plot_model_component

sherpa.astro.ui.plot_model_component(id, model=None, **kwargs)

Plot a component of the model for a data set.

This function evaluates and plots a component of the model expression for a data set, including any instrument response. Use plot_source_component to display without any 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 display (the name, if a string).
  • replot (bool, optional) – Set to True to use the values calculated by the last call to plot_model_component. The default is False.
  • overplot (bool, optional) – If True then add the data to an exsiting plot, otherwise create a new plot. The default is False.

See also

get_model_component_plot()
Return the data used by plot_model_component.
get_default_id()
Return the default data set identifier.
plot()
Create one or more plot types.
plot_source_component()
Plot a component of the source expression for a data set.
plot_model()
Plot the model for a data set.
set_xlinear()
New plots will display a linear X axis.
set_xlog()
New plots will display a logarithmically-scaled X axis.
set_ylinear()
New plots will display a linear Y axis.
set_ylog()
New plots will display a logarithmically-scaled Y axis.

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

Overplot the pl component of the model expression for the default data set:

>>> plot_model()
>>> plot_model_component(pl, overplot=True)

Display the results for the ‘jet’ data set (data and model), and then overplot the pl component evaluated for the ‘jet’ and ‘core’ data sets:

>>> plot_fit('jet')
>>> plot_model_component('jet', pl, overplot=True)
>>> plot_model_component('core', pl, overplot=True)