Rename (and move) boost.python.numpy to boost.numpy.

libs/numpy/src/Jamfile

@@ -0,0 +1,64 @@
+import python ;
+#import numpy ;
+import regex ;
+using python ;
+
+libraries = ;
+
+if [ python.configured ]
+{
+
+project boost/numpy
+  : source-location .
+#  : requirements
+  ;
+
+lib boost_python ;
+
+rule numpy-includes ( properties * )
+{
+  import feature ;
+  local python-interpreter = [ feature.get-values python.interpreter : $(properties) ] ;
+  if $(python-interpreter)
+  {
+    local full-cmd =
+      $(python-interpreter)" -c \"from numpy.distutils import misc_util; print ':'.join(misc_util.get_numpy_include_dirs())\" " ;
+    local output = [ SHELL $(full-cmd) ] ;
+    local includes = [ regex.split $(output) ":" ] ;
+    return <include>$(includes) ;
+  }
+}
+
+lib boost_numpy
+  : # sources
+    dtype.cpp
+    scalars.cpp
+    ndarray.cpp
+    matrix.cpp
+    ufunc.cpp
+    numpy.cpp
+  : # requirements
+    <library>/python//python_for_extensions
+    #<library>/boost/python//boost_python
+    <library>boost_python
+    <conditional>@numpy-includes
+  : # default build
+    <link>shared
+  : # usage requirements
+    <conditional>@numpy-includes
+  ;
+
+libraries += boost_numpy ;  
+
+}
+else if ! ( --without-python in [ modules.peek : ARGV ] )
+{
+    message boost_numpy
+        : "warning: No python installation configured and autoconfiguration"
+        : "note: failed.  See http://www.boost.org/libs/python/doc/building.html"
+        : "note: for configuration instructions or pass --without-python to"
+        : "note: suppress this message and silently skip all Boost.NumPy targets"
+        ;
+}
+
+#boost-install $(libraries) ;

libs/numpy/src/SConscript

@@ -0,0 +1,4 @@
+Import("boost_numpy_env")
+lib = boost_numpy_env.SharedLibrary("boost_numpy", Glob("*.cpp"))
+
+Return("lib")

libs/numpy/src/dtype.cpp

@@ -0,0 +1,102 @@
+#define BOOST_NUMPY_INTERNAL
+#include <boost/numpy/internal.hpp>
+
+#define NUMPY_DTYPE_TRAITS_BUILTIN(ctype,code)                          \
+template <> struct dtype_traits<ctype>				        \
+{									\
+  static dtype get()							\
+  {									\
+    return dtype(python::detail::new_reference				\
+      (reinterpret_cast<PyObject*>(PyArray_DescrFromType(code))));      \
+  }									\
+};									\
+template dtype dtype::get_builtin<ctype>()
+
+#define NUMPY_DTYPE_TRAITS_COMPLEX(creal, ctype, code)                  \
+template <> struct dtype_traits< std::complex<creal> >		        \
+{									\
+  static dtype get()							\
+  {									\
+    if (sizeof(ctype) != sizeof(std::complex<creal>))			\
+    {									\
+      PyErr_SetString(PyExc_TypeError, "Cannot reinterpret std::complex<T> as T[2]"); \
+      python::throw_error_already_set();				\
+    }									\
+    return dtype(python::detail::new_reference				\
+      (reinterpret_cast<PyObject*>(PyArray_DescrFromType(code))));      \
+  }									\
+};									\
+template dtype dtype::get_builtin< std::complex<creal> >()
+
+namespace boost 
+{
+namespace python 
+{
+namespace converter 
+{
+NUMPY_OBJECT_MANAGER_TRAITS_IMPL(PyArrayDescr_Type, numpy::dtype)
+} // namespace boost::python::converter
+} // namespace boost::python
+
+namespace numpy 
+{
+
+template <typename T> struct dtype_traits;
+
+python::detail::new_reference dtype::convert(python::object const & arg, bool align) 
+{
+  PyArray_Descr* obj=NULL;
+  if (align)
+  {
+    if (PyArray_DescrAlignConverter(arg.ptr(), &obj) < 0)
+      python::throw_error_already_set();
+  } 
+  else
+  {
+    if (PyArray_DescrConverter(arg.ptr(), &obj) < 0)
+      python::throw_error_already_set();
+  }
+  return python::detail::new_reference(reinterpret_cast<PyObject*>(obj));
+}
+
+int dtype::get_itemsize() const { return reinterpret_cast<PyArray_Descr*>(ptr())->elsize;}
+
+template <typename T>
+dtype dtype::get_builtin() { return dtype_traits<T>::get(); }
+
+NUMPY_DTYPE_TRAITS_BUILTIN(bool, NPY_BOOL);
+NUMPY_DTYPE_TRAITS_BUILTIN(npy_ubyte, NPY_UBYTE);
+NUMPY_DTYPE_TRAITS_BUILTIN(npy_byte, NPY_BYTE);
+NUMPY_DTYPE_TRAITS_BUILTIN(npy_ushort, NPY_USHORT);
+NUMPY_DTYPE_TRAITS_BUILTIN(npy_short, NPY_SHORT);
+NUMPY_DTYPE_TRAITS_BUILTIN(npy_uint, NPY_UINT);
+NUMPY_DTYPE_TRAITS_BUILTIN(npy_int, NPY_INT);
+NUMPY_DTYPE_TRAITS_BUILTIN(npy_ulong, NPY_ULONG);
+NUMPY_DTYPE_TRAITS_BUILTIN(npy_long, NPY_LONG);
+NUMPY_DTYPE_TRAITS_BUILTIN(npy_longlong, NPY_LONGLONG);
+NUMPY_DTYPE_TRAITS_BUILTIN(npy_float, NPY_FLOAT);
+NUMPY_DTYPE_TRAITS_BUILTIN(npy_double, NPY_DOUBLE);
+NUMPY_DTYPE_TRAITS_BUILTIN(npy_longdouble, NPY_LONGDOUBLE);
+NUMPY_DTYPE_TRAITS_BUILTIN(npy_cfloat, NPY_CFLOAT);
+NUMPY_DTYPE_TRAITS_BUILTIN(npy_cdouble, NPY_CDOUBLE);
+NUMPY_DTYPE_TRAITS_BUILTIN(npy_clongdouble, NPY_CLONGDOUBLE);
+NUMPY_DTYPE_TRAITS_COMPLEX(float, npy_cfloat, NPY_CFLOAT);
+NUMPY_DTYPE_TRAITS_COMPLEX(double, npy_cdouble, NPY_CDOUBLE);
+NUMPY_DTYPE_TRAITS_COMPLEX(long double, npy_clongdouble, NPY_CLONGDOUBLE);
+
+#if 0
+template <> struct dtype_traits<bool> 
+{
+  static dtype get()
+  {
+    if (sizeof(bool) == sizeof(npy_ubyte)) return dtype_traits<npy_ubyte>::get();
+    if (sizeof(bool) == sizeof(npy_bool)) return dtype_traits<npy_bool>::get();
+    PyErr_SetString(PyExc_TypeError, "Cannot determine numpy dtype corresponding to C++ bool.");
+    python::throw_error_already_set();
+  }
+};
+template dtype dtype::get_builtin<bool>();
+#endif
+
+} // namespace boost::numpy
+} // namespace boost

libs/numpy/src/matrix.cpp

@@ -0,0 +1,63 @@
+#define BOOST_NUMPY_INTERNAL
+#include <boost/numpy/internal.hpp>
+#include <boost/numpy/matrix.hpp>
+
+namespace boost 
+{
+namespace numpy 
+{ 
+namespace detail 
+{
+inline python::object get_matrix_type() 
+{
+  python::object module = python::import("numpy");
+  return module.attr("matrix");
+}
+} // namespace boost::numpy::detail
+} // namespace boost::numpy
+
+namespace python
+{
+namespace converter 
+{
+
+PyTypeObject const * object_manager_traits<numpy::matrix>::get_pytype()
+{
+  return reinterpret_cast<PyTypeObject*>(numpy::detail::get_matrix_type().ptr());
+}
+
+} // namespace boost::python::converter
+} // namespace boost::python
+
+namespace numpy 
+{
+
+python::object matrix::construct(python::object const & obj, dtype const & dt, bool copy) 
+{
+  return numpy::detail::get_matrix_type()(obj, dt, copy);
+}
+
+python::object matrix::construct(python::object const & obj, bool copy) 
+{
+  return numpy::detail::get_matrix_type()(obj, object(), copy);
+}
+
+matrix matrix::view(dtype const & dt) const 
+{
+  return matrix(python::detail::new_reference
+    (PyObject_CallMethod(this->ptr(), const_cast<char*>("view"), const_cast<char*>("O"), dt.ptr())));
+}
+
+matrix matrix::copy() const 
+{
+  return matrix(python::detail::new_reference
+    (PyObject_CallMethod(this->ptr(), const_cast<char*>("copy"), const_cast<char*>(""))));
+}
+
+matrix matrix::transpose() const 
+{
+  return matrix(python::extract<matrix>(ndarray::transpose()));
+}
+
+} // namespace boost::numpy
+} // namespace boost

