def test_transformation_in_different_basis(self):
"""(LINDBLAD) Testing transformations into different bases
"""
#Manager().warn_about_basis_change = True
#Manager().warn_about_basis_changing_objects = True
LT1 = LindbladForm(self.H1, self.sbi1, as_operators=True, name="LT1")
LT2 = LindbladForm(self.H1, self.sbi1, as_operators=False, name="LT2")
rho0 = ReducedDensityMatrix(dim=self.H1.dim, name="ahoj")
with eigenbasis_of(self.H1):
rho0.data[1, 1] = 0.7
rho0.data[0, 0] = 0.3
with eigenbasis_of(self.H1):
rhot1_e = LT1.apply(rho0, copy=True)
with eigenbasis_of(self.H1):
rhot2_e = LT2.apply(rho0, copy=True)
rhot1_l = LT1.apply(rho0, copy=True)
rhot2_l = LT2.apply(rho0, copy=True)
numpy.testing.assert_allclose(rhot1_l.data, rhot1_e.data)
numpy.testing.assert_allclose(rhot2_l.data, rhot2_e.data)
numpy.testing.assert_allclose(rhot1_e.data,
rhot2_e.data) #, rtol=1.0e-2)
def test_propagation_in_different_basis(self):
"""(LINDBLAD) Testing comparison of propagations in different bases
"""
LT1 = LindbladForm(self.H1, self.sbi1, as_operators=True)
LT2 = LindbladForm(self.H1, self.sbi1, as_operators=False)
time = TimeAxis(0.0, 1000, 1.0)
prop1 = ReducedDensityMatrixPropagator(time, self.H1, LT1)
prop2 = ReducedDensityMatrixPropagator(time, self.H1, LT2)
rho0 = ReducedDensityMatrix(dim=self.H1.dim)
rho0.data[1, 1] = 1.0
with eigenbasis_of(self.H1):
rhot1_e = prop1.propagate(rho0)
with eigenbasis_of(self.H1):
rhot2_e = prop2.propagate(rho0)
rhot1_l = prop1.propagate(rho0)
rhot2_l = prop2.propagate(rho0)
numpy.testing.assert_allclose(rhot1_l.data, rhot1_e.data)
numpy.testing.assert_allclose(rhot2_l.data, rhot2_e.data)
numpy.testing.assert_allclose(rhot1_e.data,
rhot2_e.data) #, rtol=1.0e-2)
def test_transformation_in_different_basis(self):
"""(LINDBLAD) Testing transformations into different bases
"""
#Manager().warn_about_basis_change = True
#Manager().warn_about_basis_changing_objects = True
LT1 = LindbladForm(self.H1, self.sbi1, as_operators=True, name="LT1")
LT2 = LindbladForm(self.H1, self.sbi1, as_operators=False, name="LT2")
rho0 = ReducedDensityMatrix(dim=self.H1.dim, name="ahoj")
with eigenbasis_of(self.H1):
rho0.data[1,1] = 0.7
rho0.data[0,0] = 0.3
with eigenbasis_of(self.H1):
rhot1_e = LT1.apply(rho0, copy=True)
with eigenbasis_of(self.H1):
rhot2_e = LT2.apply(rho0, copy=True)
rhot1_l = LT1.apply(rho0, copy=True)
rhot2_l = LT2.apply(rho0, copy=True)
numpy.testing.assert_allclose(rhot1_l.data, rhot1_e.data)
numpy.testing.assert_allclose(rhot2_l.data, rhot2_e.data)
numpy.testing.assert_allclose(rhot1_e.data, rhot2_e.data) #, rtol=1.0e-2)
def test_propagation_in_different_basis(self):
"""(LINDBLAD) Testing comparison of propagations in different bases
"""
LT1 = LindbladForm(self.H1, self.sbi1, as_operators=True)
LT2 = LindbladForm(self.H1, self.sbi1, as_operators=False)
time = TimeAxis(0.0, 1000, 1.0)
prop1 = ReducedDensityMatrixPropagator(time, self.H1, LT1)
prop2 = ReducedDensityMatrixPropagator(time, self.H1, LT2)
rho0 = ReducedDensityMatrix(dim=self.H1.dim)
rho0.data[1,1] = 1.0
with eigenbasis_of(self.H1):
rhot1_e = prop1.propagate(rho0)
with eigenbasis_of(self.H1):
