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Results Manager

PermutationManager

calculate_p_values(true_results, perms) staticmethod

Calculate p-values based on true results and permutation results.

:param true_results: DataFrame with the true results. :param perms: DataFrame with the permutation results. :return: DataFrame with the calculated p-values.

calculate_permutation_results(results_directory, logger) staticmethod

Calculate and save the permutation test results.

:param results_directory: Directory where the results are saved.

ResultsManager

A class to handle the aggregation, formatting, and saving of results.

Parameters:

Name Type Description Default
output_dir str

Directory where results will be saved.

 required

calculate_edge_stability(write=True, best_param_id=None)

Calculate and save edge stability and overlap.

:param cv_edges: Cross-validation edges. :param results_directory: Directory to save the results.

calculate_final_cv_results()

Calculate mean and standard deviation of cross-validation results and save to CSV.

:param cv_results: DataFrame with cross-validation results. :param results_directory: Directory to save the results. :return: Updated cross-validation results DataFrame.

calculate_model_increments()

Calculate model increments comparing full model to a baseline.

:param cv_results: Cross-validation results. :param metrics: List of metrics to calculate. :return: Cross-validation results with increments.

initialize_edges(n_folds, n_features, n_params=None) staticmethod

Initialize a dictionary to store edges for cross-validation.

:param n_folds: Number of outer folds. :param n_features: Number of features in the data. :return: Dictionary to store edges.

load_cv_results(folder) staticmethod

Load cross-validation results from a CSV file.

:param folder: Directory containing the results file. :return: DataFrame with the loaded results.

save_network_strengths()

Save network strengths to CSV.

save_predictions()

Save predictions to CSV.

store_metrics(metrics, params, fold, param_id)

Update metrics DataFrame with new metrics and parameters.

:param metrics: Dictionary with computed metrics. :param params: Best hyperparameters from inner cross-validation. :param fold: Current fold number. :return: Updated metrics DataFrame.

store_predictions(y_pred, y_true, params, fold, param_id, test_indices)

Update predictions DataFrame with new predictions and parameters.

:param y_pred: Predicted values. :param y_true: True values. :param params: Best hyperparameters from inner cross-validation. :param fold: Current fold number. :return: Updated predictions DataFrame.

update_results_directory(output_dir)

Determine the directory to save results.

:param output_dir: :return: Results directory path.