dragonfruit.ionic_liquids.adf_scripts module
This file contains scripts for running ADF calculations from python. This depends on the ADF python environment and therefore should not be imported normally as the required modules will be missing.
- class dragonfruit.ionic_liquids.adf_scripts.AdfOptimisation(*_args, **_kwargs)
Bases:
dragonfruit.ionic_liquids.adf_scripts.AdfTaskAn ADF geometry optimisation using ASE.
This uses ASE to perform geometry optimisation calling the ADF code for energy/force evaluations.
- TYPE_ID = UUID('86124647-c193-4d40-aefa-3ce34c42a7d4')
- property keep_files
- property results_history
- run(fmax=0.05, max_steps=1000, **kwargs)
Run the optimisation for until the maximum force threshold or the maximum number of steps is reached.
- property stored_files: Dict[str, mincepy.files.File]
The dictionary of stored files. These are updated each time the run is saved based on the keep files attribute
- class dragonfruit.ionic_liquids.adf_scripts.AdfTask(*_args, **_kwargs)
Bases:
mincepy.base_savable.SimpleSavable,dragonfruit.ase_utils.AseVisualizableA generic ADF task. This can be used to store information about an ADF execution including the initial, final, and any intermediate structures (in the case of geometry optimisations).
Typically this task would be subclassed to perform the particular workflow desired.
- TYPE_ID = UUID('a9361ffe-708a-4cb6-b544-07e76e7a1d6a')
- property atoms
Get the current atoms, this is typically the update-to-date atoms, while the atoms_history holds copies of the atoms objects as the task progressed.
- property atoms_history
- property final_atoms: Optional[ase.atoms.Atoms]
- get_visualizable()
- property initial_atoms: Optional[ase.atoms.Atoms]
- property label
Get the label for this task
- load_instance_state(saved_state, loader: mincepy.depositors.Loader)
Take the given object and load the instance state into it
- property settings
Get the settings that were used for this run
- property take_charge_from