diff --git a/cmake b/cmake
index 93ec987ecdc016039c8731e203943e5a83eb96d5..321eb1ccf1d94570eb564f3659b13ef3ef82239e 160000
--- a/cmake
+++ b/cmake
@@ -1 +1 @@
-Subproject commit 93ec987ecdc016039c8731e203943e5a83eb96d5
+Subproject commit 321eb1ccf1d94570eb564f3659b13ef3ef82239e
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/package.xml b/package.xml
index b713cf3ab74423c42deeb4ca66dc6d6a016f7d78..cc7c6eb2a6cd8f3d58ae23346774393c21dbac19 100644
--- a/package.xml
+++ b/package.xml
@@ -1,7 +1,7 @@
<?xml version="1.0"?>
<package format="2">
<name>eigenpy</name>
- <version>2.1.2</version>
+ <version>2.2.0</version>
<description>Bindings between Numpy and Eigen using Boost.Python</description>
<maintainer email="justin.carpentier@inria.fr">Justin Carpentier</maintainer>
<maintainer email="wolfgang.merkt@ed.ac.uk">Wolfgang Merkt</maintainer>
diff --git a/src/eigenpy.cpp b/src/eigenpy.cpp
index c2f49067d105f24fb919f7a5cfa0c510e0b9e58f..805581fca167dba9588500765f37b66aed62f58a 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 from Eigen to Numpy.");
+
+ bp::def("sharedMemory",
+ (bool (*)())NumpyType::sharedMemory,
+ "Status of the shared memory when converting from Eigen to Numpy.\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.");
diff --git a/unittest/python/test_return_by_ref.py b/unittest/python/test_return_by_ref.py
index 969f84672335af20ec65b1d91cb64e26c17f1830..59f6d130a9925bc772d55cd70cc5b9eed1e05e38 100644
--- a/unittest/python/test_return_by_ref.py
+++ b/unittest/python/test_return_by_ref.py
@@ -1,7 +1,8 @@
+import return_by_ref
from return_by_ref import Matrix, RowMatrix, Vector
import numpy as np
-def test(mat):
+def test_shared(mat):
m_ref = mat.ref()
m_ref.fill(0)
@@ -22,6 +23,27 @@ def test(mat):
except:
assert True
+def test_not_shared(mat):
+
+ m_ref = mat.ref()
+ m_ref.fill(100.)
+ m_copy = mat.copy()
+ assert not np.array_equal(m_ref,m_copy)
+
+ m_const_ref = mat.const_ref()
+ assert np.array_equal(m_const_ref,m_copy)
+ assert not np.array_equal(m_const_ref,m_ref)
+
+ m_ref.fill(10.)
+ assert not np.array_equal(m_ref,m_copy)
+ assert not np.array_equal(m_const_ref,m_ref)
+
+ try:
+ m_const_ref.fill(2)
+ assert True
+ except:
+ assert False
+
rows = 10
cols = 30
@@ -29,6 +51,13 @@ mat = Matrix(rows,cols)
row_mat = RowMatrix(rows,cols)
vec = Vector(rows,1)
-test(mat)
-test(row_mat)
-test(vec)
+test_shared(mat)
+test_shared(row_mat)
+test_shared(vec)
+
+return_by_ref.sharedMemory(False)
+test_not_shared(mat)
+test_not_shared(row_mat)
+test_not_shared(vec)
+
+