IterFit

class sherpa.fit.IterFit(data, model, stat, method, itermethod_opts=None)[source] [edit on github]

Bases: NoNewAttributesAfterInit

Methods Summary

fit(statfunc, pars, parmins, parmaxes[, ...])

sigmarej(statfunc, pars, parmins, parmaxes)

Exclude points that are significately far away from the best fit.

Methods Documentation

fit(statfunc, pars, parmins, parmaxes, statargs=(), statkwargs=None)[source] [edit on github]
sigmarej(statfunc, pars, parmins, parmaxes, statargs=(), statkwargs=None, cache=True)[source] [edit on github]

Exclude points that are significately far away from the best fit.

The sigmarej scheme is based on the IRAF sfit function 3, where after a fit data points are excluded if the value of (data-model) / error exceeds a threshold, and the data re-fit. This removal of data points continues until the fit has converged or a maximum number of iterations has been reached. The error removal can be asymmetric, since there are separate options for the lower and upper limits.

Raises

sherpa.utils.err.FitErr – This exception is raised if the statistic is not supported. This method can only be used with Chi-Square statistics with errors.

Notes

The following keys are looked for in the itermethod_opts dictionary:

Key

Type

Description

maxiters

int > 0

The maximum number of iterations.

lrej

number > 0

The number of sigma below the model to reject.

hrej

number > 0

The number of sigma above the model to reject.

grow

int >= 0

If greater than zero, also remove this many data points to either side of the identified element.

References

3

http://iraf.net/irafhelp.php?val=sfit