TuringLang
diff --git a/‎Project.toml‎
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diff --git a/‎README.md‎
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diff --git a/‎docs/src/api.md‎
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diff --git a/‎src/AdvancedHMC.jl‎
Lines changed: 7 additions & 36 deletions b/‎src/AdvancedHMC.jl‎
Lines changed: 7 additions & 36 deletions
@@ -1,6 +1,6 @@
 name = "AdvancedHMC"
 uuid = "0bf59076-c3b1-5ca4-86bd-e02cd72cde3d"
-version = "0.4.6"
+version = "0.5.0"
 
 [deps]
 AbstractMCMC = "80f14c24-f653-4e6a-9b94-39d6b0f70001"
 
@@ -17,6 +17,10 @@ If you are interested in using AdvancedHMC.jl through a probabilistic programmin
 - We presented a poster for AdvancedHMC.jl at [StanCon 2019](https://mc-stan.org/events/stancon2019Cambridge/) in Cambridge, UK. ([pdf](https://github.com/TuringLang/AdvancedHMC.jl/files/3730367/StanCon-AHMC.pdf))
 
 **API CHANGES**
+- [v0.5.0] **Breaking!** Convinience constructors for common samplers changed to:
+  - `HMC(init_ϵ::Float64=init_ϵ, n_leapfrog::Int=n_leapfrog)`
+  - `NUTS(n_adapts::Int=n_adapts, δ::Float64=δ)` 
+  - `HMCDA(n_adapts::Int=n_adapts, δ::Float64=δ, λ::Float64=λ)`
 - [v0.2.22] Three functions are renamed.
   - `Preconditioner(metric::AbstractMetric)` -> `MassMatrixAdaptor(metric)` and 
   - `NesterovDualAveraging(δ, integrator::AbstractIntegrator)` -> `StepSizeAdaptor(δ, integrator)`
 
@@ -8,15 +8,14 @@ Documentation for AdvancedHMC.jl
 ## Structs
 ```@docs
 ClassicNoUTurn
+HMCSampler
+HMC
+NUTS
+HMCDA
 ```
 
 ## Functions
 
 ```@docs
 sample
-```
-
-## Index
-
-```@index
 ```
@@ -66,28 +66,6 @@ export Trajectory,
 
 # Useful defaults
 
-struct NUTS{TS,TC} end
-
-"""
-$(SIGNATURES)
-
-Convenient constructor for the no-U-turn sampler (NUTS).
-This falls back to `HMCKernel(Trajectory{TS}(int, TC(args...; kwargs...)))` where
-
-- `TS<:Union{MultinomialTS, SliceTS}` is the type for trajectory sampler
-- `TC<:Union{ClassicNoUTurn, GeneralisedNoUTurn, StrictGeneralisedNoUTurn}` is the type for termination criterion.
-
-See [`ClassicNoUTurn`](@ref), [`GeneralisedNoUTurn`](@ref) and [`StrictGeneralisedNoUTurn`](@ref) for details in parameters.
-"""
-NUTS{TS,TC}(int::AbstractIntegrator, args...; kwargs...) where {TS,TC} =
-    HMCKernel(Trajectory{TS}(int, TC(args...; kwargs...)))
-NUTS(int::AbstractIntegrator, args...; kwargs...) =
-    HMCKernel(Trajectory{MultinomialTS}(int, GeneralisedNoUTurn(args...; kwargs...)))
-NUTS(ϵ::AbstractScalarOrVec{<:Real}) =
-    HMCKernel(Trajectory{MultinomialTS}(Leapfrog(ϵ), GeneralisedNoUTurn()))
-
-export NUTS
-
 # Deprecations for trajectory.jl
 
 abstract type AbstractTrajectory end
@@ -103,25 +81,14 @@ struct StaticTrajectory{TS} end
     Trajectory{EndPointTS}(Leapfrog(ϵ), FixedNSteps(L)),
 )
 
-struct HMCDA{TS} end
-@deprecate HMCDA{TS}(int::AbstractIntegrator, λ) where {TS} HMCKernel(
-    Trajectory{TS}(int, FixedIntegrationTime(λ)),
-)
-@deprecate HMCDA(int::AbstractIntegrator, λ) HMCKernel(
-    Trajectory{EndPointTS}(int, FixedIntegrationTime(λ)),
-)
-@deprecate HMCDA(ϵ::AbstractScalarOrVec{<:Real}, λ) HMCKernel(
-    Trajectory{EndPointTS}(Leapfrog(ϵ), FixedIntegrationTime(λ)),
-)
-
 @deprecate find_good_eps find_good_stepsize
 
-export StaticTrajectory, HMCDA, find_good_eps
+export StaticTrajectory, find_good_eps
 
 include("adaptation/Adaptation.jl")
 using .Adaptation
 import .Adaptation:
-    StepSizeAdaptor, MassMatrixAdaptor, StanHMCAdaptor, NesterovDualAveraging
+    StepSizeAdaptor, MassMatrixAdaptor, StanHMCAdaptor, NesterovDualAveraging, NoAdaptation
 
 # Helpers for initializing adaptors via AHMC structs
 
@@ -161,13 +128,17 @@ export StepSizeAdaptor,
     WelfordVar,
     WelfordCov,
     NaiveHMCAdaptor,
-    StanHMCAdaptor
+    StanHMCAdaptor,
+    NoAdaptation
 
 include("diagnosis.jl")
 
 include("sampler.jl")
 export sample
 
+include("constructors.jl")
+export HMCSampler, HMC, NUTS, HMCDA
+
 include("abstractmcmc.jl")
 
 ## Without explicit AD backend