public override async Task <FResult> Forecast(List <double> data, int lead, string savePlot, int frequency, int plotWidth, int plotHeight)
{
var returnData = new FResult();
var template = $@"
data <- ts(data, {(frequency > 0 ? $"frequency = {frequency}" : "")})
forec <- holt(data,h={lead})
";
returnData = await IBasicMethod.Forecast(returnData, data, template, savePlot, plotWidth, plotHeight);
return(returnData);
}
public async Task <ActionResult> Result(ForecastingRequest request)
{
ForecastingResult dataResult = new ForecastingResult();
List <double> items = null;
using (var db = new dbContext()) {
items = db.Sales_Histories.Where(x => x.Entry_No >= request.From && x.Entry_No <= request.To).OrderBy(x => x.Entry_No).Select(x => (double)x.Sales_Quantity).ToList();
}
IBasicMethod method = null;
foreach (var cMethod in methods)
{
if (cMethod.GetMethodName() == request.Method)
{
method = cMethod;
}
}
if (method == null)
{
dataResult.Error = "Couldn't found method that you need!";
return(View(dataResult));
}
FResult result = null;
var imageName = Guid.NewGuid().ToString();
var dir = Server.MapPath("/Images");
var imageFileName = Path.Combine(dir, imageName + ".png");
dataResult.Image = imageName;
try {
result = await method.Forecast(items, request.Count, imageFileName, request.Periodicity, request.ImageWidth, request.ImageHeight);
} catch (Exception ex) {
dataResult.Error = "Unknown error appeared while trying to forecast data";
return(View(dataResult));
}
if (result.Data != null)
{
dataResult.ForecastData = result.Data;
dataResult.Low80Data = result.Low80;
dataResult.High80Data = result.High80;
dataResult.Low95Data = result.Low95;
dataResult.High95Data = result.High95;
dataResult.Error = "";
}
else
{
dataResult.Error = result.Error;
}
return(View(dataResult));
}
public override async Task <FResult> Forecast(List <double> data, int lead, string savePlot, int frequency, int plotWidth, int plotHeight)
{
var returnData = new FResult();
if (frequency <= 1)
{
returnData.Error = "Period should be higher than 1";
return(returnData);
}
var template = $@"
data <- ts(data, frequency = {frequency})
forec <- hw(data,h={lead})
";
returnData = await IBasicMethod.Forecast(returnData, data, template, savePlot, plotWidth, plotHeight);
return(returnData);
}
/// <summary>
/// Update data in specified chart controll
/// </summary>
/// <param name="chart">Chart, which need to update</param>
/// <param name="data">New data</param>
public static void RefreshForecastChart(LiveCharts.WinForms.CartesianChart chart, FResult data)
{
Dictionary <string, List <double> > lines = new Dictionary <string, List <double> >
{
{ "Forecast points", Enumerable.Repeat(double.NaN, data.TimeSeriesPoints.Count).ToList() },
{ "Lo 80", Enumerable.Repeat(double.NaN, data.TimeSeriesPoints.Count).ToList() },
{ "Hi 80", Enumerable.Repeat(double.NaN, data.TimeSeriesPoints.Count).ToList() },
{ "Lo 95", Enumerable.Repeat(double.NaN, data.TimeSeriesPoints.Count).ToList() },
{ "Hi 95", Enumerable.Repeat(double.NaN, data.TimeSeriesPoints.Count).ToList() },
{ "Time Series", data.TimeSeriesPoints }
};
int count = 0;
for (int i = 0; i < data.ResultDataFrame.Data[0].Count; i++)
{
for (int j = 0; j < data.ResultDataFrame.Data.Count; j++)
{
if (count == 0)
{
lines["Forecast points"].Add(Convert.ToDouble(data.ResultDataFrame.Data[j][i]));
}
else if (count == 1)
{
lines["Lo 80"].Add(Convert.ToDouble(data.ResultDataFrame.Data[j][i]));
}
else if (count == 2)
{
lines["Hi 80"].Add(Convert.ToDouble(data.ResultDataFrame.Data[j][i]));
}
else if (count == 3)
{
lines["Lo 95"].Add(Convert.ToDouble(data.ResultDataFrame.Data[j][i]));
}
else if (count == 4)
{
lines["Hi 95"].Add(Convert.ToDouble(data.ResultDataFrame.Data[j][i]));
}
count++;
if (count == 5)
{
count = 0;
}
}
}
List <SeriesOption> lineOptions = lines.Select((line) => new SeriesOption {
Title = line.Key, Values = line.Value
}).ToList();
lineOptions.Where(line => line.Title.Equals("Forecast points"))
.ToList()
.ForEach(line => {
line.IsDashed = true;
line.PointGeometry = DefaultGeometries.Diamond;
});
lineOptions.Where(line => line.Title.Equals("Time Series"))
.ToList()
.ForEach(line =>
{
line.LineColor = Brushes.Black;
});
chart.Series = CreateSeriesCollection(lineOptions);
}
/// <summary>
/// this is the recommended constructor. Use others if you know what you're doing.
