Normal Mixtures

Associated Constructors

Normal Mixtures

Syntax: Normal Mixtures( Y( column(s) ), Number of Clusters( number ) )

Description: Clusters rows based on numeric variables when your data come from a mixture of overlapping multivariate normal distributions. You must specify the number of clusters in advance.

dt = Open( "$SAMPLE_DATA/Iris.jmp" );
obj = dt << Normal Mixtures(
    Y( :Sepal length, :Sepal width, :Petal length, :Petal width ),
    Number of Clusters( 3 )
);
obj << Go;

Columns

By

Syntax: obj = Normal Mixtures(...<By( column(s) )>...)

JMP Version Added: 14

dt = Open( "$SAMPLE_DATA/Iris.jmp" );
dt << New Column( "_bycol",
    Character,
    Nominal,
    set values( Repeat( {"A", "B"}, N Rows( dt ) )[1 :: N Rows( dt )] )
);
obj = dt << Normal Mixtures(
    Y( :Sepal length, :Sepal width, :Petal length, :Petal width ),
    Number of Clusters( 3 ),
    By( _bycol )
);
obj << Go;

Freq

Syntax: obj = Normal Mixtures(...<Freq( column )>...)

JMP Version Added: 14

K Means Example

dt = Open( "$SAMPLE_DATA/Quality Control/Failure3Freq.jmp" );
obj = K Means Cluster(
    Y(
        :contamination, :corrosion, :doping, :metallization, :miscellaneous, :oxide defect,
        :silicon defect
    ),
    Freq( :SampleSize ),
    Number of Clusters( 2 ),
    Go
);

Normal Mixtures Example

dt = Open( "$SAMPLE_DATA/Quality Control/Failure3Freq.jmp" );
obj = Normal Mixtures(
    Y(
        :contamination, :corrosion, :doping, :metallization, :miscellaneous, :oxide defect,
        :silicon defect
    ),
    Freq( :SampleSize ),
    Number of Clusters( 2 ),
    Go
);

Weight

Syntax: obj = Normal Mixtures(...<Weight( column )>...)

JMP Version Added: 14

K Means Example

dt = Open( "$SAMPLE_DATA/Quality Control/Failure3Freq.jmp" );
obj = K Means Cluster(
    Y(
        :contamination, :corrosion, :doping, :metallization, :miscellaneous, :oxide defect,
        :silicon defect
    ),
    Weight( :SampleSize ),
    Number of Clusters( 2 ),
    Go
);

Normal Mixtures Example

dt = Open( "$SAMPLE_DATA/Quality Control/Failure3Freq.jmp" );
obj = Normal Mixtures(
    Y(
        :contamination, :corrosion, :doping, :metallization, :miscellaneous, :oxide defect,
        :silicon defect
    ),
    Weight( :SampleSize ),
    Number of Clusters( 2 ),
    Go
);

Y

Syntax: obj = Normal Mixtures(...Y( column(s) )...)

JMP Version Added: 14

dt = Open( "$SAMPLE_DATA/Iris.jmp" );
obj = Normal Mixtures(
    Y( :Sepal length, :Sepal width, :Petal length, :Petal width ),
    Number of Clusters( 3 ),
    Go
);

Item Messages

Diagonal Variance

Syntax: obj << Diagonal Variance( state=0|1 )

Description: Assumes the covariances are zero and uses only the diagonal of the variance-covariance matrix for Normal Mixtures.

JMP Version Added: 14

dt = Open( "$SAMPLE_DATA/Iris.jmp" );
obj = dt << Normal Mixtures( Y( :Sepal length, :Sepal width, :Petal length, :Petal width ) );
obj << Diagonal Variance( 1 );
obj << Go;

Go

Syntax: obj << Go

Description: Launches the platform by completing the iterations.

JMP Version Added: 14

K Means Example

dt = Open( "$SAMPLE_DATA/Iris.jmp" );
obj = K Means Cluster(
    Y( :Sepal length, :Sepal width, :Petal length, :Petal width ),
    Number of Clusters( 3 )
);
obj << Go;

Normal Mixtures Example

dt = Open( "$SAMPLE_DATA/Iris.jmp" );
obj = Normal Mixtures(
    Y( :Sepal length, :Sepal width, :Petal length, :Petal width ),
    Number of Clusters( 3 )
);
obj << Go;

Mixtures MaxIter

Syntax: obj << Mixtures MaxIter( number )

Description: Sets the maximum number of iterations for Normal Mixtures. The default is 300.

