openpathsampling.analysis.tis.EnsembleHistogrammer

class openpathsampling.analysis.tis.EnsembleHistogrammer(ensembles, f, hist_parameters)[source]

Generic code to calculate the properly weighted histograms of trajectory properties per ensemble.

Parameters:

ensembles (list of Ensemble) – ensembles to be included in the histogram
f (callable) – the function to be histogrammed
hist_parameters (dict) – allowed keys are ‘bin_width’ and ‘bin_range’; value for ‘bin_width’ is a float; for ‘bin_range’ is a tuple with (left_edge, right_edge) (only left edge is used)

Methods

`__init__`(ensembles, f, hist_parameters)
`args`()	Return a list of args of the __init__ function of a class
`base`()	Return the most parent class actually derived from StorableObject
`calculate`(steps[, ensembles])	Perform the analysis, using steps as input.
`combine_results`(result_1, result_2)	Combine two sets of results from this analysis.
`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
`from_weighted_trajectories`(input_dict)	Calculate results from a weighted trajectories dictionary.
`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
`reverse_uuid`()
`ruuid`(uid)
`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`
`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`
`progress`