add test for extrema(!)

Generalize sparsevector reduction

and add few more optimization for `min/max/extrema`

Author: N5N3

test/reducedim.jl

@@ -458,17 +458,47 @@ end
     for R in (fill(0, 4), fill(0, 4, 1), fill(0, 4, 1, 1))
         @test @inferred(maximum!(R, B)) == reshape(21:24, size(R))
         @test @inferred(minimum!(R, B)) == reshape(1:4, size(R))
+        @test @inferred(extrema!(fill((0,0), size(R)), B)) == reshape(tuple.(1:4, 21:24), size(R))
     end
     for R in (fill(0, 1, 3), fill(0, 1, 3, 1))
         @test @inferred(maximum!(R, B)) == reshape(16:4:24, size(R))
         @test @inferred(minimum!(R, B)) == reshape(1:4:9, size(R))
+        @test @inferred(extrema!(fill((0,0), size(R)), B)) == reshape(tuple.(1:4:9, 16:4:24), size(R))
+    end
+    for (ini, f!) in zip((0,0,(0,0)), (maximum!, minimum!, extrema!))
+        @test_throws DimensionMismatch f!(fill(ini, 4, 1, 1, 1), B)
+        @test_throws DimensionMismatch f!(fill(ini, 1, 3, 1, 1), B)
+        @test_throws DimensionMismatch f!(fill(ini, 1, 1, 2, 1), B)
+    end
+end
+
+function unordered_test_for_extrema(a; dims_test = ((), 1, 2, (1,2), 3))
+    for dims in dims_test
+        vext = extrema(a; dims)
+        vmin, vmax = minimum(a; dims), maximum(a; dims)
+        @test isequal(extrema!(copy(vext), a), vext)
+        @test all(x -> isequal(x[1], x[2:3]), zip(vext,vmin,vmax))
+    end
+end
+@testset "0.0,-0.0 test for extrema with dims" begin
+    @test extrema([-0.0;0.0], dims = 1)[1] === (-0.0,0.0)
+    @test tuple(extrema([-0.0;0.0], dims = 2)...) === ((-0.0, -0.0), (0.0, 0.0))
+end
+@testset "NaN/missing test for extrema with dims #43599" begin
+    for sz = (3, 10, 100)
+        for T in (Int, BigInt, Float64, BigFloat)
+            Aₘ = Matrix{Union{T, Missing}}(rand(-sz:sz, sz, sz))
+            Aₘ[rand(1:sz*sz, sz)] .= missing
+            unordered_test_for_extrema(Aₘ)
+            if T <: AbstractFloat
+                Aₙ = map(i -> ismissing(i) ? T(NaN) : i, Aₘ)
+                unordered_test_for_extrema(Aₙ)
+                p = rand(1:sz*sz, sz)
+                Aₘ[p] .= NaN
+                unordered_test_for_extrema(Aₘ)
+            end
+        end
     end
-    @test_throws DimensionMismatch maximum!(fill(0, 4, 1, 1, 1), B)
-    @test_throws DimensionMismatch minimum!(fill(0, 4, 1, 1, 1), B)
-    @test_throws DimensionMismatch maximum!(fill(0, 1, 3, 1, 1), B)
-    @test_throws DimensionMismatch minimum!(fill(0, 1, 3, 1, 1), B)
-    @test_throws DimensionMismatch maximum!(fill(0, 1, 1, 2, 1), B)
-    @test_throws DimensionMismatch minimum!(fill(0, 1, 1, 2, 1), B)
 end
 
 # issue #26709