def test_c2pk_cell_opt() -> None:
"""Test CP2K cell optimization calculations with the :class:`CP2K_MM` class."""
mol = Molecule(PATH / 'cspbbr3_3d.xyz')
s = Settings()
s.specific.cp2k += cell_opt.specific.cp2k_mm.copy()
s.specific.cp2k.motion.cell_opt.max_iter = 10
s.specific.cp2k.motion.print['forces low'].filename = ''
s.gmax = [22, 22, 22]
s.cell_parameters = [25.452, 35.995, 24.452]
s.charge = {
'param': 'charge',
'Cs': 0.2,
'Pb': 0.4,
'Br': -0.2,
}
s.lennard_jones = {
'param': ('sigma', 'epsilon'),
'unit': ('nm', 'kjmol'),
'Cs Cs': (0.585, 1),
'Cs Pb': (0.510, 1),
'Br Se': (0.385, 1),
'Pb Pb': (0.598, 1),
'Br Pb': (0.290, 1),
'Br Br': (0.426, 1),
}
job = cp2k_mm(settings=s, mol=mol, job_name='cp2k_mm_cell_opt')
result = run(job, path=PATH)
assertion.eq(result.status, 'successful')
def validate_prop_group(group: h5py.Group) -> None:
"""Validate the passed hdf5 **group**, ensuring it is compatible with :func:`create_prop_group` and :func:`create_prop_group`.
This method is called automatically when an exception is raised by :func:`update_prop_dset`.
Parameters
----------
group : :class:`h5py.Group`
The to-be validated hdf5 Group.
Raises
------
:exc:`AssertionError`
Raised if the validation process fails.
""" # noqa: E501
assertion.isinstance(group, h5py.Group)
idx_ref = group.attrs['index']
idx = group.file[idx_ref]
iterator = ((k, v) for k, v in group.items() if not k.endswith('_names'))
for name, dset in iterator:
assertion.le(len(dset),
len(idx),
message=f'{name!r} invalid dataset length')
assertion.contains(dset.dims[0].keys(),
'index',
message=f'{name!r} missing dataset scale')
assertion.eq(dset.dims[0]['index'],
idx,
message=f'{name!r} invalid dataset scale')
def test_float() -> None:
"""Tests for :meth:`NDRepr.repr_float`."""
assertion.eq('5.0000', aNDRepr.repr(5.0))
assertion.eq('5.0000', aNDRepr.repr(5.00000000000))
assertion.eq('5.0000', aNDRepr.repr(5.0000))
assertion.eq('5.0000e+10', aNDRepr.repr(5.0 * 10**10))
assertion.eq('5.0000e-10', aNDRepr.repr(5.0 * 10**-10))
def test_adf_mock(mocker: MockFixture):
"""Mock the ADF output."""
mol = Molecule(PATH_MOLECULES / "acetonitrile.xyz")
job = adf(templates.geometry, mol)
run_mocked = mocker.patch("qmflows.run")
jobname = "ADFjob"
dill_path = WORKDIR / jobname / "ADFjob.dill"
plams_dir = WORKDIR / jobname
run_mocked.return_value = ADF_Result(templates.geometry,
mol,
jobname,
dill_path=dill_path,
work_dir=plams_dir,
plams_dir=plams_dir)
rs = run_mocked(job)
assertion.isfinite(rs.energy)
assertion.isfinite(rs.h**o)
assertion.isfinite(rs.lumo)
# Array of runtime for each optimization
assertion.isfinite(rs.runtime[-1])
# 3-dimensional vector
assertion.len_eq(rs.dipole, 3)
# number of steps until convergence
assertion.eq(rs.optcycles, 8)
# Test molecule
# Molecule
mol = rs.molecule
assertion.isinstance(mol, Molecule)
assertion.len_eq(mol, 6) # there are 6 atoms
def test_lig_mapping() -> None:
"""Tests for :func:`nanoCAT.bde.dissociate_xyn._lig_mapping`."""
