boostorg-python/src/numpy/dtype.cpp at develop · InfinityOfficialNetwork/boostorg-python · GitHub

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// Copyright Jim Bosch 2010-2012.

// Copyright Stefan Seefeld 2016.

// Distributed under the Boost Software License, Version 1.0.

// (See accompanying file LICENSE_1_0.txt or copy at

// http://www.boost.org/LICENSE_1_0.txt)

#ifdef _MSC_VER

#include <boost/cstdint.hpp>

#endif

#define BOOST_PYTHON_NUMPY_INTERNAL

#include <boost/python/numpy/internal.hpp>

#define DTYPE_FROM_CODE(code) \

dtype(python::detail::new_reference(reinterpret_cast<PyObject*>(PyArray_DescrFromType(code))))

#define BUILTIN_INT_DTYPE(bits) \

template <> struct builtin_int_dtype<bits, false> \

{ \

static dtype get() { return DTYPE_FROM_CODE(NPY_INT ## bits);} \

}; \

template <> struct builtin_int_dtype<bits, true> \

{ \

static dtype get() { return DTYPE_FROM_CODE(NPY_UINT ## bits);} \

}; \

template BOOST_NUMPY_DECL dtype get_int_dtype<bits, false>(); \

template BOOST_NUMPY_DECL dtype get_int_dtype<bits, true>()

#define BUILTIN_FLOAT_DTYPE(bits) \

template <> struct builtin_float_dtype<bits> \

{ \

static dtype get() { return DTYPE_FROM_CODE(NPY_FLOAT ## bits);} \

}; \

template BOOST_NUMPY_DECL dtype get_float_dtype<bits>()

#define BUILTIN_COMPLEX_DTYPE(bits) \

template <> struct builtin_complex_dtype<bits> \

{ \

static dtype get() { return DTYPE_FROM_CODE(NPY_COMPLEX ## bits);} \

}; \

template BOOST_NUMPY_DECL dtype get_complex_dtype<bits>()

namespace boost { namespace python { namespace converter {

NUMPY_OBJECT_MANAGER_TRAITS_IMPL(PyArrayDescr_Type, numpy::dtype)

} // namespace boost::python::converter

namespace numpy {

namespace detail {

dtype builtin_dtype<bool,true>::get() { return DTYPE_FROM_CODE(NPY_BOOL); }

template <int bits, bool isUnsigned> struct builtin_int_dtype;

template <int bits> struct builtin_float_dtype;

template <int bits> struct builtin_complex_dtype;

template <int bits, bool isUnsigned> dtype get_int_dtype() {

return builtin_int_dtype<bits,isUnsigned>::get();

}

template <int bits> dtype get_float_dtype() { return builtin_float_dtype<bits>::get(); }

template <int bits> dtype get_complex_dtype() { return builtin_complex_dtype<bits>::get(); }

BUILTIN_INT_DTYPE(8);

BUILTIN_INT_DTYPE(16);

BUILTIN_INT_DTYPE(32);

BUILTIN_INT_DTYPE(64);

#ifdef NPY_FLOAT16

BUILTIN_FLOAT_DTYPE(16);

#endif

BUILTIN_FLOAT_DTYPE(32);

BUILTIN_FLOAT_DTYPE(64);

BUILTIN_COMPLEX_DTYPE(64);

BUILTIN_COMPLEX_DTYPE(128);

#if NPY_BITSOF_LONGDOUBLE > NPY_BITSOF_DOUBLE

template <> struct builtin_float_dtype< NPY_BITSOF_LONGDOUBLE > {

static dtype get() { return DTYPE_FROM_CODE(NPY_LONGDOUBLE); }

};

template dtype get_float_dtype< NPY_BITSOF_LONGDOUBLE >();

template <> struct builtin_complex_dtype< 2 * NPY_BITSOF_LONGDOUBLE > {

static dtype get() { return DTYPE_FROM_CODE(NPY_CLONGDOUBLE); }

};

template dtype get_complex_dtype< 2 * NPY_BITSOF_LONGDOUBLE >();

#endif

} // namespace detail

python::detail::new_reference dtype::convert(object const & arg, bool align)

{

PyArray_Descr* obj=NULL;

if (align)

{

if (PyArray_DescrAlignConverter(arg.ptr(), &obj) < 0)

throw_error_already_set();

}

else

{

if (PyArray_DescrConverter(arg.ptr(), &obj) < 0)

throw_error_already_set();

}

return python::detail::new_reference(reinterpret_cast<PyObject*>(obj));

}

int dtype::get_itemsize() const { return reinterpret_cast<PyArray_Descr*>(ptr())->elsize;}

bool equivalent(dtype const & a, dtype const & b) {

// On Windows x64, the behaviour described on

// http://docs.scipy.org/doc/numpy/reference/c-api.array.html for

// PyArray_EquivTypes unfortunately does not extend as expected:

// "For example, on 32-bit platforms, NPY_LONG and NPY_INT are equivalent".

