asterion.priors#
Prior models.
Module Contents#
- class AsyFunction(delta_nu, epsilon=None)[source]#
Bases:
PriorPrior on the linear asymptotic function \(f\), where \(f(n) = \Delta\nu (n + \epsilon)\).
- Parameters
delta_nu (dist_like) – Prior for the large frequency separation \(\Delta\nu\). Pass either the arguments of
dist.Normal, or adist.Distribution.epsilon (dist_like) – Prior for the phase term \(\epsilon\). Pass either the arguments of
dist.LogNormal, or adist.Distribution. Defaults to(np.log(1.4), 0.4).
- delta_nu#
The distribution for \(\Delta\nu\).
- epsilon#
The distribution for \(\epsilon\).
- class CZGlitchFunction(nu_max, log_tau, phi=None)[source]#
Bases:
_GlitchFunctionPrior on the base of the convective zone glitch function \(f\), where \(f(\nu) = a_\mathrm{CZ} \nu^{-2} \sin(4\pi\tau_\mathrm{CZ}\nu + \phi_\mathrm{CZ})\)
The priors for the glitch parameters \(a_\mathrm{He},b_\mathrm{He},\tau_\mathrm{He}\) are inferred from that of the frequency at maximum power, \(\nu_\max\) using scaling relations derived from stellar models (Lyttle et al. in prep.).
- Parameters
nu_max (dist_like) – The prior for the frequency at maximum power, \(\nu_\max\). Pass either the arguments of
dist.Normalor adist.Distribution.log_tau (dist_like) – The prior for the acoustic depth of the glitch, \(\tau_\mathrm{BCZ}\). Pass either the arguments of
dist.Normal, or adist.Distribution.phi (dist_like) – The prior for the phase of the glitch, \(\phi_\mathrm{BCZ}\). Pass either the arguments of
dist.Uniform, or adist.Distribution.
- log_a#
The distribution for the glitch amplitude parameter \(\log a_\mathrm{BCZ}\)
- log_tau#
The distribution for \(\log\tau_\mathrm{BCZ}\).
- phi#
The distribution for \(\phi_\mathrm{BCZ}\).
- amplitude(self, nu)[source]#
The amplitude of the glitch, \(a_\mathrm{CZ} / \nu^{-2}\).
- Parameters
nu (array_like) – Mode frequency, \(\nu\).
- Returns
Base of the convective zone glitch amplitude.
- Return type
- class HeGlitchFunction(nu_max, log_tau, phi=None)[source]#
Bases:
_GlitchFunctionPrior on the second ionisation of helium glitch function \(f\), where \(f(\nu) = a_\mathrm{He} \nu \exp(-b_\mathrm{He} \nu^2) \sin(4\pi\tau_\mathrm{He}\nu + \phi_\mathrm{He})\).
The priors for the glitch parameters \(a_\mathrm{He},b_\mathrm{He},\tau_\mathrm{He}\) are inferred from that of the frequency at maximum power, \(\nu_\max\) using scaling relations derived from stellar models (Lyttle et al. in prep.).
- Parameters
nu_max (dist_like) – The prior for the frequency at maximum power, \(\nu_\max\). Pass either the arguments of
dist.Normal, or adist.Distribution.log_tau (dist_like) – The prior for the acoustic depth of the glitch, \(\tau_\mathrm{He}\). Pass either the arguments of
dist.Normal, or adist.Distribution.phi (dist_like) – The prior for the phase of the glitch, \(\phi_\mathrm{He}\). Pass either the arguments of
dist.Uniform, or adist.Distribution.
- log_a#
The distribution for the glitch amplitude parameter \(\log a_\mathrm{He}\).
- log_b#
The distribution for the glitch decay parameter \(\log b_\mathrm{He}\).
- log_tau#
The distribution for \(\log\tau_\mathrm{He}\).
- phi#
The distribution for \(\phi_\mathrm{He}\).
- amplitude(self, nu)[source]#
The amplitude of the glitch, \(a_\\mathrm{He} \\nu \\exp(-b_\\mathrm{He} \\nu^2)\).
- Parameters
nu (array_like) – Mode frequency, \(\\nu\).
- Returns
Helium glitch amplitude.
- Return type
- class Prior(*args, **kwargs)[source]#
Prior class.
A prior is a model which returns a parameter or function when called and has no observed sample sites.
- Parameters
*args – Positional arguments to display in the object representation.
**kwargs – Keyword arguments to display in the object representation.