lig_mapping = _lig_mapping(MOL, LIG_IDX)
ref = {
127: [124, 125, 126, 127, 128, 129, 130],
134: [131, 132, 133, 134, 135, 136, 137],
141: [138, 139, 140, 141, 142, 143, 144],
148: [145, 146, 147, 148, 149, 150, 151],
155: [152, 153, 154, 155, 156, 157, 158],
162: [159, 160, 161, 162, 163, 164, 165],
169: [166, 167, 168, 169, 170, 171, 172],
176: [173, 174, 175, 176, 177, 178, 179],
183: [180, 181, 182, 183, 184, 185, 186],
190: [187, 188, 189, 190, 191, 192, 193],
197: [194, 195, 196, 197, 198, 199, 200],
204: [201, 202, 203, 204, 205, 206, 207],
211: [208, 209, 210, 211, 212, 213, 214],
218: [215, 216, 217, 218, 219, 220, 221],
225: [222, 223, 224, 225, 226, 227, 228],
232: [229, 230, 231, 232, 233, 234, 235],
239: [236, 237, 238, 239, 240, 241, 242],
246: [243, 244, 245, 246, 247, 248, 249],
253: [250, 251, 252, 253, 254, 255, 256],
260: [257, 258, 259, 260, 261, 262, 263],
267: [264, 265, 266, 267, 268, 269, 270],
274: [271, 272, 273, 274, 275, 276, 277],
281: [278, 279, 280, 281, 282, 283, 284],
288: [285, 286, 287, 288, 289, 290, 291],
295: [292, 293, 294, 295, 296, 297, 298],
302: [299, 300, 301, 302, 303, 304, 305]
}
assertion.eq(lig_mapping, ref)
def test_package_wrapper() -> None:
"""Tests for :class:`PackageWrapper<qmflows.packages.package_wrapper.PackageWrapper>`."""
s1 = Settings()
s1.input.ams.Task = 'GeometryOptimization'
s1.input.ams.GeometryOptimization.Convergence.Gradients = 1.0e-4
s1.input.ams.Properties.NormalModes = 'true'
s1.input.DFTB.Model = 'DFTB3'
s1.input.DFTB.ResourcesDir = 'DFTB.org/3ob-3-1'
s2 = Settings()
s2.input.basis.type = 'DZP'
s2.input.basis.core = 'None'
s2.input.basis.createoutput = 'None'
mol = from_smiles('O') # H2O
job1 = PackageWrapper(AMSJob)(s1, mol, name='amsjob')
result1 = _get_result(job1, AMSJob)
assertion.isinstance(result1, ResultWrapper)
assertion.eq(result1.results.job.status, 'successful')
job2 = PackageWrapper(ADFJob)(s2, mol, name='adfjob')
result2 = _get_result(job2, ADFJob)
assertion.isinstance(result2, ADF_Result)
assertion.eq(result2.results.job.status, 'successful')
def _validate(atom: str, value: float, param: pd.Series) -> None:
"""Validate the moves of :func:`test_constraint_blocks`."""
ident = f"{atom}={value}"
assertion.isclose(param[atom],
value,
abs_tol=0.001,
message=f'{atom} ({ident})')
for min_, max_, (key, v) in zip(PRM_MIN, PRM_MAX, param.items()):
assertion.le(min_, v, message=f'{key} ({ident})')
assertion.ge(max_, v, message=f'{key} ({ident})')
assertion.isclose((param * COUNT).sum(),
0,
abs_tol=0.001,
message=f"net charge ({ident})")
for key in EXCLUDE:
assertion.eq(param[key], PARAM[key], message=f'{key} ({ident})')
idx1 = ATOM_COEFS[0].index
idx2 = ATOM_COEFS[1].index
v1 = (param[idx1] * ATOM_COEFS[0]).sum()
v2 = (param[idx2] * ATOM_COEFS[1]).sum()
assertion.isclose(v1,
v2,
abs_tol=0.001,
message=f"{idx1} and {idx2} ({ident})")
def test_map_psf_atoms() -> None:
"""Tests for :func:`map_psf_atoms`."""
