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How to create seperate table of selective Variability gauge chart GRR report and Linearity and Bias Report

aravindan880

Community Trekker

Joined:

Apr 5, 2016

How do i create a seperate table for Variability gauge Report GRR for selective items in the report

First Report

12666_pastedImage_5.png

Current JMP Script to display First Report

Clear Globals();

popup = Dialog(

  "Enter specification tolerance",

  selection = editnumber(),

  "Select Reproducibility Factor",

  selection1 = combobox("Equipment","Operator"),

  Button( "Ok" ),

  Button( "Cancel" ));

If( popup["Button"] == -1,

  Throw( "cancel" ));

specrange = popup["Selection"];

reproducibility=popup["Selection1"];

Column( 1 ) << modeling type( nominal );

Column( 2 ) << modeling type( nominal ) << Set name(eval(if(reproducibility==1,"Equipment","Operator")));

Column( 3 ) << modeling type( continuous );

var=Variability Chart(

  Y( Column (3) ),

  X( Column (2) , Column (1) ),

  Model( "Crossed" ),

  Max Iter( 20 ),

  Analysis Type( Name( "Choose best analysis (EMS REML Bayesian)" ) ),

  Historical Sigma( 0 ),

  Connect Cell Means( 1 ),

  Show Group Means( 1 ),

  Show Grand Mean( 1 ),

  Std Dev Chart( 1 ),

  Gauge RR( 5.15, specrange, 0, 0 ),

  Gauge RR Report( 1 ),

  Show Box Plots( 1 ),

  Mean Plots( 1 ),

  Std Dev Plots( 1 )

);

var << Set Report Title("GRR Results")


______________________________________________________________________________________________________________________________________________

Second Report

How do i create a seperate table for Variability gauge Report (linearty and Bias report)  for selective items in the report

12667_pastedImage_10.png

JMP Script for second report

Clear Globals();

Column( 1 ) << modeling type( nominal );

Column( 2 ) << modeling type( continuous );

Column( 3 ) << modeling type( continuous );

Column( 4 ) << modeling type( nominal );

var=Variability Chart(

  Y( Column(3) ),

  X( Column(2) ),

  By( Column(4) ),

  Analysis Type( Name( "Choose best analysis (EMS REML Bayesian)" ) ),

  Standard( Column(2) ),

  Connect Cell Means( 1 ),

  Show Group Means( 1 ),

  Show Grand Mean( 1 ),

  Std Dev Chart( 1 ),

  Show Box Plots( 1 ),

  Bias Report,

  Linearity Study( 0.05 )

);

var << Set Report Title("Linearity/Bias Results")

1 ACCEPTED SOLUTION

Accepted Solutions
Solution

There may be a better way, but this produces the result you're after.  The trick is to expose the Tree Structure of the report or outline box that contains the information you want. Right-click on the outline's disclosure button and select Edit->Show Tree Structure:

12673_pastedImage_0.png

The resulting window will display the tree structure for the objects in the report so that you can reference them in your script. See below for the code that I appended to your script to produce the table for your first report:

 

repvar = var << Report;

 

LBL1 = repvar["Gauge R&R"][String Col Box( 1 )];

 

LBL2 = repvar["Gauge R&R"][String Col Box( 2 )];

 

VAL1 = repvar["Gauge R&R"][Number Col Box( 3 )];

 

VAL2 = repvar["Gauge R&R"][Number Col Box( 6 )];

 

 

win1 = New Window( "The Report",

 

     Table Box( String Col Box( "Attribute", {LBL1[5], LBL1[1], LBL1[6], LBL1[2], "Number of Distinct Categories", "P/T %"} ),

 

     String Col Box( "Abrev", {LBL2[5], LBL2[1], LBL2[6], LBL2[2]} ),

 

     Number Col Box( "Value", {VAL1[5], VAL1[1], VAL1[6], VAL1[2], VAL2[4], VAL2[6]*100} )

 

     )

 

);

 

The result:

12674_pastedImage_0.png

Hope this helps.

3 REPLIES
Solution

There may be a better way, but this produces the result you're after.  The trick is to expose the Tree Structure of the report or outline box that contains the information you want. Right-click on the outline's disclosure button and select Edit->Show Tree Structure:

12673_pastedImage_0.png

The resulting window will display the tree structure for the objects in the report so that you can reference them in your script. See below for the code that I appended to your script to produce the table for your first report:

 

repvar = var << Report;

 

LBL1 = repvar["Gauge R&R"][String Col Box( 1 )];

 

LBL2 = repvar["Gauge R&R"][String Col Box( 2 )];

 

VAL1 = repvar["Gauge R&R"][Number Col Box( 3 )];

 

VAL2 = repvar["Gauge R&R"][Number Col Box( 6 )];

 

 

win1 = New Window( "The Report",

 

     Table Box( String Col Box( "Attribute", {LBL1[5], LBL1[1], LBL1[6], LBL1[2], "Number of Distinct Categories", "P/T %"} ),

 

     String Col Box( "Abrev", {LBL2[5], LBL2[1], LBL2[6], LBL2[2]} ),

 

     Number Col Box( "Value", {VAL1[5], VAL1[1], VAL1[6], VAL1[2], VAL2[4], VAL2[6]*100} )

 

     )

 

);

 

The result:

12674_pastedImage_0.png

Hope this helps.

aravindan880

Community Trekker

Joined:

Apr 5, 2016

Thanks Jerry Cooper it works great!!!

The Linearity and Bias report is slightly tricky as there could be more than 1 Linearity and Bias report and we need to grab the min of the linearity% and Bias%

jerry_cooper

Staff

Joined:

Jul 10, 2014

Glad it worked.  As you work through the second report, keep in mind that when you have a By variable, you'll have a Display Box for each By group. Use an index to reference the report for each By group.  If there was a By group in the example I used above, in order to access the report layer for each, my code might have looked like this:

LBL1a = repvar[1]["Gauge....]  for the first "By" group, and

LBL1b = repvar[2]["Gauge....] for the second "By" group.