def test_incompatible_db_ignores_with_kwarg_ignore():
"Symbol names too long for Thermo-Calc are ignored the database written as given."
test_dbf = Database.from_string(INVALID_TDB_STR, fmt='tdb')
with warnings.catch_warnings(record=True) as w:
invalid_dbf = test_dbf.to_string(fmt='tdb', if_incompatible='ignore')
not_expected_string_fragment = 'Ignoring that the following function names are beyond the 8 character TDB limit'
assert all([not_expected_string_fragment not in str(warning.message) for warning in w])
assert test_dbf == Database.from_string(invalid_dbf, fmt='tdb')
def test_incompatible_db_warns_by_default():
"Symbol names too long for Thermo-Calc warn and write the database as given by default."
test_dbf = Database.from_string(INVALID_TDB_STR, fmt='tdb')
with warnings.catch_warnings(record=True) as w:
invalid_dbf = test_dbf.to_string(fmt='tdb')
assert len(w) >= 1
expected_string_fragment = 'Ignoring that the following function names are beyond the 8 character TDB limit'
assert any([expected_string_fragment in str(warning.message) for warning in w])
assert test_dbf == Database.from_string(invalid_dbf, fmt='tdb')
def test_incompatible_db_mangles_names_with_kwarg_fix():
"Symbol names too long for Thermo-Calc are mangled and replaced in symbol names, symbol expressions, and parameter expressions."
test_dbf = Database.from_string(INVALID_TDB_STR, fmt='tdb')
test_dbf_copy = deepcopy(test_dbf)
mangled_dbf = Database.from_string(test_dbf.to_string(fmt='tdb', if_incompatible='fix'), fmt='tdb')
# check that the long function name was hashed correctly
a_very_long_function_name_hash_symbol = 'F' + str(hashlib.md5('A_VERY_LONG_FUNCTION_NAME'.encode('UTF-8')).hexdigest()).upper()[:7]
assert a_very_long_function_name_hash_symbol in mangled_dbf.symbols.keys()
assert 'COMPAT' in mangled_dbf.symbols.keys() # test that compatible keys are not removed
assert test_dbf_copy == test_dbf # make sure test_dbf has not mutated
assert test_dbf != mangled_dbf # also make sure test_dbf has not mutated
def test_tdb_species_are_parsed_correctly():
"""The TDB speciescommand should be properly parsed."""
tdb_species_str = """
ELEMENT /- ELECTRON_GAS 0.0000E+00 0.0000E+00 0.0000E+00!
ELEMENT VA VACUUM 0.0000E+00 0.0000E+00 0.0000E+00!
ELEMENT AL FCC_A1 2.6982E+01 4.5773E+03 2.8321E+01!
ELEMENT O 1/2_MOLE_O2(G) 1.5999E+01 4.3410E+03 1.0252E+02!
SPECIES AL+3 AL1/+3!
SPECIES O-2 O1/-2!
SPECIES O1 O!
SPECIES O2 O2!
SPECIES O3 O3!
SPECIES AL1O1 AL1O1!
SPECIES AL1O2 AL1O2!
SPECIES AL2 AL2!
SPECIES AL2O AL2O1!
SPECIES AL2O1 AL2O1!
SPECIES AL2O2 AL2O2!
SPECIES AL2O3 AL2O3!
SPECIES ALO AL1O1!
SPECIES ALO2 AL1O2!
SPECIES ALO3/2 AL1O1.5!
"""
test_dbf = Database.from_string(tdb_species_str, fmt='tdb')
assert len(test_dbf.species) == 19
species_dict = {sp.name: sp for sp in test_dbf.species}
assert species_dict['AL'].charge == 0
assert species_dict['O2'].constituents['O'] == 2
assert species_dict['O1'].constituents['O'] == 1
assert species_dict['AL1O2'].constituents['AL'] == 1
assert species_dict['AL1O2'].constituents['O'] == 2
assert species_dict['ALO3/2'].constituents['O'] == 1.5
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
initial_params = {param: orig_val}
zpf_kwargs = {
'zpf_data': get_zpf_data(dbf, comps, phases, datasets_db,
initial_params),
'data_weight': 1.0,
}
opt = EmceeOptimizer(dbf)
res = opt.predict([10],
prior_rvs=[rv_zero()],
symbols_to_fit=[param],
zpf_kwargs=zpf_kwargs)
assert np.isreal(res)
assert np.isclose(res, -31.309645520830344, rtol=1e-4)
res_2 = opt.predict([10000000],
prior_rvs=[rv_zero()],
symbols_to_fit=[param],
zpf_kwargs=zpf_kwargs)
assert not np.isclose(res_2, -31.309645520830344, rtol=1e-6)
def test_tdb_species_are_parsed_correctly():
"""The TDB speciescommand should be properly parsed."""
tdb_species_str = """
ELEMENT /- ELECTRON_GAS 0.0000E+00 0.0000E+00 0.0000E+00!
ELEMENT VA VACUUM 0.0000E+00 0.0000E+00 0.0000E+00!
ELEMENT AL FCC_A1 2.6982E+01 4.5773E+03 2.8321E+01!
ELEMENT O 1/2_MOLE_O2(G) 1.5999E+01 4.3410E+03 1.0252E+02!
SPECIES AL+3 AL1/+3!
SPECIES O-2 O1/-2!
SPECIES O1 O!
SPECIES O2 O2!
SPECIES O3 O3!
SPECIES AL1O1 AL1O1!
SPECIES AL1O2 AL1O2!
SPECIES AL2 AL2!
SPECIES AL2O AL2O1!
SPECIES AL2O1 AL2O1!
SPECIES AL2O2 AL2O2!
SPECIES AL2O3 AL2O3!
SPECIES ALO AL1O1!
SPECIES ALO2 AL1O2!
SPECIES ALO3/2 AL1O1.5!
