GaussianAbsorption1D¶
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class
astropy.modeling.functional_models.GaussianAbsorption1D[source] [edit on github]¶ Bases:
astropy.modeling.functional_models.BaseGaussian1DOne dimensional Gaussian absorption line model.
Parameters: amplitude : float
Amplitude of the gaussian absorption.
mean : float
Mean of the gaussian.
stddev : float
Standard deviation of the gaussian.
Other Parameters: fixed : a dict
A dictionary
{parameter_name: boolean}of parameters to not be varied during fitting. True means the parameter is held fixed. Alternatively thefixedproperty of a parameter may be used.tied : dict
A dictionary
{parameter_name: callable}of parameters which are linked to some other parameter. The dictionary values are callables providing the linking relationship. Alternatively thetiedproperty of a parameter may be used.bounds : dict
eqcons : list
A list of functions of length
nsuch thateqcons[j](x0,*args) == 0.0in a successfully optimized problem.ineqcons : list
A list of functions of length
nsuch thatieqcons[j](x0,*args) >= 0.0is a successfully optimized problem.See also
Notes
Model formula:
f(x) = 1 - A e^{- \frac{\left(x - x_{0}\right)^{2}}{2 \sigma^{2}}}
Examples
import numpy as np import matplotlib.pyplot as plt from astropy.modeling.models import GaussianAbsorption1D plt.figure() s1 = GaussianAbsorption1D() r = np.arange(-5, 5, .01) for factor in range(1, 4): s1.amplitude = factor plt.plot(r, s1(r), color=str(0.25 * factor), lw=2) plt.axis([-5, 5, -3, 2]) plt.show()
Attributes Summary
param_namesMethods Summary
evaluate(x, amplitude, mean, stddev)GaussianAbsorption1D model function. fit_deriv(x, amplitude, mean, stddev)GaussianAbsorption1D model function derivatives. Attributes Documentation
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param_names= ('amplitude', 'mean', 'stddev')¶
Methods Documentation
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static
evaluate(x, amplitude, mean, stddev)[source] [edit on github]¶ GaussianAbsorption1D model function.
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static
fit_deriv(x, amplitude, mean, stddev)[source] [edit on github]¶ GaussianAbsorption1D model function derivatives.
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