private ProductDemandEstimated[] ExtractEstimatedValue(Dictionary <string, string>[] output)
{
var result = new List <ProductDemandEstimated>();
foreach (var dic in output)
{
var pd = new ProductDemandEstimated();
try
{
pd.Quantity = float.Parse(dic[MlSettings.ScoredValueFieldName]);
pd.Locationid = int.Parse(dic["Locationid"]);
pd.Plu = int.Parse(dic["PLU"]);
pd.Year = int.Parse(dic["Year"]);
pd.Month = int.Parse(dic["Month"]);
pd.Day = int.Parse(dic["Day"]);
}
catch (FormatException e)
{
var message = JsonConvert.SerializeObject(dic);
throw new FormatException(message, e);
}
result.Add(pd);
}
return(result.ToArray());
}
public ProductDemandEstimated[] GetMovingAveragePredictions(ProductDemand[] data)
{
var result = new List <ProductDemandEstimated>();
var salesHistory = DataSource.GetSalesHistory();
foreach (var demand in data)
{
// 4 weeks average
var productSales = salesHistory.Where(s =>
s.Plu == demand.Plu &&
s.Locationid == demand.Locationid &&
s.Salesdate < demand.Salesdate &&
s.Salesdate >= demand.Salesdate.AddDays(-4 * 7)).ToArray();
var salesAverage = 0f;
if (productSales.Length > 0)
{
salesAverage = productSales
.Select(s => s.Quantity)
.Sum() / (4 * 7); // 28 sale days
}
var estimatedDemand = new ProductDemandEstimated
{
Locationid = demand.Locationid,
Plu = demand.Plu,
Year = demand.Year,
Month = demand.Month,
Day = demand.Day,
Quantity = salesAverage // estimation
};
result.Add(estimatedDemand);
}
return(result.ToArray());
}
