如何从 C++ 中的 hdf5 文件中读取数据块？
How to read chunk of the data from a hdf5 file in c++?
我想读取一大块数据，它只是存储在一个数据集中的许多帧中的一帧。整个数据集的shape为(10, 11214,3)，10帧，每帧11214行4列。这里是file。我要读取的块的形状为 (11214,3)。我可以使用打印预定义数组，但我不确定如何从 hdf5 文件中读取数据。这是我的代码，
#include <h5xx/h5xx.hpp>
#include <boost/multi_array.hpp>
#include <iostream>
#include <vector>
#include <cstdio>
typedef boost::multi_array<int, 2> array_2d_t;
const int NI=10;
const int NJ=NI;
void print_array(array_2d_t const& array)
{
for (unsigned int j = 0; j < array.shape()[1]; j++)
{
for (unsigned int i = 0; i < array.shape()[0]; i++)
{
printf("%2d ", array[j][i]);
}
printf("\n");
}
}
void write_int_data(std::string const& filename, array_2d_t const& array)
{
h5xx::file file(filename, h5xx::file::trunc);
std::string name;
{
// --- create dataset and fill it with the default array data (positive values)
name = "integer array";
h5xx::create_dataset(file, name, array);
h5xx::write_dataset(file, name, array);
// --- create a slice object (aka hyperslab) to specify the location in the dataset to be overwritten
std::vector<int> offset; int offset_raw[2] = {4,4}; offset.assign(offset_raw, offset_raw + 2);
std::vector<int> count; int count_raw[2] = {2,2}; count.assign(count_raw, count_raw + 2);
h5xx::slice slice(offset, count);
}
}
void read_int_data(std::string const& filename)
{
h5xx::file file(filename, h5xx::file::in);
std::string name = "integer array";
// read and print the full dataset
{
array_2d_t array;
// --- read the complete dataset into array, the array is resized and overwritten internally
h5xx::read_dataset(file, name, array);
printf("original integer array read from file, negative number patch was written using a slice\n");
print_array(array);
printf("\n");
}
}
int main(int argc, char** argv)
{
std::string filename = argv[0];
filename.append(".h5");
// --- do a few demos/tests using integers
{
array_2d_t array(boost::extents[NJ][NI]);
{
const int nelem = NI*NJ;
int data[nelem];
for (int i = 0; i < nelem; i++)
data[i] = i;
array.assign(data, data + nelem);
}
write_int_data(filename, array);
read_int_data(filename);
}
return 0;
}
我正在使用 h5xx — HDF5 库 link 和 boost 库的基于模板的 C++ 包装器。
数据集存储在 particles/lipids/box/positions 路径中。数据集名称值包含帧。
argv[0] 不是你想要的（参数从 1 开始，0 是程序名称）。还要考虑边界检查：
std::vector<std::string> const args(argv, argv + argc);
std::string const filename = args.at(1) + ".h5";
直接初始化就可以了，不需要临时数组（multi_array干什么，不然？）
for (size_t i = 0; i < array.num_elements(); i++)
array.data()[i] = i;
或者实际上，让它成为一个算法：
std::iota(array.data(), array.data() + array.num_elements(), 0);
与矢量相同：
std::vector<int> offset; int offset_raw[2] = {4,4}; offset.assign(offset_raw, offset_raw + 2);
std::vector<int> count; int count_raw[2] = {2,2}; count.assign(count_raw, count_raw + 2);
除了格式混乱之外，还可以简单地
std::vector offset{4,4}, count{2,2};
h5xx::slice slice(offset, count);
进入真正的问题
代码与文件无关。完全没有。我创建了一些 debug/tracing 代码来转储文件内容：
void dump(h5xx::group const& g, std::string indent = "") {
auto dd = g.datasets();
auto gg = g.groups();
for (auto it = dd.begin(); it != dd.end(); ++it) {
std::cout << indent << " ds:" << it.get_name() << "\n";
}
for (auto it = gg.begin(); it != gg.end(); ++it) {
dump(*it, indent + "/" + it.get_name());
}
}
int main()
{
h5xx::file xaa("xaa.h5", h5xx::file::mode::in);
dump(xaa);
}
版画
/particles/lipids/box/edges ds:box_size
/particles/lipids/box/edges ds:step
/particles/lipids/box/edges ds:time
/particles/lipids/box/edges ds:value
/particles/lipids/box/positions ds:step
/particles/lipids/box/positions ds:time
/particles/lipids/box/positions ds:value
现在我们可以深入到数据集。让我们看看是否可以找出正确的类型。它肯定不是 array_2d_t:
h5xx::dataset ds(xaa, "particles/lipids/box/positions/value");
array_2d_t a;
h5xx::datatype detect(a);
std::cout << "type: " << std::hex << ds.get_type() << std::dec << "\n";
std::cout << "detect: " << std::hex << detect.get_type_id() << std::dec << "\n";
版画
type: 30000000000013b
detect: 30000000000000c
这是类型不匹配。我想我也必须学会阅读那些乱码...
