Implement HierarchicalLogLikelihood

[DavAug]

A HierarchicalLogLikelihood

• Takes a list of pints.LogPDFs
• Takes a list of PopulationLogPDFs.
• Implement a PopulationLogPDF base class
  • n_pop_params - population level parameters
  • sample for fixed pop parameters
  • call takes individual and pop parameters and returns score
  • pools_parameters return False or True
• Implement a PoolParameters class that simply takes all parameters and sets them equal.
  • Evaluation returns 0
  • sampling return the input parameter
• HierarchicalLogLikelihood checks whether pop pools, if so, adds just n_pop_params to input parameters, if not adds individual params and n_pop_params.
• Then distributes the right parameters to the right log_likelihoods and PopulationLogPDFs. Possibly index entries for each individual loglikelihood and also index(mask) parameters for the population parameters.

Implement support in the ProblemModellingController

• Extend the set_population_model class.