format

docs/make.jl

@@ -8,33 +8,33 @@ makedocs(sitename = "OrdinaryDiffEq.jl",
     clean = true,
     doctest = false,
     modules = [OrdinaryDiffEq,
-               OrdinaryDiffEq.OrdinaryDiffEqAdamsBashforthMoulton,
-               OrdinaryDiffEq.OrdinaryDiffEqBDF,
-               OrdinaryDiffEq.OrdinaryDiffEqDefault,
-               OrdinaryDiffEq.OrdinaryDiffEqExplicitRK,
-               OrdinaryDiffEq.OrdinaryDiffEqExponentialRK,
-               OrdinaryDiffEq.OrdinaryDiffEqExtrapolation,
-               OrdinaryDiffEq.OrdinaryDiffEqFeagin,
-               OrdinaryDiffEq.OrdinaryDiffEqFIRK,
-               OrdinaryDiffEq.OrdinaryDiffEqHighOrderRK,
-               OrdinaryDiffEq.OrdinaryDiffEqIMEXMultistep,
-               OrdinaryDiffEq.OrdinaryDiffEqLinear,
-               OrdinaryDiffEq.OrdinaryDiffEqLowOrderRK,
-               OrdinaryDiffEq.OrdinaryDiffEqLowStorageRK,
-               OrdinaryDiffEq.OrdinaryDiffEqNordsieck,
-               OrdinaryDiffEq.OrdinaryDiffEqPDIRK,
-               OrdinaryDiffEq.OrdinaryDiffEqPRK,
-               OrdinaryDiffEq.OrdinaryDiffEqQPRK,
-               OrdinaryDiffEq.OrdinaryDiffEqRKN,
-               OrdinaryDiffEq.OrdinaryDiffEqRosenbrock,
-               OrdinaryDiffEq.OrdinaryDiffEqSDIRK,
-               OrdinaryDiffEq.OrdinaryDiffEqSSPRK,
-               OrdinaryDiffEq.OrdinaryDiffEqStabilizedIRK,
-               OrdinaryDiffEq.OrdinaryDiffEqStabilizedRK,
-               OrdinaryDiffEq.OrdinaryDiffEqSymplecticRK,
-               OrdinaryDiffEq.OrdinaryDiffEqTsit5,
-               OrdinaryDiffEq.OrdinaryDiffEqVerner,
-        ],
+        OrdinaryDiffEq.OrdinaryDiffEqAdamsBashforthMoulton,
+        OrdinaryDiffEq.OrdinaryDiffEqBDF,
+        OrdinaryDiffEq.OrdinaryDiffEqDefault,
+        OrdinaryDiffEq.OrdinaryDiffEqExplicitRK,
+        OrdinaryDiffEq.OrdinaryDiffEqExponentialRK,
+        OrdinaryDiffEq.OrdinaryDiffEqExtrapolation,
+        OrdinaryDiffEq.OrdinaryDiffEqFeagin,
+        OrdinaryDiffEq.OrdinaryDiffEqFIRK,
+        OrdinaryDiffEq.OrdinaryDiffEqHighOrderRK,
+        OrdinaryDiffEq.OrdinaryDiffEqIMEXMultistep,
+        OrdinaryDiffEq.OrdinaryDiffEqLinear,
+        OrdinaryDiffEq.OrdinaryDiffEqLowOrderRK,
+        OrdinaryDiffEq.OrdinaryDiffEqLowStorageRK,
+        OrdinaryDiffEq.OrdinaryDiffEqNordsieck,
+        OrdinaryDiffEq.OrdinaryDiffEqPDIRK,
+        OrdinaryDiffEq.OrdinaryDiffEqPRK,
+        OrdinaryDiffEq.OrdinaryDiffEqQPRK,
+        OrdinaryDiffEq.OrdinaryDiffEqRKN,
+        OrdinaryDiffEq.OrdinaryDiffEqRosenbrock,
+        OrdinaryDiffEq.OrdinaryDiffEqSDIRK,
+        OrdinaryDiffEq.OrdinaryDiffEqSSPRK,
+        OrdinaryDiffEq.OrdinaryDiffEqStabilizedIRK,
+        OrdinaryDiffEq.OrdinaryDiffEqStabilizedRK,
+        OrdinaryDiffEq.OrdinaryDiffEqSymplecticRK,
+        OrdinaryDiffEq.OrdinaryDiffEqTsit5,
+        OrdinaryDiffEq.OrdinaryDiffEqVerner
+    ],
     warnonly = [:docs_block, :missing_docs, :eval_block],
     format = Documenter.HTML(analytics = "UA-90474609-3",
         assets = ["assets/favicon.ico"],
@@ -56,7 +56,7 @@ makedocs(sitename = "OrdinaryDiffEq.jl",
             "explicit/SymplecticRK.md",
             "explicit/PRK.md",
             "explicit/QPRK.md",
-            "explicit/Extrapolation.md",
+            "explicit/Extrapolation.md"
         ],
         "Implicit Solvers" => [
             "implicit/SDIRK.md",

