sherpa.astro.ui.load_table_model(modelname, filename, method=<function linear_interp>, *args, **kwargs)

Load tabular or image data and use it as a model component.


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 from load_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.

  • 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 a 1D convolution model.


Create a PSF model


Load a set of templates and use it as a model component.


Load a XSPEC table model.


Set the source model expression for a data set.


Define the convolved model expression for a data set.


Examples of interpolation schemes provided by sherpa.utils are: linear_interp, nearest_interp, neville, and neville2d.


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)