Bug when using auto-algorithm selection with continious callbacks

[MasonProtter]

Describe the bug 🐞

Trying to use automatic algorithm selection together with continious callbacks is erroring. Here's the example from https://docs.sciml.ai/DiffEqDocs/stable/features/callback_functions/#Example-1:-Bouncing-Ball but with sol = solve(prob, Tsit5(), callback = cb) replaced with solve(prob; callback = cb) (works fine if Tsit5() is specified):

Minimal Reproducible Example 👇

using DifferentialEquations
function f(du, u, p, t)
    du[1] = u[2]
    du[2] = -p
end
function condition(u, t, integrator) # Event when condition(u,t,integrator) == 0
    u[1]
end
function affect!(integrator)
    integrator.u[2] = -integrator.u[2]
end
let
    cb = ContinuousCallback(condition, affect!)
    u0 = [50.0, 0.0]
    tspan = (0.0, 15.0)
    p = 9.8
    prob = ODEProblem(f, u0, tspan, p)
    sol = solve(prob; callback = cb)
end

Error & Stacktrace ⚠️

ERROR: MethodError: no method matching get_tmp_cache(::OrdinaryDiffEq.ODEIntegrator{…}, ::CompositeAlgorithm{…}, ::OrdinaryDiffEq.DefaultCache{…})

Closest candidates are:
  get_tmp_cache(::StochasticDiffEq.SDEIntegrator, ::Any, ::Any)
   @ StochasticDiffEq ~/.julia/packages/StochasticDiffEq/aR0ZE/src/integrators/integrator_interface.jl:54
  get_tmp_cache(::Any, ::OrdinaryDiffEqAlgorithm, ::OrdinaryDiffEq.OrdinaryDiffEqMutableCache)
   @ OrdinaryDiffEq ~/.julia/packages/OrdinaryDiffEq/YXsFS/src/integrators/integrator_interface.jl:125
  get_tmp_cache(::Any, ::OrdinaryDiffEqAlgorithm, ::OrdinaryDiffEq.OrdinaryDiffEqConstantCache)
   @ OrdinaryDiffEq ~/.julia/packages/OrdinaryDiffEq/YXsFS/src/integrators/integrator_interface.jl:118
  ...

