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remove broken tests
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@TorkelE
TorkelE committed Jul 26, 2024
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332 changes: 0 additions & 332 deletions test/sciml_problem_inputs.jl
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Expand Up @@ -118,43 +118,6 @@ let
end
end

# Perform SDE simulations (singular and ensemble).
let
# Creates normal and ensemble problems.
base_sprob = SDEProblem(ssys, u0_alts[1], tspan, p_alts[1])
base_sol = solve(base_sprob, ImplicitEM(); seed, saveat = 1.0)
base_eprob = EnsembleProblem(base_sprob)
base_esol = solve(base_eprob, ImplicitEM(); seed, trajectories = 2, saveat = 1.0)

# Simulates problems for all input types, checking that identical solutions are found.
@test_broken false # first remake in subsequent test yields a `ERROR: type Nothing has no field portion`.
for u0 in u0_alts, p in p_alts
# sprob = remake(base_sprob; u0, p)
# @test base_sol == solve(sprob, ImplicitEM(); seed, saveat = 1.0)
# eprob = remake(base_eprob; u0, p)
# @test base_esol == solve(eprob, ImplicitEM(); seed, trajectories = 2, saveat = 1.0)
end
end

# Perform jump simulations (singular and ensemble).
let
# Creates normal and ensemble problems.
base_dprob = DiscreteProblem(jsys, u0_alts[1], tspan, p_alts[1])
base_jprob = JumpProblem(jsys, base_dprob, Direct(); rng)
base_sol = solve(base_jprob, SSAStepper(); seed, saveat = 1.0)
base_eprob = EnsembleProblem(base_jprob)
base_esol = solve(base_eprob, SSAStepper(); seed, trajectories = 2, saveat = 1.0)

# Simulates problems for all input types, checking that identical solutions are found.
@test_broken false # first remake in subsequent test yields a `ERROR: type Nothing has no field portion`.
for u0 in u0_alts, p in p_alts
# jprob = remake(base_jprob; u0, p)
# @test base_sol == solve(base_jprob, SSAStepper(); seed, saveat = 1.0)
# eprob = remake(base_eprob; u0, p)
# @test base_esol == solve(eprob, SSAStepper(); seed, trajectories = 2, saveat = 1.0)
end
end

# Solves a nonlinear problem (EnsembleProblems are not possible for these).
let
base_nlprob = NonlinearProblem(nsys, u0_alts[1], p_alts[1])
Expand Down Expand Up @@ -183,298 +146,3 @@ let
@test base_esol == solve(eprob, DynamicSS(Tsit5()); trajectories = 2)
end
end

### Checks Errors On Faulty Inputs ###

# Checks various erroneous problem inputs, ensuring that these throw errors.
let
# Prepare system components.
@parameters k1 k2 k3
@variables X1(t) X2(t) X3(t)
alg_eqs = [
0 ~ -k1 * X1 + k2 * X2,
0 ~ k1 * X1 - k2 * X2
]
diff_eqs = [
D(X1) ~ -k1 * X1 + k2 * X2,
D(X2) ~ k1 * X1 - k2 * X2
]
noise_eqs = fill(0.01, 2, 2)
jumps = [
MassActionJump(k1, [X1 => 1], [X1 => -1, X2 => 1]),
MassActionJump(k2, [X2 => 1], [X1 => 1, X2 => -1])
]

# Create systems (without structural_simplify, since that might modify systems to affect intended tests).
osys = complete(ODESystem(diff_eqs, t; name = :osys))
ssys = complete(SDESystem(diff_eqs, noise_eqs, t, [X1, X2], [k1, k2]; name = :ssys))
jsys = complete(JumpSystem(jumps, t, [X1, X2], [k1, k2]; name = :jsys))
nsys = complete(NonlinearSystem(alg_eqs; name = :nsys))

