plot_model

Synopsis

Plot the convolved source model

plot_model( [id], [replot=False, overplot=False] )

Description

The plot_model command plots the convolved source model. The plot_source command is available for plotting the unconvolved model amplitudes.

Note that the plot_model command always plots the ungrouped, full-resolution source model on a grouped data set. To view the grouped model overlaid on the grouped data spectrum, use the generic 'plot' function with the 'model' option, e.g. "plot("data",1,"model",1)".

The plot is displayed in a ChIPS plotting window. If there is no plotting window open, one is created. If a plotting window exists, the overplot parameter value determines whether the new plot is overlaid on any existing plots in the window or if the window is cleared before the plot is drawn.

ChIPS commands may be used within Sherpa to modify plot characteristics and create hardcopies; refer to the ChIPS website for information.

The default values for the plot can be read - and changed - using the get_model_plot_prefs() command. See

unix% ahelp get_model_plot

and the examples below for more information.

Plotting Multiple Objects

To plot multiple Sherpa objects - e.g. data, model, fit, residuals - in a single window, use the plot command.

Example 1

sherpa> plot_model()
sherpa> log_scale(XY_AXIS)
sherpa> print_window()

Plot the convolved source model for the default dataset. The ChIPS command log_scale() is used to change the scaling of the axes to logarithmic and the print_window() command is used to send a postscript version of the plot to the default printer (since no argument is given).

Example 2

sherpa> get_model_plot_prefs()["xlog"] = True
sherpa> get_model_plot_prefs()["ylog"] = True
sherpa> plot_model()

The plot preferences for model plots is changed to use a logarithmic scale for both X and Y axes. Any new plots created by plot_model() will therefore be drawn with both axes logged.

Example 3

sherpa> plot_data("src")
sherpa> plot_model("src", overplot=True)

PLot the data and then overplot the convolved source model for the "src" dataset (this is essentially what plot_fit("src") does).

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, prof_data, prof_delchi, prof_fit, prof_fit_delchi, prof_fit_resid, prof_model, prof_resid, prof_source

data

get_arf_plot, get_bkg_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_order_plot, get_par, get_pileup_model, get_source, get_source_component_image, get_source_component_plot, image_model, image_model_component, image_source, image_source_component, integrate, integrate1d, link, load_table_model, load_template_model, load_user_model, normal_sample, reset, save_model, save_source, set_bkg_model, set_full_model, set_model_autoassign_func, set_pileup_model, set_source, set_xsabund, set_xscosmo, set_xsxsect, set_xsxset, t_sample, uniform_sample

plotting

get_energy_flux_hist, get_lrt_plot, get_lrt_results, get_photon_flux_hist, get_pvalue_plot, get_pvalue_results, get_split_plot, plot, plot_arf, plot_bkg, plot_cdf, plot_chisqr, plot_data, plot_delchi, plot_energy_flux, plot_fit, plot_lrt, 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, get_ratio, get_resid