chore: format

src/adjoint_common.jl

@@ -223,7 +223,8 @@ function adjointdiffcache(g::G, sensealg, discrete, sol, dgdu::DG1, dgdp::DG2, f
  else
  pf = RODEParamJacobianWrapper(unwrappedf, _t, y, _W)
  end
- paramjac_config = build_param_jac_config(sensealg, pf, y, SciMLStructures.replace(Tunable(), p, tunables))
+ paramjac_config = build_param_jac_config(
+ sensealg, pf, y, SciMLStructures.replace(Tunable(), p, tunables))
  else
  if !isRODE
  pf = ParamGradientWrapper(unwrappedf, _t, y)
@@ -315,7 +316,8 @@ function adjointdiffcache(g::G, sensealg, discrete, sol, dgdu::DG1, dgdp::DG2, f
  prob.noise_rate_prototype)
  jac_noise_config = build_jac_config(sensealg, uf, u0)
  end
- paramjac_noise_config = build_param_jac_config(sensealg, pf, y, SciMLStructures.replace(Tunable(), p, tunables))
+ paramjac_noise_config = build_param_jac_config(
+ sensealg, pf, y, SciMLStructures.replace(Tunable(), p, tunables))
  else
  if StochasticDiffEq.is_diagonal_noise(prob)
  pf = ParamGradientWrapper(unwrappedf, _t, y)
@@ -372,7 +374,8 @@ function get_paramjac_config(autojacvec::ReverseDiffVJP, p, f, y, _p, _t;
  end
  if isinplace
  if !isRODE
- __p = p isa SciMLBase.NullParameters ? _p : SciMLStructures.replace(Tunable(), p, _p)
+ __p = p isa SciMLBase.NullParameters ? _p :
+ SciMLStructures.replace(Tunable(), p, _p)
  tape = ReverseDiff.GradientTape((y, __p, [_t])) do u, p, t
  du1 = (p !== nothing && p !== DiffEqBase.NullParameters()) ?
  similar(p, size(u)) : similar(u)
@@ -394,7 +397,8 @@ function get_paramjac_config(autojacvec::ReverseDiffVJP, p, f, y, _p, _t;
  # GradientTape doesn't handle NullParameters; hence _p isa zeros(...)
  # Cannot define replace(Tunable(), ::NullParameters, ::Vector)
  # because hasportion(Tunable(), NullParameters) == false
- __p = p isa SciMLBase.NullParameters ? _p : SciMLStructures.replace(Tunable(), p, _p)
+ __p = p isa SciMLBase.NullParameters ? _p :
+ SciMLStructures.replace(Tunable(), p, _p)
  tape = ReverseDiff.GradientTape((y, __p, [_t])) do u, p, t
  vec(f(u, p, first(t)))
  end

src/derivative_wrappers.jl

@@ -441,9 +441,9 @@ function _vecjacobian!(dλ, y, λ, p, t, S::TS, isautojacvec::ReverseDiffVJP, dg
  end
 
  if p === nothing || p isa SciMLBase.NullParameters
-  tunables, repack = p, identity
+  tunables, repack = p, identity
  else
-  tunables, repack, aliases = canonicalize(Tunable(), p)
+  tunables, repack, aliases = canonicalize(Tunable(), p)
  end
 
  u0 = state_values(prob)

src/forward_sensitivity.jl

@@ -158,7 +158,8 @@ function ODEForwardSensitivityProblem(f::F, args...; kwargs...) where {F}
 end
 
 function ODEForwardSensitivityProblem(prob::ODEProblem, alg; kwargs...)
- ODEForwardSensitivityProblem(prob.f, state_values(prob), prob.tspan, parameter_values(prob), alg; kwargs...)
+ ODEForwardSensitivityProblem(
+ prob.f, state_values(prob), prob.tspan, parameter_values(prob), alg; kwargs...)
 end
 
 const FORWARD_SENSITIVITY_PARAMETER_COMPATIBILITY_MESSAGE = """
@@ -526,7 +527,6 @@ function extract_local_sensitivities(sol, asmatrix::Bool)
  extract_local_sensitivities(sol, Val{asmatrix}())
 end
 function extract_local_sensitivities(sol, i::Integer, asmatrix::Val = Val(false))
-
  _extract(sol, sol.prob.problem_type.sensealg, state_values(sol, i), asmatrix)
 end
 function extract_local_sensitivities(sol, i::Integer, asmatrix::Bool)
@@ -644,7 +644,8 @@ function SciMLBase.remake(
  {uType, tType, isinplace, P, F, K}
  _p = p === nothing ? parameter_values(prob) : p
  _f = f === nothing ? prob.f.f : f
- _u0 = u0 === nothing ? state_values(prob, 1:(prob.f.numindvar)) : u0[1:(prob.f.numindvar)]
+ _u0 = u0 === nothing ? state_values(prob, 1:(prob.f.numindvar)) :
+ u0[1:(prob.f.numindvar)]
  _tspan = tspan === nothing ? prob.tspan : tspan
  ODEForwardSensitivityProblem(_f, _u0,
  _tspan, _p, prob.problem_type.sensealg;

