openpathsampling.analysis.tis.MultiEnsembleSamplingAnalyzer

class openpathsampling.analysis.tis.MultiEnsembleSamplingAnalyzer(ensembles=None)

Abstract class for statistics from MC steps sampling multiple ensembles.

Parameters:

ensembles (list of Ensemble) – ensembles to be used in the calculation; can be overridden by calculate()

__init__(ensembles=None)

Methods

__init__([ensembles])
args()	Return a list of args of the __init__ function of a class
base()	Return the most parent class actually derived from StorableObject
calculate(steps[, ensembles])	Perform the analysis, using steps as input.
combine_results(result_1, result_2)	Combine two sets of results from this analysis.
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
from_weighted_trajectories(input_dict)	Calculate results from weighted trajectories dictionary.
get_uuid()
idx(store)	Return the index which is used for the object in the given store.
named(name)	Name an unnamed object.
objects()	Returns a dictionary of all storable objects
reverse_uuid()
ruuid(uid)
set_observer(active)	(De-)Activate observing creation of storable objects
to_dict()	Convert object into a dictionary representation

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.
is_named	True if this object has a custom name.
name	Return the current name of the object.
observe_objects
progress