astrobase.periodbase.utils module

This contains some utilities for periodbase functions.

FIXME: add an iterative peak-removal and refit mode to all period-finders here.

astrobase.periodbase.utils.resort_by_time(times, mags, errs)[source]

Resorts the input arrays so they’re in time order.

NOTE: the input arrays must not have nans in them.

Parameters:times,mags,errs (np.arrays) – The times, mags, and errs arrays to resort by time. The times array is assumed to be the first one in the input args.
Returns:times,mags,errs – The resorted times, mags, errs arrays.
Return type:np.arrays
astrobase.periodbase.utils.independent_freq_count(frequencies, times, conservative=True)[source]

This estimates the number of independent frequencies in a periodogram.

This follows the terminology on page 3 of Zechmeister & Kurster (2009):

M = DELTA_f / delta_f

where:

DELTA_f = freq.max() - freq.min()
delta_f = 1.0/(times.max() - times.min())
Parameters:
  • frequencies (np.array) – The frequencies array used for the calculation of the GLS periodogram.
  • times (np.array) – The array of input times used for the calculation of the GLS periodogram.
  • conservative (bool) –

    If True, will follow the prescription given in Schwarzenberg-Czerny (2003):

    http://adsabs.harvard.edu/abs/2003ASPC..292..383S

    and estimate the number of independent frequences as:

    min(N_obs, N_freq, DELTA_f/delta_f)
Returns:

M – The number of independent frequencies.
Return type:

int
astrobase.periodbase.utils.get_frequency_grid(times, samplesperpeak=5, nyquistfactor=5, minfreq=None, maxfreq=None, returnf0dfnf=False)[source]

This calculates a frequency grid for the period finding functions in this module.

Based on the autofrequency function in astropy.stats.lombscargle.

http://docs.astropy.org/en/stable/_modules/astropy/stats/lombscargle/core.html#LombScargle.autofrequency

Parameters:
  • times (np.array) – The times to use to generate the frequency grid over.
  • samplesperpeak (int) – The minimum sample coverage each frequency point in the grid will get.
  • nyquistfactor (int) – The multiplier over the Nyquist rate to use.
  • minfreq,maxfreq (float or None) – If not None, these will be the limits of the frequency grid generated.
  • returnf0dfnf (bool) – If this is True, will return the values of f0, df, and Nf generated for this grid.
Returns:

A grid of frequencies.
Return type:

np.array
astrobase.periodbase.utils.make_combined_periodogram(pflist, outfile, addmethods=False)[source]

This just puts all of the period-finders on a single periodogram.

This will renormalize all of the periodograms so their values lie between 0 and 1, with values lying closer to 1 being more significant. Periodograms that give the same best periods will have their peaks line up together.

Parameters:
  • pflist (list of dict) –

    This is a list of result dicts from any of the period-finders in periodbase. To use your own period-finders’ results here, make sure the result dict is of the form and has at least the keys below:

    {'periods': np.array of all periods searched by the period-finder,
 'lspvals': np.array of periodogram power value for each period,
 'bestperiod': a float value that is the period with the highest
               peak in the periodogram, i.e. the most-likely actual
               period,
 'method': a three-letter code naming the period-finder used; must
           be one of the keys in the
           `astrobase.periodbase.METHODLABELS` dict,
 'nbestperiods': a list of the periods corresponding to periodogram
                 peaks (`nbestlspvals` below) to annotate on the
                 periodogram plot so they can be called out
                 visually,
 'nbestlspvals': a list of the power values associated with
                 periodogram peaks to annotate on the periodogram
                 plot so they can be called out visually; should be
                 the same length as `nbestperiods` above,
 'kwargs': dict of kwargs passed to your own period-finder function}
  • outfile (str) – This is the output file to write the output to. NOTE: EPS/PS won’t work because we use alpha transparency to better distinguish between the various periodograms.
  • addmethods (bool) – If this is True, will add all of the normalized periodograms together, then renormalize them to between 0 and 1. In this way, if all of the period-finders agree on something, it’ll stand out easily. FIXME: implement this kwarg.
Returns:

The name of the generated plot file.
Return type:

str