LinearHypothesis

class remu.likelihood.LinearHypothesis(M, b=None, *args, **kwargs)

Bases: remu.likelihood.CompositeHypothesis

Special case of CompositeHypothesis for linear combinations.

Parameters:

M : 2-dimensional ndarray

The matrix translating the parameter vector into a truth vector:

truth = M.dot(parameters)

b : ndarray, optional

A constant (vector) to be added to the truth vector:

truth = M.dot(parameters) + b

*args, **kwargs : optional

Other arguments are passed on to the CompositeHypothesis init method.

See also

TemplateHypothesis

fix_parameters(fix_values)

Return a new CompositeHypothesis by fixing some parameters.

Parameters:

fix_values : iterable of values

This iterable must have the same length as the vector of parameters of the CompositeHypothesis. The parameters of the new CompositeHypothesis are fixed to the given values. Parameters that should not be fixed must be specified with None. For example, to fix the first and third parameter of a 3-parameter hypothesis, fix_values must look like this:

(1.23, None, 9.87)

The resulting CompositeHypothesis has one free parameter, the second parameter of the original hypothesis.

translate(parameters)

Translate the parameter vector to a truth vector.

Parameters:

parameters : ndarray like

Vector of the hypothesis parameters.

Returns:

ndarray

Vector of the corresponding truth space expectation values.