rhot2_e = prop2.propagate(rho0)
rhot1_l = prop1.propagate(rho0)
rhot2_l = prop2.propagate(rho0)
numpy.testing.assert_allclose(rhot1_l.data, rhot1_e.data)
numpy.testing.assert_allclose(rhot2_l.data, rhot2_e.data)
numpy.testing.assert_allclose(rhot1_e.data, rhot2_e.data) #, rtol=1.0e-2)
def test_trace_over_vibrations(self):
"""Testing trace over vibrational DOF
"""
agg = self.vagg
ham = agg.get_Hamiltonian()
rho = ReducedDensityMatrix(dim=ham.dim)
rho._data[5, 5] = 1.0
redr = agg.trace_over_vibrations(rho)
numpy.testing.assert_almost_equal(numpy.trace(redr._data), 1.0,
decimal=7)
N = agg.Nb[0]
rho = ReducedDensityMatrix(dim=ham.dim)
rho._data[N+5, N+5] = 1.0
redr = agg.trace_over_vibrations(rho)
numpy.testing.assert_almost_equal(numpy.trace(redr._data), 1.0,
decimal=3)
N = agg.Nb[1]
rho = ReducedDensityMatrix(dim=ham.dim)
rho._data[N+5, N+5] = 1.0
redr = agg.trace_over_vibrations(rho)
numpy.testing.assert_almost_equal(numpy.trace(redr._data), 1.0,
decimal=2)
def test_conversion_2_populations(self):
"""Testing conversion of reduced density matrix to population vector
"""
rdm = ReducedDensityMatrix(
data=[[0.5, 0.0, 0.1], [0.0, 0.3, 0.0], [0.1, 0.0, 0.2]])
pop = rdm.get_populations()
self.assertTrue(numpy.allclose(pop, [0.5, 0.3, 0.2]))
def test_conversion_2_populations(self):
"""Testing conversion of reduced density matrix to population vector
"""
rdm = ReducedDensityMatrix(data=[[0.5, 0.0, 0.1],
[0.0, 0.3, 0.0],
[0.1, 0.0, 0.2]])
pop = rdm.get_populations()
self.assertTrue(numpy.allclose(pop,[0.5,0.3,0.2]))
def test_comparison_with_and_without_vib(self):
"""Testing ElectronicLindbladForm in propagation
"""
# Lindblad forms
LT = ElectronicLindbladForm(self.ham, self.sbi, as_operators=False)
vLT = ElectronicLindbladForm(self.vham, self.vsbi, as_operators=False)
# Propagators
time = TimeAxis(0.0, 1000, 1.0)
el_prop = ReducedDensityMatrixPropagator(time, self.ham, LT)
vib_prop = ReducedDensityMatrixPropagator(time, self.vham, vLT)
# electronic initial condition
rho0 = ReducedDensityMatrix(dim=self.ham.dim)
rho0.data[2,2] = 1.0
# vibronic intial condition
vrho0 = ReducedDensityMatrix(dim=self.vham.dim)
agg = self.vsbi.system
Nin = agg.vibindices[2][0]
vrho0.data[Nin, Nin] = 1.0
# propagations
rhot = el_prop.propagate(rho0)
vrhot = vib_prop.propagate(vrho0)
# averaging over vibrational level at t=0
Nel = agg.Nel
aver_vrhot0 = agg.trace_over_vibrations(vrho0)
# Test
numpy.testing.assert_allclose(rhot._data[0,:,:], rho0._data)
numpy.testing.assert_allclose(rhot._data[0,:,:], aver_vrhot0._data)
aver_vrhot10 = agg.trace_over_vibrations(vrhot, 10)
numpy.testing.assert_allclose(rhot._data[10,:,:],
aver_vrhot10._data)
aver_vrhot800 = agg.trace_over_vibrations(vrhot, 800)
numpy.testing.assert_allclose(rhot._data[800,:,:],
aver_vrhot800._data)
def test_saveable(self):
"""Testing reduced density matrix as Saveable
"""
rdm = ReducedDensityMatrix(data=[[0.5, 0.0, 0.1],
[0.0, 0.3, 0.0],
[0.1, 0.0, 0.2]])
#import h5py
#with h5py.File("test_file_operators",driver="core",
# backing_store=False) as fid:
import tempfile
with tempfile.TemporaryFile() as fid:
rdm.save(fid) #, test=True)
fid.seek(0)
rdm2 = ReducedDensityMatrix()
