Fix prefixing test and docs

Author: penelopeysm

docs/src/api.md

@@ -40,7 +40,7 @@ even though [`Prior()`](@ref) is actually defined in the `Turing.Inference` modu
 | `@model`             | [`DynamicPPL.@model`](@extref)             | Define a probabilistic model                                                                 |
 | `@varname`           | [`AbstractPPL.@varname`](@extref)          | Generate a `VarName` from a Julia expression                                                 |
 | `to_submodel`        | [`DynamicPPL.to_submodel`](@extref)        | Define a submodel                                                                            |
-| `prefix`             | [`DynamicPPL.prefix`](@extref)             | Prefix all variable names in a model with a given symbol                                     |
+| `prefix`             | [`DynamicPPL.prefix`](@extref)             | Prefix all variable names in a model with a given VarName                                    |
 | `LogDensityFunction` | [`DynamicPPL.LogDensityFunction`](@extref) | A struct containing all information about how to evaluate a model. Mostly for advanced users |
 
 ### Inference

test/optimisation/Optimisation.jl

@@ -71,13 +71,9 @@ using Turing
         end
 
         @testset "With prefixes" begin
-            function prefix_μ(model)
-                return DynamicPPL.contextualize(
-                    model, DynamicPPL.PrefixContext{:inner}(model.context)
-                )
-            end
-            m1 = prefix_μ(model1(x))
-            m2 = prefix_μ(model2() | (var"inner.x"=x,))
+            vn = @varname(inner)
+            m1 = prefix(model1(x), vn)
+            m2 = prefix((model2() | (x=x,)), vn)
             ctx = Turing.Optimisation.OptimizationContext(DynamicPPL.LikelihoodContext())
             @test Turing.Optimisation.OptimLogDensity(m1, ctx)(w) ==
                 Turing.Optimisation.OptimLogDensity(m2, ctx)(w)