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Diagnostic tools for the advanced LIGO timing distribution system.

Project description

# Introduction to GECo Statistics Reports

[![Documentation Status](https://readthedocs.org/projects/geco-statistics/badge/?version=latest)](http://geco-statistics.readthedocs.org/en/latest/?badge=latest) [ ![Codeship Status for stefco/geco_stat](https://codeship.com/projects/e9762300-bd59-0133-0ed3-2a1d867cc1c8/status?branch=master)](https://codeship.com/projects/136547)

## Purpose

geco_stat can be used to easily generate histograms, statistics, and anomaly reports for timing signals generated by LIGO interferometers. It is meant to simplify the handling of massive amounts of diagnostic data by providing a simple, organized interface to relevant statistics, easy progress tracking for large jobs, effortless data visualization, and convenient ways to combine reports, so that very long timeseries can be efficiently analyzed in parallel and then recombined into single, monolithic reports covering entire eras.

Future versions of geco_statistics will also provide tools for automating report generation, reducing the amount of effort that has to go into creating reports on LIGO’s functioning.

## Dependencies

This is a python-2.6 compatible Python module intended for use in LIGO production environments. Its python dependencies are minimal, which means it should work out of the box on most python distributions for viewing and manipulating existing reports generated using the package. At time of writing, generating new reports requires tools installed in LIGO production environments; it is intended primarily to be run on LIGO servers, though future implementations may integrate remote access tools.

If you are just interested in viewing existing diagnostic report data, you can use Python, though iPython is recommended for interactive use. [You can install iPython from the project website.](http://ipython.org) If you are running this module on a LIGO production environment, no additional dependencies should be necessary.

You can get around any of these problems by just running create_virtualenv.sh (though this does require virtualenv) and then running source env/bin/activate, after which python will work just fine.

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