group_width
- sherpa.astro.ui.group_width(id, num=None, bkg_id=None, tabStops=None)
Group into a fixed bin width.
Combine the data so that each bin contains
num
channels. The binning scheme is applied to all the channels, but any existing filter - created by theignore
ornotice
set of functions - is re-applied after the data has been grouped.Changed in version 4.15.1: The filter is now reported, noting any changes the new grouping scheme has made.
- 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
.num (int) – The number of channels to combine into a group.
bkg_id (int or str, optional) – Set to group the background associated with the data set. When
bkg_id
is None (which is the default), the grouping is applied to all the associated background data sets as well as the source data set.tabStops (array of int or bool, optional) – If set, indicate one or more ranges of channels that should not be included in the grouped output. The array should match the number of channels in the data set and non-zero or
True
means that the channel should be ignored from the grouping (use 0 orFalse
otherwise).
- Raises:
sherpa.utils.err.ArgumentErr – If the data set does not contain a PHA data set.
See also
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.
set_grouping
Apply a set of grouping flags to a PHA data set.
set_quality
Apply a set of quality 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
num
parameter. If given two un-named arguments, then they are interpreted as theid
andnum
parameters, respectively. The remaining parameters are expected to be given as named arguments.Unlike
group
, it is possible to callgroup_width
multiple times on the same data set without needing to callungroup
.Unless the requested bin width is a factor of the number of channels (and no
tabStops
parameter is given), then some channels will be “left over”. If this happens, a warning message will be displayed to the screen and the quality value for these channels will be set to 2. This information can be found with theget_quality
command.Examples
Group the default data set so that each bin contains 20 channels:
>>> group_width(20)
Plot two versions of the ‘jet’ data set: the first uses 20 channels per group and the second is 50 channels per group:
>>> group_width('jet', 20) >>> plot_data('jet') >>> group_width('jet', 50) >>> plot_data('jet', overplot=True)
The grouping is applied to the full data set, and then the filter - in this case defined over the range 0.5 to 8 keV - will be applied.
>>> set_analysis('energy') >>> notice(0.5, 8) >>> group_width(50) >>> plot_data()
The grouping is not applied to channels 101 to 149, inclusive:
>>> notice() >>> channels = get_data().channel >>> ign = (channels > 100) & (channels < 150) >>> group_width(40, tabStops=ign) >>> plot_data()