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spaCy/include/numpy/ndarraytypes.h

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#ifndef NDARRAYTYPES_H
#define NDARRAYTYPES_H
#include "npy_common.h"
#include "npy_endian.h"
#include "npy_cpu.h"
#include "utils.h"
#ifdef NPY_ENABLE_SEPARATE_COMPILATION
#define NPY_NO_EXPORT NPY_VISIBILITY_HIDDEN
#else
#define NPY_NO_EXPORT static
#endif
/* Only use thread if configured in config and python supports it */
#if defined WITH_THREAD && !NPY_NO_SMP
#define NPY_ALLOW_THREADS 1
#else
#define NPY_ALLOW_THREADS 0
#endif
/*
* There are several places in the code where an array of dimensions
* is allocated statically. This is the size of that static
* allocation.
*
* The array creation itself could have arbitrary dimensions but all
* the places where static allocation is used would need to be changed
* to dynamic (including inside of several structures)
*/
#define NPY_MAXDIMS 32
#define NPY_MAXARGS 32
/* Used for Converter Functions "O&" code in ParseTuple */
#define NPY_FAIL 0
#define NPY_SUCCEED 1
/*
* Binary compatibility version number. This number is increased
* whenever the C-API is changed such that binary compatibility is
* broken, i.e. whenever a recompile of extension modules is needed.
*/
#define NPY_VERSION NPY_ABI_VERSION
/*
* Minor API version. This number is increased whenever a change is
* made to the C-API -- whether it breaks binary compatibility or not.
* Some changes, such as adding a function pointer to the end of the
* function table, can be made without breaking binary compatibility.
* In this case, only the NPY_FEATURE_VERSION (*not* NPY_VERSION)
* would be increased. Whenever binary compatibility is broken, both
* NPY_VERSION and NPY_FEATURE_VERSION should be increased.
*/
#define NPY_FEATURE_VERSION NPY_API_VERSION
enum NPY_TYPES { NPY_BOOL=0,
NPY_BYTE, NPY_UBYTE,
NPY_SHORT, NPY_USHORT,
NPY_INT, NPY_UINT,
NPY_LONG, NPY_ULONG,
NPY_LONGLONG, NPY_ULONGLONG,
NPY_FLOAT, NPY_DOUBLE, NPY_LONGDOUBLE,
NPY_CFLOAT, NPY_CDOUBLE, NPY_CLONGDOUBLE,
NPY_OBJECT=17,
NPY_STRING, NPY_UNICODE,
NPY_VOID,
/*
* New 1.6 types appended, may be integrated
* into the above in 2.0.
*/
NPY_DATETIME, NPY_TIMEDELTA, NPY_HALF,
NPY_NTYPES,
NPY_NOTYPE,
NPY_CHAR, /* special flag */
NPY_USERDEF=256, /* leave room for characters */
/* The number of types not including the new 1.6 types */
NPY_NTYPES_ABI_COMPATIBLE=21
};
/* basetype array priority */
#define NPY_PRIORITY 0.0
/* default subtype priority */
#define NPY_SUBTYPE_PRIORITY 1.0
/* default scalar priority */
#define NPY_SCALAR_PRIORITY -1000000.0
/* How many floating point types are there (excluding half) */
#define NPY_NUM_FLOATTYPE 3
/*
* These characters correspond to the array type and the struct
* module
*/
enum NPY_TYPECHAR {
NPY_BOOLLTR = '?',
NPY_BYTELTR = 'b',
NPY_UBYTELTR = 'B',
NPY_SHORTLTR = 'h',
NPY_USHORTLTR = 'H',
NPY_INTLTR = 'i',
NPY_UINTLTR = 'I',
NPY_LONGLTR = 'l',
NPY_ULONGLTR = 'L',
NPY_LONGLONGLTR = 'q',
NPY_ULONGLONGLTR = 'Q',
NPY_HALFLTR = 'e',
NPY_FLOATLTR = 'f',
NPY_DOUBLELTR = 'd',
NPY_LONGDOUBLELTR = 'g',
NPY_CFLOATLTR = 'F',
NPY_CDOUBLELTR = 'D',
NPY_CLONGDOUBLELTR = 'G',
NPY_OBJECTLTR = 'O',
NPY_STRINGLTR = 'S',
NPY_STRINGLTR2 = 'a',
NPY_UNICODELTR = 'U',
NPY_VOIDLTR = 'V',
NPY_DATETIMELTR = 'M',
NPY_TIMEDELTALTR = 'm',
NPY_CHARLTR = 'c',
/*
* No Descriptor, just a define -- this let's
* Python users specify an array of integers
* large enough to hold a pointer on the
* platform
*/
NPY_INTPLTR = 'p',
NPY_UINTPLTR = 'P',
/*
* These are for dtype 'kinds', not dtype 'typecodes'
* as the above are for.
*/
NPY_GENBOOLLTR ='b',
NPY_SIGNEDLTR = 'i',
NPY_UNSIGNEDLTR = 'u',
NPY_FLOATINGLTR = 'f',
NPY_COMPLEXLTR = 'c'
};
typedef enum {
NPY_QUICKSORT=0,
NPY_HEAPSORT=1,
NPY_MERGESORT=2
} NPY_SORTKIND;
#define NPY_NSORTS (NPY_MERGESORT + 1)
typedef enum {
NPY_INTROSELECT=0
} NPY_SELECTKIND;
#define NPY_NSELECTS (NPY_INTROSELECT + 1)
typedef enum {
NPY_SEARCHLEFT=0,
NPY_SEARCHRIGHT=1
} NPY_SEARCHSIDE;
#define NPY_NSEARCHSIDES (NPY_SEARCHRIGHT + 1)
typedef enum {
NPY_NOSCALAR=-1,
NPY_BOOL_SCALAR,
NPY_INTPOS_SCALAR,
NPY_INTNEG_SCALAR,
NPY_FLOAT_SCALAR,
NPY_COMPLEX_SCALAR,
NPY_OBJECT_SCALAR
} NPY_SCALARKIND;
#define NPY_NSCALARKINDS (NPY_OBJECT_SCALAR + 1)
/* For specifying array memory layout or iteration order */
typedef enum {
/* Fortran order if inputs are all Fortran, C otherwise */
NPY_ANYORDER=-1,
/* C order */
NPY_CORDER=0,
/* Fortran order */
NPY_FORTRANORDER=1,
/* An order as close to the inputs as possible */
NPY_KEEPORDER=2
} NPY_ORDER;
/* For specifying allowed casting in operations which support it */
typedef enum {
/* Only allow identical types */
NPY_NO_CASTING=0,
/* Allow identical and byte swapped types */
NPY_EQUIV_CASTING=1,
/* Only allow safe casts */
NPY_SAFE_CASTING=2,
/* Allow safe casts or casts within the same kind */
NPY_SAME_KIND_CASTING=3,
/* Allow any casts */
NPY_UNSAFE_CASTING=4
} NPY_CASTING;
typedef enum {
NPY_CLIP=0,
NPY_WRAP=1,
NPY_RAISE=2
} NPY_CLIPMODE;
/* The special not-a-time (NaT) value */
#define NPY_DATETIME_NAT NPY_MIN_INT64
/*
* Upper bound on the length of a DATETIME ISO 8601 string
* YEAR: 21 (64-bit year)
* MONTH: 3
* DAY: 3
* HOURS: 3
* MINUTES: 3
* SECONDS: 3
* ATTOSECONDS: 1 + 3*6
* TIMEZONE: 5
* NULL TERMINATOR: 1
*/
#define NPY_DATETIME_MAX_ISO8601_STRLEN (21+3*5+1+3*6+6+1)
typedef enum {
NPY_FR_Y = 0, /* Years */
NPY_FR_M = 1, /* Months */
NPY_FR_W = 2, /* Weeks */
/* Gap where 1.6 NPY_FR_B (value 3) was */
NPY_FR_D = 4, /* Days */
NPY_FR_h = 5, /* hours */
NPY_FR_m = 6, /* minutes */
NPY_FR_s = 7, /* seconds */
NPY_FR_ms = 8, /* milliseconds */
NPY_FR_us = 9, /* microseconds */
NPY_FR_ns = 10,/* nanoseconds */
NPY_FR_ps = 11,/* picoseconds */
NPY_FR_fs = 12,/* femtoseconds */
NPY_FR_as = 13,/* attoseconds */
NPY_FR_GENERIC = 14 /* Generic, unbound units, can convert to anything */
} NPY_DATETIMEUNIT;
/*
* NOTE: With the NPY_FR_B gap for 1.6 ABI compatibility, NPY_DATETIME_NUMUNITS
* is technically one more than the actual number of units.