# Declares valid initial conditions and parameter values
u0_valid = [X1 => 1, X2 => 2]
ps_valid = [k1 => 0.5, k2 => 0.1]

# Declares invalid initial conditions and parameters. This includes both cases where values are
# missing, or additional ones are given. Includes vector/Tuple/Dict forms.
u0s_invalid = [
# Missing a value.
[X1 => 1],
[osys.X1 => 1],
SA[X1 => 1],
SA[osys.X1 => 1],
Dict([X1 => 1]),
Dict([osys.X1 => 1]),
(X1 => 1),
(osys.X1 => 1),
# Contain an additional value.
[X1 => 1, X2 => 2, X3 => 3],
SA[X1 => 1, X2 => 2, X3 => 3],
Dict([X1 => 1, X2 => 2, X3 => 3]),
(X1 => 1, X2 => 2, X3 => 3)
]
ps_invalid = [
# Missing a value.
[k1 => 1.0],
[osys.k1 => 1.0],
SA[k1 => 1.0],
SA[osys.k1 => 1.0],
Dict([k1 => 1.0]),
Dict([osys.k1 => 1.0]),
(k1 => 1.0),
(osys.k1 => 1.0),
# Contain an additional value.
[k1 => 1.0, k2 => 2.0, k3 => 3.0],
SA[k1 => 1.0, k2 => 2.0, k3 => 3.0],
Dict([k1 => 1.0, k2 => 2.0, k3 => 3.0]),
(k1 => 1.0, k2 => 2.0, k3 => 3.0)
]

# Loops through all potential parameter sets, checking their inputs yield errors.
# Broken tests are due to this issue: https://github.com/SciML/ModelingToolkit.jl/issues/2779
for ps in [[ps_valid]; ps_invalid], u0 in [[u0_valid]; u0s_invalid]
# Handles problems with/without tspan separately. Special check ensuring that valid inputs passes.
for (xsys, XProblem) in zip([osys, ssys, jsys],
[ODEProblem, SDEProblem, DiscreteProblem])
if isequal(ps, ps_valid) && isequal(u0, u0_valid)
XProblem(xsys, u0, (0.0, 1.0), ps)
@test true
else
@test_broken false
continue
@test_throws Exception XProblem(xsys, u0, (0.0, 1.0), ps)
end
end
for (xsys, XProblem) in zip([nsys, osys], [NonlinearProblem, SteadyStateProblem])
if isequal(ps, ps_valid) && isequal(u0, u0_valid)
XProblem(xsys, u0, ps)
@test true
else
@test_broken false
continue
@test_throws Exception XProblem(xsys, u0, ps)
end
end
end
end

### Vector Parameter/Variable Inputs ###

begin
# Declares the model (with vector species/parameters, with/without default values, and observables).
@variables X(t)[1:2] Y(t)[1:2]=[10.0, 20.0] XY(t)[1:2]
@parameters p[1:2] d[1:2]=[0.2, 0.5]
alg_eqs = [
0 ~ p[1] - d[1] * X[1],
0 ~ p[2] - d[2] * X[2],
0 ~ p[1] - d[1] * Y[1],
0 ~ p[2] - d[2] * Y[2]
]
diff_eqs = [
D(X[1]) ~ p[1] - d[1] * X[1],
D(X[2]) ~ p[2] - d[2] * X[2],
D(Y[1]) ~ p[1] - d[1] * Y[1],
D(Y[2]) ~ p[2] - d[2] * Y[2]
]
noise_eqs = fill(0.01, 4, 8)
jumps = [
MassActionJump(p[1], Pair{Symbolics.BasicSymbolic{Real}, Int64}[], [X[1] => 1]),
MassActionJump(p[2], Pair{Symbolics.BasicSymbolic{Real}, Int64}[], [X[2] => 1]),
MassActionJump(d[1], [X[1] => 1], [X[1] => -1]),
MassActionJump(d[2], [X[2] => 1], [X[2] => -1]),
MassActionJump(p[1], Pair{Symbolics.BasicSymbolic{Real}, Int64}[], [Y[1] => 1]),
MassActionJump(p[2], Pair{Symbolics.BasicSymbolic{Real}, Int64}[], [Y[2] => 1]),
MassActionJump(d[1], [Y[1] => 1], [Y[1] => -1]),
MassActionJump(d[2], [Y[2] => 1], [Y[2] => -1])
]
observed = [XY[1] ~ X[1] + Y[1], XY[2] ~ X[2] + Y[2]]

# Create systems (without structural_simplify, since that might modify systems to affect intended tests).
osys = complete(ODESystem(diff_eqs, t; observed, name = :osys))
ssys = complete(SDESystem(
diff_eqs, noise_eqs, t, [X[1], X[2], Y[1], Y[2]], [p, d]; observed, name = :ssys))
jsys = complete(JumpSystem(
jumps, t, [X[1], X[2], Y[1], Y[2]], [p, d]; observed, name = :jsys))
nsys = complete(NonlinearSystem(alg_eqs; observed, name = :nsys))

