Package: pygwb
pygwbpygwb: A python-based, user-friendly library for gravitational-wave background (GWB) searches with ground-based interferometers.pygwbprovides a modular and flexible codebase to analyse laser interferometer data and design a GWB search pipeline. It is tailored to current ground-based interferometers: LIGO Hanford, LIGO Livingston, and Virgo, but can be generalized to other configurations. It is based on the existing packagesgwpyandbilby, for optimal integration with widely-used GW data anylsis tools.pygwbalso includes a set of pre-packaged analysis scripts which may be used to analyse data and perform large-scale searches on a high-performance computing cluster efficiently.DocumentationInstallation instructionsEssentials to supportpygwbare present in live igwn conda environmentshttps://computing.docs.ligo.org/conda/More precisely, current dependencies arenumpyscipy>=1.8.0matplotlibcornergwpy>=3.0.1bilby>=1.4astropy>=5.2lalsuite>=7.3gwdetchargwsummpycondorlogurujson5seabornModulesThe code is structured into a set of modules and objects.detector.py: contains theInterferometerobject. TheInterferometermanages data reading, preprocessing, and PSD estimation.baseline.py: contains theBaselineobject. TheBaselineis the core manager object in the stochastic analysis.network.py:  contains theNetworkobject. TheNetworkis used to combine results from indibidualBaselinesas well as simulating data across anInterferometernetwork.preprocessing.py: methods for initial data-conditioning steps (high-pass filter and downsampling) on data from an individual detector. Supports importing public, private, or local data.spectral.py: methods to calculate CSDs and PSDs for sub-segments in a dataset, made of coincident time segments for a pair of detectors.postprocessing.py: methods to combine individual segment cross-correlation spectrograms into a final spectrum, in units of fractional energy density.omega_spectra.py: contains theOmegaSpectrumandOmegaSpectrogramobjects.pe.py: contains model objects to perform pe withBilby.statistical_checks.py: Contains theStatisticalChecksobject, and methods to run statistical checks on results from an analysis run.simulator.py: Contains theSimulatorobject, which can simulate data for a set of detectors.delta_sigma_cut.py: Methods to perform the delta-sigma data quality cut.notch.py: Contains theStochNotchandStochNotchListobjects, which store information about frequency notches to be applied to the analyzed data spectra.constants.py: contains numerical values of constants used throughout the codebase.orfs.py: Methods to calcuate overlap reduction functions.parameters.py: Contains theParametersdataclass.util.py: contains miscellaneous useful functions used throughout the codebase.ScriptsA set of scripts are included and maintained to run every-day stochastic tasks.pygwb_pipe: runs the cross-correlation stochastic analysis over data from selected detector pair, within the timeframes requested.pygwb_combine: combines over multiplepygwb_pipeoutput files. Useful when running long analyses in parallel.pygwb_pe: runs parameter estimation on desired model.pygwb_stats: produces regular statistical checks output.pygwb_dag: supports the creation of a dag file for condor job submission.