🟠 Periodic predator-prey model

• 🟠 Periodic predator-prey model
• • Simulation of the model
  • Utility functions
  • Periodic orbits with trapezoid method
  • Periodic orbits with parallel standard shooting
  • Periodic orbits with orthogonal collocation
  • Continuation of Fold / PD of periodic orbits with Collocation
  • References

This example is found in the MatCont ecosystem.

The following is a periodically forced predator-prey model studied in ^[Kuznetsov] using shooting techniques.

\[\tag{E}\left\{\begin{aligned} \dot{x} & =r\left(1-\frac{x}{K}\right) x-\frac{a x y}{b_0(1+\varepsilon u)+x} \\ \dot{y} & =e \frac{a x y}{b_0(1+\varepsilon u)+x}-d y \\ \dot{u} & =u-2 \pi v-\left(u^2+v^2\right) u \\ \dot{v} & =2 \pi u+v-\left(u^2+v^2\right) v \end{aligned}\right.\]

This tutorial is useful in that we show how to start periodic orbits continuation from solutions obtained from solving ODEs. We are interested in cases where $(u,v)\neq (0,0)$ for which we have only periodic solutions. Thus, we cannot rely on branching from equilibria to find these periodic orbits.

using Revise, Plots
using BifurcationKit
const BK = BifurcationKit

function Pop!(du, X, p, t = 0)
	(;r,K,a,ϵ,b0,e,d) = p
	x, y, u, v = X
	p = a * x / (b0 * (1 + ϵ * u) + x)
	du[1] = r * (1 - x/K) * x - p * y
	du[2] = e * p * y - d * y
	s = u^2 + v^2
	du[3] = u-2pi * v - s * u
	du[4] = 2pi * u + v - s * v
	du
end

par_pop = ( K = 1., r = 6.28, a = 12.56, b0 = 0.25, e = 1., d = 6.28, ϵ = 0.2, )

z0 = [0.1,0.1,1,0]

prob = BifurcationProblem(Pop!, z0, par_pop, (@optic _.b0);
	record_from_solution = (x, p; k...) -> (x = x[1], y = x[2], u = x[3]))

opts_br = ContinuationPar(p_min = 0., p_max = 20.0, ds = 0.002, dsmax = 0.01, n_inversion = 6, nev = 4)

Simulation of the model

This is very straightforward thanks to SciML.

using DifferentialEquations
prob_de = ODEProblem(Pop!, z0, (0,200.), par_pop)
sol = DifferentialEquations.solve(prob_de, Rodas5())
prob_de = ODEProblem(Pop!, sol.u[end], (0,3.), par_pop, reltol = 1e-8, abstol = 1e-10)
sol = DifferentialEquations.solve(prob_de, Rodas5())
plot(sol)

Utility functions

We start with two helper functions that record and plot the periodic orbits. The following works for shooting, collocation and trapezoid methods for computing periodic orbits.

argspo = (record_from_solution = (x, p; k...) -> begin
		xtt = get_periodic_orbit(p.prob, x, p.p)
		return (max = maximum(xtt[1,:]),
				min = minimum(xtt[1,:]),
				period = getperiod(p.prob, x, p.p))
	end,
	plot_solution = (x, p; k...) -> begin
		xtt = get_periodic_orbit(p.prob, x, p.p)
		plot!(xtt.t, xtt[1,:]; label = "x", k...)
		plot!(xtt.t, xtt[2,:]; label = "y", k...)
		# plot!(br; subplot = 1, putspecialptlegend = false)
	end)

(record_from_solution = Main.var"#4#8"(), plot_solution = Main.var"#6#9"())

Periodic orbits with trapezoid method

We compute periodic orbits of (E) using the Trapezoid method. We are now equipped to build a periodic orbit problem from a solution sol::ODEProblem.

# function to build probtrap from sol
probtrap, ci = BK.generate_ci_problem(PeriodicOrbitTrapProblem(M = 150),
	prob, sol, 2.)

opts_po_cont = ContinuationPar(opts_br, max_steps = 50, tol_stability = 1e-8)
brpo_fold = continuation(probtrap, ci, PALC(), opts_po_cont;
	verbosity = 3, plot = true,
	argspo...
	)

scene = plot(brpo_fold)

We continue w.r.t. to $\epsilon$ and find a period-doubling bifurcation.

prob2 = @set probtrap.prob_vf.lens = @optic _.ϵ
brpo_pd = continuation(prob2, ci, PALC(), opts_po_cont;
	argspo...
	)
scene = plot(brpo_pd)

Periodic orbits with parallel standard shooting

We are now ready to build a periodic orbit problem from a solution sol::ODEProblem.

probsh, cish = generate_ci_problem( ShootingProblem(M=3),
	prob, prob_de, sol, 2.; alg = Rodas5(), abstol = 1e-12, reltol = 1e-10)

opts_po_cont = ContinuationPar(opts_br, max_steps = 50, tol_stability = 1e-3)
br_fold_sh = continuation(probsh, cish, PALC(tangent = Bordered()), opts_po_cont;
	argspo...
)

scene = plot(br_fold_sh)

We continue w.r.t. to $\epsilon$ and find a period-doubling bifurcation.

probsh2 = @set probsh.lens = @optic _.ϵ
brpo_pd_sh = continuation(probsh2, cish, PALC(), opts_po_cont;
	argspo...
	)
scene = plot(brpo_pd_sh)

Periodic orbits with orthogonal collocation

We do the same as in the previous section but using orthogonal collocation. This is the most reliable and precise method for ODE. When the dimension of the ODE is large, it becomes prohibitive.

