sherpa.astro.ui.ignore_bad(id=None, bkg_id=None)

Exclude channels marked as bad in a PHA data set.

Ignore any bin in the PHA data set which has a quality value that is larger than zero.

Changed in version 4.15.0: The change in the filter is now reported for the dataset, to match the behavior of notice and ignore.

  • id (int or str, optional) – The data set to change. If not given then the default identifier is used, as returned by get_default_id.

  • bkg_id (int or str, optional) – The identifier for the background (the default of None uses the first component).


sherpa.utils.err.DataErr – If the data set has no quality array.

See also


Exclude data from the fit.


Include data in the fit.


Apply a set of quality flags to a PHA data set.


The load_pha command - and others that create a PHA data set - do not exclude these bad-quality bins automatically.

If the data set has been grouped, then calling ignore_bad will remove any filter applied to the data set. If this happens a warning message will be displayed.


Remove any bins that are marked bad in the default data set:

>>> load_pha('src.pi')
>>> ignore_bad()
dataset 1: 1:256 Channel (unchanged)

The data set ‘jet’ is grouped, and a filter applied. After ignoring the bad-quality points, the filter has been removed and will need to be re-applied:

>>> group_counts('jet', 20)
>>> notice_id('jet', 0.5, 7)
dataset jet: 0.00146:14.9504 -> 0.438:13.4612 Energy (keV)
>>> get_filter('jet')
>>> ignore_bad('jet')
WARNING: filtering grouped data with quality flags, previous filters deleted
dataset jet: 0.438:13.4612 -> 0.00146:14.9504 Energy (keV)
>>> get_filter('jet')