"""
test_dbf = Database.from_string(tdb_species_str, fmt='tdb')
assert len(test_dbf.species) == 19
species_dict = {sp.name: sp for sp in test_dbf.species}
assert species_dict['AL'].charge == 0
assert species_dict['O2'].constituents['O'] == 2
assert species_dict['O1'].constituents['O'] == 1
assert species_dict['AL1O2'].constituents['AL'] == 1
assert species_dict['AL1O2'].constituents['O'] == 2
assert species_dict['ALO3/2'].constituents['O'] == 1.5
def test_incompatible_db_mangles_names_with_kwarg_fix():
"Symbol names too long for Thermo-Calc are mangled and replaced in symbol names, symbol expressions, and parameter expressions."
test_dbf = Database.from_string(INVALID_TDB_STR, fmt='tdb')
test_dbf_copy = deepcopy(test_dbf)
mangled_dbf = Database.from_string(test_dbf.to_string(
fmt='tdb', if_incompatible='fix'),
fmt='tdb')
# check that the long function name was hashed correctly
a_very_long_function_name_hash_symbol = 'F' + str(
hashlib.md5('A_VERY_LONG_FUNCTION_NAME'.encode(
'UTF-8')).hexdigest()).upper()[:7]
assert a_very_long_function_name_hash_symbol in mangled_dbf.symbols.keys()
assert 'COMPAT' in mangled_dbf.symbols.keys(
) # test that compatible keys are not removed
assert test_dbf_copy == test_dbf # make sure test_dbf has not mutated
assert test_dbf != mangled_dbf # also make sure test_dbf has not mutated
def test_species_are_parsed_in_tdb_phases_and_parameters():
"""Species defined in the tdb phases and parameters should be parsed."""
tdb_str = """
ELEMENT /- ELECTRON_GAS 0.0000E+00 0.0000E+00 0.0000E+00!
ELEMENT VA VACUUM 0.0000E+00 0.0000E+00 0.0000E+00!
ELEMENT AL FCC_A1 2.6982E+01 4.5773E+03 2.8321E+01!
ELEMENT O 1/2_MOLE_O2(G) 1.5999E+01 4.3410E+03 1.0252E+02!
SPECIES AL+3 AL1/+3!
SPECIES O-2 O1/-2!
SPECIES O2 O2!
SPECIES AL2 AL2!
PHASE TEST_PH % 1 1 !
CONSTITUENT TEST_PH :AL,AL2,O-2: !
PARA G(TEST_PH,AL;0) 298.15 +10; 6000 N !
PARA G(TEST_PH,AL2;0) 298.15 +100; 6000 N !
PARA G(TEST_PH,O-2;0) 298.15 +1000; 6000 N !
PHASE T2SL % 2 1 1 !
CONSTITUENT T2SL :AL+3:O-2: !
PARA L(T2SL,AL+3:O-2;0) 298.15 +2; 6000 N !
"""
from tinydb import where
test_dbf = Database.from_string(tdb_str, fmt='tdb')
written_tdb_str = test_dbf.to_string(fmt='tdb')
test_dbf_reread = Database.from_string(written_tdb_str, fmt='tdb')
assert set(test_dbf_reread.phases.keys()) == {'TEST_PH', 'T2SL'}
assert test_dbf_reread.phases['TEST_PH'].constituents[0] == {
'AL', 'AL2', 'O-2'
}
assert len(
test_dbf_reread._parameters.search(
where('constituent_array') == (('AL', ), ))) == 1
assert len(
test_dbf_reread._parameters.search(
where('constituent_array') == (('AL2', ), ))) == 1
assert len(
test_dbf_reread._parameters.search(
where('constituent_array') == (('O-2', ), ))) == 1
assert test_dbf_reread.phases['T2SL'].constituents == ({'AL+3'}, {'O-2'})
assert len(
test_dbf_reread._parameters.search(
where('constituent_array') == (('AL+3', ), ('O-2', )))) == 1
def test_lnprob_does_not_raise_on_LinAlgError(datasets_db):
"""lnprob() should catch LinAlgError 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_export_import():
"Equivalence of Model using re-imported database."
test_model = Model(
Database.from_string(ALNIPT_DBF.to_string(fmt='tdb',
if_incompatible='ignore'),
fmt='tdb'), ['PT', 'NI', 'VA'], 'FCC_L12')
ref_model = Model(ALNIPT_DBF, ['NI', 'PT', 'VA'], 'FCC_L12')
assert test_model == ref_model
def test_database_parameter_with_species_that_is_not_a_stoichiometric_formula():
"""Species names used in parameters do not have to be stoichiometric formulas"""
# names are taken from the Thermo-Calc documentation set, Database Manager Guide, SPECIES
tdb_string = """
ELEMENT /- ELECTRON_GAS 0.0000E+00 0.0000E+00 0.0000E+00!
ELEMENT VA VACUUM 0.0000E+00 0.0000E+00 0.0000E+00!
ELEMENT O 1/2_MOLE_O2(G) 0.0000E+00 0.0000E+00 0.0000E+00!
ELEMENT SI HCP_A3 0.0000E+00 0.0000E+00 0.0000E+00!
ELEMENT NA HCP_A3 0.0000E+00 0.0000E+00 0.0000E+00!
ELEMENT SB RHOMBOHEDRAL_A7 0.0000E+00 0.0000E+00 0.0000E+00!
ELEMENT H 1/2_MOLE_H2(G) 0.0000E+00 0.0000E+00 0.0000E+00!
SPECIES SILICA SI1O2 ! $ tests for arbitrary names
SPECIES NASB_6OH NA1SB1O6H6 ! $ tests for underscores
SPECIES SB-3 SB/-3 ! $ tests for charge
SPECIES ALCL2OH.3WATER AL1O1H1CL2H6O3 ! $ tests for charge
PHASE LIQUID:L % 1 1.0 !
CONSTITUENT LIQUID:L : O, SI, NA, SB, H, SILICA, NASB_6OH, SB-3, ALCL2OH.3WATER : !
PARAMETER G(LIQUID,SILICA;0) 298.15 10; 3000 N !
PARAMETER G(LIQUID,NASB_6OH;0) 298.15 100; 3000 N !
PARAMETER G(LIQUID,ALCL2OH.3WATER;0) 298.15 1000; 3000 N !
PARAMETER G(LIQUID,SB-3;0) 298.15 10000; 3000 N !
