Formula Depot

Associated Constructors

Formula Depot

Syntax: Formula Depot

Description: A container for prediction models that supports model comparison, profiling, and scoring code generation. The Formula Depot is launched through the analyze menu, Publish commands in modeling platforms, Recode, and the Formula Editor.

fd1 = Formula Depot();
dt = Open( "$SAMPLE_DATA\Iris.jmp" );
model = dt << RunScript( "Nominal Logistic" );
model << Publish Probability Formulas;
fd_script = fd1 << Get Script;
Save Text File( "$TEMP\fd.jrp", Char( Name Expr( fd_script ) ) );
fd1 << Close Window;
Open( "$TEMP\fd.jrp" );
fd2 = Formula Depot[1];

Item Messages

Add Formula from Column

Syntax: Predictor = obj << Add Formula from Column( Table(name|reference), Columns(name|index|reference, ...), <Expand Intermediate Formulas(number)> )

Description: Add an existing prediction formula column from the given table to the Formula Depot

dt = Open( "$SAMPLE_DATA\Iris.jmp" );
model = dt << RunScript( "Nominal Logistic" );
fd = Formula Depot();
model << Save Probability Formula;
mp = fd << Add Formula From Column( Table( dt ), Columns( 11 ) ); // "Most Likely Species"
mp << Generate Python Code;

Copy Formulas as Functions

Syntax: obj << Copy Formulas as Functions( <Formulas(name|index|reference, ...)> )

Description: Copies the given models onto the clipboard as a scalar Function() statement.

JMP Version Added: 14

dt = Open( "$SAMPLE_DATA\Iris.jmp" );
model = dt << RunScript( "Nominal Logistic" );
fd = Formula Depot();
predictor = model << Publish Probability Formulas;
fd << Copy Formulas as Functions( Formulas( predictor ) );
Wait( 0 );
text = Get Clipboard();
Show( text );

Copy Formulas as Transforms

Syntax: obj << Copy Formulas as Transforms( <Table(name|reference)>, <Formulas(name|index|reference, ...)> )

Description: Copies the given models onto the clipboard within a Transform Column() statement.

dt = Open( "$SAMPLE_DATA\Iris.jmp" );
model = dt << RunScript( "Nominal Logistic" );
fd = Formula Depot();
model << Publish Probability Formulas;
fd << Copy Formulas as Transforms(
    // English: Formulas("Fit Nominal Logistic - Species")
    Formulas( 1 )
);
Wait( 0 );
text = Get Clipboard();
Show( text );

Copy Scripts

Syntax: obj << Copy Scripts( <Formulas(name|index|reference, ...)> )

Description: Copies the scripts for the given formulas stored in the Formula Depot to the clipboard.

dt = Open( "$SAMPLE_DATA\Iris.jmp" );
model = dt << RunScript( "Nominal Logistic" );
fd = Formula Depot();
predictor = model << Publish Probability Formulas;
fd << Copy Scripts( Formulas( predictor ) );
Wait( 0 );
text = Get Clipboard();
Show( text );

Generate C Code

Syntax: obj << Generate C Code( <Formulas(name|index|reference, ...)>, <No Editor> )

Description: Generates C code for the given models stored in the Formula Depot. Output goes to an editor window or to a string variable if the 'No Editor' argument is given.

fd = Formula Depot();
dt = Open( "$SAMPLE_DATA/Iris.jmp" );
md = dt << Run Script( "Nominal Logistic" );
predictor = md << Publish Probability Formulas;
// Save code to string 
c_code = fd << Generate C Code( Formulas( predictor ), No Editor );
// shortcut using predictor reference
// c_code = predictor << Generate C Code(No Editor);
Save Text File( "$TEMP\logist.c", c_code );
// Open code in editor window
fd << Generate C Code( Formulas( predictor ) );

Generate JavaScript Code

Syntax: obj << Generate JavaScript Code( <Formulas(name|index|reference, ...)>, <No Editor> )

Description: Generates JavaScript code for the given models stored in the Formula Depot. Output goes to an editor window or to a string variable if the 'No Editor' argument is given.

fd = Formula Depot();
dt = Open( "$SAMPLE_DATA/Iris.jmp" );
md = dt << Run Script( "Nominal Logistic" );
predictor = md << Publish Probability Formulas;
// Save code to string 
js_code = fd << Generate JavaScript Code( Formulas( predictor ), No Editor );
// shortcut using predictor reference
// js_code = predictor << Generate JavaScript Code(No Editor);
Save Text File( "$TEMP\logist.js", js_code );
// Open code in editor window
fd << Generate JavaScript Code( Formulas( predictor ) );

