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H5Inspector_misc.hpp
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H5Inspector_misc.hpp
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/*
* Copyright (c) 2022 Blue Brain Project
*
* Distributed under the Boost Software License, Version 1.0.
* (See accompanying file LICENSE_1_0.txt or copy at
* http://www.boost.org/LICENSE_1_0.txt)
*
*/
#pragma once
#include <type_traits>
#include <cstring>
#include <cassert>
#include <numeric>
#include "../H5Reference.hpp"
#include "string_padding.hpp"
#ifdef H5_USE_BOOST
#include <boost/multi_array.hpp>
// starting Boost 1.64, serialization header must come before ublas
#include <boost/serialization/vector.hpp>
#include <boost/numeric/ublas/matrix.hpp>
#endif
#ifdef H5_USE_EIGEN
#include <Eigen/Eigen>
#endif
namespace HighFive {
namespace details {
inline bool checkDimensions(const std::vector<size_t>& dims, size_t n_dim_requested) {
size_t n_dim_actual = dims.size();
// We should allow reading scalar from shapes like `(1, 1, 1)`.
if (n_dim_requested == 0) {
if (n_dim_actual == 0ul) {
return true;
}
return size_t(std::count(dims.begin(), dims.end(), 1ul)) == n_dim_actual;
}
// For non-scalar datasets, we can squeeze away singleton dimension, but
// we never add any.
if (n_dim_actual < n_dim_requested) {
return false;
}
// Special case for 1-dimensional arrays, which can squeeze `1`s from either
// side simultaneously if needed.
if (n_dim_requested == 1ul) {
return n_dim_actual >= 1ul &&
size_t(std::count(dims.begin(), dims.end(), 1ul)) >= n_dim_actual - 1ul;
}
// All other cases strip front only. This avoid unstable behaviour when
// squeezing singleton dimensions.
size_t n_dim_excess = n_dim_actual - n_dim_requested;
bool squeeze_back = true;
for (size_t i = 1; i <= n_dim_excess; ++i) {
if (dims[n_dim_actual - i] != 1) {
squeeze_back = false;
break;
}
}
return squeeze_back;
}
inline std::vector<size_t> squeezeDimensions(const std::vector<size_t>& dims,
size_t n_dim_requested) {
auto format_error_message = [&]() -> std::string {
return "Can't interpret dims = " + format_vector(dims) + " as " +
std::to_string(n_dim_requested) + "-dimensional.";
};
if (n_dim_requested == 0) {
if (!checkDimensions(dims, n_dim_requested)) {
throw std::invalid_argument(format_error_message());
}
return {1ul};
}
auto n_dim = dims.size();
if (n_dim < n_dim_requested) {
throw std::invalid_argument(format_error_message());
}
if (n_dim_requested == 1ul) {
size_t non_singleton_dim = size_t(-1);
for (size_t i = 0; i < n_dim; ++i) {
if (dims[i] != 1ul) {
if (non_singleton_dim == size_t(-1)) {
non_singleton_dim = i;
} else {
throw std::invalid_argument(format_error_message());
}
}
}
return {dims[std::min(non_singleton_dim, n_dim - 1)]};
}
size_t n_dim_excess = dims.size() - n_dim_requested;
for (size_t i = 1; i <= n_dim_excess; ++i) {
if (dims[n_dim - i] != 1) {
throw std::invalid_argument(format_error_message());
}
}
return std::vector<size_t>(dims.begin(),
dims.end() - static_cast<std::ptrdiff_t>(n_dim_excess));
}
} // namespace details
inline size_t compute_total_size(const std::vector<size_t>& dims) {
return std::accumulate(dims.begin(), dims.end(), size_t{1u}, std::multiplies<size_t>());
}
template <typename T>
using unqualified_t = typename std::remove_const<typename std::remove_reference<T>::type>::type;
/*****
inspector<T> {
using type = T
// base_type is the base type inside c++ (e.g. std::vector<int> => int)
using base_type
// hdf5_type is the base read by hdf5 (c-type) (e.g. std::vector<std::string> => const char*)
using hdf5_type
// Number of dimensions starting from here
static constexpr size_t recursive_ndim
// Is the inner type trivially copyable for optimisation
// If this value is true: data() is mandatory
// If this value is false: getSizeVal, getSize, serialize, unserialize are mandatory
static constexpr bool is_trivially_copyable
// Reading:
// Allocate the value following dims (should be recursive)
static void prepare(type& val, const std::vector<std::size_t> dims)
