load_rmf

sherpa.astro.ui.load_rmf(id, arg=None, resp_id: IdType | None = None, bkg_id: IdType | None = None) None

Load a RMF from a file and add it to a PHA data set.

Load in the redistribution matrix function for a PHA data set, or its background. The load_bkg_rmf function can be used for setting most background RMFs.

Changed in version 4.16.0: This command does not support multi-matrix RMF files and will warn the user when given such a file (as only the first matrix is read in, the results will not be correct).

Parameters:
  • id (int or str, optional) – The data set to use. If not given then the default identifier is used, as returned by get_default_id.

  • arg – Identify the RMF: a file name, or a data structure representing the data to use, as used by the I/O backend in use by Sherpa: a RMFCrateDataset for crates, as used by CIAO, or an AstroPy HDUList object.

  • resp_id (int, str, or None, optional) – The identifier for the RMF within this data set, if there are multiple responses.

  • bkg_id (int, str, or None, optional) – Set this to identify the RMF as being for use with the background.

See also

get_rmf

Return the RMF associated with a PHA data set.

load_bkg_rmf

Load a RMF from a file and add it to the background of a PHA data set.

load_arf

Load an ARF from a file and add it to a PHA data set.

load_multi_rmfs

Load multiple RMFs for a PHA data set.

load_pha

Load a file as a PHA data set.

set_full_model

Define the convolved model expression for a data set.

set_rmf

Load a RMF from a file and add it to a PHA data set.

unpack_rmf

Read in a RMF from a file.

Notes

The function does not follow the normal Python standards for parameter use, since it is designed for easy interactive use. When called with a single un-named argument, it is taken to be the arg parameter. If given two un-named arguments, then they are interpreted as the id and arg parameters, respectively. The remaining parameters are expected to be given as named arguments.

If a PHA data set has an associated RMF - either from when the data was loaded or explicitly with the set_rmf function - then the model fit to the data will include the effect of the RMF when the model is created with set_model or set_source. In this case the get_source function returns the user model, and get_model the model that is fit to the data (i.e. it includes any response information; that is the ARF and RMF, if set). To include the RMF explicitly, use set_full_model.

The minimum_energy setting of the ogip section of the Sherpa configuration file determines the behavior when an RMF with a minimum energy of 0 is read in. The default is to replace the 0 by the value 1e-10, which will also cause a warning message to be displayed.

Examples

Use the contents of the file ‘src.rmf’ as the RMF for the default data set.

>>> load_rmf('src.rmf')

Read in a RMF from the file ‘bkg.rmf’ and set it as the RMF for the background model of data set “core”:

>>> load_rmf('core', 'bkg.rmf', bkg_id=1)