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Adds support for `xt::xtensor`, `xt::xarray` and `xt::xview`, both row and column major. This works by wrapping the internal row-major with `xt::adapt`. Therefore, the `T` in `xt::xtensor<T, ...>` must be scalar (trivial).
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| Original file line number | Diff line number | Diff line change |
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| @@ -0,0 +1,212 @@ | ||
| #pragma once | ||
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| #include "bits/H5Inspector_decl.hpp" | ||
| #include "H5Exception.hpp" | ||
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| #include <xtensor/xtensor.hpp> | ||
| #include <xtensor/xarray.hpp> | ||
| #include <xtensor/xadapt.hpp> | ||
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| namespace HighFive { | ||
| namespace details { | ||
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| template <class XTensor> | ||
| struct xtensor_get_rank; | ||
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| template <typename T, size_t N, xt::layout_type L> | ||
| struct xtensor_get_rank<xt::xtensor<T, N, L>> { | ||
| static constexpr size_t value = N; | ||
| }; | ||
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| template <class EC, size_t N, xt::layout_type L, class Tag> | ||
| struct xtensor_get_rank<xt::xtensor_adaptor<EC, N, L, Tag>> { | ||
| static constexpr size_t value = N; | ||
| }; | ||
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| template <class Derived, class XTensorType, xt::layout_type L> | ||
| struct xtensor_inspector_base { | ||
| using type = XTensorType; | ||
| using value_type = typename type::value_type; | ||
| using base_type = typename inspector<value_type>::base_type; | ||
| using hdf5_type = base_type; | ||
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| static_assert(std::is_same<value_type, base_type>::value, | ||
| "HighFive's XTensor support only works for scalar elements."); | ||
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| static constexpr bool IsConstExprRowMajor = L == xt::layout_type::row_major; | ||
| static constexpr bool is_trivially_copyable = IsConstExprRowMajor && | ||
| std::is_trivially_copyable<value_type>::value && | ||
| inspector<value_type>::is_trivially_copyable; | ||
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| static constexpr bool is_trivially_nestable = false; | ||
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| static size_t getRank(const type& val) { | ||
| // Non-scalar elements are not supported. | ||
| return val.shape().size(); | ||
| } | ||
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| static const value_type& getAnyElement(const type& val) { | ||
| return val.unchecked(0); | ||
| } | ||
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| static value_type& getAnyElement(type& val) { | ||
| return val.unchecked(0); | ||
| } | ||
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| static std::vector<size_t> getDimensions(const type& val) { | ||
| auto shape = val.shape(); | ||
| return {shape.begin(), shape.end()}; | ||
| } | ||
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| static void prepare(type& val, const std::vector<size_t>& dims) { | ||
| val.resize(Derived::shapeFromDims(dims)); | ||
| } | ||
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| static hdf5_type* data(type& val) { | ||
| if (!is_trivially_copyable) { | ||
| throw DataSetException("Invalid used of `inspector<xarray>::data`."); | ||
| } | ||
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| if (val.size() == 0) { | ||
| return nullptr; | ||
| } | ||
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| return inspector<value_type>::data(getAnyElement(val)); | ||
| } | ||
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| static const hdf5_type* data(const type& val) { | ||
| if (!is_trivially_copyable) { | ||
| throw DataSetException("Invalid used of `inspector<xarray>::data`."); | ||
| } | ||
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| if (val.size() == 0) { | ||
| return nullptr; | ||
| } | ||
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| return inspector<value_type>::data(getAnyElement(val)); | ||
| } | ||
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| static void serialize(const type& val, const std::vector<size_t>& dims, hdf5_type* m) { | ||
| // since we only support scalar types we know all dims belong to us. | ||
| size_t size = compute_total_size(dims); | ||
| xt::adapt(m, size, xt::no_ownership(), dims) = val; | ||
| } | ||
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| static void unserialize(const hdf5_type* vec_align, | ||
| const std::vector<size_t>& dims, | ||
| type& val) { | ||
| // since we only support scalar types we know all dims belong to us. | ||
| size_t size = compute_total_size(dims); | ||
| val = xt::adapt(vec_align, size, xt::no_ownership(), dims); | ||
| } | ||
| }; | ||
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| template <class XTensorType, xt::layout_type L> | ||
| struct xtensor_inspector | ||
| : public xtensor_inspector_base<xtensor_inspector<XTensorType, L>, XTensorType, L> { | ||
