Merge pull request #172 from jcarpent/devel

Authorize the sharing of memory between Eigen and Numpy

Author: jcarpent

cmake

@@ -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);
+      }
     }
   };
 

include/eigenpy/numpy-allocator.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;
   };
 }
 

include/eigenpy/numpy-type.hpp

@@ -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="[email protected]">Justin Carpentier</maintainer>
   <maintainer email="[email protected]">Wolfgang Merkt</maintainer>

package.xml

@@ -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.");
 

src/eigenpy.cpp

@@ -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)
@@ -22,13 +23,41 @@ 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
 
 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)
+
+