HighFive is a modern C++/C++11 friendly interface for libhdf5.

HighFive supports STL vector/string, Boost::UBLAS and Boost::Multi-array. It handles C++ from/to HDF5 automatic type mapping. HighFive does not require an additional library and supports both HDF5 thread safety and Parallel HDF5 (contrary to the official hdf5 cpp)

• Simple C++-ish minimalist interface
• No other dependency than libhdf5
• Zero overhead
• Support C++11 ( compatible with C++98 )

• libhdf5
• (optional) boost >= 1.41

HighFive can easily be used by other C++ CMake projects. Below is a very simple foo project creating a bar C++ program using HighFive library:

cmake_minimum_required(VERSION 3.0 FATAL_ERROR)
project(foo)
set(CMAKE_CXX_STANDARD 11)

find_package(HighFive 2.0 REQUIRED)
add_executable(bar bar.cpp)
target_include_directories(
  bar
  PUBLIC $<TARGET_PROPERTY:HighFive,INTERFACE_INCLUDE_DIRECTORIES>)
target_link_libraries(
  bar
  PUBLIC $<TARGET_PROPERTY:HighFive,INTERFACE_LINK_LIBRARIES>)

using namespace HighFive;
// we create a new hdf5 file
File file("/tmp/new_file.h5", File::ReadWrite | File::Create | File::Truncate);

std::vector<int> data(50, 1);

// let's create a dataset of native integer with the size of the vector 'data'
DataSet dataset = file.createDataSet<int>("/dataset_one",  DataSpace::From(data));

// let's write our vector of int to the HDF5 dataset
dataset.write(data);

// read back
std::vector<int> result;
dataset.read(result);

Note: if you can use DataSpace::From on your data, you can combine the create and write into one statement:

DataSet dataset = file.createDataSet("/dataset_one",  data);

This works with createAttribute, as well.

See create_dataset_double.cpp

See boost_ublas_double.cpp

See select_partial_dataset_cpp11.cpp

See create_attribute_string_integer.cpp

See src/examples/ subdirectory for more info.

c++ -o program -I/path/to/highfive/include source.cpp  -lhdf5

For several 'standard' use cases the HighFive/H5Easy.hpp interface is available. It allows:

• Reading/writing in a single line of:

  • scalars (to/from an extendible DataSet),
  • strings,
  • vectors (of standard types),
  • Eigen::Matrix (optional, enable CMake option USE_EIGEN),
  • xt::xarray and xt::xtensor (optional, enable CMake option USE_XTENSOR).

• Getting in a single line:

  • the size of a DataSet,
  • the shape of a DataSet.

The general idea is to

#include <HighFive/H5Easy.hpp>

int main()
{
    H5Easy::File file("example.h5", H5Easy::File::Overwrite);

    int A = ...;

    H5Easy::dump(file, "/path/to/A", A);

    A = H5Easy::load<int>(file, "/path/to/A");
}

whereby the int type of this example can be replaced by any of the above types. See easy_load_dump.cpp for more details.

Note that classes such as H5Easy::File are just short for the regular HighFive classes (in this case HighFive::File). They can thus be used interchangeably.

Remember: Compilation is not required. Used only for unit test and examples

mkdir build; pushd build
cmake ../
make
make test

• create/read/write file, dataset, group, dataspace.
• automatic memory management / ref counting
• automatic conversion of std::vector and nested std::vector from/to any dataset with basic types
• automatic conversion of std::string to/from variable length string dataset
• selection() / slice support
• parallel Read/Write operations from several nodes with Parallel HDF5
• support HDF5 attributes

• Adrien Devresse [email protected] - Blue Brain Project
• Ali Can Demiralp [email protected] -
• Fernando Pereira [email protected] - Blue Brain Project
• Stefan Eilemann [email protected] - Blue Brain Project
• Tristan Carel [email protected] - Blue Brain Project
• Wolf Vollprecht [email protected] - QuantStack
• Tom de Geus [email protected] - EPFL

Boost Software License 1.0