libs/numpy/src/ndarray.cpp

@@ -0,0 +1,269 @@
+#define BOOST_NUMPY_INTERNAL
+#include <boost/numpy/internal.hpp>
+
+namespace boost 
+{ 
+namespace python 
+{
+namespace converter 
+{
+NUMPY_OBJECT_MANAGER_TRAITS_IMPL(PyArray_Type, numpy::ndarray)
+} // namespace boost::python::converter
+} // namespace boost::python
+
+namespace numpy 
+{
+namespace detail 
+{
+
+ndarray::bitflag numpy_to_bitflag(int const f) 
+{
+  ndarray::bitflag r = ndarray::NONE;
+  if (f & NPY_C_CONTIGUOUS) r = (r | ndarray::C_CONTIGUOUS);
+  if (f & NPY_F_CONTIGUOUS) r = (r | ndarray::F_CONTIGUOUS);
+  if (f & NPY_ALIGNED) r = (r | ndarray::ALIGNED);
+  if (f & NPY_WRITEABLE) r = (r | ndarray::WRITEABLE);
+  return r;
+}
+
+int const bitflag_to_numpy(ndarray::bitflag f) 
+{
+  int r = 0;
+  if (f & ndarray::C_CONTIGUOUS) r |= NPY_C_CONTIGUOUS;
+  if (f & ndarray::F_CONTIGUOUS) r |= NPY_F_CONTIGUOUS;
+  if (f & ndarray::ALIGNED) r |= NPY_ALIGNED;
+  if (f & ndarray::WRITEABLE) r |= NPY_WRITEABLE;
+  return r;
+}
+
+bool is_c_contiguous(std::vector<Py_intptr_t> const & shape,
+		     std::vector<Py_intptr_t> const & strides,
+		     int itemsize)
+{
+  std::vector<Py_intptr_t>::const_reverse_iterator j = strides.rbegin();
+  int total = itemsize;
+  for (std::vector<Py_intptr_t>::const_reverse_iterator i = shape.rbegin(); i != shape.rend(); ++i, ++j) 
+  {
+    if (total != *j) return false;
+    total *= (*i);
+  }
+  return true;
+}
+
+bool is_f_contiguous(std::vector<Py_intptr_t> const & shape,
+		     std::vector<Py_intptr_t> const & strides,
+		     int itemsize)
+{
+  std::vector<Py_intptr_t>::const_iterator j = strides.begin();
+  int total = itemsize;
+  for (std::vector<Py_intptr_t>::const_iterator i = shape.begin(); i != shape.end(); ++i, ++j)
+  {
+    if (total != *j) return false;
+    total *= (*i);
+  }
+  return true;
+}
+
+bool is_aligned(std::vector<Py_intptr_t> const & strides,
+		int itemsize)
+{
+  for (std::vector<Py_intptr_t>::const_iterator i = strides.begin(); i != strides.end(); ++i) 
+  {
+    if (*i % itemsize) return false;
+  }
+  return true;
+}
+
+inline PyArray_Descr * incref_dtype(dtype const & dt) 
+{
+  Py_INCREF(dt.ptr());
+  return reinterpret_cast<PyArray_Descr*>(dt.ptr());
+}
+
+ndarray from_data_impl(void * data, 
+		       dtype const & dt, 
+		       python::object const & shape,
+		       python::object const & strides,
+		       python::object const & owner,
+		       bool writeable)
+{
+  std::vector<Py_intptr_t> shape_(len(shape));
+  std::vector<Py_intptr_t> strides_(len(strides));
+  if (shape_.size() != strides_.size()) 
+  {
+    PyErr_SetString(PyExc_ValueError, "Length of shape and strides arrays do not match.");
+    python::throw_error_already_set();
+  }
+  for (std::size_t i = 0; i < shape_.size(); ++i) 
+  {
+    shape_[i] = python::extract<Py_intptr_t>(shape[i]);
+    strides_[i] = python::extract<Py_intptr_t>(strides[i]);
+  }
+  return from_data_impl(data, dt, shape_, strides_, owner, writeable);
+}
+
+ndarray from_data_impl(void * data, 
+		       dtype const & dt, 
+		       std::vector<Py_intptr_t> const & shape,
+		       std::vector<Py_intptr_t> const & strides,
+		       python::object const & owner,
+		       bool writeable)
+{
+  if (shape.size() != strides.size()) 
+  {
+    PyErr_SetString(PyExc_ValueError, "Length of shape and strides arrays do not match.");
+    python::throw_error_already_set();
+  }
+  int itemsize = dt.get_itemsize();
+  int flags = 0;
+  if (writeable) flags |= NPY_WRITEABLE;
+  if (is_c_contiguous(shape, strides, itemsize)) flags |= NPY_C_CONTIGUOUS;
+  if (is_f_contiguous(shape, strides, itemsize)) flags |= NPY_F_CONTIGUOUS;
+  if (is_aligned(strides, itemsize)) flags |= NPY_ALIGNED;
+  ndarray r(python::detail::new_reference
+    (PyArray_NewFromDescr(&PyArray_Type,
+			  incref_dtype(dt),
+			  shape.size(),
+			  const_cast<Py_intptr_t*>(&shape.front()),
+			  const_cast<Py_intptr_t*>(&strides.front()),
+			  data,
+			  flags,
