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"""Test functionalities of removing loops in model."""
from typing import Callable
import pytest
from optlang.interface import INFEASIBLE, OPTIMAL
from cobra.core import Metabolite, Model, Reaction
from cobra.flux_analysis.loopless import add_loopless, loopless_solution
from cobra.util import solver as sutil
def construct_ll_test_model() -> Model:
"""Construct test model."""
test_model = Model()
test_model.add_metabolites(Metabolite("A"))
test_model.add_metabolites(Metabolite("B"))
test_model.add_metabolites(Metabolite("C"))
EX_A = Reaction("EX_A")
EX_A.add_metabolites({test_model.metabolites.A: 1})
DM_C = Reaction("DM_C")
DM_C.add_metabolites({test_model.metabolites.C: -1})
v1 = Reaction("v1")
v1.add_metabolites({test_model.metabolites.A: -1, test_model.metabolites.B: 1})
v2 = Reaction("v2")
v2.add_metabolites({test_model.metabolites.B: -1, test_model.metabolites.C: 1})
v3 = Reaction("v3")
v3.add_metabolites({test_model.metabolites.C: -1, test_model.metabolites.A: 1})
test_model.add_reactions([EX_A, DM_C, v1, v2, v3])
DM_C.objective_coefficient = 1
return test_model
@pytest.fixture(
scope="function",
params=[s for s in ["glpk", "cplex", "gurobi"] if s in sutil.solvers],
)
def ll_test_model(request: pytest.FixtureRequest) -> Model:
"""Return test model set with different solvers."""
test_model = construct_ll_test_model()
test_model.solver = request.param
return test_model
def test_loopless_benchmark_before(benchmark: Callable) -> None:
"""Benchmark initial condition."""
test_model = construct_ll_test_model()
def _():
with test_model:
add_loopless(test_model)
test_model.optimize()
benchmark(_)
def test_loopless_benchmark_after(benchmark: Callable) -> None:
"""Benchmark final condition."""
test_model = construct_ll_test_model()
benchmark(loopless_solution, test_model)
def test_loopless_solution(ll_test_model: Model) -> None:
"""Test loopless_solution()."""
opt_feasible = ll_test_model.slim_optimize()
solution_feasible = loopless_solution(ll_test_model)
ll_test_model.reactions.v3.lower_bound = 1
opt_infeasible = ll_test_model.slim_optimize()
solution_infeasible = loopless_solution(ll_test_model)
assert solution_feasible.fluxes["v3"] == 0.0
assert solution_feasible.objective_value == pytest.approx(opt_feasible)
assert solution_infeasible.fluxes["v3"] == 1.0
assert solution_infeasible.objective_value == pytest.approx(opt_infeasible)
def test_loopless_solution_fluxes(model: Model) -> None:
"""Test fluxes of loopless_solution()."""
sol = model.optimize()
ll_solution = loopless_solution(model, fluxes=sol.fluxes)
assert len(ll_solution.fluxes) == len(model.reactions)
assert ll_solution.objective_value == pytest.approx(sol.objective_value)
def test_add_loopless(ll_test_model: Model) -> None:
"""Test add_loopless()."""
add_loopless(ll_test_model)
feasible_status = ll_test_model.optimize().status
ll_test_model.reactions.v3.lower_bound = 1
ll_test_model.slim_optimize()
infeasible_status = ll_test_model.solver.status
assert feasible_status == OPTIMAL
assert infeasible_status == INFEASIBLE
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