Exemplo n.º 1
0
fig = moabb_plt.paired_plot(results, "CSP+LDA", "RG+LDA")
plt.show()

###############################################################################
# Statistical testing and further plots
# ----------------------------------------
#
# If the statistical significance of results is of interest, the method
# compute_dataset_statistics allows one to show a meta-analysis style plot as
# well. For an overview of how all algorithms perform in comparison with each
# other, the method find_significant_differences and the summary_plot are
# possible.

stats = compute_dataset_statistics(results)
P, T = find_significant_differences(stats)

###############################################################################
# The meta-analysis style plot shows the standardized mean difference within
# each tested dataset for the two algorithms in question, in addition to a
# meta-effect and significances both per-dataset and overall.
fig = moabb_plt.meta_analysis_plot(stats, "CSP+LDA", "RG+LDA")
plt.show()

###############################################################################
# The summary plot shows the effect and significance related to the hypothesis
# that the algorithm on the y-axis significantly out-performed the algorithm on
# the x-axis over all datasets
moabb_plt.summary_plot(P, T)
plt.show()
fig = moabb_plt.paired_plot(results, 'CSP + LDA', 'RG + LDA')
plt.show()

###############################################################################
# Statistical testing and further plots
# ----------------------------------------
#
# If the statistical significance of results is of interest, the method
# compute_dataset_statistics allows one to show a meta-analysis style plot as
# well. For an overview of how all algorithms perform in comparison with each
# other, the method find_significant_differences and the summary_plot are
# possible.

stats = compute_dataset_statistics(results)
P, T = find_significant_differences(stats)

###############################################################################
# The meta-analysis style plot shows the standardized mean difference within
# each tested dataset for the two algorithms in question, in addition to a
# meta-effect and significances both per-dataset and overall.
fig = moabb_plt.meta_analysis_plot(stats, 'CSP + LDA', 'RG + LDA')
plt.show()

###############################################################################
# The summary plot shows the effect and significance related to the hypothesis
# that the algorithm on the y-axis significantly out-performed the algorithm on
# the x-axis over all datasets
moabb_plt.summary_plot(P, T)
plt.show()