JuliaFormatter.jl

src/initialization/autodiffinit.jl

@@ -15,7 +15,7 @@ function initial_update!(integ, cache, init::AutodiffInitializationScheme)
 
     f_derivatives = get_derivatives(init, u, f, p, t)
     integ.stats.nf += init.order
-    @assert length(f_derivatives) == init.order+1
+    @assert length(f_derivatives) == init.order + 1
 
     # This is hacky and should definitely be removed. But it also works so 🤷
     MM = if f.mass_matrix isa UniformScaling
@@ -49,7 +49,13 @@ end
 """
     Compute initial derivatives of an IIP ODEProblem with TaylorIntegration.jl
 """
-function get_derivatives(init::TaylorModeInit, u, f::SciMLBase.AbstractODEFunction{true}, p, t)
+function get_derivatives(
+    init::TaylorModeInit,
+    u,
+    f::SciMLBase.AbstractODEFunction{true},
+    p,
+    t,
+)
     q = init.order
     tT = Taylor1(typeof(t), q)
     tT[0] = t
@@ -64,7 +70,13 @@ function get_derivatives(init::TaylorModeInit, u, f::SciMLBase.AbstractODEFuncti
     return [evaluate.(differentiate.(uT, i)) for i in 0:q]
 end
 
-function get_derivatives(init::ForwardDiffInit, u, f::SciMLBase.AbstractODEFunction{true}, p, t)
+function get_derivatives(
+    init::ForwardDiffInit,
+    u,
+    f::SciMLBase.AbstractODEFunction{true},
+    p,
+    t,
+)
     q = init.order
     _f(u) = (du = copy(u); f(du, u, p, t); du)
     f_n = _f
@@ -85,8 +97,14 @@ function forwarddiff_oop_vectorfield_derivative_iteration(f_n, f_0)
     return df
 end
 
-
-function forwarddiff_get_derivatives!(out, u, f::SciMLBase.AbstractODEFunction{true}, p, t, q)
+function forwarddiff_get_derivatives!(
+    out,
+    u,
+    f::SciMLBase.AbstractODEFunction{true},
+    p,
+    t,
+    q,
+)
     _f(du, u) = f(du, u, p, t)
     d = length(u0)
     f_n = _f