def testAll(self):
data = {
'CC':[1,0],
'CCC':[2,0],
'CCCC':[3,1],
'C=C':[0,0],
'C=CC':[1,0],
'C=C[CH2]':[0,0],
'CC=C[CH2]':[1,0],
'C1CCCC1':[0,0],
'CO':[1,0],
'C=CO':[1,1],
}
for name in data:
par = Parameters()
qc = QuantumChemistry(par)
mol = StationaryPoint(name,0,1,smiles = name)
mol.characterize()
hir_exp = data[name][0]
conf_exp = data[name][1]
hir_calc = len(mol.dihed)
conf_calc = len(mol.conf_dihed)
self.assertEqual(hir_exp ,hir_calc ,name + ': HIR, expected: {}, calculated: {}'.format(hir_exp,hir_calc))
self.assertEqual(conf_exp ,conf_calc ,name + ': CONF, expected: {}, calculated: {}'.format(conf_exp,conf_calc))
def main():
smi = '[CH2]CC'
mult = 1
charge = 0
mol = StationaryPoint('well0', charge, mult, smiles=smi)
mol.characterize()
reactions = generate_all_product_bond_matrices(mol)
def testNumberOfHitsWithStartAtom(self):
"""
Test the molecular formula creator, which is
basically a RDKit feature, but used in KinBot
for postprocessing
"""
# the data contains the smiles as key and as value:
# 1. the multiplicity
# 2. start atom
# 3. the motif which will be searched for
# 4. the expected number of hits of the motif
data = {'CCCO[O]': [2, 0, ['C', 'C', 'C', 'O', 'O'], 1],
'C=C': [1, 0, ['X', 'X', 'X'], 2],
'S=S': [1, 0, ['S', 'S'], 1],
}
for smi in data:
mult = data[smi][0]
start = data[smi][1]
motif = data[smi][2]
exp = data[smi][3]
st_pt = StationaryPoint(smi, 0, mult, smiles=smi)
st_pt.characterize()
bond = st_pt.bond
natom = st_pt.natom
atom = st_pt.atom
# do not use any equivalencies
eqv = [[k] for k in range(natom)]
hits = find_motif.start_motif(motif, natom, bond, atom, start, eqv)
cal = len(hits)
warn = 'Unexpected number of motif hits for '
warn += '{}, expected {}, calculated {}'.format(smi, exp, cal)
self.assertEqual(exp, cal, warn)
def testNumberOfHitsWithStartAtom(self):
"""
Test the molecular formula creator, which is
basically a RDKit feature, but used in KinBot
for postprocessing
"""
# the data contains the smiles as key and as value:
# 1. the multiplicity
# 2. start atom
# 3. the motif which will be searched for
# 4. the expected number of hits of the motif
data = {
'CCCO[O]': [2, 0, ['C', 'C', 'C', 'O', 'O'], 1],
'C=C': [1, 0, ['X', 'X', 'X'], 2],
'S=S': [1, 0, ['S', 'S'], 1],
}
for smi in data:
mult = data[smi][0]
start = data[smi][1]
motif = data[smi][2]
exp = data[smi][3]
st_pt = StationaryPoint(smi, 0, mult, smiles=smi)
st_pt.characterize()
bond = st_pt.bond
natom = st_pt.natom
atom = st_pt.atom
# do not use any equivalencies
eqv = [[k] for k in range(natom)]
hits = find_motif.start_motif(motif, natom, bond, atom, start, eqv)
cal = len(hits)
warn = 'Unexpected number of motif hits for '
warn += '{}, expected {}, calculated {}'.format(smi, exp, cal)
self.assertEqual(exp, cal, warn)
def testBondFilter(self):
"""
Test the molecular formula creator, which is
basically a RDKit feature, but used in KinBot
for postprocessing
"""
smi = 'CCC=CCC'
motif = ['C', 'C', 'C', 'C']
bondpattern = [2, 'X', 'X']
exp = 2
st_pt = StationaryPoint(smi, 0, 1, smiles=smi)
st_pt.characterize()
bond = st_pt.bond
natom = st_pt.natom
atom = st_pt.atom
# do not use any equivalencies
eqv = [[k] for k in range(natom)]
hits = find_motif.start_motif(motif, natom, bond, atom, -1, eqv)
count = 0
for hit in hits:
if find_motif.bondfilter(hit, bond, bondpattern) == 0:
count += 1
warn = 'Unexpected number of motif hits for '
warn += '{}, expected {}, calculated {}'.format(smi, exp, count)
self.assertEqual(exp, count, warn)
def testDihedralChangeHeptyl(self):
"""
The generation of ring conformers requires qc calculations and is therefore slow!
"""
if not os.path.exists('conf/'):
os.mkdir('conf/')
par = Parameters()
qc = QuantumChemistry(par)
smi = '[CH2]CCCCC'
mol = StationaryPoint(smi, 0, 2, smiles=smi)
mol.characterize()
changes = [
[0, 3, 4, 5, 25.],
[3, 4, 5, 6, 25.],
[4, 5, 6, 7, 25.],
[5, 6, 7, 16, 25.],
]
name = 'hexyl_dihedral'
success, new_geom = kinbot.modify_geom.modify_coordinates(
mol,
name,
mol.geom,
changes,
mol.bond,
write_files=self.write_files)
def testNewRingDihedrals(self):
"""
Test the calculation of new dihedrals necessary for the update
"""
smi = 'CCCC'
mol = StationaryPoint(smi, 0, 1, smiles=smi)
mol.characterize()
ins = [0, 1, 2, 3] # change the C-C-C-C dihedral
step_nr = 0 # This corresponds to the first dihedral update
# there are 12 steps done in total, this means that the dihedral
# angle should be changed by 1/10 of the total change
total_nr_of_steps = 10
# final dihedral value we are shooting for after 10 updates
# this is a default value for a instance of 5 or less atoms
final_val = 15.
# initial dihedral
ini = geometry.calc_dihedral(mol.geom[ins[0]],
mol.geom[ins[1]],
mol.geom[ins[2]],
mol.geom[ins[3]])[0]
# this is the new dihedral angle after one step
update = geometry.new_ring_dihedrals(mol, ins, step_nr,
total_nr_of_steps)
exp = ini - (ini - final_val) / 10
cal = update[0]
warn = 'Dihedral update is not correct: '
warn += 'expected {}, calculated {}'.format(exp, cal)
self.assertEqual(exp, cal, msg=warn)
def testAll(self):
data = {
'CC': [1, 0],
'CCC': [2, 0],
'CCCC': [3, 1],
'C=C': [0, 0],
'C=CC': [1, 0],
'C=C[CH2]': [0, 0],
'CC=C[CH2]': [1, 0],
'C1CCCC1': [0, 0],
'CO': [1, 0],
'C=CO': [1, 1],
}
for name in data:
par = Parameters()
qc = QuantumChemistry(par)
mol = StationaryPoint(name, 0, 1, smiles=name)
mol.characterize()
hir_exp = data[name][0]
conf_exp = data[name][1]
hir_calc = len(mol.dihed)
conf_calc = len(mol.conf_dihed)
self.assertEqual(
hir_exp, hir_calc,
name + ': HIR, expected: {}, calculated: {}'.format(
hir_exp, hir_calc))
self.assertEqual(
conf_exp, conf_calc,
name + ': CONF, expected: {}, calculated: {}'.format(
conf_exp, conf_calc))
def testBondFilter(self):
"""
Test the molecular formula creator, which is
basically a RDKit feature, but used in KinBot
for postprocessing
"""
smi = 'CCC=CCC'
motif = ['C', 'C', 'C', 'C']
bondpattern = [2, 'X', 'X']
exp = 2
st_pt = StationaryPoint(smi, 0, 1, smiles=smi)
st_pt.characterize()
bond = st_pt.bond
natom = st_pt.natom
atom = st_pt.atom
# do not use any equivalencies
eqv = [[k] for k in range(natom)]
hits = find_motif.start_motif(motif, natom, bond, atom, -1, eqv)
count = 0
for hit in hits:
if find_motif.bondfilter(hit, bond, bondpattern) == 0:
count += 1
warn = 'Unexpected number of motif hits for '
warn += '{}, expected {}, calculated {}'.format(smi, exp, count)
self.assertEqual(exp, count, warn)
def testAll(self):
with open('symmetry_data.json') as f:
data = json.load(f)
messages = [
'Expected external symmetry: {}, calculated: {}',
'Expected internal symmetry: {}, calculated: {}',
'Expected number of single events symmetry: {}, calculated: {}',
]
for name in data:
par = Parameters()
qc = QuantumChemistry(par)
mol = StationaryPoint(name, 0, 1, smiles=name)
mol.characterize()
kinbot.symmetry.calculate_symmetry(mol)
sigma_int = 1
for row in mol.sigma_int:
for at in row:
sigma_int *= at
calc = [mol.sigma_ext, sigma_int, mol.nopt]
for i in range(3):
cal = calc[i]
exp = data[name]['expected_values'][i]
self.assertEqual(exp, cal,
name + ': ' + messages[i].format(exp, cal))
def main():
smi = '[CH2]CC'
mult = 1
charge = 0
mol = StationaryPoint('well0', charge, mult, smiles=smi)
mol.characterize()
reactions = generate_all_product_bond_matrices(mol)
print(len(reactions))
def testAll(self):
with open('multimolecular_data.json') as f:
data = json.load(f)
for name in data:
print(name)
par = Parameters()
qc = QuantumChemistry(par)
structure = data[name]['structure']
mol = StationaryPoint(name,0,1,structure = structure)
mol.characterize()
mols = mol.start_multi_molecular()
calculated = len(mols)
expected = data[name]['expected_value']
self.assertEqual(calculated,expected, name + ': expected: {}, calculated: {}'.format(expected,calculated))
def create_geometries(self):
"""
Cut the species in two parts and save the geometries of both parts into
new stationary point objects
"""
# copy the reactant stationary point
atom = copy.deepcopy(self.species.atom)
geom = copy.deepcopy(self.species.geom)
temp = StationaryPoint('temp', self.species.charge,
self.species.mult, atom=atom, geom=geom)
temp.characterize()
# set the bond order of the breaking bond to 0
temp.bond[self.bond[0]][self.bond[1]] = 0
temp.bond[self.bond[1]][self.bond[0]] = 0
self.products, maps = temp.start_multi_molecular()
def testAll(self):
with open('multimolecular_data.json') as f:
data = json.load(f)
for name in data:
print name
par = Parameters()
qc = QuantumChemistry(par)
structure = data[name]['structure']
mol = StationaryPoint(name,0,1,structure = structure)
mol.characterize()
mols = mol.start_multi_molecular()
calculated = len(mols)
expected = data[name]['expected_value']
self.assertEqual(calculated,expected, name + ': expected: {}, calculated: {}'.format(expected,calculated))
def create_geometries(self):
"""
Cut the species in two parts and save the geometries of both parts into
new stationary point objects
"""
# copy the reactant stationary point
atom = copy.deepcopy(self.species.atom)
geom = copy.deepcopy(self.species.geom)
temp = StationaryPoint('temp', self.species.charge,
self.species.mult, atom=atom, geom=geom)
temp.characterize()
# set the bond order of the breaking bond to 0
temp.bond[self.bond[0]][self.bond[1]] = 0
temp.bond[self.bond[1]][self.bond[0]] = 0
self.products, maps = temp.start_multi_molecular()
def testAll(self):
data = {"C1=CC=CC=C1":2,
"C1=CC=C(C)C=C1":2,
"C=C[CH2]":2,
"C=C=C":1,
"C#C[CH2]":2,
"S=S":1,
"O=S=C":1,
"O=S(C)[CH2]":3,
"C1CC=CC=C1":1
}
for name in data:
par = Parameters()
qc = QuantumChemistry(par)
mol = StationaryPoint(name,0,1,smiles = name)
mol.characterize()
cal = len(mol.bonds)
exp = data[name]
self.assertEqual(exp ,cal ,name + ': expected: {}, calculated: {}'.format(exp,cal))
def testBondChangeEthane(self):
"""
The generation of a longer C-C bond in ethane
"""
if not os.path.exists('conf/'):
os.mkdir('conf/')
par = Parameters()
qc = QuantumChemistry(par)
smi = 'CC'
mol = StationaryPoint(smi, 0, 1, smiles=smi)
mol.characterize()
changes = [
[0, 1, 1.8],
]
name = 'ethane_bond_length_test'
success, new_geom = kinbot.modify_geom.modify_coordinates(
mol,
name,
mol.geom,
changes,
mol.bond,
write_files=self.write_files)
def testNewBondLength(self):
"""
Test the calculation of new bond length necessary for the update
"""
smi = 'CCCC'
mol = StationaryPoint(smi, 0, 1, smiles=smi)
mol.characterize()
ati = 0
atj = 1
step_nr = 1 # This corresponds to the first bond length update
# there are 12 steps done in total, this means that the bond
# length should be changed by 1/10 of the total change
total_nr_of_steps = 10
# final bond length we are shooting for after 10 updates
final_val = 2.0
# initial bond length
ini = np.linalg.norm(mol.geom[ati] - mol.geom[atj])
# this is the new bond length one step
cal = geometry.new_bond_length(mol, ati, atj, step_nr,
total_nr_of_steps, final_val)
exp = ini + (final_val - ini) / 10
warn = 'Dihedral update is not correct: '
warn += 'expected {}, calculated {}'.format(exp, cal)
self.assertEqual(exp, cal, msg=warn)
def testAll(self):
with open('symmetry_data.json') as f:
data = json.load(f)
messages = [
'Expected external symmetry: {}, calculated: {}',
'Expected internal symmetry: {}, calculated: {}',
'Expected number of single events symmetry: {}, calculated: {}',]
for name in data:
par = Parameters()
qc = QuantumChemistry(par)
mol = StationaryPoint(name,0,1,smiles = name)
mol.characterize()
kinbot.symmetry.calculate_symmetry(mol)
sigma_int = 1
for row in mol.sigma_int:
for at in row:
sigma_int *= at
calc = [mol.sigma_ext, sigma_int, mol.nopt]
for i in range(3):
cal = calc[i]
exp = data[name]['expected_values'][i]
self.assertEqual(exp ,cal ,name + ': ' + messages[i].format(exp,cal))
def main():
try:
input_file = sys.argv[1]
except IndexError:
print(
'To use the pes script, supply one argument being the input file!')
