mirror of
https://github.com/explosion/spaCy.git
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1732 lines
59 KiB
C
1732 lines
59 KiB
C
#ifndef NDARRAYTYPES_H
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#define NDARRAYTYPES_H
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/* numpyconfig.h is auto-generated by the installer */
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#include "numpyconfig.h"
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#include "npy_common.h"
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#include "npy_endian.h"
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#include "npy_cpu.h"
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#include "utils.h"
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#ifdef NPY_ENABLE_SEPARATE_COMPILATION
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#define NPY_NO_EXPORT NPY_VISIBILITY_HIDDEN
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#else
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#define NPY_NO_EXPORT static
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#endif
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/* Only use thread if configured in config and python supports it */
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#if defined WITH_THREAD && !NPY_NO_SMP
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#define NPY_ALLOW_THREADS 1
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#else
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#define NPY_ALLOW_THREADS 0
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#endif
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/*
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* There are several places in the code where an array of dimensions
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* is allocated statically. This is the size of that static
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* allocation.
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*
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* The array creation itself could have arbitrary dimensions but all
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* the places where static allocation is used would need to be changed
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* to dynamic (including inside of several structures)
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*/
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#define NPY_MAXDIMS 32
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#define NPY_MAXARGS 32
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/* Used for Converter Functions "O&" code in ParseTuple */
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#define NPY_FAIL 0
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#define NPY_SUCCEED 1
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/*
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* Binary compatibility version number. This number is increased
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* whenever the C-API is changed such that binary compatibility is
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* broken, i.e. whenever a recompile of extension modules is needed.
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*/
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#define NPY_VERSION NPY_ABI_VERSION
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/*
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* Minor API version. This number is increased whenever a change is
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* made to the C-API -- whether it breaks binary compatibility or not.
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* Some changes, such as adding a function pointer to the end of the
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* function table, can be made without breaking binary compatibility.
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* In this case, only the NPY_FEATURE_VERSION (*not* NPY_VERSION)
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* would be increased. Whenever binary compatibility is broken, both
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* NPY_VERSION and NPY_FEATURE_VERSION should be increased.
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*/
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#define NPY_FEATURE_VERSION NPY_API_VERSION
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enum NPY_TYPES { NPY_BOOL=0,
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NPY_BYTE, NPY_UBYTE,
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NPY_SHORT, NPY_USHORT,
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NPY_INT, NPY_UINT,
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NPY_LONG, NPY_ULONG,
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NPY_LONGLONG, NPY_ULONGLONG,
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NPY_FLOAT, NPY_DOUBLE, NPY_LONGDOUBLE,
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NPY_CFLOAT, NPY_CDOUBLE, NPY_CLONGDOUBLE,
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NPY_OBJECT=17,
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NPY_STRING, NPY_UNICODE,
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NPY_VOID,
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/*
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* New 1.6 types appended, may be integrated
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* into the above in 2.0.
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*/
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NPY_DATETIME, NPY_TIMEDELTA, NPY_HALF,
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NPY_NTYPES,
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NPY_NOTYPE,
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NPY_CHAR, /* special flag */
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NPY_USERDEF=256, /* leave room for characters */
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/* The number of types not including the new 1.6 types */
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NPY_NTYPES_ABI_COMPATIBLE=21
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};
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/* basetype array priority */
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#define NPY_PRIORITY 0.0
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/* default subtype priority */
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#define NPY_SUBTYPE_PRIORITY 1.0
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/* default scalar priority */
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#define NPY_SCALAR_PRIORITY -1000000.0
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/* How many floating point types are there (excluding half) */
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#define NPY_NUM_FLOATTYPE 3
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/*
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* These characters correspond to the array type and the struct
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* module
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*/
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enum NPY_TYPECHAR {
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NPY_BOOLLTR = '?',
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NPY_BYTELTR = 'b',
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NPY_UBYTELTR = 'B',
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NPY_SHORTLTR = 'h',
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NPY_USHORTLTR = 'H',
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NPY_INTLTR = 'i',
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NPY_UINTLTR = 'I',
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NPY_LONGLTR = 'l',
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NPY_ULONGLTR = 'L',
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NPY_LONGLONGLTR = 'q',
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NPY_ULONGLONGLTR = 'Q',
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NPY_HALFLTR = 'e',
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NPY_FLOATLTR = 'f',
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NPY_DOUBLELTR = 'd',
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NPY_LONGDOUBLELTR = 'g',
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NPY_CFLOATLTR = 'F',
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NPY_CDOUBLELTR = 'D',
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NPY_CLONGDOUBLELTR = 'G',
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NPY_OBJECTLTR = 'O',
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NPY_STRINGLTR = 'S',
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NPY_STRINGLTR2 = 'a',
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NPY_UNICODELTR = 'U',
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NPY_VOIDLTR = 'V',
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NPY_DATETIMELTR = 'M',
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NPY_TIMEDELTALTR = 'm',
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NPY_CHARLTR = 'c',
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/*
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* No Descriptor, just a define -- this let's
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* Python users specify an array of integers
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* large enough to hold a pointer on the
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* platform
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*/
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NPY_INTPLTR = 'p',
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NPY_UINTPLTR = 'P',
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/*
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* These are for dtype 'kinds', not dtype 'typecodes'
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* as the above are for.
