asterion.models#
Probabilistic models for asteroseismic oscillation mode frequencies.
Module Contents#
- class GlitchModel(nu_max, delta_nu, teff=None, epsilon=None, seed=0, window_width='full')[source]#
Bases:
ModelAsteroseismic glitch model.
\[\nu_\mathrm{obs} \sim \mathcal{GP}(m(n), k(n, n') + \sigma^2\mathcal{I})\]Where the mean function is,
\[\begin{split}m(n) &= \nu_\mathrm{bkg} + \delta_\mathrm{He} + \delta_\mathrm{CZ},\\ \nu_\mathrm{bkg} &= f_\mathrm{bkg}(n),\\ \delta_\mathrm{He} &= f_\mathrm{He}(\nu_\mathrm{bkg}),\\ \delta_\mathrm{CZ} &= f_\mathrm{CZ}(\nu_\mathrm{bkg}),\end{split}\]and the kernel function is,
\[k(n, n') = \sigma_k^2 \exp\left( - \frac{(n' - n)^2}{l^2} \right).\]- Parameters
n (array_like) – Radial order of model observations.
nu_max (dist_like) – Prior on the frequency at maximum power.
delta_nu (dist_like) – Prior on the large frequency separation.
teff (dist_like, optional) – Prior on the effective temperature. This is used for estimating a prior on the glitch acoustic depths. If None (default), a prior of Normal(5000, 700) is assumed.
epsilon (dist_like, optional) – Prior on the asymptotic phase parameter.
num_pred (int) – The number of points in radial order for which to make predictions.
seed (int) – The seed used to generate samples from the prior on the glitch periods (acoustic depths) tau_he and tau_cz.
window_width (float) – The number of delta_nu either side of nu_max over which to average the helium glitch amplitude for the parameter ‘he_amplitude’.
- n#
Radial order of model observations.
- Type
- n_pred#
Radial order of model predictions.
- Type
- class Model(*args, **kwargs)[source]#
Bases:
asterion.priors.PriorModel class.
A model is a probabilistic object which may be given to Inference. It does not need to return anything during inference, but should have at least one observed sample sites.