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This is a wrapper library for interfacing Eigen datatypes with the HDF5 file format.
It allows one to easily save/read Eigen data in an open and cross-platform and cross language manner.
The overall goal is to emulate h5py
in easy of use with numpy/Eigen based data.
It currently supports the following:
- Opening HDF5 Files in read only, read/write, truncate modes
- Given an HDF5 file create subsequent groups, or datasets
- Given a group create more subgroups or datasets
- Read/Write any Eigen variable (currently setup primarily for
Eigen::DenseBase
objects)
All of the functionality is included in the HDF5
namespace and is exposed to your program using
#include "hdf5.hpp"
There are several different modes for operating on files:
HDF5::File::ReadOnly; /**< Read only access */
HDF5::File::ReadWrite; /**< ReadWrite access */
HDF5::File::Truncate; /**< Overwrite a file if it exists or create a new one */
HDF5::File::Excl; /**< Only open if the file doesn't exist */
HDF5::File::Create; /**< Create a new file */
Here is a basic example of reading/writing Eigen matrices.
You can try this yourself using main
Look in the tests
directory for more examples
#include "hdf5.hpp"
#include <Eigen/Dense>
#include <iostream>
void write_data() {
Eigen::MatrixXd matrix(3, 3);
matrix << 1, 2, 3, 4, 5, 6, 7, 8, 9;
// open the file
HDF5::File hf = HDF5::File("filename.hdf5", HDF5::File::Truncate);
// write the data
hf.write("dataset_name", matrix);
std::cout << "Original Matrix: " << std::endl;
std::cout << matrix << std::endl;
}
void read_data() {
// open the file for reading
HDF5::File hf = HDF5::File("filename.hdf5", HDF5::File::ReadOnly);
Eigen::MatrixXd matrix;
hf.read("dataset_name", matrix);
std::cout << "Matrix read: " << std::endl;
std::cout << matrix << std::endl;
}
int main() {
write_data();
read_data();
return 0;
}
An HDF5 file is a container for two kinds of objects:
-
datasets - array like collections of data (Eigen data in this case)
-
groups - folder like containers that hold other datasets or groups
The important thing to remember is that within an HDF5 file, data is stored in a unix like file structure consisiting of a root group,
/
, and nested groups/datasets.
You can create any arbitrary number of groups:
HDF5::File hf = HDF5::File("filename.hdf5", HDF5::File::Truncate);
HDF5::Group group1 = hf.group("group_name");
HDF5::Group group2 = group1.group("group_name");
And any number of datasets within the groups, or within the root group (file)
HDF5::DataSet group1_dataset = group1.dataset("dataset_name", matrix);
HDF5::DataSet group2_dataset = group2.dataset("dataset_name", matrix);
HDF5::DataSet hf_dataset = hf.dataset("dataset_name", matrix);
Finally, if you only want to read/write directly without creating additional objects
group1.write("dataset_name", matrix);
hf.write("dataset_name", matrix);
This library depends on both Eigen
and HDF5
which can be installed using the included scripts.
build_eigen.sh
- InstallEigen
to/usr/local
build_hdf5.sh
- Build and installHDF5
build_cmake.sh
= Buildcmake
from source
From the source directory:
mkdir build && cd build
cmake ..
make
sudo checkinstall (or make install)
Which uses checkinstall
(sudo apt-get install checkinstall
) to allow one to easily uninstall
sudo dpkg -r fdcl-hdf5
To use the shared library in your own project, execute everything above then add the following to your project CMakeLists.txt
find_package(FDCL_HDF5 REQUIRED)
add_executable(<your_target> <source_files>)
target_link_libraries(<your_target> fdcl_hdf5)
Also all integers versions
VectorXd - Matrix<double, -1, 1> VectorXi - Matrix<int, -1, 1>
RowVectorXd - Matrix<double, 1, -1> RowVectorXi - Matrix<int, 1, -1>
Matrix<double, -1, -1> Matrix<double, -1, 3>
Matrix<double, 3, -1>
Matrix<double, 1, 18> Matirx<double, 18, 1>
Matrix<double, 3, 1> Matrix<double, 1, 3>
Matrix<double, 3, 3> All above implemented fro teh file
Matrix<double, 4, 1> Matrix<double, 1, 4>
Matrix<double, 15, 15>
This borrows heavily from lots of other great work: