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README | ||
README.md | ||
trex.org |
TREXIO
TREX library for efficient I/O.
Minimal requirements (for users):
- Autotools (autoconf >= 2.69, automake >= 1.11, libtool >= 2.2) or CMake (>= 3.16)
- C compiler (gcc/icc/clang)
- Fortran compiler (gfortran/ifort)
- HDF5 library (>= 1.8) [optional, recommended for high performance]
Installation procedure from the tarball (for users):
- Download the
trexio-<version>.tar.gz
file gzip -cd trexio-<version>.tar.gz | tar xvf -
cd trexio-<version>
./configure
make
make check
sudo make install
Note: on systems with no sudo
access, one can
replace ./configure
with
./configure prefix=${PWD}/build
in order to execute
make install/uninstall
commands without sudo
privileges.
Note: when linking against an MPI-enabled HDF5 library one
usually has to specify the MPI wrapper for the C compiler by adding,
e.g., CC=mpicc
to the ./configure
command.
Additional requirements (for developers):
- python3 (>= 3.6)
- Emacs (>= 26.0)
- SWIG (>= 4.0) [required for the Python API]
Installation procedure from the GitHub repo clone (for developers):
git clone https://github.com/TREX-CoE/trexio.git
cd trexio
./autogen.sh
./configure
make
make check
sudo make install
Installation procedure for CMake users (from the tarball or GitHub repo clone):
The aforementioned instructions rely on Autotools build system. CMake users can achieve the same with the following steps (an example of out-of-source build):
cmake -S. -Bbuild
cd build
make
ctest
(ormake test
)sudo make install
Note: on systems with no sudo
access, one can
add -DCMAKE_INSTALL_PREFIX=build
as an argument to the
cmake
command so that make install/uninstall
can be run without sudo
privileges.
Note: when linking against an MPI-enabled HDF5 library one
usually has to specify the MPI wrapper for the C compiler by adding,
e.g., -DCMAKE_C_COMPILER=mpicc
to the cmake
command.
Installation procedure for conda users
The official releases of TREXIO >2.0.0
are also
available via the conda-forge
channel. The pre-compiled
stable binaries of trexio
can be installed as follows:
conda install trexio -c conda-forge
More details can be found in the corresponding trexio-feedstock.
Note that both parallel (see mpi_openmpi
prefix) and serial
(nompi
) variants are provided.
Compilation without the HDF5 library
By default, the configuration step proceeds to search for the HDF5 library.
This search can be disabled if HDF5 is not present/installable on the
user machine. To build TREXIO without HDF5 back end, append
--without-hdf5
option to configure
script or
-DENABLE_HDF5=OFF
option to cmake
. For
example,
./configure --without-hdf5
cmake -S. -Bbuild -DENABLE_HDF5=OFF
Linking to your program
The make install
command takes care of installing the
TREXIO shared library on the user machine. Once installed, add
-ltrexio
to the list of compiler options.
In some cases (e.g. when using custom prefix
during
configuration), the TREXIO library might end up installed in a
directory, which is absent in the default $LIBRARY_PATH
. In
order to link the program against TREXIO, the search paths can be
modified as follows:
export LIBRARY_PATH=$LIBRARY_PATH:<path_to_trexio>/lib
(same holds for $LD_LIBRARY_PATH
). The
<path_to_trexio>
has to be replaced by the prefix
used during the installation.
If your project relies on CMake build system, feel free to use the FindTREXIO.cmake module to find and link TREXIO library automatically.
In Fortran applications, make sure that the trexio_f.f90
module file is included in the source tree. You might have to manually
copy it into your program source directory. The
trexio_f.f90
module file can be found in the
include/
directory of the TREXIO source code
distribution.
Note: there is no need to include
trexio.h
header file during compilation of Fortran
programs. Only the installed library and the Fortran module file are
required.
Naming convention
The primary TREXIO API is composed of the following functions:
trexio_open
trexio_write_[group]_[variable]
trexio_read_[group]_[variable]
trexio_has_[group]_[variable]
trexio_close
where [group]
and [variable]
substitutions
correspond to the contents of the trex.json
configuration
file (for more details, see the corresponding documentation
page). For example, consider the coord
variable (array),
which belongs to the nucleus
group. The TREXIO user can
write or read it using trexio_write_nucleus_coord
or
trexio_read_nucleus_coord
functions, respectively.
Note: the [variable]
names have to be unique only within
the corresponding parent [group]
. There is no naming
conflict when, for example, num
variable exists both in the
nucleus
group (i.e. the number of nuclei) and in the
mo
group (i.e. the number of molecular orbitals). These
quantities can be accessed using the corresponding
trexio_[has|read|write]_nucleus_num
and
trexio_[has|read|write]_mo_num
, respectively.
Python API
For more details regarding the installation and usage of the TREXIO Python API, see this page.
The aforementioned instructions are adapted for users installing from the source code distribution (periodically updated). In order to install the Python API with the latest changes, follow the developer installation guide and run the following command in the end
make python-install
Note: this implies that both HDF5 and SWIG are installed and available. At the moment, it is not possible to configure the Python API without HDF5 library.
We rely on the pytest
package for unit testing. It can
be installed via pip install pytest
. To test the
installation, run
make python-test
We highly recommend to use virtual environments to avoid compatibility issues and to improve reproducibility.
Tutorial
TREXIO tutorials in Jupyter notebook format can be found in the corresponding GitHub repository or on Binder.
For example, the tutorial covering TREXIO basics using benzene molecule as an example can be viewed and executed online by clicking on this badge:
Documentation
Documentation generated from TREXIO org-mode files.
Miscellaneous
Note: The code should be compliant with the C99 CERT
C coding standard. This can be checked with the
cppcheck
tool.
TREX: Targeting Real Chemical Accuracy at the Exascale project has received funding from the European Union’s Horizon 2020 - Research and Innovation program - under grant agreement no. 952165. The content of this document does not represent the opinion of the European Union, and the European Union is not responsible for any use that might be made of such content.