static void Main()
{
Application.EnableVisualStyles();
Application.SetCompatibleTextRenderingDefault(false);
Mtb.Application mtbApp = new Mtb.Application();
mtbApp.UserInterface.DisplayAlerts = false;
mtbApp.UserInterface.Visible = true;
Mtb.Project proj = mtbApp.ActiveProject;
Mtb.Worksheet ws;
try
{
proj.Worksheets.Open(@"C:\Users\Yalibuda\Desktop\data_16.mtw");
ws = proj.ActiveWorksheet;
}
catch
{
mtbApp.Quit();
return;
}
Mtb.Column rawDataCol = ws.Columns.Item("VALUE");
double mean = Mtblib.Tools.MtbTools.MISSINGVALUE;
double stdev = Mtblib.Tools.MtbTools.MISSINGVALUE;
double maximum = Mtblib.Tools.MtbTools.MISSINGVALUE;
double minimum = Mtblib.Tools.MtbTools.MISSINGVALUE;
try
{
mean = ((double[])rawDataCol.GetData()).Where(x => x < Mtblib.Tools.MtbTools.MISSINGVALUE).Average();
stdev = ((double[])rawDataCol.GetData()).Where(x => x < Mtblib.Tools.MtbTools.MISSINGVALUE).StdDev();
maximum = ((double[])rawDataCol.GetData()).Where(x => x < Mtblib.Tools.MtbTools.MISSINGVALUE).Max();
minimum = ((double[])rawDataCol.GetData()).Where(x => x < Mtblib.Tools.MtbTools.MISSINGVALUE).Min();
}
catch (Exception ee)
{
MessageBox.Show(ee.Message);
}
Console.WriteLine("Stdev:{0}", stdev);
//double sstdev = ((double[])ws.Columns.Item("C10").GetData()).StdDev();
//Console.Write(sstdev);
//Chart barchart = new Chart(proj,ws);
//barchart.Variables = "C10 C11";
//barchart.BarsRepresent = Chart.ChartRepresent.TWO_WAY_TABLE;
//barchart.GroupingVariables = "C2 C3";
//barchart.Bar.GroupingBy = "C2 C3";
//barchart.NoMissing = true;
//barchart.NoEmpty = true;
//string path2 = MtbTools.BuildTemporaryMacro("mycode.mtb", barchart.GetCommand());
//proj.ExecuteCommand(string.Format("% \"{0}\" 1", path2));
//proj.Worksheets.Open(@"D:\Dropbox\Workspace\Test\test20160611.mtw");
//proj.Worksheets.Open(@"D:\Dropbox\Workspace\03.PFG\06.Dataset\熔爐資料\FurnWall.mtw");
//proj.Worksheets.Open(@"D:\Dropbox\Workspace\Test\test20160810.mtw");
//ws = proj.ActiveWorksheet;
//Mtb.Column[] cols = new Mtb.Column[] {
// ws.Columns.Item("C1"),
// ws.Columns.Item("C2"),
// ws.Columns.Item("C3"),
// ws.Columns.Item("C4"),
// ws.Columns.Item("C5"),
// ws.Columns.Item("C6")
//};
//ws.Columns.Add().Name="xxx";
//ws.Columns.Item("xxx").SetData("a", 1, 10);
//System.Data.DataTable dt = Mtblib.Tools.MtbTools.GetDataTableFromMtbCols(cols);
//System.Data.DataTable result = Mtblib.Tools.MtbTools.Apply(
// "C3", Mtblib.Tools.Arithmetic.NMiss, new string[] { "C1", "C2" }, dt);
//proj.Worksheets.Open(@"D:\Dropbox\Workspace\03.PFG\06.Dataset\熔爐資料\FurnWall.mtw");
//ws = proj.ActiveWorksheet;
//double[] data = ws.Columns.Item("C5").GetData();
//string[] name = ws.Columns.Item("C3").GetData();
//DateTime[] timeorder = ws.Columns.Item("C4").GetData();
//var data1 = data.Zip(name, (x, y) => new { Value = x, Name = y });
//var datas = data1.Zip(timeorder, (x, y) => new { Value = x.Value, Name = x.Name, Time = y }).ToArray();
//string num = "17";
//var subdata = datas.Where(x => x.Name == num).Select(x => x.Value).ToArray();
//Mtblib.Stat.ChangePoints.ChangePointInfo[] changePts = Mtblib.Stat.ChangePoints.Run(subdata);
//System.Text.StringBuilder cmnd = new System.Text.StringBuilder();
//cmnd.AppendLine("plot c5*c4;");
//cmnd.AppendLine("symb;");
//cmnd.AppendLine("conn;");
//cmnd.AppendLine("Include;");
//cmnd.AppendFormat("where \"c3=\"\"{0}\"\" \";\r\n",num);
//dynamic xvalue = datas.Where(x => x.Name == num).Select(x => x.Time).ToArray();
//double[] dxvalue;
//if (xvalue is DateTime[])
//{
// dxvalue = ((DateTime[])xvalue).Select(x => x.ToOADate()).ToArray();
//}
//else
//{
// dxvalue = xvalue;
//}
//if (changePts != null)
//{
// cmnd.AppendLine("refe 1 &");
// foreach (var item in changePts)
// {
// Console.WriteLine("Change Points={0}, Confidence level={1}", item.Index, item.ConfidenceLevel);
