csep.utils.plots.plot_likelihood_test

csep.utils.plots.plot_likelihood_test(evaluation_result, axes=None, show=True, plot_args=None)[source]

Takes result from evaluation and generates a specific histogram plot to show the results of the statistical evaluation for the L-test.

Parameters:

evaluation_result – object-like var that implements the interface of the above EvaluationResult
axes (matplotlib.Axes) – axes object used to chain this plot
show (bool) – if true, call pyplot.show()
plot_args (dict) – optional argument containing a dictionary of plotting arguments, with keys as strings and items as described below

Optional plotting arguments:

figsize: (list/tuple) - default: [6.4, 4.8]
title: (str) - default: name of the first evaluation result type
title_fontsize: (float) Fontsize of the plot title - default: 10
xlabel: (str) - default: ‘X’
xlabel_fontsize: (float) - default: 10
xticks_fontsize: (float) - default: 10
ylabel_fontsize: (float) - default: 10
text_fontsize: (float) - default: 14
tight_layout: (bool) Set matplotlib.figure.tight_layout to remove excess blank space in the plot - default: True
percentile (float) Critial region to shade on histogram - default: 95
bins: (str) - Set binning type. see matplotlib.hist for more info - default: ‘auto’
xy: (list/tuple) - default: (0.55, 0.3)