ase.md

ASE Toolkit

ai2-kit tool ase

This toolkit is a command line wrapper of ASE to allow user to process trajectory via command line.

Usage

ai2-kit tool ase  # show all commands
ai2-kit tool ase to_dpdata -h  # show doc of specific command

This toolkit include the following commands:

Command	Description	Example	Reference
read	Read trajectory files into memory. This command by itself is useless, you should chain other command after reading data into memory.	ai2-kit tool ase read ./path/to/traj.xyz	ase.io.read, support wildcard, can be call multiple times
write	Write all frame of a trajectory into a single file.	ai2-kit tool ase read ./path/to/traj.xyz - write ./path/to/output.xyz	ase.io.write
write_frames	Write each frame of a trajectory into a separated file. The file name should include {i} or other valid Python str.format to indicate the frame number	ai2-kit tool ase read ./path/to/traj.xyz - write_frames ./path/to/POSCAR-{i:04d} --format vasp	ase.io.write
set_cell	Set the cell of all frames in the trajectory.	see in Example	ase.Atoms.set_cell
set_pbc	Set the periodic boundary condition of all frames in the trajectory.	see in Example	ase.Atoms.set_pbc
delete_atoms	Delete atoms from all frames in the trajectory.	see in Example
write_dplr_lammps_data	Write data in the format LAMMPS data for DPLR	see in Example
slice	use slice expression to process systems	see in Example
sample	sample data by different methods, current supported method are even and random	see in Example
to_dpdata	convert ase.Atoms to dpdata and use dpdata tool to process	see in Example

Those commands are chainable and can be used to process trajectory in a pipeline fashion (separated by -). For more information, please refer to the following examples.

Example

# Convert every frame in xyz trajectory to separated POSCAR files
ai2-kit tool ase read ./path/to/traj.xyz - write_frames "POSCAR-{i:04d}" --format vasp

# Convert every 20th frame in xyz trajectory to separated POSCAR files
# For more information about the index syntax, please refer to https://wiki.fysik.dtu.dk/ase/ase/io/io.html#ase.io.read
ai2-kit tool ase read ./path/to/traj.xyz --index '::20' - write_frames "POSCAR-{i:04d}" --format vasp 

# Convert a single lammps dump data to a POSCAR file
ai2-kit tool ase read ./path/to/lammp-dump.data --format lammps-dump-text --specorder [O,H] - write POSCAR --format vasp

# Delete atoms from a trajectory
ai2-kit tool ase read lammps.data --format lammps-data --style atomic - delete_atoms [10,12] - write lammps-fin.data --format lammps-data

# Read multiple files and write them into a single file
ai2-kit tool ase read ./path/to/data1/*.xyz - read ./path/to/data2/*.xyz - write all.xyz

# Read all `good` structures generate by CLL training workflow use glob
ai2-kit tool ase read ./workdir/iters-*/selector*/model-devi/*/good.xyz  - write all-good.syz

# Convert xyz file to cp2k-inc file
ai2-kit tool ase read coord.xyz - set_cell "[10,10,10,90,90,90]" - write coord_n_cell.inc --format cp2k-inc

# Convert xyz file to DPLR LAMMPS data
# Note: don't have space in the list or else you have to quote it with ""
ai2-kit tool ase read h2o.xyz - write_dplr_lammps_data tmp/dplr/{i}.lammps.data --type_map [O,H] --sel_type [0] --sys_charge_map [6,1] --model_charge_map [-8]

# Drop the first 10 frames and then sample 10 frames use random method, and save it as dpdata.System format
ai2-kit tool ase read h2o.lammpstrj --specorder [H,O] - slice 10: - sample 10 --method random - to_dpdata - write dp-h2o --nomerge