Pointlike Tutorial: Prerequisite Steps

Assumptions

For the purposes of this tutorial, it is assumed that you are:

• running on a SLAC Central Linux RHEL5-64 machine in a bash shell from within your data directory.

• using ScienceTools-09-23-02, or higher.

Caveats: As of 05/23/2011, when this was written, ScienceTools-09-23-01 was the highest release version and did not incorporate the latest changes to pointlike. Therefore, it was only with the then LATEST version of the ScienceTools that you could:

• avoid a problem with CALDB, the workaround of which is noticed in the

• have access to the FTOOLS and the GLAST_EXT libraries.
  

1. Get the data.

2. Run gtselect.

3. Select GTIs (using gtmktime).

Note: Steps 1 and 2, enable you to eliminate photons coming from the Earth limb by applying a zenith angle cut of 105^o; gtmktime also updates the Good Time Intervals (GTIs) to match the FT2 data.

For a more detailed discussion, see Agreed procedures for data preparation: Removing Earth's Albedo and Correcting GTIs.

4. Create an exposure cube (using gtltcube).

Note: gtltcube outputs an expCube.fits file, a HealPix table covering the full sky of the integrated livetime as a function.

5. Create a source model file.

1. Get the data.

1. Setup SLAC Central Linux.
2. Get 6 months of data using the new AstroServer and copy the data to your data subdirectory.
   
   Note: For the purposes of this tutorial, we used the same FT1 and FT2 files that are used in the pyLikelihood tutorials.
   

• Job Name — enter a meaningful name for your job (e.g., pyLike_6mosData_binned)
• Event Sample — select p6_public_v2
• Energy Range — Min: 100 Max:300000
• Time Range — Min: 243756000 Max: 259308000
• Position — RA: 343.6566 DEC: 16.1494
• Radius — 15.0 degrees
• Event Classes — Diffuse
• Output — FT2 (fits).
• Output — FT1 (fits) FT2 (fits)
• Debug Mode — False
• User Comment — optional
• Click on the Proceed button

If you wish to use the same files that are used in this tutorial, you can download them here (note that these are the same data files used for the pyLikelihood Binned Analysis):

http://www.slac.stanford.edu/exp/glast/workbook/sciToolsData/pointlike_tutorial/

Available files include:

• pyLike_6mosData_binned-ft1.fits (6.6 MB)
• pyLike_6mosData_binned-ft2-30s.fits (57.8 MB)
• example_3C454-srcModel.xml
  
  Note: 3C454.3 is EMS 1524.
  
  
• gll_iem_v02.txt
• isotropic_iem_v02.txt
• pointlike_test.py
  
• 3C454-ft1.fits
• 3C454_GTI.fits
• 3C454-expCube.fits

1. Run gtselect as follows:

Note: Since we obtained our data from the Astro Data server and are only running gtselect to filter out any data greater than 105^o, the maximum zenith angle, we could simply enter: Input FT1 file; Output FT1 file; radius of the new search region [180]; and maximum zenith angle value [105].

2. Verify that the output file is now in your work directory.

Tip: Use gtvcut if you wish to view the Data SubSpace Keywords. (See gtvcut Help file; also see Data SubSpace Keywords.

1. Run gtltcube.

2. Verify that the output file is now in your work data subdirectory.

5. Create a Source Model File

1. Get extragalactic diffuse file (e.g., isotropic_iem_v02.txt) and place it in your data subdirectory.

2. Get galactic diffuse file (e.g., gll_iem_v02.fit) and place it in your data subdirectory.

3. Create source model file (see example_3C454-srcModel.xml) and place it in your data subdirectory.