openpathsampling.analysis.tis.StandardTransitionProbability

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

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)[source]

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