librascal is a versatile and scalable fingerprint and machine learning code. It focuses on the efficient construction of representations of atomic structures, that can then be fed to any supervised or unsupervised learning algorithm. Simple regression code will be included for testing purposes, but the long-term goal is to develop a separate collection of tools to this end.
librascal is currently considered a standalone code. However, we aim to provide enough flexibility to interface it with other codes such as LAMMPS and PLUMED-2.0. It can be used as a C++ library as well as a python module. To be able to call it from python, we have used the pybind11 library.
Although at the moment is a serial-only code, we aim to write it in MPI so that it will be possible to take advantage of parallelization to speed up the calculations significantly. Parallelization is possible especially over atoms in a structure (for large structures), over structures in a collection (for large collections of small structures), or over components of a representation (for representations with a large number of independent functions or components).
It comes with a GNU Lesser General Public License of version 3, which means that it can be modified and freely distributed, although we take no responsibility for its misuse.
For more information, have a look at the documentation!
The code is currently in the alpha development phase; it is not yet suitable for public use. Nevertheless, there is a significant amount of functionality (including two tutorials) currently working and available to test if you’re feeling adventurous. Feedback and bug reports are welcome, as long as you keep the above in mind.
See Helpers for Developers below for some essential tools if you want to help develop libRascal. Be sure to also read CONTRIBUTING.rst if you plan on making a contribution.
The installation of the library for python use can be done simply with:
pip install .
assuming that python 3.5 (or higher) and gcc or clang are available.
Before installing librascal, please make sure you have at least the following packages installed:
Package | Required version |
---|---|
gcc (g++) | 4.9 or higher |
clang | 4.0 or higher |
cmake | 2.8 or higher |
python | 3.6 or higher |
numpy | 1.13 or higher |
ASE | 3.18 or higher |
Other necessary packages (such as Eigen and PyBind11) are downloaded automatically when compiling Rascal.
The following packages are required for building some optional features:
Feature | Package | Required version |
---|---|---|
Documentation | pandoc | (latest) |
sphinx | 2.1.2 | |
breathe | 4.13.1 | |
nbsphinx | (latest) |
To compile the code it is necessary to have CMake 3.0 and a C++ compiler supporting C++14. During the configuration, it will automatically try to download the external libraries on which it depends:
- Eigen
- Pybind11
- Boost (only the unit test framework library)
- Python3
And the following libraries to build the documentation:
- Doxygen
- Sphinx
- Breathe
Beware, Python3 is mandatory. The code won’t work with a Python version older than 3.
You can then use pip to install all python packages required for the usage and development of rascal:
pip install -r requirements.txt
To configure and compile the code with the default options, on *nix systems (Windows is not supported):
mkdir build
cd build
cmake ..
make
The library supports several alternative builds that have additional
dependencies. Note that the ncurses
GUI for cmake (ccmake) is quite
helpful to customize the build options.
Librascal source code is extensively tested (both c++ and python). The BOOST unit_test_framework is required to build the tests (see BOOST.md for further details on how to install the boost library). To build and run the tests:
cd build
cmake -DBUILD_TESTS=ON ..
make
ctest -V
You can also run the tests with Valgrind (a memory-error checker) by passing
-DRASCAL_TESTS_USE_VALGRIND=ON
to cmake
.
In addition to testing the behaviour of the code, the test suite also check for formatting compliance with the clang-format and autopep8 packages (these dependencies are optional). To install these dependencies on Ubuntu:
sudo apt-get install clang-format
pip3 install autopep8
Several build types are available Release (default), Debug and RelWithDebInfo. To build an alternative mode
cd build
cmake -DCMAKE_BUILD_TYPE=Debug
..
make
Or
cd build
cmake -DCMAKE_BUILD_TYPE=RelWithDebInfo \\
CMAKE_C_FLAGS_RELWITHDEBUBINFO="-03 -g -DNDEBUG" ..
make
The documentation relies on the sphinx (with nbsphinx and breathe extensions), doxygen, pandoc, and graphviz packages. To install them on ubuntu:
pip3 install sphinx sphinx_rtd_theme breathe nbsphinx
sudo apt-get install pandoc doxygen graphviz
Then to build the documentation run:
cd build
cmake -DBUILD_DOC=ON ..
make doc
and open :file:`build/docs/html/index.html` in a browser.
Librascal relies on the pybind11 library to automate the generation of the python bindings which are built by default. Nevertheless, to build only the c++ library:
cd build
cmake -DBUILD_BINDINGS=OFF ..
make
To install the python library with c++ bindings:
pip install .
To remove all the cmake files/folders except for the external library (enable glob and remove):
shopt -s extglob
rm -fr -- !(external|third-party)
To help developers conform their contribution to the coding convention, the formatting of new functionalities can be automated using clang-format (for the c++ files) and autopep8 (for the python files). The .clang-format and .pycodestyle files define common settings to be used.
To enable these functionalities (optional) you can install these tools with:
sudo apt-get install clang-format
pip install autopep8
The automatic formating of the c++ and python files can be trigered by:
cd build
cmake ..
make pretty-cpp
make pretty-python
Please use these tools with caution as they can potentially introduce unwanted changes to the code. If code needs to be specifically excluded from auto formatting, e.g. a matrix which should be human-readable, code comments tells the formatters to ignore lines:
C++
// clang-format off SOME CODE TO IGNORE // clang-format on
python
SOME LINE TO IGNORE # noqa
where
noqa
stands forno
q
ualitya
ssurance.
If you are contributing any code in IPython/Jupyter notebooks, please install the nbstripout extension (available e.g. on github and PyPI). After installing, activate it for this project by running:
nbstripout --install --attributes .gitattributes
from the top-level repository directory. Please note that that
nbstripout
will not strip output from cells with the metadata fields
keep_output
or init_cell
set to True
, so use these fields
judiciously. You can ignore these settings with the following command:
git config filter.nbstripout.extrakeys '\
cell.metadata.keep_output cell.metadata.init_cell'
(The keys metadata.kernel_spec.name
and
metadata.kernel_spec.display_name
may also be useful to reduce diff
noise.)
Nonetheless, it is highly discouraged to contribute code in the form of
notebooks; even with filters like nbstripout
they're a hassle to use
in version control. Use them only for tutorials or stable examples that
are either meant to be run interactively or are meant to be processed by
sphinx (nbsphinx) for
inclusion in the
tutorials page.
- Common cmake flags:
- -DCMAKE_CXX_COMPILER
- -DCMAKE_C_COMPILER
- -DCMAKE_BUILD_TYPE
- -DBUILD_BINDINGS
- -DINSTALL_PATH
- -DBUILD_DOC
- -DBUILD_TESTS
- Special flags:
- -DBUILD_BINDINGS:
- ON (default) -> build python binding
- OFF -> does not build python binding
- -DINSTALL_PATH:
- empty (default) -> does not install in a custom folder
- custom string -> root path for the installation
- -DBUILD_BINDINGS:
To build librascal as a docker environment:
sudo docker build -t test -f ./docker/install_env.dockerfile .
sudo docker run -it -v /path/to/repo/:/home/user/ test