JMP Version Added: 14

dt = Open( "$SAMPLE_DATA/Iris.jmp" );
obj = dt << Normal Mixtures( Y( :Sepal length, :Sepal width, :Petal length, :Petal width ) );
obj << Mixtures MaxIter( 100 );
obj << Go;

Mixtures N Starts

Syntax: obj << Mixtures N Starts( number )

Description: Sets the number of times Normal Mixtures starts over in forming clusters. The default is 30. This is referred to as Tours in the Advanced Controls report.

JMP Version Added: 14

dt = Open( "$SAMPLE_DATA/Iris.jmp" );
obj = dt << Normal Mixtures( Y( :Sepal length, :Sepal width, :Petal length, :Petal width ) );
obj << Mixtures N Starts( 20 );
obj << Go;

Mixtures Tolerance

Syntax: obj << Mixtures Tolerance( number )

Description: Sets the convergence criterion for Normal Mixtures. The default is 1e-8. This is referred to as Convergence Criterion in the Advanced Controls report.

JMP Version Added: 14

dt = Open( "$SAMPLE_DATA/Iris.jmp" );
obj = dt << Normal Mixtures( Y( :Sepal length, :Sepal width, :Petal length, :Petal width ) );
obj << Mixtures Tolerance( 1e-7 );
obj << Go;

Number of Clusters

Syntax: obj << Number of Clusters( number )

Description: Changes the number of clusters.

JMP Version Added: 14

K Means Example

dt = Open( "$SAMPLE_DATA/Iris.jmp" );
obj = K Means Cluster(
    Y( :Sepal length, :Sepal width, :Petal length, :Petal width ),
    Number of Clusters( 3 ),
    Go
);
Wait( 1 );
obj << Number of Clusters( 5 );
obj << Go;

Normal Mixtures Example

dt = Open( "$SAMPLE_DATA/Iris.jmp" );
obj = Normal Mixtures(
    Y( :Sepal length, :Sepal width, :Petal length, :Petal width ),
    Number of Clusters( 3 ),
    Go
);
Wait( 1 );
obj << Number of Clusters( 5 );
obj << Go;

Outlier Cluster

Syntax: obj << Outlier Cluster( state=0|1 )

Description: Provides an extra cluster with uniform distribution to collect outliers. This cluster is designated Cluster 0.

JMP Version Added: 14

dt = Open( "$SAMPLE_DATA/Iris.jmp" );
obj = dt << Normal Mixtures( Y( :Sepal length, :Sepal width, :Petal length, :Petal width ) );
obj << Outlier Cluster( 1 );
obj << Go;

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" ) );

Automatic Recalc

Syntax: obj << Automatic Recalc( state=0|1 )

Description: Redoes the analysis automatically for exclude and data changes. If the Automatic Recalc option is turned on, you should consider using Wait(0) commands to ensure that the exclude and data changes take effect before the recalculation.

dt = Open( "$SAMPLE_DATA/Iris.jmp" );
obj = dt << Normal Mixtures(
    Y( :Sepal length, :Sepal width, :Petal length, :Petal width ),
    Number of Clusters( 3 )
);
obj << Go;
obj << Automatic Recalc( 1 );
dt << Select Rows( 5 ) << Exclude( 1 );

Broadcast

Syntax: obj << Broadcast(message)

Description: Broadcasts a message to a platform. If return results from individual objects are tables, they are concatenated if possible, and the final format is identical to either the result from the Save Combined Table option in a Table Box or the result from the Concatenate option using a Source column. Other than those, results are stored in a list and returned.

JMP Version Added: 18

dt = Open( "$SAMPLE_DATA/Quality Control/Diameter.jmp" );
objs = Control Chart Builder(
    Variables( Subgroup( :DAY ), Y( :DIAMETER ) ),
    By( :OPERATOR )
);
objs[1] << Broadcast( Save Summaries );

Column Switcher

Syntax: obj << Column Switcher(column reference, {column reference, ...}, < Title(title) >, < Close Outline(0|1) >, < Retain Axis Settings(0|1) >, < Layout(0|1) >)

Description: Adds a control panel for changing the platform's variables

dt = Open( "$SAMPLE_DATA/Car Poll.jmp" );
obj = dt << Contingency( Y( :size ), X( :marital status ) );
ColumnSwitcherObject = obj << Column Switcher(
    :marital status,
    {:sex, :country, :marital status}
);

Copy ByGroup Script

Syntax: obj << Copy ByGroup Script

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

dt = Open( "$SAMPLE_DATA/Iris.jmp" );
dt << New Column( "_bycol",
    Character,
    Nominal,
    set values( Repeat( {"A", "B"}, N Rows( dt ) )[1 :: N Rows( dt )] )
);
obj = dt << Normal Mixtures(
    Y( :Sepal length, :Sepal width, :Petal length, :Petal width ),
    Number of Clusters( 3 ),
    By( _bycol )
);
obj << Go;
obj[1] << Copy ByGroup Script;

