bilby.core.likelihood.JointLikelihood
- class bilby.core.likelihood.JointLikelihood(*likelihoods)[source]
Bases:
Likelihood
- __init__(*likelihoods)[source]
A likelihood for combining pre-defined likelihoods. The parameters dict is automagically combined through parameters dicts of the given likelihoods. If parameters have different values have initially different values across different likelihoods, the value of the last given likelihood is chosen. This does not matter when using the JointLikelihood for sampling, because the parameters will be set consistently
- Parameters:
- *likelihoods: bilby.core.likelihood.Likelihood
likelihoods to be combined parsed as arguments
- __call__(*args, **kwargs)
Call self as a function.
Methods
__init__
(*likelihoods)A likelihood for combining pre-defined likelihoods.
This is just the sum of the log likelihoods of all parts of the joint likelihood
Difference between log likelihood and noise log likelihood
This is just the sum of the noise likelihoods of all parts of the joint likelihood
Attributes
The list of likelihoods
marginalized_parameters
meta_data
- property likelihoods
The list of likelihoods
- log_likelihood()[source]
This is just the sum of the log likelihoods of all parts of the joint likelihood