def test_estimate_posteriors_data_overlay_indep_axes_slope(
add_data, add_data_plot, add_group_slope):
window = BayesRegression(df=df,
add_data=add_data,
y='isi',
treatment='stim',
condition='neuron',
group='mouse')
window.fit(model=models.model_hierarchical,
add_group_slope=add_group_slope)
chart = window.plot(independent_axes=True, add_data=add_data_plot)
chart.display()
if add_group_slope and add_data_plot:
chart = window.facet(column='neuron', row='mouse')
else:
chart = window.facet(column='neuron')
chart.display()
def random_tests():
# TODO make a notebook for this
window = BayesRegression(df=df,
y='isi',
treatment='stim',
condition='neuron',
group='mouse')
window.fit(model=models.model_hierarchical, num_chains=1)
window.plot(x='neuron',
color='mouse',
independent_axes=True,
finalize=True)
window.plot(independent_axes=False, x='neuron:O', color='mouse')
window.plot(add_box=False,
independent_axes=True,
x='neuron:O',
color='mouse')
window.plot(independent_axes=False, x='neuron:O', color='mouse')
chart = window.plot(independent_axes=True, x='neuron:O', color='mouse')
chart.display()
chart.resolve_scale(y='independent')
window.facet(column='neuron')
window = BayesRegression(df=df,
y='isi',
treatment='stim',
condition='neuron',
group='mouse')
window.fit(model=models.model_hierarchical, num_chains=1)
window.plot(x='neuron', color='i_trial')
window.plot() # x='Stim phase', color='Fid')#,independent_axes=True)
window.facet(column='neuron', row='mouse')
def facet(self, **kwargs):
from bayes_window import BayesRegression
return BayesRegression.facet(self, **kwargs)
