Gauss1D

class sherpa.models.basic.Gauss1D(name='gauss1d')[source] [edit on github]

Bases: RegriddableModel1D

One-dimensional gaussian function.

fwhm

The Full-Width Half Maximum of the gaussian. It is related to the sigma value by: FWHM = sqrt(8 * log(2)) * sigma.

pos

The center of the gaussian.

ampl

The amplitude refers to the maximum peak of the model.

Notes

The functional form of the model for points is:

f(x) = ampl * exp(-4 * log(2) * (x - pos)^2 / fwhm^2)

and for an integrated grid it is the integral of this over the bin.

Examples

Compare the gaussian and normalized gaussian models:

>>> m1 = sherpa.models.basic.Gauss1D()
>>> m2 = sherpa.models.basic.NormGauss1D()
>>> m1.pos, m2.pos = 10, 10
>>> m1.ampl, m2.ampl = 10, 10
>>> m1.fwhm, m2.fwhm = 5, 5
>>> m1(10)
10.0
>>> m2(10)
1.8788745573993026
>>> m1.fwhm, m2.fwhm = 1, 1
>>> m1(10)
10.0
>>> m2(10)
9.394372786996513

The normalised version will sum to the amplitude when given an integrated grid - i.e. both low and high edges rather than points - that covers all the signal (and with a bin size a lot smaller than the FWHM):

>>> m1.fwhm, m2.fwhm = 12.2, 12.2
>>> grid = np.arange(-90, 110, 0.01)
>>> glo, ghi = grid[:-1], grid[1:]
>>> m1(glo, ghi).sum()
129.86497637060958
>>> m2(glo, ghi).sum()
10.000000000000002

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) Clear the cache. Display the cache status. calc(*args, **kwargs) Evaluate the model on a grid. freeze() Freeze any thawed parameters of the model. 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(pos, *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.

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.

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.

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(*args, **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).

freeze() [edit on github]

Freeze any thawed parameters of the model.

get_center()[source] [edit on github]
guess(dep, *args, **kwargs)[source] [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(pos, *args, **kwargs)[source] [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.

teardown

teardown() [edit on github]

Called after a model may be evaluated multiple times.