/dflow-autotest

DPGEN autotest package based on dflow

Primary LanguagePythonMIT LicenseMIT

dflow-props

General properties test with VASP, ABACUS, and LAMMPS in autotest.

This workflow is a part of AI Square. We want to refract the autotest code based on dflow. This is "general properties test" (elastic parameters, EOS, surface energy, interstitial energy, vacancy energy and stacking fault energy supported so far) using VASP, LAMMPS, or ABACUS.

Easy Install:

pip install "git+https://github.com/ZLI-afk/dflow-autotest.git"

Quick Start

You can go to the example folder and there are some examples for reference. You can go to one of them and fill in the global.json file. Then you can submit the workflow.

If you want to use VASP code to do the DFT autotest, like the folder vasp_demo. You need to prepare INCAR, POTCAR, POSCAR, global.json(notice that json files for relaxation and properties task are needed as input arguments), then :

dflowprops param_relax.json param.props.json --vasp

If you want to run only relaxation or only propertie test (notice that properties test requires relaxation results under corresponding path under ./confs), for example of relaxation, just give one argument like:

dflowprops param_relax.json --vasp

This is same for the following case:

If you want to use ABACUS code, like the folder abacus_demo. You need to prepare INPUT, STRU, *.UPF, global.json and param_prop.json (notice that *.orb and KPT are optional ), then:

dflowprops param_relax.json param_props.json --abacus

If you want to use LAMMPS to do MD calculation, like the folder dp_demo. You need to prepare POSCAR, frozen_model.pb, global.json and param_prop.json, then:

dflowprops param_relax.json param_props.json --lammps

You can monitor the workflow process on the website.