Multiple Factor Analysis
Associated Constructors
Multiple Factor Analysis
Syntax: Multiple Factor Analysis( MFABLocks({"Block 1", columns},{"Block 2", columns}) )
Description: Analyzes agreement among panelists in sensory data analysis.
JMP Version Added: 14
dt = Open( "$SAMPLE_DATA/Wine Sensory Data.jmp" );
dt << Multiple Factor Analysis(
Product ID( :Vineyard ),
Z( :Region ),
MFA Blocks(
{"Susan Fruity etc.", :Susan Fruity, :Susan Flowery, :Susan Spicy, :Susan Crispness},
{"Florence Flowery etc.", :Florence Flowery, :Florence Crispness, :Florence Tannin,
:Florence Savory, :Florence Lightness},
{"Xavier Fruity etc.", :Xavier Fruity, :Xavier Spicy, :Xavier Crispness,
:Xavier Alcohol, :Xavier Savory, :Xavier Lightness},
{"Robert Fruity etc.", :Robert Fruity, :Robert Flowery, :Robert Spicy,
:Robert Crispness, :Robert Tannin, :Robert Alcohol, :Robert Savory, :Robert Lightness
},
{"Paula Fruity etc.", :Paula Fruity, :Paula Flowery, :Paula Spicy, :Paula Crispness,
:Paula Tannin, :Paula Savory},
{"Monica Fruity etc.", :Monica Fruity, :Monica Flowery, :Monica Spicy, :Monica Tannin,
:Monica Alcohol, :Monica Savory, :Monica Lightness},
{"Frank Fruity etc.", :Frank Fruity, :Frank Flowery, :Frank Spicy, :Frank Crispness,
:Frank Tannin, :Frank Alcohol, :Frank Savory, :Frank Lightness}
)
);
Columns
By
Syntax: obj = Multiple Factor Analysis(...<By( column(s) )>...)
Description: Performs a separate analysis for each level of the specified column.
JMP Version Added: 14
dt = Open( "$SAMPLE_DATA/Wine Sensory Data.jmp" );
dt << New Column( "_bycol",
Character,
Nominal,
set values( Repeat( {"A", "B"}, N Rows( dt ) )[1 :: N Rows( dt )] )
);
dt << Multiple Factor Analysis(
Product ID( :Vineyard ),
Z( :Region ),
MFA Blocks(
{"Susan Fruity etc.", :Susan Fruity, :Susan Flowery, :Susan Spicy, :Susan Crispness},
{"Florence Flowery etc.", :Florence Flowery, :Florence Crispness, :Florence Tannin,
:Florence Savory, :Florence Lightness},
{"Xavier Fruity etc.", :Xavier Fruity, :Xavier Spicy, :Xavier Crispness,
:Xavier Alcohol, :Xavier Savory, :Xavier Lightness},
{"Robert Fruity etc.", :Robert Fruity, :Robert Flowery, :Robert Spicy,
:Robert Crispness, :Robert Tannin, :Robert Alcohol, :Robert Savory, :Robert Lightness
},
{"Paula Fruity etc.", :Paula Fruity, :Paula Flowery, :Paula Spicy, :Paula Crispness,
:Paula Tannin, :Paula Savory},
{"Monica Fruity etc.", :Monica Fruity, :Monica Flowery, :Monica Spicy, :Monica Tannin,
:Monica Alcohol, :Monica Savory, :Monica Lightness},
{"Frank Fruity etc.", :Frank Fruity, :Frank Flowery, :Frank Spicy, :Frank Crispness,
:Frank Tannin, :Frank Alcohol, :Frank Savory, :Frank Lightness}
),
By( _bycol )
);
Freq
Syntax: obj = Multiple Factor Analysis(...<Freq( column )>...)
Description: Specifies a column whose values assign a frequency to each row for the analysis.
JMP Version Added: 14
dt = Open( "$SAMPLE_DATA/Wine Sensory Data.jmp" );
dt << New Column( "_freqcol", Numeric, Continuous, Formula( Random Integer( 1, 5 ) ) );
dt << Multiple Factor Analysis(
Product ID( :Vineyard ),
Z( :Region ),
MFA Blocks(
{"Susan Fruity etc.", :Susan Fruity, :Susan Flowery, :Susan Spicy, :Susan Crispness},
{"Florence Flowery etc.", :Florence Flowery, :Florence Crispness, :Florence Tannin,
:Florence Savory, :Florence Lightness},
{"Xavier Fruity etc.", :Xavier Fruity, :Xavier Spicy, :Xavier Crispness,
:Xavier Alcohol, :Xavier Savory, :Xavier Lightness},
{"Robert Fruity etc.", :Robert Fruity, :Robert Flowery, :Robert Spicy,
:Robert Crispness, :Robert Tannin, :Robert Alcohol, :Robert Savory, :Robert Lightness
},
{"Paula Fruity etc.", :Paula Fruity, :Paula Flowery, :Paula Spicy, :Paula Crispness,
:Paula Tannin, :Paula Savory},
{"Monica Fruity etc.", :Monica Fruity, :Monica Flowery, :Monica Spicy, :Monica Tannin,
:Monica Alcohol, :Monica Savory, :Monica Lightness},
{"Frank Fruity etc.", :Frank Fruity, :Frank Flowery, :Frank Spicy, :Frank Crispness,
:Frank Tannin, :Frank Alcohol, :Frank Savory, :Frank Lightness}
),
Freq( _freqcol )
);
MFA Blocks
Syntax: obj = Multiple Factor Analysis(...<MFA Blocks( column )>...)
Description: Specifies groups of columns that should be treated as sub-tables within the multiple factor analysis.
JMP Version Added: 14
dt = Open( "$SAMPLE_DATA/Wine Sensory Data.jmp" );
dt << Multiple Factor Analysis(
Product ID( :Wine ),
MFA Blocks(
{"Susan", :Susan Fruity, :Susan Flowery, :Susan Spicy, :Susan Crispness},
{"Florence", :Florence Flowery, :Florence Crispness, :Florence Tannin,
:Florence Savory, :Florence Lightness}
)
);
Product ID
Syntax: obj = Multiple Factor Analysis(...<Product ID( column )>...)
Description: Specifies columns of items or products to be analyzed.
JMP Version Added: 14
dt = Open( "$SAMPLE_DATA/Wine Sensory Data.jmp" );
dt << Multiple Factor Analysis(
Product ID( :Wine ),
MFA Blocks(
{"Susan", :Susan Fruity, :Susan Flowery, :Susan Spicy, :Susan Crispness},
{"Florence", :Florence Flowery, :Florence Crispness, :Florence Tannin,
:Florence Savory, :Florence Lightness}
)
);
Supplementary
Syntax: obj = Multiple Factor Analysis(...<Supplementary( column )>...)
Description: Specifies one or more supplementary variables. Supplementary variables are not used in any of the calculations in the platform and including them does not affect the results. These variables can improve data interpretation or be used in future analyses.
JMP Version Added: 14
dt = Open( "$SAMPLE_DATA/Wine Sensory Data.jmp" );
dt << Multiple Factor Analysis(
Product ID( :Wine ),
Z( :Region ),
MFA Blocks(
{"Susan", :Susan Fruity, :Susan Flowery, :Susan Spicy, :Susan Crispness},
{"Florence", :Florence Flowery, :Florence Crispness, :Florence Tannin,
:Florence Savory, :Florence Lightness}
)
);
Weight
Syntax: obj = Multiple Factor Analysis(...<Weight( column )>...)
Description: Specifies a column whose values assign a weight to each row for the analysis.
JMP Version Added: 14
dt = Open( "$SAMPLE_DATA/Wine Sensory Data.jmp" );
dt << New Column( "_weightcol", Numeric, Continuous, Formula( Random Beta( 1, 1 ) ) );
dt << Multiple Factor Analysis(
Product ID( :Vineyard ),
Z( :Region ),
MFA Blocks(
{"Susan Fruity etc.", :Susan Fruity, :Susan Flowery, :Susan Spicy, :Susan Crispness},
{"Florence Flowery etc.", :Florence Flowery, :Florence Crispness, :Florence Tannin,
:Florence Savory, :Florence Lightness},
{"Xavier Fruity etc.", :Xavier Fruity, :Xavier Spicy, :Xavier Crispness,
:Xavier Alcohol, :Xavier Savory, :Xavier Lightness},
{"Robert Fruity etc.", :Robert Fruity, :Robert Flowery, :Robert Spicy,
:Robert Crispness, :Robert Tannin, :Robert Alcohol, :Robert Savory, :Robert Lightness
},
{"Paula Fruity etc.", :Paula Fruity, :Paula Flowery, :Paula Spicy, :Paula Crispness,
:Paula Tannin, :Paula Savory},
{"Monica Fruity etc.", :Monica Fruity, :Monica Flowery, :Monica Spicy, :Monica Tannin,
:Monica Alcohol, :Monica Savory, :Monica Lightness},
{"Frank Fruity etc.", :Frank Fruity, :Frank Flowery, :Frank Spicy, :Frank Crispness,
:Frank Tannin, :Frank Alcohol, :Frank Savory, :Frank Lightness}
),
Weight( _weightcol )
);
Z
Syntax: obj = Multiple Factor Analysis(...<Z( column )>...)
