Name change to ReversibleJumpMCMC.jl

Author: kalidke

Project.toml

@@ -1,4 +1,4 @@
-name = "RJMCMC"
+name = "ReversibleJumpMCMC"
 uuid = "4e599b9b-5231-4225-b353-2dfd54e54db8"
 authors = ["Keith Lidke <klidke@unm.edu> and contributors"]
 version = "0.1.0"

docs/make.jl

@@ -1,19 +1,19 @@
 push!(LOAD_PATH,"../src/")
 
 using Documenter
-using RJMCMC
+using ReversibleJumpMCMC
 
 makedocs(
-    sitename = "RJMCMC",
+    sitename = "ReversibleJumpMCMC",
     format = Documenter.HTML(),
-    modules = [RJMCMC]
+    modules = [ReversibleJumpMCMC]
 )
 
 # Documenter can also automatically deploy documentation to gh-pages.
 # See "Hosting Documentation" and deploydocs() in the Documenter manual
 # for more information.
 
 deploydocs(;
-    repo="github.com/LidkeLab/RJMCMC.jl.git",
+    repo="github.com/LidkeLab/ReversibleJumpMCMC.jl.git",
     devbranch = "main"
 )

docs/src/RJMCMCLibrary.md

@@ -1,7 +1,7 @@
-# RJMCMC.jl Library
+# Library
 
-Documentation for RJMCMC.jl
+Documentation for ReversibleJumpMCMC.jl
 
 ```@autodocs
-Modules = [RJMCMC]
+Modules = [ReversibleJumpMCMC]
 ```

docs/src/index.md

@@ -1,6 +1,6 @@
-# RJMCMC.jl
+# Overview
 
-RJMCMC.jl provides a lightweight framework for Reversible Jump Markov Chain Monte Carlo.  
+ReversibleJumpMCMC.jl provides a lightweight framework for Reversible Jump Markov Chain Monte Carlo.  
 
 The framework is based around the following code block. 
 

examples/gaussPDFmcmc.jl

@@ -1,5 +1,5 @@
 # Explore a 1D Gaussian PDF using a basic MCMC chain
-using RJMCMC
+using ReversibleJumpMCMC
 using Distributions
 using Plots
 
@@ -33,13 +33,13 @@ njumptypes = 1 # number of jump types for RJMCMC
 jumpprobability = [1] # vector
 proposalfuns = [mypropose] # vector
 acceptfuns = [myaccept] # vector
-rjs = RJMCMC.RJMCMCStruct(burnin, iterations, njumptypes, jumpprobability, proposalfuns, acceptfuns)
+rjs = ReversibleJumpMCMC.RJMCMCStruct(burnin, iterations, njumptypes, jumpprobability, proposalfuns, acceptfuns)
 
 # initial state
 state0 = state1D(0f0)
 
 # run chain
-rjc = RJMCMC.buildchain(rjs, mhs, state0)
+rjc = ReversibleJumpMCMC.buildchain(rjs, mhs, state0)
 
 # extract states
 xchain = zeros(Float32, iterations)

src/RJMCMC.jl src/ReversibleJumpMCMC.jlsrc/RJMCMC.jl renamed to src/ReversibleJumpMCMC.jl

@@ -1,4 +1,4 @@
-module RJMCMC
+module ReversibleJumpMCMC
 
 using Plots