Copy Script

Syntax: obj << Copy Script

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

dt = Open( "$SAMPLE_DATA/Iris.jmp" );
obj = dt << Normal Mixtures(
    Y( :Sepal length, :Sepal width, :Petal length, :Petal width ),
    Number of Clusters( 3 )
);
obj << Go;
obj << Copy Script;

Data Table Window

Syntax: obj << Data Table Window

Description: Move the data table window for this analysis to the front.

dt = Open( "$SAMPLE_DATA/Iris.jmp" );
obj = dt << Normal Mixtures(
    Y( :Sepal length, :Sepal width, :Petal length, :Petal width ),
    Number of Clusters( 3 )
);
obj << Go;
obj << Data Table Window;

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 ByGroup Script

Syntax: obj << Get ByGroup Script

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

dt = Open( "$SAMPLE_DATA/Iris.jmp" );
dt << New Column( "_bycol",
    Character,
    Nominal,
    set values( Repeat( {"A", "B"}, N Rows( dt ) )[1 :: N Rows( dt )] )
);
obj = dt << Normal Mixtures(
    Y( :Sepal length, :Sepal width, :Petal length, :Petal width ),
    Number of Clusters( 3 ),
    By( _bycol )
);
obj << Go;
t = obj[1] << Get ByGroup Script;
Show( t );

Get Container

Syntax: obj << Get Container

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

General

dt = Open( "$SAMPLE_DATA/Iris.jmp" );
obj = dt << Normal Mixtures(
    Y( :Sepal length, :Sepal width, :Petal length, :Petal width ),
    Number of Clusters( 3 )
);
obj << Go;
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.

dt = Open( "$SAMPLE_DATA/Iris.jmp" );
obj = dt << Normal Mixtures(
    Y( :Sepal length, :Sepal width, :Petal length, :Petal width ),
    Number of Clusters( 3 )
);
obj << Go;
t = obj << Get Datatable;
Show( N Rows( t ) );

Get Group Platform

Syntax: obj << Get Group Platform

Description: Return the Group Platform object if this platform is part of a Group. Otherwise, returns Empty().

dt = Open( "$SAMPLE_DATA/Big Class.jmp" );
biv = dt << Bivariate( Y( :weight ), X( :height ), By( :sex ) );
group = biv[1] << Get Group Platform;
Wait( 1 );
group << Layout( "Arrange in Tabs" );

Get Script

Syntax: obj << Get Script

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

dt = Open( "$SAMPLE_DATA/Iris.jmp" );
obj = dt << Normal Mixtures(
    Y( :Sepal length, :Sepal width, :Petal length, :Petal width ),
    Number of Clusters( 3 )
);
obj << Go;
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.

dt = Open( "$SAMPLE_DATA/Iris.jmp" );
obj = dt << Normal Mixtures(
    Y( :Sepal length, :Sepal width, :Petal length, :Petal width ),
    Number of Clusters( 3 )
);
obj << Go;
t = obj << Get Script With Data Table;
Show( t );

Get Timing

Syntax: obj << Get Timing

Description: Times the platform launch.

dt = Open( "$SAMPLE_DATA/Iris.jmp" );
obj = dt << Normal Mixtures(
    Y( :Sepal length, :Sepal width, :Petal length, :Petal width ),
    Number of Clusters( 3 )
);
obj << Go;
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 ) )
);

Local Data Filter

Syntax: obj << Local Data Filter

Description: To filter data to specific groups or ranges, but local to this platform

dt = Open( "$SAMPLE_DATA/Car Poll.jmp" );
dt << Distribution(
    Nominal Distribution( Column( :country ) ),
    Local Data Filter(
        Add Filter( columns( :sex ), Where( :sex == "Female" ) ),
        Mode( Show( 1 ), Include( 1 ) )
    )
);

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();

Paste Local Data Filter

Syntax: obj << Paste Local Data Filter

Description: Apply the local data filter from the clipboard to the current report.

dt = Open( "$SAMPLE_DATA/Cities.jmp" );
dist = Distribution( Continuous Distribution( Column( :POP ) ) );
filter = dist << Local Data Filter(
    Add Filter( columns( :Region ), Where( :Region == "MW" ) )
);
filter << Copy Local Data Filter;
dist2 = Distribution( Continuous Distribution( Column( :Lead ) ) );
Wait( 1 );
dist2 << Paste Local Data Filter;

Redo Analysis

Syntax: obj << Redo Analysis

Description: Rerun this same analysis in a new window. The analysis will be different if the data has changed.

