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