def setup(self):
if not HAS_MDTRAJ:
pytest.skip("Unable to import MDTraj")
pytest.importorskip('simtk.unit')
self.mdt = md.load(data_filename("ala_small_traj.pdb"))
top = MDTrajTopology(self.mdt.topology)
self.traj = ops_omm.tools.trajectory_from_mdtraj(self.mdt)
self.cv = MDTrajFunctionCV(md.compute_distances, top,
atom_pairs=[[0, 1]])
def setup(self):
self.ad_pdb = data_filename("ala_small_traj.pdb")
self.yml = "\n".join([
"name: phi",
"type: mdtraj",
"topology: " + self.ad_pdb,
"period_min: -np.pi",
"period_max: np.pi",
"func: {func}",
"kwargs:",
" {kwargs}",
])
self.kwargs = "indices: [[4, 6, 8, 14]]"
def setup(self):
# PES is one-dimensional zero function (y(x) = 0)
pes = toys.LinearSlope(m=[0.0], c=[0.0])
topology = toys.Topology(n_spatial=1, masses=[1.0], pes=pes)
integrator = toys.LeapfrogVerletIntegrator(0.02)
options = {
'integ' : integrator,
'n_frames_max' : 1000,
'n_steps_per_frame' : 1
}
self.engine = toys.Engine(options=options, topology=topology)
# test uses snapshots with different velocities
self.initial_snapshots = [toys.Snapshot(
coordinates=np.array([[0.0]]),
velocities=np.array([[1.0]]),
engine=self.engine),
toys.Snapshot(
coordinates=np.array([[0.1]]),
velocities=np.array([[-1.0]]),
engine=self.engine),
toys.Snapshot(
coordinates=np.array([[-0.2]]),
velocities=np.array([[2.0]]),
engine=self.engine)]
# trajectory length is set to 100 steps
self.l = 100
# reaction coordinate is just x coordinate
rc = paths.FunctionCV("Id", lambda snap : snap.coordinates[0][0])
# state S: [-0.5, 0.5]
self.state_S = paths.CVDefinedVolume(rc, -0.5, 0.5)
# define state labels
self.state_labels = {
"S" : self.state_S,
"NotS" :~self.state_S}
# velocities are not randomized
randomizer = paths.NoModification()
self.filename = data_filename("sshooting_test.nc")
self.storage = paths.Storage(self.filename, mode="w")
self.storage.save(self.initial_snapshots)
self.simulation = SShootingSimulation(
storage=self.storage,
engine=self.engine,
state_S=self.state_S,
randomizer=randomizer,
initial_snapshots=self.initial_snapshots,
trajectory_length=self.l
)
self.simulation.output_stream = open(os.devnull, 'w')
def _make_gromacs_snap(self):
# gromacs-specific
test_dir = data_filename("gromacs_engine")
engine = paths.engines.gromacs.Engine(
gro="conf.gro",
mdp="md.mdp",
top="topol.top",
options={},
base_dir=test_dir,
prefix="proj"
)
snap_file = os.path.join(test_dir, "project_trr", "0000000.trr")
snap = paths.engines.gromacs.ExternalMDSnapshot(
file_name=snap_file,
file_position=2,
engine=engine
)
return snap
def test_build_topology_file(self):
ad_pdb = data_filename("ala_small_traj.pdb")
topology = build_topology(ad_pdb)
assert topology.n_spatial == 3
assert topology.n_atoms == 1651
def setup(self):
if not HAS_MDTRAJ:
pytest.skip()
self.filename = data_filename('ala_small_traj.pdb')
def _make_openmm_snap(self):
mm = pytest.importorskip('simtk.openmm')
traj_file = data_filename('ala_small_traj.pdb')
traj = paths.engines.openmm.tools.ops_load_trajectory(traj_file)
snap = traj[0]
return snap
def setup(self):
# PES is one-dimensional negative slope (y(x) = -x)
pes = toys.LinearSlope(m=[-1.0], c=[0.0])
topology = toys.Topology(n_spatial=1, masses=[1.0], pes=pes)
integrator = toys.LeapfrogVerletIntegrator(0.02)
options = {
'integ': integrator,
'n_frames_max': 1000,
'n_steps_per_frame': 1
}
self.engine = toys.Engine(options=options, topology=topology)
# test uses snapshots with different velocities
# (1) does not ever reach A
# (2) goes form A to S to B
# (3) goes from B to S to A
self.initial_snapshots = [
toys.Snapshot(coordinates=np.array([[0.0]]),
velocities=np.array([[1.0]]),
engine=self.engine),
toys.Snapshot(coordinates=np.array([[0.1]]),
velocities=np.array([[2.0]]),
engine=self.engine),
toys.Snapshot(coordinates=np.array([[-0.2]]),
velocities=np.array([[-2.0]]),
engine=self.engine)
]
# trajectory length is set to 100 steps
self.l = 100
# reaction coordinate is just x coordinate
rc = paths.FunctionCV("Id", lambda snap: snap.coordinates[0][0])
# state A: [-inf, -1]
self.state_A = paths.CVDefinedVolume(rc, float("-inf"), -1.0)
# state B: [1, inf]
self.state_B = paths.CVDefinedVolume(rc, 1.0, float("inf"))
# state S: [-0.5, 0.5]
self.state_S = paths.CVDefinedVolume(rc, -0.5, 0.5)
# define state labels
self.state_labels = {
"A": self.state_A,
"B": self.state_B,
"S": self.state_S,
"None": ~(self.state_A | self.state_B | self.state_S)
}
# velocities are not randomized
randomizer = paths.NoModification()
self.filename = data_filename("sshooting_test.nc")
self.storage = paths.Storage(self.filename, mode="w")
self.storage.save(self.initial_snapshots)
self.simulation = SShootingSimulation(
storage=self.storage,
engine=self.engine,
state_S=self.state_S,
randomizer=randomizer,
initial_snapshots=self.initial_snapshots,
trajectory_length=self.l)
self.simulation.output_stream = open(os.devnull, 'w')
self.simulation.run(n_per_snapshot=1)
self.analysis = SShootingAnalysis(
steps=self.storage.steps,
states=[self.state_A, self.state_B, self.state_S])