*/
#define NPY_DATETIME_NUMUNITS (NPY_FR_GENERIC + 1)
#define NPY_DATETIME_DEFAULTUNIT NPY_FR_GENERIC
/*
* Business day conventions for mapping invalid business
* days to valid business days.
*/
typedef enum {
/* Go forward in time to the following business day. */
NPY_BUSDAY_FORWARD,
NPY_BUSDAY_FOLLOWING = NPY_BUSDAY_FORWARD,
/* Go backward in time to the preceding business day. */
NPY_BUSDAY_BACKWARD,
NPY_BUSDAY_PRECEDING = NPY_BUSDAY_BACKWARD,
/*
* Go forward in time to the following business day, unless it
* crosses a month boundary, in which case go backward
*/
NPY_BUSDAY_MODIFIEDFOLLOWING,
/*
* Go backward in time to the preceding business day, unless it
* crosses a month boundary, in which case go forward.
*/
NPY_BUSDAY_MODIFIEDPRECEDING,
/* Produce a NaT for non-business days. */
NPY_BUSDAY_NAT,
/* Raise an exception for non-business days. */
NPY_BUSDAY_RAISE
} NPY_BUSDAY_ROLL;
/************************************************************
* NumPy Auxiliary Data for inner loops, sort functions, etc.
************************************************************/
/*
* When creating an auxiliary data struct, this should always appear
* as the first member, like this:
*
* typedef struct {
* NpyAuxData base;
* double constant;
* } constant_multiplier_aux_data;
*/
typedef struct NpyAuxData_tag NpyAuxData;
/* Function pointers for freeing or cloning auxiliary data */
typedef void (NpyAuxData_FreeFunc) (NpyAuxData *);
typedef NpyAuxData *(NpyAuxData_CloneFunc) (NpyAuxData *);
struct NpyAuxData_tag {
NpyAuxData_FreeFunc *free;
NpyAuxData_CloneFunc *clone;
/* To allow for a bit of expansion without breaking the ABI */
void *reserved[2];
};
/* Macros to use for freeing and cloning auxiliary data */
#define NPY_AUXDATA_FREE(auxdata) \
do { \
if ((auxdata) != NULL) { \
(auxdata)->free(auxdata); \
} \
} while(0)
#define NPY_AUXDATA_CLONE(auxdata) \
((auxdata)->clone(auxdata))
#define NPY_ERR(str) fprintf(stderr, #str); fflush(stderr);
#define NPY_ERR2(str) fprintf(stderr, str); fflush(stderr);
#define NPY_STRINGIFY(x) #x
#define NPY_TOSTRING(x) NPY_STRINGIFY(x)
/*
* Macros to define how array, and dimension/strides data is
* allocated.
*/
/* Data buffer - PyDataMem_NEW/FREE/RENEW are in multiarraymodule.c */
#define NPY_USE_PYMEM 1
#if NPY_USE_PYMEM == 1
#define PyArray_malloc PyMem_Malloc
#define PyArray_free PyMem_Free
#define PyArray_realloc PyMem_Realloc
#else
#define PyArray_malloc malloc
#define PyArray_free free
#define PyArray_realloc realloc
#endif
/* Dimensions and strides */
#define PyDimMem_NEW(size) \
((npy_intp *)PyArray_malloc(size*sizeof(npy_intp)))
#define PyDimMem_FREE(ptr) PyArray_free(ptr)
#define PyDimMem_RENEW(ptr,size) \
((npy_intp *)PyArray_realloc(ptr,size*sizeof(npy_intp)))
/* forward declaration */
struct _PyArray_Descr;
/* These must deal with unaligned and swapped data if necessary */
typedef PyObject * (PyArray_GetItemFunc) (void *, void *);
typedef int (PyArray_SetItemFunc)(PyObject *, void *, void *);
typedef void (PyArray_CopySwapNFunc)(void *, npy_intp, void *, npy_intp,
npy_intp, int, void *);
typedef void (PyArray_CopySwapFunc)(void *, void *, int, void *);
typedef npy_bool (PyArray_NonzeroFunc)(void *, void *);
/*
* These assume aligned and notswapped data -- a buffer will be used
* before or contiguous data will be obtained
*/
typedef int (PyArray_CompareFunc)(const void *, const void *, void *);
typedef int (PyArray_ArgFunc)(void*, npy_intp, npy_intp*, void *);
typedef void (PyArray_DotFunc)(void *, npy_intp, void *, npy_intp, void *,
npy_intp, void *);
typedef void (PyArray_VectorUnaryFunc)(void *, void *, npy_intp, void *,
void *);
/*
* XXX the ignore argument should be removed next time the API version
* is bumped. It used to be the separator.
*/
typedef int (PyArray_ScanFunc)(FILE *fp, void *dptr,
char *ignore, struct _PyArray_Descr *);
typedef int (PyArray_FromStrFunc)(char *s, void *dptr, char **endptr,
struct _PyArray_Descr *);
typedef int (PyArray_FillFunc)(void *, npy_intp, void *);
typedef int (PyArray_SortFunc)(void *, npy_intp, void *);
typedef int (PyArray_ArgSortFunc)(void *, npy_intp *, npy_intp, void *);
typedef int (PyArray_PartitionFunc)(void *, npy_intp, npy_intp,
npy_intp *, npy_intp *,
void *);
typedef int (PyArray_ArgPartitionFunc)(void *, npy_intp *, npy_intp, npy_intp,
npy_intp *, npy_intp *,
void *);
typedef int (PyArray_FillWithScalarFunc)(void *, npy_intp, void *, void *);
typedef int (PyArray_ScalarKindFunc)(void *);
typedef void (PyArray_FastClipFunc)(void *in, npy_intp n_in, void *min,
void *max, void *out);
typedef void (PyArray_FastPutmaskFunc)(void *in, void *mask, npy_intp n_in,
void *values, npy_intp nv);
typedef int (PyArray_FastTakeFunc)(void *dest, void *src, npy_intp *indarray,
npy_intp nindarray, npy_intp n_outer,
npy_intp m_middle, npy_intp nelem,
NPY_CLIPMODE clipmode);
typedef struct {
npy_intp *ptr;
int len;
} PyArray_Dims;
typedef struct {
/*
* Functions to cast to most other standard types
* Can have some NULL entries. The types
* DATETIME, TIMEDELTA, and HALF go into the castdict
* even though they are built-in.
*/
PyArray_VectorUnaryFunc *cast[NPY_NTYPES_ABI_COMPATIBLE];
/* The next four functions *cannot* be NULL */
/*
* Functions to get and set items with standard Python types
* -- not array scalars
*/
PyArray_GetItemFunc *getitem;
PyArray_SetItemFunc *setitem;
/*
* Copy and/or swap data. Memory areas may not overlap
* Use memmove first if they might
*/
PyArray_CopySwapNFunc *copyswapn;
PyArray_CopySwapFunc *copyswap;
/*
* Function to compare items
* Can be NULL
*/
PyArray_CompareFunc *compare;
/*
* Function to select largest
* Can be NULL
*/
PyArray_ArgFunc *argmax;
/*
* Function to compute dot product
* Can be NULL
*/
PyArray_DotFunc *dotfunc;
/*
* Function to scan an ASCII file and
* place a single value plus possible separator
* Can be NULL
*/
PyArray_ScanFunc *scanfunc;
/*
* Function to read a single value from a string
* and adjust the pointer; Can be NULL
*/
PyArray_FromStrFunc *fromstr;
/*
* Function to determine if data is zero or not
* If NULL a default version is
* used at Registration time.
*/
PyArray_NonzeroFunc *nonzero;
/*
* Used for arange.
* Can be NULL.
*/
PyArray_FillFunc *fill;
/*
* Function to fill arrays with scalar values
* Can be NULL
*/
PyArray_FillWithScalarFunc *fillwithscalar;
/*
* Sorting functions
* Can be NULL
*/
PyArray_SortFunc *sort[NPY_NSORTS];
PyArray_ArgSortFunc *argsort[NPY_NSORTS];
/*
* Dictionary of additional casting functions
* PyArray_VectorUnaryFuncs
* which can be populated to support casting
* to other registered types. Can be NULL
*/
PyObject *castdict;
/*
* Functions useful for generalizing
* the casting rules.
