Apply JuliaFormatter to fix code formatting

- Applied JuliaFormatter with SciML style guide
- Formatted 3 files

🤖 Generated by OrgMaintenanceScripts.jl

Author: SciML Bot

lib/NonlinearProblemLibrary/src/NonlinearProblemLibrary.jl

@@ -264,7 +264,7 @@ p12_dict = Dict("n" => n, "start" => x_start, "sol" => x_sol,
 
 @inbounds function p13_f!(out, x, p = nothing)
     n = length(x)
-    out[1] = broyden_tridiag_kernel(x[1]) -2.0 * x[2]
+    out[1] = broyden_tridiag_kernel(x[1]) - 2.0 * x[2]
     for k in 2:(n - 1)
         out[k] = broyden_tridiag_kernel(x[k]) - x[k - 1] - 2.0 * x[k + 1]
     end

lib/ODEProblemLibrary/src/ode_simple_nonlinear_prob.jl

@@ -70,7 +70,8 @@ with ``μ=1.0`` and ``u_0=[x => \\sqrt{3}, y => 0]``
 
 Non-stiff parameters.
 """
-prob_ode_vanderpol = ODEProblem(van, [y => 0, x => sqrt(3), μ => 1.0], (0.0, 1.0), jac=true, eval_module = @__MODULE__)
+prob_ode_vanderpol = ODEProblem(van, [y => 0, x => sqrt(3), μ => 1.0], (0.0, 1.0),
+    jac = true, eval_module = @__MODULE__)
 
 """
 Van der Pol Equations
@@ -86,7 +87,8 @@ with ``μ=10^6`` and ``u_0=[x => \\sqrt{3}, y => 0]``
 
 Stiff parameters.
 """
-prob_ode_vanderpol_stiff = ODEProblem(van, [y => 0, x => sqrt(3), μ => 1e6], (0.0, 1.0), jac=true, eval_module = @__MODULE__)
+prob_ode_vanderpol_stiff = ODEProblem(van, [y => 0, x => sqrt(3), μ => 1e6], (0.0, 1.0),
+    jac = true, eval_module = @__MODULE__)
 
 # ROBER
 @parameters k₁ k₂ k₃
@@ -116,7 +118,9 @@ Hairer Norsett Wanner Solving Ordinary Differential Equations I - Nonstiff Probl
 
 Usually solved on ``[0,1e11]``
 """
-prob_ode_rober = ODEProblem(rober, [[y₁, y₂, y₃] .=> [1.0; 0.0; 0.0]; [k₁, k₂, k₃] .=> (0.04, 3e7, 1e4)], (0.0, 1e11), jac = true, eval_module = @__MODULE__)
+prob_ode_rober = ODEProblem(
+    rober, [[y₁, y₂, y₃] .=> [1.0; 0.0; 0.0]; [k₁, k₂, k₃] .=> (0.04, 3e7, 1e4)],
+    (0.0, 1e11), jac = true, eval_module = @__MODULE__)
 
 # Three Body
 const threebody_μ = big(0.012277471);
@@ -200,8 +204,10 @@ or Hairer Norsett Wanner Solving Ordinary Differential Equations I - Nonstiff Pr
 
 Usually solved from 0 to 20.
 """
-prob_ode_rigidbody = ODEProblem(rigid, [[y₁, y₂, y₃] .=> [1.0, 0.0, 0.9]; [I₁, I₂, I₃] .=> (-2.0, 1.25, -0.5)], (0.0, 20.0),
-                                jac = true, eval_module = @__MODULE__)
+prob_ode_rigidbody = ODEProblem(
+    rigid, [[y₁, y₂, y₃] .=> [1.0, 0.0, 0.9]; [I₁, I₂, I₃] .=> (-2.0, 1.25, -0.5)],
+    (0.0, 20.0),
+    jac = true, eval_module = @__MODULE__)
 
