CONAN._classes.load_lightcurves.supersample
===========================================

.. py:method:: CONAN._classes.load_lightcurves.supersample(lc_list=None, ss_factor=1, verbose=True)

   Supersample long intergration time of lcs in lc_list. This divides each exposure of the lc into int(ss_factor) subexposures to attain a sampling rate of exp_time/ss_factor.
   the exp_time is calculated from the  time spacing of the data points as `np.ceil(np.median(np.diff(t)))`
   e.g. with ss_factor=30, a lc with 30 minute exp_time will be divided into 30 subexposures of 1 minute each.
   while 2 minute sampling will require ss_factor=15.

   :param lc_list: list of lc files to supersample. set to "all" to use supersampling for all lc files. Default is None.
   :type lc_list: list, str, optional
   :param ss_factor: exposure time of each lc to supersample rounded to the nearest minute. if different for each lc in lc_list, give list with exp_time for each lc.
                     Default is 1 for no supersampling.
   :type ss_factor: float, tuple, list, optional
   :param verbose: print output. Default is True.
   :type verbose: bool, optional

   .. attribute:: _ss

      list of supersampling objects for each light curve. Default is None for no supersampling.

      :type: list

   .. rubric:: Examples

   To supersample a light curve that has a long cadence of 30mins (0.0208days) to 1 min, 30 points are needed to subdivide each exposure.

   >>> lc_obj.supersample( lc_list   = "lc1.dat",
   >>>                     ss_factor = 30)