def kw_to_int(**kwargs):
steps_per_hmc = kwargs["steps_per_hmc"]
timestep = kwargs["timestep"]
group0_iterations = kwargs["group0_iterations"]
temperature = kwargs["temperature"]
print("*" * 80)
print("steps=%d, timestep=%f, extra_chances=%d, group0_iterations=%d" %
(steps_per_hmc, timestep, 0, group0_iterations))
timestep = timestep * u.femtoseconds
steps_per_hmc = int(steps_per_hmc)
group0_iterations = int(group0_iterations)
n_groups = max(
kwargs["groups"]
) + 1 # 1 group means group number = 0, assumes zero index and ordering
groups = num_to_groups(group0_iterations, n_groups)
print(n_groups)
print(groups)
if kwargs["group0_iterations"] == 0 and kwargs["extra_chances"] == 0:
integrator = hmc_integrators.GHMCIntegrator(
temperature, steps_per_hmc=steps_per_hmc, timestep=timestep)
elif kwargs["group0_iterations"] > 0 and kwargs["extra_chances"] > 0:
integrator = hmc_integrators.XCGHMCRESPAIntegrator(
temperature,
steps_per_hmc=steps_per_hmc,
timestep=timestep,
groups=groups)
elif kwargs["group0_iterations"] > 0 and kwargs["extra_chances"] == 0:
integrator = hmc_integrators.GHMCRESPAIntegrator(
temperature,
steps_per_hmc=steps_per_hmc,
timestep=timestep,
groups=groups)
elif kwargs["group0_iterations"] == 0 and kwargs["extra_chances"] > 0:
integrator = hmc_integrators.XCGHMCIntegrator(
temperature,
steps_per_hmc=steps_per_hmc,
timestep=timestep,
groups=groups)
return integrator
def inner_objective(args):
steps_per_hmc, timestep, extra_chances = args
print("steps=%d, timestep=%f, extra_chances=%d" %
(steps_per_hmc, timestep, extra_chances))
current_timestep = timestep * u.femtoseconds
extra_chances = int(extra_chances)
steps_per_hmc = int(steps_per_hmc)
integrator = hmc_integrators.XCGHMCRESPAIntegrator(
temperature,
steps_per_hmc=steps_per_hmc,
timestep=current_timestep,
extra_chances=extra_chances,
groups=groups)
simulation = lb_loader.build(testsystem,
integrator,
temperature,
precision=precision,
platform_name=platform_name)
integrator.reset_time()
integrator.step(n_steps)
return integrator, simulation # Have to pass simulation to keep it from being garbage collected
output = integrator.vstep(10) integrator.effective_timestep integrator = hmc_integrators.GHMCIntegrator(temperature, steps_per_hmc=10, timestep=timestep, collision_rate=1.0 / u.picoseconds) context = lb_loader.build(system, integrator, positions, temperature) integrator.step(40) output = integrator.vstep(10) integrator.effective_timestep integrator = hmc_integrators.XCGHMCIntegrator(temperature, steps_per_hmc=10, timestep=timestep, collision_rate=1.0 / u.picoseconds, extra_chances=extra_chances, take_debug_steps=False) context = lb_loader.build(system, integrator, positions, temperature) integrator.step(40) output = integrator.vstep(10) integrator.effective_timestep integrator = hmc_integrators.XCGHMCRESPAIntegrator(temperature, steps_per_hmc=10, timestep=timestep, collision_rate=1.0 / u.picoseconds, extra_chances=extra_chances, groups=groups) context = lb_loader.build(system, integrator, positions, temperature) integrator.step(40) output = integrator.vstep(10) integrator.effective_timestep integrator = hmc_integrators.XCHMCIntegrator(temperature, steps_per_hmc=10, timestep=timestep, extra_chances=extra_chances, take_debug_steps=False) context = lb_loader.build(system, integrator, positions, temperature) integrator.step(40) output = integrator.vstep(10) integrator.effective_timestep integrator = hmc_integrators.XCHMCRESPAIntegrator(temperature, steps_per_hmc=10, timestep=timestep, extra_chances=extra_chances, groups=groups) context = lb_loader.build(system, integrator, positions, temperature) integrator.step(40) output = integrator.vstep(10)
def enumerate_experiments():
experiments = OrderedDict()
############################################################################
sysname = "switchedljbox"
system, positions, groups, temperature, timestep, langevin_timestep, testsystem, equil_steps, steps_per_hmc = lb_loader.load(
sysname)
############################################################################
for timestep in [2.5 * u.femtoseconds, 5.0 * u.femtoseconds]:
collision_rate = 1.0 / u.picoseconds
integrator = mm.LangevinIntegrator(temperature, collision_rate,
timestep)
prms = dict(sysname=sysname,
timestep=timestep / u.femtoseconds,
collision=lb_loader.fixunits(collision_rate))
expt = Experiment(integrator=integrator, sysname=sysname, prms=prms)
collision_rate = None
for timestep in [20.0 * u.femtoseconds]:
integrator = hmc_integrators.GHMCIntegrator(
temperature=temperature,
steps_per_hmc=steps_per_hmc,
timestep=timestep,
collision_rate=collision_rate)
prms = dict(sysname=sysname,
timestep=timestep / u.femtoseconds,
collision=lb_loader.fixunits(collision_rate))
expt = Experiment(integrator=integrator, sysname=sysname, prms=prms)
timestep = 35.0 * u.femtoseconds
extra_chances = 2
collision_rate = 1.0 / u.picoseconds
integrator = hmc_integrators.XCGHMCIntegrator(
temperature=temperature,
steps_per_hmc=steps_per_hmc,
timestep=timestep,
extra_chances=extra_chances,