"""
dbf = Database.from_string(tdb_string, fmt='tdb')
species_dict = {sp.name: sp for sp in dbf.species}
species_names = list(species_dict.keys())
# check that the species are found
assert 'SILICA' in species_names
assert 'NASB_6OH' in species_names
assert 'ALCL2OH.3WATER' in species_names
assert 'SB-3' in species_names
import tinydb
silica = dbf._parameters.search(tinydb.where('constituent_array') == ((species_dict['SILICA'],),))
assert len(silica) == 1
assert silica[0]['parameter'].args[0][0] == 10
nasb_6oh = dbf._parameters.search(tinydb.where('constituent_array') == ((species_dict['NASB_6OH'],),))
assert len(nasb_6oh) == 1
assert nasb_6oh[0]['parameter'].args[0][0] == 100
alcl2oh_3water = dbf._parameters.search(tinydb.where('constituent_array') == ((species_dict['ALCL2OH.3WATER'],),))
assert len(alcl2oh_3water) == 1
assert alcl2oh_3water[0]['parameter'].args[0][0] == 1000
sbminus3 = dbf._parameters.search(tinydb.where('constituent_array') == ((species_dict['SB-3'],),))
assert len(sbminus3) == 1
assert sbminus3[0]['parameter'].args[0][0] == 10000
def test_lnprob_does_not_raise_on_LinAlgError(datasets_db):
"""lnprob() should catch LinAlgError raised by equilibrium and return -np.inf"""
dbf = Database.from_string(CU_MG_TDB, fmt='tdb')
comps = ['CU', 'MG', 'VA']
phases = ['LIQUID', 'FCC_A1', 'HCP_A3', 'LAVES_C15', 'CUMG2']
datasets_db.insert(CU_MG_DATASET_ZPF_WORKING)
zpf_kwargs = {'dbf': dbf, 'phases': phases, 'zpf_data': get_zpf_data(comps, phases, datasets_db), 'data_weight': 1.0}
res = opt.predict([10], prior_rvs=[rv_zero()], symbols_to_fit=['VV0001'], zpf_kwargs=zpf_kwargs)
assert np.isneginf(res)
def test_emcee_opitmizer_can_restart(datasets_db):
"""A restart trace can be passed to the Emcee optimizer """
dbf = Database.from_string(CU_MG_TDB, fmt='tdb')
datasets_db.insert(CU_MG_DATASET_ZPF_WORKING)
param = 'VV0001'
opt = EmceeOptimizer(dbf)
restart_tr = -4*np.ones((2, 10, 1)) # 2 chains, 10 iterations, 1 parameter
opt.fit([param], datasets_db, iterations=1, chains_per_parameter=2, restart_trace=restart_tr)
assert opt.sampler.chain.shape == (2, 1, 1)
def test_binary_magnetic_reimported():
"Export and re-import a TDB before the calculation."
dbf_imported = Database.from_string(DBF.to_string(fmt='tdb'), fmt='tdb')
check_energy(Model(dbf_imported, ['CR', 'NI'], 'L12_FCC'),
{v.T: 500, v.SiteFraction('L12_FCC', 0, 'CR'): 0.33,
v.SiteFraction('L12_FCC', 0, 'NI'): 0.67,
v.SiteFraction('L12_FCC', 1, 'CR'): 0.33,
v.SiteFraction('L12_FCC', 1, 'NI'): 0.67},
-1.68840e4, mode='sympy')
def test_tdb_content_after_line_end_is_neglected():
"""Any characters after the line ending '!' are neglected as in commercial software."""
tdb_line_ending_str = """$ Characters after line endings should be discarded.
PARAMETER G(PH,A;0) 298.15 +42; 6000 N ! SHOULD_NOT_RAISE_ERROR
$ G(PH,C;0) should not parse
PARAMETER G(PH,B;0) 298.15 +9001; 6000 N ! PARAMETER G(PH,C;0) 298.15 +2; 600 N !
PARAMETER G(PH,D;0) 298.15 -42; 6000 N !
"""
test_dbf = Database.from_string(tdb_line_ending_str, fmt='tdb')
assert len(test_dbf._parameters) == 3
def test_tdb_content_after_line_end_is_neglected():
"""Any characters after the line ending '!' are neglected as in commercial software."""
tdb_line_ending_str = """$ Characters after line endings should be discarded.
PARAMETER G(PH,A;0) 298.15 +42; 6000 N ! SHOULD_NOT_RAISE_ERROR
$ G(PH,C;0) should not parse
PARAMETER G(PH,B;0) 298.15 +9001; 6000 N ! PARAMETER G(PH,C;0) 298.15 +2; 600 N !
PARAMETER G(PH,D;0) 298.15 -42; 6000 N !
"""
test_dbf = Database.from_string(tdb_line_ending_str, fmt='tdb')
assert len(test_dbf._parameters) == 3
def test_database_passes_with_diffusion_commands():
"DIFFUSION and ZEROVOLUME_SPECIES commands do not raise errors while parsing (doesn't test implementation)."
tdb_string = """
ELEMENT /- ELECTRON_GAS 0.0000E+00 0.0000E+00 0.0000E+00 !
ELEMENT VA VACUUM 0.0000E+00 0.0000E+00 0.0000E+00 !
ZEROVOLUME_SPECIES VA !
DIFFUSION MAGNETIC BCC_A2 ALPHA=0.3 !
"""
dbf = Database.from_string(tdb_string, fmt='tdb')
def test_writing_tdb_with_species_gives_same_result():
"""Species defined in the tdb should be written back to the TDB correctly"""
tdb_species_str = """
ELEMENT /- ELECTRON_GAS 0.0000E+00 0.0000E+00 0.0000E+00!
ELEMENT VA VACUUM 0.0000E+00 0.0000E+00 0.0000E+00!
ELEMENT AL FCC_A1 2.6982E+01 4.5773E+03 2.8321E+01!
ELEMENT O 1/2_MOLE_O2(G) 1.5999E+01 4.3410E+03 1.0252E+02!
SPECIES AL+3 AL1/+3!
SPECIES O-2 O1/-2!
SPECIES O2 O2!
SPECIES AL2 AL2!
"""
test_dbf = Database.from_string(tdb_species_str, fmt='tdb')
written_tdb_str = test_dbf.to_string(fmt='tdb')
test_dbf_reread = Database.from_string(written_tdb_str, fmt='tdb')
assert len(test_dbf_reread.species) == 8
species_dict = {sp.name: sp for sp in test_dbf_reread.species}
assert species_dict['AL'].charge == 0
assert species_dict['AL+3'].charge == 3
assert species_dict['O-2'].charge == -2
def test_writing_tdb_with_species_gives_same_result():
"""Species defined in the tdb should be written back to the TDB correctly"""
tdb_species_str = """
ELEMENT /- ELECTRON_GAS 0.0000E+00 0.0000E+00 0.0000E+00!
