get_source_plot

sherpa.astro.ui.get_source_plot(id: IdType | None = None, lo=None, hi=None, recalc=True)

Return the data used by plot_source.

Parameters:

  • id (int, str, or None, optional) – The data set that provides the data. If not given then the default identifier is used, as returned by get_default_id.

  • lo (number, optional) – The low value to plot (only used for PHA data sets).

  • hi (number, optional) – The high value to plot (only use for PHA data sets).

  • recalc (bool, optional) – If False then the results from the last call to plot_source (or get_source_plot) are returned, otherwise the data is re-generated.

Returns:

An object representing the data used to create the plot by plot_source. The return value depends on the data set (e.g. PHA, 1D binned, 1D un-binned). If lo or hi were set then the mask attribute of the object can be used to apply the filter to the xlo, xhi, and y attributes.

Return type:

instance

See also

get_model_plot

Return the data used by plot_model.

plot_model

Plot the model for a data set.

plot_source

Plot the source expression for a data set.

Examples

Retrieve the source plot information for the default data set and then display it:

>>> splot = get_source_plot()
>>> print(splot)

Return the plot data for data set 2, and then use it to create a plot:

>>> s2 = get_source_plot(2)
>>> s2.plot()

Retrieve the source plots for the 0.5 to 7 range of the ‘jet’ and ‘core’ data sets and display them on the same plot:

>>> splot1 = get_source_plot(id='jet', lo=0.5, hi=7)
>>> splot2 = get_source_plot(id='core', lo=0.5, hi=7)
>>> splot1.plot()
>>> splot2.overplot()

Access the plot data (for a PHA data set) and select only the bins corresponding to the 2-7 keV range defined in the call:

>>> splot = get_source_plot(lo=2, hi=7)
>>> xlo = splot.xlo[splot.mask]
>>> xhi = splot.xhi[splot.mask]
>>> y = splot.y[splot.mask]

For a PHA data set, the units on both the X and Y axes of the plot are controlled by the set_analysis command. In this case the Y axis will be in units of photon/s/cm^2/keV x Energy and the X axis in keV:

>>> set_analysis('energy', factor=1)
>>> splot = get_source_plot()
>>> print(splot)