def runEthyleneTest(dir, N):
filename = dir.join('ethylene-test_%s' % N)
print('Running %s...' % filename)
# Set Simulation parameters
temperature = 200 * unit.kelvin
collision_rate = 1 / unit.picoseconds
timestep = 1.0 * unit.femtoseconds
n_steps = 20
nIter = 100
reportInterval = 5
alchemical_atoms = [2, 3, 4, 5, 6, 7]
platform = openmm.Platform.getPlatformByName('CPU')
context_cache = cache.ContextCache(platform)
# Load a Parmed Structure for the Topology and create our openmm.Simulation
structure_pdb = utils.get_data_filename(
'blues', 'tests/data/ethylene_structure.pdb')
structure = parmed.load_file(structure_pdb)
nc_reporter = NetCDF4Storage(filename + '_MD.nc', reportInterval)
# Iniitialize our Move set
rot_move = RandomLigandRotationMove(timestep=timestep,
n_steps=n_steps,
atom_subset=alchemical_atoms,
context_cache=context_cache,
reporters=[nc_reporter])
langevin_move = ReportLangevinDynamicsMove(timestep=timestep,
collision_rate=collision_rate,
n_steps=n_steps,
reassign_velocities=True,
context_cache=context_cache)
# Load our OpenMM System and create Integrator
system_xml = utils.get_data_filename('blues',
'tests/data/ethylene_system.xml')
with open(system_xml, 'r') as infile:
xml = infile.read()
system = openmm.XmlSerializer.deserialize(xml)
thermodynamic_state = ThermodynamicState(system=system,
temperature=temperature)
sampler_state = SamplerState(
positions=structure.positions.in_units_of(unit.nanometers))
sampler = BLUESSampler(thermodynamic_state=thermodynamic_state,
sampler_state=sampler_state,
ncmc_move=rot_move,
dynamics_move=langevin_move,
topology=structure.topology)
sampler.run(nIter)
return filename
def get_states():
# Set Simulation parameters
temperature = 200 * unit.kelvin
collision_rate = 1 / unit.picoseconds
timestep = 1.0 * unit.femtoseconds
n_steps = 20
nIter = 100
alchemical_atoms = [2, 3, 4, 5, 6, 7]
platform = openmm.Platform.getPlatformByName('CPU')
context_cache = cache.ContextCache(platform)
# Load a Parmed Structure for the Topology and create our openmm.Simulation
structure_pdb = utils.get_data_filename(
'blues', 'tests/data/ethylene_structure.pdb')
structure = parmed.load_file(structure_pdb)
# Load our OpenMM System and create Integrator
system_xml = utils.get_data_filename('blues',
'tests/data/ethylene_system.xml')
with open(system_xml, 'r') as infile:
xml = infile.read()
system = openmm.XmlSerializer.deserialize(xml)
thermodynamic_state = ThermodynamicState(system=system,
temperature=temperature)
sampler_state = SamplerState(
positions=structure.positions.in_units_of(unit.nanometers))
alch_system = generateAlchSystem(thermodynamic_state.get_system(),
alchemical_atoms)
alch_state = alchemy.AlchemicalState.from_system(alch_system)
alch_thermodynamic_state = ThermodynamicState(
alch_system, thermodynamic_state.temperature)
alch_thermodynamic_state = CompoundThermodynamicState(
alch_thermodynamic_state, composable_states=[alch_state])
return structure, thermodynamic_state, alch_thermodynamic_state
def setup(self,
n_states,
temperature,
storage_file,
minimisation_steps=100,
n_replicas=None,
lambda_schedule=None,
lambda_protocol=LambdaProtocol(),
endstates=True):
from perses.dispersed import feptasks
hybrid_system = self._factory.hybrid_system
positions = self._factory.hybrid_positions
lambda_zero_alchemical_state = RelativeAlchemicalState.from_system(
hybrid_system)
thermostate = ThermodynamicState(hybrid_system,
temperature=temperature)
compound_thermodynamic_state = CompoundThermodynamicState(
thermostate, composable_states=[lambda_zero_alchemical_state])
thermodynamic_state_list = []
sampler_state_list = []
context_cache = cache.ContextCache()
if n_replicas is None:
_logger.info(
f'n_replicas not defined, setting to match n_states, {n_states}'
)
n_replicas = n_states
elif n_replicas > n_states:
_logger.warning(
f'More sampler states: {n_replicas} requested greater than number of states: {n_states}. Setting n_replicas to n_states: {n_states}'
)
n_replicas = n_states
# TODO this feels like it should be somewhere else... just not sure where. Maybe into lambda_protocol
if lambda_schedule is None:
lambda_schedule = np.linspace(0., 1., n_states)
else:
assert (
len(lambda_schedule) == n_states
), 'length of lambda_schedule must match the number of states, n_states'
assert (
lambda_schedule[0] == 0.), 'lambda_schedule must start at 0.'
