Add BVPFunction

src/SciMLBase.jl

@@ -655,9 +655,9 @@ function specialization(::Union{ODEFunction{iip, specialize},
     ImplicitDiscreteFunction{iip, specialize},
     RODEFunction{iip, specialize},
     NonlinearFunction{iip, specialize},
-    OptimizationFunction{iip, specialize}}) where {iip,
+    OptimizationFunction{iip, specialize},
+    BVPFunction{iip, specialize}}) where {iip,
     specialize}
-    specialize
 end
 
 specialization(f::AbstractSciMLFunction) = FullSpecialize
@@ -784,7 +784,7 @@ export remake
 
 export ODEFunction, DiscreteFunction, ImplicitDiscreteFunction, SplitFunction, DAEFunction,
     DDEFunction, SDEFunction, SplitSDEFunction, RODEFunction, SDDEFunction,
-    IncrementingODEFunction, NonlinearFunction, IntervalNonlinearFunction
+    IncrementingODEFunction, NonlinearFunction, IntervalNonlinearFunction, BVPFunction
 
 export OptimizationFunction
 

src/ensemble/basic_ensemble_solve.jl

@@ -47,7 +47,7 @@ function __solve(prob::EnsembleProblem{<:AbstractVector{<:AbstractSciMLProblem}}
     ensemblealg::BasicEnsembleAlgorithm; kwargs...)
     # TODO: @invoke
     invoke(__solve, Tuple{AbstractEnsembleProblem, typeof(alg), typeof(ensemblealg)},
-        prob, alg, ensemblealg; trajectories=length(prob.prob), kwargs...)
+        prob, alg, ensemblealg; trajectories = length(prob.prob), kwargs...)
 end
 
 function __solve(prob::AbstractEnsembleProblem,

src/ensemble/ensemble_problems.jl

@@ -16,7 +16,11 @@ DEFAULT_REDUCTION(u, data, I) = append!(u, data), false
 DEFAULT_VECTOR_PROB_FUNC(prob, i, repeat) = prob[i]
 function EnsembleProblem(prob::AbstractVector{<:AbstractSciMLProblem}; kwargs...)
     # TODO: @invoke
-    invoke(EnsembleProblem, Tuple{Any}, prob; prob_func=DEFAULT_VECTOR_PROB_FUNC, kwargs...)
+    invoke(EnsembleProblem,
+        Tuple{Any},
+        prob;
+        prob_func = DEFAULT_VECTOR_PROB_FUNC,
+        kwargs...)
 end
 function EnsembleProblem(prob;
     output_func = DEFAULT_OUTPUT_FUNC,
@@ -36,20 +40,23 @@ function EnsembleProblem(; prob,
     EnsembleProblem(prob, prob_func, output_func, reduction, u_init, safetycopy)
 end
 
-struct WeightedEnsembleProblem{T1<:AbstractEnsembleProblem, T2<:AbstractVector} <: AbstractEnsembleProblem
-  ensembleprob::T1
-  weights::T2
+struct WeightedEnsembleProblem{T1 <: AbstractEnsembleProblem, T2 <: AbstractVector} <:
+       AbstractEnsembleProblem
+    ensembleprob::T1
+    weights::T2
+end
+function Base.propertynames(e::WeightedEnsembleProblem)
+    (Base.propertynames(getfield(e, :ensembleprob))..., :weights)
 end
-Base.propertynames(e::WeightedEnsembleProblem) = (Base.propertynames(getfield(e, :ensembleprob))..., :weights)
 function Base.getproperty(e::WeightedEnsembleProblem, f::Symbol)
-  f === :weights && return getfield(e, :weights)
-  f === :ensembleprob && return getfield(e, :ensembleprob)
-  return getproperty(getfield(e, :ensembleprob), f)
+    f === :weights && return getfield(e, :weights)
+    f === :ensembleprob && return getfield(e, :ensembleprob)
+    return getproperty(getfield(e, :ensembleprob), f)
 end
 function WeightedEnsembleProblem(args...; weights, kwargs...)
-  # TODO: allow skipping checks?
-  @assert sum(weights) ≈ 1
-  ep = EnsembleProblem(args...; kwargs...)
-  @assert length(ep.prob) == length(weights)
-  WeightedEnsembleProblem(ep, weights)
+    # TODO: allow skipping checks?
+    @assert sum(weights) ≈ 1
+    ep = EnsembleProblem(args...; kwargs...)
+    @assert length(ep.prob) == length(weights)
+    WeightedEnsembleProblem(ep, weights)
 end

src/ensemble/ensemble_solutions.jl

@@ -46,7 +46,7 @@ function EnsembleSolution(sim::T, elapsedTime,
         converged)
 end
 