让我们添加一些诊断：
void diag_type(hid_t type)
{
std::cout << " Class " << ::H5Tget_class(type) << std::endl;
std::cout << " Size " << ::H5Tget_size(type) << std::endl;
std::cout << " Sign " << ::H5Tget_sign(type) << std::endl;
std::cout << " Order " << ::H5Tget_order(type) << std::endl;
std::cout << " Precision " << ::H5Tget_precision(type) << std::endl;
std::cout << " NDims " << ::H5Tget_array_ndims(type) << std::endl;
std::cout << " NMembers " << ::H5Tget_nmembers(type) << std::endl;
}
int main()
{
h5xx::file xaa("xaa.h5", h5xx::file::mode::in);
// dump(xaa);
{
h5xx::group g(xaa, "particles/lipids/box/positions");
h5xx::dataset ds(g, "value");
std::cout << "dataset: " << std::hex << ds.get_type() << std::dec << std::endl;
diag_type(ds.get_type());
}
{
array_2d_t a(boost::extents[NJ][NI]);
h5xx::datatype detect(a);
std::cout << "detect: " << std::hex << detect.get_type_id() << std::dec << std::endl;
diag_type(detect.get_type_id());
}
}
版画
dataset: 30000000000013b
Class 1
Size 4
Sign -1
Order 0
Precision 32
NDims -1
NMembers -1
detect: 30000000000000c
Class 0
Size 4
Sign 1
Order 0
Precision 32
NDims -1
NMembers -1
至少我们知道 HST_FLOAT (class 1) 是必需的。让我们修改 array_2d_t:
using array_2d_t = boost::multi_array<float, 2>;
array_2d_t a(boost::extents[11214][3]);
这至少使数据看起来相似。让我们...天真地尝试阅读：
h5xx::read_dataset(ds, a);
哎呀，可预见的抛出
terminate called after throwing an instance of 'h5xx::error'
what(): /home/sehe/Projects/Whosebug/deps/h5xx/h5xx/dataset/boost_multi_array.hpp:176:read_dataset(): dataset "/particles/lipi
ds/box/positions/value" and target array have mismatching dimensions
不用担心，我们可以猜到：
using array_3d_t = boost::multi_array<float, 3>;
array_3d_t a(boost::extents[10][11214][3]);
h5xx::read_dataset(ds, a);
至少这个确实有效。调整打印功能：
template <typename T> void print_array(T const& array) {
for (auto const& row : array) {
for (auto v : row) printf("%5f ", v);
printf("\n");
}
}
现在我们可以打印第一帧了：
h5xx::read_dataset(ds, a);
print_array(*a.begin()); // print the first frame
这会打印：
80.480003 35.360001 4.250000
37.450001 3.920000 3.960000
18.530001 -9.690000 4.680000
55.389999 74.339996 4.600000
22.110001 68.709999 3.850000
-4.130000 24.040001 3.730000
40.160000 6.390000 4.730000
-5.400000 35.730000 4.850000
36.669998 22.450001 4.080000
-3.680000 -10.660000 4.180000
(...)
结帐 h5ls -r -d xaa.h5/particles/lipids/box/positions/value:
particles/lipids/box/positions/value Dataset {75/Inf, 11214, 3}
Data:
(0,0,0) 80.48, 35.36, 4.25, 37.45, 3.92, 3.96, 18.53, -9.69, 4.68,
(0,3,0) 55.39, 74.34, 4.6, 22.11, 68.71, 3.85, -4.13, 24.04, 3.73,
(0,6,0) 40.16, 6.39, 4.73, -5.4, 35.73, 4.85, 36.67, 22.45, 4.08, -3.68,
(0,9,1) -10.66, 4.18, 35.95, 36.43, 5.15, 57.17, 3.88, 5.08, -23.64,
(0,12,1) 50.44, 4.32, 6.78, 8.24, 4.36, 21.34, 50.63, 5.21, 16.29,
(0,15,1) -1.34, 5.28, 22.26, 71.25, 5.4, 19.76, 10.38, 5.34, 78.62,
(0,18,1) 11.13, 5.69, 22.14, 59.7, 4.92, 15.65, 47.28, 5.22, 82.41,
(0,21,1) 2.09, 5.24, 16.87, -11.68, 5.35, 15.54, -0.63, 5.2, 81.25,
(...)
