openpathsampling.pathmover.ConditionalSequentialMover

class openpathsampling.pathmover.ConditionalSequentialMover(movers)[source]

Performs each move in its movers list until complete or until one is not accepted. If any move in not accepted, all previous samples are updated to have set their acceptance to False.

For example, this would be used to create a minus move, which consists of first a replica exchange and then a shooting (extension) move. If the replica exchange fails, the move is aborted before doing the dynamics.

ConditionalSequentialMover only works if there is a single active sample per replica.

__init__(movers)
Parameters

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

Methods

__init__(movers)

param movers

the list of pathmovers to be run in sequence

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