openpathsampling.analysis.ChannelAnalysis

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

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)[source]

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