Generate Python Code

Syntax: obj << Generate Python Code( <Formulas(name|index|reference, ...)>, <No Editor> )

Description: Generates Python code for the given models stored in the Formula Depot. Output goes to an editor window or to a string variable if the 'No Editor' argument is given.

fd = Formula Depot();
dt = Open( "$SAMPLE_DATA/Iris.jmp" );
md = dt << Run Script( "Nominal Logistic" );
predictor = md << Publish Probability Formulas;
// Save code to string 
py_code = fd << Generate Python Code( Formulas( predictor ), No Editor );
// shortcut using predictor reference
// py_code = predictor << Generate Python Code(No Editor);
Save Text File( "$TEMP\logist.py", py_code );
// Open code in editor window
fd << Generate Python Code( Formulas( predictor ) );

Generate SAS Code

Syntax: obj << Generate SAS Code( <Formulas(name|index|reference, ...)>, <No Editor> )

Description: Generates SAS (DS2) code for the given models stored in the Formula Depot. Output goes to an editor window or to a string variable if the 'No Editor' argument is given.

fd = Formula Depot();
dt = Open( "$SAMPLE_DATA/Iris.jmp" );
md = dt << Run Script( "Nominal Logistic" );
predictor = md << Publish Probability Formulas;
// Save code to string 
sas_code = fd << Generate SAS Code( Formulas( predictor ), No Editor );
// shortcut using predictor reference
// sas_code = predictor << Generate SAS Code(No Editor);
Save Text File( "$TEMP\logist.sas", sas_code );
// Open code in editor window
fd << Generate SAS Code( Formulas( predictor ) );

Generate SQL Code

Syntax: obj << Generate SQL Code( <Formulas(name|index|reference, ...)>, <No Editor>, <QUOTE_STYLE> )

Description: Generates SQL code (column definitions suitable for use in an SQL Select statement) for the given models stored in the Formula Depot. Output goes to an editor window or to a string variable if the "No Editor" argument is given. QUOTE_STYLE is a string denoting one of the SQL databases supported by JMP (MySQL, Impala, Hive, and so on) or a SQL quoting type ("Underline", "Backquote", "Bracket" or "Doublequote").

fd = Formula Depot();
dt = Open( "$SAMPLE_DATA/Liver Cancer.jmp" );
md = dt << Run Script( "Elastic Net Poisson, BIC" );
mp_obs = md << xpath( "//OutlineBox" );
scriptables = Filter Each( {ob}, mp_obs << Get Scriptable Object(), !Is Empty( ob ) );
mp = scriptables[2];
predictor = mp << Publish Prediction Formula;
// Save code to string 
sql_code = fd << Generate SQL Code( Formulas( 1 ), No Editor );
// shortcut using predictor reference
// sql_code = predictor << Generate SQL Code(No Editor);
Save Text File( "$TEMP\genreg.sql", sql_code );
// Open code in editor window
fd << Generate SQL Code( Formulas( predictor ), "MySQL" );

Model Comparison

Syntax: obj << Model Comparison( <Table(name|reference)>, <Formulas(name|index|reference, ...)> )

Description: Compares the given models stored in the Formula Depot using the model comparison utility, based on the contents of the given table.

fd = Formula Depot();
dt = Open( "$SAMPLE_DATA/Iris.jmp" );
nl_md = dt << Run Script( "Nominal Logistic" );
nl_mp = nl_md << Publish Probability Formulas;
nn_md = Neural(
    Y( :Species ),
    X( :Sepal length, :Sepal width, :Petal length, :Petal width ),
    Informative Missing( 0 ),
    Validation Method( "Holdback", 0.3333 ),
    Fit( NTanH( 3 ) )
);
nn_mp = nn_md << Publish Prediction Formula;
mc_plat = fd << ModelComparison( Formulas( 1, 2 ) );
// Other options:
// mds = {"Fit Nominal Logistic - Species", "Neural - Species"};
// fd << ModelComparison( Formulas( mds ) );
// fd << ModelComparison( Formulas( 1 ), Formulas( 2 ) );
// fd << ModelComparison; // all models

