avocado.AstronomicalObject.fit_gaussian_process

AstronomicalObject.fit_gaussian_process(fix_scale=False, verbose=False, guess_length_scale=20.0, **preprocessing_kwargs)

Fit a Gaussian Process model to the light curve.

We use a 2-dimensional Matern kernel to model the transient. The kernel width in the wavelength direction is fixed. We fit for the kernel width in the time direction as different transients evolve on very different time scales.

Parameters:

• fix_scale (bool (optional)) – If True, the scale is fixed to an initial estimate. If False (default), the scale is a free fit parameter.
• verbose (bool (optional)) – If True, output additional debugging information.
• guess_length_scale (float (optional)) – The initial length scale to use for the fit. The default is 20 days.
• preprocessing_kwargs (kwargs (optional)) – Additional preprocessing arguments that are passed to preprocess_observations.

Returns:

• gaussian_process (function) – A Gaussian process conditioned on the object’s lightcurve. This is a wrapper around the george predict method with the object flux fixed.
• gp_observations (pandas.DataFrame) – The processed observations that the GP was fit to. This could have effects such as background subtraction applied to it.
• gp_fit_parameters (list) – A list of the resulting GP fit parameters.