VIZ_UTILS

viz_utils.plot_history(out, history[, ...])
viz_utils.plot_scatter(data, classes, out[, ...])
viz_utils.plot_error(y_true, y_pred, batch, ...)
viz_utils.plot_array(nparray, xlabel, ...)
viz_utils.plot_density_observed_vs_predicted(...)	Functionality to plot a 2D histogram of the distribution of observed (ground truth) values vs.
viz_utils.plot_2d_density_sigma_vs_error(...)	Functionality to plot a 2D histogram of the distribution of the standard deviations computed for the predictions vs.
viz_utils.plot_histogram_error_per_sigma(...)	Functionality to plot a 1D histogram of the distribution of computed errors (i.e. values of observed - predicted) observed for specific values of standard deviations computed.
viz_utils.plot_decile_predictions(Ypred, ...)	Functionality to plot the mean of the deciles predicted.
viz_utils.plot_calibration_interpolation(...)	Functionality to plot empirical calibration curves estimated by interpolation of the computed standard deviations and errors.
viz_utils.plot_calibrated_std(y_test, ...[, ...])	Functionality to plot values in testing set after calibration.
viz_utils.plot_contamination(y_true, y_pred, ...)	Functionality to plot results for the contamination model.
viz_utils.plot_metrics(history[, title, ...])	Plots keras training curves history.