/// </summary>
public FAIStimulus(UAISense sense, float stimulusStrength, FVector inStimulusLocation, FVector inReceiverLocation, FResult result, string inStimulusTag) :
base(E_CreateStruct_FAIStimulus_UAISense_float_FVector_FVector_FResult_FName(sense, stimulusStrength, inStimulusLocation, inReceiverLocation, (byte)result, inStimulusTag), false)
{
}
private async void button2_Click(object sender, EventArgs e)
{
if (comboBox1.SelectedIndex == -1)
{
MessageBox.Show("Please, select fitting method to use!");
return;
}
if (comboBox1.SelectedIndex > availableMethods.Count)
{
MessageBox.Show("Method currently not available!");
return;
}
int days;
var ok = int.TryParse(textBox1.Text, out days);
int count;
var ok2 = int.TryParse(textBox2.Text, out count);
int period;
var ok3 = int.TryParse(textBox3.Text, out period);
if (!ok || !ok2 || days <= 0 || count <= 0 || (ok3 && period < 0))
{
MessageBox.Show("Invalid count!");
return;
}
List <double> items = null;
using (var db = new dbContext())
{
/*items = db.Sales_Histories
* .OrderByDescending(u => u.Entry_No)
* .Take(days)
* .OrderBy(u => u.Entry_No)
* .Select(x => (double)x.Sales_Quantity)
* .ToList();*/
items = db.Sales_Histories
.GroupBy(x => x.Invoice_Date)
.OrderByDescending(x => x.Key)
.Take(days)
.OrderBy(x => x.Key)
.Select(x => x.Select(o => (double)o.Sales_Quantity).ToList().Sum())
.ToList();
}
IBasicMethod method = availableMethods[comboBox1.SelectedIndex];
if (!ok3)
{
period = 0;
}
FResult result = null;
if (items.Count != days)
{
textBox1.Text = items.Count.ToString();
}
var filepath = Directory.GetCurrentDirectory() + "\\result.png";
try
{
result = await method.Forecast(items, count, filepath, period, 1920, 1080);
}
catch (Exception ex)
{
Console.WriteLine(ex);
MessageBox.Show("Unknown error appeared while trying to forecast data " + ex.Message);
return;
}
if (result.Data == null)
{
MessageBox.Show(result.Error);
}
else
{
pictureBox1.ImageLocation = filepath;
dataGridView1.Columns.Clear();
dataGridView1.Columns.Add("Value", "Value");
dataGridView1.Rows.Clear();
foreach (var item in result.Data)
{
dataGridView1.Rows.Add(new object[] { item });
}
ChartService.RefreshForecastChart(testChart, result);
testChart.Zoom = ZoomingOptions.Xy;
testChart.LegendLocation = LegendLocation.Left;
}
}
