Lighweight python stochastic GWB analysis pipeline
Project description
pygwb
Installation instructions
-
Essentials to support
pygwb
are present in live igwn conda environments https://computing.docs.ligo.org/conda/ -
More precisely, current dependencies are
numpy
scipy==1.8.0
matplotlib
corner
gwpy==3.0.1
bilby
astropy>=4.3.0
lalsuite==7.3
loguru
json5
jinja2==3.0.3
seaborn
Modules
The code is structured into many small modules.
pre-processing.py
applies initial data-conditioning steps (high-pass filter and downsampling) on data from individual detector. Also supports importing simualted data.spectral.py
calculated CSDs and PSDs for each segment in a job (a coincident time segment of a pair of detectors)postprocessing.py
combines the cross-correlation spectrograms into a final spectrum.pe.py
defines classes to perform pe with bilby for various models.constants.py
contains numerical values of constants used throughout the code. Constants should never be redefined elsewhere.util.py
contains miscellaneous useful classes and functionality.
Scripts
A set of scripts are supported 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_pipe
output files. Useful when running long analyses in parallel.pygwb_pe
runs parameter estimation on desired parameters.pygwb_stats
produces regular statistical checks output.
Project details
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