Profiler

Syntax: obj << Profiler( <Table(name|reference)>, <Formulas(name|index|reference, ...)> )

Description: Profiles the given models stored in the Formula Depot using the Profiler utility, based on the contents of the given table.

fd = Formula Depot();
dt = Open( "$SAMPLE_DATA/Iris.jmp" );
nl_md = dt << Run Script( "Nominal Logistic" );
nl_mp = nl_md << Publish Probability Formulas;
nn_md = Neural(
    Y( :Species ),
    X( :Sepal length, :Sepal width, :Petal length, :Petal width ),
    Informative Missing( 0 ),
    Validation Method( "Holdback", 0.3333 ),
    Fit( NTanH( 3 ) )
);
nn_mp = nn_md << Publish Prediction Formula;
fd << Profiler( Formulas( nl_mp, nn_mp ) );

Remove Model Comparison

Syntax: obj << Remove Model Comparison

Description: Removes all Model Comparison reports from the current Formula Depot.

fd = Formula Depot();
dt = Open( "$SAMPLE_DATA/Iris.jmp" );
nl_md = dt << Run Script( "Nominal Logistic" );
nl_md << Publish Probability Formulas;
fd << Model Comparison();
fd << Remove Model Comparison();

Remove Profiler

Syntax: obj << Remove Profiler

Description: Removes all Profilers from the current Formula Depot.

fd = Formula Depot();
dt = Open( "$SAMPLE_DATA/Iris.jmp" );
nl_md = dt << Run Script( "Nominal Logistic" );
nl_md << Publish Probability Formulas;
fd << Profiler();
fd << Remove Profiler();

Rename Formula Depot

Syntax: obj << Rename Formula Depot( text )

fd = Formula Depot();
fd << Rename Formula Depot( "New Name" );

Run Scripts

Syntax: obj << Run Scripts( <Table(name|reference)>, <Formulas(name|index|reference, ...)> )

Description: Saves the given models to the current or given JMP data table as one or more formula columns.

// Create a Formula Depot to store the model
dt1 = Open( "$SAMPLE_DATA\Iris.jmp" );
model = dt1 << RunScript( "Nominal Logistic" );
fd1 = Formula Depot();
model << Publish Probability Formulas;
fd_script = fd1 << Get Script;
Save Text File( "$TEMP\fd.jrp", Char( Name Expr( fd_script ) ) );
// Clean-up
Close( dt1, NoSave );
fd1 << Close Window;
// Read FD from disk
Open( "$TEMP\fd.jrp" );
fd2 = Formula Depot[1];
// Create columns from stored model; usually this is a new table with a compatible schema
dt2 = Open( "$SAMPLE_DATA\Iris.jmp" );
fd2 << Run Scripts( Table( dt2 ), Formulas( 1 ) );

Show Scripts

Syntax: obj << Show Scripts( <Formulas(name|index|reference, ...)> )

Description: Opens a new Formula Window (or appends to an open Formula Window) that contains scripts for the given formulas stored in the Formula Depot.

dt = Open( "$SAMPLE_DATA\Iris.jmp" );
model = dt << RunScript( "Nominal Logistic" );
fd = Formula Depot();
model << Publish Probability Formulas;
fd << Show Scripts( Formulas( 1 ) );

Shared Item Messages

Action

Syntax: obj << Action

Description: All-purpose trapdoor within a platform to insert expressions to evaluate. Temporarily sets the DisplayBox and DataTable contexts to the Platform.

dt = Open( "$SAMPLE_DATA/Big Class.jmp" );
dt << Bivariate(
    Y( :height ),
    X( :weight ),
    Action( Distribution( Y( :height, :weight ), Histograms Only ) )
);

Apply Preset

Syntax: Apply Preset( preset ); Apply Preset( source, label, <Folder( folder {, folder2, ...} )> )

Description: Apply a previously created preset to the object, updating the options and customizations to match the saved settings.

