hepdata_like¶
-
class
pyhf.simplemodels.
hepdata_like
(signal_data, bkg_data, bkg_uncerts, batch_size=None)[source]¶ Construct a simple single channel
Model
with ashapesys
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