Description: Specifies one or more supplementary variables. Supplementary variables are not used in any of the calculations in the platform and including them does not affect the results. These variables can improve data interpretation or be used in future analyses.
JMP Version Added: 14
dt = Open( "$SAMPLE_DATA/Wine Sensory Data.jmp" );
dt << Multiple Factor Analysis(
Product ID( :Wine ),
Z( :Region ),
MFA Blocks(
{"Susan", :Susan Fruity, :Susan Flowery, :Susan Spicy, :Susan Crispness},
{"Florence", :Florence Flowery, :Florence Crispness, :Florence Tannin,
:Florence Savory, :Florence Lightness}
)
);
Item Messages
Arrow Lines
Syntax: obj << Arrow Lines( state=0|1 )
Description: Shows or hides the arrow lines in the graph. On by default.
JMP Version Added: 14
dt = Open( "$SAMPLE_DATA/Wine Sensory Data.jmp" );
obj = dt << Multiple Factor Analysis(
MFA Blocks(
{"Carolyn Peppery etc.", :Carolyn Peppery, :Carolyn Tannic, :Carolyn Aromatic,
:Carolyn Berry Notes},
{"Susan Fruity etc.", :Susan Fruity, :Susan Flowery, :Susan Spicy, :Susan Crispness}
)
);
obj << Arrow Lines( 0 );
Biplot
Syntax: obj << Biplot( state=0|1 )
Description: Shows or hides a plot that overlays the score plot and the loading plot for the specified number of components.
JMP Version Added: 14
dt = Open( "$SAMPLE_DATA/Wine Sensory Data.jmp" );
obj = dt << Multiple Factor Analysis(
MFA Blocks(
{"Carolyn Peppery etc.", :Carolyn Peppery, :Carolyn Tannic, :Carolyn Aromatic,
:Carolyn Berry Notes},
{"Susan Fruity etc.", :Susan Fruity, :Susan Flowery, :Susan Spicy, :Susan Crispness}
)
);
obj << Biplot( 1 );
Biplot Select Component
Syntax: obj<<Biplot Select Component( 1, 3 )
Description: Selects the components that are used as axes in the biplot.
JMP Version Added: 14
dt = Open( "$SAMPLE_DATA/Wine Sensory Data.jmp" );
obj = dt << Multiple Factor Analysis(
MFA Blocks(
{"Carolyn Peppery etc.", :Carolyn Peppery, :Carolyn Tannic, :Carolyn Aromatic,
:Carolyn Berry Notes},
{"Susan Fruity etc.", :Susan Fruity, :Susan Flowery, :Susan Spicy, :Susan Crispness}
)
);
obj << Biplot Select Component( 1, 3 );
Block Partial Contributions
Syntax: obj << Block Partial Contributions( state=0|1 )
Description: Displays or hides block contributions which is the sum of the contributions of its variables.
JMP Version Added: 14
dt = Open( "$SAMPLE_DATA/Wine Sensory Data.jmp" );
obj = dt << Multiple Factor Analysis(
MFA Blocks(
{"Carolyn Peppery etc.", :Carolyn Peppery, :Carolyn Tannic, :Carolyn Aromatic,
:Carolyn Berry Notes},
{"Susan Fruity etc.", :Susan Fruity, :Susan Flowery, :Susan Spicy, :Susan Crispness}
)
);
obj << Block Partial Contributions( 1 );
Block Partial Inertias
Syntax: obj << Block Partial Inertias( state=0|1 )
Description: Displays or hides rescaled block contributions, such that the sum of inertia across blocks equals the principal component's eigenvalue.
JMP Version Added: 14
dt = Open( "$SAMPLE_DATA/Wine Sensory Data.jmp" );
obj = dt << Multiple Factor Analysis(
MFA Blocks(
{"Carolyn Peppery etc.", :Carolyn Peppery, :Carolyn Tannic, :Carolyn Aromatic,
:Carolyn Berry Notes},
{"Susan Fruity etc.", :Susan Fruity, :Susan Flowery, :Susan Spicy, :Susan Crispness}
)
);
obj << Block Partial Inertias( 1 );
Block Partial and Consensus Correlations
Syntax: obj << Block Partial and Consensus Correlations( state=0|1 )
Description: Displays or hides a matrix of coefficients indicating the correlations between partial and consensus scores on each principal component dimension.
JMP Version Added: 14
dt = Open( "$SAMPLE_DATA/Wine Sensory Data.jmp" );
obj = dt << Multiple Factor Analysis(
MFA Blocks(
{"Carolyn Peppery etc.", :Carolyn Peppery, :Carolyn Tannic, :Carolyn Aromatic,
:Carolyn Berry Notes},
{"Susan Fruity etc.", :Susan Fruity, :Susan Flowery, :Susan Spicy, :Susan Crispness}
)
);
obj << Block Partial and Consensus Correlations( 1 );
Block Squared Cosines
Syntax: obj << Block Squared Cosines( state=0|1 )
Description: Displays or hides the proportion of overlap in variance between blocks and principal component dimensions.
JMP Version Added: 14
dt = Open( "$SAMPLE_DATA/Wine Sensory Data.jmp" );
obj = dt << Multiple Factor Analysis(
MFA Blocks(
{"Carolyn Peppery etc.", :Carolyn Peppery, :Carolyn Tannic, :Carolyn Aromatic,
:Carolyn Berry Notes},
{"Susan Fruity etc.", :Susan Fruity, :Susan Flowery, :Susan Spicy, :Susan Crispness}
)
);
obj << Block Squared Cosines( 1 );
Block Weights
Syntax: obj << Block Weights( state=0|1 )
Description: Displays or hides a matrix of block weight which is the inverse of each block's first singular value.
JMP Version Added: 14
dt = Open( "$SAMPLE_DATA/Wine Sensory Data.jmp" );
obj = dt << Multiple Factor Analysis(
MFA Blocks(
{"Carolyn Peppery etc.", :Carolyn Peppery, :Carolyn Tannic, :Carolyn Aromatic,
:Carolyn Berry Notes},
{"Susan Fruity etc.", :Susan Fruity, :Susan Flowery, :Susan Spicy, :Susan Crispness}
)
);
obj << Block Weights( 1 );
Consensus Map
Syntax: obj << Consensus Map( state=0|1 )
Description: Displays or hides a Consensus Map which overlays the centroid scores and partial scores from each block. On by default.
JMP Version Added: 14
dt = Open( "$SAMPLE_DATA/Wine Sensory Data.jmp" );
obj = dt << Multiple Factor Analysis(
MFA Blocks(
{"Carolyn Peppery etc.", :Carolyn Peppery, :Carolyn Tannic, :Carolyn Aromatic,
:Carolyn Berry Notes},
{"Susan Fruity etc.", :Susan Fruity, :Susan Flowery, :Susan Spicy, :Susan Crispness}
)
);
obj << Consensus Map( 0 );
Consensus Map Select Component
Syntax: obj<<Consensus Map Select Component( 1, 3 )
Description: Selects the components that are used as axes in the consensus map.
JMP Version Added: 14
dt = Open( "$SAMPLE_DATA/Wine Sensory Data.jmp" );
obj = dt << Multiple Factor Analysis(
MFA Blocks(
{"Carolyn Peppery etc.", :Carolyn Peppery, :Carolyn Tannic, :Carolyn Aromatic,
:Carolyn Berry Notes},
{"Susan Fruity etc.", :Susan Fruity, :Susan Flowery, :Susan Spicy, :Susan Crispness}
)
);
obj << Consensus Map Select Component( 1, 3 );
Eigenvalues
Syntax: obj << Eigenvalues( state=0|1 )
Description: Shows or hides the sorted eigenvalues, their percent of variation, and the cumulative percent of variation.
JMP Version Added: 14
dt = Open( "$SAMPLE_DATA/Wine Sensory Data.jmp" );
obj = dt << Multiple Factor Analysis(
MFA Blocks(
{"Carolyn Peppery etc.", :Carolyn Peppery, :Carolyn Tannic, :Carolyn Aromatic,
:Carolyn Berry Notes},
{"Susan Fruity etc.", :Susan Fruity, :Susan Flowery, :Susan Spicy, :Susan Crispness}
)
);
obj << Eigenvalues( 1 );
Eigenvectors
Syntax: obj << Eigenvectors( state=0|1 )
Description: Shows or hides a report of the eigenvectors for each of the principal components.
JMP Version Added: 14
dt = Open( "$SAMPLE_DATA/Wine Sensory Data.jmp" );
obj = dt << Multiple Factor Analysis(
MFA Blocks(
{"Carolyn Peppery etc.", :Carolyn Peppery, :Carolyn Tannic, :Carolyn Aromatic,
:Carolyn Berry Notes},
{"Susan Fruity etc.", :Susan Fruity, :Susan Flowery, :Susan Spicy, :Susan Crispness}
)
);
obj << Eigenvectors( 1 );
Highlight Product
Syntax: obj<<Partial Axes Plot Select Component( 1, 3 )
Description: Highlights product clusters based on the specified inertial value.
JMP Version Added: 14
dt = Open( "$SAMPLE_DATA/Wine Sensory Data.jmp" );
obj = dt << Multiple Factor Analysis(
MFA Blocks(
{"Carolyn Peppery etc.", :Carolyn Peppery, :Carolyn Tannic, :Carolyn Aromatic,
:Carolyn Berry Notes},
{"Susan Fruity etc.", :Susan Fruity, :Susan Flowery, :Susan Spicy, :Susan Crispness}
),
Consensus Map( 1 )
);
obj << Highlight Product( "Small Inertia", 4 );
Lg Coefficients
Syntax: obj << Lg Coefficients( state=0|1 )
Description: Displays or hides a matrix of coefficients indicating the similarity between blocks. Equivalent to unstandardized RV correlations.