sys.exit(-1)
# TODO: write information about the arguments
# change this to nice argument parsers with
# dashes etc.
no_kinbot = 0
task = 'all'
names = []
if len(sys.argv) > 2:
if sys.argv[2] == 'no-kinbot':
no_kinbot = 1
if len(sys.argv) > 3:
# possible tasks are:
# 1. all: This is the default showing all pathways
# 2. lowestpath: show the lowest path between the species
# corresponding to the names
# 3. allpaths: show all paths between the species
# corresponding to the names
# 4. wells: show all reactions of one wells
# corresponding to the names
task = sys.argv[3]
names = sys.argv[4:]
# print the license message to the console
print(license_message.message)
# initialize the parameters
par = Parameters(input_file)
# set up the logging environment
logging.basicConfig(filename='pes.log', level=logging.INFO)
logging.info(license_message.message)
msg = 'Starting the PES search at {}'.format(datetime.datetime.now())
logging.info(msg)
if par.par['pes'] and par.par['specific_reaction']:
logging.error('Specific reaction cannot be searched in PES mode.')
return
well0 = StationaryPoint('well0',
par.par['charge'],
par.par['mult'],
smiles=par.par['smiles'],
structure=par.par['structure'])
well0.characterize(dimer=par.par['dimer'])
write_input(par, well0, par.par['barrier_threshold'], os.getcwd())
# add the initial well to the chemids
with open('chemids', 'w') as f:
f.write(str(well0.chemid) + '\n')
# create a directory for the L3 single point calculations
# directory has the name of the code, e.g., molpro
try:
os.mkdir(par.par['single_point_qc'])
except OSError:
pass
#List of chemids to skip KinBot submissions for.
skipChemids = par.par['skip_chemids']
# maximum number of kinbot jobs that run simultaneously
max_running = par.par['simultaneous_kinbot']
# jobs that are running
running = []
# jobs that are finished
finished = []
# list of all jobs
jobs = []
# dict of the pid's for all jobs
pids = {}
a = 0
b = 0
c = 0
while 1:
j = len(jobs)
if j != a:
logging.info('{0} {1} {2}'.format("len(jobs): ", j, "\n"))
a = j
with open('chemids', 'r') as f:
jobs = f.read().split('\n')
jobs = [ji for ji in jobs if ji != '']
if len(jobs) > j:
logging.info('\tPicked up new jobs: ' + ' '.join(jobs[j:]))
k = len(running)
l = len(finished)
if b != k:
logging.info('{0} {1} {2}'.format("len(running): ", len(running),
"\n"))
b = k
if c != l:
logging.info('{0} {1} {2}'.format("len(finished): ", len(finished),
"\n"))
c = l
if len(finished) == len(jobs):
time.sleep(2)
if len(finished) == len(jobs):
break
while (len(running) < max_running
and len(running) + len(finished) < len(jobs)):
# start a new job
job = jobs[len(running) + len(finished)]
kb = 1
logging.info('Job: {}'.format(job))
if 'none' in skipChemids:
logging.info('No KinBot runs to be skipped')
else:
if job in skipChemids:
kb = 0
logging.info('kb: {}'.format(kb))
if kb == 1:
pid = 0
if not no_kinbot:
pid = submit_job(job, par) # kinbot is submitted here
else:
get_wells(job)
pids[job] = pid
t = datetime.datetime.now()
logging.info('\tStarted job {} at {}'.format(job, t))
running.append(job)
elif kb == 0:
logging.info('Skipping Kinbot for {}'.format(job))
finished.append(job)
else:
logging.info('kb value not 0 or 1')
# check if a thread is done
for job in running:
if not check_status(job, pids[job]):
t = datetime.datetime.now()
logging.info('\tFinished job {} at {}'.format(job, t))
finished.append(job)
if not no_kinbot:
# write a temporary pes file
# remove old xval and im_extent files
try:
os.remove('{}_xval.txt'.format(par.par['title']))
except OSError:
pass
try:
os.remove('{}_im_extent.txt'.format(par.par['title']))
except OSError:
pass
# remove the finished threads
for job in finished:
if job in running:
running.remove(job)
if not no_kinbot:
# write a summary of what is running and finished
summary_lines = []
summary_lines.append('Total\t\t{}'.format(len(jobs)))
summary_lines.append('Running\t\t{}'.format(len(running)))
summary_lines.append('Finished\t{}'.format(len(finished)))
summary_lines.append('')
summary_lines.append('Running:')
for job in running:
summary_lines.append('\t{}'.format(job))
summary_lines.append('')
summary_lines.append('Finished:')
for job in finished:
summary_lines.append('\t{}'.format(job))
with open('pes_summary.txt', 'w') as f:
f.write('\n'.join(summary_lines))
time.sleep(1)
# delete skipped jobs from the jobs before sending to postprocess
for skip in skipChemids:
try:
jobs.pop(jobs.index(skip))
except ValueError:
pass
postprocess(par, jobs, task, names)
# make molpro inputs for all keys above
# place submission script in the directory for offline submission
# read in the molpro energies for the keys in the above three dicts
# for key in newdict.keys():
# print(key)
# if all energies are there
# do something like postprocess, but with new energies
# postprocess_L3(saddle_zpe, well_zpe, prod_zpe, saddle_energy, well_energy, prod_energyi, conn)
# Notify user the search is done
logging.info('PES search done!')
print('PES search done!')
def generate(self):
"""
Creates the input for each reaction, runs them, and tests for success.
If successful, it creates the barrier and product objects.
It also then does the conformational search, and finally, the hindered rotor scans.
To make the code the most efficient, all of these happen in parallel, in a sense that
the jobs are not waiting for each other. E.g., one reaction can still be in the stage
of TS search, while the other can be already at the hindered rotor scan. This way,
all cores are occupied efficiently.
The switching between the various stages are done via the reac_ts_done variable.
0: initiate the TS search
1: check barrier height and errors in TS, and initiates normal mode displacement test, start the irc calculations
2: submit product optimization
3: submit the frequency calculation
4: do the optimization of the ts and the products
5: follow up on the optimizations
6: finalize calculations, check for wrong number of negative frequencies
If at any times the calculation fails, reac_ts_done is set to -999.
If all steps are successful, reac_ts_done is set to -1.
"""
deleted = []
if len(self.species.reac_inst) > 0:
alldone = 1
else:
alldone = 0
# status to see of kinbot needs to wait for the product optimizations
# from another kinbot run, to avoid duplication of calculations
products_waiting_status = [[] for i in self.species.reac_inst]
count = 0
for i in self.species.reac_inst:
count = count + 1
frag_unique = []
while alldone:
for index, instance in enumerate(self.species.reac_inst):
obj = self.species.reac_obj[index]
# START REACTION SEARCH
if self.species.reac_ts_done[
index] == 0 and self.species.reac_step[index] == 0:
# verify after restart if search has failed in previous kinbot run
status = self.qc.check_qc(obj.instance_name)
if status == 'error' or status == 'killed':
logging.info(
'\tRxn search failed (error or killed) for {}'.
format(obj.instance_name))
self.species.reac_ts_done[index] = -999
if self.species.reac_type[
index] == 'hom_sci' and self.species.reac_ts_done[
index] == 0: # no matter what, set to 2
# somewhat messy manipulation to force the new bond matrix for hom_sci
obj.products = copy.deepcopy(obj.species)
obj.products.bonds = copy.deepcopy(
obj.species.bond) # plural/non plural!
obj.products.bonds[obj.instance[0]][
obj.instance[1]] = 0 # delete bond
obj.products.bonds[obj.instance[1]][
obj.instance[0]] = 0 # delete bond
obj.products.bond[obj.instance[0]][
obj.instance[1]] = 0 # delete bond
obj.products.bond[obj.instance[1]][
obj.instance[0]] = 0 # delete bond
obj.product_bonds = copy.deepcopy(
obj.species.bonds[0]) # the first resonance structure
obj.product_bonds[obj.instance[0]][
obj.instance[1]] = 0 # delete bond
obj.product_bonds[obj.instance[1]][
obj.instance[0]] = 0 # delete bond
self.species.reac_ts_done[index] = 2
if self.species.reac_ts_done[
index] == 0: # ts search is ongoing
if obj.scan == 0: # don't do a scan of a bond
if self.species.reac_step[index] == obj.max_step + 1:
status, freq = self.qc.get_qc_freq(
obj.instance_name, self.species.natom)
if status == 0 and freq[0] < 0. and freq[1] > 0.:
self.species.reac_ts_done[index] = 1
elif status == 0 and freq[0] > 0.:
logging.info(
'\tRxn search failed for {}, no imaginary freq.'
.format(obj.instance_name))
self.species.reac_ts_done[index] = -999
elif status == 0 and freq[1] < 0.:
logging.info(
'\tRxn search failed for {}, more than one imaginary freq.'
.format(obj.instance_name))
self.species.reac_ts_done[index] = -999
elif status == -1:
logging.info(
'\tRxn search failed for {}'.format(
obj.instance_name))
self.species.reac_ts_done[index] = -999
else:
self.species.reac_step[
index] = reac_family.carry_out_reaction(
obj, self.species.reac_step[index],
self.par['qc_command'])
else: # do a bond scan
if self.species.reac_step[
index] == self.par['scan_step'] + 1:
status, freq = self.qc.get_qc_freq(
obj.instance_name, self.species.natom)
if status == 0 and freq[0] < 0. and freq[1] > 0.:
self.species.reac_ts_done[index] = 1
elif status == 0 and freq[0] > 0.:
logging.info(
'\tRxn search failed for {}, no imaginary freq.'
.format(obj.instance_name))
self.species.reac_ts_done[index] = -999
elif status == 0 and freq[1] < 0.:
logging.info(
'\tRxn search failed for {}, more than one imaginary freq.'
.format(obj.instance_name))
self.species.reac_ts_done[index] = -999
elif status == -1:
logging.info(
'\tRxn search using scan failed for {} in TS optimization stage.'
.format(obj.instance_name))
self.species.reac_ts_done[index] = -999
else:
if self.species.reac_step[index] == 0:
self.species.reac_step[
index] = reac_family.carry_out_reaction(
obj, self.species.reac_step[index],
self.par['qc_command'])
elif self.species.reac_step[index] < self.par[
'scan_step']:
status = self.qc.check_qc(obj.instance_name)
if status == 'error' or status == 'killed':
logging.info(
'\tRxn search using scan failed for {} in step {}'
.format(obj.instance_name,
self.species.reac_step[index]))
self.species.reac_ts_done[index] = -999
else:
err, energy = self.qc.get_qc_energy(
obj.instance_name)
if err == 0:
self.species.reac_scan_energy[
index].append(energy)
# need at least 3 points for a maximum
if len(self.species.
reac_scan_energy[index]) >= 3:
ediff = np.diff(
self.species.
reac_scan_energy[index])
if ediff[-1] < 0 and ediff[
-2] > 0: # max
self.species.reac_step[
index] = self.par[
'scan_step'] # ending the scan
if len(ediff) >= 3:
if 10. * (
ediff[-3] / ediff[-2]
) < (
ediff[-2] / ediff[-1]
): # sudden change in slope
self.species.reac_step[
index] = self.par[
'scan_step'] # ending the scan
logging.info(
'\tCurrent raw scan energy for {}: {} Hartree.'
.format(
obj.instance_name,
self.species.
reac_scan_energy[index][-1]))
# scan continues, and if reached scan_step, then goes for full optimization
self.species.reac_step[
index] = reac_family.carry_out_reaction(
obj,
self.species.reac_step[index],
self.par['qc_command'])
else: # the last step was reached, and no max or inflection was found
logging.info(
'\tRxn search using scan failed for {}, no saddle guess found.'
.format(obj.instance_name))
db = connect('{}/kinbot.db'.format(
os.getcwd()))
rows = db.select(name=obj.instance_name)
for row in self.reversed_iterator(rows):
row.data['status'] = 'error'
break # only write error to the last calculation
self.species.reac_ts_done[index] = -999
elif self.species.reac_ts_done[index] == 1:
status = self.qc.check_qc(obj.instance_name)
if status == 'running':
continue
elif status == 'error':
logging.info(
'\tRxn search failed (gaussian error) for {}'.
format(obj.instance_name))
self.species.reac_ts_done[index] = -999
else:
# check the barrier height:
ts_energy = self.qc.get_qc_energy(obj.instance_name)[1]
ts_zpe = self.qc.get_qc_zpe(obj.instance_name)[1]
if self.species.reac_type[
index] == 'R_Addition_MultipleBond':
ending = 'well_mp2'
elif self.species.reac_type[
index] == 'barrierless_saddle':
ending = 'well_bls'
else:
ending = 'well'
sp_energy = self.qc.get_qc_energy('{}_{}'.format(
str(self.species.chemid), ending))[1]
sp_zpe = self.qc.get_qc_zpe('{}_{}'.format(
str(self.species.chemid), ending))[1]
try:
barrier = (ts_energy + ts_zpe - sp_energy -
sp_zpe) * constants.AUtoKCAL
except TypeError:
logging.error(
f'Faulty calculations, check or delete files for {obj.instance_name}.'
