HighFive - HDF5 header-only C++ Library

Brief

HighFive is a modern header-only C++11 friendly interface for libhdf5.

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

It integrates nicely with other CMake projects by defining (and exporting) a HighFive target.

Design

• Simple C++-ish minimalist interface
• No other dependency than libhdf5
• Zero overhead
• Support C++11

Feature support

• create/read/write files, datasets, attributes, groups, dataspaces.
• 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
• Advanced types: Compound, Enum, Arrays of Fixed-length strings, References
• etc... (see ChangeLog)

Dependencies

• hdf5 (dev)
• hdf5-mpi (optional, opt-in with -D*DHIGHFIVE_PARALLEL_HDF5*=ON)
• boost >= 1.41 (recommended, opt-out with -D*DHIGHFIVE_USE_BOOST*=OFF)
• eigen3 (optional, opt-in with -D*HIGHFIVE_USE_EIGEN*=ON)
• xtensor (optional, opt-in with -D*HIGHFIVE_USE_XTENSOR*=ON)

Examples

Write a std::vector<int> to 1D HDF5 dataset and read it back

 {c++}
#include <highfive/H5File.hpp>
 
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: H5File.hpp is the top-level header of HighFive core which should be always included.

Note: If you can use DataSpace::From on your data, you can combine the create and write into one statement. Such shortcut syntax is available for both createDataSet and createAttribute.

 {c++}
DataSet dataset = file.createDataSet("/dataset_one",  data);

Write a 2 dimensional C double float array to a 2D HDF5 dataset

See create_dataset_double.cpp

Write and read a matrix of double float (boost::ublas) to a 2D HDF5 dataset

See boost_ublas_double.cpp

Write and read a subset of a 2D double dataset

See select_partial_dataset_cpp11.cpp

Create, write and list HDF5 attributes

See create_attribute_string_integer.cpp

And others

See src/examples/ subdirectory for more info.

Compiling with HighFive

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

H5Easy

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 HIGHFIVE_USE_EIGEN),
  • xt::xarray and xt::xtensor (optional, enable CMake option HIGHFIVE_USE_XTENSOR).
  • cv::Mat_ (optional, enable CMake option HIGHFIVE_USE_OPENCV).
• Getting in a single line:
  • the size of a DataSet,
  • the shape of a DataSet.

Example

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

CMake integration

HighFive can easily be used by other C++ CMake projects.

You may use HighFive from a folder in your project (typically a git submodule).

cmake_minimum_required(VERSION 3.1 FATAL_ERROR)
project(foo)
set(CMAKE_CXX_STANDARD 11)
 
add_subdirectory(highfive_folder)
add_executable(bar bar.cpp)
target_link_libraries(bar HighFive)

Alternativelly you can install HighFive once and use it in several projects via find_package().

A HighFive target will bring the compilation settings to find HighFive headers and all chosen dependencies.

# ...
find_package(HighFive REQUIRED)
add_executable(bar bar.cpp)
target_link_libraries(bar HighFive)

Note: Like with other libraries you may need to provide CMake the location to find highfive: CMAKE_PREFIX_PATH=<highfive_install_dir>

Note: find_package(HighFive) will search dependencies as well (e.g. Boost if requested). In order to use the same dependencies found at HighFive install time (e.g. for system deployments) you may set HIGHFIVE_USE_INSTALL_DEPS=YES

Installing

When installing via CMake, besides the headers, a HighFiveConfig.cmake is generated which provides the HighFive target, as seen before. Note: You may need to set CMAKE_INSTALL_PREFIX: ```bash mkdir build && cd build

Look up HighFive CMake options, consider inspecting with <tt>ccmake</tt>

cmake .. -DHIGHFIVE_EXAMPLES=OFF -DCMAKE_INSTALL_PREFIX="<highfive_install_dir>" make install

### Test Compilation
As a header-only library, HighFive doesn't require compilation. You may however build tests and examples.
 
```bash
mkdir build && cd build
cmake ../
make  # build tests and examples
make test  # build and run unit tests

Note: Unit tests require Boost. In case it's unavailable you may use -DHIGHFIVE_USE_BOOST=OFF. HighFive with disable support for Boost types as well as unit tests (though most examples will build).

Contributors

See the list of contributors on GitHub

Originally created by Adrien Devresse adrie.nosp@m.n.de.nosp@m.vress.nosp@m.e@ep.nosp@m.fl.ch - Blue Brain Project

Maintained by the Computing/HPC team, Blue Brain Project - EPFL

License

Boost Software License 1.0