Last modified: December 2023

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AHELP for CIAO 4.16 Sherpa


Context: plotting


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


plot_fit(id=None, replot=False, overplot=False, clearwindow=True,

id - int or str, optional
replot - bool, optional
overplot - bool, optional
clearwindow - bool, optional


This function creates a plot containing the data and the model (including any instrument response) for a data set.


Example 1

Plot the fit results for the default data set:

>>> plot_fit()

Example 2

Overplot the 'core' results on those from the 'jet' data set, using a logarithmic scale for the X axis:

>>> set_xlog()
>>> plot_fit('jet')
>>> plot_fit('core', overplot=True)

Example 3

Keyword arguments can be given to override the plot preferences; for example the following sets the y axis to a log scale, but only for this plot:

>>> plot_fit(ylog=True)

Example 4

The color can be changed for both the data and model using (note that the keyword name and supported values depends on the plot backend; this example assumes that Matplotlib is being used):

>>> plot_fit(color='orange')

Example 5

Draw the fits for two datasets, setting the second one partially transparent (this assumes Matplotlib is used):

>>> plot_fit(1)
>>> plot_fit(2, alpha=0.7, overplot=True)


The parameters for this function are:

Parameter Definition
id The data set. If not given then the default identifier is used, as returned by `get_default_id` .
replot Set to True to use the values calculated by the last call to `plot_fit` . The default is False .
overplot If True then add the data to an existing plot, otherwise create a new plot. The default is False .
clearwindow Should the existing plot area be cleared before creating this new plot (e.g. for multi-panel plots)?


The additional arguments supported by `plot_fit` are the same as the keywords of the dictionary returned by `get_data_plot_prefs` .


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

See Also

get_data_prof, get_data_prof_prefs, get_delchi_prof, get_delchi_prof_prefs, get_fit_prof, get_model_prof, get_model_prof_prefs, get_resid_prof, get_resid_prof_prefs, get_source_prof, get_source_prof_prefs, plot_chart_spectrum, plot_marx_spectrum, prof_data, prof_delchi, prof_fit, prof_fit_delchi, prof_fit_resid, prof_model, prof_resid, prof_source
get_arf_plot, get_bkg_chisqr_plot, get_bkg_delchi_plot, get_bkg_fit_plot, get_bkg_model_plot, get_bkg_plot, get_bkg_ratio_plot, get_bkg_resid_plot, get_bkg_source_plot
fit, simulfit
get_iter_method_name, get_iter_method_opt, list_iter_methods, set_iter_method, set_iter_method_opt
normal_sample, t_sample, uniform_sample
get_cdf_plot, get_energy_flux_hist, get_pdf_plot, get_photon_flux_hist, get_pvalue_plot, get_pvalue_results, get_split_plot, plot, plot_arf, plot_bkg, plot_bkg_chisqr, plot_bkg_delchi, plot_bkg_fit, plot_bkg_fit_delchi, plot_bkg_fit_resid, plot_bkg_model, plot_bkg_ratio, plot_bkg_resid, plot_bkg_source, plot_cdf, plot_chisqr, plot_data, plot_delchi, plot_energy_flux, plot_fit_delchi, plot_fit_ratio, plot_fit_resid, plot_model, plot_model_component, plot_order, plot_pdf, plot_photon_flux, plot_pvalue, plot_ratio, plot_resid, plot_scatter, plot_source, plot_source_component, plot_trace, set_xlinear, set_xlog, set_ylinear, set_ylog
get_chisqr_plot, get_delchi_plot, get_stat, get_stat_name
calc_chisqr, calc_stat
contour_resid, image_fit