plot_source_component
- sherpa.ui.plot_source_component(id, model=None, replot=False, overplot=False, clearwindow=True, **kwargs)
Plot a component of the source expression for a data set.
This function evaluates and plots a component of the model expression for a data set, without any instrument response. Use
plot_model_component
to include 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 toplot_source_component
. The default isFalse
.overplot (bool, optional) – If
True
then add the data to an existing plot, otherwise create a new plot. The default isFalse
.clearwindow (bool, optional) – Should the existing plot area be cleared before creating this new plot (e.g. for multi-panel plots)?
See also
get_source_component_plot
Return the data used by plot_source_component.
get_default_id
Return the default data set identifier.
plot
Create one or more plot types.
plot_model_component
Plot a component of the model for a data set.
plot_source
Plot the source expression 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 theid
andmodel
parameters, respectively.The additional keyword arguments match the keywords of the dictionary returned by get_model_plot_prefs.
Examples
Overplot the
pl
component of the source expression for the default data set:>>> plot_source() >>> plot_source_component(pl, overplot=True)