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Julia

# External dependencies
using TypedPolynomials
using LinearAlgebra
# Local dependencies
include("random_poly.jl")
include("start-system.jl")
include("homotopy.jl")
include("euler-newton.jl")
include("adapt-step.jl")
include("plot.jl")
using .RandomPoly
using .StartSystem
using .Homotopy
using .EulerNewton
using .AdaptStep
using .Plot
# Main homotopy continuation loop
function solve(F, (G, roots) = start_system(F), maxsteps = 1000)
H=homotopy(F,G)
solutions = []
step_array = []
Threads.@threads for r in roots
# for r in roots
println("New root")
t = 1.0
step_size = 0.01
x0 = r
m = 0
steps = 0
while t > 0 && steps < maxsteps
x0 = en_step(H, x0, t, step_size)
(m, step_size) = adapt_step(H, x0, t, step_size, m)
t -= step_size
steps += 1
end
push!(solutions, x0)
push!(step_array, steps)
end
return (solutions, step_array)
end
# Input polynomial systems
# @polyvar x y
# C = [x^3 - y + 5x^2 - 10, 2x^2 - y - 10]
# Q = [x^2 + 2y, y - 3x^3]
# F = [x*y - 1, x^2 + y^2 - 4]
# T = [x*y - 1, x^2 + y^2 - 2]
dimension = 2
R = random_system(2, 2)
println(R)
# (sC, stepsC) = solve(C)
# (sQ, stepsQ) = solve(Q)
# (sF, stepsF) = solve(F)
# (sT, stepsT) = solve(T)
(sR, stepsR) = solve(R)
# println("C: ", stepsC)
# println("Q: ", stepsQ)
# println("F: ", stepsF)
# println("T: ", stepsT)
println("R: ", stepsR)
# sC = filter(u -> imag(u[1]) < 0.1 && imag(u[2]) < 0.1, sC)
# sQ = filter(u -> imag(u[1]) < 0.1 && imag(u[2]) < 0.1, sQ)
# sF = filter(u -> imag(u[1]) < 0.1 && imag(u[2]) < 0.1, sF)
# sT = filter(u -> imag(u[1]) < 0.1 && imag(u[2]) < 0.1, sT)
sR = filter(u -> imag(u[1]) < 0.1 && imag(u[2]) < 0.1, sR)
vars = variables(R)
println("solutions: ", sR)
println([LinearAlgebra.norm([f(vars=>s) for f in R]) for s in sR])
# Plotting the system and the real solutions
ENV["GKSwstype"]="nul"
# plot_real(sC, C, 6, 12, "1")
# plot_real(sQ, Q, 2, 2, "2")
# plot_real(sF, F, 4, 4, "3")
# plot_real(sT, T, 4, 4, "4")
plot_real(sR, R, 5, 5, "random")