def METHOD_NAME(daily_data):
  '''
  Data has to be provided as daily_data
  it will compute the difference between the current day and the previous day
  i.e. X(t+1) - X(t), nans for the last index 
  in Booth et al., 2017, vprime = (x(t+1) - x(t))/2. 
  '''
  # pad the right of the array with nan values along the first dimension
  # then extract the values from the 2nd column (index = 1) to the end
  # this will give us a shifted array of daily data, i.e. X(t+1)
  daily_data_shift = np.pad(daily_data, ((0,1), (0,0), (0,0)), mode='constant', constant_values=np.nan)[1:, :, :]
  return (daily_data_shift - daily_data)/2. # X(t+1) - X(t), with nan values for the last time dimension