JMP Version Added: 18

Anonymous preset

dt = Open( "$SAMPLE_DATA/Big Class.jmp" );
obj = dt << Oneway( Y( :height ), X( :sex ), t Test( 1 ) );
preset = obj << New Preset();
dt2 = Open( "$SAMPLE_DATA/Dogs.jmp" );
obj2 = dt2 << Oneway( Y( :LogHist0 ), X( :drug ) );
Wait( 1 );
obj2 << Apply Preset( preset );

Search by name

dt = Open( "$SAMPLE_DATA/Big Class.jmp" );
obj = dt << Oneway( Y( :height ), X( :sex ) );
Wait( 1 );
obj << Apply Preset( "Sample Presets", "Compare Distributions" );

Search within folder(s)

dt = Open( "$SAMPLE_DATA/Big Class.jmp" );
obj = dt << Oneway( Y( :height ), X( :sex ) );
Wait( 1 );
obj << Apply Preset( "Sample Presets", "t-Tests", Folder( "Compare Means" ) );

Copy Script

Syntax: obj << Copy Script

Description: Create a JSL script to produce this analysis, and put it on the clipboard.

fd1 = Formula Depot();
dt = Open( "$SAMPLE_DATA\Iris.jmp" );
model = dt << RunScript( "Nominal Logistic" );
model << Publish Probability Formulas;
fd_script = fd1 << Get Script;
Save Text File( "$TEMP\fd.jrp", Char( Name Expr( fd_script ) ) );
fd1 << Close Window;
Open( "$TEMP\fd.jrp" );
fd2 = Formula Depot[1];
obj << Copy Script;

Get By Levels

Syntax: obj << Get By Levels

Description: Returns an associative array mapping the by group columns to their values.

JMP Version Added: 18

dt = Open( "$SAMPLE_DATA/Big Class.jmp" );
biv = dt << Bivariate( X( :height ), Y( :weight ), By( :sex ) );
biv << Get By Levels;

Get Container

Syntax: obj << Get Container

Description: Returns a reference to the container box that holds the content for the object.

General

fd1 = Formula Depot();
dt = Open( "$SAMPLE_DATA\Iris.jmp" );
model = dt << RunScript( "Nominal Logistic" );
model << Publish Probability Formulas;
fd_script = fd1 << Get Script;
Save Text File( "$TEMP\fd.jrp", Char( Name Expr( fd_script ) ) );
fd1 << Close Window;
Open( "$TEMP\fd.jrp" );
fd2 = Formula Depot[1];
t = obj << Get Container;
Show( (t << XPath( "//OutlineBox" )) << Get Title );

Platform with Filter

dt = Open( "$SAMPLE_DATA/Big Class.jmp" );
gb = Graph Builder(
    Show Control Panel( 0 ),
    Variables( X( :height ), Y( :weight ) ),
    Elements( Points( X, Y, Legend( 1 ) ), Smoother( X, Y, Legend( 2 ) ) ),
    Local Data Filter(
        Add Filter(
            columns( :age, :sex, :height ),
            Where( :age == {12, 13, 14} ),
            Where( :sex == "F" ),
            Where( :height >= 55 ),
            Display( :age, N Items( 6 ) )
        )
    )
);
New Window( "platform boxes",
    H List Box(
        Outline Box( "Report(platform)", Report( gb ) << Get Picture ),
        Outline Box( "platform << Get Container", (gb << Get Container) << Get Picture )
    )
);

Get Data Table

Syntax: obj << Get Data Table

Description: Returns a reference to the data table.

fd1 = Formula Depot();
dt = Open( "$SAMPLE_DATA\Iris.jmp" );
model = dt << RunScript( "Nominal Logistic" );
model << Publish Probability Formulas;
fd_script = fd1 << Get Script;
Save Text File( "$TEMP\fd.jrp", Char( Name Expr( fd_script ) ) );
fd1 << Close Window;
Open( "$TEMP\fd.jrp" );
fd2 = Formula Depot[1];
t = obj << Get Datatable;
Show( N Rows( t ) );

Get Script

Syntax: obj << Get Script

Description: Creates a script (JSL) to produce this analysis and returns it as an expression.

fd1 = Formula Depot();
dt = Open( "$SAMPLE_DATA\Iris.jmp" );
model = dt << RunScript( "Nominal Logistic" );
model << Publish Probability Formulas;
fd_script = fd1 << Get Script;
Save Text File( "$TEMP\fd.jrp", Char( Name Expr( fd_script ) ) );
fd1 << Close Window;
Open( "$TEMP\fd.jrp" );
fd2 = Formula Depot[1];
t = obj << Get Script;
Show( t );

Get Script With Data Table

Syntax: obj << Get Script With Data Table

Description: Creates a script(JSL) to produce this analysis specifically referencing this data table and returns it as an expression.

