Last modified: December 2020

URL: https://cxc.cfa.harvard.edu/sherpa/ahelp/ungroup.html
AHELP for CIAO 4.13 Sherpa v1

ungroup

Context: data

Synopsis

Turn off the grouping for a PHA data set.

Syntax

ungroup(id=None, bkg_id=None)

id - int or str, optional
bkg_id - int or str, optional

Description

A PHA data set can be grouped either because it contains grouping information [1] , which is automatically applied when the data is read in with `load_pha` or `load_data` , or because the group_xxx set of routines has been used to dynamically re-group the data. The `ungroup` function removes this grouping (however it was created).


Examples

Example 1

Ungroup the data in the default data set:

>>> ungroup()
>>> get_data().grouped
False

Example 2

Ungroup the first background component of the 'core' data set:

>>> ungroup('core', bkg_id=1)
>>> get_bkg('core', bkg_id=1).grouped
False

PARAMETERS

The parameters for this function are:

Parameter Definition
id The identifier for the data set to use. If not given then the default identifier is used, as returned by `get_default_id` .
bkg_id Set to ungroup the background associated with the data set.

Notes

PHA data is often grouped to improve the signal to noise of the data, by decreasing the number of bins, so that a chi-square statistic can be used when fitting the data. After calling `ungroup` , anything that uses the data set - such as a plot, fit, or error analysis - will use the original data values. Models should be re-fit if `ungroup` is called; this may require a change of statistic depending on the counts per channel in the spectrum.

The grouping is implemented by separate arrays to the main data - the information is stored in the grouping and quality arrays of the PHA data set - so that a data set can be grouped and ungrouped many times, without losing information.

The grouped field of a PHA data set is set to False when the data is not grouped.

If subtracting the background estimate from a data set, the grouping applied to the source data set is used for both source and background data sets.

References


Bugs

See the bugs pages on the Sherpa website for an up-to-date listing of known bugs.

See Also

data
copy_data, dataspace1d, dataspace2d, datastack, delete_data, fake, get_axes, get_bkg_chisqr_plot, get_bkg_delchi_plot, get_bkg_fit_plot, get_bkg_model_plot, get_bkg_plot, get_bkg_ratio_plot, get_bkg_resid_plot, get_bkg_source_plot, get_counts, get_data, get_data_contour, get_data_contour_prefs, get_data_image, get_data_plot, get_data_plot_prefs, get_dep, get_dims, get_error, get_grouping, get_quality, get_specresp, get_staterror, get_syserror, group, group_adapt, group_adapt_snr, group_bins, group_counts, group_snr, group_width, load_ascii, load_data, load_grouping, load_quality, set_data, set_grouping, set_quality, unpack_ascii, unpack_data
filtering
get_filter, load_filter, set_filter
info
get_default_id, list_data_ids, list_response_ids
modeling
clean
plotting
plot_data, set_xlinear, set_xlog, set_ylinear, set_ylog
saving
save_error, save_filter, save_grouping, save_quality, save_staterror, save_syserror
utilities
calc_data_sum, calc_data_sum2d, calc_ftest, calc_kcorr, calc_mlr, calc_model_sum2d, calc_source_sum2d, get_rate
visualization
contour, contour_data, contour_ratio, histogram1d, histogram2d, image_data, rebin