Analysis

Plotting

plotting.score_plot(data[, pipelines])

Plot scores for all pipelines and all datasets

plotting.paired_plot(data, alg1, alg2)

Generate a figure with a paired plot

plotting.summary_plot(sig_df, effect_df[, …])

Significance matrix to compare pipelines

plotting.meta_analysis_plot(stats_df, alg1, alg2)

Meta-analysis to compare two algorithms across several datasets

Statistics

meta_analysis.find_significant_differences(df)

Compute differences between pipelines across datasets

meta_analysis.compute_dataset_statistics(df)

Compute meta-analysis statistics from results dataframe

meta_analysis.combine_effects(effects, nsubs)

Combining effects for meta-analysis statistics

meta_analysis.combine_pvalues(p, nsubs)

Combining p-values for meta-analysis statistics

meta_analysis.collapse_session_scores(df)

Prepare results dataframe for computing statistics