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Generalize symbolic indexing of ODE/DDE to multivariate variables #3738

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Generalize symbolic indexing of ODE/DDE to multivariate variables #3738

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e2ca4b2
Generalize getsym of DDEs to multivariate variables
hersle Jun 14, 2025
3539901
Test symbolic indexing of DDE with multivariate variable
hersle Jun 14, 2025
a731add
Test symbolic indexing of ODE with multivariate variable
hersle Jun 14, 2025
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4 changes: 2 additions & 2 deletions src/systems/abstractsystem.jl
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Original file line number Diff line number Diff line change
Expand Up @@ -320,8 +320,8 @@ for traitT in [
elseif is_timeseries_parameter(sys, s)
push!(ts_idxs, timeseries_parameter_index(sys, s).timeseries_idx)
elseif is_time_dependent(sys) && iscall(s) && issym(operation(s)) &&
is_variable(sys, operation(s)(get_iv(sys)))
# DDEs case, to detect x(t - k)
is_variable(sys, operation(s)(get_iv(sys), arguments(s)[2:end]...))
# DDEs case, to detect x(t - k), and x(t - k, arg2, arg3, ...)
push!(ts_idxs, ContinuousTimeseries())
else
if has_index_cache(sys) && (ic = get_index_cache(sys)) !== nothing
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5 changes: 4 additions & 1 deletion test/dde.jl
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Expand Up @@ -76,8 +76,9 @@ prob = SDDEProblem(hayes_modelf, hayes_modelg, [1.0], h, tspan, pmul;
constant_lags = (pmul[1],));
sol = solve(prob, RKMil(), seed = 100)

@variables x(..) delx(t)
@parameters a=-4.0 b=-2.0 c=10.0 α=-1.3 β=-1.2 γ=1.1
@variables x(..)
@variables delx(t, a, b, c, α, β, γ) # equivalent to just delx(t)
@brownians η
τ = 1.0
eqs = [D(x(t)) ~ a * x(t) + b * x(t - τ) + c + (α * x(t) + γ) * η, delx ~ x(t - τ)]
Expand All @@ -88,6 +89,8 @@ eqs = [D(x(t)) ~ a * x(t) + b * x(t - τ) + c + (α * x(t) + γ) * η, delx ~ x(
@test equations(sys) == [D(x(t)) ~ a * x(t) + b * x(t - τ) + c]
@test isequal(ModelingToolkit.get_noise_eqs(sys), [α * x(t) + γ;;])
prob_mtk = SDDEProblem(sys, [x(t) => 1.0 + t], tspan; constant_lags = (τ,));
@test prob_mtk[delx] isa Float64
@test prob_mtk[x(t - τ)] isa Float64
@test_nowarn sol_mtk = solve(prob_mtk, RKMil(), seed = 100)

prob_sa = SDDEProblem(
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10 changes: 10 additions & 0 deletions test/odesystem.jl
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Expand Up @@ -1573,3 +1573,13 @@ end
prob = ODEProblem(sys, [x => 1.0], (0.0, 1.0))
@test prob.problem_type == "A"
end

# https://github.com/SciML/ModelingToolkit.jl/issues/3737
@testset "ODE with multivariate variables" begin
@parameters k
@variables x(t, k) y(t, k) # equivalent to x(t) and y(t)
@mtkbuild sys = System([D(x) ~ 0, y ~ x + 1], t)
prob = ODEProblem(sys, [x => 0.0], (0.0, 1.0))
@test prob[x] == 0.0 # unknown
@test prob[y] == 1.0 # observed
end
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