astrobase.lcmodels.flares module

This contains a stellar flare model from Pitkin+ 2014.

http://adsabs.harvard.edu/abs/2014MNRAS.445.2268P

astrobase.lcmodels.flares.flare_model(flareparams, times, mags, errs)[source]

This is a flare model function, similar to Kowalski+ 2011.

From the paper by Pitkin+ 2014: http://adsabs.harvard.edu/abs/2014MNRAS.445.2268P

Parameters:
  • flareparams (list of float) –

    This defines the flare model:

    [amplitude,
 flare_peak_time,
 rise_gaussian_stdev,
 decay_time_constant]

    where:

    amplitude: the maximum flare amplitude in mags or flux. If flux, then amplitude should be positive. If mags, amplitude should be negative.

    flare_peak_time: time at which the flare maximum happens.

    rise_gaussian_stdev: the stdev of the gaussian describing the rise of the flare.

    decay_time_constant: the time constant of the exponential fall of the flare.

  • times,mags,errs (np.array) – The input time-series of measurements and associated errors for which the model will be generated. The times will be used to generate model mags.
Returns:

(modelmags, times, mags, errs) – Returns the model mags evaluated at the input time values. Also returns the input times, mags, and errs.
Return type:

tuple
astrobase.lcmodels.flares.flare_model_residual(flareparams, times, mags, errs)[source]

This returns the residual between model mags and the actual mags.

Parameters:
  • flareparams (list of float) –

    This defines the flare model:

    [amplitude,
 flare_peak_time,
 rise_gaussian_stdev,
 decay_time_constant]

    where:

    amplitude: the maximum flare amplitude in mags or flux. If flux, then amplitude should be positive. If mags, amplitude should be negative.

    flare_peak_time: time at which the flare maximum happens.

    rise_gaussian_stdev: the stdev of the gaussian describing the rise of the flare.

    decay_time_constant: the time constant of the exponential fall of the flare.

  • times,mags,errs (np.array) – The input time-series of measurements and associated errors for which the model will be generated. The times will be used to generate model mags.
Returns:

The residuals between the input mags and generated modelmags, weighted by the measurement errors in errs.
Return type:

np.array