TrapezoidFit

class exovetter.trapezoid_fit.TrapezoidFit(time_series, data_series, error_series, trp_parameters=None, trp_originalestimates=None, trp_planetestimates=None, t_ratio=0.2, error_scale=1.0, logger=None)

Bases: object

Class to handle trapezoid fits.

Parameters:

time_series, data_series, error_seriesarray_like

Data, uncertainty, and time series.

trp_parametersTrapezoidFitParameters or None

Trapezoid fit parameters. If not given, defaults are used.

trp_originalestimatesTrapezoidOriginalEstimates or None

Trapezoid fit original estimates. If not given, defaults are used.

trp_planetestimatesTrapezoidOriginalEstimates or None

Trapezoid fit planet model estimates. If not given, defaults are used.

t_ratiofloat

Value for TRatio in physvals.

error_scalefloat

Errorbars scaling for trp_likehood() residual calculation.

loggerobj

Python logger. If not given, default logger is used.

Attributes:

loggerobj

Logger.

parmTrapezoidFitParameters

Trapezoid fit parameters.

origestsTrapezoidOriginalEstimates

Trapezoid fit original estimates.

planetestsTrapezoidPlanetEstimates

Planet model estimates to be set in trp_estimate_planet().

normlcarray_like

Data series (light curve).

normesarray_like

Uncertainty of data series.

normotsarray_like

Original time series.

timezptfloat

Zeropoint of time series.

normtsarray_like

Normalized time series.

sampleitarray_like

Region for over-sampling.

fitdataarray_like

Region for fitting.

physvalsarray_like

Values corresponding to physval_names.

physval_minsarray_like

Minimum limits for physvals.

physval_maxsarray_like

Maximum limits for physvals.

physvalsavsarray_like

Store physvals parameters that are fixed during the calculation.

bestphysvalsarray_like

Best physvals to be calculated in trp_iterate_solution().

boundedvalsarray_like

Bounded version of physvals set in set_boundedvals().

boundedvalsavsarray_like

Store boundedvals parameters that are fixed during the calculation.

bestboundedvalsarray_like

Best boundedvals to be calculated in trp_iterate_solution().

fixedarray_like

Flags for whether a physvals element is fixed during fitting.

nparmint

Number of elements in physvals.

modellcarray_like

Trapezoid model to be set in trapezoid_model().

error_scalefloat

Errorbars scaling for trp_likehood() residual calculation.

chi2minfloat

Best chi-squared to be set in trp_iterate_solution().

likecountint

Number of times trp_likehood() was called.

minimizedbool

Flag of whether fitting has occured or not.

Attributes Summary

physval_names

Description of stored physval` values.

Methods Summary

plot_likehood([show_legend])	Plot results from trp_likehood().
set_boundedvals()	Convert parameters to bounded versions that the minimizer will use.
set_physvals()	Convert bounded parameter values that the minimizer uses to physical values.
trapezoid_fit(time_series, data_series, ...)	Perform a trapezoid fit to a normalized flux time series.
trapezoid_model()	Generate a subsampled model at the current parameters.
trapezoid_model_onemodel(ts, period, epoch, ...)	Make a trapezoid model at the given input parameters.
trapezoid_model_raw(epoch, depth, big_t, ...)	Generate another model at a different epoch depth duration and ingress time.
trp_estimate_planet()	Perform crude estimate of a planet model that is close to the trapezoid solution, which must be present for this to work.
trp_iterate_solution([n_iter, method, ...])	Perform multiple iterations starting from random initial conditions.
trp_likehood(pars)	Likelihood function used for Scipy optimizer.
trp_validate()	Validate that trapezoid fit inputs look reasonable.

Attributes Documentation

physval_names

Description of stored physval` values.

Methods Documentation

plot_likehood(show_legend=False)

Plot results from trp_likehood().

set_boundedvals()

Convert parameters to bounded versions that the minimizer will use.

This sets self.boundedvals.

