Wind.utils.score_function

def Wind.utils.score_function(true_values, predicted_values) [source]

Calculate a score to evaluate the performance of a time series prediction model.

Parameters: true_values (numpy.ndarray): Array of true values for the time series. predicted_values (numpy.ndarray): Array of predicted values for the time series.

Returns: float: Score representing the performance of the prediction model.

Wind.utils.experiment_results

def Wind.utils.experiment_results(names, results, title='Results') [source]

Display experiment results in a formatted table with optional title.

Parameters: names (list): List of model names. results (list of dict): List of dictionaries containing metric results for each model. title (str, optional): Title to be displayed above the results table. Default is 'Results'.

This function takes model names and their corresponding metric results and displays them in a formatted table. It includes options to display a title above the table and make the best values bold. If any metric value is 0, it is displayed as '-' in the table.

Example: names = ["Model 1", "Model 2", "Model 3"] results = [ {"MAE": 0.1, "RMSE": 0.2, "R2": 0.9}, {"MAE": 0, "RMSE": 0.25, "R2": 0.85}, {"MAE": 0.12, "RMSE": 0.22, "R2": 0.88}, ] experiment_results(names, results, title='Experiment 1 Results')