load_grouping
- sherpa.astro.ui.load_grouping(id, filename=None, bkg_id: IdType | None = None, *args, **kwargs) None
Load the grouping scheme from a file and add to a PHA data set.
This function sets the grouping column but does not automatically group the data, since the quality array may also need updating. The
group
function will apply the grouping information.- 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 that contains the grouping information. This file can be a FITS table or an ASCII file. Selection of the relevant column depends on the I/O library in use (Crates or AstroPy).
bkg_id (int, str, or None, optional) – Set if the grouping scheme should be associated with the background associated with the data set.
colkeys (array of str, optional) – An array of the column name to read in. The default is
None
.sep (str, optional) – The separator character. The default is
' '
.comment (str, optional) – The comment character. The default is
'#'
.
See also
get_grouping
Return the grouping array for a PHA data set.
group
Turn on the grouping for a PHA data set.
load_quality
Load the quality array from a file and add to a PHA data set.
save_grouping
Save the grouping scheme to a file.
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 theid
andfilename
parameters, respectively. The remaining parameters are expected to be given as named arguments.There is no check made to see if the grouping array contains valid data.
Examples
When using Crates as the I/O library, select the grouping column from the file ‘src.pi’, and use it to set the values in the default data set:
>>> load_grouping('src.pi[cols grouping]')
Use the
colkeys
option to define the column in the input file:>>> load_grouping('src.pi', colkeys=['grouping'])
Load the first column in ‘grp.dat’ and use it to populate the grouping array of the data set called ‘core’.
>>> load_grouping('core', 'grp.dat')
Use
group_counts
to calculate a grouping scheme for the data set labelled ‘src1’, save this scheme to the file ‘grp.dat’, and then load this scheme in for data set ‘src2’.>>> group_counts('src1', 10) >>> save_grouping('src1', 'grp.dat') >>> load_grouping('src2', 'grp.dat', colkeys=['groups'])