// cmnd.AppendFormat("{0} &\r\n", dxvalue[item.Index + 1].ToString());
// }
// cmnd.AppendLine(";");
//}
//cmnd.AppendFormat("title \"爐區={0}\";\r\n", num);
//cmnd.AppendLine(".");
//proj.ExecuteCommand(cmnd.ToString());
//List<double[]> d = new List<double[]>();
//d.Add(ws.Columns.Item("C3").GetData());
//d.Add(ws.Columns.Item("C4").GetData());
//d.Add(ws.Columns.Item("C5").GetData());
//Mtblib.Tools.GScale[] gg = Mtblib.Tools.MtbTools.GetMinitabGScaleInfo(d, proj, ws);
// Test
//Mtb.Application mtbApp = new Mtb.Application();
//mtbApp.UserInterface.Visible = true;
//mtbApp.UserInterface.DisplayAlerts = false;
//Mtb.Project proj = mtbApp.ActiveProject;
// summary data
//proj.Worksheets.Open(@"D:\Dropbox\Workspace\01.chipMOS\06.Dataset\Top 3 Cust.mtw");
// stacked data
//proj.Worksheets.Open(@"D:\Dropbox\Workspace\Test\test20160611.mtw");
//Mtb.Worksheet ws = proj.ActiveWorksheet;
// count data
//proj.Worksheets.Open(@"D:\Dropbox\Workspace\Test\test20160628.mtw");
//Mtb.Worksheet ws = proj.ActiveWorksheet;
////Scatter plot
//Plot p = new Plot(proj, ws);
//p.YVariables = "C4 C5";
//p.XVariables = "C3";
//p.GraphType = Plot.MultipleGraphType.Overlay;
//p.YScale.SecScale.Variable = "C5";
//p.YScale.SecScale.Label.Text= "HEHEHE";
//p.YScale.Label.Text = "AAAAA";
//p.XScale.Ticks.SetLabels(new string[] { "\"A\"","\"B\"" });
//p.Connectline.Visible = true;
//Console.WriteLine(p.GetCommand());
//proj.ExecuteCommand(p.GetCommand());
//HighlevelBarLinePlot hchart = new HighlevelBarLinePlot(proj,ws);
//hchart.chart.Variables = "C3";
//hchart.chart.GroupingVariables = "C1 C2";
//hchart.chart.Bar.GroupingBy = "C2";
//hchart.chart.FuncType = Chart.ChartFunctionType.MEAN;
//hchart.chart.Title.Text = "AAA";
//hchart.chart.XScale.Ticks.TShow = 1;
//hchart.Run();
// Chart
//using (Chart barchart = new Chart(proj, ws))
//{
// // Chart 的基本設定 (Two-way table)
// //barchart.BarsRepresent = Chart.ChartRepresent.TWO_WAY_TABLE;
// //barchart.Variables = "C4-C7";
// //barchart.GroupingVariables = "C1";
// //Chart 的基本設定 (stacked data)
// //barchart.FuncType = Chart.ChartFunctionType.MEAN;
// //barchart.BarsRepresent = Chart.ChartRepresent.A_FUNCTION_OF_A_VARIABLE;
// //barchart.Variables = "C3";
// //barchart.GroupingVariables = "C1-C2";
// //Chart 的基本設定 (count data)
// barchart.BarsRepresent = Chart.ChartRepresent.COUNT_OF_UNIQUE_VALUES;
// barchart.Variables = "C1";
// barchart.GroupingVariables = "C2";
// barchart.AdjDatlabAtStackBar = true;
// barchart.DataLabel.Visible = true;
// barchart.DataLabel.DatlabType = Datlab.DisplayType.Column;
// barchart.StackType = Chart.ChartStackType.Stack;
// barchart.XScale.Label.Text = "AAAAA";
// barchart.XScale.Ticks.TShow = 1;
// barchart.YScale.Label.Text = "BBBB";
// barchart.Bar.AssignAttributeByVariables = true;
// //barchart.Panel.PaneledBy = "C1";
// //barchart.Panel.RowColumn = new int[] { 3, 1 };
// barchart.FootnoteLst.Add(new Footnote() { Text = "CCCCC" });
// //barchart.FigureRegion.SetCoordinate(0, 1, 0, 0.6);
// barchart.Title.Visible = false;
// barchart.Title.Text = "xxxx";
// barchart.ShowSeparateSubTitle = false;
// barchart.ShowPersonalSubTitle = false;
// barchart.XScale.Refes.Values = 1.5;
// barchart.XScale.Refes.Labels = "\"AAAA\"";
// barchart.YScale.Refes.Values = new double[]{100,120};
// barchart.YScale.Refes.Color = new int[] { 3, 4 };
// string path1 = MtbTools.BuildTemporaryMacro("testchart.mac", barchart.GetCommand());
// System.Text.StringBuilder cmnd = new System.Text.StringBuilder();
// cmnd.AppendFormat("%\"{0}\" {1};\r\n", path1,
// string.Join(" &\r\n", ((Mtb.Column[])barchart.Variables).Select(x => x.SynthesizedName).ToArray())
// );
// if (barchart.GroupingVariables != null)
// {
// cmnd.AppendFormat("group {0};\r\n",
