def test_freeze_with_adf():
mol = molkit.from_smiles('CO')
s = Settings()
s.freeze = ["C", "O"]
expected_settings = Settings({
'freeze': ["C", "O"],
'specific': {
'adf': {
'constraints': {
'atom 1': '',
'atom 2': ''
},
'geometry': {
'optim': 'cartesian'
}
}
}
})
assert str(adf.generic2specific(s, mol)) == str(expected_settings)
s.freeze = [1, 2]
expected_settings = Settings({
'freeze': [1, 2],
'specific': {
'adf': {
'constraints': {
'atom 1': '',
'atom 2': ''
},
'geometry': {
'optim': 'cartesian'
}
}
}
})
assert str(adf.generic2specific(s, mol)) == str(expected_settings)
def test_freeze_with_orca():
mol = molkit.from_smiles('CO')
s = Settings()
s.freeze = ["C", "O"]
expected_settings = Settings({
'freeze': ['C', 'O'],
'specific': {
'orca': {
'geom': {
'Constraints': {
'_end': '{ C 0 C }{ C 1 C }'
}
}
}
}
})
assert str(orca.generic2specific(s, mol)) == str(expected_settings)
s.freeze = [1, 2]
expected_settings = Settings({
'freeze': [1, 2],
'specific': {
'orca': {
'geom': {
'Constraints': {
'_end': '{ C 0 C }{ C 1 C }'
}
}
}
}
})
assert str(orca.generic2specific(s, mol)) == str(expected_settings)
def test_freeze_with_adf():
mol = molkit.from_smiles('CO')
s = Settings()
s.freeze = ["C", "O"]
expected_settings = Settings({'freeze': ["C", "O"], 'specific': adf_const})
assert str(adf.generic2specific(s, mol)) == str(expected_settings)
s.freeze = [1, 2]
expected_settings = Settings({'freeze': [1, 2], 'specific': adf_const})
assert str(adf.generic2specific(s, mol)) == str(expected_settings)
def test_freeze_with_dftb():
mol = molkit.from_smiles('CO')
s = Settings()
s.freeze = ["C", "O"]
expected_settings = Settings(
{'freeze': ['C', 'O'], 'specific': dftb_const})
assert str(dftb.generic2specific(s, mol)) == str(expected_settings)
s.freeze = [1, 2]
expected_settings = Settings(
{'freeze': [1, 2], 'specific': dftb_const})
assert str(dftb.generic2specific(s, mol)) == str(expected_settings)
def test_freeze_with_adf():
mol = molkit.from_smiles('CO')
s = Settings()
s.freeze = ["C", "O"]
expected_settings = Settings(
{'freeze': ["C", "O"], 'specific': adf_const})
assert str(adf.generic2specific(s, mol)) == str(expected_settings)
s.freeze = [1, 2]
expected_settings = Settings(
{'freeze': [1, 2], 'specific': adf_const})
assert str(adf.generic2specific(s, mol)) == str(expected_settings)
def test_freeze_with_dftb():
"""Test freeze keyword for DFTB."""
mol = molkit.from_smiles('CO')
s = Settings()
s.freeze = ["C", "O"]
expected_settings = Settings(
{'freeze': ['C', 'O'], 'specific': dftb_const})
assertion.eq(str(dftb.generic2specific(s, mol)), str(expected_settings))
s.freeze = [1, 2]
expected_settings = Settings(
{'freeze': [1, 2], 'specific': dftb_const})
assertion.eq(str(dftb.generic2specific(s, mol)), str(expected_settings))
def test_freeze_with_adf():
"""Test the freeze keyword with ADF."""
mol = molkit.from_smiles('CO')
s = Settings()
s.freeze = ["C", "O"]
expected_settings = Settings(
{'freeze': ["C", "O"], 'specific': adf_const})
assertion.eq(str(adf.generic2specific(s, mol)), str(expected_settings))
s.freeze = [1, 2]
expected_settings = Settings(
{'freeze': [1, 2], 'specific': adf_const})
assertion.eq(str(adf.generic2specific(s, mol)), str(expected_settings))
def test_freeze_with_dftb():
mol = molkit.from_smiles('CO')
s = Settings()
s.freeze = ["C", "O"]
expected_settings = Settings({
'freeze': ['C', 'O'],
'specific': dftb_const
})
assert str(dftb.generic2specific(s, mol)) == str(expected_settings)
s.freeze = [1, 2]
expected_settings = Settings({'freeze': [1, 2], 'specific': dftb_const})
assert str(dftb.generic2specific(s, mol)) == str(expected_settings)
def test_freeze_with_gamess():
mol = molkit.from_smiles('CO')
s = Settings()
s.freeze = ["C", "O"]
expected_settings = Settings({
'freeze': ['C', 'O'],
'specific': {
'gamess': {
'statpt': 'IFREEZ(1)=1,2,3,4,5,6'
}
}
})
assert str(gamess.generic2specific(s, mol)) == str(expected_settings)
s = Settings()
s.freeze = [1, 2]
expected_settings = Settings({
'freeze': [1, 2],
'specific': {
'gamess': {
'statpt': 'IFREEZ(1)=1,2,3,4,5,6'
}
}
})
assert str(gamess.generic2specific(s, mol)) == str(expected_settings)
def example_partial_geometry_opt():
"""
Performa partial optimization freezing the Hydrogen atoms
"""
methanol = molkit.from_smiles('CO')
# optimize only H atoms
s = Settings()
s.freeze = [1, 2]
geom_job1 = adf(templates.geometry.overlay(s), methanol, job_name='geom_job1').molecule
# optimize only H atoms
s = Settings()
s.selected_atoms = ['H']
geom_job2 = adf(templates.geometry.overlay(s), methanol, job_name='geom_job2').molecule
geom1, geom2 = run(gather(geom_job1, geom_job2), n_processes=1)
return geom1, geom2
def example_partial_geometry_opt():
"""Performa partial optimization freezing the Hydrogen atoms."""
methanol = molkit.from_smiles('CO')
# optimize only H atoms
s = Settings()
s.freeze = [1, 2]
geom_job1 = adf(templates.geometry.overlay(s),
methanol,
job_name='geom_job1').molecule
# optimize only H atoms
s = Settings()
s.selected_atoms = ['H']
geom_job2 = adf(templates.geometry.overlay(s),
methanol,
job_name='geom_job2').molecule
geom1, geom2 = run(gather(geom_job1, geom_job2), n_processes=1)
return geom1, geom2
newmol = molkit.apply_template(HH, template)
# Change the 2 hydrogens to dummy atoms
temp = molkit.modify_atom(newmol, 47, '*')
temp = molkit.modify_atom(temp, 48, '*')
# Put coordinates of dummy atoms to 0.0, this will force generating new
# 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)