// This should also hold for 64-bit platforms (and does on Linux), but not

// on Windows. Implement an alternative:

#ifdef _MSC_VER

if (sizeof(long) == sizeof(int) &&

// Manually take care of the type equivalence.

((a == dtype::get_builtin<long>() || a == dtype::get_builtin<int>()) &&

(b == dtype::get_builtin<long>() || b == dtype::get_builtin<int>()) ||

(a == dtype::get_builtin<unsigned int>() || a == dtype::get_builtin<unsigned long>()) &&

(b == dtype::get_builtin<unsigned int>() || b == dtype::get_builtin<unsigned long>()))) {

return true;

} else {

return PyArray_EquivTypes(

reinterpret_cast<PyArray_Descr*>(a.ptr()),

reinterpret_cast<PyArray_Descr*>(b.ptr())

);

}

#else

return PyArray_EquivTypes(

reinterpret_cast<PyArray_Descr*>(a.ptr()),

reinterpret_cast<PyArray_Descr*>(b.ptr())

);

#endif

}

namespace

{

namespace pyconv = boost::python::converter;

template <typename T>

class array_scalar_converter

{

public:

static PyTypeObject const * get_pytype()

{

// This implementation depends on the fact that get_builtin returns pointers to objects

// NumPy has declared statically, and that the typeobj member also refers to a static

// object. That means we don't need to do any reference counting.

// In fact, I'm somewhat concerned that increasing the reference count of any of these

// might cause leaks, because I don't think Boost.Python ever decrements it, but it's

// probably a moot point if everything is actually static.

return reinterpret_cast<PyArray_Descr*>(dtype::get_builtin<T>().ptr())->typeobj;

}

static void * convertible(PyObject * obj)

{

if (obj->ob_type == get_pytype())

{

return obj;

}

else

{

dtype dt(python::detail::borrowed_reference(obj->ob_type));

if (equivalent(dt, dtype::get_builtin<T>()))

{

return obj;

}

return 0;

}

static void convert(PyObject * obj, pyconv::rvalue_from_python_stage1_data* data)

{

void * storage = reinterpret_cast<pyconv::rvalue_from_python_storage<T>*>(data)->storage.bytes;

// We assume std::complex is a "standard layout" here and elsewhere; not guaranteed by

// C++03 standard, but true in every known implementation (and guaranteed by C++11).

PyArray_ScalarAsCtype(obj, reinterpret_cast<T*>(storage));

data->convertible = storage;

}

static void declare()

{

pyconv::registry::push_back(&convertible, &convert, python::type_id<T>()

#ifndef BOOST_PYTHON_NO_PY_SIGNATURES

, &get_pytype

#endif

);

}

};

} // anonymous

void dtype::register_scalar_converters()

{

array_scalar_converter<bool>::declare();

array_scalar_converter<npy_uint8>::declare();

array_scalar_converter<npy_int8>::declare();

array_scalar_converter<npy_uint16>::declare();

array_scalar_converter<npy_int16>::declare();

array_scalar_converter<npy_uint32>::declare();

array_scalar_converter<npy_int32>::declare();

#ifdef _MSC_VER

// Since the npy_(u)int32 types are defined as long types and treated

// as being different from the int32 types, these converters must be declared

// explicitely.

array_scalar_converter<boost::uint32_t>::declare();

array_scalar_converter<boost::int32_t>::declare();

#endif

array_scalar_converter<npy_uint64>::declare();

array_scalar_converter<npy_int64>::declare();

array_scalar_converter<float>::declare();

array_scalar_converter<double>::declare();

array_scalar_converter< std::complex<float> >::declare();

array_scalar_converter< std::complex<double> >::declare();

#if NPY_BITSOF_LONGDOUBLE > NPY_BITSOF_DOUBLE

array_scalar_converter<long double>::declare();

array_scalar_converter< std::complex<long double> >::declare();

#endif

}

}}} // namespace boost::python::numpy

boostorg-python/src/numpy/dtype.cpp at develop · InfinityOfficialNetwork/boostorg-python · GitHub

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