XSrgsxsrc

class sherpa.astro.xspec.XSrgsxsrc(name='xsrgsxsrc')

Bases: sherpa.astro.xspec.XSConvolutionKernel

The XSPEC rgsxsrc convolution model: convolve an RGS spectrum for extended emission.

The model is described at 1.

New in version 4.12.2.

order

The order, which must be -1 to -3 inclusive.

Notes

Unlike XSPEC, the convolution model is applied directly to the model, or models, rather than using the multiplication symbol.

The set_xsxset function must be used to set the RGS_XSOURCE_FILE value to point to a file as described in 1.

References

1(1,2)

https://heasarc.gsfc.nasa.gov/xanadu/xspec/manual/XSmodelRgxsrc.html

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	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)
cache_clear()	Clear the cache.
cache_status()	Display the cache status.
calc(pars, rhs, *args, **kwargs)	Evaluate the convolved 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.

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.

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)

cache_clear()

Clear the cache.

cache_status()

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(pars, rhs, *args, **kwargs)

Evaluate the convolved model.

Note that this method is not cached by sherpa.models.modelCacher1d (may change in the future).

Parameters

• pars (sequence of numbers) – The parameters of the convolved model. The first npars parameters (where npars is the lenth of the objecs pars attribute) are applied to the convolution model, and the remaining are passed to the rhs model.

• rhs (sherpa.models.model.ArithmeticModel) – The model that is being convolved.

• *args – The model grid. There should be two arrays (the low and high edges of the bin) to make sure the wrapped model is evaluated correctly.

• **kwargs – At present all additional keyword arguments are dropped.

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

startup