Merge pull request #37 from brenhinkeller/check-empty

`@turbo check_empty=true` in most all cases

Project.toml

@@ -1,7 +1,7 @@
 name = "NaNStatistics"
 uuid = "b946abbf-3ea7-4610-9019-9858bfdeaf2d"
 authors = ["C. Brenhin Keller"]
-version = "0.6.27"
+version = "0.6.28"
 
 [deps]
 IfElse = "615f187c-cbe4-4ef1-ba3b-2fcf58d6d173"
@@ -11,7 +11,7 @@ Static = "aedffcd0-7271-4cad-89d0-dc628f76c6d3"
 
 [compat]
 IfElse = "0.1"
-LoopVectorization = "0.12.159"
+LoopVectorization = "0.12.113"
 PrecompileTools = "1"
 Static = "0.8"
 julia = "1.8"

src/ArrayStats/ArrayStats.jl

@@ -13,7 +13,7 @@
     """
     function countnans(A)
         n = 0
-        @turbo for i ∈ eachindex(A)
+        @turbo check_empty=true for i ∈ eachindex(A)
             n += A[i]!=A[i]
         end
         return n
@@ -28,7 +28,7 @@
     """
     function countnotnans(A)
         n = 0
-        @turbo for i ∈ eachindex(A)
+        @turbo check_empty=true for i ∈ eachindex(A)
             n += A[i]==A[i]
         end
         return n

src/ArrayStats/nancov.jl

@@ -2,7 +2,7 @@ function _nancov(x::AbstractVector, y::AbstractVector, corrected::Bool, μᵪ::N
     # Calculate covariance
     σᵪᵧ = ∅ = zero(promote_type(typeof(μᵪ), typeof(μᵧ), Int))
     n = 0
-    @turbo for i ∈ eachindex(x,y)
+    @turbo check_empty=true for i ∈ eachindex(x,y)
             δᵪ = x[i] - μᵪ
             δᵧ = y[i] - μᵧ
             δ² = δᵪ * δᵧ
@@ -19,7 +19,7 @@ function _nancov(x::AbstractVector, y::AbstractVector, corrected::Bool)
     n = 0
     Σᵪ = ∅ᵪ = zero(eltype(x))
     Σᵧ = ∅ᵧ = zero(eltype(y))
-    @turbo for i ∈ eachindex(x,y)
+    @turbo check_empty=true for i ∈ eachindex(x,y)
         xᵢ, yᵢ = x[i], y[i]
         notnan = (xᵢ==xᵢ) & (yᵢ==yᵢ)
         n += notnan
@@ -110,7 +110,7 @@ function _nancor(x::AbstractVector, y::AbstractVector, corrected::Bool)
     n = 0
     Σᵪ = ∅ᵪ = zero(eltype(x))
     Σᵧ = ∅ᵧ = zero(eltype(y))
-    @turbo for i ∈ eachindex(x,y)
+    @turbo check_empty=true for i ∈ eachindex(x,y)
         xᵢ, yᵢ = x[i], y[i]
         notnan = (xᵢ==xᵢ) & (yᵢ==yᵢ)
         n += notnan
@@ -124,7 +124,7 @@ function _nancor(x::AbstractVector, y::AbstractVector, corrected::Bool)
     # Pairwise nan-variances
     σ²ᵪ = ∅ᵪ = zero(typeof(μᵪ))
     σ²ᵧ = ∅ᵧ = zero(typeof(μᵧ))
-    @turbo for i ∈ eachindex(x,y)
+    @turbo check_empty=true for i ∈ eachindex(x,y)
         δᵪ = x[i] - μᵪ
         δᵧ = y[i] - μᵧ
         notnan = (δᵪ==δᵪ) & (δᵧ==δᵧ)

src/ArrayStats/nanmean.jl

@@ -54,7 +54,7 @@ function _nanmean(A::StridedArray, ::Colon)
     Tₒ = Base.promote_op(/, eltype(A), Int)
     n = 0
     Σ = ∅ = zero(Tₒ)
-    @turbo for i ∈ eachindex(A)
+    @turbo check_empty=true for i ∈ eachindex(A)
         Aᵢ = A[i]
         notnan = Aᵢ==Aᵢ
         n += notnan
@@ -65,7 +65,7 @@ end
 function _nanmean(A::StridedArray{<:Integer}, ::Colon)
     Tₒ = Base.promote_op(/, eltype(A), Int)
     Σ = zero(Tₒ)
-    @turbo for i ∈ eachindex(A)
+    @turbo check_empty=true for i ∈ eachindex(A)
         Σ += A[i]
     end
     return Σ / length(A)

src/ArrayStats/nanstd.jl

@@ -37,7 +37,7 @@ export nanstd
 
 sqrt!(x::Number) = sqrt(x)
 function sqrt!(A::StridedArray)
-    @turbo for i ∈ eachindex(A)
+    @turbo check_empty=true for i ∈ eachindex(A)
         A[i] = sqrt(A[i])
     end
     return A