// string.Join(" &\r\n", ((Mtb.Column[])barchart.GroupingVariables).Select(x => x.SynthesizedName).ToArray())
// );
// }
// if (barchart.Panel.PaneledBy != null)
// {
// cmnd.AppendFormat("pane {0};\r\n",
// string.Join(" &\r\n", (string[])barchart.Panel.PaneledBy)
// );
// }
// if (barchart.DataLabel.LabelColumn != null)
// {
// cmnd.AppendFormat("datlab {0};\r\n", barchart.DataLabel.LabelColumn);
// }
// cmnd.Append(".");
// string path2 = MtbTools.BuildTemporaryMacro("mycode.mtb", cmnd.ToString());
// proj.ExecuteCommand(string.Format("exec \"{0}\" 1", path2));
//}
////Boxplot
//BoxPlot boxplot = new BoxPlot(proj, ws);
//boxplot.Mean.Visible = true;
//boxplot.Mean.Type = 6;
//boxplot.Mean.Color = MtbColor.DarkSkyBlue;
//boxplot.CMean.Visible = true;
//boxplot.Individual.Visible = true;
//boxplot.IQRBox.Visible = false;
//boxplot.Whisker.Visible = false;
//boxplot.Outlier.Visible = false;
//boxplot.Variables = "C3";
//boxplot.GroupingVariables = "C1 C2";
//boxplot.XScale.Label.Visible = false;
//boxplot.XScale.Ticks.TShow = new int[] { 1, 2 };
//boxplot.XScale.Ticks.HideAllTick = true;
//boxplot.FootnoteLst.Add(
// new Footnote()
// {
// Text = "AAAAAA"
// });
//boxplot.MeanDatlab.Visible = true;
//LabelPosition lpos = new LabelPosition(1, "");
//boxplot.MeanDatlab.PosititionList.Add(lpos);
////boxplot.GraphPath = @"D:\test.jpg";
//boxplot.GraphRegion.SetCoordinate(10, 4);
//boxplot.Title.Text = "BoxxxxxPlot";
//boxplot.FigureRegion.SetCoordinate(0, 1, 0.6, 1);
//System.Text.StringBuilder cmnd = new System.Text.StringBuilder();
//cmnd.AppendLine("layout.");
//cmnd.Append(barchart.GetCommand());
//cmnd.Append(boxplot.GetCommand());
//cmnd.AppendLine("endl");
//proj.ExecuteCommand(cmnd.ToString());
//proj.ExecuteCommand(boxplot.GetCommand() + ".");
//Datlab dd = new Datlab();
//string text = "C1-C5";
//Regex regex = new Regex(@"('.*?'|C[\d]+)-('.*?'|C[\d]+)");
//if (regex.IsMatch(text))
//{
// MatchCollection mm = regex.Matches(text);
// foreach (Match m in mm)
// {
// for (int i = 0; i < m.Groups.Count; i++)
// {
// Console.WriteLine(m.Groups[i].Value);
// }
// }
//}
Application.Run(new Form1());
}
/// <summary>
/// 判斷individaul T2管制圖的參數是否合法? 如果合法不回發生任何事，若不合法則回傳例外。
/// </summary>
/// <param name="paraSet"></param>
/// <returns></returns>
private void ParaValidation(ParaSetInfo paraSet)
{
DataTable mean = paraSet.Mean;
DataTable cov = paraSet.Cov;
int? ssiz = paraSet.SampleSize;
if (mean == null || cov == null)
{
throw new ArgumentNullException("尚未輸入平均數向量或共變異數矩陣");
}
if (SampleSize == null || SampleSize <= 0)
{
throw new Exception("樣本數內容不正確");
}
//確認輸入的數據是否正確(數量、共變異矩陣對稱、對角項大於0、正定等特性)
int r = cov.Columns.Count;
int c = cov.Rows.Count;
double result;
if (mean.Rows.Cast <DataRow>().Any(x => x.ItemArray.Any(y => !Double.TryParse(y.ToString(), out result))))
{
throw new Exception("平均數欄位內容必須為數字");
}
if (cov.Rows.Cast <DataRow>().Any(x => x.ItemArray.Any(y => !Double.TryParse(y.ToString(), out result))))
{
throw new Exception("共變異數內容必須為數字");
}
//將共變異數矩陣轉到Minitab中判斷是否合法
double[] covArray = new double[r * c];
for (int cCnt = 0; cCnt < c; cCnt++)
{
for (int rCnt = cCnt; rCnt < r; rCnt++)
{
if (rCnt == cCnt)
{
double value = double.Parse(cov.Rows[rCnt][cCnt].ToString());
if (value <= 0)
{
throw new Exception("共變異數矩陣對角項小於等於0");
}
covArray[cCnt * r + rCnt] = value;
}
else
{
if (cov.Rows[rCnt][cCnt].ToString() != cov.Rows[cCnt][rCnt].ToString())
{
throw new Exception("共變異數矩陣不對稱");
}
double value = double.Parse(CovarianceMatrix.Rows[rCnt][cCnt].ToString());
covArray[cCnt * r + rCnt] = value;
covArray[rCnt * r + cCnt] = value;
}
}
}
Mtb.Worksheet ws = Project.Worksheets.Add(1);
Mtb.Matrix mat = ws.Matrices.Add(Quantity: 1);
Mtb.Column col = ws.Columns.Add(Quantity: 1);
mat.SetData(covArray, 1, 1);
