# spacepy.datamodel.resample

spacepy.datamodel.resample(data, time=[], winsize=0, overlap=0, st_time=None, outtimename='Epoch')

  resample a SpaceData to a new time interval

  Parameters
    data SpaceData or dmarray

      SpaceData with data to resample or dmarray with data to resample, variables can only be 1d or 2d, if time is specified only variables the same length as time are resampled, otherwise only variables with length equal to the longest length are resampled

    time array-like

      dmarray of times the correspond to the data

    winsize datetime.timedelta

      Time frame to average the data over

    overlap datetime.timedelta

      Overlap in the moving average

    st_time datetime.datetime

      Starting time for the resample, if not specified the time of the first data point is used (see spacepy.toolbox.windowMean)

  Returns
    ans SpaceData

      Resampled data, included keys are in the input keys (with the data caveats above) and Epoch which contains the output time

  Examples

      >>> import datetime
      >>> import spacepy.datamodel as dm
      >>> a = dm.SpaceData()
      >>> a.attrs['foo'] = 'bar'
      >>> a['a'] = dm.dmarray(range(10*2)).reshape(10,2)
      >>> a['b'] = dm.dmarray(range(10)) + 4
      >>> a['c'] = dm.dmarray(range(3)) + 10
      >>> times = [datetime.datetime(2010, 1, 1) + datetime.timedelta(hours=i) for i in range(10)]
      >>> out = dm.resample(a, times, winsize=datetime.timedelta(hours=2), overlap=datetime.timedelta(hours=0))
      >>> out.tree(verbose=1, attrs=1)
      # +
      # :|____foo (str [3])
      # |____Epoch (spacepy.datamodel.dmarray (4,))
      # |____a (spacepy.datamodel.dmarray (4, 2))
      # :|____DEPEND_0 (str [5])
      #
      # Things to note:
      #    - attributes are preserved
      #    - the output variables have their DEPEND_0 changed to Epoch (or outtimename)
      #    - each dimension of a 2d array is resampled individually