def setUpClass(cls):
"""
A method that is run before all unit tests in this class.
"""
cls.maxDiff = None
cls.ess_settings = {'gaussian': ['server1'], 'molpro': ['server2', 'server1'], 'qchem': ['server1']}
cls.project_directory = os.path.join(arc_path, 'Projects', 'arc_project_for_testing_delete_after_usage3')
cls.spc1 = ARCSpecies(label=str('methylamine'), smiles=str('CN'))
cls.spc2 = ARCSpecies(label=str('C2H6'), smiles=str('CC'))
cls.job1 = Job(project='project_test', ess_settings=cls.ess_settings, species_name='methylamine',
xyz='C 0.0 0.0 0.0', job_type='conformer', conformer=0, level_of_theory='b97-d3/6-311+g(d,p)',
multiplicity=1, project_directory=cls.project_directory, job_num=101)
cls.job2 = Job(project='project_test', ess_settings=cls.ess_settings, species_name='methylamine',
xyz='C 0.0 0.0 0.0', job_type='conformer', conformer=1, level_of_theory='b97-d3/6-311+g(d,p)',
multiplicity=1, project_directory=cls.project_directory, job_num=102)
cls.job3 = Job(project='project_test', ess_settings=cls.ess_settings, species_name='C2H6', xyz='C 0.0 0.0 0.0',
job_type='freq', level_of_theory='wb97x-d3/6-311+g(d,p)', multiplicity=1,
project_directory=cls.project_directory, software='qchem', job_num=103)
cls.rmgdb = rmgdb.make_rmg_database_object()
cls.job_types1 = {'conformers': True,
'opt': True,
'fine_grid': False,
'freq': True,
'sp': True,
'1d_rotors': False,
'orbitals': False,
'lennard_jones': False,
}
cls.sched1 = Scheduler(project='project_test', ess_settings=cls.ess_settings, species_list=[cls.spc1, cls.spc2],
composite_method='', conformer_level=default_levels_of_theory['conformer'],
opt_level=default_levels_of_theory['opt'], freq_level=default_levels_of_theory['freq'],
sp_level=default_levels_of_theory['sp'], scan_level=default_levels_of_theory['scan'],
ts_guess_level=default_levels_of_theory['ts_guesses'], rmgdatabase=cls.rmgdb,
project_directory=cls.project_directory, testing=True, job_types=cls.job_types1,
orbitals_level=default_levels_of_theory['orbitals'], adaptive_levels=None)
def test_determine_adaptive_level(self):
"""Test the determine_adaptive_level() method"""
adaptive_levels = {(1, 5): {'optfreq': 'wb97xd/6-311+g(2d,2p)',
'sp': 'ccsd(t)-f12/aug-cc-pvtz-f12'},
(6, 15): {'optfreq': 'b3lyp/cbsb7',
'sp': 'dlpno-ccsd(t)/def2-tzvp/c'},
(16, 30): {'optfreq': 'b3lyp/6-31g(d,p)',
'sp': 'wb97xd/6-311+g(2d,2p)'},
(31, 'inf'): {'optfreq': 'b3lyp/6-31g(d,p)',
'sp': 'b3lyp/6-311+g(d,p)'}}
sched2 = Scheduler(project='project_test', ess_settings=self.ess_settings, species_list=[self.spc1, self.spc2],
composite_method='', conformer_level=default_levels_of_theory['conformer'],
opt_level=default_levels_of_theory['opt'], freq_level=default_levels_of_theory['freq'],
sp_level=default_levels_of_theory['sp'], scan_level=default_levels_of_theory['scan'],
ts_guess_level=default_levels_of_theory['ts_guesses'], rmgdatabase=self.rmgdb,
project_directory=self.project_directory, testing=True, job_types=self.job_types1,
orbitals_level=default_levels_of_theory['orbitals'], adaptive_levels=adaptive_levels)
level1 = sched2.determine_adaptive_level(original_level_of_theory='some_original_level',
job_type='opt', heavy_atoms=5)
level2 = sched2.determine_adaptive_level(original_level_of_theory='some_original_level',
job_type='freq', heavy_atoms=5)
level3 = sched2.determine_adaptive_level(original_level_of_theory='some_original_level',
job_type='opt', heavy_atoms=20)
level4 = sched2.determine_adaptive_level(original_level_of_theory='some_original_level',
job_type='composite', heavy_atoms=50)
level5 = sched2.determine_adaptive_level(original_level_of_theory='some_original_level',
job_type='orbitals', heavy_atoms=5)
level6 = sched2.determine_adaptive_level(original_level_of_theory='some_original_level',
job_type='sp', heavy_atoms=7)
level7 = sched2.determine_adaptive_level(original_level_of_theory='some_original_level',
job_type='sp', heavy_atoms=25)
self.assertEqual(level1, 'wb97xd/6-311+g(2d,2p)')
self.assertEqual(level2, 'wb97xd/6-311+g(2d,2p)')
self.assertEqual(level3, 'b3lyp/6-31g(d,p)')
self.assertEqual(level4, 'b3lyp/6-31g(d,p)')
self.assertEqual(level5, 'some_original_level')
self.assertEqual(level6, 'dlpno-ccsd(t)/def2-tzvp/c')
self.assertEqual(level7, 'wb97xd/6-311+g(2d,2p)')
def determine_scaling_factors(
levels: List[Union[Level, dict, str]],
ess_settings: Optional[dict] = None,
init_log: Optional[bool] = True,
) -> list:
"""
Determine the zero-point energy, harmonic frequencies, and fundamental frequencies scaling factors
for a given frequencies level of theory.
