Add median function implementation (#41)

* add tests for median function

* add median implementation

* add documentation for median

* version bump

* change readme to include median function

* do not change the inputs in median

* use multiple dispatch rather than dims to flatten multidimensional array

* Ensure type stability for median

Co-authored-by: Nick Robinson <[email protected]>

* add Float32 test

* format comment according to REPL convention

Co-authored-by: Miha Zgubic <[email protected]>
Co-authored-by: Nick Robinson <[email protected]>

Author: 3 people

Project.toml

@@ -2,7 +2,7 @@ name = "NaNMath"
 uuid = "77ba4419-2d1f-58cd-9bb1-8ffee604a2e3"
 repo = "https://github.com/mlubin/NaNMath.jl.git"
 authors = ["Miles Lubin"]
-version = "0.3.3"
+version = "0.3.4"
 
 [deps]
 

README.md

@@ -21,6 +21,7 @@ maximum
 minimum
 extrema
 mean
+median
 var
 std
 min

src/NaNMath.jl

@@ -61,6 +61,51 @@ function sum(x::AbstractArray{T}) where T<:AbstractFloat
     return result
 end
 
+"""
+NaNMath.median(A)
+
+##### Args:
+* `A`: An array of floating point numbers
+
+##### Returns:
+*   Returns the median of all elements in the array, ignoring NaN's.
+    Returns NaN for an empty array or array containing NaNs only.
+
+##### Examples:
+```jldoctest
+julia> using NaNMath
+
+julia> NaNMath.median([1., 2., 3., NaN])
+2.
+
+julia> NaNMath.median([1., 2., NaN])
+1.5
+
+julia> NaNMath.median([NaN])
+NaN
+```
+"""
+median(x::AbstractArray{<:AbstractFloat}) = median(collect(Iterators.flatten(x)))
+
+function median(x::AbstractVector{<:AbstractFloat})
+
+    x = sort(filter(!isnan, x))
+
+    n = length(x)
+    if n == 0
+        return convert(eltype(x), NaN)
+    elseif isodd(n)
+        ind = ceil(Int, n/2)
+        return x[ind]
+    else
+        ind = Int(n/2)
+        lower = x[ind]
+        upper = x[ind+1]
+        return (lower + upper) / 2
+    end
+
+end
+
 """
 NaNMath.maximum(A)
 
@@ -313,4 +358,3 @@ for f in (:min, :max)
 end
 
 end
-

test/runtests.jl

@@ -25,6 +25,18 @@ using Test
 @test NaNMath.var([1., 2., NaN]) == 0.5
 @test NaNMath.std([1., 2., NaN]) == 0.7071067811865476
 
+@test NaNMath.median([1.]) == 1.
+@test NaNMath.median([1., NaN]) == 1.
+@test NaNMath.median([NaN, 1., 3.]) == 2.
+@test NaNMath.median([1., 3., 2., NaN]) == 2.
+@test NaNMath.median([NaN, 1, 3]) == 2.
+@test NaNMath.median([1, 2, NaN]) == 1.5
+@test NaNMath.median([1 2; NaN NaN]) == 1.5
+@test NaNMath.median([NaN 2; 1 NaN]) == 1.5
+@test isnan(NaNMath.median(Float64[]))
+@test isnan(NaNMath.median(Float32[]))
+@test isnan(NaNMath.median([NaN]))
+
 @test NaNMath.min(1, 2) == 1
 @test NaNMath.min(1.0, 2.0) == 1.0
 @test NaNMath.min(1, 2.0) == 1.0