Restoring authorship annotation for <[email protected]>. Commit 2 of 2.

1 files changed, 301 insertions, 301 deletions

diff --git a/contrib/restricted/boost/libs/python/src/numpy/ndarray.cpp b/contrib/restricted/boost/libs/python/src/numpy/ndarray.cpp
index 895f33968de..af09ecc3381 100644
--- a/contrib/restricted/boost/libs/python/src/numpy/ndarray.cpp
+++ b/contrib/restricted/boost/libs/python/src/numpy/ndarray.cpp
@@ -1,301 +1,301 @@
-// Copyright Jim Bosch 2010-2012. 
-// Copyright Stefan Seefeld 2016. 
-// Distributed under the Boost Software License, Version 1.0. 
-// (See accompanying file LICENSE_1_0.txt or copy at 
-// http://www.boost.org/LICENSE_1_0.txt) 
- 
-#define BOOST_PYTHON_NUMPY_INTERNAL 
-#include <boost/python/numpy/internal.hpp> 
-#include <boost/scoped_array.hpp> 
- 
-namespace boost { namespace python { 
-namespace converter  
-{ 
-NUMPY_OBJECT_MANAGER_TRAITS_IMPL(PyArray_Type, numpy::ndarray) 
-} // namespace boost::python::converter 
- 
-namespace numpy  
-{ 
-namespace detail  
-{ 
- 
-ndarray::bitflag numpy_to_bitflag(int const f) 
-{ 
-  ndarray::bitflag r = ndarray::NONE; 
-  if (f & NPY_ARRAY_C_CONTIGUOUS) r = (r | ndarray::C_CONTIGUOUS); 
-  if (f & NPY_ARRAY_F_CONTIGUOUS) r = (r | ndarray::F_CONTIGUOUS); 
-  if (f & NPY_ARRAY_ALIGNED) r = (r | ndarray::ALIGNED); 
-  if (f & NPY_ARRAY_WRITEABLE) r = (r | ndarray::WRITEABLE); 
-  return r; 
-} 
- 
-int bitflag_to_numpy(ndarray::bitflag f) 
-{ 
-  int r = 0; 
-  if (f & ndarray::C_CONTIGUOUS) r |= NPY_ARRAY_C_CONTIGUOUS; 
-  if (f & ndarray::F_CONTIGUOUS) r |= NPY_ARRAY_F_CONTIGUOUS; 
-  if (f & ndarray::ALIGNED) r |= NPY_ARRAY_ALIGNED; 
-  if (f & ndarray::WRITEABLE) r |= NPY_ARRAY_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_ARRAY_WRITEABLE; 
-  if (is_c_contiguous(shape, strides, itemsize)) flags |= NPY_ARRAY_C_CONTIGUOUS; 
-  if (is_f_contiguous(shape, strides, itemsize)) flags |= NPY_ARRAY_F_CONTIGUOUS; 
-  if (is_aligned(strides, itemsize)) flags |= NPY_ARRAY_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 
- 
-namespace { 
-    int normalize_index(int n,int nlim) // wraps [-nlim:nlim) into [0:nlim), throw IndexError otherwise 
-    { 
-        if (n<0) 
-            n += nlim; // negative indices work backwards from end 
-        if (n < 0 || n >= nlim) 
-        { 
-            PyErr_SetObject(PyExc_IndexError, Py_None); 
-            throw_error_already_set(); 
-        } 
-        return n; 
-    } 
-} 
- 
-Py_intptr_t ndarray::shape(int n) const 
-{ 
-    return get_shape()[normalize_index(n,get_nd())]; 
-} 
- 
-Py_intptr_t ndarray::strides(int n) const 
-{ 
-    return get_strides()[normalize_index(n,get_nd())]; 
-} 
- 
-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::astype(dtype const & dt) const 
-{ 
-  return ndarray(python::detail::new_reference 
-    (PyObject_CallMethod(this->ptr(), const_cast<char*>("astype"), 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.ptr()) 
-  { 
-    Py_INCREF(base.ptr()); 
-    get_struct()->base = base.ptr(); 
-  } 
-  else 
-  { 
-    get_struct()->base = NULL; 
-  } 
-} 
- 
-ndarray::bitflag 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); 
-  boost::scoped_array<Py_intptr_t> dims(new Py_intptr_t[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.get(), 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); 
-  boost::scoped_array<Py_intptr_t> dims(new Py_intptr_t[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.get(), 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_ARRAY_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_ARRAY_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))); 
-} 
- 
-}}} // namespace boost::python::numpy 
+// Copyright Jim Bosch 2010-2012.