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*/
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NPY_GENBOOLLTR ='b',
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NPY_SIGNEDLTR = 'i',
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NPY_UNSIGNEDLTR = 'u',
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NPY_FLOATINGLTR = 'f',
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NPY_COMPLEXLTR = 'c'
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};
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typedef enum {
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NPY_QUICKSORT=0,
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NPY_HEAPSORT=1,
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NPY_MERGESORT=2
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} NPY_SORTKIND;
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#define NPY_NSORTS (NPY_MERGESORT + 1)
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typedef enum {
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NPY_SEARCHLEFT=0,
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NPY_SEARCHRIGHT=1
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} NPY_SEARCHSIDE;
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#define NPY_NSEARCHSIDES (NPY_SEARCHRIGHT + 1)
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typedef enum {
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NPY_NOSCALAR=-1,
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NPY_BOOL_SCALAR,
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NPY_INTPOS_SCALAR,
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NPY_INTNEG_SCALAR,
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NPY_FLOAT_SCALAR,
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NPY_COMPLEX_SCALAR,
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NPY_OBJECT_SCALAR
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} NPY_SCALARKIND;
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#define NPY_NSCALARKINDS (NPY_OBJECT_SCALAR + 1)
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/* For specifying array memory layout or iteration order */
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typedef enum {
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/* Fortran order if inputs are all Fortran, C otherwise */
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NPY_ANYORDER=-1,
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/* C order */
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NPY_CORDER=0,
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/* Fortran order */
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NPY_FORTRANORDER=1,
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/* An order as close to the inputs as possible */
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NPY_KEEPORDER=2
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} NPY_ORDER;
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/* For specifying allowed casting in operations which support it */
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typedef enum {
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/* Only allow identical types */
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NPY_NO_CASTING=0,
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/* Allow identical and byte swapped types */
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NPY_EQUIV_CASTING=1,
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/* Only allow safe casts */
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NPY_SAFE_CASTING=2,
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/* Allow safe casts or casts within the same kind */
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NPY_SAME_KIND_CASTING=3,
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/* Allow any casts */
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NPY_UNSAFE_CASTING=4,
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/*
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* Temporary internal definition only, will be removed in upcoming
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* release, see below
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* */
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NPY_INTERNAL_UNSAFE_CASTING_BUT_WARN_UNLESS_SAME_KIND = 100,
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} NPY_CASTING;
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typedef enum {
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NPY_CLIP=0,
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NPY_WRAP=1,
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NPY_RAISE=2
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} NPY_CLIPMODE;
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/* The special not-a-time (NaT) value */
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#define NPY_DATETIME_NAT NPY_MIN_INT64
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/*
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* Upper bound on the length of a DATETIME ISO 8601 string
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* YEAR: 21 (64-bit year)
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* MONTH: 3
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* DAY: 3
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* HOURS: 3
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* MINUTES: 3
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* SECONDS: 3
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* ATTOSECONDS: 1 + 3*6
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* TIMEZONE: 5
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* NULL TERMINATOR: 1
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*/
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#define NPY_DATETIME_MAX_ISO8601_STRLEN (21+3*5+1+3*6+6+1)
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typedef enum {
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NPY_FR_Y = 0, /* Years */
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NPY_FR_M = 1, /* Months */
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NPY_FR_W = 2, /* Weeks */
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/* Gap where 1.6 NPY_FR_B (value 3) was */
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NPY_FR_D = 4, /* Days */
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NPY_FR_h = 5, /* hours */
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NPY_FR_m = 6, /* minutes */
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NPY_FR_s = 7, /* seconds */
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NPY_FR_ms = 8, /* milliseconds */
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NPY_FR_us = 9, /* microseconds */
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NPY_FR_ns = 10,/* nanoseconds */
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NPY_FR_ps = 11,/* picoseconds */
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NPY_FR_fs = 12,/* femtoseconds */
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NPY_FR_as = 13,/* attoseconds */
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NPY_FR_GENERIC = 14 /* Generic, unbound units, can convert to anything */
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} NPY_DATETIMEUNIT;
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/*
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* NOTE: With the NPY_FR_B gap for 1.6 ABI compatibility, NPY_DATETIME_NUMUNITS
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* is technically one more than the actual number of units.
