gtburstFit

See gtburstFit:

Help | Example

Also see:

Synopsis:

Analyzes burst light curves by applying a Bayesian algorithm to determine the optimum set of blocks to follow the burst profile shape, then optionally fitting a model to the data using the Bayesian Block definitions to determine the number of model components and initial values for the model parameters.

Usage: gtburstfit evfile fitguess amp time0 tau1 tau2 bckgnd

Links:

General Parameters

 

evfile [file]

   

Name of input event file.

Currently, only binned events (binned light curves in a RATE FITS extension) are supported, for both GBM and LAT data. The original events file, containing the event data can be obtained from SLAC's Data Portal. Those event files can be binned using the gtbin tool.

     
 

fitguess [string: AUTO|MAN|CALC]

   

This parameter sets how the initial values for the fit be determined.
(default: AUTO)

Currently there are three options: AUTO, MAN, CALC.

  • In the CALC option, the initial values for the fit process are taken from the Bayesian Blocks. By definition, any peak in the Bayesian Block profile is statistically significant, so the model will include one pulse for each block peak.

For each pulse, the initial value of the amplitude (A) is determined from the height of the block in the peak above the background. The time of the pulse (time0) is the start point of the block peak. The rise coefficient (tau1) and decay cofficient (tau2) are both one half the width of the block peak.

  • In the MAN option, the initial guess for the fit of the amplitude (A), the time of the pulse (time0), the rise coefficient (tau1), decay coefficient (tau2), and background (bckgnd) are set manually using the tool parameters of the same names. A limitation of this mode is that only one pulse may be included in the model.
  • The AUTO option is the same as the CALC option unless the GUI is enabled (gui=yes).

In GUI mode, one can rerun the tool interactively multiple times by clicking the "Run" button.

When fitguess=AUTO, the first time the tool is run the behavior is the same as when fitguess=CALC. However, after the run, you can move the peak parameters (burst time, amplitude and decay time) by clicking and dragging with the left mouse button.

Clicking with the right mouse button will add a new pulse to the model:

  • The first right click sets the pulse start time (time0).
  • The second the peak position (amplitude and tau1).
  • And the third the decay (tau2).

Then, by clicking the Run button, you can rerun the tool with these changes to the initial values.

     
  amp = 0 [double]
    This is the amplitude (A) of pulse.

The model used to fit the data is a constant background added to a sum
of terms of the form:

A * exp(tau1 / (t - time0) + (t - time0) / tau2), (1)

where A is the amplitude of the pulse, time0 is the time of the pulse,
tau1 is the "Rise Coefficient", and tau2 is the "Decay Coefficient" of
the pulse.

     
  time0 = 0 [double]
    This is the start time (time0) of pulse.
     
  tau1 = 0 [double]
    This is the rise coefficient (tau1).
     
  tau2 = 0 [double]
    This is the decay coefficient.
     
  bckgnd = 0 [double]
    This is the constant background rate.
     
  (evtable = RATE) [string]
    Event table extension name. This is a hidden parameter. (default: RATE)
     
  (fit = YES) [bool]
   

If "yes", causes gtburstfit to fit parameters to minimize Chi Square for the deviation from the fit model.

If "no", only the definitions of Bayesian blocks found by the tool will be presented. This is a hidden parameter. (default: yes)

     
  (plot = YES) [bool]
    If "yes", causes gtburstfit to display a plot showing the data, the Bayesian Blocks, which were created for the data, and the results of the fit. (The fit will only be displayed if the fit parameter is set to YES). This is a hidden parameter. (default: yes)
     
  (ncpprior = 9.) [double]
    This number represents a heuristic bias against creating new blocks, used to allow some control over the number of blocks created. If too many (too few) blocks are being created for a given set of data, you can increase (decrease) this parameter value. This is a hidden parameter. (default: 9)
     
  (plotres = NO) [bool]
    If "yes", the tool displays the plot of the residuals. This is a hidden parameter. (default: no)
     
  title = DEFAULT [string]
    This parameter allows the user to include a title for the plot. This is a hidden parameter. (default: DEFAULT)
     
  (chatter)
    This parameter fixes the output verbosity: no screen output (0), nominal screen output (2), maximum verbosity (4). (default: 2)
     
  (clobber = yes)
    If true, an existing file of the same name will be overwritten. This is a hidden parameter. (default: yes)
     
  (debug = no)
   

Activate debugging mode. (default: no)

When debug is "no", all exceptions that are not caught and handled by individual tool-specific code are caught by a top-level exception handler that displays information about the exception and then exits.

When debug is "yes", such exceptions are not caught by the top level code. Instead the tool produces a segmentation violation, which is more useful for debugging. When debugging mode is enabled, the tool produces more verbose output describing any errors or exceptions that are encountered.

     
  (gui = no)
    If "yes", the graphical user Interface (GUI) mode is activated.
(default: no)
     
  (mode = ql)
    Mode of automatic parameters. (default: ql)
     

Algorithms

The model used to fit the data is a constant background added to a sum of terms of the form:

A * exp(tau1 / (t - t0) + (t - t0) / tau2)

The number of these terms is determined automatically by gtburstfit by looking for peaks and valleys in the Bayesian block definitions, and using these to determine the number of peaks detected, and their approximate positions, heights and widths.


Owned by:

James Peachey peachey@milkyway.gsfc.nasa.gov

  Lawrence Brown elwin@milkyway.gsfc.nasa.gov
Last updated by: Chuck Patterson 02/09/2011