Args:
levels (list): A list of frequencies levels of theory for which scaling factors are determined.
Entries are either Level instances, dictionaries, or simple string representations.
If a single entry is given, it will be converted to a list.
ess_settings (dict, optional): A dictionary of available ESS (keys) and a corresponding server list (values).
init_log (bool, optional): Whether to initialize the logger. ``True`` to initialize.
Should be ``True`` when called as a standalone, but ``False`` when called within ARC.
Returns:
list: The determined frequency scaling factors.
"""
if init_log:
initialize_log(log_file='scaling_factor.log',
project='Scaling Factors')
if not isinstance(levels, (list, tuple)):
levels = [levels]
levels = [
Level(repr=level) if not isinstance(level, Level) else level
for level in levels
]
t0 = time.time()
logger.info('\n\n\n')
logger.info(HEADER)
logger.info('\n\nstarting ARC...\n')
# only run opt (fine) and freq
job_types = initialize_job_types(
dict()) # get the defaults, so no job type is missing
job_types = {job_type: False for job_type in job_types.keys()}
job_types['opt'], job_types['fine'], job_types['freq'] = True, True, True
lambda_zpes, zpe_dicts, times = list(), list(), list()
for level in levels:
t1 = time.time()
logger.info(
f'\nComputing scaling factors at the {level} level of theory...\n\n'
)
renamed_level = rename_level(str(level))
project = 'scaling_' + renamed_level
project_directory = os.path.join(arc_path, 'Projects',
'scaling_factors', project)
if os.path.isdir(project_directory):
shutil.rmtree(project_directory)
species_list = get_species_list()
if level.method_type == 'composite':
freq_level = None
composite_method = level
job_types['freq'] = False
else:
freq_level = level
composite_method = None
ess_settings = check_ess_settings(ess_settings or global_ess_settings)
Scheduler(project=project,
project_directory=project_directory,
species_list=species_list,
composite_method=composite_method,
opt_level=freq_level,
freq_level=freq_level,
ess_settings=ess_settings,
job_types=job_types,
allow_nonisomorphic_2d=True)
zpe_dict = dict()
for spc in species_list:
zpe_dict[spc.label] = parse_zpe(
os.path.join(project_directory, 'output', 'Species', spc.label,
'geometry',
'freq.out')) * 1000 # convert to J/mol
zpe_dicts.append(zpe_dict)
lambda_zpes.append(
calculate_truhlar_scaling_factors(zpe_dict=zpe_dict,
level=str(level)))
times.append(time_lapse(t1))
summarize_results(lambda_zpes=lambda_zpes,
levels=[str(level) for level in levels],
zpe_dicts=zpe_dicts,
times=times,
overall_time=time_lapse(t0))
logger.info('\n\n\n')
logger.info(HEADER)
harmonic_freq_scaling_factors = [
lambda_zpe * 1.014 for lambda_zpe in lambda_zpes
]
return harmonic_freq_scaling_factors
def setUpClass(cls):
"""
A method that is run before all unit tests in this class.
