Always return a solution type

Author: YingboMa

src/scalar.jl

@@ -8,18 +8,18 @@ function DiffEqBase.solve(prob::NonlinearProblem{<:Number}, ::NewtonRaphson, arg
   xo = oftype(x, Inf)
   for i in 1:maxiters
     fx, dfx = value_derivative(f, x)
-    iszero(fx) && return x
+    iszero(fx) && return NewtonSolution(x, :Default)
     Δx = dfx \ fx
     x -= Δx
     if isapprox(x, xo, atol=atol, rtol=rtol)
-        return x
+        return NewtonSolution(x, :Default)
     end
     xo = x
   end
-  return oftype(x, NaN)
+  return NewtonSolution(x, :MaxitersExceeded)
 end
 
-function DiffEqBase.solve(prob::NonlinearProblem{<:Number}, ::Bisection, args...; maxiters = 1000, kwargs...)
+function DiffEqBase.solve(prob::NonlinearProblem, ::Bisection, args...; maxiters = 1000, kwargs...)
   f = Base.Fix2(prob.f, prob.p)
   left, right = prob.u0
   fl, fr = f(left), f(right)

src/solve.jl

@@ -9,6 +9,7 @@ end
 function DiffEqBase.init(prob::NonlinearProblem{uType, iip}, alg::AbstractBracketingAlgorithm, args...;
     alias_u0 = false,
     maxiters = 1000,
+    # bracketing algorithms only solve scalar problems
     immutable = (prob.u0 isa StaticArray || prob.u0 isa Number),
     kwargs...
   ) where {uType, iip}

test/runtests.jl

@@ -23,11 +23,14 @@ end
 f, u0 = (u,p) -> u .* u .- 2, @SVector[1.0, 1.0]
 sf, su0 = (u,p) -> u * u - 2, 1.0
 sol = benchmark_immutable(f, u0)
+@test sol.retcode === :Default
 @test all(sol.u .* sol.u .- 2 .< 1e-9)
 sol = benchmark_mutable(f, u0)
+@test sol.retcode === :Default
 @test all(sol.u .* sol.u .- 2 .< 1e-9)
 sol = benchmark_scalar(sf, su0)
-@test sol * sol - 2 < 1e-9
+@test sol.retcode === :Default
+@test sol.u * sol.u - 2 < 1e-9
 
 @test (@ballocated benchmark_immutable($f, $u0)) == 0
 @test (@ballocated benchmark_mutable($f, $u0)) < 200