyModule_GetDict(__pyx_m); + if (!py_globals) goto bad; + py_frame = PyFrame_New( + PyThreadState_GET(), /*PyThreadState *tstate,*/ + py_code, /*PyCodeObject *code,*/ + py_globals, /*PyObject *globals,*/ + 0 /*PyObject *locals*/ + ); + if (!py_frame) goto bad; + py_frame->f_lineno = py_line; + PyTraceBack_Here(py_frame); +bad: + Py_XDECREF(py_code); + Py_XDECREF(py_frame); +} + +static int __Pyx_InitStrings(__Pyx_StringTabEntry *t) { + while (t->p) { + #if PY_MAJOR_VERSION < 3 + if (t->is_unicode) { + *t->p = PyUnicode_DecodeUTF8(t->s, t->n - 1, NULL); + } else if (t->intern) { + *t->p = PyString_InternFromString(t->s); + } else { + *t->p = PyString_FromStringAndSize(t->s, t->n - 1); + } + #else /* Python 3+ has unicode identifiers */ + if (t->is_unicode | t->is_str) { + if (t->intern) { + *t->p = PyUnicode_InternFromString(t->s); + } else if (t->encoding) { + *t->p = PyUnicode_Decode(t->s, t->n - 1, t->encoding, NULL); + } else { + *t->p = PyUnicode_FromStringAndSize(t->s, t->n - 1); + } + } else { + *t->p = PyBytes_FromStringAndSize(t->s, t->n - 1); + } + #endif + if (!*t->p) + return -1; + ++t; + } + return 0; +} + + +/* Type Conversion Functions */ + +static CYTHON_INLINE int __Pyx_PyObject_IsTrue(PyObject* x) { + int is_true = x == Py_True; + if (is_true | (x == Py_False) | (x == Py_None)) return is_true; + else return PyObject_IsTrue(x); +} + +static CYTHON_INLINE PyObject* __Pyx_PyNumber_Int(PyObject* x) { + PyNumberMethods *m; + const char *name = NULL; + PyObject *res = NULL; +#if PY_VERSION_HEX < 0x03000000 + if (PyInt_Check(x) || PyLong_Check(x)) +#else + if (PyLong_Check(x)) +#endif + return Py_INCREF(x), x; + m = Py_TYPE(x)->tp_as_number; +#if PY_VERSION_HEX < 0x03000000 + if (m && m->nb_int) { + name = "int"; + res = PyNumber_Int(x); + } + else if (m && m->nb_long) { + name = "long"; + res = PyNumber_Long(x); + } +#else + if (m && m->nb_int) { + name = "int"; + res = PyNumber_Long(x); + } +#endif + if (res) { +#if PY_VERSION_HEX < 0x03000000 + if (!PyInt_Check(res) && !PyLong_Check(res)) { +#else + if (!PyLong_Check(res)) { +#endif + PyErr_Format(PyExc_TypeError, + "__%s__ returned non-%s (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 = PyNumber_Index(b); + if (!x) return -1; + ival = PyInt_AsSsize_t(x); + Py_DECREF(x); + return ival; +} + +static CYTHON_INLINE PyObject * __Pyx_PyInt_FromSize_t(size_t ival) { +#if PY_VERSION_HEX < 0x02050000 + if (ival <= LONG_MAX) + return PyInt_FromLong((long)ival); + else { + unsigned char *bytes = (unsigned char *) &ival; + int one = 1; int little = (int)*(unsigned char*)&one; + return _PyLong_FromByteArray(bytes, sizeof(size_t), little, 0); + } +#else + return PyInt_FromSize_t(ival); +#endif +} + +static CYTHON_INLINE size_t __Pyx_PyInt_AsSize_t(PyObject* x) { + unsigned PY_LONG_LONG val = __Pyx_PyInt_AsUnsignedLongLong(x); + if (unlikely(val == (unsigned PY_LONG_LONG)-1 && PyErr_Occurred())) { + return (size_t)-1; + } else if (unlikely(val != (unsigned PY_LONG_LONG)(size_t)val)) { + PyErr_SetString(PyExc_OverflowError, + "value too large to convert to size_t"); + return (size_t)-1; + } + return (size_t)val; +} + + +#endif /* Py_PYTHON_H */ diff --git a/sklearn/metrics/_euclidean_fast.pyx b/sklearn/metrics/_euclidean_fast.pyx