MethodError: no method matching copyto!

[Volker-Weissmann]

Running this code

using SimpleDiffEq
f(u,p,t) = 2u
g(u,p,t) = 1
u0 = 0.5
tspan = (0.0,1.0)
prob = SDEProblem(f,g,u0,tspan)
sol = solve(prob,SimpleEM(),dt=0.25)
g(du,u,p,t) = du .= 2.0 * u
function f(du, u, p, t)
    g(du,u,p,t)
end

using SimpleDiffEq
f(u,p,t) = 2u
g(u,p,t) = 1
u0 = 0.5
tspan = (0.0,1.0)
prob = SDEProblem(f,g,u0,tspan)
sol = solve(prob,SimpleEM(),dt=0.25)
g(du,u,p,t) = du .= 2.0 * u
function f(du, u, p, t)
    g(du,u,p,t)
end

outputs:

ERROR: LoadError: MethodError: no method matching copyto!(::Float64, ::Base.Broadcast.Broadcasted{Base.Broadcast.DefaultArrayStyle{0}, Tuple{}, typeof(identity), Tuple{Float64}})
Closest candidates are:
  copyto!(::DiffEqArrayOperator, ::Any) at /home/volker/.julia/packages/SciMLBase/dyqr8/src/operators/basic_operators.jl:112
  copyto!(::Any, ::Base.Broadcast.Broadcasted{var"#s155", Axes, F, Args} where {var"#s155"<:StaticArrays.StaticArrayStyle, Axes, F, Args<:Tuple}) at /home/volker/.julia/packages/StaticArrays/xV8rq/src/broadcast.jl:29
  copyto!(::DiffEqBase.DiffEqBC, ::Base.Broadcast.Broadcasted{var"#s7", Axes, F, Args} where {var"#s7"<:Base.Broadcast.AbstractArrayStyle{0}, Axes, F, Args<:Tuple}) at /home/volker/.julia/packages/DiffEqBase/qntkj/src/diffeqfastbc.jl:42
  ...
Stacktrace:
 [1] materialize!
   @ ./broadcast.jl:894 [inlined]
 [2] materialize!
   @ ./broadcast.jl:891 [inlined]
 [3] g(du::Float64, u::Float64, p::SciMLBase.NullParameters, t::Float64)
   @ Main ~/Sync/DatenVolker/git/sm_with_julia/bug.jl:8
 [4] f(du::Float64, u::Float64, p::SciMLBase.NullParameters, t::Float64)
   @ Main ~/Sync/DatenVolker/git/sm_with_julia/bug.jl:10
 [5] (::SDEFunction{true, typeof(f), typeof(g), LinearAlgebra.UniformScaling{Bool}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing})(::Float64, ::Vararg{Any, N} where N)
   @ SciMLBase ~/.julia/packages/SciMLBase/dyqr8/src/scimlfunctions.jl:395
 [6] solve(::SDEProblem{Float64, Tuple{Float64, Float64}, true, SciMLBase.NullParameters, Nothing, SDEFunction{true, typeof(f), typeof(g), LinearAlgebra.UniformScaling{Bool}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing}, typeof(g), Base.Iterators.Pairs{Union{}, Union{}, Tuple{}, NamedTuple{(), Tuple{}}}, Nothing}, ::SimpleEM; dt::Float64)
   @ SimpleDiffEq ~/.julia/packages/SimpleDiffEq/vIpeG/src/euler_maruyama.jl:57
 [7] top-level scope
   @ ~/Sync/DatenVolker/git/sm_with_julia/bug.jl:19
in expression starting at /home/volker/Sync/DatenVolker/git/sm_with_julia/bug.jl:19

[YingboMa]

u0 should be an array, given your ODE definition. Try u0 = [0.5]

[ChrisRackauckas]

For standard solvers you now get:

using StochasticDiffEq
f(u,p,t) = 2u
g(u,p,t) = 1
u0 = 0.5
tspan = (0.0,1.0)
prob = SDEProblem(f,g,u0,tspan)
sol = solve(prob,EM(),dt=0.25)

ERROR: Initial condition incompatible with functional form.
Detected an in-place function with an initial condition of type Number or SArray.
This is incompatible because Numbers cannot be mutated, i.e.
`x = 2.0; y = 2.0; x .= y` will error.

