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Merge NumPy extension from https://github.com/ndarray/Boost.NumPy/.
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src/numpy/dtype.cpp
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src/numpy/dtype.cpp
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// Copyright Jim Bosch 2010-2012.
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// Distributed under the Boost Software License, Version 1.0.
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// (See accompanying file LICENSE_1_0.txt or copy at
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// http://www.boost.org/LICENSE_1_0.txt)
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#ifdef _MSC_VER
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#include <boost/cstdint.hpp>
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#endif
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#define BOOST_NUMPY_INTERNAL
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#include <boost/numpy/internal.hpp>
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#define DTYPE_FROM_CODE(code) \
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dtype(python::detail::new_reference(reinterpret_cast<PyObject*>(PyArray_DescrFromType(code))))
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#define BUILTIN_INT_DTYPE(bits) \
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template <> struct builtin_int_dtype< bits, false > { \
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static dtype get() { return DTYPE_FROM_CODE(NPY_INT ## bits); } \
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}; \
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template <> struct builtin_int_dtype< bits, true > { \
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static dtype get() { return DTYPE_FROM_CODE(NPY_UINT ## bits); } \
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}; \
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template dtype get_int_dtype< bits, false >(); \
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template dtype get_int_dtype< bits, true >()
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#define BUILTIN_FLOAT_DTYPE(bits) \
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template <> struct builtin_float_dtype< bits > { \
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static dtype get() { return DTYPE_FROM_CODE(NPY_FLOAT ## bits); } \
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}; \
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template dtype get_float_dtype< bits >()
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#define BUILTIN_COMPLEX_DTYPE(bits) \
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template <> struct builtin_complex_dtype< bits > { \
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static dtype get() { return DTYPE_FROM_CODE(NPY_COMPLEX ## bits); } \
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}; \
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template dtype get_complex_dtype< bits >()
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namespace boost { namespace python { namespace converter {
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NUMPY_OBJECT_MANAGER_TRAITS_IMPL(PyArrayDescr_Type, numpy::dtype)
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}}} // namespace boost::python::converter
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namespace boost { namespace numpy {
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namespace detail {
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dtype builtin_dtype<bool,true>::get() { return DTYPE_FROM_CODE(NPY_BOOL); }
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template <int bits, bool isUnsigned> struct builtin_int_dtype;
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template <int bits> struct builtin_float_dtype;
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template <int bits> struct builtin_complex_dtype;
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template <int bits, bool isUnsigned> dtype get_int_dtype() {
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return builtin_int_dtype<bits,isUnsigned>::get();
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}
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template <int bits> dtype get_float_dtype() { return builtin_float_dtype<bits>::get(); }
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template <int bits> dtype get_complex_dtype() { return builtin_complex_dtype<bits>::get(); }
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BUILTIN_INT_DTYPE(8);
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BUILTIN_INT_DTYPE(16);
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BUILTIN_INT_DTYPE(32);
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BUILTIN_INT_DTYPE(64);
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BUILTIN_FLOAT_DTYPE(16);
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BUILTIN_FLOAT_DTYPE(32);
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BUILTIN_FLOAT_DTYPE(64);
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BUILTIN_COMPLEX_DTYPE(64);
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BUILTIN_COMPLEX_DTYPE(128);
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#if NPY_BITSOF_LONGDOUBLE > NPY_BITSOF_DOUBLE
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template <> struct builtin_float_dtype< NPY_BITSOF_LONGDOUBLE > {
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static dtype get() { return DTYPE_FROM_CODE(NPY_LONGDOUBLE); }
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};
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template dtype get_float_dtype< NPY_BITSOF_LONGDOUBLE >();
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template <> struct builtin_complex_dtype< 2 * NPY_BITSOF_LONGDOUBLE > {
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static dtype get() { return DTYPE_FROM_CODE(NPY_CLONGDOUBLE); }
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};
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template dtype get_complex_dtype< 2 * NPY_BITSOF_LONGDOUBLE >();
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#endif
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} // namespace detail
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python::detail::new_reference dtype::convert(python::object const & arg, bool align) {
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PyArray_Descr* obj=NULL;
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if (align) {
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if (PyArray_DescrAlignConverter(arg.ptr(), &obj) < 0)
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python::throw_error_already_set();
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} else {
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if (PyArray_DescrConverter(arg.ptr(), &obj) < 0)
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python::throw_error_already_set();
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}
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return python::detail::new_reference(reinterpret_cast<PyObject*>(obj));
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}
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int dtype::get_itemsize() const { return reinterpret_cast<PyArray_Descr*>(ptr())->elsize;}
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bool equivalent(dtype const & a, dtype const & b) {
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// On Windows x64, the behaviour described on
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// http://docs.scipy.org/doc/numpy/reference/c-api.array.html for
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// PyArray_EquivTypes unfortunately does not extend as expected:
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// "For example, on 32-bit platforms, NPY_LONG and NPY_INT are equivalent".
