XSjet

class sherpa.astro.xspec.XSjet(name='jet')[source] [edit on github]

Bases: XSAdditiveModel

The XSPEC jet model: Leptonic relativistic jet model.

The model is described at [1].

mass: Black hole mass, in solar masses.

Dco: Comoving distance, as in XSoptxagnf.

log_mdot: log (accretion power / Eddington luminosity), in units of log L / logLEdd. See [1] for a full discussion of this parameter.

thetaobs: The inclination angle (deg) between the jet axis and line of sight.

BulkG: Bulk lorentz factor of the jet.

phi: The angular size scale - in radians - of the jet acceleration region as seen from the black hole. See [1] for more details.

zdiss: The vertical distance from the black hole of the jet dissipation region, in units of Rg=GM/c^2. See [1] for more details.

B: The magnetic field (in Gauss) in the jet.

logPrel: The log of the power injected in relativisitic particles, which is measured in ergs/s.

gmin_inj: The minimum lorentz factor of the injected electrons.

gbreak: The lorentz factor of the break in injected electron distribution.

gmax: The maximum lorentz factor.

s1: The injected index of the electron distribution below the break.

s2: The injected index of the electron distribution above the break.

z: The cosmological redshift corresponding to the Dco parameter.

norm: MUST BE FIXED AT UNITY as the jet spectrum normalisation is set by the relativisitic particle power.

See also

XSoptxagnf

References

Attributes Summary

`cache`	The maximum size of the cache.
`ndim`	A one-dimensional 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`()
`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.

ndim = 1: A one-dimensional model.

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.

See also

thawedparhardmins, thawedparmaxes

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.

See also

thawedparhardmaxes, thawedparmins

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.

See also

thawedparmaxes, thawedparmins

version_enabled = True

Methods Documentation

apply(outer, *otherargs, **otherkwargs) [edit on github]

cache_clear() [edit on github]: Clear the cache.

cache_status() [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() [edit on github]: Freeze any thawed parameters of the model.

get_center() [edit on github]

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
>>> mybox = Box1D()
>>> request_space = np.arange(1, 10, 0.1)
>>> regrid_model = mybox.regrid(request_space, interp=linear_interp)

reset() [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=False) [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() [edit on github]: Called after a model may be evaluated multiple times.

See also

startup

thaw() [edit on github]

Thaw any frozen parameters of the model.

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