From 6c0c71907fbfdef40438831e2964dcc7b92378e8 Mon Sep 17 00:00:00 2001
From: Sylvain Corlay <sylvain.corlay@gmail.com>
Date: Mon, 15 Apr 2019 12:06:11 -0700
Subject: [PATCH] Update xtensor to 0.20.4

---
 .appveyor.yml                       | 2 +-
 .travis.yml                         | 2 +-
 README.md                           | 2 +-
 include/xtensor-python/pyarray.hpp  | 6 ++++--
 include/xtensor-python/pytensor.hpp | 2 +-
 5 files changed, 8 insertions(+), 6 deletions(-)

diff --git a/.appveyor.yml b/.appveyor.yml
index 4d871ae..1648676 100644
--- a/.appveyor.yml
+++ b/.appveyor.yml
@@ -22,7 +22,7 @@ install:
   - conda update -q conda
   - conda info -a
   - conda install gtest cmake -c conda-forge
-  - conda install pytest numpy pybind11==2.2.1 xtensor==0.20.0 -c conda-forge
+  - conda install pytest numpy pybind11==2.2.1 xtensor==0.20.4 -c conda-forge
   - "set PYTHONHOME=%MINICONDA%"
   - cmake -G "NMake Makefiles" -D CMAKE_INSTALL_PREFIX=%MINICONDA%\\Library -D BUILD_TESTS=ON -D PYTHON_EXECUTABLE=%MINICONDA%\\python.exe .
   - nmake test_xtensor_python
diff --git a/.travis.yml b/.travis.yml
index 45dd41e..77d7003 100644
--- a/.travis.yml
+++ b/.travis.yml
@@ -147,7 +147,7 @@ install:
       else
         conda install pybind11==${PYBIND11_VERSION} -c conda-forge
       fi
-    - conda install xtensor==0.20.0 -c conda-forge
+    - conda install xtensor==0.20.4 -c conda-forge
     - cmake -D DOWNLOAD_GTEST=ON -D CMAKE_INSTALL_PREFIX=$HOME/miniconda -D PYTHON_EXECUTABLE=$PY_EXE .
     - make -j2 test_xtensor_python
     - make install
diff --git a/README.md b/README.md
index 2dd7833..85d1f73 100644
--- a/README.md
+++ b/README.md
@@ -195,7 +195,7 @@ from the `docs` subdirectory.
 
 | `xtensor-python` | `xtensor` |  `pybind11`      |
 |------------------|-----------|------------------|
-| master           |  ^0.20.0  | ~2.2.1           |
+| master           |  ^0.20.4  | ~2.2.1           |
 | 0.22.x           |  ^0.19.0  | ~2.2.1           |
 | 0.21.x           |  ^0.18.0  | ~2.2.1           |
 | 0.20.x           |  ^0.17.0  | ~2.2.1           |
diff --git a/include/xtensor-python/pyarray.hpp b/include/xtensor-python/pyarray.hpp
index ec70d6a..20d7e74 100644
--- a/include/xtensor-python/pyarray.hpp
+++ b/include/xtensor-python/pyarray.hpp
@@ -320,10 +320,12 @@ namespace xt
      * @class pyarray
      * @brief Multidimensional container providing the xtensor container semantics to a numpy array.
      *
-     * pyarray is similar to the xarray container in that it has a dynamic dimensionality. Reshapes of
-     * a pyarray container are reflected in the underlying numpy array.
+     * pyarray is similar to the xarray container in that it has a dynamic dimensionality.
+     * Reshapes of a pyarray container are reflected in the underlying numpy array.
      *
      * @tparam T The type of the element stored in the pyarray.
+     * @tparam L Static layout of the pyarray
+     *
      * @sa pytensor
      */
     template <class T, layout_type L>
diff --git a/include/xtensor-python/pytensor.hpp b/include/xtensor-python/pytensor.hpp
index 0f0cac4..b7886f6 100644
--- a/include/xtensor-python/pytensor.hpp
+++ b/include/xtensor-python/pytensor.hpp
@@ -131,7 +131,7 @@ namespace xt
      *
      * pytensor is similar to the xtensor container in that it has a static dimensionality.
      *
-     * Unlike with the pyarray container, pytensor cannot be reshaped with a different number of dimensions
+     * Unlike the pyarray container, pytensor cannot be reshaped with a different number of dimensions
      * and reshapes are not reflected on the Python side. However, pytensor has benefits compared to pyarray
      * in terms of performances. pytensor shapes are stack-allocated which makes iteration upon pytensor
      * faster than with pyarray.