0-element Vector{Base.Stacktraces.StackFrame}

[ChrisRackauckas]

# DiffEqBase#diffcache
# OrdinaryDiffEq#precompile

using OrdinaryDiffEq, SnoopCompile
function lorenz(du,u,p,t)
 du[1] = 10.0(u[2]-u[1])
 du[2] = u[1]*(28.0-u[3]) - u[2]
 du[3] = u[1]*u[2] - (8/3)*u[3]
end
u0 = [1.0;0.0;0.0]
tspan = (0.0,100.0)
prob = ODEProblem(OrdinaryDiffEq.lorenz,u0,tspan)
alg = Tsit5()
tinf = @snoopi_deep solve(prob,alg)
itrigs = inference_triggers(tinf)
itrig = itrigs[13]
ascend(itrig)

julia> itrig = itrigs[13]
Inference triggered to call perform_step!(::OrdinaryDiffEq.ODEIntegrator{Tsit5, true, Vector{Float64}, Nothing, Float64, SciMLBase.NullParameters, Float64, Float64, Float64, Float64, Vector{Vector{Float64}}, ODESolution{Float64, 2, Vector{Vector{Float64}}, Nothing, Nothing, Vector{Float64}, Vector{Vector{Vector{Float64}}}, ODEProblem{Vector{Float64}, Tuple{Float64, Float64}, true, SciMLBase.NullParameters, ODEFunction{true, typeof(OrdinaryDiffEq.lorenz), 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}, Tsit5, OrdinaryDiffEq.InterpolationData{ODEFunction{true, typeof(OrdinaryDiffEq.lorenz), LinearAlgebra.UniformScaling{Bool}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing}, Vector{Vector{Float64}}, Vector{Float64}, Vector{Vector{Vector{Float64}}}, OrdinaryDiffEq.Tsit5Cache{Vector{Float64}, Vector{Float64}, Vector{Float64}, OrdinaryDiffEq.Tsit5ConstantCache{Float64, Float64}}}, DiffEqBase.DEStats}, ODEFunction{true, typeof(OrdinaryDiffEq.lorenz), LinearAlgebra.UniformScaling{Bool}, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, Nothing, typeof(SciMLBase.DEFAULT_OBSERVED), Nothing}, OrdinaryDiffEq.Tsit5Cache{Vector{Float64}, Vector{Float64}, Vector{Float64}, OrdinaryDiffEq.Tsit5ConstantCache{Float64, Float64}}, OrdinaryDiffEq.DEOptions{Float64, Float64, Float64, Float64, PIController{Rational{Int64}}, typeof(DiffEqBase.ODE_DEFAULT_NORM), typeof(LinearAlgebra.opnorm), Nothing, CallbackSet{Tuple{}, Tuple{}}, typeof(DiffEqBase.ODE_DEFAULT_ISOUTOFDOMAIN), typeof(DiffEqBase.ODE_DEFAULT_PROG_MESSAGE), typeof(DiffEqBase.ODE_DEFAULT_UNSTABLE_CHECK), DataStructures.BinaryMinHeap{Float64}, DataStructures.BinaryMinHeap{Float64}, Nothing, Nothing, Int64, Tuple{}, Tuple{}, Tuple{}}, Vector{Float64}, Float64, Nothing, OrdinaryDiffEq.DefaultInit}, ::OrdinaryDiffEq.Tsit5Cache{Vector{Float64}, Vector{Float64}, Vector{Float64}, OrdinaryDiffEq.Tsit5ConstantCache{Float64, Float64}}, ::Bool) called from toplevel

julia> ascend(itrig)
ERROR: BoundsError: attempt to access 0-element Vector{Base.StackTraces.StackFrame} at index [0]
Stacktrace:
 [1] getindex
   @ .\array.jl:801 [inlined]
 [2] callstring(io::IOBuffer, sfs::Vector{Base.StackTraces.StackFrame})
   @ Cthulhu C:\Users\accou\.julia\packages\Cthulhu\wsvdB\src\backedges.jl:104
 [3] treelist!(parent::FoldingTrees.Node{Cthulhu.Data{Core.MethodInstance}}, io::IOBuffer, mi::InferenceTrigger, indent::String, visited::Base.IdSet{Core.MethodInstance})
   @ Cthulhu C:\Users\accou\.julia\packages\Cthulhu\wsvdB\src\backedges.jl:125
 [4] treelist(mi::InferenceTrigger)
   @ Cthulhu C:\Users\accou\.julia\packages\Cthulhu\wsvdB\src\backedges.jl:118
 [5] ascend(mi::InferenceTrigger; kwargs::Base.Iterators.Pairs{Union{}, Union{}, Tuple{}, NamedTuple{(), Tuple{}}})
   @ Cthulhu C:\Users\accou\.julia\packages\Cthulhu\wsvdB\src\Cthulhu.jl:285
 [6] ascend(mi::InferenceTrigger)
   @ Cthulhu C:\Users\accou\.julia\packages\Cthulhu\wsvdB\src\Cthulhu.jl:285
 [7] top-level scope
   @ REPL[17]:1

@timholy

[ChrisRackauckas]

New branches:

# DiffEqBase#cthulhu
# OrdinaryDiffEq#cthulhu

using OrdinaryDiffEq, SnoopCompile
function lorenz(du,u,p,t)
 du[1] = 10.0(u[2]-u[1])
 du[2] = u[1]*(28.0-u[3]) - u[2]
 du[3] = u[1]*u[2] - (8/3)*u[3]
end
u0 = [1.0;0.0;0.0]
tspan = (0.0,100.0)
prob = ODEProblem(OrdinaryDiffEq.lorenz,u0,tspan)
alg = Tsit5()
tinf = @snoopi_deep solve(prob,alg)
itrigs = inference_triggers(tinf)
itrig = itrigs[11]
ascend(itrig)