ref = {
'C331': 'C',
'C321': 'C',
'C2O3': 'C',
'O2D2': 'O',
'HGA2': 'H',
'HGA3': 'H'
}
path_like = PATH_MOLECULES / 'mol.psf'
file_like = StringIO(PSF_STR)
assertion.eq(map_psf_atoms(path_like), ref)
assertion.eq(map_psf_atoms(file_like), ref)
# Incorrect input types
assertion.assert_(map_psf_atoms, None, exception=TypeError)
assertion.assert_(map_psf_atoms, {1: 1}, exception=TypeError)
assertion.assert_(map_psf_atoms, 'bob.psf', exception=FileNotFoundError)
# Incorrect mode (bytes)
file_bytes = BytesIO(PSF_STR.encode())
assertion.assert_(map_psf_atoms,
file_bytes,
mode='rb',
exception=TypeError)
# The !NATOM will now be missing
file_wrong1 = StringIO(PSF_STR[24:])
assertion.assert_(map_psf_atoms, file_wrong1, exception=ValueError)
# Rows [5:] will now be missing
file_wrong2 = StringIO('\n'.join(i[:25] for i in PSF_STR.splitlines()))
assertion.assert_(map_psf_atoms, file_wrong2, exception=ValueError)
def test_yaml2Settings():
"""Test the conversion from yaml to settings."""
s1 = yaml2Settings(CP2K_PBE_GUESS)
s2 = yaml2Settings(CP2K_PBE_GUESS.encode())
assertion.eq(s1.specific, REF.specific)
assertion.eq(s2.specific, REF.specific)
def test_freq():
"""Do some constraint optimizations then launch a freq calc."""
mol = Molecule(PATH_MOLECULES / "ethene.xyz", "xyz")
geo_opt = dftb(templates.geometry, mol)
freq_calc = dftb(templates.freq, geo_opt.molecule, job_name="freq")
r = run(freq_calc)
assertion.eq(int(r.frequencies[0]), 831)
assertion.len_eq(r.frequencies, 12)
def test_index_other() -> None:
"""Test :func:`dataCAT.update_hdf5_log`."""
copyfile(HDF5_READ, HDF5_TMP)
with h5py.File(HDF5_TMP, 'r+') as f:
scale = f['ligand/index']
group = PDBContainer.create_hdf5_group(f, 'test', scale=scale)
dset = group['atoms']
assertion.eq(scale, dset.dims[0]['index'])
def test_multiple_geometries():
"""Test the reading of multiples molecular geometries from a file."""
path_xyz = PATH / "molecules" / "five_points_ethylene.xyz"
with open(path_xyz, 'r') as f:
ls = f.readlines()
xs = [''.join(x) for x in chunked(ls, 8)]
assertion.eq(list(map(parse_string_xyz, xs)), manyXYZ(path_xyz))
def test_eval_param() -> None:
"""Tests for :func:`_eval_param`."""
msg1 = 'Angles '
msg2 = 'Urey-Bradley '
out1 = _eval_param(msg1)
out2 = _eval_param(msg2)
assertion.eq(out1, msg1.rstrip())
assertion.is_(out2, None)
def test_eval_charge() -> None:
"""Tests for :func:`_eval_charge`."""
msg1 = 'bob 1.2 '
msg2 = 'bob 1.02 '
out1 = _eval_charge(msg1)
out2 = _eval_charge(msg2)
assertion.eq(out1, msg1.rstrip())
assertion.is_(out2, None)
def test_log_to_dataframe() -> None:
"""Test :func:`dataCAT.log_to_dataframe`."""
copyfile(HDF5_READ, HDF5_TMP)
with h5py.File(HDF5_TMP, 'r+', libver='latest') as f:
group = f['ligand/logger']
reset_hdf5_log(group)
df = log_to_dataframe(group)
dct = {k: v.dtype for k, v in df.items()}
assertion.eq(dct, REF_COLUMNS)
def test_exception() -> None:
"""Tests for :meth:`NDRepr.repr_exception`."""
repr_instance = NDRepr()
repr_instance.maxException = 80
exc1 = repr_instance.repr(TypeError('bob'))
exc2 = repr_instance.repr(TypeError('bob' * 100))
ref1 = 'TypeError(bob)'
ref2 = 'TypeError(bobbobbobbobbobbobbobbobbobbobbobbobbobbobbobbobbobbobbobbobbobbobbobbobbobbobbo...)' # noqa: E501
assertion.eq(exc1, ref1)
assertion.eq(exc2, ref2)
def test_fail_orca(tmpdir):
"""Orca package should returns ``None`` if the computation fails."""