// Return the size of the vector pass to/from hdf5 from a vector of dims
static size_t getSize(const std::vector<size_t>& dims)
// Return a pointer of the first value of val (for reading)
static hdf5_type* data(type& val)
// Take a serialized vector 'in', some dims and copy value to val (for reading)
static void unserialize(const hdf5_type* in, const std::vector<size_t>&i, type& val)
// Writing:
// Return the size of the vector pass to/from hdf5 from a value
static size_t getSizeVal(const type& val)
// Return a point of the first value of val
static const hdf5_type* data(const type& val)
// Take a val and serialize it inside 'out'
static void serialize(const type& val, hdf5_type* out)
// Return an array of dimensions of the space needed for writing val
static std::vector<size_t> getDimensions(const type& val)
}
*****/
namespace details {
template <typename T>
struct type_helper {
using type = unqualified_t<T>;
using base_type = unqualified_t<T>;
using hdf5_type = base_type;
static constexpr size_t ndim = 0;
static constexpr size_t recursive_ndim = ndim;
static constexpr bool is_trivially_copyable = std::is_trivially_copyable<type>::value;
static std::vector<size_t> getDimensions(const type& /* val */) {
return {};
}
static size_t getSizeVal(const type& val) {
return compute_total_size(getDimensions(val));
}
static size_t getSize(const std::vector<size_t>& dims) {
return compute_total_size(dims);
}
static void prepare(type& /* val */, const std::vector<size_t>& /* dims */) {}
static hdf5_type* data(type& val) {
static_assert(is_trivially_copyable, "The type is not trivially copyable");
return &val;
}
static const hdf5_type* data(const type& val) {
static_assert(is_trivially_copyable, "The type is not trivially copyable");
return &val;
}
static void serialize(const type& val, hdf5_type* m) {
static_assert(is_trivially_copyable, "The type is not trivially copyable");
*m = val;
}
static void unserialize(const hdf5_type* vec,
const std::vector<size_t>& /* dims */,
type& val) {
static_assert(is_trivially_copyable, "The type is not trivially copyable");
val = vec[0];
}
};
template <typename T>
struct inspector: type_helper<T> {};
enum class Boolean : int8_t {
HighFiveFalse = 0,
HighFiveTrue = 1,
};
template <>
struct inspector<bool>: type_helper<bool> {
using base_type = Boolean;
using hdf5_type = int8_t;
static constexpr bool is_trivially_copyable = false;
static hdf5_type* data(type& /* val */) {
throw DataSpaceException("A boolean cannot be read directly.");
}
static const hdf5_type* data(const type& /* val */) {
throw DataSpaceException("A boolean cannot be written directly.");
}
static void unserialize(const hdf5_type* vec,
const std::vector<size_t>& /* dims */,
type& val) {
val = vec[0] != 0 ? true : false;
}
static void serialize(const type& val, hdf5_type* m) {
*m = val ? 1 : 0;
}
};
template <>
struct inspector<std::string>: type_helper<std::string> {
using hdf5_type = const char*;
static hdf5_type* data(type& /* val */) {
throw DataSpaceException("A std::string cannot be read directly.");
}
static const hdf5_type* data(const type& /* val */) {
throw DataSpaceException("A std::string cannot be written directly.");
}
static void serialize(const type& val, hdf5_type* m) {
*m = val.c_str();
}
static void unserialize(const hdf5_type* vec,
const std::vector<size_t>& /* dims */,
type& val) {
val = vec[0];
}
};
template <>
struct inspector<Reference>: type_helper<Reference> {
using hdf5_type = hobj_ref_t;
static constexpr bool is_trivially_copyable = false;
static hdf5_type* data(type& /* val */) {
throw DataSpaceException("A Reference cannot be read directly.");
}
static const hdf5_type* data(const type& /* val */) {
throw DataSpaceException("A Reference cannot be written directly.");
}
static void serialize(const type& val, hdf5_type* m) {
hobj_ref_t ref;
val.create_ref(&ref);
*m = ref;
}
static void unserialize(const hdf5_type* vec,
const std::vector<size_t>& /* dims */,
type& val) {
val = type{vec[0]};
}
};
template <size_t N>
struct inspector<FixedLenStringArray<N>> {