最后一步：添加切片
array_2d_t read_frame(int frame_no) {
h5xx::file xaa("xaa.h5", h5xx::file::mode::in);
h5xx::group g(xaa, "particles/lipids/box/positions");
h5xx::dataset ds(g, "value");
array_2d_t a(boost::extents[11214][3]);
std::vector offsets{frame_no, 0, 0}, counts{1, 11214, 3};
h5xx::slice slice(offsets, counts);
h5xx::read_dataset(ds, a, slice);
return a;
}
给你。现在我们可以打印任何帧了：
print_array(read_frame(0));
打印和以前一样。让我们试试最后一帧：
print_array(read_frame(9));
版画
79.040001 36.349998 3.990000
37.250000 3.470000 4.140000
18.600000 -9.270000 4.900000
55.669998 75.070000 5.370000
21.920000 67.709999 3.790000
-4.670000 24.770000 3.690000
40.000000 6.060000 5.240000
-5.340000 36.320000 5.410000
36.369999 22.490000 4.130000
-3.520000 -10.430000 4.280000
(...)
再次检查 h5ls -r -d xaa.h5/particles/lipids/box/positions/value |& grep '(9' | head 确认：
(9,0,0) 79.04, 36.35, 3.99, 37.25, 3.47, 4.14, 18.6, -9.27, 4.9, 55.67,
(9,3,1) 75.07, 5.37, 21.92, 67.71, 3.79, -4.67, 24.77, 3.69, 40, 6.06,
(9,6,2) 5.24, -5.34, 36.32, 5.41, 36.37, 22.49, 4.13, -3.52, -10.43,
(9,9,2) 4.28, 35.8, 36.43, 4.99, 56.6, 4.09, 5.04, -23.37, 49.42, 3.81,
(9,13,0) 6.31, 8.83, 4.56, 22.01, 50.38, 5.43, 16.3, -2.92, 5.4, 22.02,
(9,16,1) 70.09, 5.36, 20.23, 11.12, 5.66, 78.48, 11.34, 6.09, 20.26,
(9,19,1) 61.45, 5.35, 14.25, 48.32, 5.35, 79.95, 1.71, 5.38, 17.56,
(9,22,1) -11.61, 5.39, 15.64, -0.19, 5.06, 80.43, 71.77, 5.29, 75.54,
(9,25,1) 35.14, 5.26, 22.45, 56.86, 5.56, 16.47, 52.97, 6.16, 20.62,
(9,28,1) 65.12, 5.26, 19.68, 71.2, 5.52, 23.39, 49.84, 5.28, 22.7,
完整列表
#include <boost/multi_array.hpp>
#include <h5xx/h5xx.hpp>
#include <iostream>
using array_2d_t = boost::multi_array<float, 2>;
template <typename T> void print_array(T const& array)
{
for (auto const& row : array) { for (auto v : row)
printf("%5f ", v);
printf("\n");
}
}
void dump(h5xx::group const& g, std::string indent = "") {
auto dd = g.datasets();
auto gg = g.groups();
for (auto it = dd.begin(); it != dd.end(); ++it) {
std::cout << indent << " ds:" << it.get_name() << std::endl;
}
for (auto it = gg.begin(); it != gg.end(); ++it) {
dump(*it, indent + "/" + it.get_name());
}
}
array_2d_t read_frame(int frame_no) {
h5xx::file xaa("xaa.h5", h5xx::file::mode::in);
h5xx::group g(xaa, "particles/lipids/box/positions");
h5xx::dataset ds(g, "value");
array_2d_t arr(boost::extents[11214][3]);
std::vector offsets{frame_no, 0, 0}, counts{1, 11214, 3};
h5xx::slice slice(offsets, counts);
h5xx::read_dataset(ds, arr, slice);
return arr;
}
int main()
{
print_array(read_frame(9));
}
我想读取一大块数据，它只是存储在一个数据集中的许多帧中的一帧。整个数据集的shape为(10, 11214,3)，10帧，每帧11214行4列。这里是file。我要读取的块的形状为 (11214,3)。我可以使用打印预定义数组，但我不确定如何从 hdf5 文件中读取数据。这是我的代码，
#include <h5xx/h5xx.hpp>
#include <boost/multi_array.hpp>
#include <iostream>
#include <vector>
#include <cstdio>
typedef boost::multi_array<int, 2> array_2d_t;
const int NI=10;
const int NJ=NI;
void print_array(array_2d_t const& array)
{
for (unsigned int j = 0; j < array.shape()[1]; j++)
{
for (unsigned int i = 0; i < array.shape()[0]; i++)
{
printf("%2d ", array[j][i]);
}
printf("\n");
}
}
void write_int_data(std::string const& filename, array_2d_t const& array)
{
h5xx::file file(filename, h5xx::file::trunc);
