fix: BifurcationKit test path + format

Project.toml

@@ -33,6 +33,7 @@ MacroTools = "1914dd2f-81c6-5fcd-8719-6d5c9610ff09"
 NaNMath = "77ba4419-2d1f-58cd-9bb1-8ffee604a2e3"
 OrdinaryDiffEq = "1dea7af3-3e70-54e6-95c3-0bf5283fa5ed"
 PrecompileTools = "aea7be01-6a6a-4083-8856-8a6e6704d82a"
+PrettyPrint = "8162dcfd-2161-5ef2-ae6c-7681170c5f98"
 RecursiveArrayTools = "731186ca-8d62-57ce-b412-fbd966d074cd"
 Reexport = "189a3867-3050-52da-a836-e630ba90ab69"
 RuntimeGeneratedFunctions = "7e49a35a-f44a-4d26-94aa-eba1b4ca6b47"

docs/src/systems/JumpSystem.md

@@ -26,6 +26,7 @@ structural_simplify
 ```@docs; canonical=false
 DiscreteProblem(sys::ModelingToolkit.DiscreteSystem, u0map, tspan)
 ```
+
 ```@docs
 JumpProblem(sys::JumpSystem, prob, aggregator)
 ```

docs/src/systems/SDESystem.md

@@ -26,6 +26,7 @@ sde = SDESystem(ode, noiseeqs)
 structural_simplify
 alias_elimination
 ```
+
 ```@docs
 ModelingToolkit.Girsanov_transform
 ```

docs/src/tutorials/bifurcation_diagram_computation.md

@@ -1,65 +1,91 @@
 # [Bifurcation Diagrams](@id bifurcation_diagrams)
+
 Bifurcation diagrams describes how, for a dynamic system, the quantity and quality of its steady states changes with a parameter's value. These can be computed through the [BifurcationKit.jl](https://github.com/bifurcationkit/BifurcationKit.jl) package. ModelingToolkit provides a simple interface for creating BifurcationKit compatible `BifurcationProblem`s from `NonlinearSystem`s and `ODESystem`s. All teh features provided by BifurcationKit can then be applied to these systems. This tutorial provides a brief introduction for these features, with BifurcationKit.jl providing [a more extensive documentation](https://bifurcationkit.github.io/BifurcationKitDocs.jl/stable/).
 
 ### Creating a `BifurcationProblem`
+
 Let us first consider a simple `NonlinearSystem`:
+
 ```@example Bif1
 using ModelingToolkit
 @variables t x(t) y(t)
 @parameters μ α
-eqs = [0 ~ μ*x - x^3 + α*y,
-        0 ~ -y]
+eqs = [0 ~ μ * x - x^3 + α * y,
+    0 ~ -y]
 @named nsys = NonlinearSystem(eqs, [x, y], [μ, α])
 ```
+
 we wish to compute a bifurcation diagram for this system as we vary the parameter `μ`. For this, we need to provide the following information:
-1. The system for which we wish to compute the bifurcation diagram (`nsys`).
-2. The parameter which we wish to vary (`μ`).
-3. The parameter set for which we want to compute the bifurcation diagram.
-4. An initial guess of the state of the system for which there is a steady state at our provided parameter value.
-5. The variable which value we wish to plot in the bifurcation diagram (this argument is optional, if not provided, BifurcationKit default plot functions are used).
+
+ 1. The system for which we wish to compute the bifurcation diagram (`nsys`).
+ 2. The parameter which we wish to vary (`μ`).
+ 3. The parameter set for which we want to compute the bifurcation diagram.
+ 4. An initial guess of the state of the system for which there is a steady state at our provided parameter value.
+ 5. The variable which value we wish to plot in the bifurcation diagram (this argument is optional, if not provided, BifurcationKit default plot functions are used).
 
 We declare this additional information:
+
 ```@example Bif1
 bif_par = μ
 p_start = [μ => -1.0, α => 1.0]
 u0_guess = [x => 1.0, y => 1.0]
 plot_var = x;
 ```
+
 For the initial state guess (`u0_guess`), typically any value can be provided, however, read BifurcatioKit's documentation for more details.
 
 We can now create our `BifurcationProblem`, which can be provided as input to BifurcationKit's various functions.
+
 ```@example Bif1
 using BifurcationKit
-bprob = BifurcationProblem(nsys, u0_guess, p_start, bif_par; plot_var=plot_var, jac=false)
+bprob = BifurcationProblem(nsys,
+    u0_guess,
+    p_start,
+    bif_par;
+    plot_var = plot_var,
+    jac = false)
 ```
-Here, the `jac` argument (by default set to `true`) sets whenever to provide BifurcationKit with a Jacobian or not.
 
+Here, the `jac` argument (by default set to `true`) sets whenever to provide BifurcationKit with a Jacobian or not.
 
 ### Computing a bifurcation diagram
 
-Let us consider the `BifurcationProblem` from the last section. If we wish to compute the corresponding bifurcation diagram we must first declare various settings used by BifurcationKit to compute the diagram. These are stored in a `ContinuationPar` structure (which also contain a `NewtonPar` structure). 
+Let us consider the `BifurcationProblem` from the last section. If we wish to compute the corresponding bifurcation diagram we must first declare various settings used by BifurcationKit to compute the diagram. These are stored in a `ContinuationPar` structure (which also contain a `NewtonPar` structure).
+
 ```@example Bif1
 p_span = (-4.0, 6.0)
 opt_newton = NewtonPar(tol = 1e-9, max_iterations = 20)
 opts_br = ContinuationPar(dsmin = 0.001, dsmax = 0.05, ds = 0.01,
-	max_steps = 100, nev = 2, newton_options = opt_newton,
-	p_min = p_span[1], p_max = p_span[2],
-	detect_bifurcation = 3, n_inversion = 4, tol_bisection_eigenvalue = 1e-8, dsmin_bisection = 1e-9);
+    max_steps = 100, nev = 2, newton_options = opt_newton,
+    p_min = p_span[1], p_max = p_span[2],
+    detect_bifurcation = 3, n_inversion = 4, tol_bisection_eigenvalue = 1e-8,
+    dsmin_bisection = 1e-9);
 ```
+
 Here, `p_span` sets the interval over which we wish to compute the diagram.
 
 Next, we can use this as input to our bifurcation diagram, and then plot it.
+
 ```@example Bif1
-bf = bifurcationdiagram(bprob, PALC(), 2, (args...) -> opts_br; bothside=true)
+bf = bifurcationdiagram(bprob, PALC(), 2, (args...) -> opts_br; bothside = true)
 ```
+
 Here, the value `2` sets how sub-branches of the diagram that BifurcationKit should compute. Generally, for bifurcation diagrams, it is recommended to use the `bothside=true` argument.
+
 ```@example Bif1
 using Plots
-plot(bf; putspecialptlegend=false, markersize=2, plotfold=false, xguide="μ", yguide = "x")
+plot(bf;
+    putspecialptlegend = false,
+    markersize = 2,
+    plotfold = false,
+    xguide = "μ",
+    yguide = "x")
 ```
+
 Here, the system exhibits a pitchfork bifurcation at *μ=0.0*.
 
 ### Using `ODESystem` inputs
+
 It is also possible to use `ODESystem`s (rather than `NonlinearSystem`s) as input to `BifurcationProblem`. Here follows a brief such example.
 
