def test_equilibrium_thermochemical_correct_probability(datasets_db):
"""Integration test for equilibrium thermochemical error."""
dbf = Database(CU_MG_TDB)
opt = EmceeOptimizer(dbf)
datasets_db.insert(CU_MG_EQ_HMR_LIQUID)
ctx = setup_context(dbf, datasets_db, ['VV0017'])
ctx.update(opt.get_priors(None, ['VV0017'], [0]))
prob = opt.predict(np.array([-31626.6]), **ctx)
expected_prob = norm(loc=0, scale=500).logpdf([-31626.6 * 0.5 * 0.5]).sum()
assert np.isclose(prob, expected_prob)
# change to -40000
prob = opt.predict(np.array([-40000], dtype=np.float_), **ctx)
expected_prob = norm(loc=0, scale=500).logpdf([-40000 * 0.5 * 0.5]).sum()
assert np.isclose(prob, expected_prob)
def test_equilibrium_thermochemical_context_is_pickleable(datasets_db):
"""Test that the context for equilibrium thermochemical data is pickleable"""
datasets_db.insert(CU_MG_EQ_HMR_LIQUID)
dbf = Database(CU_MG_TDB)
symbols_to_fit = database_symbols_to_fit(dbf)
initial_guess = np.array([unpack_piecewise(dbf.symbols[s]) for s in symbols_to_fit])
prior_dict = EmceeOptimizer.get_priors(None, symbols_to_fit, initial_guess)
ctx = setup_context(dbf, datasets_db)
ctx.update(prior_dict)
ctx_pickle = pickle.dumps(ctx)
ctx_unpickled = pickle.loads(ctx_pickle)
regular_predict = EmceeOptimizer.predict(initial_guess, **ctx)
unpickle_predict = EmceeOptimizer.predict(initial_guess, **ctx_unpickled)
assert np.isclose(regular_predict, unpickle_predict)
def test_zpf_context_is_pickleable(datasets_db):
"""Test that the context for ZPF data is pickleable"""
datasets_db.insert(CU_MG_DATASET_ZPF_ZERO_ERROR)
dbf = Database(CU_MG_TDB)
symbols_to_fit = database_symbols_to_fit(dbf)
initial_guess = np.array([unpack_piecewise(dbf.symbols[s]) for s in symbols_to_fit])
prior_dict = EmceeOptimizer.get_priors(None, symbols_to_fit, initial_guess)
ctx = setup_context(dbf, datasets_db)
ctx.update(prior_dict)
ctx_pickle = pickle.dumps(ctx)
ctx_unpickled = pickle.loads(ctx_pickle)
regular_predict = EmceeOptimizer.predict(initial_guess, **ctx)
unpickle_predict = EmceeOptimizer.predict(initial_guess, **ctx_unpickled)
assert np.isclose(regular_predict, unpickle_predict)