Remove the temporary skip. (#74)

JuliaSparse · Jan 29, 2022 · 8cf1c26 · 8cf1c26
1 parent 8d397cc
commit 8cf1c26
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Showing 2 changed files with 20 additions and 34 deletions.
diff --git a/src/sparsematrix.jl b/src/sparsematrix.jl
@@ -1921,10 +1921,8 @@ _mapreducezeros(f, op::Union{typeof(Base.mul_prod),typeof(*)},::Type{T}, nzeros:
     nzeros == 0 ? op(one(v0), v0) : op(f(zero(T))^nzeros, v0)
 _mapreducezeros(f, op::Union{typeof(min),typeof(max)}, ::Type{T}, nzeros::Integer, v0) where {T} =
     nzeros == 0 ? v0 : op(v0, f(zero(T)))
-if isdefined(Base, :_extrema_rf)
-    _mapreducezeros(f::Base.ExtremaMap, op::typeof(Base._extrema_rf), ::Type{T}, nzeros::Integer, v0) where {T} =
-        nzeros == 0 ? v0 : op(v0, f(zero(T)))
-end
+_mapreducezeros(f::Base.ExtremaMap, op::typeof(Base._extrema_rf), ::Type{T}, nzeros::Integer, v0) where {T} =
+    nzeros == 0 ? v0 : op(v0, f(zero(T)))
 
 function Base._mapreduce(f, op::typeof(*), ::Base.IndexCartesian, A::AbstractSparseMatrixCSC{T}) where T
     nzeros = widelength(A)-nnz(A)

diff --git a/test/higherorderfns.jl b/test/higherorderfns.jl
@@ -709,51 +709,39 @@ end
     @test extrema(f, x) == extrema(f, y)
     @test extrema(spzeros(n, n)) == (0.0, 0.0)
     @test extrema(spzeros(n)) == (0.0, 0.0)
-    # TODO: Remove the temporary skip once https://github.com/JuliaLang/julia/pull/43604 is merged
-    if isdefined(Base, :_extrema_rf)
-        @test_throws "reducing over an empty" extrema(spzeros(0, 0))
-        @test_throws "reducing over an empty" extrema(spzeros(0))
-    end
+    @test_throws "reducing over an empty" extrema(spzeros(0, 0))
+    @test_throws "reducing over an empty" extrema(spzeros(0))
     @test extrema(sparse(ones(n, n))) == (1.0, 1.0)
     @test extrema(sparse(ones(n))) == (1.0, 1.0)
     @test extrema(A; dims=:) == extrema(B; dims=:)
     @test extrema(A; dims=1) == extrema(B; dims=1)
     @test extrema(A; dims=2) == extrema(B; dims=2)
     @test extrema(A; dims=(1,2)) == extrema(B; dims=(1,2))
     @test extrema(f, A; dims=1) == extrema(f, B; dims=1)
-    # TODO: Remove the temporary skip once https://github.com/JuliaLang/julia/pull/43604 is merged
-    if isdefined(Base, :_extrema_rf)
-        @test_throws "reducing over an empty" extrema(sparse(C); dims=1) == extrema(C; dims=1)
-    end
+    @test_throws "reducing over an empty" extrema(sparse(C); dims=1) == extrema(C; dims=1)
     @test extrema(A; dims=[]) == extrema(B; dims=[])
     @test extrema(x; dims=:) == extrema(y; dims=:)
     @test extrema(x; dims=1) == extrema(y; dims=1)
     @test extrema(f, x; dims=1) == extrema(f, y; dims=1)
-    # TODO: Remove the temporary skip once https://github.com/JuliaLang/julia/pull/43604 is merged
-    if isdefined(Base, :_extrema_rf)
-        @test_throws "reducing over an empty" extrema(sparse(z); dims=1)
-    end
+    @test_throws "reducing over an empty" extrema(sparse(z); dims=1)
     @test extrema(x; dims=[]) == extrema(y; dims=[])
 end
 
-# TODO: Remove the temporary skip once https://github.com/JuliaLang/julia/pull/43604 is merged
-if isdefined(Base, :_extrema_rf)
-    function test_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 all(x -> isequal(x[1], x[2:3]), zip(vext,vmin,vmax))
-        end
+function test_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 all(x -> isequal(x[1], x[2:3]), zip(vext,vmin,vmax))
     end
-    @testset "NaN test for sparse extrema" begin
-        for sz = (3, 10, 100)
-            A = sprand(sz, sz, 0.3)
-            A[rand(1:sz^2,sz)] .= NaN
-            test_extrema(A)
-            A = sprand(sz*sz, 0.3)
-            A[rand(1:sz^2,sz)] .= NaN
-            test_extrema(A; dims_test = ((), 1, 2))
-        end
+end
+@testset "NaN test for sparse extrema" begin
+    for sz = (3, 10, 100)
+        A = sprand(sz, sz, 0.3)
+        A[rand(1:sz^2,sz)] .= NaN
+        test_extrema(A)
+        A = sprand(sz*sz, 0.3)
+        A[rand(1:sz^2,sz)] .= NaN
+        test_extrema(A; dims_test = ((), 1, 2))
     end
 end