Event Analysis Tool - Sample Scripts

Event Analysis Tool - Sample Scripts

Event Analysis Tool QuickStart guide
Event Analysis Tool Package Documentation
More advanced examples (L. Cadonati).

Basic Examples

To execute sample scripts, type scripts line by line or .x <file name>. on the ROOT command line.
Get scripts and data.

All sample data are taken from Metadatabase through GUILD.

**Sample Scripts**
File Name	Description
BasicTS.cc	Read pemLVEA.xml and plot a time series of event rate.
BasicH1D.cc	Read TFClusters.xml and plot histogram of Amplitude, Duration and SNR.
BasicCoinc.cc	Read pemLVEA.xml and pemEX.xml, find coincident events, then plot 2-D histogram of SIZE of each coincident events.
BasicClst.cc	Read glitchMon.xml, make clusters of more than 2 events, then plot time series of cluster order and event rate.

**BasicTS.cc**
	Very simple example. Read events from pemLVEA.xml into a Set container and create a time series of the integrated event rate.

**BasicH1D.cc**
	Read events from TFClusters.xml and create three 1-D histogram of Amplitude, Duration, and SNR. Then, plot those histograms on a DMT graphics pad. The interface of the graphics pad is the same as the one in DTT/DMT viewer. To divide the pad into multiple plots, use "Options..." button on the bottom of the pad. To change plot settings, use an option pad. It comes out by clicking the small triangle button on the left side of each plots.

**BasicCoinc.cc**
	This example gives basic idea to use coincidence algorithm in the Event Tool. First, events from pemLVEA.xml and pemEX.xml are loaded into a Set container. Next, all the events are sorted in chronological order, then the coincidence algorithm is executed. Each coincidence event looks like this. Event(0) and Event(1) hold each of coincided events. In the end , the script makes a 2-D histogram of SIZE of Event(0) and Event(1) and plot it on the ROOT graphics pad.

**BasicClst.cc**
	This script makes clusters of more than two events from glitchMon.xml. First, glitchMon.xml is imported into a Set and creates a time series of event rate. Next, the event set goes through the cluster algorithm. Contents of the event set is replaced by the cluster events. Then, time series of cluster order is created and plot two time series. Cluster event looks like this. Number of events stored in a cluster varies depend on the number of events found within the specified time window.

M. Ito
April 2, 2002