openpathsampling.analysis.tis.StandardTransitionProbability

class openpathsampling.analysis.tis.StandardTransitionProbability(transition, tcp_method, ctp_method)

Calculate the transition probability according to the TCP/CTP split.

The transition probability is the probability that a path that starts from interface A_0 ends in some other state B, and is denoted P(B|A_0). What we call the “standard” approach to calculate this splits that probability into P(B|A_0) = P(B|A_m) P(A_m|A_0), where the first term in the product is the ConditionalTransitionProbability and the second term is determined by the TotalCrossingProbability. In practice, one instance of this object is created for each transition.

Parameters:

• transition (TISTransition) – the transition to calculate the transition probability for

• tcp_method (TotalCrossingProbability) – the object to calculate the total crossing probability function; many details can be modified here including the details of the histograms that are generated or of the method used to combine the histograms

• ctp_method (ConditionalTransitionProbability) – the object to calculate the conditional transition probability (details on which ensembles and which states to analyze can be modified here)

__init__(transition, tcp_method, ctp_method)

Methods

__init__(transition, tcp_method, ctp_method)
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_intermediate_results(tcp, ctp)	Calculate results from intermediates.
from_weighted_trajectories(input_dict)	Calculate results from a 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