hyperiax.mcmc package
Submodules
hyperiax.mcmc.fixedparameter module
- class hyperiax.mcmc.fixedparameter.FixedParameter(value)
Bases:
ParameterA parameter that is constant regardless of updates. The parameter always have the value passed in the constructor
- log_prior()
Logarithm of the prior probability of the parameter
- Returns:
as the parameter is fixed
- propose(key)
Propose a new value for the parameter
- Parameters:
key – A key to sample with
- Returns:
Copy of the parameter
- update(value, accepted)
Update the parameter. Does nothing as the parameter is fixed, i.e. the new value is discarded
- Parameters:
value – The new value to update the parameter with
accepted – Whether the new value was accepted
hyperiax.mcmc.metropolis_hastings module
hyperiax.mcmc.parameter module
- class hyperiax.mcmc.parameter.Parameter(value)
Bases:
ABCBase class for a parameter in a Markov Chain Monte Carlo simulation.
- abstract log_prior()
Logarithm of the prior probability of the parameter.
- Returns:
The logarithm of the prior probability of the parameter.
- abstract propose(key) Parameter
Propose a new parameter given a key
- Parameters:
key – the key to generate the parameter with
- Returns:
A new parameter proposal
- abstract update(value, accepted=True)
Update the value of the parameter, if accepted.
value: The new value of the parameter. accepted: Whether the new value is accepted. Default true.
hyperiax.mcmc.parameterstore module
- class hyperiax.mcmc.parameterstore.ParameterStore(params: Dict[str, Parameter])
Bases:
objectThe parameter store hosts a set of parameters.
- log_prior()
Logarithm of the prior probability of the parameters.
- Returns:
The logarithm of the prior probability of the parameters.
- propose(key) ParameterStore
Propose a new parameter store, containing newly sampled parameters.
- Parameters:
key – A key to sample with.
- Returns:
The newly sampled parameter store.
- values()
Gets the values of the parameters in the store
- Returns:
The parameters in a dictionary.