Allow for quantile to operate over an entire Matrix (#108)

Author: this-josh

src/Statistics.jl

@@ -958,12 +958,19 @@ function quantile!(v::AbstractVector, p::Union{AbstractArray, Tuple{Vararg{Real}
     end
     return map(x->_quantile(v, x, alpha=alpha, beta=beta), p)
 end
+quantile!(a::AbstractArray, p::Union{AbstractArray,Tuple{Vararg{Real}}};
+          sorted::Bool=false, alpha::Real=1.0, beta::Real=alpha) =
+    quantile!(vec(a), p, sorted=sorted, alpha=alpha, beta=alpha)
 
-quantile!(v::AbstractVector, p::Real; sorted::Bool=false, alpha::Real=1., beta::Real=alpha) =
+quantile!(q::AbstractArray, a::AbstractArray, p::Union{AbstractArray,Tuple{Vararg{Real}}};
+          sorted::Bool=false, alpha::Real=1.0, beta::Real=alpha) =
+    quantile!(q, vec(a), p, sorted=sorted, alpha=alpha, beta=alpha)
+
+quantile!(v::AbstractVector, p::Real; sorted::Bool=false, alpha::Real=1.0, beta::Real=alpha) =
     _quantile(_quantilesort!(v, sorted, p, p), p, alpha=alpha, beta=beta)
 
 # Function to perform partial sort of v for quantiles in given range
-function _quantilesort!(v::AbstractArray, sorted::Bool, minp::Real, maxp::Real)
+function _quantilesort!(v::AbstractVector, sorted::Bool, minp::Real, maxp::Real)
     isempty(v) && throw(ArgumentError("empty data vector"))
     require_one_based_indexing(v)
 

test/runtests.jl

@@ -613,6 +613,9 @@ end
     @test quantile(Any[1, Float16(2), 3], Float16(0.5)) isa Float16
     @test quantile(Any[1, big(2), 3], Float16(0.5)) isa BigFloat
 
+    @test quantile(reshape(1:100, (10, 10)), [0.00, 0.25, 0.50, 0.75, 1.00]) ==
+        [1.0, 25.75, 50.5, 75.25, 100.0]
+
     # Need a large vector to actually check consequences of partial sorting
     x = rand(50)
     for sorted in (false, true)
@@ -639,6 +642,11 @@ end
     @test quantile!(y, x, [0.1, 0.5, 0.9]) === y
     @test y ≈ [1.2, 2.0, 2.8]
 
+    x = reshape(collect(1:100), (10, 10))
+    y = zeros(5)
+    @test quantile!(y, x, [0.00, 0.25, 0.50, 0.75, 1.00]) === y
+    @test y ≈ [1.0, 25.75, 50.5, 75.25, 100.0]
+
     #tests for quantile calculation with configurable alpha and beta parameters
     v = [2, 3, 4, 6, 9, 2, 6, 2, 21, 17]