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Merge pull request #157 from ReactionMechanismGenerator/conf_dft
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Allow dont_gen_confs as an attribute of ARC
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@alongd
alongd committed Aug 2, 2019
2 parents 64ca1ed + 7b7f280 commit 17feba8
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Showing 3 changed files with 143 additions and 43 deletions.
13 changes: 11 additions & 2 deletions arc/main.py
View file
Original file line number Diff line number Diff line change
Expand Up @@ -96,6 +96,8 @@ class ARC(object):
confs_to_dft (int, optional): The number of lowest MD conformers to DFT at the conformers_level.
keep_checks (bool, optional): Whether to keep all Gaussian checkfiles when ARC terminates. True to keep,
default is False.
dont_gen_confs (list, optional): A list of species labels for which conformer generation should be avoided
if xyz is given.
Attributes:
project (str): The project's name. Used for naming the working directory.
Expand Down Expand Up @@ -141,6 +143,8 @@ class ARC(object):
bath_gas (str): A bath gas. Currently used in OneDMin to calc L-J parameters.
Allowed values are He, Ne, Ar, Kr, H2, N2, O2.
keep_checks (bool): Whether to keep all Gaussian checkfiles when ARC terminates. True to keep, default is False.
dont_gen_confs (list): A list of species labels for which conformer generation should be avoided
if xyz is given.
"""

Expand All @@ -150,7 +154,7 @@ def __init__(self, input_dict=None, project=None, arc_species_list=None, arc_rxn
t_max=None, t_count=None, verbose=logging.INFO, project_directory=None, max_job_time=120,
allow_nonisomorphic_2d=False, job_memory=14, ess_settings=None, bath_gas=None,
adaptive_levels=None, freq_scale_factor=None, calc_freq_factor=True, confs_to_dft=5,
keep_checks=False):
keep_checks=False, dont_gen_confs=None):
self.__version__ = VERSION
self.verbose = verbose
self.output = dict()
Expand Down Expand Up @@ -184,6 +188,7 @@ def __init__(self, input_dict=None, project=None, arc_species_list=None, arc_rxn
os.makedirs(self.project_directory)
initialize_log(log_file=os.path.join(self.project_directory, 'arc.log'), project=self.project,
project_directory=self.project_directory, verbose=self.verbose)
self.dont_gen_confs = dont_gen_confs if dont_gen_confs is not None else list()
self.t0 = time.time() # init time
self.execution_time = None
self.initial_trsh = initial_trsh if initial_trsh is not None else dict()
Expand Down Expand Up @@ -438,6 +443,8 @@ def as_dict(self):
if self.freq_scale_factor is not None:
restart_dict['freq_scale_factor'] = self.freq_scale_factor
restart_dict['calc_freq_factor'] = self.calc_freq_factor
if self.dont_gen_confs:
restart_dict['dont_gen_confs'] = self.dont_gen_confs
restart_dict['species'] = [spc.as_dict() for spc in self.arc_species_list]
restart_dict['reactions'] = [rxn.as_dict() for rxn in self.arc_rxn_list]
restart_dict['output'] = self.output # if read from_dict then it has actual values
Expand Down Expand Up @@ -511,6 +518,7 @@ def from_dict(self, input_dict, project=None, project_directory=None):
and input_dict['use_bac'] else ''
ess_settings = input_dict['ess_settings'] if 'ess_settings' in input_dict else global_ess_settings
self.ess_settings = check_ess_settings(ess_settings)
self.dont_gen_confs = input_dict['dont_gen_confs'] if 'dont_gen_confs' in input_dict else list()
if not self.job_types['fine']:
logger.info('\n')
logger.warning('Not using a fine grid for geometry optimization jobs')
Expand Down Expand Up @@ -702,7 +710,8 @@ def execute(self):
restart_dict=self.restart_dict, project_directory=self.project_directory,
max_job_time=self.max_job_time, allow_nonisomorphic_2d=self.allow_nonisomorphic_2d,
memory=self.memory, orbitals_level=self.orbitals_level,
adaptive_levels=self.adaptive_levels, confs_to_dft=self.confs_to_dft)
adaptive_levels=self.adaptive_levels, confs_to_dft=self.confs_to_dft,
dont_gen_confs=self.dont_gen_confs)

self.save_project_info_file()

