XSkyrline

class sherpa.astro.xspec.XSkyrline(name='kyrline')

Bases: sherpa.astro.xspec.XSAdditiveModel

The XSPEC kyrline model: relativistic line from axisymmetric accretion disk

The model is described at 1.

a

Black Hole angular momentum, in units of GM/c.

theta_o

The observer inclination, where 0 is pole on. The units are degrees.

rin

The inner radius (units of GM/c^2).

ms

A flag that determines whether to integrate from rin (0) or to integrate emission from above the marginally-stable orbit only (1)

rout

The outer radius (units of GM/c^2).

Erest

The line energy in keV.

alpha

The accretion disk emissivity scales as r^(-alpha) for r < rb.

beta

The accretion disk emissivity scales as r^(-beta) for r > rb.

rb

The boundary radius between the inner and outer emissivity laws (units of GM/c^2).

zshift

The overall Doppler shift.

limb

0 means isotropic emission, 1 means Laor’s limb darkening (1 + 0.26 mu), 2 means Haardt’s limb brightening (ln(1 + 1/mu))

norm

The normalization.

Notes

This model is only available when used with XSPEC 12.10.1 or later.

Early releases of XSPEC 12.10.1 refer to the first parameter as a/M. As this is not a valid Python name, the parameter has been renamed “a” to better match other XSPEC models (after consultation with Keith Arnaud).

References

1

https://heasarc.gsfc.nasa.gov/xanadu/xspec/manual/XSmodelKyrline.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