methanol = Molecule(PATH_MOLECULES / 'methanol.xyz')
s = Settings()
s.specific.orca.main = "RKS The_Cow_Functional SVP Opt TightSCF SmallPrint"
opt = orca(s, methanol, job_name='fail_orca')
result = run(opt.molecule, path=tmpdir)
assertion.eq(result, None)
def test_c2pk_md_mock(mocker: MockFixture) -> None:
"""Mock a call to CP2K."""
s = SETTINGS.copy()
s.specific.cp2k += md.specific.cp2k_mm
job = cp2k_mm(s, MOL)
run_mocked = mock_runner(mocker, settings=s, jobname="cp2k_mm_md")
result = run_mocked(job)
assertion.eq(result.status, 'successful')
assertion.isfile(result.results['cp2k-1_1000.restart'])
def test_get_nan_row() -> None:
"""Test :func:`dataCAT.functions.get_nan_row`."""
df = pd.DataFrame(index=pd.RangeIndex(0, 10))
df[0] = None
df[1] = 0
df[2] = 0.0
df[3] = False
df[4] = np.datetime64('2005-02-25')
out = get_nan_row(df)
ref = [None, -1, np.nan, False, None]
assertion.eq(out, ref)
def test_from_pdb_array() -> None:
"""Test :func:`dataCAT.functions.as_pdb_array`."""
mol = molkit.readpdb(join(PATH, 'Methanol.pdb'))
pdb_ar = as_pdb_array([mol], warn=False)[0]
out1 = from_pdb_array(pdb_ar, warn=False)
assertion.isinstance(out1, Chem.Mol)
out2 = from_pdb_array(pdb_ar, rdmol=False, warn=False)
for at1, at2 in zip(out2, mol):
assertion.eq(at1.coords, at2.coords)
assertion.eq(at1.atnum, at2.atnum)
def test_ndarray() -> None:
"""Tests for :meth:`NDRepr.repr_ndarray`."""
ar1 = np.ones((10, 10), dtype=float)
ar2 = np.ones((10, 10), dtype=int)
ref1 = 'array([[1.0000, 1.0000, 1.0000, ..., 1.0000, 1.0000, 1.0000],\n [1.0000, 1.0000, 1.0000, ..., 1.0000, 1.0000, 1.0000],\n [1.0000, 1.0000, 1.0000, ..., 1.0000, 1.0000, 1.0000],\n ...,\n [1.0000, 1.0000, 1.0000, ..., 1.0000, 1.0000, 1.0000],\n [1.0000, 1.0000, 1.0000, ..., 1.0000, 1.0000, 1.0000],\n [1.0000, 1.0000, 1.0000, ..., 1.0000, 1.0000, 1.0000]])' # noqa
ref2 = 'array([[1, 1, 1, ..., 1, 1, 1],\n [1, 1, 1, ..., 1, 1, 1],\n [1, 1, 1, ..., 1, 1, 1],\n ...,\n [1, 1, 1, ..., 1, 1, 1],\n [1, 1, 1, ..., 1, 1, 1],\n [1, 1, 1, ..., 1, 1, 1]])' # noqa
str1 = aNDRepr.repr(ar1)
str2 = aNDRepr.repr(ar2)
assertion.eq(str1, ref1)
assertion.eq(str2, ref2)
def test_signature() -> None:
"""Tests for :meth:`NDRepr.repr_Signature`."""
sgn1 = inspect.signature(len)
sgn2 = inspect.signature(np.testing.assert_allclose)
ref1 = '(obj, /)'
ref2 = "(actual, desired, rtol=1e-07, atol=0, equal_nan=True, ...)"
str1 = aNDRepr.repr(sgn1)
str2 = aNDRepr.repr(sgn2)
assertion.eq(str1, ref1)
assertion.eq(str2, ref2)
def test_even_index() -> None:
"""Test :func:`dataCAT.functions.even_index`."""
df1 = pd.DataFrame(np.random.rand(10, 5))
df2 = pd.DataFrame(np.random.rand(20, 5))
out1 = even_index(df1, df2)
assertion.eq(out1.shape, df2.shape)
np.testing.assert_array_equal(out1.index, df2.index)
assert np.isnan(out1.values[10:, :]).all()
out2 = even_index(df1, df1.copy())
assertion.is_(df1, out2)
def test_nullcontext():
"""Tests for :class:`nullcontext` and :data:`_NullContextBackup`."""
