Trouble using Koopman.jl #64
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Do you have an MWE? |
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By MWE, you mean Minimal working example?
On Tue, Jul 26, 2022 at 3:33 AM Christopher Rackauckas < ***@***.***> wrote:
Do you have an MWE?
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Regards,
Lakshay Arora
PhD Student, Aerospace Engineering,
Carleton University
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yes |
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I used the example already given in the package's ReadMe file. The example
is this one:
*using DiffEqUncertainty, OrdinaryDiffEq, Distributions
function f!(du,u,p,t)
du[1] = p[1]*u[1] - p[2]*u[1]*u[2] #prey
du[2] = -p[3]*u[2] + p[4]*u[1]*u[2] #predator
end
tspan = (0.0,10.0)
u0 = [1.0;1.0]
p = [1.5,1.0,3.0,1.0]
prob = ODEProblem(f!,u0,tspan,p)
u0_dist = [1.0, Uniform(0.8, 1.1)]
p_dist = [1.5,1.0,3.0,truncated(Normal(1.0,.1),.6, 1.4)]
g(sol) = sol[1,end]
expectation(g, prob, u0_dist, p_dist, MonteCarlo(), Tsit5();
trajectories = 100_000) ------> This one is working
expectation(g, prob, u0_dist, p_dist, Koopman(), Tsit5()) -------->
This one is not*
…On Tue, Jul 26, 2022 at 1:14 PM Christopher Rackauckas < ***@***.***> wrote:
yes
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Regards,
Lakshay Arora
PhD Student, Aerospace Engineering,
Carleton University
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I have the same error as @lakshaya17, the example in the readme no longer works. |
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Should be fixed by #63 |
Its working now. Thank you so much. |
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I was running my code with Koopman.jl the other day and I got the following issue. Before when I ran my code, it was working perfectly fine.
MethodError: no method matching init(::IntegralProblem{false, Vector{Float64}, DiffEqUncertainty.var"#10#23"{DiffEqUncertainty.var"#20#33", DiffEqUncertainty.var"#21#34", typeof(loss), DiffEqUncertainty.var"#6#7"{Base.Iterators.Pairs{Symbol, CallbackSet{Tuple{ContinuousCallback{typeof(ground_condition), typeof(ground_affect!), typeof(ground_affect!), typeof(SciMLBase.INITIALIZE_DEFAULT), typeof(SciMLBase.FINALIZE_DEFAULT), Float64, Int64, Rational{Int64}, Nothing, Int64}, ContinuousCallback{typeof(stop_condition), typeof(terminate!), typeof(terminate!), typeof(SciMLBase.INITIALIZE_DEFAULT), typeof(SciMLBase.FINALIZE_DEFAULT), Float64, Int64, Rational{Int64}, Nothing, Int64}}, Tuple{}}, Tuple{Symbol}, NamedTuple{(:callback,), Tuple{CallbackSet{Tuple{ContinuousCallback{typeof(ground_condition), typeof(ground_affect!), typeof(ground_affect!), typeof(SciMLBase.INITIALIZE_DEFAULT), typeof(SciMLBase.FINALIZE_DEFAULT), Float64, Int64, Rational{Int64}, Nothing, Int64}, ContinuousCallback{typeof(stop_condition), typeof(terminate!), typeof(terminate!), typeof(SciMLBase.INITIALIZE_DEFAULT), typeof(SciMLBase.FINALIZE_DEFAULT), Float64, Int64, Rational{Int64}, Nothing, Int64}}, Tuple{}}}}}, ODEProblem{Vector{Float64}, Tuple{Float64, Float64}, true, Vector{Float64}, ODEFunction{true, typeof(ball!), LinearAlgebra.UniformScaling{Bool}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing}, Base.Iterators.Pairs{Union{}, Union{}, Tuple{}, NamedTuple{(), Tuple{}}}, SciMLBase.StandardODEProblem}, Tuple{Tsit5{typeof(OrdinaryDiffEq.trivial_limiter!), typeof(OrdinaryDiffEq.trivial_limiter!), Static.False}}}, Vector{Float64}, Vector{Any}, Vector{Bool}, Int64}, Vector{Float64}, Vector{Float64}, Base.Iterators.Pairs{Union{}, Union{}, Tuple{}, NamedTuple{(), Tuple{}}}}, ::HCubatureJL; reltol=1.0e-5, abstol=0.01, maxiters=1000000)
Closest candidates are:
init(::SciMLBase.AbstractDEProblem, ::Any...; kwargshandle, kwargs...) at C:\Users\Lakshay Arora.julia\packages\DiffEqBase\S7V8q\src\solve.jl:191
Stacktrace:
