save_grouping

sherpa.astro.ui.save_grouping(id, filename=None, bkg_id=None, ascii=True, clobber=False)

Save the grouping scheme to a file.

The output is a two-column file, containing the channel and grouping columns from the data set.

Parameters:
  • id (int or str, optional) – The identifier for the data set to use. If not given then the default identifier is used, as returned by get_default_id.

  • filename (str) – The name of the file to write the array to. The format is determined by the ascii argument.

  • bkg_id (int or str, optional) – Set if the grouping array should be taken from the background associated with the data set.

  • ascii (bool, optional) – If False then the data is written as a FITS format binary table. The default is True. The exact format of the output file depends on the I/O library in use (Crates or AstroPy).

  • clobber (bool, optional) – If outfile is not None, then this flag controls whether an existing file can be overwritten (True) or if it raises an exception (False, the default setting).

Raises:

sherpa.utils.err.IOErr – If filename already exists and clobber is False.

See also

get_grouping

Return the grouping array for a PHA data set.

load_quality

Load the quality array from a file and add to a PHA data set.

set_grouping

Apply a set of grouping flags to a PHA data set.

Notes

The function does not follow the normal Python standards for parameter use, since it is designed for easy interactive use. When called with a single un-named argument, it is taken to be the filename parameter. If given two un-named arguments, then they are interpreted as the id and filename parameters, respectively. The remaining parameters are expected to be given as named arguments.

The column names are ‘CHANNEL’ and ‘GROUPS’.

Examples

Save the channel and grouping columns from the default data set to the file ‘group.dat’ as an ASCII file:

>>> save_grouping('group.dat')

Over-write the ‘grp.fits’ file, if it exists, and write out the grouping data from the ‘jet’ data set, as a FITS format file:

>>> save_grouping('jet', 'grp.fits', ascii=False, clobber=True)