IML Workshop 2.0

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IML Workshop 2.0
May 21, 2003 Charlie Hallahan
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IML Workshop Programming Environment

• Program editor, output window, error log window
• Program editor color-codes IML syntax
• Editable output window
• Multiple independent program environments
• Multithreaded
• these notes are based on a tutorial at SUGI 28
  presented by
• Simon Smith and Rick Wicklin of SAS Institute

Demo
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The IML Workshop Environment
Plot window
Program editor
Data table window
Output window
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Programming with IMLPlus

• Use same syntax as for PROC IML
• Execute data/procedure steps from PROC IML
• Create high-level statistical graphics
• Call modules without explicitly loading them
• Call external functions written in C/Fortran/Java

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Graphics Programming with IMLPlus

• Create and manipulate graphics using objects
• Use declare statement to define variables that
  refer to objects
• declare
  ScatterPlot plot
• Call Create method to construct new object
• plot
  ScatterPlot.Create(Example, x, y)
• Use dot syntax to invoke methods
• plot.ShowAxisReferenceLine
  s(YAXIS)

Demo
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Creating a Scatter Plot
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Creating Graphs Using IMLPlus, Part 1
/ BasicGraphs2.iml / x 1200 e 30
normal( x ) y x e declare ScatterPlot
splot splot ScatterPlot.Create( "Example", x,
y ) declare Histogram hist hist
Histogram.Create( "Error Distribution", e ) ?
These graphs are not dynamically linked.
Demo
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Unlinked Scatter Plot and Histogram
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Dynamic Linking Infrastructure

• DataObject and DataView classes are the backbone
• DataObject contains the data being displayed
• DataView renders the data in a specific way

ScatterPlot Histogram
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The DataObject Class

• Methods for adding data from matrices
• Methods for loading SAS data sets
• Methods for accessing data/metadata
• Every graph is based on a DataObject

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The DataView Class Hierarchy
DataView DataTable
Plot Plot2D
BarChart
BoxPlot
ContourPlot
Histogram
LinePlot
MosaicPlot
PolygonPlot
ScatterPlot Plot3D
RotatingPlot
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Creating Graphs Using IMLPlus, Part 2
/ BasicGraphs3.iml / x 1200 e 30
normal( x ) y x e declare DataObject
dobj dobj DataObject.Create( "Data", "X",
"Y", "E", xye ) declare ScatterPlot
splot splot ScatterPlot.Create( dobj, "X", "Y"
) declare Histogram hist hist
Histogram.Create( dobj, "E" )
? These graphs are dynamically linked.
Demo
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Linked Scatter Plot and Histogram
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Color-Coding Observations by Interval Data
colormatrix 255 0 0, 255 255
0, 255 0 0 run
ColorCode(dobj,"E",colormatrix,9) splot.SetMarker
Size(7)
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Color-Coding Observations by Interval Data
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IMLPlus Module Library

• Collection of prewritten modules
• Similar to IMLMLIB modules
• DrawLegend module adds legends to a graph
• DoDialog and DoMessageBox modules enable
• interaction with the user

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Graphing Data Stored in SAS Data Sets
declare DataObject dobj dobj
DataObject.CreateFromFile("Business.sas7bdat") de
clare ScatterPlot plot plot ScatterPlot.Create(
dobj,"Sales","Profits") plot.SetObsLabelVar("Comp
any")
Demo
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Graphing Data Stored in SAS Data Sets
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Creating Graphs Using the GUI

• Use File menu to open SAS data set (data table
  appears)
• Use Plot menu to create graphs
• Can use graphs GUI to customize appearance
• Can copy and paste graphs into other Windows
  apps

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Creating Graphs Using the GUI
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Modifying Graph Properties Using GUI

• Graph window divided into Plot Area and Graph
  Area
• Right-click area to change properties
• Right-click axis to modify axis properties
• Right-click axis title to change text/font

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Modifying Graph Properties Using GUI
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Local Selection

• Technique for using graphs to filter data
• Terminology Selector view, Observer view
• Each graph is either Selector view or Observer
  view
• Selector views enable user to select
  observations
• Observer views display either union or
  intersection
• of selections

