def setUp(self):
np.random.seed(
0
) # set random seed in order for the examples to reproduce the exact references
# setup molecules
molecule = Molecule()
molecule1 = molecule.copy()
molecule1.set_coordinates([0])
molecule1.name = 'TypeA'
molecule2 = molecule.copy()
molecule2.set_coordinates([1])
molecule2.name = 'TypeB'
molecule3 = molecule.copy()
molecule3.set_coordinates([2])
molecule3.name = 'TypeC'
# setup system
self.system = System(molecules=[molecule1, molecule2, molecule3],
supercell=[[3]])
# set initial exciton
# self.system.add_excitation_index(tt, 1)
# self.system.add_excitation_random(s1, 2)
self.system.add_excitation_index(s1, 0)
self.system.add_excitation_index(s1, 1)
def regular_system(molecule,
lattice=None,
orientation=None,
):
if lattice is None:
lattice = {'size': [1], 'parameters': [1.0]} # default 1D 1 molecule system
molecules = [] # list of instances of class molecule
for subset in itertools.product(*[list(range(n)) for n in lattice['size']]):
coordinates = np.multiply(subset, lattice['parameters'])
final_orientation = list(orientation)
for j in range(3):
if final_orientation[j] is None:
final_orientation[j] = np.random.random_sample() * 2 * np.pi
molecule = molecule.copy() # copy of the generic instance
molecule.set_coordinates(coordinates)
molecule.set_orientation(final_orientation)
molecules.append(molecule)
supercell = np.diag(np.multiply(lattice['size'], lattice['parameters']))
return System(molecules, supercell)
def setUp(self):
# setup molecules
molecule = Molecule()
molecule1 = molecule.copy()
molecule1.set_coordinates([0])
molecule1.name = 'TypeA'
molecule2 = molecule.copy()
molecule2.set_coordinates([1])
molecule2.name = 'TypeB'
molecule3 = molecule.copy()
molecule3.set_coordinates([2])
molecule3.name = 'TypeC'
# setup system
self.system = System(molecules=[molecule1, molecule2, molecule3],
supercell=[[3]])
# set initial exciton
self.system.add_excitation_index(s1, 1)
self.system.add_excitation_index(s1, 0)
def crystal_system(molecules,
scaled_site_coordinates,
dimensions=None,
unitcell=None,
orientations=None,
):
unitcell = np.array(unitcell)
scaled_site_coordinates = np.array(scaled_site_coordinates)
n_mol, n_dim = scaled_site_coordinates.shape
if dimensions is None:
dimensions = [1] * n_dim
if orientations is None:
orientations = [None for _ in range(n_mol)]
molecules_list = [] # list of instances of class molecule
for i, (coordinate, molecule_type) in enumerate(zip(scaled_site_coordinates, molecules)):
for subset in itertools.product(*[list(range(n)) for n in dimensions]):
r_cell = np.sum([s * lattice_vector for s, lattice_vector in zip(subset, unitcell)], axis=0)
coor = r_cell + np.dot(unitcell.T, coordinate)
molecule = molecule_type.copy() # copy of the generic instance
molecule.set_coordinates(coor)
molecule.name = 'a{}'.format(i+1)
final_orientation = list(orientations[i])
for j in range(3):
if final_orientation[j] is None:
final_orientation[j] = np.random.random_sample() * 2 * np.pi
else:
final_orientation[j] = final_orientation[j]
molecule.set_orientation(final_orientation)
molecules_list.append(molecule)
supercell = np.dot(unitcell.T, np.diag(dimensions)).T
return System(molecules_list, supercell)
class Test1DFast(unittest.TestCase):
def setUp(self):
# setup molecules
molecule = Molecule()
molecule1 = molecule.copy()
molecule1.set_coordinates([0])
molecule1.name = 'TypeA'
molecule2 = molecule.copy()
molecule2.set_coordinates([1])
molecule2.name = 'TypeB'
molecule3 = molecule.copy()
molecule3.set_coordinates([2])
molecule3.name = 'TypeC'
# setup system
self.system = System(molecules=[molecule1, molecule2, molecule3],
supercell=[[3]])
# set initial exciton
self.system.add_excitation_index(s1, 1)
self.system.add_excitation_index(s1, 0)
def test_kmc_algorithm(self):
np.random.seed(
0
) # set random seed in order for the examples to reproduce the exact references
# set additional system parameters
self.system.process_scheme = [
DirectRate(initial_states=(s1, gs),
final_states=(gs, s1),
rate_constant_function=transfer_rate,
arguments={'custom_constant': 1},
description='transport s1'),
DirectRate(initial_states=(s1, s1),
final_states=(tt, ),
rate_constant_function=transfer_rate,
arguments={'custom_constant': 1},
