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Verified Commit 3373c680 authored by Justin Carpentier's avatar Justin Carpentier
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core: create dedicated file for eigen allocation

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CMakeLists.txt
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......@@ -106,6 +106,7 @@ SET(${PROJECT_NAME}_HEADERS
include/eigenpy/expose.hpp
include/eigenpy/details.hpp
include/eigenpy/fwd.hpp
include/eigenpy/eigen-allocator.hpp
include/eigenpy/map.hpp
include/eigenpy/geometry.hpp
include/eigenpy/geometry-conversion.hpp
......
include/eigenpy/details.hpp
+ 4
− 199
View file @ 3373c680
......@@ -12,9 +12,12 @@
#include <patchlevel.h> // For PY_MAJOR_VERSION
#include <iostream>
#include "eigenpy/numpy-type.hpp"
#include "eigenpy/scalar-conversion.hpp"
#include "eigenpy/eigenpy.hpp"
#include "eigenpy/numpy-type.hpp"
#include "eigenpy/eigen-allocator.hpp"
#include "eigenpy/registration.hpp"
#include "eigenpy/map.hpp"
#include "eigenpy/exception.hpp"
......@@ -56,206 +59,8 @@ namespace boost { namespace python { namespace detail {
namespace eigenpy
{
namespace bp = boost::python;
template<typename MatType, bool IsVectorAtCompileTime = MatType::IsVectorAtCompileTime>
struct initEigenObject
{
static MatType * run(PyArrayObject * pyArray, void * storage)
{
assert(PyArray_NDIM(pyArray) == 1 || PyArray_NDIM(pyArray) == 2);
int rows = -1, cols = -1;
if(PyArray_NDIM(pyArray) == 2)
{
rows = (int)PyArray_DIMS(pyArray)[0];
cols = (int)PyArray_DIMS(pyArray)[1];
}
else if(PyArray_NDIM(pyArray) == 1)
{
rows = (int)PyArray_DIMS(pyArray)[0];
cols = 1;
}
return new (storage) MatType(rows,cols);
}
};
template<typename MatType>
struct initEigenObject<MatType,true>
{
static MatType * run(PyArrayObject * pyArray, void * storage)
{
if(PyArray_NDIM(pyArray) == 1)
{
const int rows_or_cols = (int)PyArray_DIMS(pyArray)[0];
return new (storage) MatType(rows_or_cols);
}
else
{
const int rows = (int)PyArray_DIMS(pyArray)[0];
const int cols = (int)PyArray_DIMS(pyArray)[1];
return new (storage) MatType(rows,cols);
}
}
};
template<typename Scalar, typename NewScalar, bool cast_is_valid = FromTypeToType<Scalar,NewScalar>::value >
struct CastMatToMat
{
template<typename MatrixIn, typename MatrixOut>
static void run(const Eigen::MatrixBase<MatrixIn> & input,
const Eigen::MatrixBase<MatrixOut> & dest)
{
MatrixOut & dest_ = const_cast<MatrixOut &>(dest.derived());
if(dest.rows() == input.rows())
dest_ = input.template cast<NewScalar>();
else
dest_ = input.transpose().template cast<NewScalar>();
}
};
template<typename Scalar, typename NewScalar>
struct CastMatToMat<Scalar,NewScalar,false>
{
template<typename MatrixIn, typename MatrixOut>
static void run(const Eigen::MatrixBase<MatrixIn> & /*input*/,
const Eigen::MatrixBase<MatrixOut> & /*dest*/)
{
// do nothing
assert("Must never happened");
}
};
#define EIGENPY_CAST_FROM_PYARRAY_TO_EIGEN_MATRIX(MatType,Scalar,NewScalar,pyArray,mat) \
CastMatToMat<Scalar,NewScalar>::run(MapNumpy<MatType,Scalar>::map(pyArray),mat)
#define EIGENPY_CAST_FROM_EIGEN_MATRIX_TO_PYARRAY(MatType,Scalar,NewScalar,mat,pyArray) \
CastMatToMat<Scalar,NewScalar>::run(mat,MapNumpy<MatType,NewScalar>::map(pyArray))
template<typename MatType>
struct EigenObjectAllocator
{
typedef MatType Type;
typedef typename MatType::Scalar Scalar;
static void allocate(PyArrayObject * pyArray, void * storage)
{
