openpathsampling.high_level.network.MISTISNetwork

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

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)

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