openpathsampling.analysis.ChannelAnalysis

class openpathsampling.analysis.ChannelAnalysis(steps, channels, replica=0)

Analyze path sampling simulation for multiple channels.

User defines several channels (e.g., mechanisms) as Ensemble objects. This checks which channels each path satisfies, and provides analysis of switching and residence.

Parameters:

• steps (iterable of MCStep) – the steps to analyze

• channels (dict of {string: Ensemble}) – names (keys) and ensembles (values) representing subtrajectories of the channels of interest

• replica (int) – replica ID to analyze from the steps, default is 0.

__init__(steps, channels, replica=0)

Methods

__init__(steps, channels[, replica])
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_uuid()
idx(store)	Return the index which is used for the object in the given store.
label_to_string(label)	Convert set of string/None to comma-separated string.
labels_by_step([treat_multiples])	Prepare internally stored results for primary analysis routines.
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
status(step_number)	Reports which channel(s) are associated with a given step number.
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
residence_times	Dict[string, List[int]]: number of steps spent in each channel for each "stay" in that channel; allows calculations of distribution properties.
switching_matrix	pandas.DataFrame: number of switches from one channel to another.
total_time	Dict[string, int]: total number of steps spent in each channel for each "stay" in that channel.
treat_multiples	method for handling paths that match multiple channels