-struct WeightedEnsembleSolution{T1<:AbstractEnsembleSolution, T2<:Number}
+struct WeightedEnsembleSolution{T1 <: AbstractEnsembleSolution, T2 <: Number}
     ensol::T1
     weights::Vector{T2}
     function WeightedEnsembleSolution(ensol, weights)
@@ -207,13 +207,18 @@ end
     end
 end
 
-
 Base.@propagate_inbounds function Base.getindex(x::AbstractEnsembleSolution, s, ::Colon)
     return [xi[s] for xi in x]
 end
 
-Base.@propagate_inbounds function Base.getindex(x::AbstractEnsembleSolution, ::Colon, args::Colon...)
-    return invoke(getindex, Tuple{RecursiveArrayTools.AbstractVectorOfArray, Colon, typeof.(args)...}, x, :, args...)
+Base.@propagate_inbounds function Base.getindex(x::AbstractEnsembleSolution,
+    ::Colon,
+    args::Colon...)
+    return invoke(getindex,
+        Tuple{RecursiveArrayTools.AbstractVectorOfArray, Colon, typeof.(args)...},
+        x,
+        :,
+        args...)
 end
 
 function (sol::AbstractEnsembleSolution)(args...; kwargs...)

src/problems/bvp_problems.jl

@@ -78,53 +78,41 @@ every solve call.
 * `p`: The parameters for the problem. Defaults to `NullParameters`
 * `kwargs`: The keyword arguments passed onto the solves.
 """
-struct BVProblem{uType, tType, isinplace, P, F, bF, PT, K} <:
+struct BVProblem{uType, tType, isinplace, P, F, BF, PT, K} <:
        AbstractBVProblem{uType, tType, isinplace}
     f::F
-    bc::bF
+    bc::BF
     u0::uType
     tspan::tType
     p::P
     problem_type::PT
     kwargs::K
-    @add_kwonly function BVProblem{iip}(f::AbstractODEFunction, bc, u0, tspan,
+
+    @add_kwonly function BVProblem{iip}(f::AbstractBVPFunction{iip}, bc, u0, tspan,
         p = NullParameters(),
         problem_type = StandardBVProblem();
         kwargs...) where {iip}
         _tspan = promote_tspan(tspan)
         warn_paramtype(p)
         new{typeof(u0), typeof(_tspan), iip, typeof(p),
-            typeof(f), typeof(bc),
-            typeof(problem_type), typeof(kwargs)}(f, bc, u0, _tspan, p,
+            typeof(f.f), typeof(bc),
+            typeof(problem_type), typeof(kwargs)}(f.f, bc, u0, _tspan, p,
             problem_type, kwargs)
     end
 
     function BVProblem{iip}(f, bc, u0, tspan, p = NullParameters(); kwargs...) where {iip}
-        BVProblem(ODEFunction{iip}(f), bc, u0, tspan, p; kwargs...)
+        BVProblem(BVPFunction{iip}(f, bc), bc, u0, tspan, p; kwargs...)
     end
 end
 
 TruncatedStacktraces.@truncate_stacktrace BVProblem 3 1 2
 
-function BVProblem(f::AbstractODEFunction, bc, u0, tspan, args...; kwargs...)
-    BVProblem{isinplace(f, 4)}(f, bc, u0, tspan, args...; kwargs...)
-end
-
 function BVProblem(f, bc, u0, tspan, p = NullParameters(); kwargs...)
-    BVProblem(ODEFunction(f), bc, u0, tspan, p; kwargs...)
+    BVProblem(BVPFunction(f, bc), u0, tspan, p; kwargs...)
 end
 
-# convenience interfaces:
-# Allow any previous timeseries solution
-function BVProblem(f::AbstractODEFunction, bc, sol::T, tspan::Tuple, p = NullParameters();
-    kwargs...) where {T <: AbstractTimeseriesSolution}
-    BVProblem(f, bc, sol.u, tspan, p)
-end
-# Allow a function of time for the initial guess
-function BVProblem(f::AbstractODEFunction, bc, initialGuess, tspan::AbstractVector,
-    p = NullParameters(); kwargs...)
-    u0 = [initialGuess(i) for i in tspan]
-    BVProblem(f, bc, u0, (tspan[1], tspan[end]), p)
+function BVProblem(f::AbstractBVPFunction, u0, tspan, p = NullParameters(); kwargs...)
+    BVProblem{isinplace(f)}(f.f, f.bc, u0, tspan, p; kwargs...)
 end
 
 """