Project.ExecuteCommand(string.Format("Eigen {0} {1}.\r\n", mat.SynthesizedName, col.SynthesizedName), ws);
double[] eigvalue = col.GetData();
if (eigvalue.Any(x => x <= 0))
{
throw new Exception("共變異數矩陣不為正定");
}
ws.Delete();
Project.Commands.Delete();
}
public override void Execute(Mtb.Project proj)
{
// 將資料匯入 Minitab
if (_rawdata == null || _rawdata.Rows.Count == 0)
{
return;
}
_rptLst = new List <IRptOutput>(); //重新建立一個分析結果列舉
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 <string> varnames = new List <string>();
List <Mtb.Column> varCols = new List <Mtb.Column>(); //變數的欄位集合
for (int i = 0; i < _rawdata.Columns.Count; i++)
{
DataColumn col = _rawdata.Columns[i];
switch (col.ColumnName)
{
case "TIMESTAMP":
case "CHART_PARA_INDEX":
break;
default:
varnames.Add(col.ColumnName);
varCols.Add(ws.Columns.Item(col.ColumnName));
break;
}
}
foreach (var col in varCols)
{
if ((int)col.DataType == 3 || col.MissingCount == col.RowCount)
{
throw new ArgumentNullException(string.Format("[{0}]查無資料-多變量管制圖", col.Name));
}
}
StringBuilder cmnd = new StringBuilder();
List <TsquareParameters> tmpParaList = new List <TsquareParameters>(); //用於計算 decomposition
string[] colIds = Mtblib.Tools.MtbTools.CreateVariableStrArray(ws, 4, Mtblib.Tools.MtbVarType.Column); //Plot point, CL, UCL and Test column
// 指定繪圖時需要的欄位變數
Mtb.Column
pplotCol = ws.Columns.Item(colIds[0]),
clCol = ws.Columns.Item(colIds[1]),
uclCol = ws.Columns.Item(colIds[2]),
oocCol = ws.Columns.Item(colIds[3]),
timeCol = ws.Columns.Item("TIMESTAMP");
// 計算 T2 plot points
if (_parameters == null || _parameters.Count == 0)
{
//自己算的時候需要的變數和子命令
#region Phase I
cmnd.AppendLine("macro");
cmnd.AppendLine("myt2calculator x.1-x.p;");
cmnd.AppendLine("variance cov ssiz;");
cmnd.AppendLine("meanvect location; ");
cmnd.AppendLine("ppoint t2;");
cmnd.AppendLine("climit cl ucl;");
cmnd.AppendLine("test ooc;");
cmnd.AppendLine("siglevel alpha.");
cmnd.AppendLine("mcolumn x.1-x.p t2");
cmnd.AppendLine("mcolumn loc.1-loc.p xx.1-xx.p tmp.1-tmp.3 ooc ucl cl");
cmnd.AppendLine("mconstant ssiz m alpha conf a1 a2 kk");
cmnd.AppendLine("mmatrix location diff cov tdiff invCov");
cmnd.AppendLine("default alpha = 0.0027");
cmnd.AppendLine("rnmiss x.1-x.p tmp.1");
cmnd.AppendLine("copy x.1-x.p xx.1-xx.p;");
cmnd.AppendLine("exclude;");
cmnd.AppendFormat("where \"tmp.1>0\".\r\n");
cmnd.AppendLine("cova xx.1-xx.p cov"); // Get Covariance matrix
cmnd.AppendLine("let ssiz = n(xx.1)"); // Get the sample size of covariance calculation, ALSO..THAT IS THE NUMBER OF NONMISSING OBSERVATIONS
cmnd.AppendLine("stat x.1-x.p;");
cmnd.AppendLine("mean loc.1-loc.p."); //Get mean vector.
/*
* Check if there is enough nonmissing observation to calculate control limit under
* Tsquare command (m>p+1, where m=#observation, include missing obs, p=#items)
* If no, you still need to draw plot points on graph..
* The trick is we given parameters (Mean & Covariance) and given a fake sample size, then
* you get t-sq value, becasue we don't need the CL & UCL from Minitab.
* (WE USE REGULAR COVARIANCE INSTEAD OF COVARIANCE BY Sullivan & Woodall)
*
*/
cmnd.AppendLine("if(ssiz < p+1)");
cmnd.AppendLine("let kk = p+1");
cmnd.AppendLine("else");
cmnd.AppendLine("copy ssiz kk\r\n");
cmnd.AppendLine("endif");
cmnd.AppendLine("tsquare x.1-x.p 1;");
cmnd.AppendLine("mu loc.1-loc.p;");
cmnd.AppendLine("sigma cov;");
cmnd.AppendLine("number kk;");
cmnd.AppendLine("sampsize tmp.1;"); //Get subgroup size.
cmnd.AppendLine("ppoint t2."); //Get Tsquare value.
cmnd.AppendLine("copy loc.1-loc.p location"); //Copy column to mean vector
cmnd.AppendLine("let m = sum(tmp.1)"); //Get the actual sample size (include missing observations)
cmnd.AppendLine("if (m <= p+1)"); // Check if there is enough obs to calc contril limit...