docs/src/explicit/Extrapolation.md

@@ -15,4 +15,4 @@ first_steps("OrdinaryDiffEqExtrapolation", "ExtrapolationMidpointDeuflhard")
 AitkenNeville
 ExtrapolationMidpointDeuflhard
 ExtrapolationMidpointHairerWanner
-```
+```

docs/src/explicit/Nordsieck.md

@@ -11,7 +11,6 @@ The Nordsieck implementations here are considered experimental implementations o
 and are generally considered inferior to the fixed-leading history-based BDF implementation of FBDF, and thus for all standard usage we recommend FBDF.
 However, this algorithm is kept for experimental research and development purposes with the possibility of one day becoming a more discontinuity-aware BDF implementation.
 
-
 ```@eval
 first_steps = evalfile("./common_first_steps.jl")
 first_steps("OrdinaryDiffEqNordsieck", "AN5")

docs/src/explicit/RKN.md

@@ -8,11 +8,13 @@ To be able to access the solvers in `OrdinaryDiffEqRKN`, you must first install
 using Pkg
 Pkg.add("OrdinaryDiffEqRKN")
 ```
+
 This will only install the solvers listed at the bottom of this page.
 If you want to explore other solvers for your problem,
 you will need to install some of the other libraries listed in the navigation bar on the left.
 
 ## Example usage
+
 ```julia
 using OrdinaryDiffEqOrdinaryDiffEqRKN
 function HH_acceleration!(dv, v, u, p, t)

docs/src/explicit/SymplecticRK.md

@@ -5,20 +5,23 @@ Because of discretization error, when it is solving a Hamiltonian system it does
 Instead, that trajectory itself is perturbed `O(Δtn)` for the order n from the true trajectory.
 Then there's a linear drift due to numerical error of this trajectory over time
 Normal integrators tend to have a quadratic (or more) drift, and do not have any good global guarantees about this phase space path (just local).
-What means is that symplectic integrators tend to capture the long-time patterns better than normal integrators because of this lack of drift and this almost guarantee of periodicity. 
+What means is that symplectic integrators tend to capture the long-time patterns better than normal integrators because of this lack of drift and this almost guarantee of periodicity.
 
 ## Installation
+
 To be able to access the solvers in `OrdinaryDiffEqSymplecticRK`, you must first install them use the Julia package manager:
 
 ```julia
 using Pkg
 Pkg.add("OrdinaryDiffEqSymplecticRK")
 ```
+
 This will only install the solvers listed at the bottom of this page.
 If you want to explore other solvers for your problem,
 you will need to install some of the other libraries listed in the navigation bar on the left.
 
 ## Example usage
+
 ```julia
 using OrdinaryDiffEqSymplecticRK
 function HH_acceleration!(dv, v, u, p, t)

docs/src/implicit/BDF.md

@@ -29,6 +29,7 @@ SBDF2
 SBDF3
 SBDF4
 ```
+
 ### IMEX SDIRK
 
 ```@docs
@@ -42,4 +43,4 @@ IMEXEulerARK
 DImplicitEuler
 DABDF2
 DFBDF
-```
+```

docs/src/implicit/Extrapolation.md

@@ -2,7 +2,7 @@
 
 Solvers based on within method parallelism.
 These solvers perform well for medium sized systems of ordinary differential equations, of about 20 to 500 equations,
-at low tolerances. 
+at low tolerances.
 
 ```@eval
 first_steps = evalfile("./common_first_steps.jl")
@@ -16,4 +16,4 @@ ImplicitEulerExtrapolation
 ImplicitDeuflhardExtrapolation
 ImplicitHairerWannerExtrapolation
 ImplicitEulerBarycentricExtrapolation
-```
+```

docs/src/implicit/FIRK.md

@@ -33,4 +33,4 @@ first_steps("OrdinaryDiffEqFIRK", "RadauIIA5")
 RadauIIA3
 RadauIIA5
 RadauIIA9
-```
+```

docs/src/implicit/PDIRK.md

@@ -9,15 +9,15 @@ There are some advantages to this,
 as no SDIRK method can be a higher order than 5,
 while DIRK methods generally can have arbitrarily high order and lower error coefficients,
 leading to lower errors at larger dt sizes.
-With the right construction of the tableau, 
+With the right construction of the tableau,
 these matrices can be factorized and the underlying steps can be computed in parallel,
 which is why these are the parallel DIRK methods.
 
 !!! warning "Experimental"
+
     `OrdinaryDiffEqPDIRK` is experimental,
     as there are no parallel DIRK tableaus that achieve good performance in the literature.
 