If using a immutable initial condition type, please use the out-of-place form.
I.e. define the function `du=f(u,p,t)` instead of attempting to "mutate" the immutable `du`.

If your differential equation function was defined with multiple dispatches and one is
in-place, then the automatic detection will choose in-place. In this case, override the
choice in the problem constructor, i.e. `ODEProblem{false}(f,u0,tspan,p,kwargs...)`.

For a longer discussion on mutability vs immutability and in-place vs out-of-place, see:
https://diffeq.sciml.ai/stable/tutorials/faster_ode_example/#Example-Accelerating-a-Non-Stiff-Equation:-The-Lorenz-Equation

Stacktrace:
 [1] get_concrete_u0(prob::SDEProblem{Float64, Tuple{Float64, Float64}, true, SciMLBase.NullParameters, Nothing, SDEFunction{true, typeof(f), typeof(g), LinearAlgebra.UniformScaling{Bool}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing}, typeof(g), Base.Pairs{Symbol, Union{}, Tuple{}, NamedTuple{(), Tuple{}}}, Nothing}, isadapt::Bool, t0::Float64, kwargs::Base.Pairs{Symbol, Any, Tuple{Symbol, Symbol, Symbol}, NamedTuple{(:u0, :p, :dt), Tuple{Float64, SciMLBase.NullParameters, Float64}}})
   @ DiffEqBase C:\Users\accou\.julia\dev\DiffEqBase\src\solve.jl:490
 [2] get_concrete_problem(prob::SDEProblem{Float64, Tuple{Float64, Float64}, true, SciMLBase.NullParameters, Nothing, SDEFunction{true, typeof(f), typeof(g), LinearAlgebra.UniformScaling{Bool}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing}, typeof(g), Base.Pairs{Symbol, Union{}, Tuple{}, NamedTuple{(), Tuple{}}}, Nothing}, isadapt::Bool; kwargs::Base.Pairs{Symbol, Any, Tuple{Symbol, Symbol, Symbol}, NamedTuple{(:u0, :p, :dt), Tuple{Float64, SciMLBase.NullParameters, Float64}}})
   @ DiffEqBase C:\Users\accou\.julia\dev\DiffEqBase\src\solve.jl:388
 [3] solve_up(prob::SDEProblem{Float64, Tuple{Float64, Float64}, true, SciMLBase.NullParameters, Nothing, SDEFunction{true, typeof(f), typeof(g), LinearAlgebra.UniformScaling{Bool}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing}, typeof(g), Base.Pairs{Symbol, Union{}, Tuple{}, NamedTuple{(), Tuple{}}}, Nothing}, sensealg::Nothing, u0::Float64, p::SciMLBase.NullParameters, args::EM{true}; kwargs::Base.Pairs{Symbol, Float64, Tuple{Symbol}, NamedTuple{(:dt,), Tuple{Float64}}})
   @ DiffEqBase C:\Users\accou\.julia\dev\DiffEqBase\src\solve.jl:313
 [4] solve(prob::SDEProblem{Float64, Tuple{Float64, Float64}, true, SciMLBase.NullParameters, Nothing, SDEFunction{true, typeof(f), typeof(g), LinearAlgebra.UniformScaling{Bool}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing}, typeof(g), Base.Pairs{Symbol, Union{}, Tuple{}, NamedTuple{(), Tuple{}}}, Nothing}, args::EM{true}; sensealg::Nothing, u0::Nothing, p::Nothing, kwargs::Base.Pairs{Symbol, Float64, Tuple{Symbol}, NamedTuple{(:dt,), Tuple{Float64}}})
   @ DiffEqBase C:\Users\accou\.julia\dev\DiffEqBase\src\solve.jl:299
 [5] top-level scope
   @ c:\Users\accou\OneDrive\Computer\Desktop\test.jl:19

SimpleDiffEq.jl is by definition not a standard differential equation solver library, and has overly simplified implementations for very specific purposes. For that reason, it doesn't do the same error catching here, though we should think about whether it should be linked into that system in the future.