load_table_model
- sherpa.astro.ui.load_table_model(modelname, filename, method=<function linear_interp>, *args, **kwargs) None
Load tabular or image data and use it as a model component.
Note
Deprecated in Sherpa 4.9 The new
load_xstable_model
routine should be used for loading XSPEC table model files. Support for these files will be removed fromload_table_model
in the 4.17 release.A table model is defined on a grid of points which is interpolated onto the independent axis of the data set. The model has a single parameter,
ampl
, which is used to scale the data, and it can be fixed or allowed to vary during a fit.- Parameters:
modelname (str) – The identifier for this table model.
filename (str) – The name of the file containing the data, which should contain two columns, which are the x and y values for the data, or be an image.
method (func) – The interpolation method to use to map the input data onto the coordinate grid of the data set. Linear, nearest-neighbor, and polynomial schemes are provided in the sherpa.utils module.
args – Arguments for reading in the data.
kwargs – Keyword arguments for reading in the data.
See also
load_conv
Load a 1D convolution model.
load_psf
Create a PSF model
load_template_model
Load a set of templates and use it as a model component.
load_xstable_model
Load a XSPEC table model.
set_model
Set the source model expression for a data set.
set_full_model
Define the convolved model expression for a data set.
Notes
Examples of interpolation schemes provided by
sherpa.utils
are:linear_interp
,nearest_interp
,neville
, andneville2d
.Examples
Load in the data from filt.fits and use it to multiply the source model (a power law and a gaussian). Allow the amplitude for the table model to vary between 1 and 1e6, starting at 1e3.
>>> load_table_model('filt', 'filt.fits') >>> set_source(filt * (powlaw1d.pl + gauss1d.gline)) >>> set_par(filt.ampl, 1e3, min=1, max=1e6)
Load in an image (“broad.img”) and use the pixel values as a model component for data set “img”:
>>> load_table_model('emap', 'broad.img') >>> set_source('img', emap * gauss2d)