States
A State in BayesBay is a data structure containing all numerical values associated with a certain Markov chain step. Depending on the inference problem at hand, it could contain information about:
Discretization. For example, the nuclei positions in a Voronoi tessellation.
Free parameters. For example, the value of the physical property to be inferred, associated with each Voronoi cell.
Data noise. This includes standard deviation and noise correlation.
Cached information. This consists of a Python dictionary containing arbitrary objects that the user might want to store and reuse at the next Markov chain step (see
bayesbay.State.save_to_cache()).
Data structure that stores a Markov chain state, including all the necessary information to perform the forward operation |
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Data structure that stores the state of a parameter space. |
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Data structure that stores the state of the data noise parameters during the inference. |