new file mode 100644 index 0000000000000..7bd0de2114e4c --- /dev/null +++ b/sklearn/metrics/_euclidean_fast.pyx @@ -0,0 +1,227 @@ +# Optimized euclidean distances computation between multiple points +# +# Author: Vlad Niculae +# License: Simple BSD. +# +#cython: boundscheck=True +#cython: wraparound=False +#cython: cdivision=True + +import numpy as np +cimport numpy as np + +cimport cython +ctypedef np.int32_t INTEGER +ctypedef np.float64_t DTYPE_t + +cdef extern from "math.h": + double sqrt "sqrt"(double x) + +cdef extern from "cblas.h": + void dgemm "cblas_dgemm"(char storage, char transa, char transb, int m, + int n, int k, double alpha, double *A, int lda, + double *B, int ldb, double beta, double *C, + int ldc) + void dsyrk "cblas_dsyrk"(char storage, char uplo, char trans, int n, int k, + double alpha, double *A, int lda, double beta, + double *C, int ldc) + + +cdef inline _euclidean_distances(int X_rows, + int Y_rows, + np.ndarray[DTYPE_t, ndim=1] X_norm_squared, + np.ndarray[DTYPE_t, ndim=1] Y_norm_squared, + np.ndarray[DTYPE_t, ndim=2] XYt, + bint squared=False, + bint sym=False): + cdef DTYPE_t tmp + for ii from 0 <= ii < X_rows: + for jj from 0 <= jj < Y_rows: + if ii == jj and sym: + XYt[ii, jj] = 0 + else: + tmp = XYt[jj, ii] if sym and ii < jj else XYt[ii, jj] + tmp = X_norm_squared[ii] + Y_norm_squared[jj] - 2 * tmp + XYt[ii, jj] = (tmp if squared else sqrt(tmp)) if tmp > 0 else 0 + + +cdef inline dense_sum_sq(int X_rows, int X_cols, + np.ndarray[DTYPE_t, ndim=2] X, + np.ndarray[DTYPE_t, ndim=1] out): + cdef unsigned int ii, jj + for ii from 0 <= ii < X_rows: + out[ii] = 0 + for jj from 0 <= jj < X_cols: + out[ii] += X[ii, jj] * X[ii, jj] + + +cdef inline sparse_sum_sq(int X_rows, np.ndarray[DTYPE_t, ndim=1] X_data, + np.ndarray[int, ndim=1] X_indices, + np.ndarray[int, ndim=1] X_indptr, + np.ndarray[DTYPE_t, ndim=1] out): + cdef unsigned int ii, jj + for ii from 0 <= ii < X_rows: + out[ii] = 0 + for jj from X_indptr[ii] <= jj < X_indptr[ii + 1]: + out[ii] += X_data[jj] * X_data[jj] + + +def dense_euclidean_distances(int X_rows, + int Y_rows, + int X_cols, + np.ndarray[DTYPE_t, ndim=2, mode="c"] X, + np.ndarray[DTYPE_t, ndim=2, mode="c"] Y, + np.ndarray[DTYPE_t, ndim=1] X_norm_preallocated, + np.ndarray[DTYPE_t, ndim=1] Y_norm_preallocated, + np.ndarray[DTYPE_t, ndim=1] X_norm_precomputed, + np.ndarray[DTYPE_t, ndim=1] Y_norm_precomputed, + np.ndarray[DTYPE_t, ndim=2, mode="c"] out, + bint squared=False): + if X_norm_preallocated is not None and X_norm_precomputed is not None: + raise ValueError + elif X_norm_precomputed is None: + if X_norm_preallocated is None: + X_norm_preallocated = np.empty(X_rows, dtype=np.float64) + dense_sum_sq(X_rows, X_cols, X, X_norm_preallocated) + else: + X_norm_preallocated = X_norm_precomputed + + if Y_norm_preallocated is not None and Y_norm_precomputed is not None: + raise ValueError + elif Y_norm_precomputed is None: + if Y_norm_preallocated is None: + Y_norm_preallocated = np.empty(Y_rows, dtype=np.float64) + dense_sum_sq(Y_rows, X_cols, Y, Y_norm_preallocated) + else: + Y_norm_preallocated = Y_norm_precomputed + + # 101 = c-order, 111 = no transpose, 112 = transpose (computes XY') + dgemm(101, 111, 112, X_rows, Y_rows, X_cols, 