JMP Version Added: 14
dt = Open( "$SAMPLE_DATA/Wine Sensory Data.jmp" );
obj = dt << Multiple Factor Analysis(
MFA Blocks(
{"Carolyn Peppery etc.", :Carolyn Peppery, :Carolyn Tannic, :Carolyn Aromatic,
:Carolyn Berry Notes},
{"Susan Fruity etc.", :Susan Fruity, :Susan Flowery, :Susan Spicy, :Susan Crispness}
)
);
obj << Lg Coefficients( 1 );
Partial Axes Plot
Syntax: obj << Partial Axes Plot( state=0|1 )
Description: Displays or hides a Partial Axes Plot which shows the link between centroid plane and blocks.
JMP Version Added: 14
dt = Open( "$SAMPLE_DATA/Wine Sensory Data.jmp" );
obj = dt << Multiple Factor Analysis(
MFA Blocks(
{"Carolyn Peppery etc.", :Carolyn Peppery, :Carolyn Tannic, :Carolyn Aromatic,
:Carolyn Berry Notes},
{"Susan Fruity etc.", :Susan Fruity, :Susan Flowery, :Susan Spicy, :Susan Crispness}
)
);
obj << Partial Axes Plot( 1 );
Partial Axes Plot Select Component
Syntax: obj<<Partial Axes Plot Select Component( 1, 3 )
Description: Selects the components that are used as axes in the Partial Axes Plot.
JMP Version Added: 14
dt = Open( "$SAMPLE_DATA/Wine Sensory Data.jmp" );
obj = dt << Multiple Factor Analysis(
MFA Blocks(
{"Carolyn Peppery etc.", :Carolyn Peppery, :Carolyn Tannic, :Carolyn Aromatic,
:Carolyn Berry Notes},
{"Susan Fruity etc.", :Susan Fruity, :Susan Flowery, :Susan Spicy, :Susan Crispness}
),
Partial Axes Plot( 1 )
);
obj << Partial Axes Plot Select component( 1, 3 );
RV Correlations
Syntax: obj << RV Correlations( state=0|1 )
Description: Displays or hides a matrix of squared correlation coefficients between blocks. RV coefficients range from 0 to 1.
JMP Version Added: 14
dt = Open( "$SAMPLE_DATA/Wine Sensory Data.jmp" );
obj = dt << Multiple Factor Analysis(
MFA Blocks(
{"Carolyn Peppery etc.", :Carolyn Peppery, :Carolyn Tannic, :Carolyn Aromatic,
:Carolyn Berry Notes},
{"Susan Fruity etc.", :Susan Fruity, :Susan Flowery, :Susan Spicy, :Susan Crispness}
)
);
obj << RV Correlations( 1 );
Save Block Partial Scores
Syntax: obj << Save Block Partial Scores
Description: Saves block partial scores to new columns in a data table.
JMP Version Added: 14
dt = Open( "$SAMPLE_DATA/Wine Sensory Data.jmp" );
obj = dt << Multiple Factor Analysis(
MFA Blocks(
{"Carolyn Peppery etc.", :Carolyn Peppery, :Carolyn Tannic, :Carolyn Aromatic,
:Carolyn Berry Notes},
{"Susan Fruity etc.", :Susan Fruity, :Susan Flowery, :Susan Spicy, :Susan Crispness}
)
);
obj << Save Block Partial Scores();
Save Individual Partial Contributions
Syntax: obj << Save Individual Partial Contributions
Description: Saves individual partial contributions to new columns in the data table.
JMP Version Added: 14
dt = Open( "$SAMPLE_DATA/Wine Sensory Data.jmp" );
obj = dt << Multiple Factor Analysis(
MFA Blocks(
{"Carolyn Peppery etc.", :Carolyn Peppery, :Carolyn Tannic, :Carolyn Aromatic,
:Carolyn Berry Notes},
{"Susan Fruity etc.", :Susan Fruity, :Susan Flowery, :Susan Spicy, :Susan Crispness}
)
);
obj << Save Individual Partial Contributions();
Save Individual Scores
Syntax: obj << Save Individual Scores
Description: Saves the given number of principal components to new columns in the data table.
JMP Version Added: 14
dt = Open( "$SAMPLE_DATA/Wine Sensory Data.jmp" );
obj = dt << Multiple Factor Analysis(
MFA Blocks(
{"Carolyn Peppery etc.", :Carolyn Peppery, :Carolyn Tannic, :Carolyn Aromatic,
:Carolyn Berry Notes},
{"Susan Fruity etc.", :Susan Fruity, :Susan Flowery, :Susan Spicy, :Susan Crispness}
)
);
obj << Save Individual Scores();
Save Individual Squared Cosines
Syntax: obj << Save Individual Squared Cosines
Description: Saves individual squared cosines to new columns in the data table.
JMP Version Added: 14
dt = Open( "$SAMPLE_DATA/Wine Sensory Data.jmp" );
obj = dt << Multiple Factor Analysis(
MFA Blocks(
{"Carolyn Peppery etc.", :Carolyn Peppery, :Carolyn Tannic, :Carolyn Aromatic,
:Carolyn Berry Notes},
{"Susan Fruity etc.", :Susan Fruity, :Susan Flowery, :Susan Spicy, :Susan Crispness}
)
);
obj << Save Individual Squared Cosines();
Save Partial Axes Coordinates
Syntax: obj << Save Partial Axes Coordinates
Description: Saves partial axes coordinates to new columns in a data table.
JMP Version Added: 14
dt = Open( "$SAMPLE_DATA/Wine Sensory Data.jmp" );
obj = dt << Multiple Factor Analysis(
MFA Blocks(
{"Carolyn Peppery etc.", :Carolyn Peppery, :Carolyn Tannic, :Carolyn Aromatic,
:Carolyn Berry Notes},
{"Susan Fruity etc.", :Susan Fruity, :Susan Flowery, :Susan Spicy, :Susan Crispness}
)
);
obj << Save Partial Axes Coordinates();
Show Labels
Syntax: obj << Show Labels( state=0|1 )
Description: Displays or hides the labels of points in the graph.
JMP Version Added: 14
dt = Open( "$SAMPLE_DATA/Wine Sensory Data.jmp" );
obj = dt << Multiple Factor Analysis(
MFA Blocks(
{"Carolyn Peppery etc.", :Carolyn Peppery, :Carolyn Tannic, :Carolyn Aromatic,
:Carolyn Berry Notes},
{"Susan Fruity etc.", :Susan Fruity, :Susan Flowery, :Susan Spicy, :Susan Crispness}
)
);
obj << Show Labels( 1 );
Summary Plot Select Component
Syntax: obj<<Summary Plot Select Component( 1, 3 )
Description: Selects the components that are used as axes in the summary plots.
JMP Version Added: 14
dt = Open( "$SAMPLE_DATA/Wine Sensory Data.jmp" );
obj = dt << Multiple Factor Analysis(
MFA Blocks(
{"Carolyn Peppery etc.", :Carolyn Peppery, :Carolyn Tannic, :Carolyn Aromatic,
:Carolyn Berry Notes},
{"Susan Fruity etc.", :Susan Fruity, :Susan Flowery, :Susan Spicy, :Susan Crispness}
)
);
obj << Summary Plot Select Component( 1, 3 );
Summary Plots
Syntax: obj << Summary Plots( state=0|1 )
Description: Shows or hides an outline node that contains a plot of the eigenvalues, a score plot, and a loading plot. On by default.
JMP Version Added: 14
dt = Open( "$SAMPLE_DATA/Wine Sensory Data.jmp" );
obj = dt << Multiple Factor Analysis(
MFA Blocks(
{"Carolyn Peppery etc.", :Carolyn Peppery, :Carolyn Tannic, :Carolyn Aromatic,
:Carolyn Berry Notes},
{"Susan Fruity etc.", :Susan Fruity, :Susan Flowery, :Susan Spicy, :Susan Crispness}
)
);
obj << Summary Plots( 0 );
Variable Loadings
Syntax: obj << Variable Loadings( state=0|1 )
Description: Displays or hides a report showing the columns corresponding to the component loadings.
JMP Version Added: 14
dt = Open( "$SAMPLE_DATA/Wine Sensory Data.jmp" );
obj = dt << Multiple Factor Analysis(
MFA Blocks(
{"Carolyn Peppery etc.", :Carolyn Peppery, :Carolyn Tannic, :Carolyn Aromatic,
:Carolyn Berry Notes},
{"Susan Fruity etc.", :Susan Fruity, :Susan Flowery, :Susan Spicy, :Susan Crispness}
)
);
obj << Variable Loadings( 1 );
Variable Partial Contributions
Syntax: obj << Variable Partial Contributions( state=0|1 )
Description: Shows or hides a table that contains the partial contributions of variables and a plot of the partial contributions for the first three principal components.
