show_kernel
- sherpa.astro.ui.show_kernel(id: IdType | None = None, outfile=None, clobber=False) None
Display any kernel applied to a data set.
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.- Parameters:
id (int, str, or None, optional) – The data set. If not given then all data sets are displayed.
outfile (str, optional) – 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 (bool, optional) – If
outfile
is notNone
, then this flag controls whether an existing file can be overwritten (True
) or if it raises an exception (False
, the default setting).
- Raises:
sherpa.utils.err.IOErr – If
outfile
already exists andclobber
isFalse
.
See also
image_kernel
Plot the 2D kernel applied to a data set.
list_data_ids
List the identifiers for the loaded data sets.
load_psf
Create a PSF model.
plot_kernel
Plot the 1D kernel applied to a data set.
set_psf
Add a PSF model to a data set.
show_all
Report the current state of the Sherpa session.
show_psf
Display any PSF model applied to a data set.
Notes
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 usingset_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.