remove accessors

Author: Red-Portal

Project.toml

@@ -1,10 +1,9 @@
 name = "SliceSampling"
 uuid = "43f4d3e8-9711-4a8c-bd1b-03ac73a255cf"
-version = "0.7.4"
+version = "0.7.5"
 
 [deps]
 AbstractMCMC = "80f14c24-f653-4e6a-9b94-39d6b0f70001"
-Accessors = "7d9f7c33-5ae7-4f3b-8dc6-eff91059b697"
 Distributions = "31c24e10-a181-5473-b8eb-7969acd0382f"
 LinearAlgebra = "37e2e46d-f89d-539d-b4ee-838fcccc9c8e"
 LogDensityProblems = "6fdf6af0-433a-55f7-b3ed-c6c6e0b8df7c"
@@ -19,7 +18,6 @@ SliceSamplingTuringExt = ["Turing"]
 
 [compat]
 AbstractMCMC = "4, 5"
-Accessors = "0.1"
 Distributions = "0.25"
 LinearAlgebra = "1"
 LogDensityProblems = "2"

src/SliceSampling.jl

@@ -1,7 +1,6 @@
 
 module SliceSampling
 
-using Accessors
 using AbstractMCMC
 using Distributions
 using LinearAlgebra

src/multivariate/randpermgibbs.jl

@@ -38,7 +38,8 @@ end
 
 function LogDensityProblems.logdensity(gibbs::GibbsTarget, θi)
     (; model, idx, θ) = gibbs
-    return LogDensityProblems.logdensity(model, (@set θ[idx] = θi))
+    θ[idx] = θi
+    return LogDensityProblems.logdensity(model, θ)
 end
 
 function AbstractMCMC.step(