ELEMENT VA VACUUM 0.0000E+00 0.0000E+00 0.0000E+00!
ELEMENT AL FCC_A1 2.6982E+01 4.5773E+03 2.8321E+01!
ELEMENT O 1/2_MOLE_O2(G) 1.5999E+01 4.3410E+03 1.0252E+02!
SPECIES AL+3 AL1/+3!
SPECIES O-2 O1/-2!
SPECIES O2 O2!
SPECIES AL2 AL2!
"""
test_dbf = Database.from_string(tdb_species_str, fmt='tdb')
written_tdb_str = test_dbf.to_string(fmt='tdb')
test_dbf_reread = Database.from_string(written_tdb_str, fmt='tdb')
assert len(test_dbf_reread.species) == 8
species_dict = {sp.name: sp for sp in test_dbf_reread.species}
assert species_dict['AL'].charge == 0
assert species_dict['AL+3'].charge == 3
assert species_dict['O-2'].charge == -2
def test_binary_magnetic_reimported():
"Export and re-import a TDB before the calculation."
dbf_imported = Database.from_string(DBF.to_string(fmt='tdb'), fmt='tdb')
check_energy(Model(dbf_imported, ['CR', 'NI'], 'L12_FCC'), {
v.T: 500,
v.SiteFraction('L12_FCC', 0, 'CR'): 0.33,
v.SiteFraction('L12_FCC', 0, 'NI'): 0.67,
v.SiteFraction('L12_FCC', 1, 'CR'): 0.33,
v.SiteFraction('L12_FCC', 1, 'NI'): 0.67
},
-1.68840e4,
mode='numpy')
def test_species_are_parsed_in_tdb_phases_and_parameters():
"""Species defined in the tdb phases and parameters should be parsed."""
tdb_str = """
ELEMENT /- ELECTRON_GAS 0.0000E+00 0.0000E+00 0.0000E+00!
ELEMENT VA VACUUM 0.0000E+00 0.0000E+00 0.0000E+00!
ELEMENT AL FCC_A1 2.6982E+01 4.5773E+03 2.8321E+01!
ELEMENT O 1/2_MOLE_O2(G) 1.5999E+01 4.3410E+03 1.0252E+02!
SPECIES AL+3 AL1/+3!
SPECIES O-2 O1/-2!
SPECIES O2 O2!
SPECIES AL2 AL2!
PHASE TEST_PH % 1 1 !
CONSTITUENT TEST_PH :AL,AL2,O-2: !
PARA G(TEST_PH,AL;0) 298.15 +10; 6000 N !
PARA G(TEST_PH,AL2;0) 298.15 +100; 6000 N !
PARA G(TEST_PH,O-2;0) 298.15 +1000; 6000 N !
PHASE T2SL % 2 1 1 !
CONSTITUENT T2SL :AL+3:O-2: !
PARA L(T2SL,AL+3:O-2;0) 298.15 +2; 6000 N !
"""
from tinydb import where
test_dbf = Database.from_string(tdb_str, fmt='tdb')
written_tdb_str = test_dbf.to_string(fmt='tdb')
test_dbf_reread = Database.from_string(written_tdb_str, fmt='tdb')
assert set(test_dbf_reread.phases.keys()) == {'TEST_PH', 'T2SL'}
assert test_dbf_reread.phases['TEST_PH'].constituents[0] == {Species('AL'), Species('AL2'), Species('O-2')}
assert len(test_dbf_reread._parameters.search(where('constituent_array') == ((Species('AL'),),))) == 1
assert len(test_dbf_reread._parameters.search(where('constituent_array') == ((Species('AL2'),),))) == 1
assert len(test_dbf_reread._parameters.search(where('constituent_array') == ((Species('O-2'),),))) == 1
assert test_dbf_reread.phases['T2SL'].constituents == ({Species('AL+3')}, {Species('O-2')})
assert len(test_dbf_reread._parameters.search(where('constituent_array') == ((Species('AL+3'),),(Species('O-2'),)))) == 1
def test_symbol_names_are_propagated_through_symbols_and_parameters():
"""A map of old symbol names to new symbol names should propagate through symbol and parameter SymPy expressions"""
tdb_propagate_str = """$ Mangled function names should propagate through other symbols and parameters
ELEMENT A PH 0 0 0 !
FUNCTION FN1 298.15 -42; 6000 N !
FUNCTION FN2 298.15 FN1#; 6000 N !
PARAMETER G(PH,A;0) 298.15 FN1# + FN2#; 6000 N !