* Can be NULL;
*/
PyArray_ScalarKindFunc *scalarkind;
int **cancastscalarkindto;
int *cancastto;
PyArray_FastClipFunc *fastclip;
PyArray_FastPutmaskFunc *fastputmask;
PyArray_FastTakeFunc *fasttake;
/*
* Function to select smallest
* Can be NULL
*/
PyArray_ArgFunc *argmin;
} PyArray_ArrFuncs;
/* The item must be reference counted when it is inserted or extracted. */
#define NPY_ITEM_REFCOUNT 0x01
/* Same as needing REFCOUNT */
#define NPY_ITEM_HASOBJECT 0x01
/* Convert to list for pickling */
#define NPY_LIST_PICKLE 0x02
/* The item is a POINTER */
#define NPY_ITEM_IS_POINTER 0x04
/* memory needs to be initialized for this data-type */
#define NPY_NEEDS_INIT 0x08
/* operations need Python C-API so don't give-up thread. */
#define NPY_NEEDS_PYAPI 0x10
/* Use f.getitem when extracting elements of this data-type */
#define NPY_USE_GETITEM 0x20
/* Use f.setitem when setting creating 0-d array from this data-type.*/
#define NPY_USE_SETITEM 0x40
/* A sticky flag specifically for structured arrays */
#define NPY_ALIGNED_STRUCT 0x80
/*
*These are inherited for global data-type if any data-types in the
* field have them
*/
#define NPY_FROM_FIELDS (NPY_NEEDS_INIT | NPY_LIST_PICKLE | \
NPY_ITEM_REFCOUNT | NPY_NEEDS_PYAPI)
#define NPY_OBJECT_DTYPE_FLAGS (NPY_LIST_PICKLE | NPY_USE_GETITEM | \
NPY_ITEM_IS_POINTER | NPY_ITEM_REFCOUNT | \
NPY_NEEDS_INIT | NPY_NEEDS_PYAPI)
#define PyDataType_FLAGCHK(dtype, flag) \
(((dtype)->flags & (flag)) == (flag))
#define PyDataType_REFCHK(dtype) \
PyDataType_FLAGCHK(dtype, NPY_ITEM_REFCOUNT)
typedef struct _PyArray_Descr {
PyObject_HEAD
/*
* the type object representing an
* instance of this type -- should not
* be two type_numbers with the same type
* object.
*/
PyTypeObject *typeobj;
/* kind for this type */
char kind;
/* unique-character representing this type */
char type;
/*
* '>' (big), '<' (little), '|'
* (not-applicable), or '=' (native).
*/
char byteorder;
/* flags describing data type */
char flags;
/* number representing this type */
int type_num;
/* element size (itemsize) for this type */
int elsize;
/* alignment needed for this type */
int alignment;
/*
* Non-NULL if this type is
* is an array (C-contiguous)
* of some other type
*/
struct _arr_descr *subarray;
/*
* The fields dictionary for this type
* For statically defined descr this
* is always Py_None
*/
PyObject *fields;
/*
* An ordered tuple of field names or NULL
* if no fields are defined
*/
PyObject *names;
/*
* a table of functions specific for each
* basic data descriptor
*/
PyArray_ArrFuncs *f;
/* Metadata about this dtype */
PyObject *metadata;
/*
* Metadata specific to the C implementation
* of the particular dtype. This was added
* for NumPy 1.7.0.
*/
NpyAuxData *c_metadata;
/* Cached hash value (-1 if not yet computed).
* This was added for NumPy 2.0.0.
*/
npy_hash_t hash;
} PyArray_Descr;
typedef struct _arr_descr {
PyArray_Descr *base;
PyObject *shape; /* a tuple */
} PyArray_ArrayDescr;
/*
* The main array object structure.
*
* It has been recommended to use the inline functions defined below
* (PyArray_DATA and friends) to access fields here for a number of
* releases. Direct access to the members themselves is deprecated.
* To ensure that your code does not use deprecated access,
* #define NPY_NO_DEPRECATED_API NPY_1_7_API_VERSION
* (or NPY_1_8_API_VERSION or higher as required).
*/
/* This struct will be moved to a private header in a future release */
typedef struct tagPyArrayObject_fields {
PyObject_HEAD
/* Pointer to the raw data buffer */
char *data;
/* The number of dimensions, also called 'ndim' */
int nd;
/* The size in each dimension, also called 'shape' */
npy_intp *dimensions;
/*
* Number of bytes to jump to get to the
* next element in each dimension
*/
npy_intp *strides;
/*
* This object is decref'd upon
* deletion of array. Except in the
* case of UPDATEIFCOPY which has
* special handling.
*
* For views it points to the original
* array, collapsed so no chains of
* views occur.
*
* For creation from buffer object it
* points to an object that shold be
* decref'd on deletion
*
* For UPDATEIFCOPY flag this is an
* array to-be-updated upon deletion
* of this one
*/
PyObject *base;
/* Pointer to type structure */
PyArray_Descr *descr;
/* Flags describing array -- see below */
int flags;
/* For weak references */
PyObject *weakreflist;
} PyArrayObject_fields;
/*
* To hide the implementation details, we only expose
* the Python struct HEAD.
*/
#if !defined(NPY_NO_DEPRECATED_API) || \
(NPY_NO_DEPRECATED_API < NPY_1_7_API_VERSION)
/*
* Can't put this in npy_deprecated_api.h like the others.
* PyArrayObject field access is deprecated as of NumPy 1.7.
*/
typedef PyArrayObject_fields PyArrayObject;
#else
typedef struct tagPyArrayObject {
PyObject_HEAD
} PyArrayObject;
#endif
#define NPY_SIZEOF_PYARRAYOBJECT (sizeof(PyArrayObject_fields))
/* Array Flags Object */
typedef struct PyArrayFlagsObject {
PyObject_HEAD
PyObject *arr;
int flags;
} PyArrayFlagsObject;
/* Mirrors buffer object to ptr */
typedef struct {
PyObject_HEAD
PyObject *base;
void *ptr;
npy_intp len;
int flags;
} PyArray_Chunk;
typedef struct {
NPY_DATETIMEUNIT base;
int num;
} PyArray_DatetimeMetaData;
typedef struct {
NpyAuxData base;
PyArray_DatetimeMetaData meta;
} PyArray_DatetimeDTypeMetaData;
/*
* This structure contains an exploded view of a date-time value.
* NaT is represented by year == NPY_DATETIME_NAT.
*/
typedef struct {
npy_int64 year;
npy_int32 month, day, hour, min, sec, us, ps, as;
} npy_datetimestruct;
/* This is not used internally. */
typedef struct {
npy_int64 day;
npy_int32 sec, us, ps, as;
} npy_timedeltastruct;
typedef int (PyArray_FinalizeFunc)(PyArrayObject *, PyObject *);
/*
* Means c-style contiguous (last index varies the fastest). The data
* elements right after each other.
*
* This flag may be requested in constructor functions.
* This flag may be tested for in PyArray_FLAGS(arr).
*/
#define NPY_ARRAY_C_CONTIGUOUS 0x0001
/*
* Set if array is a contiguous Fortran array: the first index varies
* the fastest in memory (strides array is reverse of C-contiguous
* array)
*
* This flag may be requested in constructor functions.
* This flag may be tested for in PyArray_FLAGS(arr).
*/
#define NPY_ARRAY_F_CONTIGUOUS 0x0002
/*
* Note: all 0-d arrays are C_CONTIGUOUS and F_CONTIGUOUS. If a
* 1-d array is C_CONTIGUOUS it is also F_CONTIGUOUS. Arrays with
* more then one dimension can be C_CONTIGUOUS and F_CONTIGUOUS
* at the same time if they have either zero or one element.
* If NPY_RELAXED_STRIDES_CHECKING is set, a higher dimensional
* array is always C_CONTIGUOUS and F_CONTIGUOUS if it has zero elements
* and the array is contiguous if ndarray.squeeze() is contiguous.
* I.e. dimensions for which `ndarray.shape[dimension] == 1` are
* ignored.
*/
/*
* If set, the array owns the data: it will be free'd when the array
* is deleted.
*
* This flag may be tested for in PyArray_FLAGS(arr).
*/
#define NPY_ARRAY_OWNDATA 0x0004
/*
* An array never has the next four set; they're only used as parameter
* flags to the the various FromAny functions
*
* This flag may be requested in constructor functions.
*/
/* Cause a cast to occur regardless of whether or not it is safe. */
#define NPY_ARRAY_FORCECAST 0x0010
/*
* Always copy the array. Returned arrays are always CONTIGUOUS,
* ALIGNED, and WRITEABLE.
*
* This flag may be requested in constructor functions.
*/
#define NPY_ARRAY_ENSURECOPY 0x0020
/*
* Make sure the returned array is a base-class ndarray
*
* This flag may be requested in constructor functions.
