Support init keyword in maximum/minimum

base/reduce.jl

@@ -45,7 +45,7 @@ function mapfoldl_impl(f::F, op::OP, nt, itr) where {F,OP}
 end
 
 function foldl_impl(op::OP, nt, itr) where {OP}
-    v = _foldl_impl(op, get(nt, :init, _InitialValue()), itr)
+    v = _foldl_impl(op, nt, itr)
     v isa _InitialValue && return reduce_empty_iter(op, itr)
     return v
 end
@@ -157,7 +157,7 @@ Like [`mapreduce`](@ref), but with guaranteed left associativity, as in [`foldl`
 If provided, the keyword argument `init` will be used exactly once. In general, it will be
 necessary to provide `init` to work with empty collections.
 """
-mapfoldl(f, op, itr; kw...) = mapfoldl_impl(f, op, kw.data, itr)
+mapfoldl(f, op, itr; init=_InitialValue()) = mapfoldl_impl(f, op, init, itr)
 
 """
     foldl(op, itr; [init])
@@ -200,7 +200,7 @@ Like [`mapreduce`](@ref), but with guaranteed right associativity, as in [`foldr
 provided, the keyword argument `init` will be used exactly once. In general, it will be
 necessary to provide `init` to work with empty collections.
 """
-mapfoldr(f, op, itr; kw...) = mapfoldr_impl(f, op, kw.data, itr)
+mapfoldr(f, op, itr; init=_InitialValue()) = mapfoldr_impl(f, op, init, itr)
 
 
 """
@@ -606,35 +606,47 @@ function mapreduce_impl(f, op::Union{typeof(max), typeof(min)},
 end
 
 """
-    maximum(f, itr)
+    maximum(f, itr; [init])
 
 Returns the largest result of calling function `f` on each element of `itr`.
+If provided, `init` must be a neutral element for `max` that will be returned
+for empty collections.
 
 # Examples
 ```jldoctest
 julia> maximum(length, ["Julion", "Julia", "Jule"])
 6
+
+julia> maximum(length, []; init=-1)
+-1
 ```
 """
-maximum(f, a) = mapreduce(f, max, a)
+maximum(f, a; kw...) = mapreduce(f, max, a; kw...)
 
 """
-    minimum(f, itr)
+    minimum(f, itr; [init])
 
 Returns the smallest result of calling function `f` on each element of `itr`.
+If provided, `init` must be a neutral element for `min` that will be returned
+for empty collections.
 
 # Examples
 ```jldoctest
 julia> minimum(length, ["Julion", "Julia", "Jule"])
 4
+
+julia> minimum(length, []; init=-1)
+-1
 ```
 """
-minimum(f, a) = mapreduce(f, min, a)
+minimum(f, a; kw...) = mapreduce(f, min, a; kw...)
 
 """
-    maximum(itr)
+    maximum(itr; [init])
 
 Returns the largest element in a collection.
+If provided, `init` must be a neutral element for `max` that will be returned
+for empty collections.
 
 # Examples
 ```jldoctest
@@ -643,14 +655,24 @@ julia> maximum(-20.5:10)
 
 julia> maximum([1,2,3])
 3
+
+julia> maximum(())
+ERROR: ArgumentError: reducing over an empty collection is not allowed
+Stacktrace:
+[...]
+
+julia> maximum((); init=-1)
+-1
 ```
 """
-maximum(a) = mapreduce(identity, max, a)
+maximum(a; kw...) = mapreduce(identity, max, a; kw...)
 
 """
-    minimum(itr)
+    minimum(itr; [init])
 
 Returns the smallest element in a collection.
+If provided, `init` must be a neutral element for `min` that will be returned
+for empty collections.
 
 # Examples
 ```jldoctest
@@ -659,9 +681,17 @@ julia> minimum(-20.5:10)
 
 julia> minimum([1,2,3])
 1
+
+julia> minimum([])
+ERROR: ArgumentError: reducing over an empty collection is not allowed
+Stacktrace:
+[...]
+
+julia> minimum([]; init=-1)
+-1
 ```
 """
-minimum(a) = mapreduce(identity, min, a)
+minimum(a; kw...) = mapreduce(identity, min, a; kw...)
 