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// This should also hold for 64-bit platforms (and does on Linux), but not
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// on Windows. Implement an alternative:
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#ifdef _MSC_VER
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if (sizeof(long) == sizeof(int) &&
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// Manually take care of the type equivalence.
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((a == dtype::get_builtin<long>() || a == dtype::get_builtin<int>()) &&
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(b == dtype::get_builtin<long>() || b == dtype::get_builtin<int>()) ||
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(a == dtype::get_builtin<unsigned int>() || a == dtype::get_builtin<unsigned long>()) &&
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(b == dtype::get_builtin<unsigned int>() || b == dtype::get_builtin<unsigned long>()))) {
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return true;
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} else {
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return PyArray_EquivTypes(
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reinterpret_cast<PyArray_Descr*>(a.ptr()),
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reinterpret_cast<PyArray_Descr*>(b.ptr())
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);
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}
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#else
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return PyArray_EquivTypes(
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reinterpret_cast<PyArray_Descr*>(a.ptr()),
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reinterpret_cast<PyArray_Descr*>(b.ptr())
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);
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#endif
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}
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namespace {
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namespace pyconv = boost::python::converter;
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template <typename T>
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class array_scalar_converter {
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public:
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static PyTypeObject const * get_pytype() {
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// This implementation depends on the fact that get_builtin returns pointers to objects
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// NumPy has declared statically, and that the typeobj member also refers to a static
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// object. That means we don't need to do any reference counting.
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// In fact, I'm somewhat concerned that increasing the reference count of any of these
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// might cause leaks, because I don't think Boost.Python ever decrements it, but it's
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// probably a moot point if everything is actually static.
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return reinterpret_cast<PyArray_Descr*>(dtype::get_builtin<T>().ptr())->typeobj;
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}
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static void * convertible(PyObject * obj) {
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if (obj->ob_type == get_pytype()) {
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return obj;
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} else {
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dtype dt(python::detail::borrowed_reference(obj->ob_type));
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if (equivalent(dt, dtype::get_builtin<T>())) {
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return obj;
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}
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}
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return 0;
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}
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static void convert(PyObject * obj, pyconv::rvalue_from_python_stage1_data* data) {
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void * storage = reinterpret_cast<pyconv::rvalue_from_python_storage<T>*>(data)->storage.bytes;
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// We assume std::complex is a "standard layout" here and elsewhere; not guaranteed by
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// C++03 standard, but true in every known implementation (and guaranteed by C++11).
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PyArray_ScalarAsCtype(obj, reinterpret_cast<T*>(storage));
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data->convertible = storage;
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}
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static void declare() {
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pyconv::registry::push_back(
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&convertible, &convert, python::type_id<T>()
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#ifndef BOOST_PYTHON_NO_PY_SIGNATURES
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, &get_pytype
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#endif
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);
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}
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};
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} // anonymous
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void dtype::register_scalar_converters() {
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array_scalar_converter<bool>::declare();
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array_scalar_converter<npy_uint8>::declare();
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array_scalar_converter<npy_int8>::declare();
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array_scalar_converter<npy_uint16>::declare();
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array_scalar_converter<npy_int16>::declare();
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array_scalar_converter<npy_uint32>::declare();
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array_scalar_converter<npy_int32>::declare();
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#ifdef _MSC_VER
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// Since the npy_(u)int32 types are defined as long types and treated
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// as being different from the int32 types, these converters must be declared
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// explicitely.
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array_scalar_converter<boost::uint32_t>::declare();
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array_scalar_converter<boost::int32_t>::declare();
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#endif
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array_scalar_converter<npy_uint64>::declare();
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array_scalar_converter<npy_int64>::declare();
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array_scalar_converter<float>::declare();
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array_scalar_converter<double>::declare();
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array_scalar_converter< std::complex<float> >::declare();
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array_scalar_converter< std::complex<double> >::declare();
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#if NPY_BITSOF_LONGDOUBLE > NPY_BITSOF_DOUBLE
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array_scalar_converter<long double>::declare();
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array_scalar_converter< std::complex<long double> >::declare();
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#endif
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}
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} // namespace boost::numpy
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} // namespace boost
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