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*/
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#define NPY_DATETIME_NUMUNITS (NPY_FR_GENERIC + 1)
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#define NPY_DATETIME_DEFAULTUNIT NPY_FR_GENERIC
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/*
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* Business day conventions for mapping invalid business
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* days to valid business days.
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*/
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typedef enum {
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/* Go forward in time to the following business day. */
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NPY_BUSDAY_FORWARD,
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NPY_BUSDAY_FOLLOWING = NPY_BUSDAY_FORWARD,
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/* Go backward in time to the preceding business day. */
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NPY_BUSDAY_BACKWARD,
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NPY_BUSDAY_PRECEDING = NPY_BUSDAY_BACKWARD,
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/*
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* Go forward in time to the following business day, unless it
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* crosses a month boundary, in which case go backward
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*/
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NPY_BUSDAY_MODIFIEDFOLLOWING,
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/*
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* Go backward in time to the preceding business day, unless it
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* crosses a month boundary, in which case go forward.
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*/
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NPY_BUSDAY_MODIFIEDPRECEDING,
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/* Produce a NaT for non-business days. */
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NPY_BUSDAY_NAT,
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/* Raise an exception for non-business days. */
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NPY_BUSDAY_RAISE
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} NPY_BUSDAY_ROLL;
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/************************************************************
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* NumPy Auxiliary Data for inner loops, sort functions, etc.
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************************************************************/
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/*
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* When creating an auxiliary data struct, this should always appear
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* as the first member, like this:
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*
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* typedef struct {
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* NpyAuxData base;
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* double constant;
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* } constant_multiplier_aux_data;
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*/
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typedef struct NpyAuxData_tag NpyAuxData;
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/* Function pointers for freeing or cloning auxiliary data */
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typedef void (NpyAuxData_FreeFunc) (NpyAuxData *);
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typedef NpyAuxData *(NpyAuxData_CloneFunc) (NpyAuxData *);
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struct NpyAuxData_tag {
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NpyAuxData_FreeFunc *free;
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NpyAuxData_CloneFunc *clone;
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/* To allow for a bit of expansion without breaking the ABI */
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void *reserved[2];
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};
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/* Macros to use for freeing and cloning auxiliary data */
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#define NPY_AUXDATA_FREE(auxdata) \
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do { \
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if ((auxdata) != NULL) { \
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(auxdata)->free(auxdata); \
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} \
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} while(0)
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#define NPY_AUXDATA_CLONE(auxdata) \
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((auxdata)->clone(auxdata))
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#define NPY_ERR(str) fprintf(stderr, #str); fflush(stderr);
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#define NPY_ERR2(str) fprintf(stderr, str); fflush(stderr);
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#define NPY_STRINGIFY(x) #x
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#define NPY_TOSTRING(x) NPY_STRINGIFY(x)
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/*
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* Macros to define how array, and dimension/strides data is
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* allocated.
