/// <summary>
/// 計算多變量管制圖的 Tsquare decomposition
/// </summary>
/// <param name="data"></param>
/// <param name="mean"></param>
/// <param name="S"></param>
/// <returns></returns>
public static LinearAlgebra.Matrix <double> T2Decomposition(LinearAlgebra.Matrix <double> data, LinearAlgebra.Matrix <double> mean, LinearAlgebra.Matrix <double> S)
{
//mean 的 #column = #columns of data = #columns of covariance
if (data.ColumnCount != mean.ColumnCount || data.ColumnCount != S.ColumnCount || mean.ColumnCount != S.ColumnCount)
{
throw new ArgumentException("矩陣的維度無法計算");
}
LinearAlgebra.Matrix <double> invS = S.Inverse();
List <double> tsquare = new List <double>();
for (int i = 0; i < data.RowCount; i++)
{
tsquare.Add(CalculateTSquare(data.Row(i).ToRowMatrix(), mean, invS));
}
List <double> decoValue = new List <double>();
for (int c = 0; c < data.ColumnCount; c++)
{
LinearAlgebra.Matrix <double> subData = data.RemoveColumn(c);
LinearAlgebra.Matrix <double> subMean = mean.RemoveColumn(c);
LinearAlgebra.Matrix <double> subS = S.RemoveColumn(c).RemoveRow(c);
LinearAlgebra.Matrix <double> invSubS = subS.Inverse();
for (int r = 0; r < data.RowCount; r++)
{
decoValue.Add(tsquare[r] - CalculateTSquare(subData.Row(r).ToRowMatrix(), subMean, invSubS));
}
}
LinearAlgebra.Matrix <double> m = LinearAlgebra.Matrix <double> .Build.DenseOfColumnMajor(data.RowCount, data.ColumnCount, decoValue);
return(m);
}
public override void Execute(Mtb.Project proj)
{
// 將資料匯入 Minitab
if (_rawdata == null || _rawdata.Rows.Count == 0)
{
throw new ArgumentNullException("查無對應資料");
}
_rptLst = new List <IRptOutput>(); //重新建立一個分析結果列舉
proj.Commands.Delete();
proj.Worksheets.Delete();
Mtb.Worksheet ws = proj.Worksheets.Add(1); //新增工作表
Mtblib.Tools.MtbTools.InsertDataTableToMtbWs(_rawdata, ws); //匯入資料至 Minitab
List <Mtb.Column> varCols = new List <Mtb.Column>(); //變數的欄位集合
List <Mtb.Column> bkCols = new List <Mtb.Column>(); //斷絲率的集合
Mtb.Column timeCol = null;
for (int i = 0; i < _rawdata.Columns.Count; i++)
{
DataColumn col = _rawdata.Columns[i];
switch (col.ColumnName)
{
case "TIMESTAMP":
timeCol = ws.Columns.Item(col.ColumnName);
break;
case "RPT_TIMEHOUR":
case "GROUP_ID":
case "SITE_ID":
break;
default:
if (col.ColumnName.Substring(0, 2) == "BK")
{
bkCols.Add(ws.Columns.Item(col.ColumnName));
}
else
{
varCols.Add(ws.Columns.Item(col.ColumnName));
}
break;
}
}
foreach (var col in bkCols)
{
if ((int)col.DataType == 3 || col.MissingCount == col.RowCount)
{
throw new ArgumentNullException(string.Format("[{0}]查無資料", col.Name));
}
}
foreach (var col in varCols)
{
if ((int)col.DataType == 3 || col.MissingCount == col.RowCount)
{
throw new ArgumentNullException(string.Format("[{0}]查無資料", col.Name));
}
}
StringBuilder cmnd = new StringBuilder();
/*
* Create TSPlot
* 該圖會將數據於多個平面中顯示(k*1的方式)，所以要先設定 Panel 的安排方式
*
*/
cmnd.AppendLine("notitle");
cmnd.AppendLine("brief 0");
cmnd.AppendFormat("fdate {0};\r\n", timeCol.SynthesizedName);
cmnd.AppendLine("format(dtyyyy-MM-dd hh:mm).");
cmnd.AppendFormat("tsplot {0} {1};\r\n", string.Join(" &\r\n", bkCols.Select(x => x.SynthesizedName)),
string.Join(" &\r\n", varCols.Select(x => x.SynthesizedName)));
double gHeight = 3;
//if (varCols.Count > 3) gHeight = Math.Min(30, 4 + ((double)varCols.Count - 3) * 0.8);
cmnd.AppendFormat("graph 8 {0};\r\n", gHeight);
string gpath_trend = System.IO.Path.Combine(Environment.GetEnvironmentVariable("tmp"), "Minitab", string.Format("trend_{0}.jpg", _rawdata.TableName));
cmnd.AppendFormat("gsave \"{0}\";\r\n", gpath_trend);
cmnd.AppendLine("repl;");
cmnd.AppendLine("jpeg;");
//cmnd.AppendLine("panel;");
//cmnd.AppendFormat("rc {0} 1;\r\n", varCols.Count + bkCols.Count);
//cmnd.AppendLine("noal;");
//cmnd.AppendLine("label;");
//cmnd.AppendLine(" psize 5;");
cmnd.AppendLine("scale 1;");
cmnd.AppendLine(" psize 8;");
cmnd.AppendLine("grid 1;");
cmnd.AppendLine("axlab 1;");
cmnd.AppendLine("lshow;");
cmnd.AppendLine(" angle 90;");
cmnd.AppendLine("grid 2;");
cmnd.AppendLine("scale 2;");
cmnd.AppendLine(" psize 8;");
