===========
NumPy C-API
===========
::
unsigned int
PyArray_GetNDArrayCVersion(void )
Included at the very first so not auto-grabbed and thus not labeled.
::
int
PyArray_SetNumericOps(PyObject *dict)
Set internal structure with number functions that all arrays will use
::
PyObject *
PyArray_GetNumericOps(void )
Get dictionary showing number functions that all arrays will use
::
int
PyArray_INCREF(PyArrayObject *mp)
For object arrays, increment all internal references.
::
int
PyArray_XDECREF(PyArrayObject *mp)
Decrement all internal references for object arrays.
(or arrays with object fields)
::
void
PyArray_SetStringFunction(PyObject *op, int repr)
Set the array print function to be a Python function.
::
PyArray_Descr *
PyArray_DescrFromType(int type)
Get the PyArray_Descr structure for a type.
::
PyObject *
PyArray_TypeObjectFromType(int type)
Get a typeobject from a type-number -- can return NULL.
New reference
::
char *
PyArray_Zero(PyArrayObject *arr)
Get pointer to zero of correct type for array.
::
char *
PyArray_One(PyArrayObject *arr)
Get pointer to one of correct type for array
::
PyObject *
PyArray_CastToType(PyArrayObject *arr, PyArray_Descr *dtype, int
is_f_order)
For backward compatibility
Cast an array using typecode structure.
steals reference to dtype --- cannot be NULL
This function always makes a copy of arr, even if the dtype
doesn't change.
::
int
PyArray_CastTo(PyArrayObject *out, PyArrayObject *mp)
Cast to an already created array.
::
int
PyArray_CastAnyTo(PyArrayObject *out, PyArrayObject *mp)
Cast to an already created array. Arrays don't have to be "broadcastable"
Only requirement is they have the same number of elements.
::
int
PyArray_CanCastSafely(int fromtype, int totype)
Check the type coercion rules.
::
npy_bool
PyArray_CanCastTo(PyArray_Descr *from, PyArray_Descr *to)
leaves reference count alone --- cannot be NULL
PyArray_CanCastTypeTo is equivalent to this, but adds a 'casting'
parameter.
::
int
PyArray_ObjectType(PyObject *op, int minimum_type)
Return the typecode of the array a Python object would be converted to
Returns the type number the result should have, or NPY_NOTYPE on error.
::
PyArray_Descr *
PyArray_DescrFromObject(PyObject *op, PyArray_Descr *mintype)
new reference -- accepts NULL for mintype
::
PyArrayObject **
PyArray_ConvertToCommonType(PyObject *op, int *retn)
This function is only used in one place within NumPy and should
generally be avoided. It is provided mainly for backward compatibility.
The user of the function has to free the returned array with PyDataMem_FREE.
::
PyArray_Descr *
PyArray_DescrFromScalar(PyObject *sc)
Return descr object from array scalar.
New reference
::
PyArray_Descr *
PyArray_DescrFromTypeObject(PyObject *type)
::
npy_intp
PyArray_Size(PyObject *op)
Compute the size of an array (in number of items)
::
PyObject *
PyArray_Scalar(void *data, PyArray_Descr *descr, PyObject *base)
Get scalar-equivalent to a region of memory described by a descriptor.
::
PyObject *
PyArray_FromScalar(PyObject *scalar, PyArray_Descr *outcode)
Get 0-dim array from scalar
0-dim array from array-scalar object
always contains a copy of the data
unless outcode is NULL, it is of void type and the referrer does
not own it either.
steals reference to outcode
::
void
PyArray_ScalarAsCtype(PyObject *scalar, void *ctypeptr)
Convert to c-type
no error checking is performed -- ctypeptr must be same type as scalar
in case of flexible type, the data is not copied
into ctypeptr which is expected to be a pointer to pointer
::
int
PyArray_CastScalarToCtype(PyObject *scalar, void
*ctypeptr, PyArray_Descr *outcode)
Cast Scalar to c-type
The output buffer must be large-enough to receive the value
Even for flexible types which is different from ScalarAsCtype
where only a reference for flexible types is returned
This may not work right on narrow builds for NumPy unicode scalars.
