From 0f93c1c69ddfb916b58f819db3493ff041b3e7b0 Mon Sep 17 00:00:00 2001
From: Felix Benning <felix.benning@gmail.com>
Date: Wed, 17 May 2023 16:09:22 +0200
Subject: [PATCH] attempt a fix

---
 src/diffKernel.jl | 30 ++++++++++++++----------------
 1 file changed, 14 insertions(+), 16 deletions(-)

diff --git a/src/diffKernel.jl b/src/diffKernel.jl
index fc8ff197c..425d33e14 100644
--- a/src/diffKernel.jl
+++ b/src/diffKernel.jl
@@ -18,12 +18,12 @@ for higher order derivatives partial can be any iterable, i.e.
 	k(DiffPt(x, partial=(1,2)), y) # = Cov(∂₁∂₂Z(x), Z(y))
 ```
 """
-struct DiffPt{Dim}
+struct DiffPt
     pos # the actual position
     partial
 end
 
-DiffPt(x; partial=()) = DiffPt{length(x)}(x, partial) # convenience constructor
+DiffPt(x; partial=()) = DiffPt(x, partial) # convenience constructor
 
 """ 
 	partial(fun, idx)
@@ -34,10 +34,8 @@ Return ∂ᵢf where
 """
 function partial(fun, idx)
 	return x -> FD.derivative(0) do dx
-		y = similar(x)
-		y = copyto!(y, x)
-		y[idx] += dx
-		fun(y)
+		dim = length(x)
+		fun(x .+ dx * OneHotVector(idx, dim))
 	end
 end
 
@@ -58,23 +56,23 @@ end
 Take the partial derivative of a function with two dim-dimensional inputs,
 i.e. 2*dim dimensional input
 """
-function partial(k, dim; partials_x=(), partials_y=())
-    local f(x, y) = partial(t -> k(t, y), dim, partials_x)(x)
-    return (x, y) -> partial(t -> f(x, t), dim, partials_y)(y)
+function partial(k; partials_x=(), partials_y=())
+    local f(x, y) = partial(t -> k(t, y), partials_x...)(x)
+    return (x, y) -> partial(t -> f(x, t), partials_y...)(y)
 end
 
 """
-	_evaluate(k::T, x::DiffPt{Dim}, y::DiffPt{Dim}) where {Dim, T<:Kernel}
+	_evaluate(k::T, x::DiffPt, y::DiffPt) where {T<:Kernel}
 
-implements `(k::T)(x::DiffPt{Dim}, y::DiffPt{Dim})` for all kernel types. But since
+implements `(k::T)(x::DiffPt, y::DiffPt)` for all kernel types. But since
 generics are not allowed in the syntax above by the dispatch system, this
 redirection over `_evaluate` is necessary
 
 unboxes the partial instructions from DiffPt and applies them to k,
 evaluates them at the positions of DiffPt
 """
-function _evaluate(k::T, x::DiffPt{Dim}, y::DiffPt{Dim}) where {Dim,T<:Kernel}
-    return partial(k, Dim; partials_x=x.partial, partials_y=y.partial)(x.pos, y.pos)
+function _evaluate(k::T, x::DiffPt, y::DiffPt) where {T<:Kernel}
+    return partial(k, partials_x=x.partial, partials_y=y.partial)(x.pos, y.pos)
 end
 
 #=
@@ -101,7 +99,7 @@ for T in [
 		NormalizedKernel,
 		KernelTensorProduct
 	] #subtypes(Kernel)
-    (k::T)(x::DiffPt{Dim}, y::DiffPt{Dim}) where {Dim} = _evaluate(k, x, y)
-    (k::T)(x::DiffPt{Dim}, y) where {Dim} = _evaluate(k, x, DiffPt(y))
-    (k::T)(x, y::DiffPt{Dim}) where {Dim} = _evaluate(k, DiffPt(x), y)
+    (k::T)(x::DiffPt, y::DiffPt)= _evaluate(k, x, y)
+    (k::T)(x::DiffPt, y) = _evaluate(k, x, DiffPt(y))
+    (k::T)(x, y::DiffPt) = _evaluate(k, DiffPt(x), y)
 end