Revision ab5cae54e29175a1ac7672e4a83788ea5c0e77dd authored by Alex Nitz on 06 November 2020, 21:00:02 UTC, committed by GitHub on 06 November 2020, 21:00:02 UTC
* update for gwtc-2 catalog * Update catalog.py
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workflow.rst
.. _workflowhomepage:
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Workflow: the inspiral analysis workflow generator (``pycbc.workflow``)
########################################################################
============
Introduction
============
Pycbc's workflow module is a tool used to create the workflows needed to perform coincident analyses of gravitational-wave data searching for compact-binary-coalescences using matched-filtering.
The pycbc workflow runs through a number of stages, which are designed to be as independent of each other as possible, while also allowing an integrated end-to-end workflow to be constructed.
Documentation of the workflow module and how to run it can be found below.
Please see the `following poster <https://dcc.ligo.org/LIGO-G1400223>`_, presentied at the March LVC meeting, 2014, for an introduction to the workflow module (referred to as "ahope"). Especially see the following top-level workflow generation model.
.. image:: images/workflow_planning.png
:width: 100 %
==============================
Workflow module documentation
==============================
The following contains a list of the sub-modules in pycbc's workflow module, a bried description of what each does, and a link to documentation on how to use each module. Collectively these pages should provide complete details on how to set up a workflow from scratch.
---------------------
Basics and overview
---------------------
The following page gives a description of how the workflow module expects
configuration files to be layed out and how the basic command-line interface
functions. If writing a workflow for the first time we recommend you read
through this page!
.. toctree::
:maxdepth: 1
workflow/initialization
--------------------
Generating segments
--------------------
Obtain the science segments and data-quality segments from making queries to a segment database.
.. toctree::
:maxdepth: 1
workflow/segments
--------------------
Obtaining data
--------------------
Run queries to the datafind server to find the needed frames and test these for
consistency if desired
.. toctree::
:maxdepth: 1
workflow/datafind
----------------------------
Injection generation
----------------------------
Generate injection files for use later in the analysis
.. toctree::
:maxdepth: 1
workflow/injections
----------------------------------
Template bank
----------------------------------
Construct a template bank, or banks, of CBC waveforms that will be used to matched-filter the data with.
.. toctree::
:maxdepth: 1
workflow/template_bank
----------------------------------
Split table
----------------------------------
Split an output file into numerous parts to allow parallel analysis. Normally used to split the template bank up to allow matched-filtering in parallel
.. toctree::
:maxdepth: 1
workflow/splittable
----------------------------------
Matched-filtering
----------------------------------
Perform the matched-filters and calculate any signal-based consistency tests that should be calculated.
.. toctree:: :maxdepth: 1
workflow/matched_filter
----------------------------------
Coincidence
----------------------------------
Determine if "triggers" seen in one detector are also seen in other detectors. Also check for coincidence between time-slid triggers for background evaluation
.. toctree:: :maxdepth: 1
workflow/hdf_coincidence
====================
Method documentation
====================
The documentation for all functions/modules within pycbc.workflow follows, unless you are looking for a specific function, it might be easier to navigate through the section links above.
.. toctree::
pycbc.workflow
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