def test_lnprob_does_not_raise_on_ValueError(datasets_db):
"""lnprob() should catch ValueError raised by equilibrium and return -np.inf"""
dbf = Database.from_string(CU_MG_TDB, fmt='tdb')
datasets_db.insert(CU_MG_DATASET_ZPF_WORKING)
res = lnprob([10], comps=['CU', 'MG', 'VA'], dbf=dbf,
phases=['LIQUID', 'FCC_A1', 'HCP_A3', 'LAVES_C15', 'CUMG2'],
datasets=datasets_db, symbols_to_fit=['VV0001'], phase_models=None)
assert np.isneginf(res)
def test_lnprob_calculates_probability_for_success(datasets_db):
"""lnprob() successfully calculates the probability for equilibrium """
datasets_db.insert(zpf_json)
res = lnprob([10], comps=['CU','MG', 'VA'], dbf=dbf,
phases=['LIQUID', 'FCC_A1', 'HCP_A3', 'LAVES_C15', 'CUMG2'],
datasets=datasets_db, symbols_to_fit=['VV0001'], phase_models=None, scheduler=None)
assert np.isreal(res)
assert np.isclose(res, -5740.542839073727)
def test_lnprob_does_not_raise_on_ValueError(datasets_db):
"""lnprob() should catch ValueError raised by equilibrium and return -np.inf"""
datasets_db.insert(zpf_json)
res = lnprob([10],
comps=['CU', 'MG', 'VA'],
dbf=dbf,
phases=['LIQUID', 'FCC_A1', 'HCP_A3', 'LAVES_C15', 'CUMG2'],
datasets=datasets_db,
symbols_to_fit=['VV0001'],
phase_models=None,
scheduler=None)
assert np.isneginf(res)
def test_lnprob_calculates_multi_phase_probability_for_success(datasets_db):
"""lnprob() successfully calculates the probability for equilibrium """
dbf = Database.from_string(CU_MG_TDB, fmt='tdb')
datasets_db.insert(CU_MG_DATASET_ZPF_WORKING)
comps = ['CU', 'MG', 'VA']
phases = ['LIQUID', 'FCC_A1', 'HCP_A3', 'LAVES_C15', 'CUMG2']
param = 'VV0001'
orig_val = dbf.symbols[param].args[0].expr
eq_callables = build_callables(dbf, comps, phases, model=Model, parameters={param: orig_val})
eq_callables['phase_models'] = eq_callables.pop('model')
eq_callables.pop('phase_records')
res = lnprob([10], comps=comps, dbf=dbf, phases=phases,
datasets=datasets_db, symbols_to_fit=[param], callables=eq_callables)
assert np.isreal(res)
assert np.isclose(res, -5740.54416621)
res_2 = lnprob([10000000], comps=comps, dbf=dbf, phases=phases,
datasets=datasets_db, symbols_to_fit=[param], callables=eq_callables)
assert not np.isclose(res_2, -5740.54416621)
def test_lnprob_calculates_single_phase_probability_for_success(datasets_db):
"""lnprob() succesfully calculates the probability from single phase data"""
datasets_db.insert(single_phase_json)
res = lnprob(
[10],
comps=['CU', 'MG', 'VA'],
dbf=dbf,
phases=['LIQUID', 'FCC_A1', 'HCP_A3', 'LAVES_C15', 'CUMG2'],
datasets=datasets_db,
symbols_to_fit=['VV0001'],
phase_models=None,
scheduler=None,
)
assert np.isreal(res)
assert np.isclose(res, -19859.38)