fix: allow passing guesses to linearization_function

Author: AayushSabharwal

src/linearization.jl

@@ -41,6 +41,7 @@ function linearization_function(sys::AbstractSystem, inputs,
         initialization_solver_alg = TrustRegion(),
         eval_expression = false, eval_module = @__MODULE__,
         warn_initialize_determined = true,
+        guesses = Dict(),
         kwargs...)
     op = Dict(op)
     inputs isa AbstractVector || (inputs = [inputs])
@@ -66,11 +67,8 @@ function linearization_function(sys::AbstractSystem, inputs,
         initializealg = initialize ? OverrideInit() : NoInit()
     end
 
-    fun, u0, p = process_SciMLProblem(
-        ODEFunction{true, SciMLBase.FullSpecialize}, sys, op, p;
-        t = 0.0, build_initializeprob = initializealg isa OverrideInit,
-        allow_incomplete = true, algebraic_only = true)
-    prob = ODEProblem(fun, u0, (nothing, nothing), p)
+    prob = ODEProblem{true, SciMLBase.FullSpecialize}(sys, op, (nothing, nothing), p; allow_incomplete = true, algebraic_only = true, guesses)
+    u0 = state_values(prob)
 
     ps = parameters(sys)
     h = build_explicit_observed_function(sys, outputs; eval_expression, eval_module)

test/downstream/linearize.jl

@@ -317,12 +317,14 @@ matrices = linfun([1.0], Dict(p => 3.0), 1.0)
     @test matrices.f_u[] == 3.0
 end
 
-@testset "Issue #2941" begin
-    @variables x(t) y(t) [guess = 1.0]
+@testset "Issue #2941 and #3400" begin
+    @variables x(t) y(t)
     @parameters p
     eqs = [0 ~ x * log(y) - p]
     @named sys = ODESystem(eqs, t; defaults = [p => 1.0])
     sys = complete(sys)
-    @test_nowarn linearize(
+    @test_throws ModelingToolkit.MissingVariablesError linearize(
         sys, [x], []; op = Dict(x => 1.0), allow_input_derivatives = true)
+    @test_nowarn linearize(
+        sys, [x], []; op = Dict(x => 1.0), guesses = Dict(y => 1.0), allow_input_derivatives = true)
 end