wip: drop staticArrays as a hard requirement

Author: sjkelly

Project.toml

@@ -2,18 +2,15 @@ name = "Contour"
 uuid = "d38c429a-6771-53c6-b99e-75d170b6e991"
 version = "0.5.7"
 
-[deps]
-StaticArrays = "90137ffa-7385-5640-81b9-e52037218182"
-
 [compat]
-StaticArrays = "0.10,0.11,0.12, 1.0"
 julia = "0.7, 1"
 
 [extras]
 LinearAlgebra = "37e2e46d-f89d-539d-b4ee-838fcccc9c8e"
 OffsetArrays = "6fe1bfb0-de20-5000-8ca7-80f57d26f881"
+StaticArrays = "90137ffa-7385-5640-81b9-e52037218182"
 StatsBase = "2913bbd2-ae8a-5f71-8c99-4fb6c76f3a91"
 Test = "8dfed614-e22c-5e08-85e1-65c5234f0b40"
 
 [targets]
-test = ["LinearAlgebra", "StatsBase", "Test", "OffsetArrays"]
+test = ["LinearAlgebra", "StatsBase", "Test", "OffsetArrays", "StaticArrays"]

src/Contour.jl

@@ -17,7 +17,7 @@ export
 import Base: push!, length, eltype, show
 
 struct Curve2{T}
-    vertices::Vector{SVector{2,T}}
+    vertices::Vector{NTuple{2,T}}
 end
 Curve2(::Type{T}) where {T} = Curve2(SVector{2,T}[])
 show(io::IO, ::MIME"text/plain", c2::Curve2) = write(io, "$(typeof(c2))\n  with $(length(c2.vertices)-1) vertices")
@@ -273,7 +273,7 @@ function trace_contour(x, y, z, h::Number, cells::Dict)
     yi_range = first(y_ax):last(y_ax)-1
 
 
-    VT = SVector{2,promote_type(map(eltype, (x, y, z))...)}
+    VT = NTuple{2,promote_type(map(eltype, (x, y, z))...)}
 
     # When tracing out contours, this algorithm picks an arbitrary
     # starting cell, then first follows the contour in one direction

src/interpolate.jl

@@ -17,7 +17,7 @@ function interpolate(x, y, z::AbstractMatrix, h::Number, ind, edge::UInt8, ::Typ
         x_interp = x[xi] + (x[xi + 1] - x[xi]) * (h - z[xi, yi]) / (z[xi + 1, yi] - z[xi, yi])
     end
 
-    return VT(x_interp, y_interp)
+    return VT <: Tuple ? (x_interp, y_interp) : VT(x_interp, y_interp)
 end
 
 function interpolate(x::AbstractRange, y::AbstractRange, z::AbstractMatrix, h::Number, ind, edge::UInt8, ::Type{VT}) where {VT}
@@ -36,7 +36,7 @@ function interpolate(x::AbstractRange, y::AbstractRange, z::AbstractMatrix, h::N
         x_interp = x[xi] + step(x) * (h - z[xi, yi]) / (z[xi + 1, yi] - z[xi, yi])
     end
 
-    return VT(x_interp, y_interp)
+    return VT <: Tuple ? (x_interp, y_interp) : VT(x_interp, y_interp)
 end
 
 function interpolate(x::AbstractMatrix, y::AbstractMatrix, z::AbstractMatrix, h::Number, ind, edge::UInt8, ::Type{VT}) where {VT}
@@ -59,5 +59,5 @@ function interpolate(x::AbstractMatrix, y::AbstractMatrix, z::AbstractMatrix, h:
         x_interp = x[xi,yi] + Δ[2]
     end
 
-    return VT(x_interp, y_interp)
+    return VT <: Tuple ? (x_interp, y_interp) : VT(x_interp, y_interp)
 end

test/verify_vertices.jl

@@ -65,7 +65,7 @@ lines = Contour.contour(X, Y, Z, h).lines
 
 for line in lines
     @test length(line.vertices) == 2
-    d = line.vertices[2] - line.vertices[1]
+    d = line.vertices[2] .- line.vertices[1]
     @test d[2] / d[1] ≈ -1.0
 end
 
@@ -80,7 +80,7 @@ lines = Contour.contour(X, Y, Z, h).lines
 
 for line in lines
     @test length(line.vertices) == 2
-    d = line.vertices[2] - line.vertices[1]
+    d = line.vertices[2] .- line.vertices[1]
     @test d[2] / d[1] ≈ 1.0
 end
 
@@ -94,7 +94,7 @@ lines = Contour.contour(X, Y, Z, h).lines
 
 for line in lines
     @test length(line.vertices) == 2
-    d = line.vertices[2] - line.vertices[1]
+    d = line.vertices[2] .- line.vertices[1]
     @test d[2] / d[1] ≈ 1.0
 end
 
@@ -109,7 +109,7 @@ lines = Contour.contour(X, Y, Z, h).lines
 
 for line in lines
     @test length(line.vertices) == 2
-    d = line.vertices[2] - line.vertices[1]
+    d = line.vertices[2] .- line.vertices[1]
     @test d[2] / d[1] ≈ -1.0
 end