Return missing when calculating area_under_curve() for empty inputs

.JuliaFormatter.toml

@@ -0,0 +1 @@
+style = "yas"

Project.toml

@@ -1,7 +1,7 @@
 name = "Lighthouse"
 uuid = "ac2c24cd-07f0-4848-96b2-1b82c3ea0e59"
 authors = ["Beacon Biosignals, Inc."]
-version = "0.13.3"
+version = "0.13.4"
 
 [deps]
 Dates = "ade2ca70-3891-5945-98fb-dc099432e06a"

src/metrics.jl

@@ -105,7 +105,7 @@ Return `(κ, p₀)` where `κ` is Cohen's kappa and `p₀` percent agreement giv
 their equivalents in [`confusion_matrix`](@ref)).
 """
 function cohens_kappa(class_count, hard_label_pairs)
-    @assert all(issubset(pair, 1:class_count) for pair in hard_label_pairs)
+    all(issubset(pair, 1:class_count) for pair in hard_label_pairs) || throw(ArgumentError("Unexpected class in `hard_label_pairs`."))
     p₀ = accuracy(confusion_matrix(class_count, hard_label_pairs))
     pₑ = _probability_of_chance_agreement(class_count, hard_label_pairs)
     return _cohens_kappa(p₀, pₑ), p₀

src/utilities.jl

@@ -13,10 +13,11 @@ end
     area_under_curve(x, y)
 
 Calculates the area under the curve specified by the `x` vector and `y` vector
-using the trapezoidal rule.
+using the trapezoidal rule. If inputs are empty, return `missing`.
 """
 function area_under_curve(x, y)
-    @assert length(x) == length(y)
+    length(x) == length(y) || throw(ArgumentError("Length of inputs must match."))
+    length(x) == 0 && return missing
     auc = zero(middle(one(eltype(x)), one(eltype(y))))
     perms = sortperm(x)
     sorted_x = view(x, perms)
@@ -32,10 +33,10 @@ end
     area_under_curve_unit_square(x, y)
 
 Calculates the area under the curve specified by the `x` vector and `y` vector
-for a unit square, using the trapezoidal rule.
+for a unit square, using the trapezoidal rule. If inputs are empty, return `missing`.
 """
 function area_under_curve_unit_square(x, y)
-    @assert length(x) == length(y)
+    length(x) == length(y) || throw(ArgumentError("Length of inputs must match."))
     kept = [(i, j)
             for (i, j) in zip(x, y)
             if !(ismissing(i) || ismissing(j)) && (0 <= i <= 1 && 0 <= j <= 1)]

test/metrics.jl

@@ -1,11 +1,9 @@
 @testset "agreement/confusion matrix tests" begin
     hard_label_pairs = zip([1, 1, 3, 1, 3, 1, 2, 1], [2, 2, 1, 1, 3, 2, 3, 1])
     c = confusion_matrix(3, hard_label_pairs)
-    @test c == [
-        2 3 0
-        0 0 1
-        1 0 1
-    ]
+    @test c == [2 3 0
+                0 0 1
+                1 0 1]
     kappa, percent_agreement = cohens_kappa(3, hard_label_pairs)
     chance = Lighthouse._probability_of_chance_agreement(3, hard_label_pairs)
     @test chance == (5 * 3 + 1 * 3 + 2 * 2) / 8^2
@@ -91,6 +89,8 @@
             @test Lighthouse._cohens_kappa(p, p / 2) > 0
         end
     end
+
+    @test_throws ArgumentError cohens_kappa(3, [(4, 5), (8, 2)])
 end
 
 @testset "`calibration_curve`" begin

test/utilities.jl

@@ -7,15 +7,17 @@
 end
 
 @testset "`Lighthouse.area_under_curve`" begin
-    @test_throws AssertionError Lighthouse.area_under_curve([0, 1, 2], [0, 1])
+    @test_throws ArgumentError Lighthouse.area_under_curve([0, 1, 2], [0, 1])
+    @test ismissing(Lighthouse.area_under_curve([], []))
     @test isapprox(Lighthouse.area_under_curve(collect(0:0.01:1), collect(0:0.01:1)), 0.5;
                    atol=0.01)
     @test isapprox(Lighthouse.area_under_curve(collect(0:0.01:(2π)), sin.(0:0.01:(2π))),
                    0.0; atol=0.01)
 end
 
 @testset "`Lighthouse.area_under_curve_unit_square`" begin
-    @test_throws AssertionError Lighthouse.area_under_curve_unit_square([0, 1, 2], [0, 1])
+    @test_throws ArgumentError Lighthouse.area_under_curve_unit_square([0, 1, 2], [0, 1])
+    @test ismissing(Lighthouse.area_under_curve_unit_square([], []))
     @test isapprox(Lighthouse.area_under_curve_unit_square(collect(0:0.01:1),
                                                            collect(0:0.01:1)), 0.5;
                    atol=0.01)