Add quality tests (#431)

Author: ErikQQY

src/AdvancedHMC.jl

@@ -172,9 +172,12 @@ function Hamiltonian(metric::AbstractMetric, ℓπ, kind::Union{Symbol,Val,Modul
             ),
         )
     end
-    ℓ = LogDensityProblemsAD.ADgradient(
-        kind isa Val ? kind : Val(Symbol(kind)), ℓπ; kwargs...
-    )
+    _kind = if kind isa Val || kind isa Symbol
+        kind
+    else
+        Symbol(kind)
+    end
+    ℓ = LogDensityProblemsAD.ADgradient(_kind, ℓπ; kwargs...)
     return Hamiltonian(metric, ℓ)
 end
 

src/adaptation/massmatrix.jl

@@ -171,8 +171,6 @@ end
 
 NaiveCov{T}(sz::Tuple{Int}) where {T<:AbstractFloat} = NaiveCov(Vector{Vector{T}}())
 
-NaiveCov(sz::Union{Tuple{Int},Tuple{Int,Int}}; kwargs...) = NaiveCov{Float64}(sz; kwargs...)
-
 Base.push!(nc::NaiveCov, s::AbstractVector) = push!(nc.S, s)
 
 reset!(nc::NaiveCov{T}) where {T} = resize!(nc.S, 0)

src/integrator.jl

@@ -218,7 +218,7 @@ function step(
     res = if FullTraj
         Vector{P}(undef, n_steps)
     else
-        z
+        Vector{P}(undef, 1)
     end
 
     (; θ, r) = z
@@ -242,7 +242,7 @@ function step(
         if FullTraj
             res[i] = z
         else
-            res = z
+            res[1] = z
         end
         if !isfinite(z)
             # Remove undef
@@ -252,5 +252,9 @@ function step(
             break
         end
     end
-    return res
+    return if FullTraj
+        res
+    else
+        first(res)
+    end
 end

src/metric.jl

@@ -80,7 +80,7 @@ end
 function DenseEuclideanMetric(
     M⁻¹::Union{AbstractMatrix{T},AbstractArray{T,3}}
 ) where {T<:AbstractFloat}
-    _temp = Vector{T}(undef, Base.front(size(M⁻¹)))
+    _temp = Vector{T}(undef, first(size(M⁻¹)))
     return DenseEuclideanMetric(M⁻¹, cholesky(Symmetric(M⁻¹)).U, _temp)
 end
 DenseEuclideanMetric(::Type{T}, D::Int) where {T} = DenseEuclideanMetric(Matrix{T}(I, D, D))

src/trajectory.jl

@@ -444,6 +444,7 @@ end
 TurnStatistic() = TurnStatistic(undef)
 
 TurnStatistic(::ClassicNoUTurn, ::PhasePoint) = TurnStatistic()
+TurnStatistic(::ClassicNoUTurn, ::Vector{<:PhasePoint}) = TurnStatistic()
 function TurnStatistic(::Union{GeneralisedNoUTurn,StrictGeneralisedNoUTurn}, z::PhasePoint)
     return TurnStatistic(z.r)
 end
@@ -776,7 +777,7 @@ function find_good_stepsize(
         ϵ′ = ratio_too_high ? d * ϵ : invd * ϵ
         _, H′ = A(h, z, ϵ)
         ΔH = H - H′
-        @debug "Crossing step" direction H′ ϵ α = min(1, exp(ΔH))
+        @debug "Crossing step" H′ ϵ α = min(1, exp(ΔH))
         # stop if there is no crossing; otherwise, continue to half or double stepsize. 
         if xor(ratio_too_high, ΔH > log_a_cross)
             break

test/Project.toml

@@ -8,6 +8,7 @@ ComponentArrays = "b0b7db55-cfe3-40fc-9ded-d10e2dbeff66"
 Distributions = "31c24e10-a181-5473-b8eb-7969acd0382f"
 FillArrays = "1a297f60-69ca-5386-bcde-b61e274b549b"
 ForwardDiff = "f6369f11-7733-5829-9624-2563aa707210"
+JET = "c3a54625-cd67-489e-a8e7-0a5a0ff4e31b"
 LinearAlgebra = "37e2e46d-f89d-539d-b4ee-838fcccc9c8e"
 LogDensityProblems = "6fdf6af0-433a-55f7-b3ed-c6c6e0b8df7c"
 LogDensityProblemsAD = "996a588d-648d-4e1f-a8f0-a84b347e47b1"

test/aqua.jl

@@ -0,0 +1,13 @@
+using AdvancedHMC
+using ReTest
+using Aqua: Aqua
+using JET
+using ForwardDiff
+
+@testset "Aqua" begin
+    Aqua.test_all(AdvancedHMC)
+end
+
+@testset "JET" begin
+    JET.test_package(AdvancedHMC; target_defined_modules=true)
+end

test/quality.jl

@@ -19,7 +19,7 @@ include("common.jl")
 if GROUP == "All" || GROUP == "AdvancedHMC"
     using ReTest
 
-    include("aqua.jl")
+    include("quality.jl")
     include("metric.jl")
     include("hamiltonian.jl")
     include("integrator.jl")