Priors

class radvel.prior.EccentricityPrior(num_planets, upperlims=0.99)

Physical eccentricities

Prior to keep eccentricity between 0 and a specified upper limit.

Parameters:

• num_planets (int or list) – Planets to apply the eccentricity prior. If an integer is given then all planets with indexes up to and including the specified integer will be included in the prior. If a list is given then the prior will only be applied to the specified planets.
• upperlims (float or list of floats) – List of eccentricity upper limits to assign to each of the planets. If a float is given then all planets must have eccentricities less then this value. If a list of floats is given then each planet can have a different eccentricity upper limit.

class radvel.prior.Gaussian(param, mu, sigma)

Gaussian prior

Guassian prior on a given parameter.

Parameters:

• param (string) – parameter label
• mu (float) – center of Gaussian prior
• sigma (float) – width of Gaussian prior

class radvel.prior.HardBounds(param, minval, maxval)

Prior for hard boundaries

This prior allows for hard boundaries to be established for a given parameter.

Parameters:

• param (string) – parameter label
• minval (float) – minimum allowed value
• maxval (float) – maximum allowed value

class radvel.prior.InformativeBaselinePrior(param, baseline, duration=0.0)

Informative baseline prior suggested by A. Vanderburg (see Blunt et al. 2019).

This prior follows the distribution:

\[ \begin{align}\begin{aligned}p(x) \propto 1\, \mathrm{{if}}\, x-t_{{d}} \lt B\\ \propto (B+t_{{d}})/x\, \mathrm{{else}}\end{aligned}\end{align} \]

with upper bound.

Parameters:

• param (string) – parameter label
• baseline (float) – \(B\) in eq above
• duration (float) – \(t_{{d}}\) in eq above (default: 0.0)

class radvel.prior.Jeffreys(param, minval, maxval)

Jeffrey’s prior

This prior follows the distribution:

\[p(x) \propto \frac{1}{x}\]

with upper and lower bounds to prevent singularity at \(x=0\).

Parameters:

• param (string) – parameter label
• minval (float) – minimum allowed value
• maxval (float) – maximum allowed value

class radvel.prior.ModifiedJeffreys(param, minval, maxval, kneeval)

Modified Jeffry’s prior

This prior follows the distribution:

\[p(x) \propto \frac{1}{x-x_0}\]

with upper bound.

Parameters:

• param (string) – parameter label
• kneeval (float) – “knee” of Jeffrey’s prior (\(x_0\) in eq above)
• minval (float) – minimum allowed value. minval must be larger than kneeval
• maxval (float) – maximum allowed value

class radvel.prior.NumericalPrior(param_list, values, bw_method=None)

Prior defined by an input array of values

Wrapper for scipy.stats.gaussian_kde.

This prior uses Gaussian Kernel Density Estimation to estimate the probability density function from which a set of values are randomly drawn.

Useful for defining a prior given a posterior obtained from a complementary fitting process. For example, you might use transit data to obtain constraints on secosw and sesinw, then use the posterior on secosw as a prior for a RadVel fit.

Parameters:

• param_list (list of str) – list of parameter label(s).
• values (numpy array of float) – values of param you wish to use to define this prior. For example, this might be a posterior array of values of secosw derived from transit data. In case of univariate data this is a 1-D array, otherwise a 2-D array with shape (# of elements in param_list, # of data points).
• bw_method (str, scalar, or callable [optional]) – see scipy.stats.gaussian_kde

Note: the larger the input array of values, the longer it will take for calls to this prior to be evaluated. Consider thinning large input arrays to speed up performance.

class radvel.prior.PositiveKPrior(num_planets)

K must be positive

A prior to prevent K going negative. Be careful with this as it can introduce a bias to larger K values.

Parameters:num_planets (int) – Number of planets. Used to ensure K for each planet is positive

class radvel.prior.SecondaryEclipsePrior(planet_num, ts, ts_err)

Secondary eclipse prior

Implied prior on eccentricity and omega by specifying measured secondary eclipse time

Parameters:

• planet_num (int) – Number of planet with measured secondary eclipse
• ts (float) – Secondary eclipse midpoint time. Should be in the same units as the timestamps of your data.
• ts_err (float) – Uncertainty on secondary eclipse time

class radvel.prior.UserDefinedPrior(param_list, func, tex_rep)

Interface for user to define a prior

with an arbitrary functional form.

Parameters:

• param_list (list of str) – list of parameter label(s).
• func (function) – a Python function that takes in a list of values (ordered as in param_list), and returns the corresponding log-value of a pdf.
• tex_rep (str) – TeX-readable string representation of this prior, to be passed into radvel report and plotting code.

Example

>>> def myPriorFunc(inp_list):
...     if inp_list[0] > 0. and inp_list[0] < 1.:
...         return 0.
...     else:
...         return -np.inf
>>> myTexString = 'Uniform Prior on $\sqrt{e}$'
>>> myPrior = radvel.prior.UserDefinedPrior(['se'], myPriorFunc, myTexString)

Note

func must be properly normalized; i.e. integrating over the entire parameter space must give a probability of 1.