openpathsampling.high_level.network.MISTISNetwork

class openpathsampling.high_level.network.MISTISNetwork(trans_info, ms_outers=None, strict_sampling=False)[source]

Multiple interface set TIS network.

Input is given as a list of 4-tuples. Each 4-tuple represents a transition, and is in the order:

(initial_state, interfaces, order_parameter, final_states)

This will create the input_transitions objects.

input_transitions

the transitions given as input

Type

list of TISTransition

sampling_transitions

the transitions used in sampling

Type

list of TISTransition

transitions

the transitions used in analysis

Type

list of TISTransition

Note

The distinction between the three types of transitions in the object are a bit subtle, but important. The input_transitions are, of course, the transitions given in the input. These are A->B transitions, but would allow any other state. The sampling_transitions are what are used in sampling. These are A->any transitions if strict sampling is off, or “A->B & not_others” if strict sampling is on. Finally, the regular transitions are the transitions that are used for analysis (use the sampling ensembles for the interfaces, but also A->B).

Parameters
  • trans_info (list of tuple) – Details of each interface set. 3-tuple in the order (initial_state, interfaces, final_state) where initial_state and final_state are Volumes, and interfaces is an InterfaceSet

  • ms_outers (MSOuterTISInterface or list of MSOuterTISInterface) – mutliple state outer interfaces for this network

  • strict_sampling (bool) – whether the final state from the tuple is the only allowed final state in the sampling; default False

__init__(trans_info, ms_outers=None, strict_sampling=False)[source]

Methods

__init__(trans_info[, ms_outers, ...])

add_ms_outer_interface(ms_outer, transitions)

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

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_state(snapshot)

Find which core state a snapshot is in, if any

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

rate_matrix(steps[, force])

reverse_uuid()

ruuid(uid)

set_fluxes(flux_dictionary)

param flux_dictionary

keys are in the form (state, interface), and values are the

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

all_ensembles

All ensembles in the sampling transitions, including special ensembles.

all_states

analysis_ensembles

Ensembles from the analysis transitions, excluding special ensembles.

analysis_to_sampling

dict mapping analysis transitions to sampling transitions

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.

minus_ensembles

ms_outers

name

Return the current name of the object.

observe_objects

sampling_ensemble_for

dict mapping ensembles (incl.

sampling_ensembles

Ensembles from the sampling transitions, excluding special ensembles.

sampling_to_analysis

dict mapping sampling transitions to analysis transitions

sampling_transitions

The transitions used in sampling