private int calculateRuns(_Worksheet sheet, DataSet dataSet, Range range, double cutoff)
{
int runs = 1;
double[,] array = RangeHelper.To2DDoubleArray(range);
double[] array2 = new double[array.Length];
for (int i = 0; i < array.Length; i++)
{
array2[i] = array[i, 0];
}
for (int i = 0; i < array.Length - 1; i++)
{
if (Math.Sign(array2[i] - cutoff) != Math.Sign(array2[i + 1] - cutoff))
{
runs++;
}
}
return(runs);
}
// vanaf hier copy van oude code
public void Print(DataSet dataSet, List <Variable> variables, bool rdbMovingAverage, bool rdbSimpleExponentialSmoothing, bool rdbHoltsExponentialSmoothing, bool rdbWintersExponentialSmoothing, bool doOptimizeParameters, int numberOfForecasts, int numberOfHoldouts, int seasonalPeriod, int span, string level, string trend, string seasonality)
{
// Create new sheet
var sheet = WorksheetHelper.NewWorksheet("Forecast");
// use variables
_doOptimizeParameters = doOptimizeParameters;
_numberOfForecasts = numberOfForecasts;
_numberOfHoldouts = numberOfHoldouts;
_seasonalPeriod = seasonalPeriod;
_span = span;
// variables for writing on sheet and writing of title
int title = 1;
int forcastingConstants = 3;
int summaryName = forcastingConstants + 5;
int row = summaryName + 5;
sheet.Cells[title, 1] = "Forecast ";
sheet.Cells[forcastingConstants, 1] = "Forecasting Constants";
sheet.Cells[summaryName, 1] = "Summary";
sheet.Cells[summaryName + 1, 1] = "Mean Absolute Error";
sheet.Cells[summaryName + 2, 1] = "Root Mean Squared Error";
sheet.Cells[summaryName + 3, 1] = "Mean Absolute Percentage Error";
((Range)sheet.Cells[row, 1]).EntireColumn.AutoFit();
// variables to count number of forecast, holdouts and data
var nForecasts = Convert.ToDouble(numberOfForecasts);
var nHoldouts = Convert.ToDouble(numberOfHoldouts);
var nData = Convert.ToDouble(dataSet.rangeSize());
int column = 2;
foreach (Variable variable in variables)
{
row = 1;
double[,] array = RangeHelper.To2DDoubleArray(variable.getRange());
double[] array2 = new double[array.Length];
for (int i = 0; i < array.Length; i++)
{
array2[i] = array[i, 0]; // hier moet nog iets komen waardoor het mogelijk wordt om variabelen in rijen te verwerken
}
//Print data
column++;
sheet.Cells[row++, column] = variable.name;
for (int i = 0; i < array2.Length; i++)
{
sheet.Cells[row++, column] = array2[i];
}
row = 1;
column++;
// Plot next figure below the data and the forecast
int rowFigure = row + variables.Count + Convert.ToInt16(nForecasts) + 2;
// Calculate moving average forecast if box is checked
if (rdbMovingAverage)
{
EvaluateMovingAverage(array2, row, column, sheet);
string name = "Forecast Moving Average: " + variable.name;
//var rangeLabels = sheet.Range[sheet.Cells[row + 1, column], sheet.Cells[row + nData + nForecasts, column]];
var rangeData = sheet.Range[sheet.Cells[row + 2, column - 1], sheet.Cells[row + nData + nForecasts, column - 1]];
var rangeForecast = sheet.Range[sheet.Cells[row + 2, column], sheet.Cells[row + nData + nForecasts, column]];
new TimeSeriesGraph().CreateNewGraph2(sheet, rowFigure, rangeData, rangeForecast, name);
}
// Calculate exponential smoothing (simple) forecast if box is checked
if (rdbSimpleExponentialSmoothing)
{
CalculateSimple(array2, row, sheet, column);
string name = "Forecast Exponential smoothing (Simple): " + variable.name;
//var rangeLabels = sheet.Range[sheet.Cells[row + 1, column], sheet.Cells[row + nData + nForecasts, column]];
var rangeData = sheet.Range[sheet.Cells[row + 2, column - 1], sheet.Cells[row + nData + nForecasts, column - 1]];
var rangeForecast = sheet.Range[sheet.Cells[row + 2, column + 1], sheet.Cells[row + nData + nForecasts, column + 1]];
new TimeSeriesGraph().CreateNewGraph2(sheet, rowFigure, rangeData, rangeForecast, name);
}
// Calculate exponential smoothing (holt) forecast if box is checked
if (rdbHoltsExponentialSmoothing)
{
CalculateHolt(array2, row, sheet, column);
string name = "Forecast Exponential smoothing (Holt): " + variable.name;
//var rangeLabels = sheet.Range[sheet.Cells[row + 1, column], sheet.Cells[row + nData + nForecasts, column]];
var rangeData = sheet.Range[sheet.Cells[row + 2, column - 1], sheet.Cells[row + nData + nForecasts, column - 1]];
var rangeForecast = sheet.Range[sheet.Cells[row + 2, column + 2], sheet.Cells[row + nData + nForecasts, column + 2]];
new TimeSeriesGraph().CreateNewGraph2(sheet, rowFigure, rangeData, rangeForecast, name);
}
// Calculate exponential smoothing (winters) forecast if box is checked
if (rdbWintersExponentialSmoothing)
{
CalculateWinter(array2, row, sheet, column);
string name = "Forecast Exponential smoothing (Winter): " + variable.name;
//var rangeLabels = sheet.Range[sheet.Cells[row + 1, column], sheet.Cells[row + nData + nForecasts, column]];
var rangeData = sheet.Range[sheet.Cells[row + 2, column - 1], sheet.Cells[row + nData + nForecasts, column - 1]];
var rangeForecast = sheet.Range[sheet.Cells[row + 2, column + 3], sheet.Cells[row + nData + nForecasts, column + 3]];
new TimeSeriesGraph().CreateNewGraph2(sheet, rowFigure, rangeData, rangeForecast, name);
}
column = column + 6;
}
}