using type = FixedLenStringArray<N>;
using value_type = char*;
using base_type = FixedLenStringArray<N>;
using hdf5_type = char;
static constexpr size_t ndim = 1;
static constexpr size_t recursive_ndim = ndim;
static constexpr bool is_trivially_copyable = false;
static std::vector<size_t> getDimensions(const type& val) {
return std::vector<size_t>{val.size()};
}
static size_t getSizeVal(const type& val) {
return N * compute_total_size(getDimensions(val));
}
static size_t getSize(const std::vector<size_t>& dims) {
return N * compute_total_size(dims);
}
static void prepare(type& /* val */, const std::vector<size_t>& dims) {
if (dims[0] > N) {
std::ostringstream os;
os << "Size of FixedlenStringArray (" << N << ") is too small for dims (" << dims[0]
<< ").";
throw DataSpaceException(os.str());
}
}
static hdf5_type* data(type& val) {
return val.data();
}
static const hdf5_type* data(const type& val) {
return val.data();
}
static void serialize(const type& val, hdf5_type* m) {
for (size_t i = 0; i < val.size(); ++i) {
std::memcpy(m + i * N, val[i], N);
}
}
static void unserialize(const hdf5_type* vec, const std::vector<size_t>& dims, type& val) {
for (size_t i = 0; i < dims[0]; ++i) {
std::array<char, N> s;
std::memcpy(s.data(), vec + (i * N), N);
val.push_back(s);
}
}
};
template <typename T>
struct inspector<std::vector<T>> {
using type = std::vector<T>;
using value_type = unqualified_t<T>;
using base_type = typename inspector<value_type>::base_type;
using hdf5_type = typename inspector<value_type>::hdf5_type;
static constexpr size_t ndim = 1;
static constexpr size_t recursive_ndim = ndim + inspector<value_type>::recursive_ndim;
static constexpr bool is_trivially_copyable = std::is_trivially_copyable<value_type>::value &&
inspector<value_type>::is_trivially_copyable;
static std::vector<size_t> getDimensions(const type& val) {
std::vector<size_t> sizes(recursive_ndim, 1ul);
sizes[0] = val.size();
if (!val.empty()) {
auto s = inspector<value_type>::getDimensions(val[0]);
assert(s.size() + ndim == sizes.size());
for (size_t i = 0; i < s.size(); ++i) {
sizes[i + ndim] = s[i];
}
}
return sizes;
}
static size_t getSizeVal(const type& val) {
return compute_total_size(getDimensions(val));
}
static size_t getSize(const std::vector<size_t>& dims) {
return compute_total_size(dims);
}
static void prepare(type& val, const std::vector<size_t>& dims) {
val.resize(dims[0]);
std::vector<size_t> next_dims(dims.begin() + 1, dims.end());
for (auto&& e: val) {
inspector<value_type>::prepare(e, next_dims);
}
}
static hdf5_type* data(type& val) {
return inspector<value_type>::data(val[0]);
}
static const hdf5_type* data(const type& val) {
return inspector<value_type>::data(val[0]);
}
template <class It>
static void serialize(const type& val, It m) {
size_t subsize = inspector<value_type>::getSizeVal(val[0]);
for (auto&& e: val) {
inspector<value_type>::serialize(e, m);
m += subsize;
}
}
template <class It>
static void unserialize(const It& vec_align, const std::vector<size_t>& dims, type& val) {
std::vector<size_t> next_dims(dims.begin() + 1, dims.end());
size_t next_size = compute_total_size(next_dims);
for (size_t i = 0; i < dims[0]; ++i) {
inspector<value_type>::unserialize(vec_align + i * next_size, next_dims, val[i]);
}
}
};
template <>
struct inspector<std::vector<bool>> {
using type = std::vector<bool>;
using value_type = bool;
using base_type = Boolean;
using hdf5_type = uint8_t;
static constexpr size_t ndim = 1;
static constexpr size_t recursive_ndim = ndim;
static constexpr bool is_trivially_copyable = false;
static std::vector<size_t> getDimensions(const type& val) {
std::vector<size_t> sizes{val.size()};
return sizes;
}
static size_t getSizeVal(const type& val) {
return val.size();
}
static size_t getSize(const std::vector<size_t>& dims) {
if (dims.size() > 1) {
throw DataSpaceException("std::vector<bool> is only 1 dimension.");
}
return dims[0];
}
static void prepare(type& val, const std::vector<size_t>& dims) {
if (dims.size() > 1) {
throw DataSpaceException("std::vector<bool> is only 1 dimension.");
