ignore_id

sherpa.astro.ui.ignore_id(ids, lo=None, hi=None, **kwargs)

Exclude data from the fit for a data set.

Select one or more ranges of data to exclude by filtering on the independent axis value. The filter is applied to the given data set, or sets.

Changed in version 4.14.0: Integrated data sets - so Data1DInt and DataPHA when using energy or wavelengths - now ensure that the hi argument is exclusive and better handling of the lo argument when it matches a bin edge. This can result in the same filter selecting a smaller number of bins than in earlier versions of Sherpa.

Parameters
  • ids (int or str, or array of int or str) – The data set, or sets, to use.

  • lo (number or str, optional) – The lower bound of the filter (when a number) or a string expression listing ranges in the form a:b, with multiple ranges allowed, where the ranges are separated by a ,. The term :b means exclude everything up to b (an exclusive limit for integrated datasets), and a: means exclude everything that is higher than, or equal to, a.

  • hi (number, optional) – The upper bound of the filter when lo is not a string.

  • bkg_id (int or str, optional) – The filter will be applied to the associated background component of the data set if bkg_id is set. Only PHA data sets support this option; if not given, then the filter is applied to all background components as well as the source data.

See also

ignore

Exclude data from the fit.

sherpa.astro.ui.ignore2d

Exclude a spatial region from an image.

notice_id

Include data from the fit for a data set.

show_filter

Show any filters applied to a data set.

Notes

The order of ignore and notice calls is important.

The units used depend on the analysis setting of the data set, if appropriate.

To filter a 2D data set by a shape use ignore2d.

Examples

Ignore all data points with an X value (the independent axis) between 12 and 18 for data set 1:

>>> ignore_id(1, 12, 18)

Ignore the range up to 0.5 and 7 and above, for data sets 1, 2, and 3:

>>> ignore_id([1,2,3], None, 0.5)
>>> ignore_id([1,2,3], 7, None)

Apply the same filter as the previous example, but to data sets “core” and “jet”:

>>> ignore_id(["core","jet"], ":0.5,7:")