numina.modeling
— Model for fitting
- class numina.modeling.enclosed.EnclosedGaussian(amplitude, stddev, **kwargs)
Enclosed Gaussian model
- static evaluate(x, amplitude, stddev)
Evaluate the model on some input variables.
- static fit_deriv(x, amplitude, stddev)
- param_names = ('amplitude', 'stddev')
Names of the parameters that describe models of this type.
The parameters in this tuple are in the same order they should be passed in when initializing a model of a specific type. Some types of models, such as polynomial models, have a different number of parameters depending on some other property of the model, such as the degree.
When defining a custom model class the value of this attribute is automatically set by the ~astropy.modeling.Parameter attributes defined in the class body.
- class numina.modeling.gaussbox.GaussBox(amplitude=1.0, mean=0.0, stddev=1.0, hpix=0.5, **kwargs)
Model for fitting a 1D Gaussina convolved with a square
- static evaluate(x, amplitude, mean, stddev, hpix)
Evaluate the model on some input variables.
- static fit_deriv(x, amplitude, mean, stddev, hpix)
- param_names = ('amplitude', 'mean', 'stddev', 'hpix')
Names of the parameters that describe models of this type.
The parameters in this tuple are in the same order they should be passed in when initializing a model of a specific type. Some types of models, such as polynomial models, have a different number of parameters depending on some other property of the model, such as the degree.
When defining a custom model class the value of this attribute is automatically set by the ~astropy.modeling.Parameter attributes defined in the class body.
- numina.modeling.gaussbox.gauss_box_model(x, amplitude=1.0, mean=0.0, stddev=1.0, hpix=0.5)
Integrate a Gaussian profile.
- numina.modeling.gaussbox.gauss_box_model_deriv(x, amplitude=1.0, mean=0.0, stddev=1.0, hpix=0.5)
Derivative of the integral of a Gaussian profile.
- numina.modeling.sumofgauss.sum_of_gaussian_factory(N)
Return a model of the sum of N Gaussians and a constant background.