SimulFitModel

class sherpa.models.model.SimulFitModel(name, parts)

Bases: sherpa.models.model.CompositeModel

Store multiple models.

This class is for use with sherpa.data.DataSimulFit.

Parameters:

• name (str) – The name for the collection of models.
• parts (sequence of Model objects) – The models.

parts

sequence of Model

See also

sherpa.data.DataSimulFit

Examples

>>> m1 = Polynom1D('m1')
>>> m2 = Gauss1D('g1')
>>> mall = SimulFitModel('comp', (m1, m1 + m2))

If dall is a DataSimulFit object then the model components can be evaluated for the composite object using:

>>> ymdl = dall.eval_model_to_fit(mall)

Attributes Summary

thawedparhardmaxes
thawedparhardmins
thawedparmaxes
thawedparmins
thawedpars

Methods Summary

calc(p, \*args, \*\*kwargs)	Evaluate the model on a grid.
get_center()
guess(dep, \*args, \*\*kwargs)	Set an initial guess for the parameter values.
reset()
set_center(\*args, \*\*kwargs)
startup()
teardown()

Attributes Documentation

thawedparhardmaxes

thawedparhardmins

thawedparmaxes

thawedparmins

thawedpars

Methods Documentation

calc(p, *args, **kwargs)

Evaluate the model on a grid.

Parameters:

• p (sequence of numbers) – The parameter values to use. The order matches the pars field.
• *args – The model grid. The values can be scalar or arrays, and the number depends on the dimensionality of the model and whether it is being evaluated over an integrated grid or at a point (or points).

get_center()

guess(dep, *args, **kwargs)

Set an initial guess for the parameter values.

Attempt to set the parameter values, and ranges, for the model to match the data values. This is intended as a rough guess, so it is expected that the model is only evaluated a small number of times, if at all.

reset()

set_center(*args, **kwargs)

startup()

teardown()