src/gauss_adjoint.jl

@@ -375,10 +375,9 @@ function GaussIntegrand(sol, sensealg, checkpoints, dgdp = nothing)
  if p === nothing || p isa DiffEqBase.NullParameters
  tunables, repack = p, identity
  elseif isscimlstructure(p)
- tunables, repack, _=  canonicalize(Tunable(), p)
+ tunables, repack, _ = canonicalize(Tunable(), p)
  else
- tunables, repack = Functors.functor(p)
-
+ tunables, repack = Functors.functor(p)
  end
 
  numparams = length(tunables)
@@ -394,15 +393,17 @@ function GaussIntegrand(sol, sensealg, checkpoints, dgdp = nothing)
 
  if sensealg.autojacvec isa ReverseDiffVJP
  tape = if DiffEqBase.isinplace(prob)
- ReverseDiff.GradientTape((y, tunables, [tspan[2]])) do u, tunables, t
+ ReverseDiff.GradientTape((y, tunables, [tspan[2]])) do u, tunables, t
  du1 = similar(tunables, size(u))
  du1 .= false
- unwrappedf(du1, u, SciMLStructures.replace(Tunable(), p, tunables), first(t))
+ unwrappedf(
+ du1, u, SciMLStructures.replace(Tunable(), p, tunables), first(t))
  return vec(du1)
  end
  else
  ReverseDiff.GradientTape((y, tunables, [tspan[2]])) do u, tunables, t
- vec(unwrappedf(u, SciMLStructures.replace(Tunable(), p, tunables), first(t)))
+ vec(unwrappedf(
+ u, SciMLStructures.replace(Tunable(), p, tunables), first(t)))
  end
  end
  if compile_tape(sensealg.autojacvec)
@@ -452,11 +453,11 @@ function vec_pjac!(out, λ, y, t, S::GaussIntegrand)
  isautojacvec = get_jacvec(sensealg)
  # y is aliased
  if p === nothing || p isa SciMLBase.NullParameters
-  tunables, repack = p, identity
+  tunables, repack = p, identity
  elseif isscimlstructure(p)
-  tunables, repack, _ = canonicalize(Tunable(), p)
+  tunables, repack, _ = canonicalize(Tunable(), p)
  else
-  tunables, repack = Functors.functor(p)
+  tunables, repack = Functors.functor(p)
  end
 
  if !isautojacvec
@@ -540,18 +541,17 @@ function _adjoint_sensitivities(sol, sensealg::GaussAdjoint, alg; t = nothing,
  corfunc_analytical = false,
  callback = CallbackSet(),
  kwargs...)
-
  p = SymbolicIndexingInterface.parameter_values(sol)
  if !isscimlstructure(p) && !isfunctor(p)
  throw(SciMLStructuresCompatibilityError())
  end
 
  if p === nothing || p isa SciMLBase.NullParameters
- tunables, repack = p, identity
+ tunables, repack = p, identity
  elseif isscimlstructure(p)
  tunables, repack, _ = canonicalize(Tunable(), p)
  elseif isfunctor(p)
- tunables, repack = Functors.functor(p)
+ tunables, repack = Functors.functor(p)
  else
  throw(SciMLStructuresCompatibilityError())
  end

src/interpolating_adjoint.jl

@@ -59,7 +59,8 @@ function ODEInterpolatingAdjointSensitivityFunction(g, sensealg, discrete, sol,
  dt = choose_dt((_sol.W.t[idx1] - _sol.W.t[idx1 + 1]), _sol.W.t, interval)
 
  _ts = current_time(_sol)
- cpsol = solve(remake(sol.prob, tspan = interval, u0 = sol(interval[1]),
+ cpsol = solve(
+ remake(sol.prob, tspan = interval, u0 = sol(interval[1]),
  noise = forwardnoise),
  sol.alg, save_noise = false; dt = dt, tstops = _ts[idx1:end],
  tols...)
@@ -264,17 +265,17 @@ end
 