)
sys.exit(-1)
if barrier > self.par['barrier_threshold']:
logging.info(
'\tRxn barrier too high ({0:.2f} kcal/mol) for {1}'
.format(barrier, obj.instance_name))
self.species.reac_ts_done[index] = -999
else:
obj.irc = IRC(
obj, self.par
) # TODO: this doesn't seem like a good design
irc_status = obj.irc.check_irc()
if 0 in irc_status:
logging.info(
'\tRxn barrier is {0:.2f} kcal/mol for {1}'
.format(barrier, obj.instance_name))
# No IRC started yet, start the IRC now
logging.info(
'\tStarting IRC calculations for {}'.
format(obj.instance_name))
obj.irc.do_irc_calculations()
elif irc_status[0] == 'running' or irc_status[
1] == 'running':
continue
else:
# IRC's have successfully finished, have an error or were killed, in any case
# read the geometries and try to make products out of them
# verify which of the ircs leads back to the reactant, if any
prod = obj.irc.irc2stationary_pt()
if prod == 0:
logging.info(
'\t\tNo product found for {}'.format(
obj.instance_name))
self.species.reac_ts_done[index] = -999
else:
obj.products = prod
obj.product_bonds = prod.bond
self.species.reac_ts_done[index] = 2
elif self.species.reac_ts_done[index] == 2:
if len(products_waiting_status[index]) == 0:
# identify bimolecular products and wells
fragments, maps = obj.products.start_multi_molecular()
obj.products = []
a = []
for frag in fragments:
a.append(frag)
if len(frag_unique) == 0:
frag_unique.append(frag)
elif len(frag_unique) > 0:
new = 1
for fragb in frag_unique:
if frag.chemid == fragb.chemid:
e, geom2 = self.qc.get_qc_geom(
str(fragb.chemid) + '_well',
fragb.natom)
if e == 0:
a.pop()
frag = fragb
a.append(frag)
new = 0
break
if new:
frag_unique.append(frag)
obj.products_final = []
for frag in a:
self.qc.qc_opt(frag, frag.geom)
e, geom2 = self.qc.get_qc_geom(
str(frag.chemid) + '_well', frag.natom)
obj.products_final.append(frag)
# check products make sure they are the same
for i, st_pt_i in enumerate(obj.products_final):
for j, st_pt_j in enumerate(obj.products_final):
if st_pt_i.chemid == st_pt_j.chemid and i < j:
obj.products_final[j] = obj.products_final[
i]
# print products generated by IRC
products = []
for i, st_pt in enumerate(obj.products_final):
products.append(st_pt.chemid)
products.extend([' ', ' ', ' '])
logging.info(
'\tReaction {} leads to products {} {} {}'.format(
obj.instance_name, products[0], products[1],
products[2]))
for i, st_pt in enumerate(obj.products_final):
chemid = st_pt.chemid
e, st_pt.geom = self.qc.get_qc_geom(
str(st_pt.chemid) + '_well', st_pt.natom)
if e < 0:
logging.info(
'\tProduct optimization failed for {}, product {}'
.format(obj.instance_name, st_pt.chemid))
self.species.reac_ts_done[index] = -999
err = -1
elif e != 0:
err = -1
else:
e2, st_pt.energy = self.qc.get_qc_energy(
str(st_pt.chemid) + '_well')
e2, st_pt.zpe = self.qc.get_qc_zpe(
str(st_pt.chemid) + '_well')
st_pt.characterize(
dimer=0
) # not allowed to use the dimer option here
if chemid != st_pt.chemid:
obj.products_final.pop(i)
newfrags, newmaps = st_pt.start_multi_molecular(
) # newfrags is list of stpt obj
products_waiting_status[index] = [
0 for frag in newfrags
]
frag_chemid = []
for i, newfr in enumerate(newfrags):
newfr.characterize(dimer=0)
for prod in frag_unique:
if newfr.chemid == prod.chemid:
newfrags.pop(i)
newfr = prod
j = i - 1
newfrags.insert(j, newfr)
j = i - 1
obj.products_final.insert(j, newfr)
self.qc.qc_opt(newfr, newfr.geom, 0)
frag_chemid.append(newfr.chemid)
if len(frag_chemid) == 1:
frag_chemid.append(" ")
for i, frag in enumerate(newfrags):
products_waiting_status[index][i] = 1
logging.info(
'\ta) Product optimized to other structure for {}'
', product {} to {} {}'.format(
obj.instance_name, chemid,
frag_chemid[0], frag_chemid[1]))
obj.products = []
for prod in obj.products_final:
obj.products.append(prod)
obj.products_final = []
if all([pi == 1 for pi in products_waiting_status[index]]):
self.species.reac_ts_done[index] = 3
elif self.species.reac_ts_done[index] == 3:
# wait for the optimization to finish
# if two st_pt are the same in the products, we make them exactly identical otherwise
# the different ordering of the atoms causes the chemid of the second to be seemingly wrong
for i, st_pt_i in enumerate(obj.products):
for j, st_pt_j in enumerate(obj.products):
if st_pt_i.chemid == st_pt_j.chemid and i < j:
obj.products[j] = obj.products[i]
err = 0
for st_pt in obj.products:
chemid = st_pt.chemid
e, st_pt.geom = self.qc.get_qc_geom(
str(st_pt.chemid) + '_well', st_pt.natom)
if e < 0:
logging.info(
'\tProduct optimization failed for {}, product {}'
.format(obj.instance_name, st_pt.chemid))
self.species.reac_ts_done[index] = -999
err = -1
elif e != 0:
err = -1
else:
e2, st_pt.energy = self.qc.get_qc_energy(
str(st_pt.chemid) + '_well')
e2, st_pt.zpe = self.qc.get_qc_zpe(
str(st_pt.chemid) + '_well')
st_pt.characterize(
dimer=0
) # not allowed to use the dimer option here
if chemid != st_pt.chemid:
# product was optimized to another structure, give warning but don't remove reaction
logging.info(
'\tb) Product optimized to other structure for {}'
', product {} to {}'.format(
obj.instance_name, chemid,
st_pt.chemid))
e, st_pt.geom = self.qc.get_qc_geom(
str(st_pt.chemid) + '_well', st_pt.natom)
if e < 0:
err = -1
if err == 0:
self.species.reac_ts_done[index] = 4
elif self.species.reac_ts_done[index] == 4:
# Do the TS and product optimization
# make a stationary point object of the ts
bond_mx = np.zeros(
(self.species.natom, self.species.natom), dtype=int)
for i in range(self.species.natom):
for j in range(self.species.natom):
bond_mx[i][j] = max(self.species.bond[i][j],
obj.product_bonds[i][j])
if self.species.reac_type[index] != 'hom_sci':
err, geom = self.qc.get_qc_geom(
obj.instance_name, self.species.natom)
ts = StationaryPoint(obj.instance_name,
self.species.charge,
self.species.mult,
atom=self.species.atom,
geom=geom,
wellorts=1)
err, ts.energy = self.qc.get_qc_energy(
obj.instance_name)
err, ts.zpe = self.qc.get_qc_zpe(
obj.instance_name) # NEW STOPS HERE
err, ts.freq = self.qc.get_qc_freq(
obj.instance_name, self.species.natom)
ts.distance_mx()
ts.bond = bond_mx
ts.find_cycle()
ts.find_conf_dihedral()
obj.ts = ts
# do the ts optimization
obj.ts_opt = Optimize(obj.ts, self.par, self.qc)
obj.ts_opt.do_optimization()
else:
obj.ts = copy.deepcopy(
obj.species
) # the TS will be for now the species itself
obj.ts.wellorts = 1
# do the products optimizations
for st_pt in obj.products:
# do the products optimizations
# check for products of other reactions that are the same as this product
# in the case such products are found, use the same Optimize object for both
for i, inst_i in enumerate(self.species.reac_inst):
new = 1
if not i == index:
obj_i = self.species.reac_obj[i]
if self.species.reac_ts_done[i] > 3:
for j, st_pt_i in enumerate(
obj_i.products):
if st_pt_i.chemid == st_pt.chemid:
if len(obj_i.prod_opt) > j:
prod_opt = obj_i.prod_opt[j]
new = 0
break
if new:
prod_opt = Optimize(st_pt, self.par, self.qc)
prod_opt.do_optimization()
obj.prod_opt.append(prod_opt)
for st_pt in obj.products:
# section where comparing products in same reaction occurs
if len(obj.prod_opt) > 0:
for j, st_pt_opt in enumerate(obj.prod_opt):
if st_pt.chemid == st_pt_opt.species.chemid:
if len(obj.prod_opt) > j:
prod_opt = obj.prod_opt[j]
break
self.species.reac_ts_done[index] = 5
elif self.species.reac_ts_done[index] == 5:
# check up on the TS and product optimizations
opts_done = 1
fails = 0
# check if ts is done
if self.species.reac_type[index] != 'hom_sci':
if not obj.ts_opt.shir == 1: # last stage in optimize
opts_done = 0
obj.ts_opt.do_optimization()
if obj.ts_opt.shigh == -999:
logging.info(
"Reaction {} ts_opt_shigh failure".format(
obj.instance_name))
fails = 1
for pr_opt in obj.prod_opt:
if not pr_opt.shir == 1:
opts_done = 0
pr_opt.do_optimization()
if pr_opt.shigh == -999:
logging.info(
"Reaction {} pr_opt_shigh failure".format(
obj.instance_name))
fails = 1
break
if fails:
self.species.reac_ts_done[index] = -999
elif opts_done:
self.species.reac_ts_done[index] = 6
elif self.species.reac_ts_done[index] == 6:
# Finilize the calculations
# continue to PES search in case a new well was found
if self.par['pes']:
# verify if product is monomolecular, and if it is new
if len(obj.products) == 1:
st_pt = obj.prod_opt[0].species
chemid = st_pt.chemid
new_barrier_threshold = self.par[
'barrier_threshold'] - (
st_pt.energy -
self.species.energy) * constants.AUtoKCAL
dirwell = os.path.dirname(os.getcwd())
jobs = open(dirwell + '/chemids',
'r').read().split('\n')
jobs = [ji for ji in jobs]
if not str(chemid) in jobs:
# this well is new, add it to the jobs
while 1:
try:
# try to open the file and write to it
pes.write_input(
self.inp, obj.products[0],
new_barrier_threshold, dirwell)
with open(dirwell + '/chemids',
'a') as f:
f.write('{}\n'.format(chemid))
break
except IOError:
# wait a second and try again
time.sleep(1)
pass
# copy the files of the species to an upper directory
frags = obj.products
for frag in frags:
filecopying.copy_to_database_folder(
self.species.chemid, frag.chemid, self.qc)
# check for wrong number of negative frequencies
neg_freq = 0
for st_pt in obj.products:
if any([fi < 0. for fi in st_pt.reduced_freqs]):
neg_freq = 1
if any([fi < 0. for fi in obj.ts.reduced_freqs[1:]]):
neg_freq = 1
if neg_freq:
logging.info('\tFound negative frequency for ' +
obj.instance_name)
self.species.reac_ts_done[index] = -999
else:
# the reaction search is finished
self.species.reac_ts_done[
index] = -1 # this is the success code
# write a temporary pes input file
# remove old xval and im_extent files
if os.path.exists('{}_xval.txt'.format(
self.species.chemid)):
os.remove('{}_xval.txt'.format(
self.species.chemid))
if os.path.exists('{}_im_extent.txt'.format(
self.species.chemid)):
os.remove('{}_im_extent.txt'.format(
self.species.chemid))
postprocess.createPESViewerInput(
self.species, self.qc, self.par)
elif self.species.reac_ts_done[index] == -999:
if self.par['delete_intermediate_files'] == 1:
if not self.species.reac_obj[
index].instance_name in deleted:
self.delete_files(
self.species.reac_obj[index].instance_name)
deleted.append(
self.species.reac_obj[index].instance_name)
alldone = 1
for index, instance in enumerate(self.species.reac_inst):
if any(self.species.reac_ts_done[i] >= 0
for i in range(len(self.species.reac_inst))):
alldone = 1
break
else:
alldone = 0
# write a small summary while running
with open('kinbot_monitor.out', 'w') as f_out:
for index, instance in enumerate(self.species.reac_inst):
if self.species.reac_ts_done[index] == -1:
prodstring = []
for pp in self.species.reac_obj[index].products:
prodstring.append(str(pp.chemid))
f_out.write('{}\t{}\t{}\t{}\n'.format(
self.species.reac_ts_done[index],
self.species.reac_step[index],
self.species.reac_obj[index].instance_name,
' '.join(prodstring)))
else:
f_out.write('{}\t{}\t{}\n'.format(
self.species.reac_ts_done[index],
self.species.reac_step[index],
self.species.reac_obj[index].instance_name))
time.sleep(1)
# Create molpro file for the BLS products
for index, instance in enumerate(self.species.reac_inst):
if self.species.reac_type[index] == 'barrierless_saddle':
obj = self.species.reac_obj[index]
if len(obj.products) == 2:
blsprodatom = np.append(obj.products[0].atom,
obj.products[1].atom)
# vector connecting the centers
# assumed: the two structures are naturally separated at the end of the IRC
x0 = 0
y0 = 0
z0 = 0
for g in obj.products[0].geom:
x0 += g[0]
y0 += g[1]
z0 += g[1]
x0 /= obj.products[0].natom
y0 /= obj.products[0].natom
z0 /= obj.products[0].natom
x1 = 0
y1 = 0
z1 = 0
for g in obj.products[1].geom:
x1 += g[0]
y1 += g[1]
z1 += g[1]
x1 /= obj.products[1].natom
y1 /= obj.products[1].natom
z1 /= obj.products[1].natom
center_vec = [x1 - x0, y1 - y0, z1 - z0]
blsprodgeom = np.append(obj.products[0].geom,
obj.products[1].geom)
blsprodgeom = np.reshape(blsprodgeom, (-1, 3))
bps = list(zip(blsprodatom, blsprodgeom))
bps1 = [item for sublist in bps for item in sublist]
blsprodstruct = [
item for sublist in bps1 for item in sublist
]
blsprod = StationaryPoint('blsprod',
self.par['charge'],
self.par['mult'],
structure=blsprodstruct)
blsprod.characterize()
molp = Molpro(blsprod, self.par)
molpname = '{}_prod'.format(obj.instance_name)
molp.create_molpro_input(bls=1,
name=molpname,
shift_vec=center_vec,
natom1=len(obj.products[1].geom))
molp.create_molpro_submit(name=molpname)
s = []
for index, instance in enumerate(self.species.reac_inst):
obj = self.species.reac_obj[index]
# Write a summary on the combinatorial exploration
if 'combinatorial' in obj.instance_name:
s.append('NAME\t' + obj.instance_name)
# Write the bonds that were broken and formed
s.append('BROKEN_BONDS\t' +
'\t'.join('[{}, {}]'.format(re[0], re[1])
for re in obj.reac))
s.append('FORMED_BONDS\t' +
'\t'.join('[{}, {}]'.format(pr[0], pr[1])
for pr in obj.prod))
# Populate the ts_bond_lengths dict with the values
# of this reaction
if self.species.reac_ts_done[index] == -1:
for i in range(self.species.natom - 1):
for j in range(i + 1, self.species.natom):
if self.species.bond[i][j] != obj.product_bonds[i][
j]:
if (self.species.bond[i][j] == 0
or obj.product_bonds[i][j] == 0):
syms = []
syms.append(self.species.atom[i])
syms.append(self.species.atom[j])
syms = ''.join(sorted(syms))
dist = np.linalg.norm(obj.ts.geom[i] -
obj.ts.geom[j])
s.append('TS_BOND_LENGTHS\t{}\t{}'.format(
syms, dist))
# write the expected inchis
s.append('EXPECTED_INCHIS\t' +
'\t'.join(inchi for inchi in obj.prod_inchi))
# get the inchis the reaction found
if self.species.reac_ts_done[index] == -1:
inchis = obj.get_final_inchis()
s.append('FOUND_INCHIS\t' + '\t'.join(inchis))
s.append('\n')
with open('combinatorial.txt', 'w') as f:
f.write('\n'.join(s) + '\n')
logging.info("Reaction generation done!")
