Last modified: December 2023

URL: https://cxc.cfa.harvard.edu/sherpa/ahelp/plot_model.html
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AHELP for CIAO 4.16 Sherpa

plot_model

Context: plotting

Synopsis

Plot the model for a data set.

Syntax

plot_model(id=None, replot=False, overplot=False, clearwindow=True,
**kwargs)

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

Description

This function plots the model for a data set, which includes any instrument response (e.g. a convolution created by `set_psf` ).


Examples

Example 1

Plot the convolved source model for the default data set:

>>> plot_model()

Example 2

Overplot the model for data set 2 on data set 1:

>>> plot_model(1)
>>> plot_model(2, overplot=True)

Example 3

Create the equivalent of plot_fit('jet') :

>>> plot_data('jet')
>>> plot_model('jet', overplot=True)

Example 4

Additional arguments can be given that are passed to the plot backend: the supported arguments match the keywords of the dictionary returned by `get_model_plot_prefs` . The following plots the model using a log scale for both axes, and then overplots the model from data set 2 using a dashed line and slightly transparent:

>>> plot_model(xlog=True, ylog=True)
>>> plot_model(2, overplot=True, alpha=0.7, linestyle='dashed')

PARAMETERS

The parameters for this function are:

Parameter Definition
id The data set that provides the data. 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_model` . 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)?

Notes

The additional arguments supported by `plot_model` are the same as the keywords of the dictionary returned by `get_model_plot_prefs` .

For PHA data sets the model plot created by `plot_model` differs to the model plot created by `plot_fit` : the fit version uses the grouping of the data set whereas the `plot_model` version shows the ungrouped data (that is, it uses the instrumental grid). The filters used are the same in both cases.


Bugs

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

See Also

contrib
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
data
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
info
list_model_ids, show_bkg_model, show_bkg_source
modeling
add_model, add_user_pars, clean, create_model_component, delete_bkg_model, delete_model, delete_model_component, get_model, get_model_autoassign_func, get_model_component, get_model_component_image, get_model_component_plot, get_model_plot, get_num_par, get_num_par_frozen, get_num_par_thawed, get_order_plot, get_par, get_pileup_model, get_source, get_source_component_image, get_source_component_plot, get_source_contour, get_source_image, get_source_plot, get_xsabund, get_xscosmo, get_xsxsect, get_xsxset, image_model, image_model_component, image_source, image_source_component, integrate, link, load_table_model, load_template_interpolator, load_template_model, load_user_model, normal_sample, reset, save_model, save_source, set_bkg_model, set_bkg_source, set_full_model, set_model, set_model_autoassign_func, set_pileup_model, set_source, set_xsabund, set_xscosmo, set_xsxsect, set_xsxset, t_sample, uniform_sample
plotting
get_cdf_plot, get_energy_flux_hist, get_model_plot_prefs, 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, plot_fit_delchi, plot_fit_resid, 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
psfs
delete_psf, load_conv, plot_kernel
saving
save_delchi, save_resid
statistics
get_chisqr_plot, get_delchi_plot
utilities
calc_chisqr, calc_energy_flux, calc_model_sum, calc_photon_flux, calc_source_sum, calc_stat, eqwidth
visualization
contour_model, contour_ratio, contour_resid