"""
cls.maxDiff = None
cls.ess_settings = {
'gaussian': ['server1'],
'molpro': ['server2', 'server1'],
'qchem': ['server1']
}
cls.project_directory = os.path.join(
arc_path, 'Projects',
'arc_project_for_testing_delete_after_usage3')
cls.spc1 = ARCSpecies(label='methylamine', smiles='CN')
cls.spc2 = ARCSpecies(label='C2H6', smiles='CC')
xyz1 = """C 1.11424367 -0.01231165 -0.11493630
C -0.07257945 -0.17830906 -0.16010022
O -1.38500471 -0.36381519 -0.20928090
H 2.16904830 0.12689206 -0.07152274
H -1.82570782 0.42754384 -0.56130718"""
cls.spc3 = ARCSpecies(label='CtripCO', smiles='C#CO', xyz=xyz1)
xyz2 = {
'symbols': ('C', ),
'isotopes': (12, ),
'coords': ((0.0, 0.0, 0.0), )
}
cls.job1 = Job(project='project_test',
ess_settings=cls.ess_settings,
species_name='methylamine',
xyz=xyz2,
job_type='conformer',
conformer=0,
level={
'method': 'b97-d3',
'basis': '6-311+g(d,p)'
},
multiplicity=1,
project_directory=cls.project_directory,
job_num=101)
cls.job2 = Job(project='project_test',
ess_settings=cls.ess_settings,
species_name='methylamine',
xyz=xyz2,
job_type='conformer',
conformer=1,
level={
'method': 'b97-d3',
'basis': '6-311+g(d,p)'
},
multiplicity=1,
project_directory=cls.project_directory,
job_num=102)
cls.job3 = Job(project='project_test',
ess_settings=cls.ess_settings,
species_name='C2H6',
xyz=xyz2,
job_type='freq',
level={
'method': 'wb97x-d3',
'basis': '6-311+g(d,p)'
},
multiplicity=1,
project_directory=cls.project_directory,
software='qchem',
job_num=103)
cls.rmg_database = rmgdb.make_rmg_database_object()
cls.job_types1 = {
'conformers': True,
'opt': True,
'fine_grid': False,
'freq': True,
'sp': True,
'rotors': False,
'orbitals': False,
'lennard_jones': False,
}
cls.sched1 = Scheduler(
project='project_test',
ess_settings=cls.ess_settings,
species_list=[cls.spc1, cls.spc2, cls.spc3],
composite_method=None,
conformer_level=Level(repr=default_levels_of_theory['conformer']),
opt_level=Level(repr=default_levels_of_theory['opt']),
freq_level=Level(repr=default_levels_of_theory['freq']),
sp_level=Level(repr=default_levels_of_theory['sp']),
scan_level=Level(repr=default_levels_of_theory['scan']),
ts_guess_level=Level(repr=default_levels_of_theory['ts_guesses']),
rmg_database=cls.rmg_database,
project_directory=cls.project_directory,
testing=True,
job_types=cls.job_types1,
orbitals_level=default_levels_of_theory['orbitals'],
adaptive_levels=None,
)
def test_determine_adaptive_level(self):
"""Test the determine_adaptive_level() method"""
# adaptive_levels get converted to ``Level`` objects in main, but here we skip main and test Scheduler directly
adaptive_levels = {
(1, 5): {
('opt', 'freq'): Level(repr='wb97xd/6-311+g(2d,2p)'),
('sp', ): Level(repr='ccsd(t)-f12/aug-cc-pvtz-f12')
},
(6, 15): {
('opt', 'freq'): Level(repr='b3lyp/cbsb7'),
('sp', ): Level(repr='dlpno-ccsd(t)/def2-tzvp')
},
(16, 30): {
('opt', 'freq'): Level(repr='b3lyp/6-31g(d,p)'),
('sp', ): Level(repr='wb97xd/6-311+g(2d,2p)')
},
(31, 'inf'): {
('opt', 'freq'): Level(repr='b3lyp/6-31g(d,p)'),
('sp', ): Level(repr='b3lyp/6-311+g(d,p)')
}
}
sched2 = Scheduler(
project='project_test',
ess_settings=self.ess_settings,
species_list=[self.spc1, self.spc2],
composite_method=None,
conformer_level=default_levels_of_theory['conformer'],
opt_level=default_levels_of_theory['opt'],
freq_level=default_levels_of_theory['freq'],
sp_level=default_levels_of_theory['sp'],
scan_level=default_levels_of_theory['scan'],
ts_guess_level=default_levels_of_theory['ts_guesses'],
rmg_database=self.rmg_database,
project_directory=self.project_directory,
testing=True,
job_types=self.job_types1,
orbitals_level=default_levels_of_theory['orbitals'],
adaptive_levels=adaptive_levels)
original_level = Level(method='CBS-QB3')
level1 = sched2.determine_adaptive_level(
original_level_of_theory=original_level,
job_type='opt',
heavy_atoms=5)
level2 = sched2.determine_adaptive_level(
original_level_of_theory=original_level,
job_type='freq',
heavy_atoms=5)
level3 = sched2.determine_adaptive_level(
original_level_of_theory=original_level,
job_type='opt',
heavy_atoms=20)
level4 = sched2.determine_adaptive_level(
original_level_of_theory=original_level,
job_type='composite',
