Configuration Options

ADEPT needs a yaml file with the following datamodel to run the simulation. The datamodel is defined in the following class.

class adept._vlasov1d.datamodel.ConfigModel(*, units: UnitsModel, density: DensityModel, grid: GridModel, save: SaveModel, solver: str, mlflow: MLFlowModel, drivers: DriversModel, terms: TermsModel)Source 

Each of the objects used to initialize this datamodel can be treated just like dictionaries. Each dictionary needs to be compiled into a megadictionary that is passed to the solver. The yaml configs accomplish this because a yaml is also a nested dictionary. The following documents those classes

High Level

These are the high level configuration options for the Vlasov1D solver. Each of these either contains a fundamental type such as bool, int, float, or str or is another nested datamodel which can be treated just like a dictionary.

class adept._vlasov1d.datamodel.UnitsModel(*, laser_wavelength: str, normalizing_temperature: str, normalizing_density: str, Z: int, Zp: int)Source 

class adept._vlasov1d.datamodel.DensityModel(*, quasineutrality: bool, species_background: SpeciesBackgroundModel)Source 

class adept._vlasov1d.datamodel.GridModel(*, dt: float, nv: int, nx: int, tmin: float, tmax: float, vmax: float, xmax: float, xmin: float)Source 

class adept._vlasov1d.datamodel.SaveModel(*, fields: dict[str, TimeSaveModel], electron: dict[str, TimeSaveModel])Source 

class adept._vlasov1d.datamodel.MLFlowModel(*, experiment: str, run: str)Source 

class adept._vlasov1d.datamodel.TermsModel(*, field: str, edfdv: str, time: str, fokker_planck: FokkerPlanckModel, krook: KrookModel)Source 

Low Level

The documentation for the nested datamodels is still TBD. To investigate them further, go to the source code.