NormBeta1D

class sherpa.astro.models.NormBeta1D(name='normbeta1d')

Bases: sherpa.models.model.RegriddableModel1D

One-dimensional normalized beta model function.

This is the same model as the Beta1D model but with a different slope parameter and normalisation.

pos

The center of the line.

w

The line width.

alpha

The slope of the profile at large radii.

ampl

The amplitude refers to the integral of the model.

See also

Beta1D, Lorentz1D

Notes

The functional form of the model for points is:

f(x) = A * (1 + ((x - pos) / w)^2)^(-alpha)

   A = ampl / integral f(x) dx

The grid version is evaluated by numerically intgerating the function over each bin using a non-adaptive Gauss-Kronrod scheme suited for smooth functions [1], falling over to a simple trapezoid scheme if this fails.

References

[1]	https://www.gnu.org/software/gsl/manual/html_node/QNG-non_002dadaptive-Gauss_002dKronrod-integration.html

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)

calc(pars, xlo, *args, **kwargs)

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.

regrid(*arrays, **kwargs)

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()

set_center(pos, *args, **kwargs)

startup(cache)

Called before a model may be evaluated multiple times.

See also

teardown()

teardown()

Called after a model may be evaluated multiple times.

See also

setup()