Type * mat_ptr = initEigenObject<Type>::run(pyArray,storage);
Type & mat = *mat_ptr;
const int pyArray_Type = GET_PY_ARRAY_TYPE(pyArray);
if(pyArray_Type == NumpyEquivalentType<Scalar>::type_code)
{
mat = MapNumpy<MatType,Scalar>::map(pyArray); // avoid useless cast
return;
}
switch(pyArray_Type)
{
case NPY_INT:
EIGENPY_CAST_FROM_PYARRAY_TO_EIGEN_MATRIX(MatType,int,Scalar,pyArray,mat);
break;
case NPY_LONG:
EIGENPY_CAST_FROM_PYARRAY_TO_EIGEN_MATRIX(MatType,long,Scalar,pyArray,mat);
break;
case NPY_FLOAT:
EIGENPY_CAST_FROM_PYARRAY_TO_EIGEN_MATRIX(MatType,float,Scalar,pyArray,mat);
break;
case NPY_CFLOAT:
EIGENPY_CAST_FROM_PYARRAY_TO_EIGEN_MATRIX(MatType,std::complex<float>,Scalar,pyArray,mat);
break;
case NPY_DOUBLE:
EIGENPY_CAST_FROM_PYARRAY_TO_EIGEN_MATRIX(MatType,double,Scalar,pyArray,mat);
break;
case NPY_CDOUBLE:
EIGENPY_CAST_FROM_PYARRAY_TO_EIGEN_MATRIX(MatType,std::complex<double>,Scalar,pyArray,mat);
break;
case NPY_LONGDOUBLE:
EIGENPY_CAST_FROM_PYARRAY_TO_EIGEN_MATRIX(MatType,long double,Scalar,pyArray,mat);
break;
case NPY_CLONGDOUBLE:
EIGENPY_CAST_FROM_PYARRAY_TO_EIGEN_MATRIX(MatType,std::complex<long double>,Scalar,pyArray,mat);
break;
default:
throw Exception("You asked for a conversion which is not implemented.");
}
}
/// \brief Copy mat into the Python array using Eigen::Map
template<typename MatrixDerived>
static void copy(const Eigen::MatrixBase<MatrixDerived> & mat_,
PyArrayObject * pyArray)
{
const MatrixDerived & mat = const_cast<const MatrixDerived &>(mat_.derived());
const int pyArray_Type = GET_PY_ARRAY_TYPE(pyArray);
typedef typename MapNumpy<MatType,Scalar>::EigenMap MapType;
if(pyArray_Type == NumpyEquivalentType<Scalar>::type_code) // no cast needed
{
MapType map_pyArray = MapNumpy<MatType,Scalar>::map(pyArray);
if(mat.rows() == map_pyArray.rows())
map_pyArray = mat;
else
map_pyArray = mat.transpose();
return;
}
switch(pyArray_Type)
{
case NPY_INT:
EIGENPY_CAST_FROM_EIGEN_MATRIX_TO_PYARRAY(MatType,Scalar,int,mat,pyArray);
break;
case NPY_LONG:
EIGENPY_CAST_FROM_EIGEN_MATRIX_TO_PYARRAY(MatType,Scalar,long,mat,pyArray);
break;
case NPY_FLOAT:
EIGENPY_CAST_FROM_EIGEN_MATRIX_TO_PYARRAY(MatType,Scalar,float,mat,pyArray);
break;
case NPY_CFLOAT:
EIGENPY_CAST_FROM_EIGEN_MATRIX_TO_PYARRAY(MatType,Scalar,std::complex<float>,mat,pyArray);
break;
case NPY_DOUBLE:
EIGENPY_CAST_FROM_EIGEN_MATRIX_TO_PYARRAY(MatType,Scalar,double,mat,pyArray);
break;
case NPY_CDOUBLE:
EIGENPY_CAST_FROM_EIGEN_MATRIX_TO_PYARRAY(MatType,Scalar,std::complex<double>,mat,pyArray);
break;
case NPY_LONGDOUBLE:
EIGENPY_CAST_FROM_EIGEN_MATRIX_TO_PYARRAY(MatType,Scalar,long double,mat,pyArray);
break;
case NPY_CLONGDOUBLE:
EIGENPY_CAST_FROM_EIGEN_MATRIX_TO_PYARRAY(MatType,Scalar,std::complex<long double>,mat,pyArray);
break;
default:
throw Exception("You asked for a conversion which is not implemented.");
}
}
};
#if EIGEN_VERSION_AT_LEAST(3,2,0)
template<typename MatType>
struct EigenObjectAllocator< eigenpy::Ref<MatType> >
{
typedef eigenpy::Ref<MatType> Type;
typedef typename MatType::Scalar Scalar;
static void allocate(PyArrayObject * pyArray, void * storage)
{
typename MapNumpy<MatType,Scalar>::EigenMap numpyMap = MapNumpy<MatType,Scalar>::map(pyArray);
new (storage) Type(numpyMap);
}
static void copy(Type const & mat, PyArrayObject * pyArray)
{
EigenObjectAllocator<MatType>::copy(mat,pyArray);
}
};
#endif
/* --- TO PYTHON -------------------------------------------------------------- */
template<typename MatType>
......
