def test_harmonic_oscillators():
nc_filename = tempfile.mkdtemp() + "/out.nc"
T_min = 1.0 * unit.kelvin
T_i = [T_min, T_min * 10., T_min * 100.]
n_replicas = len(T_i)
ho = testsystems.HarmonicOscillator()
system = ho.system
positions = ho.positions
states = [ ThermodynamicState(system=system, temperature=T_i[i]) for i in range(n_replicas) ]
coordinates = [positions] * n_replicas
mpicomm = dummympi.DummyMPIComm()
parameters = {"number_of_iterations":1000}
replica_exchange = ReplicaExchange.create(states, coordinates, nc_filename, mpicomm=mpicomm, parameters=parameters)
replica_exchange.run()
u_permuted = replica_exchange.database.ncfile.variables["energies"][:]
s = replica_exchange.database.ncfile.variables["states"][:]
u = permute_energies(u_permuted, s)
u0 = np.array([[ho.reduced_potential_expectation(s0, s1) for s1 in states] for s0 in states])
l0 = np.log(u0) # Compare on log scale because uncertainties are proportional to values
l1 = np.log(u.mean(0))
eq(l0, l1, decimal=1)
def test_harmonic_oscillators_save_and_load():
nc_filename = tempfile.mkdtemp() + "/out.nc"
T_min = 1.0 * unit.kelvin
T_i = [T_min, T_min * 10., T_min * 100.]
n_replicas = len(T_i)
ho = testsystems.HarmonicOscillator()
system = ho.system
positions = ho.positions
states = [ ThermodynamicState(system=system, temperature=T_i[i]) for i in range(n_replicas) ]
coordinates = [positions] * n_replicas
mpicomm = dummympi.DummyMPIComm()
parameters = {"number_of_iterations":200}
replica_exchange = ReplicaExchange.create(states, coordinates, nc_filename, mpicomm=mpicomm, parameters=parameters)
replica_exchange.run()
replica_exchange.extend(100)
replica_exchange = resume(nc_filename, mpicomm=mpicomm)
eq(replica_exchange.iteration, 200)
replica_exchange.run()
def test_check_positions():
nc_filename = tempfile.mkdtemp() + "/out.nc"
T_min = 1.0 * unit.kelvin
T_i = [T_min, T_min * 10., T_min * 100.]
n_replicas = len(T_i)
ho = testsystems.HarmonicOscillator()
system = ho.system
positions = ho.positions
states = [
ThermodynamicState(system=system, temperature=T_i[i])
for i in range(n_replicas)
]
coordinates = [positions] * n_replicas
mpicomm = dummympi.DummyMPIComm()
parameters = {"number_of_iterations": 10}
replica_exchange = ReplicaExchange.create(states,
coordinates,
nc_filename,
mpicomm=mpicomm,
parameters=parameters)
replica_exchange.run()
db = replica_exchange.database
db.check_energies()
def test_harmonic_oscillators_save_and_load():
nc_filename = tempfile.mkdtemp() + "/out.nc"
T_min = 1.0 * unit.kelvin
T_i = [T_min, T_min * 10., T_min * 100.]
n_replicas = len(T_i)
ho = testsystems.HarmonicOscillator()
system = ho.system
positions = ho.positions
states = [
ThermodynamicState(system=system, temperature=T_i[i])
for i in range(n_replicas)
]
coordinates = [positions] * n_replicas
mpicomm = dummympi.DummyMPIComm()
parameters = {"number_of_iterations": 200}
replica_exchange = ReplicaExchange.create(states,
coordinates,
nc_filename,
mpicomm=mpicomm,
parameters=parameters)
replica_exchange.run()
replica_exchange.extend(100)
replica_exchange = resume(nc_filename, mpicomm=mpicomm)
eq(replica_exchange.iteration, 200)
replica_exchange.run()
def test_get_traj():
nc_filename = tempfile.mkdtemp() + "/out.nc"
T_min = 300.0 * unit.kelvin
T_i = [T_min, T_min * 1.01, T_min * 1.1]
n_replicas = len(T_i)
ho = testsystems.AlanineDipeptideExplicit()
system = ho.system
positions = ho.positions
states = [ ThermodynamicState(system=system, temperature=T_i[i]) for i in range(n_replicas) ]
coordinates = [positions] * n_replicas
mpicomm = dummympi.DummyMPIComm()
parameters = {"number_of_iterations":3}
replica_exchange = ReplicaExchange.create(states, coordinates, nc_filename, mpicomm=mpicomm, parameters=parameters)
replica_exchange.run()
db = replica_exchange.database
trj0 = md.load("repex/data/alanine-dipeptide-explicit/alanine-dipeptide.pdb")
db.set_traj(trj0)
trj1 = db.get_traj(state_index=0)
trj2 = db.get_traj(replica_index=0)
def test_output_diagnostics():
tempdir = tempfile.mkdtemp()
nc_filename = tempdir + "/out.nc"
T_min = 1.0 * unit.kelvin
T_i = [T_min, T_min * 10., T_min * 100.]
