ASE (Atomic Simulation Environment) provides a set of Python tools for setting, running, and analysing atomic simulations. We have developed an ABACUS calculator (ase-abacus) to be used together with the ASE tools, which exists as an external project with respect to ASE and is maintained by ABACUS developers.
git clone https://github.com/deepprinciple/Abacus-Python.git
cd Abacus-Python
pip install .Another direct way:
pip install git+https://github.com/deepprinciple/Abacus-Python.gitABACUS supports two types of basis sets: PW, LCAO. The path of pseudopotential and numerical orbital files can be set throught the environment variables ABACUS_PP_PATH and ABACUS_ORBITAL_PATH, respectively, e.g.:
PP=${HOME}/pseudopotentials
ORB=${HOME}/orbitals
export ABACUS_PP_PATH=${PP}
export ABACUS_ORBITAL_PATH=${ORB}For PW calculations, only ABACUS_PP_PATH is needed. For LCAO calculations, both ABACUS_PP_PATH and ABACUS_ORBITAL_PATH should be set.
Also, one can manally set the paths of PP and ORB when using ABACUS calculator in ASE.
The default initialization command for the ABACUS calculator is
from ase_abacus.calculators.abacus import AbacusIn order to run a calculation, you have to ensure that at least the following parameters are specified, either in the initialization or as environment variables:
| keyword | description |
|---|---|
pp |
dict of pseudopotentials for involved elememts, such as pp={'Al':'Al_ONCV_PBE-1.0.upf',...}. |
pseudo_dir |
directory where the pseudopotential are located, Can also be specified with the ABACUS_PP_PATH environment variable. Default: pseudo_dir=./. |
basis |
dict of orbital files for involved elememts, such as basis={'Al':'Al_gga_10au_100Ry_4s4p1d.orb'}.It must be set if you want to do LCAO calculations. But for pw calculations, it can be omitted. |
basis_dir |
directory where the orbital files are located, Can also be specified with the ABACUS_ORBITAL_PATHenvironment variable. Default: basis_dir=./. |
xc |
which exchange-correlation functional is used. An alternative way to set this parameter is via seting dft_functional which is an ABACUS parameter used to specify exchange-correlation functional |
kpts |
a tuple (or list) of 3 integers kpts=(int, int, int), it is interpreted as the dimensions of a Monkhorst-Pack grid, when kmode is Gamma or MP. It is interpreted as k-points, when kmode is Direct,Cartesian or Line, and knumber should alsobe set in these modes to denote the number of k-points. Some other parameters for k-grid settings: including koffset and kspacing. |
For more information on pseudopotentials and numerical orbitals, please visit [ABACUS]. The elaboration of input parameters can be found here.
The input parameters can be set like::
# for ABACUS calculator
calc = Abacus(profile=profile,
ecutwfc=100,
scf_nmax=100,
smearing_method='gaussian',
smearing_sigma=0.01,
basis_type='pw',
ks_solver='dav',
calculation='scf',
pp=pp,
basis=basis,
kpts=kpts)The command to run jobs can be set by specifying AbacusProfile::
from ase_abacus.calculators.abacus import AbacusProfile
# for OpenMP setting inside python env
import os
os.environ("OMP_NUM_THREADS") = 1
# for MPI setting used in abacus
mpi_num = 4
# for ABACUS Profile
abacus = '/usr/local/bin/abacus' # specify abacus exec
profile = AbacusProfile(command=f'mpirun -n {mpi_num} {abacus}') # directly the command for running ABACUSin which abacus sets the absolute path of the abacus executable.
After molecular dynamics calculations, the log file running_md.log can be read. If the 'STRU_MD_*' files are not continuous (e.g. 'STRU_MD_0', 'STRU_MD_5', 'STRU_MD_10'...), the index parameter of read should be as a slice object. For example, when using the command read('running_md.log', index=slice(0, 15, 5), format='abacus-out') to parse 'running_md.log', 'STRU_MD_0', 'STRU_MD_5' and 'STRU_MD_10' will be read.
The MD_dump file is also supported to be read-in by read('MD_dump', format='abacus-md')
SPAP (Structure Prototype Analysis Package) is written by Dr. Chuanxun Su to analyze symmetry and compare similarity of large amount of atomic structures. The coordination characterization function (CCF) is used to measure structural similarity. An unique and advanced clustering method is developed to automatically classify structures into groups.
If you use this program and method in your research, please read and cite the publication:
Su C, Lv J, Li Q, Wang H, Zhang L, Wang Y, Ma Y. Construction of crystal structure prototype database: methods and applications. J Phys Condens Matter. 2017 Apr 26;29(16):165901.
and you should install it first with command pip install spap.
To run the tests, you need to install the package with pip install -e '.[dev]' first.
Then run the commands as follows in the test/ directory:
OMP_NUM_THREADS=1 pytest -q -rsx \
--abacus-exec "mpirun -n 12 abacus" \
--abacus-pp-dir "/path/to/your/pseudopotentials/" \
--abacus-basis-dir "/path/to/your/orbitals/" \
--abacus-rundir "/path/to/your/abacus-run-test-dir/"