def main():
try:
input_file = sys.argv[1]
except IndexError:
print('To use the pes script, supply one argument being the input file!')
sys.exit(-1)
# TODO: write information about the arguments
# change this to nice argument parsers with
# dashes etc.
no_kinbot = 0
task = 'all'
names = []
if len(sys.argv) > 2:
if sys.argv[2] == 'no-kinbot':
no_kinbot = 1
if len(sys.argv) > 3:
# possible tasks are:
# 1. all: This is the default showing all pathways
# 2. lowestpath: show the lowest path between the species
# corresponding to the names
# 3. allpaths: show all paths between the species
# corresponding to the names
# 4. wells: show all reactions of one wells
# corresponding to the names
task = sys.argv[3]
names = sys.argv[4:]
# print the license message to the console
print(license_message.message)
# initialize the parameters
par = Parameters(input_file)
# set up the logging environment
logging.basicConfig(filename='pes.log', level=logging.INFO)
logging.info(license_message.message)
msg = 'Starting the PES search at {}'.format(datetime.datetime.now())
logging.info(msg)
if par.par['pes'] and par.par['specific_reaction']:
logging.error('Specific reaction cannot be searched in PES mode.')
return
well0 = StationaryPoint('well0',
par.par['charge'],
par.par['mult'],
smiles=par.par['smiles'],
structure=par.par['structure'])
well0.characterize(par.par['dimer'])
write_input(par, well0, par.par['barrier_threshold'], os.getcwd())
# add the initial well to the chemids
with open('chemids', 'w') as f:
f.write(str(well0.chemid) + '\n')
# create a directory for the L3 single point calculations
# direcotry has the name of the code, e.g., molpro
try:
os.mkdir(par.par['single_point_qc'])
except OSError:
pass
# maximum number of kinbot jobs that run simultaneously
max_running = par.par['simultaneous_kinbot']
# jobs that are running
running = []
# jobs that are finished
finished = []
# list of all jobs
jobs = []
# dict of the pid's for all jobs
pids = {}
while 1:
j = len(jobs)
with open('chemids', 'r') as f:
jobs = f.read().split('\n')
jobs = [ji for ji in jobs if ji != '']
if len(jobs) > j:
logging.info('\tPicked up new jobs: ' + ' '.join(jobs[j:]))
if len(finished) == len(jobs):
break
while (len(running) < max_running and
len(running) + len(finished) < len(jobs)):
# start a new job
job = jobs[len(running) + len(finished)]
pid = 0
if not no_kinbot:
pid = submit_job(job, par) # kinbot is submitted here
else:
get_wells(job)
pids[job] = pid
t = datetime.datetime.now()
logging.info('\tStarted job {} at {}'.format(job, t))
running.append(job)
# check if a thread is done
for job in running:
if not check_status(job, pids[job]):
t = datetime.datetime.now()
logging.info('\tFinished job {} at {}'.format(job, t))
finished.append(job)
if not no_kinbot:
# write a temporary pes file
# remove old xval and im_extent files
try:
os.remove('{}_xval.txt'.format(par.par['title']))
except OSError:
pass
try:
os.remove('{}_im_extent.txt'.format(par.par['title']))
except OSError:
pass
postprocess(par, jobs, task, names)
# remove the finished threads
for job in finished:
if job in running:
running.remove(job)
if not no_kinbot:
# write a summary of what is running and finished
summary_lines = []
summary_lines.append('Total\t\t{}'.format(len(jobs)))
summary_lines.append('Running\t\t{}'.format(len(running)))
summary_lines.append('Finished\t{}'.format(len(finished)))
summary_lines.append('')
summary_lines.append('Running:')
for job in running:
summary_lines.append('\t{}'.format(job))
summary_lines.append('')
summary_lines.append('Finished:')
for job in finished:
summary_lines.append('\t{}'.format(job))
with open('pes_summary.txt', 'w') as f:
f.write('\n'.join(summary_lines))
time.sleep(1)
postprocess(par, jobs, task, names)
# make molpro inputs for all keys above
# place submission script in the directory for offline submission
# read in the molpro energies for the keys in the above three dicts
# for key in newdict.keys():
# print(key)
# if all energies are there
# do something like postprocess, but with new energies
# postprocess_L3(saddle_zpe, well_zpe, prod_zpe, saddle_energy, well_energy, prod_energyi, conn)
# Notify user the search is done
logging.info('PES search done!')
print('PES search done!')
def testFrequencies(self):
"""
Test the frequency calculator based on the hessian
by projecting out the translations, external rotations
and internal rotations
"""
# smiles of the speciesdata
smi = 'CCCC'
# geometry of the species
geom = [[0.91879892, -0.04331223, 0.12849174],
[0.40326992, 1.40563299, 0.15982756],
[0.89480303, 2.27635373, -1.01612317],
[0.37978671, 1.82281002, -2.39283836],
[0.56484506, -0.58104398, -0.75857814],
[0.58013979, -0.60154787, 1.00923604],
[2.01620768, -0.06868878, 0.11831706],
[-0.69710354, 1.40285362, 0.16867873],
[0.71679336, 1.87619548, 1.10252902],
[0.58079101, 3.31524962, -0.84143554],
[1.99516746, 2.28446562, -1.02104071],
[-0.71762425, 1.80824531, -2.41526122],
[0.72083567, 2.50053168, -3.18429864],
[0.73195359, 0.81628395, -2.64600957]]
geom = np.array(geom)
# hessian matrix
hess = [
[
0.557479281000, 0.036110582900, -0.001644922990,
-0.094996623900, 0.033793056500, 0.001227901360,
0.004435637720, -0.010301447300, -0.000714141524,
-0.000402278745, 0.000207775781, 0.000217081305,
-0.079155177000, -0.041443873100, -0.069861527200,
-0.075582477100, -0.041043274800, 0.066112977000,
-0.304832510000, 0.000618737475, 0.001591972160,
-0.011587172100, 0.035782319500, 0.001443997110,
0.003566576500, -0.009402669700, -0.000876604471,
-0.000457712074, -0.002463678640, 0.002595980330,
0.000811779351, -0.001430576500, 0.000032881273,
0.000129362928, -0.000033252298, 0.000111660638,
0.000157802640, -0.000276891050, 0.000074700177,
0.000433511158, -0.000116808738, -0.000311955226
],
[
0.036110582900, 0.481460445000, -0.001497124110,
0.032529383300, -0.168787802000, -0.006867396700,
0.006092748400, -0.023937567300, 0.003730351660,
-0.000262084184, 0.001441647380, 0.000316178114,
-0.041989591900, -0.107986603000, -0.100880979000,
-0.041503733500, -0.111783765000, 0.104729927000,
0.001080107490, -0.048474562500, -0.000241263827,
-0.000265123753, -0.003449223290, -0.000371820596,
0.007618533730, -0.018717902300, 0.000837312337,
-0.000555734072, -0.000078154904, 0.001999374050,
0.000646690960, 0.001260483370, -0.001360417570,
0.000088413780, -0.000085577196, 0.000164034911,
-0.000076331932, -0.000238612455, -0.000622223468,
0.000486138870, -0.000622805294, 0.000064046666
],
[
-0.001644922990, -0.001497124110, 0.575851102000,
0.001964210840, -0.005551021620, -0.083609101600,
-0.009286228620, 0.027728004900, 0.001373639180,
-0.000137246872, 0.000910607647, 0.001051929890,
-0.069899107500, -0.100194460000, -0.221142958000,
0.066308541300, 0.103907569000, -0.219256026000,
0.001583703380, -0.000080359730, -0.050839140900,
-0.000325149456, 0.000352021138, 0.000321544325,
0.010807393200, -0.028918001700, -0.000253208170,
0.001475456680, 0.004079204780, -0.004016767400,
-0.000771004699, -0.000846365220, 0.001019809380,
-0.000285363620, 0.000091087635, -0.000075059137,
-0.000051358279, -0.000192607794, 0.000123367411,
0.000261076583, 0.000211445408, -0.000549130393
],
[
-0.094996623900, 0.032529383300, 0.001964210840,
0.570648686000, 0.013726467600, 0.029803019800,
-0.093894628800, -0.017540296600, 0.025240052300,
0.004430547620, 0.007089239030, -0.008470974800,
0.003985664600, -0.011160808500, -0.000344880024,
0.003352509560, -0.011319168200, -0.000141509338,
-0.012312369900, 0.035615059900, 0.001341132350,
-0.296633947000, -0.002814851200, -0.001857303680,
-0.074252517800, -0.032055118900, -0.063305094900,
0.003016262880, 0.007165737430, -0.008147262180,
-0.013171250400, -0.021050691300, 0.028389638100,
0.000515556167, 0.000833930927, -0.001531483210,
-0.000733957654, -0.000834470892, -0.003543541800,
0.000046069520, -0.000184412716, 0.000603996490
],
[
0.033793056500, -0.168787802000, -0.005551021620,
0.013726467600, 0.471256701000, 0.045550224600,
-0.019055559200, -0.110456357000, 0.036788918500,
0.003690246720, 0.008042833690, -0.005946132620,
0.007450531200, -0.016991805700, 0.000566738577,
0.007662075620, -0.017473385800, -0.003434017560,
-0.000361925575, -0.003081819410, 0.000169600942,
-0.002141608270, -0.048419727000, -0.001543381080,
-0.032001313400, -0.092648760200, -0.091748171900,
-0.012965805500, -0.019490702300, 0.027544257800,
0.000385145313, -0.001607085100, 0.002202751810,
0.000097042391, 0.000342026851, -0.000085156640,
-0.000935724242, -0.000536578498, -0.003946142400,
0.000657370855, -0.000147538049, -0.000568468443
],
[
0.001227901360, -0.006867396700, -0.083609101600,
0.029803019800, 0.045550224600, 0.530185827000, 0.024067639100,
0.038254723800, -0.133557501000, 0.009656895150,
0.018083768400, -0.030339996500, 0.011176997800,
-0.027940521700, 0.000197610447, -0.010718813500,
0.027683119400, 0.001610715360, -0.000005380242,
0.000353950668, -0.000058645732, -0.001385963250,
-0.001490240310, -0.050945021400, -0.064025490200,
-0.091980721200, -0.231554605000, -0.000068702298,
-0.003001675120, 0.001414867140, 0.000375944632,
0.002432713030, -0.002619663450, 0.000967738003,
0.000578480710, 0.002131790000, -0.001665661510,
-0.002059701750, -0.003910908180, 0.000593875240,
0.000403276118, 0.001054632250
],
[
0.004435637720, 0.006092748400, -0.009286228620,
-0.093894628800, -0.019055559200, 0.024067639100,
0.570900497000, -0.032595232800, -0.004232877500,
-0.095277421800, -0.011406581600, -0.030607826800,
0.000043159915, -0.000514838503, 0.000373962854,
-0.000738247952, 0.003637838290, -0.000237140037,
0.000536641625, 0.001192182950, -0.001206594120,
-0.013027642100, -0.020980119300, 0.028551488200,
0.003004879320, 0.005695987090, -0.009218334250,
-0.074383197800, 0.070019040800, 0.012170299900,
-0.296727831000, 0.002527681320, 0.001997681770,
-0.012251640800, -0.011694206300, -0.033682439000,
0.003373175160, 0.003467893310, 0.010833941000, 0.004006619800,
0.003613165550, 0.010476427500
],
[
-0.010301447300, -0.023937567300, 0.027728004900,
-0.017540296600, -0.110456357000, 0.038254723800,
-0.032595232800, 0.550390617000, 0.021569897200,
-0.011111359900, -0.094250354100, -0.029239287500,
-0.000711297419, 0.000972151769, 0.000156692325,
0.001860692500, -0.005293631350, -0.000606360776,
-0.000954457648, 0.002153894160, 0.000019371190,
-0.000397838529, -0.001228430010, 0.002336752460,
0.003859667870, 0.006484974130, -0.010940182100,
0.070740800200, -0.270987312000, -0.037645349500,
0.001896728730, -0.051464188100, -0.000592835086,
0.000107061175, -0.000144181197, -0.000504021609,
0.007980792090, 0.006761052700, 0.020233362800,
-0.012833812400, -0.009000668610, -0.030770768100
],
[
-0.000714141524, 0.003730351660, 0.001373639180,
0.025240052300, 0.036788918500, -0.133557501000,
-0.004232877500, 0.021569897200, 0.451154731000,
-0.032090962200, -0.028197579400, -0.158290659000,