}
val.resize(dims[0]);
}
static hdf5_type* data(type& /* val */) {
throw DataSpaceException("A std::vector<bool> cannot be read directly.");
}
static const hdf5_type* data(const type& /* val */) {
throw DataSpaceException("A std::vector<bool> cannot be written directly.");
}
static void serialize(const type& val, hdf5_type* m) {
for (size_t i = 0; i < val.size(); ++i) {
m[i] = val[i] ? 1 : 0;
}
}
static void unserialize(const hdf5_type* vec_align,
const std::vector<size_t>& dims,
type& val) {
for (size_t i = 0; i < dims[0]; ++i) {
val[i] = vec_align[i] != 0 ? true : false;
}
}
};
template <typename T, size_t N>
struct inspector<std::array<T, N>> {
using type = std::array<T, N>;
using value_type = unqualified_t<T>;
using base_type = typename inspector<value_type>::base_type;
using hdf5_type = typename inspector<value_type>::hdf5_type;
static constexpr size_t ndim = 1;
static constexpr size_t recursive_ndim = ndim + inspector<value_type>::recursive_ndim;
static constexpr bool is_trivially_copyable = std::is_trivially_copyable<value_type>::value &&
inspector<value_type>::is_trivially_copyable;
static std::vector<size_t> getDimensions(const type& val) {
std::vector<size_t> sizes{N};
if (!val.empty()) {
auto s = inspector<value_type>::getDimensions(val[0]);
sizes.insert(sizes.end(), s.begin(), s.end());
}
return sizes;
}
static size_t getSizeVal(const type& val) {
return compute_total_size(getDimensions(val));
}
static size_t getSize(const std::vector<size_t>& dims) {
return compute_total_size(dims);
}
static void prepare(type& /* val */, const std::vector<size_t>& dims) {
if (dims[0] > N) {
std::ostringstream os;
os << "Size of std::array (" << N << ") is too small for dims (" << dims[0] << ").";
throw DataSpaceException(os.str());
}
}
static hdf5_type* data(type& val) {
return inspector<value_type>::data(val[0]);
}
static const hdf5_type* data(const type& val) {
return inspector<value_type>::data(val[0]);
}
template <class It>
static void serialize(const type& val, It m) {
size_t subsize = inspector<value_type>::getSizeVal(val[0]);
for (auto& e: val) {
inspector<value_type>::serialize(e, m);
m += subsize;
}
}
template <class It>
static void unserialize(const It& vec_align, const std::vector<size_t>& dims, type& val) {
if (dims[0] != N) {
std::ostringstream os;
os << "Impossible to pair DataSet with " << dims[0] << " elements into an array with "
<< N << " elements.";
throw DataSpaceException(os.str());
}
std::vector<size_t> next_dims(dims.begin() + 1, dims.end());
size_t next_size = compute_total_size(next_dims);
for (size_t i = 0; i < dims[0]; ++i) {
inspector<value_type>::unserialize(vec_align + i * next_size, next_dims, val[i]);
}
}
};
// Cannot be use for reading
template <typename T>
struct inspector<T*> {
using type = T*;
using value_type = unqualified_t<T>;
using base_type = typename inspector<value_type>::base_type;
using hdf5_type = typename inspector<value_type>::hdf5_type;
static constexpr size_t ndim = 1;
static constexpr size_t recursive_ndim = ndim + inspector<value_type>::recursive_ndim;
static constexpr bool is_trivially_copyable = std::is_trivially_copyable<value_type>::value &&
inspector<value_type>::is_trivially_copyable;
static size_t getSizeVal(const type& /* val */) {
throw DataSpaceException("Not possible to have size of a T*");
}
static std::vector<size_t> getDimensions(const type& /* val */) {
throw DataSpaceException("Not possible to have size of a T*");
}
static const hdf5_type* data(const type& val) {
return reinterpret_cast<const hdf5_type*>(val);
}
/* it works because there is only T[][][] currently
we will fix it one day */
static void serialize(const type& /* val */, hdf5_type* /* m */) {
throw DataSpaceException("Not possible to serialize a T*");
}
};
// Cannot be use for reading
template <typename T, size_t N>
struct inspector<T[N]> {
using type = T[N];
using value_type = unqualified_t<T>;
using base_type = typename inspector<value_type>::base_type;
using hdf5_type = typename inspector<value_type>::hdf5_type;