Expand Down
109 changes: 71 additions & 38 deletions arc/scheduler.py
View file
Original file line number Diff line number Diff line change
Expand Up @@ -74,7 +74,7 @@ class Scheduler(object):
label_2: {...},
}
Note that rotor scans are located under Species.rotors_dict
Note: The rotor scan dicts are located under Species.rotors_dict
Args:
project (str): The project's name. Used for naming the working directory.
Expand All @@ -91,22 +91,22 @@ class Scheduler(object):
ts_guess_level (str, optional): The level of theory to use for TS guess comparisons.
orbitals_level (str, optional): The level of theory to use for calculating MOs (for plotting).
adaptive_levels (dict, optional): A dictionary of levels of theory for ranges of the number of heavy atoms in
the molecule. Keys are tuples of (min_num_atoms, max_num_atoms), values are
dictionaries with 'optfreq' and 'sp' as keys and levels of theory as values.
the molecule. Keys are tuples of (min_num_atoms, max_num_atoms), values are
dictionaries with 'optfreq' and 'sp' as keys and levels of theory as values.
rmgdatabase (RMGDatabase, optional): The RMG database object.
job_types (dict, optional): A dictionary of job types to execute. Keys are job types, values are boolean.
initial_trsh (dict, optional): Troubleshooting methods to try by default. Keys are ESS software,
values are trshs.
values are trshs.
bath_gas (str, optional): A bath gas. Currently used in OneDMin to calc L-J parameters.
Allowed values are He, Ne, Ar, Kr, H2, N2, O2.
Allowed values are He, Ne, Ar, Kr, H2, N2, O2.
restart_dict (dict, optional): A restart dictionary parsed from a YAML restart file.
max_job_time (int, optional): The maximal allowed job time on the server in hours.
allow_nonisomorphic_2d (bool, optional): Whether to optimize species even if they do not have a 3D conformer
that is isomorphic to the 2D graph representation.
that is isomorphic to the 2D graph representation.
memory (int, optional): The total allocated job memory in GB (14 by default).
testing (bool, optional): Used for internal ARC testing (generating the object w/o executing it).
dont_gen_confs (list, optional): A list of species labels for which conformer jobs were loaded from a restart
file, and additional conformer generation should be avoided.
file, or user-requested. Additional conformer generation should be avoided.
confs_to_dft (int, optional): The number of lowest MD conformers to DFT at the conformers_level.
Attributes:
Expand All @@ -117,35 +117,34 @@ class Scheduler(object):
rxn_list (list): Contains input :ref:`ARCReaction <reaction>` objects.
unique_species_labels (list): A list of species labels (checked for duplicates).
adaptive_levels (dict): A dictionary of levels of theory for ranges of the number of heavy atoms in the
molecule. Keys are tuples of (min_num_atoms, max_num_atoms), values are
dictionaries with 'optfreq' and 'sp' as keys and levels of theory as values.
molecule. Keys are tuples of (min_num_atoms, max_num_atoms), values are
dictionaries with 'optfreq' and 'sp' as keys and levels of theory as values.
job_dict (dict): A dictionary of all scheduled jobs. Keys are species / TS labels,
values are dictionaries where keys are job names (corresponding to
'running_jobs' if job is running) and values are the Job objects.
values are dictionaries where keys are job names (corresponding to
'running_jobs' if job is running) and values are the Job objects.
running_jobs (dict): A dictionary of currently running jobs (a subset of `job_dict`).
Keys are species/TS label, values are lists of job names
(e.g. 'conformer3', 'opt_a123').
Keys are species/TS label, values are lists of job names (e.g. 'conformer3', 'opt_a123').
servers_jobs_ids (list): A list of relevant job IDs currently running on the server.
output (dict): Output dictionary with status and final QM file paths for all species.
ess_settings (dict): A dictionary of available ESS and a corresponding server list.
initial_trsh (dict): Troubleshooting methods to try by default. Keys are ESS software, values are trshs.
restart_dict (dict): A restart dictionary parsed from a YAML restart file.
project_directory (str): Folder path for the project: the input file path or ARC/Projects/project-name.
save_restart (bool): Whether to start saving a restart file. ``True`` only after all species are loaded
(otherwise saves a partial file and may cause loss of information).
(otherwise saves a partial file and may cause loss of information).
restart_path (str): Path to the `restart.yml` file to be saved.
max_job_time (int): The maximal allowed job time on the server in hours.
testing (bool): Used for internal ARC testing (generating the object w/o executing it).
rmgdb (RMGDatabase): The RMG database object.
allow_nonisomorphic_2d (bool): Whether to optimize species even if they do not have a 3D conformer that is
isomorphic to the 2D graph representation.
isomorphic to the 2D graph representation.
dont_gen_confs (list): A list of species labels for which conformer jobs were loaded from a restart file,
and additional conformer generation should be avoided.
or user-requested. Additional conformer generation should be avoided for them.
confs_to_dft (int): The number of lowest MD conformers to DFT at the conformers_level.
memory (int): The total allocated job memory in GB (14 by default).
job_types (dict): A dictionary of job types to execute. Keys are job types, values are boolean.
bath_gas (str): A bath gas. Currently used in OneDMin to calc L-J parameters.
Allowed values are He, Ne, Ar, Kr, H2, N2, O2.
Allowed values are He, Ne, Ar, Kr, H2, N2, O2.
composite_method (str): A composite method to use.
"""
Expand Down Expand Up @@ -695,15 +694,13 @@ def run_conformer_jobs(self):
if not self.species_dict[label].is_ts and 'opt converged' not in self.output[label]['status'] \
and 'opt' not in self.job_dict[label] and 'composite' not in self.job_dict[label] \
and all([e is None for e in self.species_dict[label].conformer_energies]) \
and self.species_dict[label].number_of_atoms > 1 and label not in self.dont_gen_confs \
and 'geo' not in self.output[label] \
and (self.job_types['conformers'] or (not self.job_types['conformers']
and self.species_dict[label].initial_xyz is None
and self.species_dict[label].final_xyz is None
and not self.species_dict[label].conformers)):
# This is not a TS, opt (/composite) did not converged nor running, and conformer energies were not set
# (and it's not in self.dont_gen_confs). Also, either 'conformers' are set to True in job_types,
# or they are set to False but the species has no 3D information. Generate conformers.
and self.species_dict[label].number_of_atoms > 1 and 'geo' not in self.output[label] \
and (self.job_types['conformers'] and label not in self.dont_gen_confs
or self.species_dict[label].get_xyz(get_cheap=False) is None):
# This is not a TS, opt (/composite) did not converged nor running, and conformer energies were not set.
# Also, either 'conformers' are set to True in job_types (and it's not in dont_gen_confs),
# or they are set to False (or it's in dont_gen_confs), but the species has no 3D information.
# Generate conformers.
if not log_info_printed:
logger.info('\nStarting (non-TS) species conformational analysis...\n')
log_info_printed = True
Expand All @@ -720,10 +717,9 @@ def run_conformer_jobs(self):
else:
# run the combinatorial method w/o fitting a force field
self.species_dict[label].generate_conformers(confs_to_dft=self.confs_to_dft,
plot_path=os.path.join(self.project_directory,
'output', 'Species',
label, 'geometry',
'conformers'))
plot_path=os.path.join(
self.project_directory, 'output', 'Species',
label, 'geometry', 'conformers'))
self.process_conformers(label)
elif not self.job_types['conformers']:
# we're not running conformer jobs
Expand All @@ -743,10 +739,25 @@ def run_ts_conformer_jobs(self, label):
multiplicity=self.species_dict[label].multiplicity,
charge=self.species_dict[label].charge, is_ts=True,
ts_methods=[tsg.method for tsg in self.species_dict[label].ts_guesses])
self.job_dict[label]['conformers'] = dict()
for i, tsg in enumerate(self.species_dict[label].ts_guesses):
self.run_job(label=label, xyz=tsg.xyz, level_of_theory=self.ts_guess_level, job_type='conformer',
conformer=i)
if len(self.species_dict[label].conformers) > 1:
self.job_dict[label]['conformers'] = dict()
for i, xyz in enumerate(self.species_dict[label].conformers):
self.run_job(label=label, xyz=xyz, level_of_theory=self.ts_guess_level, job_type='conformer',
conformer=i)
elif len(self.species_dict[label].conformers) == 1:
if 'opt' not in self.job_dict[label] and 'composite' not in self.job_dict[label]:
# proceed only if opt (/composite) not already spawned
rxn = ''
if self.species_dict[label].rxn_label is not None:
rxn = ' of reaction ' + self.species_dict[label].rxn_label
logger.info('Only one TS guess is available for species {0}{1},'
' using it for geometry optimization'.format(label, rxn))
self.species_dict[label].initial_xyz = self.species_dict[label].conformers[0]
if not self.composite_method:
self.run_opt_job(label)
else:
self.run_composite_job(label)
self.species_dict[label].chosen_ts_method = self.species_dict[label].ts_guesses[0].method