dt = Open( "$SAMPLE_DATA/Iris.jmp" );
obj = dt << Normal Mixtures(
    Y( :Sepal length, :Sepal width, :Petal length, :Petal width ),
    Number of Clusters( 3 )
);
obj << Go;
obj << Redo Analysis;

Redo ByGroup Analysis

Syntax: obj << Redo ByGroup Analysis

Description: Rerun this same analysis in a new window. The analysis will be different if the data has changed.

dt = Open( "$SAMPLE_DATA/Iris.jmp" );
dt << New Column( "_bycol",
    Character,
    Nominal,
    set values( Repeat( {"A", "B"}, N Rows( dt ) )[1 :: N Rows( dt )] )
);
obj = dt << Normal Mixtures(
    Y( :Sepal length, :Sepal width, :Petal length, :Petal width ),
    Number of Clusters( 3 ),
    By( _bycol )
);
obj << Go;
obj[1] << Redo ByGroup Analysis;

Relaunch Analysis

Syntax: obj << Relaunch Analysis

Description: Opens the platform launch window and recalls the settings that were used to create the report.

dt = Open( "$SAMPLE_DATA/Iris.jmp" );
obj = dt << Normal Mixtures(
    Y( :Sepal length, :Sepal width, :Petal length, :Petal width ),
    Number of Clusters( 3 )
);
obj << Go;
obj << Relaunch Analysis;

Relaunch ByGroup

Syntax: obj << Relaunch ByGroup

Description: Opens the platform launch window and recalls the settings that were used to create the report.

dt = Open( "$SAMPLE_DATA/Iris.jmp" );
dt << New Column( "_bycol",
    Character,
    Nominal,
    set values( Repeat( {"A", "B"}, N Rows( dt ) )[1 :: N Rows( dt )] )
);
obj = dt << Normal Mixtures(
    Y( :Sepal length, :Sepal width, :Petal length, :Petal width ),
    Number of Clusters( 3 ),
    By( _bycol )
);
obj << Go;
obj[1] << Relaunch ByGroup;

Remove Column Switcher

Syntax: obj << Remove Column Switcher

Description: Removes the most recent Column Switcher that has been added to the platform.

dt = Open( "$SAMPLE_DATA/Car Poll.jmp" );
obj = dt << Contingency( Y( :size ), X( :marital status ) );
ColumnSwitcherObject = obj << Column Switcher(
    :marital status,
    {:sex, :country, :marital status}
);
Wait( 2 );
obj << Remove Column Switcher;

Remove Local Data Filter

Syntax: obj << Remove Local Data Filter

Description: If a local data filter has been created, this removes it and restores the platform to use all the data in the data table directly

dt = Open( "$SAMPLE_DATA/Car Poll.jmp" );
dist = dt << Distribution(
    Nominal Distribution( Column( :country ) ),
    Local Data Filter(
        Add Filter( columns( :sex ), Where( :sex == "Female" ) ),
        Mode( Show( 1 ), Include( 1 ) )
    )
);
Wait( 2 );
dist << remove local data filter;

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.

dt = Open( "$SAMPLE_DATA/Iris.jmp" );
obj = dt << Normal Mixtures(
    Y( :Sepal length, :Sepal width, :Petal length, :Petal width ),
    Number of Clusters( 3 )
);
obj << Go;
r = obj << Report;
t = r[Outline Box( 1 )] << Get Title;
Show( t );

Report View

Syntax: obj << Report View( "Full"|"Summary" )

Description: The report view determines the level of detail visible in a platform report. Full shows all of the detail, while Summary shows only select content, dependent on the platform. For customized behavior, display boxes support a <<Set Summary Behavior message.

dt = Open( "$SAMPLE_DATA/Iris.jmp" );
obj = dt << Normal Mixtures(
    Y( :Sepal length, :Sepal width, :Petal length, :Petal width ),
    Number of Clusters( 3 )
);
obj << Go;
obj << Report View( "Summary" );

Save ByGroup Script to Data Table

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

Description: Creates a JSL script to produce this analysis, and save it as a table property in the data table. You can specify a name for the script. The Append Suffix option appends a numeric suffix to the script name, which differentiates the script from an existing script with the same name. The Prompt option prompts the user to specify a script name. The Replace option replaces an existing script with the same name.

dt = Open( "$SAMPLE_DATA/Iris.jmp" );
dt << New Column( "_bycol",
    Character,
    Nominal,
    set values( Repeat( {"A", "B"}, N Rows( dt ) )[1 :: N Rows( dt )] )
);
obj = dt << Normal Mixtures(
    Y( :Sepal length, :Sepal width, :Petal length, :Petal width ),
    Number of Clusters( 3 ),
    By( _bycol )
);
obj << Go;
obj[1] << Save ByGroup Script to Data Table;

