Improve test coverage for utilities (#304)

* Spelling * Add allequal methods, increase test coverage * Update test/likelihoodratiotest.jl Co-Authored-By: Phillip Alday <[email protected]> Co-authored-by: Phillip Alday <[email protected]>
JuliaStats · Apr 14, 2020 · 872bba1 · 872bba1
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diff --git a/src/likelihoodratiotest.jl b/src/likelihoodratiotest.jl
@@ -53,7 +53,7 @@ Note that nesting of the models is not checked.  It is incumbent on the user to
 """
 function likelihoodratiotest(m::LinearMixedModel...)
     allequal(getproperty.(getproperty.(m,:optsum),:REML)) ||
-        throw(ArgumentError("Models must all be fit with the same objective (i.e. alll ML or all REML)"))
+        throw(ArgumentError("Models must all be fit with the same objective (i.e. all ML or all REML)"))
     if any(getproperty.(getproperty.(m,:optsum),:REML))
         allequal(coefnames.(m))  ||
                 throw(ArgumentError("Likelihood-ratio tests for REML-fitted models are only valid when the fixed-effects specifications are identical"))

diff --git a/src/utilities.jl b/src/utilities.jl
@@ -7,6 +7,10 @@ function allequal(x::Array; comparison=isequal)::Bool
     all(comparison.(first(x),  x))
 end
 
+allequal(x::Vector{Bool})::Bool = !any(x) || all(x)
+
+allequal(x::NTuple{N,Bool}) where {N} = !any(x) || all(x)
+
 function allequal(x::Tuple; comparison=isequal)::Bool
     all(comparison.(first(x),  x))
 end
@@ -50,7 +54,7 @@ end
 densify(A::AbstractMatrix, threshold::Real = 0.3) = A
 
 densify(A::SparseVector, threshold::Real = 0.3) = Vector(A)
-densify(A::Diagonal{T,SparseVector}, threshold::Real = 0.3) where {T} =
+densify(A::Diagonal{T,SparseVector{T,Ti}}, threshold::Real = 0.3) where {T,Ti} =
     Diagonal(Vector(A.diag))
 
 """

diff --git a/test/likelihoodratiotest.jl b/test/likelihoodratiotest.jl
@@ -1,46 +1,50 @@
-using MixedModels, Test
-import GLM: ProbitLink
+using MixedModels
+using Test
+
+using MixedModels: dataset, likelihoodratiotest
+using GLM: ProbitLink
 
 @testset "likelihoodratio test" begin
-    slp = MixedModels.dataset(:sleepstudy);
+    slp = dataset(:sleepstudy);
     fm0 = fit(MixedModel,@formula(reaction ~ 1 + (1+days|subj)),slp);
     fm1 = fit(MixedModel,@formula(reaction ~ 1 + days + (1+days|subj)),slp);
-    lrt = MixedModels.likelihoodratiotest(fm0,fm1);
+    lrt = likelihoodratiotest(fm0,fm1);
 
     @test [deviance(fm0), deviance(fm1)] == lrt.deviance
-    @test deviance(fm0) - deviance(fm1) == first(lrt.tests.deviancediff)
-    @test first(lrt.tests.dofdiff) == 1
+    @test deviance(fm0) - deviance(fm1) == only(lrt.tests.deviancediff)
+    @test only(lrt.tests.dofdiff) == 1
     @test sum(map(length,lrt.tests)) == 3
     @test sum(map(length,lrt.pvalues)) == 1
     @test sum(map(length,lrt.models)) == 4
     @test length(lrt.formulae) == 2
     show(IOBuffer(),lrt);
+    @test :pvalues in propertynames(lrt)
 
 
     # mix of REML and ML
     fm0 = fit(MixedModel,@formula(reaction ~ 1 + (1+days|subj)),slp, REML=true);
-    @test_throws ArgumentError MixedModels.likelihoodratiotest(fm0,fm1)
+    @test_throws ArgumentError likelihoodratiotest(fm0,fm1)
 
