def setUp(self):
m1 = Molecule(name="Molecule 1", elenergies=[0.0, 1.0])
m2 = Molecule(name="Molecule 2", elenergies=[0.0, 1.0])
time = TimeAxis(0.0, 1000, 1.0)
params = dict(ftype="OverdampedBrownian", reorg=20, cortime=100, T=300)
with energy_units("1/cm"):
fc = CorrelationFunction(time, params)
m1.set_transition_environment((0,1), fc)
m1.position = [0.0, 0.0, 0.0]
m1.set_dipole(0,1,[10.0, 0.0, 0.0])
m2.set_transition_environment((0,1), fc)
m2.position = [10.0, 0.0, 0.0]
m2.set_dipole(0,1,[10.0, 0.0, 0.0])
self.agg = Aggregate(name="TestAgg", molecules=[m1,m2])
self.agg.set_coupling_by_dipole_dipole()
self.agg.build()
m3 = Molecule(name="Molecule 1", elenergies=[0.0, 1.0])
m4 = Molecule(name="Molecule 2", elenergies=[0.0, 1.0])
m3.add_Mode(Mode(0.01))
m4.add_Mode(Mode(0.01))
mod3 = m3.get_Mode(0)
mod4 = m4.get_Mode(0)
mod3.set_nmax(0, 4)
mod3.set_nmax(1, 4)
mod3.set_HR(1, 0.1)
mod4.set_nmax(0, 4)
mod4.set_nmax(1, 4)
mod4.set_HR(1, 0.3)
self.vagg = Aggregate(molecules=[m3, m4])
self.vagg.build()
def setUp(self):
m1 = Molecule(name="Molecule 1", elenergies=[0.0, 1.0])
m2 = Molecule(name="Molecule 2", elenergies=[0.0, 1.0])
time = TimeAxis(0.0, 1000, 1.0)
params = dict(ftype="OverdampedBrownian", reorg=20, cortime=100, T=300)
with energy_units("1/cm"):
fc = CorrelationFunction(time, params)
m1.set_transition_environment((0, 1), fc)
m1.position = [0.0, 0.0, 0.0]
m1.set_dipole(0, 1, [10.0, 0.0, 0.0])
m2.set_transition_environment((0, 1), fc)
m2.position = [10.0, 0.0, 0.0]
m2.set_dipole(0, 1, [10.0, 0.0, 0.0])
self.agg = Aggregate(name="TestAgg", molecules=[m1, m2])
self.agg.set_coupling_by_dipole_dipole()
self.agg.build()
m3 = Molecule(name="Molecule 1", elenergies=[0.0, 1.0])
m4 = Molecule(name="Molecule 2", elenergies=[0.0, 1.0])
m3.add_Mode(Mode(0.01))
m4.add_Mode(Mode(0.01))
mod3 = m3.get_Mode(0)
mod4 = m4.get_Mode(0)
mod3.set_nmax(0, 4)
mod3.set_nmax(1, 4)
mod3.set_HR(1, 0.1)
mod4.set_nmax(0, 4)
mod4.set_nmax(1, 4)
mod4.set_HR(1, 0.3)
self.vagg = Aggregate(molecules=[m3, m4])
self.vagg.build()
class TestMoleculeVibrations(unittest.TestCase):
def setUp(self):
en = [0.0, 1.0]
self.m = Molecule(name="Molecule", elenergies=en)
mod1 = Mode(frequency=0.1)
self.m.add_Mode(mod1)
mod1.set_nmax(0, 3)
mod1.set_nmax(1, 3)
en2 = [0.0, 0.1, 0.1]
self.m2 = Molecule(name="AdMolecule", elenergies=en2)
self.m2.set_adiabatic_coupling(1, 2, 0.02)
mod2 = Mode(frequency=0.01)
self.m2.add_Mode(mod2)
mod2.set_nmax(0, 3)
mod2.set_nmax(1, 3)
mod2.set_nmax(2, 3)
def test_molecule_with_vibrations_1(self):
"""Testing hamiltonian of a two-level molecule with one mode
"""
H1 = self.m.get_Hamiltonian()
H1expected = numpy.diag([0.0, 0.1, 0.2, 1.0, 1.1, 1.2])
self.assertTrue(numpy.allclose(H1expected, H1.data))
mod1 = self.m.get_Mode(0)
mod1.set_nmax(1, 2)
H2 = self.m.get_Hamiltonian()
H2expected = numpy.diag([0.0, 0.1, 0.2, 1.0, 1.1])
self.assertTrue(numpy.allclose(H2expected, H2.data))
def test_thermal_density_matrix_0_temp(self):
"""Thermal density matrix: molecule with one mode, zero temperature
"""
rho_eq = self.m.get_thermal_ReducedDensityMatrix()