::
int
PyArray_CastScalarDirect(PyObject *scalar, PyArray_Descr
*indescr, void *ctypeptr, int outtype)
Cast Scalar to c-type
::
PyObject *
PyArray_ScalarFromObject(PyObject *object)
Get an Array Scalar From a Python Object
Returns NULL if unsuccessful but error is only set if another error occurred.
Currently only Numeric-like object supported.
::
PyArray_VectorUnaryFunc *
PyArray_GetCastFunc(PyArray_Descr *descr, int type_num)
Get a cast function to cast from the input descriptor to the
output type_number (must be a registered data-type).
Returns NULL if un-successful.
::
PyObject *
PyArray_FromDims(int NPY_UNUSED(nd) , int *NPY_UNUSED(d) , int
NPY_UNUSED(type) )
Deprecated, use PyArray_SimpleNew instead.
::
PyObject *
PyArray_FromDimsAndDataAndDescr(int NPY_UNUSED(nd) , int
*NPY_UNUSED(d) , PyArray_Descr
*descr, char *NPY_UNUSED(data) )
Deprecated, use PyArray_NewFromDescr instead.
::
PyObject *
PyArray_FromAny(PyObject *op, PyArray_Descr *newtype, int
min_depth, int max_depth, int flags, PyObject
*context)
Does not check for NPY_ARRAY_ENSURECOPY and NPY_ARRAY_NOTSWAPPED in flags
Steals a reference to newtype --- which can be NULL
::
PyObject *
PyArray_EnsureArray(PyObject *op)
This is a quick wrapper around
PyArray_FromAny(op, NULL, 0, 0, NPY_ARRAY_ENSUREARRAY, NULL)
that special cases Arrays and PyArray_Scalars up front
It *steals a reference* to the object
It also guarantees that the result is PyArray_Type
Because it decrefs op if any conversion needs to take place
so it can be used like PyArray_EnsureArray(some_function(...))
::
PyObject *
PyArray_EnsureAnyArray(PyObject *op)
::
PyObject *
PyArray_FromFile(FILE *fp, PyArray_Descr *dtype, npy_intp num, char
*sep)
Given a ``FILE *`` pointer ``fp``, and a ``PyArray_Descr``, return an
array corresponding to the data encoded in that file.
The reference to `dtype` is stolen (it is possible that the passed in
dtype is not held on to).
The number of elements to read is given as ``num``; if it is < 0, then
then as many as possible are read.
If ``sep`` is NULL or empty, then binary data is assumed, else
text data, with ``sep`` as the separator between elements. Whitespace in
the separator matches any length of whitespace in the text, and a match
for whitespace around the separator is added.
For memory-mapped files, use the buffer interface. No more data than
necessary is read by this routine.
::
PyObject *
PyArray_FromString(char *data, npy_intp slen, PyArray_Descr
*dtype, npy_intp num, char *sep)
Given a pointer to a string ``data``, a string length ``slen``, and
a ``PyArray_Descr``, return an array corresponding to the data
encoded in that string.
If the dtype is NULL, the default array type is used (double).
If non-null, the reference is stolen.
If ``slen`` is < 0, then the end of string is used for text data.
It is an error for ``slen`` to be < 0 for binary data (since embedded NULLs
would be the norm).
The number of elements to read is given as ``num``; if it is < 0, then
then as many as possible are read.
If ``sep`` is NULL or empty, then binary data is assumed, else
text data, with ``sep`` as the separator between elements. Whitespace in
the separator matches any length of whitespace in the text, and a match
for whitespace around the separator is added.