n_replicas = len(T_i)
ho = testsystems.HarmonicOscillator()
system = ho.system
positions = ho.positions
states = [ ThermodynamicState(system=system, temperature=T_i[i]) for i in range(n_replicas) ]
coordinates = [positions] * n_replicas
mpicomm = dummympi.DummyMPIComm()
parameters = {"number_of_iterations":10}
replica_exchange = ReplicaExchange.create(states, coordinates, nc_filename, mpicomm=mpicomm, parameters=parameters)
replica_exchange.run()
db = replica_exchange.database
db.check_energies()
db.output_diagnostics(tempdir + "/diagnostics/")
def test_harmonic_oscillators():
nc_filename = tempfile.mkdtemp() + "/out.nc"
T_min = 1.0 * unit.kelvin
T_i = [T_min, T_min * 10., T_min * 100.]
n_replicas = len(T_i)
ho = testsystems.HarmonicOscillator()
system = ho.system
positions = ho.positions
states = [
ThermodynamicState(system=system, temperature=T_i[i])
for i in range(n_replicas)
]
coordinates = [positions] * n_replicas
mpicomm = dummympi.DummyMPIComm()
parameters = {"number_of_iterations": 1000}
replica_exchange = ReplicaExchange.create(states,
coordinates,
nc_filename,
mpicomm=mpicomm,
parameters=parameters)
replica_exchange.run()
u_permuted = replica_exchange.database.ncfile.variables["energies"][:]
s = replica_exchange.database.ncfile.variables["states"][:]
u = permute_energies(u_permuted, s)
u0 = np.array([[ho.reduced_potential_expectation(s0, s1) for s1 in states]
for s0 in states])
l0 = np.log(
u0
) # Compare on log scale because uncertainties are proportional to values
l1 = np.log(u.mean(0))
eq(l0, l1, decimal=1)
def test_get_traj():
nc_filename = tempfile.mkdtemp() + "/out.nc"
T_min = 300.0 * unit.kelvin
T_i = [T_min, T_min * 1.01, T_min * 1.1]
n_replicas = len(T_i)
ho = testsystems.AlanineDipeptideExplicit()
system = ho.system
positions = ho.positions
states = [
ThermodynamicState(system=system, temperature=T_i[i])
for i in range(n_replicas)
]
coordinates = [positions] * n_replicas
mpicomm = dummympi.DummyMPIComm()
parameters = {"number_of_iterations": 3}
replica_exchange = ReplicaExchange.create(states,
coordinates,
nc_filename,
mpicomm=mpicomm,
parameters=parameters)
replica_exchange.run()
db = replica_exchange.database
prmtop_filename = testsystems.get_data_filename(
"data/alanine-dipeptide-explicit/alanine-dipeptide.prmtop")
crd_filename = testsystems.get_data_filename(
"data/alanine-dipeptide-explicit/alanine-dipeptide.crd")
trj0 = md.load_restrt(crd_filename, top=prmtop_filename)
db.set_traj(trj0)
trj1 = db.get_traj(state_index=0)
trj2 = db.get_traj(replica_index=0)
pdb_filename = "./1vii.pdb"
temperature = 300 * u.kelvin
friction = 0.3 / u.picosecond
timestep = 2.0 * u.femtosecond
forcefield = app.ForceField("amber10.xml", "tip3p.xml")
pdb = app.PDBFile(pdb_filename)
model = app.modeller.Modeller(pdb.topology, pdb.positions)
model.addSolvent(forcefield, padding=0.01 * u.nanometer)
system = forcefield.createSystem(
model.topology, nonbondedMethod=app.PME, nonbondedCutoff=1.0 * u.nanometers, constraints=app.HAngles
)
states = [ThermodynamicState(system=system, temperature=T_i[i]) for i in range(n_replicas)]
coordinates = [model.getPositions()] * n_replicas
# database = repex.netcdf_io.NetCDFDatabase(nc_filename, states, coordinates)
# replica_exchange = ReplicaExchange(states, coordinates, nc_filename)
# replica_exchange = ReplicaExchange.create_repex(states, coordinates, nc_filename, mpicomm=MPI.COMM_WORLD, **{})
replica_exchange = ReplicaExchange.resume_repex(nc_filename, mpicomm=MPI.COMM_WORLD, **{})
replica_exchange.number_of_iterations = 30
replica_exchange.run()
temperature = 300 * u.kelvin
friction = 0.3 / u.picosecond
timestep = 2.0 * u.femtosecond
forcefield = app.ForceField("amber10.xml", "tip3p.xml")
pdb = app.PDBFile(pdb_filename)
model = app.modeller.Modeller(pdb.topology, pdb.positions)
model.addSolvent(forcefield, padding=0.01 * u.nanometer)
system = forcefield.createSystem(model.topology,
nonbondedMethod=app.PME,
nonbondedCutoff=1.0 * u.nanometers,
constraints=app.HAngles)
states = [
