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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 _compute_anom_data_decay_all(self):
 """ Compute anomaly scores using a lagging window covering all the data points before. """

        anom_scores = {}
        values = self.time_series.values
        ema = utils.compute_ema(self.smoothing_factor, values)
        stdev = numpy.std(values)
        for i, (timestamp, value) in enumerate(self.time_series_items):
            anom_score = abs((value - ema[i]) / stdev) if stdev else value - ema[i]
            anom_scores[timestamp] = anom_score
        self.anom_scores = TimeSeries(self._denoise_scores(anom_scores))