XScflow

class sherpa.astro.xspec.XScflow(name='cflow')

Bases: sherpa.astro.xspec.XSAdditiveModel

The XSPEC cflow model: cooling flow.

The model is described at [1]. The results of this model depend on the cosmology settings set with set_xscosmo.

slope

The power-law index of the emissivity function.

lowT

The minimum temperature, in keV.

highT

The maxmimum temperature, in keV.

Abundanc

The abundance relative to Solar, as set by set_xsabund.

redshift

The redshift of the plasma.

norm

The mass accretion rate (solar mass per year).

See also

XScevmkl, XSmkcflow

References

[1]	https://heasarc.gsfc.nasa.gov/xanadu/xspec/manual/XSmodelCflow.html

Attributes Summary

thawedparhardmaxes
thawedparhardmins
thawedparmaxes
thawedparmins
thawedpars
version_enabled

Methods Summary

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

thawedparhardmaxes

thawedparhardmins

thawedparmaxes

thawedparmins

thawedpars

version_enabled = True

Methods Documentation

apply(outer, *otherargs, **otherkwargs)

calc(pars, xlo, *args, **kwargs)

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(*arrays, **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()

set_center(*args, **kwargs)

startup(cache)

Called before a model may be evaluated multiple times.

See also

teardown()

teardown()

Called after a model may be evaluated multiple times.

See also

setup()