1.0, + X.data, X.strides[0] / sizeof(DTYPE_t), + Y.data, Y.strides[0] / sizeof(DTYPE_t), 0.0, + out.data, out.strides[0] / sizeof(DTYPE_t)) + + _euclidean_distances(X_rows, Y_rows, X_norm_preallocated, + Y_norm_preallocated, out, squared) + + +def dense_euclidean_distances_sym(int X_rows, + int X_cols, + np.ndarray[DTYPE_t, ndim=2, mode="c"] X, + np.ndarray[DTYPE_t, ndim=1] X_norm_preallocated, + np.ndarray[DTYPE_t, ndim=1] X_norm_precomputed, + np.ndarray[DTYPE_t, ndim=2, mode="c"] out, + bint squared=False): + + if X_norm_preallocated is not None and X_norm_precomputed is not None: + raise ValueError + elif X_norm_precomputed is None: + if X_norm_preallocated is None: + X_norm_preallocated = np.empty(X_rows, dtype=np.float64) + dense_sum_sq(X_rows, X_cols, X, X_norm_preallocated) + else: + X_norm_preallocated = X_norm_precomputed + + # 101 = c-order, 122 = lower triangular, 111 = no transpose (computes XX') + # Attention, the upper triangle contains garbage. + dsyrk(101, 122, 111, X_rows, X_cols, 1.0, X.data, + X.strides[0] / sizeof(DTYPE_t), 0.0, out.data, + out.strides[0] / sizeof(DTYPE_t)) + + _euclidean_distances(X_rows, X_rows, X_norm_preallocated, + X_norm_preallocated, out, squared, True) + + +# This function assumes the XYt parameter contains the precomputed outer dot +def sparse_euclidean_distances(int X_rows, + int Y_rows, + np.ndarray[DTYPE_t, ndim=1] X_data, + np.ndarray[int, ndim=1] X_indices, + np.ndarray[int, ndim=1] X_indptr, + np.ndarray[DTYPE_t, ndim=1] Y_data, + np.ndarray[int, ndim=1] Y_indices, + np.ndarray[int, ndim=1] Y_indptr, + np.ndarray[DTYPE_t, ndim=1] X_norm_preallocated, + np.ndarray[DTYPE_t, ndim=1] Y_norm_preallocated, + np.ndarray[DTYPE_t, ndim=1] X_norm_precomputed, + np.ndarray[DTYPE_t, ndim=1] Y_norm_precomputed, + np.ndarray[DTYPE_t, ndim=2] XYt, + bint squared=False): + if X_norm_preallocated is not None and X_norm_precomputed is not None: + raise ValueError + elif X_norm_precomputed is None: + if X_norm_preallocated is None: + X_norm_preallocated = np.empty(X_rows, dtype=np.float64) + sparse_sum_sq(X_rows, X_data, X_indices, X_indptr, X_norm_preallocated) + else: + X_norm_preallocated = X_norm_precomputed + + if Y_norm_preallocated is not None and Y_norm_precomputed is not None: + raise ValueError + elif Y_norm_precomputed is None: + if Y_norm_preallocated is None: + Y_norm_preallocated = np.empty(Y_rows, dtype=np.float64) + sparse_sum_sq(Y_rows, Y_data, Y_indices, Y_indptr, Y_norm_preallocated) + else: + Y_norm_preallocated = Y_norm_precomputed + + _euclidean_distances(X_rows, Y_rows, X_norm_preallocated, + Y_norm_preallocated, XYt, squared) + + +# This function assumes the XXt parameter contains the precomputed outer dot +def sparse_euclidean_distances_sym( + int X_rows, + np.ndarray[DTYPE_t, ndim=1] X_data, + np.ndarray[int, ndim=1] X_indices, + np.ndarray[int, ndim=1] X_indptr, + np.ndarray[DTYPE_t, ndim=1] X_norm_preallocated, + np.ndarray[DTYPE_t, ndim=1] X_norm_precomputed, + np.ndarray[DTYPE_t, ndim=2] XXt, + bint squared=False): + if X_norm_preallocated is not None and X_norm_precomputed is not None: + raise ValueError + elif X_norm_precomputed is None: + if X_norm_preallocated is None: + X_norm_preallocated = np.empty(X_rows, dtype=np.float64) + sparse_sum_sq(X_rows, X_data, X_indices, X_indptr, X_norm_preallocated) + else: + X_norm_preallocated = X_norm_precomputed + _euclidean_distances(X_rows, X_rows, X_norm_preallocated, + X_norm_preallocated, XXt, squared, True) + + +# This function assumes the XYt parameter contains the precomputed outer dot +def sparse_dense_euclidean_distances( + int X_rows, + int X_cols, + int Y_rows, + np.ndarray[DTYPE_t, ndim=1] X_data, + np.ndarray[int, ndim=1] X_indices, + np.ndarray[int, ndim=1] X_indptr, + np.ndarray[DTYPE_t, ndim=2, mode="c"] Y, + np.ndarray[DTYPE_t, ndim=1] X_norm_preallocated, + np.ndarray[DTYPE_t, ndim=1] Y_norm_preallocated, + np.ndarray[DTYPE_t, ndim=1] X_norm_precomputed, + np.ndarray[DTYPE_t, ndim=1] Y_norm_precomputed, + np.ndarray[DTYPE_t, ndim=2] XYt, + bint squared=False): + if X_norm_preallocated is not None and X_norm_precomputed is not None: + raise ValueError + elif X_norm_precomputed is None: + if X_norm_preallocated is None: + X_norm_preallocated = np.empty(X_rows, dtype=np.float64) + sparse_sum_sq(X_rows, X_data, X_indices, X_indptr, X_norm_preallocated) + else: + X_norm_preallocated = X_norm_precomputed + + if Y_norm_preallocated is not None and Y_norm_precomputed is not None: + raise ValueError + elif Y_norm_precomputed is None: + if Y_norm_preallocated is None: + Y_norm_preallocated = np.empty(Y_rows, dtype=np.float64) + dense_sum_sq(Y_rows, X_cols, Y, Y_norm_preallocated) + else: + Y_norm_preallocated = Y_norm_precomputed + _euclidean_distances(X_rows, Y_rows, X_norm_preallocated, + Y_norm_preallocated, XYt, squared) diff --git a/sklearn/metrics/pairwise.py b/sklearn/metrics/pairwise.py index 08c962c41b417..013d4879ba762 100644 --- a/sklearn/metrics/pairwise.py +++ b/sklearn/metrics/pairwise.py @@ -38,7 +38,11 @@ from scipy.spatial import distance from scipy.sparse import csr_matrix from scipy.sparse import issparse - +from ._euclidean_fast import dense_euclidean_distances +from ._euclidean_fast import dense_euclidean_distances_sym +from ._euclidean_fast import sparse_euclidean_distances +from ._euclidean_fast import sparse_euclidean_distances_sym +from ._euclidean_fast import sparse_dense_euclidean_distances from ..utils import safe_asarray from ..utils import atleast2d_or_csr from ..utils import gen_even_slices @@ -80,12 +84,12 @@ def check_pairwise_arrays(X, Y): """ if Y is X or Y is None: X = safe_asarray(X) - X = Y = atleast2d_or_csr(X, dtype=np.float) + X = Y = atleast2d_or_csr(X, dtype=np.float, order='c') else: X = safe_asarray(X) Y = safe_asarray(Y) - X = atleast2d_or_csr(X, dtype=np.float) - Y = atleast2d_or_csr(Y, dtype=np.float) + X = atleast2d_or_csr(X, dtype=np.float, order='c') + Y = atleast2d_or_csr(Y, dtype=np.float, order='c') if len(X.shape) < 2: raise ValueError("X is required to be at least two dimensional.") if len(Y.shape) < 2: @@ -98,7 +102,9 @@ def check_pairwise_arrays(X, Y): # Distances -def euclidean_distances(X, Y=None, Y_norm_squared=None, squared=False): +def euclidean_distances(X, Y=None, X_norm_preallocated=None, + Y_norm_preallocated=None, X_norm_precomputed=None, + Y_norm_precomputed=None, out=None, squared=False): """ Considering the rows of X (and Y=X) as vectors, compute the distance matrix between each pair of vectors. @@ -119,9 +125,26 @@ def euclidean_distances(X, Y=None, Y_norm_squared=None, squared=False): Y : {array-like, sparse matrix}, shape = [n_samples_2, n_features] - Y_norm_squared : array-like, shape = [n_samples_2], optional - Pre-computed dot-products of vectors in Y (e.g., - ``(Y**2).sum(axis=1)``) + X_norm_preallocated : array-like, shape = [n_samples_1], optional + Preallocated space for the dot-products of vectors in X. This is + mutually exclusive with `X_norm_precomputed`. + + Y_norm_preallocated : array-like, shape = [n_samples_2], optional + Preallocated space for the dot-products of vectors in Y. This is + mutually exclusive with `Y_norm_precomputed`. + + X_norm_precomputed : array-like, shape = [n_samples_1], optional. + Precomputed dot-products of vectors in X (e.g., + ``(X**2).sum(axis=1)``). This is mutually exclusive with + `X_norm_preallocated`. + + Y_norm_precomputed : array-like, shape = [n_samples_2], optional. + Precomputed dot-products of vectors in Y (e.g., + ``(Y**2).sum(axis=1)``). This is mutually exclusive with + `Y_norm_preallocated`. + + out : array, shape = [n_samples_1, n_samples_2], optional + Preallocated array that will store the output. squared : boolean, optional Return squared Euclidean distances. @@ -146,43 +169,51 @@ def euclidean_distances(X, Y=None, Y_norm_squared=None, squared=False): # should not need X_norm_squared because if you could precompute that as # well as Y, then you should just pre-compute the output and not even # call this function. + # @vene The only case where X_norm_squared is useful instead of + # Y_norm_squared is in the sparse-dense case, so I added it. X, Y = check_pairwise_arrays(X, Y) - if issparse(X): - XX = X.multiply(X).sum(axis=1) - else: - XX = np.sum(X * X, axis=1)[:, np.newaxis] - - if X is Y: # shortcut in the common case euclidean_distances(X, X) - YY = XX.T - elif Y_norm_squared is None: + X_rows, X_cols = X.shape + Y_rows = Y.shape[0] + + if out is None: + out = np.empty((X_rows, Y_rows), dtype=X.dtype) + if issparse(X) or issparse(Y): + if not issparse(X): + out = out.T + euclidean_distances( + Y, X, Y_norm_preallocated, X_norm_preallocated, + Y_norm_precomputed, X_norm_precomputed, out, squared) + out = out.T + return out + X = X.tocsr() if issparse(Y): - # scipy.sparse matrices don't have element-wise scalar - # exponentiation, and tocsr has a copy kwarg only on CSR matrices. - YY = Y.copy() if isinstance(Y, csr_matrix) else Y.tocsr() - YY.data **= 2 - YY = np.asarray(YY.sum(axis=1)).T + Y = Y.tocsr() + safe_sparse_dot(X, Y.T, out=out) + if X is Y: + sparse_euclidean_distances_sym( + X_rows, X.data, X.indices, X.indptr, X_norm_preallocated, + X_norm_precomputed, out, squared) + elif issparse(Y): + sparse_euclidean_distances( + X_rows, Y_rows, X.data, X.indices, X.indptr, Y.data, Y.indices, + Y.indptr, X_norm_preallocated, Y_norm_preallocated, + X_norm_precomputed, Y_norm_precomputed, out, squared) else: - YY = np.sum(Y ** 2, axis=1)[np.newaxis, :] + sparse_dense_euclidean_distances( + X_rows, X_cols, Y_rows, X.data, X.indices, X.indptr, Y, + X_norm_preallocated, Y_norm_preallocated, X_norm_precomputed, + Y_norm_precomputed, out, squared) else: - YY = atleast2d_or_csr(Y_norm_squared) - if YY.shape != (1, Y.shape[0]): - raise ValueError( - "Incompatible dimensions for Y and Y_norm_squared") - - # TODO: a faster Cython implementation would do the clipping of negative - # values in a single pass over the output matrix. - distances = safe_sparse_dot(X, Y.T, dense_output=True) - distances *= -2 - distances += XX - distances += YY - np.maximum(distances, 0, distances) - - if X is Y: - # Ensure that distances between vectors and themselves are set to 0.0. - # This may not be the case due to floating point rounding errors. - distances.flat[::distances.shape[0] + 1] = 0.0 - - return distances if squared else np.sqrt(distances) + if X is Y: + dense_euclidean_distances_sym( + X_rows, X_cols, X, X_norm_preallocated, X_norm_precomputed, + out, squared) + else: + dense_euclidean_distances( + X_rows, Y_rows, X_cols, X, Y, X_norm_preallocated, + Y_norm_preallocated, X_norm_precomputed, Y_norm_precomputed, + out, squared) + return out def manhattan_distances(X, Y=None, sum_over_features=True): diff --git a/sklearn/metrics/setup.py b/sklearn/metrics/setup.py new file mode 100644 index 0000000000000..ed4483c903c67 --- /dev/null +++ b/sklearn/metrics/setup.py @@ -0,0 +1,37 @@ +import os +from os.path import join + +import numpy + +from sklearn._build_utils import get_blas_info + + +def configuration(parent_package='', top_path=None): + from numpy.distutils.misc_util import Configuration + + config = Configuration('metrics', parent_package, top_path) + + # euclidean_fast needs CBLAS + cblas_libs, blas_info = get_blas_info() + + if os.name == 'posix': + cblas_libs.append('m') + + config.add_extension('_euclidean_fast', + sources=['_euclidean_fast.c'], + libraries=cblas_libs, + include_dirs=[join('..', 'src', 'cblas'), + numpy.get_include(), + blas_info.pop('include_dirs', [])], + extra_compile_args=blas_info.pop('extra_compile_args', []), + **blas_info + ) + + # add other directories + config.add_subpackage('tests') + + return config + +if __name__ == '__main__': + from numpy.distutils.core import setup + setup(**configuration(top_path='').todict()) diff --git a/sklearn/metrics/tests/test_pairwise.py b/sklearn/metrics/tests/test_pairwise.py index 43c0ee25e3d80..186ddf68775b6 100644 --- a/sklearn/metrics/tests/test_pairwise.py +++ b/sklearn/metrics/tests/test_pairwise.py @@ -157,6 +157,15 @@ def test_euclidean_distances(): assert_array_almost_equal(D, [[1., 2.]]) +def test_euclidean_distances_dense_sparse(): + X = csr_matrix([[0]]) + Y = np.array([[1], [2]], dtype=np.float) + D1 = euclidean_distances(X, Y) + D2 = euclidean_distances(Y, X) + assert_array_almost_equal(D1, [[1., 2.]]) + assert_array_almost_equal(D2, [[1.], [2.]]) + + def test_kernel_symmetry(): """ Valid kernels should be symmetric""" rng = np.random.RandomState(0) diff --git a/sklearn/utils/extmath.py b/sklearn/utils/extmath.py index 6ce09e502f3fd..207ea189b950f 100644 --- a/sklearn/utils/extmath.py +++ b/sklearn/utils/extmath.py @@ -6,10 +6,19 @@ import numpy as np from scipy import linalg +from scipy.sparse.sparsetools import coo_todense from . import check_random_state from .fixes import qr_economic +# coo_todense has changed signature in Mars: +coo_todense_extra_arg = False +try: + coo_todense(2, 2, 2, np.array([1, 2], np.int32), + np.array([1, 