Here is my take on using the Spec Limits in each columns' Column Property to test each row. The method used for the testing is to apply a Range Check to each column. This is used because it is a very efficient way to deal with all of the data in a column with one operation. Given the number of columns you are dealing with, this method should be more efficient than testing each cell. In the script I use the Semiconductor Data Table from the Sample Data folder. It has all spec limits set for all 128 measurement columns.
Names Default To Here( 1 );
dtOrig = Open("$SAMPLE_DATA/Semiconductor Capability.jmp");
colNamesList = dtOrig << get column names( continuous, string );
// Create a work table of just the continuous columns
dt = dtOrig << subset( columns( colNamesList ), selected rows( 0 ) );
// Loop across all of the columns and apply a Range Check to eliminate
// all data outside of the upper and lower spec limits
For( theCol = 1, theCol <= N Items( colNamesList ), theCol++,
specs = Column( dt, colNamesList[theCol] ) << get property( "spec limits" );
Eval(
Substitute(
Expr(
Column( dt, colNamesList[theCol] ) << set property(
"Range Check",
(LELE( __LSL__, __USL__ ))
)
),
Expr( __LSL__ ), specs["LSL"],
Expr( __USL__ ), specs["USL"]
)
);
// Now convert the column to numeric
Column( dt, colNamesList[theCol] ) << data type( character );
// Now find all cells where values were eliminated
dt << select where( As Column( dt, colNamesList[theCol] ) == "" );
// If non passing rows were found, process the column to change the passing rows to
// a blank, and non passing to the name of the column
If( N Rows( dt << get selected rows ) > 0,
// Now set all eliminated cells to have the value of the name of the column
Column( dt, colNamesList[theCol] )[dt << get selected rows] = Column( dt, colNamesList[theCol] ) <<
get name;
// Invert the row selection, to select all rows where values passed and set them to a blank
dt << invert row selection;
Column( dt, colNamesList[theCol] )[dt << get selected rows] = "";
, // else set all
Column( dt, colNamesList[theCol] )[Index( 1, N Rows( dt ) )] = ""
);
);
// Now create a new column to hold the information on either that the row Passed or
// which columns failed
dt << New Column( "Pass_Fail", Character );
// Loop across all rows and set the values for the new column
For( theRow = 1, theRow <= N Rows( dt ), theRow++,
If( Trim( Concat Items( dt[theRow, 0, ""] ) ) == "",
:Pass_Fail[theRow] = "Pass"
,
thePass_Fail = Concat Items( dt[theRow, 0], "," );
For( i = Length( thePass_Fail ), i >= 2, i--,
If( Substr( thePass_Fail, i, 1 ) == ",",
If( Substr( thePass_Fail, i - 1, 1 ) == ",",
thePass_Fail = Substr( thePass_Fail, 1, i - 1 ) || Substr( thePass_Fail, i + 1 )
)
)
);
If( Right( thePass_Fail, 1) == ",", thePass_Fail = Left( thePass_Fail, length( thePass_Fail ) - 1 ) );
:Pass_Fail[theRow] = thePass_Fail;
)
);
// Only the new column is what is needed, so delete all other columns
dt << delete columns( eval(colNamesList) );
// Add the new column to the original data table
dtOrig << Update(
With( dt )
);
// Delete the no longer needed work table
close(dt, nosave );
Jim