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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def _check_normalization(self):
 """Checks, if the TimeSeries is normalized. :return: Returns :py:const:`True` if all data entries of the TimeSeries have an equal temporal distance, :py:const:`False` otherwise. """

        lastDistance = None
        distance     = None
        for idx in xrange(len(self) - 1):
            distance = self[idx+1][0] - self[idx][0]

            # first run
            if lastDistance is None:
                lastDistance = distance
                continue

            if lastDistance != distance:
                return False

            lastDistance = distance

        return True