fd1 = Formula Depot();
dt = Open( "$SAMPLE_DATA\Iris.jmp" );
model = dt << RunScript( "Nominal Logistic" );
model << Publish Probability Formulas;
fd_script = fd1 << Get Script;
Save Text File( "$TEMP\fd.jrp", Char( Name Expr( fd_script ) ) );
fd1 << Close Window;
Open( "$TEMP\fd.jrp" );
fd2 = Formula Depot[1];
t = obj << Get Script With Data Table;
Show( t );

Get Timing

Syntax: obj << Get Timing

Description: Times the platform launch.

fd1 = Formula Depot();
dt = Open( "$SAMPLE_DATA\Iris.jmp" );
model = dt << RunScript( "Nominal Logistic" );
model << Publish Probability Formulas;
fd_script = fd1 << Get Script;
Save Text File( "$TEMP\fd.jrp", Char( Name Expr( fd_script ) ) );
fd1 << Close Window;
Open( "$TEMP\fd.jrp" );
fd2 = Formula Depot[1];
t = obj << Get Timing;
Show( t );

Get Web Support

Syntax: obj << Get Web Support

Description: Return a number indicating the level of Interactive HTML support for the display object. 1 means some or all elements are supported. 0 means no support.

dt = Open( "$SAMPLE_DATA/Big Class.jmp" );
obj = dt << Bivariate( Y( :Weight ), X( :Height ) );
s = obj << Get Web Support();
Show( s );

Get Where Expr

Syntax: obj << Get Where Expr

Description: Returns the Where expression for the data subset, if the platform was launched with By() or Where(). Otherwise, returns Empty()

JMP Version Added: 18

dt = Open( "$SAMPLE_DATA/Big Class.jmp" );
biv = dt << Bivariate( X( :height ), Y( :weight ), By( :sex ) );
biv2 = dt << Bivariate( X( :height ), Y( :weight ), Where( :age < 14 & :height > 60 ) );
Show( biv[1] << Get Where Expr, biv2 << Get Where Expr );

Ignore Platform Preferences

Syntax: Ignore Platform Preferences( state=0|1 )

Description: Ignores the current settings of the platform's preferences. The message is ignored when sent to the platform after creation.

dt = Open( "$SAMPLE_DATA/Big Class.jmp" );
dt << Bivariate(
    Ignore Platform Preferences( 1 ),
    Y( :height ),
    X( :weight ),
    Action( Distribution( Y( :height, :weight ), Histograms Only ) )
);

New JSL Preset

Syntax: New JSL Preset( preset )

Description: For testing purposes, create a preset directly from a JSL expression. Like <<New Preset, it will return a Platform Preset that can be applied using <<Apply Preset. But it allows you to specify the full JSL expression for the preset to test outside of normal operation. You will get an Assert on apply if the platform names do not match, but that is expected.

JMP Version Added: 18

dt = Open( "$SAMPLE_DATA/Big Class.jmp" );
obj = dt << Oneway( Y( :Height ), X( :Age ) );
preset = obj << New JSL Preset( Oneway( Y( :A ), X( :B ), Each Pair( 1 ) ) );
Wait( 1 );
obj << Apply Preset( preset );

New Preset

Syntax: obj = New Preset()

Description: Create an anonymous preset representing the options and customizations applied to the object. This object can be passed to Apply Preset to copy the settings to another object of the same type.

JMP Version Added: 18

dt = Open( "$SAMPLE_DATA/Big Class.jmp" );
obj = dt << Oneway( Y( :height ), X( :sex ), t Test( 1 ) );
preset = obj << New Preset();

Render Preset

Syntax: Render Preset( preset )

Description: For testing purposes, show the platform rerun script that would be used when applying a platform preset to the platform in the log. No changes are made to the platform.