 # Pleiades Problem
 
@@ -365,8 +371,9 @@ u0[1] = 1
 u0[8] = 0.0057
 
 u0 = [y1, y2, y3, y4, y5, y6, y7, y8] .=> u0
-p = [p1, p2, p3, p4, p5, p6, p7, p8, p9, p10, p11, p12] .=> (1.71, 0.43, 8.32, 0.0007, 8.75,
-    10.03, 0.035, 1.12, 1.745, 280.0, 0.69, 1.81)
+p = [p1, p2, p3, p4, p5, p6, p7, p8, p9, p10, p11, p12] .=>
+    (1.71, 0.43, 8.32, 0.0007, 8.75,
+        10.03, 0.035, 1.12, 1.745, 280.0, 0.69, 1.81)
 
 """
 Hires Problem (Stiff)
@@ -390,7 +397,8 @@ where ``f`` is defined by
 Reference: [demohires.pdf](http://www.radford.edu/~thompson/vodef90web/problems/demosnodislin/Demos_Pitagora/DemoHires/demohires.pdf)
 Notebook: [Hires.ipynb](http://nbviewer.jupyter.org/github/JuliaDiffEq/DiffEqBenchmarks.jl/blob/master/StiffODE/Hires.ipynb)
 """
-prob_ode_hires = ODEProblem(hires, [u0; p], (0.0, 321.8122), jac = true, eval_module = @__MODULE__)
+prob_ode_hires = ODEProblem(
+    hires, [u0; p], (0.0, 321.8122), jac = true, eval_module = @__MODULE__)
 
 @parameters p1 p2 p3
 @variables y1(t) y2(t) y3(t)
@@ -418,4 +426,6 @@ where ``s=77.27``, ``w=0.161`` and ``q=8.375⋅10^{-6}``.
 Reference: [demoorego.pdf](http://www.radford.edu/~thompson/vodef90web/problems/demosnodislin/Demos_Pitagora/DemoOrego/demoorego.pdf)
 Notebook: [Orego.ipynb](http://nbviewer.jupyter.org/github/JuliaDiffEq/DiffEqBenchmarks.jl/blob/master/StiffODE/Orego.ipynb)
 """
-prob_ode_orego = ODEProblem(orego, [[y1, y2, y3] .=> [1.0, 2.0, 3.0]; [p1, p2, p3] .=> [77.27, 8.375e-6, 0.161]], (0.0, 30.0), jac = true, eval_module = @__MODULE__)
+prob_ode_orego = ODEProblem(
+    orego, [[y1, y2, y3] .=> [1.0, 2.0, 3.0]; [p1, p2, p3] .=> [77.27, 8.375e-6, 0.161]],
+    (0.0, 30.0), jac = true, eval_module = @__MODULE__)

lib/ODEProblemLibrary/src/strange_attractors.jl

@@ -23,7 +23,7 @@ $(latexify(thomas))
 
 [Wikipedia](https://en.wikipedia.org/wiki/Thomas%27_cyclically_symmetric_attractor)
 """
-prob_ode_thomas = ODEProblem(thomas, [], (0.0, 1.0), jac=true, eval_module = @__MODULE__)
+prob_ode_thomas = ODEProblem(thomas, [], (0.0, 1.0), jac = true, eval_module = @__MODULE__)
 
 # Lorenz
 @parameters σ=10 ρ=28 β=8 / 3
@@ -46,7 +46,7 @@ $(latexify(lorenz))
 
 [Wikipedia](https://en.wikipedia.org/wiki/Lorenz_system)
 """
-prob_ode_lorenz = ODEProblem(lorenz, [], (0.0, 1.0), jac=true, eval_module = @__MODULE__)
+prob_ode_lorenz = ODEProblem(lorenz, [], (0.0, 1.0), jac = true, eval_module = @__MODULE__)
 
