Display any kernel applied to a data set.
show_kernel(id=None, outfile=None, clobber=False) id - int or str, optional outfile - str, optional clobber - bool, optional
The kernel represents the subset of the PSF model that is used to fit the data. The `show_psf` function shows the un-filtered version.
The parameters for this function are:
|id||The data set. If not given then all data sets are displayed.|
|outfile||If not given the results are displayed to the screen, otherwise it is taken to be the name of the file to write the results to.|
|clobber||If `outfile` is not none , then this flag controls whether an existing file can be overwritten ( True ) or if it raises an exception ( False , the default setting).|
The point spread function (PSF) is defined by the full (unfiltered) PSF image or model expression evaluated over the full range of the dataset; both types of PSFs are established with `load_psf` . The kernel is the subsection of the PSF image or model which is used to convolve the data: this is changed using `set_psf` . While the kernel and PSF might be congruent, defining a smaller kernel helps speed the convolution process by restricting the number of points within the PSF that must be evaluated.
See the bugs pages on the Sherpa website for an up-to-date listing of known bugs.