*/
#define NPY_ARRAY_ENSUREARRAY 0x0040
/*
* Make sure that the strides are in units of the element size Needed
* for some operations with record-arrays.
*
* This flag may be requested in constructor functions.
*/
#define NPY_ARRAY_ELEMENTSTRIDES 0x0080
/*
* Array data is aligned on the appropiate memory address for the type
* stored according to how the compiler would align things (e.g., an
* array of integers (4 bytes each) starts on a memory address that's
* a multiple of 4)
*
* This flag may be requested in constructor functions.
* This flag may be tested for in PyArray_FLAGS(arr).
*/
#define NPY_ARRAY_ALIGNED 0x0100
/*
* Array data has the native endianness
*
* This flag may be requested in constructor functions.
*/
#define NPY_ARRAY_NOTSWAPPED 0x0200
/*
* Array data is writeable
*
* This flag may be requested in constructor functions.
* This flag may be tested for in PyArray_FLAGS(arr).
*/
#define NPY_ARRAY_WRITEABLE 0x0400
/*
* If this flag is set, then base contains a pointer to an array of
* the same size that should be updated with the current contents of
* this array when this array is deallocated
*
* This flag may be requested in constructor functions.
* This flag may be tested for in PyArray_FLAGS(arr).
*/
#define NPY_ARRAY_UPDATEIFCOPY 0x1000
/*
* NOTE: there are also internal flags defined in multiarray/arrayobject.h,
* which start at bit 31 and work down.
*/
#define NPY_ARRAY_BEHAVED (NPY_ARRAY_ALIGNED | \
NPY_ARRAY_WRITEABLE)
#define NPY_ARRAY_BEHAVED_NS (NPY_ARRAY_ALIGNED | \
NPY_ARRAY_WRITEABLE | \
NPY_ARRAY_NOTSWAPPED)
#define NPY_ARRAY_CARRAY (NPY_ARRAY_C_CONTIGUOUS | \
NPY_ARRAY_BEHAVED)
#define NPY_ARRAY_CARRAY_RO (NPY_ARRAY_C_CONTIGUOUS | \
NPY_ARRAY_ALIGNED)
#define NPY_ARRAY_FARRAY (NPY_ARRAY_F_CONTIGUOUS | \
NPY_ARRAY_BEHAVED)
#define NPY_ARRAY_FARRAY_RO (NPY_ARRAY_F_CONTIGUOUS | \
NPY_ARRAY_ALIGNED)
#define NPY_ARRAY_DEFAULT (NPY_ARRAY_CARRAY)
#define NPY_ARRAY_IN_ARRAY (NPY_ARRAY_CARRAY_RO)
#define NPY_ARRAY_OUT_ARRAY (NPY_ARRAY_CARRAY)
#define NPY_ARRAY_INOUT_ARRAY (NPY_ARRAY_CARRAY | \
NPY_ARRAY_UPDATEIFCOPY)
#define NPY_ARRAY_IN_FARRAY (NPY_ARRAY_FARRAY_RO)
#define NPY_ARRAY_OUT_FARRAY (NPY_ARRAY_FARRAY)
#define NPY_ARRAY_INOUT_FARRAY (NPY_ARRAY_FARRAY | \
NPY_ARRAY_UPDATEIFCOPY)
#define NPY_ARRAY_UPDATE_ALL (NPY_ARRAY_C_CONTIGUOUS | \
NPY_ARRAY_F_CONTIGUOUS | \
NPY_ARRAY_ALIGNED)
/* This flag is for the array interface, not PyArrayObject */
#define NPY_ARR_HAS_DESCR 0x0800
/*
* Size of internal buffers used for alignment Make BUFSIZE a multiple
* of sizeof(npy_cdouble) -- usually 16 so that ufunc buffers are aligned
*/
#define NPY_MIN_BUFSIZE ((int)sizeof(npy_cdouble))
#define NPY_MAX_BUFSIZE (((int)sizeof(npy_cdouble))*1000000)
#define NPY_BUFSIZE 8192
/* buffer stress test size: */
/*#define NPY_BUFSIZE 17*/
#define PyArray_MAX(a,b) (((a)>(b))?(a):(b))
#define PyArray_MIN(a,b) (((a)<(b))?(a):(b))
#define PyArray_CLT(p,q) ((((p).real==(q).real) ? ((p).imag < (q).imag) : \
((p).real < (q).real)))
#define PyArray_CGT(p,q) ((((p).real==(q).real) ? ((p).imag > (q).imag) : \
((p).real > (q).real)))
#define PyArray_CLE(p,q) ((((p).real==(q).real) ? ((p).imag <= (q).imag) : \
((p).real <= (q).real)))
#define PyArray_CGE(p,q) ((((p).real==(q).real) ? ((p).imag >= (q).imag) : \
((p).real >= (q).real)))
#define PyArray_CEQ(p,q) (((p).real==(q).real) && ((p).imag == (q).imag))
#define PyArray_CNE(p,q) (((p).real!=(q).real) || ((p).imag != (q).imag))
/*
* C API: consists of Macros and functions. The MACROS are defined
* here.
*/
#define PyArray_ISCONTIGUOUS(m) PyArray_CHKFLAGS(m, NPY_ARRAY_C_CONTIGUOUS)
#define PyArray_ISWRITEABLE(m) PyArray_CHKFLAGS(m, NPY_ARRAY_WRITEABLE)
#define PyArray_ISALIGNED(m) PyArray_CHKFLAGS(m, NPY_ARRAY_ALIGNED)
#define PyArray_IS_C_CONTIGUOUS(m) PyArray_CHKFLAGS(m, NPY_ARRAY_C_CONTIGUOUS)
#define PyArray_IS_F_CONTIGUOUS(m) PyArray_CHKFLAGS(m, NPY_ARRAY_F_CONTIGUOUS)
/* the variable is used in some places, so always define it */
#define NPY_BEGIN_THREADS_DEF PyThreadState *_save=NULL;
#if NPY_ALLOW_THREADS
#define NPY_BEGIN_ALLOW_THREADS Py_BEGIN_ALLOW_THREADS
#define NPY_END_ALLOW_THREADS Py_END_ALLOW_THREADS
#define NPY_BEGIN_THREADS do {_save = PyEval_SaveThread();} while (0);
#define NPY_END_THREADS do { if (_save) \
{ PyEval_RestoreThread(_save); _save = NULL;} } while (0);
#define NPY_BEGIN_THREADS_THRESHOLDED(loop_size) do { if (loop_size > 500) \
{ _save = PyEval_SaveThread();} } while (0);
#define NPY_BEGIN_THREADS_DESCR(dtype) \
do {if (!(PyDataType_FLAGCHK(dtype, NPY_NEEDS_PYAPI))) \
NPY_BEGIN_THREADS;} while (0);
#define NPY_END_THREADS_DESCR(dtype) \
do {if (!(PyDataType_FLAGCHK(dtype, NPY_NEEDS_PYAPI))) \
NPY_END_THREADS; } while (0);
#define NPY_ALLOW_C_API_DEF PyGILState_STATE __save__;
#define NPY_ALLOW_C_API do {__save__ = PyGILState_Ensure();} while (0);
#define NPY_DISABLE_C_API do {PyGILState_Release(__save__);} while (0);
#else
#define NPY_BEGIN_ALLOW_THREADS
#define NPY_END_ALLOW_THREADS
#define NPY_BEGIN_THREADS
#define NPY_END_THREADS
#define NPY_BEGIN_THREADS_THRESHOLDED(loop_size)
#define NPY_BEGIN_THREADS_DESCR(dtype)
#define NPY_END_THREADS_DESCR(dtype)
#define NPY_ALLOW_C_API_DEF
#define NPY_ALLOW_C_API
#define NPY_DISABLE_C_API
#endif
/**********************************
* The nditer object, added in 1.6
**********************************/
/* The actual structure of the iterator is an internal detail */
typedef struct NpyIter_InternalOnly NpyIter;
/* Iterator function pointers that may be specialized */
typedef int (NpyIter_IterNextFunc)(NpyIter *iter);
typedef void (NpyIter_GetMultiIndexFunc)(NpyIter *iter,
npy_intp *outcoords);
/*** Global flags that may be passed to the iterator constructors ***/
/* Track an index representing C order */
#define NPY_ITER_C_INDEX 0x00000001
/* Track an index representing Fortran order */
#define NPY_ITER_F_INDEX 0x00000002
/* Track a multi-index */
#define NPY_ITER_MULTI_INDEX 0x00000004
/* User code external to the iterator does the 1-dimensional innermost loop */
#define NPY_ITER_EXTERNAL_LOOP 0x00000008
/* Convert all the operands to a common data type */
#define NPY_ITER_COMMON_DTYPE 0x00000010
/* Operands may hold references, requiring API access during iteration */
