From 0334425f10b4f1c8cec7bfae23cd11af3225153f Mon Sep 17 00:00:00 2001
From: Justin Carpentier <justin.carpentier@inria.fr>
Date: Wed, 18 Mar 2020 18:09:15 +0100
Subject: [PATCH] core: add the possibility to share or not the memory between
Numpy and Eigen
---
include/eigenpy/numpy-allocator.hpp | 38 ++++++++++++++++++++---------
include/eigenpy/numpy-type.hpp | 14 +++++++++++
src/eigenpy.cpp | 11 +++++++++
3 files changed, 51 insertions(+), 12 deletions(-)
diff --git a/include/eigenpy/numpy-allocator.hpp b/include/eigenpy/numpy-allocator.hpp
index e0fd8828..fbbcab86 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 3085b55e..8b5cbb24 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 c2f49067..9fac52ae 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.");
--
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