# Declares various u0 versions (scalarised and vector forms).
u0_alts_vec = [
# Vectors not providing default values.
[X => [1.0, 2.0]],
[X[1] => 1.0, X[2] => 2.0],
[osys.X => [1.0, 2.0]],
[osys.X[1] => 1.0, osys.X[2] => 2.0],
# Vectors providing default values.
[X => [1.0, 2.0], Y => [10.0, 20.0]],
[X[1] => 1.0, X[2] => 2.0, Y[1] => 10.0, Y[2] => 20.0],
[osys.X => [1.0, 2.0], osys.Y => [10.0, 20.0]],
[osys.X[1] => 1.0, osys.X[2] => 2.0, osys.Y[1] => 10.0, osys.Y[2] => 20.0],
# Static vectors not providing default values.
SA[X => [1.0, 2.0]],
SA[X[1] => 1.0, X[2] => 2.0],
SA[osys.X => [1.0, 2.0]],
SA[osys.X[1] => 1.0, osys.X[2] => 2.0],
# Static vectors providing default values.
SA[X => [1.0, 2.0], Y => [10.0, 20.0]],
SA[X[1] => 1.0, X[2] => 2.0, Y[1] => 10.0, Y[2] => 20.0],
SA[osys.X => [1.0, 2.0], osys.Y => [10.0, 20.0]],
SA[osys.X[1] => 1.0, osys.X[2] => 2.0, osys.Y[1] => 10.0, osys.Y[2] => 20.0],
# Dicts not providing default values.
Dict([X => [1.0, 2.0]]),
Dict([X[1] => 1.0, X[2] => 2.0]),
Dict([osys.X => [1.0, 2.0]]),
Dict([osys.X[1] => 1.0, osys.X[2] => 2.0]),
# Dicts providing default values.
Dict([X => [1.0, 2.0], Y => [10.0, 20.0]]),
Dict([X[1] => 1.0, X[2] => 2.0, Y[1] => 10.0, Y[2] => 20.0]),
Dict([osys.X => [1.0, 2.0], osys.Y => [10.0, 20.0]]),
Dict([osys.X[1] => 1.0, osys.X[2] => 2.0, osys.Y[1] => 10.0, osys.Y[2] => 20.0]),
# Tuples not providing default values.
(X => [1.0, 2.0]),
(X[1] => 1.0, X[2] => 2.0),
(osys.X => [1.0, 2.0]),
(osys.X[1] => 1.0, osys.X[2] => 2.0),
# Tuples providing default values.
(X => [1.0, 2.0], Y => [10.0, 20.0]),
(X[1] => 1.0, X[2] => 2.0, Y[1] => 10.0, Y[2] => 20.0),
(osys.X => [1.0, 2.0], osys.Y => [10.0, 20.0]),
(osys.X[1] => 1.0, osys.X[2] => 2.0, osys.Y[1] => 10.0, osys.Y[2] => 20.0)
]

# Declares various ps versions (vector forms only).
p_alts_vec = [
# Vectors not providing default values.
[p => [1.0, 2.0]],
[osys.p => [1.0, 2.0]],
# Vectors providing default values.
[p => [4.0, 5.0], d => [0.2, 0.5]],
[osys.p => [4.0, 5.0], osys.d => [0.2, 0.5]],
# Static vectors not providing default values.
SA[p => [1.0, 2.0]],
SA[osys.p => [1.0, 2.0]],
# Static vectors providing default values.
SA[p => [4.0, 5.0], d => [0.2, 0.5]],
SA[osys.p => [4.0, 5.0], osys.d => [0.2, 0.5]],
# Dicts not providing default values.
Dict([p => [1.0, 2.0]]),
Dict([osys.p => [1.0, 2.0]]),
# Dicts providing default values.
Dict([p => [4.0, 5.0], d => [0.2, 0.5]]),
Dict([osys.p => [4.0, 5.0], osys.d => [0.2, 0.5]]),
# Tuples not providing default values.
(p => [1.0, 2.0]),
(osys.p => [1.0, 2.0]),
# Tuples providing default values.
(p => [4.0, 5.0], d => [0.2, 0.5]),
(osys.p => [4.0, 5.0], osys.d => [0.2, 0.5])
]

# Declares a timespan.
tspan = (0.0, 10.0)
end

# Perform ODE simulations (singular and ensemble).
let
# Creates normal and ensemble problems.
base_oprob = ODEProblem(osys, u0_alts_vec[1], tspan, p_alts_vec[1])
base_sol = solve(base_oprob, Tsit5(); saveat = 1.0)
base_eprob = EnsembleProblem(base_oprob)
base_esol = solve(base_eprob, Tsit5(); trajectories = 2, saveat = 1.0)

