10000 Merge pull request #194 from JohanMabille/xtensor_020 · robertodr/xtensor-python@a8b72e3 · GitHub
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JohanMabilleJohanMabille
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Merge pull request xtensor-stack#194 from JohanMabille/xtensor_020
Upgraded to xtensor 0.20.0
2 parents 1a0ee4c + a9f5a83 commit a8b72e3

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‎.appveyor.yml

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@@ -22,7 +22,7 @@ install:
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- conda update -q conda
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- conda info -a
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- conda install gtest cmake -c conda-forge
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- conda install pytest numpy pybind11==2.2.1 xtensor==0.19.2 -c conda-forge
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- conda install pytest numpy pybind11==2.2.1 xtensor==0.20.0 -c conda-forge
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- "set PYTHONHOME=%MINICONDA%"
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- cmake -G "NMake Makefiles" -D CMAKE_INSTALL_PREFIX=%MINICONDA%\\Library -D BUILD_TESTS=ON -D PYTHON_EXECUTABLE=%MINICONDA%\\python.exe .
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- nmake test_xtensor_python

‎.travis.yml

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@@ -147,7 +147,7 @@ install:
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else
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conda install pybind11==${PYBIND11_VERSION} -c conda-forge
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fi
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- conda install xtensor==0.19.2 -c conda-forge
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- conda install xtensor==0.20.0 -c conda-forge
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- cmake -D DOWNLOAD_GTEST=ON -D CMAKE_INSTALL_PREFIX=$HOME/miniconda -D PYTHON_EXECUTABLE=$PY_EXE .
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- make -j2 test_xtensor_python
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- make install

‎README.md

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@@ -195,7 +195,7 @@ from the `docs` subdirectory.
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| `xtensor-python` | `xtensor` | `pybind11` |
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|------------------|-----------|------------------|
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| master | ^0.19.0 | ~2.2.1 |
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| master | ^0.20.0 | ~2.2.1 |
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| 0.22.x | ^0.19.0 | ~2.2.1 |
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| 0.21.x | ^0.18.0 | ~2.2.1 |
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| 0.20.x | ^0.17.0 | ~2.2.1 |

‎include/xtensor-python/pyarray.hpp

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@@ -264,6 +264,8 @@ namespace xt
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using const_iterator = pybackstrides_iterator<self_type>;
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using iterator = const_iterator;
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using reverse_iterator = std::reverse_iterator<iterator>;
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using const_reverse_iterator = std::reverse_iterator<const_iterator>;
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pyarray_backstrides() = default;
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pyarray_backstrides(const array_type& a);
@@ -281,6 +283,11 @@ namespace xt
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const_iterator cbegin() const;
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const_iterator cend() const;
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const_reverse_iterator rbegin() const;
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const_reverse_iterator rend() const;
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const_reverse_iterator crbegin() const;
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const_reverse_iterator crend() const;
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private:
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const array_type* p_a;
@@ -472,6 +479,30 @@ namespace xt
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return const_iterator(this, size());
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}
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template <class A>
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inline auto pyarray_backstrides<A>::rbegin() const -> const_reverse_iterator
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{
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return crbegin();
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}
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template <class A>
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inline auto pyarray_backstrides<A>::rend() const -> const_reverse_iterator
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{
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return crend();
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}
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template <class A>
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inline auto pyarray_backstrides<A>::crbegin() const -> const_reverse_iterator
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{
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return const_reverse_iterator(end());
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}
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template <class A>
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inline auto pyarray_backstrides<A>::crend() const -> const_reverse_iterator
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{
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return const_reverse_iterator(begin());
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}
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/**************************
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* pyarray implementation *
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**************************/
@@ -760,7 +791,7 @@ namespace xt
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m_strides = inner_strides_type(reinterpret_cast<difference_type*>(PyArray_STRIDES(this->python_array())),
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static_cast<size_type>(PyArray_NDIM(this->python_array())));
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if (L != layout_type::dynamic && !do_strides_match(m_shape, m_strides, L))
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if (L != layout_type::dynamic && !do_strides_match(m_shape, m_strides, L, 1))
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{
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throw std::runtime_error("NumPy: passing container with bad strides for layout (is it a view?).");
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}

‎include/xtensor-python/pytensor.hpp

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@@ -460,7 +460,7 @@ namespace xt
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[](auto v) { return v / sizeof(T); });
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adapt_strides(m_shape, m_strides, m_backstrides);
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if (L != layout_type::dynamic && !do_strides_match(m_shape, m_strides, L))
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if (L != layout_type::dynamic && !do_strides_match(m_shape, m_strides, L, 1))
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{
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throw std::runtime_error("NumPy: passing container with bad strides for layout (is it a view?).");
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}

‎test/test_pyarray.cpp

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@@ -19,6 +19,21 @@ namespace xt
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{
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using container_type = std::vector<npy_intp>;
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template <class T>
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using ndarray = pyarray<T, xt::layout_type::row_major>;
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void test1 (ndarray<int>const& x)
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{
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ndarray<int> y = x;
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ndarray<int> z = xt::zeros<int>({10});
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}
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double compute(ndarray<double> const& xs)
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{
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auto v = xt::view (xs, 0, xt::all());
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return v(0);
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}
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TEST(pyarray, initializer_constructor)
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{
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pyarray<int> t

‎test_python/main.cpp

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@@ -181,6 +181,15 @@ void col_major_array(xt::pyarray<double, xt::layout_type::column_major>& arg)
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}
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}
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template <class T>
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using ndarray = xt::pyarray<T, xt::layout_type::row_major>;
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void test_rm(ndarray<int>const& x)
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{
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ndarray<int> y = x;
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ndarray<int> z = xt::zeros<int>({10});
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}
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PYBIND11_MODULE(xtensor_python_test, m)
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{
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xt::import_numpy();
@@ -206,6 +215,8 @@ PYBIND11_MODULE(xtensor_python_test, m)
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return a.shape() == b.shape();
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});
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m.def("test_rm", test_rm);
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m.def("int_overload", int_overload<uint8_t>);
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m.def("int_overload", int_overload<int8_t>);
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m.def("int_overload", int_overload<uint16_t>);

‎test_python/test_pyarray.py

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@@ -23,6 +23,9 @@
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class XtensorTest(TestCase):
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def test_rm(self):
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xt.test_rm(np.array([10], dtype=int))
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def test_example1(self):
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self.assertEqual(4, xt.example1([4, 5, 6]))
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