if (timeCol != null && (int)timeCol.DataType != 3)
{
cmnd.AppendFormat("stamp {0};\r\n", timeCol.SynthesizedName);
}
cmnd.AppendLine("symb;");
cmnd.AppendLine("conn;");
//cmnd.AppendFormat("foot \"建立時間: {0}\";\r\n", DateTime.Now);
cmnd.AppendLine("nodt.");
//Create Matrix Plot
cmnd.AppendFormat("matrixplot ({0})*({1});\r\n", string.Join(" &\r\n", bkCols.Select(x => x.SynthesizedName)),
string.Join(" &\r\n", varCols.Select(x => x.SynthesizedName)));
double gWidth = 8;
if (varCols.Count > 5)
{
gWidth = Math.Min(30, 8 + ((double)varCols.Count - 5) * 0.8);
}
cmnd.AppendFormat("graph {0} 5;\r\n", gWidth);
string gpath_corr = System.IO.Path.Combine(Environment.GetEnvironmentVariable("tmp"), "Minitab", string.Format("corr_{0}.jpg", _rawdata.TableName));
cmnd.AppendFormat("gsave \"{0}\";\r\n", gpath_corr);
cmnd.AppendLine("repl;");
cmnd.AppendLine("jpeg;");
cmnd.AppendLine("scale 1;");
cmnd.AppendLine(" psize 8;");
cmnd.AppendLine("nojitter;");
cmnd.AppendLine("full;");
cmnd.AppendLine("bound;");
cmnd.AppendLine("noal;");
cmnd.AppendLine("regr;");
cmnd.AppendLine("symb;");
cmnd.AppendLine("nodt.");
//Calculate correlation coefficient
string[] matIds = Mtblib.Tools.MtbTools.CreateVariableStrArray(ws, 1, Mtblib.Tools.MtbVarType.Matrix);
cmnd.AppendFormat("corr {0} {1} {2}\r\n", string.Join(" &\r\n", bkCols.Select(x => x.SynthesizedName)),
string.Join(" &\r\n", varCols.Select(x => x.SynthesizedName)),
string.Join(" &\r\n", matIds)
);
//刪除所有圖形
cmnd.AppendLine("gmana;");
cmnd.AppendLine("all;");
cmnd.AppendLine("close;");
cmnd.AppendLine("nopr.");
string fpath = Mtblib.Tools.MtbTools.BuildTemporaryMacro("mymacro.mtb", cmnd.ToString());
proj.ExecuteCommand(string.Format("exec \"{0}\" 1", fpath), ws);
//將檔案轉為二進位陣列
string _root = System.IO.Path.Combine(Environment.GetEnvironmentVariable("tmp"), "Minitab", string.Format("trend_{0}", _rawdata.TableName));
string _file;
for (int i = 0; i < bkCols.Count + varCols.Count; i++)
{
_file = _root + (i + 1).ToString("D3") + ".jpg";
if (File.Exists(_file))
{
this.Contents.Add(new RptOutput()
{
OType = MtbOType.GRAPH,
OutputInByteArr = File.ReadAllBytes(_file),
Tag = "Trend"
});
}
}
//if (File.Exists(gpath_trend))
//{
// this.Contents.Add(new RptOutput()
// {
// OType = MtbOType.GRAPH,
// OutputInByteArr = File.ReadAllBytes(gpath_trend),
// Tag = "Trend"
// });
//}
if (File.Exists(gpath_corr))
{
this.Contents.Add(new RptOutput()
{
OType = MtbOType.GRAPH,
OutputInByteArr = File.ReadAllBytes(gpath_corr),
Tag = "Scatter"
});
}
//Create Correlation table
DataTable corrTable = new DataTable();
corrTable.Columns.Add("熔爐項目", typeof(string));
foreach (Mtb.Column col in bkCols)
{
corrTable.Columns.Add(col.Name, typeof(double));
}
//corrTable.Columns.Add("CorrCoef", typeof(double));
var corrMat = ws.Matrices.Item(matIds[0]).GetData(); //取出 correlation matrix
var mBuilder = LinearAlgebra.Matrix <double> .Build;
LinearAlgebra.Matrix <double> corM = mBuilder.DenseOfColumnMajor(bkCols.Count + varCols.Count, bkCols.Count + varCols.Count, corrMat);
LinearAlgebra.Matrix <double> subCorrMat = corM.SubMatrix(bkCols.Count, varCols.Count, 0, bkCols.Count);
string[] labNames = varCols.Select(x => x.Name).ToArray();
List <object> itemArray;
DataRow dr;
for (int i = 0; i < varCols.Count; i++)
{
itemArray = new List <object>();
itemArray.Add(labNames[i]);
itemArray.AddRange(subCorrMat.Row(i).ToArray().Select(x => (object)Math.Round(x, 3)).ToArray());
//dr = corrTable.NewRow();
//dr.ItemArray = itemArray;
corrTable.Rows.Add(itemArray.ToArray());
}
//double[] subCorr = new double[varCols.Count];
//double[] corr = corrMat as double[];
//if (corr != null)
//{
// Array.Copy(corr, 1, subCorr, 0, varCols.Count);
//
// DataRow dr;
// for (int i = 0; i < subCorr.Length; i++)
// {
// dr = corrTable.NewRow();
// dr[0] = labNames[i];
// dr[1] = subCorr[i];
// corrTable.Rows.Add(dr);
// }
//}
this.Contents.Add(new RptOutput()
{
OType = MtbOType.TABLE,
OutputInByteArr = Tool.ConvertDataSetToByteArray(corrTable),
Tag = "Table"
});
}