cmnd.AppendLine("let cl[m]=miss()"); //no center line
cmnd.AppendLine("let ucl[m]=miss()"); //no control limit
cmnd.AppendLine("set ooc"); //no ooc
cmnd.AppendLine("(0)m");
cmnd.AppendLine("end");
cmnd.AppendLine("else");
cmnd.AppendLine("let conf = 1-alpha");
cmnd.AppendLine("let a1 = p/2");
cmnd.AppendLine("let a2 = (m-p-1)/2");
// Calculate UCL
cmnd.AppendLine("set tmp.1");
cmnd.AppendLine("(conf)m");
cmnd.AppendLine("end");
cmnd.AppendLine("invcdf tmp.1 ucl;");
cmnd.AppendLine(" beta a1 a2.");
cmnd.AppendLine("let ucl = (m-1)**2/m*ucl"); //Get upper control limit
// Calculate CL
cmnd.AppendLine("set tmp.1");
cmnd.AppendLine("(0.5)m");
cmnd.AppendLine("end");
cmnd.AppendLine("invcdf tmp.1 cl;");
cmnd.AppendLine(" beta a1 a2.");
cmnd.AppendLine("let cl = (m-1)**2/m*cl"); //Get center line
cmnd.AppendLine("let ooc = if(t2>ucl and t2<>MISS(),1,0)"); //Get OOC info
cmnd.AppendLine("endif");
//刪除所有圖形
cmnd.AppendLine("gmana;");
cmnd.AppendLine("all;");
cmnd.AppendLine("close;");
cmnd.AppendLine("nopr.");
cmnd.AppendLine("endmacro");
string macPath = Mtblib.Tools.MtbTools.BuildTemporaryMacro("mytsquare.mac", cmnd.ToString());
string[] matIds = Mtblib.Tools.MtbTools.CreateVariableStrArray(ws, 2, Mtblib.Tools.MtbVarType.Matrix); //紀錄Mean vecot & Covariance matrix
string[] constIds = Mtblib.Tools.MtbTools.CreateVariableStrArray(ws, 1, Mtblib.Tools.MtbVarType.Constant); // Sample size of Covariance matrix
cmnd.Clear();
cmnd.AppendLine("notitle");
cmnd.AppendLine("brief 0");
cmnd.AppendFormat("%\"{0}\" {1};\r\n", macPath, string.Join(" &\r\n", varCols.Select(x => x.SynthesizedName)));
cmnd.AppendFormat("variance {0} {1};\r\n", matIds[0], constIds[0]);
cmnd.AppendFormat("meanvect {0};\r\n", matIds[1]);
cmnd.AppendFormat("ppoint {0};\r\n", pplotCol.SynthesizedName);
cmnd.AppendFormat("climit {0} {1};\r\n", clCol.SynthesizedName, uclCol.SynthesizedName);
cmnd.AppendFormat("test {0}.\r\n", oocCol.SynthesizedName);
string path = Mtblib.Tools.MtbTools.BuildTemporaryMacro("mymacro.mtb", cmnd.ToString());
proj.ExecuteCommand(string.Format("exec \"{0}\" 1", path), ws);
#endregion
//取得參數組
TsquareParameters tmpPara = new TsquareParameters();
Mtb.Matrix mat;
mat = ws.Matrices.Item(matIds[1]);
tmpPara.Mean = LinearAlgebra.Matrix <double> .Build.DenseOfColumnMajor(1, mat.ColumnCount, mat.GetData());
mat = ws.Matrices.Item(matIds[0]);
tmpPara.Covariance = LinearAlgebra.Matrix <double> .Build.DenseOfColumnMajor(mat.RowCount, mat.ColumnCount, mat.GetData());
tmpPara.SampleSize = ws.Constants.Item(constIds[0]).GetData();
tmpPara.SubgroupSize = 1;
tmpPara.ParaID = null;
tmpParaList.Add(tmpPara);
}
else
{
//有指定參數的時候
#region Phase II
int nParas = ws.Columns.Item("CHART_PARA_INDEX").GetNumDistinctRows(); //宣告多組參數組
cmnd.AppendLine("macro");
cmnd.AppendLine("myt2calculator x.1-x.p;");
cmnd.AppendFormat("variance cov.1-cov.{0} ssiz.1-ssiz.{0};\r\n", nParas);
cmnd.AppendFormat("meanvect mvect.1-mvect.{0};\r\n", nParas);
cmnd.AppendLine("ppoint t2;");
cmnd.AppendLine("climit cl ucl;");
cmnd.AppendLine("test ooc;");
cmnd.AppendLine("siglevel alpha.");
cmnd.AppendLine("mcolumn x.1-x.p xx.1-xx.p xxx.1-xxx.p loc.1-loc.p");
