def test_hessian_transfer():
"""Test DFTB -> Orca hessian transfer."""
h2o = molkit.from_smiles('O')
h2o.properties.symmetry = 'C1'
h2o_freq = dftb(templates.freq, h2o, job_name="freq").hessian
s = Settings()
s.inithess = h2o_freq
h2o_opt = orca(templates.geometry.overlay(s), h2o, job_name="opt")
energy = h2o_opt.energy
dipole = h2o_opt.dipole
wf = gather(energy, dipole)
logger.info(run(wf))
def test_orca_init_hessian():
"""Test the translation from settings to CP2K specific keywords."""
# Read Hessian from DFTB
PATH_RKF = PATH / "output_dftb" / "dftb_freq" / "dftb.rkf"
assertion.truth(PATH_RKF.exists())
hess = kfreader(PATH_RKF, section="AMSResults", prop="Hessian")
water = molkit.from_smiles('[OH2]', forcefield='mmff')
# Tess Hessian initialization
s = Settings()
hess = np.array(hess).reshape(9, 9)
s.inithess = hess
ORCA.handle_special_keywords(s, "inithess", hess, water)
# Test that the hessian is readable
new_hess = parse_hessian(s.specific.orca.geom.InHessName)
new_hess = np.array(new_hess, dtype=np.float64)
assertion.truth(np.allclose(hess, new_hess, atol=1e-5))
def test_hessian_transfer():
"""
Test DFTB -> Orca hessian transfer
"""
h2o = molkit.from_smiles('O')
h2o.properties.symmetry = 'C1'
h2o_freq = dftb(templates.freq, h2o, job_name="freq").hessian
s = Settings()
s.inithess = h2o_freq
h2o_opt = orca(templates.geometry.overlay(s), h2o, job_name="opt")
energy = h2o_opt.energy
dipole = h2o_opt.dipole
wf = gather(energy, dipole)
print(run(wf))
def example_H2O2_TS():
"""
This example generates an approximate TS for rotation in hydrogen peroxide
using DFTB, and performs a full TS optimization in Orca.
It illustrates using a hessian from one package, DFTB in this case,
to initialize a TS optimization in another, i.e. Orca in this case
"""
# Generate hydrogen peroxide molecule
h2o2 = molkit.from_smarts('[H]OO[H]')
# Define dihedral angle
dihe = Dihedral(1, 2, 3, 4)
# Constrained geometry optimization with DFTB
# The dihedral is set to 0.0 to obtain an approximate TS
s1 = Settings()
s1.constraint.update(dihe.get_settings(0.0))
dftb_opt = dftb(templates.geometry.overlay(s1), h2o2)
# Calculate the DFTB hessian
dftb_freq = dftb(templates.freq, dftb_opt.molecule)
# Transition state calculation using the DFTB hessian as starting point
s2 = Settings()
s2.inithess = dftb_freq.hessian
orca_ts = orca(templates.ts.overlay(s2), dftb_opt.molecule)
# Execute the workflow
result = run(orca_ts)
# Analyse the result
ts_dihe = round(dihe.get_current_value(result.molecule))
n_optcycles = result.optcycles
print('Dihedral angle (degrees): {:.0f}'.format(ts_dihe))
print('Number of optimization cycles: {:d}'.format(n_optcycles))
return ts_dihe, n_optcycles
consset = Settings()
consset.constraint.update(bond1.get_settings(2.0 + d * 0.1))
consset.constraint.update(bond2.get_settings(2.0 + d * 0.1))
pes_name = name + "_pes_" + str(d)
pes_dftb = dftb(templates.geometry.overlay(settings).overlay(consset), p.molecule, job_name=pes_name + "_DFTB")
pes = adf(templates.singlepoint.overlay(settings), pes_dftb.molecule, job_name=pes_name)
pes_jobs.append(pes)
# Get the result with the maximum energy
apprTS = select_max(gather(*pes_jobs), 'energy')
# Calculate the DFTB hessian
DFTBfreq = dftb(templates.freq.overlay(settings), apprTS.molecule, job_name=name + "_freq_DFTB")
# Run the TS optimization, using the initial hession from DFTB
t = Settings()
t.inithess = DFTBfreq.hessian
TS = adf(templates.ts.overlay(settings).overlay(t), DFTBfreq.molecule, job_name=name + "_TS")
# Perform a freq calculation
# freq_setting = Settings()
# freq_setting.specific.adf.geometry.frequencies = ""
# freq_setting.specific.adf.geometry.__block_replace = True
# TSfreq = adf(templates.geometry.overlay(settings).overlay(freq_setting), TS.molecule, job_name=name + "_freq")
TSfreq = adf(templates.freq.overlay(settings), TS.molecule, job_name=name + "_freq")
# Add the jobs to the job list
job_list.append(gather(r1_freq, r2_freq, p_freq, TS, TSfreq))
# Finalize and draw workflow
wf = gather(*job_list)
draw_workflow("wf.svg", wf._workflow)
dftb_set.specific.dftb.dftb.scc
# Calculate the DFTB hessian
freq_dftb = dftb(templates.freq.overlay(dftb_set),
guessTS,
job_name="freq_dftb")
# User define Settings
settings = Settings()
settings.functional = "b3lyp"
settings.specific.orca.basis.basis = "_3_21G"
settings.specific.orca.basis.pol = "_d"
settings.specific.orca.basis.diff = "_p"
# Run the TS optimization, using the initial hessian from DFTB
settings.inithess = freq_dftb.hessian
# Define job
ts = orca(templates.ts.overlay(settings), guessTS, job_name="ts")
# Actual execution of the jobs
ts_result = run(ts)
# Bonds to be formed (based on atom numbers in de product)
bond1 = Distance(0, 1)
bond2 = Distance(3, 4)
d1 = bond1.get_current_value(ts_result.molecule)
d2 = bond2.get_current_value(ts_result.molecule)
optcycles = ts_result.optcycles
# coordinates for the new atoms
temp.atoms[47].move_to((0.0, 0.0, 0.0))
temp.atoms[48].move_to((0.0, 0.0, 0.0))
# Replace dummy atoms by new groups, generate coordinates only for new atoms
job_list = []
for mod, smirks in list_of_modifications.items():
print(mod)
temp2, freeze = molkit.apply_reaction_smarts(temp, smirks, complete=True)
# generate job
s = Settings()
s.freeze = freeze
s.specific.dftb.dftb.resourcesdir = 'QUASINANO2015'
partial_geometry = dftb(templates.geometry.overlay(s),
temp2,
job_name="partial_opt_" + mod)
freq_dftb = dftb(templates.freq.overlay(s),
partial_geometry.molecule,
job_name="freq_" + mod)
s = Settings()
s.specific.orca.main = "B97-D"
s.specific.orca.basis.basis = "_6_31G"
s.specific.orca.basis.pol = "_d"
s.inithess = freq_dftb.hessian
ts = orca(templates.ts.overlay(s),
freq_dftb.molecule,
job_name="ts_" + mod)
freq = orca(templates.freq.overlay(s), ts.molecule, job_name="freq" + mod)
job_list.append(freq)
results = run(gather(*job_list), folder="Chris_results", n_processes=1)