load_conv

Context: psfs

Synopsis

Load a 1D convolution model.

Syntax

load_conv(modelname, filename_or_model, *args, **kwargs)

Description

The convolution model can be defined either by a data set, read from a file, or an analytic model, using a Sherpa model instance. A source model can be convolved with this model by including modelname in the `set_model` call, using the form:

modelname(modelexpr)

Examples

Example 1

Create a 1D data set, assign a box model - which is flat between the xlow and xhi values and zero elsewhere - and then display the model values. Then add in a convolution component by a gaussian and overplot the resulting source model with two different widths.

>>> dataspace1d(-10, 10, 0.5, id='tst', dstype=Data1D)
>>> set_source('tst', box1d.bmdl)
>>> bmdl.xlow = -2
>>> bmdl.xhi = 3
>>> plot_source('tst')
>>> load_conv('conv', normgauss1d.gconv)
>>> gconv.fwhm = 2
>>> set_source('tst', conv(bmdl))
>>> plot_source('tst', overplot=True)
>>> gconv.fwhm = 5
>>> plot_source('tst', overplot=True)

Example 2

Create a convolution component called "cmodel" which uses the data in the file "conv.dat", which should have two columns (the X and Y values).

>>> load_conv('cmodel', 'conv.dat')

PARAMETERS

The parameters for this function are:

Parameter	Type information	Definition
modelname	str	The identifier for this PSF model.
filename_or_model	str or model instance	This can be the name of an ASCII file or a Sherpa model component.
args		Arguments for `unpack_data` if `filename_or_model` is a file.
kwargs		Keyword arguments for `unpack_data` if `filename_or_model` is a file.

Bugs

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