plot_psf

sherpa.ui.plot_psf(id: IdType | None = None, replot=False, overplot=False, clearwindow=True, **kwargs) → None

Plot the 1D PSF model applied to a data set.

The plot_kernel function shows the data used to convolve the model.

Parameters:

  • id (int, str, or None, 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_psf. 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 a PSF model has not been created for the data set.

See also

get_psf_plot

Return the data used by plot_psf.

get_default_id

Return the default data set identifier.

plot

Create one or more plot types.

plot_kernel

Plot the 1D kernel applied to a data set.

set_psf

Add a PSF model to 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.

Examples

Create a model (a step function) that is convolved by a gaussian, and display the PSF:

>>> dataspace1d(1, 10, step=1, dstype=Data1D)
>>> set_model(steplo1d.stp)
>>> stp.xcut = 4.4
>>> load_psf('psf1', gauss1d.gline)
>>> set_psf('psf1')
>>> gline.fwhm = 1.2
>>> plot_psf()