cmnd.AppendLine("mcolumn tmp t2 ucl cl ooc tmpT2 tmpUCL tmpCL tmpOOC");
cmnd.AppendFormat("mmatrix mvect.1-mvect.{0} cov.1-cov.{0}\r\n", nParas);
cmnd.AppendFormat("mconstant m histm alpha conf a1 a2 ssiz.1-ssiz.{0} kk\r\n", nParas);
cmnd.AppendLine("default alpha = 0.0027");
var _chartparaindex = _rawdata.AsEnumerable()
.Select(x => x.Field <string>("CHART_PARA_INDEX")).ToArray();
var _distinctIds = _chartparaindex.Distinct().ToArray();
for (int i = 0; i < _distinctIds.Length; i++) //對每個參數與對應的資料計算 Tsquare 和管制界限
{
string id = _distinctIds[i];
cmnd.AppendLine("copy x.1-x.p xx.1-xx.p;");
cmnd.AppendLine("include;");
cmnd.AppendFormat("rows {0}.\r\n",
string.Join(" &\r\n",
_chartparaindex.Select((x, rowid) => new { Value = x, RowId = rowid + 1 })
.Where(x => x.Value == id).Select(x => x.RowId).ToArray()));
#region Set parameter information into Minitab macro
TsquareParameters para = new TsquareParameters();
para.Mean = null; para.Covariance = null; para.SampleSize = MISSINGVALUE; para.SubgroupSize = 1;
if (id != null)
{
para = _parameters.Where(x => x.ParaID == id).First();
}
if (para.Mean != null) //把已知的 Mean vector 寫入 Minitab
{
cmnd.AppendLine("read loc.1-loc.p");
cmnd.AppendFormat("{0}\r\n", string.Join(" &\r\n", para.Mean.Enumerate()));
cmnd.AppendLine("end");
}
else
{
cmnd.AppendLine("stat xx.1-xx.p;");
cmnd.AppendLine("mean loc.1-loc.p.");
}
if (para.Covariance != null) //把已知的 Covariance 寫入 Minitab
{
cmnd.AppendFormat("read {1} {2} cov.{0} \r\n", i + 1, para.Covariance.RowCount, para.Covariance.ColumnCount);
List <LinearAlgebra.Vector <double> > valuesByRow = para.Covariance.EnumerateRows().ToList();
for (int r = 0; r < para.Covariance.RowCount; r++)
{
cmnd.AppendFormat("{0}\r\n", string.Join(" &\r\n", valuesByRow[r]));
}
cmnd.AppendLine("end");
cmnd.AppendFormat("let ssiz.{0}={1}\r\n", i + 1, para.SampleSize);
}
else
{
cmnd.AppendLine("rnmiss xx.1-xx.p tmp");
cmnd.AppendLine("copy xx.1-xx.p xxx.1-xxx.p;");
cmnd.AppendLine("exclud;");
cmnd.AppendFormat("where \"tmp>0\".\r\n");
cmnd.AppendFormat("cova xxx.1-xxx.p cov.{0}\r\n", i + 1);
cmnd.AppendFormat("let ssiz.{0} = count(xxx.1)\r\n", i + 1);
}
#endregion
//Tsquare command
cmnd.AppendFormat("if(ssiz.{0} < p+1)\r\n", i + 1);
cmnd.AppendLine("let kk = p+1");
cmnd.AppendLine("else");
cmnd.AppendFormat("copy ssiz.{0} kk\r\n", i + 1);
cmnd.AppendLine("endif");
if (id == null && _chartparaindex.Where(x => x == id).Count() == 1) //如果只有一個觀測值且沒有參數設定
{
cmnd.AppendLine("let tmp=1");
cmnd.AppendLine("let tmpT2=miss()");
}
else
{
cmnd.AppendFormat("tsquare xx.1-xx.p {0};\r\n", para.SubgroupSize);
cmnd.AppendLine(" mu loc.1-loc.p;");
cmnd.AppendFormat(" sigma cov.{0};\r\n", i + 1);
cmnd.AppendLine(" number kk;");
cmnd.AppendLine("sampsize tmp;"); //Get subgroup size.
cmnd.AppendLine("ppoint tmpT2."); //Get Tsquare value.
}
cmnd.AppendFormat("copy loc.1-loc.p mvect.{0}\r\n", i + 1); //Copy column to mean vector
/*
* Get the value of m which use to calculate UCL, CL.
* In phase II, m is the sample size of the data used to calculate historical
* covariance matrix.
* In phase I, m is the number of observations.