"""
test_dbf = Database.from_string(tdb_propagate_str, fmt='tdb')
rename_map = {'FN1': 'RENAMED_FN1', 'FN2': 'RENAMED_FN2'}
_apply_new_symbol_names(test_dbf, rename_map)
assert 'RENAMED_FN1' in test_dbf.symbols
assert 'FN1' not in test_dbf.symbols # check that the old key was removed
assert test_dbf.symbols['RENAMED_FN2'] == Piecewise((Symbol('RENAMED_FN1'), And(v.T < 6000.0, v.T >= 298.15)), (0, True))
assert test_dbf._parameters.all()[0]['parameter'] == Piecewise((Symbol('RENAMED_FN1')+Symbol('RENAMED_FN2'), And(v.T < 6000.0, v.T >= 298.15)), (0, True))
def test_emcee_optimizer_can_restart(datasets_db):
"""A restart trace can be passed to the Emcee optimizer """
dbf = Database.from_string(CU_MG_TDB, fmt='tdb')
datasets_db.insert(CU_MG_DATASET_ZPF_WORKING)
param = 'VV0001'
opt = EmceeOptimizer(dbf)
restart_tr = np.array([[[-4], [-3], [-2], [-1], [0], [1], [2], [3], [4],
[5]],
[[-6], [-4], [-2], [0], [2], [4], [6], [8], [10],
[12]]]) # 2 chains, 10 iterations, 1 parameter
opt.fit([param],
datasets_db,
iterations=1,
chains_per_parameter=2,
restart_trace=restart_tr)
assert opt.sampler.chain.shape == (2, 1, 1)
def test_lnprob_calculates_single_phase_probability_for_success(datasets_db):
"""lnprob() succesfully calculates the probability from single phase data"""
dbf = Database.from_string(CU_MG_TDB_FCC_ONLY, fmt='tdb')
datasets_db.insert(CU_MG_HM_MIX_SINGLE_FCC_A1)
comps = ['CU', 'MG', 'VA']
phases = ['FCC_A1']
param = 'VV0003'
orig_val = -14.0865
eq_callables = build_callables(dbf, comps, phases, model=Model, parameters={param: orig_val})
pm = eq_callables.pop('model')
eq_callables.pop('phase_records')
mods_no_idmix = {}
for phase_name in phases:
mods_no_idmix[phase_name] = Model(dbf, comps, phase_name, parameters=[sympy.Symbol(param)])
mods_no_idmix[phase_name].models['idmix'] = 0
prop = 'HM_MIX' # from the dataset
thermochemical_callables = {}
from sympy import Symbol
thermochemical_callables[prop] = build_callables(dbf, comps, phases, model=mods_no_idmix, output=prop, parameters={param: orig_val}, build_gradients=False)
# pop off the callables not used in properties because we don't want them around (they should be None, anyways)
thermochemical_callables[prop].pop('phase_records')
# thermochemical_callables[prop].pop('model')
res_orig = lnprob([orig_val], comps=comps, dbf=dbf, phases=phases, phase_models=pm,
datasets=datasets_db, symbols_to_fit=[Symbol(param)], callables=eq_callables,
thermochemical_callables=thermochemical_callables)
assert np.isreal(res_orig)
assert np.isclose(res_orig, -19859.38)
res_10 = lnprob([10], comps=comps, dbf=dbf, phases=phases, phase_models=pm,
datasets=datasets_db, symbols_to_fit=[Symbol(param)], callables=eq_callables,
thermochemical_callables=thermochemical_callables)
assert np.isreal(res_10)
assert np.isclose(res_10, -20100.125)
res_1e5 = lnprob([1e5], comps=comps, dbf=dbf, phases=phases, phase_models=pm,
datasets=datasets_db, symbols_to_fit=[param], callables=eq_callables,
thermochemical_callables=thermochemical_callables)
assert np.isreal(res_1e5)
assert np.isclose(res_1e5, -13520000.0)
def test_tdb_order_disorder_model_hints_applied_correctly():
"""Phases using the order/disorder model should have model_hints added to
both phases, regardless of the order by which the phases were specified.
Model hints should also be applied correctly if only one of the phases has
the order/disorder type defintion applied, since this is allowed by
commercial software.
"""
# This test creates a starting template and then tries to add the phase and
# type definitions in any order. In this case, the BCC_A2 phase does not
# have the type definition while the BCC_B2 phase does.
TEMPLATE_TDB = """
ELEMENT VA VACUUM .0000E+00 .0000E+00 .0000E+00!
ELEMENT AL FCC_A1 2.6982E+01 4.5773E+03 2.8322E+01!
ELEMENT NI FCC_A1 5.8690E+01 4.7870E+03 2.9796E+01!
TYPE_DEFINITION % SEQ *!
"""
PHASE_A2 = """
PHASE BCC_A2 % 2 1 3 !
CONST BCC_A2 :AL,NI : VA : !
"""
PHASE_B2 = """
PHASE BCC_B2 %C 3 .5 .5 3 !
CONST BCC_B2 :AL,NI : AL,NI : VA: !
"""
TYPE_DEF_ORD = """
TYPE_DEFINITION C GES A_P_D BCC_B2 DIS_PART BCC_A2 !
"""
import itertools
for (k1, v1), (k2, v2), (k3, v3) in itertools.permutations([
('PHASE_A2 ', PHASE_A2), ('PHASE_B2 ', PHASE_B2),
('TYPE_DEF ', TYPE_DEF_ORD)
]):
print(k1 + k2 + k3)
dbf = Database(TEMPLATE_TDB + v1 + v2 + v3)
assert 'disordered_phase' in dbf.phases['BCC_A2'].model_hints
assert 'ordered_phase' in dbf.phases['BCC_A2'].model_hints
assert 'disordered_phase' in dbf.phases['BCC_B2'].model_hints
assert 'ordered_phase' in dbf.phases['BCC_B2'].model_hints
roundtrip_dbf = Database.from_string(dbf.to_string(fmt='tdb'),
fmt='tdb')
assert roundtrip_dbf == dbf
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
models = instantiate_models(dbf,
comps,
phases,
parameters={param: orig_val})
eq_callables = build_callables(dbf,
comps,
phases,
models,
parameter_symbols=[param],
output='GM',
build_gradients=True,
build_hessians=True,
additional_statevars={v.N, v.P, v.T})
zpf_kwargs = {
'dbf': dbf,
'phases': phases,
'zpf_data': get_zpf_data(comps, phases, datasets_db),
'phase_models': models,
'callables': eq_callables,
'data_weight': 1.0,
}
opt = EmceeOptimizer(dbf)
res = opt.predict([10],
prior_rvs=[rv_zero()],
symbols_to_fit=[param],
zpf_kwargs=zpf_kwargs)
assert np.isreal(res)
assert np.isclose(res, -31.309645520830344, rtol=1e-6)
res_2 = opt.predict([10000000],
prior_rvs=[rv_zero()],
symbols_to_fit=[param],
zpf_kwargs=zpf_kwargs)
assert not np.isclose(res_2, -31.309645520830344, rtol=1e-6)
def test_tdb_species_with_charge_are_parsed_correctly():
"""The TDB species that have a charge should be properly parsed."""
tdb_species_str = """
ELEMENT /- ELECTRON_GAS 0.0000E+00 0.0000E+00 0.0000E+00!
ELEMENT VA VACUUM 0.0000E+00 0.0000E+00 0.0000E+00!
ELEMENT AL FCC_A1 2.6982E+01 4.5773E+03 2.8321E+01!
ELEMENT O 1/2_MOLE_O2(G) 1.5999E+01 4.3410E+03 1.0252E+02!
SPECIES AL+3 AL1/+3!
SPECIES O-2 O1/-2!
SPECIES O2 O2!
SPECIES AL2 AL2!