description='merge s1-s1 -> tt'),
DirectRate(initial_states=(tt, ),
final_states=(gs, gs),
rate_constant_function=decay_rate,
description='decay tt'),
DirectRate(initial_states=(tt, gs),
final_states=(gs, tt),
rate_constant_function=decay_rate,
description='transport tt')
]
self.system.cutoff_radius = 10.0 # interaction cutoff radius in Angstrom
p = DirectRate(initial_states=(s1, s1),
final_states=(tt, ),
rate_constant_function=transfer_rate,
arguments={'custom_constant': 1},
description='custom2')
#print(p.get_transition_connections())
#exit()
# some system analyze functions
system_test_info(self.system)
trajectories = calculate_kmc(
self.system,
num_trajectories=10, # number of trajectories that will be simulated
max_steps=50, # maximum number of steps for trajectory allowed
silent=True)
# Results analysis
analysis = TrajectoryAnalysis(trajectories)
print('diffusion coefficient: {:9.5f} Angs^2/ns'.format(
analysis.diffusion_coefficient('tt')))
print('lifetime: {:9.5f} ns'.format(
analysis.lifetime('tt')))
print('diffusion length: {:9.5f} Angs'.format(
analysis.diffusion_length('tt')))
print('diffusion tensor (Angs^2/ns)')
print(analysis.diffusion_coeff_tensor('tt'))
print('diffusion length square tensor (Angs)')
print(analysis.diffusion_length_square_tensor('tt'))
test = {
'diffusion coefficient':
np.around(analysis.diffusion_coefficient('tt'), decimals=4),
'lifetime':
np.around(analysis.lifetime('tt'), decimals=4),
'diffusion length':
np.around(analysis.diffusion_length('tt'), decimals=4),
'diffusion tensor':
np.around(analysis.diffusion_coeff_tensor('tt'),
decimals=4).tolist(),
'diffusion length tensor':
np.around(np.sqrt(analysis.diffusion_length_square_tensor('tt')),
decimals=4).tolist()
}
ref = {
'diffusion coefficient': 0.4819,
'lifetime': 28.3726,
'diffusion length': 4.1018,
'diffusion tensor': [[0.4819]],
'diffusion length tensor': [[4.1018]]
}
self.assertDictEqual(ref, test)
class Test1DFast(unittest.TestCase):
def setUp(self):
# setup molecules
molecule = Molecule()
molecule1 = molecule.copy()
molecule1.set_coordinates([0])
molecule1.name = 'TypeA'
molecule2 = molecule.copy()
molecule2.set_coordinates([1])
molecule2.name = 'TypeB'
molecule3 = molecule.copy()
molecule3.set_coordinates([2])
molecule3.name = 'TypeC'
# setup system
self.system = System(molecules=[molecule1, molecule2, molecule3],
supercell=[[3]])
# set initial exciton
self.system.add_excitation_index(s2, 1)
self.system.add_excitation_index(s1, 2)
def test_kmc_algorithm(self):
np.random.seed(
0
) # set random seed in order for the examples to reproduce the exact references
# set additional system parameters
self.system.process_scheme = [
DirectRate(initial_states=(s1, gs),
final_states=(gs, s1),
rate_constant_function=transfer_rate,
arguments={'custom_constant': 1},
description='transport'),
DirectRate(initial_states=(s1, ),
final_states=(gs, ),
rate_constant_function=decay_rate,
description='custom decay rate'),
DirectRate(initial_states=(s2, s2),
final_states=(gs, s1),
rate_constant_function=decay_rate,
description='merge'),
DirectRate(initial_states=(s1, gs),
final_states=(s2, s2),
rate_constant_function=decay_rate,
description='split'),
DirectRate(initial_states=(s2, gs),
final_states=(gs, s2),
rate_constant_function=transfer_rate,
arguments={'custom_constant': 1},
description='transport 2'),
DirectRate(initial_states=(s2, ),
final_states=(gs, ),
rate_constant_function=decay_rate,
description='custom decay rate 2'),
]
#print([s.label for s in self.system.decay_scheme[0].initial], '--',
# [s.label for s in self.system.decay_scheme[0].final])
#print([s.label for s in self.system.decay_scheme[1].initial], '--',
# [s.label for s in self.system.decay_scheme[1].final])
self.system.cutoff_radius = 10.0 # interaction cutoff radius in Angstrom
# some system analyze functions
system_test_info(self.system)
trajectories = calculate_kmc(
self.system,
num_trajectories=50, # number of trajectories that will be simulated
max_steps=18, # maximum number of steps for trajectory allowed
silent=True)
# Results analysis
analysis = TrajectoryAnalysis(trajectories)
for traj in trajectories:
print('diff:', traj.get_diffusion('s1'))
print('diff none:', traj.get_diffusion(None))
#print('path:', traj._trajectory_node_path())