 ```@example Bif2
@@ -68,26 +94,38 @@ using BifurcationKit, ModelingToolkit, Plots
 @variables t x(t) y(t)
 @parameters μ
 D = Differential(t)
-eqs = [D(x) ~ μ*x - y - x*(x^2+y^2), 
-        D(y) ~ x + μ*y - y*(x^2+y^2)]
+eqs = [D(x) ~ μ * x - y - x * (x^2 + y^2),
+    D(y) ~ x + μ * y - y * (x^2 + y^2)]
 @named osys = ODESystem(eqs, t)
 
 bif_par = μ
 plot_var = x
 p_start = [μ => 1.0]
-u0_guess = [x => 0.0, y=> 0.0]
+u0_guess = [x => 0.0, y => 0.0]
 
-bprob = BifurcationProblem(osys, u0_guess, p_start, bif_par; plot_var=plot_var, jac=false)
+bprob = BifurcationProblem(osys,
+    u0_guess,
+    p_start,
+    bif_par;
+    plot_var = plot_var,
+    jac = false)
 
 p_span = (-3.0, 3.0)
 opt_newton = NewtonPar(tol = 1e-9, max_iterations = 20)
 opts_br = ContinuationPar(dsmin = 0.001, dsmax = 0.05, ds = 0.01,
-	max_steps = 100, nev = 2, newton_options = opt_newton,
-	p_max = p_span[2], p_min = p_span[1],
-	detect_bifurcation = 3, n_inversion = 4, tol_bisection_eigenvalue = 1e-8, dsmin_bisection = 1e-9)
+    max_steps = 100, nev = 2, newton_options = opt_newton,
+    p_max = p_span[2], p_min = p_span[1],
+    detect_bifurcation = 3, n_inversion = 4, tol_bisection_eigenvalue = 1e-8,
+    dsmin_bisection = 1e-9)
 