-0.000492084585, -0.000980152816, 0.000034862639,
0.000407801351, -0.002484344690, 0.000853888771,
0.000202037882, -0.000630194064, 0.000364010457,
-0.000276661410, 0.002092844910, -0.002923760270,
0.012375619200, 0.019611685600, -0.024571878400,
0.011914527900, -0.037319661200, -0.053342229400,
0.001505776140, -0.000642112942, -0.047826423400,
0.000374606934, -0.000789448823, -0.002922212160,
-0.010438695000, -0.010818867900, -0.022572722700,
-0.003774999570, -0.001931336020, -0.007773745060
],
[
-0.000402278745, -0.000262084184, -0.000137246872,
0.004430547620, 0.003690246720, 0.009656895150,
-0.095277421800, -0.011111359900, -0.032090962200,
0.558209213000, -0.009125619780, -0.034709539800,
0.000415340383, 0.000358171193, 0.000000905828, 0.000159128422,
0.000009821173, 0.000284856041, 0.000131990037,
-0.000097828362, 0.000069311231, 0.000786266725,
0.000375904422, 0.001427105050, -0.000456009865,
-0.001763774920, 0.003115461590, 0.003579063430,
0.003594264790, 0.008763686330, -0.011547639900,
-0.011824677300, -0.033753097500, -0.305000167000,
-0.001072859680, -0.000565352953, -0.076013943900,
-0.051443542800, 0.058887756100, -0.079014088600,
0.078673338600, 0.019050222000
],
[
0.000207775781, 0.001441647380, 0.000910607647, 0.007089239030,
0.008042833690, 0.018083768400, -0.011406581600,
-0.094250354100, -0.028197579400, -0.009125619780,
0.566853551000, -0.028314924300, -0.000405813331,
-0.000316988707, 0.000087265018, 0.000073046030,
-0.000135428465, -0.000227947707, 0.000240096907,
-0.000003210597, 0.000052913364, 0.000562715807,
0.000386702658, -0.000586865840, -0.001249462100,
-0.001984311450, 0.004661147410, -0.012569365100,
-0.009659129560, -0.031620324000, 0.000388942723,
-0.000027569785, -0.000685633791, -0.001195716590,
-0.050831902500, 0.000607484566, -0.051498752000,
-0.151306241000, 0.115957274000, 0.078889494300,
-0.268209599000, -0.050727185300
],
[
0.000217081305, 0.000316178114, 0.001051929890,
-0.008470974800, -0.005946132620, -0.030339996500,
-0.030607826800, -0.029239287500, -0.158290659000,
-0.034709539800, -0.028314924300, 0.489796505000,
-0.000391829054, 0.000142067560, -0.000688267160,
0.000058546643, -0.000657571583, 0.000021899914,
-0.000169145634, 0.000141233266, -0.000156069524,
-0.000870684066, -0.001083763300, 0.001824089140,
0.000966571121, 0.002585026930, -0.002110201450,
-0.004138394740, -0.001918643950, -0.009243037780,
0.000150249840, -0.001426379210, -0.003164852780,
-0.000834451580, 0.000361231775, -0.048518990600,
0.059364188600, 0.116743826000, -0.179560342000,
0.019436209100, -0.051702861200, -0.060622006300
],
[
-0.079155177000, -0.041989591900, -0.069899107500,
0.003985664600, 0.007450531200, 0.011176997800, 0.000043159915,
-0.000711297419, -0.000492084585, 0.000415340383,
-0.000405813331, -0.000391829054, 0.082170568700,
0.043883239500, 0.078044112600, 0.003495229520, 0.005401929110,
0.009954809490, -0.011350612800, -0.016458449400,
-0.029453532500, 0.000665737135, -0.000625010895,
0.000511858440, 0.000059291070, 0.003007766240, 0.000159750828,
-0.000060170797, -0.000108422372, 0.000205866966,
0.000026998545, -0.000052468999, -0.000060908234,
-0.000223489041, 0.000140719611, -0.000038210872,
-0.000144869281, 0.000150427844, 0.000065183444,
0.000072328995, 0.000316440754, 0.000217093184
],
[
-0.041443873100, -0.107986603000, -0.100194460000,
-0.011160808500, -0.016991805700, -0.027940521700,
-0.000514838503, 0.000972151769, -0.000980152816,
0.000358171193, -0.000316988707, 0.000142067560,
0.043883239500, 0.119840850000, 0.111814261000, 0.005906654280,
0.008066891770, 0.014503839500, 0.000290968064,
-0.000150240230, 0.000002063185, 0.000111922593,
0.001514337600, 0.000276003926, 0.002702457800,
-0.005775080730, 0.000445401249, 0.000111932829,
0.000347388012, 0.000177052371, -0.000006786294,
-0.000145911482, 0.000108411307, 0.000058268378,
-0.000061770157, 0.000096427007, -0.000010851744,
0.000535119260, 0.000099909733, -0.000286456542,
0.000151661591, 0.001449697830
],
[
-0.069861527200, -0.100880979000, -0.221142958000,
-0.000344880024, 0.000566738577, 0.000197610447,
0.000373962854, 0.000156692325, 0.000034862639, 0.000000905828,
0.000087265018, -0.000688267160, 0.078044112600,
0.111814261000, 0.242817300000, -0.010493946400,
-0.013936543100, -0.022850703000, 0.001401288830,
0.000811652521, 0.000387534637, 0.000611035395,
-0.000326880526, 0.000202559149, 0.000448151560,
0.000430071969, 0.001316161050, -0.000015506148,
-0.000226147940, 0.000124908040, 0.000053325603,
0.000066745555, -0.000005338059, 0.000029804814,
-0.000043582456, -0.000002800832, 0.000036585620,
0.000161681863, 0.000229922299, -0.000283313413,
0.001319024070, -0.000620791338
],
[
-0.075582477100, -0.041503733500, 0.066308541300,
0.003352509560, 0.007662075620, -0.010718813500,
-0.000738247952, 0.001860692500, 0.000407801351,
0.000159128422, 0.000073046030, 0.000058546643, 0.003495229520,
0.005906654280, -0.010493946400, 0.078647598400,
0.043929663400, -0.073931943100, -0.010722735000,
-0.017236570000, 0.029041201600, 0.000394715293,
-0.000537710690, -0.000362268343, 0.000241854679,
-0.000788101770, 0.000060932686, 0.000467445735,
0.000365561370, -0.000302900477, 0.000423918964,
0.000300000013, -0.000134663171, 0.000006452519,
-0.000023320384, 0.000023532240, -0.000000863259,
0.000025535986, 0.000019870589, -0.000144529814,
-0.000033792868, 0.000024108483
],
[
-0.041043274800, -0.111783765000, 0.103907569000,
-0.011319168200, -0.017473385800, 0.027683119400,
0.003637838290, -0.005293631350, -0.002484344690,
0.000009821173, -0.000135428465, -0.000657571583,
0.005401929110, 0.008066891770, -0.013936543100,
0.043929663400, 0.124958213000, -0.115530393000,
0.000325281332, -0.000125007354, -0.000129258723,
0.000384143980, 0.001259101570, 0.000001306272,
-0.000870123215, 0.001042362100, -0.000426380057,
-0.000426090514, -0.001300320690, 0.001591298870,
0.000048406439, 0.000287275840, -0.000388354266,
0.000055737630, 0.000018935809, 0.000059096657,
-0.000026671850, 0.000148561268, 0.000149502306,
-0.000107492816, 0.000330197117, 0.000160952609
],
[
0.066112977000, 0.104729927000, -0.219256026000,
-0.000141509338, -0.003434017560, 0.001610715360,
-0.000237140037, -0.000606360776, 0.000853888771,
0.000284856041, -0.000227947707, 0.000021899914,
0.009954809490, 0.014503839500, -0.022850703000,
-0.073931943100, -0.115530393000, 0.238426713000,
-0.001172378760, -0.000473740575, -0.000085975425,
-0.000598006922, 0.000347859264, -0.000022101354,
-0.000104883229, 0.000359811438, 0.000893666466,
0.000047613768, -0.000039210588, -0.000025405264,
0.000008736166, -0.000126420940, -0.000048007771,
-0.000081103354, 0.000034200394, 0.000014479678,
-0.000018292858, 0.000237094498, 0.000030248075,
-0.000123734870, 0.000225358158, 0.000436607680
],
[
-0.304832510000, 0.001080107490, 0.001583703380,
-0.012312369900, -0.000361925575, -0.000005380242,
0.000536641625, -0.000954457648, 0.000202037882,
0.000131990037, 0.000240096907, -0.000169145634,
-0.011350612800, 0.000290968064, 0.001401288830,
-0.010722735000, 0.000325281332, -0.001172378760,
0.335968234000, -0.003796974450, -0.002196966940,
0.001014683130, 0.002301249850, 0.000503015956, 0.000603465592,
0.000253289215, 0.000532380180, 0.000412280046,
-0.000005518885, -0.000002154967, 0.000632261852,
0.000727256027, -0.000699875116, 0.000142228293,
-0.000106601886, 0.000148869356, 0.000006913742,
0.000060554518, -0.000076997589, -0.000230470931,
-0.000053324956, -0.000048396325
],
[
0.000618737475, -0.048474562500, -0.000080359730,
0.035615059900, -0.003081819410, 0.000353950668,
0.001192182950, 0.002153894160, -0.000630194064,
-0.000097828362, -0.000003210597, 0.000141233266,
-0.016458449400, -0.000150240230, 0.000811652521,
-0.017236570000, -0.000125007354, -0.000473740575,
-0.003796974450, 0.054324381900, 0.000328044615,
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0.019050222000, -0.050727185300, -0.060622006300,
0.000217093184, 0.001449697830, -0.000620791338,
0.000024108483, 0.000160952609, 0.000436607680,
-0.000048396325, 0.000051313421, -0.000045791452,
0.000021980223, 0.000034002544, -0.000161425910,
-0.000113295827, 0.000240416270, 0.000346357198,
-0.002453862220, -0.001611656380, -0.005414335160,
0.000067580103, 0.000648275660, 0.001417002250, 0.000095977887,
-0.000132316779, -0.000404681882, -0.008677730390,
0.023139046100, 0.005232700240, -0.018952145900,
0.058022644000, 0.067104607900
]
]
hess = np.array(hess)
st_pt = StationaryPoint(smi, 0, 1, smiles=smi)
st_pt.characterize()
natom = st_pt.natom
freq, reduced_freqs = frequencies.get_frequencies(st_pt, hess, geom)
# check the number of frequencies when neglecting internal rotors
warn = 'Wrong number of frequencies for '
warn += '{}, expected {}, calculated {}'.format(
smi, 3 * natom - 6, len(freq))
self.assertEqual(len(freq), 3 * natom - 6, warn)
# check the number of freauencies when including internal rotors
warn = 'Wrong number of frequencies for '
warn += '{}, expected {}, calculated {}'.format(
smi, 3 * natom - 6 - 3, len(reduced_freqs))
self.assertEqual(len(reduced_freqs), 3 * natom - 6 - 3, warn)
# check if the frequencies are as expected
exps = [
114.00308362581993, 217.27775429467988, 258.3569949257438,
324.95225959788496, 444.19934314923285, 775.6200599866132,
809.834778642176, 851.31690919327, 978.7594097713534,
1001.6985870040352, 1016.7427610310635, 1110.2892683008433,
1182.5149554411457, 1226.4874456219302, 1318.400582167711,
1338.054870101307, 1396.7770994771845, 1417.5721206176297,
1452.5015242293932, 1460.9939823348343, 1533.7500760993864,
1534.471579819868, 1544.1270899676583, 1549.977599644375,
1552.1602547884133, 1556.1540474667054, 3018.3546194275327,
3020.597688051164, 3036.615370205335, 3039.4844797216215,
3056.030309062557, 3060.954764774267, 3108.0034857725796,
3110.0837061265997, 3114.029978361547, 3121.6966999165047
]
for i, exp in enumerate(exps):
warn = 'Frequency values have wrong number: '
warn += 'expected {}, calculated {}'.format(exp, freq[i])
self.assertAlmostEqual(exp, freq[i], places=2, msg=warn)
# check if the reduced frequencies are as expected
exps = [
323.2231139328416, 443.06424130022316, 670.1999625377555,
765.4302138965138, 805.4817609384712, 923.6453995768678,
998.4208652995756, 1010.1550075636384, 1026.2590199716992,
1035.9563299669474, 1110.728140649036, 1237.3899533374413,
1297.0701335112522, 1319.639259548847, 1338.4248295874343,
1402.476769356911, 1417.8484347981505, 1476.7358681560938,
1487.8976160436305, 1525.2008164401302, 1544.0032443689747,
1547.12404969892, 1549.9807205743023, 2426.2794467384574,
2507.323795982035, 2864.813636413937, 3024.7798090881265,
3034.7484086579275, 3037.1066584298032, 3052.278595042064,
3107.809971415559, 3113.170533468414, 3113.8054919074493
]
for i, exp in enumerate(exps):
warn = 'Frequency values have wrong number: '
