Last modified: December 2022

URL: https://cxc.cfa.harvard.edu/sherpa/ahelp/load_rmf.html
Jump to: Description · Examples · PARAMETERS · Notes · Bugs · See Also


AHELP for CIAO 4.15 Sherpa

load_rmf

Context: data

Synopsis

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

Syntax

load_rmf(id, arg=None, resp_id=None, bkg_id=None)

id - int or str, optional
resp_id - int or str, optional
bkg_id - int or str, optional

Description

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.


Examples

Example 1

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

>>> load_rmf('src.rmf')

Example 2

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)

PARAMETERS

The parameters for this function are:

Parameter Definition
id 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 The identifier for the RMF within this data set, if there are multiple responses.
bkg_id Set this to identify the RMF as being for use with the background.

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.


Bugs

See the bugs pages on the Sherpa website for an up-to-date listing of known bugs.

See Also

data
dataspace1d, dataspace2d, datastack, fake, get_bkg, get_bkg_arf, get_bkg_model, get_bkg_rmf, get_bkg_source, get_rmf, load_arf, load_arrays, load_ascii, load_bkg, load_bkg_arf, load_bkg_rmf, load_data, load_grouping, load_image, load_multi_arfs, load_multi_rmfs, load_pha, load_quality, load_staterror, load_syserror, load_table, pack_image, pack_pha, pack_table, set_rmf, unpack_arf, unpack_arrays, unpack_ascii, unpack_bkg, unpack_data, unpack_image, unpack_pha, unpack_rmf, unpack_table
filtering
load_filter
info
get_default_id, list_bkg_ids, list_data_ids, list_response_ids
modeling
add_model, add_user_pars, get_response, load_table_model, load_template_interpolator, load_template_model, load_user_model, save_model, save_source
saving
save_arrays, save_data, save_delchi, save_error, save_filter, save_grouping, save_image, save_pha, save_quality, save_resid, save_staterror, save_syserror, save_table
statistics
load_user_stat