def main(reaction_label=None, reaction_family=None):
"""
Run AutoTST to generate a TS guess
Currently only works for H Abstraction
"""
if has_auto_tst:
if reaction_label is None:
# Parse the command-line arguments (requires the argparse module)
args = parse_command_line_arguments()
reaction_label = str(args.reaction_label)
reaction_family = str(args.reaction_family)
reaction_family = str('H_Abstraction') if reaction_family is None else reaction_family
try:
reaction = AutoTST_Reaction(label=reaction_label, reaction_family=reaction_family)
except AssertionError as e:
logger.error('Could not generate a TS guess using AutoTST for reaction {0}'.format(reaction_label))
raise TSError('Could not generate AutoTST guess:\n{0}'.format(e))
else:
positions = reaction.ts.ase_ts.get_positions()
numbers = reaction.ts.ase_ts.get_atomic_numbers()
xyz_guess = xyz_to_str(xyz_dict=xyz_from_data(coords=positions, numbers=numbers))
xyz_path = os.path.join(arc_path, 'arc', 'ts', 'auto_tst.xyz')
with open(xyz_path, 'w') as f:
f.write(xyz_guess)
def main():
"""
Run AutoTST to generate a TS guess
Currently only works for H Abstraction
"""
# Parse the command-line arguments (requires the argparse module)
args = parse_command_line_arguments()
reaction_label = str(args.reaction_label)
reaction_family = str(args.reaction_family)
try:
reaction = AutoTST_Reaction(label=reaction_label,
reaction_family=reaction_family)
except AssertionError:
logging.error(
'Could not generate a TS guess using AutoTST for reaction {0}'.
format(reaction_label))
raise TSError('Could not generate AutoTST guess')
else:
positions = reaction.ts.ase_ts.get_positions()
numbers = reaction.ts.ase_ts.get_atomic_numbers()
xyz_guess = get_xyz_string(coord=positions, number=numbers)
xyz_path = os.path.join(arc_path, 'arc', 'ts', 'auto_tst.xyz')
with open(xyz_path, 'wb') as f:
f.write(xyz_guess)
from autotst.geometry import Bond, Angle, Torsion
from ase.io.gaussian import read_gaussian_out
# To perform TS search
from ase.calculators.gaussian import Gaussian
from autotst.calculators.gaussian import AutoTST_Gaussian
from autotst.calculators.vibrational_analysis import Vibrational_Analysis, percent_change
from autotst.calculators.cantherm import AutoTST_CanTherm
# For conformer analysis
from ase.calculators.lj import LennardJones
from autotst.conformer.utilities import create_initial_population, select_top_population
from autotst.conformer.ga import perform_ga
from autotst.conformer.simple_es import perform_simple_es
test_reaction = AutoTST_Reaction("[CH]=CC=C+[O]O_[CH]=C[C]=C+OO",
"H_Abstraction")
scratch_dir = "./gaussian_example"
### Performing the partial optimizations
tst_calculators = AutoTST_Gaussian(test_reaction,
scratch=scratch_dir,
save_directory=".")
kinetics = tst_calculators.read_kinetics_file()
if kinetics:
logging.info("We have previously loaded kinetics:")
logging.info("{0!r}".format(kinetics['reaction']))
else:
def xyz_graph_reader_ts(graph_file):
with open(graph_file, 'rb') as f:
na = int(f.readline())
properties = f.readline()
g, l = init_graph_ts(properties)
atom_properties = []
# Atoms properties
for i in range(na):
a_properties = f.readline()
a_properties = a_properties.replace('.*^', 'e')
a_properties = a_properties.replace('*^', 'e')
a_properties = a_properties.split()
atom_properties.append(a_properties)
# rxn_string
rxn_label = graph_file.split('/')[-1].split('.')[0]
autotst_ts = AutoTST_Reaction(rxn_label, "H_Abstraction")
rdkit_ts = autotst_ts.ts.rdkit_ts
fdef_name = os.path.join(RDConfig.RDDataDir, 'BaseFeatures.fdef')
factory = ChemicalFeatures.BuildFeatureFactory(fdef_name)
feats = factory.GetFeaturesForMol(rdkit_ts)
for i in range(0, rdkit_ts.GetNumAtoms()):
atom_i = rdkit_ts.GetAtomWithIdx(i)
g.add_node(
i,
a_type=atom_i.GetSymbol(),
a_num=atom_i.GetAtomicNum(),
acceptor=0,
donor=0,
aromatic=atom_i.GetIsAromatic(),
hybridization=atom_i.GetHybridization(),
num_h=atom_i.GetTotalNumHs(),
coord=np.array(atom_properties[i][1:4]).astype(np.float),
)
for i in range(0, len(feats)):
if feats[i].GetFamily() == 'Donor':
node_list = feats[i].GetAtomIds()
for i in node_list:
g.node[i]['donor'] = 1
elif feats[i].GetFamily() == 'Acceptor':
node_list = feats[i].GetAtomIds()
for i in node_list:
g.node[i]['acceptor'] = 1
# Read Edges
for i in range(0, rdkit_ts.GetNumAtoms()):
for j in range(0, rdkit_ts.GetNumAtoms()):
e_ij = rdkit_ts.GetBondBetweenAtoms(i, j)
if e_ij is not None:
g.add_edge(i,
j,
b_type=e_ij.GetBondType(),
distance=np.linalg.norm(g.node[i]['coord'] -
g.node[j]['coord']))
else:
# Unbonded
g.add_edge(i,
j,
b_type=None,
distance=np.linalg.norm(g.node[i]['coord'] -
g.node[j]['coord']))
return g, l