XSoptxagnf

class sherpa.astro.xspec.XSoptxagnf(name='optxagnf')

Bases: sherpa.astro.xspec.XSAdditiveModel

The XSPEC optxagnf model: Colour temperature corrected disc and energetically coupled Comptonisation model for AGN.

The model is described at 1.

Note

Deprecated in Sherpa 4.10.0

The logLLEdd parameter has been renamed logLoLedd to match the XSPEC definition. The name logLLEdd can still be used to access the parameter, but this name will be removed in a future release.

mass

The black hole mass in solar masses.

dist

The comoving (proper) distance in Mpc.

logLoLEdd

The Eddington ratio.

astar

The dimensionless black hole spin.

rcor

The coronal radius in Rg=GM/c^2. See 1 for more details.

logrout

The log of the outer radius of the disk in units of Rg. See 1 for more details.

kT_e

The electron temperature for the soft Comptonisation component (soft excess), in keV.

tau

The optical depth of the soft Comptonisation component. If this parameter is negative then only the soft Compton component is used.

Gamma

The spectral index of the hard Comptonisation component (‘power law’) which has temperature fixed to 100 keV.

fpl

The fraction of the power below rcor which is emitted in the hard comptonisation component. If this parameter is negative then only the hard Compton component is used.

Redshift

The redshift.

norm

The normalization of the model. It must be frozen.

See also

XSoptxagn

Notes

The minimum allowed value for the Gamma parameter has been changed from 0.5 to 1.05 to match the XSPEC 12.10.0 model.dat file.

References

1(1,2,3)

https://heasarc.gsfc.nasa.gov/xanadu/xspec/manual/XSmodelOptxagn.html

Attributes Summary

ndim
thawedparhardmaxes	The hard maximum values for the thawed parameters.
thawedparhardmins	The hard minimum values for the thawed parameters.
thawedparmaxes	Access to the maximum limits for the thawed parameters
thawedparmins	Access to the minimum limits for the thawed parameters
thawedpars	Access to the thawed parameters of the model
version_enabled

Methods Summary

apply(outer, *otherargs, **otherkwargs)
calc(pars, xlo, *args, **kwargs)	Evaluate the model on a grid.
get_center()
guess(dep, *args, **kwargs)	Set an initial guess for the parameter values.
regrid(*args, **kwargs)	The class RegriddableModel1D allows the user to evaluate in the requested space then interpolate onto the data space.
reset()	Reset the parameter values.
set_center(*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

ndim = 1

thawedparhardmaxes

The hard maximum values for the thawed parameters.

thawedparhardmins

The hard minimum values for the thawed parameters.

thawedparmaxes

Access to the maximum limits for the thawed parameters

thawedparmins

Access to the minimum limits for the thawed parameters

thawedpars

Access to the thawed parameters of the model

version_enabled = True

Methods Documentation

apply(outer, *otherargs, **otherkwargs)

calc(pars, xlo, *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.

regrid(*args, **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()

Reset the parameter values.

set_center(*args, **kwargs)

startup(cache=False)

Called before a model may be evaluated multiple times.

Parameters

cache (bool, optional) – Should a cache be used when evaluating the models.

See also

teardown

teardown()

Called after a model may be evaluated multiple times.

See also

setup