Set uniform data (can be state dependent)

Attributes¶

data_source: str or pandas.DataFrame or dict

Either a file name, or a data frame, both assuming state dependent data. Or a dict for state independent uniform data (i.e., scalars)

ovars: list of str

The variables to be written

var2col: dict

Mapping from variable names to data column names

Public members¶

SetUniformData(data_source, output_vars, var2col={}, ...)[source]

Constructor.

load_data(algo, verbosity=0)[source]

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

output_point_vars(algo)[source]

The variables which are being modified by the model.

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

” The main model calculation.

ensure_variables(algo, mdata, fdata, tdata)[source]

Add variables to tdata, 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.

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

data_to_store(name, algo, data)[source]

Adds data from mdata to the local store, intended for iterative runs.

from_data_or_store(name, algo, data, ret_dims=False, safe=False)[source]

Get data from mdata or local store