Calculates the data by interpolation of lookup-table data

Attributes¶

data_source: str or pandas.DataFrame

The lookup-table data

input_vars: list of str

The foxes input variables

output_vars: list of str

The foxes output variables

varmap: dict

Mapping from foxes variable names to column names in the data_source

Public members¶

LookupTable(data_source, input_vars, output_vars, varmap={}, ...)[source]

Constructor.

output_farm_vars(algo)[source]

The variables which are being modified by the model.

load_data(algo, verbosity=0)[source]

Load and/or create all model data that is subject to chunking.

calculate(algo, mdata, fdata, st_sel)[source]

The main model calculation.

classmethod new(tmodel_type, *args, **kwargs)[source]

Run-time turbine model factory.

output_coords()[source]

Gets the coordinates of all output arrays

ensure_variables(algo, mdata, fdata)[source]

Add variables to fdata, initialized with NaN

run_calculation(algo, *data, out_vars, **calc_pars)[source]

Starts the model calculation in parallel, via xarray’s apply_ufunc.

__repr__()[source]

Return repr(self).

property model_id

Unique id based on the model type.

var(v)[source]

Creates a model specific variable name.

property initialized

Initialization flag.

sub_models()[source]

List of all sub-models

initialize(algo, verbosity=0, force=False)[source]

Initializes the model.

property running

Flag for currently running models

set_running(algo, data_stash, sel=None, isel=None, verbosity=0)[source]

Sets this model status to running, and moves all large data to stash.

unset_running(algo, data_stash, sel=None, isel=None, verbosity=0)[source]

Sets this model status to not running, recovering large data from stash

finalize(algo, verbosity=0)[source]

Finalizes the model.

get_data(variable, target, lookup='smfp', mdata=None, ...)[source]

Getter for a data entry in the model object or provided data sources