def test_onesite_sams_sampling_binary_all_stages(self):
"""Test the one site sams sampling approach with binary updates through all 4 stages of the algorithm"""
old_log_level = log.getEffectiveLevel()
log.setLevel(logging.INFO)
pep = self.setup_peptide_implicit("yeah", createsim=False)
pep.drive.enable_calibration(
SAMSApproach.ONESITE,
group_index=0,
min_burn=200,
min_fast=100,
min_slow=100,
flatness_criterion=0.15,
)
pep.simulation = app.ConstantPHSimulation(
pep.topology,
pep.system,
pep.integrator,
pep.drive,
platform=TestSAMS.platform,
)
pep.simulation.context.setPositions(pep.positions)
pep.context = pep.simulation.context
pep.simulation.minimizeEnergy()
total_iterations = 1000
for x in range(total_iterations):
if x == total_iterations - 1:
log.setLevel(logging.DEBUG)
pep.simulation.step(1)
pep.simulation.update(1)
pep.simulation.adapt()
# log.info(pep.drive.calibration_state.observed_counts)
log.setLevel(old_log_level)
def test_calibration_class_multisite(self):
"""Test the multisite SAMS sampling approach."""
old_log_level = log.getEffectiveLevel()
pep = self.setup_peptide_implicit("yeah", createsim=True)
pep.drive.enable_calibration(SAMSApproach.MULTISITE)
sampler = SAMSCalibrationEngine(pep.drive)
total_iterations = 1500
for x in range(total_iterations):
if x == total_iterations - 1:
log.setLevel(logging.DEBUG)
pep.simulation.step(1)
pep.simulation.update(1)
sampler.adapt_zetas(UpdateRule.BINARY, b=0.51, stage=Stage.NODECAY)
log.setLevel(old_log_level)
return
def test_onesite_sams_sampling_global(self):
"""Test the one site sams sampling approach with global updates"""
old_log_level = log.getEffectiveLevel()
pep = self.setup_peptide_implicit("yeah")
pep.drive.enable_calibration(SAMSApproach.ONESITE, group_index=1)
sampler = SAMSCalibrationEngine(pep.drive)
total_iterations = 1500
for x in range(total_iterations):
if x == total_iterations - 1:
log.setLevel(logging.DEBUG)
pep.simulation.step(1)
pep.simulation.update(1)
sampler.adapt_zetas(UpdateRule.GLOBAL, b=0.51, stage=Stage.NODECAY)
log.setLevel(old_log_level)
def test_dummy_moving_mc(self) -> None:
"""Move dummies with monte carlo and evaluate the energy differences."""
md_steps_between_mc = 100
total_loops = 100
viologen = self.setup_viologen_vacuum()
# viologen = self.setup_viologen_water()
if log.getEffectiveLevel() == logging.DEBUG:
viologen.simulation.reporters.append(
app.DCDReporter(
"cooh-viologen-{}.dcd".format(str(uuid.uuid4())),
md_steps_between_mc // 10,
))
cooh1 = COOHDummyMover.from_system(viologen.system, viologen.cooh1)
cooh2 = COOHDummyMover.from_system(viologen.system, viologen.cooh2)
moveset = {cooh1.random_move, cooh2.random_move}
n_accept = 0
for iteration in range(total_loops):
viologen.simulation.step(md_steps_between_mc)
state = viologen.context.getState(getPositions=True,
getVelocities=True)
pos = state.getPositions(asNumpy=True)._value
# perform a move.
move = sample(moveset, 1)[0]
log.debug(move.__name__)
new_pos, logp = move(pos)
if exp(logp) > uniform(0.0, 1.0):
log.debug("Accepted: logp %f", logp)
viologen.context.setPositions(new_pos)
viologen.context.setVelocitiesToTemperature(
viologen.temperature)
n_accept += 1
else:
log.debug("Rejected: logp %f", logp)
raise RuntimeError("These moves should never be rejected.")
return
def test_dummy_moving_mc(self) -> None:
"""Move dummies with monte carlo and evaluate the energy differences."""
md_steps_between_mc = 100
total_loops = 100
viologen = self.setup_viologen_vacuum()
# viologen = self.setup_viologen_water()
if log.getEffectiveLevel() == logging.DEBUG:
viologen.simulation.reporters.append(
app.DCDReporter(
"cooh-viologen-{}.dcd".format(str(uuid.uuid4())),
md_steps_between_mc // 10,
)
)
cooh1 = COOHDummyMover.from_system(viologen.system, viologen.cooh1)
cooh2 = COOHDummyMover.from_system(viologen.system, viologen.cooh2)
moveset = {cooh1.random_move, cooh2.random_move}
n_accept = 0
for iteration in range(total_loops):
viologen.simulation.step(md_steps_between_mc)
state = viologen.context.getState(getPositions=True, getVelocities=True)
pos = state.getPositions(asNumpy=True)._value
# perform a move.
move = sample(moveset, 1)[0]
log.debug(move.__name__)
new_pos, logp = move(pos)
if exp(logp) > uniform(0.0, 1.0):
log.debug("Accepted: logp %f", logp)
viologen.context.setPositions(new_pos)
viologen.context.setVelocitiesToTemperature(viologen.temperature)
n_accept += 1
else:
log.debug("Rejected: logp %f", logp)
raise RuntimeError("These moves should never be rejected.")
