ModShift

class exovetter.vetters.ModShift(lc_name='flux')

Bases: BaseVetter

Modshift vetter.

Parameters:

lc_namestr

Name of the flux array in the lightkurve object.

Attributes:

timearray

Time values of the TCE, populated by run().

lc_namestr

Input lc_name.

fluxarray

Flux values of the TCE, populated by run().

period_daysfloat

period of the TCE in days, populated by run().

epoch_daysfloat

epoch of the TCE in days, populated by run().

duration_hrsfloat

transit duration of the TCE in hours, populated by run().

boxastropy.units.Quantity object

Flux from boxcar model of the TCE, populated by run().

metricsdict

modshift result dictionary populated by run().

Methods Summary

plot()	Generate a diagnostic plot.
run(tce, lightcurve[, plot])	Runs modshift.compute_modeshift_metrics to populate the vetter object.

Methods Documentation

plot()

Generate a diagnostic plot.

Parameters:

tce, lightcurve

See run().

run(tce, lightcurve, plot=False)

Runs modshift.compute_modeshift_metrics to populate the vetter object.

Parameters:

tcetce object

tce object is a dictionary that contains information about the tce to vet, like period, epoch, duration, depth

lightcurvelightkurve object

lightkurve object with the time and flux to use for vetting.

plot: bool

option to show plot when initialy populating the metrics. Same as using the plot() method.

Returns:

metricsdict

modshift result dictionary containing the following:

pri : primary signal sec : secondary signal ter : tertiary signal pos : largest positive event false_alarm_threshold : threshold for the 1 sigma false alarm Fred : red noise level, std(convolution) divided by std(lightcurve)