pyhf.contrib.viz.brazil.plot_cls_components#

pyhf.contrib.viz.brazil.plot_cls_components(test_pois, tail_probs, ax, **kwargs)[source]#

Plot the values of \(\mathrm{CL}_{s+b}\) and \(\mathrm{CL}_{b}\) — the components of the \(\mathrm{CL}_{s}\) ratio — for a series of hypothesis tests for various POI values.

Example

plot_cls_components() is generally meant to be used inside plot_results() but can be used by itself.

>>> import numpy as np
>>> import matplotlib.pyplot as plt
>>> import pyhf
>>> import pyhf.contrib.viz.brazil
>>> pyhf.set_backend("numpy")
>>> model = pyhf.simplemodels.uncorrelated_background(
...     signal=[12.0, 11.0], bkg=[50.0, 52.0], bkg_uncertainty=[3.0, 7.0]
... )
>>> observations = [51, 48]
>>> data = observations + model.config.auxdata
>>> test_pois = np.linspace(0, 5, 41)
>>> results = [
...     pyhf.infer.hypotest(
...         test_poi, data, model, return_expected_set=True, return_tail_probs=True
...     )
...     for test_poi in test_pois
... ]
>>> tail_probs = np.array([test[1] for test in results])
>>> fig, ax = plt.subplots()
>>> artists = pyhf.contrib.viz.brazil.plot_cls_components(test_pois, tail_probs, ax)

Parameters:

test_pois (list or array) – The values of the POI where the hypothesis tests were performed.
tail_probs (list or array) – The values of \(\mathrm{CL}_{s+b}\) and \(\mathrm{CL}_{b}\) for the POIs tested in test_pois.
ax (matplotlib.axes.Axes) – The matplotlib axis object to plot on.
Keywords –
- no_clb (bool): Bool for not plotting the \(\mathrm{CL}_{b}\) component.
- no_clsb (bool): Bool for not plotting the \(\mathrm{CL}_{s+b}\) component.

Returns:

The matplotlib.lines.Line2D artists drawn.

Return type:

tuple