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*/
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/* Data buffer - PyDataMem_NEW/FREE/RENEW are in multiarraymodule.c */
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#define NPY_USE_PYMEM 1
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#if NPY_USE_PYMEM == 1
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#define PyArray_malloc PyMem_Malloc
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#define PyArray_free PyMem_Free
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#define PyArray_realloc PyMem_Realloc
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#else
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#define PyArray_malloc malloc
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#define PyArray_free free
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#define PyArray_realloc realloc
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#endif
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/* Dimensions and strides */
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#define PyDimMem_NEW(size) \
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((npy_intp *)PyArray_malloc(size*sizeof(npy_intp)))
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#define PyDimMem_FREE(ptr) PyArray_free(ptr)
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#define PyDimMem_RENEW(ptr,size) \
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((npy_intp *)PyArray_realloc(ptr,size*sizeof(npy_intp)))
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/* forward declaration */
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struct _PyArray_Descr;
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/* These must deal with unaligned and swapped data if necessary */
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typedef PyObject * (PyArray_GetItemFunc) (void *, void *);
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typedef int (PyArray_SetItemFunc)(PyObject *, void *, void *);
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typedef void (PyArray_CopySwapNFunc)(void *, npy_intp, void *, npy_intp,
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npy_intp, int, void *);
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typedef void (PyArray_CopySwapFunc)(void *, void *, int, void *);
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typedef npy_bool (PyArray_NonzeroFunc)(void *, void *);
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/*
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* These assume aligned and notswapped data -- a buffer will be used
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* before or contiguous data will be obtained
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*/
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typedef int (PyArray_CompareFunc)(const void *, const void *, void *);
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typedef int (PyArray_ArgFunc)(void*, npy_intp, npy_intp*, void *);
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typedef void (PyArray_DotFunc)(void *, npy_intp, void *, npy_intp, void *,
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npy_intp, void *);
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typedef void (PyArray_VectorUnaryFunc)(void *, void *, npy_intp, void *,
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void *);
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/*
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* XXX the ignore argument should be removed next time the API version
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* is bumped. It used to be the separator.
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*/
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typedef int (PyArray_ScanFunc)(FILE *fp, void *dptr,
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char *ignore, struct _PyArray_Descr *);
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typedef int (PyArray_FromStrFunc)(char *s, void *dptr, char **endptr,
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struct _PyArray_Descr *);
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typedef int (PyArray_FillFunc)(void *, npy_intp, void *);
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typedef int (PyArray_SortFunc)(void *, npy_intp, void *);
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typedef int (PyArray_ArgSortFunc)(void *, npy_intp *, npy_intp, void *);
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typedef int (PyArray_FillWithScalarFunc)(void *, npy_intp, void *, void *);
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typedef int (PyArray_ScalarKindFunc)(void *);
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typedef void (PyArray_FastClipFunc)(void *in, npy_intp n_in, void *min,
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void *max, void *out);
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typedef void (PyArray_FastPutmaskFunc)(void *in, void *mask, npy_intp n_in,
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void *values, npy_intp nv);
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typedef int (PyArray_FastTakeFunc)(void *dest, void *src, npy_intp *indarray,
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npy_intp nindarray, npy_intp n_outer,
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npy_intp m_middle, npy_intp nelem,
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NPY_CLIPMODE clipmode);
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typedef struct {
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npy_intp *ptr;
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int len;
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} PyArray_Dims;
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typedef struct {
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/*
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* Functions to cast to most other standard types
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* Can have some NULL entries. The types
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* DATETIME, TIMEDELTA, and HALF go into the castdict
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* even though they are built-in.
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*/
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PyArray_VectorUnaryFunc *cast[NPY_NTYPES_ABI_COMPATIBLE];
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/* The next four functions *cannot* be NULL */
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/*
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* Functions to get and set items with standard Python types
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* -- not array scalars
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*/
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PyArray_GetItemFunc *getitem;
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PyArray_SetItemFunc *setitem;
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/*
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* Copy and/or swap data. Memory areas may not overlap
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* Use memmove first if they might
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*/
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PyArray_CopySwapNFunc *copyswapn;
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PyArray_CopySwapFunc *copyswap;
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/*
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* Function to compare items
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* Can be NULL
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*/
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PyArray_CompareFunc *compare;
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/*
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* Function to select largest
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* Can be NULL
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*/
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PyArray_ArgFunc *argmax;
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/*
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* Function to compute dot product
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* Can be NULL
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*/
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PyArray_DotFunc *dotfunc;
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/*
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* Function to scan an ASCII file and
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* place a single value plus possible separator
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* Can be NULL
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*/
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PyArray_ScanFunc *scanfunc;
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/*
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* Function to read a single value from a string
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* and adjust the pointer; Can be NULL
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*/
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PyArray_FromStrFunc *fromstr;
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/*
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* Function to determine if data is zero or not
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* If NULL a default version is
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* used at Registration time.