rdm2 = rdm2.load(fid) #, test=True)
self.assertTrue(numpy.allclose(rdm2.data,rdm.data))
def test_comparison_of_dynamics(self):
"""Testing site basis dynamics by Lindblad
"""
LT1 = LindbladForm(self.H1, self.sbi1, as_operators=True)
LT2 = LindbladForm(self.H1, self.sbi1, as_operators=False)
time = TimeAxis(0.0, 1000, 1.0)
prop1 = ReducedDensityMatrixPropagator(time, self.H1, LT1)
prop2 = ReducedDensityMatrixPropagator(time, self.H1, LT2)
rho0 = ReducedDensityMatrix(dim=self.H1.dim)
rho0.data[1,1] = 1.0
rhot1 = prop1.propagate(rho0)
rhot2 = prop2.propagate(rho0)
numpy.testing.assert_allclose(rhot1.data,rhot2.data) #, rtol=1.0e-2)
def test_comparison_of_dynamics(self):
"""Testing site basis dynamics by Lindblad
"""
LT1 = LindbladForm(self.H1, self.sbi1, as_operators=True)
LT2 = LindbladForm(self.H1, self.sbi1, as_operators=False)
time = TimeAxis(0.0, 1000, 1.0)
prop1 = ReducedDensityMatrixPropagator(time, self.H1, LT1)
prop2 = ReducedDensityMatrixPropagator(time, self.H1, LT2)
rho0 = ReducedDensityMatrix(dim=self.H1.dim)
rho0.data[1, 1] = 1.0
rhot1 = prop1.propagate(rho0)
rhot2 = prop2.propagate(rho0)
numpy.testing.assert_allclose(rhot1.data, rhot2.data) #, rtol=1.0e-2)
def test_trace_over_vibrations(self):
"""(Aggregate) Testing trace over vibrational DOF
"""
agg = self.vagg
ham = agg.get_Hamiltonian()
rho = ReducedDensityMatrix(dim=ham.dim)
rho._data[5, 5] = 1.0
redr = agg.trace_over_vibrations(rho)
numpy.testing.assert_almost_equal(numpy.trace(redr._data), 1.0,
decimal=7)
N = agg.Nb[0]
rho = ReducedDensityMatrix(dim=ham.dim)
rho._data[N+5, N+5] = 1.0
redr = agg.trace_over_vibrations(rho)
numpy.testing.assert_almost_equal(numpy.trace(redr._data), 1.0,
decimal=3)
N = agg.Nb[1]
rho = ReducedDensityMatrix(dim=ham.dim)
rho._data[N+5, N+5] = 1.0
redr = agg.trace_over_vibrations(rho)
numpy.testing.assert_almost_equal(numpy.trace(redr._data), 1.0,
decimal=2)
def test_comparison_with_and_without_vib(self):
"""Testing ElectronicLindbladForm in propagation
"""
# Lindblad forms
LT = ElectronicLindbladForm(self.ham, self.sbi, as_operators=False)
vLT = ElectronicLindbladForm(self.vham, self.vsbi, as_operators=False)
# Propagators
time = TimeAxis(0.0, 1000, 1.0)
el_prop = ReducedDensityMatrixPropagator(time, self.ham, LT)
vib_prop = ReducedDensityMatrixPropagator(time, self.vham, vLT)
# electronic initial condition
rho0 = ReducedDensityMatrix(dim=self.ham.dim)
rho0.data[2, 2] = 1.0
# vibronic intial condition
vrho0 = ReducedDensityMatrix(dim=self.vham.dim)
agg = self.vsbi.system
Nin = agg.vibindices[2][0]
vrho0.data[Nin, Nin] = 1.0
# propagations
rhot = el_prop.propagate(rho0)
vrhot = vib_prop.propagate(vrho0)
# averaging over vibrational level at t=0
Nel = agg.Nel
aver_vrhot0 = agg.trace_over_vibrations(vrho0)
# Test
numpy.testing.assert_array_equal(rhot._data[0, :, :], rho0._data)
numpy.testing.assert_array_equal(rhot._data[0, :, :],
aver_vrhot0._data)
aver_vrhot10 = agg.trace_over_vibrations(vrhot, 10)
numpy.testing.assert_array_equal(rhot._data[10, :, :],
aver_vrhot10._data)
aver_vrhot800 = agg.trace_over_vibrations(vrhot, 800)
numpy.testing.assert_array_equal(rhot._data[800, :, :],