JMP Version Added: 18

dt = Open( "$SAMPLE_DATA/Big Class.jmp" );
obj = dt << Oneway( Y( :Height ), X( :Age ) );
obj << Render Preset( Expr( Oneway( Y( :A ), X( :B ), Each Pair( 1 ) ) ) );

Report

Syntax: obj << Report;Report( obj )

Description: Returns a reference to the report object.

fd1 = Formula Depot();
dt = Open( "$SAMPLE_DATA\Iris.jmp" );
model = dt << RunScript( "Nominal Logistic" );
model << Publish Probability Formulas;
fd_script = fd1 << Get Script;
Save Text File( "$TEMP\fd.jrp", Char( Name Expr( fd_script ) ) );
fd1 << Close Window;
Open( "$TEMP\fd.jrp" );
fd2 = Formula Depot[1];
r = obj << Report;
t = r[Outline Box( 1 )] << Get Title;
Show( t );

Save Script for All Objects

Syntax: obj << Save Script for All Objects

Description: Creates a script for all report objects in the window and appends it to the current Script window. This option is useful when you have multiple reports in the window.

fd1 = Formula Depot();
dt = Open( "$SAMPLE_DATA\Iris.jmp" );
model = dt << RunScript( "Nominal Logistic" );
model << Publish Probability Formulas;
fd_script = fd1 << Get Script;
Save Text File( "$TEMP\fd.jrp", Char( Name Expr( fd_script ) ) );
fd1 << Close Window;
Open( "$TEMP\fd.jrp" );
fd2 = Formula Depot[1];
obj << Save Script for All Objects;

Save Script for All Objects To Data Table

Syntax: obj << Save Script for All Objects To Data Table( <name> )

Description: Saves a script for all report objects to the current data table. This option is useful when you have multiple reports in the window. The script is named after the first platform unless you specify the script name in quotes.

Example 1

fd1 = Formula Depot();
dt = Open( "$SAMPLE_DATA\Iris.jmp" );
dt << New Column( "_bycol",
    Character,
    Nominal,
    set values( Repeat( {"A", "B"}, N Rows( dt ) )[1 :: N Rows( dt )] )
);
model = dt << RunScript( "Nominal Logistic" );
model << Publish Probability Formulas;
fd_script = fd1 << Get Script;
Save Text File( "$TEMP\fd.jrp", Char( Name Expr( fd_script ) ), By( _bycol ) );
fd1 << Close Window;
Open( "$TEMP\fd.jrp" );
fd2 = Formula Depot[1];
obj[1] << Save Script for All Objects To Data Table;

Example 2

fd1 = Formula Depot();
dt = Open( "$SAMPLE_DATA\Iris.jmp" );
dt << New Column( "_bycol",
    Character,
    Nominal,
    set values( Repeat( {"A", "B"}, N Rows( dt ) )[1 :: N Rows( dt )] )
);
model = dt << RunScript( "Nominal Logistic" );
model << Publish Probability Formulas;
fd_script = fd1 << Get Script;
Save Text File( "$TEMP\fd.jrp", Char( Name Expr( fd_script ) ), By( _bycol ) );
fd1 << Close Window;
Open( "$TEMP\fd.jrp" );
fd2 = Formula Depot[1];
obj[1] << Save Script for All Objects To Data Table( "My Script" );

Save Script to Data Table

Syntax: Save Script to Data Table( <name>, < <<Prompt(0|1)>, < <<Replace(0|1)> );

Description: Create a JSL script to produce this analysis, and save it as a table property in the data table.

fd1 = Formula Depot();
dt = Open( "$SAMPLE_DATA\Iris.jmp" );
model = dt << RunScript( "Nominal Logistic" );
model << Publish Probability Formulas;
fd_script = fd1 << Get Script;
Save Text File( "$TEMP\fd.jrp", Char( Name Expr( fd_script ) ) );
fd1 << Close Window;
Open( "$TEMP\fd.jrp" );
fd2 = Formula Depot[1];
obj << Save Script to Data Table( "My Analysis", <<Prompt( 0 ), <<Replace( 0 ) );

Save Script to Journal

Syntax: obj << Save Script to Journal

Description: Create a JSL script to produce this analysis, and add a Button to the journal containing this script.

fd1 = Formula Depot();
dt = Open( "$SAMPLE_DATA\Iris.jmp" );
model = dt << RunScript( "Nominal Logistic" );
model << Publish Probability Formulas;
fd_script = fd1 << Get Script;
Save Text File( "$TEMP\fd.jrp", Char( Name Expr( fd_script ) ) );
fd1 << Close Window;
Open( "$TEMP\fd.jrp" );
fd2 = Formula Depot[1];
obj << Save Script to Journal;

Save Script to Report

Syntax: obj << Save Script to Report

Description: Create a JSL script to produce this analysis, and show it in the report itself. Useful to preserve a printed record of what was done.

