mirror of
https://github.com/triqs/dft_tools
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201 lines
9.7 KiB
C++
201 lines
9.7 KiB
C++
/*******************************************************************************
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*
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* TRIQS: a Toolbox for Research in Interacting Quantum Systems
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*
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* Copyright (C) 2011-2013 by O. Parcollet
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*
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* TRIQS is free software: you can redistribute it and/or modify it under the
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* terms of the GNU General Public License as published by the Free Software
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* Foundation, either version 3 of the License, or (at your option) any later
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* version.
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*
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* TRIQS is distributed in the hope that it will be useful, but WITHOUT ANY
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* WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
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* FOR A PARTICULAR PURPOSE. See the GNU General Public License for more
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* details.
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*
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* You should have received a copy of the GNU General Public License along with
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* TRIQS. If not, see <http://www.gnu.org/licenses/>.
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*
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******************************************************************************/
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#ifndef TRIQS_ARRAYS_H5_LOWLEVEL_H
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#define TRIQS_ARRAYS_H5_LOWLEVEL_H
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#include <triqs/arrays/array.hpp>
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#include <triqs/arrays/vector.hpp>
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#include <triqs/h5.hpp>
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#include "../cache.hpp"
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namespace triqs {
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namespace arrays {
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namespace h5_impl {
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template <typename A> const void* __get_array_data_cptr(A const& a) { return h5::get_data_ptr(&(a.storage()[0])); }
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template <typename A> void* __get_array_data_ptr(A& x) { return h5::get_data_ptr(&(x.storage()[0])); }
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// the dataspace corresponding to the array. Contiguous data only...
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template <typename ArrayType> H5::DataSpace data_space(ArrayType const& A) {
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if (!A.indexmap().is_contiguous()) TRIQS_RUNTIME_ERROR << " h5 : internal error : array not contiguous";
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static const unsigned int R = ArrayType::rank;
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mini_vector<hsize_t, R> S;
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auto const& S1(A.indexmap().strides());
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for (int u = 0; u < R; ++u) {
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if (S1[u] <= 0) TRIQS_RUNTIME_ERROR << " negative strides not permitted in h5";
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S[u] = 1;
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}
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static const bool is_complex = boost::is_complex<typename ArrayType::value_type>::value;
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return h5::dataspace_from_LS<R, is_complex>(A.indexmap().domain().lengths(), A.indexmap().domain().lengths(), S);
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}
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/******************** resize or check the size ****************************************************/
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template <typename A> ENABLE_IF(is_amv_value_class<A>) resize_or_check(A& a, mini_vector<size_t, A::rank> const& dimsf) {
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a.resize(indexmaps::cuboid::domain_t<A::rank>(dimsf));
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}
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template <typename A> ENABLE_IF(is_amv_view_class<A>) resize_or_check(A const& a, mini_vector<size_t, A::rank> const& dimsf) {
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if (a.indexmap().domain().lengths() != dimsf)
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TRIQS_RUNTIME_ERROR << "Dimension error : the view can not be resized : "
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<< "\n in file : " << dimsf.to_string()
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<< "\n in view : " << a.indexmap().domain().lengths().to_string();
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}
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/*********************************** WRITE array ****************************************************************/
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/*
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* Write an array or a view into an hdf5 file
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*
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* f The h5 file or group of type H5::H5File or H5::Group
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* name The name of the hdf5 array in the file/group where the stack will be stored
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* A The array to be stored
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* C_reorder bool If true [default] the data will be stored in C order in the hdf5, hence making a temporary
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* cache of the data to reorder them in memory.
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* If false, the array is stored as it [if you know what you are doing]
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* The HDF5 exceptions will be caught and rethrown as TRIQS_RUNTIME_ERROR (with a full stackstrace, cf triqs doc).
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*/
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template <typename T, int R>
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void write_array_impl(h5::group g, std::string const& name, array_const_view<T, R> A, bool C_reorder) {
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static_assert(!std::is_base_of<std::string, T>::value, " Not implemented"); // 1d is below
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if (C_reorder) {
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write_array_impl(g, name, make_const_cache(A).view(), false);
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return;
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}
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try {
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H5::DataSet ds = g.create_dataset(name, h5::data_type_file<T>(), data_space(A));
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ds.write(__get_array_data_cptr(A), h5::data_type_memory<T>(), data_space(A));
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// if complex, to be python compatible, we add the __complex__ attribute
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if (boost::is_complex<T>::value) h5::write_string_attribute(&ds, "__complex__", "1");
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}
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TRIQS_ARRAYS_H5_CATCH_EXCEPTION;
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}
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template <typename A> void write_array(h5::group g, std::string const& name, A const& a, bool C_reorder = true) {
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write_array_impl(g, name, typename A::const_view_type{a}, C_reorder);
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}
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/*********************************** READ array ****************************************************************/
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/*
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* Read an array or a view from an hdf5 file
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* ArrayType The type of the array/matrix/vector, etc..
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* f The h5 file or group of type H5::H5File or H5::Group
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* name The name of the hdf5 array in the file/group where the stack will be stored
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* A The array to be stored
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* C_reorder bool If true [default] the data will be stored in C order in the hdf5, hence making a temporary
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* cache of the data to reorder them in memory. If false, the array is stored as it [if you know what you are doing]
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* The HDF5 exceptions will be caught and rethrown as TRIQS_RUNTIME_ERROR (with a full stackstrace, cf triqs doc).