#define NPY_ITER_REFS_OK 0x00000020
/* Zero-sized operands should be permitted, iteration checks IterSize for 0 */
#define NPY_ITER_ZEROSIZE_OK 0x00000040
/* Permits reductions (size-0 stride with dimension size > 1) */
#define NPY_ITER_REDUCE_OK 0x00000080
/* Enables sub-range iteration */
#define NPY_ITER_RANGED 0x00000100
/* Enables buffering */
#define NPY_ITER_BUFFERED 0x00000200
/* When buffering is enabled, grows the inner loop if possible */
#define NPY_ITER_GROWINNER 0x00000400
/* Delay allocation of buffers until first Reset* call */
#define NPY_ITER_DELAY_BUFALLOC 0x00000800
/* When NPY_KEEPORDER is specified, disable reversing negative-stride axes */
#define NPY_ITER_DONT_NEGATE_STRIDES 0x00001000
/*** Per-operand flags that may be passed to the iterator constructors ***/
/* The operand will be read from and written to */
#define NPY_ITER_READWRITE 0x00010000
/* The operand will only be read from */
#define NPY_ITER_READONLY 0x00020000
/* The operand will only be written to */
#define NPY_ITER_WRITEONLY 0x00040000
/* The operand's data must be in native byte order */
#define NPY_ITER_NBO 0x00080000
/* The operand's data must be aligned */
#define NPY_ITER_ALIGNED 0x00100000
/* The operand's data must be contiguous (within the inner loop) */
#define NPY_ITER_CONTIG 0x00200000
/* The operand may be copied to satisfy requirements */
#define NPY_ITER_COPY 0x00400000
/* The operand may be copied with UPDATEIFCOPY to satisfy requirements */
#define NPY_ITER_UPDATEIFCOPY 0x00800000
/* Allocate the operand if it is NULL */
#define NPY_ITER_ALLOCATE 0x01000000
/* If an operand is allocated, don't use any subtype */
#define NPY_ITER_NO_SUBTYPE 0x02000000
/* This is a virtual array slot, operand is NULL but temporary data is there */
#define NPY_ITER_VIRTUAL 0x04000000
/* Require that the dimension match the iterator dimensions exactly */
#define NPY_ITER_NO_BROADCAST 0x08000000
/* A mask is being used on this array, affects buffer -> array copy */
#define NPY_ITER_WRITEMASKED 0x10000000
/* This array is the mask for all WRITEMASKED operands */
#define NPY_ITER_ARRAYMASK 0x20000000
#define NPY_ITER_GLOBAL_FLAGS 0x0000ffff
#define NPY_ITER_PER_OP_FLAGS 0xffff0000
/*****************************
* Basic iterator object
*****************************/
/* FWD declaration */
typedef struct PyArrayIterObject_tag PyArrayIterObject;
/*
* type of the function which translates a set of coordinates to a
* pointer to the data
*/
typedef char* (*npy_iter_get_dataptr_t)(PyArrayIterObject* iter, npy_intp*);
struct PyArrayIterObject_tag {
PyObject_HEAD
int nd_m1; /* number of dimensions - 1 */
npy_intp index, size;
npy_intp coordinates[NPY_MAXDIMS];/* N-dimensional loop */
npy_intp dims_m1[NPY_MAXDIMS]; /* ao->dimensions - 1 */
npy_intp strides[NPY_MAXDIMS]; /* ao->strides or fake */
npy_intp backstrides[NPY_MAXDIMS];/* how far to jump back */
npy_intp factors[NPY_MAXDIMS]; /* shape factors */
PyArrayObject *ao;
char *dataptr; /* pointer to current item*/
npy_bool contiguous;
npy_intp bounds[NPY_MAXDIMS][2];
npy_intp limits[NPY_MAXDIMS][2];
npy_intp limits_sizes[NPY_MAXDIMS];
npy_iter_get_dataptr_t translate;
} ;
/* Iterator API */
#define PyArrayIter_Check(op) PyObject_TypeCheck(op, &PyArrayIter_Type)
#define _PyAIT(it) ((PyArrayIterObject *)(it))
#define PyArray_ITER_RESET(it) do { \
_PyAIT(it)->index = 0; \
_PyAIT(it)->dataptr = PyArray_BYTES(_PyAIT(it)->ao); \
memset(_PyAIT(it)->coordinates, 0, \
(_PyAIT(it)->nd_m1+1)*sizeof(npy_intp)); \
} while (0)
#define _PyArray_ITER_NEXT1(it) do { \
(it)->dataptr += _PyAIT(it)->strides[0]; \
(it)->coordinates[0]++; \
} while (0)
#define _PyArray_ITER_NEXT2(it) do { \
if ((it)->coordinates[1] < (it)->dims_m1[1]) { \
(it)->coordinates[1]++; \
(it)->dataptr += (it)->strides[1]; \
} \
else { \
(it)->coordinates[1] = 0; \
(it)->coordinates[0]++; \
(it)->dataptr += (it)->strides[0] - \
(it)->backstrides[1]; \
} \
} while (0)
#define PyArray_ITER_NEXT(it) do { \
_PyAIT(it)->index++; \
if (_PyAIT(it)->nd_m1 == 0) { \
_PyArray_ITER_NEXT1(_PyAIT(it)); \
} \
else if (_PyAIT(it)->contiguous) \
_PyAIT(it)->dataptr += PyArray_DESCR(_PyAIT(it)->ao)->elsize; \
else if (_PyAIT(it)->nd_m1 == 1) { \
_PyArray_ITER_NEXT2(_PyAIT(it)); \
} \
else { \
int __npy_i; \
for (__npy_i=_PyAIT(it)->nd_m1; __npy_i >= 0; __npy_i--) { \
if (_PyAIT(it)->coordinates[__npy_i] < \
_PyAIT(it)->dims_m1[__npy_i]) { \
_PyAIT(it)->coordinates[__npy_i]++; \
_PyAIT(it)->dataptr += \
_PyAIT(it)->strides[__npy_i]; \
break; \
} \
else { \
_PyAIT(it)->coordinates[__npy_i] = 0; \
_PyAIT(it)->dataptr -= \
_PyAIT(it)->backstrides[__npy_i]; \
} \
} \
} \
} while (0)
#define PyArray_ITER_GOTO(it, destination) do { \
int __npy_i; \
_PyAIT(it)->index = 0; \
_PyAIT(it)->dataptr = PyArray_BYTES(_PyAIT(it)->ao); \
for (__npy_i = _PyAIT(it)->nd_m1; __npy_i>=0; __npy_i--) { \
if (destination[__npy_i] < 0) { \
destination[__npy_i] += \
_PyAIT(it)->dims_m1[__npy_i]+1; \
} \
_PyAIT(it)->dataptr += destination[__npy_i] * \
_PyAIT(it)->strides[__npy_i]; \
_PyAIT(it)->coordinates[__npy_i] = \
destination[__npy_i]; \
_PyAIT(it)->index += destination[__npy_i] * \
( __npy_i==_PyAIT(it)->nd_m1 ? 1 : \
_PyAIT(it)->dims_m1[__npy_i+1]+1) ; \
} \
} while (0)
#define PyArray_ITER_GOTO1D(it, ind) do { \
int __npy_i; \
npy_intp __npy_ind = (npy_intp) (ind); \
if (__npy_ind < 0) __npy_ind += _PyAIT(it)->size; \
_PyAIT(it)->index = __npy_ind; \
if (_PyAIT(it)->nd_m1 == 0) { \
_PyAIT(it)->dataptr = PyArray_BYTES(_PyAIT(it)->ao) + \
__npy_ind * _PyAIT(it)->strides[0]; \
} \
else if (_PyAIT(it)->contiguous) \
_PyAIT(it)->dataptr = PyArray_BYTES(_PyAIT(it)->ao) + \
__npy_ind * PyArray_DESCR(_PyAIT(it)->ao)->elsize; \
else { \
_PyAIT(it)->dataptr = PyArray_BYTES(_PyAIT(it)->ao); \
for (__npy_i = 0; __npy_i<=_PyAIT(it)->nd_m1; \
__npy_i++) { \
_PyAIT(it)->dataptr += \
(__npy_ind / _PyAIT(it)->factors[__npy_i]) \
* _PyAIT(it)->strides[__npy_i]; \
__npy_ind %= _PyAIT(it)->factors[__npy_i]; \
} \
} \
} while (0)
#define PyArray_ITER_DATA(it) ((void *)(_PyAIT(it)->dataptr))
#define PyArray_ITER_NOTDONE(it) (_PyAIT(it)->index < _PyAIT(it)->size)
/*
* Any object passed to PyArray_Broadcast must be binary compatible
* with this structure.