2], np.int32), np.ones(2), np.ones(4)) +except NotImplementedError: + coo_todense_extra_arg = True + def norm(v): v = np.asarray(v) @@ -66,16 +75,52 @@ def density(w, **kwargs): return d -def safe_sparse_dot(a, b, dense_output=False): - """Dot product that handle the sparse matrix case correctly""" +def safe_sparse_dot(a, b, dense_output=False, out=None): + """Dot product that handle the sparse matrix case correctly + + Computes the matrix multiplication a * b. + + Parameters + ---------- + a: array-like or sparse matrix, shape: [m, n] + Left factor in the matrix product. + + b: array-like or sparse matrix, shape: [n, p] + Right factor in the matrix product. + + dense_output: boolean, default: False + In case both a and b are sparse, their product can be compactly + stored as a sparse matrix itself, and this is the default behaviour. + If you want to override this, set `dense_output=True`. This doesn't + do anything if at least one of the factors is dense. + + out: array, shape: [m, p] or None + If not None, use the dense preallocated array as storage. If a and b + are both sparse, this forces `dense_output=True`. + """ from scipy import sparse if sparse.issparse(a) or sparse.issparse(b): ret = a * b - if dense_output and hasattr(ret, "toarray"): + if out is None and dense_output and hasattr(ret, "toarray"): ret = ret.toarray() - return ret else: - return np.dot(a, b) + ret = np.dot(a, b) + if out is not None: + if hasattr(ret, "tocoo"): + # Save time and space by using the preallocated output + ret = ret.tocoo() + out.fill(0.) + if coo_todense_extra_arg: + coo_todense(ret.shape[0], ret.shape[1], ret.nnz, ret.row, + ret.col, ret.data, out.ravel(), 0) + else: + coo_todense(ret.shape[0], ret.shape[1], ret.nnz, ret.row, + ret.col, ret.data, out.ravel()) + else: + out[:] = ret + return out + else: + return ret def randomized_range_finder(A, size, n_iterations, random_state=None): diff --git a/sklearn/utils/tests/test_utils.py b/sklearn/utils/tests/test_utils.py index 441f5d04dc500..47647fd57ed01 100644 --- a/sklearn/utils/tests/test_utils.py +++ b/sklearn/utils/tests/test_utils.py @@ -7,11 +7,14 @@ from nose.tools import assert_equal, assert_raises, assert_true from numpy.testing import assert_almost_equal +from numpy.testing import assert_array_equal + from sklearn.utils import check_random_state from sklearn.utils import deprecated from sklearn.utils import resample from sklearn.utils import safe_mask from sklearn.utils.extmath import pinvh +from sklearn.utils.extmath import safe_sparse_dot def test_make_rng(): @@ -117,3 +120,20 @@ def test_pinvh_simple_complex(): a = np.dot(a, a.conj().T) a_pinv = pinvh(a) assert_almost_equal(np.dot(a, a_pinv), np.eye(3)) + + +def test_safe_sparse_dot(): + from scipy.sparse import csr_matrix, coo_matrix, lil_matrix + from itertools import product + + X = np.array([[1., 2., 3.]]) + ref = np.dot(X.T, X) + formats = (np.array, csr_matrix, coo_matrix, lil_matrix) + for fmt_l, fmt_r in product(formats, formats): + assert_array_equal(safe_sparse_dot(fmt_l(X.T), fmt_r(X), + dense_output=True), ref) + # test the use of preallocated space + out = np.empty_like(ref) + safe_sparse_dot(fmt_l(X.T), fmt_r(X), out=out) + #print fmt_l, fmt_r + assert_array_equal(out, ref)