Save ByGroup Script to Journal

Syntax: obj << Save ByGroup Script to Journal

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

dt = Open( "$SAMPLE_DATA/Iris.jmp" );
dt << New Column( "_bycol",
    Character,
    Nominal,
    set values( Repeat( {"A", "B"}, N Rows( dt ) )[1 :: N Rows( dt )] )
);
obj = dt << Normal Mixtures(
    Y( :Sepal length, :Sepal width, :Petal length, :Petal width ),
    Number of Clusters( 3 ),
    By( _bycol )
);
obj << Go;
obj[1] << Save ByGroup Script to Journal;

Save ByGroup Script to Script Window

Syntax: obj << Save ByGroup Script to Script Window

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

dt = Open( "$SAMPLE_DATA/Iris.jmp" );
dt << New Column( "_bycol",
    Character,
    Nominal,
    set values( Repeat( {"A", "B"}, N Rows( dt ) )[1 :: N Rows( dt )] )
);
obj = dt << Normal Mixtures(
    Y( :Sepal length, :Sepal width, :Petal length, :Petal width ),
    Number of Clusters( 3 ),
    By( _bycol )
);
obj << Go;
obj[1] << Save ByGroup Script to Script Window;

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.

dt = Open( "$SAMPLE_DATA/Iris.jmp" );
obj = dt << Normal Mixtures(
    Y( :Sepal length, :Sepal width, :Petal length, :Petal width ),
    Number of Clusters( 3 )
);
obj << Go;
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

dt = Open( "$SAMPLE_DATA/Iris.jmp" );
dt << New Column( "_bycol",
    Character,
    Nominal,
    set values( Repeat( {"A", "B"}, N Rows( dt ) )[1 :: N Rows( dt )] )
);
obj = dt << Normal Mixtures(
    Y( :Sepal length, :Sepal width, :Petal length, :Petal width ),
    Number of Clusters( 3 ),
    By( _bycol )
);
obj << Go;
obj[1] << Save Script for All Objects To Data Table;

Example 2

dt = Open( "$SAMPLE_DATA/Iris.jmp" );
dt << New Column( "_bycol",
    Character,
    Nominal,
    set values( Repeat( {"A", "B"}, N Rows( dt ) )[1 :: N Rows( dt )] )
);
obj = dt << Normal Mixtures(
    Y( :Sepal length, :Sepal width, :Petal length, :Petal width ),
    Number of Clusters( 3 ),
    By( _bycol )
);
obj << Go;
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.

dt = Open( "$SAMPLE_DATA/Iris.jmp" );
obj = dt << Normal Mixtures(
    Y( :Sepal length, :Sepal width, :Petal length, :Petal width ),
    Number of Clusters( 3 )
);
obj << Go;
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.

dt = Open( "$SAMPLE_DATA/Iris.jmp" );
obj = dt << Normal Mixtures(
    Y( :Sepal length, :Sepal width, :Petal length, :Petal width ),
    Number of Clusters( 3 )
);
obj << Go;
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.

dt = Open( "$SAMPLE_DATA/Iris.jmp" );
obj = dt << Normal Mixtures(
    Y( :Sepal length, :Sepal width, :Petal length, :Petal width ),
    Number of Clusters( 3 )
);
obj << Go;
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.

dt = Open( "$SAMPLE_DATA/Iris.jmp" );
obj = dt << Normal Mixtures(
    Y( :Sepal length, :Sepal width, :Petal length, :Petal width ),
    Number of Clusters( 3 )
);
obj << Go;
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 )} ) )
);

Sync to Data Table Changes

Syntax: obj << Sync to Data Table Changes

Description: Sync with the exclude and data changes that have been made.

dt = Open( "$SAMPLE_DATA/Cities.jmp" );
dist = Distribution( Continuous Distribution( Column( :POP ) ) );
Wait( 1 );
dt << Delete Rows( dt << Get Rows Where( :Region == "W" ) );
dist << Sync To Data Table Changes;

Title

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

Description: Sets the title of the platform.

dt = Open( "$SAMPLE_DATA/Iris.jmp" );
obj = dt << Normal Mixtures(
    Y( :Sepal length, :Sepal width, :Petal length, :Petal width ),
    Number of Clusters( 3 )
);
obj << Go;
obj << Title( "My Platform" );

Top Report

Syntax: obj << Top Report

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

dt = Open( "$SAMPLE_DATA/Iris.jmp" );
obj = dt << Normal Mixtures(
    Y( :Sepal length, :Sepal width, :Petal length, :Petal width ),
    Number of Clusters( 3 )
);
obj << Go;
r = obj << Top Report;
t = r[Outline Box( 1 )] << Get Title;
Show( t );

Transform Column

Syntax: obj = <Platform>(... Transform Column(<name>, Formula(<expression>), [Random Seed(<n>)], [Numeric|Character|Expression], [Continuous|Nominal|Ordinal|Unstructured Text], [column properties]) ...)

