group

Synopsis

Turn on the grouping for a PHA data set.

group(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` set of routines has been used to dynamically re-group the data. The `ungroup` function removes this grouping (however it was created). The `group` function re-applies this grouping. The grouping scheme can be changed dynamically, using the group_xxx series of routines.

Examples

Example 1

Group the data in the default data set:

>>> group()
>>> get_data().grouped
True

Example 2

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

>>> group('core', bkg_id=1)
>>> get_bkg('core', bkg_id=1).grouped
True

Example 3

The data is fit using the ungrouped data, and then plots of the data and best-fit, and the residuals, are created. The first plot uses the ungrouped data, and the second plot uses the grouped data.

>>> ungroup()
>>> fit()
>>> plot_fit_resid()
>>> group()
>>> plot_fit_resid()

PARAMETERS

The parameters for this function are:

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 `group` , anything that uses the data set - such as a plot, fit, or error analysis - will use the grouped data values. Models should be re-fit if `group` is called; the increase in the signal of the bins may mean that a chi-square statistic can now be used.

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 `group` command does not create this information; this is either created by modifying the PHA file before it is read in, or by using the group_xxx routines once the data has been loaded.

The grouped field of a PHA data set is set to True when the data is grouped.

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

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_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, ungroup, unpack_ascii, unpack_data

filtering

get_filter, ignore, ignore2d, ignore2d_id, ignore_bad, ignore_id, load_filter, notice, notice2d, notice2d_id, notice_id, set_filter, show_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