About hlrauch

hlrauch · ‎11-30-2016

If the data type of the Values column is "Character" (and therefore the modeling type of the Values column is either nominal or ordinal), then x is a list instead of a matrix. (Values in a list is enclosed in curly braces {} instead of brackets [] ). In that case try using the N Items() function instead of the N Rows() function. lastitem = x[N Items( x )];

hlrauch · ‎08-03-2016

Also check that the variable's Modeling Type is "Continuous" instead of "Nominal" or "Ordinal." There should be a blue triangle next to it in the Columns pane, or you can check the modeling type by selecting "Column Info" from the "Cols" menu. JMP provides different graphs and analyses depending on the selected modeling type. Howard

hlrauch · ‎07-19-2016

Thanks Phil. This does help, in particular by confirming that I'm not missing any obvious way to open the various launch windows using the Control Chart() platform call, and that the Main Menu() command is the only known work-around. Howard

hlrauch · ‎07-13-2016

The JMP Scripting Guide shows how to display the launch window for a platform, so a user can select columns and other options (V12 Scripting Guide, p. 387). The guide's example displays the Distribution launch window: Distribution(Weight({})) ; This works well in most cases. However I can't figure out how to display the launch windows for the control chart platforms. I can run the following: Control Chart() ; but this (and some variations of this code) always opens the X-Bar Control Chart launcher. I can't display the launch windows for run charts, IR (individual measurement & moving range) charts, or any of the other control charts. The following two attempts, for example, produce errors. Control Chart( Sample Size( 1 ) , KSigma( 3 ) , Chart Col( {} , Run Chart ) ) ; Control Chart( Sample Size( 1 ) , KSigma( 3 ) , Chart Col( {} )) ) ; I may have a work-around method, but I would rather do this using the documented techniques. Any suggestions for displaying the launch windows for these other control charts? Thanks! Howard

hlrauch · ‎11-23-2015

I agree with MS: I'm not sure what the << On Close() function is doing either. The JSL Syntax Reference (under Help > Books) explains the On Close function differently than the Scripting Index. From the Scripting Reference: " <<On Close (expr) runs expr when the window is closed. Returns 0 if the window fails to close." So does an argument of 0 prevent the window from closing or does a window failing to close generate a 0 result from the function? Very confusing. Getting back to the issue of your modal dialog box... I think that the << Modal command treats the "OK" and "Cancel" buttons as special buttons (same behavior as old Dialog() function). So scripts can not be attached to the "OK" and "Cancel" buttons (an error appears in the log). So here's another approach that may work for your modal window. Create other buttons that can perform actions by attaching scripts to those buttons. The window stays open until the "OK" button is clicked. Unfortunately I don't think that you can rename the "OK" button to "Close" or allow another button to close the modal window. Names Default To Here( 1 ); win = New Window( "Example", << Modal, << On Close ( Print( "Closed" ) ), // prints to log window Show Menu( 0 ), Show Toolbars( 0 ), Suppress Autohide, Text Box( "Example: Modal Dialog Window" ), Text Box( "" ), H List Box( Button Box( "Say Hello", Print( "Hello" ) ), // prints to log window Button Box( "New Window", newwin = New Window( "New Window" ) ), Button Box( "OK" ) ) ); I have included an example of << On Close() in this script. You can see that it performs this script action when the window is closed. Good luck! Howard

hlrauch · ‎11-21-2015

msharp, It sounds like you want to add the "Keep Dialog Open" as a check box in the dialog window, right? If that's the case, here's part of a script that I've used to add one or more columns of random numbers. The script behind the "OK" button closes the window only if the check box is unchecked. Names Default to Here( 1 ); keepopen = 0; New Window( "Example", Show Menu( 0 ), Show Toolbars( 0 ), Suppress Autohide, Text Box( "Example: Keep Dialog Open Checkbox" ), Text Box( "" ), H List Box( keepcbox = Check Box( "Keep dialog open", keepopen = keepcbox << get( 1 ) ), Button Box( "OK", // Insert name of an expression to run as a script If( !keepopen, Current Window() << Close Window); ), Button Box( "Cancel", Current Window() << Close Window ) ) ); Of course you would want to add more options to the dialog window ( advanced example in the JMP Scripting Guide; pages 454-456). I don't think that you can add a similar check box using the older (modal) Column Dialog() method. You can make the above window modal by adding a <<Modal option, but that may require some additional tricks. Howard