*
*/
cmnd.AppendLine("let m = sum(tmp)"); //Get the actual sample size (include missing data)
if (para.Covariance != null)
{
cmnd.AppendFormat("let histm = ssiz.{0}\r\n", i + 1);
}
else
{
cmnd.AppendLine("copy m histm");
}
// Calculate control limits
if (id == null && _chartparaindex.Where(x => x == id).Count() == 1)
{
cmnd.AppendLine("let tmpUCL=miss()");
cmnd.AppendLine("let tmpCL=miss()");
}
else
{
cmnd.AppendLine("let conf = 1-alpha");
cmnd.AppendLine("let a1 = p");
cmnd.AppendLine("let a2 = histm");
#region Get UCL
cmnd.AppendLine("set tmp");
cmnd.AppendLine("(conf)m");
cmnd.AppendLine("end");
if (id == null) //phase I case
{
cmnd.AppendLine("invcdf tmp tmpUCL;");
cmnd.AppendLine(" beta a1 a2.");
cmnd.AppendLine("let tmpUCL = (m-1)**2/m*tmpUCL"); //Get upper control limit
}
else //phase II case
{
cmnd.AppendLine("invcdf tmp tmpUCL;");
cmnd.AppendLine(" f a1 a2.");
cmnd.AppendLine("let tmpUCL = p*(histm+1)*(histm-1)/histm/(histm-p)*tmpUCL"); //Get upper control limit
}
#endregion
#region Get CL
cmnd.AppendLine("set tmp");
cmnd.AppendLine("(0.5)m");
cmnd.AppendLine("end");
if (id == null)
{
cmnd.AppendLine("invcdf tmp tmpCL;");
cmnd.AppendLine(" beta a1 a2.");
cmnd.AppendLine("let tmpCL = (m-1)**2/m*tmpCL"); //Get upper control limit
}
else
{
cmnd.AppendLine("invcdf tmp tmpCL;");
cmnd.AppendLine(" f a1 a2.");
cmnd.AppendLine("let tmpCL = p*(histm+1)*(histm-1)/histm/(histm-p)*tmpCL"); //Get center line
}
#endregion
}
cmnd.AppendLine("let tmpOOC = if(tmpT2>tmpUCL AND tmpT2<>MISS(),1,0)"); //Get OOC info
if (i == 0)
{
cmnd.AppendLine("copy tmpT2 tmpUCL tmpCL tmpOOC t2 ucl cl ooc");
}
else
{
cmnd.AppendLine("stack (t2 ucl cl ooc) (tmpT2 tmpUCL tmpCL tmpOOC) (t2 ucl cl ooc)");
}
}
//刪除所有圖形
cmnd.AppendLine("gmana;");
cmnd.AppendLine("all;");
cmnd.AppendLine("close;");
cmnd.AppendLine("nopr.");
cmnd.AppendLine("endmacro");
string macPath = Mtblib.Tools.MtbTools.BuildTemporaryMacro("mytsquare.mac", cmnd.ToString());
string[] matMeanIds = Mtblib.Tools.MtbTools.CreateVariableStrArray(ws, nParas, Mtblib.Tools.MtbVarType.Matrix);
string[] matCovIds = Mtblib.Tools.MtbTools.CreateVariableStrArray(ws, nParas, Mtblib.Tools.MtbVarType.Matrix);
string[] constIds = Mtblib.Tools.MtbTools.CreateVariableStrArray(ws, 1 * nParas, Mtblib.Tools.MtbVarType.Constant);
cmnd.Clear();
cmnd.AppendLine("notitle");
cmnd.AppendLine("brief 0");
cmnd.AppendFormat("%\"{0}\" {1};\r\n", macPath, string.Join(" &\r\n", varCols.Select(x => x.SynthesizedName)));
cmnd.AppendFormat("variance {0} {1};\r\n", string.Join(" &\r\n", matCovIds), string.Join(" &\r\n", constIds));
cmnd.AppendFormat("meanvect {0};\r\n", string.Join(" &\r\n", matMeanIds));
cmnd.AppendFormat("ppoint {0};\r\n", pplotCol.SynthesizedName);
cmnd.AppendFormat("climit {0} {1};\r\n", clCol.SynthesizedName, uclCol.SynthesizedName);
cmnd.AppendFormat("test {0}.\r\n", oocCol.SynthesizedName);
string path = Mtblib.Tools.MtbTools.BuildTemporaryMacro("mymacro.mtb", cmnd.ToString());
proj.ExecuteCommand(string.Format("exec \"{0}\" 1", path), ws);
#endregion
//取得參數組
TsquareParameters tmpPara;
Mtb.Matrix mat;
for (int i = 0; i < _distinctIds.Length; i++)
{
tmpPara = new TsquareParameters();
tmpPara.ParaID = _distinctIds[i];
mat = ws.Matrices.Item(matMeanIds[i]);
tmpPara.Mean = LinearAlgebra.Matrix <double> .Build.DenseOfColumnMajor(mat.RowCount, mat.ColumnCount, mat.GetData());
mat = ws.Matrices.Item(matCovIds[i]);
tmpPara.Covariance = LinearAlgebra.Matrix <double> .Build.DenseOfColumnMajor(mat.RowCount, mat.ColumnCount, mat.GetData());
tmpPara.SampleSize = ws.Constants.Item(constIds[i]).GetData();
tmpParaList.Add(tmpPara);
}
}
//繪圖
//會使用 TIMESTAMP, PPOINT, CL, UCL, TEST
#region 繪製 T2 Control Chart (TSPLOT)
string gpath = System.IO.Path.Combine(Environment.GetEnvironmentVariable("tmp"), "Minitab", string.Format("tsquare_{0}.jpg", _rawdata.TableName));
cmnd.Clear();
cmnd.AppendFormat("fdate {0};\r\n", timeCol.SynthesizedName);
cmnd.AppendLine("format(dtyyyy-MM-dd hh:mm).");
