<jupyter_start><jupyter_text>Start point<jupyter_code>results = []

for hemisphere in ['L', 'R']:
    for segment in ['A', 'B', 'C']:
        
        model = get_model('final_super_model_startpoint_group_zscored_STh_%s_%s' % (hemisphere, segment), 'L')
        traces = model.get_traces()

        tmp = pandas.DataFrame({'value':traces['z_cue_coding:STh_{hemisphere}_{segment}_cue'.format(**locals())],
                          'segment':segment,
                          'hemisphere':hemisphere})
        
        results.append(tmp)
df = pandas.concat(results, ignore_index=True)
df.groupby(['hemisphere', 'segment']).apply(lambda x: (x.value > 0).mean())
fac = sns.FacetGrid(df, col='hemisphere')
fac.map(sns.violinplot, 'value', 'segment', palette='Set1')


fac.fig.set_size_inches(25, 6)

for ax in fac.axes.ravel():
    ax.axvline(0, c='k', ls='--')<jupyter_output><empty_output>
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