"""
test_dbf = Database.from_string(tdb_species_str, fmt='tdb')
assert len(test_dbf.species) == 8
species_dict = {sp.name: sp for sp in test_dbf.species}
assert species_dict['AL'].charge == 0
assert species_dict['AL+3'].charge == 3
assert species_dict['O-2'].charge == -2
def test_tdb_species_with_charge_are_parsed_correctly():
"""The TDB species that have a charge should be properly parsed."""
tdb_species_str = """
ELEMENT /- ELECTRON_GAS 0.0000E+00 0.0000E+00 0.0000E+00!
ELEMENT VA VACUUM 0.0000E+00 0.0000E+00 0.0000E+00!
ELEMENT AL FCC_A1 2.6982E+01 4.5773E+03 2.8321E+01!
ELEMENT O 1/2_MOLE_O2(G) 1.5999E+01 4.3410E+03 1.0252E+02!
SPECIES AL+3 AL1/+3!
SPECIES O-2 O1/-2!
SPECIES O2 O2!
SPECIES AL2 AL2!
"""
test_dbf = Database.from_string(tdb_species_str, fmt='tdb')
assert len(test_dbf.species) == 8
species_dict = {sp.name: sp for sp in test_dbf.species}
assert species_dict['AL'].charge == 0
assert species_dict['AL+3'].charge == 3
assert species_dict['O-2'].charge == -2
def test_lnprob_calculates_single_phase_probability_for_success(datasets_db):
"""lnprob() succesfully calculates the probability from single phase data"""
dbf = Database.from_string(CU_MG_TDB_FCC_ONLY, fmt='tdb')
datasets_db.insert(CU_MG_HM_MIX_SINGLE_FCC_A1)
comps = ['CU', 'MG', 'VA']
phases = ['FCC_A1']
param = 'VV0003'
orig_val = -14.0865
opt = EmceeOptimizer(dbf)
thermochemical_data = get_thermochemical_data(dbf,
comps,
phases,
datasets_db,
symbols_to_fit=[param])
thermochemical_kwargs = {
'dbf': dbf,
'comps': comps,
'thermochemical_data': thermochemical_data
}
res_orig = opt.predict([orig_val],
prior_rvs=[rv_zero()],
symbols_to_fit=[param],
thermochemical_kwargs=thermochemical_kwargs)
assert np.isreal(res_orig)
assert np.isclose(res_orig, -9.119484935312146, rtol=1e-6)
res_10 = opt.predict([10],
prior_rvs=[rv_zero()],
symbols_to_fit=[param],
thermochemical_kwargs=thermochemical_kwargs)
assert np.isreal(res_10)
assert np.isclose(res_10, -9.143559131626864, rtol=1e-6)
res_1e5 = opt.predict([1e5],
prior_rvs=[rv_zero()],
symbols_to_fit=[param],
thermochemical_kwargs=thermochemical_kwargs)
assert np.isreal(res_1e5)
assert np.isclose(res_1e5, -1359.1335466316268, rtol=1e-6)
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_associate_tdb(datasets_db):
"""lnprob() successfully calculates the probability for equilibrium """
dbf = Database.from_string(CU_MG_TDB_ASSOC, 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]
initial_params = {param: orig_val}
zpf_kwargs = {
'zpf_data': get_zpf_data(dbf, comps, phases, datasets_db,
initial_params),
'data_weight': 1.0,
}
opt = EmceeOptimizer(dbf)
res = opt.predict([10],
prior_rvs=[rv_zero()],
symbols_to_fit=[param],
zpf_kwargs=zpf_kwargs)
assert np.isreal(res)
assert not np.isinf(res)
assert np.isclose(res, -31.309645520830344, rtol=1e-6)
# The purpose of this part is to test that the driving forces (and probability)
# are different than the case of VV0001 = 10.
res_2 = opt.predict([-10000000],
prior_rvs=[rv_zero()],
symbols_to_fit=[param],
zpf_kwargs=zpf_kwargs)
assert np.isreal(res_2)
assert not np.isinf(res_2)
# Accept a large rtol becuase the results should be _very_ different
assert not np.isclose(res_2, -31.309645520830344, rtol=1e-2)
def test_database_parsing_of_floats_with_multiple_leading_zeros():
"""Floats with multiple leading zeros should be properly parsed (gh-143)"""
tdb_string = """$ The element has multiple leading zeros in '00.546'
ELEMENT CU FCC_A1 00.546 5004.0 33.15 !"""
dbf = Database.from_string(tdb_string, fmt='tdb')
assert "CU" in dbf.elements
def test_unknown_format_from_file():
"from_string: Unknown import file format raises NotImplementedError."
Database.from_string(ALCRNI_TDB, fmt='_fail_')
def test_unspecified_format_from_string():
"from_string: Unspecified string format raises ValueError."
Database.from_string(ALCRNI_TDB)
def test_export_import():
"Equivalence of Model using re-imported database."
test_model = Model(Database.from_string(ALNIPT_DBF.to_string(fmt='tdb'), fmt='tdb'), ['PT', 'NI', 'VA'], 'FCC_L12')
ref_model = Model(ALNIPT_DBF, ['NI', 'PT', 'VA'], 'FCC_L12')
assert test_model == ref_model
def test_incompatible_db_raises_error_with_kwarg_raise():
"Symbol names too long for Thermo-Calc raise error on write with kwarg raise."
test_dbf = Database.from_string(INVALID_TDB_STR, fmt='tdb')
test_dbf.to_string(fmt='tdb', if_incompatible='raise')
def test_unspecified_format_from_string():
"from_string: Unspecified string format raises ValueError."
Database.from_string(ALCRNI_TDB)
def test_database_diffusion():
"Diffusion database support."
assert Database(DIFFUSION_TDB).phases == \
Database.from_string(Database(DIFFUSION_TDB).to_string(fmt='tdb'), fmt='tdb').phases
def test_load_from_string():
"Test database loading from a string."
test_model = Model(Database.from_string(ALCRNI_TDB, fmt='tdb'), ['CR', 'NI'], 'L12_FCC')
assert test_model == REFERENCE_MOD
def test_export_import():
"Equivalence of re-imported database to original."
test_dbf = Database(ALNIPT_TDB)
assert Database.from_string(test_dbf.to_string(fmt='tdb'), fmt='tdb') == test_dbf
def test_export_import():
"Equivalence of Model using re-imported database."
test_model = Model(Database.from_string(ALCRNI_DBF.to_string(fmt='tdb'), fmt='tdb'), ['CR', 'NI'], 'L12_FCC')
ref_model = Model(ALCRNI_DBF, ['CR', 'NI'], 'L12_FCC')
assert test_model == ref_model
def test_database_diffusion():
"Diffusion database support."
assert Database(DIFFUSION_TDB).phases == \
Database.from_string(Database(DIFFUSION_TDB).to_string(fmt='tdb'), fmt='tdb').phases
def test_database_parsing_of_floats_with_multiple_leading_zeros():
"""Floats with multiple leading zeros should be properly parsed (gh-143)"""
tdb_string = """$ The element has multiple leading zeros in '00.546'
ELEMENT CU FCC_A1 00.546 5004.0 33.15 !"""
dbf = Database.from_string(tdb_string, fmt='tdb')
assert "CU" in dbf.elements
def test_database_parsing_of_floats_with_no_values_after_decimal():
"""Floats with no values after the decimal should be properly parsed (gh-143)"""
tdb_string = """$ The element has no values after the decimal in '5004.'
