override def detect()

in src/main/scala/com/amazon/deequ/anomalydetection/seasonal/HoltWinters.scala [202:248]
37 lines of code
3 McCabe index (conditional complexity)

  override def detect(
      dataSeries: Vector[Double],
      searchInterval: (Int, Int) = (0, Int.MaxValue))
    : Seq[(Int, Anomaly)] = {

    require(dataSeries.nonEmpty, "Provided data series is empty")

    val (start, end) = searchInterval

    require(start < end,
      "Start must be before end")
    require(start >= 0 && end >= 0,
      "The search interval needs to be strictly positive")
    require(start >= seriesPeriodicity * 2,
      "Need at least two full cycles of data to estimate model")

    val numberOfObservationsToForecast =
      if (start >= dataSeries.size) {
        1
      } else {
        math.min(end, dataSeries.size) - start
      }

    val trainingSeries = dataSeries.slice(0, start)
    val optimalParameters = modelSelectionFor(trainingSeries, numberOfObservationsToForecast)
    println("Found optimal parameters for level, trend and seasonality to be " +
      s"${optimalParameters.alpha}, ${optimalParameters.beta} and ${optimalParameters.gamma} " +
      "respectively.")

    // Forecast with estimated parameters
    val modelResults = additiveHoltWinters(
      trainingSeries,
      seriesPeriodicity,
      numberOfObservationsToForecast,
      optimalParameters.alpha,
      optimalParameters.beta,
      optimalParameters.gamma
    )

    val residualsStandardDeviation =
      breeze.stats.stddev(modelResults.residuals.map(math.abs))

    require(modelResults.forecasts.size == numberOfObservationsToForecast)

    val testSeries = dataSeries.drop(start)
    findAnomalies(testSeries, modelResults.forecasts, start, residualsStandardDeviation)
  }