added more tests to improve codecov

src/options.jl

@@ -93,7 +93,7 @@ Returns an instance of `Options` configured for optimization over the positive d
 
 # Specific Settings
 - `A_init_value = 1`: Initializes `A` with a positive value.
-- `A_upper = 1e-4`: Upper bound for `A` is constrained to a small positive value.
+- `A_lower = 1e-4`: Lower bound for `A` is constrained to a small positive value.
 - `V_init_value = 1`: Initializes `V` with a positive value.
 - `V_lower = 1e-4`: Lower bound for `V` is constrained to a small positive value.
 
@@ -117,7 +117,7 @@ function PositiveDomain(
         tol = tol,
         maxiter = maxiter,
         A_init_value = 1.0,
-        A_upper = 1e-4,
+        A_lower = 1e-4,
         V_init_value = 1.0,
         V_lower = 1e-4,
     )

src/utils.jl

@@ -78,11 +78,6 @@ function _invert_legendre(f, options::Options)
     return g
 end
 
-function is_constant_matrix(A::AbstractMatrix)
-    flag = length(unique(A)) == 1
-    return flag
-end
-
 function _optimize(
     f::F, 
     lower::Union{Real, Nothing}, 

test/family/test_gamma.jl

@@ -1,7 +1,7 @@
 @testset "Gamma" begin
     n = 2
-    indim = 5
-    outdim = 5
+    indim = 3
+    outdim = 3
     X = rand(n, indim) * 100
 
     M1 = GammaEPCA(indim, outdim)
@@ -11,6 +11,6 @@
         M1,
         A1,
         X,
-        atol=2.5
+        atol=1.5
     )
 end

test/options_tests.jl

@@ -0,0 +1,103 @@
+@testset "Misc Options Tests" begin
+    n = 2
+    indim = 5
+    outdim = 5
+    X = (rand(n, indim) .- 0.5) .* 100
+
+    ϵ = eps()
+    G(θ) = θ^2 / 2
+    g = identity
+    F = G
+    f = identity
+    B(p, q) = Distances.sqeuclidean(p, q) / 2
+    Bg = B
+    μ = 1
+
+    run_EPCA_tests(
+        GaussianEPCA,
+        indim,
+        outdim,
+        Bg,
+        F,
+        G,
+        f,
+        g,
+        B,
+        X;
+        custom_options = Options(A_use_sobol=true, V_use_sobol=true)
+    )
+
+    run_EPCA_tests(
+        GaussianEPCA,
+        indim,
+        outdim,
+        Bg,
+        F,
+        G,
+        f,
+        g,
+        B,
+        X;
+        custom_options = Options(metaprogramming=false)
+    )
+
+    M1 = GaussianEPCA(indim, outdim; options=Options(A_lower=-1000., A_upper=1000.))
+    A1 = fit!(M1, X)
+    smoke_test(
+        M1,
+        A1,
+        X,
+        atol=0.5
+    )
+end
+
+@testset "Positive Domain" begin
+    n = 2
+    indim = 5
+    outdim = 5
+    X = rand(-100:100, n, indim)
+
+    M1 = GaussianEPCA(indim, outdim; options=PositiveDomain())
+    A1 = fit!(M1, X)
+    Θ = A1 * M1.V
+    @test all(Θ .> 0)
+end
+
+@testset "Negative Domain" begin
+    @testset "Negative Binomial" begin
+        r = 2
+        n = 2
+        indim = 3
+        outdim = 3
+        X = rand(1:10, indim, outdim)
+
+        M1 = NegativeBinomialEPCA(indim, outdim, r; options=NegativeDomain())
+        A1 = fit!(M1, X)
+        Θ = A1 * M1.V
+        @test all(Θ .< 0)
+    end
+
+    @testset "Gamma" begin
+        n = 2
+        indim = 5
+        outdim = 5
+        X = rand(n, indim) * 100
+
+        M1 = GammaEPCA(indim, outdim; options=NegativeDomain())
+        A1 = fit!(M1, X)
+        Θ = A1 * M1.V
+        @test all(Θ .< 0)
+    end
+
+    @testset "Weibull" begin
+        n = 2
+        indim = 3
+        outdim = 3
+        X = rand(indim, outdim) * 2.5
+
+        M1 = WeibullEPCA(indim, outdim; options=NegativeDomain())
+        A1 = fit!(M1, X)
+        Θ = A1 * M1.V
+        @test all(Θ .< 0)
+    end
+end

test/runtests.jl

@@ -20,4 +20,5 @@ include("utils.jl")
     include("family/test_negative_binomial.jl")
     include("family/test_pareto.jl")
     include("family/test_weibull.jl")
+    include("options_tests.jl")
 end

test/utils.jl

@@ -55,9 +55,15 @@ function run_EPCA_tests(
     f::Function, 
     g::Function, 
     B::Union{Function, PreMetric}, 
-    X::AbstractMatrix
+    X::AbstractMatrix;
+    custom_options::Union{Nothing, Options} = nothing
 )
-    M1 = epca_constructor(indim, outdim)
+    if !isnothing(custom_options)
+        M1 = epca_constructor(indim, outdim; options=custom_options)
+    else
+        M1 = epca_constructor(indim, outdim)
+    end
+
     A1 = fit!(M1, X)
 
     smoke_test(