assert (
lambda_schedule[-1] == 1.), 'lambda_schedule must end at 1.'
difference = np.diff(lambda_schedule)
assert (all(i >= 0. for i in difference)
), 'lambda_schedule must be monotonicly increasing'
#starting with the initial positions generated py geometry.py
sampler_state = SamplerState(
positions,
box_vectors=hybrid_system.getDefaultPeriodicBoxVectors())
for lambda_val in lambda_schedule:
compound_thermodynamic_state_copy = copy.deepcopy(
compound_thermodynamic_state)
compound_thermodynamic_state_copy.set_alchemical_parameters(
lambda_val, lambda_protocol)
thermodynamic_state_list.append(compound_thermodynamic_state_copy)
# now generating a sampler_state for each thermodyanmic state, with relaxed positions
context, context_integrator = context_cache.get_context(
compound_thermodynamic_state_copy)
feptasks.minimize(compound_thermodynamic_state_copy, sampler_state)
sampler_state_list.append(copy.deepcopy(sampler_state))
reporter = storage_file
# making sure number of sampler states equals n_replicas
if len(sampler_state_list) != n_replicas:
# picking roughly evenly spaced sampler states
# if n_replicas == 1, then it will pick the first in the list
idx = np.round(
np.linspace(0,
len(sampler_state_list) - 1,
n_replicas)).astype(int)
sampler_state_list = [
state for i, state in enumerate(sampler_state_list) if i in idx
]
assert len(sampler_state_list) == n_replicas
if endstates:
# generating unsampled endstates
_logger.info('Generating unsampled endstates.')
unsampled_dispersion_endstates = create_endstates(
copy.deepcopy(thermodynamic_state_list[0]),
copy.deepcopy(thermodynamic_state_list[-1]))
self.create(
thermodynamic_states=thermodynamic_state_list,
sampler_states=sampler_state_list,
storage=reporter,
unsampled_thermodynamic_states=unsampled_dispersion_endstates)
else:
self.create(thermodynamic_states=thermodynamic_state_list,
sampler_states=sampler_state_list,
storage=reporter)
def setup(self,
n_states,
temperature,
storage_file,
minimisation_steps=100,
lambda_schedule=None,
lambda_protocol=LambdaProtocol(),
endstates=True):
from perses.dispersed import feptasks
hybrid_system = self._factory.hybrid_system
positions = self._factory.hybrid_positions
lambda_zero_alchemical_state = RelativeAlchemicalState.from_system(
hybrid_system)
thermostate = ThermodynamicState(hybrid_system,
temperature=temperature)
compound_thermodynamic_state = CompoundThermodynamicState(
thermostate, composable_states=[lambda_zero_alchemical_state])
thermodynamic_state_list = []
sampler_state_list = []
context_cache = cache.ContextCache()
if lambda_schedule is None:
lambda_schedule = np.linspace(0., 1., n_states)
else:
assert (
len(lambda_schedule) == n_states
), 'length of lambda_schedule must match the number of states, n_states'
assert (
lambda_schedule[0] == 0.), 'lambda_schedule must start at 0.'
assert (
lambda_schedule[-1] == 1.), 'lambda_schedule must end at 1.'
difference = np.diff(lambda_schedule)
assert (all(i >= 0. for i in difference)
), 'lambda_schedule must be monotonicly increasing'
#starting with the initial positions generated py geometry.py
sampler_state = SamplerState(
positions,
box_vectors=hybrid_system.getDefaultPeriodicBoxVectors())
for lambda_val in lambda_schedule:
compound_thermodynamic_state_copy = copy.deepcopy(
compound_thermodynamic_state)
compound_thermodynamic_state_copy.set_alchemical_parameters(
lambda_val, lambda_protocol)
thermodynamic_state_list.append(compound_thermodynamic_state_copy)
# now generating a sampler_state for each thermodyanmic state, with relaxed positions
context, context_integrator = context_cache.get_context(
compound_thermodynamic_state_copy)
feptasks.minimize(compound_thermodynamic_state_copy, sampler_state)
sampler_state_list.append(copy.deepcopy(sampler_state))
reporter = storage_file
if endstates:
# generating unsampled endstates
logger.info('Generating unsampled endstates.')
unsampled_dispersion_endstates = create_endstates(
copy.deepcopy(thermodynamic_state_list[0]),
copy.deepcopy(thermodynamic_state_list[-1]))
self.create(
thermodynamic_states=thermodynamic_state_list,
sampler_states=sampler_state_list,
storage=reporter,
unsampled_thermodynamic_states=unsampled_dispersion_endstates)
else:
self.create(thermodynamic_states=thermodynamic_state_list,
sampler_states=sampler_state_list,
storage=reporter)