astrobase.varclass.periodicfeatures module

This contains functions that calculate various light curve features using information about periods and fits to phased light curves.

astrobase.varclass.periodicfeatures.lcfit_features(times, mags, errs, period, fourierorder=5, transitparams=(-0.01, 0.1, 0.1), ebparams=(-0.2, 0.3, 0.7, 0.5), sigclip=10.0, magsarefluxes=False, fitfailure_means_featurenan=False, verbose=True)[source]

This calculates various features related to fitting models to light curves.

This function:

  • calculates R_ij and phi_ij ratios for Fourier fit amplitudes and phases.
  • calculates the reduced chi-sq for fourier, EB, and planet transit fits.
  • calculates the reduced chi-sq for fourier, EB, planet transit fits w/2 x period.
Parameters:
  • times,mags,errs (np.array) – The input mag/flux time-series to calculate periodic features for.
  • period (float) – The period of variabiity to use to phase the light curve.
  • fourierorder (int) – The Fourier order to use to generate sinusoidal function and fit that to the phased light curve.
  • transitparams (list of floats) – The transit depth, duration, and ingress duration to use to generate a trapezoid planet transit model fit to the phased light curve. The period used is the one provided in period, while the epoch is automatically obtained from a spline fit to the phased light curve.
  • ebparams (list of floats) – The primary eclipse depth, eclipse duration, the primary-secondary depth ratio, and the phase of the secondary eclipse to use to generate an eclipsing binary model fit to the phased light curve. The period used is the one provided in period, while the epoch is automatically obtained from a spline fit to the phased light curve.
  • sigclip (float or int or sequence of two floats/ints or None) –

    If a single float or int, a symmetric sigma-clip will be performed using the number provided as the sigma-multiplier to cut out from the input time-series.

    If a list of two ints/floats is provided, the function will perform an ‘asymmetric’ sigma-clip. The first element in this list is the sigma value to use for fainter flux/mag values; the second element in this list is the sigma value to use for brighter flux/mag values. For example, sigclip=[10., 3.], will sigclip out greater than 10-sigma dimmings and greater than 3-sigma brightenings. Here the meaning of “dimming” and “brightening” is set by physics (not the magnitude system), which is why the magsarefluxes kwarg must be correctly set.

    If sigclip is None, no sigma-clipping will be performed, and the time-series (with non-finite elems removed) will be passed through to the output.

  • magsarefluxes (bool) – Set this to True if the input measurements in mags are actually fluxes.
  • fitfailure_means_featurenan (bool) – If the planet, EB and EBx2 fits don’t return standard errors because the covariance matrix could not be generated, then the fit is suspicious and the features calculated can’t be trusted. If fitfailure_means_featurenan is True, then the output features for these fits will be set to nan.
  • verbose (bool) – If True, will indicate progress while working.
Returns:

A dict of all the features calculated is returned.
Return type:

dict
astrobase.varclass.periodicfeatures.periodogram_features(pgramlist, times, mags, errs, sigclip=10.0, pdiff_threshold=0.0001, sidereal_threshold=0.0001, sampling_peak_multiplier=5.0, sampling_startp=None, sampling_endp=None, verbose=True)[source]

This calculates various periodogram features (for each periodogram).

The following features are obtained:

  • For all best periods from all periodogram methods in pgramlist, calculates the number of these with peaks that are at least sampling_peak_multiplier x time-sampling periodogram peak at the same period. This indicates how likely the pgramlist periodogram peaks are to being real as opposed to just being caused by time-sampling window-function of the observations.
  • For all best periods from all periodogram methods in pgramlist, calculates the number of best periods which are consistent with a sidereal day (1.0027379 and 0.9972696), likely indicating that they’re not real.
  • For all best periods from all periodogram methods in pgramlist, calculates the number of cross-wise period differences for all of these that fall below the pdiff_threshold value. If this is high, most of the period-finders in pgramlist agree on their best period results, so it’s likely the periods found are real.
Parameters:
  • pgramlist (list of dicts) – This is a list of dicts returned by any of the periodfinding methods in astrobase.periodbase. This can also be obtained from the resulting pickle from the :py:func:astrobase.lcproc.periodsearch.run_pf` function. It’s a good idea to make pgramlist a list of periodogram lists from all magnitude columns in the input light curve to test periodic variability across all magnitude columns (e.g. period diffs between EPD and TFA mags)
  • times,mags,errs (np.array) – The input flux/mag time-series to use to calculate features. These are used to recalculate the time-sampling L-S periodogram (using astrobase.periodbase.zgls.specwindow_lsp()) if one is not present in pgramlist. If it’s present, these can all be set to None.
  • sigclip (float or int or sequence of two floats/ints or None) –

    If a single float or int, a symmetric sigma-clip will be performed using the number provided as the sigma-multiplier to cut out from the input time-series.

    If a list of two ints/floats is provided, the function will perform an ‘asymmetric’ sigma-clip. The first element in this list is the sigma value to use for fainter flux/mag values; the second element in this list is the sigma value to use for brighter flux/mag values. For example, sigclip=[10., 3.], will sigclip out greater than 10-sigma dimmings and greater than 3-sigma brightenings. Here the meaning of “dimming” and “brightening” is set by physics (not the magnitude system), which is why the magsarefluxes kwarg must be correctly set.

    If sigclip is None, no sigma-clipping will be performed, and the time-series (with non-finite elems removed) will be passed through to the output.

  • pdiff_threshold (float) – This is the max difference between periods to consider them the same.
  • sidereal_threshold (float) – This is the max difference between any of the ‘best’ periods and the sidereal day periods to consider them the same.
  • sampling_peak_multiplier (float) – This is the minimum multiplicative factor of a ‘best’ period’s normalized periodogram peak over the sampling periodogram peak at the same period required to accept the ‘best’ period as possibly real.
  • sampling_endp (sampling_startp,) – If the pgramlist doesn’t have a time-sampling Lomb-Scargle periodogram, it will be obtained automatically. Use these kwargs to control the minimum and maximum period interval to be searched when generating this periodogram.
  • verbose (bool) – If True, will indicate progress and report errors.
Returns:

Returns a dict with all of the periodogram features calculated.
Return type:

dict
astrobase.varclass.periodicfeatures.phasedlc_features(times, mags, errs, period, nbrtimes=None, nbrmags=None, nbrerrs=None)[source]

This calculates various phased LC features for the object.

Some of the features calculated here come from:

Kim, D.-W., Protopapas, P., Bailer-Jones, C. A. L., et al. 2014, Astronomy and Astrophysics, 566, A43, and references therein (especially Richards, et al. 2011).

Parameters:
  • times,mags,errs (np.array) – The input mag/flux time-series to calculate the phased LC features for.
  • period (float) – The period used to phase the input mag/flux time-series.
  • nbrtimes,nbrmags,nbrerrs (np.array or None) – If nbrtimes, nbrmags, and nbrerrs are all provided, they should be ndarrays with times, mags, errs of this object’s closest neighbor (close within some small number x FWHM of telescope to check for blending). This function will then also calculate extra features based on the neighbor’s phased LC using the period provided for the target object.
Returns:

Returns a dict with phased LC features.
Return type:

dict