XSbwcycl

class sherpa.astro.xspec.XSbwcycl(name='bwcycl')

Bases: sherpa.astro.xspec.XSAdditiveModel

The XSPEC bwcycl model: Becker-Wolff self-consistent cyclotron line model.

The model is described at 1. Please review the restrictions on the model and parameter values at this reference before using the model.

Radius

The radius of the Neutron star, in km. Keep frozen.

Mass

The mass of the Neutron star, in solar units. Keep frozen.

csi

Parameter linked to the photon escape time (order of some unities).

delta

Ratio between bulk and thermal Comptonization importances.

B

The magnetic field in units of 10^12 G.

Mdot

The mass accretion rate, in 10^17 g/s.

Te

The electron temperature in units of keV.

r0

The column radius in m.

D

The source distance in kpc. Keep frozen.

BBnorm

The normalization of the blackbody seed photon component (fix it to zero at first).

CYCnorm

The normalization of the cyclotron emission seed photon component (fix it to one).

FFnorm

The normalization of the Bremsstrahlung emission seed photon component (fix it to one).

norm

The normalization of the model (fix it to one).

Notes

This model is only available when used with XSPEC 12.11.0 or later.

References

1

https://heasarc.gsfc.nasa.gov/xanadu/xspec/manual/XSmodelBwcycl.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()