xtensor-stack · wolfv · Mar 29, 2019
diff --git a/docs/source/array_tensor.rst b/docs/source/array_tensor.rst
@@ -4,8 +4,8 @@
 
    The full license is in the file LICENSE, distributed with this software.
 
-Arrays and tensors
-==================
+Arrays, Tensors and NumPy Views
+===============================
 
 ``xtensor-python`` provides two container types wrapping numpy arrays: ``pyarray`` and ``pytensor``. They are the counterparts
 to ``xarray`` and ``xtensor`` containers.
@@ -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!
+
diff --git a/include/xtensor-python/pyarray.hpp b/include/xtensor-python/pyarray.hpp
@@ -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;
 }
 
@@ -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();
@@ -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();
@@ -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 with bad strides for layout (is it a view?).");
+            throw std::runtime_error("pyarray: passing container with wrong strides for static layout. If you are trying to pass a 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
@@ -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;
 }
 
@@ -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();
@@ -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());
@@ -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 with bad strides for layout (is it a view?).");
+            throw std::runtime_error("pytensor: passing container with wrong strides for static layout. If you are trying to pass a 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())),