TransitLightCurve

class salter.TransitLightCurve(times=None, fluxes=None, errors=None, quarters=None, name=None, params=None)

Bases: salter.LightCurve

Container for a single transit light curve. Subclass of LightCurve.

Parameters:

times : ndarray

Times in JD

fluxes : ndarray

Fluxes (normalized or not)

errors : ndarray

Uncertainties on the fluxes

quarters : ndarray (optional)

Kepler Quarter for each flux

name : str

Name this light curve (optional)

Methods Summary

chi2_lc_3param(p)	Compute chi^2 for a three-parameter light curve model with parameters in tuple p consisting of the planet-star radius ratio, and two limb-darkening parameters (Kipping 2013)
fit_lc_3param()	Fit three-parameter light curve model, and replace the transit parameters in self.params with the best fit planet-star radius ratio, and two limb-darkening parameters (Kipping 2013).
fit_linear_baseline([cadence, …])	Find OOT portions of transit light curve using similar method to LightCurve.mask_out_of_transit, fit linear baseline to OOT.
fit_polynomial_baseline([order, cadence, …])	Find OOT portions of transit light curve using similar method to LightCurve.mask_out_of_transit, fit linear baseline to OOT
remove_linear_baseline([plots, cadence])	Find OOT portions of transit light curve using similar method to LightCurve.mask_out_of_transit, fit linear baseline to OOT, divide whole light curve by that fit.
remove_polynomial_baseline([order, plots, …])	Find OOT portions of transit light curve using similar method to LightCurve.mask_out_of_transit, fit linear baseline to OOT, divide whole light curve by that fit.
scale_by_baseline(linear_baseline_params)
subtract_add_divide_without_outliers(…[, …])
subtract_polynomial_baseline([plots, order, …])	Find OOT portions of transit light curve using similar method to LightCurve.mask_out_of_transit, fit polynomial baseline to OOT, subtract whole light curve by that fit.

Methods Documentation

chi2_lc_3param(p)

Compute chi^2 for a three-parameter light curve model with parameters in tuple p consisting of the planet-star radius ratio, and two limb-darkening parameters (Kipping 2013)

fit_lc_3param()

Fit three-parameter light curve model, and replace the transit parameters in self.params with the best fit planet-star radius ratio, and two limb-darkening parameters (Kipping 2013).

fit_linear_baseline(cadence=<Quantity 30. min>, return_near_transit=False, plots=False)

Find OOT portions of transit light curve using similar method to LightCurve.mask_out_of_transit, fit linear baseline to OOT.

Parameters:

cadence : Quantity (optional)

Length of the exposure time for each flux. Default is 1 min.

return_near_transit : bool (optional)

Return the mask for times in-transit.

Returns:

linear_baseline : numpy.ndarray

Baseline trend of out-of-transit fluxes

near_transit : numpy.ndarray (optional)

The mask for times in-transit.

fit_polynomial_baseline(order=2, cadence=<Quantity 30. min>, plots=False, mask=None)

Find OOT portions of transit light curve using similar method to LightCurve.mask_out_of_transit, fit linear baseline to OOT

remove_linear_baseline(plots=False, cadence=<Quantity 30. min>)

Find OOT portions of transit light curve using similar method to LightCurve.mask_out_of_transit, fit linear baseline to OOT, divide whole light curve by that fit.

Parameters:

cadence : Quantity (optional)

Length of the exposure time for each flux. Default is 1 min.

plots : bool (optional)

Show diagnostic plots.

remove_polynomial_baseline(order=2, plots=False, cadence=<Quantity 30. min>)

Find OOT portions of transit light curve using similar method to LightCurve.mask_out_of_transit, fit linear baseline to OOT, divide whole light curve by that fit.

Parameters:

cadence : Quantity (optional)

Length of the exposure time for each flux. Default is 1 min.

plots : bool (optional)

Show diagnostic plots.

scale_by_baseline(linear_baseline_params)

subtract_add_divide_without_outliers(quarterly_max, order=2, cadence=<Quantity 30. min>, outlier_error_multiplier=50, outlier_tolerance_depth_factor=0.2, plots=False)

subtract_polynomial_baseline(plots=False, order=2, cadence=<Quantity 30. min>)

Find OOT portions of transit light curve using similar method to LightCurve.mask_out_of_transit, fit polynomial baseline to OOT, subtract whole light curve by that fit.