FM

class sherpa.astro.optical.FM(name='fm')[source] [edit on github]

Bases: sherpa.models.model.RegriddableModel1D

UV extinction curve: Fitzpatrick and Massa 1988.

The UV extinction is calculated using 1. This model is intended to be used to modify another model (e.g. by multiplying the two together). It is for use when the independent axis is in Angstrom.

ebv

E(B-V)

x0

Position of the Drude bump.

width

Width of the Drude bump.

c1

The intercept of the linear term.

c2

The slope of the linear term.

c3

Normalization of the Drude bump.

c4

Normalization of the FUV curvature.

See also

CCM, LMC, Seaton, SM, SMC, XGAL

Notes

When evaluated on a binned grid, the lower-edges of the bins are used for the calculation.

References

1

Fitzpatrick and Massa 1988 http://adsabs.harvard.edu/abs/1988ApJ…328..734F

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

The maximum limits of the thawed parameters.

thawedparmins

The minimum limits of the thawed parameters.

thawedpars

The thawed parameters of the model.

Methods Summary

apply(outer, *otherargs, **otherkwargs)

cache_clear()

Clear the cache.

cache_status()

Display the cache status.

calc(p, x[, xhi])

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

cache = 5

The maximum size of the cache.

ndim = 1

A one-dimensional model.

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.

Methods Documentation

apply(outer, *otherargs, **otherkwargs) [edit on github]
cache_clear() [edit on github]

Clear the cache.

cache_status() [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, x, xhi=None, **kwargs)[source] [edit on github]

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() [edit on github]
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
>>> mybox = Box1D()
>>> request_space = np.arange(1, 10, 0.1)
>>> regrid_model = mybox.regrid(request_space, interp=linear_interp)
reset() [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=False) [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() [edit on github]

Called after a model may be evaluated multiple times.

See also

startup