Light Curves

lightcurve() can be used to fit a source in a sequence of time bins.

Examples

# Generate a lightcurve with two bins
lc = gta.lightcurve('sourceA', nbins=2)

# Generate a lightcurve with 1-week binning
lc = gta.lightcurve('sourceA', binsz=86400.*7.0)

Reference/API

GTAnalysis.lightcurve(name, **kwargs)

Generate a lightcurve for the named source. The function will complete the basic analysis steps for each bin and perform a likelihood fit for each bin. Extracted values (along with errors) are Integral Flux, spectral model, Spectral index, TS value, pred. # of photons.

Parameters:
  • name (str) – source name
  • binsz (float) – Set the lightcurve bin size in seconds. (default : 86400.0)
  • free_background (bool) – Leave background parameters free when performing the fit. If True then any parameters that are currently free in the model will be fit simultaneously with the source of interest. (default : False)
  • free_radius (float) – Free normalizations of background sources within this angular distance in degrees from the source of interest. If None then no sources will be freed. (default : None)
  • free_sources (list) – List of sources to be freed. These sources will be added to the list of sources satisfying the free_radius selection. (default : None)
  • make_plots (bool) – Generate diagnostic plots. (default : False)
  • nbins (int) – Set the number of lightcurve bins. The total time range will be evenly split into this number of time bins. (default : None)
  • time_bins (list) – Set the lightcurve bin edge sequence in MET. This option takes precedence over binsz and nbins. (default : None)
  • use_local_ltcube (bool) – (default : True)
  • write_fits (bool) – Write the output to a FITS file. (default : True)
  • write_npy (bool) – Write the output dictionary to a numpy file. (default : True)
Returns:

LightCurve – Dictionary containing output of the LC analysis

Return type:

dict