*/
typedef struct {
PyObject_HEAD
int numiter; /* number of iters */
npy_intp size; /* broadcasted size */
npy_intp index; /* current index */
int nd; /* number of dims */
npy_intp dimensions[NPY_MAXDIMS]; /* dimensions */
PyArrayIterObject *iters[NPY_MAXARGS]; /* iterators */
} PyArrayMultiIterObject;
#define _PyMIT(m) ((PyArrayMultiIterObject *)(m))
#define PyArray_MultiIter_RESET(multi) do { \
int __npy_mi; \
_PyMIT(multi)->index = 0; \
for (__npy_mi=0; __npy_mi < _PyMIT(multi)->numiter; __npy_mi++) { \
PyArray_ITER_RESET(_PyMIT(multi)->iters[__npy_mi]); \
} \
} while (0)
#define PyArray_MultiIter_NEXT(multi) do { \
int __npy_mi; \
_PyMIT(multi)->index++; \
for (__npy_mi=0; __npy_mi < _PyMIT(multi)->numiter; __npy_mi++) { \
PyArray_ITER_NEXT(_PyMIT(multi)->iters[__npy_mi]); \
} \
} while (0)
#define PyArray_MultiIter_GOTO(multi, dest) do { \
int __npy_mi; \
for (__npy_mi=0; __npy_mi < _PyMIT(multi)->numiter; __npy_mi++) { \
PyArray_ITER_GOTO(_PyMIT(multi)->iters[__npy_mi], dest); \
} \
_PyMIT(multi)->index = _PyMIT(multi)->iters[0]->index; \
} while (0)
#define PyArray_MultiIter_GOTO1D(multi, ind) do { \
int __npy_mi; \
for (__npy_mi=0; __npy_mi < _PyMIT(multi)->numiter; __npy_mi++) { \
PyArray_ITER_GOTO1D(_PyMIT(multi)->iters[__npy_mi], ind); \
} \
_PyMIT(multi)->index = _PyMIT(multi)->iters[0]->index; \
} while (0)
#define PyArray_MultiIter_DATA(multi, i) \
((void *)(_PyMIT(multi)->iters[i]->dataptr))
#define PyArray_MultiIter_NEXTi(multi, i) \
PyArray_ITER_NEXT(_PyMIT(multi)->iters[i])
#define PyArray_MultiIter_NOTDONE(multi) \
(_PyMIT(multi)->index < _PyMIT(multi)->size)
/*
* Store the information needed for fancy-indexing over an array. The
* fields are slightly unordered to keep consec, dataptr and subspace
* where they were originally.
*/
typedef struct {
PyObject_HEAD
/*
* Multi-iterator portion --- needs to be present in this
* order to work with PyArray_Broadcast
*/
int numiter; /* number of index-array
iterators */
npy_intp size; /* size of broadcasted
result */
npy_intp index; /* current index */
int nd; /* number of dims */
npy_intp dimensions[NPY_MAXDIMS]; /* dimensions */
NpyIter *outer; /* index objects
iterator */
void *unused[NPY_MAXDIMS - 2];
PyArrayObject *array;
/* Flat iterator for the indexed array. For compatibility solely. */
PyArrayIterObject *ait;
/*
* Subspace array. For binary compatibility (was an iterator,
* but only the check for NULL should be used).
*/
PyArrayObject *subspace;
/*
* if subspace iteration, then this is the array of axes in
* the underlying array represented by the index objects
*/
int iteraxes[NPY_MAXDIMS];
npy_intp fancy_strides[NPY_MAXDIMS];
/* pointer when all fancy indices are 0 */
char *baseoffset;
/*
* after binding consec denotes at which axis the fancy axes
* are inserted.
*/
int consec;
char *dataptr;
int nd_fancy;
npy_intp fancy_dims[NPY_MAXDIMS];
/* Whether the iterator (any of the iterators) requires API */
int needs_api;
/*
* Extra op information.
*/
PyArrayObject *extra_op;
PyArray_Descr *extra_op_dtype; /* desired dtype */
npy_uint32 *extra_op_flags; /* Iterator flags */
NpyIter *extra_op_iter;
NpyIter_IterNextFunc *extra_op_next;
char **extra_op_ptrs;
/*
* Information about the iteration state.
*/
NpyIter_IterNextFunc *outer_next;
char **outer_ptrs;
npy_intp *outer_strides;
/*
* Information about the subspace iterator.
*/
NpyIter *subspace_iter;
NpyIter_IterNextFunc *subspace_next;
char **subspace_ptrs;
npy_intp *subspace_strides;
/* Count for the external loop (which ever it is) for API iteration */
npy_intp iter_count;
} PyArrayMapIterObject;
enum {
NPY_NEIGHBORHOOD_ITER_ZERO_PADDING,
NPY_NEIGHBORHOOD_ITER_ONE_PADDING,
NPY_NEIGHBORHOOD_ITER_CONSTANT_PADDING,
NPY_NEIGHBORHOOD_ITER_CIRCULAR_PADDING,
NPY_NEIGHBORHOOD_ITER_MIRROR_PADDING
};
typedef struct {
PyObject_HEAD
/*
* PyArrayIterObject part: keep this in this exact order
*/
int nd_m1; /* number of dimensions - 1 */
npy_intp index, size;
npy_intp coordinates[NPY_MAXDIMS];/* N-dimensional loop */
npy_intp dims_m1[NPY_MAXDIMS]; /* ao->dimensions - 1 */
npy_intp strides[NPY_MAXDIMS]; /* ao->strides or fake */
npy_intp backstrides[NPY_MAXDIMS];/* how far to jump back */
npy_intp factors[NPY_MAXDIMS]; /* shape factors */
PyArrayObject *ao;
char *dataptr; /* pointer to current item*/
npy_bool contiguous;
npy_intp bounds[NPY_MAXDIMS][2];
npy_intp limits[NPY_MAXDIMS][2];
npy_intp limits_sizes[NPY_MAXDIMS];
npy_iter_get_dataptr_t translate;
/*
* New members
*/
npy_intp nd;
/* Dimensions is the dimension of the array */
npy_intp dimensions[NPY_MAXDIMS];
/*
* Neighborhood points coordinates are computed relatively to the
* point pointed by _internal_iter
*/
PyArrayIterObject* _internal_iter;
/*
* To keep a reference to the representation of the constant value
* for constant padding
*/
char* constant;
int mode;
} PyArrayNeighborhoodIterObject;
/*
* Neighborhood iterator API
*/
/* General: those work for any mode */
static NPY_INLINE int
PyArrayNeighborhoodIter_Reset(PyArrayNeighborhoodIterObject* iter);
static NPY_INLINE int
PyArrayNeighborhoodIter_Next(PyArrayNeighborhoodIterObject* iter);
#if 0
static NPY_INLINE int
PyArrayNeighborhoodIter_Next2D(PyArrayNeighborhoodIterObject* iter);
#endif
/*
* Include inline implementations - functions defined there are not
* considered public API
*/
#define _NPY_INCLUDE_NEIGHBORHOOD_IMP
#include "_neighborhood_iterator_imp.h"
#undef _NPY_INCLUDE_NEIGHBORHOOD_IMP
/* The default array type */
#define NPY_DEFAULT_TYPE NPY_DOUBLE
/*
* All sorts of useful ways to look into a PyArrayObject. It is recommended
* to use PyArrayObject * objects instead of always casting from PyObject *,
* for improved type checking.
*
* In many cases here the macro versions of the accessors are deprecated,
* but can't be immediately changed to inline functions because the
* preexisting macros accept PyObject * and do automatic casts. Inline
* functions accepting PyArrayObject * provides for some compile-time
* checking of correctness when working with these objects in C.
*/
#define PyArray_ISONESEGMENT(m) (PyArray_NDIM(m) == 0 || \
PyArray_CHKFLAGS(m, NPY_ARRAY_C_CONTIGUOUS) || \
PyArray_CHKFLAGS(m, NPY_ARRAY_F_CONTIGUOUS))
#define PyArray_ISFORTRAN(m) (PyArray_CHKFLAGS(m, NPY_ARRAY_F_CONTIGUOUS) && \
(!PyArray_CHKFLAGS(m, NPY_ARRAY_C_CONTIGUOUS)))
#define PyArray_FORTRAN_IF(m) ((PyArray_CHKFLAGS(m, NPY_ARRAY_F_CONTIGUOUS) ? \
NPY_ARRAY_F_CONTIGUOUS : 0))
#if (defined(NPY_NO_DEPRECATED_API) && (NPY_1_7_API_VERSION <= NPY_NO_DEPRECATED_API))
/*
* Changing access macros into functions, to allow for future hiding
* of the internal memory layout. This later hiding will allow the 2.x series
* to change the internal representation of arrays without affecting
* ABI compatibility.
