openpathsampling.engines.toy.ToyEngine

class openpathsampling.engines.toy.ToyEngine(options, topology)

Engine for toy models. Mostly used for 2D examples.

Parameters:

• options (dict) –

  A dictionary providing additional settings. Keys can be

  ’integ’ToyIntegrator

  the integrator for this engine

  ’n_frames_max’int

  the maximum number of frames allowed for a returned trajectory, default is 5000

  ’n_steps_per_frame’int

  number of integration steps per returned snapshot, default is 10.

• topology (ToyTopology) – object which includes masses, potential energy surface, and the dimensions n_atoms and n_spatial; plays a role similar to a topology in molecular mechanics

pes

potential energy surface

Type:

PES

mass

mass of each atom

Type:

array-like

snapshot_timestep

time step between reported snapshots

Type:

float

current_snapshot

the current state of the system, as a snapshot

Type:

Snapshot

__init__(options, topology)

Create an empty DynamicsEngine object

Notes

The purpose of an engine is to create trajectories and keep track of the results. The main method is ‘generate’ to create a trajectory, which is a list of snapshots and then can store the in the associated storage. In the initialization this storage is created as well as the related Trajectory and Snapshot classes are initialized.

Methods

__init__(options, topology)	Create an empty DynamicsEngine object
args()	Return a list of args of the __init__ function of a class
base()	Return the most parent class actually derived from StorableObject
check_snapshot_type(snapshot)
count_weaks()	Return number of objects subclassed from StorableObject still in memory
descendants()	Return a list of all subclassed objects
fix_name()	Set the objects name to be immutable.
from_dict(dct)	Reconstruct an object from a dictionary representaiton
generate(snapshot[, running, direction])	Generate a trajectory consisting of ntau segments of tau_steps in between storage of Snapshots.
generate_n_frames([n_frames])	Generates n_frames, from but not including the current snapshot.
generate_next_frame()
get_uuid()
has_constraints()
idx(store)	Return the index which is used for the object in the given store.
is_valid_snapshot(snapshot)	Test the snapshot to be valid.
iter_generate(initial[, running, direction, ...])	Return a generator that will generate a trajectory, returning the current trajectory in given intervals
n_degrees_of_freedom()
named(name)	Name an unnamed object.
objects()	Returns a dictionary of all storable objects
reverse_uuid()
ruuid(uid)
set_as_default()
set_observer(active)	(De-)Activate observing creation of storable objects
start([snapshot])
stop(trajectory)	Nothing special needs to be done for direct-control simulations when you hit a stop condition.
stop_conditions(trajectory[, ...])	Test whether we can continue; called by generate a couple of times, so the logic is separated here.
to_dict()	Convert object into a dictionary representation

Attributes

ACTIVE_LONG
BACKWARD
CREATION_COUNT
FORWARD
INSTANCE_UUID
base_cls	Return the base class
base_cls_name	Return the name of the base class
clear_snapshot_cache
cls	Return the class name as a string
current_snapshot
default_name	Return the default name.
default_options
dimensions
ignore_linear_momentum
is_named	True if this object has a custom name.
mass
n_steps_per_frame
name	Return the current name of the object.
observe_objects
pes
snapshot_timestep
units