collision_rate=collision_rate)
itype = type(integrator).__name__
prms = dict(sysname=sysname,
itype=itype,
timestep=timestep / u.femtoseconds,
collision=lb_loader.fixunits(collision_rate))
expt = Experiment(integrator=integrator, sysname=sysname, prms=prms)
return
collision_rate = None
for timestep in []: # [2.0 * u.femtoseconds]:
integrator = hmc_integrators.XCGHMCIntegrator(
temperature=temperature,
steps_per_hmc=steps_per_hmc,
timestep=timestep,
extra_chances=extra_chances,
collision_rate=collision_rate)
itype = type(integrator).__name__
prms = dict(sysname=sysname,
itype=itype,
timestep=timestep / u.femtoseconds,
collision=lb_loader.fixunits(collision_rate))
int_string = lb_loader.format_int_name(prms)
key = (sysname, int_string)
experiments[key] = integrator
############################################################################
sysname = "switchedaccurateflexiblewater"
system, positions, groups, temperature, timestep, langevin_timestep, testsystem, equil_steps, steps_per_hmc = lb_loader.load(
sysname)
############################################################################
for timestep in [
0.10 * u.femtoseconds, 0.15 * u.femtoseconds, 0.5 * u.femtoseconds
]:
collision_rate = 1.0 / u.picoseconds
integrator = mm.LangevinIntegrator(temperature, collision_rate,
timestep)
itype = type(integrator).__name__
prms = dict(sysname=sysname,
itype=itype,
timestep=timestep / u.femtoseconds,
collision=lb_loader.fixunits(collision_rate))
int_string = lb_loader.format_int_name(prms)
key = (sysname, int_string)
experiments[key] = integrator
xcghmc_parms = dict(timestep=0.668 * u.femtoseconds,
steps_per_hmc=10,
extra_chances=1,
collision_rate=None)
integrator = hmc_integrators.XCGHMCIntegrator(temperature=temperature,
**xcghmc_parms)
itype = type(integrator).__name__
prms = dict(sysname=sysname,
itype=itype,
timestep=integrator.timestep / u.femtoseconds,
collision=lb_loader.fixunits(None))
int_string = lb_loader.format_int_name(prms)
key = (sysname, int_string)
experiments[key] = integrator
# hyperopt determined optimal settings obtain ~113 effective ns / day
xcghmc_parms = dict(timestep=1.1868 * u.femtoseconds,
steps_per_hmc=23,
collision_rate=None,
groups=((0, 1), (1, 4)))
integrator = hmc_integrators.GHMCRESPAIntegrator(temperature=temperature,
**xcghmc_parms)
itype = type(integrator).__name__
prms = dict(sysname=sysname,
itype=itype,
timestep=integrator.timestep / u.femtoseconds,
collision=lb_loader.fixunits(None))
int_string = lb_loader.format_int_name(prms)
key = (sysname, int_string)
experiments[key] = integrator
# Obtained by taking hyperopt optimal GHMCRespa parameters and adding 2 extra chances
xcghmc_parms = dict(timestep=1.1868 * u.femtoseconds,
steps_per_hmc=23,
collision_rate=None,
extra_chances=2,
groups=((0, 1), (1, 4)))
integrator = hmc_integrators.XCGHMCRESPAIntegrator(temperature=temperature,
**xcghmc_parms)
itype = type(integrator).__name__
prms = dict(sysname=sysname,
itype=itype,
timestep=integrator.timestep / u.femtoseconds,
collision=lb_loader.fixunits(None))
int_string = lb_loader.format_int_name(prms)
key = (sysname, int_string)
experiments[key] = integrator
# hyperopt determined optimal settings obtain ~79.8 effective ns/day
xcghmc_parms = dict(timestep=0.6791 * u.femtoseconds,
steps_per_hmc=20,
collision_rate=None)
integrator = hmc_integrators.GHMCIntegrator(temperature=temperature,
**xcghmc_parms)
itype = type(integrator).__name__
prms = dict(sysname=sysname,
itype=itype,
timestep=integrator.timestep / u.femtoseconds,
collision=lb_loader.fixunits(None))
int_string = lb_loader.format_int_name(prms)
key = (sysname, int_string)
experiments[key] = integrator
xcghmc_parms = dict(timestep=0.6791 * u.femtoseconds,
steps_per_hmc=20,
collision_rate=None)
xcghmc_parms.update(dict())
integrator = hmc_integrators.XCGHMCIntegrator(temperature=temperature,
**xcghmc_parms)
itype = type(integrator).__name__
prms = dict(sysname=sysname,
itype=itype,
timestep=timestep / u.femtoseconds,
collision=lb_loader.fixunits(collision_rate))
int_string = lb_loader.format_int_name(prms)
key = (sysname, int_string)
experiments[key] = integrator
############################################################################
sysname = "switchedaccuratebigflexiblewater"
system, positions, groups, temperature, timestep, langevin_timestep, testsystem, equil_steps, steps_per_hmc = lb_loader.load(
sysname)
############################################################################
experiments = OrderedDict()
# hyperopt determined optimal settings obtain ~113 effective ns / day
xcghmc_parms = dict(timestep=0.256927 * u.femtoseconds,
steps_per_hmc=24,
collision_rate=None,
groups=((0, 4), (1, 1)))
integrator = hmc_integrators.GHMCRESPAIntegrator(temperature=temperature,
**xcghmc_parms)
itype = type(integrator).__name__
prms = dict(sysname=sysname,
itype=itype,
timestep=integrator.timestep / u.femtoseconds,
collision=lb_loader.fixunits(None))
int_string = lb_loader.format_int_name(prms)
key = (sysname, int_string)
experiments[key] = integrator