-
 ```@eval
 first_steps = evalfile("./common_first_steps.jl")
 first_steps("OrdinaryDiffEqPDIRK", "PDIRK44")
@@ -27,4 +27,4 @@ first_steps("OrdinaryDiffEqPDIRK", "PDIRK44")
 
 ```@docs
 PDIRK44
-```
+```

docs/src/implicit/Rosenbrock.md

@@ -49,4 +49,4 @@ Velds4
 GRK4T
 GRK4A
 Ros4LStab
-```
+```

docs/src/implicit/SDIRK.md

@@ -31,7 +31,9 @@ Hairer42
 Kvaerno4
 Kvaerno5
 ```
+
 ### IMEX SDIRK
+
 ```@docs
 KenCarp4
 KenCarp47
@@ -42,4 +44,4 @@ ESDIRK436L2SA2
 ESDIRK437L2SA
 ESDIRK547L2SA2
 ESDIRK659L2SA
-```
+```

docs/src/implicit/StabalizedIRK.md

@@ -17,4 +17,3 @@ first_steps("OrdinaryDiffEqStabalizedIRK", "IRKC")
 ```@docs
 IRKC
 ```
-

docs/src/implicit/StabalizedRK.md

@@ -22,4 +22,3 @@ SERK2
 ESERK4
 ESERK5
 ```
-

