Converted MarkovChain to an abstract base-class for MCMC samplers and moved it to a dedicated module.
EnsembleSampler now also inherits from MarkovChain and can make use of inherited methods.
Standardised the naming of some instance attributes across MCMC samplers to allow more functionality to be moved onto MarkovChain. This may cause previously saved sampler data to not load correctly.
Removed the burn and thin instance attributes of MCMC samplers used to set global burn and thin values. This means burn and thin values must now be passed explicitly to MarkovChain methods, but avoids potentially error-prone behavior of burning / thinning being applied implicitly even when the burn and thin kwargs are not specified.
Removed some obsolete demo scripts and modernised others.
MarkovChainto an abstract base-class for MCMC samplers and moved it to a dedicated module.EnsembleSamplernow also inherits fromMarkovChainand can make use of inherited methods.MarkovChain. This may cause previously saved sampler data to not load correctly.burnandthininstance attributes of MCMC samplers used to set global burn and thin values. This means burn and thin values must now be passed explicitly toMarkovChainmethods, but avoids potentially error-prone behavior of burning / thinning being applied implicitly even when theburnandthinkwargs are not specified.