Mar 29, 2019
diff --git a/docs/source/array_tensor.rst b/docs/source/array_tensor.rst

   The full license is in the file LICENSE, distributed with this software.

 Arraysandtensors
 ==================
 Arrays, TensorsandNumPy Views
 ===============================

 ``xtensor-python`` provides two container types wrapping numpy arrays: ``pyarray`` and ``pytensor``. They are the counterparts
 to ``xarray`` and ``xtensor`` containers.
 the shape of the ``pytensor`` upon creation. As a consequence, reshapes are not reflected across languages. However, this drawback
 is offset by a more effective computation of shape and broadcast.

 NumPy views
 -----------

 If you are trying to call a xtensor function with a NumPy view, you might read the following:
 "passing container with wrong strides for static layout". This means, that the *static layout*
 of the pytensor does not match the layout of the NumPy array (or view) that you are using to
 call the function.

 One fix for this is to choose the ``dynamic`` layout for your pyarray or pytensor:

 .. code::

    void my_function(xt::pyarray<double, xt::layout_type::dynamic> input)

 When choosing the dynamic layout, you can pass any NumPy container (with Fortran order, or
 an arbitrary view).
 Note that iterators on a pyarray with dynamic layout are generally slower!

diff --git a/include/xtensor-python/pyarray.hpp b/include/xtensor-python/pyarray.hpp

 namespace xt
 {
    template <class T, layout_type L = layout_type::dynamic>
    template <class T, layout_type L = layout_type::row_major>
    class pyarray;
 }


        if (!tmp)
        {
            throw std::runtime_error("NumPy: unable to create ndarray");
            throw std::runtime_error("pyarray: unable to create ndarray");
        }

        this->m_ptr = tmp.release().ptr();

        if (!tmp)
        {
            throw std::runtime_error("NumPy: unable to create ndarray");
            throw std::runtime_error("pyarray: unable to create ndarray");
        }

        this->m_ptr = tmp.release().ptr();

        if (L != layout_type::dynamic && !do_strides_match(m_shape, m_strides, L, 1))
        {
            throw std::runtime_error("NumPy: passing container withbad strides for layout (is ita view?).");
            throw std::runtime_error("pyarray: passing container withwrong strides forstaticlayout. If you are trying to passa view, set the pytensor layout template parameter to `layout_type::dynamic`, or `layout_type::column_major` for col major.");
        }

        m_backstrides = backstrides_type(*this);
diff --git a/include/xtensor-python/pytensor.hpp b/include/xtensor-python/pytensor.hpp

 namespace xt
 {
    template <class T, std::size_t N, layout_type L = layout_type::dynamic>
    template <class T, std::size_t N, layout_type L = layout_type::row_major>
    class pytensor;
 }


        if (!tmp)
        {
            throw std::runtime_error("NumPy: unable to create ndarray");
            throw std::runtime_error("pytensor: unable to create ndarray");
        }

        this->m_ptr = tmp.release().ptr();

        if (PyArray_NDIM(this->python_array()) != N)
        {
            throw std::runtime_error("NumPy: ndarray has incorrect number of dimensions");
            throw std::runtime_error("pytensor: ndarray has incorrect number of dimensions");
        }

        std::copy(PyArray_DIMS(this->python_array()), PyArray_DIMS(this->python_array()) + N, m_shape.begin());

        if (L != layout_type::dynamic && !do_strides_match(m_shape, m_strides, L, 1))
        {
            throw std::runtime_error("NumPy: passing container withbad strides for layout (is ita view?).");
            throw std::runtime_error("pytensor: passing container withwrong strides forstaticlayout. If you are trying to passa view, set the pytensor layout template parameter to `layout_type::dynamic`, or `layout_type::column_major` for col major.");
        }

        m_storage = storage_type(reinterpret_cast<pointer>(PyArray_DATA(this->python_array())),
Original file line number	Diff line number	Diff line change
Expand Up		@@ -4,8 +4,8 @@

		The full license is in the file LICENSE, distributed with this software.

