chemicalchecker.util.plot.multiplot.MultiPlot

class MultiPlot(chemchecker, plot_path, limit_dataset=None, svg=False, dpi=200, grey=False, style=None)[source]

Bases: object

MultiPlot class.

Produce Chemical Checker plots using multiple datasets.

Initialize a MultiPlot instance.

Produce plots integrating data from multiple datasets.

Parameters:

Methods

`all_sign_validations`
`cc_colors`
`cc_palette`	Return a list of colors a.k.a.
`cctype_CCA`
`cctype_similarity_search`
`cctype_validation_comparison`
`cmap_discretize`	Return a discrete colormap from the continuous colormap cmap.
`diagnosis_confidences_projection`
`diagnosis_euclidean_distances`
`diagnosis_projections`
`plot_adanet_subnetwork_layer_size`
`quick_gaussian_kde`
`sign2_grid_search_node2vec_plot`
`sign2_grid_search_plot`
`sign2_node2vec_stats`	Plot the stats for sign2.
`sign3_adanet_performance_all_plot`
`sign3_adanet_performance_overall`
`sign3_adanet_performance_overall_heatmap`
`sign3_all_crossfit_plot`
`sign3_confidence_distribution`
`sign3_confidence_summary`
`sign3_correlation_distribution`
`sign3_coverage_barplot`
`sign3_coverage_heatmap`
`sign3_error_predictors`
`sign3_examplary_test_correlation`
`sign3_grid_search_plot`
`sign3_mfp_confidence_predictor`
`sign3_mfp_predictor`
`sign3_neig2_jaccard`
`sign3_novel_confidence_distribution`
`sign3_test_distribution`
`sign3_test_error_distribution`
`sign_adanet_stats`
`sign_feature_distribution_plot`
`sign_property_distribution`
`spy_augment`
`spy_sign2_universe_matrix`

cmap_discretize(N)[source]

Return a discrete colormap from the continuous colormap cmap.

cmap: colormap instance, eg. cm.jet. N: number of colors.

Example: x = resize(arange(100), (5,100)) djet = cmap_discretize(cm.jet, 5) imshow(x, cmap=djet)