JMP Version Added: 14
dt = Open( "$SAMPLE_DATA/Wine Sensory Data.jmp" );
obj = dt << Multiple Factor Analysis(
MFA Blocks(
{"Carolyn Peppery etc.", :Carolyn Peppery, :Carolyn Tannic, :Carolyn Aromatic,
:Carolyn Berry Notes},
{"Susan Fruity etc.", :Susan Fruity, :Susan Flowery, :Susan Spicy, :Susan Crispness}
)
);
obj << Variable Partial Contributions( 1 );
Variable Squared Cosines
Syntax: obj << Variable Squared Cosines( state=0|1 )
Description: Shows or hides a table that contains the squared cosines of variables.
JMP Version Added: 14
dt = Open( "$SAMPLE_DATA/Wine Sensory Data.jmp" );
obj = dt << Multiple Factor Analysis(
MFA Blocks(
{"Carolyn Peppery etc.", :Carolyn Peppery, :Carolyn Tannic, :Carolyn Aromatic,
:Carolyn Berry Notes},
{"Susan Fruity etc.", :Susan Fruity, :Susan Flowery, :Susan Spicy, :Susan Crispness}
)
);
obj << Variable Squared Cosines( 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( "$SAMPLE_DATA/Big Class.jmp" );
obj = dt << Oneway( Y( :height ), X( :sex ) );
Wait( 1 );
obj << Apply Preset( "Sample Presets", "t-Tests", Folder( "Compare Means" ) );
Automatic Recalc
Syntax: obj << Automatic Recalc( state=0|1 )
Description: Redoes the analysis automatically for exclude and data changes. If the Automatic Recalc option is turned on, you should consider using Wait(0) commands to ensure that the exclude and data changes take effect before the recalculation.
dt = Open( "$SAMPLE_DATA/Wine Sensory Data.jmp" );
dt << Multiple Factor Analysis(
Product ID( :Vineyard ),
Z( :Region ),
MFA Blocks(
{"Susan Fruity etc.", :Susan Fruity, :Susan Flowery, :Susan Spicy, :Susan Crispness},
{"Florence Flowery etc.", :Florence Flowery, :Florence Crispness, :Florence Tannin,
:Florence Savory, :Florence Lightness},
{"Xavier Fruity etc.", :Xavier Fruity, :Xavier Spicy, :Xavier Crispness,
:Xavier Alcohol, :Xavier Savory, :Xavier Lightness},
{"Robert Fruity etc.", :Robert Fruity, :Robert Flowery, :Robert Spicy,
:Robert Crispness, :Robert Tannin, :Robert Alcohol, :Robert Savory, :Robert Lightness
},
{"Paula Fruity etc.", :Paula Fruity, :Paula Flowery, :Paula Spicy, :Paula Crispness,
:Paula Tannin, :Paula Savory},
{"Monica Fruity etc.", :Monica Fruity, :Monica Flowery, :Monica Spicy, :Monica Tannin,
:Monica Alcohol, :Monica Savory, :Monica Lightness},
{"Frank Fruity etc.", :Frank Fruity, :Frank Flowery, :Frank Spicy, :Frank Crispness,
:Frank Tannin, :Frank Alcohol, :Frank Savory, :Frank Lightness}
)
);
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( "$SAMPLE_DATA/Wine Sensory Data.jmp" );
dt << New Column( "_bycol",
Character,
Nominal,
set values( Repeat( {"A", "B"}, N Rows( dt ) )[1 :: N Rows( dt )] )
);
dt << Multiple Factor Analysis(
Product ID( :Vineyard ),
Z( :Region ),
MFA Blocks(
{"Susan Fruity etc.", :Susan Fruity, :Susan Flowery, :Susan Spicy, :Susan Crispness},
{"Florence Flowery etc.", :Florence Flowery, :Florence Crispness, :Florence Tannin,
:Florence Savory, :Florence Lightness},
{"Xavier Fruity etc.", :Xavier Fruity, :Xavier Spicy, :Xavier Crispness,
:Xavier Alcohol, :Xavier Savory, :Xavier Lightness},
{"Robert Fruity etc.", :Robert Fruity, :Robert Flowery, :Robert Spicy,
:Robert Crispness, :Robert Tannin, :Robert Alcohol, :Robert Savory, :Robert Lightness
},
{"Paula Fruity etc.", :Paula Fruity, :Paula Flowery, :Paula Spicy, :Paula Crispness,
:Paula Tannin, :Paula Savory},
{"Monica Fruity etc.", :Monica Fruity, :Monica Flowery, :Monica Spicy, :Monica Tannin,
:Monica Alcohol, :Monica Savory, :Monica Lightness},
{"Frank Fruity etc.", :Frank Fruity, :Frank Flowery, :Frank Spicy, :Frank Crispness,
:Frank Tannin, :Frank Alcohol, :Frank Savory, :Frank Lightness}
),
By( _bycol )
);
obj[1] << Copy ByGroup Script;
Copy Script
Syntax: obj << Copy Script
Description: Create a JSL script to produce this analysis, and put it on the clipboard.
dt = Open( "$SAMPLE_DATA/Wine Sensory Data.jmp" );
dt << Multiple Factor Analysis(
Product ID( :Vineyard ),
Z( :Region ),
MFA Blocks(
{"Susan Fruity etc.", :Susan Fruity, :Susan Flowery, :Susan Spicy, :Susan Crispness},
{"Florence Flowery etc.", :Florence Flowery, :Florence Crispness, :Florence Tannin,
:Florence Savory, :Florence Lightness},
{"Xavier Fruity etc.", :Xavier Fruity, :Xavier Spicy, :Xavier Crispness,
:Xavier Alcohol, :Xavier Savory, :Xavier Lightness},
{"Robert Fruity etc.", :Robert Fruity, :Robert Flowery, :Robert Spicy,
:Robert Crispness, :Robert Tannin, :Robert Alcohol, :Robert Savory, :Robert Lightness
},
{"Paula Fruity etc.", :Paula Fruity, :Paula Flowery, :Paula Spicy, :Paula Crispness,
:Paula Tannin, :Paula Savory},
{"Monica Fruity etc.", :Monica Fruity, :Monica Flowery, :Monica Spicy, :Monica Tannin,
:Monica Alcohol, :Monica Savory, :Monica Lightness},
{"Frank Fruity etc.", :Frank Fruity, :Frank Flowery, :Frank Spicy, :Frank Crispness,
:Frank Tannin, :Frank Alcohol, :Frank Savory, :Frank Lightness}
)
);
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( "$SAMPLE_DATA/Wine Sensory Data.jmp" );
dt << Multiple Factor Analysis(
Product ID( :Vineyard ),
Z( :Region ),
MFA Blocks(
{"Susan Fruity etc.", :Susan Fruity, :Susan Flowery, :Susan Spicy, :Susan Crispness},
{"Florence Flowery etc.", :Florence Flowery, :Florence Crispness, :Florence Tannin,
:Florence Savory, :Florence Lightness},
{"Xavier Fruity etc.", :Xavier Fruity, :Xavier Spicy, :Xavier Crispness,
:Xavier Alcohol, :Xavier Savory, :Xavier Lightness},
{"Robert Fruity etc.", :Robert Fruity, :Robert Flowery, :Robert Spicy,
:Robert Crispness, :Robert Tannin, :Robert Alcohol, :Robert Savory, :Robert Lightness
},
{"Paula Fruity etc.", :Paula Fruity, :Paula Flowery, :Paula Spicy, :Paula Crispness,
:Paula Tannin, :Paula Savory},
{"Monica Fruity etc.", :Monica Fruity, :Monica Flowery, :Monica Spicy, :Monica Tannin,
:Monica Alcohol, :Monica Savory, :Monica Lightness},
{"Frank Fruity etc.", :Frank Fruity, :Frank Flowery, :Frank Spicy, :Frank Crispness,
:Frank Tannin, :Frank Alcohol, :Frank Savory, :Frank Lightness}
)
);
obj << Data Table Window;
Get By Levels
Syntax: obj << Get By Levels
Description: Returns an associative array mapping the by group columns to their values.
JMP Version Added: 18
dt = Open( "$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( "$SAMPLE_DATA/Wine Sensory Data.jmp" );
dt << New Column( "_bycol",
Character,
Nominal,
set values( Repeat( {"A", "B"}, N Rows( dt ) )[1 :: N Rows( dt )] )
);
dt << Multiple Factor Analysis(
Product ID( :Vineyard ),
Z( :Region ),
MFA Blocks(
{"Susan Fruity etc.", :Susan Fruity, :Susan Flowery, :Susan Spicy, :Susan Crispness},
{"Florence Flowery etc.", :Florence Flowery, :Florence Crispness, :Florence Tannin,
:Florence Savory, :Florence Lightness},
{"Xavier Fruity etc.", :Xavier Fruity, :Xavier Spicy, :Xavier Crispness,
:Xavier Alcohol, :Xavier Savory, :Xavier Lightness},
{"Robert Fruity etc.", :Robert Fruity, :Robert Flowery, :Robert Spicy,
:Robert Crispness, :Robert Tannin, :Robert Alcohol, :Robert Savory, :Robert Lightness
},
{"Paula Fruity etc.", :Paula Fruity, :Paula Flowery, :Paula Spicy, :Paula Crispness,
:Paula Tannin, :Paula Savory},
{"Monica Fruity etc.", :Monica Fruity, :Monica Flowery, :Monica Spicy, :Monica Tannin,
:Monica Alcohol, :Monica Savory, :Monica Lightness},
{"Frank Fruity etc.", :Frank Fruity, :Frank Flowery, :Frank Spicy, :Frank Crispness,
:Frank Tannin, :Frank Alcohol, :Frank Savory, :Frank Lightness}
),
By( _bycol )
);
t = obj[1] << Get ByGroup Script;
Show( t );
Get Container
Syntax: obj << Get Container
Description: Returns a reference to the container box that holds the content for the object.
