Add Aqua to tests (#2257)

* Add running Aqua to test suite

* Remove undefined imports

* Add compat entries for stdlib dependencies

See
https://discourse.julialang.org/t/psa-compat-requirements-in-the-general-registry-are-changing/104958
for why this is necessary

* Disable Aqua checking method ambiguities

Author: mhauru

Project.toml

@@ -68,13 +68,16 @@ Compat = "4.15.0"
 EllipticalSliceSampling = "0.5, 1, 2"
 ForwardDiff = "0.10.3"
 Libtask = "0.7, 0.8"
+LinearAlgebra = "1"
 LogDensityProblems = "2"
 LogDensityProblemsAD = "1.7.0"
 MCMCChains = "5, 6"
 NamedArrays = "0.9, 0.10"
 Optimization = "3"
 OptimizationOptimJL = "0.1, 0.2, 0.3"
 OrderedCollections = "1"
+Printf = "1"
+Random = "1"
 Optim = "1"
 Reexport = "0.2, 1"
 Requires = "0.5, 1.0"

src/Turing.jl

@@ -92,8 +92,6 @@ export @model,                 # modelling
     SGHMC,
     HMCDA,
     NUTS,
-    DynamicNUTS,
-    ANUTS,
     PolynomialStepsize,
     IS,                     # particle-based sampling
     SMC,
@@ -121,7 +119,6 @@ export @model,                 # modelling
     NamedDist,              # Exports from DynamicPPL
     predict,
     pointwise_loglikelihoods,
-    elementwise_loglikelihoods,
     generated_quantities,
     logprior,
     logjoint,

src/essential/Essential.jl

@@ -19,27 +19,10 @@ include("container.jl")
 
 export @model,
     @varname,
-    generate_observe,
-    translate_tilde!,
-    get_vars,
-    get_data,
-    get_default_values,
-    ParticleContainer,
-    Particle,
-    Trace,
-    fork,
-    forkr,
-    current_trace,
-    getweights,
-    getweight,
-    effectiveSampleSize,
-    sweep!,
-    ResampleWithESSThreshold,
     AutoForwardDiff,
     AutoTracker,
     AutoZygote,
     AutoReverseDiff,
-    value,
     @logprob_str,
     @prob_str
 

src/mcmc/Inference.jl

@@ -38,7 +38,6 @@ import StatsBase: predict
 
 export  InferenceAlgorithm,
         Hamiltonian,
-        GibbsComponent,
         StaticHamiltonian,
         AdaptiveHamiltonian,
         SampleFromUniform,
@@ -54,7 +53,6 @@ export  InferenceAlgorithm,
         SGHMC,
         HMCDA,
         NUTS,       # Hamiltonian-like sampling
-        DynamicNUTS,
         IS,
         SMC,
         CSMC,

test/Aqua.jl

@@ -0,0 +1,10 @@
+module AquaTests
+
+using Aqua: Aqua
+using Turing
+
+# TODO(mhauru) We skip testing for method ambiguities because it catches a lot of problems
+# in dependencies. Would like to check it for just Turing.jl itself though.
+Aqua.test_all(Turing; ambiguities=false)
+
+end

test/Project.toml

@@ -3,6 +3,7 @@ AbstractMCMC = "80f14c24-f653-4e6a-9b94-39d6b0f70001"
 AdvancedMH = "5b7e9947-ddc0-4b3f-9b55-0d8042f74170"
 AdvancedPS = "576499cb-2369-40b2-a588-c64705576edc"
 AdvancedVI = "b5ca4192-6429-45e5-a2d9-87aec30a685c"
+Aqua = "4c88cf16-eb10-579e-8560-4a9242c79595"
 Clustering = "aaaa29a8-35af-508c-8bc3-b662a17a0fe5"
 Distributions = "31c24e10-a181-5473-b8eb-7969acd0382f"
 DistributionsAD = "ced4e74d-a319-5a8a-b0ac-84af2272839c"
@@ -39,6 +40,7 @@ AbstractMCMC = "5"
 AdvancedMH = "0.6, 0.7, 0.8"
 AdvancedPS = "0.6.0"
 AdvancedVI = "0.2"
+Aqua = "0.8"
 Clustering = "0.14, 0.15"
 Distributions = "0.25"
 DistributionsAD = "0.6.3"
@@ -47,6 +49,7 @@ DynamicPPL = "0.27"
 FiniteDifferences = "0.10.8, 0.11, 0.12"
 ForwardDiff = "0.10.12 - 0.10.32, 0.10"
 HypothesisTests = "0.11"
+LinearAlgebra = "1"
 LogDensityProblems = "2"
 LogDensityProblemsAD = "1.4"
 MCMCChains = "5, 6"
@@ -57,6 +60,8 @@ OptimizationBBO = "0.1, 0.2"
 OptimizationNLopt = "0.1, 0.2"
 OptimizationOptimJL = "0.1, 0.2, 0.3"
 PDMats = "0.10, 0.11"
+Pkg = "1"
+Random = "1"
 ReverseDiff = "1.4.2"
 SpecialFunctions = "0.10.3, 1, 2"
 StableRNGs = "1"

test/runtests.jl

@@ -26,6 +26,10 @@ macro timeit_include(path::AbstractString)
 end
 
 @testset "Turing" begin
+    @testset "Aqua" begin
+        @timeit_include("Aqua.jl")
+    end
+
     @testset "essential" begin
         @timeit_include("essential/ad.jl")
         @timeit_include("essential/container.jl")