Added a PDMat option

Author: theogf

Project.toml

@@ -6,6 +6,7 @@ version = "0.2.0"
 Distances = "b4f34e82-e78d-54a5-968a-f98e89d6e8f7"
 IRTools = "7869d1d1-7146-5819-86e3-90919afe41df"
 LinearAlgebra = "37e2e46d-f89d-539d-b4ee-838fcccc9c8e"
+PDMats = "90014a1f-27ba-587c-ab20-58faa44d9150"
 SpecialFunctions = "276daf66-3868-5448-9aa4-cd146d93841b"
 StatsFuns = "4c63d2b9-4356-54db-8cca-17b64c39e42c"
 Zygote = "e88e6eb3-aa80-5325-afca-941959d7151f"

src/KernelFunctions.jl

@@ -16,6 +16,7 @@ using Distances, LinearAlgebra
 using Zygote: @adjoint
 using SpecialFunctions: lgamma, besselk
 using StatsFuns: logtwo
+using PDMats
 
 const defaultobs = 2
 
@@ -32,7 +33,7 @@ kernels = ["exponential","matern","polynomial","constant","rationalquad","expone
 for k in kernels
     include(joinpath("kernels",k*".jl"))
 end
-include("kernelmatrix.jl")
+include("matrix/kernelmatrix.jl")
 include("kernels/kernelsum.jl")
 include("kernels/kernelproduct.jl")
 

src/kernelmatrix.jl renamed to src/matrix/kernelmatrix.jl

@@ -0,0 +1,18 @@
+"""
+    Guarantees to return a positive-definite matrix in the form of a `PDMat` matrix with the cholesky decomposition precomputed
+"""
+function kernelpdmat(
+        κ::Kernel,
+        X::AbstractMatrix;
+        obsdim::Int = defaultobs
+        )
+    K = kernelmatrix(κ,X,obsdim=obsdim)
+    α = eps(eltype(K))
+    while !isposdef(K+αI) && α < 0.01*maximum(K)
+        α *= 2.0
+    end
+    if α >= 0.01*maximum(K)
+        @error "Adding noise on the diagonal was not sufficient to build a positive-definite matrix:\n - Check that your kernel parameters are not extreme\n - Check that your data is sufficiently sparse\n - Maybe use a different kernel"
+    end
+    return PDMat(K+αI)
+end