Usage

Finally, once the data and configuration files have been prepared, you can run UNIQUE in the following way:

from unique import Pipeline

# Prepare UNIQUE pipeline
pipeline = Pipeline.from_config("/path/to/config.yaml")

# Run UNIQUE pipeline
uq_methods_outputs, uq_evaluation_outputs = pipeline.fit()
# Returns: (Dict[str, np.ndarray], Dict[str, pd.DataFrame])

Fitting the Pipeline will return two dictionaries:

uq_methods_outputs	uq_evaluation_outputs
Contains each computed UQ method’s name (as in "UQ_Method_Name[Input_Name(s)]") and corresponding UQ values.	Contains, for each evaluation benchmark, the evaluation metrics for all the computed UQ methods (organized in one pd.DataFrame for each evaluation benchmark).

Additionally, UNIQUE also generates graphical outputs in the form of tables and evaluation plots (if display_outputs is enabled and the code is running in a JupyterNotebook cell).

See also

Check out the Examples to see UNIQUE in action.