public async Task ConvertToPdf(IEnumerable <ExcelFileInfos> excelFilesInfos)
{
await Task.Run(() =>
{
using (var excelApplication = new ExcelApplicationWrapper())
{
foreach (var excelFileInfo in excelFilesInfos)
{
var thisFileWorkbook = excelApplication.ExcelApplication.Workbooks.Open(excelFileInfo.FilePath);
string newPdfFilePath = Path.Combine(
Path.GetDirectoryName(excelFileInfo.FilePath),
$"{excelFileInfo.FileNameWithoutExtension}.pdf");
thisFileWorkbook.ExportAsFixedFormat(Microsoft.Office.Interop.Excel.XlFixedFormatType.xlTypePDF, newPdfFilePath);
thisFileWorkbook.Close(false, excelFileInfo.FilePath);
Marshal.ReleaseComObject(thisFileWorkbook);
}
}
});
}
static void Main(string[] args)
{
string filename = Environment.GetEnvironmentVariable("TSF_NET_DIR") + "Sample_Periodic\\NorwichTemp2.csv";
Dictionary<string, List<double>> inputData = ParseCSVRows(filename);
ExcelApplicationWrapper excelApp = new ExcelApplicationWrapper();
excelApp.OpenExcel();
foreach (string q1 in inputData.Keys)
{
string strTab = q1 + ", trends";
if (strTab.Length > 30)
{
strTab = strTab.Substring(0, 30);
}
int c_maxIter = 2;
List<DateTime> timeline = null;
List<double> data = inputData[q1];
//Done extracting and aggregating data for query q1
int periodicityHint = 12;
//Step1. Detect deviant patterns and outlying spikes
//A slower much more precise model builder commented out here
//AAdAdrWithShocks modelBuilder = new AAdAdrWithShocks(periodicityHint, 0.1, (List<int>) null, null);
//modelBuilder.InterferenceLag = 12;
AAdArapidEventDetector modelBuilder = new AAdArapidEventDetector(periodicityHint);
IList<EventImpactTrace> detectionHistory = null;
bool fOK = modelBuilder.EventDetectionLoop(data, 0, c_maxIter, false,
out detectionHistory);
int fcastRange = 12;
IList<IScalarDistribution> fullForecast = null;
HoltWintersMultithreadedDimensionalityReduction forecaster =
new HoltWintersMultithreadedDimensionalityReduction(periodicityHint);
IList<double> paramtrs = null;
IList<double> residuals = null;
try
{
//Example of "full service" forecast, with expected values and predict distributions
forecaster.SingleThreadForecast(data, 0, fcastRange, "NONPARAMETRIC", 0.0, double.MaxValue,
out paramtrs, out fullForecast, out residuals);
}
catch (Exception outerException)
{
}
//Preparing for ... and using Excel middleware to generate Excel chart programmatically
Dictionary<Timestamp, double> dictSigmas = null;
Dictionary<Timestamp, double> dictMeans = null;
List<Timestamp> timeIndex = null;
MakeForecastOnlyDictionaries
(data.Count, fullForecast, out timeIndex, out dictMeans, out dictSigmas);
//Cosmetics tweak
dictMeans.Add(new Timestamp(data.Count - 1), data.Last());
AddExcelChart(excelApp, detectionHistory.Last(), q1,
MakeDataDictionary(timeIndex, data), dictMeans, dictSigmas);
}
//excelApp.CloseExcel(); //Uncomment to get the workbook closed automatically
}
static void AddExcelChart(ExcelApplicationWrapper excelApp, EventImpactTrace eventTrace,
string name,
Dictionary<Timestamp, double> dictData,
Dictionary<Timestamp, double> dictForecast,
Dictionary<Timestamp, double> dictSigmas
)
{
List<Timestamp> timeline = new List<Timestamp>(dictData.Keys);
timeline.Sort();
Dictionary<string, Dictionary<int, string>> dictLabels =
new Dictionary<string, Dictionary<int, string>>(1);
Dictionary<int, string> eventLabels = new Dictionary<int, string>();
//Label standalone (observation) spikes
if ((eventTrace != null) && (eventTrace.ObservationShocks != null))
{
foreach (int ilk in eventTrace.ObservationShocks.Keys)
{
eventLabels.Add(ilk, "M");
}
}
//Label inflection points in broad, deviant patterns
foreach (int ilk in eventTrace.StateShocks.Keys)
{
if ((ilk >= 0) && (!eventLabels.ContainsKey(ilk)))
{
eventLabels.Add(ilk, "S");
}
}
dictLabels.Add(name, eventLabels);
Dictionary<string, Dictionary<int, string>> dictNews =
new Dictionary<string, Dictionary<int, string>>(1);
Dictionary<string, Dictionary<Timestamp, double>> tmp =
new Dictionary<string, Dictionary<Timestamp, double>>(2);
tmp.Add(name, dictData);
Dictionary<string, Dictionary<Timestamp, double>> tmpSigmas = null;
if (dictForecast != null)
{
string strForecastName = name + " (forecast)";
tmp.Add(strForecastName, dictForecast);
foreach (Timestamp fts in dictForecast.Keys)
{
if (!timeline.Contains(fts))
{
timeline.Add(fts);
}
}
timeline.Sort();
tmpSigmas = new Dictionary<string, Dictionary<Timestamp, double>>(1);
tmpSigmas.Add(strForecastName, dictSigmas);
}
try
{
excelApp.CreateChart(name + ", trends", timeline,
tmp,
tmpSigmas,
0, int.MaxValue, dictLabels, dictNews);
}
catch (COMException comExIgnore)
{
}
}
