ai2_kit.feat.catalysis package#

Submodules#

Module contents#

class ai2_kit.feat.catalysis.CmdEntries[source]#

Bases: object

build_config()[source]#

Build config file for catalyst

class ai2_kit.feat.catalysis.ConfigBuilder[source]#

Bases: object

gen_cp2k_input(out_dir: str = 'out', basis_set_file: List[str] | str = 'BASIS_MOLOPT', potential_file: List[str] | str = 'GTH_POTENTIALS', style: Literal['metal', 'semi'] = 'metal', accuracy: Literal['high', 'medium', 'low'] = 'medium', aimd: bool = False, temp: float = 330.0, steps: int = 1000, timestep: float = 0.5, parameter_file: str = 'dftd3.dat', template_file: str = '/opt/hostedtoolcache/Python/3.10.15/x64/lib/python3.10/site-packages/ai2_kit/res/catalysis/cp2k.inp')[source]#

Generate CP2K input files

You should call load_system first to load system into memory. And you may also need to ensure the basic set and potential files you want to use are available in CP2K_DATA_DIR, or else you have to specify the full path instead of their file name.

Parameters:

  • basis_set_file – basic set file, can be path or file in CP2K_DATA_DIR, use list to specify multiple files

  • potential_file – potential file, can be path or file in CP2K_DATA_DIR, use list to specify multiple files

  • out_dir – output directory, cp2k.inp and coord_n_cell.inc will be generated in this directory

  • style – ‘metal’ or ‘semi’

  • accuracy – ‘high’, ‘medium’ or ‘low’

  • aimd – whether to run AIMD

  • temp – temperature for AIMD

  • steps – steps for AIMD

  • timestep – timestep for AIMD

  • parameter_file – parameter file, can be path or file in CP2K_DATA_DIR

  • template_file – template file, no need to change in most cases

gen_deepmd_input(out_dir: str = 'out', steps: int = 10000, template_file: str = '/opt/hostedtoolcache/Python/3.10.15/x64/lib/python3.10/site-packages/ai2_kit/res/catalysis/deepmd.json')[source]#
gen_lammps_input(out_dir='./out', abs_path=True, **kwargs)[source]#
gen_mlp_training_input(out_dir: str = 'out', train_data: List[str] | None = None, explore_data: List[str] | None = None, artifacts: List[dict] | None = None, template_file: str = '/opt/hostedtoolcache/Python/3.10.15/x64/lib/python3.10/site-packages/ai2_kit/res/catalysis/mlp-training.yml')[source]#
gen_plumed_input(out_dir: str = 'out')[source]#

Generate Plumed input files :param out_dir: output directory, plumed.inp will be generated in this directory

get_plumed_group()[source]#

Get auto generated plumed group

load_system(file: str, **kwargs)[source]#

Loading system to memory using ASE

ai2_kit.feat.catalysis.cli_main()[source]#

Command line entry for ai2-cat command

ai2_kit.feat.catalysis.dump_artifacts(artifacts: List[dict]) → str[source]#
ai2_kit.feat.catalysis.find_cp2k_data_file(file: str)[source]#

find CP2K data file in CP2K_DATA_DIR

ai2_kit.feat.catalysis.get_basis_n_potential(basis_set_files: List[str], potential_files: List[str])[source]#
ai2_kit.feat.catalysis.get_type_map(atoms: Atoms)[source]#
ai2_kit.feat.catalysis.get_valence_electron(name: str) → int[source]#
ai2_kit.feat.catalysis.inspect_lammps_output(lammps_dir: str, save_to: str | None = None, fig_ax=None)[source]#
ai2_kit.feat.catalysis.parse_cp2k_data_file(fp, parsed=None)[source]#

get all available basic set and potential from CP2K data file

ai2_kit.feat.catalysis.select_basis_set(choices: List[str], preferred: str | None = None)[source]#

select basis set by matching preferred basis set

ai2_kit.feat.catalysis.select_potential(choices: List[str], ve: int, xc_function='PBE')[source]#

select potential by matching valence electron and xc_function

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