# Check if the matrix is diagonal
dat = rho_eq.data.copy()
for i in range(dat.shape[0]):
dat[i, i] = 0.0
zer = numpy.zeros(dat.shape, dtype=numpy.float)
self.assertTrue(numpy.allclose(dat, zer))
# Check if diagonal is a thermal population
pop = numpy.zeros(dat.shape[0])
# get temperature from the molecule
T = self.m.get_temperature()
self.assertEquals(T, 0.0)
# get density matrix
rho = self.m.get_thermal_ReducedDensityMatrix()
rpop = rho.get_populations()
if numpy.abs(T) < 1.0e-10:
pop[0] = 1.0
else:
# thermal populations
pass
self.assertTrue(numpy.allclose(pop, rpop))
def test_thermal_density_matrix_finite_temp(self):
"""Thermal density matrix: molecule with one mode, finite temperature
"""
timeAxis = TimeAxis(0.0, 1000, 1.0)
params = {
"ftype": "OverdampedBrownian",
"T": 300,
"reorg": 30,
"cortime": 100
}
cfcion = CorrelationFunction(timeAxis, params)
self.m.set_egcf((0, 1), cfcion)
rho_eq = self.m.get_thermal_ReducedDensityMatrix()
# Check if the matrix is diagonal
dat = rho_eq.data.copy()
for i in range(dat.shape[0]):
dat[i, i] = 0.0
zer = numpy.zeros(dat.shape, dtype=numpy.float)
self.assertTrue(numpy.allclose(dat, zer))
# Check if diagonal is a thermal population
pop = numpy.zeros(dat.shape[0])
# get temperature from the molecule
T = self.m.get_temperature()
self.assertTrue(T == 300.0)
# get density matrix
rpop = rho_eq.get_populations()
# get Hamiltonian
H = self.m.get_Hamiltonian()
if numpy.abs(T) < 1.0e-10:
pop[0] = 1.0
else:
# thermal populations
psum = 0.0
for n in range(pop.shape[0]):
pop[n] = numpy.exp(-H.data[n, n] / (kB_intK * T))
psum += pop[n]
pop *= 1.0 / psum
self.assertTrue(numpy.allclose(pop, rpop))
def test_thermal_density_matrix_finite_temp_nondiag(self):
"""Thermal density matrix: finite temperature, non-diagonal Hamiltonian
"""
timeAxis = TimeAxis(0.0, 1000, 1.0)
params = {
"ftype": "OverdampedBrownian",
"T": 300.0,
"reorg": 30,
"cortime": 100
}
cfcion = CorrelationFunction(timeAxis, params)
self.m2.set_egcf((0, 1), cfcion)
self.m2.set_egcf((0, 2), cfcion)
rho_eq = self.m2.get_thermal_ReducedDensityMatrix()
pop = numpy.zeros(rho_eq._data.shape[0])
# get temperature from the molecule
T = self.m2.get_temperature()
self.assertTrue(numpy.abs(T - 300.0) < 1.0e-10)
# get Hamiltonian
H = self.m2.get_Hamiltonian()
with eigenbasis_of(H):
# get density matrix
rpop = rho_eq.get_populations()
if numpy.abs(T) < 1.0e-10:
pop[0] = 1.0
else:
# thermal populations
psum = 0.0
for n in range(pop.shape[0]):
pop[n] = numpy.exp(-H.data[n, n] / (kB_intK * T))
psum += pop[n]
pop *= 1.0 / psum
self.assertTrue(numpy.allclose(pop, rpop))
def test_saving_of_molecule(self):
"""Testing the saving capability of the Molecule class
"""
use_temporary_file = True
with energy_units("1/cm"):
mod = Mode(frequency=150)
mod1 = Mode(frequency=100)
m2 = Molecule(elenergies=[0.0, 2.0])
m2.add_Mode(mod)
m2.add_Mode(mod1)
if use_temporary_file:
#drv = "core"
#bcs = False
#with h5py.File('tempfile.hdf5',
# driver=drv,
# backing_store=bcs) as f:
with tempfile.TemporaryFile() as f:
#self.m.save_as(f,"Molecule")
self.m.save(f, test=True)
# reread it
m = Molecule()
#m.load_as(f,"Molecule")