ELEMENT CU FCC_A1 63.546 5004. 33.15 !"""
dbf = Database.from_string(tdb_string, fmt='tdb')
assert "CU" in dbf.elements
def test_unknown_format_from_file():
"from_string: Unknown import file format raises NotImplementedError."
Database.from_string(ALCRNI_TDB, fmt='_fail_')
def test_database_parsing_of_floats_with_no_values_after_decimal():
"""Floats with no values after the decimal should be properly parsed (gh-143)"""
tdb_string = """$ The element has no values after the decimal in '5004.'
ELEMENT CU FCC_A1 63.546 5004. 33.15 !"""
dbf = Database.from_string(tdb_string, fmt='tdb')
assert "CU" in dbf.elements
def test_comma_templims():
"""Accept TEMPERATURE_LIMITS and default-limit commas."""
tdb_string = """
ELEMENT VA VACUUM 0.0 0.0 0.0 !
ELEMENT AL FCC_A1 26.98154 4540. 28.30 !
ELEMENT C GRAPHITE 12.011 1054.0 5.7423 !
ELEMENT CO HCP_A3 58.9332 4765.567 30.0400 !
ELEMENT CR BCC_A2 51.996 4050.0 23.5429 !
ELEMENT FE BCC_A2 55.847 4489.0 27.2797 !
ELEMENT MN CBCC_A12 54.9380 4995.696 32.2206 !
ELEMENT NI FCC_A1 58.69 4787.0 29.7955 !
TEMP-LIM 298 6000 !
$ ------------------------------------------------------------------------------
$
$ Fcc (cF4, Fm-3m) and MeX (cF8, Fm-3m)
$
PHASE FCC_A1 %A 2 1 1 !
CONST FCC_A1 : AL% CO% CR FE% MN% NI% : C VA% : !
$
$ Disordered part of FCC_4SL, identical to FCC_A1
$
PHASE A1_FCC %A 2 1 1 !
CONST A1_FCC : AL CO CR FE MN NI : C VA% : !
$
$ Bcc (cI2, Im-3m)
$
PHASE BCC_A2 %B 2 1 3 !
CONST BCC_A2 : AL CO CR% FE% MN% NI : C VA% : !
$
$ Disordered part of B2_BCC, identical to BCC_A2 (except Va)
$
PHASE A2_BCC %B 2 1 3 !
CONST A2_BCC : AL CO CR FE MN NI VA : C VA% : !
$
$ Prototype CsCl (cP2, Pm-3m)
$
PHASE B2_BCC %BO 3 0.5 0.5 3 !
CONST B2_BCC : AL CO CR FE MN% NI VA : AL CO CR FE MN NI% VA : C VA% : !
$
$ Hcp (hP2, P6_3/mmc) and Me2X (NiAs-type, hP4, P6_3/mmc, B8_1)
$
PHASE HCP_A3 %A 2 1 0.5 !
CONST HCP_A3 : AL CO% CR FE MN NI : C VA% : !
$ ------------------------------------------------------------------------------
$ Defaults
$
DEFINE-SYSTEM-DEFAULT ELEMENT 2 !
DEFAULT-COM DEFINE_SYSTEM_ELEMENT VA !
DEFAULT-COM REJECT_PHASE FCC_A1 BCC_A2 !
$DEFAULT-COM REJECT_PHASE A1_FCC FCC_4SL A2_BCC B2_BCC !
TYPE-DEF % SEQ * !
TYPE-DEF A GES AMEND_PHASE_DESCRIPTION @ MAGNETIC -3 0.28 !
TYPE-DEF B GES AMEND_PHASE_DESCRIPTION @ MAGNETIC -1 0.4 !
TYPE-DEF O GES AMEND_PHASE_DESCRIPTION B2_BCC DIS_PART A2_BCC !
TYPE-DEF Y GES AMEND_PHASE_DESCRIPTION FCC_4SL DIS_PART A1_FCC !
FUNCTION ZERO 298.15 0; 6000 N !
FUNCTION UN_ASS 298.15 0; 6000 N !
FUNCTION R 298.15 +8.31451; 6000 N !
$ ------------------------------------------------------------------------------
$ Element data
$ ------------------------------------------------------------------------------
$ Al
$
$ BCT_A5 and DIAMOND_A4 added in unary 3.0
$
PAR G(FCC_A1,AL:VA),, +GHSERAL; ,, N 91Din !
PAR G(A1_FCC,AL:VA),, +GHSERAL; , N 91Din !
PAR G(BCC_A2,AL:VA),, +GHSERAL+10083-4.813*T; 2900 N 91Din !
PAR G(A2_BCC,AL:VA),, +GHSERAL+10083-4.813*T; 2900 N 91Din !
PAR G(HCP_A3,AL:VA),, +GHSERAL+5481-1.8*T; 2900 N 91Din !
PAR G(CBCC_A12,AL:VA),, +GHSERAL
+10083.4-4.813*T; 2900 N 91Din !
PAR G(CUB_A13,AL:VA),, +GHSERAL
+10920.44-4.8116*T; 2900 N 91Din !
PAR G(BCT_A5,AL),, +GHSERAL+10083-4.813*T; 2900 N SGCOST !
PAR G(DIAMOND_A4,AL),, +GHSERAL+30*T; 2900 N SGCOST !