std::string name;
{
// --- create dataset and fill it with the default array data (positive values)
name = "integer array";
h5xx::create_dataset(file, name, array);
h5xx::write_dataset(file, name, array);
// --- create a slice object (aka hyperslab) to specify the location in the dataset to be overwritten
std::vector<int> offset; int offset_raw[2] = {4,4}; offset.assign(offset_raw, offset_raw + 2);
std::vector<int> count; int count_raw[2] = {2,2}; count.assign(count_raw, count_raw + 2);
h5xx::slice slice(offset, count);
}
}
void read_int_data(std::string const& filename)
{
h5xx::file file(filename, h5xx::file::in);
std::string name = "integer array";
// read and print the full dataset
{
array_2d_t array;
// --- read the complete dataset into array, the array is resized and overwritten internally
h5xx::read_dataset(file, name, array);
printf("original integer array read from file, negative number patch was written using a slice\n");
print_array(array);
printf("\n");
}
}
int main(int argc, char** argv)
{
std::string filename = argv[0];
filename.append(".h5");
// --- do a few demos/tests using integers
{
array_2d_t array(boost::extents[NJ][NI]);
{
const int nelem = NI*NJ;
int data[nelem];
for (int i = 0; i < nelem; i++)
data[i] = i;
array.assign(data, data + nelem);
}
write_int_data(filename, array);
read_int_data(filename);
}
return 0;
}
我正在使用 h5xx — HDF5 库 link 和 boost 库的基于模板的 C++ 包装器。 数据集存储在 particles/lipids/box/positions 路径中。数据集名称值包含帧。
argv[0]不是你想要的（参数从 1 开始，0 是程序名称）。还要考虑边界检查：std::vector<std::string> const args(argv, argv + argc); std::string const filename = args.at(1) + ".h5";直接初始化就可以了，不需要临时数组（multi_array干什么，不然？）
for (size_t i = 0; i < array.num_elements(); i++) array.data()[i] = i;或者实际上，让它成为一个算法：
std::iota(array.data(), array.data() + array.num_elements(), 0);与矢量相同：
std::vector<int> offset; int offset_raw[2] = {4,4}; offset.assign(offset_raw, offset_raw + 2); std::vector<int> count; int count_raw[2] = {2,2}; count.assign(count_raw, count_raw + 2);除了格式混乱之外，还可以简单地
std::vector offset{4,4}, count{2,2}; h5xx::slice slice(offset, count);
进入真正的问题
代码与文件无关。完全没有。我创建了一些 debug/tracing 代码来转储文件内容：
void dump(h5xx::group const& g, std::string indent = "") {
auto dd = g.datasets();
auto gg = g.groups();
for (auto it = dd.begin(); it != dd.end(); ++it) {
std::cout << indent << " ds:" << it.get_name() << "\n";
}
for (auto it = gg.begin(); it != gg.end(); ++it) {
dump(*it, indent + "/" + it.get_name());
}
}
int main()
{
h5xx::file xaa("xaa.h5", h5xx::file::mode::in);
dump(xaa);
}
版画
/particles/lipids/box/edges ds:box_size
/particles/lipids/box/edges ds:step
/particles/lipids/box/edges ds:time
/particles/lipids/box/edges ds:value
/particles/lipids/box/positions ds:step
/particles/lipids/box/positions ds:time
/particles/lipids/box/positions ds:value
现在我们可以深入到数据集。让我们看看是否可以找出正确的类型。它肯定不是 array_2d_t:
h5xx::dataset ds(xaa, "particles/lipids/box/positions/value");
array_2d_t a;
h5xx::datatype detect(a);
std::cout << "type: " << std::hex << ds.get_type() << std::dec << "\n";
std::cout << "detect: " << std::hex << detect.get_type_id() << std::dec << "\n";
版画
type: 30000000000013b
detect: 30000000000000c
这是类型不匹配。我想我也必须学会阅读那些乱码...
