openpathsampling.pathmover.PartialAcceptanceSequentialMover

class openpathsampling.pathmover.PartialAcceptanceSequentialMover(movers)

Performs each move in its movers list until complete or until one is not accepted. If any move is not accepted, further moves are not attempted, but the previous accepted samples remain accepted.

For example, this would be used to create a bootstrap promotion move, which starts with a shooting move, followed by an EnsembleHop/Replica promotion ConditionalSequentialMover. Even if the EnsembleHop fails, the accepted shooting move should be accepted.

__init__(movers)

Parameters:

movers (list of openpathsampling.PathMover) – the list of pathmovers to be run in sequence

Methods

__init__(movers)
args()	Return a list of args of the __init__ function of a class
base()	Return the most parent class actually derived from StorableObject
count_weaks()	Return number of objects subclassed from StorableObject still in memory
depth_post_order(fnc[, level])	Traverse the tree in post-order applying a function with depth
depth_pre_order(fnc[, level, only_canonical])	Traverse the tree of node in pre-order applying a function
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
get_uuid()
idx(store)	Return the index which is used for the object in the given store.
key(change)
keylist()	Return a list of key : subtree tuples
legal_sample_set(sample_set[, ensembles, ...])	This returns all the samples from sample_set which are in both self.replicas and the parameter ensembles.
map_post_order(fnc, **kwargs)	Traverse the tree in post-order applying a function
map_pre_order(fnc, **kwargs)	Traverse the tree in pre-order applying a function
map_tree(fnc)	Apply a function to each node and return a nested tree of results
move(sample_set)	Run the generation starting with the initial sample_set specified.
move_replica_state(replica_states)
named(name)	Name an unnamed object.
objects()	Returns a dictionary of all storable objects
reverse_uuid()
ruuid(uid)
select_sample(sample_set[, ensembles, replicas])	Returns one of the legal samples given self.replica and the ensemble set in ensembles.
set_observer(active)	(De-)Activate observing creation of storable objects
sub_replica_state(replica_states)	Return set of replica states that a submover might be called with
to_dict()	Convert object into a dictionary representation
tree()	Return the object as a tree structure of nested lists of nodes

Attributes

ACTIVE_LONG
CREATION_COUNT
INSTANCE_UUID
base_cls	Return the base class
base_cls_name	Return the name of the base class
cls	Return the class name as a string
default_name	Return the default name.
ensemble_signature
ensemble_signature_set
identifier	A unique identifier to build the unique key for a position in a tree
in_out	List the input -> output relation for ensembles
input_ensembles	Return a list of possible used ensembles for this mover
is_canonical
is_ensemble_change_mover
is_named	True if this object has a custom name.
name	Return the current name of the object.
observe_objects
output_ensembles	Return a list of possible returned ensembles for this mover
submovers	Returns a list of submovers