hlrauch · ‎11-04-2015

Sebastian, Just to build on MS's excellent reply... We've written a very similar script to add the R2 Predicted value to the Fit Model output. Instead of displaying a dialog box to select the appropriate report, you can run the script from the menu or a toolbar of the current report window (the script must be added to the menu or a toolbar). Then the Current Window() command provides a reference to the report window, and you can search the outline boxes within the report window. Here is a portion of our script. curwin = Current Window(); For( i = 1, i < 10000, i++, Try( outlinebox = curwin[Outline Box( i )]; Try( outlineboxobj = outlinebox << Get Scriptable Object; // DETAILS NOT SHOWN: // Check that the outline box is the top of a Fit Model analysis, with Standard Least Squares personality. // Pull the PRESS statistic and SS(treatment) to calculate R2-Predicted and append it to the Summary of Fit. ); , Break(); // If no more outline boxes are found, the first "Try()" goes here and forces an escape from the For() loop. ); ); Our script actually inserts the R2 Predicted value into every Fit Model analysis in that window (works for multiple Y's and by-variables). It does this by looking at every outline box in the report window. Comments: 1. The JSL documentation does not do justice to the "<< Get Scriptable Object" message. I looked for a very long time for a method to access existing report windows (standard analyses that had already been created by a user, not by a script). This capability opens up a lot of scripting opportunities. 2. To keep all of us from re-inventing the wheel, it would be nice if JMP included the R2-Predicted value in the standard Fit Least Squares output. Howard

hlrauch · ‎10-30-2015

Here's one solution. There may be some smarter solutions out there. A spacer box creates a flexible or fixed-size space in the layout. Place a very wide spacer box below the globalbox (within a V list box) to reserve a fixed amount of horizontal space. var1 = 11; var2 = 22; New Window( "Side-by-Side Display Boxes", Hlistbox( Vlistbox( globalbox(var1), spacerbox( size(100, 1) ) ), Vlistbox( globalbox(var2), spacerbox( size(100, 1) ) ), ) ); Will that work? Howard

hlrauch · ‎10-25-2015

Craig, this article was very helpful to me in my continuing quest to understand how to deal with expressions. I actually had a good application for your final trick, where you turned items in a list into arguments of the Less() function. I wanted to generate a column formula containing the Col Mean() function, based on user input from a dialog window. The Col Means() function takes one or more arguments, and I've never had a slick way to substitute a varying number of arguments (often variable names) into a function. Here are the key lines in my script: arglist = {"height", "age", "sex"}; // results from a dialog window statformula = Substitute ( arglist, Expr( {} ), Expr( Col Mean() ) ); // items in arglist become arguments in Col Means() function newcol << Formula( Name Expr( statformula ) ); The actual script is more complex because it needs to deal with messy column names that require Name(" "), but you get the idea. Thanks for showing me this neat trick. Howard Rauch

hlrauch · ‎09-23-2015

One more simple way: 1. Select Tables > Summary. In the column dialog window, select Person and Sex and make them Group variables. (No Statistics columns needed here.) Click OK. This produces a table with no duplicate rows. Person Sex N Rows 1 F 1 2 F 2 3 M 2 4 M 1 5 F 2 2. Select Tables > Summary for this new table. In the column dialog window, just select Sex and make it a Group variable. Click OK. Sex N Rows F 3 M 2 Howard

hlrauch · ‎08-28-2015

A couple more ideas: Instead of creating a totally new designed experiment or repeating the same experimental runs, you can add experiments to your current data using the "Augment" feature. With your current data table open, select DOE > Augment Design from the menu bar. Enter ISOD as the Y and the other two variables as X's.In the Augment Design window, click on the Augment button. For a standard model that is useful for prediction (interactions and curvature effects), click on the RSM button. The new designed experiment will consist of your 6 experimental runs plus several more runs to complete. Regarding predicted values above 100: one could do a Logitpct transform on the response data. I would want to know more about the nature of the response before transforming it, but this would guarantee that the model predictions stay between 0 and 100. In the model dialog, put ISOD in the Y role, click on it to select it, and then click on the Transform red triangle and select LogitPct. Howard

hlrauch · ‎07-31-2015

I don't know why it's still visible for you. However, as you see, Vince's solution should definitely do the trick for you. Howard

hlrauch · ‎07-31-2015

I should clarify: I'm able to use your script to open a table, and the table BECOMES invisible immediately. If the table is already open and visible, and it is currently your active table, you can "name" the table and make it invisible as follows: cdt = Current Data Table(); cdt << Show Window(0); Howard

hlrauch · ‎07-31-2015

Your script works fine for me. I'm able to use it to open a data table that is invisible. When you say the script "doesn't work" do you mean that the data table remains visible, or does it not appear at all (even in the window list)? Is it possible that, if the table is very large or if the table is open from a remote location, the script needs to pause to let the table open completely? In that case, I'm guessing that inserting a Wait(1.0); command between your two lines of code could help. Otherwise, check for typos. Howard