让我们添加一些诊断：
void diag_type(hid_t type)
{
std::cout << " Class " << ::H5Tget_class(type) << std::endl;
std::cout << " Size " << ::H5Tget_size(type) << std::endl;
std::cout << " Sign " << ::H5Tget_sign(type) << std::endl;
std::cout << " Order " << ::H5Tget_order(type) << std::endl;
std::cout << " Precision " << ::H5Tget_precision(type) << std::endl;
std::cout << " NDims " << ::H5Tget_array_ndims(type) << std::endl;
std::cout << " NMembers " << ::H5Tget_nmembers(type) << std::endl;
}
int main()
{
h5xx::file xaa("xaa.h5", h5xx::file::mode::in);
// dump(xaa);
{
h5xx::group g(xaa, "particles/lipids/box/positions");
h5xx::dataset ds(g, "value");
std::cout << "dataset: " << std::hex << ds.get_type() << std::dec << std::endl;
diag_type(ds.get_type());
}
{
array_2d_t a(boost::extents[NJ][NI]);
h5xx::datatype detect(a);
std::cout << "detect: " << std::hex << detect.get_type_id() << std::dec << std::endl;
diag_type(detect.get_type_id());
}
}
版画
dataset: 30000000000013b
Class 1
Size 4
Sign -1
Order 0
Precision 32
NDims -1
NMembers -1
detect: 30000000000000c
Class 0
Size 4
Sign 1
Order 0
Precision 32
NDims -1
NMembers -1
至少我们知道 HST_FLOAT (class 1) 是必需的。让我们修改 array_2d_t:
using array_2d_t = boost::multi_array<float, 2>;
array_2d_t a(boost::extents[11214][3]);
这至少使数据看起来相似。让我们...天真地尝试阅读：
h5xx::read_dataset(ds, a);
哎呀，可预见的抛出
terminate called after throwing an instance of 'h5xx::error'
what(): /home/sehe/Projects/Whosebug/deps/h5xx/h5xx/dataset/boost_multi_array.hpp:176:read_dataset(): dataset "/particles/lipi
ds/box/positions/value" and target array have mismatching dimensions
不用担心，我们可以猜到：
using array_3d_t = boost::multi_array<float, 3>;
array_3d_t a(boost::extents[10][11214][3]);
h5xx::read_dataset(ds, a);
至少这个确实有效。调整打印功能：
template <typename T> void print_array(T const& array) {
for (auto const& row : array) {
for (auto v : row) printf("%5f ", v);
printf("\n");
}
}
现在我们可以打印第一帧了：
h5xx::read_dataset(ds, a);
print_array(*a.begin()); // print the first frame
这会打印：
80.480003 35.360001 4.250000
37.450001 3.920000 3.960000
18.530001 -9.690000 4.680000
55.389999 74.339996 4.600000
22.110001 68.709999 3.850000
-4.130000 24.040001 3.730000
40.160000 6.390000 4.730000
-5.400000 35.730000 4.850000
36.669998 22.450001 4.080000
-3.680000 -10.660000 4.180000
(...)
结帐 h5ls -r -d xaa.h5/particles/lipids/box/positions/value:
particles/lipids/box/positions/value Dataset {75/Inf, 11214, 3}
Data:
(0,0,0) 80.48, 35.36, 4.25, 37.45, 3.92, 3.96, 18.53, -9.69, 4.68,
(0,3,0) 55.39, 74.34, 4.6, 22.11, 68.71, 3.85, -4.13, 24.04, 3.73,
(0,6,0) 40.16, 6.39, 4.73, -5.4, 35.73, 4.85, 36.67, 22.45, 4.08, -3.68,
(0,9,1) -10.66, 4.18, 35.95, 36.43, 5.15, 57.17, 3.88, 5.08, -23.64,
(0,12,1) 50.44, 4.32, 6.78, 8.24, 4.36, 21.34, 50.63, 5.21, 16.29,
(0,15,1) -1.34, 5.28, 22.26, 71.25, 5.4, 19.76, 10.38, 5.34, 78.62,
(0,18,1) 11.13, 5.69, 22.14, 59.7, 4.92, 15.65, 47.28, 5.22, 82.41,
(0,21,1) 2.09, 5.24, 16.87, -11.68, 5.35, 15.54, -0.63, 5.2, 81.25,
(...)