aver_vrhot800._data)
ham = vagg.get_Hamiltonian()
print("Hamiltonian dimension: ", ham.dim)
print("Constructing electronic Lindblad form")
eLF = ElectronicLindbladForm(ham, vsbi, as_operators=True)
print("...done")
time = TimeAxis(0.0, 1000, 1.0)
from quantarhei.qm import ReducedDensityMatrixPropagator
vibprop = ReducedDensityMatrixPropagator(time, ham, eLF)
from quantarhei.qm import ReducedDensityMatrix
rho0 = ReducedDensityMatrix(dim=ham.dim)
Ni = vagg.vibindices[3][0]
rho0.data[Ni, Ni] = 1.0
print("Density matrix propagation: ")
rhot = vibprop.propagate(rho0)
print("...done")
print("\nThe same but NO vibrational modes")
m1v = Molecule([0.0, 1.0])
m2v = Molecule([0.0, 1.1])
m3v = Molecule([0.0, 1.2])
vagg2 = Aggregate(molecules=[m1v, m2v, m3v])
vagg2.build()
def test_comparison_of_exciton_dynamics(self):
"""Testing exciton basis dynamics by Lindblad
"""
# site basis form to be compared with
LT1 = LindbladForm(self.H1, self.sbi1, as_operators=True)
# exciton basis forms
LT13 = LindbladForm(self.H3, self.sbi3, as_operators=True)
LT23 = LindbladForm(self.H3, self.sbi3, as_operators=False)
LT4e = LindbladForm(self.H4, self.sbi4e, as_operators=True)
LT4s = LindbladForm(self.H4s, self.sbi4s, as_operators=True)
time = TimeAxis(0.0, 1000, 1.0)
#
# Propagators
#
prop0 = ReducedDensityMatrixPropagator(time, self.H1, LT1)
prop1 = ReducedDensityMatrixPropagator(time, self.H3, LT13)
prop2 = ReducedDensityMatrixPropagator(time, self.H3, LT23)
prop4e = ReducedDensityMatrixPropagator(time, self.H4, LT4e)
prop4s = ReducedDensityMatrixPropagator(time, self.H4s, LT4s)
#
# Initial conditions
#
rho0 = ReducedDensityMatrix(dim=self.H3.dim)
rho0c = ReducedDensityMatrix(dim=self.H1.dim) # excitonic
with eigenbasis_of(self.H3):
rho0c.data[1,1] = 1.0
rho0.data[1,1] = 1.0
rho04e = ReducedDensityMatrix(dim=self.H4.dim)
rho04s = ReducedDensityMatrix(dim=self.H4.dim)
with eigenbasis_of(self.H4):
rho04e.data[2,2] = 1.0
rho04s.data[2,2] = 1.0
#
# Propagations
#
rhotc = prop0.propagate(rho0c)
rhot1 = prop1.propagate(rho0)
rhot2 = prop2.propagate(rho0)
rhot4e = prop4e.propagate(rho04e)
rhot4s = prop4s.propagate(rho04s)
# propagation with operator- and tensor forms should be the same
numpy.testing.assert_allclose(rhot1.data,rhot2.data) #, rtol=1.0e-2)
#
# Population time evolution by Lindblad is independent
# of the level structure and basis, as long as I compare
# populations in basis in which the Lindblad form was defined
#
P = numpy.zeros((2, time.length))
Pc = numpy.zeros((2, time.length))
P4e = numpy.zeros((3, time.length))
P4s = numpy.zeros((3, time.length))
with eigenbasis_of(self.H3):
for i in range(time.length):
P[0,i] = numpy.real(rhot1.data[i,0,0]) # population of exciton 0
P[1,i] = numpy.real(rhot1.data[i,1,1]) # population of exciton 1
for i in range(time.length):
Pc[0,i] = numpy.real(rhotc.data[i,0,0]) # population of exciton 0
Pc[1,i] = numpy.real(rhotc.data[i,1,1]) # population of exciton 1
# we compare populations
numpy.testing.assert_allclose(Pc,P) #, rtol=1.0e-2)
with eigenbasis_of(self.H4):
for i in range(time.length):
P4e[0,i] = numpy.real(rhot4e.data[i,0,0]) # population of exciton 0