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*/
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PyArray_NonzeroFunc *nonzero;
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/*
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* Used for arange.
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* Can be NULL.
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*/
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PyArray_FillFunc *fill;
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/*
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* Function to fill arrays with scalar values
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* Can be NULL
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*/
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PyArray_FillWithScalarFunc *fillwithscalar;
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/*
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* Sorting functions
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* Can be NULL
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*/
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PyArray_SortFunc *sort[NPY_NSORTS];
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PyArray_ArgSortFunc *argsort[NPY_NSORTS];
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/*
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* Dictionary of additional casting functions
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* PyArray_VectorUnaryFuncs
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* which can be populated to support casting
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* to other registered types. Can be NULL
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*/
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PyObject *castdict;
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/*
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* Functions useful for generalizing
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* the casting rules.
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* Can be NULL;
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*/
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PyArray_ScalarKindFunc *scalarkind;
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int **cancastscalarkindto;
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int *cancastto;
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PyArray_FastClipFunc *fastclip;
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PyArray_FastPutmaskFunc *fastputmask;
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PyArray_FastTakeFunc *fasttake;
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|
|
/*
|
|
* 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;
|
|
} 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_VERSION
|
|
* (or NPY_1_8_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_API_VERSION <= NPY_NO_DEPRECATED_API))
|
|
/*
|
|
* 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
|
|
*/
|
|
|
|
/*
|
|
* 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)
|
|
|
|
#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_DEF PyThreadState *_save=NULL;
|
|
#define NPY_BEGIN_THREADS do {_save = PyEval_SaveThread();} while (0);
|
|
#define NPY_END_THREADS do {if (_save) PyEval_RestoreThread(_save);} 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_DEF
|
|
#define NPY_BEGIN_THREADS
|
|
#define NPY_END_THREADS
|
|
#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_NEXT3(it) do { \
|
|
if ((it)->coordinates[2] < (it)->dims_m1[2]) { \
|
|
(it)->coordinates[2]++; \
|
|
(it)->dataptr += (it)->strides[2]; \
|
|
} \
|
|
else { \
|
|
(it)->coordinates[2] = 0; \
|
|
(it)->dataptr -= (it)->backstrides[2]; \
|
|
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 */
|
|
|
|
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 */
|
|
PyArrayIterObject *iters[NPY_MAXDIMS]; /* index object
|
|
iterators */
|
|
PyArrayIterObject *ait; /* flat Iterator for
|
|
underlying array */
|
|
|
|
/* flat iterator for subspace (when numiter < nd) */
|
|
PyArrayIterObject *subspace;
|
|
|
|
/*
|
|
* if subspace iteration, then this is the array of axes in
|
|
* the underlying array represented by the index objects
|
|
*/
|
|
int iteraxes[NPY_MAXDIMS];
|
|
/*
|
|
* if subspace iteration, the these are the coordinates to the
|
|
* start of the subspace.
|
|
*/
|
|
npy_intp bscoord[NPY_MAXDIMS];
|
|
|
|
PyObject *indexobj; /* creating obj */
|
|
int consec;
|
|
char *dataptr;
|
|
|
|
} 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_NDIM(m) > 1))
|
|
|
|
#define PyArray_FORTRAN_IF(m) ((PyArray_CHKFLAGS(m, NPY_ARRAY_F_CONTIGUOUS) ? \
|
|
NPY_ARRAY_F_CONTIGUOUS : 0))
|
|
|
|
#if (defined(NPY_NO_DEPRECATED_API) && (NPY_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 PyObject *
|
|
PyArray_BASE(PyArrayObject *arr)
|
|
{
|
|
return ((PyArrayObject_fields *)arr)->base;
|
|
}
|
|
|
|
static NPY_INLINE 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);
|
|
|
|
#if !(defined(NPY_NO_DEPRECATED_API) && (NPY_API_VERSION <= NPY_NO_DEPRECATED_API))
|
|
#include "npy_deprecated_api.h"
|
|
#endif
|
|
|
|
#endif /* NPY_ARRAYTYPES_H */
|