 ## all & any
 

base/reducedim.jl

@@ -307,21 +307,21 @@ julia> mapreduce(isodd, |, a, dims=1)
  1  1  1  1
 ```
 """
-mapreduce(f, op, A::AbstractArrayOrBroadcasted; dims=:, kw...) =
-    _mapreduce_dim(f, op, kw.data, A, dims)
+mapreduce(f, op, A::AbstractArrayOrBroadcasted; dims=:, init=_InitialValue()) =
+    _mapreduce_dim(f, op, init, A, dims)
 mapreduce(f, op, A::AbstractArrayOrBroadcasted...; kw...) =
     reduce(op, map(f, A...); kw...)
 
-_mapreduce_dim(f, op, nt::NamedTuple{(:init,)}, A::AbstractArrayOrBroadcasted, ::Colon) =
-    mapfoldl(f, op, A; nt...)
+_mapreduce_dim(f, op, nt, A::AbstractArrayOrBroadcasted, ::Colon) =
+    mapfoldl_impl(f, op, nt, A)
 
-_mapreduce_dim(f, op, ::NamedTuple{()}, A::AbstractArrayOrBroadcasted, ::Colon) =
+_mapreduce_dim(f, op, ::_InitialValue, A::AbstractArrayOrBroadcasted, ::Colon) =
     _mapreduce(f, op, IndexStyle(A), A)
 
-_mapreduce_dim(f, op, nt::NamedTuple{(:init,)}, A::AbstractArrayOrBroadcasted, dims) =
-    mapreducedim!(f, op, reducedim_initarray(A, dims, nt.init), A)
+_mapreduce_dim(f, op, nt, A::AbstractArrayOrBroadcasted, dims) =
+    mapreducedim!(f, op, reducedim_initarray(A, dims, nt), A)
 
-_mapreduce_dim(f, op, ::NamedTuple{()}, A::AbstractArrayOrBroadcasted, dims) =
+_mapreduce_dim(f, op, ::_InitialValue, A::AbstractArrayOrBroadcasted, dims) =
     mapreducedim!(f, op, reducedim_init(f, op, A, dims), A)
 
 """
@@ -717,12 +717,12 @@ for (fname, _fname, op) in [(:sum,     :_sum,     :add_sum), (:prod,    :_prod,
                             (:maximum, :_maximum, :max),     (:minimum, :_minimum, :min)]
     @eval begin
         # User-facing methods with keyword arguments
-        @inline ($fname)(a::AbstractArray; dims=:) = ($_fname)(a, dims)
-        @inline ($fname)(f, a::AbstractArray; dims=:) = ($_fname)(f, a, dims)
+        @inline ($fname)(a::AbstractArray; dims=:, kw...) = ($_fname)(a, dims; kw...)
+        @inline ($fname)(f, a::AbstractArray; dims=:, kw...) = ($_fname)(f, a, dims; kw...)
 
         # Underlying implementations using dispatch
-        ($_fname)(a, ::Colon) = ($_fname)(identity, a, :)
-        ($_fname)(f, a, ::Colon) = mapreduce(f, $op, a)
+        ($_fname)(a, ::Colon; kw...) = ($_fname)(identity, a, :; kw...)
+        ($_fname)(f, a, ::Colon; kw...) = mapreduce(f, $op, a; kw...)
     end
 end
 
@@ -743,8 +743,8 @@ for (fname, op) in [(:sum, :add_sum), (:prod, :mul_prod),
             mapreducedim!(f, $(op), initarray!(r, $(op), init, A), A)
         $(fname!)(r::AbstractArray, A::AbstractArray; init::Bool=true) = $(fname!)(identity, r, A; init=init)
 
-        $(_fname)(A, dims)    = $(_fname)(identity, A, dims)
-        $(_fname)(f, A, dims) = mapreduce(f, $(op), A, dims=dims)
+        $(_fname)(A, dims; kw...)    = $(_fname)(identity, A, dims; kw...)
+        $(_fname)(f, A, dims; kw...) = mapreduce(f, $(op), A; dims=dims, kw...)
     end
 end
 

test/reduce.jl

@@ -208,6 +208,9 @@ prod2(itr) = invoke(prod, Tuple{Any}, itr)
 @test_throws ArgumentError maximum(Int[])
 @test_throws ArgumentError minimum(Int[])
 
+@test maximum(Int[]; init=-1) == -1
+@test minimum(Int[]; init=-1) == -1
+
 @test maximum(5) == 5
 @test minimum(5) == 5
 @test extrema(5) == (5, 5)

test/reducedim.jl

@@ -75,6 +75,11 @@ safe_minabs(A::Array{T}, region) where {T} = safe_mapslices(minimum, abs.(A), re
     @test @inferred(count(!, Breduc, dims=region)) ≈ safe_count(.!Breduc, region)
 end
 
+# Combining dims and init
+A = Array{Int}(undef, 0, 3)
+@test_throws ArgumentError maximum(A; dims=1)
+@test maximum(A; dims=1, init=-1) == reshape([-1,-1,-1], 1, 3)
+
 # Test reduction along first dimension; this is special-cased for
 # size(A, 1) >= 16
 Breduc = rand(64, 3)