Atten

class sherpa.astro.models.Atten(name='atten')

Bases: sherpa.models.model.RegriddableModel1D

Model the attenuation by the Inter-Stellar Medium (ISM).

This model calculates the transmission of the interstellar medium using the description of the ISM absorption of 1. It includes neutral He autoionization features. Between 1.2398 and 43.655 Angstroms (i.e. in the 0.28-10 keV range) the model also accounts for metals as described in 2. It should only be used when the independent axis has units of Angstroms.

hcol

The column density of HI in atoms cm^-2.

heiRatio

The ratio of the HeI to HI column densities.

heiiRatio

The ratio of the HeII to HI column densities.

Notes

The code uses the best available photoionization cross-sections to date from the atomic data literature and combines them in an arbitrary mixture of the three ionic species: HI, HeI, and HeII.

This model provided courtesy of Pat Jelinsky.

The grid version is evaluated by numerically intgerating the function over each bin using a non-adaptive Gauss-Kronrod scheme suited for smooth functions 3, falling over to a simple trapezoid scheme if this fails.

References

1

Rumph, Bowyer, & Vennes 1994, AJ 107, 2108 http://adsabs.harvard.edu/abs/1994AJ….107.2108R

2

Morrison & McCammon 1983, ApJ 270, 119 http://adsabs.harvard.edu/abs/1983ApJ…270..119M

3

https://www.gnu.org/software/gsl/manual/html_node/QNG-non_002dadaptive-Gauss_002dKronrod-integration.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

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

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()