warn += 'expected {}, calculated {}'.format(exp, reduced_freqs[i])
self.assertAlmostEqual(exp, reduced_freqs[i], places=2, msg=warn)
def testFrequencies(self):
"""
Test the frequency calculator based on the hessian
by projecting out the translations, external rotations
and internal rotations
"""
# smiles of the speciesdata
smi = 'CCCC'
# geometry of the species
geom = [[ 0.91879892, -0.04331223, 0.12849174],
[ 0.40326992, 1.40563299, 0.15982756],
[ 0.89480303, 2.27635373, -1.01612317],
[ 0.37978671, 1.82281002, -2.39283836],
[ 0.56484506, -0.58104398, -0.75857814],
[ 0.58013979, -0.60154787, 1.00923604],
[ 2.01620768, -0.06868878, 0.11831706],
[-0.69710354, 1.40285362, 0.16867873],
[ 0.71679336, 1.87619548, 1.10252902],
[ 0.58079101, 3.31524962, -0.84143554],
[ 1.99516746, 2.28446562, -1.02104071],
[-0.71762425, 1.80824531, -2.41526122],
[ 0.72083567, 2.50053168, -3.18429864],
[ 0.73195359, 0.81628395, -2.64600957]]
geom = np.array(geom)
# hessian matrix
hess = [[ 0.557479281000, 0.036110582900, -0.001644922990, -0.094996623900, 0.033793056500, 0.001227901360, 0.004435637720, -0.010301447300, -0.000714141524, -0.000402278745, 0.000207775781, 0.000217081305, -0.079155177000, -0.041443873100, -0.069861527200, -0.075582477100, -0.041043274800, 0.066112977000, -0.304832510000, 0.000618737475, 0.001591972160, -0.011587172100, 0.035782319500, 0.001443997110, 0.003566576500, -0.009402669700, -0.000876604471, -0.000457712074, -0.002463678640, 0.002595980330, 0.000811779351, -0.001430576500, 0.000032881273, 0.000129362928, -0.000033252298, 0.000111660638, 0.000157802640, -0.000276891050, 0.000074700177, 0.000433511158, -0.000116808738, -0.000311955226],
[ 0.036110582900, 0.481460445000, -0.001497124110, 0.032529383300, -0.168787802000, -0.006867396700, 0.006092748400, -0.023937567300, 0.003730351660, -0.000262084184, 0.001441647380, 0.000316178114, -0.041989591900, -0.107986603000, -0.100880979000, -0.041503733500, -0.111783765000, 0.104729927000, 0.001080107490, -0.048474562500, -0.000241263827, -0.000265123753, -0.003449223290, -0.000371820596, 0.007618533730, -0.018717902300, 0.000837312337, -0.000555734072, -0.000078154904, 0.001999374050, 0.000646690960, 0.001260483370, -0.001360417570, 0.000088413780, -0.000085577196, 0.000164034911, -0.000076331932, -0.000238612455, -0.000622223468, 0.000486138870, -0.000622805294, 0.000064046666],
[-0.001644922990, -0.001497124110, 0.575851102000, 0.001964210840, -0.005551021620, -0.083609101600, -0.009286228620, 0.027728004900, 0.001373639180, -0.000137246872, 0.000910607647, 0.001051929890, -0.069899107500, -0.100194460000, -0.221142958000, 0.066308541300, 0.103907569000, -0.219256026000, 0.001583703380, -0.000080359730, -0.050839140900, -0.000325149456, 0.000352021138, 0.000321544325, 0.010807393200, -0.028918001700, -0.000253208170, 0.001475456680, 0.004079204780, -0.004016767400, -0.000771004699, -0.000846365220, 0.001019809380, -0.000285363620, 0.000091087635, -0.000075059137, -0.000051358279, -0.000192607794, 0.000123367411, 0.000261076583, 0.000211445408, -0.000549130393],
[-0.094996623900, 0.032529383300, 0.001964210840, 0.570648686000, 0.013726467600, 0.029803019800, -0.093894628800, -0.017540296600, 0.025240052300, 0.004430547620, 0.007089239030, -0.008470974800, 0.003985664600, -0.011160808500, -0.000344880024, 0.003352509560, -0.011319168200, -0.000141509338, -0.012312369900, 0.035615059900, 0.001341132350, -0.296633947000, -0.002814851200, -0.001857303680, -0.074252517800, -0.032055118900, -0.063305094900, 0.003016262880, 0.007165737430, -0.008147262180, -0.013171250400, -0.021050691300, 0.028389638100, 0.000515556167, 0.000833930927, -0.001531483210, -0.000733957654, -0.000834470892, -0.003543541800, 0.000046069520, -0.000184412716, 0.000603996490],
[ 0.033793056500, -0.168787802000, -0.005551021620, 0.013726467600, 0.471256701000, 0.045550224600, -0.019055559200, -0.110456357000, 0.036788918500, 0.003690246720, 0.008042833690, -0.005946132620, 0.007450531200, -0.016991805700, 0.000566738577, 0.007662075620, -0.017473385800, -0.003434017560, -0.000361925575, -0.003081819410, 0.000169600942, -0.002141608270, -0.048419727000, -0.001543381080, -0.032001313400, -0.092648760200, -0.091748171900, -0.012965805500, -0.019490702300, 0.027544257800, 0.000385145313, -0.001607085100, 0.002202751810, 0.000097042391, 0.000342026851, -0.000085156640, -0.000935724242, -0.000536578498, -0.003946142400, 0.000657370855, -0.000147538049, -0.000568468443],
[ 0.001227901360, -0.006867396700, -0.083609101600, 0.029803019800, 0.045550224600, 0.530185827000, 0.024067639100, 0.038254723800, -0.133557501000, 0.009656895150, 0.018083768400, -0.030339996500, 0.011176997800, -0.027940521700, 0.000197610447, -0.010718813500, 0.027683119400, 0.001610715360, -0.000005380242, 0.000353950668, -0.000058645732, -0.001385963250, -0.001490240310, -0.050945021400, -0.064025490200, -0.091980721200, -0.231554605000, -0.000068702298, -0.003001675120, 0.001414867140, 0.000375944632, 0.002432713030, -0.002619663450, 0.000967738003, 0.000578480710, 0.002131790000, -0.001665661510, -0.002059701750, -0.003910908180, 0.000593875240, 0.000403276118, 0.001054632250],
[ 0.004435637720, 0.006092748400, -0.009286228620, -0.093894628800, -0.019055559200, 0.024067639100, 0.570900497000, -0.032595232800, -0.004232877500, -0.095277421800, -0.011406581600, -0.030607826800, 0.000043159915, -0.000514838503, 0.000373962854, -0.000738247952, 0.003637838290, -0.000237140037, 0.000536641625, 0.001192182950, -0.001206594120, -0.013027642100, -0.020980119300, 0.028551488200, 0.003004879320, 0.005695987090, -0.009218334250, -0.074383197800, 0.070019040800, 0.012170299900, -0.296727831000, 0.002527681320, 0.001997681770, -0.012251640800, -0.011694206300, -0.033682439000, 0.003373175160, 0.003467893310, 0.010833941000, 0.004006619800, 0.003613165550, 0.010476427500],
[-0.010301447300, -0.023937567300, 0.027728004900, -0.017540296600, -0.110456357000, 0.038254723800, -0.032595232800, 0.550390617000, 0.021569897200, -0.011111359900, -0.094250354100, -0.029239287500, -0.000711297419, 0.000972151769, 0.000156692325, 0.001860692500, -0.005293631350, -0.000606360776, -0.000954457648, 0.002153894160, 0.000019371190, -0.000397838529, -0.001228430010, 0.002336752460, 0.003859667870, 0.006484974130, -0.010940182100, 0.070740800200, -0.270987312000, -0.037645349500, 0.001896728730, -0.051464188100, -0.000592835086, 0.000107061175, -0.000144181197, -0.000504021609, 0.007980792090, 0.006761052700, 0.020233362800, -0.012833812400, -0.009000668610, -0.030770768100],
[-0.000714141524, 0.003730351660, 0.001373639180, 0.025240052300, 0.036788918500, -0.133557501000, -0.004232877500, 0.021569897200, 0.451154731000, -0.032090962200, -0.028197579400, -0.158290659000, -0.000492084585, -0.000980152816, 0.000034862639, 0.000407801351, -0.002484344690, 0.000853888771, 0.000202037882, -0.000630194064, 0.000364010457, -0.000276661410, 0.002092844910, -0.002923760270, 0.012375619200, 0.019611685600, -0.024571878400, 0.011914527900, -0.037319661200, -0.053342229400, 0.001505776140, -0.000642112942, -0.047826423400, 0.000374606934, -0.000789448823, -0.002922212160, -0.010438695000, -0.010818867900, -0.022572722700, -0.003774999570, -0.001931336020, -0.007773745060],
[-0.000402278745, -0.000262084184, -0.000137246872, 0.004430547620, 0.003690246720, 0.009656895150, -0.095277421800, -0.011111359900, -0.032090962200, 0.558209213000, -0.009125619780, -0.034709539800, 0.000415340383, 0.000358171193, 0.000000905828, 0.000159128422, 0.000009821173, 0.000284856041, 0.000131990037, -0.000097828362, 0.000069311231, 0.000786266725, 0.000375904422, 0.001427105050, -0.000456009865, -0.001763774920, 0.003115461590, 0.003579063430, 0.003594264790, 0.008763686330, -0.011547639900, -0.011824677300, -0.033753097500, -0.305000167000, -0.001072859680, -0.000565352953, -0.076013943900, -0.051443542800, 0.058887756100, -0.079014088600, 0.078673338600, 0.019050222000],
[ 0.000207775781, 0.001441647380, 0.000910607647, 0.007089239030, 0.008042833690, 0.018083768400, -0.011406581600, -0.094250354100, -0.028197579400, -0.009125619780, 0.566853551000, -0.028314924300, -0.000405813331, -0.000316988707, 0.000087265018, 0.000073046030, -0.000135428465, -0.000227947707, 0.000240096907, -0.000003210597, 0.000052913364, 0.000562715807, 0.000386702658, -0.000586865840, -0.001249462100, -0.001984311450, 0.004661147410, -0.012569365100, -0.009659129560, -0.031620324000, 0.000388942723, -0.000027569785, -0.000685633791, -0.001195716590, -0.050831902500, 0.000607484566, -0.051498752000, -0.151306241000, 0.115957274000, 0.078889494300, -0.268209599000, -0.050727185300],
[ 0.000217081305, 0.000316178114, 0.001051929890, -0.008470974800, -0.005946132620, -0.030339996500, -0.030607826800, -0.029239287500, -0.158290659000, -0.034709539800, -0.028314924300, 0.489796505000, -0.000391829054, 0.000142067560, -0.000688267160, 0.000058546643, -0.000657571583, 0.000021899914, -0.000169145634, 0.000141233266, -0.000156069524, -0.000870684066, -0.001083763300, 0.001824089140, 0.000966571121, 0.002585026930, -0.002110201450, -0.004138394740, -0.001918643950, -0.009243037780, 0.000150249840, -0.001426379210, -0.003164852780, -0.000834451580, 0.000361231775, -0.048518990600, 0.059364188600, 0.116743826000, -0.179560342000, 0.019436209100, -0.051702861200, -0.060622006300],
[-0.079155177000, -0.041989591900, -0.069899107500, 0.003985664600, 0.007450531200, 0.011176997800, 0.000043159915, -0.000711297419, -0.000492084585, 0.000415340383, -0.000405813331, -0.000391829054, 0.082170568700, 0.043883239500, 0.078044112600, 0.003495229520, 0.005401929110, 0.009954809490, -0.011350612800, -0.016458449400, -0.029453532500, 0.000665737135, -0.000625010895, 0.000511858440, 0.000059291070, 0.003007766240, 0.000159750828, -0.000060170797, -0.000108422372, 0.000205866966, 0.000026998545, -0.000052468999, -0.000060908234, -0.000223489041, 0.000140719611, -0.000038210872, -0.000144869281, 0.000150427844, 0.000065183444, 0.000072328995, 0.000316440754, 0.000217093184],
[-0.041443873100, -0.107986603000, -0.100194460000, -0.011160808500, -0.016991805700, -0.027940521700, -0.000514838503, 0.000972151769, -0.000980152816, 0.000358171193, -0.000316988707, 0.000142067560, 0.043883239500, 0.119840850000, 0.111814261000, 0.005906654280, 0.008066891770, 0.014503839500, 0.000290968064, -0.000150240230, 0.000002063185, 0.000111922593, 0.001514337600, 0.000276003926, 0.002702457800, -0.005775080730, 0.000445401249, 0.000111932829, 0.000347388012, 0.000177052371, -0.000006786294, -0.000145911482, 0.000108411307, 0.000058268378, -0.000061770157, 0.000096427007, -0.000010851744, 0.000535119260, 0.000099909733, -0.000286456542, 0.000151661591, 0.001449697830],
