Gauss1D¶
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class
sherpa.models.basic.
Gauss1D
(name='gauss1d')[source] [edit on github]¶ Bases:
sherpa.models.model.RegriddableModel1D
One-dimensional gaussian function.
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fwhm
¶ The Full-Width Half Maximum of the gaussian. It is related to the sigma value by: FWHM = sqrt(8 * log(2)) * sigma.
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pos
¶ The center of the gaussian.
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ampl
¶ The amplitude refers to the maximum peak of the model.
See also
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
thawedparhardmaxes
thawedparhardmins
thawedparmaxes
thawedparmins
thawedpars
Methods Summary
apply
(outer, *otherargs, **otherkwargs)calc
(pars, xlo, *args, **kwargs)get_center
()guess
(dep, *args, **kwargs)Set an initial guess for the parameter values. regrid
(*arrays, **kwargs)The class RegriddableModel1D allows the user to evaluate in the requested space then interpolate onto the data space. reset
()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. Attributes Documentation
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thawedparhardmaxes
¶
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thawedparhardmins
¶
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thawedparmaxes
¶
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thawedparmins
¶
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thawedpars
¶
Methods Documentation
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apply
(outer, *otherargs, **otherkwargs) [edit on github]¶
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calc
(pars, xlo, *args, **kwargs) [edit on github]¶
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get_center
()[source] [edit on github]¶
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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.
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regrid
(*arrays, **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)
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reset
() [edit on github]¶
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set_center
(pos, *args, **kwargs)[source] [edit on github]¶
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startup
(cache) [edit on github]¶ Called before a model may be evaluated multiple times.
See also
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teardown
() [edit on github]¶ Called after a model may be evaluated multiple times.
See also
setup()
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