P4e[1,i] = numpy.real(rhot4e.data[i,1,1]) # population of exciton 1
P4e[2,i] = numpy.real(rhot4e.data[i,2,2]) # population of exciton 1
for i in range(time.length):
P4s[0,i] = numpy.real(rhot4s.data[i,0,0]) # population of exciton 0
P4s[1,i] = numpy.real(rhot4s.data[i,1,1]) # population of exciton 1
P4s[2,i] = numpy.real(rhot4s.data[i,2,2]) # population of exciton 1
# import matplotlib.pyplot as plt
#
# plt.plot(time.data,P4s[0,:], "-r")
# plt.plot(time.data,P4s[1,:], "-r")
# plt.plot(time.data,P4s[2,:], "-r")
# plt.plot(time.data,P4e[0,:], "-g")
# plt.plot(time.data,P4e[1,:], "-g")
# plt.plot(time.data,P4e[2,:], "-g")
# plt.show()
numpy.testing.assert_allclose(P4e, P4s, atol=1.0e-8)
from quantarhei.qm import ElectronicLindbladForm
ham = vagg.get_Hamiltonian()
print("Hamiltonian dimension: ", ham.dim)
print("Constructing electronic Lindblad form")
eLF = ElectronicLindbladForm(ham, vsbi, as_operators=True)
print("...done")
time = TimeAxis(0.0, 1000, 1.0)
from quantarhei.qm import ReducedDensityMatrixPropagator
vibprop = ReducedDensityMatrixPropagator(time, ham, eLF)
from quantarhei.qm import ReducedDensityMatrix
rho0 = ReducedDensityMatrix(dim=ham.dim)
Ni = vagg.vibindices[3][0]
rho0.data[Ni, Ni] = 1.0
print("Density matrix propagation: ")
rhot = vibprop.propagate(rho0)
print("...done")
print("\nThe same but NO vibrational modes")
m1v = Molecule([0.0, 1.0])
m2v = Molecule([0.0, 1.1])
m3v = Molecule([0.0, 1.2])
vagg2 = Aggregate(molecules=[m1v, m2v, m3v])
vagg2.build()
def test_comparison_of_exciton_dynamics(self):
"""Testing exciton basis dynamics by Lindblad
"""
# site basis form to be compared with
LT1 = LindbladForm(self.H1, self.sbi1, as_operators=True)
# exciton basis forms
LT13 = LindbladForm(self.H3, self.sbi3, as_operators=True)
LT23 = LindbladForm(self.H3, self.sbi3, as_operators=False)
LT4e = LindbladForm(self.H4, self.sbi4e, as_operators=True)
LT4s = LindbladForm(self.H4s, self.sbi4s, as_operators=True)
time = TimeAxis(0.0, 1000, 1.0)
#
# Propagators
#
prop0 = ReducedDensityMatrixPropagator(time, self.H1, LT1)
prop1 = ReducedDensityMatrixPropagator(time, self.H3, LT13)
prop2 = ReducedDensityMatrixPropagator(time, self.H3, LT23)
prop4e = ReducedDensityMatrixPropagator(time, self.H4, LT4e)
prop4s = ReducedDensityMatrixPropagator(time, self.H4s, LT4s)
#
# Initial conditions
#
rho0 = ReducedDensityMatrix(dim=self.H3.dim)
rho0c = ReducedDensityMatrix(dim=self.H1.dim) # excitonic
with eigenbasis_of(self.H3):
rho0c.data[1, 1] = 1.0
rho0.data[1, 1] = 1.0
rho04e = ReducedDensityMatrix(dim=self.H4.dim)
rho04s = ReducedDensityMatrix(dim=self.H4.dim)
with eigenbasis_of(self.H4):
rho04e.data[2, 2] = 1.0
rho04s.data[2, 2] = 1.0
#
# Propagations
#
rhotc = prop0.propagate(rho0c)
rhot1 = prop1.propagate(rho0)
rhot2 = prop2.propagate(rho0)
rhot4e = prop4e.propagate(rho04e)
rhot4s = prop4s.propagate(rho04s)
# propagation with operator- and tensor forms should be the same
numpy.testing.assert_allclose(rhot1.data, rhot2.data) #, rtol=1.0e-2)
#
# Population time evolution by Lindblad is independent
# of the level structure and basis, as long as I compare
# populations in basis in which the Lindblad form was defined
#
P = numpy.zeros((2, time.length))
