corrections docs

docs/src/periodicOrbitCollocation.md

@@ -91,7 +91,7 @@ H_{0,0}^1 & H_{0,1}^1 & H_{1,0}^1 & & & & & * \\
 & & & & H_{2,0}^0 & H_{2,1}^0 & H_{3,0}^0 & * \\
 & & & & H_{2,0}^1 & H_{2,1}^1 & H_{3,0}^1 & * \\
 & & & & & & & * \\
-I & & & & & & -I & * \\
+-I & & & & & & I & * \\
 * & * & * & * & * & * & * & *
 \end{array}\right)$$
 

docs/src/tutorials/mittelmannGridap.md

@@ -16,10 +16,11 @@ with Neumann boundary condition on $\Omega = (0,1)^2$ and where $NL(\lambda,u)\e
 We start by installing the package [GridapBifurcationKit.jl](https://github.com/rveltz/GridapBifurcationKit). Then, we can import the different packages:
 
 ```julia
-using Revise
-using Plots, Gridap
+using Revise, Plots
+using Gridap
 using Gridap.FESpaces
-using GridapBifurcationKit, BifurcationKit
+using GridapBifurcationKit
+using BifurcationKit
 
 # custom plot function to deal with Gridap
 plotgridap!(x; k...) = (n=isqrt(length(x));heatmap!(reshape(x,n,n); color=:viridis, k...))
@@ -64,7 +65,11 @@ uh = zero(U)
 par_bratu = (λ = 0.01,)
 
 # problem definition
-prob = GridapBifProblem(res, uh, par_bratu, V, U, (@lens _.λ); jac = jac, d2res = d2res, d3res = d3res, plot_solution = (x,p; k...) -> plotgridap!(x;  k...))
+prob = GridapBifProblem(res, uh, par_bratu, V, U, (@lens _.λ); 
+		jac = jac,
+		d2res = d2res,
+		d3res = d3res,
+		plot_solution = (x,p; k...) -> plotgridap!(x;  k...))
 ```
 
 We can call then the newton solver:
@@ -101,22 +106,19 @@ We obtain:
 
 ```julia
 julia> br
- ┌─ Number of points: 56
- ├─ Curve of EquilibriumCont
+ ┌─ Curve type: EquilibriumCont
+ ├─ Number of points: 56
  ├─ Type of vectors: Vector{Float64}
  ├─ Parameter λ starts at 0.01, ends at 0.01
  ├─ Algo: PALC
  └─ Special points:
 
-If `br` is the name of the branch,
-ind_ev = index of the bifurcating eigenvalue e.g. `br.eig[idx].eigenvals[ind_ev]`
-
-- #  1,       bp at λ ≈ +0.36787944 ∈ (+0.36787944, +0.36787944), |δp|=1e-12, [converged], δ = ( 1,  0), step =  13, eigenelements in eig[ 14], ind_ev =   1
-- #  2,       nd at λ ≈ +0.27234314 ∈ (+0.27234314, +0.27234328), |δp|=1e-07, [converged], δ = ( 2,  0), step =  21, eigenelements in eig[ 22], ind_ev =   3
-- #  3,       bp at λ ≈ +0.15185452 ∈ (+0.15185452, +0.15185495), |δp|=4e-07, [converged], δ = ( 1,  0), step =  29, eigenelements in eig[ 30], ind_ev =   4
-- #  4,       nd at λ ≈ +0.03489122 ∈ (+0.03489122, +0.03489170), |δp|=5e-07, [converged], δ = ( 2,  0), step =  44, eigenelements in eig[ 45], ind_ev =   6
-- #  5,       nd at λ ≈ +0.01558733 ∈ (+0.01558733, +0.01558744), |δp|=1e-07, [converged], δ = ( 2,  0), step =  51, eigenelements in eig[ 52], ind_ev =   8
-- #  6, endpoint at λ ≈ +0.01000000,                                                                     step =  55
+- #  1,       bp at λ ≈ +0.36787944 ∈ (+0.36787944, +0.36787944), |δp|=1e-12, [converged], δ = ( 1,  0), step =  13
+- #  2,       nd at λ ≈ +0.27234314 ∈ (+0.27234314, +0.27234328), |δp|=1e-07, [converged], δ = ( 2,  0), step =  21
+- #  3,       bp at λ ≈ +0.15185452 ∈ (+0.15185452, +0.15185495), |δp|=4e-07, [converged], δ = ( 1,  0), step =  29
+- #  4,       nd at λ ≈ +0.03489122 ∈ (+0.03489122, +0.03489170), |δp|=5e-07, [converged], δ = ( 2,  0), step =  44
+- #  5,       nd at λ ≈ +0.01558733 ∈ (+0.01558733, +0.01558744), |δp|=1e-07, [converged], δ = ( 2,  0), step =  51
+- #  6, endpoint at λ ≈ +0.01000000,  
 ```
 
