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fix: fix incorrect incidence after tearing some differential equations #3994

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Merged
merged 3 commits into from
Oct 29, 2025
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fix: fix incorrect incidence after tearing some differential equations #3994

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1cb6b6a
fix: fix incorrect incidence graph after tearing
AayushSabharwal Oct 28, 2025
1d6d6ca
fix: re-enable usage of `torn_system_jacobian_sparsity` in `jacobian_…
AayushSabharwal Oct 28, 2025
091e68e
test: test correct incidence after simplification
AayushSabharwal Oct 28, 2025
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6 changes: 6 additions & 0 deletions src/structural_transformation/symbolics_tearing.jl
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Expand Up @@ -773,8 +773,14 @@ function codegen_equation!(eg::EquationGenerator,
dx = D(simplify_shifts(fullvars[lv]))

neweq = make_differential_equation(var, dx, eq, total_sub)
# We will add `neweq.lhs` to `total_sub`, so any equation involving it won't be
# incident on it. Remove the edges incident on `iv` from the graph, and add
# the replacement vertices from `ieq` so that the incidence is still correct.
for e in 𝑑neighbors(graph, iv)
e == ieq && continue
for v in 𝑠neighbors(graph, ieq)
add_edge!(graph, e, v)
end
rem_edge!(graph, e, iv)
end

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5 changes: 2 additions & 3 deletions src/systems/codegen.jl
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Expand Up @@ -455,9 +455,8 @@ end
Return the sparsity pattern of the jacobian of `sys` as a matrix.
"""
function jacobian_sparsity(sys::System)
# disable to fix https://github.com/SciML/ModelingToolkit.jl/issues/3871
#sparsity = torn_system_jacobian_sparsity(sys)
#sparsity === nothing || return sparsity
sparsity = torn_system_jacobian_sparsity(sys)
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how is this related?

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This is how jacobian_sparsity was prior to #3871. That PR commented out the use of torn_system_jacobian_sparsity due to incorrect results. This PR fixes torn_system_jacobian_sparsity, which means we can use it again.

sparsity === nothing || return sparsity

Symbolics.jacobian_sparsity([eq.rhs for eq in full_equations(sys)],
[dv for dv in unknowns(sys)])
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6 changes: 6 additions & 0 deletions test/jacobiansparsity.jl
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Expand Up @@ -153,4 +153,10 @@ end
prob = ODEProblem(sys, [x => 1.0, y => 0.0], (0.0, 1.0); jac = true, sparse = true)
sol = solve(prob, FBDF())
@test SciMLBase.successful_retcode(sol)
ts = ModelingToolkit.get_tearing_state(sys)
for ieq in 1:2
vars1 = ts.fullvars[ModelingToolkit.BipartiteGraphs.𝑠neighbors(ts.structure.graph, ieq)]
vars2 = ModelingToolkit.vars(equations(sys)[ieq])
@test issetequal(vars1, vars2)
end
end
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