最后一步：添加切片
array_2d_t read_frame(int frame_no) {
h5xx::file xaa("xaa.h5", h5xx::file::mode::in);
h5xx::group g(xaa, "particles/lipids/box/positions");
h5xx::dataset ds(g, "value");
array_2d_t a(boost::extents[11214][3]);
std::vector offsets{frame_no, 0, 0}, counts{1, 11214, 3};
h5xx::slice slice(offsets, counts);
h5xx::read_dataset(ds, a, slice);
return a;
}
给你。现在我们可以打印任何帧了：
print_array(read_frame(0));
打印和以前一样。让我们试试最后一帧：
print_array(read_frame(9));
版画
79.040001 36.349998 3.990000
37.250000 3.470000 4.140000
18.600000 -9.270000 4.900000
55.669998 75.070000 5.370000
21.920000 67.709999 3.790000
-4.670000 24.770000 3.690000
40.000000 6.060000 5.240000
-5.340000 36.320000 5.410000
36.369999 22.490000 4.130000
-3.520000 -10.430000 4.280000
(...)
再次检查 h5ls -r -d xaa.h5/particles/lipids/box/positions/value |& grep '(9' | head 确认：
(9,0,0) 79.04, 36.35, 3.99, 37.25, 3.47, 4.14, 18.6, -9.27, 4.9, 55.67,
(9,3,1) 75.07, 5.37, 21.92, 67.71, 3.79, -4.67, 24.77, 3.69, 40, 6.06,
(9,6,2) 5.24, -5.34, 36.32, 5.41, 36.37, 22.49, 4.13, -3.52, -10.43,
(9,9,2) 4.28, 35.8, 36.43, 4.99, 56.6, 4.09, 5.04, -23.37, 49.42, 3.81,
(9,13,0) 6.31, 8.83, 4.56, 22.01, 50.38, 5.43, 16.3, -2.92, 5.4, 22.02,
(9,16,1) 70.09, 5.36, 20.23, 11.12, 5.66, 78.48, 11.34, 6.09, 20.26,
(9,19,1) 61.45, 5.35, 14.25, 48.32, 5.35, 79.95, 1.71, 5.38, 17.56,
(9,22,1) -11.61, 5.39, 15.64, -0.19, 5.06, 80.43, 71.77, 5.29, 75.54,
(9,25,1) 35.14, 5.26, 22.45, 56.86, 5.56, 16.47, 52.97, 6.16, 20.62,
(9,28,1) 65.12, 5.26, 19.68, 71.2, 5.52, 23.39, 49.84, 5.28, 22.7,
完整列表
#include <boost/multi_array.hpp>
#include <h5xx/h5xx.hpp>
#include <iostream>
using array_2d_t = boost::multi_array<float, 2>;
template <typename T> void print_array(T const& array)
{
for (auto const& row : array) { for (auto v : row)
printf("%5f ", v);
printf("\n");
}
}
void dump(h5xx::group const& g, std::string indent = "") {
auto dd = g.datasets();
auto gg = g.groups();
for (auto it = dd.begin(); it != dd.end(); ++it) {
std::cout << indent << " ds:" << it.get_name() << std::endl;
}
for (auto it = gg.begin(); it != gg.end(); ++it) {
dump(*it, indent + "/" + it.get_name());
}
}
array_2d_t read_frame(int frame_no) {
h5xx::file xaa("xaa.h5", h5xx::file::mode::in);
h5xx::group g(xaa, "particles/lipids/box/positions");
h5xx::dataset ds(g, "value");
array_2d_t arr(boost::extents[11214][3]);
std::vector offsets{frame_no, 0, 0}, counts{1, 11214, 3};
h5xx::slice slice(offsets, counts);
h5xx::read_dataset(ds, arr, slice);
return arr;
}
int main()
{
print_array(read_frame(9));
}