static constexpr size_t ndim = 1;
static constexpr size_t recursive_ndim = ndim + inspector<value_type>::recursive_ndim;
static constexpr bool is_trivially_copyable = std::is_trivially_copyable<value_type>::value &&
inspector<value_type>::is_trivially_copyable;
static size_t getSizeVal(const type& val) {
return compute_total_size(getDimensions(val));
}
static std::vector<size_t> getDimensions(const type& val) {
std::vector<size_t> sizes{N};
if (N > 0) {
auto s = inspector<value_type>::getDimensions(val[0]);
sizes.insert(sizes.end(), s.begin(), s.end());
}
return sizes;
}
static const hdf5_type* data(const type& val) {
return inspector<value_type>::data(val[0]);
}
/* it works because there is only T[][][] currently
we will fix it one day */
static void serialize(const type& val, hdf5_type* m) {
size_t subsize = inspector<value_type>::getSizeVal(val[0]);
for (size_t i = 0; i < N; ++i) {
inspector<value_type>::serialize(val[i], m + i * subsize);
}
}
};
#ifdef H5_USE_EIGEN
template <typename T, int M, int N>
struct inspector<Eigen::Matrix<T, M, N>> {
using type = Eigen::Matrix<T, M, N>;
using value_type = T;
using base_type = typename inspector<value_type>::base_type;
using hdf5_type = base_type;
static constexpr size_t ndim = 2;
static constexpr size_t recursive_ndim = ndim + inspector<value_type>::recursive_ndim;
static constexpr bool is_trivially_copyable = std::is_trivially_copyable<value_type>::value &&
inspector<value_type>::is_trivially_copyable;
static void assert_not_buggy(Eigen::Index nrows, Eigen::Index ncols) {
if (nrows > 1 && ncols > 1) {
throw std::runtime_error(
"HighFive has been broken for Eigen::Matrix. Please check "
"https://github.com/BlueBrain/HighFive/issues/532.");
}
}
static std::vector<size_t> getDimensions(const type& val) {
assert_not_buggy(val.rows(), val.cols());
std::vector<size_t> sizes{static_cast<size_t>(val.rows()), static_cast<size_t>(val.cols())};
auto s = inspector<value_type>::getDimensions(val.data()[0]);
sizes.insert(sizes.end(), s.begin(), s.end());
return sizes;
}
static size_t getSizeVal(const type& val) {
return compute_total_size(getDimensions(val));
}
static size_t getSize(const std::vector<size_t>& dims) {
return compute_total_size(dims);
}
static void prepare(type& val, const std::vector<size_t>& dims) {
if (dims[0] != static_cast<size_t>(val.rows()) ||
dims[1] != static_cast<size_t>(val.cols())) {
val.resize(static_cast<typename type::Index>(dims[0]),
static_cast<typename type::Index>(dims[1]));
}
assert_not_buggy(val.rows(), val.cols());
}
static hdf5_type* data(type& val) {
assert_not_buggy(val.rows(), val.cols());
return inspector<value_type>::data(*val.data());
}
static const hdf5_type* data(const type& val) {
assert_not_buggy(val.rows(), val.cols());
return inspector<value_type>::data(*val.data());
}
static void serialize(const type& val, hdf5_type* m) {
assert_not_buggy(val.rows(), val.cols());
std::memcpy(m, val.data(), static_cast<size_t>(val.size()) * sizeof(hdf5_type));
}
static void unserialize(const hdf5_type* vec_align,
const std::vector<size_t>& dims,
type& val) {
assert_not_buggy(val.rows(), val.cols());
if (dims.size() < 2) {
std::ostringstream os;
os << "Impossible to pair DataSet with " << dims.size()
<< " dimensions into an eigen-matrix.";
throw DataSpaceException(os.str());
}
std::memcpy(val.data(), vec_align, compute_total_size(dims) * sizeof(hdf5_type));
}
};
#endif
#ifdef H5_USE_BOOST
template <typename T, size_t Dims>
struct inspector<boost::multi_array<T, Dims>> {
using type = boost::multi_array<T, Dims>;
using value_type = T;
using base_type = typename inspector<value_type>::base_type;
using hdf5_type = typename inspector<value_type>::hdf5_type;
static constexpr size_t ndim = Dims;
static constexpr size_t recursive_ndim = ndim + inspector<value_type>::recursive_ndim;
static constexpr bool is_trivially_copyable = std::is_trivially_copyable<value_type>::value &&
inspector<value_type>::is_trivially_copyable;
static std::vector<size_t> getDimensions(const type& val) {
std::vector<size_t> sizes;
