API - Configuring Erebus

Planet

To find the parameters for a planet we recommend you use the Exoplanet Archive where t0 is the time of conjunction (tc on the Exoplanet archive), p is the orbital period in days, rp_rstar is the ratio of the planet's radius to the star's radius, a_rstar is the ratio of the planet's semi-major axis to the star's radius, inc is the inclination of the planet (in degrees), ecc is the eccentricity of the planet (0 inclusive to 1 exclusive), and w is the agument of periastron of the planet (in degrees).

Class which represents known planet values with uncertainties. Loaded from a yaml file and optionally validated against a schema. Uncertainties are expressed by writing the values into the yaml file as a list of floats, where the first value is the absolute value of the measurement. The second value is taken as the symmetric error, and if a third value is provided it is taken a the upper error.

Attributes:

Name	Type	Description
name	str	The name of the planet.
t0	uncertainties.core.Variable | float	Midpoint time of reference transit in BJD
t0_lookup_path	str	Optional replacement for t0, relative path to csv file with calculated TTVs (Two columns: t0 in BJD-2,450,000, error)
a_rstar	uncertainties.core.Variable | float	The ratio of semi-major axis to star radius.
p	uncertainties.core.Variable | float	The period of the planet in days.
rp_rstar	uncertainties.core.Variable | float	The ratio of the planet's radius to the star's radius.
inc	uncertainties.core.Variable | float	The inclination of the planet in degrees.
ecc	uncertainties.core.Variable | float	The eccentricity of the planet (0 inclusive to 1 exclusive).
w	uncertainties.core.Variable | float	The argument of periastron of the planet (degrees).

Methods:

Name	Description
get_closest_t0	Given a start time in BJD-2,400,000.5, use the lookup file to get
get_next_t0	Given a start time in BJD-2,400,000.5, use the lookup file to get
get_predicted_tsec	Given a start time in BJD-2,400,000.5, use the lookup file or t0

get_closest_t0(obs_start)

Given a start time in BJD-2,400,000.5, use the lookup file to get the closest t0

get_next_t0(obs_start)

Given a start time in BJD-2,400,000.5, use the lookup file to get the following t0

get_predicted_tsec(obs_start)

Given a start time in BJD-2,400,000.5, use the lookup file or t0 and P to get the next eclipse time

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ErebusRunConfig

Bases: pydantic.BaseModel

Settings for running through the entire Erebus pipeline. Serializable to/from YAML. One of perform_joint_fit or perform_individual_fits must be true else the run will not do anything.

Attributes:

Name	Type	Description
fit_fnpca	bool	Optional bool to use FN-PCA in the systematic model.
fit_exponential	bool	Optional bool to use an exponential curve in the systematic model.
fit_linear	bool	Optional bool to use a linear slope in the systematic model.
perform_joint_fit	bool	Optional bool to fit all visits together with a shared eclipse depth.
perform_individual_fits	bool	Optional bool to fit each visit with their own eclipse depth.
calints_path	str	Relative path from the folder containing this file to where the .fits files are.
planet_path	str	Relative path from the folder containing this file to where the planet config is.
aperture_radius	int	Pixel radius for aperture photometry.
annulus_start	int	Inner pixel radius of disk used for background subtraction.
annulus_end	int	Outer pixel radius of disk used for background subtraction.
skip_visits	list[int]	Optional list of indices to skip when doing individual fits. Index based on visit ID.
trim_integrations	list[int]	Length-two list with the number of integrations to clip from the start and end. Optional.
star_position	list[int]	X and y pixel coordinates of the star. Optional (will search for the star or assume its centered).
prevent_negative_eclipse_depth	bool	Optional bool to force eclipse depth to be positive.
fix_eclipse_timing	bool	Optional bool to force t0, period, ecosw to be fixed

Methods:

Name	Description
set_custom_systematic_model	Optionally provide a callable function and dictionary of Parameter objects for bayesian priors.
set_custom_systematic_model_prior_for_visit_index	Optionally override custom systematic model priors for specific visits

set_custom_systematic_model(model, params)

Optionally provide a callable function and dictionary of Parameter objects for bayesian priors.

Order of parameters must match their order in the model method signature.

Params are given as a dictionary of their names (matching the method signature) to a Parameter object.

Model method signature must start with x.

When used in conjunction with built-in fitting model provided by Erebus this model will be multiplied by those fitting models and a best-fit y-offset applied.

set_custom_systematic_model_prior_for_visit_index(index, params)

Optionally override custom systematic model priors for specific visits

Params are given as a dictionary of their names (matching the method signature) to a Parameter object.

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Parameters

Represents a parameter with Bayesian priors To be used with mcmc_model.py

Methods:

Name	Description
fixed	Creates a fixed parameter
gamma_prior	Creates a gamma prior
gaussian_prior	Creates a gaussian prior
positive_gaussian_prior	Creates a positive gaussian prior
set_initial_value	Set the initial value of this parameter. Will print an error if this value is impossible according to our priors
set_value	Set the current value of this parameter, will update the log_prior accordingly
uniform_prior	Creates a uniform prior, constant between min and max

fixed(value) classmethod

Creates a fixed parameter

gamma_prior(alpha, beta) classmethod

Creates a gamma prior

gaussian_prior(mu, sigma) classmethod

Creates a gaussian prior

positive_gaussian_prior(mu, sigma) classmethod

Creates a positive gaussian prior

set_initial_value(value)

Set the initial value of this parameter. Will print an error if this value is impossible according to our priors

set_value(value)

Set the current value of this parameter, will update the log_prior accordingly

uniform_prior(initial_guess, minimum, maximum) classmethod

Creates a uniform prior, constant between min and max