[-0.069861527200, -0.100880979000, -0.221142958000, -0.000344880024, 0.000566738577, 0.000197610447, 0.000373962854, 0.000156692325, 0.000034862639, 0.000000905828, 0.000087265018, -0.000688267160, 0.078044112600, 0.111814261000, 0.242817300000, -0.010493946400, -0.013936543100, -0.022850703000, 0.001401288830, 0.000811652521, 0.000387534637, 0.000611035395, -0.000326880526, 0.000202559149, 0.000448151560, 0.000430071969, 0.001316161050, -0.000015506148, -0.000226147940, 0.000124908040, 0.000053325603, 0.000066745555, -0.000005338059, 0.000029804814, -0.000043582456, -0.000002800832, 0.000036585620, 0.000161681863, 0.000229922299, -0.000283313413, 0.001319024070, -0.000620791338],
[-0.075582477100, -0.041503733500, 0.066308541300, 0.003352509560, 0.007662075620, -0.010718813500, -0.000738247952, 0.001860692500, 0.000407801351, 0.000159128422, 0.000073046030, 0.000058546643, 0.003495229520, 0.005906654280, -0.010493946400, 0.078647598400, 0.043929663400, -0.073931943100, -0.010722735000, -0.017236570000, 0.029041201600, 0.000394715293, -0.000537710690, -0.000362268343, 0.000241854679, -0.000788101770, 0.000060932686, 0.000467445735, 0.000365561370, -0.000302900477, 0.000423918964, 0.000300000013, -0.000134663171, 0.000006452519, -0.000023320384, 0.000023532240, -0.000000863259, 0.000025535986, 0.000019870589, -0.000144529814, -0.000033792868, 0.000024108483],
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[ 0.000433511158, 0.000486138870, 0.000261076583, 0.000046069520, 0.000657370855, 0.000593875240, 0.004006619800, -0.012833812400, -0.003774999570, -0.079014088600, 0.078889494300, 0.019436209100, 0.000072328995, -0.000286456542, -0.000283313413, -0.000144529814, -0.000107492816, -0.000123734870, -0.000230470931, -0.000007975487, -0.000144934523, 0.000030532015, 0.000080159392, 0.000006043879, -0.000061535147, -0.000164903323, 0.000164720405, 0.000063586822, -0.001026058750, -0.002821565820, 0.000650645014, -0.000305373851, 0.000738835582, -0.011228983200, 0.032915002300, 0.007154649910, 0.003504547540, -0.011175418200, -0.002254716580, 0.081871766900, -0.087120674300, -0.018952145900],
[-0.000116808738, -0.000622805294, 0.000211445408, -0.000184412716, -0.000147538049, 0.000403276118, 0.003613165550, -0.009000668610, -0.001931336020, 0.078673338600, -0.268209599000, -0.051702861200, 0.000316440754, 0.000151661591, 0.001319024070, -0.000033792868, 0.000330197117, 0.000225358158, -0.000053324956, 0.000015565803, -0.000084799847, -0.000057961271, 0.000038523433, 0.000025108980, -0.000019191454, 0.000129961184, -0.000158353984, -0.001218387310, 0.000957816966, -0.001619506420, -0.000611794096, 0.000327669725, 0.000048572694, -0.001439226010, 0.000556604861, 0.000544568335, 0.008252628830, -0.020016956200, -0.005303140270, -0.087120674300, 0.295489566000, 0.058022644000],
[-0.000311955226, 0.000064046666, -0.000549130393, 0.000603996490, -0.000568468443, 0.001054632250, 0.010476427500, -0.030770768100, -0.007773745060, 0.019050222000, -0.050727185300, -0.060622006300, 0.000217093184, 0.001449697830, -0.000620791338, 0.000024108483, 0.000160952609, 0.000436607680, -0.000048396325, 0.000051313421, -0.000045791452, 0.000021980223, 0.000034002544, -0.000161425910, -0.000113295827, 0.000240416270, 0.000346357198, -0.002453862220, -0.001611656380, -0.005414335160, 0.000067580103, 0.000648275660, 0.001417002250, 0.000095977887, -0.000132316779, -0.000404681882, -0.008677730390, 0.023139046100, 0.005232700240, -0.018952145900, 0.058022644000, 0.067104607900]]
hess = np.array(hess)
st_pt = StationaryPoint(smi, 0, 1, smiles=smi)
st_pt.characterize()
natom = st_pt.natom
freq, reduced_freqs = frequencies.get_frequencies(st_pt, hess, geom)
# check the number of frequencies when neglecting internal rotors
warn = 'Wrong number of frequencies for '
warn += '{}, expected {}, calculated {}'.format(smi, 3 * natom - 6, len(freq))
self.assertEqual(len(freq), 3 * natom - 6, warn)
# check the number of freauencies when including internal rotors
warn = 'Wrong number of frequencies for '
warn += '{}, expected {}, calculated {}'.format(smi, 3 * natom - 6 - 3, len(reduced_freqs))
self.assertEqual(len(reduced_freqs), 3 * natom - 6 - 3, warn)
# check if the frequencies are as expected
exps = [114.00308362581993, 217.27775429467988, 258.3569949257438, 324.95225959788496, 444.19934314923285, 775.6200599866132, 809.834778642176, 851.31690919327, 978.7594097713534, 1001.6985870040352, 1016.7427610310635, 1110.2892683008433, 1182.5149554411457, 1226.4874456219302, 1318.400582167711, 1338.054870101307, 1396.7770994771845, 1417.5721206176297, 1452.5015242293932, 1460.9939823348343, 1533.7500760993864, 1534.471579819868, 1544.1270899676583, 1549.977599644375, 1552.1602547884133, 1556.1540474667054, 3018.3546194275327, 3020.597688051164, 3036.615370205335, 3039.4844797216215, 3056.030309062557, 3060.954764774267, 3108.0034857725796, 3110.0837061265997, 3114.029978361547, 3121.6966999165047]
for i, exp in enumerate(exps):
warn = 'Frequency values have wrong number: '
warn += 'expected {}, calculated {}'.format(exp, freq[i])
self.assertAlmostEqual(exp, freq[i], places=2, msg=warn)
# check if the reduced frequencies are as expected
exps = [323.2231139328416, 443.06424130022316, 670.1999625377555, 765.4302138965138, 805.4817609384712, 923.6453995768678, 998.4208652995756, 1010.1550075636384, 1026.2590199716992, 1035.9563299669474, 1110.728140649036, 1237.3899533374413, 1297.0701335112522, 1319.639259548847, 1338.4248295874343, 1402.476769356911, 1417.8484347981505, 1476.7358681560938, 1487.8976160436305, 1525.2008164401302, 1544.0032443689747, 1547.12404969892, 1549.9807205743023, 2426.2794467384574, 2507.323795982035, 2864.813636413937, 3024.7798090881265, 3034.7484086579275, 3037.1066584298032, 3052.278595042064, 3107.809971415559, 3113.170533468414, 3113.8054919074493]
for i, exp in enumerate(exps):
warn = 'Frequency values have wrong number: '
warn += 'expected {}, calculated {}'.format(exp, reduced_freqs[i])
self.assertAlmostEqual(exp, reduced_freqs[i], places=2, msg=warn)
def irc2stationary_pt(self):
"""
Read the irc files
There are three possible scenarios:
1. One of the ircs leads the initial well and
the other to another well or bimolecular product
2. Neither of the ircs lead to the inital well,
transition state structure is not the one
kinbot was looking for
3. Both the ircs lead to the initial well,
KinBot found either an identical reaction
or the ts is not correct
"""
instance_name = self.rxn.instance_name
directions = ['Forward', 'Reverse']
ini_well_hits = 0
prod_hit = -1
st_pts = [-1, -1]
for i, direction in enumerate(directions):
irc_name = '{}_IRC_{}_prod'.format(instance_name, direction[0])
err, geom = self.rxn.qc.get_qc_geom(irc_name,
self.rxn.species.natom,
allow_error=1)
if err == -1:
return 0
if self.problem_in_geom(geom):
# this happens seldom that all the atoms are
# very close to one another (problem in Gaussian)
logging.info('\tProblem with product geometry for {}'.format(
instance_name))
return 0
temp = StationaryPoint(irc_name,
self.rxn.species.charge,
self.rxn.species.mult,
atom=self.rxn.species.atom,
geom=geom)
temp.characterize()
st_pts[i] = temp
if temp.chemid == self.rxn.species.chemid and all(
temp.chiral[at] == self.rxn.species.chiral[at]
for at in range(self.rxn.species.natom)):
ini_well_hits += 1
elif str(temp.chemid) in self.par['skip_chemids']:
logging.info(
'\tReaction {} leads to forbidden chemid {}'.format(
instance_name, temp.chemid))
return 0
else:
prod_hit = i # this leaves the possibility of a chirality changing reaction
if ini_well_hits == 0:
logging.info(
'\tNeither IRC leads to the well for {}'.format(instance_name))
return 0
elif ini_well_hits == 2:
logging.info(
'\tBoth IRCs lead to the well, identical reaction found: {}'.
format(instance_name))
return 0
else:
# ircs OK: well and product found
logging.info('\tIRCs successful for {}'.format(instance_name))
return st_pts[prod_hit]
def create_mess_input(par, wells, products, reactions, barrierless,
well_energies, prod_energies, parent):
"""
When calculating a full pes, the files from the separate wells
are read and concatenated into one file
Two things per file need to be updated
1. the names of all the wells, bimolecular products and ts's
2. all the zpe corrected energies
"""
# generate short names for all startionary points
well_short, pr_short, fr_short, ts_short, nobar_short = create_short_names(
wells, products, reactions, barrierless)
# list of the strings to write to mess input file
s = []
#create mess0 label for mess header
well0 = StationaryPoint('well0',
par.par['charge'],
par.par['mult'],
smiles=par.par['smiles'],
structure=par.par['structure'])
well0.characterize(dimer=par.par['dimer'])
"""
Create the header block for MESS
"""
# Read the header template
header_file = pkg_resources.resource_filename('tpl', 'mess_header.tpl')
with open(header_file) as f:
tpl = f.read()
header = tpl.format(
TemperatureList=' '.join(
[str(ti) for ti in par.par['TemperatureList']]),
PressureList=' '.join([str(pi) for pi in par.par['PressureList']]),
EnergyStepOverTemperature=par.par['EnergyStepOverTemperature'],
ExcessEnergyOverTemperature=par.par['ExcessEnergyOverTemperature'],
ModelEnergyLimit=par.par['ModelEnergyLimit'],
CalculationMethod=par.par['CalculationMethod'],
ChemicalEigenvalueMax=par.par['ChemicalEigenvalueMax'],
Reactant=well_short[wells[0]],
EnergyRelaxationFactor=par.par['EnergyRelaxationFactor'],
EnergyRelaxationPower=par.par['EnergyRelaxationPower'],
EnergyRelaxationExponentCutoff=par.
par['EnergyRelaxationExponentCutoff'],
e_coll=constants.epsilon[par.par['collider']],
s_coll=constants.sigma[par.par['collider']],
m_coll=constants.mass[par.par['collider']],
e_well=par.par['epsilon'],
s_well=par.par['sigma'],
m_well=well0.mass,
)
# write the wells
s.append('######################')
s.append('# WELLS')
s.append('######################')
for well in wells:
name = well_short[well] + ' ! ' + well
energy = well_energies[well]
with open(parent[well] + '/' + well + '.mess') as f:
s.append(f.read().format(name=name, zeroenergy=energy))
s.append('!****************************************')
# write the products
s.append('######################')
s.append('# BIMOLECULAR PRODUCTS')
s.append('######################')
a = 0
for prod in products:
name = pr_short[prod] + ' ! ' + prod
energy = prod_energies[prod]
fr_names = {}
for fr in prod.split('_'):
key = 'fr_name_{}'.format(fr)
value = fr_short[fr] + ' ! ' + fr
fr_names[key] = value
with open(parent[prod] + '/' + prod + '.mess') as f:
s.append(f.read().format(name=name,
ground_energy=energy,
**fr_names))
a = a + 1
s.append('!****************************************')
# write the barrier
s.append('######################')
s.append('# BARRIERS')
s.append('######################')
for rxn in reactions:
name = [ts_short[rxn[1]]]
name.append(well_short[rxn[0]])
if len(rxn[2]) == 1:
name.append(well_short[rxn[2][0]])
else:
name.append(pr_short['_'.join(sorted(rxn[2]))])
name.append('!')