for (size_t i = 0; i < ndim; ++i) {
sizes.push_back(val.shape()[i]);
}
auto s = inspector<value_type>::getDimensions(val.data()[0]);
sizes.insert(sizes.end(), s.begin(), s.end());
return sizes;
}
static size_t getSizeVal(const type& val) {
return compute_total_size(getDimensions(val));
}
static size_t getSize(const std::vector<size_t>& dims) {
return compute_total_size(dims);
}
static void prepare(type& val, const std::vector<size_t>& dims) {
if (dims.size() < ndim) {
std::ostringstream os;
os << "Only '" << dims.size() << "' given but boost::multi_array is of size '" << ndim
<< "'.";
throw DataSpaceException(os.str());
}
boost::array<typename type::index, Dims> ext;
std::copy(dims.begin(), dims.begin() + ndim, ext.begin());
val.resize(ext);
std::vector<size_t> next_dims(dims.begin() + Dims, dims.end());
std::size_t size = std::accumulate(dims.begin(),
dims.begin() + Dims,
std::size_t{1},
std::multiplies<size_t>());
for (size_t i = 0; i < size; ++i) {
inspector<value_type>::prepare(*(val.origin() + i), next_dims);
}
}
static hdf5_type* data(type& val) {
return inspector<value_type>::data(*val.data());
}
static const hdf5_type* data(const type& val) {
return inspector<value_type>::data(*val.data());
}
template <class It>
static void serialize(const type& val, It m) {
size_t size = val.num_elements();
size_t subsize = inspector<value_type>::getSizeVal(*val.origin());
for (size_t i = 0; i < size; ++i) {
inspector<value_type>::serialize(*(val.origin() + i), m + i * subsize);
}
}
template <class It>
static void unserialize(It vec_align, const std::vector<size_t>& dims, type& val) {
std::vector<size_t> next_dims(dims.begin() + ndim, dims.end());
size_t subsize = compute_total_size(next_dims);
for (size_t i = 0; i < val.num_elements(); ++i) {
inspector<value_type>::unserialize(vec_align + i * subsize,
next_dims,
*(val.origin() + i));
}
}
};
template <typename T>
struct inspector<boost::numeric::ublas::matrix<T>> {
using type = boost::numeric::ublas::matrix<T>;
using value_type = unqualified_t<T>;
using base_type = typename inspector<value_type>::base_type;
using hdf5_type = typename inspector<value_type>::hdf5_type;
static constexpr size_t ndim = 2;
static constexpr size_t recursive_ndim = ndim + inspector<value_type>::recursive_ndim;
static constexpr bool is_trivially_copyable = std::is_trivially_copyable<value_type>::value &&
inspector<value_type>::is_trivially_copyable;
static std::vector<size_t> getDimensions(const type& val) {
std::vector<size_t> sizes{val.size1(), val.size2()};
auto s = inspector<value_type>::getDimensions(val(0, 0));
sizes.insert(sizes.end(), s.begin(), s.end());
return sizes;
}
static size_t getSizeVal(const type& val) {
return compute_total_size(getDimensions(val));
}
static size_t getSize(const std::vector<size_t>& dims) {
return compute_total_size(dims);
}
static void prepare(type& val, const std::vector<size_t>& dims) {
if (dims.size() < ndim) {
std::ostringstream os;
os << "Impossible to pair DataSet with " << dims.size() << " dimensions into a " << ndim
<< " boost::numeric::ublas::matrix";
throw DataSpaceException(os.str());
}
val.resize(dims[0], dims[1], false);
}
static hdf5_type* data(type& val) {
return inspector<value_type>::data(val(0, 0));
}
static const hdf5_type* data(const type& val) {
return inspector<value_type>::data(val(0, 0));
}
static void serialize(const type& val, hdf5_type* m) {
size_t size = val.size1() * val.size2();
size_t subsize = inspector<value_type>::getSizeVal(val(0, 0));
for (size_t i = 0; i < size; ++i) {
inspector<value_type>::serialize(*(&val(0, 0) + i), m + i * subsize);
}
}
static void unserialize(const hdf5_type* vec_align,
const std::vector<size_t>& dims,
type& val) {
std::vector<size_t> next_dims(dims.begin() + ndim, dims.end());
size_t subsize = compute_total_size(next_dims);
size_t size = val.size1() * val.size2();
for (size_t i = 0; i < size; ++i) {
inspector<value_type>::unserialize(vec_align + i * subsize,
next_dims,
*(&val(0, 0) + i));
}
}
};
#endif
} // namespace details
} // namespace HighFive