+// Copyright Stefan Seefeld 2016.
+// Distributed under the Boost Software License, Version 1.0.
+// (See accompanying file LICENSE_1_0.txt or copy at
+// http://www.boost.org/LICENSE_1_0.txt)
+
+#define BOOST_PYTHON_NUMPY_INTERNAL
+#include <boost/python/numpy/internal.hpp>
+#include <boost/scoped_array.hpp>
+
+namespace boost { namespace python {
+namespace converter 
+{
+NUMPY_OBJECT_MANAGER_TRAITS_IMPL(PyArray_Type, numpy::ndarray)
+} // namespace boost::python::converter
+
+namespace numpy 
+{
+namespace detail 
+{
+
+ndarray::bitflag numpy_to_bitflag(int const f)
+{
+  ndarray::bitflag r = ndarray::NONE;
+  if (f & NPY_ARRAY_C_CONTIGUOUS) r = (r | ndarray::C_CONTIGUOUS);
+  if (f & NPY_ARRAY_F_CONTIGUOUS) r = (r | ndarray::F_CONTIGUOUS);
+  if (f & NPY_ARRAY_ALIGNED) r = (r | ndarray::ALIGNED);
+  if (f & NPY_ARRAY_WRITEABLE) r = (r | ndarray::WRITEABLE);
+  return r;
+}
+
+int bitflag_to_numpy(ndarray::bitflag f)
+{
+  int r = 0;
+  if (f & ndarray::C_CONTIGUOUS) r |= NPY_ARRAY_C_CONTIGUOUS;
+  if (f & ndarray::F_CONTIGUOUS) r |= NPY_ARRAY_F_CONTIGUOUS;
+  if (f & ndarray::ALIGNED) r |= NPY_ARRAY_ALIGNED;
+  if (f & ndarray::WRITEABLE) r |= NPY_ARRAY_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_ARRAY_WRITEABLE;
+  if (is_c_contiguous(shape, strides, itemsize)) flags |= NPY_ARRAY_C_CONTIGUOUS;
+  if (is_f_contiguous(shape, strides, itemsize)) flags |= NPY_ARRAY_F_CONTIGUOUS;
+  if (is_aligned(strides, itemsize)) flags |= NPY_ARRAY_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
+
+namespace {
+    int normalize_index(int n,int nlim) // wraps [-nlim:nlim) into [0:nlim), throw IndexError otherwise
+    {
+        if (n<0)
+            n += nlim; // negative indices work backwards from end
+        if (n < 0 || n >= nlim)
+        {
+            PyErr_SetObject(PyExc_IndexError, Py_None);
+            throw_error_already_set();
+        }
+        return n;
+    }
+}
+
+Py_intptr_t ndarray::shape(int n) const
+{
+    return get_shape()[normalize_index(n,get_nd())];
+}
+
+Py_intptr_t ndarray::strides(int n) const
+{
+    return get_strides()[normalize_index(n,get_nd())];
+}
+
+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::astype(dtype const & dt) const
+{
+  return ndarray(python::detail::new_reference
+    (PyObject_CallMethod(this->ptr(), const_cast<char*>("astype"), 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.ptr())
+  {
+    Py_INCREF(base.ptr());
+    get_struct()->base = base.ptr();
+  }
+  else
+  {
+    get_struct()->base = NULL;
+  }
+}
+
+ndarray::bitflag 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);
+  boost::scoped_array<Py_intptr_t> dims(new Py_intptr_t[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.get(), 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);
+  boost::scoped_array<Py_intptr_t> dims(new Py_intptr_t[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.get(), 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_ARRAY_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_ARRAY_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)));
+}
+
+}}} // namespace boost::python::numpy