flotilla.visualize.ipython_interact module¶

Named ipython_interact.py rather than just interact.py to differentiate between IPython interactive visualizations vs D3 interactive visualizations.

class flotilla.visualize.ipython_interact.Interactive(*args, **kwargs)[source]¶

Bases: object

static get_feature_subsets(study, data_types)[source]¶

Given a study and list of data types, get the relevant feature subsets

Parameters:	study : flotilla.Study A study object which

static interactive_choose_outliers(data_types=('expression', 'splicing'), sample_subsets=None, feature_subsets=None, featurewise=False, x_pc=(1, 3), y_pc=(1, 3), show_point_labels=False, kernel=('rbf', 'linear', 'poly', 'sigmoid'), gamma=(0, 25), nu=(0.1, 9.9))[source]¶

static interactive_classifier(data_types=('expression', 'splicing'), sample_subsets=None, feature_subsets=None, categorical_variables=None, predictor_types=None, score_coefficient=(0.1, 20), draw_labels=False)[source]¶

static interactive_clustermap()[source]¶

static interactive_correlations()[source]¶

static interactive_graph(data_types=('expression', 'splicing'), sample_subsets=None, feature_subsets=None, featurewise=False, cov_std_cut=(0.1, 3), degree_cut=(0, 10), n_pcs=(2, 100), draw_labels=False, feature_of_interest='RBFOX2', weight_fun=None, use_pc_1=True, use_pc_2=True, use_pc_3=True, use_pc_4=True, savefile='figures/last.graph.pdf')[source]¶

static interactive_lavalamp_pooled_inconsistent(sample_subsets=None, feature_subsets=None, difference_threshold=(0.001, 1.0), colors=['red', 'green', 'blue', 'purple', 'yellow'], savefile='')[source]¶

static interactive_localZ()[source]¶

static interactive_pca(data_types=('expression', 'splicing'), sample_subsets=None, feature_subsets=None, color_samples_by=None, featurewise=False, x_pc=(1, 10), y_pc=(1, 10), show_point_labels=False, list_link='', plot_violins=False, scale_by_variance=True, savefile='figures/last.pca.pdf')[source]¶

static interactive_plot_modalities_lavalamps(sample_subsets=None, feature_subsets=None, color=u'#e41a1c', x_offset=0, use_these_modalities=True, bootstrapped=False, bootstrapped_kws=None, savefile='')[source]¶

static interactive_reset_outliers()[source]¶

User selects from columns that start with ‘outlier_‘ to merge multiple outlier classifications