+			  NULL)));
+    r.set_base(owner);
+    return r;
+}
+
+} // namespace detail
+
+ndarray ndarray::view(dtype const & dt) const
+{
+  return ndarray(python::detail::new_reference
+    (PyObject_CallMethod(this->ptr(), const_cast<char*>("view"), const_cast<char*>("O"), dt.ptr())));
+}
+
+ndarray ndarray::copy() const 
+{
+  return ndarray(python::detail::new_reference
+    (PyObject_CallMethod(this->ptr(), const_cast<char*>("copy"), const_cast<char*>(""))));
+}
+
+dtype ndarray::get_dtype() const 
+{
+  return dtype(python::detail::borrowed_reference(get_struct()->descr));
+}
+
+python::object ndarray::get_base() const 
+{
+  if (get_struct()->base == NULL) return object();
+  return python::object(python::detail::borrowed_reference(get_struct()->base));
+}
+
+void ndarray::set_base(object const & base) 
+{
+  Py_XDECREF(get_struct()->base);
+  if (base != object()) 
+  {
+    Py_INCREF(base.ptr());
+    get_struct()->base = base.ptr();
+  }
+  else
+  {
+    get_struct()->base = NULL;
+  }
+}
+
+ndarray::bitflag const ndarray::get_flags() const 
+{
+  return numpy::detail::numpy_to_bitflag(get_struct()->flags);
+}
+
+ndarray ndarray::transpose() const 
+{
+  return ndarray(python::detail::new_reference
+    (PyArray_Transpose(reinterpret_cast<PyArrayObject*>(this->ptr()), NULL)));
+}
+
+ndarray ndarray::squeeze() const 
+{
+  return ndarray(python::detail::new_reference
+    (PyArray_Squeeze(reinterpret_cast<PyArrayObject*>(this->ptr()))));
+}
+
+ndarray ndarray::reshape(python::tuple const & shape) const 
+{
+  return ndarray(python::detail::new_reference
+    (PyArray_Reshape(reinterpret_cast<PyArrayObject*>(this->ptr()), shape.ptr())));
+}
+
+python::object ndarray::scalarize() const 
+{
+  Py_INCREF(ptr());
+  return python::object(python::detail::new_reference(PyArray_Return(reinterpret_cast<PyArrayObject*>(ptr()))));
+}
+
+ndarray zeros(python::tuple const & shape, dtype const & dt) 
+{
+  int nd = len(shape);
+  Py_intptr_t dims[nd];
+  for (int n=0; n<nd; ++n) dims[n] = python::extract<Py_intptr_t>(shape[n]);
+  return ndarray(python::detail::new_reference
+    (PyArray_Zeros(nd, dims, detail::incref_dtype(dt), 0)));
+}
+
+ndarray zeros(int nd, Py_intptr_t const * shape, dtype const & dt) 
+{
+  return ndarray(python::detail::new_reference
+    (PyArray_Zeros(nd, const_cast<Py_intptr_t*>(shape), detail::incref_dtype(dt), 0)));
+}
+
+ndarray empty(python::tuple const & shape, dtype const & dt) 
+{
+  int nd = len(shape);
+  Py_intptr_t dims[nd];
+  for (int n=0; n<nd; ++n) dims[n] = python::extract<Py_intptr_t>(shape[n]);
+  return ndarray(python::detail::new_reference
+    (PyArray_Empty(nd, dims, detail::incref_dtype(dt), 0)));    
+}
+
+ndarray empty(int nd, Py_intptr_t const * shape, dtype const & dt)
+{
+  return ndarray(python::detail::new_reference
+    (PyArray_Empty(nd, const_cast<Py_intptr_t*>(shape), detail::incref_dtype(dt), 0)));
+}
+
+ndarray array(python::object const & obj) 
+{
+  return ndarray(python::detail::new_reference
+    (PyArray_FromAny(obj.ptr(), NULL, 0, 0, NPY_ENSUREARRAY, NULL)));
+}
+
+ndarray array(python::object const & obj, dtype const & dt) 
+{
+  return ndarray(python::detail::new_reference
+    (PyArray_FromAny(obj.ptr(), detail::incref_dtype(dt), 0, 0, NPY_ENSUREARRAY, NULL)));
+}
+
+ndarray from_object(python::object const & obj, dtype const & dt, int nd_min, int nd_max, ndarray::bitflag flags)
+{
+  int requirements = detail::bitflag_to_numpy(flags);
+  return ndarray(python::detail::new_reference
+    (PyArray_FromAny(obj.ptr(),
+		     detail::incref_dtype(dt),
+		     nd_min, nd_max,
+		     requirements,
+		     NULL)));
+}
+
+ndarray from_object(python::object const & obj, int nd_min, int nd_max, ndarray::bitflag flags) 
+{
+  int requirements = detail::bitflag_to_numpy(flags);
+  return ndarray(python::detail::new_reference
+    (PyArray_FromAny(obj.ptr(),
+		     NULL,
+		     nd_min, nd_max,
+		     requirements,
+		     NULL)));
+}
+
+}
+}