cmnd.AppendFormat("tsplot {0} {1} {2};\r\n", pplotCol.SynthesizedName, uclCol.SynthesizedName, clCol.SynthesizedName);
cmnd.AppendFormat("gsave \"{0}\";\r\n", gpath);
cmnd.AppendLine("repl;");
cmnd.AppendLine("jpeg;");
cmnd.AppendLine("over;");
cmnd.AppendFormat("symb {0};\r\n", oocCol.SynthesizedName);
cmnd.AppendLine("type &");
double[] oocData = oocCol.GetData();
if (oocData.Any(x => x == 0))
{
cmnd.AppendLine("6 &");
}
if (oocData.Any(x => x == 1))
{
cmnd.AppendLine("12 &");
}
cmnd.AppendLine("0 0 0 0;");
cmnd.AppendLine("size 1;");
cmnd.AppendLine("color &");
if (oocData.Any(x => x == 0))
{
cmnd.AppendLine("1 &"); //r17 color 64
}
if (oocData.Any(x => x == 1))
{
cmnd.AppendLine("2 &");
}
cmnd.AppendLine(";");
cmnd.AppendLine("conn;");
cmnd.AppendLine("type 1 1 1;");
cmnd.AppendLine("color 1 2 120;"); //r17 conn:64 cl: 9, climit:8
//cmnd.AppendLine("graph;");
//cmnd.AppendLine("color 22;");
cmnd.AppendLine("nole;");
cmnd.AppendFormat("stamp {0};\r\n", timeCol.SynthesizedName);
cmnd.AppendLine("scale 1;");
cmnd.AppendFormat("tick 1:{0}/{1};\r\n", pplotCol.RowCount,
pplotCol.RowCount > 35 ? Math.Ceiling((double)pplotCol.RowCount / 35) : 1);
cmnd.AppendLine("axla 1;");
cmnd.AppendLine("adis 0;");
cmnd.AppendLine("axla 2;");
cmnd.AppendLine("adis 0;");
string ttlString = string.Join(",", varnames);
if (ttlString.Length > 23)
{
ttlString = ttlString.Substring(0, 20) + "...";
}
cmnd.AppendLine("graph 8 4;");
cmnd.AppendFormat("title \"T2管制圖 {0}\";\r\n", ttlString);
cmnd.AppendFormat("footn \"更新時間: {0}\";\r\n", DateTime.Now);
cmnd.AppendFormat("ZTag \"{0}\";\r\n", "_T2CHART");
cmnd.AppendLine(".");
//刪除所有圖形
cmnd.AppendLine("gmana;");
cmnd.AppendLine("all;");
cmnd.AppendLine("close;");
cmnd.AppendLine("nopr.");
string t2MacroPath = Mtblib.Tools.MtbTools.BuildTemporaryMacro("myt2macro.mtb", cmnd.ToString());
proj.ExecuteCommand(string.Format("exec \"{0}\" 1", t2MacroPath), ws);
#endregion
//將檔案轉為二進位陣列
this.Contents.Add(new RptOutput()
{
OType = MtbOType.GRAPH,
OutputInByteArr = File.ReadAllBytes(gpath)
});
//計算 Decomposition
if (oocData.Any(x => x == 1))
{
DataTable tmpDataTable = _rawdata.Copy();
tmpDataTable.Columns.Add("OOC", typeof(int));
for (int r = 0; r < tmpDataTable.Rows.Count; r++)
{
DataRow dr = tmpDataTable.Rows[r];
dr["OOC"] = oocData[r];
}
//建立 Decomposition 的表格
DataTable decoTable = new DataTable();
decoTable.Columns.Add("TIMESTAMP", typeof(DateTime));
foreach (var item in varnames)
{
decoTable.Columns.Add(item, typeof(double));
}
//將OOC的項目值取出
var subData = tmpDataTable.Select("OOC=1").CopyToDataTable();
var oocParaSet = subData.AsEnumerable().Select(dr => dr.Field <string>("CHART_PARA_INDEX")).Distinct().ToArray(); //OOC 的參數組有哪些
foreach (var item in tmpParaList)
{
if (oocParaSet.Contains(item.ParaID)) //該參數組的觀測值是OOC
{
//把對應的觀測值轉換成 List<double[]>，其中每個 double[] 是每個 row 的數據
var subsubData = subData.Select(string.Format("CHART_PARA_INDEX {0}", item.ParaID == null ? "IS NULL" : "='" + item.ParaID + "'"))
.CopyToDataTable();
var obsArray = subsubData.DefaultView.ToTable(false, varnames.ToArray())
.AsEnumerable().Select(x => x.ItemArray.Select(o => Convert.ToDouble(o)).ToArray()).ToList();
LinearAlgebra.Matrix <double> obs = LinearAlgebra.Matrix <double> .Build.DenseOfRowArrays(obsArray);
LinearAlgebra.Matrix <double> t2deco = Tool.T2Decomposition(obs, item.Mean, item.Covariance);
var t2decoByRow = t2deco.EnumerateRows().ToArray();
for (int r = 0; r < t2decoByRow.Count(); r++)
{
DataRow dr = decoTable.NewRow();
object[] o = new object[1 + t2deco.ColumnCount];
t2decoByRow[r].ToArray().CopyTo(o, 1);
o[0] = subsubData.Rows[r].Field <DateTime>("TIMESTAMP");
decoTable.Rows.Add(o);
}
}
}
cmnd.Clear();
//LinearAlgebra.Matrix<double> obs = LinearAlgebra.Matrix<double>.Build.DenseOfRowArrays(subData);
this.Contents.Add(new RptOutput()
{
OType = MtbOType.TABLE,
OutputInByteArr = Tool.ConvertDataSetToByteArray(decoTable)
});
}
else // 沒有 OOC 就不做
{
this.Contents.Add(new RptOutput()
{
OType = MtbOType.TABLE,
OutputInByteArr = null
});
}
//Console.ReadKey();
}