Raises:

ValueError

Bounded values are invalid.

set_physvals()

Convert bounded parameter values that the minimizer uses to physical values.

This sets self.physvals.

Raises:

ValueError

Physical values are invalid.

classmethod trapezoid_fit(time_series, data_series, error_series, signal_period, signal_epoch, signal_duration, signal_depth, fit_trial_n=13, fit_region=4.0, error_scale=1.0, sample_n=15, seed=None)

Perform a trapezoid fit to a normalized flux time series. Assumes all data has the same cadence duration. Period is fixed during the trapezoid fitting.

Parameters:

time_seriesarray_like

Mid cadence time stamps.

data_seriesarray_like

Normalized time series.

error_seriesarray_like

Uncertainty (error) time series.

signal_periodfloat

Period of signal in days. Assumed fixed during model fitting.

signal_epochfloat

Estimated epoch of signal in days. Must be on the same system as time_series.

signal_durationfloat

Estimated signal duration in hours.

signal_depthfloat

Estimated signal depth in ppm.

fit_trial_nint

How many trial fits to perform starting at random initial locations. Increase this if the minimization is returning local minima.

fit_regionfloat

Fit data within fit_region * signal_duration of signal_epoch.

error_scalefloat

Scale the errorbars by this factor.

sample_nint

Subsample each cadence by this factor.

seedint or None

Seed for Numpy random generator. Usually used in testing for reproducibility.

Returns:

ioblkTrapezoidFit

Instance storing all the information pertaining to fit results.

trapezoid_model()

Generate a subsampled model at the current parameters.

This sets self.modellc.

Raises:

ValueError

Model generation failed.

classmethod trapezoid_model_onemodel(ts, period, epoch, depth, big_t, little_t, subsamplen)

Make a trapezoid model at the given input parameters.

You can save time if you want to generate many models by calling this once to generate the instance and then call trapezoid_model_raw() to generate the models at other inputs, thus bypassing some of the setup routines.

Parameters:

tsarray_like

Mid-cadence time stamps.

periodfloat

Period of signal. Assumed fixed during model generation.

epochfloat

Estimated epoch of signal. Must be on the same system as ts.

depthfloat

Model depth in ppm.

big_tfloat

Full transit duration in hours.

little_tfloat

Ingress time in hours.

subsamplenint

Subsample each cadence by this factor.

Returns:

ioblkTrapezoidFit

Instance that is used in the transit model. It has model light curve in its modellc attribute.

trapezoid_model_raw(epoch, depth, big_t, little_t)

Generate another model at a different epoch depth duration and ingress time.

Run this after you have a pre-existing TrapezoidFit instance from fit or from trapezoid_model_onemodel().

Note

Period is not variable at this point.

Parameters:

epochfloat

Estimated epoch of signal. Must be on the same system time series.

depthfloat

Model depth in ppm.

big_tfloat

Full transit duration in hours.

little_tfloat

Ingress time in hours.

Returns:

ioblkTrapezoidFit

New instance containing model light curve in its modellc attribute.

trp_estimate_planet()

Perform crude estimate of a planet model that is close to the trapezoid solution, which must be present for this to work.

This mainly sets self.planetests.

trp_iterate_solution(n_iter=20, method='Powell', options=None, seed=None)

Perform multiple iterations starting from random initial conditions. Attributes are updated in-place with the best solution in a chi-squared sense among the iterations.

Parameters:

n_iterint

Number of iterations to run.

methodstr

See scipy.optimize.minimize().

optionsdict or None

See scipy.optimize.minimize(). If not given, some pre-defined defaults are used.

seedint or None

Seed for Numpy random generator. Usually used in testing for reproducibility.

trp_likehood(pars)

Likelihood function used for Scipy optimizer. Some attributes are modified in-place as well.

Parameters:

parsarray_like

Vector of parameter values.

Returns:

residualsarray_like

Sum of squares of residuals of data - model.

trp_validate()

Validate that trapezoid fit inputs look reasonable.

Raises:

ValueError

Validation failed.