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腳本 - 從分銷過程能力中提取規格限制

我正在嘗試編寫一個腳本（JMP 16.0）來從資料集中選擇列，建立分佈，執行連續擬合“ALL”並產生最佳擬合的過程能力（見下文）。

我遇到的問題是弄清楚如何產生具有分佈特徵的表，特別是產生的規格限制。此外，我也很難將所有發行版組合到一個視窗中。任何指針將不勝感激，我曾嘗試查看可編寫腳本的對象文檔，但沒有任何運氣。

file = Current Data Table ();
TableList = List ();
For (i = 1, i <= NTable(), i++,
     TableList [i] = Data Table (i) << Get Name
);
ColSelect = Column Dialog (
     Column Use = ColList ("Add", Max Col (N Col()))
);
For (i = 1, i <= N Items(ColSelect["ColumnUse"]), i++,
    colName = ColSelect ["ColumnUse"] [i] << Get Name;
     obj = file << Distribution(
         Continuous Distribution(Column(Eval(colName)), Fit ALL)
     );
     specLimits = obj << (Fit Handle["best"] << Process Capability( Set Sigma Multiplier for Quantile Spec Limits( 3 ), show limits ));
      );

數據探索和視覺化品質和工藝工程回复：腳本 - 從分配過程能力中提取規格限制

下面的腳本怎麼樣？ 希望能幫助到你。

file = Open("$SAMPLE_DATA/Cities.jmp");
ColSelect = Column Dialog( Column Use = ColList( "Add", Max Col( N Col() ) ) );
If( ColSelect["Button"] != 1,
 Throw();
);

spec limit aa = Associative Array();

nw = New Window( "Combined Results",
 H List Box(
  For( i = 1, i <= N Items( ColSelect["ColumnUse"] ), i++,
   colName = ColSelect["ColumnUse"][i] << Get Name;
   obj = file << Distribution(
    Continuous Distribution( Column( Eval( colName ) ), Fit ALL )
   );

   rpt = obj << report;
   best dist = rpt[Outline Box( "Compare Distributions" )][Table Box( 1 )][
   String Col Box( 1 )] << get( 1 );

   Eval(
    Eval Expr(
     obj << (Fit Handle[Expr( best dist )] <<
     Process Capability( Set Sigma Multiplier for Quantile Spec Limits( 3 ) ))
    )
   );

   spec limits = rpt[Outline Box( "Process Capability" )][
   Outline Box( "Process Summary" )][Table Box( 1 )][Number Col Box( 1 )] << get;
   spec limit aa[colName] = Eval List( {spec limits, best dist} );
  )
 )
);

//Save to New Data Table
result dt = New Table( "Results" );
colnames = spec limit aa << get keys;

result dt << addmultiplecolumns( "key", N Items( colnames ), Numeric );

For( i = 1, i <= N Col( result dt ), i++,
 Column( result dt, i ) << set name( colnames[i] )
);

result dt << addrows( 5 );

For( j = 1, j <= N Col( result dt ), j++,
 For Each Row(
  i = Row();
  Try( result dt[i, colnames[j]] = spec limit aa[colnames[j]][1][i] );
 )
);