 # g is either g(t,u,p) or discrete g(t,u,i)
 @noinline function ODEAdjointProblem(sol, sensealg::InterpolatingAdjoint, alg,
- t = nothing,
- dgdu_discrete::DG1 = nothing,
- dgdp_discrete::DG2 = nothing,
- dgdu_continuous::DG3 = nothing,
- dgdp_continuous::DG4 = nothing,
- g::G = nothing,
- ::Val{RetCB} = Val(false);
- checkpoints = current_time(sol),
- callback = CallbackSet(),
- reltol = nothing, abstol = nothing,
- kwargs...) where {DG1, DG2, DG3, DG4, G, RetCB}
+  t = nothing,
+  dgdu_discrete::DG1 = nothing,
+  dgdp_discrete::DG2 = nothing,
+  dgdu_continuous::DG3 = nothing,
+  dgdp_continuous::DG4 = nothing,
+  g::G = nothing,
+  ::Val{RetCB} = Val(false);
+  checkpoints = current_time(sol),
+  callback = CallbackSet(),
+  reltol = nothing, abstol = nothing,
+  kwargs...) where {DG1, DG2, DG3, DG4, G, RetCB}
  dgdu_discrete === nothing && dgdu_continuous === nothing && g === nothing &&
  error("Either `dgdu_discrete`, `dgdu_continuous`, or `g` must be specified.")
  t !== nothing && dgdu_discrete === nothing && dgdp_discrete === nothing &&
@@ -287,12 +288,11 @@ end
  u0 = state_values(sol.prob)
 
  if p === nothing || p isa SciMLBase.NullParameters
-  tunables, repack = p, identity
+  tunables, repack = p, identity
  else
-  tunables, repack, _ = canonicalize(Tunable(), p)
+  tunables, repack, _ = canonicalize(Tunable(), p)
  end
 
-
  ## Force recompile mode until vjps are specialized to handle this!!!
  f = if sol.prob.f isa ODEFunction &&
  sol.prob.f.f isa FunctionWrappersWrappers.FunctionWrappersWrapper
@@ -394,17 +394,17 @@ end
 end
 
 @noinline function SDEAdjointProblem(sol, sensealg::InterpolatingAdjoint, alg,
- t = nothing,
- dgdu_discrete::DG1 = nothing,
- dgdp_discrete::DG2 = nothing,
- dgdu_continuous::DG3 = nothing,
- dgdp_continuous::DG4 = nothing,
- g::G = nothing;
- checkpoints = current_time(sol),
- callback = CallbackSet(),
- reltol = nothing, abstol = nothing,
- diffusion_jac = nothing, diffusion_paramjac = nothing,
- kwargs...) where {DG1, DG2, DG3, DG4, G}
+  t = nothing,
+  dgdu_discrete::DG1 = nothing,
+  dgdp_discrete::DG2 = nothing,
+  dgdu_continuous::DG3 = nothing,
+  dgdp_continuous::DG4 = nothing,
+  g::G = nothing;
+  checkpoints = current_time(sol),
+  callback = CallbackSet(),
+  reltol = nothing, abstol = nothing,
+  diffusion_jac = nothing, diffusion_paramjac = nothing,
+  kwargs...) where {DG1, DG2, DG3, DG4, G}
  dgdu_discrete === nothing && dgdu_continuous === nothing && g === nothing &&
  error("Either `dgdu_discrete`, `dgdu_continuous`, or `g` must be specified.")
  t !== nothing && dgdu_discrete === nothing && dgdp_discrete === nothing &&
@@ -536,16 +536,16 @@ end
 end
 
 @noinline function RODEAdjointProblem(sol, sensealg::InterpolatingAdjoint, alg,
- t = nothing,
- dgdu_discrete::DG1 = nothing,
- dgdp_discrete::DG2 = nothing,
- dgdu_continuous::DG3 = nothing,
- dgdp_continuous::DG4 = nothing,
- g::G = nothing;
- checkpoints = current_time(sol),
- callback = CallbackSet(),
- reltol = nothing, abstol = nothing,
- kwargs...) where {DG1, DG2, DG3, DG4, G}
+  t = nothing,
+  dgdu_discrete::DG1 = nothing,
+  dgdp_discrete::DG2 = nothing,
+  dgdu_continuous::DG3 = nothing,
+  dgdp_continuous::DG4 = nothing,
+  g::G = nothing;
+  checkpoints = current_time(sol),
+  callback = CallbackSet(),
+  reltol = nothing, abstol = nothing,
+  kwargs...) where {DG1, DG2, DG3, DG4, G}
  dgdu_discrete === nothing && dgdu_continuous === nothing && g === nothing &&
  error("Either `dgdu_discrete`, `dgdu_continuous`, or `g` must be specified.")
  t !== nothing && dgdu_discrete === nothing && dgdp_discrete === nothing &&

src/sensitivity_interface.jl

@@ -356,9 +356,8 @@ res3 = Calculus.gradient(G,[1.5,1.0,3.0])
 ```
 """
 function adjoint_sensitivities(sol, args...;
- sensealg = InterpolatingAdjoint(),
- verbose = true, kwargs...)
-
+ sensealg = InterpolatingAdjoint(),
+ verbose = true, kwargs...)
  p = SymbolicIndexingInterface.parameter_values(sol)
  if !(p === nothing || p isa SciMLBase.NullParameters)
  if !isscimlstructure(p) && !isfunctor(p)