Description: Create a transform column in the local context of an object, usually a platform. The transform column is active only for the lifetime of the platform.

JMP Version Added: 16

dt = Open( "$SAMPLE_DATA/Big Class.jmp" );
dt << Distribution(
    Transform Column( "age^2", Format( "Fixed Dec", 5, 0 ), Formula( :age * :age ) ),
    Continuous Distribution( Column( :"age^2"n ) )
);

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;

Window View

Syntax: obj = Normal Mixtures(...Window View( "Visible"|"Invisible"|"Private" )...)

Description: Set the type of the window to be created for the report. By default a Visible report window will be created. An Invisible window will not appear on screen, but is discoverable by functions such as Window(). A Private window responds to most window messages but is not discoverable and must be addressed through the report object

dt = Open( "$SAMPLE_DATA/Big Class.jmp" );
biv = dt << Bivariate( Window View( "Private" ), Y( :weight ), X( :height ), Fit Line );
eqn = Report( biv )["Linear Fit", Text Edit Box( 1 )] << Get Text;
biv << Close Window;
New Window( "Bivariate Equation",
    Outline Box( "Big Class Linear Fit", Text Box( eqn, <<Set Base Font( "Title" ) ) )
);

Normal Mixtures Fit

Item Messages

Biplot

Syntax: obj << Biplot( state=0|1 )

Description: Shows or hides a plot of the points and clusters in the first two principal components of the data.

JMP Version Added: 14

K Means Example

dt = Open( "$SAMPLE_DATA/Iris.jmp" );
obj = K Means Cluster(
    Y( :Sepal length, :Sepal width, :Petal length, :Petal width ),
    Number of Clusters( 3 ),
    Go
);
obj << Biplot( 1 );

Normal Mixtures Example

dt = Open( "$SAMPLE_DATA/Iris.jmp" );
obj = Normal Mixtures(
    Y( :Sepal length, :Sepal width, :Petal length, :Petal width ),
    Number of Clusters( 3 ),
    Go
);
obj << Biplot( 1 );

Biplot 3D

Syntax: obj << Biplot 3D( state=0|1 )

Description: Shows or hides a plot of the points and clusters in the first three principal components of the data.

JMP Version Added: 14

K Means Example

dt = Open( "$SAMPLE_DATA/Iris.jmp" );
obj = K Means Cluster(
    Y( :Sepal length, :Sepal width, :Petal length, :Petal width ),
    Number of Clusters( 3 ),
    Go
);
obj << Biplot 3D( 1 );

Normal Mixtures Example

dt = Open( "$SAMPLE_DATA/Iris.jmp" );
obj = Normal Mixtures(
    Y( :Sepal length, :Sepal width, :Petal length, :Petal width ),
    Number of Clusters( 3 ),
    Go
);
obj << Biplot 3D( 1 );

Biplot Contour Density

Syntax: obj << Biplot Contour Density( density percent )

Description: Sets the level for the density contour.

JMP Version Added: 14

K Means Example

dt = Open( "$SAMPLE_DATA/Iris.jmp" );
obj = K Means Cluster(
    Y( :Sepal length, :Sepal width, :Petal length, :Petal width ),
    Number of Clusters( 3 ),
    Go( Biplot( 1 ) )
);
obj << Biplot Contour Density( .95 );

Normal Mixtures Example

dt = Open( "$SAMPLE_DATA/Iris.jmp" );
obj = Normal Mixtures(
    Y( :Sepal length, :Sepal width, :Petal length, :Petal width ),
    Number of Clusters( 3 ),
    Go( Biplot( 1 ) )
);
obj << Biplot Contour Density( .95 );

Biplot Ray Position

Syntax: obj << Biplot Ray Position( [X, Y, scaling] )

Description: Moves the biplot ray display.

JMP Version Added: 14

K Means Example

dt = Open( "$SAMPLE_DATA/Iris.jmp" );
obj = K Means Cluster(
    Y( :Sepal length, :Sepal width, :Petal length, :Petal width ),
    Number of Clusters( 3 ),
    Go( Biplot( 1 ) )
);
obj << Biplot Ray Position( [-1, -1, 2] );

Normal Mixtures Example

dt = Open( "$SAMPLE_DATA/Iris.jmp" );
obj = Normal Mixtures(
    Y( :Sepal length, :Sepal width, :Petal length, :Petal width ),
    Number of Clusters( 3 ),
    Go( Biplot( 1 ) )
);
obj << Biplot Ray Position( [-1, -1, 2] );

Get Statistics

Syntax: obj << Get Statistics

Description: Returns the mean and standard deviation for each variable within each cluster.