::
PyObject *
PyArray_FromBuffer(PyObject *buf, PyArray_Descr *type, npy_intp
count, npy_intp offset)
::
PyObject *
PyArray_FromIter(PyObject *obj, PyArray_Descr *dtype, npy_intp count)
steals a reference to dtype (which cannot be NULL)
::
PyObject *
PyArray_Return(PyArrayObject *mp)
Return either
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这是一个使用Python编写的,运行在Kali Linux系统中的安全测试软件,主要用于对WPA3-SAE进行安全研究。它可以实现WPA3中除去密钥组降级攻击以及侧信道攻击外所有的攻击。这种工具测试软件为全新设计,全网只此一份。 ****本软件为安全测试制作,请合法使用,严禁用于非法用途******* 注意: 1.请使用带有监听模式的无线网卡,并开启监听模式 2.在搜索完Wi-Fi后请插拔网卡并重新开启监听模式 3.开始攻击测试前请务必设置所有必要的参数 4.源码还有很多不足,你可以任意对源码进行修改,但如有转载务必注明出处。 5.本软件依赖scapy
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WPA3-SAE安全测试系统 (2000个子文件)
fortranobject.c 45KB
wrapmodule.c 7KB
extra_avx512f_reduce.c 2KB
cpu_avx512_knm.c 1KB
cpu_popcnt.c 1KB
cpu_avx512_skx.c 1010B
cpu_avx512_icl.c 1004B
cpu_avx512_knl.c 956B
cpu_avx512_cnl.c 948B
extra_vsx_asm.c 945B
cpu_f16c.c 868B
cpu_avx512_clx.c 842B
cpu_asimd.c 818B
cpu_fma3.c 817B
cpu_vxe.c 788B
cpu_avx.c 779B
cpu_avx512cd.c 759B
cpu_avx512f.c 755B
cpu_avx2.c 749B
cpu_ssse3.c 705B
cpu_sse2.c 697B
cpu_sse42.c 692B
cpu_sse3.c 689B
cpu_sse.c 686B
cpu_sse41.c 675B
extra_avx512bw_mask.c 636B
cpu_vxe2.c 624B
cpu_neon_vfpv4.c 609B
cpu_neon.c 600B
cpu_asimdfhm.c 529B
extra_avx512dq_mask.c 504B
extra_vsx4_mma.c 499B
cpu_vsx.c 478B
cpu_vx.c 461B
cpu_asimddp.c 432B
cpu_asimdhp.c 379B
limited_api.c 344B
cpu_vsx4.c 305B
cpu_fma4.c 301B
cpu_vsx2.c 263B
cpu_neon_fp16.c 251B
cpu_vsx3.c 250B
cpu_xop.c 234B
gfortran_vs2003_hack.c 77B
test_flags.c 16B
generate_umath_validation_data.cpp 6KB
libdivide.h 78KB
ndarraytypes.h 67KB
__multiarray_api.h 61KB
npy_common.h 38KB
experimental_dtype_api.h 19KB
npy_math.h 19KB
npy_3kcompat.h 16KB
__ufunc_api.h 12KB
ufuncobject.h 12KB
ndarrayobject.h 10KB
distributions.h 10KB
noprefix.h 7KB
old_defines.h 6KB
fortranobject.h 6KB
npy_cpu.h 4KB
npy_1_7_deprecated_api.h 4KB
arrayscalars.h 4KB
numpyconfig.h 3KB
npy_endian.h 3KB
halffloat.h 2KB
npy_interrupt.h 2KB
_neighborhood_iterator_imp.h 2KB
utils.h 1KB
npy_os.h 1KB
_numpyconfig.h 971B
oldnumeric.h 899B
npy_no_deprecated_api.h 678B
bitgen.h 488B
arrayobject.h 282B
AUTHORS.md 2KB
generic.py 409KB
frame.py 388KB
test_multiarray.py 362KB
definitions.py 327KB
core.py 266KB
definitions.py 266KB
fastjsonschema_validations.py 264KB
base.py 238KB
core.py 208KB
core.py 208KB
core.py 208KB
test_core.py 206KB
_add_newdocs.py 204KB
uts46data.py 202KB
series.py 182KB
function_base.py 181KB
diameter.py 180KB
test_umath.py 168KB
pytables.py 168KB
inet6.py 151KB
style.py 146KB
test_function_base.py 146KB
groupby.py 140KB
_emoji_codes.py 137KB
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