def test_symms_benzene(self):
""" Do the carbons in benzene ring get assigned with roughly equal charges?
Discrepancy between carbons do exist in this test due to grid coarseness and limited
size of the grid. One can do a larger test, for example, using 160x170x80 size grid to
obtain [5.63728706, 5.89862956, 5.73956182, 5.63728706, 5.73963179, 5.8996759].
In comparison, `bader`, which is implemented by Henkelman group which proposed
the algorithm, reports [5.947370, 6.032509, 5.873431, 5.947370, 5.873431, 6.033485].
`bader` uses fuzzy boundaries which result in slightly higher carbon charges.
"""
benzenepath = os.path.join(os.path.dirname(os.path.realpath(__file__)),
"benzene.out")
data = ccread(benzenepath)
vol = volume.read_from_cube(
os.path.join(os.path.dirname(os.path.realpath(__file__)),
"benzene.cube"))
assert_allclose(vol.origin,
numpy.array([-4.1805, -4.498006, -2.116709]),
atol=1e-3)
analysis = Bader(data, vol)
analysis.calculate()
self.assertAlmostEqual(analysis.fragcharges[0:6].max(),
analysis.fragcharges[0:6].min(),
delta=0.5)
class BaderTest(unittest.TestCase):
"""Bader's QTAIM method tests."""
def setUp(self):
super(BaderTest, self).setUp()
self.parse()
def parse(self):
self.data, self.logfile = getdatafile(Psi4, "basicPsi4-1.2.1", ["water_mp2.out"])
self.volume = Volume((-4, -4, -4), (4, 4, 4), (0.2, 0.2, 0.2))
def testmissingrequiredattributes(self):
"""Is an error raised when required attributes are missing?"""
for missing_attribute in Bader.required_attrs:
self.parse()
delattr(self.data, missing_attribute)
with self.assertRaises(MissingAttributeError):
trialBader = Bader(self.data, self.volume)
def test_val(self):
"""Do the calculated values match with known values?
"""
self.data, logfile = getdatafile(Psi4, "basicPsi4-1.2.1", ["water_mp2.out"])
self.volume = Volume((-4, -4, -4), (4, 4, 4), (0.2, 0.2, 0.2))
self.analysis = Bader(self.data, self.volume)
self.analysis.calculate()
refData = [6.9378, 0.3639, 0.3827] # values from `bader` package
assert_allclose(self.analysis.fragcharges, refData, atol=0.15)
def test_chgsum_hf(self):
"""Does the sum of charges equate to the number of electrons for a simple molecule?"""
hfpath = os.path.join(os.path.dirname(os.path.realpath(__file__)),
"hf.out")
data = ccread(hfpath)
vol = volume.Volume((-6, -6, -6), (6, 6, 6), (0.2, 0.2, 0.2))
analysis = Bader(data, vol)
analysis.calculate()
self.assertAlmostEqual(numpy.sum(analysis.fragcharges), 10, delta=1)
def test_val(self):
"""Do the calculated values match with known values?
"""
self.data, logfile = getdatafile(Psi4, "basicPsi4-1.2.1", ["water_mp2.out"])
self.volume = Volume((-4, -4, -4), (4, 4, 4), (0.2, 0.2, 0.2))
self.analysis = Bader(self.data, self.volume)
self.analysis.calculate()
refData = [6.9378, 0.3639, 0.3827] # values from `bader` package
assert_allclose(self.analysis.fragcharges, refData, atol=0.15)
def testmissingrequiredattributes(self):
"""Is an error raised when required attributes are missing?"""
for missing_attribute in Bader.required_attrs:
self.parse()
delattr(self.data, missing_attribute)
with self.assertRaises(MissingAttributeError):
trialBader = Bader(self.data, self.volume)
class BaderTest(unittest.TestCase):
"""Bader's QTAIM method tests."""
def setUp(self):
super(BaderTest, self).setUp()
self.parse()
def parse(self):
self.data, self.logfile = getdatafile(Psi4, "basicPsi4-1.2.1",
["water_mp2.out"])
self.volume = volume.Volume((-4, -4, -4), (4, 4, 4), (0.2, 0.2, 0.2))
def testmissingrequiredattributes(self):
"""Is an error raised when required attributes are missing?"""
for missing_attribute in Bader.required_attrs:
self.parse()
delattr(self.data, missing_attribute)
with self.assertRaises(MissingAttributeError):
trialBader = Bader(self.data, self.volume)
def test_val(self):
"""Do the calculated values match with known values?
"""
self.data, logfile = getdatafile(Psi4, "basicPsi4-1.2.1",
["water_mp2.out"])
self.volume = volume.Volume((-4, -4, -4), (4, 4, 4), (0.2, 0.2, 0.2))
self.analysis = Bader(self.data, self.volume)
self.analysis.calculate()
refData = [6.9378, 0.3639, 0.3827] # values from `bader` package
assert_allclose(self.analysis.fragcharges, refData, atol=0.15)
def test_chgsum_hf(self):
"""Does the sum of charges equate to the number of electrons for a simple molecule?"""
hfpath = os.path.join(os.path.dirname(os.path.realpath(__file__)),
"hf.out")
data = ccread(hfpath)
vol = volume.Volume((-6, -6, -6), (6, 6, 6), (0.2, 0.2, 0.2))
analysis = Bader(data, vol)
analysis.calculate()
self.assertAlmostEqual(numpy.sum(analysis.fragcharges), 10, delta=1)
def test_symms_benzene(self):
""" Do the carbons in benzene ring get assigned with roughly equal charges?
Discrepancy between carbons do exist in this test due to grid coarseness and limited
size of the grid. One can do a larger test, for example, using 160x170x80 size grid to
obtain [5.63728706, 5.89862956, 5.73956182, 5.63728706, 5.73963179, 5.8996759].
In comparison, `bader`, which is implemented by Henkelman group which proposed
the algorithm, reports [5.947370, 6.032509, 5.873431, 5.947370, 5.873431, 6.033485].
`bader` uses fuzzy boundaries which result in slightly higher carbon charges.
"""
benzenepath = os.path.join(os.path.dirname(os.path.realpath(__file__)),
"benzene.out")
data = ccread(benzenepath)
vol = volume.read_from_cube(
os.path.join(os.path.dirname(os.path.realpath(__file__)),
"benzene.cube"))
assert_allclose(vol.origin,
numpy.array([-4.1805, -4.498006, -2.116709]),
atol=1e-3)
analysis = Bader(data, vol)
analysis.calculate()
self.assertAlmostEqual(analysis.fragcharges[0:6].max(),
analysis.fragcharges[0:6].min(),
delta=0.5)