Test gradient descent for sphere in tetrahedron

This commit is contained in:
Aaron Fenyes 2024-07-07 17:58:55 -07:00
parent ea354b6c2b
commit 736ac50b07

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include("Engine.jl")
using SparseArrays
using AbstractAlgebra
using PolynomialRoots
# initialize the partial gram matrix for a sphere inscribed in a regular
# tetrahedron
J = Int64[]
K = Int64[]
values = BigFloat[]
for j in 1:5
for k in 1:5
push!(J, j)
push!(K, k)
if j == k
push!(values, 1)
elseif (j <= 4 && k <= 4)
push!(values, -1/BigFloat(3))
else
push!(values, -1)
end
end
end
gram = sparse(J, K, values)
# set initial guess
Random.seed!(99230)
guess = sqrt(1/BigFloat(3)) * BigFloat[
1 1 -1 -1 0
1 -1 1 -1 0
1 -1 -1 1 0
1 1 1 1 -2
1 1 1 1 1
] + 0.2*Engine.rand_on_shell(fill(BigFloat(-1), 5))
# complete the gram matrix using gradient descent
L, history = Engine.realize_gram(gram, guess)
completed_gram = L'*Engine.Q*L
println("Completed Gram matrix:\n")
display(completed_gram)
println("\nSteps: ", size(history.stepsize, 1))
println("Loss: ", history.scaled_loss[end], "\n")