Last modified: December 2023

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AHELP for CIAO 4.16 Sherpa


Context: fitting


Fit a model to one or more background PHA data sets.


fit_bkg(id=None, *otherids, **kwargs)

id - int or str, optional
*otherids - sequence of int or str, optional
outfile - str, optional
clobber - bool, optional


Fit only the backgound components of PHA data sets. This can be used to find the best-fit background parameters, which can then be frozen before fitting the data, or to ensure that these parameters are well defined before performing a simultaneous source and background fit.


Example 1

Simultaneously fit all background data sets with models and then store the results in the variable fres:

>>> fit_bkg()
>>> fres = get_fit_results()

Example 2

Fit the background for data sets 1 and 2, then do a simultaneous fit to the source and background data sets:

>>> fit_bkg(1, 2)
>>> fit(1, 2)


The parameters for this function are:

Parameter Definition
id The data set that provides the background data. If not given then all data sets with an associated background model are fit simultaneously.
*otherids Other data sets to use in the calculation.
outfile If set, then the fit results will be written to a file with this name. The file contains the per-iteration fit results.
clobber This flag controls whether an existing file can be overwritten ( True ) or if it raises an exception ( False , the default setting).


This is only for PHA data sets where the background is being modelled, rather than subtracted from the data.


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

See Also