m = m.load(f, test=True)
else:
#with h5py.File('tempfile.hdf5') as f:
with open('tempfile.qrp', 'wb') as f:
#self.m.save_as(f,"Molecules")
self.m.save(f)
#with h5py.File('tempfile.hdf5') as f:
with open('tempfile.qrp', 'rb') as f:
m = Molecule()
#m.load_as(f,"Molecules")
m = m.load(f)
self.assertEqual(self.m.name, m.name)
self.assertEqual(self.m.nel, m.nel)
numpy.testing.assert_array_equal(self.m.elenergies, m.elenergies)
numpy.testing.assert_array_equal(
self.m.get_transition_environment((0, 1)).data, self.fc.data)
#with h5py.File('tempfile.hdf5',
# driver=drv,
# backing_store=bcs) as f:
with tempfile.TemporaryFile() as f:
#self.m.save_as(f,"Molecule")
m2.save(f, test=True)
# reread it
m3 = Molecule()
#m.load_as(f,"Molecule")
m3 = m3.load(f, test=True)
self.assertEqual(m2.name, m3.name)
self.assertEqual(m2.nel, m3.nel)
numpy.testing.assert_array_equal(m2.elenergies, m3.elenergies)
self.assertEqual(m2.get_Mode(0).get_energy(0), mod.get_energy(0))
self.assertEqual(m2.get_Mode(1).get_energy(0), mod1.get_energy(0))
def test_saving_of_molecule(self):
"""Testing the saving capability of the Molecule class
"""
use_temporary_file = True
with energy_units("1/cm"):
mod = Mode(frequency=150)
mod1 = Mode(frequency=100)
m2 = Molecule(elenergies=[0.0, 2.0])
m2.add_Mode(mod)
m2.add_Mode(mod1)
if use_temporary_file:
#drv = "core"
#bcs = False
#with h5py.File('tempfile.hdf5',
# driver=drv,
# backing_store=bcs) as f:
with tempfile.TemporaryFile() as f:
#self.m.save_as(f,"Molecule")
self.m.save(f, test=True)
# reread it
m = Molecule()
#m.load_as(f,"Molecule")
m = m.load(f, test=True)
else:
#with h5py.File('tempfile.hdf5') as f:
with open('tempfile.qrp', 'wb') as f:
#self.m.save_as(f,"Molecules")
self.m.save(f)
#with h5py.File('tempfile.hdf5') as f:
with open('tempfile.qrp', 'rb') as f:
m = Molecule()
#m.load_as(f,"Molecules")
m = m.load(f)
self.assertEqual(self.m.name, m.name)
self.assertEqual(self.m.nel, m.nel)
numpy.testing.assert_array_equal(self.m.elenergies, m.elenergies)
numpy.testing.assert_array_equal(
self.m.get_transition_environment((0,1)).data, self.fc.data)
#with h5py.File('tempfile.hdf5',
# driver=drv,
# backing_store=bcs) as f:
with tempfile.TemporaryFile() as f:
#self.m.save_as(f,"Molecule")
m2.save(f, test=True)
# reread it
m3 = Molecule()
#m.load_as(f,"Molecule")
m3 = m3.load(f, test=True)
self.assertEqual(m2.name, m3.name)
self.assertEqual(m2.nel, m3.nel)
numpy.testing.assert_array_equal(m2.elenergies, m3.elenergies)
self.assertEqual(m2.get_Mode(0).get_energy(0), mod.get_energy(0))
self.assertEqual(m2.get_Mode(1).get_energy(0), mod1.get_energy(0))
class TestMoleculeVibrations(unittest.TestCase):
def setUp(self):
en = [0.0, 1.0]
self.m = Molecule(name="Molecule",elenergies=en)
mod1 = Mode(frequency=0.1)
self.m.add_Mode(mod1)
mod1.set_nmax(0,3)
mod1.set_nmax(1,3)
en2 = [0.0,0.1,0.1]
self.m2 = Molecule(name="AdMolecule",elenergies=en2)
self.m2.set_adiabatic_coupling(1,2,0.02)
mod2 = Mode(frequency=0.01)
self.m2.add_Mode(mod2)
mod2.set_nmax(0,3)
mod2.set_nmax(1,3)
mod2.set_nmax(2,3)
def test_molecule_with_vibrations_1(self):