ThermodynamicState(system=system, temperature=T_i[i])
for i in range(n_replicas)
]
coordinates = [model.getPositions()] * n_replicas
#database = repex.netcdf_io.NetCDFDatabase(nc_filename, states, coordinates)
#replica_exchange = ReplicaExchange(states, coordinates, nc_filename)
#replica_exchange = ReplicaExchange.create_repex(states, coordinates, nc_filename, **{})
replica_exchange = ReplicaExchange.resume_repex(nc_filename, **{})
replica_exchange.number_of_iterations = 20
replica_exchange.run()
T_i = [ T_min + (T_max - T_min) * (np.exp(float(i) / float(n_replicas-1)) - 1.0) / (np.e - 1.0) for i in range(n_replicas) ]
pdb_filename = "./1vii.pdb"
temperature = 300 * u.kelvin
friction = 0.3 / u.picosecond
timestep = 2.0 * u.femtosecond
forcefield = app.ForceField("amber10.xml", "tip3p.xml")
pdb = app.PDBFile(pdb_filename)
model = app.modeller.Modeller(pdb.topology, pdb.positions)
model.addSolvent(forcefield, padding=0.01 * u.nanometer)
system = forcefield.createSystem(model.topology, nonbondedMethod=app.PME, nonbondedCutoff=1.0 * u.nanometers, constraints=app.HAngles)
states = [ ThermodynamicState(system=system, temperature=T_i[i]) for i in range(n_replicas) ]
coordinates = [model.getPositions()] * n_replicas
#database = repex.netcdf_io.NetCDFDatabase(nc_filename, states, coordinates)
#replica_exchange = ReplicaExchange(states, coordinates, nc_filename)
#replica_exchange = ReplicaExchange.create_repex(states, coordinates, nc_filename, mpicomm=MPI.COMM_WORLD, **{})
replica_exchange = ReplicaExchange.resume_repex(nc_filename, mpicomm=MPI.COMM_WORLD, **{})
replica_exchange.number_of_iterations = 30
replica_exchange.run()
T_i = [ T_min + (T_max - T_min) * (np.exp(float(i) / float(n_replicas-1)) - 1.0) / (np.e - 1.0) for i in range(n_replicas) ]
pdb_filename = "./1vii.pdb"
temperature = 300 * u.kelvin
friction = 0.3 / u.picosecond
timestep = 2.0 * u.femtosecond
forcefield = app.ForceField("amber10.xml", "tip3p.xml")
pdb = app.PDBFile(pdb_filename)
model = app.modeller.Modeller(pdb.topology, pdb.positions)
model.addSolvent(forcefield, padding=0.01 * u.nanometer)
system = forcefield.createSystem(model.topology, nonbondedMethod=app.PME, nonbondedCutoff=1.0 * u.nanometers, constraints=app.HAngles)
states = [ ThermodynamicState(system=system, temperature=T_i[i]) for i in range(n_replicas) ]
coordinates = [model.getPositions()] * n_replicas
#database = repex.netcdf_io.NetCDFDatabase(nc_filename, states, coordinates)
#replica_exchange = ReplicaExchange(states, coordinates, nc_filename)
#replica_exchange = ReplicaExchange.create_repex(states, coordinates, nc_filename, **{})
replica_exchange = ReplicaExchange.resume_repex(nc_filename, **{})
replica_exchange.number_of_iterations = 20
replica_exchange.run()
T_i = [ T_min + (T_max - T_min) * (math.exp(float(i) / float(n_replicas-1)) - 1.0) / (math.e - 1.0) for i in range(n_replicas) ]
pdb_filename = "1VII.pdb"
temperature = 300 * u.kelvin
friction = 0.3 / u.picosecond
timestep = 2.0 * u.femtosecond
forcefield = app.ForceField("amber10.xml", "tip3p.xml")
pdb = app.PDBFile(pdb_filename)
model = app.modeller.Modeller(pdb.topology, pdb.positions)
model.addSolvent(forcefield, padding=0.4 * u.nanometer)
system = forcefield.createSystem(model.topology, nonbondedMethod=app.PME, nonbondedCutoff=1.0 * u.nanometers, constraints=app.HAngles)
states = [ ThermodynamicState(system=system, temperature=T_i[i]) for i in range(n_replicas) ]
simulation = ReplicaExchange(states, [model.getPositions()] * n_replicas, nc_filename) # initialize the replica-exchange simulation
simulation.minimize = False
simulation.number_of_iterations = 2 # set the simulation to only run 2 iterations
simulation.timestep = 2.0 * u.femtoseconds # set the timestep for integration
simulation.nsteps_per_iteration = 50 # run 50 timesteps per iteration
simulation.run() # run the simulation
database = repex.netdf_io.NetCDFDatabase(nc_filename)
simulation = ReplicaExchange(states, [model.getPositions()] * n_replicas, database) # initialize the replica-exchange simulation