AGAT (Atomic Graph ATtention networks)
Using AGAT
The documentation of AGAT API is available.
Installation
Install with conda environment
-
Download the
agat_linux_gpu_cu124.ymlfile. -
Run
conda env create -f agat_linux_gpu_cu124.yml
-
Install CUDA and CUDNN [Optional].
- For HPC, you may load CUDA by checking
module av, or you can contact your administrator for help. - CUDA Toolkit
- cuDNN
- For HPC, you may load CUDA by checking
-
More installation options: Customized installation
Quick start
Prepare VASP calculations
Run VASP calculations at this step.
Collect paths of VASP calculations
-
We provided examples of VASP outputs at VASP_calculations_example.
-
Find all directories containing
OUTCARfile:find . -name OUTCAR > paths.log -
Remove the string 'OUTCAR' in
paths.log.sed -i 's/OUTCAR$//g' paths.log -
Specify the absolute paths in
paths.log.sed -i "s#^.#${PWD}#g" paths.log
Build database
from agat.data import BuildDatabase
if __name__ == '__main__':
database = BuildDatabase(mode_of_NN='ase_dist', num_of_cores=16)
dataset = database.build()
Train AGAT model
from agat.model import Fit
f = Fit()
f.fit()
Application (geometry optimization)
from ase.optimize import BFGS
from ase.io import read
from agat.app import AgatCalculator
model_save_dir = 'agat_model'
graph_build_scheme_dir = 'dataset'
atoms = read('POSCAR')
calculator=AgatCalculator(model_save_dir,
graph_build_scheme_dir)
atoms = Atoms(atoms, calculator=calculator)
dyn = BFGS(atoms, trajectory='test.traj')
dyn.run(fmax=0.05)
Application (high-throughput prediction)
from agat.app.cata import HtAds
model_save_dir = 'agat_model'
graph_build_scheme_dir = 'dataset'
formula='NiCoFePdPt'
ha = HtAds(model_save_dir=model_save_dir, graph_build_scheme_dir=graph_build_scheme_dir)
ha.run(formula=formula)
Tips:
See API doc for more details. For example:
- Manipulating
agat.dataset: - AGAT molecular dynamics simulations:
- More options for controlling the AGAT training process: docs/sphinx/source/Default parameters.md.
Some default parameters
agat/default_parameters.py; Explanations: docs/sphinx/source/Default parameters.md.
Package structure
Change log
Please check Change_log.md
1 maintainer
Release files for agat 9.1.1
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| agat-9.1.1.tar.gz | 80.3 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| agat-9.1.1-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 165.3 kB
Release files / agat-9.1.1.tar.gz
| Download URL | agat-9.1.1.tar.gz |
|---|---|
| Size | 80.3 kB |
| Tags | Source |
|
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Release files / agat-9.1.1-py3-none-any.whl
| Download URL | agat-9.1.1-py3-none-any.whl |
|---|---|
| Size | 85.0 kB |
| Tags | Python 3 |
|
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| Uploaded via |
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