General
dt = Open( "$SAMPLE_DATA/Wine Sensory Data.jmp" );
dt << Multiple Factor Analysis(
Product ID( :Vineyard ),
Z( :Region ),
MFA Blocks(
{"Susan Fruity etc.", :Susan Fruity, :Susan Flowery, :Susan Spicy, :Susan Crispness},
{"Florence Flowery etc.", :Florence Flowery, :Florence Crispness, :Florence Tannin,
:Florence Savory, :Florence Lightness},
{"Xavier Fruity etc.", :Xavier Fruity, :Xavier Spicy, :Xavier Crispness,
:Xavier Alcohol, :Xavier Savory, :Xavier Lightness},
{"Robert Fruity etc.", :Robert Fruity, :Robert Flowery, :Robert Spicy,
:Robert Crispness, :Robert Tannin, :Robert Alcohol, :Robert Savory, :Robert Lightness
},
{"Paula Fruity etc.", :Paula Fruity, :Paula Flowery, :Paula Spicy, :Paula Crispness,
:Paula Tannin, :Paula Savory},
{"Monica Fruity etc.", :Monica Fruity, :Monica Flowery, :Monica Spicy, :Monica Tannin,
:Monica Alcohol, :Monica Savory, :Monica Lightness},
{"Frank Fruity etc.", :Frank Fruity, :Frank Flowery, :Frank Spicy, :Frank Crispness,
:Frank Tannin, :Frank Alcohol, :Frank Savory, :Frank Lightness}
)
);
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/Wine Sensory Data.jmp" );
dt << Multiple Factor Analysis(
Product ID( :Vineyard ),
Z( :Region ),
MFA Blocks(
{"Susan Fruity etc.", :Susan Fruity, :Susan Flowery, :Susan Spicy, :Susan Crispness},
{"Florence Flowery etc.", :Florence Flowery, :Florence Crispness, :Florence Tannin,
:Florence Savory, :Florence Lightness},
{"Xavier Fruity etc.", :Xavier Fruity, :Xavier Spicy, :Xavier Crispness,
:Xavier Alcohol, :Xavier Savory, :Xavier Lightness},
{"Robert Fruity etc.", :Robert Fruity, :Robert Flowery, :Robert Spicy,
:Robert Crispness, :Robert Tannin, :Robert Alcohol, :Robert Savory, :Robert Lightness
},
{"Paula Fruity etc.", :Paula Fruity, :Paula Flowery, :Paula Spicy, :Paula Crispness,
:Paula Tannin, :Paula Savory},
{"Monica Fruity etc.", :Monica Fruity, :Monica Flowery, :Monica Spicy, :Monica Tannin,
:Monica Alcohol, :Monica Savory, :Monica Lightness},
{"Frank Fruity etc.", :Frank Fruity, :Frank Flowery, :Frank Spicy, :Frank Crispness,
:Frank Tannin, :Frank Alcohol, :Frank Savory, :Frank Lightness}
)
);
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/Wine Sensory Data.jmp" );
dt << Multiple Factor Analysis(
Product ID( :Vineyard ),
Z( :Region ),
MFA Blocks(
{"Susan Fruity etc.", :Susan Fruity, :Susan Flowery, :Susan Spicy, :Susan Crispness},
{"Florence Flowery etc.", :Florence Flowery, :Florence Crispness, :Florence Tannin,
:Florence Savory, :Florence Lightness},
{"Xavier Fruity etc.", :Xavier Fruity, :Xavier Spicy, :Xavier Crispness,
:Xavier Alcohol, :Xavier Savory, :Xavier Lightness},
{"Robert Fruity etc.", :Robert Fruity, :Robert Flowery, :Robert Spicy,
:Robert Crispness, :Robert Tannin, :Robert Alcohol, :Robert Savory, :Robert Lightness
},
{"Paula Fruity etc.", :Paula Fruity, :Paula Flowery, :Paula Spicy, :Paula Crispness,
:Paula Tannin, :Paula Savory},
{"Monica Fruity etc.", :Monica Fruity, :Monica Flowery, :Monica Spicy, :Monica Tannin,
:Monica Alcohol, :Monica Savory, :Monica Lightness},
{"Frank Fruity etc.", :Frank Fruity, :Frank Flowery, :Frank Spicy, :Frank Crispness,
:Frank Tannin, :Frank Alcohol, :Frank Savory, :Frank Lightness}
)
);
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( "$SAMPLE_DATA/Wine Sensory Data.jmp" );
dt << Multiple Factor Analysis(
Product ID( :Vineyard ),
Z( :Region ),
MFA Blocks(
{"Susan Fruity etc.", :Susan Fruity, :Susan Flowery, :Susan Spicy, :Susan Crispness},
{"Florence Flowery etc.", :Florence Flowery, :Florence Crispness, :Florence Tannin,
:Florence Savory, :Florence Lightness},
{"Xavier Fruity etc.", :Xavier Fruity, :Xavier Spicy, :Xavier Crispness,
:Xavier Alcohol, :Xavier Savory, :Xavier Lightness},
{"Robert Fruity etc.", :Robert Fruity, :Robert Flowery, :Robert Spicy,
:Robert Crispness, :Robert Tannin, :Robert Alcohol, :Robert Savory, :Robert Lightness
},
{"Paula Fruity etc.", :Paula Fruity, :Paula Flowery, :Paula Spicy, :Paula Crispness,
:Paula Tannin, :Paula Savory},
{"Monica Fruity etc.", :Monica Fruity, :Monica Flowery, :Monica Spicy, :Monica Tannin,
:Monica Alcohol, :Monica Savory, :Monica Lightness},
{"Frank Fruity etc.", :Frank Fruity, :Frank Flowery, :Frank Spicy, :Frank Crispness,
:Frank Tannin, :Frank Alcohol, :Frank Savory, :Frank Lightness}
)
);
t = obj << Get Script With Data Table;
Show( t );
Get Timing
Syntax: obj << Get Timing
Description: Times the platform launch.
dt = Open( "$SAMPLE_DATA/Wine Sensory Data.jmp" );
dt << Multiple Factor Analysis(
Product ID( :Vineyard ),
Z( :Region ),
MFA Blocks(
{"Susan Fruity etc.", :Susan Fruity, :Susan Flowery, :Susan Spicy, :Susan Crispness},
{"Florence Flowery etc.", :Florence Flowery, :Florence Crispness, :Florence Tannin,
:Florence Savory, :Florence Lightness},
{"Xavier Fruity etc.", :Xavier Fruity, :Xavier Spicy, :Xavier Crispness,
:Xavier Alcohol, :Xavier Savory, :Xavier Lightness},
{"Robert Fruity etc.", :Robert Fruity, :Robert Flowery, :Robert Spicy,
:Robert Crispness, :Robert Tannin, :Robert Alcohol, :Robert Savory, :Robert Lightness
},
{"Paula Fruity etc.", :Paula Fruity, :Paula Flowery, :Paula Spicy, :Paula Crispness,
:Paula Tannin, :Paula Savory},
{"Monica Fruity etc.", :Monica Fruity, :Monica Flowery, :Monica Spicy, :Monica Tannin,
:Monica Alcohol, :Monica Savory, :Monica Lightness},
{"Frank Fruity etc.", :Frank Fruity, :Frank Flowery, :Frank Spicy, :Frank Crispness,
:Frank Tannin, :Frank Alcohol, :Frank Savory, :Frank Lightness}
)
);
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/Wine Sensory Data.jmp" );
dt << Multiple Factor Analysis(
Product ID( :Vineyard ),
Z( :Region ),
MFA Blocks(
{"Susan Fruity etc.", :Susan Fruity, :Susan Flowery, :Susan Spicy, :Susan Crispness},
{"Florence Flowery etc.", :Florence Flowery, :Florence Crispness, :Florence Tannin,
:Florence Savory, :Florence Lightness},
{"Xavier Fruity etc.", :Xavier Fruity, :Xavier Spicy, :Xavier Crispness,
:Xavier Alcohol, :Xavier Savory, :Xavier Lightness},
{"Robert Fruity etc.", :Robert Fruity, :Robert Flowery, :Robert Spicy,
:Robert Crispness, :Robert Tannin, :Robert Alcohol, :Robert Savory, :Robert Lightness
},
{"Paula Fruity etc.", :Paula Fruity, :Paula Flowery, :Paula Spicy, :Paula Crispness,
:Paula Tannin, :Paula Savory},
{"Monica Fruity etc.", :Monica Fruity, :Monica Flowery, :Monica Spicy, :Monica Tannin,
:Monica Alcohol, :Monica Savory, :Monica Lightness},
{"Frank Fruity etc.", :Frank Fruity, :Frank Flowery, :Frank Spicy, :Frank Crispness,
:Frank Tannin, :Frank Alcohol, :Frank Savory, :Frank Lightness}
)
);
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( "$SAMPLE_DATA/Wine Sensory Data.jmp" );
dt << New Column( "_bycol",
Character,
Nominal,
set values( Repeat( {"A", "B"}, N Rows( dt ) )[1 :: N Rows( dt )] )
);
dt << Multiple Factor Analysis(
Product ID( :Vineyard ),
Z( :Region ),
MFA Blocks(
{"Susan Fruity etc.", :Susan Fruity, :Susan Flowery, :Susan Spicy, :Susan Crispness},
{"Florence Flowery etc.", :Florence Flowery, :Florence Crispness, :Florence Tannin,
:Florence Savory, :Florence Lightness},
{"Xavier Fruity etc.", :Xavier Fruity, :Xavier Spicy, :Xavier Crispness,
:Xavier Alcohol, :Xavier Savory, :Xavier Lightness},
{"Robert Fruity etc.", :Robert Fruity, :Robert Flowery, :Robert Spicy,
:Robert Crispness, :Robert Tannin, :Robert Alcohol, :Robert Savory, :Robert Lightness
},
{"Paula Fruity etc.", :Paula Fruity, :Paula Flowery, :Paula Spicy, :Paula Crispness,
:Paula Tannin, :Paula Savory},
{"Monica Fruity etc.", :Monica Fruity, :Monica Flowery, :Monica Spicy, :Monica Tannin,
:Monica Alcohol, :Monica Savory, :Monica Lightness},
{"Frank Fruity etc.", :Frank Fruity, :Frank Flowery, :Frank Spicy, :Frank Crispness,
:Frank Tannin, :Frank Alcohol, :Frank Savory, :Frank Lightness}
),
By( _bycol )
);
obj[1] << Redo ByGroup Analysis;
Relaunch Analysis
Syntax: obj << Relaunch Analysis
Description: Opens the platform launch window and recalls the settings that were used to create the report.