-bf = bifurcationdiagram(bprob, PALC(), 2, (args...) -> opts_br; bothside=true)
+bf = bifurcationdiagram(bprob, PALC(), 2, (args...) -> opts_br; bothside = true)
 using Plots
-plot(bf; putspecialptlegend=false, markersize=2, plotfold=false, xguide="μ", yguide = "x")
+plot(bf;
+    putspecialptlegend = false,
+    markersize = 2,
+    plotfold = false,
+    xguide = "μ",
+    yguide = "x")
 ```
-Here, the value of `x` in the steady state does not change, however, at `μ=0` a Hopf bifurcation occur and the steady state turn unstable.
+
+Here, the value of `x` in the steady state does not change, however, at `μ=0` a Hopf bifurcation occur and the steady state turn unstable.

ext/MTKBifurcationKitExt.jl

@@ -9,15 +9,23 @@ import BifurcationKit
 ### Creates BifurcationProblem Overloads ###
 
 # When input is a NonlinearSystem.
-function BifurcationKit.BifurcationProblem(nsys::NonlinearSystem, u0_bif, ps, bif_par, args...; plot_var=nothing, record_from_solution=BifurcationKit.record_sol_default, jac=true, kwargs...)
+function BifurcationKit.BifurcationProblem(nsys::NonlinearSystem,
+    u0_bif,
+    ps,
+    bif_par,
+    args...;
+    plot_var = nothing,
+    record_from_solution = BifurcationKit.record_sol_default,
+    jac = true,
+    kwargs...)
     # Creates F and J functions.
-    ofun = NonlinearFunction(nsys; jac=jac)
+    ofun = NonlinearFunction(nsys; jac = jac)
     F = ofun.f
     J = jac ? ofun.jac : nothing
 
     # Computes bifurcation parameter and plot var indexes.
     bif_idx = findfirst(isequal(bif_par), parameters(nsys))
-    if !isnothing(plot_var) 
+    if !isnothing(plot_var)
         plot_idx = findfirst(isequal(plot_var), states(nsys))
         record_from_solution = (x, p) -> x[plot_idx]
     end
@@ -26,12 +34,22 @@ function BifurcationKit.BifurcationProblem(nsys::NonlinearSystem, u0_bif, ps, bi
     u0_bif = ModelingToolkit.varmap_to_vars(u0_bif, states(nsys))
     ps = ModelingToolkit.varmap_to_vars(ps, parameters(nsys))
 
-    return BifurcationKit.BifurcationProblem(F, u0_bif, ps, (@lens _[bif_idx]), args...; record_from_solution = record_from_solution, J = J, kwargs...)
+    return BifurcationKit.BifurcationProblem(F,
+        u0_bif,
+        ps,
+        (@lens _[bif_idx]),
+        args...;
+        record_from_solution = record_from_solution,
+        J = J,
+        kwargs...)
 end
 
 # When input is a ODESystem.
 function BifurcationKit.BifurcationProblem(osys::ODESystem, args...; kwargs...)
-    nsys = NonlinearSystem([0 ~ eq.rhs for eq in equations(osys)], states(osys), parameters(osys); name=osys.name)
+    nsys = NonlinearSystem([0 ~ eq.rhs for eq in equations(osys)],
+        states(osys),
+        parameters(osys);
+        name = osys.name)
     return BifurcationKit.BifurcationProblem(nsys, args...; kwargs...)
 end
 

test/extensions/bifurcationkit.jl

@@ -1,29 +1,35 @@
 using BifurcationKit, ModelingToolkit, Test
 
 # Checks pitchfork diagram and that there are the correct number of branches (a main one and two children)
-let 
+let
     @variables t x(t) y(t)
     @parameters μ α
-    eqs = [0 ~ μ*x - x^3 + α*y,
-            0 ~ -y]
+    eqs = [0 ~ μ * x - x^3 + α * y,
+        0 ~ -y]
     @named nsys = NonlinearSystem(eqs, [x, y], [μ, α])
 
     bif_par = μ
     p_start = [μ => -1.0, α => 1.0]
     u0_guess = [x => 1.0, y => 1.0]
-    plot_var = x;
+    plot_var = x
 
     using BifurcationKit
-    bprob = BifurcationProblem(nsys, u0_guess, p_start, bif_par; plot_var=plot_var, jac=false)
+    bprob = BifurcationProblem(nsys,
+        u0_guess,
+        p_start,
+        bif_par;
+        plot_var = plot_var,
+        jac = false)
 
     p_span = (-4.0, 6.0)
     opt_newton = NewtonPar(tol = 1e-9, max_iterations = 20)
     opts_br = ContinuationPar(dsmin = 0.001, dsmax = 0.05, ds = 0.01,
         max_steps = 100, nev = 2, newton_options = opt_newton,
         p_min = p_span[1], p_max = p_span[2],
-        detect_bifurcation = 3, n_inversion = 4, tol_bisection_eigenvalue = 1e-8, dsmin_bisection = 1e-9);
+        detect_bifurcation = 3, n_inversion = 4, tol_bisection_eigenvalue = 1e-8,
+        dsmin_bisection = 1e-9)
 
-    bf = bifurcationdiagram(bprob, PALC(), 2, (args...) -> opts_br; bothside=true)
+    bf = bifurcationdiagram(bprob, PALC(), 2, (args...) -> opts_br; bothside = true)
 
     @test length(bf.child) == 2
-end
+end

test/runtests.jl

@@ -59,4 +59,4 @@ end
 if VERSION >= v"1.9"
     @safetestset "Latexify recipes Test" include("latexify.jl")
 end
-@safetestset "BifurcationKit Extension Test" include("extensions/bifurcationkit.jl")
+@safetestset "BifurcationKit Extension Test" include("extensions/bifurcationkit.jl")