83 lines
2.6 KiB
Plaintext
83 lines
2.6 KiB
Plaintext
// Copyright Jim Bosch 2010-2012.
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// Copyright Stefan Seefeld 2016.
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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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#ifndef boost_python_numpy_matrix_hpp_
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#define boost_python_numpy_matrix_hpp_
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/**
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* @brief Object manager for numpy.matrix.
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*/
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#include <boost/python.hpp>
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#include <boost/python/numpy/numpy_object_mgr_traits.hpp>
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#include <boost/python/numpy/ndarray.hpp>
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namespace boost { namespace python { namespace numpy {
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/**
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* @brief A boost.python "object manager" (subclass of object) for numpy.matrix.
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*
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* @internal numpy.matrix is defined in Python, so object_manager_traits<matrix>::get_pytype()
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* is implemented by importing numpy and getting the "matrix" attribute of the module.
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* We then just hope that doesn't get destroyed while we need it, because if we put
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* a dynamic python object in a static-allocated boost::python::object or handle<>,
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* bad things happen when Python shuts down. I think this solution is safe, but I'd
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* love to get that confirmed.
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*/
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class matrix : public ndarray
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{
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static object construct(object_cref obj, dtype const & dt, bool copy);
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static object construct(object_cref obj, bool copy);
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public:
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BOOST_PYTHON_FORWARD_OBJECT_CONSTRUCTORS(matrix, ndarray);
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/// @brief Equivalent to "numpy.matrix(obj,dt,copy)" in Python.
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explicit matrix(object const & obj, dtype const & dt, bool copy=true)
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: ndarray(extract<ndarray>(construct(obj, dt, copy))) {}
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/// @brief Equivalent to "numpy.matrix(obj,copy=copy)" in Python.
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explicit matrix(object const & obj, bool copy=true)
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: ndarray(extract<ndarray>(construct(obj, copy))) {}
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/// \brief Return a view of the matrix with the given dtype.
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matrix view(dtype const & dt) const;
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/// \brief Copy the scalar (deep for all non-object fields).
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matrix copy() const;
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/// \brief Transpose the matrix.
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matrix transpose() const;
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};
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/**
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* @brief CallPolicies that causes a function that returns a numpy.ndarray to
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* return a numpy.matrix instead.
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*/
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template <typename Base = default_call_policies>
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struct as_matrix : Base
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{
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static PyObject * postcall(PyObject *, PyObject * result)
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{
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object a = object(handle<>(result));
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numpy::matrix m(a, false);
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Py_INCREF(m.ptr());
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return m.ptr();
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}
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};
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} // namespace boost::python::numpy
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namespace converter
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{
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NUMPY_OBJECT_MANAGER_TRAITS(numpy::matrix);
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}}} // namespace boost::python::converter
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#endif
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