include/eigenpy/eigen-allocator.hpp 0 → 100644
+ 211
− 0
View file @ 3373c680
//
// Copyright (c) 2014-2020 CNRS INRIA
//
#ifndef __eigenpy_eigen_allocator_hpp__
#define __eigenpy_eigen_allocator_hpp__
#include "eigenpy/fwd.hpp"
#include "eigenpy/map.hpp"
#include "eigenpy/scalar-conversion.hpp"
namespace eigenpy
{
template<typename MatType, bool IsVectorAtCompileTime = MatType::IsVectorAtCompileTime>
struct initEigenObject
{
static MatType * run(PyArrayObject * pyArray, void * storage)
{
assert(PyArray_NDIM(pyArray) == 1 || PyArray_NDIM(pyArray) == 2);
int rows = -1, cols = -1;
if(PyArray_NDIM(pyArray) == 2)
{
rows = (int)PyArray_DIMS(pyArray)[0];
cols = (int)PyArray_DIMS(pyArray)[1];
}
else if(PyArray_NDIM(pyArray) == 1)
{
rows = (int)PyArray_DIMS(pyArray)[0];
cols = 1;
}
return new (storage) MatType(rows,cols);
}
};
template<typename MatType>
struct initEigenObject<MatType,true>
{
static MatType * run(PyArrayObject * pyArray, void * storage)
{
if(PyArray_NDIM(pyArray) == 1)
{
const int rows_or_cols = (int)PyArray_DIMS(pyArray)[0];
return new (storage) MatType(rows_or_cols);
}
else
{
const int rows = (int)PyArray_DIMS(pyArray)[0];
const int cols = (int)PyArray_DIMS(pyArray)[1];
return new (storage) MatType(rows,cols);
}
}
};
template<typename Scalar, typename NewScalar, bool cast_is_valid = FromTypeToType<Scalar,NewScalar>::value >
struct CastMatToMat
{
template<typename MatrixIn, typename MatrixOut>
static void run(const Eigen::MatrixBase<MatrixIn> & input,
const Eigen::MatrixBase<MatrixOut> & dest)
{
MatrixOut & dest_ = const_cast<MatrixOut &>(dest.derived());
if(dest.rows() == input.rows())
dest_ = input.template cast<NewScalar>();
else
dest_ = input.transpose().template cast<NewScalar>();
}
};
template<typename Scalar, typename NewScalar>
struct CastMatToMat<Scalar,NewScalar,false>
{
template<typename MatrixIn, typename MatrixOut>
static void run(const Eigen::MatrixBase<MatrixIn> & /*input*/,
const Eigen::MatrixBase<MatrixOut> & /*dest*/)
{
// do nothing
assert("Must never happened");
}
};
#define EIGENPY_CAST_FROM_PYARRAY_TO_EIGEN_MATRIX(MatType,Scalar,NewScalar,pyArray,mat) \
CastMatToMat<Scalar,NewScalar>::run(MapNumpy<MatType,Scalar>::map(pyArray),mat)
#define EIGENPY_CAST_FROM_EIGEN_MATRIX_TO_PYARRAY(MatType,Scalar,NewScalar,mat,pyArray) \
CastMatToMat<Scalar,NewScalar>::run(mat,MapNumpy<MatType,NewScalar>::map(pyArray))
template<typename MatType>
struct EigenObjectAllocator
{
typedef MatType Type;
typedef typename MatType::Scalar Scalar;
static void allocate(PyArrayObject * pyArray, void * storage)
{
Type * mat_ptr = initEigenObject<Type>::run(pyArray,storage);
Type & mat = *mat_ptr;
const int pyArray_Type = GET_PY_ARRAY_TYPE(pyArray);
if(pyArray_Type == NumpyEquivalentType<Scalar>::type_code)
{
mat = MapNumpy<MatType,Scalar>::map(pyArray); // avoid useless cast
return;
}
switch(pyArray_Type)
{
case NPY_INT:
EIGENPY_CAST_FROM_PYARRAY_TO_EIGEN_MATRIX(MatType,int,Scalar,pyArray,mat);
break;
case NPY_LONG:
