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)