# Simulates problems for all input types, checking that identical solutions are found.
@test_broken false # Does not work for certain inputs, likely related to https://github.com/SciML/ModelingToolkit.jl/issues/2804.
for u0 in u0_alts_vec, p in p_alts_vec
oprob = remake(base_oprob; u0, p)
# @test base_sol == solve(oprob, Tsit5(); saveat = 1.0)
eprob = remake(base_eprob; u0, p)
# @test base_esol == solve(eprob, Tsit5(); trajectories = 2, saveat = 1.0)
end
end

# Perform SDE simulations (singular and ensemble).
let
# Creates normal and ensemble problems.
base_sprob = SDEProblem(ssys, u0_alts_vec[1], tspan, p_alts_vec[1])
base_sol = solve(base_sprob, ImplicitEM(); seed, saveat = 1.0)
base_eprob = EnsembleProblem(base_sprob)
base_esol = solve(base_eprob, ImplicitEM(); seed, trajectories = 2, saveat = 1.0)

# Simulates problems for all input types, checking that identical solutions are found.
@test_broken false # Does not work for certain inputs, likely related to https://github.com/SciML/ModelingToolkit.jl/issues/2804.
for u0 in u0_alts_vec, p in p_alts_vec
sprob = remake(base_sprob; u0, p)
# @test base_sol == solve(sprob, ImplicitEM(); seed, saveat = 1.0)
eprob = remake(base_eprob; u0, p)
# @test base_esol == solve(eprob, ImplicitEM(); seed, trajectories = 2, saveat = 1.0)
end
end

# Perform jump simulations (singular and ensemble).
# Fails. At least partially related to https://github.com/SciML/ModelingToolkit.jl/issues/2804.
@test_broken let
# Creates normal and ensemble problems.
base_dprob = DiscreteProblem(jsys, u0_alts_vec[1], tspan, p_alts_vec[1])
base_jprob = JumpProblem(jsys, base_dprob, Direct(); rng)
base_sol = solve(base_jprob, SSAStepper(); seed, saveat = 1.0)
base_eprob = EnsembleProblem(base_jprob)
base_esol = solve(base_eprob, SSAStepper(); seed, trajectories = 2, saveat = 1.0)

# Simulates problems for all input types, checking that identical solutions are found.
@test_broken false # Does not work for certain inputs, likely related to https://github.com/SciML/ModelingToolkit.jl/issues/2804.
for u0 in u0_alts_vec, p in p_alts_vec
jprob = remake(base_jprob; u0, p)
# @test base_sol == solve(base_jprob, SSAStepper(); seed, saveat = 1.0)
eprob = remake(base_eprob; u0, p)
# @test base_esol == solve(eprob, SSAStepper(); seed, trajectories = 2, saveat = 1.0)
end
end

# Solves a nonlinear problem (EnsembleProblems are not possible for these).
let
base_nlprob = NonlinearProblem(nsys, u0_alts_vec[1], p_alts_vec[1])
base_sol = solve(base_nlprob, NewtonRaphson())
@test_broken false # Does not work for certain inputs, likely related to https://github.com/SciML/ModelingToolkit.jl/issues/2804.
for u0 in u0_alts_vec, p in p_alts_vec
nlprob = remake(base_nlprob; u0, p)
# @test base_sol == solve(nlprob, NewtonRaphson())
end
end

# Perform steady state simulations (singular and ensemble).
# Fails. At least partially related to https://github.com/SciML/ModelingToolkit.jl/issues/2804.
let
# Creates normal and ensemble problems.
base_ssprob = SteadyStateProblem(osys, u0_alts_vec[1], p_alts_vec[1])
base_sol = solve(base_ssprob, DynamicSS(Tsit5()))
base_eprob = EnsembleProblem(base_ssprob)
base_esol = solve(base_eprob, DynamicSS(Tsit5()); trajectories = 2)

# Simulates problems for all input types, checking that identical solutions are found.
@test_broken false # Does not work for certain inputs, likely related to https://github.com/SciML/ModelingToolkit.jl/issues/2804.
for u0 in u0_alts_vec, p in p_alts_vec
ssprob = remake(base_ssprob; u0, p)
# @test base_sol == solve(ssprob, DynamicSS(Tsit5()))
eprob = remake(base_eprob; u0, p)
# @test base_esol == solve(eprob, DynamicSS(Tsit5()); trajectories = 2)
end
end

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