JMP Version Added: 14

K Means Example

dt = Open( "$SAMPLE_DATA/Iris.jmp" );
obj = K Means Cluster(
    Y( :Sepal length, :Sepal width, :Petal length, :Petal width ),
    Number of Clusters( 3 ),
    Go
);
stats = obj << Get Statistics;
Show( stats );

Normal Mixtures Example

dt = Open( "$SAMPLE_DATA/Iris.jmp" );
obj = Normal Mixtures(
    Y( :Sepal length, :Sepal width, :Petal length, :Petal width ),
    Number of Clusters( 3 ),
    Go
);
stats = obj << Get Statistics;
Show( stats );

Mark Clusters

Syntax: obj << Mark Clusters

Description: Sets the markers in the row state for each row in the data table. Each cluster is assigned a different marker. This affects plots across platforms using rowstate markers, including the Biplot in Cluster.

JMP Version Added: 14

K Means Example

dt = Open( "$SAMPLE_DATA/Iris.jmp" );
obj = K Means Cluster(
    Y( :Sepal length, :Sepal width, :Petal length, :Petal width ),
    Number of Clusters( 3 ),
    Go
);
obj << Biplot( 1 );
obj << Mark Clusters;

Normal Mixtures Example

dt = Open( "$SAMPLE_DATA/Iris.jmp" );
obj = Normal Mixtures(
    Y( :Sepal length, :Sepal width, :Petal length, :Petal width ),
    Number of Clusters( 3 ),
    Go
);
obj << Biplot( 1 );
obj << Mark Clusters;

Parallel Coord Plots

Syntax: obj << Parallel Coord Plots( state=0|1 )

Description: Shows or hides a plot for each cluster separately showing connected line segments that represent each row of the data table.

JMP Version Added: 14

K Means Example

dt = Open( "$SAMPLE_DATA/Iris.jmp" );
obj = K Means Cluster(
    Y( :Sepal length, :Sepal width, :Petal length, :Petal width ),
    Number of Clusters( 3 ),
    Go
);
obj << Parallel Coord Plots( 1 );

Normal Mixtures Example

dt = Open( "$SAMPLE_DATA/Iris.jmp" );
obj = Normal Mixtures(
    Y( :Sepal length, :Sepal width, :Petal length, :Petal width ),
    Number of Clusters( 3 ),
    Go
);
obj << Parallel Coord Plots( 1 );

Publish Cluster Formulas

Syntax: obj << Publish Cluster Formulas

Description: Builds probability formulas and publishes them as a formula column script in Formula Depot.

JMP Version Added: 14

K Means Example

dt = Open( "$SAMPLE_DATA/Iris.jmp" );
obj = K Means Cluster(
    Y( :Sepal length, :Sepal width, :Petal length, :Petal width ),
    Number of Clusters( 3 ),
    Go
);
obj << Publish Cluster Formulas;

Normal Mixtures Example

dt = Open( "$SAMPLE_DATA/Iris.jmp" );
obj = Normal Mixtures(
    Y( :Sepal length, :Sepal width, :Petal length, :Petal width ),
    Number of Clusters( 3 ),
    Go
);
obj << Publish Cluster Formulas;

Save Cluster Formula

Syntax: obj << Save Cluster Formula

Description: Saves a column to the data table with a formula that determines the most likely cluster.

JMP Version Added: 14

K Means Example

dt = Open( "$SAMPLE_DATA/Iris.jmp" );
obj = K Means Cluster(
    Y( :Sepal length, :Sepal width, :Petal length, :Petal width ),
    Number of Clusters( 3 ),
    Go
);
obj << Save Cluster Formula;

Normal Mixtures Example

dt = Open( "$SAMPLE_DATA/Iris.jmp" );
obj = Normal Mixtures(
    Y( :Sepal length, :Sepal width, :Petal length, :Petal width ),
    Number of Clusters( 3 ),
    Go
);
obj << Save Cluster Formula;

Save Clusters

Syntax: obj << Save Clusters

Description: Saves a new column to the data table that contains the most likely cluster for each row.

JMP Version Added: 14

K Means Example

dt = Open( "$SAMPLE_DATA/Iris.jmp" );
obj = K Means Cluster(
    Y( :Sepal length, :Sepal width, :Petal length, :Petal width ),
    Number of Clusters( 3 ),
    Go
);
obj << Save Clusters;

Normal Mixtures Example

dt = Open( "$SAMPLE_DATA/Iris.jmp" );
obj = Normal Mixtures(
    Y( :Sepal length, :Sepal width, :Petal length, :Petal width ),
    Number of Clusters( 3 ),
    Go
);
obj << Save Clusters;

Save Colors to Table

Syntax: obj << Save Colors to Table

Description: Saves the color assigned to the row state in each row according to the cluster membership.