*/
static NPY_INLINE int
PyArray_NDIM(const PyArrayObject *arr)
{
return ((PyArrayObject_fields *)arr)->nd;
}
static NPY_INLINE void *
PyArray_DATA(PyArrayObject *arr)
{
return ((PyArrayObject_fields *)arr)->data;
}
static NPY_INLINE char *
PyArray_BYTES(PyArrayObject *arr)
{
return ((PyArrayObject_fields *)arr)->data;
}
static NPY_INLINE npy_intp *
PyArray_DIMS(PyArrayObject *arr)
{
return ((PyArrayObject_fields *)arr)->dimensions;
}
static NPY_INLINE npy_intp *
PyArray_STRIDES(PyArrayObject *arr)
{
return ((PyArrayObject_fields *)arr)->strides;
}
static NPY_INLINE npy_intp
PyArray_DIM(const PyArrayObject *arr, int idim)
{
return ((PyArrayObject_fields *)arr)->dimensions[idim];
}
static NPY_INLINE npy_intp
PyArray_STRIDE(const PyArrayObject *arr, int istride)
{
return ((PyArrayObject_fields *)arr)->strides[istride];
}
static NPY_INLINE NPY_RETURNS_BORROWED_REF PyObject *
PyArray_BASE(PyArrayObject *arr)
{
return ((PyArrayObject_fields *)arr)->base;
}
static NPY_INLINE NPY_RETURNS_BORROWED_REF PyArray_Descr *
PyArray_DESCR(PyArrayObject *arr)
{
return ((PyArrayObject_fields *)arr)->descr;
}
static NPY_INLINE int
PyArray_FLAGS(const PyArrayObject *arr)
{
return ((PyArrayObject_fields *)arr)->flags;
}
static NPY_INLINE npy_intp
PyArray_ITEMSIZE(const PyArrayObject *arr)
{
return ((PyArrayObject_fields *)arr)->descr->elsize;
}
static NPY_INLINE int
PyArray_TYPE(const PyArrayObject *arr)
{
return ((PyArrayObject_fields *)arr)->descr->type_num;
}
static NPY_INLINE int
PyArray_CHKFLAGS(const PyArrayObject *arr, int flags)
{
return (PyArray_FLAGS(arr) & flags) == flags;
}
static NPY_INLINE PyObject *
PyArray_GETITEM(const PyArrayObject *arr, const char *itemptr)
{
return ((PyArrayObject_fields *)arr)->descr->f->getitem(
(void *)itemptr, (PyArrayObject *)arr);
}
static NPY_INLINE int
PyArray_SETITEM(PyArrayObject *arr, char *itemptr, PyObject *v)
{
return ((PyArrayObject_fields *)arr)->descr->f->setitem(
v, itemptr, arr);
}
#else
/* These macros are deprecated as of NumPy 1.7. */
#define PyArray_NDIM(obj) (((PyArrayObject_fields *)(obj))->nd)
#define PyArray_BYTES(obj) (((PyArrayObject_fields *)(obj))->data)
#define PyArray_DATA(obj) ((void *)((PyArrayObject_fields *)(obj))->data)
#define PyArray_DIMS(obj) (((PyArrayObject_fields *)(obj))->dimensions)
#define PyArray_STRIDES(obj) (((PyArrayObject_fields *)(obj))->strides)
#define PyArray_DIM(obj,n) (PyArray_DIMS(obj)[n])
#define PyArray_STRIDE(obj,n) (PyArray_STRIDES(obj)[n])
#define PyArray_BASE(obj) (((PyArrayObject_fields *)(obj))->base)
#define PyArray_DESCR(obj) (((PyArrayObject_fields *)(obj))->descr)
#define PyArray_FLAGS(obj) (((PyArrayObject_fields *)(obj))->flags)
#define PyArray_CHKFLAGS(m, FLAGS) \
((((PyArrayObject_fields *)(m))->flags & (FLAGS)) == (FLAGS))
#define PyArray_ITEMSIZE(obj) \
(((PyArrayObject_fields *)(obj))->descr->elsize)
#define PyArray_TYPE(obj) \
(((PyArrayObject_fields *)(obj))->descr->type_num)
#define PyArray_GETITEM(obj,itemptr) \
PyArray_DESCR(obj)->f->getitem((char *)(itemptr), \
(PyArrayObject *)(obj))
#define PyArray_SETITEM(obj,itemptr,v) \
PyArray_DESCR(obj)->f->setitem((PyObject *)(v), \
(char *)(itemptr), \
(PyArrayObject *)(obj))
#endif
static NPY_INLINE PyArray_Descr *
PyArray_DTYPE(PyArrayObject *arr)
{
return ((PyArrayObject_fields *)arr)->descr;
}
static NPY_INLINE npy_intp *
PyArray_SHAPE(PyArrayObject *arr)
{
return ((PyArrayObject_fields *)arr)->dimensions;
}
/*
* Enables the specified array flags. Does no checking,
* assumes you know what you're doing.
*/
static NPY_INLINE void
PyArray_ENABLEFLAGS(PyArrayObject *arr, int flags)
{
((PyArrayObject_fields *)arr)->flags |= flags;
}
/*
* Clears the specified array flags. Does no checking,
* assumes you know what you're doing.
*/
static NPY_INLINE void
PyArray_CLEARFLAGS(PyArrayObject *arr, int flags)
{
((PyArrayObject_fields *)arr)->flags &= ~flags;
}
#define PyTypeNum_ISBOOL(type) ((type) == NPY_BOOL)
#define PyTypeNum_ISUNSIGNED(type) (((type) == NPY_UBYTE) || \
((type) == NPY_USHORT) || \
((type) == NPY_UINT) || \
((type) == NPY_ULONG) || \
((type) == NPY_ULONGLONG))
#define PyTypeNum_ISSIGNED(type) (((type) == NPY_BYTE) || \
((type) == NPY_SHORT) || \
((type) == NPY_INT) || \
((type) == NPY_LONG) || \
((type) == NPY_LONGLONG))
#define PyTypeNum_ISINTEGER(type) (((type) >= NPY_BYTE) && \
((type) <= NPY_ULONGLONG))
#define PyTypeNum_ISFLOAT(type) ((((type) >= NPY_FLOAT) && \
((type) <= NPY_LONGDOUBLE)) || \
((type) == NPY_HALF))
#define PyTypeNum_ISNUMBER(type) (((type) <= NPY_CLONGDOUBLE) || \
((type) == NPY_HALF))
#define PyTypeNum_ISSTRING(type) (((type) == NPY_STRING) || \
((type) == NPY_UNICODE))
#define PyTypeNum_ISCOMPLEX(type) (((type) >= NPY_CFLOAT) && \
((type) <= NPY_CLONGDOUBLE))
#define PyTypeNum_ISPYTHON(type) (((type) == NPY_LONG) || \
((type) == NPY_DOUBLE) || \
((type) == NPY_CDOUBLE) || \
((type) == NPY_BOOL) || \
((type) == NPY_OBJECT ))
#define PyTypeNum_ISFLEXIBLE(type) (((type) >=NPY_STRING) && \
((type) <=NPY_VOID))
#define PyTypeNum_ISDATETIME(type) (((type) >=NPY_DATETIME) && \
((type) <=NPY_TIMEDELTA))
#define PyTypeNum_ISUSERDEF(type) (((type) >= NPY_USERDEF) && \
((type) < NPY_USERDEF+ \
NPY_NUMUSERTYPES))
#define PyTypeNum_ISEXTENDED(type) (PyTypeNum_ISFLEXIBLE(type) || \
PyTypeNum_ISUSERDEF(type))
#define PyTypeNum_ISOBJECT(type) ((type) == NPY_OBJECT)
#define PyDataType_ISBOOL(obj) PyTypeNum_ISBOOL(_PyADt(obj))
#define PyDataType_ISUNSIGNED(obj) PyTypeNum_ISUNSIGNED(((PyArray_Descr*)(obj))->type_num)
#define PyDataType_ISSIGNED(obj) PyTypeNum_ISSIGNED(((PyArray_Descr*)(obj))->type_num)
#define PyDataType_ISINTEGER(obj) PyTypeNum_ISINTEGER(((PyArray_Descr*)(obj))->type_num )
#define PyDataType_ISFLOAT(obj) PyTypeNum_ISFLOAT(((PyArray_Descr*)(obj))->type_num)
#define PyDataType_ISNUMBER(obj) PyTypeNum_ISNUMBER(((PyArray_Descr*)(obj))->type_num)