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*/
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template <typename ArrayType1> void read_array(h5::group g, std::string const& name, ArrayType1&& A, bool C_reorder = true) {
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typedef typename std::remove_reference<ArrayType1>::type ArrayType;
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static_assert(!std::is_base_of<std::string, typename ArrayType::value_type>::value, " Not implemented"); // 1d is below
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try {
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H5::DataSet ds = g.open_dataset(name);
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H5::DataSpace dataspace = ds.getSpace();
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static const unsigned int Rank = ArrayType::rank + (boost::is_complex<typename ArrayType::value_type>::value ? 1 : 0);
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int rank = dataspace.getSimpleExtentNdims();
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if (rank != Rank)
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TRIQS_RUNTIME_ERROR << "triqs::array::h5::read. Rank mismatch : the array has rank = " << Rank
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<< " while the array stored in the hdf5 file has rank = " << rank;
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mini_vector<hsize_t, Rank> dims_out;
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dataspace.getSimpleExtentDims(&dims_out[0], NULL);
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mini_vector<size_t, ArrayType::rank> d2;
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for (size_t u = 0; u < ArrayType::rank; ++u) d2[u] = dims_out[u];
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resize_or_check(A, d2);
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if (C_reorder) {
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read_array(g, name, make_cache(A).view(), false);
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//read_array(g, name, cache<ArrayType, typename ArrayType::regular_type>(A).view(), false);
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} else
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ds.read(__get_array_data_ptr(A), h5::data_type_memory<typename ArrayType::value_type>(), data_space(A), dataspace);
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}
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TRIQS_ARRAYS_H5_CATCH_EXCEPTION;
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}
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// overload : special treatment for arrays of strings (one dimension only).
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inline void write_array(h5::group f, std::string const& name, vector_const_view<std::string> V) {
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h5::detail::write_1darray_vector_of_string_impl(f, name, V);
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}
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inline void write_array(h5::group f, std::string const& name, array_const_view<std::string, 1> V) {
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write_array(f, name, vector_const_view<std::string>(V));
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}
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inline void read_array(h5::group f, std::string const& name, arrays::vector<std::string>& V) {
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h5::detail::read_1darray_vector_of_string_impl(f, name, V);
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}
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// I can not use the generic code, just because the resize of the array take a shape, not a size_t as std::vector and vector
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inline void read_array(h5::group f, std::string const& name, arrays::array<std::string, 1>& V) {
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arrays::vector<std::string> res;
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read_array(f, name, res);
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V = res;
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}
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} // namespace h5impl
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// a trait to detect if A::value_type exists and is a scalar or a string
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// used to exclude array<array<..>>
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template <typename A, typename Enable = void> struct has_scalar_or_string_value_type : std::false_type {};
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template <typename A>
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struct has_scalar_or_string_value_type<
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A, decltype(nop(std::declval<
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typename A::value_type>()))> : std::integral_constant<bool, is_scalar<typename A::value_type>::value ||
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std::is_base_of<std::string,
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typename A::value_type>::value> {};
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// get_triqs_hdf5_data_scheme
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template <typename ArrayType>
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TYPE_ENABLE_IFC(std::string, is_amv_value_or_view_class<ArrayType>::value) get_triqs_hdf5_data_scheme(ArrayType const&) {
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using triqs::get_triqs_hdf5_data_scheme; // for the basic types, not found by ADL
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std::stringstream fs;
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fs << "array<" << get_triqs_hdf5_data_scheme(typename ArrayType::value_type()) << "," << ArrayType::rank << ">";
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return fs.str();
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}
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/*
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* Read an array or a view from an hdf5 file
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* ArrayType The type of the array/matrix/vector, etc..
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* g The h5 group
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* name The name of the hdf5 array in the file/group where the stack will be stored
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* A The array to be stored
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* The HDF5 exceptions will be caught and rethrown as TRIQS_RUNTIME_ERROR (with a full stackstrace, cf triqs doc).
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*/
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template <typename ArrayType>
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ENABLE_IFC(is_amv_value_or_view_class<ArrayType>::value&& has_scalar_or_string_value_type<ArrayType>::value)
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h5_read(h5::group g, std::string const& name, ArrayType& A) {
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h5_impl::read_array(g, name, A);
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}
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/*
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* Write an array or a view into an hdf5 file
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* ArrayType The type of the array/matrix/vector, etc..
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* g The h5 group
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* name The name of the hdf5 array in the file/group where the stack will be stored
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* A The array to be stored
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* The HDF5 exceptions will be caught and rethrown as TRIQS_RUNTIME_ERROR (with a full stackstrace, cf triqs doc).
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*/
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template <typename ArrayType>
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ENABLE_IFC(is_amv_value_or_view_class<ArrayType>::value&& has_scalar_or_string_value_type<ArrayType>::value)
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h5_write(h5::group g, std::string const& name, ArrayType const& A) {
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h5_impl::write_array(g, name, array_const_view<typename ArrayType::value_type, ArrayType::rank>(A));
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}
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}
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}
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#endif
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