JMP Version Added: 14

K Means Example

dt = Open( "$SAMPLE_DATA/Iris.jmp" );
obj = K Means Cluster(
    Y( :Sepal length, :Sepal width, :Petal length, :Petal width ),
    Number of Clusters( 3 )
);
obj << Go;
obj << Save Colors to Table;

Normal Mixtures Example

dt = Open( "$SAMPLE_DATA/Iris.jmp" );
obj = Normal Mixtures(
    Y( :Sepal length, :Sepal width, :Petal length, :Petal width ),
    Number of Clusters( 3 )
);
obj << Go;
obj << Save Colors to Table;

Save Density Formula

Syntax: obj << Save Density Formula

Description: Saves the density formula in the data table.

JMP Version Added: 14

dt = Open( "$SAMPLE_DATA/Iris.jmp" );
obj = dt << Normal Mixtures(
    Y( :Sepal length, :Sepal width, :Petal length, :Petal width ),
    Number of Clusters( 3 ),
    Go
);
obj << Save Density Formula;

Save Mixture Formulas

Syntax: obj << Save Mixture Formulas

Description: Saves the mixture probability formula to each cluster as a separate column in the data table.

JMP Version Added: 14

dt = Open( "$SAMPLE_DATA/Iris.jmp" );
obj = dt << Normal Mixtures(
    Y( :Sepal length, :Sepal width, :Petal length, :Petal width ),
    Number of Clusters( 3 ),
    Go
);
obj << Save Mixture Formulas;

Save Mixture Probabilities

Syntax: obj << Save Mixture Probabilities

Description: Saves the probability of membership to each cluster as a separate column in the data table.

JMP Version Added: 14

dt = Open( "$SAMPLE_DATA/Iris.jmp" );
obj = dt << Normal Mixtures(
    Y( :Sepal length, :Sepal width, :Petal length, :Petal width ),
    Number of Clusters( 3 ),
    Go
);
obj << Save Mixture Probabilities;

Scatterplot Matrix

Syntax: obj << Scatterplot Matrix( state=0|1 )

Description: Creates a scatterplot matrix in a new window with confidence ellipses based on the current number of clusters.

JMP Version Added: 14

K Means Example

dt = Open( "$SAMPLE_DATA/Iris.jmp" );
obj = K Means Cluster(
    Y( :Sepal length, :Sepal width, :Petal length, :Petal width ),
    Number of Clusters( 3 )
);
obj << Go;
obj << Scatterplot Matrix;

Normal Mixtures Example

dt = Open( "$SAMPLE_DATA/Iris.jmp" );
obj = Normal Mixtures(
    Y( :Sepal length, :Sepal width, :Petal length, :Petal width ),
    Number of Clusters( 3 )
);
obj << Go;
obj << Scatterplot Matrix;

Show Biplot Rays

Syntax: obj << Show Biplot Rays( state=0|1 )

Description: Shows or hides the rays on the biplot. On by default.

JMP Version Added: 14

K Means Example

dt = Open( "$SAMPLE_DATA/Iris.jmp" );
obj = K Means Cluster(
    Y( :Sepal length, :Sepal width, :Petal length, :Petal width ),
    Number of Clusters( 3 ),
    Go( Biplot( 1 ) )
);
obj << Show Biplot Rays( 1 );

Normal Mixtures Example

dt = Open( "$SAMPLE_DATA/Iris.jmp" );
obj = Normal Mixtures(
    Y( :Sepal length, :Sepal width, :Petal length, :Petal width ),
    Number of Clusters( 3 ),
    Go( Biplot( 1 ) )
);
obj << Show Biplot Rays( 1 );

Simulate Clusters

Syntax: obj << Simulate Clusters

Description: Creates a new data table with simulated data using the estimated cluster mixing probabilities, means, and standard deviations for each cluster.

JMP Version Added: 14

K Means Example

dt = Open( "$SAMPLE_DATA/Iris.jmp" );
obj = K Means Cluster(
    Y( :Sepal length, :Sepal width, :Petal length, :Petal width ),
    Number of Clusters( 3 ),
    Go
);
obj << Simulate Clusters( 1000 );

Normal Mixtures Example

dt = Open( "$SAMPLE_DATA/Iris.jmp" );
obj = Normal Mixtures(
    Y( :Sepal length, :Sepal width, :Petal length, :Petal width ),
    Number of Clusters( 3 ),
    Go
);
obj << Simulate Clusters( 1000 );