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, **kwargs) The class RegriddableModel1D allows the user to evaluate in the requested space then interpolate onto the data space.
reset()
set_center(pos, *args, **kwargs)
startup(cache) 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, **kwargs) [edit on github]

The class RegriddableModel1D allows the user to evaluate in the requested space then interpolate onto the data space. An optional argument ‘interp’ enables the user to change the interpolation method.

Examples

>>> import numpy as np
>>> from sherpa.models.basic import Box1D
>>> mybox = Box1D()
>>> request_space = np.arange(1, 10, 0.1)
>>> regrid_model = mybox.regrid(request_space, interp=linear_interp)
reset() [edit on github]
set_center(pos, *args, **kwargs)[source] [edit on github]
startup(cache) [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()