hepdata_like

class pyhf.simplemodels.hepdata_like(signal_data, bkg_data, bkg_uncerts, batch_size=None)[source]

Construct a simple single channel Model with a shapesys modifier representing an uncorrelated background uncertainty.

Example

>>> import pyhf
>>> pyhf.set_backend("numpy")
>>> model = pyhf.simplemodels.hepdata_like(
...     signal_data=[12.0, 11.0], bkg_data=[50.0, 52.0], bkg_uncerts=[3.0, 7.0]
... )
>>> model.schema
'model.json'
>>> model.config.channels
['singlechannel']
>>> model.config.samples
['background', 'signal']
>>> model.config.parameters
['mu', 'uncorr_bkguncrt']
>>> model.expected_data(model.config.suggested_init())
array([ 62.        ,  63.        , 277.77777778,  55.18367347])
Parameters
  • signal_data (list) – The data in the signal sample

  • bkg_data (list) – The data in the background sample

  • bkg_uncerts (list) – The statistical uncertainty on the background sample counts

  • batch_size (None or int) – Number of simultaneous (batched) Models to compute

Returns

The statistical model adhering to the model.json schema

Return type

Model