dt = Open( "$SAMPLE_DATA/Wine Sensory Data.jmp" );
dt << Multiple Factor Analysis(
Product ID( :Vineyard ),
Z( :Region ),
MFA Blocks(
{"Susan Fruity etc.", :Susan Fruity, :Susan Flowery, :Susan Spicy, :Susan Crispness},
{"Florence Flowery etc.", :Florence Flowery, :Florence Crispness, :Florence Tannin,
:Florence Savory, :Florence Lightness},
{"Xavier Fruity etc.", :Xavier Fruity, :Xavier Spicy, :Xavier Crispness,
:Xavier Alcohol, :Xavier Savory, :Xavier Lightness},
{"Robert Fruity etc.", :Robert Fruity, :Robert Flowery, :Robert Spicy,
:Robert Crispness, :Robert Tannin, :Robert Alcohol, :Robert Savory, :Robert Lightness
},
{"Paula Fruity etc.", :Paula Fruity, :Paula Flowery, :Paula Spicy, :Paula Crispness,
:Paula Tannin, :Paula Savory},
{"Monica Fruity etc.", :Monica Fruity, :Monica Flowery, :Monica Spicy, :Monica Tannin,
:Monica Alcohol, :Monica Savory, :Monica Lightness},
{"Frank Fruity etc.", :Frank Fruity, :Frank Flowery, :Frank Spicy, :Frank Crispness,
:Frank Tannin, :Frank Alcohol, :Frank Savory, :Frank Lightness}
)
);
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( "$SAMPLE_DATA/Wine Sensory Data.jmp" );
dt << New Column( "_bycol",
Character,
Nominal,
set values( Repeat( {"A", "B"}, N Rows( dt ) )[1 :: N Rows( dt )] )
);
dt << Multiple Factor Analysis(
Product ID( :Vineyard ),
Z( :Region ),
MFA Blocks(
{"Susan Fruity etc.", :Susan Fruity, :Susan Flowery, :Susan Spicy, :Susan Crispness},
{"Florence Flowery etc.", :Florence Flowery, :Florence Crispness, :Florence Tannin,
:Florence Savory, :Florence Lightness},
{"Xavier Fruity etc.", :Xavier Fruity, :Xavier Spicy, :Xavier Crispness,
:Xavier Alcohol, :Xavier Savory, :Xavier Lightness},
{"Robert Fruity etc.", :Robert Fruity, :Robert Flowery, :Robert Spicy,
:Robert Crispness, :Robert Tannin, :Robert Alcohol, :Robert Savory, :Robert Lightness
},
{"Paula Fruity etc.", :Paula Fruity, :Paula Flowery, :Paula Spicy, :Paula Crispness,
:Paula Tannin, :Paula Savory},
{"Monica Fruity etc.", :Monica Fruity, :Monica Flowery, :Monica Spicy, :Monica Tannin,
:Monica Alcohol, :Monica Savory, :Monica Lightness},
{"Frank Fruity etc.", :Frank Fruity, :Frank Flowery, :Frank Spicy, :Frank Crispness,
:Frank Tannin, :Frank Alcohol, :Frank Savory, :Frank Lightness}
),
By( _bycol )
);
obj[1] << Relaunch ByGroup;
Remove Column Switcher
Syntax: obj << Remove Column Switcher
Description: Removes the most recent Column Switcher that has been added to the platform.
dt = Open( "$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( "$SAMPLE_DATA/Wine Sensory Data.jmp" );
dt << Multiple Factor Analysis(
Product ID( :Vineyard ),
Z( :Region ),
MFA Blocks(
{"Susan Fruity etc.", :Susan Fruity, :Susan Flowery, :Susan Spicy, :Susan Crispness},
{"Florence Flowery etc.", :Florence Flowery, :Florence Crispness, :Florence Tannin,
:Florence Savory, :Florence Lightness},
{"Xavier Fruity etc.", :Xavier Fruity, :Xavier Spicy, :Xavier Crispness,
:Xavier Alcohol, :Xavier Savory, :Xavier Lightness},
{"Robert Fruity etc.", :Robert Fruity, :Robert Flowery, :Robert Spicy,
:Robert Crispness, :Robert Tannin, :Robert Alcohol, :Robert Savory, :Robert Lightness
},
{"Paula Fruity etc.", :Paula Fruity, :Paula Flowery, :Paula Spicy, :Paula Crispness,
:Paula Tannin, :Paula Savory},
{"Monica Fruity etc.", :Monica Fruity, :Monica Flowery, :Monica Spicy, :Monica Tannin,
:Monica Alcohol, :Monica Savory, :Monica Lightness},
{"Frank Fruity etc.", :Frank Fruity, :Frank Flowery, :Frank Spicy, :Frank Crispness,
:Frank Tannin, :Frank Alcohol, :Frank Savory, :Frank Lightness}
)
);
r = obj << Report;
t = r[Outline Box( 1 )] << Get Title;
Show( t );
Report View
Syntax: obj << Report View( "Full"|"Summary" )
Description: The report view determines the level of detail visible in a platform report. Full shows all of the detail, while Summary shows only select content, dependent on the platform. For customized behavior, display boxes support a <<Set Summary Behavior message.
dt = Open( "$SAMPLE_DATA/Wine Sensory Data.jmp" );
dt << Multiple Factor Analysis(
Product ID( :Vineyard ),
Z( :Region ),
MFA Blocks(
{"Susan Fruity etc.", :Susan Fruity, :Susan Flowery, :Susan Spicy, :Susan Crispness},
{"Florence Flowery etc.", :Florence Flowery, :Florence Crispness, :Florence Tannin,
:Florence Savory, :Florence Lightness},
{"Xavier Fruity etc.", :Xavier Fruity, :Xavier Spicy, :Xavier Crispness,
:Xavier Alcohol, :Xavier Savory, :Xavier Lightness},
{"Robert Fruity etc.", :Robert Fruity, :Robert Flowery, :Robert Spicy,
:Robert Crispness, :Robert Tannin, :Robert Alcohol, :Robert Savory, :Robert Lightness
},
{"Paula Fruity etc.", :Paula Fruity, :Paula Flowery, :Paula Spicy, :Paula Crispness,
:Paula Tannin, :Paula Savory},
{"Monica Fruity etc.", :Monica Fruity, :Monica Flowery, :Monica Spicy, :Monica Tannin,
:Monica Alcohol, :Monica Savory, :Monica Lightness},
{"Frank Fruity etc.", :Frank Fruity, :Frank Flowery, :Frank Spicy, :Frank Crispness,
:Frank Tannin, :Frank Alcohol, :Frank Savory, :Frank Lightness}
)
);
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( "$SAMPLE_DATA/Wine Sensory Data.jmp" );
dt << New Column( "_bycol",
Character,
Nominal,
set values( Repeat( {"A", "B"}, N Rows( dt ) )[1 :: N Rows( dt )] )
);
dt << Multiple Factor Analysis(
Product ID( :Vineyard ),
Z( :Region ),
MFA Blocks(
{"Susan Fruity etc.", :Susan Fruity, :Susan Flowery, :Susan Spicy, :Susan Crispness},
{"Florence Flowery etc.", :Florence Flowery, :Florence Crispness, :Florence Tannin,
:Florence Savory, :Florence Lightness},
{"Xavier Fruity etc.", :Xavier Fruity, :Xavier Spicy, :Xavier Crispness,
:Xavier Alcohol, :Xavier Savory, :Xavier Lightness},
{"Robert Fruity etc.", :Robert Fruity, :Robert Flowery, :Robert Spicy,
:Robert Crispness, :Robert Tannin, :Robert Alcohol, :Robert Savory, :Robert Lightness
},
{"Paula Fruity etc.", :Paula Fruity, :Paula Flowery, :Paula Spicy, :Paula Crispness,
:Paula Tannin, :Paula Savory},
{"Monica Fruity etc.", :Monica Fruity, :Monica Flowery, :Monica Spicy, :Monica Tannin,
:Monica Alcohol, :Monica Savory, :Monica Lightness},
{"Frank Fruity etc.", :Frank Fruity, :Frank Flowery, :Frank Spicy, :Frank Crispness,
:Frank Tannin, :Frank Alcohol, :Frank Savory, :Frank Lightness}
),
By( _bycol )
);
obj[1] << Save ByGroup Script to Data Table;
Save ByGroup Script to Journal
Syntax: obj << Save ByGroup Script to Journal
Description: Create a JSL script to produce this analysis, and add a Button to the journal containing this script.