 # Aizawa
 @parameters a=0.95 b=0.7 c=0.6 d=3.5 e=0.25 f=0.1
@@ -68,7 +68,7 @@ $(latexify(aizawa))
 [Reference](https://journals.ametsoc.org/view/journals/atsc/20/2/1520-0469_1963_020_0130_dnf_2_0_co_2.xml)
 
 """
-prob_ode_aizawa = ODEProblem(aizawa, [], (0.0, 1.0), jac=true, eval_module = @__MODULE__)
+prob_ode_aizawa = ODEProblem(aizawa, [], (0.0, 1.0), jac = true, eval_module = @__MODULE__)
 
 # Dadras
 @parameters a=3 b=2.7 c=1.7 d=2 e=9
@@ -90,7 +90,7 @@ $(latexify(dadras))
 [Reference](https://www.sciencedirect.com/science/article/abs/pii/S0375960109009591)
 
 """
-prob_ode_dadras = ODEProblem(dadras, [], (0.0, 1.0), jac=true, eval_module = @__MODULE__)
+prob_ode_dadras = ODEProblem(dadras, [], (0.0, 1.0), jac = true, eval_module = @__MODULE__)
 
 # chen
 @parameters a=35 b=3 c=28
@@ -112,7 +112,7 @@ $(latexify(chen))
 [Reference](https://www.worldscientific.com/doi/abs/10.1142/S0218127499001024)
 
 """
-prob_ode_chen = ODEProblem(chen, [], (0.0, 1.0), jac=true, eval_module = @__MODULE__)
+prob_ode_chen = ODEProblem(chen, [], (0.0, 1.0), jac = true, eval_module = @__MODULE__)
 
 # rossler
 @parameters a=0.2 b=0.2 c=5.7
@@ -135,7 +135,8 @@ $(latexify(rossler))
 [Wikipedia](https://en.wikipedia.org/wiki/R%C3%B6ssler_attractor)
 
 """
-prob_ode_rossler = ODEProblem(rossler, [], (0.0, 1.0), jac=true, eval_module = @__MODULE__)
+prob_ode_rossler = ODEProblem(
+    rossler, [], (0.0, 1.0), jac = true, eval_module = @__MODULE__)
 
 # rabinovich_fabrikant
 @parameters a=0.14 b=0.10
@@ -157,7 +158,8 @@ $(latexify(rabinovich_fabrikant))
 [Reference](https://en.wikipedia.org/wiki/Rabinovich%E2%80%93Fabrikant_equations)
 
 """
-prob_ode_rabinovich_fabrikant = ODEProblem(rabinovich_fabrikant, [], (0.0, 1.0), jac=true, eval_module = @__MODULE__)
+prob_ode_rabinovich_fabrikant = ODEProblem(
+    rabinovich_fabrikant, [], (0.0, 1.0), jac = true, eval_module = @__MODULE__)
 
 # sprott
 @parameters a=2.07 b=1.79
@@ -179,7 +181,7 @@ $(latexify(sprott))
 [Reference](https://sprott.physics.wisc.edu/pubs/paper423.pdf)
 
 """
-prob_ode_sprott = ODEProblem(sprott, [], (0.0, 1.0), jac=true, eval_module = @__MODULE__)
+prob_ode_sprott = ODEProblem(sprott, [], (0.0, 1.0), jac = true, eval_module = @__MODULE__)
 
 # hindmarsh_rose
 @parameters a=1 b=3 c=1 d=5 r=1e-2 s=4 xr=-8 / 5 i=5
@@ -201,4 +203,5 @@ $(latexify(hindmarsh_rose))
 [Reference](https://en.wikipedia.org/wiki/Hindmarsh%E2%80%93Rose_model)
 
 """
-prob_ode_hindmarsh_rose = ODEProblem(hindmarsh_rose, [], (0.0, 1.0), jac=true, eval_module = @__MODULE__)
+prob_ode_hindmarsh_rose = ODEProblem(
+    hindmarsh_rose, [], (0.0, 1.0), jac = true, eval_module = @__MODULE__)