EIGENPY_CAST_FROM_PYARRAY_TO_EIGEN_MATRIX(MatType,long,Scalar,pyArray,mat);
break;
case NPY_FLOAT:
EIGENPY_CAST_FROM_PYARRAY_TO_EIGEN_MATRIX(MatType,float,Scalar,pyArray,mat);
break;
case NPY_CFLOAT:
EIGENPY_CAST_FROM_PYARRAY_TO_EIGEN_MATRIX(MatType,std::complex<float>,Scalar,pyArray,mat);
break;
case NPY_DOUBLE:
EIGENPY_CAST_FROM_PYARRAY_TO_EIGEN_MATRIX(MatType,double,Scalar,pyArray,mat);
break;
case NPY_CDOUBLE:
EIGENPY_CAST_FROM_PYARRAY_TO_EIGEN_MATRIX(MatType,std::complex<double>,Scalar,pyArray,mat);
break;
case NPY_LONGDOUBLE:
EIGENPY_CAST_FROM_PYARRAY_TO_EIGEN_MATRIX(MatType,long double,Scalar,pyArray,mat);
break;
case NPY_CLONGDOUBLE:
EIGENPY_CAST_FROM_PYARRAY_TO_EIGEN_MATRIX(MatType,std::complex<long double>,Scalar,pyArray,mat);
break;
default:
throw Exception("You asked for a conversion which is not implemented.");
}
}
/// \brief Copy mat into the Python array using Eigen::Map
template<typename MatrixDerived>
static void copy(const Eigen::MatrixBase<MatrixDerived> & mat_,
PyArrayObject * pyArray)
{
const MatrixDerived & mat = const_cast<const MatrixDerived &>(mat_.derived());
const int pyArray_Type = GET_PY_ARRAY_TYPE(pyArray);
typedef typename MapNumpy<MatType,Scalar>::EigenMap MapType;
if(pyArray_Type == NumpyEquivalentType<Scalar>::type_code) // no cast needed
{
MapType map_pyArray = MapNumpy<MatType,Scalar>::map(pyArray);
if(mat.rows() == map_pyArray.rows())
map_pyArray = mat;
else
map_pyArray = mat.transpose();
return;
}
switch(pyArray_Type)
{
case NPY_INT:
EIGENPY_CAST_FROM_EIGEN_MATRIX_TO_PYARRAY(MatType,Scalar,int,mat,pyArray);
break;
case NPY_LONG:
EIGENPY_CAST_FROM_EIGEN_MATRIX_TO_PYARRAY(MatType,Scalar,long,mat,pyArray);
break;
case NPY_FLOAT:
EIGENPY_CAST_FROM_EIGEN_MATRIX_TO_PYARRAY(MatType,Scalar,float,mat,pyArray);
break;
case NPY_CFLOAT:
EIGENPY_CAST_FROM_EIGEN_MATRIX_TO_PYARRAY(MatType,Scalar,std::complex<float>,mat,pyArray);
break;
case NPY_DOUBLE:
EIGENPY_CAST_FROM_EIGEN_MATRIX_TO_PYARRAY(MatType,Scalar,double,mat,pyArray);
break;
case NPY_CDOUBLE:
EIGENPY_CAST_FROM_EIGEN_MATRIX_TO_PYARRAY(MatType,Scalar,std::complex<double>,mat,pyArray);
break;
case NPY_LONGDOUBLE:
EIGENPY_CAST_FROM_EIGEN_MATRIX_TO_PYARRAY(MatType,Scalar,long double,mat,pyArray);
break;
case NPY_CLONGDOUBLE:
EIGENPY_CAST_FROM_EIGEN_MATRIX_TO_PYARRAY(MatType,Scalar,std::complex<long double>,mat,pyArray);
break;
default:
throw Exception("You asked for a conversion which is not implemented.");
}
}
};
#if EIGEN_VERSION_AT_LEAST(3,2,0)
template<typename MatType>
struct EigenObjectAllocator< eigenpy::Ref<MatType> >
{
typedef eigenpy::Ref<MatType> Type;
typedef typename MatType::Scalar Scalar;
static void allocate(PyArrayObject * pyArray, void * storage)
{
typename MapNumpy<MatType,Scalar>::EigenMap numpyMap = MapNumpy<MatType,Scalar>::map(pyArray);
new (storage) Type(numpyMap);
}
static void copy(Type const & mat, PyArrayObject * pyArray)
{
EigenObjectAllocator<MatType>::copy(mat,pyArray);
}
};
#endif
}
#endif // __eigenpy_eigen_allocator_hpp__
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