XSTableModel

class sherpa.astro.xspec.XSTableModel(filename, name='xstbl', parnames=(), initvals=(), delta=(), mins=(), maxes=(), hardmins=(), hardmaxes=(), nint=0, addmodel=False, addredshift=False, addescale=False, etable=False)[source] [edit on github]

Bases: XSModel

Interface to XSPEC table models.

XSPEC supports loading in user-supplied data files for use as a table model. This class provides a low-level way to access this functionality. A simpler interface is provided by read_xstable_model and sherpa.astro.ui.load_xstable_model.

Changed in version 4.16.0: The hard_max and hard_min values of the redshift parameter (for those models that support it) can now be changed. This should be done with care as it could cause memory corruption or a crash. Parameters with negative DELTA values are now made frozen, to match XSPEC. Support for models which use the ESCALE keyword has been added.

Changed in version 4.14.0: The etable argument has been added to allow exponential table models to be used.

Parameters:
  • filename (str) – The name of the FITS file containing the data for the XSPEC table model; the format is described in Arnaud, Keith A, The File Format for XSPEC Table Models.

  • name (str) – The name to use for the instance of the table model.

  • parnames (sequence) – The parameter names. This corresponds to the “NAME” column from the “PARAMETER” block of the input file. Any invalid characters in each name will be replaced by the ‘_’ character.

  • initvals (sequence) – The initial values for each parameter. This corresponds to the “INITIAL” column from the “PARAMETER” block of the input file.

  • delta (sequence) – The delta value for each parameter. This corresponds to the “DELTA” column from the “PARAMETER” block of the input file. A negative value marks a parameter as being frozen.

  • mins (sequence) – The valid range of each parameter. These correspond to the “BOTTOM”, “TOP”, “MINIMUM”, and “MAXIMUM” columns from the “PARAMETER” block of the input file.

  • maxes (sequence) – The valid range of each parameter. These correspond to the “BOTTOM”, “TOP”, “MINIMUM”, and “MAXIMUM” columns from the “PARAMETER” block of the input file.

  • hardmins (sequence) – The valid range of each parameter. These correspond to the “BOTTOM”, “TOP”, “MINIMUM”, and “MAXIMUM” columns from the “PARAMETER” block of the input file.

  • hardmaxes (sequence) – The valid range of each parameter. These correspond to the “BOTTOM”, “TOP”, “MINIMUM”, and “MAXIMUM” columns from the “PARAMETER” block of the input file.

  • nint (int) – The first nint parameters are marked as thawed by default, the remaining default to frozen.

  • addmodel (bool) – Is this an additive model (True) or multiplicative model (False)? It should be set to the value of the “ADDMODEL” keyword of the primary header of the input file. When False the etable keyword is used to distinguish between mtable and etable models.

  • addredshift (bool) – If True then a redshift parameter is added to the parameters. It should be set to the value of the “REDSHIFT” keyword of the primary header of the input file.

  • addescale (bool) – If True then an Escale parameter is added to the parameters. It should be set to the value of the “ESCALE” keyword of the primary header of the input file.

  • etable (bool) – When addmodel is False this defines whether the file is a mtable model (False, the default) or an etable model (True).

Notes

There is no support for table models that provide multiple spectra per parameter: that is, those with the NXFLTEXP keyword set.

Attributes Summary

cache

The maximum size of the cache.

lpars

Return any linked parameters.

ndim

A one-dimensional model.

pars

Return the parameters of the model.

thawedparhardmaxes

The hard maximum values for the thawed parameters.

thawedparhardmins

The hard minimum values for the thawed parameters.

thawedparmaxes

The maximum limits of the thawed parameters.

thawedparmins

The minimum limits of the thawed parameters.

thawedpars

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(p, *args, **kwargs)

Calculate the model given the parameters and grid.

fold(*args, **kwargs)

freeze()

Freeze any thawed parameters of the model.

get_center()

get_thawed_pars()

Return the thawed parameter objects.

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.

thaw()

Thaw any frozen parameters of the model.

Attributes Documentation

cache = 5

The maximum size of the cache.

lpars

Return any linked parameters.

This only returns linked parameters that are not related to the model, and each parameter is not repeated.

