From 9b307a42bc6f5fc68b3f91160b257bfcf4320097 Mon Sep 17 00:00:00 2001 From: qzhu2017 Date: Wed, 3 Mar 2021 17:56:42 -0800 Subject: [PATCH] add doc --- examples/Si-SNAP-NN-LAMMPS/README.md | 1 + examples/Si-SNAP-NN-LAMMPS/snap_train.py | 4 +++- 2 files changed, 4 insertions(+), 1 deletion(-) diff --git a/examples/Si-SNAP-NN-LAMMPS/README.md b/examples/Si-SNAP-NN-LAMMPS/README.md index df5c8e8..b096435 100644 --- a/examples/Si-SNAP-NN-LAMMPS/README.md +++ b/examples/Si-SNAP-NN-LAMMPS/README.md @@ -12,6 +12,7 @@ After training is complete, you expect to find a folder called `Si-snap` with se - `DescriptorParams.txt`: parameters to compute the descriptor in LAMMPS format - `NN_weights.txt`: weight parameters of the model in LAMMPS format +The training takes about 20-30 minutes. If you cannot wait, please skip this step and use the existing files for the following steps. ## Atomistic simulation via ASE PyXtal\_FF provides a built in `ASE` calculator. You can simply use it for some light weight calculations. diff --git a/examples/Si-SNAP-NN-LAMMPS/snap_train.py b/examples/Si-SNAP-NN-LAMMPS/snap_train.py index 34c0240..c9ba99c 100644 --- a/examples/Si-SNAP-NN-LAMMPS/snap_train.py +++ b/examples/Si-SNAP-NN-LAMMPS/snap_train.py @@ -11,7 +11,9 @@ os.system('wget ' + url + TrainData) os.system('wget ' + url + TestData) -descriptor = {'Rc': 5.0, +descriptor = {'type': 'SNAP', + 'weights': {'Si': 1.0}, + 'Rc': 5.0, 'parameters': {'lmax': 3}, 'ncpu': 1, }