dt = Open( "$SAMPLE_DATA/Wine Sensory Data.jmp" );
dt << New Column( "_bycol",
Character,
Nominal,
set values( Repeat( {"A", "B"}, N Rows( dt ) )[1 :: N Rows( dt )] )
);
dt << Multiple Factor Analysis(
Product ID( :Vineyard ),
Z( :Region ),
MFA Blocks(
{"Susan Fruity etc.", :Susan Fruity, :Susan Flowery, :Susan Spicy, :Susan Crispness},
{"Florence Flowery etc.", :Florence Flowery, :Florence Crispness, :Florence Tannin,
:Florence Savory, :Florence Lightness},
{"Xavier Fruity etc.", :Xavier Fruity, :Xavier Spicy, :Xavier Crispness,
:Xavier Alcohol, :Xavier Savory, :Xavier Lightness},
{"Robert Fruity etc.", :Robert Fruity, :Robert Flowery, :Robert Spicy,
:Robert Crispness, :Robert Tannin, :Robert Alcohol, :Robert Savory, :Robert Lightness
},
{"Paula Fruity etc.", :Paula Fruity, :Paula Flowery, :Paula Spicy, :Paula Crispness,
:Paula Tannin, :Paula Savory},
{"Monica Fruity etc.", :Monica Fruity, :Monica Flowery, :Monica Spicy, :Monica Tannin,
:Monica Alcohol, :Monica Savory, :Monica Lightness},
{"Frank Fruity etc.", :Frank Fruity, :Frank Flowery, :Frank Spicy, :Frank Crispness,
:Frank Tannin, :Frank Alcohol, :Frank Savory, :Frank Lightness}
),
By( _bycol )
);
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( "$SAMPLE_DATA/Wine Sensory Data.jmp" );
dt << New Column( "_bycol",
Character,
Nominal,
set values( Repeat( {"A", "B"}, N Rows( dt ) )[1 :: N Rows( dt )] )
);
dt << Multiple Factor Analysis(
Product ID( :Vineyard ),
Z( :Region ),
MFA Blocks(
{"Susan Fruity etc.", :Susan Fruity, :Susan Flowery, :Susan Spicy, :Susan Crispness},
{"Florence Flowery etc.", :Florence Flowery, :Florence Crispness, :Florence Tannin,
:Florence Savory, :Florence Lightness},
{"Xavier Fruity etc.", :Xavier Fruity, :Xavier Spicy, :Xavier Crispness,
:Xavier Alcohol, :Xavier Savory, :Xavier Lightness},
{"Robert Fruity etc.", :Robert Fruity, :Robert Flowery, :Robert Spicy,
:Robert Crispness, :Robert Tannin, :Robert Alcohol, :Robert Savory, :Robert Lightness
},
{"Paula Fruity etc.", :Paula Fruity, :Paula Flowery, :Paula Spicy, :Paula Crispness,
:Paula Tannin, :Paula Savory},
{"Monica Fruity etc.", :Monica Fruity, :Monica Flowery, :Monica Spicy, :Monica Tannin,
:Monica Alcohol, :Monica Savory, :Monica Lightness},
{"Frank Fruity etc.", :Frank Fruity, :Frank Flowery, :Frank Spicy, :Frank Crispness,
:Frank Tannin, :Frank Alcohol, :Frank Savory, :Frank Lightness}
),
By( _bycol )
);
obj[1] << Save ByGroup Script to Script Window;
Save Script for All Objects
Syntax: obj << Save Script for All Objects
Description: Creates a script for all report objects in the window and appends it to the current Script window. This option is useful when you have multiple reports in the window.
dt = Open( "$SAMPLE_DATA/Wine Sensory Data.jmp" );
dt << Multiple Factor Analysis(
Product ID( :Vineyard ),
Z( :Region ),
MFA Blocks(
{"Susan Fruity etc.", :Susan Fruity, :Susan Flowery, :Susan Spicy, :Susan Crispness},
{"Florence Flowery etc.", :Florence Flowery, :Florence Crispness, :Florence Tannin,
:Florence Savory, :Florence Lightness},
{"Xavier Fruity etc.", :Xavier Fruity, :Xavier Spicy, :Xavier Crispness,
:Xavier Alcohol, :Xavier Savory, :Xavier Lightness},
{"Robert Fruity etc.", :Robert Fruity, :Robert Flowery, :Robert Spicy,
:Robert Crispness, :Robert Tannin, :Robert Alcohol, :Robert Savory, :Robert Lightness
},
{"Paula Fruity etc.", :Paula Fruity, :Paula Flowery, :Paula Spicy, :Paula Crispness,
:Paula Tannin, :Paula Savory},
{"Monica Fruity etc.", :Monica Fruity, :Monica Flowery, :Monica Spicy, :Monica Tannin,
:Monica Alcohol, :Monica Savory, :Monica Lightness},
{"Frank Fruity etc.", :Frank Fruity, :Frank Flowery, :Frank Spicy, :Frank Crispness,
:Frank Tannin, :Frank Alcohol, :Frank Savory, :Frank Lightness}
)
);
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( "$SAMPLE_DATA/Wine Sensory Data.jmp" );
dt << New Column( "_bycol",
Character,
Nominal,
set values( Repeat( {"A", "B"}, N Rows( dt ) )[1 :: N Rows( dt )] )
);
dt << Multiple Factor Analysis(
Product ID( :Vineyard ),
Z( :Region ),
MFA Blocks(
{"Susan Fruity etc.", :Susan Fruity, :Susan Flowery, :Susan Spicy, :Susan Crispness},
{"Florence Flowery etc.", :Florence Flowery, :Florence Crispness, :Florence Tannin,
:Florence Savory, :Florence Lightness},
{"Xavier Fruity etc.", :Xavier Fruity, :Xavier Spicy, :Xavier Crispness,
:Xavier Alcohol, :Xavier Savory, :Xavier Lightness},
{"Robert Fruity etc.", :Robert Fruity, :Robert Flowery, :Robert Spicy,
:Robert Crispness, :Robert Tannin, :Robert Alcohol, :Robert Savory, :Robert Lightness
},
{"Paula Fruity etc.", :Paula Fruity, :Paula Flowery, :Paula Spicy, :Paula Crispness,
:Paula Tannin, :Paula Savory},
{"Monica Fruity etc.", :Monica Fruity, :Monica Flowery, :Monica Spicy, :Monica Tannin,
:Monica Alcohol, :Monica Savory, :Monica Lightness},
{"Frank Fruity etc.", :Frank Fruity, :Frank Flowery, :Frank Spicy, :Frank Crispness,
:Frank Tannin, :Frank Alcohol, :Frank Savory, :Frank Lightness}
),
By( _bycol )
);
obj[1] << Save Script for All Objects To Data Table;
Example 2
dt = Open( "$SAMPLE_DATA/Wine Sensory Data.jmp" );
dt << New Column( "_bycol",
Character,
Nominal,
set values( Repeat( {"A", "B"}, N Rows( dt ) )[1 :: N Rows( dt )] )
);
dt << Multiple Factor Analysis(
Product ID( :Vineyard ),
Z( :Region ),
MFA Blocks(
{"Susan Fruity etc.", :Susan Fruity, :Susan Flowery, :Susan Spicy, :Susan Crispness},
{"Florence Flowery etc.", :Florence Flowery, :Florence Crispness, :Florence Tannin,
:Florence Savory, :Florence Lightness},
{"Xavier Fruity etc.", :Xavier Fruity, :Xavier Spicy, :Xavier Crispness,
:Xavier Alcohol, :Xavier Savory, :Xavier Lightness},
{"Robert Fruity etc.", :Robert Fruity, :Robert Flowery, :Robert Spicy,
:Robert Crispness, :Robert Tannin, :Robert Alcohol, :Robert Savory, :Robert Lightness
},
{"Paula Fruity etc.", :Paula Fruity, :Paula Flowery, :Paula Spicy, :Paula Crispness,
:Paula Tannin, :Paula Savory},
{"Monica Fruity etc.", :Monica Fruity, :Monica Flowery, :Monica Spicy, :Monica Tannin,
:Monica Alcohol, :Monica Savory, :Monica Lightness},
{"Frank Fruity etc.", :Frank Fruity, :Frank Flowery, :Frank Spicy, :Frank Crispness,
:Frank Tannin, :Frank Alcohol, :Frank Savory, :Frank Lightness}
),
By( _bycol )
);
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( "$SAMPLE_DATA/Wine Sensory Data.jmp" );
dt << Multiple Factor Analysis(
Product ID( :Vineyard ),
Z( :Region ),
MFA Blocks(
{"Susan Fruity etc.", :Susan Fruity, :Susan Flowery, :Susan Spicy, :Susan Crispness},
{"Florence Flowery etc.", :Florence Flowery, :Florence Crispness, :Florence Tannin,
:Florence Savory, :Florence Lightness},
{"Xavier Fruity etc.", :Xavier Fruity, :Xavier Spicy, :Xavier Crispness,
:Xavier Alcohol, :Xavier Savory, :Xavier Lightness},
{"Robert Fruity etc.", :Robert Fruity, :Robert Flowery, :Robert Spicy,
:Robert Crispness, :Robert Tannin, :Robert Alcohol, :Robert Savory, :Robert Lightness
},
{"Paula Fruity etc.", :Paula Fruity, :Paula Flowery, :Paula Spicy, :Paula Crispness,
:Paula Tannin, :Paula Savory},
{"Monica Fruity etc.", :Monica Fruity, :Monica Flowery, :Monica Spicy, :Monica Tannin,
:Monica Alcohol, :Monica Savory, :Monica Lightness},
{"Frank Fruity etc.", :Frank Fruity, :Frank Flowery, :Frank Spicy, :Frank Crispness,
:Frank Tannin, :Frank Alcohol, :Frank Savory, :Frank Lightness}
)
);
obj << Save Script to Data Table( "My Analysis", <<Prompt( 0 ), <<Replace( 0 ) );
Save Script to Journal
Syntax: obj << Save Script to Journal
Description: Create a JSL script to produce this analysis, and add a Button to the journal containing this script.