# this is the function which builds probcoll from sol
probcoll, ci = generate_ci_problem(PeriodicOrbitOCollProblem(30, 4),
	prob, sol, 2.)

opts_po_cont = ContinuationPar(opts_br, max_steps = 50, tol_stability = 1e-8)
brpo_fold = continuation(probcoll, ci, PALC(), opts_po_cont;
	argspo...
	)
scene = plot(brpo_fold)

We continue w.r.t. to $\epsilon$ and find a period-doubling bifurcation.

prob2 = @set probcoll.prob_vf.lens = @optic _.ϵ
brpo_pd = continuation(prob2, ci, PALC(), ContinuationPar(opts_po_cont, dsmax = 5e-3);
	argspo...
	)

scene = plot(brpo_pd)

Continuation of Fold / PD of periodic orbits with Collocation

We continue the previously detected fold/period-doubling bifurcations as function of two parameters and detect codim 2 bifurcations. We first start with the computation of the curve of Folds.

opts_pocoll_fold = ContinuationPar(brpo_fold.contparams, detect_bifurcation = 3, max_steps = 100, p_min = 0.01, p_max = 1.2)
@reset opts_pocoll_fold.newton_options.tol = 1e-12

fold_po_coll2 = continuation(brpo_fold, 1, (@optic _.ϵ), opts_pocoll_fold;
		verbosity = 2, plot = true,
		detect_codim2_bifurcation = 2,
		jacobian_ma = :minaug,
		start_with_eigen = false,
		bothside = true,
		)

fold_po_coll1 = continuation(brpo_fold, 2, (@optic _.ϵ), opts_pocoll_fold;
		# verbosity = 2, plot = true,
		detect_codim2_bifurcation = 2,
		jacobian_ma = :minaug,
		start_with_eigen = false,
		bothside = true,
		)

 ┌─ Curve type: FoldPeriodicOrbitCont
 ├─ Number of points: 120
 ├─ Type of vectors: BorderedArray{Vector{Float64}, Float64}
 ├─ Parameters (:b0, :ϵ)
 ├─ Parameter ϵ starts at 0.01, ends at 0.7601674490980987
 ├─ Algo: PALC
 └─ Special points:

- #  1, endpoint at ϵ ≈ +0.01000000,                                                                     step =   0
- #  2,       R1 at ϵ ≈ +0.56581407 ∈ (+0.56580720, +0.56581407), |δp|=7e-06, [converged], δ = ( 0,  0), step =  49
- #  3,     cusp at ϵ ≈ +1.09294332 ∈ (+1.09285462, +1.09294332), |δp|=9e-05, [    guess], δ = ( 0,  0), step =  92
- #  4, endpoint at ϵ ≈ +0.74616031,                                                                     step = 120

We turn to the computation of the curve of PD points.

par_pop2 = @set par_pop.b0 = 0.45
sol2 = DifferentialEquations.solve(remake(prob_de, p = par_pop2, u0 = [0.1,0.1,1,0], tspan=(0,1000)), Rodas5())
sol2 = DifferentialEquations.solve(remake(sol2.prob, tspan = (0,10), u0 = sol2[end]), Rodas5())
plot(sol2, xlims= (8,10))

probcoll, ci = generate_ci_problem(PeriodicOrbitOCollProblem(30, 3), re_make(prob, params = sol2.prob.p), sol2, 1.)

prob2 = @set probcoll.prob_vf.lens = @optic _.ϵ
brpo_pd = continuation(prob2, ci, PALC(), ContinuationPar(opts_po_cont, dsmax = 5e-3);
	argspo...,
	bothside = true,
	)

opts_pocoll_pd = ContinuationPar(brpo_pd.contparams, max_steps = 40, p_min = 1.e-2, dsmax = 1e-2, ds = -1e-3)
@reset opts_pocoll_pd.newton_options.tol = 1e-12
pd_po_coll2 = continuation(brpo_pd, 2, (@optic _.b0), opts_pocoll_pd;
		detect_codim2_bifurcation = 1,
		start_with_eigen = false,
		jacobian_ma = :minaug,
		normC = norminf,
		bothside = true,
		)

plot(pd_po_coll2, vars = (:ϵ, :b0), branchlabel = "PD")
plot!(fold_po_coll1, fold_po_coll2, branchlabel = ["FOLD", "FOLD"])

References