Add a model argument to getparams and setparams!! functions

Project.toml

@@ -3,7 +3,7 @@ uuid = "80f14c24-f653-4e6a-9b94-39d6b0f70001"
 keywords = ["markov chain monte carlo", "probabilistic programming"]
 license = "MIT"
 desc = "A lightweight interface for common MCMC methods."
-version = "5.5.0"
+version = "5.5.1"
 
 [deps]
 BangBang = "198e06fe-97b7-11e9-32a5-e1d131e6ad66"

src/AbstractMCMC.jl

@@ -81,26 +81,51 @@ The `MCMCSerial` algorithm allows users to sample serially, with no thread or pr
 struct MCMCSerial <: AbstractMCMCEnsemble end
 
 """
-    getparams(state[; kwargs...])
+    getparams(model::AbstractModel, state)
+    getparams(logdensity, state)
+    getparams(state)
 
 Retrieve the values of parameters from the sampler's `state` as a `Vector{<:Real}`.
 """
 function getparams end
 
+function getparams(logdensity, state)
+    return getparams(_model(logdensity), state)
+end
+
+function getparams(model::AbstractModel, state)
+    return getparams(state)
+end
+
 """
+    setparams!!(model::AbstractModel, state, params)
+    setparams!!(logdensity, state, params)
     setparams!!(state, params)
 
 Set the values of parameters in the sampler's `state` from a `Vector{<:Real}`. 
 
 This function should follow the `BangBang` interface: mutate `state` in-place if possible and 
 return the mutated `state`. Otherwise, it should return a new `state` containing the updated parameters.
 
-Although not enforced, it should hold that `setparams!!(state, getparams(state)) == state`. In another
-word, the sampler should implement a consistent transformation between its internal representation
+Although not enforced, it should hold that `setparams!!(state, getparams(state)) == state`. In other
+words, the sampler should implement a consistent transformation between its internal representation
 and the vector representation of the parameter values.
+
+Sometimes, to maintain the consistency of the log density and parameter values, a `model::AbstractModel`
+should be provided. This is useful for samplers that need to evaluate the log density at the new parameter values.
+If `model` is not an `AbstractMCMC.AbstractModel`, by default, it is assumed to be a log density function following 
+the `LogDensityProblems.jl` interface, and will be wrapped with [`AbstractMCMC.LogDensityModel`](@ref).
 """
 function setparams!! end
 
+function setparams!!(logdensity, state, params)
+    return setparams!!(_model(logdensity), state, params)
+end
+
+function setparams!!(model::AbstractModel, state, params)
+    return setparams!!(state, params)
+end
+
 include("samplingstats.jl")
 include("logging.jl")
 include("interface.jl")