HDF5 wrapper for use with Eigen
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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:

  1. Opening HDF5 Files in read only, read/write, truncate modes
  2. Given an HDF5 file create subsequent groups, or datasets
  3. Given a group create more subgroups or datasets
  4. 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() {
    return 0;

HDF5 Primer

An HDF5 file is a container for two kinds of objects:

  1. datasets - array like collections of data (Eigen data in this case)

  2. 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.

  1. build_eigen.sh - Install Eigen to /usr/local
  2. build_hdf5.sh - Build and install HDF5
  3. build_cmake.sh = Build cmake from source

From the source directory:

mkdir build && cd build
cmake ..
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)

Eigen Sizes that are/will be implemented

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: