When getting the column names from the Col List Box in your script, you subset the list that is returned with [1]. This only returns the first selected column. If you remove the brackets and then iterate over the lists you can apply your script to multiple x and y column pairs. You likely want to summarize or concatenate your results but the basic idea would look like the script below. Note that to speed things up I only evaluate a=1 (see the commented /* 7 */)
Names Default To Here( 1 );
//wrap your script to process both variables in a function
//this is not necessary but it make the new for loops more clear
processpair = function({dt, xvar, yvar},
d = 1;
m = Matrix( 72, 5 );
l = List( 72 );
l1 = List( 72 );
l2 = List( 72 );
For( c = 1, c < 3, c++,
For( b = 1, b < 7, b++,
transb = Match( b, 1, "Log", 2, "Sqrt", 3, "Square", 4, "Reciprocal", 5, "Exp", 6, "None", );
For( a = 1, a < 7 /* 7 */, a++,
transa = Match( a, 1, "Log", 2, "Sqrt", 3, "Square", 4, "Reciprocal", 5, "Exp", 6, "None", );
biv = Bivariate(
Y( Column( yvar ) ),
X( Column( xvar ) ),
Fit Special(
xTran( transb ),
yTran( transa ),
Degree( c ),
Centered Polynomial( 0 ),
{Line Color( {213, 72, 87} )}
),
//SendToReport(
// Dispatch(
// {"Transformed Fit Log to Log"},
// "Summary of Fit",
// OutlineBox,
// {Set Title( "Summary of Fit" )}
// )
//)
);
rbiv = Report( biv );
bivmatrix = Try( rbiv[Outline Box( 3 )][1][2] << Get As Matrix );
If( Is Missing( bivmatrix = Try( rbiv[Outline Box( 3 )][1][2] << Get As Matrix ) ),
0
);
//bivmatrix2 = rbiv[Number Col Box( 7 )] << Get As Matrix;
//bivMatrix3 = rbiv[Number Col Box( 8 )] << Get As Matrix;
bivR2 = bivmatrix[1];
bivRMSE = bivmatrix[3];
//bivIntercept = bivMatrix2[1];
//bivX = bivMatrix2[2];
//bivForm = rbiv[Text Edit Box( 4 )];
//l[d] = transb || "(" || xvar || ") vs " || transa || "(" || yvar || ")";
l[d] = xvar;
l1[d] = transb;
l2[d] = transa;
m[d, 1] = c;
m[d, 2] = bivR2;
m[d, 3] = bivRMSE;
Close All( Reports, No Save );
//m[d, 3] = bivIntercept;
//m[d, 4] = bivx;
d++;
);
)
);
ds = New Table( "Tranformation Evalutation" || " " || xvar || " vs " || yvar );
ds << New Column( "Independent Variable", Character, Text, Width( 5 ), Values( l ) );
ds << New Column( "X Transformation", Character, Text, Width( 5 ), Values( l1 ) );
ds << New Column( "Y Transformation", Character, Text, Width( 5 ), Values( l2 ) );
ds << New Column( "Polynomial Degree", Numeric, Continuous, Width( 5 ), Values( m[0, 1] ) );
ds << New Column( "R2", Numeric, Continuous, Width( 5 ), Values( m[0, 2] ) );
ds << New Column( "RMSE", Numeric, Continuous, Width( 5 ), Values( m[0, 3] ) );
);
//use sample data
dt = Open( "$SAMPLE_DATA/Body Fat.jmp" );
xvar = .;
yvar = .;
win = New Window( "Transformation Variable Selection",
Text Box( " Select Numeric Columns. " ),
H List Box(
Text Box( " X, Factor " ),
x = Col List Box(
dt, // data table reference
all, // display all columns from the data table
// get the name of the selected column before the window closes
xvars = (x << Get Selected);
Show( xvar );
),
Text Box( "Y, Response" ),
y = Col List Box(
dt,
all,
yvars = (y << Get Selected);
Show( yvar );
)
),
tbStatus = Text Box("Ready."),
Button Box("Analyze Variables",
//Get variables
xvars = x << Get selected;
yvars = y << Get selected;
If( n items(xvars) == 0 | n items(yvars) == 0,
tbStatus << Set Text("Select at least one ind and one dep variable to continue."),
//for each combination of x and y variable
for( xvar_n = 1, xvar_n <= N items(xvars), xvar_n ++,
xvar = xvars[xvar_n];
show(xvar);
for(yvar_n = 1, yvar_n <= N items(yvars), yvar_n ++,
yvar = yvars[yvar_n];
show(yvar);
//Run your script
processpair( dt, xvar, yvar );
)
);
);
)
);
edited: fixed some bugs, see re-write later in thread
