Dered

class sherpa.astro.models.Dered(name='dered')

Bases: sherpa.models.model.ArithmeticModel

A de-reddening model.

The integrate flag of this model should be set to False when used with an integrated grid.

rv

The ratio of total to selective extinction.

nhgal

The absorbing column density of H_gal in units of 10^20 cm^-2.

Notes

This dereddening model uses the analytic formula for the mean extension law described in [1]:

A(lambda) = E(B-V) * (a * rv + b)
          = 1.086 tau(lambda)

where tau(lambda) is the wavelength-dependent optical depth:

I(lambda) = I(0) * exp(-tau(lambda))

and a and b are computed using wavelength-dependent formulae, which are not reproduced here, for the wavelength range 1000 Angstroms to 3.3 microns. The relationship between the color excess and the column density (nhgal) is [2]:

E(B-V) = nhgal / 58.0

where the units of nhgal is 10^20 cm^-2. The value of the ratio of total to selective extinction, rv, is initially set to 3.1, the standard value for the diffuse ISM. The final model form is:

I(lambda) = I(0) exp(-nhgal * (a * ev + b) / (58.0 * 1.086)

This model provided courtesy of Karl Forster.

References

[1]	Cardelli, Clayton, & Mathis 1989, ApJ 345, 245 http://adsabs.harvard.edu/abs/1989ApJ...345..245C

[2]	Bohlin, Savage, & Drake 1978, ApJ 224, 132 http://adsabs.harvard.edu/abs/1978ApJ...224..132B

Attributes Summary

thawedparhardmaxes
thawedparhardmins
thawedparmaxes
thawedparmins
thawedpars

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.
reset()
set_center(\*args, \*\*kwargs)
startup()
teardown()

Attributes Documentation

thawedparhardmaxes

thawedparhardmins

thawedparmaxes

thawedparmins

thawedpars

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.

reset()

set_center(*args, **kwargs)

startup()

teardown()