dt = Open( "$SAMPLE_DATA/Wine Sensory Data.jmp" );
dt << Multiple Factor Analysis(
Product ID( :Vineyard ),
Z( :Region ),
MFA Blocks(
{"Susan Fruity etc.", :Susan Fruity, :Susan Flowery, :Susan Spicy, :Susan Crispness},
{"Florence Flowery etc.", :Florence Flowery, :Florence Crispness, :Florence Tannin,
:Florence Savory, :Florence Lightness},
{"Xavier Fruity etc.", :Xavier Fruity, :Xavier Spicy, :Xavier Crispness,
:Xavier Alcohol, :Xavier Savory, :Xavier Lightness},
{"Robert Fruity etc.", :Robert Fruity, :Robert Flowery, :Robert Spicy,
:Robert Crispness, :Robert Tannin, :Robert Alcohol, :Robert Savory, :Robert Lightness
},
{"Paula Fruity etc.", :Paula Fruity, :Paula Flowery, :Paula Spicy, :Paula Crispness,
:Paula Tannin, :Paula Savory},
{"Monica Fruity etc.", :Monica Fruity, :Monica Flowery, :Monica Spicy, :Monica Tannin,
:Monica Alcohol, :Monica Savory, :Monica Lightness},
{"Frank Fruity etc.", :Frank Fruity, :Frank Flowery, :Frank Spicy, :Frank Crispness,
:Frank Tannin, :Frank Alcohol, :Frank Savory, :Frank Lightness}
)
);
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( "$SAMPLE_DATA/Wine Sensory Data.jmp" );
dt << Multiple Factor Analysis(
Product ID( :Vineyard ),
Z( :Region ),
MFA Blocks(
{"Susan Fruity etc.", :Susan Fruity, :Susan Flowery, :Susan Spicy, :Susan Crispness},
{"Florence Flowery etc.", :Florence Flowery, :Florence Crispness, :Florence Tannin,
:Florence Savory, :Florence Lightness},
{"Xavier Fruity etc.", :Xavier Fruity, :Xavier Spicy, :Xavier Crispness,
:Xavier Alcohol, :Xavier Savory, :Xavier Lightness},
{"Robert Fruity etc.", :Robert Fruity, :Robert Flowery, :Robert Spicy,
:Robert Crispness, :Robert Tannin, :Robert Alcohol, :Robert Savory, :Robert Lightness
},
{"Paula Fruity etc.", :Paula Fruity, :Paula Flowery, :Paula Spicy, :Paula Crispness,
:Paula Tannin, :Paula Savory},
{"Monica Fruity etc.", :Monica Fruity, :Monica Flowery, :Monica Spicy, :Monica Tannin,
:Monica Alcohol, :Monica Savory, :Monica Lightness},
{"Frank Fruity etc.", :Frank Fruity, :Frank Flowery, :Frank Spicy, :Frank Crispness,
:Frank Tannin, :Frank Alcohol, :Frank Savory, :Frank Lightness}
)
);
obj << Save Script to Report;
Save Script to Script Window
Syntax: obj << Save Script to Script Window
Description: Create a JSL script to produce this analysis, and append it to the current Script text window.
dt = Open( "$SAMPLE_DATA/Wine Sensory Data.jmp" );
dt << Multiple Factor Analysis(
Product ID( :Vineyard ),
Z( :Region ),
MFA Blocks(
{"Susan Fruity etc.", :Susan Fruity, :Susan Flowery, :Susan Spicy, :Susan Crispness},
{"Florence Flowery etc.", :Florence Flowery, :Florence Crispness, :Florence Tannin,
:Florence Savory, :Florence Lightness},
{"Xavier Fruity etc.", :Xavier Fruity, :Xavier Spicy, :Xavier Crispness,
:Xavier Alcohol, :Xavier Savory, :Xavier Lightness},
{"Robert Fruity etc.", :Robert Fruity, :Robert Flowery, :Robert Spicy,
:Robert Crispness, :Robert Tannin, :Robert Alcohol, :Robert Savory, :Robert Lightness
},
{"Paula Fruity etc.", :Paula Fruity, :Paula Flowery, :Paula Spicy, :Paula Crispness,
:Paula Tannin, :Paula Savory},
{"Monica Fruity etc.", :Monica Fruity, :Monica Flowery, :Monica Spicy, :Monica Tannin,
:Monica Alcohol, :Monica Savory, :Monica Lightness},
{"Frank Fruity etc.", :Frank Fruity, :Frank Flowery, :Frank Spicy, :Frank Crispness,
:Frank Tannin, :Frank Alcohol, :Frank Savory, :Frank Lightness}
)
);
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( "$SAMPLE_DATA/Wine Sensory Data.jmp" );
dt << Multiple Factor Analysis(
Product ID( :Vineyard ),
Z( :Region ),
MFA Blocks(
{"Susan Fruity etc.", :Susan Fruity, :Susan Flowery, :Susan Spicy, :Susan Crispness},
{"Florence Flowery etc.", :Florence Flowery, :Florence Crispness, :Florence Tannin,
:Florence Savory, :Florence Lightness},
{"Xavier Fruity etc.", :Xavier Fruity, :Xavier Spicy, :Xavier Crispness,
:Xavier Alcohol, :Xavier Savory, :Xavier Lightness},
{"Robert Fruity etc.", :Robert Fruity, :Robert Flowery, :Robert Spicy,
:Robert Crispness, :Robert Tannin, :Robert Alcohol, :Robert Savory, :Robert Lightness
},
{"Paula Fruity etc.", :Paula Fruity, :Paula Flowery, :Paula Spicy, :Paula Crispness,
:Paula Tannin, :Paula Savory},
{"Monica Fruity etc.", :Monica Fruity, :Monica Flowery, :Monica Spicy, :Monica Tannin,
:Monica Alcohol, :Monica Savory, :Monica Lightness},
{"Frank Fruity etc.", :Frank Fruity, :Frank Flowery, :Frank Spicy, :Frank Crispness,
:Frank Tannin, :Frank Alcohol, :Frank Savory, :Frank Lightness}
)
);
obj << Title( "My Platform" );
Top Report
Syntax: obj << Top Report
Description: Returns a reference to the root node in the report.
dt = Open( "$SAMPLE_DATA/Wine Sensory Data.jmp" );
dt << Multiple Factor Analysis(
Product ID( :Vineyard ),
Z( :Region ),
MFA Blocks(
{"Susan Fruity etc.", :Susan Fruity, :Susan Flowery, :Susan Spicy, :Susan Crispness},
{"Florence Flowery etc.", :Florence Flowery, :Florence Crispness, :Florence Tannin,
:Florence Savory, :Florence Lightness},
{"Xavier Fruity etc.", :Xavier Fruity, :Xavier Spicy, :Xavier Crispness,
:Xavier Alcohol, :Xavier Savory, :Xavier Lightness},
{"Robert Fruity etc.", :Robert Fruity, :Robert Flowery, :Robert Spicy,
:Robert Crispness, :Robert Tannin, :Robert Alcohol, :Robert Savory, :Robert Lightness
},
{"Paula Fruity etc.", :Paula Fruity, :Paula Flowery, :Paula Spicy, :Paula Crispness,
:Paula Tannin, :Paula Savory},
{"Monica Fruity etc.", :Monica Fruity, :Monica Flowery, :Monica Spicy, :Monica Tannin,
:Monica Alcohol, :Monica Savory, :Monica Lightness},
{"Frank Fruity etc.", :Frank Fruity, :Frank Flowery, :Frank Spicy, :Frank Crispness,
:Frank Tannin, :Frank Alcohol, :Frank Savory, :Frank Lightness}
)
);
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 = Multiple Factor Analysis(...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" ) ) )
);