[1] solve(::IntegralProblem{false, Vector{Float64}, DiffEqUncertainty.var"#10#23"{DiffEqUncertainty.var"#20#33", DiffEqUncertainty.var"#21#34", typeof(loss), DiffEqUncertainty.var"#6#7"{Base.Iterators.Pairs{Symbol, CallbackSet{Tuple{ContinuousCallback{typeof(ground_condition), typeof(ground_affect!), typeof(ground_affect!), typeof(SciMLBase.INITIALIZE_DEFAULT), typeof(SciMLBase.FINALIZE_DEFAULT), Float64, Int64, Rational{Int64}, Nothing, Int64}, ContinuousCallback{typeof(stop_condition), typeof(terminate!), typeof(terminate!), typeof(SciMLBase.INITIALIZE_DEFAULT), typeof(SciMLBase.FINALIZE_DEFAULT), Float64, Int64, Rational{Int64}, Nothing, Int64}}, Tuple{}}, Tuple{Symbol}, NamedTuple{(:callback,), Tuple{CallbackSet{Tuple{ContinuousCallback{typeof(ground_condition), typeof(ground_affect!), typeof(ground_affect!), typeof(SciMLBase.INITIALIZE_DEFAULT), typeof(SciMLBase.FINALIZE_DEFAULT), Float64, Int64, Rational{Int64}, Nothing, Int64}, ContinuousCallback{typeof(stop_condition), typeof(terminate!), typeof(terminate!), typeof(SciMLBase.INITIALIZE_DEFAULT), typeof(SciMLBase.FINALIZE_DEFAULT), Float64, Int64, Rational{Int64}, Nothing, Int64}}, Tuple{}}}}}, ODEProblem{Vector{Float64}, Tuple{Float64, Float64}, true, Vector{Float64}, ODEFunction{true, typeof(ball!), LinearAlgebra.UniformScaling{Bool}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing}, Base.Iterators.Pairs{Union{}, Union{}, Tuple{}, NamedTuple{(), Tuple{}}}, SciMLBase.StandardODEProblem}, Tuple{Tsit5{typeof(OrdinaryDiffEq.trivial_limiter!), typeof(OrdinaryDiffEq.trivial_limiter!), Static.False}}}, Vector{Float64}, Vector{Any}, Vector{Bool}, Int64}, Vector{Float64}, Vector{Float64}, Base.Iterators.Pairs{Union{}, Union{}, Tuple{}, NamedTuple{(), Tuple{}}}}, ::Vararg{Any, N} where N; kwargs::Base.Iterators.Pairs{Symbol, Real, Tuple{Symbol, Symbol, Symbol}, NamedTuple{(:reltol, :abstol, :maxiters), Tuple{Float64, Float64, Int64}}})
@ CommonSolve C:\Users\Lakshay Arora.julia\packages\CommonSolve\TGRvG\src\CommonSolve.jl:23
[2] expectation(g::typeof(loss), prob::ODEProblem{Vector{Float64}, Tuple{Float64, Float64}, true, Vector{Float64}, ODEFunction{true, typeof(ball!), LinearAlgebra.UniformScaling{Bool}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing}, Base.Iterators.Pairs{Union{}, Union{}, Tuple{}, NamedTuple{(), Tuple{}}}, SciMLBase.StandardODEProblem}, u0::Vector{Float64}, p::Vector{Any}, expalg::Koopman, args::Tsit5{typeof(OrdinaryDiffEq.trivial_limiter!), typeof(OrdinaryDiffEq.trivial_limiter!), Static.False}; u0_CoV::DiffEqUncertainty.var"#20#33", p_CoV::DiffEqUncertainty.var"#21#34", maxiters::Int64, batch::Int64, quadalg::HCubatureJL, ireltol::Float64, iabstol::Float64, nout::Int64, kwargs::Base.Iterators.Pairs{Symbol, CallbackSet{Tuple{ContinuousCallback{typeof(ground_condition), typeof(ground_affect!), typeof(ground_affect!), typeof(SciMLBase.INITIALIZE_DEFAULT), typeof(SciMLBase.FINALIZE_DEFAULT), Float64, Int64, Rational{Int64}, Nothing, Int64}, ContinuousCallback{typeof(stop_condition), typeof(terminate!), typeof(terminate!), typeof(SciMLBase.INITIALIZE_DEFAULT), typeof(SciMLBase.FINALIZE_DEFAULT), Float64, Int64, Rational{Int64}, Nothing, Int64}}, Tuple{}}, Tuple{Symbol}, NamedTuple{(:callback,), Tuple{CallbackSet{Tuple{ContinuousCallback{typeof(ground_condition), typeof(ground_affect!), typeof(ground_affect!), typeof(SciMLBase.INITIALIZE_DEFAULT), typeof(SciMLBase.FINALIZE_DEFAULT), Float64, Int64, Rational{Int64}, Nothing, Int64}, ContinuousCallback{typeof(stop_condition), typeof(terminate!), typeof(terminate!), typeof(SciMLBase.INITIALIZE_DEFAULT), typeof(SciMLBase.FINALIZE_DEFAULT), Float64, Int64, Rational{Int64}, Nothing, Int64}}, Tuple{}}}}})
@ DiffEqUncertainty C:\Users\Lakshay Arora.julia\packages\DiffEqUncertainty\03ndV\src\koopman.jl:104
[3] top-level scope
@ In[15]:4
[4] eval
@ .\boot.jl:360 [inlined]
[5] include_string(mapexpr::typeof(REPL.softscope), mod::Module, code::String, filename::String)
@ Base .\loading.jl:1116
I have been racking my brain with this issue. Please help.
Also, I am getting the same issue while running the example code as well. I have tried updating the packages as well.
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