sccala.interplib.epoch_interp
=============================

.. py:module:: sccala.interplib.epoch_interp


Classes
-------

.. autoapisummary::

   sccala.interplib.epoch_interp.EpochDataSet


Module Contents
---------------

.. py:class:: EpochDataSet(data, data_error, tkde, red, mjd, snname='', errorfloor=0.0, errorscale=1.0, reg_min=20.0, reg_max=60.0, extrapolate=5.0, size=50, num_live_points=800, disable_mean_fit=False, disable_white_noise_fit=False, ignore_toe_uncertainty=False)

   Class wrapping data time series and providing
   interpolation functionality


   .. py:attribute:: data


   .. py:attribute:: data_error


   .. py:attribute:: tkde


   .. py:attribute:: mjd


   .. py:attribute:: snname
      :value: ''



   .. py:attribute:: errorfloor
      :value: 0.0



   .. py:attribute:: errorscale
      :value: 1.0



   .. py:attribute:: reg_min
      :value: 20.0



   .. py:attribute:: reg_max
      :value: 60.0



   .. py:attribute:: extrapolate
      :value: 5.0



   .. py:attribute:: toe


   .. py:attribute:: time


   .. py:attribute:: data_ex


   .. py:attribute:: data_error_ex


   .. py:attribute:: time_ex


   .. py:attribute:: mjd_ex


   .. py:attribute:: data_int
      :value: None



   .. py:attribute:: size
      :value: 50



   .. py:attribute:: num_live_points
      :value: 800



   .. py:attribute:: disable_mean_fit
      :value: False



   .. py:attribute:: disable_white_noise_fit
      :value: False



   .. py:attribute:: ignore_toe_uncertainty
      :value: False



   .. py:method:: get_results()


   .. py:method:: exclude_data(beginning=True)

      Removes one datapoint from the data set.
      If beginning is True, first element is removed, otherwise last.



   .. py:method:: diagnostic_plot(diagnostic, target, flux_interp=False, interactive=False)

      Plots the output of the interpolation



   .. py:method:: data_interp(target, step=0.1, date_low=None, date_high=None, diagnostic=None, no_reject=False, flux_interp=False, interactive=False)

      Interpolate dataocities using Gaussian Process regression

      Parameters
      ----------
      target : str
          Specifies as what the data is to be interpolated. Determines
          Gaussian Process kernel. Photometry has to contain 'phot' in
          target name.
      step : float
          Resolution of the interpolated data. Default: 0.1
      date_low : int or float
          Lower epoch limit of interpolation.
      date_up : int or float
          Upper epoch limit of interpolation.
      diagnostic : str or None
          Path to directory where diagnostic plots are to be saved.
      no_reject : bool
          If True velocity fits with increasing values will not
          be rejected. Default: False
      flux_interp : bool
          If True, data is converted to flux before interpolating.
          Exported values will be converted back to magnitudes.
          Only works with 'phot' in target. Default: False
      interactive : bool
          If True, diagnostic plots will be shown interactively.

      Returns
      -------
      median : float
          median data value at date days
      data_int_error_lower : float
      data_int_error_upper : float
          return values are in m/s
      date : float
          date to which the magnitudes have been interpolated