Added in version 4.16.1.

See also

pars

Examples

By default there are no linked parameters:

>>> from sherpa.models.basic import Gauss2D
>>> mdl = Gauss2D("mdl")
>>> len(mdl.pars)
6
>>> mdl.lpars
()

Force the model to have identical xpos and ypos parameters. Since the linked parameter value (mdl.xpos) is part of the model it is not included in lpars:

>>> mdl.ypos = mdl.xpos
>>> len(mdl.pars)
6
>>> mdl.lpars
()

Add a link to allow the sigma term to be fit rather than FWHM. Since the linked parameter - here from the Const1D model - is not a part of the model it is included in lpars:

>>> import numpy as np
>>> from sherpa.models.basic import Const1D
>>> sigma = Const1D("sigma")
>>> mdl.fwhm = 2 * np.sqrt(2 * np.log(2)) * sigma.c0
>>> len(mdl.pars)
6
>>> mdl.lpars
(<Parameter 'c0' of model 'sigma'>,)
ndim: int | None = 1

A one-dimensional model.

pars

Return the parameters of the model.

This does not include any linked parameters.

Changed in version 4.16.1: The pars field can no-longer be set directly. Individual elements can still be changed.

See also

lpars

thawedparhardmaxes

The hard maximum values for the thawed parameters.

The minimum and maximum range of the parameters can be changed with thawedparmins and thawedparmaxes but only within the range given by thawedparhardmins to thawparhardmaxes.

thawedparhardmins

The hard minimum values for the thawed parameters.

The minimum and maximum range of the parameters can be changed with thawedparmins and thawedparmaxes but only within the range given by thawedparhardmins to thawparhardmaxes.

thawedparmaxes

The maximum limits of the thawed parameters.

Get or set the maximum limits of the thawed parameters of the model as a list of numbers. If there are no thawed parameters then [] is used. The ordering matches that of the pars attribute.

See also

thawedpars, thawedarhardmaxes, thawedparmins

thawedparmins

The minimum limits of the thawed parameters.

Get or set the minimum limits of the thawed parameters of the model as a list of numbers. If there are no thawed parameters then [] is used. The ordering matches that of the pars attribute.

See also

thawedpars, thawedarhardmins, thawedparmaxes

thawedpars

The thawed parameters of the model.

Get or set the thawed parameters of the model as a list of numbers. If there are no thawed parameters then [] is used. The ordering matches that of the pars attribute.

version_enabled = True

Methods Documentation

apply(outer, *otherargs, **otherkwargs) [edit on github]
cache_clear() None [edit on github]

Clear the cache.

cache_status() None [edit on github]

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(p, *args, **kwargs)[source] [edit on github]

Calculate the model given the parameters and grid.

Notes

XSPEC models must always be evaluated with low and high bin edges. Although supported by the XSPEC model interface the ability to evaluate using an XSPEC-style grid (n+1 values for n bins which we pad with a 0), we do not allow this here since it complicates the handling of the regrid method.

Keyword arguments are ignored.

fold(*args, **kwargs)[source] [edit on github]
freeze() None [edit on github]

Freeze any thawed parameters of the model.

get_center() [edit on github]
get_thawed_pars() list[Parameter] [edit on github]

Return the thawed parameter objects.

This includes linked parameters, which complicates the min/max settings, since the range on the components of a linked parameter does not match that of the original parameter, which is an issue when the limits are exceeded.

Added in version 4.16.1.

guess(dep, *args, **kwargs) [edit on github]

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) [edit on github]

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
>>> from sherpa.utils import linear_interp
>>> mybox = Box1D()
>>> request_space = np.arange(1, 10, 0.1)
>>> regrid_model = mybox.regrid(request_space, interp=linear_interp)
reset() None [edit on github]

Reset the parameter values.

Restores each parameter to the last value it was set to. This allows the parameters to be easily reset after a fit.

set_center(*args, **kwargs) [edit on github]
startup(cache: bool = False) None [edit on github]

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() None [edit on github]

Called after a model may be evaluated multiple times.

See also

startup

thaw() None [edit on github]

Thaw any frozen parameters of the model.

Those parameters that are marked as “always frozen” are skipped.