DataModel

class remu.likelihood.DataModel(data_vector)

Base class for representation of data statistical models.

The resulting object can be called like a function:

log_likelihood = likelihood_calculator(prediction)

Parameters

data_vectorarray_like

Shape: ([a,b,...,]n_reco_bins,)

Attributes

data_vector

(ndarray) The data vector k.

Methods

__call__(*args, **kwargs)	Call self as a function.
generate_toy_data(reco_vector[, size])	Generate toy data according to the expectation values.
generate_toy_data_model(*args, **kwargs)	Generate toy data model according to the expectation values.
log_likelihood(reco_vector)	Calculate the likelihood of the provided expectation values.

classmethod generate_toy_data(reco_vector, size=None)

Generate toy data according to the expectation values.

The reco vector can have a shape ([c,d,]n_reco_bins,). Assuming the requested size is (a,b,...,), the output will be of shape ([a,b,...,][c,d,...,]).

classmethod generate_toy_data_model(*args, **kwargs)

Generate toy data model according to the expectation values.

All arguments are passed to generate_toy_data().

log_likelihood(reco_vector)

Calculate the likelihood of the provided expectation values.

The reco vector can have a shape ([c,d,]n_reco_bins,). Assuming the data is of shape ([a,b,...,]n_reco_bins,), the output will be of shape ([a,b,...,][c,d,...,]).