fd1 = Formula Depot();
dt = Open( "$SAMPLE_DATA\Iris.jmp" );
model = dt << RunScript( "Nominal Logistic" );
model << Publish Probability Formulas;
fd_script = fd1 << Get Script;
Save Text File( "$TEMP\fd.jrp", Char( Name Expr( fd_script ) ) );
fd1 << Close Window;
Open( "$TEMP\fd.jrp" );
fd2 = Formula Depot[1];
obj << Save Script to Report;

Save Script to Script Window

Syntax: obj << Save Script to Script Window

Description: Create a JSL script to produce this analysis, and append it to the current Script text window.

fd1 = Formula Depot();
dt = Open( "$SAMPLE_DATA\Iris.jmp" );
model = dt << RunScript( "Nominal Logistic" );
model << Publish Probability Formulas;
fd_script = fd1 << Get Script;
Save Text File( "$TEMP\fd.jrp", Char( Name Expr( fd_script ) ) );
fd1 << Close Window;
Open( "$TEMP\fd.jrp" );
fd2 = Formula Depot[1];
obj << Save Script to Script Window;

SendToByGroup

Syntax: SendToByGroup( {":Column == level"}, command );

Description: Sends platform commands or display customization commands to each level of a by-group.

dt = Open( "$SAMPLE_DATA/Big Class.jmp" );
dt << Distribution(
    By( :Sex ),
    SendToByGroup(
        {:sex == "F"},
        Continuous Distribution( Column( :weight ), Normal Quantile Plot( 1 ) )
    ),
    SendToByGroup( {:sex == "M"}, Continuous Distribution( Column( :weight ) ) )
);

SendToEmbeddedScriptable

Syntax: SendToEmbeddedScriptable( Dispatch( "Outline name", "Element name", command );

Description: SendToEmbeddedScriptable restores settings of embedded scriptable objects.

dt = Open( "$SAMPLE_DATA/Reliability/Fan.jmp" );
dt << Life Distribution(
    Y( :Time ),
    Censor( :Censor ),
    Censor Code( 1 ),
    <<Fit Weibull,
    SendToEmbeddedScriptable(
        Dispatch(
            {"Statistics", "Parametric Estimate - Weibull", "Profilers", "Density Profiler"},
            {1, Confidence Intervals( 0 ), Term Value( Time( 6000, Lock( 0 ), Show( 1 ) ) )}
        )
    )
);

SendToReport

Syntax: SendToReport( Dispatch( "Outline name", "Element name", Element type, command );

Description: Send To Report is used in tandem with the Dispatch command to customize the appearance of a report.

dt = Open( "$SAMPLE_DATA/Big Class.jmp" );
dt << Distribution(
    Nominal Distribution( Column( :age ) ),
    Continuous Distribution( Column( :weight ) ),
    SendToReport( Dispatch( "age", "Distrib Nom Hist", FrameBox, {Frame Size( 178, 318 )} ) )
);

Title

Syntax: obj << Title( "new title" )

Description: Sets the title of the platform.

fd1 = Formula Depot();
dt = Open( "$SAMPLE_DATA\Iris.jmp" );
model = dt << RunScript( "Nominal Logistic" );
model << Publish Probability Formulas;
fd_script = fd1 << Get Script;
Save Text File( "$TEMP\fd.jrp", Char( Name Expr( fd_script ) ) );
fd1 << Close Window;
Open( "$TEMP\fd.jrp" );
fd2 = Formula Depot[1];
obj << Title( "My Platform" );

Top Report

Syntax: obj << Top Report

Description: Returns a reference to the root node in the report.

fd1 = Formula Depot();
dt = Open( "$SAMPLE_DATA\Iris.jmp" );
model = dt << RunScript( "Nominal Logistic" );
model << Publish Probability Formulas;
fd_script = fd1 << Get Script;
Save Text File( "$TEMP\fd.jrp", Char( Name Expr( fd_script ) ) );
fd1 << Close Window;
Open( "$TEMP\fd.jrp" );
fd2 = Formula Depot[1];
r = obj << Top Report;
t = r[Outline Box( 1 )] << Get Title;
Show( t );

View Web XML

Syntax: obj << View Web XML

Description: Returns the XML code that is used to create the interactive HTML report.

dt = Open( "$SAMPLE_DATA/Big Class.jmp" );
obj = dt << Bivariate( Y( :Weight ), X( :Height ) );
xml = obj << View Web XML;