docs/src/semilinear/ExponentialRK.md

@@ -36,4 +36,4 @@ EPIRK5s3
 EXPRB53s3
 EPIRK5P1
 EPIRK5P2
-```
+```

docs/src/semilinear/Linear.md

@@ -45,4 +45,4 @@ CayleyEuler
 
 ```@docs
 CG3
-```
+```

lib/OrdinaryDiffEqBDF/src/algorithms.jl

@@ -1,8 +1,8 @@
 function BDF_docstring(description::String,
-    name::String;
-    references::String = "",
-    extra_keyword_description::String = "",
-    extra_keyword_default::String = "")
+        name::String;
+        references::String = "",
+        extra_keyword_description::String = "",
+        extra_keyword_default::String = "")
     keyword_default = """
         chunk_size = Val{0}(),
         autodiff = true,
@@ -30,8 +30,8 @@ function BDF_docstring(description::String,
     )
 end
 
-
-@doc BDF_docstring("An adaptive order 2 L-stable fixed leading coefficient multistep BDF method.",
+@doc BDF_docstring(
+    "An adaptive order 2 L-stable fixed leading coefficient multistep BDF method.",
     "ABDF2",
     references = """
     E. Alberdi Celayaa, J. J. Anza Aguirrezabalab, P. Chatzipantelidisc. Implementation of
@@ -81,11 +81,11 @@ function ABDF2(; chunk_size = Val{0}(), autodiff = true, standardtag = Val{true}
         smooth_est, extrapolant, controller, step_limiter!)
 end
 
-
-@doc BDF_docstring("Implicit-explicit (IMEX) method designed for SplitODEFunction equations,
-    which reduce the size of the implicit handling to a subset of the equations.
-    It's similar to the additive Runge-Kutta methods in splitting mode,
-    like `KenCarp4`, but instead using a multistep BDF approach",
+@doc BDF_docstring(
+    "Implicit-explicit (IMEX) method designed for SplitODEFunction equations,
+which reduce the size of the implicit handling to a subset of the equations.
+It's similar to the additive Runge-Kutta methods in splitting mode,
+like `KenCarp4`, but instead using a multistep BDF approach",
     "SBDF",
     references = """@article{ascher1995implicit,
     title={Implicit-explicit methods for time-dependent partial differential equations},
@@ -205,8 +205,9 @@ See also `SBDF`.
 """
 SBDF4(; kwargs...) = SBDF(4; kwargs...)
 
-@doc BDF_docstring("An adaptive order 1 quasi-constant timestep L-stable numerical differentiation function (NDF) method.
-    Optional parameter kappa defaults to Shampine's accuracy-optimal -0.1850.",
+@doc BDF_docstring(
+    "An adaptive order 1 quasi-constant timestep L-stable numerical differentiation function (NDF) method.
+Optional parameter kappa defaults to Shampine's accuracy-optimal -0.1850.",
     "QNDF1",
     references = """@article{shampine1997matlab,
     title={The matlab ode suite},
@@ -246,7 +247,7 @@ end
 function QNDF1(; chunk_size = Val{0}(), autodiff = Val{true}(), standardtag = Val{true}(),
         concrete_jac = nothing, diff_type = Val{:forward},
         linsolve = nothing, precs = DEFAULT_PRECS, nlsolve = NLNewton(),
-        extrapolant = :linear, kappa = -37//200,
+        extrapolant = :linear, kappa = -37 // 200,
         controller = :Standard, step_limiter! = trivial_limiter!)
     QNDF1{
         _unwrap_val(chunk_size), _unwrap_val(autodiff), typeof(linsolve), typeof(nlsolve),
@@ -260,7 +261,8 @@ function QNDF1(; chunk_size = Val{0}(), autodiff = Val{true}(), standardtag = Va
         step_limiter!)
 end
 
-@doc BDF_docstring("An adaptive order 2 quasi-constant timestep L-stable numerical differentiation function (NDF) method.",
+@doc BDF_docstring(
+    "An adaptive order 2 quasi-constant timestep L-stable numerical differentiation function (NDF) method.",
     "QNDF2",
     references = """@article{shampine1997matlab,
     title={The matlab ode suite},
@@ -314,8 +316,9 @@ function QNDF2(; chunk_size = Val{0}(), autodiff = Val{true}(), standardtag = Va
         step_limiter!)
 end
 
-@doc BDF_docstring("An adaptive order quasi-constant timestep NDF method.
-    Utilizes Shampine's accuracy-optimal kappa values as defaults (has a keyword argument for a tuple of kappa coefficients).",
+@doc BDF_docstring(
+    "An adaptive order quasi-constant timestep NDF method.
+Utilizes Shampine's accuracy-optimal kappa values as defaults (has a keyword argument for a tuple of kappa coefficients).",
     "QNDF",
     references = """@article{shampine1997matlab,
     title={The matlab ode suite},
@@ -364,7 +367,8 @@ function QNDF(; max_order::Val{MO} = Val{5}(), chunk_size = Val{0}(),
         diff_type = Val{:forward},
         linsolve = nothing, precs = DEFAULT_PRECS, nlsolve = NLNewton(), κ = nothing,
         tol = nothing,
-        extrapolant = :linear, kappa = (-37//200, -1//9, -823//10000, -83//2000, 0//1),
+        extrapolant = :linear, kappa = (
+            -37 // 200, -1 // 9, -823 // 10000, -83 // 2000, 0 // 1),
         controller = :Standard, step_limiter! = trivial_limiter!) where {MO}
     QNDF{MO, _unwrap_val(chunk_size), _unwrap_val(autodiff), typeof(linsolve),
         typeof(nlsolve), typeof(precs), diff_type, _unwrap_val(standardtag),
@@ -416,9 +420,10 @@ function MEBDF2(; chunk_size = Val{0}(), autodiff = true, standardtag = Val{true
         extrapolant)
 end
 
-@doc BDF_docstring("An adaptive order quasi-constant timestep NDF method.
-    Fixed leading coefficient BDF.
-    Utilizes Shampine's accuracy-optimal kappa values as defaults (has a keyword argument for a tuple of kappa coefficients).",
+@doc BDF_docstring(
+    "An adaptive order quasi-constant timestep NDF method.
+Fixed leading coefficient BDF.
+Utilizes Shampine's accuracy-optimal kappa values as defaults (has a keyword argument for a tuple of kappa coefficients).",
     "FBDF",
     references = """@article{shampine2002solving,
     title={Solving 0= F (t, y (t), y′(t)) in Matlab},
@@ -550,8 +555,9 @@ See also `SBDF`, `IMEXEuler`.
 """
 IMEXEulerARK(; kwargs...) = SBDF(1; ark = true, kwargs...)
 
-@doc BDF_docstring("Implicit Euler for implicit DAE form.
-    It uses an apriori error estimator for adaptivity based on a finite differencing approximation from SPICE.",
+@doc BDF_docstring(
+    "Implicit Euler for implicit DAE form.
+It uses an apriori error estimator for adaptivity based on a finite differencing approximation from SPICE.",
     "DImplicitEuler",
     extra_keyword_description = """
     - `nlsolve`: TBD

lib/OrdinaryDiffEqCore/src/doc_utils.jl

@@ -75,11 +75,11 @@ function explicit_rk_docstring(description::String,
     )
 end
 function differentiation_rk_docstring(description::String,
-    name::String,
-    solver_class::String;
-    references::String = "",
-    extra_keyword_description::String = "",
-    extra_keyword_default::String = "")
+        name::String,
+        solver_class::String;
+        references::String = "",
+        extra_keyword_description::String = "",
+        extra_keyword_default::String = "")
     keyword_default = """
     chunk_size = Val{0}(),
     autodiff = true,