src/ArrayStats/nansum.jl

@@ -53,7 +53,7 @@ end
 function _nansum(A::StridedArray, ::Colon)
     Tₒ = Base.promote_op(+, eltype(A), Int)
     Σ = ∅ = zero(Tₒ)
-    @turbo for i ∈ eachindex(A)
+    @turbo check_empty=true for i ∈ eachindex(A)
         Aᵢ = A[i]
         notnan = Aᵢ==Aᵢ
         Σ += ifelse(notnan, Aᵢ, ∅)
@@ -63,7 +63,7 @@ end
 function _nansum(A::StridedArray{<:Integer}, ::Colon)
     Tₒ = Base.promote_op(+, eltype(A), Int)
     Σ = zero(Tₒ)
-    @turbo for i ∈ eachindex(A)
+    @turbo check_empty=true for i ∈ eachindex(A)
         Σ += A[i]
     end
     return Σ

src/ArrayStats/nanvar.jl

@@ -49,15 +49,15 @@ function _nanvar(::Nothing, corrected::Bool, A::StridedArray, ::Colon)
     Tₒ = Base.promote_op(/, eltype(A), Int)
     n = 0
     Σ = ∅ = zero(Tₒ)
-    @turbo for i ∈ eachindex(A)
+    @turbo check_empty=true for i ∈ eachindex(A)
         Aᵢ = A[i]
         notnan = Aᵢ==Aᵢ
         n += notnan
         Σ += ifelse(notnan, Aᵢ, ∅)
     end
     μ = Σ / n
     σ² = ∅ = zero(typeof(μ))
-    @turbo for i ∈ eachindex(A)
+    @turbo check_empty=true for i ∈ eachindex(A)
         δ = A[i] - μ
         notnan = δ==δ
         σ² += ifelse(notnan, δ * δ, ∅)
@@ -68,12 +68,12 @@ function _nanvar(::Nothing, corrected::Bool, A::StridedArray{<:Integer}, ::Colon
     Tₒ = Base.promote_op(/, eltype(A), Int)
     n = length(A)
     Σ = zero(Tₒ)
-    @turbo for i ∈ eachindex(A)
+    @turbo check_empty=true for i ∈ eachindex(A)
         Σ += A[i]
     end
     μ = Σ / n
     σ² = zero(typeof(μ))
-    @turbo for i ∈ eachindex(A)
+    @turbo check_empty=true for i ∈ eachindex(A)
         δ = A[i] - μ
         σ² += δ * δ
     end
@@ -109,7 +109,7 @@ _nanvar(μ::Number, corrected::Bool, A, dims::Tuple) = _nanvar!([μ], corrected,
 function _nanvar(μ::Number, corrected::Bool, A::AbstractArray, ::Colon)
     n = 0
     σ² = ∅ = zero(typeof(μ))
-    @turbo for i ∈ eachindex(A)
+    @turbo check_empty=true for i ∈ eachindex(A)
         δ = A[i] - μ
         notnan = δ==δ
         n += notnan
@@ -120,7 +120,7 @@ end
 function _nanvar(μ::Number, corrected::Bool, A::AbstractArray{<:Integer}, ::Colon)
     σ² = zero(typeof(μ))
     if μ==μ
-        @turbo for i ∈ eachindex(A)
+        @turbo check_empty=true for i ∈ eachindex(A)
             δ = A[i] - μ
             σ² += δ * δ
         end
@@ -149,12 +149,12 @@ end
 #     N = sum(mask, dims=region)
 #     Σ = sum(A.*mask, dims=region)./N
 #     δ = A .- Σ # Subtract mean, using broadcasting
-#     @turbo for i ∈ eachindex(δ)
+#     @turbo check_empty=true for i ∈ eachindex(δ)
 #         δᵢ = δ[i]
 #         δ[i] = ifelse(mask[i], δᵢ * δᵢ, 0)
 #     end
 #     B .= sum(δ, dims=region)
-#     @turbo for i ∈ eachindex(B)
+#     @turbo check_empty=true for i ∈ eachindex(B)
 #         B[i] = B[i] / max(N[i] - corrected, 0)
 #     end
 #     return B

src/Sorting/quicksort.jl

@@ -82,12 +82,8 @@ function quickselect!(A::AbstractArray, iₗ=firstindex(A), iᵤ=lastindex(A), k
 
     # Count up elements that must be moved to upper partition
     Nᵤ = 0
-    # @turbo 
-    @inbounds for i = (iₗ+1):iᵤ
-        if A[i] >= pivot
-            Nᵤ += 1  
-        end
-        # Nᵤ += Int(A[i] >= pivot)
+    @turbo check_empty=true for i = (iₗ+1):iᵤ
+        Nᵤ += Int(A[i] >= pivot)
     end
     Nₗ = N - Nᵤ
 
@@ -109,9 +105,15 @@ function quickselect!(A::AbstractArray, iₗ=firstindex(A), iᵤ=lastindex(A), k
     iₚ = iₗ + Nₗ - 1
     A[iₗ], A[iₚ] = A[iₚ], A[iₗ]
     # Recurse: select from partition containing k
-    (iₗ <= k < iₚ) && quickselect!(A, iₗ, iₚ, k)
-    (iₚ < k <= iᵤ) && quickselect!(A, iₚ+1, iᵤ, k)
-    return A[k]
+    if iₚ==k
+        return A[k]
+    elseif k < iₚ
+        Nₗ == 2 && return A[iₗ]
+        quickselect!(A, iₗ, iₚ, k)
+    else
+        Nᵤ == 2 && return A[iᵤ]
+        quickselect!(A, iₚ+1, iᵤ, k)
+    end
 end