#print('path:', trajectories[0]._trajectory_node_path_new())
#print('-> diff:', trajectories[8].get_diffusion('s1'))
#print('-> diff none:', trajectories[8].get_diffusion(None))
#print('path:', trajectories[8]._trajectory_node_path())
#trajectories[0].plot_graph().show()
#exit()
print('diffusion coefficient: {:9.5f} Angs^2/ns'.format(
analysis.diffusion_coefficient('s1')))
print('lifetime: {:9.5f} ns'.format(
analysis.lifetime('s1')))
print('diffusion length: {:9.5f} Angs'.format(
analysis.diffusion_length('s1')))
print('diffusion tensor (Angs^2/ns)')
print(analysis.diffusion_coeff_tensor('s1'))
print('diffusion length square tensor (Angs)')
print(analysis.diffusion_length_square_tensor('s1'))
test = {
'diffusion coefficient':
np.around(analysis.diffusion_coefficient('s1'), decimals=4),
'lifetime':
np.around(analysis.lifetime('s1'), decimals=4),
'diffusion length':
np.around(analysis.diffusion_length('s1'), decimals=4),
'diffusion tensor':
np.around(analysis.diffusion_coeff_tensor('s1'),
decimals=4).tolist(),
'diffusion length tensor':
np.around(np.sqrt(analysis.diffusion_length_square_tensor('s1')),
decimals=4).tolist()
}
print(test)
ref = {
'diffusion coefficient': 3.5571,
'lifetime': 2.2493,
'diffusion length': 3.9478,
'diffusion tensor': [[3.5571]],
'diffusion length tensor': [[3.9478]]
}
self.assertDictEqual(ref, test)
def test_kmc_algorithm_2(self):
np.random.seed(
0
) # set random seed in order for the examples to reproduce the exact references
transitions = [
Transition(s1,
gs,
tdm=[0.01],
reorganization_energy=0.07,
symmetric=True)
]
# set additional system parameters
self.system.process_scheme = [
GoldenRule(initial_states=(s1, gs),
final_states=(gs, s1),
electronic_coupling_function=forster_coupling,
description='Forster coupling',
arguments={
'ref_index': 1,
'transitions': transitions
},
vibrations=MarcusModel(transitions=transitions)),
DecayRate(initial_state=s1,
final_state=gs,
decay_rate_function=decay_rate,
description='custom decay rate')
]
self.system.cutoff_radius = 10.0 # interaction cutoff radius in Angstrom
# some system analyze functions
system_test_info(self.system)
trajectories = calculate_kmc(
self.system,
num_trajectories=10, # number of trajectories that will be simulated
max_steps=10000, # maximum number of steps for trajectory allowed
silent=True)
# Results analysis
analysis = TrajectoryAnalysis(trajectories)
print('diffusion coefficient: {:9.5f} Angs^2/ns'.format(
analysis.diffusion_coefficient('s1')))
print('lifetime: {:9.5f} ns'.format(
analysis.lifetime('s1')))
print('diffusion length: {:9.5f} Angs'.format(
analysis.diffusion_length('s1')))
print('diffusion tensor (Angs^2/ns)')
print(analysis.diffusion_coeff_tensor('s1'))
print('diffusion length square tensor (Angs)')
print(analysis.diffusion_length_square_tensor('s1'))
test = {
'diffusion coefficient':
np.around(analysis.diffusion_coefficient('s1'), decimals=4),
'lifetime':
np.around(analysis.lifetime('s1'), decimals=4),
'diffusion length':
np.around(analysis.diffusion_length('s1'), decimals=4),
'diffusion tensor':
np.around(analysis.diffusion_coeff_tensor('s1'),
decimals=4).tolist(),
'diffusion length tensor':
np.around(np.sqrt(analysis.diffusion_length_square_tensor('s1')),
decimals=6).tolist()
}
print(test)
ref = {
'diffusion coefficient': 0.4265,
'lifetime': 24.1692,
'diffusion length': 5.4498,
'diffusion tensor': [[0.4265]],
'diffusion length tensor': [[5.449771]]
}
self.assertDictEqual(ref, test)
molecule = Molecule()
molecule1 = molecule.copy()
molecule1.set_coordinates([0])
molecule1.name = 'TypeA'
molecule2 = molecule.copy()
molecule2.set_coordinates([1])
molecule2.name = 'TypeB'
molecule3 = molecule.copy()
molecule3.set_coordinates([2])
molecule3.name = 'TypeC'
# setup system
system = System(molecules=[molecule1, molecule2, molecule3], supercell=[[3]])
# set initial exciton
system.add_excitation_index(s1, 1)
system.add_excitation_index(s2, 2)
# set additional system parameters
system.process_scheme = [
DirectRate(initial_states=(s1, gs),
final_states=(gs, s1),
rate_constant_function=transfer_rate,
description='custom'),
DirectRate(initial_states=(s2, gs),
final_states=(gs, s2),
rate_constant_function=transfer_rate,
description='custom'),