idq.plots

describe module, architecture, etc.

idq.plots.calibration_accuracy(nicknames, calibmaps, series, datasets, legend=True, fig=None, plot_map_coverage=False)

plot the calibration accuracy

idq.plots.calibration_coverage(nicknames, series, datasets, calibmaps, legend=True, fig=None, plot_map_coverage=False)

plot the calibration coverage in a standard way

idq.plots.calibration_distribs(nicknames, calibmaps, legend=True, fig=None, pdf_ymin=0.0001, pdf_ymax=10000.0)

plot the distributions over observed ranks and the calibration KDEs

idq.plots.dataset_corner(nicknames, datasets)

generate a corner plot showing the correlations between ranks

idq.plots.featureimportance(nicknames, models, classifiers, start, end, datasets=None, t0=None, segdict=None, skip_plot=False, **kwargs)

delegate to models heavily here

idq.plots.histogram(nicknames, series, start, end, t0, legend=True, fig=None)

plot the series information in a standard histogram way

idq.plots.roc(nicknames, series, datasets, fig=None, annotate_auc=False, rank_roc=False)

plot the ROC curves in a standard way

idq.plots.save(path, fig)

save figure to disk and close

idq.plots.timeseries(nicknames, series, start, end, t0, legend=True, gch_gps=None, segs=None, strain=None, frange=(0, inf))

plot the series information in a standard way