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GeezerVison is showing github.com — Fixing constructor bug pytensor<..., 0> · lavaux/xtensor-python@cfb08ae

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include/xtensor-python
- pytensor.hpp
test_python
- main.cpp
- test_pyarray.py
test
- test_pytensor.cpp

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`‎include/xtensor-python/pytensor.hpp‎`

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+19-4Lines changed: 19 additions & 4 deletions

Original file line number	Diff line number	Diff line change
`@@ -100,11 +100,26 @@ namespace pybind11`
`100`	`100`	`}`
`101`	`101`	`};`
`102`	`102`
`103`		`- }`
	`103`	`+ } // namespace detail`
`104`	`104`	`}`
`105`	`105`
`106`	`106`	`namespace xt`
`107`	`107`	`{`
	`108`	`+ namespace detail {`
	`109`	`+`
	`110`	`+ template <std::size_t N, typename = void>`
	`111`	`+ struct numpy_strides`
	`112`	`+ {`
	`113`	`+ npy_intp value[N];`
	`114`	`+ };`
	`115`	`+`
	`116`	`+ template <std::size_t N>`
	`117`	`+ struct numpy_strides<N, typename std::enable_if_t<(N == 0)>::type>`
	`118`	`+ {`
	`119`	`+ npy_intp* value = nullptr;`
	`120`	`+ };`
	`121`	`+`
	`122`	`+ } // namespace detail`
`108`	`123`
`109`	`124`	`template <class T, std::size_t N, layout_type L>`
`110`	`125`	`struct xiterable_inner_types<pytensor<T, N, L>>`
`@@ -433,8 +448,8 @@ namespace xt`
`433`	`448`	`template <class T, std::size_t N, layout_type L>`
`434`	`449`	`inline void pytensor<T, N, L>::init_tensor(const shape_type& shape, const strides_type& strides)`
`435`	`450`	`{`
`436`		`- npy_intp python_strides[N];`
`437`		`- std::transform(strides.begin(), strides.end(), python_strides,`
	`451`	`+ detail::numpy_strides<N> python_strides;`
	`452`	`+ std::transform(strides.begin(), strides.end(), python_strides.value,`
`438`	`453`	`[](auto v) { return sizeof(T) * v; });`
`439`	`454`	`int flags = NPY_ARRAY_ALIGNED;`
`440`	`455`	`if (!std::is_const<T>::value)`
`@@ -445,7 +460,7 @@ namespace xt`
`445`	`460`
`446`	`461`	`auto tmp = pybind11::reinterpret_steal<pybind11::object>(`
`447`	`462`	`PyArray_NewFromDescr(&PyArray_Type, (PyArray_Descr*) dtype.release().ptr(), static_cast<int>(shape.size()),`
`448`		`- const_cast<npy_intp*>(shape.data()), python_strides,`
	`463`	`+ const_cast<npy_intp*>(shape.data()), python_strides.value,`
`449`	`464`	`nullptr, flags, nullptr));`
`450`	`465`
`451`	`466`	`if (!tmp)`

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`‎test/test_pytensor.cpp‎`

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+9Lines changed: 9 additions & 0 deletions

Original file line number	Diff line number	Diff line change
`@@ -65,6 +65,15 @@ namespace xt`
`65`	`65`	`EXPECT_THROW(pyt3::from_shape(shp), std::runtime_error);`
`66`	`66`	`}`
`67`	`67`
	`68`	`+ TEST(pytensor, scalar_from_shape)`
	`69`	`+ {`
	`70`	`+ std::array<size_t, 0> shape;`
	`71`	`+ auto a = pytensor<double, 0>::from_shape(shape);`
	`72`	`+ pytensor<double, 0> b(1.2);`
	`73`	`+ EXPECT_TRUE(a.size() == b.size());`
	`74`	`+ EXPECT_TRUE(xt::has_shape(a, b.shape()));`
	`75`	`+ }`
	`76`	`+`
`68`	`77`	`TEST(pytensor, strided_constructor)`
`69`	`78`	`{`
`70`	`79`	`central_major_result<container_type> cmr;`

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`‎test_python/main.cpp‎`

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+7Lines changed: 7 additions & 0 deletions

Original file line number	Diff line number	Diff line change
`@@ -227,6 +227,11 @@ void col_major_array(xt::pyarray<double, xt::layout_type::column_major>& arg)`
`227`	`227`	`}`
`228`	`228`	`}`
`229`	`229`
	`230`	`+xt::pytensor<int, 0> xscalar(const xt::pytensor<int, 1>& arg)`
	`231`	`+{`
	`232`	`+ return xt::sum(arg);`
	`233`	`+}`
	`234`	`+`
`230`	`235`	`template <class T>`
`231`	`236`	`using ndarray = xt::pyarray<T, xt::layout_type::row_major>;`
`232`	`237`
`@@ -285,6 +290,8 @@ PYBIND11_MODULE(xtensor_python_test, m)`
`285`	`290`	`m.def("col_major_array", col_major_array);`
`286`	`291`	`m.def("row_major_tensor", row_major_tensor);`
`287`	`292`
	`293`	`+ m.def("xscalar", xscalar);`
	`294`	`+`
`288`	`295`	`py::class_<C>(m, "C")`
`289`	`296`	`.def(py::init<>())`
`290`	`297`	`.def_property_readonly(`

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`‎test_python/test_pyarray.py‎`

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+4Lines changed: 4 additions & 0 deletions

Original file line number	Diff line number	Diff line change
`@@ -151,6 +151,10 @@ def test_col_row_major(self):`
`151`	`151`	`xt.col_major_array(varF)`
`152`	`152`	`xt.col_major_array(varF[:, :, 0]) # still col major!`
`153`	`153`
	`154`	`+ def test_xscalar(self):`
	`155`	`+ var = np.arange(50, dtype=int)`
	`156`	`+ self.assertTrue(np.sum(var) == xt.xscalar(var))`
	`157`	`+`
`154`	`158`	`def test_bad_argument_call(self):`
`155`	`159`	`with self.assertRaises(TypeError):`
`156`	`160`	`xt.simple_array("foo")`

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