get_model_component_plot

sherpa.astro.ui.get_model_component_plot(id, model=None, recalc: bool = True)

Return the data used to create the model-component plot.

For PHA data, the response model is automatically added by the routine unless the model contains a response.

Parameters:

id (int or str, optional) – The data set that provides the data. If not given then the default identifier is used, as returned by get_default_id.
model (str or sherpa.models.model.Model instance) – The component to use (the name, if a string).
recalc (bool, optional) – If False then the results from the last call to plot_model_component (or get_model_component_plot) are returned, otherwise the data is re-generated.

Returns:

An object representing the data used to create the plot by plot_model_component. The return value depends on the data set (e.g. PHA, 1D binned, or 1D un-binned).

Return type:

instance

See also

get_model_plot: Return the data used to create the model plot.
plot_model: Plot the model for a data set.
plot_model_component: Plot a component of the model for a data set.

Notes

The function does not follow the normal Python standards for parameter use, since it is designed for easy interactive use. When called with a single un-named argument, it is taken to be the model parameter. If given two un-named arguments, then they are interpreted as the id and model parameters, respectively.

Examples

Return the plot data for the pl component used in the default data set:

>>> cplot = get_model_component_plot(pl)

Return the full source model (fplot) and then for the components gal * pl and gal * gline, for the data set ‘jet’:

>>> fmodel = xsphabs.gal * (powlaw1d.pl + gauss1d.gline)
>>> set_source('jet', fmodel)
>>> fit('jet')
>>> fplot = get_model_plot('jet')
>>> plot1 = get_model_component_plot('jet', pl*gal)
>>> plot2 = get_model_component_plot('jet', gline*gal)

For PHA data sets the response is automatically added, but it can also be manually specified. In the following plot1 and plot2 contain the same data:

>>> plot1 = get_model_component_plot(pl)
>>> rsp = get_response()
>>> plot2 = get_model_component_plot(rsp(pl))