libs/numpy/src/numpy.cpp

@@ -0,0 +1,16 @@
+#define BOOST_NUMPY_INTERNAL_MAIN
+#include <boost/numpy/internal.hpp>
+
+namespace boost 
+{
+namespace numpy 
+{
+
+void initialize() 
+{
+  import_array();
+  import_ufunc();
+}
+
+}
+}

libs/numpy/src/scalars.cpp

@@ -0,0 +1,35 @@
+#define BOOST_NUMPY_INTERNAL
+#include <boost/numpy/internal.hpp>
+
+namespace boost 
+{ 
+namespace python 
+{
+namespace converter 
+{
+NUMPY_OBJECT_MANAGER_TRAITS_IMPL(PyVoidArrType_Type, numpy::void_)
+} // namespace boost::python::converter
+} // namespace boost::python
+
+namespace numpy 
+{
+
+void_::void_(Py_ssize_t size)
+  : object(python::detail::new_reference
+      (PyObject_CallFunction((PyObject*)&PyVoidArrType_Type, const_cast<char*>("i"), size)))
+{}
+
+void_ void_::view(dtype const & dt) const 
+{
+  return void_(python::detail::new_reference
+    (PyObject_CallMethod(this->ptr(), const_cast<char*>("view"), const_cast<char*>("O"), dt.ptr())));
+}
+
+void_ void_::copy() const 
+{
+  return void_(python::detail::new_reference
+    (PyObject_CallMethod(this->ptr(), const_cast<char*>("copy"), const_cast<char*>(""))));
+}
+
+}
+}

libs/numpy/src/ufunc.cpp

@@ -0,0 +1,64 @@
+#define BOOST_NUMPY_INTERNAL
+#include <boost/numpy/internal.hpp>
+#include <boost/numpy/ufunc.hpp>
+
+namespace boost 
+{
+namespace python 
+{
+namespace converter 
+{
+NUMPY_OBJECT_MANAGER_TRAITS_IMPL(PyArrayMultiIter_Type, numpy::multi_iter)
+} // namespace boost::python::converter
+} // namespace boost::python
+
+namespace numpy 
+{
+
+multi_iter make_multi_iter(python::object const & a1) 
+{
+  return multi_iter(python::detail::new_reference(PyArray_MultiIterNew(1, a1.ptr())));
+}
+
+multi_iter make_multi_iter(python::object const & a1, python::object const & a2) 
+{
+  return multi_iter(python::detail::new_reference(PyArray_MultiIterNew(2, a1.ptr(), a2.ptr())));
+}
+
+multi_iter make_multi_iter(python::object const & a1, python::object const & a2, python::object const & a3) 
+{
+  return multi_iter(python::detail::new_reference(PyArray_MultiIterNew(3, a1.ptr(), a2.ptr(), a3.ptr())));
+}
+
+void multi_iter::next() 
+{
+  PyArray_MultiIter_NEXT(ptr());
+}
+
+bool multi_iter::not_done() const 
+{
+  return PyArray_MultiIter_NOTDONE(ptr());
+}
+
+char * multi_iter::get_data(int i) const 
+{
+  return reinterpret_cast<char*>(PyArray_MultiIter_DATA(ptr(), i));
+}
+
+int const multi_iter::get_nd() const 
+{
+  return reinterpret_cast<PyArrayMultiIterObject*>(ptr())->nd;
+}
+
+Py_intptr_t const * multi_iter::get_shape() const 
+{
+  return reinterpret_cast<PyArrayMultiIterObject*>(ptr())->dimensions;
+}
+
+Py_intptr_t const multi_iter::shape(int n) const 
+{
+  return reinterpret_cast<PyArrayMultiIterObject*>(ptr())->dimensions[n];
+}
+
+}
+}