def test_lnprob_calculates_multi_phase_probability_for_success(datasets_db):
"""lnprob() successfully calculates the probability for equilibrium """
datasets_db.insert(zpf_json)
from espei.utils import eq_callables_dict
from pycalphad import Model
import sympy
comps = ['CU', 'MG', 'VA']
phases = ['LIQUID', 'FCC_A1', 'HCP_A3', 'LAVES_C15', 'CUMG2']
param = 'VV0001'
eq_callables = eq_callables_dict(
dbf,
comps,
phases,
model=Model,
param_symbols=sorted([sympy.Symbol(sym) for sym in [param]], key=str))
eq_callables['phase_models'] = eq_callables.pop('model')
orig_val = dbf.symbols.pop(param)
res = lnprob([10],
comps=comps,
dbf=dbf,
phases=phases,
datasets=datasets_db,
symbols_to_fit=[param],
scheduler=None,
**eq_callables)
# replace the value in the database
# TODO: make a fixture for this
dbf.symbols[param] = orig_val
assert np.isreal(res)
assert np.isclose(res, -5741.61962949)
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_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_mixing_energies_are_fit(datasets_db):
"""Tests that given mixing energy data, the excess parameter is fit."""
phase_models = {
"components": ["AL", "B"],
"phases": {
"LIQUID": {
"sublattice_model": [["AL", "B"]],
"sublattice_site_ratios": [1]
},
"FCC_A1": {
"sublattice_model": [["AL", "B"]],
"sublattice_site_ratios": [1]
}
}
}
dataset_excess_mixing = {
"components": ["AL", "B"],
"phases": ["FCC_A1"],
"solver": {
"sublattice_site_ratios": [1],
"sublattice_occupancies": [[[0.5, 0.5]]],
"sublattice_configurations": [[["AL", "B"]]],
"mode": "manual"
},
"conditions": {
"P": 101325,
"T": 298.15
},
"output": "HM_MIX",
"values": [[[-10000]]]
}
datasets_db.insert(dataset_excess_mixing)
dbf = generate_parameters(phase_models, datasets_db, 'SGTE91', 'linear')
assert dbf.elements == {'AL', 'B'}
assert set(dbf.phases.keys()) == {'LIQUID', 'FCC_A1'}
assert len(dbf._parameters.search(where('parameter_type') == 'L')) == 1
assert dbf.symbols['VV0000'] == -40000
# check that read/write is ok
read_dbf = dbf.from_string(dbf.to_string(fmt='tdb'), fmt='tdb')
assert read_dbf.elements == {'AL', 'B'}
assert set(read_dbf.phases.keys()) == {'LIQUID', 'FCC_A1'}
assert len(
read_dbf._parameters.search(where('parameter_type') == 'L')) == 1
# the error should be exactly 0 because we are only fitting to one point
from espei.error_functions import calculate_thermochemical_error
assert calculate_thermochemical_error(read_dbf, sorted(dbf.elements),
sorted(dbf.phases.keys()),
datasets_db) == 0
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)
def test_mixing_energies_are_fit(datasets_db):
"""Tests that given mixing energy data, the excess parameter is fit."""
phase_models = {
"components": ["AL", "B"],
"phases": {
"LIQUID": {
"sublattice_model": [["AL", "B"]],
"sublattice_site_ratios": [1]
},
"FCC_A1": {
"sublattice_model": [["AL", "B"]],
"sublattice_site_ratios": [1]
}
}
}
dataset_excess_mixing = {
"components": ["AL", "B"],
"phases": ["FCC_A1"],
"solver": {
"sublattice_site_ratios": [1],
"sublattice_occupancies": [[[0.5, 0.5]]],
"sublattice_configurations": [[["AL", "B"]]],
"mode": "manual"
},
"conditions": {
"P": 101325,
"T": 298.15
},
"output": "HM_MIX",
"values": [[[-10000]]]
}
datasets_db.insert(dataset_excess_mixing)
dbf = generate_parameters(phase_models, datasets_db, 'SGTE91', 'linear')
assert dbf.elements == {'AL', 'B'}
assert set(dbf.phases.keys()) == {'LIQUID', 'FCC_A1'}
assert len(dbf._parameters.search(where('parameter_type') == 'L')) == 1
# check that read/write is ok
read_dbf = dbf.from_string(dbf.to_string(fmt='tdb'), fmt='tdb')
assert read_dbf.elements == {'AL', 'B'}
assert set(read_dbf.phases.keys()) == {'LIQUID', 'FCC_A1'}
assert len(
read_dbf._parameters.search(where('parameter_type') == 'L')) == 1
def test_mixing_data_is_excess_only(datasets_db):
"""Tests that given an entropy of mixing datapoint of 0, no excess parameters are fit (meaning datasets do not include ideal mixing)."""
phase_models = {
"components": ["AL", "B"],
"phases": {
"LIQUID": {
"sublattice_model": [["AL", "B"]],
"sublattice_site_ratios": [1]
},
"FCC_A1": {
"sublattice_model": [["AL", "B"]],
"sublattice_site_ratios": [1]
}
}
}
dataset_excess_mixing = {
"components": ["AL", "B"],
"phases": ["FCC_A1"],
"solver": {
"sublattice_site_ratios": [1],
"sublattice_occupancies": [[[0.5, 0.5]]],
"sublattice_configurations": [[["AL", "B"]]],
"mode": "manual"
},
"conditions": {
"P": 101325,
"T": 298.15
},
"output": "SM_MIX",
"values": [[[0]]]
}
datasets_db.insert(dataset_excess_mixing)
dbf = generate_parameters(phase_models, datasets_db, 'SGTE91', 'linear')
assert dbf.elements == {'AL', 'B'}
assert set(dbf.phases.keys()) == {'LIQUID', 'FCC_A1'}
assert len(dbf._parameters.search(where('parameter_type') == 'L')) == 0
def test_multi_sublattice_mixing_energies_are_fit(datasets_db):
"""Tests the correct excess parameter is fit for phases with multiple sublattices with vacancies."""
phase_models = {
"components": ["AL", "B", "VA"],
"phases": {
"FCC_A1": {
"sublattice_model": [["AL", "B"], ["AL", "VA"]],
"sublattice_site_ratios": [1, 3]
}
}
}
dataset_excess_mixing = {
"components": ["AL", "B", "VA"],
"phases": ["FCC_A1"],
"solver": {
"sublattice_site_ratios": [1, 3],
"sublattice_occupancies": [[[0.5, 0.5], 1], [[0.5, 0.5], 1]],
"sublattice_configurations": [[["AL", "B"], "VA"],
[["AL", "B"], "AL"]],
"mode": "manual"
},
"conditions": {
"P": 101325,
"T": 298.15
},
"output": "HM_MIX",
"values": [[[-10000, -10000]]]
}
datasets_db.insert(dataset_excess_mixing)
dbf = generate_parameters(phase_models, datasets_db, 'SGTE91', 'linear')
assert set(dbf.phases.keys()) == {'FCC_A1'}
assert len(dbf._parameters.search(where('parameter_type') == 'L')) == 2
assert dbf.symbols['VV0000'] == -160000.0
assert dbf.symbols['VV0001'] == -40000.0