openpathsampling.analysis.tis.ConditionalTransitionProbability

class openpathsampling.analysis.tis.ConditionalTransitionProbability(ensembles, states)[source]

Calculate the conditional transition probability, P(B|A_m)

The conditional transition probablity is the probability that paths from a given interface end in each possible state.

Parameters
  • ensembles (list of Ensemble) – sampled ensembles to calculate the CTP for

  • states (list of Volume) – possible final states for trajectories in the given ensembles

__init__(ensembles, states)[source]

Methods

__init__(ensembles, states)

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 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