NormGauss1D

class sherpa.models.basic.NormGauss1D(name='normgauss1d')[source] [edit on github]

Bases: sherpa.models.model.RegriddableModel1D

One-dimensional normalised gaussian function.

fwhm

The Full-Width Half Maximum of the gaussian. It is related to the sigma value by: FWHM = sqrt(8 * log(2)) * sigma.

pos

The center of the gaussian.

ampl

The amplitude refers to the integral of the model over the range -infinity to infinity.

See also

Gauss1D, NormGauss2D

Notes

The functional form of the model for points is:

f(x) = ampl * exp(-4 * log(2) * (x - pos)^2 / fwhm^2)
       ----------------------------------------------
               sqrt(pi / (4 * log(2))) * fwhm

and for an integrated grid it is the integral of this over the bin.

Attributes Summary

thawedparhardmaxes
thawedparhardmins
thawedparmaxes
thawedparmins
thawedpars

Methods Summary

apply(outer, *otherargs, **otherkwargs)
calc(pars, xlo, *args, **kwargs)
get_center()
guess(dep, *args, **kwargs) Set an initial guess for the parameter values.
regrid(*arrays)
reset()
set_center(pos, *args, **kwargs)
startup() Called before a model may be evaluated multiple times.
teardown() Called after a model may be evaluated multiple times.

Attributes Documentation

thawedparhardmaxes
thawedparhardmins
thawedparmaxes
thawedparmins
thawedpars

Methods Documentation

apply(outer, *otherargs, **otherkwargs) [edit on github]
calc(pars, xlo, *args, **kwargs) [edit on github]
get_center()[source] [edit on github]
guess(dep, *args, **kwargs)[source] [edit on github]

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.

regrid(*arrays) [edit on github]
reset() [edit on github]
set_center(pos, *args, **kwargs)[source] [edit on github]
startup() [edit on github]

Called before a model may be evaluated multiple times.

See also

teardown()

teardown() [edit on github]

Called after a model may be evaluated multiple times.

See also

setup()