"""Testing hamiltonian of a two-level molecule with one mode
"""
H1 = self.m.get_Hamiltonian()
H1expected = numpy.diag([0.0, 0.1, 0.2, 1.0, 1.1, 1.2])
self.assertTrue(numpy.allclose(H1expected,H1.data))
mod1 = self.m.get_Mode(0)
mod1.set_nmax(1,2)
H2 = self.m.get_Hamiltonian()
H2expected = numpy.diag([0.0, 0.1, 0.2, 1.0, 1.1])
self.assertTrue(numpy.allclose(H2expected,H2.data))
def test_thermal_density_matrix_0_temp(self):
"""Thermal density matrix: molecule with one mode, zero temperature
"""
rho_eq = self.m.get_thermal_ReducedDensityMatrix()
# Check if the matrix is diagonal
dat = rho_eq.data.copy()
for i in range(dat.shape[0]):
dat[i,i] = 0.0
zer = numpy.zeros(dat.shape,dtype=numpy.float)
self.assertTrue(numpy.allclose(dat,zer))
# Check if diagonal is a thermal population
pop = numpy.zeros(dat.shape[0])
# get temperature from the molecule
T = self.m.get_temperature()
self.assertEquals(T,0.0)
# get density matrix
rho = self.m.get_thermal_ReducedDensityMatrix()
rpop = rho.get_populations()
if numpy.abs(T) < 1.0e-10:
pop[0] = 1.0
else:
# thermal populations
pass
self.assertTrue(numpy.allclose(pop,rpop))
def test_thermal_density_matrix_finite_temp(self):
"""Thermal density matrix: molecule with one mode, finite temperature
"""
timeAxis = TimeAxis(0.0,1000,1.0)
params = {"ftype":"OverdampedBrownian",
"T":300,
"reorg":30,
"cortime":100}
with energy_units("1/cm"):
cfcion = CorrelationFunction(timeAxis,params)
self.m.set_egcf((0,1),cfcion)
rho_eq = self.m.get_thermal_ReducedDensityMatrix()
# Check if the matrix is diagonal
dat = rho_eq.data.copy()
for i in range(dat.shape[0]):
dat[i,i] = 0.0
zer = numpy.zeros(dat.shape,dtype=numpy.float)
self.assertTrue(numpy.allclose(dat,zer))
# Check if diagonal is a thermal population
pop = numpy.zeros(dat.shape[0])
# get temperature from the molecule
T = self.m.get_temperature()
self.assertTrue(T==300.0)
# get density matrix
rpop = rho_eq.get_populations()
# get Hamiltonian
H = self.m.get_Hamiltonian()
if numpy.abs(T) < 1.0e-10:
pop[0] = 1.0
else:
# thermal populations
psum = 0.0
for n in range(pop.shape[0]):
pop[n] = numpy.exp(-H.data[n,n]/(kB_intK*T))
psum += pop[n]
pop *= 1.0/psum
self.assertTrue(numpy.allclose(pop,rpop))
def test_thermal_density_matrix_finite_temp_nondiag(self):
"""Thermal density matrix: finite temperature, non-diagonal Hamiltonian
"""
timeAxis = TimeAxis(0.0,1000,1.0)
params = {"ftype":"OverdampedBrownian",
"T":300.0,
"reorg":30,
"cortime":100}
cfcion = CorrelationFunction(timeAxis,params)
self.m2.set_egcf((0,1),cfcion)
self.m2.set_egcf((0,2),cfcion)
rho_eq = self.m2.get_thermal_ReducedDensityMatrix()
pop = numpy.zeros(rho_eq._data.shape[0])
# get temperature from the molecule
T = self.m2.get_temperature()
self.assertTrue(numpy.abs(T-300.0)<1.0e-10)
# get Hamiltonian
H = self.m2.get_Hamiltonian()
with eigenbasis_of(H):
# get density matrix
rpop = rho_eq.get_populations()
if numpy.abs(T) < 1.0e-10:
pop[0] = 1.0
else:
# thermal populations
psum = 0.0
for n in range(pop.shape[0]):
pop[n] = numpy.exp(-H.data[n,n]/(kB_intK*T))
psum += pop[n]
pop *= 1.0/psum
self.assertTrue(numpy.allclose(pop,rpop))