def __init__(self, options, topology):
if 'n_spatial' not in options:
options['n_spatial'] = topology.n_spatial
options['n_atoms'] = 1
snapshot_dimensions = {
'n_atoms': topology.n_atoms,
'n_spatial': topology.n_spatial
}
descriptor = SnapshotDescriptor.construct(
snapshot_class=Snapshot, snapshot_dimensions=snapshot_dimensions)
super(ToyEngine, self).__init__(options=options, descriptor=descriptor)
self.topology = topology
self._mass = None
self._minv = None
self.positions = None
self.velocities = None
self._mass = np.array(topology.masses)
self._pes = topology.pes
self._minv = 1.0 / self._mass
def __init__(self, options, topology):
if 'n_spatial' not in options:
options['n_spatial'] = topology.n_spatial
options['n_atoms'] = 1
snapshot_dimensions = {
'n_atoms': topology.n_atoms,
'n_spatial': topology.n_spatial
}
descriptor = SnapshotDescriptor.construct(
snapshot_class=Snapshot,
snapshot_dimensions=snapshot_dimensions
)
super(ToyEngine, self).__init__(
options=options,
descriptor=descriptor
)
self.topology = topology
self._mass = None
self._minv = None
self.positions = None
self.velocities = None
self._mass = np.array(topology.masses)
self._pes = topology.pes
self._minv = 1.0 / self._mass
def __init__(self, topology):
descriptor = SnapshotDescriptor.construct(
Snapshot, {
'n_atoms': topology.n_atoms,
'n_spatial': topology.n_spatial
})
super(NoEngine, self).__init__(descriptor=descriptor)
self.topology = topology
def to_descriptor(self):
"""
Helper function to fast create a descriptor
Returns
-------
:obj:`SnapshotDescriptor`
"""
return SnapshotDescriptor.construct(ToySnapshot, {
'n_atoms': self.n_atoms,
'n_spatial': self.n_spatial
})
def __init__(self, topology):
descriptor = SnapshotDescriptor.construct(
Snapshot,
{
'n_atoms': topology.n_atoms,
'n_spatial': topology.n_spatial
}
)
super(NoEngine, self).__init__(
descriptor=descriptor
)
self.topology = topology
def to_descriptor(self):
"""
Helper function to fast create a descriptor
Returns
-------
:obj:`SnapshotDescriptor`
"""
return SnapshotDescriptor.construct(
ToySnapshot,
{
'n_atoms': self.n_atoms,
'n_spatial': self.n_spatial
}
)
def __init__(
self,
topology,
system,
integrator,
openmm_properties=None,
options=None):
"""
Parameters
----------
topology : openpathsampling.engines.openmm.MDTopology
a template snapshots which provides the topology object to be used
to create the openmm engine
system : simtk.openmm.app.System
the openmm system object
integrator : simtk.openmm.Integrator
the openmm integrator object
openmm_properties : dict
optional setting for creating the openmm simuation object. Typical
keys include GPU floating point precision
options : dict
a dictionary that provides additional settings for the OPS engine.
Allowed are
'n_steps_per_frame' : int, default: 10
the number of integration steps per returned snapshot
'n_frames_max' : int or None, default: 5000,
the maximal number of frames allowed for a returned
trajectory object
`platform` : str, default: `fastest`,
the openmm specification for the platform to be used,
also 'fastest' is allowed which will pick the currently
fastest one available
Notes
-----
the `n_frames_max` does not limit Trajectory objects in length. It only
limits the maximal length of returned trajectory objects when this
engine is used.
"""
self.system = system
self.integrator = integrator
self.topology = topology
dimensions = {
'n_atoms': topology.n_atoms,
'n_spatial': topology.n_spatial
}
descriptor = SnapshotDescriptor.construct(
Snapshot,
dimensions
)
super(OpenMMEngine, self).__init__(
options=options,
descriptor=descriptor
)
if openmm_properties is None:
openmm_properties = {}
self.openmm_properties = openmm_properties
# set no cached snapshot
self._current_snapshot = None
self._current_momentum = None
self._current_configuration = None
self._current_box_vectors = None
self._simulation = None
def __init__(self,
topology,
system,
integrator,
openmm_properties=None,
options=None):
"""
Parameters
----------
topology : openpathsampling.engines.openmm.MDTopology
a template snapshots which provides the topology object to be used
to create the openmm engine
system : simtk.openmm.app.System
the openmm system object
integrator : simtk.openmm.Integrator
the openmm integrator object
openmm_properties : dict
optional setting for creating the openmm simuation object. Typical
keys include GPU floating point precision
options : dict
a dictionary that provides additional settings for the OPS engine.
Allowed are
'n_steps_per_frame' : int, default: 10
the number of integration steps per returned snapshot
'n_frames_max' : int or None, default: 5000,
the maximal number of frames allowed for a returned
trajectory object
`platform` : str, default: `fastest`,
the openmm specification for the platform to be used,
also 'fastest' is allowed which will pick the currently
fastest one available
Notes
-----
the `n_frames_max` does not limit Trajectory objects in length. It only
limits the maximal length of returned trajectory objects when this
engine is used.
"""
self.system = system
self.integrator = integrator
self.topology = topology
dimensions = {
'n_atoms': topology.n_atoms,
'n_spatial': topology.n_spatial
}
descriptor = SnapshotDescriptor.construct(Snapshot, dimensions)
super(OpenMMEngine, self).__init__(options=options,
descriptor=descriptor)
if openmm_properties is None:
openmm_properties = {}
self.openmm_properties = openmm_properties
# set no cached snapshot
self._current_snapshot = None
self._current_momentum = None
self._current_configuration = None
self._current_box_vectors = None
self._simulation = None
