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.

Changed in version 4.12.2: The overplot option now works.

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 existing 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')