# fit_bkg¶

sherpa.astro.ui.fit_bkg(id=None, *otherids, **kwargs)

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

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.

Parameters
• id (int or str, optional) – The data set that provides the background data. If not given then all data sets with an associated background model are fit simultaneously.

• *otherids (sequence of int or str, optional) – Other data sets to use in the calculation.

• outfile (str, optional) – If set, then the fit results will be written to a file with this name. The file contains the per-iteration fit results.

• clobber (bool, optional) – This flag controls whether an existing file can be overwritten (True) or if it raises an exception (False, the default setting).

Raises

sherpa.utils.err.FitErr – If filename already exists and clobber is False.

conf()

Estimate the confidence intervals using the confidence method.

contour_fit()

Contour the fit to a data set.

covar()

Estimate the confidence intervals using the confidence method.

fit()

Fit a model to one or more data sets.

freeze()

Fix model parameters so they are not changed by a fit.

get_fit_results()

Return the results of the last fit.

plot_fit()

Plot the fit results (data, model) for a data set.

image_fit()

Display the data, model, and residuals for a data set in the image viewer.

set_stat()

Set the statistical method.

set_method()

Change the optimization method.

set_method_opt()

Change an option of the current optimization method.

set_bkg_full_model()

Define the convolved background model expression for a PHA data set.

set_bkg_model()

Set the background model expression for a PHA data set.

set_full_model()

Define the convolved model expression for a data set.

set_iter_method()

Set the iterative-fitting scheme used in the fit.

set_model()

Set the model expression for a data set.

show_bkg_source()

Display the background model expression for a data set.

show_bkg_model()

Display the background model expression used to fit a data set.

show_fit()

Summarize the fit results.

thaw()

Allow model parameters to be varied during a fit.

Notes

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

Examples

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

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


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)