/// <summary>
/// Data input yang dimasukkan dari array 0 - akhir itu nilai reflectance dari wave length: 2501.982414 sampe 1350.724346
/// </summary>
/// <param name="DataReflectance"></param>
/// <returns></returns>
static ModelInput PreProcessData(List <float> DataReflectance)
{
try
{
var item = new ModelInput();
//convert to absorbance
for (int col = 0; col < DataReflectance.Count; col++)
{
DataReflectance[col] = (float)Math.Log(1 / DataReflectance[col]);
}
//sav gol filter
SavitzkyGolayFilter filter = new SavitzkyGolayFilter(11, 2);
List <double> rowDatas = new List <double>();
for (int col = 0; col < DataReflectance.Count; col++)
{
rowDatas.Add(DataReflectance[col]);
}
var filteredRow = filter.Process(rowDatas.ToArray());
for (int col = 0; col < DataReflectance.Count; col++)
{
DataReflectance[col] = (float)filteredRow[col];
}
//SNV
rowDatas = new List <double>();
for (int col = 0; col < DataReflectance.Count; col++)
{
rowDatas.Add(DataReflectance[col]);
}
var mean = rowDatas.Average();
var stdDev = MathExt.StdDev(rowDatas);
for (int col = 0; col < DataReflectance.Count; col++)
{
DataReflectance[col] = (float)((DataReflectance[col] - mean) / stdDev);
}
item.FeatureVector = DataReflectance.ToArray();
return(item);
}
catch
{
return(null);
}
}
static void PreProcessed(string TargetFolder, string PreProcessFolder)
{
if (!Directory.Exists(PreProcessFolder))
{
Directory.CreateDirectory(PreProcessFolder);
}
var fileCsvs = Directory.GetFiles(TargetFolder, "*.csv");
foreach (var file in fileCsvs)
{
var dt = ConvertCSVtoDataTable(file);
//convert to absorbance
foreach (DataRow dr in dt.Rows)
{
for (int col = 1; col < dt.Columns.Count; col++)
{
dr[col] = Math.Log(1 / double.Parse(dr[col].ToString()));
}
}
dt.AcceptChanges();
//sav gol filter
SavitzkyGolayFilter filter = new SavitzkyGolayFilter(11, 2);
foreach (DataRow dr in dt.Rows)
{
List <double> rowDatas = new List <double>();
for (int col = 1; col < dt.Columns.Count; col++)
{
rowDatas.Add(double.Parse(dr[col].ToString()));
}
var filteredRow = filter.Process(rowDatas.ToArray());
for (int col = 1; col < dt.Columns.Count; col++)
{
dr[col] = filteredRow[col - 1];
}
}
dt.AcceptChanges();
//SNV
foreach (DataRow dr in dt.Rows)
{
List <double> rowDatas = new List <double>();
for (int col = 1; col < dt.Columns.Count; col++)
{
rowDatas.Add(double.Parse(dr[col].ToString()));
}
var mean = rowDatas.Average();
var stdDev = MathExt.StdDev(rowDatas);
for (int col = 1; col < dt.Columns.Count; col++)
{
dr[col] = (double.Parse(dr[col].ToString()) - mean) / stdDev;
}
}
dt.AcceptChanges();
//save to file
{
var col = 0;
StringBuilder sb = new StringBuilder();
//print column name
sb.Append(dt.Columns[col].ColumnName);
for (int x = 1; x < dt.Columns.Count; x++)
{
sb.Append("," + dt.Columns[x].ColumnName);
}
sb.Append(Environment.NewLine);
//print data column
foreach (DataRow dr in dt.Rows)
{
sb.Append(dr[col].ToString());
for (int x = 1; x < dt.Columns.Count; x++)
{
sb.Append("," + dr[x].ToString());
}
sb.Append(Environment.NewLine);
}
var PathStr = PreProcessFolder + "\\" + dt.Columns[col].ColumnName + ".csv";
File.WriteAllText(PathStr, sb.ToString());
ConsoleHelper.Print($"{dt.Columns[col].ColumnName} - file generated.");
}
}
}