if sys.version_info.minor >= 7:
assertion.eq(nullcontext.__module__, 'contextlib')
else:
assertion.eq(nullcontext.__module__, 'qmflows.backports')
cm = _NullContextBackup(True)
with cm as bool_:
assertion.is_(bool_, True)
with cm as bool_:
assertion.is_(bool_, True)
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_singlepoint() -> None:
"""Test CP2K singlepoint calculations with the :class:`CP2K_MM` class."""
s = SETTINGS.copy()
s.specific.cp2k += singlepoint.specific.cp2k_mm
job = cp2k_mm(settings=s, mol=MOL, job_name='cp2k_mm_sp')
result = run(job, path=PATH)
assertion.eq(result.status, 'successful')
# Compare energies
ref = -15.4431781758
assertion.isclose(result.energy, ref, rel_tol=10**-4)
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_dataframe() -> None:
"""Tests for :meth:`NDRepr.repr_DataFrame`."""
df1 = pd.DataFrame(np.ones((10, 10), dtype=float))
df2 = pd.DataFrame(np.ones((10, 10), dtype=int))
ref1 = ' 0 1 2 ... 7 8 9\n0 1.0 1.0 1.0 ... 1.0 1.0 1.0\n1 1.0 1.0 1.0 ... 1.0 1.0 1.0\n2 1.0 1.0 1.0 ... 1.0 1.0 1.0\n3 1.0 1.0 1.0 ... 1.0 1.0 1.0\n4 1.0 1.0 1.0 ... 1.0 1.0 1.0\n5 1.0 1.0 1.0 ... 1.0 1.0 1.0\n6 1.0 1.0 1.0 ... 1.0 1.0 1.0\n7 1.0 1.0 1.0 ... 1.0 1.0 1.0\n8 1.0 1.0 1.0 ... 1.0 1.0 1.0\n9 1.0 1.0 1.0 ... 1.0 1.0 1.0\n\n[10 rows x 10 columns]' # noqa: E501
ref2 = ' 0 1 2 ... 7 8 9\n0 1 1 1 ... 1 1 1\n1 1 1 1 ... 1 1 1\n2 1 1 1 ... 1 1 1\n3 1 1 1 ... 1 1 1\n4 1 1 1 ... 1 1 1\n5 1 1 1 ... 1 1 1\n6 1 1 1 ... 1 1 1\n7 1 1 1 ... 1 1 1\n8 1 1 1 ... 1 1 1\n9 1 1 1 ... 1 1 1\n\n[10 rows x 10 columns]' # noqa: E501
str1 = aNDRepr.repr(df1)
str2 = aNDRepr.repr(df2)
assertion.eq(str1, ref1)
assertion.eq(str2, ref2)
def test_selected_atoms_with_dftb():
"""Test the DFTB selection atoms funcionality."""
mol = molkit.from_smiles('CO')
s = Settings()
s.selected_atoms = ["H"]
expected_settings = Settings(
{'selected_atoms': ['H'], 'specific': dftb_const})
assertion.eq(dftb.generic2specific(s, mol), expected_settings)
s.selected_atoms = indices
expected_settings = Settings(
{'selected_atoms': indices, 'specific': dftb_const})
assertion.eq(str(dftb.generic2specific(s, mol)), str(expected_settings))
def test_series() -> None:
"""Tests for :meth:`NDRepr.repr_Series`."""
s1 = pd.Series(np.ones(10, dtype='float64'))
s2 = pd.Series(np.ones(10, dtype='int64'))
ref1 = '0 1.0\n1 1.0\n2 1.0\n3 1.0\n4 1.0\n5 1.0\n6 1.0\n7 1.0\n8 1.0\n9 1.0\ndtype: float64' # noqa: E501
ref2 = '0 1\n1 1\n2 1\n3 1\n4 1\n5 1\n6 1\n7 1\n8 1\n9 1\ndtype: int64' # noqa: E501
str1 = aNDRepr.repr(s1)
str2 = aNDRepr.repr(s2)
assertion.eq(str1, ref1)
assertion.eq(str2, ref2)
