qmcblip.flare.otf module
On-the-fly training classes adapted for CHAMP.
- class qmcblip.flare.otf.C_OTF(*args, **kwargs)[source]
Bases:
flare.otf.OTFTrains a Gaussian process force field on the fly during molecular dynamics.
- Parameters
dt (float) – MD timestep.
number_of_steps (
int) – Number of timesteps in the training simulation.prev_pos_init ([type], optional) – Previous positions. Defaults to None.
rescale_steps (List[
int], optional) – List of frames for which the velocities of the atoms are rescaled. Defaults to [].rescale_temps (List[
int], optional) – List of rescaled temperatures. Defaults to [].gp (gp.GaussianProcess) – Initial GP model.
calculate_energy (
bool, optional) – If True, the energy of each frame is calculated with the GP. Defaults to False.calculate_efs (
bool, optional) – If True, the energy and stress of each frame is calculated with the GP. Defaults to False.write_model (
int, optional) – If 0, write never. If 1, write at end of run. If 2, write after each training and end of run. If 3, write after each time atoms are added and end of run. If 4, write after each training and end of run, and back up after each write.force_only (
bool, optional) – If True, only use forces for training. Default to False, use forces, energy and stress for training.std_tolerance_factor (float, optional) – Threshold that determines when DFT is called. Specifies a multiple of the current noise hyperparameter. If the epistemic uncertainty on a force component exceeds this value, DFT is called. Defaults to 1.
skip (
int, optional) – Number of frames that are skipped when dumping to the output file. Defaults to 0.init_atoms (List[
int], optional) – List of atoms from the input structure whose local environments and force components are used to train the initial GP model. If None is specified, all atoms are used to train the initial GP. Defaults to None.output_name (
str, optional) – Name of the output file. Defaults to ‘otf_run’.max_atoms_added (
int, optional) – Number of atoms added each time DFT is called. Defaults to 1.freeze_hyps (
int, optional) – Specifies the number of times the hyperparameters of the GP are optimized. After this many updates to the GP, the hyperparameters are frozen. Defaults to 10.min_steps_with_model (
int, optional) – Minimum number of steps the model takes in between calls to DFT. Defaults to 0.force_source (Union[
str, object], optional) – DFT code used to calculate ab initio forces during training. A custom module can be used here in place of the DFT modules available in the FLARE package. The module must contain two functions: parse_dft_input, which takes a file name (in string format) as input and returns the positions, species, cell, and masses of a structure of atoms; and run_dft_par, which takes a number of DFT related inputs and returns the forces on all atoms. Defaults to “qe”.npool (
int, optional) – Number of k-point pools for DFT calculations. Defaults to None.mpi (
str, optional) – Determines how mpi is called. Defaults to “srun”.dft_loc (
str) – Location of DFT executable.dft_input (
str) – Input file.dft_output (
str) – Output file.dft_kwargs ([type], optional) – Additional arguments which are passed when DFT is called; keyword arguments vary based on the program (e.g. ESPRESSO vs. VASP). Defaults to None.
store_dft_output (Tuple[Union[
str,List[str]],:obj:str], optional) – After DFT calculations are called, copy the file or files specified in the first element of the tuple to a directory specified as the second element of the tuple. Useful when DFT calculations are expensive and want to be kept for later use. The first element of the tuple can either be a single file name, or a list of several. Copied files will be prepended with the date and time with the format ‘Year.Month.Day:Hour:Minute:Second:’.n_cpus (
int, optional) – Number of cpus used during training. Defaults to 1.
- class qmcblip.flare.otf.C_ASE_OTF(atoms, timestep, number_of_steps, dft_calc, md_engine, md_kwargs, update_settings, calculator=None, trajectory=None, **otf_kwargs)[source]
Bases:
flare.ase.otf.ASE_OTF,qmcblip.flare.otf.C_OTFOn-the-fly training module using ASE MD engine, a subclass of OTF.
- Parameters
atoms (ASE Atoms) – the ASE Atoms object for the on-the-fly MD run.
timestep (
float) – the timestep in MD. Please use ASE units, e.g. if the timestep is 1 fs, then set timestep = 1 * units.fsnumber_of_steps (
int) – the total number of steps for MD.dft_calc (ASE Calculator) – any ASE calculator is supported, e.g. Espresso, VASP etc.
md_engine (
str) – the name of MD thermostat, only VelocityVerlet, NVTBerendsen, NPTBerendsen, NPT and Langevin, NoseHoover are supported.md_kwargs (dict) – specify the args for MD as a dictionary, the args are as required by the ASE MD modules consistent with the md_engine.
update_settings (List[List[dict]]) – array containg CHAMP simulation parameters to update.
calculator (
Calculator) –- ASE calculator.
Must have “get_uncertainties” method
implemented.
trajectory (ASE Trajectory) – default None, not recommended, currently in experiment.
The following arguments are for on-the-fly training, the user can also refer to
flare.otf.OTF- Parameters
prev_pos_init ([type], optional) – Previous positions. Defaults to None.
rescale_steps (List[
int], optional) – List of frames for which the velocities of the atoms are rescaled. Defaults to [].rescale_temps (List[
int], optional) – List of rescaled temperatures. Defaults to [].calculate_energy (
bool, optional) – If True, the energy of each frame is calculated with the GP. Defaults to False.write_model (
int, optional) – If 0, write never. If 1, write at end of run. If 2, write after each training and end of run. If 3, write after each time atoms are added and end of run. If 4, write after each training and end of run, and back up after each write.std_tolerance_factor (float, optional) – Threshold that determines when DFT is called. Specifies a multiple of the current noise hyperparameter. If the epistemic uncertainty on a force component exceeds this value, DFT is called. Defaults to 1.
skip (
int, optional) – Number of frames that are skipped when dumping to the output file. Defaults to 0.init_atoms (List[
int], optional) – List of atoms from the input structure whose local environments and force components are used to train the initial GP model. If None is specified, all atoms are used to train the initial GP. Defaults to None.output_name (
str, optional) – Name of the output file. Defaults to ‘otf_run’.max_atoms_added (
int, optional) – Number of atoms added each time DFT is called. Defaults to 1.freeze_hyps (
int, optional) – Specifies the number of times the hyperparameters of the GP are optimized. After this many updates to the GP, the hyperparameters are frozen. Defaults to 10.n_cpus (
int, optional) – Number of cpus used during training. Defaults to 1.