hlrauch · ‎07-09-2015

I'd like to build on Ian's answer. If you have a script that creates the output and then saves the desired output as an image file (.png), you can use a trick in Excel (no OLE needed). In Excel (I'm running Excel 2010) select Insert on the ribbon menu bar and then select Picture. Select your saved image file and then click on the triangle next to the Insert button and select "Insert and Link." Now, whenever the Excel file is opened, Excel will automatically link to the latest version of the image file at that location. You will only need to run the script that creates the image file; Excel will take care of the rest.. I'm not an Excel expert, so please correct me if I missed anything. Howard

hlrauch · ‎06-22-2015

Two possible approaches come to mind... 1. Create a stepped function using the Overlay Plot. Create a data table with columns for Power and Efficiency. To replicate my results, run the following script: New Table( "Example", Add Rows( 4 ), New Column( "Power", Numeric, "Continuous", Set Property( "Units", "W" ), Set Values( [10, 12, 15, 17] ) ), New Column( "Efficiency", Numeric, "Continuous", Set Property( "Units", "%" ), Set Values( [90, 93, 97, 97] ) ) ); Then create an overlay plot (Graph > Overlay) where Y is Efficiency and X is Power. Finally, click on the red triangle and select Y Options > Step. 2. Add a function to an existing graph. If you already have a graph (such as a Bivariate / Fit Y by X graph) containing data, right-click on the graph and select Customize. In the Customize Graph window, click on the "+" button and paste the following script. Y Function( If( 10 < x <= 12, 90, 12 < x <= 15, 93, 15 < x <= 17, 97, . ), x ); Then click OK.The function should be overlaid on the graph. Adjust axes if necessary. Howard

hlrauch · ‎04-17-2015

By "main effects plots", I think you're referring to the window of plots in Minitab where each plot consists of Y versus one of the X's with a sloping line showing the size of the effect of X on Y. You can get basically the same thing in JMP by requesting the LS (Least Squares) Means Plots, which are hidden in the Fit Model platform. Select Analyze > Fit Model (with Emphasis: "Effect Leverage") to run the analysis. You should see some leverage plots. Click on the red triangle above each leverage plot and select LS Means Plot. These plots are only available if X is not continuous. Also, the plots are not grouped together. Another option is the Prediction Profiler, which is also available in the Fit Model report. Select Factor Profiling > Profiler in the Fit Model report. The response here actually represents the predicted value from the model, with all the Xs at specified levels. This graph is interactive and you can slide the vertical red lines to change choices for the X's. You may find that the prediction profiler is more useful than the main effects plots. Howard

hlrauch · ‎04-13-2015

Craige's answer is probably the easiest. We often need a square version of the graph with the axes spanning the entire range. One way to do that is to determine the min and max values and set both axes to the same values. g = Bivariate( Y( :height ), X( :weight ) ); minaxis = Min( Col Min( :height ), Col Min( :weight ) ); maxaxis = Max( Col Max( :height ), Col Max( :weight ) ); (Report( g )[axisbox( 1 )]) << {Min( minaxis ), Max( maxaxis )}; (Report( g )[axisbox( 2 )]) << {Min( minaxis ), Max( maxaxis )}; (Report( g )[framebox( 1 )]) << Frame Size( 320, 320 ); The resulting graph: I sometimes add a 45-degree line to this graph to indicate X=Y. This graph is useful if X and Y represent the same property or characteristic (not height and weight). If X and Y represented values of the same characteristic measured by measurement devices X and Y, this graph would tell us that there is a problem between the two measurement devices. Some points are on the edge of the graph. This can be fixed by using a "weighted combination" of min and max values to widen the axes: minaxis = 1.05 * Min( Col Min( :height ), Col Min( :weight ) ) - 0.05 * Max( Col Max( :height ), Col Max( :weight ) ) ; maxaxis = -0.05 * Min( Col Min( :height ), Col Min( :weight ) ) + 1.05 * Max( Col Max( :height ), Col Max( :weight ) ) ; Good luck! Howard

