diff --git a/include/eigenpy/numpy-allocator.hpp b/include/eigenpy/numpy-allocator.hpp index e0fd88288795df9ef4857ae3af54ab70bfc93458..fbbcab863a4b521aaa94ed96bf7d3db2edd160dd 100644 --- a/include/eigenpy/numpy-allocator.hpp +++ b/include/eigenpy/numpy-allocator.hpp @@ -40,12 +40,19 @@ namespace eigenpy typedef typename SimilarMatrixType::Scalar Scalar; enum { NPY_ARRAY_MEMORY_CONTIGUOUS = SimilarMatrixType::IsRowMajor ? NPY_ARRAY_CARRAY : NPY_ARRAY_FARRAY }; - PyArrayObject * pyArray = (PyArrayObject*) call_PyArray_New(nd, shape, - NumpyEquivalentType<Scalar>::type_code, - mat.data(), - NPY_ARRAY_MEMORY_CONTIGUOUS | NPY_ARRAY_ALIGNED); - - return pyArray; + if(NumpyType::sharedMemory()) + { + PyArrayObject * pyArray = (PyArrayObject*) call_PyArray_New(nd, shape, + NumpyEquivalentType<Scalar>::type_code, + mat.data(), + NPY_ARRAY_MEMORY_CONTIGUOUS | NPY_ARRAY_ALIGNED); + + return pyArray; + } + else + { + return NumpyAllocator<MatType>::allocate(mat.derived(),nd,shape); + } } }; @@ -68,12 +75,19 @@ namespace eigenpy typedef typename SimilarMatrixType::Scalar Scalar; enum { NPY_ARRAY_MEMORY_CONTIGUOUS_RO = SimilarMatrixType::IsRowMajor ? NPY_ARRAY_CARRAY_RO : NPY_ARRAY_FARRAY_RO }; - PyArrayObject * pyArray = (PyArrayObject*) call_PyArray_New(nd, shape, - NumpyEquivalentType<Scalar>::type_code, - const_cast<SimilarMatrixType &>(mat.derived()).data(), - NPY_ARRAY_MEMORY_CONTIGUOUS_RO | NPY_ARRAY_ALIGNED); - - return pyArray; + if(NumpyType::sharedMemory()) + { + PyArrayObject * pyArray = (PyArrayObject*) call_PyArray_New(nd, shape, + NumpyEquivalentType<Scalar>::type_code, + const_cast<SimilarMatrixType &>(mat.derived()).data(), + NPY_ARRAY_MEMORY_CONTIGUOUS_RO | NPY_ARRAY_ALIGNED); + + return pyArray; + } + else + { + return NumpyAllocator<MatType>::allocate(mat.derived(),nd,shape); + } } }; diff --git a/include/eigenpy/numpy-type.hpp b/include/eigenpy/numpy-type.hpp index 3085b55e8ffe1dd33f4752900a97b934fad1a4c9..8b5cbb2419da7f0974f7079c4db3100d1b1f7bd1 100644 --- a/include/eigenpy/numpy-type.hpp +++ b/include/eigenpy/numpy-type.hpp @@ -96,6 +96,16 @@ namespace eigenpy switchToNumpyArray(); } + static void sharedMemory(const bool value) + { + getInstance().shared_memory = value; + } + + static bool sharedMemory() + { + return getInstance().shared_memory; + } + static void switchToNumpyArray() { getInstance().CurrentNumpyType = getInstance().NumpyArrayObject; @@ -162,6 +172,8 @@ namespace eigenpy CurrentNumpyType = NumpyArrayObject; // default conversion np_type = ARRAY_TYPE; + + shared_memory = true; } bp::object CurrentNumpyType; @@ -173,6 +185,8 @@ namespace eigenpy bp::object NumpyArrayObject; PyTypeObject * NumpyArrayType; NP_TYPE np_type; + + bool shared_memory; }; } diff --git a/src/eigenpy.cpp b/src/eigenpy.cpp index c2f49067d105f24fb919f7a5cfa0c510e0b9e58f..9fac52ae27774ee8b07a246d9f53709204216fb8 100644 --- a/src/eigenpy.cpp +++ b/src/eigenpy.cpp @@ -45,6 +45,17 @@ namespace eigenpy bp::def("switchToNumpyMatrix",&NumpyType::switchToNumpyMatrix, "Set the conversion from Eigen::Matrix to numpy.matrix."); + bp::def("sharedMemory", + (void (*)(const bool))NumpyType::sharedMemory, + bp::arg("value"), + "Share the memory when converting Eigen::Matrix to numpy.array."); + + bp::def("sharedMemory", + (bool (*)())NumpyType::sharedMemory, + "Status of the shared memory when converting Eigen::Matrix to numpy.array.\n" + "If True, the memory is shared when converting an Eigen::Matrix to a numpy.array.\n" + "Otherwise, a deep copy of the Eigen::Matrix is performed"); + bp::def("seed",&seed,bp::arg("seed_value"), "Initialize the pseudo-random number generator with the argument seed_value.");