def test_clusterview(): keys = ('cluster_groups,group_colors,group_names,' 'cluster_sizes').split(',') data = get_data() kwargs = {k: data[k] for k in keys} kwargs['cluster_colors'] = data['cluster_colors_full'] # kwargs['background'] = {5: 1, 7: 2} clusters = get_indices(data['cluster_sizes']) quality = pd.Series(np.random.rand(len(clusters)), index=clusters) kwargs['cluster_quality'] = quality kwargs['operators'] = [ lambda self: self.view.set_quality(quality), lambda self: self.view.set_background({ 5: 1, 7: 2 }), lambda self: self.view.set_background({6: 3}), lambda self: self.view.set_background({}), lambda self: (self.close() if USERPREF['test_auto_close'] != False else None), ] # Show the view. window = show_view(ClusterView, **kwargs)
def test_clusterview(): keys = ('cluster_groups,group_colors,group_names,' 'cluster_sizes').split(',') data = get_data() kwargs = {k: data[k] for k in keys} kwargs['cluster_colors'] = data['cluster_colors_full'] # kwargs['background'] = {5: 1, 7: 2} clusters = get_indices(data['cluster_sizes']) quality = pd.Series(np.random.rand(len(clusters)), index=clusters) kwargs['cluster_quality'] = quality kwargs['operators'] = [ lambda self: self.view.set_quality(quality), lambda self: self.view.set_background({5: 1, 7: 2}), lambda self: self.view.set_background({6: 3}), lambda self: self.view.set_background({}), lambda self: (self.close() if USERPREF['test_auto_close'] != False else None), ] # Show the view. window = show_view(ClusterView, **kwargs)
def test_featureprojview(): keys = ( 'features,features_background,masks,clusters,clusters_selected,' 'spiketimes,' 'cluster_colors,fetdim,nchannels,nextrafet,duration,freq').split(',') data = get_data() kwargs = {k: data[k] for k in keys} kwargs['operators'] = [ lambda self: assert_fun(self.view.get_projection(0) == (0, 0)), lambda self: assert_fun(self.view.get_projection(1) == (0, 1)), lambda self: self.view.select_channel(0, 5), lambda self: self.view.select_feature(0, 1), lambda self: self.view.select_channel(1, 32), lambda self: self.view.select_feature(1, 2), lambda self: assert_fun(self.view.get_projection(0) == (5, 1)), lambda self: assert_fun(self.view.get_projection(1) == (32, 2)), lambda self: self.view.toggle_mask(), lambda self: self.view.set_wizard_pair((2, 1), (3, 2)), lambda self: self.view.set_wizard_pair(None, (3, 2)), lambda self: self.view.set_wizard_pair((3, 2), None), lambda self: self.view.set_wizard_pair(None, None), lambda self: self.view.set_projection(0, 2, -1), lambda self: self.view.set_projection(1, 2, -1), lambda self: (self.close() if USERPREF['test_auto_close'] != False else None), ] # Show the view. show_view(FeatureProjectionView, **kwargs)
def test_similaritymatrixview(): data = get_data() kwargs = {} kwargs['similarity_matrix'] = create_similarity_matrix(nclusters) kwargs['cluster_colors_full'] = data['cluster_colors_full'] kwargs['operators'] = [ lambda self: self.view.show_selection(5, 6), lambda self: (self.close() if USERPREF['test_auto_close'] != False else None), ] # Show the view. show_view(SimilarityMatrixView, **kwargs)
def test_waveformview(): keys = ('waveforms,clusters,cluster_colors,clusters_selected,masks,' 'geometrical_positions').split(',') data = get_data() kwargs = {k: data[k] for k in keys} operators = [ lambda self: self.view.toggle_mask(), lambda self: (self.close() if USERPREF['test_auto_close'] != False else None), ] # Show the view. show_view(WaveformView, operators=operators, **kwargs)
def test_waveformview(): keys = ('waveforms,clusters,cluster_colors,clusters_selected,masks,' 'geometrical_positions' ).split(',') data = get_data() kwargs = {k: data[k] for k in keys} operators = [ lambda self: self.view.toggle_mask(), lambda self: (self.close() if USERPREF['test_auto_close'] != False else None), ] # Show the view. show_view(WaveformView, operators=operators, **kwargs)
def test_correlogramsview(): keys = ('clusters_selected,cluster_colors').split(',') data = get_data() kwargs = {k: data[k] for k in keys} kwargs['correlograms'] = create_correlograms(kwargs['clusters_selected'], ncorrbins) kwargs['baselines'] = create_baselines(kwargs['clusters_selected']) kwargs['ncorrbins'] = ncorrbins kwargs['corrbin'] = corrbin kwargs['operators'] = [ lambda self: self.view.change_normalization('uniform'), lambda self: self.view.change_normalization('row'), lambda self: (self.close() if USERPREF['test_auto_close'] != False else None), ] # Show the view. show_view(CorrelogramsView, **kwargs)
def test_featureview(): keys = ('features,features_background,masks,clusters,clusters_selected,' 'spiketimes,' 'cluster_colors,fetdim,nchannels,nextrafet,duration,freq').split(',') data = get_data() kwargs = {k: data[k] for k in keys} kwargs['operators'] = [ lambda self: self.view.toggle_mask(), lambda self: self.view.set_wizard_pair((2, 1), (3, 2)), lambda self: self.view.set_wizard_pair(None, (3, 2)), lambda self: self.view.set_wizard_pair((3, 2), None), lambda self: self.view.set_wizard_pair(None, None), lambda self: (self.close() if USERPREF['test_auto_close'] != False else None), ] # Show the view. show_view(FeatureView, **kwargs)