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# With ... = all parameters passed to seaborn's plotter
annotator = Annotator(ax, pairs, ...)

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 # With ... = all parameters passed to seaborn's plotter
  annotator = Annotator(ax, box_pairs, ...) 

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from statannotations.Annotator import Annotator

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pairs = [('Robots', 'Flight'),  # 'Robots' vs 'Flight'
         ('Flight', 'Sound'),   # 'Flight' vs 'Sound'
         ('Robots', 'Sound')]   # 'Robots' vs 'Sound'

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# pvalues with scipy:
stat_results = [
  mannwhitneyu(robots, flight, alternative="two-sided"),
  mannwhitneyu(flight, sound, alternative="two-sided"),
  mannwhitneyu(robots, sound, alternative="two-sided")
]

pvalues = [result.pvalue for result in stat_results]

print("Robots vs Flight: \n", stat_results[0], "\n")

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print("Robots: ", normaltest(robots).pvalue)
print("Flight: ", normaltest(flight).pvalue)
print("Sound: ", normaltest(sound).pvalue)
print()
print("Log(robots): ", normaltest(log_robots).pvalue)
print("Log(Flight): ", normaltest(log_flight).pvalue)
print("Log(Sound): ", normaltest(log_sound).pvalue)

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robots = rfs.loc[(rfs.Subcategory == "Robots"), "Goal"].values
flight = rfs.loc[(rfs.Subcategory == "Flight"), "Goal"].values
sound = rfs.loc[(rfs.Subcategory == "Sound"), "Goal"].values

log_robots = np.log(robots)
log_flight = np.log(flight)
log_sound = np.log(sound)

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# [code common to all plots]

# Plot with seaborn
sns.boxplot(ax=ax, data=rfs, x='State', y='Goal', order=states_order,
            palette=states_palette)

# [code common to all plots]

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with sns.plotting_context("notebook", font_scale=1.4):
    # Create new plot, setting a logarithmic scale for y
    ax = get_log_ax()

    # Plot with seaborn
    sns.boxplot(ax=ax, data=rfs, x='Subcategory', y='Goal', palette=subcat_palette[1:])

    # Label (adds axes labels and title), and show
    label_plot_for_subcats(ax)
    plt.savefig("plot1.png")

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subcat_palette = sns.dark_palette("#8BF", reverse=True, n_colors=5)
subcat_order = ['Robots', 'Flight', 'Sound']