 ![](fig1gridap.png)

docs/src/tutorials/ode/steinmetz.md

@@ -57,7 +57,8 @@ end
 
 # group parameters
 argspo = (record_from_solution = recordFromSolution,
-	plot_solution = plotSolution)
+	plot_solution = plotSolution,
+	normC = norminf)
 
 nothing #hide
 ```
@@ -68,17 +69,17 @@ We obtain some trajectories as seeds for computing periodic orbits.
 using DifferentialEquations
 alg_ode = Rodas5()
 prob_de = ODEProblem(SL!, z0, (0,136.), par_sl)
-sol = solve(prob_de, alg_ode)
-prob_de = ODEProblem(SL!, sol.u[end], (0,30.), sol.prob.p, reltol = 1e-11, abstol = 1e-13)
-sol = solve(prob_de, alg_ode)
-plot(sol)
+sol_ode = solve(prob_de, alg_ode)
+prob_de = ODEProblem(SL!, sol_ode.u[end], (0,30.), sol_ode.prob.p, reltol = 1e-11, abstol = 1e-13)
+sol_ode = solve(prob_de, alg_ode)
+plot(sol_ode)
 ```
 
 ## Computation with Shooting
 We generate a shooting problem from the computed trajectories and continue the periodic orbits as function of $k_8$
 
 ```@example STEINMETZ
-probsh, cish = generate_ci_problem( ShootingProblem(M=4), prob, prob_de, sol, 16.; reltol = 1e-10, abstol = 1e-12, parallel = true)
+probsh, cish = generate_ci_problem( ShootingProblem(M=4), prob, prob_de, sol_ode, 16.; reltol = 1e-10, abstol = 1e-12, parallel = true)
 
 opts_po_cont = ContinuationPar(p_min = 0., p_max = 20.0, ds = 0.002, dsmax = 0.05, n_inversion = 8, detect_bifurcation = 3, max_bisection_steps = 25, nev = 4, max_steps = 60, save_eigenvectors = true, tol_stability = 1e-3)
 @set! opts_po_cont.newton_options.verbose = false

docs/src/tutorials/ode/tutorialPP2.md

@@ -68,7 +68,7 @@ diagram = bifurcationdiagram(prob, PALC(),
 	# when computing the bifurcation diagram. It means we allow computing branches of branches of branches
 	# at most in the present case.
 	3,
-	(args...) -> setproperties(opts_br; ds = -0.001, dsmax = 0.01, n_inversion = 8, detect_bifurcation = 3)
+	ContinuationPar(opts_br; ds = -0.001, dsmax = 0.01, n_inversion = 8, detect_bifurcation = 3)
 	)
 
 scene = plot(diagram; code = (), title="$(size(diagram)) branches", legend = false)

docs/src/tutorials/tutorials.md

@@ -93,6 +93,10 @@ See the [tutorials](https://bifurcationkit.github.io/DDEBifurcationKit.jl/dev/tu
 
 ## Examples based on ModelingToolkit
 
+`ModelingToolkit` provides a tailored interface to `BifurcationKit` and the user is encouraged to have a look at its specific [documentation](https://docs.sciml.ai/ModelingToolkit/stable/tutorials/bifurcation_diagram_computation/).
+
+We also provide some alternative example(s): 
+
 ```@contents
 Pages = ["ode/NME-MTK.md"]
 Depth = 1

docs/src/tutorials/tutorials3.md

@@ -168,7 +168,7 @@ br_hopf = continuation(br, ind_hopf, (@lens _.β),
 	optcdim2, verbosity = 2,
 	# detection of codim 2 bifurcations with bisection
 	detect_codim2_bifurcation = 2,
-	# we update the Fold problem at every continuation step
+	# we update the Hopf problem at every continuation step
 	update_minaug_every_step = 1,
 	jacobian_ma = :minaug, # specific to large dimensions
 	normC = norminf)