TemplatePredictor

class remu.likelihood.TemplatePredictor(templates, constants=0, **kwargs)[source]

MatrixPredictor from templates.

Parameters

templatesarray like: The templates to be combined together. Each template gets its own weight parameter. Shape: ([n_systematics,]n_templates,len(template))
constantsndarray, optional: Shape: ([n_systematics,]n_reco_bins)
**kwargsoptional: Additional keyword arguments are passed to the MatrixPredictor.

Methods

`__call__`(args, *kwargs)	See `prediction()`.
`check_bounds`(parameters)	Check that all parameters are within bounds.
`compose`(other)	Return a new Predictor that is a composition with other.
`fix_parameters`(fix_values)	Return a new Predictor with fewer free parameters.
`prediction`(parameters, args, *kwargs)	Turn a set of parameters into a reco prediction.

compose(other)

Return a new Predictor that is a composition with other.

new_predictor(parameters) = self(other(parameters))

fix_parameters(fix_values)

Return a new Predictor with fewer free parameters.

Parameters

fix_valuesiterable: List of the parameter values that the parameters should be fixed at. The list must be of the same length as the number of parameters of predictor. Any parameters that should remain unfixed should be specified with None or np.nan.