Utilities for Metropolis-Hastings random walk tasks (tomographer.mhrwtasks)

class tomographer.BinningAnalysis

A dummy class whose sole purpose is to expose the following constants to Python code.

CONVERGED

The error bar has converged over the different binning levels, the error bar can be considered reliable.

NOT_CONVERGED

The error bar has not converged over the different binning levels, and it should not be considered as reliable.

UNKNOWN_CONVERGENCE

The convergence of the error bar over the different binning levels is uknown, or couldn’t be determined. It may or may not be reliable.

Utilities for tasks running Metropolis-Hastings random walks. These classes shouldn’t be used directly; rather, corresponding instances are returned by, e.g., tomographer.tomorun.tomorun().

class tomographer.mhrwtasks.MHRandomWalkValueHistogramTaskResult

Bases: object

The result of an executed Metropolis-Hastings random walk task.

This class interfaces the corresponding C++ class Tomographer::MHRWTasks::MHRandomWalkTaskResult, when specialized to the Tomographer::ValueHistogramWithErrorBarsMHRWStatsCollector stats collector type.

This class is pickleable.

stats_collector_result

An object of type ValueHistogramWithBinningMHRWStatsCollectorResult detailing the result of the stats collecting class which is responsible for determining the final histogram, and carrying out the binning analysis to come up with error bars.

mhrw_params

The parameters of the executed random walk, as an MHRWParams instance.

acceptance_ratio

The average acceptance ratio of the random walk (excluding the thermalization sweeps).