def run_opt_job(self, label):
"""
Expand Down Expand Up @@ -994,17 +1005,39 @@ def spawn_md_jobs(self, label, prev_conf_list=None, num_confs=None):
def process_conformers(self, label):
"""
Process the generated conformers and spawn DFT jobs at the conformer_level.
If more than one conformer is available, they will be optimized at the DFT conformer_level.
"""
plotter.save_conformers_file(project_directory=self.project_directory, label=label,
xyzs=self.species_dict[label].conformers, level_of_theory=self.conformer_level,
multiplicity=self.species_dict[label].multiplicity,
charge=self.species_dict[label].charge, is_ts=False) # before optimization
if self.species_dict[label].initial_xyz is None and self.species_dict[label].final_xyz is None \
and not self.testing:
self.job_dict[label]['conformers'] = dict()
for i, xyz in enumerate(self.species_dict[label].conformers):
self.run_job(label=label, xyz=xyz, level_of_theory=self.conformer_level,
job_type='conformer', conformer=i)
if len(self.species_dict[label].conformers) > 1:
self.job_dict[label]['conformers'] = dict()
for i, xyz in enumerate(self.species_dict[label].conformers):
self.run_job(label=label, xyz=xyz, level_of_theory=self.conformer_level,
job_type='conformer', conformer=i)
elif len(self.species_dict[label].conformers) == 1:
logger.info('Only one conformer is available for species {0}, '
'using it as initial xyz'.format(label))
self.species_dict[label].initial_xyz = self.species_dict[label].conformers[0]
if not self.composite_method:
if self.job_types['opt']:
self.run_opt_job(label)
else:
if self.job_types['freq']:
self.run_freq_job(label)
if self.job_types['sp']:
self.run_sp_job(label)
if self.job_types['1d_rotors']:
self.run_scan_jobs(label)
if self.job_types['onedmin']:
self.run_onedmin_job(label)
if self.job_types['orbitals']:
self.run_orbitals_job(label)
else:
self.run_composite_job(label)

def parse_conformer(self, job, label, i):
"""
Expand Down

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