XSoptxagn

class sherpa.astro.xspec.XSoptxagn(name='optxagn')[source] [edit on github]

Bases: XSAdditiveModel

The XSPEC optxagn 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.

fcol

The colour temperature correction to apply to the disc blackbody emission for radii below rcor with effective temperature > tscat.

tscat

The effective temperature limit, in K, used in the colour temperature correction.

Redshift

The redshift.

norm

The normalization of the model. It must be frozen.

See also

XSoptxagnf

References

Attributes Summary

cache

The maximum size of the cache.

lpars

Return any linked parameters.

ndim

A one-dimensional model.

pars

Return the parameters of the model.

thawedparhardmaxes

The hard maximum values for the thawed parameters.

thawedparhardmins

The hard minimum values for the thawed parameters.

thawedparmaxes

The maximum limits of the thawed parameters.

thawedparmins

The minimum limits of the thawed parameters.

thawedpars

The thawed parameters of the model.

version_enabled

Methods Summary

apply(outer, *otherargs, **otherkwargs)

cache_clear()

Clear the cache.

cache_status()

Display the cache status.

calc(p, *args, **kwargs)

Calculate the model given the parameters and grid.

freeze()

Freeze any thawed parameters of the model.

get_center()

get_thawed_pars()

Return the thawed parameter objects.

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.

thaw()

Thaw any frozen parameters of the model.

Attributes Documentation

cache = 5

The maximum size of the cache.

lpars

Return any linked parameters.

This only returns linked parameters that are not related to the model, and each parameter is not repeated.

Added in version 4.16.1.

See also

pars

Examples

By default there are no linked parameters:

>>> from sherpa.models.basic import Gauss2D
>>> mdl = Gauss2D("mdl")
>>> len(mdl.pars)
6
>>> mdl.lpars
()

Force the model to have identical xpos and ypos parameters. Since the linked parameter value (mdl.xpos) is part of the model it is not included in lpars:

>>> mdl.ypos = mdl.xpos
>>> len(mdl.pars)
6
>>> mdl.lpars
()

Add a link to allow the sigma term to be fit rather than FWHM. Since the linked parameter - here from the Const1D model - is not a part of the model it is included in lpars:

>>> import numpy as np
>>> from sherpa.models.basic import Const1D
>>> sigma = Const1D("sigma")
>>> mdl.fwhm = 2 * np.sqrt(2 * np.log(2)) * sigma.c0
>>> len(mdl.pars)
6
>>> mdl.lpars
(<Parameter 'c0' of model 'sigma'>,)
ndim: int | None = 1

A one-dimensional model.

pars

Return the parameters of the model.

This does not include any linked parameters.

Changed in version 4.16.1: The pars field can no-longer be set directly. Individual elements can still be changed.

See also

lpars

thawedparhardmaxes

The hard maximum values for the thawed parameters.

The minimum and maximum range of the parameters can be changed with thawedparmins and thawedparmaxes but only within the range given by thawedparhardmins to thawparhardmaxes.

thawedparhardmins

The hard minimum values for the thawed parameters.

The minimum and maximum range of the parameters can be changed with thawedparmins and thawedparmaxes but only within the range given by thawedparhardmins to thawparhardmaxes.

thawedparmaxes

The maximum limits of the thawed parameters.

Get or set the maximum limits of the thawed parameters of the model as a list of numbers. If there are no thawed parameters then [] is used. The ordering matches that of the pars attribute.

See also

thawedpars, thawedarhardmaxes, thawedparmins

thawedparmins

The minimum limits of the thawed parameters.

Get or set the minimum limits of the thawed parameters of the model as a list of numbers. If there are no thawed parameters then [] is used. The ordering matches that of the pars attribute.

See also

thawedpars, thawedarhardmins, thawedparmaxes

thawedpars

The thawed parameters of the model.

Get or set the thawed parameters of the model as a list of numbers. If there are no thawed parameters then [] is used. The ordering matches that of the pars attribute.

version_enabled = True

Methods Documentation

apply(outer, *otherargs, **otherkwargs) [edit on github]
cache_clear() None [edit on github]

Clear the cache.

cache_status() None [edit on github]

Display the cache status.

Information on the cache - the number of “hits”, “misses”, and “requests” - is displayed at the INFO logging level.

Example

>>> pl.cache_status()
 powlaw1d.pl                size:    5  hits:   633  misses:   240  check=  873
calc(p, *args, **kwargs) [edit on github]

Calculate the model given the parameters and grid.

Notes

XSPEC models must always be evaluated with low and high bin edges. Although supported by the XSPEC model interface the ability to evaluate using an XSPEC-style grid (n+1 values for n bins which we pad with a 0), we do not allow this here since it complicates the handling of the regrid method.

Keyword arguments are ignored.

freeze() None [edit on github]

Freeze any thawed parameters of the model.

get_center() [edit on github]
get_thawed_pars() list[Parameter] [edit on github]

Return the thawed parameter objects.

This includes linked parameters, which complicates the min/max settings, since the range on the components of a linked parameter does not match that of the original parameter, which is an issue when the limits are exceeded.

Added in version 4.16.1.

guess(dep, *args, **kwargs) [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(*args, **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
>>> from sherpa.utils import linear_interp
>>> mybox = Box1D()
>>> request_space = np.arange(1, 10, 0.1)
>>> regrid_model = mybox.regrid(request_space, interp=linear_interp)
reset() None [edit on github]

Reset the parameter values.

Restores each parameter to the last value it was set to. This allows the parameters to be easily reset after a fit.

set_center(*args, **kwargs) [edit on github]
startup(cache: bool = False) None [edit on github]

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() None [edit on github]

Called after a model may be evaluated multiple times.

See also

startup

thaw() None [edit on github]

Thaw any frozen parameters of the model.

Those parameters that are marked as “always frozen” are skipped.