return
def test_glutamic_acid_cooh(self):
"""Use the dummy mover with the amino acid glutamic acid"""
md_steps_between_mc = 10
total_loops = 5
glh = self.setup_amino_acid_water("glh")
drive = ForceFieldProtonDrive(
glh.temperature,
glh.topology,
glh.system,
glh.forcefield,
glh.ffxml_files,
pressure=glh.pressure,
perturbations_per_trial=glh.perturbations_per_trial,
propagations_per_step=glh.propagations_per_step,
residues_by_name=None,
residues_by_index=None,
)
if log.getEffectiveLevel() == logging.DEBUG:
glh.simulation.reporters.append(
app.DCDReporter(
"cooh-glh-{}.dcd".format(str(uuid.uuid4())),
md_steps_between_mc // 5,
enforcePeriodicBox=True,
)
)
drive.attach_context(glh.context)
drive.adjust_to_ph(4.6)
for iteration in range(total_loops):
glh.simulation.step(md_steps_between_mc)
drive.update("COOH", nattempts=1)
return
def test_glutamic_acid_cooh(self):
"""Use the dummy mover with the amino acid glutamic acid"""
md_steps_between_mc = 10
total_loops = 5
glh = self.setup_amino_acid_water("glh")
drive = ForceFieldProtonDrive(
glh.temperature,
glh.topology,
glh.system,
glh.forcefield,
glh.ffxml_files,
pressure=glh.pressure,
perturbations_per_trial=glh.perturbations_per_trial,
propagations_per_step=glh.propagations_per_step,
residues_by_name=None,
residues_by_index=None,
)
if log.getEffectiveLevel() == logging.DEBUG:
glh.simulation.reporters.append(
app.DCDReporter(
"cooh-glh-{}.dcd".format(str(uuid.uuid4())),
md_steps_between_mc // 5,
enforcePeriodicBox=True,
))
drive.attach_context(glh.context)
drive.adjust_to_ph(4.6)
for iteration in range(total_loops):
glh.simulation.step(md_steps_between_mc)
drive.update("COOH", nattempts=1)
return
def test_onesite_sams_sampling_binary_all_stages_serialization(self):
"""Test the one site sams sampling approach with binary updates through all 4 stages of the algorithm
and after serialization."""
old_log_level = log.getEffectiveLevel()
log.setLevel(logging.INFO)
pep = self.setup_peptide_implicit("yeah", createsim=False)
pep.drive.enable_calibration(
SAMSApproach.ONESITE,
group_index=0,
min_burn=200,
min_fast=200,
min_slow=200,
flatness_criterion=0.15,
)
pep.simulation = app.ConstantPHSimulation(
pep.topology,
pep.system,
pep.integrator,
pep.drive,
platform=TestSAMS.platform,
)
pep.simulation.context.setPositions(pep.positions)
pep.context = pep.simulation.context
pep.simulation.minimizeEnergy()
total_iterations = 1000
for x in range(total_iterations):
pep.simulation.step(1)
pep.simulation.update(1)
pep.simulation.adapt()
pep.drive: NCMCProtonDrive
drive_state = pep.drive.state_to_xml()
new_drive = NCMCProtonDrive(
pep.temperature,
pep.topology,
pep.system,
pressure=None,
perturbations_per_trial=pep.perturbations_per_trial,
propagations_per_step=pep.propagations_per_step,
)
new_drive.state_from_xml_tree(etree.fromstring(drive_state))
new_simulation = app.ConstantPHSimulation(
pep.topology,
pep.system,
create_compound_gbaoab_integrator(pep),
new_drive,
platform=TestSAMS.platform,
)
old_state: app.State = pep.simulation.context.getState(
getPositions=True, getVelocities=True
)
new_simulation.context.setPositions(old_state.getPositions())
new_simulation.context.setVelocities(old_state.getVelocities())
total_iterations = 1000
for x in range(total_iterations):
if x == total_iterations - 1:
log.setLevel(logging.DEBUG)
new_simulation.step(1)
new_simulation.update(1)
new_simulation.adapt()
log.debug("Last deviation: %f", new_simulation.last_dev)
log.info(
"Observed counts: %s", str(pep.drive.calibration_state.observed_counts)
)
log.setLevel(old_log_level)