name.append(rxn[1])
energy = rxn[3]
try:
with open(rxn[0] + '/' + rxn[1] + '.mess') as f:
s.append(f.read().format(name=' '.join(name),
zeroenergy=energy))
s.append('!****************************************')
except:
logging.info(('{0} {1} {2} {3}'.format(rxn[0], "/", rxn[1],
".mess not found\n")))
# add last end statement
s.append('!****************************************')
for rxn in barrierless:
name = [nobar_short]
name.append(rxn[0])
if len(rxn[2]) > 1:
name.append(pr_short['_'.join(sorted(rxn[2]))])
else:
name.append(rxn[2])
energy = rxn[3]
s.append('! BARRIERLESS REACTIONS !')
try:
with open(rxn[0] + '/' + rxn[2] + '.mess') as f:
s.append(f.read().format(name=' '.join(name),
zeroenergy=energy))
s.append('!****************************************')
except:
logging.info('{0} {1} {2} {3}'.format(rxn[0], "/", rxn[2],
".mess not found\n"))
# add last end statement
s.append('!****************************************')
s.append('End ! end kinetics\n')
if not os.path.exists('me'):
os.mkdir('me')
# write everything to a file
with open('me/mess.inp', 'w') as f:
f.write(header)
f.write('\n'.join(s))
dummy = StationaryPoint('dummy',
par.par['charge'],
par.par['mult'],
smiles=par.par['smiles'],
structure=par.par['structure'])
well0.characterize(dimer=par.par['dimer'])
def main():
try:
input_file = sys.argv[1]
except IndexError:
print('To use KinBot, supply one argument being the input file!')
sys.exit(-1)
# print the license message to the console
print(license_message.message)
# initialize the parameters for this run
masterpar = Parameters(input_file)
par = masterpar.par
input_file = masterpar.input_file
# set up the logging environment
if par['verbose']:
logging.basicConfig(filename='kinbot.log', level=logging.DEBUG)
else:
logging.basicConfig(filename='kinbot.log', level=logging.INFO)
# write the license message to the log file
logging.info(license_message.message)
logging.info('Input parameters')
for param in par:
logging.info('{} {}'.format(param, par[param]))
# time stamp of the KinBot start
logging.info('Starting KinBot at {}'.format(datetime.datetime.now()))
# Make the necessary directories
if not os.path.exists('perm'):
os.makedirs('perm')
if not os.path.exists('scratch'):
os.makedirs('scratch')
if not os.path.exists(par['single_point_qc']):
os.mkdir(par['single_point_qc'])
if par['rotor_scan'] == 1:
if not os.path.exists('hir'):
os.mkdir('hir')
if not os.path.exists('hir_profiles'):
os.mkdir('hir_profiles')
if not os.path.exists('perm/hir/'):
os.makedirs('perm/hir/')
if par['conformer_search'] == 1:
if not os.path.exists('conf'):
os.mkdir('conf')
if not os.path.exists('perm/conf'):
os.makedirs('perm/conf')
if not os.path.exists('me'):
os.mkdir('me')
# initialize the reactant
well0 = StationaryPoint('well0',
par['charge'],
par['mult'],
smiles=par['smiles'],
structure=par['structure'])
well0.short_name = 'w1'
# write the initial reactant geometry to a file for visualization
geom_out = open('geometry.xyz', 'w')
geom_out.write('{}\n\n'.format(well0.natom))
for i, at in enumerate(well0.atom):
x, y, z = well0.geom[i]
geom_out.write('{} {:.6f} {:.6f} {:.6f}\n'.format(at, x, y, z))
geom_out.write('\n\n')
geom_out.close()
# characterize the initial reactant
well0.characterize(dimer=par['dimer'])
well0.name = str(well0.chemid)
start_name = well0.name
# initialize the qc instance
qc = QuantumChemistry(par)
# only run filecopying if PES is turned on
# if par['pes']:
# check if this well was calcualted before in another directory
# this flag indicates that this kinbot run
# should wait for the information from another
# kinbot run to become available and copy the necessary information
# wait_for_well = 1
# while wait_for_well:
# wait_for_well = filecopying.copy_from_database_folder(well0.chemid, well0.chemid, qc)
# if wait_for_well:
# time.sleep(1)
# start the initial optimization of the reactant
logging.info('Starting optimization of intial well')
qc.qc_opt(well0, well0.geom)
err, well0.geom = qc.get_qc_geom(str(well0.chemid) + '_well',
well0.natom,
wait=1)
err, well0.freq = qc.get_qc_freq(str(well0.chemid) + '_well',
well0.natom,
wait=1)
if err < 0:
logging.error('Error with initial structure optimization.')
return
if any(well0.freq[i] <= 0 for i in range(len(well0.freq))):
logging.error('Found imaginary frequency for initial structure.')
return
# characterize again and look for differences
well0.characterize(dimer=par['dimer'])
well0.name = str(well0.chemid)
if well0.name != start_name:
logging.error(
'The first well optimized to a structure different from the input.'
)
return
# do an MP2 optimization of the reactant,
# to compare some scan barrier heigths to
if par['families'] == ['all'] or \
'birad_recombination_R' in par['families'] or \
'r12_cycloaddition' in par['families'] or \
'r14_birad_scission' in par['families'] or \
'R_Addition_MultipleBond' in par['families'] or \
(par['skip_families'] != ['none'] and \
('birad_recombination_R' not in par['skip_families'] or \
'r12_cycloaddition' not in par['skip_families'] or \
'r14_birad_scission' not in par['skip_families'] or \
'R_Addition_MultipleBond' not in par['skip_families'])) or \
par['reaction_search'] == 0:
logging.info('Starting MP2 optimization of intial well')
qc.qc_opt(well0, well0.geom, mp2=1)
err, geom = qc.get_qc_geom(
str(well0.chemid) + '_well_mp2', well0.natom, 1)
# comparison for barrierless scan
if par['barrierless_saddle']:
logging.info(
'Optimization of intial well for barrierless at {}/{}'.format(
par['barrierless_saddle_method'],
par['barrierless_saddle_basis']))
qc.qc_opt(well0, well0.geom, bls=1)
err, geom = qc.get_qc_geom(
str(well0.chemid) + '_well_bls', well0.natom, 1)
# characterize again and look for differences
well0.characterize(dimer=par['dimer'])
well0.name = str(well0.chemid)
err, well0.energy = qc.get_qc_energy(str(well0.chemid) + '_well', 1)
err, well0.zpe = qc.get_qc_zpe(str(well0.chemid) + '_well', 1)
well_opt = Optimize(well0, par, qc, wait=1)
well_opt.do_optimization()
if well_opt.shigh == -999:
logging.error(
'Error with high level optimization of initial structure.')
return
if par['pes']:
filecopying.copy_to_database_folder(well0.chemid, well0.chemid, qc)
if par['reaction_search'] == 1:
logging.info('Starting reaction searches of intial well')
rf = ReactionFinder(well0, par, qc)
rf.find_reactions()
rg = ReactionGenerator(well0, par, qc, input_file)
rg.generate()
if par['homolytic_scissions'] == 1:
logging.info('Starting the search for homolytic scission products')
well0.homolytic_scissions = HomolyticScissions(well0, par, qc)
well0.homolytic_scissions.find_homolytic_scissions()
if par['me'] > 0: # it will be 2 for kinbots when the mess file is needed but not run
mess = MESS(par, well0)
mess.write_input(qc)
if par['me'] == 1:
logging.info('Starting Master Equation calculations')
if par['me_code'] == 'mess':
mess.run()
postprocess.createSummaryFile(well0, qc, par)
postprocess.createPESViewerInput(well0, qc, par)
postprocess.creatMLInput(well0, qc, par)
logging.info('Finished KinBot at {}'.format(datetime.datetime.now()))
print("Done!")
def main():
try:
input_file = sys.argv[1]
except IndexError:
print('To use KinBot, supply one argument being the input file!')
sys.exit(-1)
# print the license message to the console
print(license_message.message)
# initialize the parameters for this run
par = Parameters(input_file)
# set up the logging environment
if par.par['verbose']:
logging.basicConfig(filename='kinbot.log', level=logging.DEBUG)
else:
logging.basicConfig(filename='kinbot.log', level=logging.INFO)
# write the license message to the log file
logging.info(license_message.message)
# time stamp of the KinBot start
logging.info('Starting KinBot at {}'.format(datetime.datetime.now()))
# Make the necessary directories
if not os.path.exists('perm'):
os.makedirs('perm')
if not os.path.exists('scratch'):
os.makedirs('scratch')
if not os.path.exists(par.par['single_point_qc']):
os.mkdir(par.par['single_point_qc'])
if par.par['rotor_scan'] == 1:
if not os.path.exists('hir'):
os.mkdir('hir')
if not os.path.exists('hir_profiles'):
os.mkdir('hir_profiles')
if not os.path.exists('perm/hir/'):
os.makedirs('perm/hir/')
if par.par['conformer_search'] == 1:
if not os.path.exists('conf'):
os.mkdir('conf')
if not os.path.exists('perm/conf'):
os.makedirs('perm/conf')
if not os.path.exists('me'):
os.mkdir('me')
if par.par['pes'] and par.par['specific_reaction']:
logging.error('Specific reaction cannot be searched in PES mode.')
return
# initialize the reactant
well0 = StationaryPoint('well0',
par.par['charge'],
par.par['mult'],
smiles=par.par['smiles'],
structure=par.par['structure'])
well0.short_name = 'w1'
# wrtie the initial reactant geometry to a file for visualization
geom_out = open('geometry.xyz', 'w')
geom_out.write('{}\n\n'.format(well0.natom))
for i, at in enumerate(well0.atom):
x, y, z = well0.geom[i]
geom_out.write('{} {:.6f} {:.6f} {:.6f}\n'.format(at, x, y, z))
geom_out.write('\n\n')
geom_out.close()
# characterize the initial reactant
well0.characterize(par.par['dimer'])
well0.name = str(well0.chemid)
start_name = well0.name
# initialize the qc instance
qc = QuantumChemistry(par)
# start the initial optimization of the reactant
logging.info('Starting optimization of intial well')
qc.qc_opt(well0, well0.geom)
err, well0.geom = qc.get_qc_geom(str(well0.chemid) + '_well',
well0.natom, wait=1)
err, well0.freq = qc.get_qc_freq(str(well0.chemid) + '_well',
well0.natom, wait=1)
if err < 0:
logging.error('Error with initial structure optimization.')
return
if any(well0.freq[i] <= 0 for i in range(len(well0.freq))):
logging.error('Found imaginary frequency for initial structure.')
return
# characterize again and look for differences
well0.characterize(par.par['dimer'])
well0.name = str(well0.chemid)
if well0.name != start_name:
logging.error('The first well optimized to a structure different from the input.')
return
# do an MP2 optimization of the reactant,
# to compare Beta scission barrier heigths to
logging.info('Starting MP2 optimization of intial well')
qc.qc_opt(well0, well0.geom, mp2=1)
err, geom = qc.get_qc_geom(str(well0.chemid) + '_well_mp2', well0.natom, 1)
# characterize again and look for differences
well0.characterize(par.par['dimer'])
well0.name = str(well0.chemid)
# read the energy and the zpe corrected energy
err, well0.energy = qc.get_qc_energy(str(well0.chemid) + '_well', 1)
err, well0.zpe = qc.get_qc_zpe(str(well0.chemid) + '_well', 1)
well_opt = Optimize(well0, par, qc, wait=1)
well_opt.do_optimization()
if well_opt.shigh == -999:
logging.error('Error with high level optimization of initial structure.')
return
# do the reaction search using heuristics
if par.par['reaction_search'] == 1:
logging.info('Starting reaction searches of intial well')
rf = ReactionFinder(well0, par, qc)
rf.find_reactions()
rg = ReactionGenerator(well0, par, qc)
rg.generate()
# do the homolytic scission products search
if par.par['homolytic_scissions'] == 1:
logging.info('Starting the search for homolytic scission products')
well0.homolytic_scissions = HomolyticScissions(well0, par, qc)
well0.homolytic_scissions.find_homolytic_scissions()
# initialize the master equation instance
mess = MESS(par, well0)
mess.write_input()
mesmer = MESMER(par, well0)
mesmer.write_input()
if par.par['me'] == 1:
logging.info('Starting Master Equation calculations')
if par.par['me_code'] == 'mess':
mess.run()
elif par.par['me_code'] == 'mesmer':
mesmer.run()
else:
logging.error('Cannot recognize me code {}'.format(par.par['me_code']))
# postprocess the calculations
postprocess.createSummaryFile(well0, qc, par)
postprocess.createPESViewerInput(well0, qc, par)
postprocess.creatMLInput(well0, qc, par)
logging.info('Finished KinBot at {}'.format(datetime.datetime.now()))
print("Done!")
