def test_variables_samples(achr: "ACHRSampler", optgp: OptGPSampler) -> None:
"""Test variable samples."""
vnames = np.array([v.name for v in achr.model.variables])
s = optgp.sample(10, fluxes=False)
assert s.shape == (10, optgp.warmup.shape[1])
assert (s.columns == vnames).all()
assert (optgp.validate(s) == "v").all()
def optgp(model: "Model") -> OptGPSampler:
"""Return OptGPSampler instance for tests."""
sampler = OptGPSampler(model, processes=1, thinning=1)
assert (sampler.n_warmup > 0) and (sampler.n_warmup <=
2 * len(model.variables))
assert all(sampler.validate(sampler.warmup) == "v")
return sampler
def test_reproject(optgp: OptGPSampler) -> None:
"""Test reprojection of sampling."""
s = optgp.sample(10, fluxes=False).values
proj = np.apply_along_axis(optgp._reproject, 1, s)
assert all(optgp.validate(proj) == "v")
s = np.random.rand(10, optgp.warmup.shape[1])
proj = np.apply_along_axis(optgp._reproject, 1, s)
assert all(optgp.validate(proj) == "v")
def optgp(model):
"""Return OptGPSampler instance for tests."""
sampler = OptGPSampler(model, processes=1, thinning=1)
assert ((sampler.n_warmup > 0) and
(sampler.n_warmup <= 2 * len(model.variables)))
assert all(sampler.validate(sampler.warmup) == "v")
return sampler
def test_complicated_model():
"""Test a complicated model.
Difficult model since the online mean calculation is numerically
unstable so many samples weakly violate the equality constraints.
"""
model = Model('flux_split')
reaction1 = Reaction('V1')
reaction2 = Reaction('V2')
reaction3 = Reaction('V3')
reaction1.bounds = (0, 6)
reaction2.bounds = (0, 8)
reaction3.bounds = (0, 10)
A = Metabolite('A')
reaction1.add_metabolites({A: -1})
reaction2.add_metabolites({A: -1})
reaction3.add_metabolites({A: 1})
model.add_reactions([reaction1, reaction2, reaction3])
optgp = OptGPSampler(model, 1, seed=42)
achr = ACHRSampler(model, seed=42)
optgp_samples = optgp.sample(100)
achr_samples = achr.sample(100)
assert any(optgp_samples.corr().abs() < 1.0)
assert any(achr_samples.corr().abs() < 1.0)
# > 95% are valid
assert sum(optgp.validate(optgp_samples) == "v") > 95
assert sum(achr.validate(achr_samples) == "v") > 95
def test_complicated_model():
"""Test a complicated model.
Difficult model since the online mean calculation is numerically
unstable so many samples weakly violate the equality constraints.
"""
model = Model('flux_split')
reaction1 = Reaction('V1')
reaction2 = Reaction('V2')
reaction3 = Reaction('V3')
reaction1.bounds = (0, 6)
reaction2.bounds = (0, 8)
reaction3.bounds = (0, 10)
A = Metabolite('A')
reaction1.add_metabolites({A: -1})
reaction2.add_metabolites({A: -1})
reaction3.add_metabolites({A: 1})
model.add_reactions([reaction1, reaction2, reaction3])
optgp = OptGPSampler(model, 1, seed=42)
achr = ACHRSampler(model, seed=42)
optgp_samples = optgp.sample(100)
achr_samples = achr.sample(100)
assert any(optgp_samples.corr().abs() < 1.0)
assert any(achr_samples.corr().abs() < 1.0)
# > 95% are valid
assert sum(optgp.validate(optgp_samples) == "v") > 95
assert sum(achr.validate(achr_samples) == "v") > 95
def test_batch_sampling(optgp: OptGPSampler) -> None:
"""Test batch sampling."""
for b in optgp.batch(5, 4):
assert all(optgp.validate(b) == "v")
def test_sampling(optgp: OptGPSampler) -> None:
"""Test sampling."""
s = optgp.sample(10)
assert all(optgp.validate(s) == "v")
def test_optgp_init_benchmark(model: "Model", benchmark: Callable) -> None:
"""Benchmark inital OptGP sampling."""
benchmark(lambda: OptGPSampler(model, processes=2))
def test_optgp_init_benchmark(model, benchmark):
"""Benchmark inital OptGP sampling."""
benchmark(lambda: OptGPSampler(model, processes=2))