hlrauch · ‎03-31-2015

This isn't a very elegant solution, but it might work for your situation. To explicitly tell Excel that the value is text ( not a numeric date value), you can place a single quote (tick mark) before the text. For example, " '09-1903 " (without the double quotes, of course). It's possible to add this single quote using formulas in JMP. If the column in JMP is numeric, then you can create a new column in JMP with the following formula: "'" || Format(:numeric column) That's a single quote inside two double quotes, 2 vertical bars (concatenate function symbol), and the Format function (translates the date variable to its formatted form as a text/character value). If the column in JMP is character, then you can create a new column in JMP with the following formula: "'" || :character column Once again, that's a single quote inside two double quotes, and 2 vertical bars (concatenate function symbol). In Excel you won't see the single quote in the cell, but it's still there, so it might create some issues if you do any Excel calculations based on that cell. Best of luck. Howard

hlrauch · ‎03-17-2015

You should be able to add an IF function around your "_function_of_x_". In other words: Y Function( If( 50<x<100, _function_of_x_ ), x ); If x is not in that range, no value is produced.

hlrauch · ‎03-17-2015

If you need the data/row number to update whenever you add or delete rows, you can create a column with a simple formula. Add a new column and then right-click on the header/name of the new column and select Formula . In the formula window click on Row in the Functions(grouped) list and then click on Row in the pop-up list of functions. The formula "Row()" will appear in the formula box. Click OK .

hlrauch · ‎02-19-2015

Great explanation on centering polynomials!

hlrauch · ‎02-02-2015

Yes, the JMP scripting language can do everything you want. However it's not a trivial effort. I suggest that you scan the JMP Scripting Guide and look at examples that might match your application. The guide is available in JMP under the Help menu and online at http://www.jmp.com/support/help/Scripting_Guide.shtml .

hlrauch · ‎12-31-2014

Hi Ramon. I have designed 2^3 factorials with 5 or 6 center points because we wanted a good understanding of the experimental noise. I have also designed 2^3 factorials with no center points, because the experimenters could not perform more than 8 runs or because the factors only had two discrete levels (on/off, old/new). The number of center points included in a factorial experiment really depends on the type of information you want to get from the experiment. Here are three types of information that you can gain by adding center points to a designed experiment: Estimate of pure experimental error - To test the effects of each factor, you need a reliable estimate of the "noise" or experimental error. Each redundant or replicated point (could be either a center point of a factorial point) provides another degree of freedom toward estimating experimental error. Create a design i n JMP, add simulated response data, run the Fit Model platform, and check out the Pure Error degrees of freedom under the "Lack of Fit" box. I have seen guideline minimum values of 3 to 6, but sometimes those minimum values still aren't possible. Detection of non-linear trends - Adding center points to a design creates a third level in the two-level factorial, and this allows for a test of curvature. Note that this test of curvature does not tell whether the curvature is due to factor 1, factor 2, ..., or factor "k". It's typical to include at least 3 or 4 center points to detect curvature with power similar to the factorial effect tests. Determination of stability over time - Assuming the experimental runs are not run simultaneously (for instance, 8 corn fields or 8 flasks at the same time), there could be a time drift or spike during the experimental runs. The center points can be dispersed evenly over the factorial runs to detect these situations. The center points could be plotted separately to check for trends. Even with 4 or 6 center points, this is still a very crude test for stability over time. Bottom line: the number of center points is a judgment call, based on your understanding of the process and the experimental objectives. It may be more important to replicate the entire factorial experiment, because you may need more power to detect main effects and interactions (especially if the changes that you want to see are small when compared to the experimental noise). Hope that is helpful. Howard Rauch

hlrauch · ‎11-18-2014

Thank you, Dan! That was a very informative answer. Howard

hlrauch · ‎11-13-2014

This is a general JMP scripting language question. I stumbled on a function called Platform() in the Scripting Index and in the Scripting Index. I continue to look for new/hidden capabilities in JSL, so I was wondering what this Platform function does. When calling a platform such as Bivariate, I would normally script it as: bivobj = datatable << Bivariate( Y, X ); It appears that this could also be scripted using the Platform function as bivobj = Platform( datatable, Bivariate( Y, X ) ); Is the Platform function just an equivalent command or does it provide some additional capabilities beyond the traditional way to call platforms/analyses? Thanks! Howard

hlrauch · ‎10-31-2014

Thanks Jeff. I just installed JMP 11.2.1, and it's working fine now. Howard

hlrauch · ‎10-24-2014

I would like to open a "control panel" window whenever a user opens a particular data table. I've written a script that creates a simple non-modal window; I named the script "On Open" and I placed the script in the left pane of the data table, so it runs automatically whenever the data table is opened. However, when the data table window opens, it remains in front of the control panel window. This is true even if I include the following statement at the end of the script: Window("Control Panel") << Bring Window to Front; . There is no problem if the data table is already open. The problem seems to occur because both windows are opening up at the same time. Any suggestions? Thanks! Howard

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