#define PyDataType_ISSTRING(obj) PyTypeNum_ISSTRING(((PyArray_Descr*)(obj))->type_num)
#define PyDataType_ISCOMPLEX(obj) PyTypeNum_ISCOMPLEX(((PyArray_Descr*)(obj))->type_num)
#define PyDataType_ISPYTHON(obj) PyTypeNum_ISPYTHON(((PyArray_Descr*)(obj))->type_num)
#define PyDataType_ISFLEXIBLE(obj) PyTypeNum_ISFLEXIBLE(((PyArray_Descr*)(obj))->type_num)
#define PyDataType_ISDATETIME(obj) PyTypeNum_ISDATETIME(((PyArray_Descr*)(obj))->type_num)
#define PyDataType_ISUSERDEF(obj) PyTypeNum_ISUSERDEF(((PyArray_Descr*)(obj))->type_num)
#define PyDataType_ISEXTENDED(obj) PyTypeNum_ISEXTENDED(((PyArray_Descr*)(obj))->type_num)
#define PyDataType_ISOBJECT(obj) PyTypeNum_ISOBJECT(((PyArray_Descr*)(obj))->type_num)
#define PyDataType_HASFIELDS(obj) (((PyArray_Descr *)(obj))->names != NULL)
#define PyDataType_HASSUBARRAY(dtype) ((dtype)->subarray != NULL)
#define PyArray_ISBOOL(obj) PyTypeNum_ISBOOL(PyArray_TYPE(obj))
#define PyArray_ISUNSIGNED(obj) PyTypeNum_ISUNSIGNED(PyArray_TYPE(obj))
#define PyArray_ISSIGNED(obj) PyTypeNum_ISSIGNED(PyArray_TYPE(obj))
#define PyArray_ISINTEGER(obj) PyTypeNum_ISINTEGER(PyArray_TYPE(obj))
#define PyArray_ISFLOAT(obj) PyTypeNum_ISFLOAT(PyArray_TYPE(obj))
#define PyArray_ISNUMBER(obj) PyTypeNum_ISNUMBER(PyArray_TYPE(obj))
#define PyArray_ISSTRING(obj) PyTypeNum_ISSTRING(PyArray_TYPE(obj))
#define PyArray_ISCOMPLEX(obj) PyTypeNum_ISCOMPLEX(PyArray_TYPE(obj))
#define PyArray_ISPYTHON(obj) PyTypeNum_ISPYTHON(PyArray_TYPE(obj))
#define PyArray_ISFLEXIBLE(obj) PyTypeNum_ISFLEXIBLE(PyArray_TYPE(obj))
#define PyArray_ISDATETIME(obj) PyTypeNum_ISDATETIME(PyArray_TYPE(obj))
#define PyArray_ISUSERDEF(obj) PyTypeNum_ISUSERDEF(PyArray_TYPE(obj))
#define PyArray_ISEXTENDED(obj) PyTypeNum_ISEXTENDED(PyArray_TYPE(obj))
#define PyArray_ISOBJECT(obj) PyTypeNum_ISOBJECT(PyArray_TYPE(obj))
#define PyArray_HASFIELDS(obj) PyDataType_HASFIELDS(PyArray_DESCR(obj))
/*
* FIXME: This should check for a flag on the data-type that
* states whether or not it is variable length. Because the
* ISFLEXIBLE check is hard-coded to the built-in data-types.
*/
#define PyArray_ISVARIABLE(obj) PyTypeNum_ISFLEXIBLE(PyArray_TYPE(obj))
#define PyArray_SAFEALIGNEDCOPY(obj) (PyArray_ISALIGNED(obj) && !PyArray_ISVARIABLE(obj))
#define NPY_LITTLE '<'
#define NPY_BIG '>'
#define NPY_NATIVE '='
#define NPY_SWAP 's'
#define NPY_IGNORE '|'
#if NPY_BYTE_ORDER == NPY_BIG_ENDIAN
#define NPY_NATBYTE NPY_BIG
#define NPY_OPPBYTE NPY_LITTLE
#else
#define NPY_NATBYTE NPY_LITTLE
#define NPY_OPPBYTE NPY_BIG
#endif
#define PyArray_ISNBO(arg) ((arg) != NPY_OPPBYTE)
#define PyArray_IsNativeByteOrder PyArray_ISNBO
#define PyArray_ISNOTSWAPPED(m) PyArray_ISNBO(PyArray_DESCR(m)->byteorder)
#define PyArray_ISBYTESWAPPED(m) (!PyArray_ISNOTSWAPPED(m))
#define PyArray_FLAGSWAP(m, flags) (PyArray_CHKFLAGS(m, flags) && \
PyArray_ISNOTSWAPPED(m))
#define PyArray_ISCARRAY(m) PyArray_FLAGSWAP(m, NPY_ARRAY_CARRAY)
#define PyArray_ISCARRAY_RO(m) PyArray_FLAGSWAP(m, NPY_ARRAY_CARRAY_RO)
#define PyArray_ISFARRAY(m) PyArray_FLAGSWAP(m, NPY_ARRAY_FARRAY)
#define PyArray_ISFARRAY_RO(m) PyArray_FLAGSWAP(m, NPY_ARRAY_FARRAY_RO)
#define PyArray_ISBEHAVED(m) PyArray_FLAGSWAP(m, NPY_ARRAY_BEHAVED)
#define PyArray_ISBEHAVED_RO(m) PyArray_FLAGSWAP(m, NPY_ARRAY_ALIGNED)
#define PyDataType_ISNOTSWAPPED(d) PyArray_ISNBO(((PyArray_Descr *)(d))->byteorder)
#define PyDataType_ISBYTESWAPPED(d) (!PyDataType_ISNOTSWAPPED(d))
/************************************************************
* A struct used by PyArray_CreateSortedStridePerm, new in 1.7.
************************************************************/
typedef struct {
npy_intp perm, stride;
} npy_stride_sort_item;
/************************************************************
* This is the form of the struct that's returned pointed by the
* PyCObject attribute of an array __array_struct__. See
* http://docs.scipy.org/doc/numpy/reference/arrays.interface.html for the full
* documentation.
************************************************************/
typedef struct {
int two; /*
* contains the integer 2 as a sanity
* check
*/
int nd; /* number of dimensions */
char typekind; /*
* kind in array --- character code of
* typestr
*/
int itemsize; /* size of each element */
int flags; /*
* how should be data interpreted. Valid
* flags are CONTIGUOUS (1), F_CONTIGUOUS (2),
* ALIGNED (0x100), NOTSWAPPED (0x200), and
* WRITEABLE (0x400). ARR_HAS_DESCR (0x800)
* states that arrdescr field is present in
* structure
*/
npy_intp *shape; /*
* A length-nd array of shape
* information
*/
npy_intp *strides; /* A length-nd array of stride information */
void *data; /* A pointer to the first element of the array */
PyObject *descr; /*
* A list of fields or NULL (ignored if flags
* does not have ARR_HAS_DESCR flag set)
*/
} PyArrayInterface;
/*
* This is a function for hooking into the PyDataMem_NEW/FREE/RENEW functions.
* See the documentation for PyDataMem_SetEventHook.
*/
typedef void (PyDataMem_EventHookFunc)(void *inp, void *outp, size_t size,
void *user_data);
/*
* Use the keyword NPY_DEPRECATED_INCLUDES to ensure that the header files
* npy_*_*_deprecated_api.h are only included from here and nowhere else.
*/
#ifdef NPY_DEPRECATED_INCLUDES
#error "Do not use the reserved keyword NPY_DEPRECATED_INCLUDES."
#endif
#define NPY_DEPRECATED_INCLUDES
#if !defined(NPY_NO_DEPRECATED_API) || \
(NPY_NO_DEPRECATED_API < NPY_1_7_API_VERSION)
#include "npy_1_7_deprecated_api.h"
#endif
/*
* There is no file npy_1_8_deprecated_api.h since there are no additional
* deprecated API features in NumPy 1.8.
*
* Note to maintainers: insert code like the following in future NumPy
* versions.
*
* #if !defined(NPY_NO_DEPRECATED_API) || \
* (NPY_NO_DEPRECATED_API < NPY_1_9_API_VERSION)
* #include "npy_1_9_deprecated_api.h"
* #endif
*/
#undef NPY_DEPRECATED_INCLUDES
#endif /* NPY_ARRAYTYPES_H */
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