heavy_atoms=50)
level5 = sched2.determine_adaptive_level(
original_level_of_theory=original_level,
job_type='orbitals',
heavy_atoms=5)
level6 = sched2.determine_adaptive_level(
original_level_of_theory=original_level,
job_type='sp',
heavy_atoms=7)
level7 = sched2.determine_adaptive_level(
original_level_of_theory=original_level,
job_type='sp',
heavy_atoms=25)
self.assertEqual(level1.simple(), 'wb97xd/6-311+g(2d,2p)')
self.assertEqual(level2.simple(), 'wb97xd/6-311+g(2d,2p)')
self.assertEqual(level3.simple(), 'b3lyp/6-31g(d,p)')
self.assertEqual(level4.simple(), 'cbs-qb3')
self.assertEqual(level5.simple(), 'cbs-qb3')
self.assertEqual(level6.simple(), 'dlpno-ccsd(t)/def2-tzvp')
self.assertEqual(level7.simple(), 'wb97xd/6-311+g(2d,2p)')
def test_append_conformers(self):
"""Test that ARC correctly parses its own conformer files"""
ess_settings = {'gaussian': 'server1', 'molpro': 'server2', 'qchem': 'server1'}
project_directory = os.path.join(arc_path, 'Projects', 'arc_project_for_testing_delete_after_usage4')
spc1 = ARCSpecies(label=str('vinoxy'), smiles=str('C=C[O]'))
rmgdb = make_rmg_database_object()
job_types1 = {'conformers': True,
'opt': True,
'fine_grid': False,
'freq': True,
'sp': True,
'1d_rotors': False,
'orbitals': False,
'lennard_jones': False,
}
sched1 = Scheduler(project='project_test', ess_settings=ess_settings, species_list=[spc1],
composite_method='', conformer_level=default_levels_of_theory['conformer'],
opt_level=default_levels_of_theory['opt'], freq_level=default_levels_of_theory['freq'],
sp_level=default_levels_of_theory['sp'], scan_level=default_levels_of_theory['scan'],
ts_guess_level=default_levels_of_theory['ts_guesses'], rmgdatabase=rmgdb,
project_directory=project_directory, testing=True, job_types=job_types1,
orbitals_level=default_levels_of_theory['orbitals'], adaptive_levels=None)
xyzs = ["""O 1.09068700 0.26516800 -0.16706300
C 2.92204100 -1.18335700 -0.38884900
C 2.27655500 -0.00373900 0.08543500
H 2.36544800 -1.88781000 -0.99914600
H 3.96112000 -1.38854500 -0.14958800
H 2.87813500 0.68828400 0.70399400
""",
"""O 1.19396100 -0.06003700 0.03890100
C 3.18797000 0.77061300 -0.87352700
C 2.43591200 -0.04439300 0.02171600
H 4.27370000 0.76090200 -0.86286100
H 2.66641700 1.41155700 -1.57757300
H 3.00398000 -0.68336800 0.72359800
""",
"""O 1.35241100 -1.02956000 -0.24056200
C -0.72084300 0.01308200 0.09573000
C 0.69217700 0.01185100 -0.09044300
H -1.25803800 -0.93018100 0.10926800
H -1.26861200 0.94177100 0.22420100
H 1.20290400 0.99303700 -0.09819400
""",
"""O -1.40102900 -0.98575100 -0.11588500
C 0.72457000 -0.01076700 0.06448800
C -0.69494600 0.03450000 -0.06206300
H 1.22539000 -0.97248000 0.11741200
H 1.31277400 0.90087100 0.10878400
H -1.16675800 1.03362600 -0.11273700
"""]
energies = [0, 5, 5, 5] # J/mol
save_conformers_file(project_directory=project_directory, label='vinoxy', xyzs=xyzs, level_of_theory='level1',
multiplicity=2, charge=0)
self.assertTrue(os.path.isfile(os.path.join(project_directory, 'output', 'Species', 'vinoxy', 'geometry',
'conformers', 'conformers_before_optimization.txt')))
save_conformers_file(project_directory=project_directory, label='vinoxy', xyzs=xyzs, level_of_theory='level1',
multiplicity=2, charge=0, energies=energies)
self.assertTrue(os.path.isfile(os.path.join(project_directory, 'output', 'Species', 'vinoxy', 'geometry',
'conformers', 'conformers_after_optimization.txt')))
spc2 = ARCSpecies(label=str('vinoxy'), smiles=str('C=C[O]'), xyz=os.path.join(
project_directory, 'output', 'Species', 'vinoxy', 'geometry', 'conformers',
'conformers_before_optimization.txt'))
spc3 = ARCSpecies(label=str('vinoxy'), smiles=str('C=C[O]'), xyz=os.path.join(
project_directory, 'output', 'Species', 'vinoxy', 'geometry', 'conformers',
'conformers_after_optimization.txt'))
self.assertEqual(spc2.conformers[2], xyzs[2])
self.assertEqual(spc3.conformers[2], xyzs[2])
self.assertEqual(spc3.conformer_energies[2], energies[2])
def determine_scaling_factors(levels_of_theory,
ess_settings=None,
init_log=True):
"""
Determine the zero-point energy, harmonic frequencies, and fundamental frequencies scaling factors
for a given frequencies level of theory.