Stacktrace:
  [1] get_tmp_cache
    @ ~/.julia/packages/OrdinaryDiffEq/YXsFS/src/integrators/integrator_interface.jl:111 [inlined]
  [2] get_tmp(integrator::OrdinaryDiffEq.ODEIntegrator{…}, callback::ContinuousCallback{…})
    @ DiffEqBase ~/.julia/packages/DiffEqBase/yM6LF/src/callbacks.jl:60
  [3] get_condition(integrator::OrdinaryDiffEq.ODEIntegrator{…}, callback::ContinuousCallback{…}, abst::Float64)
    @ DiffEqBase ~/.julia/packages/DiffEqBase/yM6LF/src/callbacks.jl:74
  [4] determine_event_occurance
    @ ~/.julia/packages/DiffEqBase/yM6LF/src/callbacks.jl:331 [inlined]
  [5] find_callback_time(integrator::OrdinaryDiffEq.ODEIntegrator{…}, callback::ContinuousCallback{…}, counter::Int64)
    @ DiffEqBase ~/.julia/packages/DiffEqBase/yM6LF/src/callbacks.jl:401
  [6] macro expansion
    @ ~/.julia/packages/DiffEqBase/yM6LF/src/callbacks.jl:132 [inlined]
  [7] find_first_continuous_callback(integrator::OrdinaryDiffEq.ODEIntegrator{…}, callbacks::Tuple{…})
    @ DiffEqBase ~/.julia/packages/DiffEqBase/yM6LF/src/callbacks.jl:127
  [8] find_first_continuous_callback
    @ ~/.julia/packages/DiffEqBase/yM6LF/src/callbacks.jl:125 [inlined]
  [9] handle_callbacks!(integrator::OrdinaryDiffEq.ODEIntegrator{…})
    @ OrdinaryDiffEq ~/.julia/packages/OrdinaryDiffEq/YXsFS/src/integrators/integrator_utils.jl:332
 [10] _loopfooter!(integrator::OrdinaryDiffEq.ODEIntegrator{…})
    @ OrdinaryDiffEq ~/.julia/packages/OrdinaryDiffEq/YXsFS/src/integrators/integrator_utils.jl:254
 [11] loopfooter!
    @ ~/.julia/packages/OrdinaryDiffEq/YXsFS/src/integrators/integrator_utils.jl:207 [inlined]
 [12] solve!(integrator::OrdinaryDiffEq.ODEIntegrator{…})
    @ OrdinaryDiffEq ~/.julia/packages/OrdinaryDiffEq/YXsFS/src/solve.jl:552
 [13] #__solve#799
    @ ~/.julia/packages/OrdinaryDiffEq/YXsFS/src/solve.jl:7 [inlined]
 [14] __solve
    @ ~/.julia/packages/OrdinaryDiffEq/YXsFS/src/solve.jl:1 [inlined]
 [15] solve_call(_prob::ODEProblem{…}, args::CompositeAlgorithm{…}; merge_callbacks::Bool, kwargshandle::Nothing, kwargs::@Kwargs{…})
    @ DiffEqBase ~/.julia/packages/DiffEqBase/yM6LF/src/solve.jl:612
 [16] solve_call
    @ ~/.julia/packages/DiffEqBase/yM6LF/src/solve.jl:569 [inlined]
 [17] solve_up(prob::ODEProblem{…}, sensealg::Nothing, u0::Vector{…}, p::Float64, args::CompositeAlgorithm{…}; kwargs::@Kwargs{…})
    @ DiffEqBase ~/.julia/packages/DiffEqBase/yM6LF/src/solve.jl:1080
 [18] solve_up
    @ ~/.julia/packages/DiffEqBase/yM6LF/src/solve.jl:1066 [inlined]
 [19] #solve#51
    @ ~/.julia/packages/DiffEqBase/yM6LF/src/solve.jl:1003 [inlined]
 [20] solve
    @ ~/.julia/packages/DiffEqBase/yM6LF/src/solve.jl:993 [inlined]
 [21] #__solve#804
    @ ~/.julia/packages/OrdinaryDiffEq/YXsFS/src/solve.jl:541 [inlined]
 [22] __solve
    @ ~/.julia/packages/OrdinaryDiffEq/YXsFS/src/solve.jl:540 [inlined]
 [23] #__solve#72
    @ ~/.julia/packages/DiffEqBase/yM6LF/src/solve.jl:1394 [inlined]
 [24] __solve
    @ ~/.julia/packages/DiffEqBase/yM6LF/src/solve.jl:1386 [inlined]
 [25] solve_call(::ODEProblem{…}; merge_callbacks::Bool, kwargshandle::Nothing, kwargs::@Kwargs{…})
    @ DiffEqBase ~/.julia/packages/DiffEqBase/yM6LF/src/solve.jl:612
 [26] solve_up(::ODEProblem{…}, ::Nothing, ::Vector{…}, ::Float64; kwargs::@Kwargs{…})
    @ DiffEqBase ~/.julia/packages/DiffEqBase/yM6LF/src/solve.jl:1072
 [27] solve_up
    @ ~/.julia/packages/DiffEqBase/yM6LF/src/solve.jl:1066 [inlined]
 [28] solve(::ODEProblem{…}; sensealg::Nothing, u0::Nothing, p::Nothing, wrap::Val{…}, kwargs::@Kwargs{…})
    @ DiffEqBase ~/.julia/packages/DiffEqBase/yM6LF/src/solve.jl:1003
 [29] top-level scope
    @ REPL[3]:18
Some type information was truncated. Use `show(err)` to see complete types.

Environment (please complete the following information):

• Output of using Pkg; Pkg.status()

Status `/tmp/jl_0eoehB/Project.toml`
  [0c46a032] DifferentialEquations v7.13.0

• Output of using Pkg; Pkg.status(; mode = PKGMODE_MANIFEST)

Status `/tmp/jl_0eoehB/Manifest.toml`
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  [1dea7af3] OrdinaryDiffEq v6.78.0
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Info Packages marked with ⌃ and ⌅ have new versions available. Those with ⌃ may be upgradable, but those with ⌅ are restricted by compatibility constraints from upgrading. To see why use `status --outdated -m`

• Output of versioninfo()

Julia Version 1.10.3
Commit 0b4590a5507 (2024-04-30 10:59 UTC)
Build Info:
  Official https://julialang.org/ release
Platform Info:
  OS: Linux (x86_64-linux-gnu)
  CPU: 12 × AMD Ryzen 5 5600X 6-Core Processor
  WORD_SIZE: 64
  LIBM: libopenlibm
  LLVM: libLLVM-15.0.7 (ORCJIT, znver3)
Threads: 6 default, 0 interactive, 3 GC (on 12 virtual cores)
Environment:
  JULIA_NUM_THREADS = 6

Additional context

Add any other context about the problem here.

[ChrisRackauckas]

The new defaulting algorithm needs to have a dispatch on the tmp cache to forward it down to the solution for the dispatch for the current chosen default. In fact, we should make sure that the whole interface here is covered:

https://github.com/SciML/OrdinaryDiffEq.jl/blob/master/src/integrators/integrator_interface.jl

We should add the new default algorithm to https://github.com/SciML/OrdinaryDiffEq.jl/blob/master/test/integrators/ode_cache_tests.jl and make it pass this set of tests.

[oscardssmith]

Good catch! This should be fixed by https://github.com/SciML/OrdinaryDiffEq.jl/pull/2225