Merge pull request #3 from JuliaAI/increase-coverage

Increase coverage and fix a bug with supports_missings_measure

Author: ablaom

src/constants.jl

@@ -20,17 +20,6 @@ const DOC_SCITYPES =
     "Scientific types can be imported from "*
     "ScientificTypesBase.jl; see also the ScientificTypes.jl documentation. "
 
-ERR_BAD_FUNCTION(f) = ErrorException(
-"It looks like you're trying to use the function $f as an aggregating "*
-    "measure but have not flagged it as such. Consider declaring "*
-    "`StatisticalMeasuresBase.can_report_unaggregated(::typeof($f)) = true`."
-)
-
-ERR_NOT_A_MEASURE(measure) = ArgumentError(
-    "$measure is not a measure, as defined in by StatisticalMeasuresBase.jl. "*
-        "Did you maybe pass a type instead of an instance? "
-)
-
 ERR_NOT_CONVERTIBLE = ArgumentError("Not convertibe to a $API.jl measure. ")
 
 const ERR_UNSUPPORTED_BY_FUSSY = ArgumentError(
@@ -86,8 +75,3 @@ ERR_BAD_TRAIT(trait) = ArgumentError(
     "$trait is not an overloadable trait. Only these traits can be overloaded: "*
     "$OVERLOADABLE_TRAITS_LIST. "
 )
-
-ERR_MEASUREMENTS_UNSUPPORTED(measure) = ArgumentError(
-    "The `measurements` cannot be called on $measure as "*
-        "`$API.consumes_multiple_observations(measure)` is `false`. "
-)

src/supports_missings_measure.jl

@@ -24,13 +24,13 @@ call(measure::SupportsMissingsMeasure, ::Missing, ::Missing, args...) = missing
 call(measure::SupportsMissingsMeasure, ::Missing, y, args...) = missing
 call(measure::SupportsMissingsMeasure, yhat, ::Missing, args...) = missing
 
-measurments(measure::SupportsMissingsMeasure, yhat, y, args...) =
-    measurments(atom(measure), yhat, y, args...)
-measurments(measure::SupportsMissingsMeasure, ::Missing, ::Missing, args...) =
+measurements(measure::SupportsMissingsMeasure, yhat, y, args...) =
+    measurements(atom(measure), yhat, y, args...)
+measurements(measure::SupportsMissingsMeasure, ::Missing, ::Missing, args...) =
     missing
-measurments(measure::SupportsMissingsMeasure, ::Missing, y, args...) =
+measurements(measure::SupportsMissingsMeasure, ::Missing, y, args...) =
     missing
-measurments(measure::SupportsMissingsMeasure, yhat, ::Missing, args...) =
+measurements(measure::SupportsMissingsMeasure, yhat, ::Missing, args...) =
     missing
 
 

test/supports_missings_measure.jl

@@ -1,4 +1,5 @@
 measure = API.supports_missings_measure(LPLossOnScalars())
+rng = srng(123)
 
 @testset "calling" begin
     @test ismissing(measure(1.0, missing))
@@ -7,6 +8,28 @@ measure = API.supports_missings_measure(LPLossOnScalars())
     @test measure(1.0, 4.5) == lploss(1.0, 4.5)
 end
 
+atom = LPLossOnVectors()
+measure = API.supports_missings_measure(atom)
+y = [1 ,2, 3]
+yhat = rand(rng, 3)
+weights = rand(3)
+class_weights = Dict(1=>rand(rng), 2=>rand(rng), 3=>rand(rng))
+
+@testset "measurements" begin
+    ms = measurements(measure, [1, missing, 2], [missing, 1, 2])
+    @test ismissing(ms[1])
+    @test ismissing(ms[2])
+    @test !ismissing(ms[3])
+    @test measurements(measure, yhat, y) ≈
+        measurements(atom, yhat, y)
+    @test measurements(measure, yhat, y, weights) ≈
+        measurements(atom, yhat, y, weights)
+    @test measurements(measure, yhat, y, class_weights) ≈
+        measurements(atom, yhat, y, class_weights)
+    @test measurements(measure, yhat, y, weights, class_weights) ≈
+        measurements(atom, yhat, y, weights, class_weights)
+end
+
 atom = TraitTester(0)
 measure =  supports_missings_measure(atom)