Args:
levels_of_theory (list, str): A list of frequencies levels of theory
for which scaling factors are determined.
A string can also be passed for just one level of theory.
ess_settings (dict, optional): A dictionary of available ESS (keys) and a corresponding server list (values).
init_log (bool, optional): Whether to initialize the logger. True to initialize.
Should be True when called as a stand alone, and False when called within ARC.
Returns:
str: The modified level of theory
"""
if init_log:
initialize_log(log_file='scaling_factor.log',
project='Scaling Factors')
if isinstance(levels_of_theory, (str, unicode)):
levels_of_theory = [levels_of_theory]
if not isinstance(levels_of_theory, list):
raise InputError(
'levels_of_theory must be a list (or a string if only one level is desired). Got: {0}'
.format(type(levels_of_theory)))
t0 = time.time()
logger.info('\n\n\n')
logger.info(HEADER)
logger.info('\n\nstarting ARC...\n')
# only run opt (fine) and freq
job_types = initialize_job_types(
dict()) # get the defaults, so no job type is missing
job_types = {job_type: False for job_type in job_types.keys()}
job_types['opt'], job_types['fine'], job_types['freq'] = True, True, True
lambda_zpes, zpe_dicts, times = list(), list(), list()
for level_of_theory in levels_of_theory:
t1 = time.time()
logger.info(
'\nComputing scaling factors at the {0} level of theory...\n\n'.
format(level_of_theory))
renamed_level = rename_level(level_of_theory)
project = 'scaling_' + renamed_level
project_directory = os.path.join(arc_path, 'Projects',
'scaling_factors', project)
species_list = get_species_list()
if '//' in level_of_theory:
raise InputError(
'Level of theory should either be a composite method or in a method/basis-set format. '
'Got {0}'.format(level_of_theory))
if '/' not in level_of_theory: # assume this is a composite method
freq_level = ''
composite_method = level_of_theory.lower()
job_types['freq'] = False
else:
freq_level = level_of_theory.lower()
composite_method = ''
job_types['freq'] = True
ess_settings = check_ess_settings(ess_settings or global_ess_settings)
Scheduler(project=project,
project_directory=project_directory,
species_list=species_list,
composite_method=composite_method,
opt_level=freq_level,
freq_level=freq_level,
ess_settings=ess_settings,
job_types=job_types,
allow_nonisomorphic_2d=True)
zpe_dict = dict()
for spc in species_list:
try:
zpe = get_zpe(
os.path.join(project_directory, 'output', 'Species',
spc.label, 'geometry', 'freq.out'))
except Exception:
zpe = None
zpe_dict[spc.label] = zpe
zpe_dicts.append(zpe_dict)
lambda_zpes.append(
calculate_truhlar_scaling_factors(zpe_dict, level_of_theory))
times.append(time_lapse(t1))
summarize_results(lambda_zpes, levels_of_theory, zpe_dicts, times,
time_lapse(t0))
logger.info('\n\n\n')
logger.info(HEADER)
harmonic_freq_scaling_factors = [
lambda_zpe * 1.014 for lambda_zpe in lambda_zpes
]
return harmonic_freq_scaling_factors
