Esempio n. 1
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  private void initLearningMetrics() {
    if (learningMetricsInitialized) {
      return;
    }
    double defaultWeight = SystemDao.getDefaultWeight();
    double lastWeekLift = getDemandUplift(SystemDao.getReviewCycleStartDate());
    Sales beginOfRunCycleSales = getSales(SystemDao.getReviewCycleStartDate());
    double beginOfRunCycleRcAvgSales = 0;
    if (beginOfRunCycleSales != null) {
      beginOfRunCycleRcAvgSales = beginOfRunCycleSales.getRcAvgSales();
    }

    rcAvgSales =
        getWeightedWeight1(learningWeekCounter, defaultWeight) * epSales / lastWeekLift
            + (1 - getWeightedWeight1(learningWeekCounter, defaultWeight))
                * beginOfRunCycleRcAvgSales;

    // Tim's documentation states:
    // Its important sales metrics are initialized to AVG_WEEKLY_SALES based on the initialization
    // logic.
    // This estimates initial values based on different combinations of the PLs product and location
    // hierarchies dependent on the specific situation for that PL
    rcAvgSalesActual = rcAvgSales;
    rcAvgDemand = rcAvgSales;
    rcOldAvgDemand = rcAvgSales;
    rcAvgDemandActual = rcAvgSales;
    epAvgInv = rcAvgSales;
    rcWass2 = Math.pow(rcAvgSales, 2);
    learningMetricsInitialized = true;
  }
Esempio n. 2
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  private String salesToString() {
    StringBuffer epSalesActualBf = new StringBuffer();
    epSalesActualBf.append("epSalesActual|");

    StringBuffer epSalesBf = new StringBuffer();
    epSalesBf.append("epSales|");

    StringBuffer rcSalesBf = new StringBuffer();
    rcSalesBf.append("rcSales|");

    StringBuffer rcAvgSalesBf = new StringBuffer();
    rcAvgSalesBf.append("rcAvgSales|");

    StringBuffer rcSalesActualBf = new StringBuffer();
    rcSalesActualBf.append("rcSalesActual|");

    StringBuffer rcAvgSalesActualBf = new StringBuffer();
    rcAvgSalesActualBf.append("rcAvgSalesActual|");

    Iterator<Years> yrItr = salesMap.keySet().iterator();
    Map<LocalDate, Sales> currSalesMap;
    LocalDate currDate;
    Years currYr;
    Sales currSale;
    // Populate Sale buffers
    while (yrItr.hasNext()) {
      currYr = yrItr.next();
      currSalesMap = salesMap.get(currYr);
      Iterator<LocalDate> itr = currSalesMap.keySet().iterator();
      while (itr.hasNext()) {
        currDate = itr.next();
        currSale = currSalesMap.get(currDate);
        // epSaleActual
        epSalesActualBf.append(currDate);
        epSalesActualBf.append(":");
        epSalesActualBf.append(currSale.getEpSalesActual());
        epSalesActualBf.append("|");
        // epSale
        epSalesBf.append(currDate);
        epSalesBf.append(":");
        epSalesBf.append(currSale.getEpSales());
        epSalesBf.append("|");
        // rc sales actual
        rcSalesActualBf.append(currDate);
        rcSalesActualBf.append(":");
        rcSalesActualBf.append(currSale.getRcSalesActual());
        rcSalesActualBf.append("|");
        // rc average sales actual
        rcAvgSalesActualBf.append(currDate);
        rcAvgSalesActualBf.append(":");
        rcAvgSalesActualBf.append(currSale.getRcAvgSalesActual());
        rcAvgSalesActualBf.append("|");
        // rc sales
        rcSalesBf.append(currDate);
        rcSalesBf.append(":");
        rcSalesBf.append(currSale.getRcSales());
        rcSalesBf.append("|");
        // rc sales average
        rcAvgSalesBf.append(currDate);
        rcAvgSalesBf.append(":");
        rcAvgSalesBf.append(currSale.getRcAvgSales());
        rcAvgSalesBf.append("|");
      }
    }
    epSalesActualBf.append(";\n");
    epSalesBf.append(";\n");
    rcSalesActualBf.append(";\n");
    rcAvgSalesActualBf.append(";\n");
    rcSalesBf.append(";\n");
    rcAvgSalesBf.append(";\n");

