plot_fit_ratio

sherpa.astro.ui.plot_fit_ratio(id=None, replot=False, overplot=False, clearwindow=True, **kwargs)

Plot the fit results, and the ratio of data to model, for a data set.

This creates two plots - the first from plot_fit and the second from plot_ratio - for a data set.

New in version 4.12.0.

Parameters
  • id (int or str, optional) – The data set. If not given then the default identifier is used, as returned by get_default_id.

  • replot (bool, optional) – Set to True to use the values calculated by the last call to plot_fit_ratio. 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.

  • clearwindow (bool, optional) – Should the existing plot area be cleared before creating this new plot (e.g. for multi-panel plots)?

Raises

sherpa.utils.err.IdentifierErr – If the data set does not exist or a source expression has not been set.

See also

get_fit_plot()

Return the data used to create the fit plot.

get_default_id()

Return the default data set identifier.

plot()

Create one or more plot types.

plot_fit()

Plot the fit results for a data set.

plot_fit_resid()

Plot the fit results, and the residuals, for a data set.

plot_fit_delchi()

Plot the fit results, and the residuals, for a data set.

plot_data()

Plot the data values.

plot_model()

Plot the model for a data set.

plot_ratio()

Plot the ratio of data to 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 additional arguments supported by plot_fit_ratio are the same as the keywords of the dictionary returned by get_data_plot_prefs, and are applied to both plots.

For the ratio plot, the ylog setting is ignored, and the Y axis is drawn using a linear scale.

Examples

Plot the results for the default data set:

>>> plot_fit_ratio()

Overplot the ‘core’ results on those from the ‘jet’ data set, using a logarithmic scale for the X axis:

>>> set_xlog()
>>> plot_fit_ratio('jet')
>>> plot_fit_ratio('core', overplot=True)

Additional arguments can be given that are passed to the plot backend: the supported arguments match the keywords of the dictionary returned by get_data_plot_prefs. The following sets the plots to use square symbols (this includes the model as well as data in the top plot) and turns off any line between plots, when using the Matplotlib backend:

>>> plot_fit_ratio(marker='s', linestyle='none')