我正在努力访问值并将它们存储在boost multi_array容器中。我尝试使用索引方法([]和。at())访问元素，但抛出错误:没有匹配函数用于调用'boost::multi_array<float,>::data(int)'，但是我可以打印数据(参见代码)，但不知道如何存储它并再次访问它以进行进一步的计算。数据是二维的(112143,3)，但在此期间，我只想将其扁平化并拥有一个值序列。所以我的问题是如何访问元素以及如何将它们存储在容器中?
#include <boost/multi_array.hpp>
#include <boost/timer/timer.hpp>
#include <boost/range/irange.hpp>
#include <h5xx/h5xx.hpp>
#include <iostream>
#include <vector>
#include <algorithm>
#include <iterator>
#include <string>
using array_2d_t = boost::multi_array<float, 2>;
//using array_2d_t = boost::multi_array<float, 3>;
template <typename T>
void print_array(T const& array)
{
for (auto const& row : array)
{ for (auto v : row)
printf("%10f ", v);
printf("n"); //prints a new line similar t0 n
}
}
h5xx::dataset open_dataset(std::string const& filename) {
h5xx::file xaa(filename, h5xx::file::mode::in);
h5xx::group g(xaa, "particles/lipids/box/positions");
return h5xx::dataset(g, "value");
}
std::vector<float> cell_from_all_frames(h5xx::dataset& ds, size_t row, size_t col) {
// determine dataset shape: frames, particle count, space dimension
auto ds_shape = h5xx::dataspace(ds).extents<3>();
std::vector<float> cells(ds_shape[0]); // number of frames
std::vector<hsize_t> offsets{0, row, col};
std::vector<hsize_t> counts{ds_shape[0], 1, 1};
h5xx::slice slice(offsets, counts);
h5xx::read_dataset(ds, cells, slice);
return cells;
}
array_2d_t read_frame(std::string const& filename, unsigned frame_no) {
//h5xx::file xaa("../../data/xaa.h5", h5xx::file::mode::in);
h5xx::file xaa(filename, h5xx::file::mode::in);
h5xx::group g(xaa, "particles/lipids/box/positions");
h5xx::dataset ds(g, "value");
// determine dataset shape: frames, particle count, space dimension
auto ds_shape = h5xx::dataspace(ds).extents<3>();
array_2d_t arr(boost::extents[ds_shape[1]][ds_shape[2]]);
std::vector<hsize_t> offsets{frame_no, 0, 0};
std::vector<hsize_t> counts{1, arr.shape()[0], arr.shape()[1]};
h5xx::slice slice(offsets, counts);
h5xx::read_dataset(ds, arr, slice);
return arr;
}
int main(int argc, char const* argv[])
{
if (argc < 2) {
std::cout << "Usage: " << argv[0] << " input.h5" << std::endl;
return -1;
}
auto ds = open_dataset(argv[1]);
std::vector<float> first_cells = cell_from_all_frames(ds, 0, 0);
// set up multi-tau correlator for the computation of time correlation functions
size_t nsamples = 10; // FIXME obtain these parameters from HDF5 file. These 10 elements would be first element of first row, first element of 11214 row, first element of 11214*2 row, first element of 11214*3 row ,..., first element of 11214*10 row.
return 0;
}
在main()中，我从函数read_frame读取数据，并尝试将其传递给nsamples。我已经尝试了一些东西，但它不起作用!!
您可以选择。
商店吗?
array_2d_t frame = read_frame(filename, 1);
访问元素?
// access individual elements:
float ele = frame[0][3];
// or with index list:
std::array<int, 2> indices{0,3};
ele = frame(indices);
或者，根据您的需要，提供数组的平面视图:
boost::multi_array_ref<float, 1> sequence(frame.origin(), boost::extents[frame.num_elements()]);
fmt::print("Sum of all {} elements: {}n",
sequence.size(),
std::accumulate(sequence.begin(), sequence.end(), 0.f));
事实上，你可以就地重塑，但你不能改变维度，所以你得到1 &;row&;在所有单元格中:
frame.reshape(std::array<size_t, 2> {1, frame.num_elements()});
// now the first "row" is the full sequence:
auto&& sequence = frame[0];
fmt::print("Sum of all {} elements: {}n",
sequence.size(),
std::accumulate(sequence.begin(), sequence.end(), 0.f));
对于切片/重新索引有很多选择，有或没有跨步，但我参考Boost文档来避免不必要的复杂化。
现场演示
#include <boost/multi_array.hpp>
#include <fmt/ranges.h>
#include <h5xx/h5xx.hpp>
#include <iostream>
#include <iterator>
using array_2d_t = boost::multi_array<float, 2>;
h5xx::dataset open_dataset(std::string const& filename) {
h5xx::file xaa(filename, h5xx::file::mode::in);
h5xx::group g(xaa, "particles/lipids/box/positions");
return h5xx::dataset(g, "value");
}
array_2d_t read_frame(h5xx::dataset& ds, unsigned frame_no) {
auto ds_shape = h5xx::dataspace(ds).extents<3>();
array_2d_t arr(boost::extents[ds_shape[1]][ds_shape[2]]);
std::vector<hsize_t> offsets{frame_no, 0, 0};
std::vector<hsize_t> counts{1, arr.shape()[0], arr.shape()[1]};
h5xx::slice slice(offsets, counts);
h5xx::read_dataset(ds, arr, slice);
return arr;
}
std::vector<float> cell_from_all_frames(h5xx::dataset& ds, size_t row, size_t col) {
// determine dataset shape: frames, particle count, space dimension
auto ds_shape = h5xx::dataspace(ds).extents<3>();
std::vector<float> cells(ds_shape[0]); // number of frames
std::vector<hsize_t> offsets{0, row, col};
std::vector<hsize_t> counts{ds_shape[0], 1, 1};
h5xx::slice slice(offsets, counts);
h5xx::read_dataset(ds, cells, slice);
return cells;
}
int main(int argc, char const* argv[])
{
if (argc < 2) {
std::cout << "Usage: " << argv[0] << " input.h5" << std::endl;
return -1;
}
auto ds = open_dataset(argv[1]);
array_2d_t frame = read_frame(ds, 1);
// access individual elements:
[[maybe_unused]] float ele = frame[0][2];
// or with index list:
std::array<int, 2> indices{0,2};
ele = frame(indices);
{
boost::multi_array_ref<float, 1> sequence(frame.origin(), boost::extents[frame.num_elements()]);
fmt::print("Sum of all {} elements: {}n",
sequence.size(),
std::accumulate(sequence.begin(), sequence.end(), 0.f));
}
{
// in fact yuou might reshape in-place, but then you cannot change dimensiaonality
frame.reshape(std::array<size_t, 2> {1, frame.num_elements()});
// now the first "row" is the full sequence:
auto&& sequence = frame[0];
fmt::print("Sum of all {} elements: {}n",
sequence.size(),
std::accumulate(sequence.begin(), sequence.end(), 0.f));
}
{
std::vector<float> first_cells = cell_from_all_frames(ds, 0, 0);
fmt::print("Sum of all {} first cells: {}n",
first_cells.size(),
std::accumulate(first_cells.begin(), first_cells.end(), 0.f));
}
}
用你的xaa。H5 from a while ago:
Sum of all 33642 elements: 737589.1
Sum of all 33642 elements: 737589.1
Sum of all 75 first cells: 6053.3496