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.

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.

The meaning of the grouping column is taken from 1, which says that +1 indicates the start of a bin, -1 if the channel is part of group, and 0 if the data grouping is undefined for all channels.

References

1(1,2)

“The OGIP Spectral File Format”, https://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 and ensure it is applied:

>>> grp = get_grouping(2)
>>> set_grouping(grp)
>>> group()

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

>>> grp = get_grouping("src1")
>>> set_grouping("src2", grp)
>>> set_grouping("src2", grp, bkg_id=1)
>>> group("src2")