Pc = numpy.zeros((2, time.length))
P4e = numpy.zeros((3, time.length))
P4s = numpy.zeros((3, time.length))
with eigenbasis_of(self.H3):
for i in range(time.length):
P[0, i] = numpy.real(rhot1.data[i, 0,
0]) # population of exciton 0
P[1, i] = numpy.real(rhot1.data[i, 1,
1]) # population of exciton 1
for i in range(time.length):
Pc[0, i] = numpy.real(rhotc.data[i, 0,
0]) # population of exciton 0
Pc[1, i] = numpy.real(rhotc.data[i, 1,
1]) # population of exciton 1
# we compare populations
numpy.testing.assert_allclose(Pc, P) #, rtol=1.0e-2)
with eigenbasis_of(self.H4):
for i in range(time.length):
P4e[0,
i] = numpy.real(rhot4e.data[i, 0,
0]) # population of exciton 0
P4e[1,
i] = numpy.real(rhot4e.data[i, 1,
1]) # population of exciton 1
P4e[2,
i] = numpy.real(rhot4e.data[i, 2,
2]) # population of exciton 1
for i in range(time.length):
P4s[0, i] = numpy.real(rhot4s.data[i, 0,
0]) # population of exciton 0
P4s[1, i] = numpy.real(rhot4s.data[i, 1,
1]) # population of exciton 1
P4s[2, i] = numpy.real(rhot4s.data[i, 2,
2]) # population of exciton 1
# import matplotlib.pyplot as plt
#
# plt.plot(time.data,P4s[0,:], "-r")
# plt.plot(time.data,P4s[1,:], "-r")
# plt.plot(time.data,P4s[2,:], "-r")
# plt.plot(time.data,P4e[0,:], "-g")
# plt.plot(time.data,P4e[1,:], "-g")
# plt.plot(time.data,P4e[2,:], "-g")
# plt.show()
numpy.testing.assert_allclose(P4e, P4s, atol=1.0e-8)
#for n in range(4):
# print(numpy.real(RT.data[n,n,5,5]))
#
#RR = RedfieldRateMatrix(HH,sbi)
#for n in range(4):
# print(numpy.real(RR.data[n,5]))
"""
IMPLEMENT AG.get_initial_RDM()
"""
# Sets an initial population of sites according to the transition dipole
#AG.set_impulsive_population()
rho = ReducedDensityMatrix(dim=HH.dim)
#rho.data = AG.rho0
#rho.data[0,0] = 1.0
rho.data[HH.dim-1,HH.dim-1] = 1.0
#rho.data[1,0] = 0.5
#rho.data[0,1] = 0.5
rho.normalize2()
print("Propagating density matrix ...")
start = tm.time()
# Convert to exciton basis in which RT was calculated
ss = HH.diagonalize() # Relaxation tensors are defined in the eigenstate basis
prop = RDMPropagator(time,HH,RTensor=RT)
#prop.setDtRefinement(10)
def test_trace_over_vibrations(self):
"""(Aggregate) Testing trace over vibrational DOF
"""
agg = self.vagg
ham = agg.get_Hamiltonian()
rho = ReducedDensityMatrix(dim=ham.dim)
rho._data[5, 5] = 1.0
redr = agg.trace_over_vibrations(rho)
numpy.testing.assert_almost_equal(numpy.trace(redr._data),
1.0,
decimal=7)
N = agg.Nb[0]
rho = ReducedDensityMatrix(dim=ham.dim)
rho._data[N + 5, N + 5] = 1.0
redr = agg.trace_over_vibrations(rho)
numpy.testing.assert_almost_equal(numpy.trace(redr._data),
1.0,
decimal=3)
N = agg.Nb[1]
rho = ReducedDensityMatrix(dim=ham.dim)
rho._data[N + 5, N + 5] = 1.0
redr = agg.trace_over_vibrations(rho)
numpy.testing.assert_almost_equal(numpy.trace(redr._data),
1.0,
decimal=2)
rho = ReducedDensityMatrix(dim=ham.dim)
n_part = 1. / (agg.Nb[0])
for state_ind in range(agg.Nb[0]):
rho._data[state_ind, state_ind] = n_part
redr = agg.trace_over_vibrations(rho)
numpy.testing.assert_almost_equal(numpy.trace(redr._data),
1.0,
decimal=7)