    StringBuffer retBf = new StringBuffer();
    retBf.append(epSalesActualBf.toString());
    retBf.append(epSalesBf.toString());
    retBf.append(rcSalesActualBf.toString());
    retBf.append(rcAvgSalesActualBf.toString());
    retBf.append(rcSalesBf.toString());
    retBf.append(rcAvgSalesBf.toString());
    retBf.append("\n");

    return retBf.toString();
  }
Esempio n. 3
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  private void processWeeklyMetrics() {
    // On the end of the review cycle (Sat night) the rcAvgDemand does not undergo weekly learning
    // For this exercise we do not have time granulity  so weekly processing is done Sunday for the
    // prior week

    LocalDate crc = SystemDao.getCrc();
    LocalDate prevCRCStartDate = SystemDao.getReviewCycleStartDate(); // getPreviousCRCStartDate();
    Sales salesData = getSales(crc);

    Sales beginOfPeriodSalesData = getSales(prevCRCStartDate);
    double beginOfPeriodRcAvgSales = 0;
    double beginOfPeriodRcActualAvgSales = 0;
    if (beginOfPeriodSalesData != null) {
      beginOfPeriodRcAvgSales = beginOfPeriodSalesData.getRcAvgSales();
      beginOfPeriodRcActualAvgSales = beginOfPeriodSalesData.getRcAvgSalesActual();
    }

    Demand demandData = getDemand(crc);
    Demand beginOfPeriodDemandData = getDemand(prevCRCStartDate);
    double beginOfPeriodRcAvgDemand = 0;
    double beginOfPeriodRcAvgActualDemand = 0;
    if (beginOfPeriodDemandData != null) {
      beginOfPeriodRcAvgDemand = beginOfPeriodDemandData.getRcAvgDemand();
      beginOfPeriodRcAvgActualDemand = beginOfPeriodDemandData.getRcAvgDemandActual();
    }
    double defaultWeight = SystemDao.getDefaultWeight();

    double lastWeekLift = getDemandUplift(prevCRCStartDate);
    double weight = 1.0;
    if (statusCd == STATUS_CD.LEARNING) {
      weight = getWeightedWeight1(learningWeekCounter, defaultWeight);
    } else if (statusCd == STATUS_CD.ACTIVE) {
      weight = getWeight1(learningWeekCounter);
    }

    rcAvgSalesActual =
        (weight * (salesData.getRcSalesActual() / lastWeekLift))
            + ((1 - weight) * beginOfPeriodRcActualAvgSales);
    rcAvgSales =
        (weight * (salesData.getRcSales() / lastWeekLift))
            + ((1 - weight) * beginOfPeriodRcAvgSales);
    rcAvgDemand =
        (weight * (demandData.getRcDemand() / lastWeekLift))
            + ((1 - weight) * beginOfPeriodRcAvgDemand);
    rcAvgDemandActual =
        (weight * (demandData.getRcDemandActual() / lastWeekLift))
            + ((1 - weight) * beginOfPeriodRcAvgActualDemand);

    // error checking
    if (rcAvgDemand == 0 && statusCd != STATUS_CD.INACTIVE) {
      System.out.println("Error: 0 demand when product status is not inactive");
    }
    if (rcAvgDemand >= 4 * rcAvgSales) {
      rcAvgSales = 4 * rcAvgSalesActual;
      System.out.println("Error: RC Actual Sales greater then 4 times RC Average Sales");
    }
    if (rcAvgDemand >= 3 * rcAvgSalesActual) {
      rcAvgSales = 3 * rcAvgSalesActual;
      System.out.println("Error: RC Actual Sales greater then 3 times RC Actual Average Sales");
    }

    storeWeeklyMetrics(crc);
    this.learningWeekCounter++;
    // this is the end of the review cycle reset hasBeenOffRange
    if (hasBeenOffRange) {
      hasBeenOffRange = false;
    }
    resetRcAccumulators();
  }