     # differing FE with REML
     fm1 = fit(MixedModel,@formula(reaction ~ 1 + days + (1+days|subj)),slp, REML=true);
-    fm10 = fit(MixedModel,@formula(reaction ~ 1 + days + (1|subj)),slp, REML=true);
-    @test_throws ArgumentError MixedModels.likelihoodratiotest(fm0,fm1);
+
+    @test_throws ArgumentError likelihoodratiotest(fm0,fm1)
 
     contra = MixedModels.dataset(:contra);
     gm0 = fit(MixedModel, @formula(use ~ 1+age+urban+livch+(1|urbdist)), contra, Bernoulli(), fast=true);
     gm1 = fit(MixedModel, @formula(use ~ 1+age+abs2(age)+urban+livch+(1|urbdist)), contra, Bernoulli(), fast=true);
-    lrt = MixedModels.likelihoodratiotest(gm0,gm1);
+    lrt = likelihoodratiotest(gm0,gm1);
     @test [deviance(gm0), deviance(gm1)] == lrt.deviance
-    @test deviance(gm0) - deviance(gm1) == first(lrt.tests.deviancediff)
+    @test deviance(gm0) - deviance(gm1) == only(lrt.tests.deviancediff)
     @test first(lrt.tests.dofdiff) == 1
-    @test sum(map(length,lrt.tests)) == 3
-    @test sum(map(length,lrt.pvalues)) == 1
-    @test sum(map(length,lrt.models)) == 4
+    @test sum(length, lrt.tests) == 3
+    @test sum(length, lrt.pvalues) == 1
+    @test sum(length, lrt.models) == 4
     @test length(lrt.formulae) == 2
 
     # mismatched links
     gm_probit = fit(MixedModel, @formula(use ~ 1+age+urban+livch+(1|urbdist)), contra, Bernoulli(), ProbitLink(), fast=true);
-    @test_throws ArgumentError MixedModels.likelihoodratiotest(gm0,gm_probit)
+    @test_throws ArgumentError likelihoodratiotest(gm0,gm_probit)
 
     # mismatched families
     gm_poisson = fit(MixedModel, @formula(use ~ 1+age+urban+livch+(1|urbdist)), contra, Poisson(), fast=true);

diff --git a/test/pls.jl b/test/pls.jl
@@ -242,7 +242,14 @@ end
 
     @testset "PCA" begin
         @test length(fm1.rePCA) == 3
-        @test length(MixedModels.PCA(fm1)) == 3
+        pca = MixedModels.PCA(fm1)
+        @test length(pca) == 3
+        @test :covcor in propertynames(first(pca))
+        str = String(take!(io))
+        show(io, first(pca), stddevs=true, variances=true)
+        str = String(take!(io))
+        @test !isempty(findall("Standard deviations:", str))
+        @test !isempty(findall("Variances:", str))        
     end
 
     show(io, BlockDescription(fm1))

diff --git a/test/utilities.jl b/test/utilities.jl
@@ -1,11 +1,32 @@
-using LinearAlgebra, MixedModels, Random, SparseArrays, Test
+using LinearAlgebra
+using MixedModels
+using Random
+using SparseArrays
+using Test
 
-@testset "utilities" begin
-	@test MixedModels.average(1.1, 1.2) == 1.15
-	@test MixedModels.densify(sparse(1:5, 1:5, ones(5))) == Diagonal(ones(5))
+using MixedModels: allequal, average, densify, dataset
+
+@testset "average" begin
+	@test average(1.1, 1.2) == 1.15
+end
+
+@testset "densify" begin
+	@test densify(sparse(1:5, 1:5, ones(5))) == Diagonal(ones(5))
 	rsparsev = SparseVector(float.(rand(MersenneTwister(123454321), Bool, 20)))
-	@test MixedModels.densify(rsparsev) == Vector(rsparsev)
-	@test MixedModels.densify(Diagonal(rsparsev)) == Diagonal(Vector(rsparsev))
+	@test densify(rsparsev) == Vector(rsparsev)
+	@test densify(Diagonal(rsparsev)) == Diagonal(Vector(rsparsev))
+end
+
+@testset "allequal" begin
+	@test allequal((true, true, true))
+	@test allequal([true, true, true])
+	@test !allequal((true, false, true))
+	@test !allequal([true, false, true])
+	@test !allequal(collect(1:4))
+	@test allequal((false, false, false))
+	@test allequal([false, false, false])
+	@test allequal(ones(3))
+	@test allequal(1, 1, 1)
 end
 
 @testset "threaded_replicate" begin