		Arraysandtensors
		==================
		Arrays, TensorsandNumPy Views
		===============================

		``xtensor-python`` provides two container types wrapping numpy arrays: ``pyarray`` and ``pytensor``. They are the counterparts
		to ``xarray`` and ``xtensor`` containers.
Expand All		@@ -25,3 +25,21 @@ Like ``xtensor``, ``pytensor`` has a static stack-allocated shape. This means th
		the shape of the ``pytensor`` upon creation. As a consequence, reshapes are not reflected across languages. However, this drawback
		is offset by a more effective computation of shape and broadcast.

		NumPy views
		-----------

		If you are trying to call a xtensor function with a NumPy view, you might read the following:
		"passing container with wrong strides for static layout". This means, that the static layout
		of the pytensor does not match the layout of the NumPy array (or view) that you are using to
		call the function.

		One fix for this is to choose the ``dynamic`` layout for your pyarray or pytensor:

		.. code::

		void my_function(xt::pyarray<double, xt::layout_type::dynamic> input)

		When choosing the dynamic layout, you can pass any NumPy container (with Fortran order, or
		an arbitrary view).
		Note that iterators on a pyarray with dynamic layout are generally slower!
Original file line number	Diff line number	Diff line change
Expand Up		@@ -23,7 +23,7 @@

		namespace xt
		{
		template <class T, layout_type L = layout_type::dynamic>
		template <class T, layout_type L = layout_type::row_major>
		class pyarray;
		}

Expand DownExpand Up		@@ -682,7 +682,7 @@ namespace xt

		if (!tmp)
		{
		throw std::runtime_error("NumPy: unable to create ndarray");
		throw std::runtime_error("pyarray: unable to create ndarray");
		}

		this->m_ptr = tmp.release().ptr();
Expand DownExpand Up		@@ -771,7 +771,7 @@ namespace xt

		if (!tmp)
		{
		throw std::runtime_error("NumPy: unable to create ndarray");
		throw std::runtime_error("pyarray: unable to create ndarray");
		}

		this->m_ptr = tmp.release().ptr();
Expand All		@@ -793,7 +793,7 @@ namespace xt

		if (L != layout_type::dynamic && !do_strides_match(m_shape, m_strides, L, 1))
		{
		throw std::runtime_error("NumPy: passing container withbad strides for layout (is ita view?).");
		throw std::runtime_error("pyarray: passing container withwrong strides forstaticlayout. If you are trying to passa view, set the pytensor layout template parameter to `layout_type::dynamic`, or `layout_type::column_major` for col major.");
		}

		m_backstrides = backstrides_type(*this);
Expand Down
Original file line number	Diff line number	Diff line change
Expand Up		@@ -24,7 +24,7 @@

		namespace xt
		{
		template <class T, std::size_t N, layout_type L = layout_type::dynamic>
		template <class T, std::size_t N, layout_type L = layout_type::row_major>
		class pytensor;
		}

Expand DownExpand Up		@@ -431,7 +431,7 @@ namespace xt

		if (!tmp)
		{
		throw std::runtime_error("NumPy: unable to create ndarray");
		throw std::runtime_error("pytensor: unable to create ndarray");
		}

		this->m_ptr = tmp.release().ptr();
Expand All		@@ -452,7 +452,7 @@ namespace xt

		if (PyArray_NDIM(this->python_array()) != N)
		{
		throw std::runtime_error("NumPy: ndarray has incorrect number of dimensions");
		throw std::runtime_error("pytensor: ndarray has incorrect number of dimensions");
		}

		std::copy(PyArray_DIMS(this->python_array()), PyArray_DIMS(this->python_array()) + N, m_shape.begin());
Expand All		@@ -462,7 +462,7 @@ namespace xt

		if (L != layout_type::dynamic && !do_strides_match(m_shape, m_strides, L, 1))
		{
		throw std::runtime_error("NumPy: passing container withbad strides for layout (is ita view?).");
		throw std::runtime_error("pytensor: passing container withwrong strides forstaticlayout. If you are trying to passa view, set the pytensor layout template parameter to `layout_type::dynamic`, or `layout_type::column_major` for col major.");
		}

		m_storage = storage_type(reinterpret_cast<pointer>(PyArray_DATA(this->python_array())),
Expand Down