| private: | ||
| using super = xtensor_inspector_base<xtensor_inspector<XTensorType, L>, XTensorType, L>; | ||
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| public: | ||
| using type = typename super::type; | ||
| using value_type = typename super::value_type; | ||
| using base_type = typename super::base_type; | ||
| using hdf5_type = typename super::hdf5_type; | ||
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| static constexpr size_t ndim = xtensor_get_rank<XTensorType>::value; | ||
| static constexpr size_t min_ndim = ndim + inspector<value_type>::min_ndim; | ||
| static constexpr size_t max_ndim = ndim + inspector<value_type>::max_ndim; | ||
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| static std::array<size_t, ndim> shapeFromDims(const std::vector<size_t>& dims) { | ||
| std::array<size_t, ndim> shape; | ||
| std::copy(dims.cbegin(), dims.cend(), shape.begin()); | ||
| return shape; | ||
| } | ||
| }; | ||
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| template <class XArrayType, xt::layout_type L> | ||
| struct xarray_inspector | ||
| : public xtensor_inspector_base<xarray_inspector<XArrayType, L>, XArrayType, L> { | ||
| private: | ||
| using super = xtensor_inspector_base<xarray_inspector<XArrayType, L>, XArrayType, L>; | ||
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| public: | ||
| using type = typename super::type; | ||
| using value_type = typename super::value_type; | ||
| using base_type = typename super::base_type; | ||
| using hdf5_type = typename super::hdf5_type; | ||
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| static constexpr size_t min_ndim = 0 + inspector<value_type>::min_ndim; | ||
| static constexpr size_t max_ndim = 1024 + inspector<value_type>::max_ndim; | ||
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| static const std::vector<size_t>& shapeFromDims(const std::vector<size_t>& dims) { | ||
| return dims; | ||
| } | ||
| }; | ||
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| template <typename T, size_t N, xt::layout_type L> | ||
| struct inspector<xt::xtensor<T, N, L>>: public xtensor_inspector<xt::xtensor<T, N, L>, L> { | ||
| private: | ||
| using super = xtensor_inspector<xt::xtensor<T, N, L>, L>; | ||
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| public: | ||
| using type = typename super::type; | ||
| using value_type = typename super::value_type; | ||
| using base_type = typename super::base_type; | ||
| using hdf5_type = typename super::hdf5_type; | ||
| }; | ||
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| template <typename T, xt::layout_type L> | ||
| struct inspector<xt::xarray<T, L>>: public xarray_inspector<xt::xarray<T, L>, L> { | ||
| private: | ||
| using super = xarray_inspector<xt::xarray<T, L>, L>; | ||
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| public: | ||
| using type = typename super::type; | ||
| using value_type = typename super::value_type; | ||
| using base_type = typename super::base_type; | ||
| using hdf5_type = typename super::hdf5_type; | ||
| }; | ||
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| template <typename CT, class... S> | ||
| struct inspector<xt::xview<CT, S...>> | ||
| : public xarray_inspector<xt::xview<CT, S...>, xt::layout_type::any> { | ||
| private: | ||
| using super = xarray_inspector<xt::xview<CT, S...>, xt::layout_type::any>; | ||
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| public: | ||
| using type = typename super::type; | ||
| using value_type = typename super::value_type; | ||
| using base_type = typename super::base_type; | ||
| using hdf5_type = typename super::hdf5_type; | ||
| }; | ||
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| template <class EC, xt::layout_type L, class SC, class Tag> | ||
| struct inspector<xt::xarray_adaptor<EC, L, SC, Tag>> | ||
| : public xarray_inspector<xt::xarray_adaptor<EC, L, SC, Tag>, xt::layout_type::any> { | ||
| private: | ||
| using super = xarray_inspector<xt::xarray_adaptor<EC, L, SC, Tag>, xt::layout_type::any>; | ||
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| public: | ||
| using type = typename super::type; | ||
| using value_type = typename super::value_type; | ||
| using base_type = typename super::base_type; | ||
| using hdf5_type = typename super::hdf5_type; | ||
| }; | ||
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| template <class EC, size_t N, xt::layout_type L, class Tag> | ||
| struct inspector<xt::xtensor_adaptor<EC, N, L, Tag>> | ||
| : public xtensor_inspector<xt::xtensor_adaptor<EC, N, L, Tag>, xt::layout_type::any> { | ||
| private: | ||
| using super = xtensor_inspector<xt::xtensor_adaptor<EC, N, L, Tag>, xt::layout_type::any>; | ||
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| public: | ||
| using type = typename super::type; | ||
| using value_type = typename super::value_type; | ||
| using base_type = typename super::base_type; | ||
| using hdf5_type = typename super::hdf5_type; | ||
| }; | ||
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| } // namespace details | ||
| } // namespace HighFive |
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