FUNCTION GHSERAL 298.15 -7976.15+137.093038*T-24.3671976*T*LN(T)
-0.001884662*T**2-8.77664E-07*T**3+74092*T**(-1);
700.00 Y -11276.24+223.048446*T-38.5844296*T*LN(T)
+0.018531982*T**2 -5.764227E-06*T**3+74092*T**(-1);
933.47 Y -11278.378+188.684153*T-31.748192*T*LN(T)
-1.230524E+28*T**(-9);
2900.00 N !
"""
dbf = Database.from_string(tdb_string, fmt='tdb')
assert "AL" in dbf.elements
def test_comma_templims():
"""Accept TEMPERATURE_LIMITS and default-limit commas."""
tdb_string = """
ELEMENT VA VACUUM 0.0 0.0 0.0 !
ELEMENT AL FCC_A1 26.98154 4540. 28.30 !
ELEMENT C GRAPHITE 12.011 1054.0 5.7423 !
ELEMENT CO HCP_A3 58.9332 4765.567 30.0400 !
ELEMENT CR BCC_A2 51.996 4050.0 23.5429 !
ELEMENT FE BCC_A2 55.847 4489.0 27.2797 !
ELEMENT MN CBCC_A12 54.9380 4995.696 32.2206 !
ELEMENT NI FCC_A1 58.69 4787.0 29.7955 !
TEMP-LIM 298 6000 !
$ ------------------------------------------------------------------------------
$
$ Fcc (cF4, Fm-3m) and MeX (cF8, Fm-3m)
$
PHASE FCC_A1 %A 2 1 1 !
CONST FCC_A1 : AL% CO% CR FE% MN% NI% : C VA% : !
$
$ Disordered part of FCC_4SL, identical to FCC_A1
$
PHASE A1_FCC %A 2 1 1 !
CONST A1_FCC : AL CO CR FE MN NI : C VA% : !
$
$ Bcc (cI2, Im-3m)
$
PHASE BCC_A2 %B 2 1 3 !
CONST BCC_A2 : AL CO CR% FE% MN% NI : C VA% : !
$
$ Disordered part of B2_BCC, identical to BCC_A2 (except Va)
$
PHASE A2_BCC %B 2 1 3 !
CONST A2_BCC : AL CO CR FE MN NI VA : C VA% : !
$
$ Prototype CsCl (cP2, Pm-3m)
$
PHASE B2_BCC %BO 3 0.5 0.5 3 !
CONST B2_BCC : AL CO CR FE MN% NI VA : AL CO CR FE MN NI% VA : C VA% : !
$
$ Hcp (hP2, P6_3/mmc) and Me2X (NiAs-type, hP4, P6_3/mmc, B8_1)
$
PHASE HCP_A3 %A 2 1 0.5 !
CONST HCP_A3 : AL CO% CR FE MN NI : C VA% : !
$ ------------------------------------------------------------------------------
$ Defaults
$
DEFINE-SYSTEM-DEFAULT ELEMENT 2 !
DEFAULT-COM DEFINE_SYSTEM_ELEMENT VA !
DEFAULT-COM REJECT_PHASE FCC_A1 BCC_A2 !
$DEFAULT-COM REJECT_PHASE A1_FCC FCC_4SL A2_BCC B2_BCC !
TYPE-DEF % SEQ * !
TYPE-DEF A GES AMEND_PHASE_DESCRIPTION @ MAGNETIC -3 0.28 !
TYPE-DEF B GES AMEND_PHASE_DESCRIPTION @ MAGNETIC -1 0.4 !
TYPE-DEF O GES AMEND_PHASE_DESCRIPTION B2_BCC DIS_PART A2_BCC !
TYPE-DEF Y GES AMEND_PHASE_DESCRIPTION FCC_4SL DIS_PART A1_FCC !
FUNCTION ZERO 298.15 0; 6000 N !
FUNCTION UN_ASS 298.15 0; 6000 N !
FUNCTION R 298.15 +8.31451; 6000 N !
$ ------------------------------------------------------------------------------
$ Element data
$ ------------------------------------------------------------------------------
$ Al
$
$ BCT_A5 and DIAMOND_A4 added in unary 3.0
$
PAR G(FCC_A1,AL:VA),, +GHSERAL; ,, N 91Din !
PAR G(A1_FCC,AL:VA),, +GHSERAL; , N 91Din !
PAR G(BCC_A2,AL:VA),, +GHSERAL+10083-4.813*T; 2900 N 91Din !
PAR G(A2_BCC,AL:VA),, +GHSERAL+10083-4.813*T; 2900 N 91Din !
PAR G(HCP_A3,AL:VA),, +GHSERAL+5481-1.8*T; 2900 N 91Din !
PAR G(CBCC_A12,AL:VA),, +GHSERAL
+10083.4-4.813*T; 2900 N 91Din !
PAR G(CUB_A13,AL:VA),, +GHSERAL
+10920.44-4.8116*T; 2900 N 91Din !
PAR G(BCT_A5,AL),, +GHSERAL+10083-4.813*T; 2900 N SGCOST !
PAR G(DIAMOND_A4,AL),, +GHSERAL+30*T; 2900 N SGCOST !
FUNCTION GHSERAL 298.15 -7976.15+137.093038*T-24.3671976*T*LN(T)
-0.001884662*T**2-8.77664E-07*T**3+74092*T**(-1);
700.00 Y -11276.24+223.048446*T-38.5844296*T*LN(T)
+0.018531982*T**2 -5.764227E-06*T**3+74092*T**(-1);
933.47 Y -11278.378+188.684153*T-31.748192*T*LN(T)
-1.230524E+28*T**(-9);
2900.00 N !
"""
dbf = Database.from_string(tdb_string, fmt='tdb')
assert "AL" in dbf.elements
def test_incompatible_db_raises_error_with_kwarg_raise():
"Symbol names too long for Thermo-Calc raise error on write with kwarg raise."
test_dbf = Database.from_string(INVALID_TDB_STR, fmt='tdb')
test_dbf.to_string(fmt='tdb', if_incompatible='raise')
def test_load_from_string():
"Test database loading from a string."
test_model = Model(Database.from_string(ALCRNI_TDB, fmt='tdb'),
['CR', 'NI'], 'L12_FCC')
assert test_model == REFERENCE_MOD
def test_export_import():
"Equivalence of re-imported database to original."
test_dbf = Database.from_string(REFERENCE_DBF.to_string(fmt='tdb'), fmt='tdb')
assert test_dbf == REFERENCE_DBF
