set_grouping¶

sherpa.astro.ui.set_grouping(id, val=None, bkg_id=None)¶

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

A group is indicated by a sequence of flag values starting with 1 and then -1 for all the channels in the group, following [1]. Setting the grouping column automatically turns on the grouping flag for that 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. val (array of int) – This must be an array of grouping values of the same length as the data array. bkg_id (int or str, optional) – Set to group the background associated with the data set.
Raises:	`sherpa.utils.err.ArgumentErr` – If the data set does not contain a PHA data set.

See also

fit(): Fit one or more data sets.
get_grouping(): Return the grouping flags for a PHA data set.
group(): Turn on the grouping for a PHA data set.
group_adapt(): Adaptively group to a minimum number of counts.
group_adapt_snr(): Adaptively group to a minimum signal-to-noise ratio.
group_bins(): Group into a fixed number of bins.
group_counts(): Group into a minimum number of counts per bin.
group_snr(): Group into a minimum signal-to-noise ratio.
group_width(): Group into a fixed bin width.
load_grouping(): Load the grouping scheme from a file and add to a PHA data set.
set_quality(): Apply a set of quality flags to a PHA data set.
ungroup(): Turn off the grouping for 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 val parameter. If given two un-named arguments, then they are interpreted as the id and val parameters, respectively.

References

[1]	Arnaud., K. & George, I., “The OGIP Spectral File Format”, http://heasarc.gsfc.nasa.gov/docs/heasarc/ofwg/docs/spectra/ogip_92_007/ogip_92_007.html

Examples

Copy the grouping array from data set 2 into the default data set:

>>> grp = get_data(2).grouping
>>> set_grouping(grp)

Copy the grouping from data set “src1” to the source and background data sets of “src2”:

>>> grp = get_data("src1").grouping
>>> set_grouping("src2", grp)
>>> set_grouping("src2", grp, bkg_id=1)