Update README.md and reexport MCMCSerial (#66)

* Update README.md * Reexport MCMCSerial * Bump version * Update README.md Co-authored-by: Cameron Pfiffer <[email protected]> Co-authored-by: Cameron Pfiffer <[email protected]>
TuringLang · Oct 20, 2021 · 361a669 · 361a669 · devmotion · Oct 20, 2021
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diff --git a/Project.toml b/Project.toml
@@ -1,6 +1,6 @@
 name = "AdvancedMH"
 uuid = "5b7e9947-ddc0-4b3f-9b55-0d8042f74170"
-version = "0.6.5"
+version = "0.6.6"
 
 [deps]
 AbstractMCMC = "80f14c24-f653-4e6a-9b94-39d6b0f70001"

diff --git a/README.md b/README.md
@@ -111,14 +111,19 @@ rw_prop = RandomWalkProposal(Normal(0,1))
 Different methods are easily composeable. One parameter can be static and another can be a random walk,
 each of which may be drawn from separate distributions.
 
-## Multithreaded sampling
+## Multiple chains
 
-AdvancedMH.jl implements the interface of [AbstractMCMC](https://github.com/TuringLang/AbstractMCMC.jl/), which means you get multiple chain sampling
-in parallel for free:
+AdvancedMH.jl implements the interface of [AbstractMCMC](https://github.com/TuringLang/AbstractMCMC.jl/) which means sampling of multiple chains is supported for free:
 
 ```julia
-# Sample 4 chains from the posterior.
-chain = psample(model, RWMH(init_params), 100000, 4; param_names=["μ","σ"], chain_type=Chains)
+# Sample 4 chains from the posterior serially, without thread or process parallelism.
+chain = sample(model, RWMH(init_params), MCMCSerial(), 100000, 4; param_names=["μ","σ"], chain_type=Chains)
+
+# Sample 4 chains from the posterior using multiple threads.
+chain = sample(model, RWMH(init_params), MCMCThreads(), 100000, 4; param_names=["μ","σ"], chain_type=Chains)
+
+# Sample 4 chains from the posterior using multiple processes.
+chain = sample(model, RWMH(init_params), MCMCDistributed(), 100000, 4; param_names=["μ","σ"], chain_type=Chains)
 ```
 
 ## Metropolis-adjusted Langevin algorithm (MALA)

diff --git a/src/AdvancedMH.jl b/src/AdvancedMH.jl
@@ -22,7 +22,7 @@ export
  MALA
 
 # Reexports
-export sample, MCMCThreads, MCMCDistributed
+export sample, MCMCThreads, MCMCDistributed, MCMCSerial
 
 # Abstract type for MH-style samplers. Needs better name? 
 abstract type MHSampler <: AbstractMCMC.AbstractSampler end