Added setindex! for ColVecs and RowVecs with tests (#196)

Author: theogf

Project.toml

@@ -1,6 +1,6 @@
 name = "KernelFunctions"
 uuid = "ec8451be-7e33-11e9-00cf-bbf324bd1392"
-version = "0.8.7"
+version = "0.8.8"
 
 [deps]
 Compat = "34da2185-b29b-5c13-b0c7-acf172513d20"

src/utils.jl

@@ -38,6 +38,7 @@ Base.size(D::ColVecs) = (size(D.X, 2),)
 Base.getindex(D::ColVecs, i::Int) = view(D.X, :, i)
 Base.getindex(D::ColVecs, i::CartesianIndex{1}) = view(D.X, :, i)
 Base.getindex(D::ColVecs, i) = ColVecs(view(D.X, :, i))
+Base.setindex!(D::ColVecs, v::AbstractVector, i) = setindex!(D.X, v, :, i)
 
 dim(x::ColVecs) = size(x.X, 1)
 
@@ -76,6 +77,7 @@ Base.size(D::RowVecs) = (size(D.X, 1),)
 Base.getindex(D::RowVecs, i::Int) = view(D.X, i, :)
 Base.getindex(D::RowVecs, i::CartesianIndex{1}) = view(D.X, i, :)
 Base.getindex(D::RowVecs, i) = RowVecs(view(D.X, i, :))
+Base.setindex!(D::RowVecs, v::AbstractVector, i) = setindex!(D.X, v, i, :)
 
 dim(x::RowVecs) = size(x.X, 2)
 
@@ -94,17 +96,6 @@ function pairwise!(out::AbstractMatrix, d::PreMetric, x::RowVecs, y::RowVecs)
     return Distances.pairwise!(out, d, x.X, y.X; dims=1)
 end
 
-"""
-Will be implemented at some point
-```julia
-    params(k::Kernel)
-    params(t::Transform)
-```
-For a kernel return a tuple with parameters of the transform followed by the specific parameters of the kernel
-For a transform return its parameters, for a `ChainTransform` return a vector of `params(t)`.
-"""
-#params
-
 dim(x) = 0 # This is the passes-by-default choice. For a proper check, implement `KernelFunctions.dim` for your datatype.
 dim(x::AbstractVector) = dim(first(x))
 dim(x::AbstractVector{<:AbstractVector{<:Real}}) = length(first(x))

test/utils.jl

@@ -1,7 +1,11 @@
 @testset "utils" begin
     using KernelFunctions: vec_of_vecs, ColVecs, RowVecs
     rng, N, D = MersenneTwister(123456), 10, 4
-    x, X = randn(rng, N), randn(rng, D, N)
+    x = randn(rng, N)
+    X = randn(rng, D, N)
+    v = randn(rng, D)
+    w = randn(rng, N)
+
     @testset "VecOfVecs" begin
         @test vec_of_vecs(X, obsdim = 2) == ColVecs(X)
         @test vec_of_vecs(X, obsdim = 1) == RowVecs(X)
@@ -19,6 +23,9 @@
         @test getindex(DX, :) == ColVecs(X)
         @test eachindex(DX) == 1:N
         @test first(DX) == X[:, 1]
+        DX[2] = v
+        @test DX[2] == v
+        @test X[:, 2] == v
 
         Y = randn(rng, D, N + 1)
         DY = ColVecs(Y)
@@ -53,6 +60,9 @@
         @test getindex(DX, :) == RowVecs(X)
         @test eachindex(DX) == 1:D
         @test first(DX) == X[1, :]
+        DX[2] = w
+        @test DX[2] == w
+        @test X[2, :] == w
 
         Y = randn(rng, D + 1, N)
         DY = RowVecs(Y)