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Local Selection Basics
Selector view ?
? Observer view (intersection)
Selector view ?
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Executing Procedures from IMLPlus

• Execute any SAS statements from IMLPlus
• Use submit and endsubmit statements to
  delineate
• SAS code block
• Use data sets to pass data
• Write modules that use procedures

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IMLPlus Module to Compute Skewness
/ CalcSkewness.iml / start CalcSkewness( x
) create InputDataSet var x append
close InputDataSet submit proc
univariate dataInputDataSet noprint var
x output outOutputDataSet
skewnessskewness quit endsubmit
use OutputDataSet read var skewness
close OutputDataSet return
(skewness) finish v 2, 4, 6, 3, 1 y
CalcSkewness( v ) print y
Output Y 0.5901287
Demo
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Putting the Pieces Together

• Filtering Data Using Graphics
• Interacting with Programs
• Integrating Statistical Results and Graphics

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Interacting with Programs
? Choose aspects of analysis at run-time ?
Data sets, parameters, PROC options, ?
Display dialog boxes to prompt for input ?
Present menu of choices for analysis
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Interacting with Programs
/ SummaryStatsCalculator.iml This program
allows you to choose a data set to select a
numeric variable of interest, and to see
summary statistics for that variable. The
statistics are MIN, MAX, N, NMISS MEDIAN, MEAN,
STD, and SUM / run GetPersonalFilesDirectory(
path ) dir path "Data Sets" ok
DoDialogGetOpenDataSetFileName( dataset, "Choose
a Data Set", dir ) if okfalse then do reset
log print "Abort. No data set chosen."
abort end declare DataObject dobj dobj
DataObject.CreateFromFile( dataset )
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Interacting with Programs
/ get list of numerical variables / numVars
dobj.GetNumVar() varNames j(numVars,1,"
")/ length 32 / do i
1 to numVars name dobj.GetVarName(i) if
dobj.IsNumeric(name) then varNamesi
name end numericVarIndex loc( varNames " "
) numNumericVars ncol( numericVarIndex ) if
numNumericVars0 then do reset log print
"Abort. The data set does not contain",
"any numeric variables. Abort" abort end
varNames varNamesnumericVarIndex
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Interacting with Programs
/ display list in a dialog / ok
DoDialogGetListItem( selection, "Numeric
Variables", "Choose a variable to display
summary statistics", varNames ) varName
varNamesselection dobj.GetVarData( varName, x
) statNames 'MIN', 'MAX', 'N',
'NMISS', 'MEDIAN', 'MEAN', 'STD',
'SUM' stats j(8,1,.) stats1 min( x
) stats2 max( x ) stats3 nrow( x
) stats4 ncol( loc(x.) ) stats5
median( x ) stats6 x
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Interacting with Programs
nonMissing stats3-stats4 / N - NMISS
/ if nonMissing gt 1 then do xCenter x -
stats6 stats7 sqrt( xCenter /
(nonMissing-1) ) end stats8 sum( x
) print statsrownamestatNames
colnamevarName if dobj.IsNominal(varName)
then BarChart.Create( dobj, varName ) else
Histogram.Create( dobj, varName )
Demo
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Interacting with Programs
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Interacting with Programs
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Interacting with Programs
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Integrating Statistical Results and Graphics

• Call procedures in other SAS products without
  losing
• state of IML program.
• Read results into IML Workshop
• Use results in program or to augment graph
• Example Add nonparametric smoother with
  confidence
• limits to ScatterPlot

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Add Kernel Density Estimation to Histogram
/ KDE.iml create a histogram / declare
DataObject dobj dobj DataObject.CreateFromFile(
"Colleges.sas7bdat" ) declare Histogram
hist hist Histogram.Create( dobj, "RoomBd"
) hist.ShowDensity() / default is frequency
/ / set up libref to data set directory / run
GetPersonalFilesDirectory( dir ) dir dir
"Data Sets" dir "d\charlie\iml
Workshop" libname dataDir (dir)
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Add Kernel Density Estimation to Histogram
/ compute kernel density estimation / / This
KDE syntax is for SAS 8.2 / submit ods
exclude all / turn off printing / proc kde
datadataDir.Colleges outKDEOut var RoomBd
quit endsubmit / read the output from the
KDE procedure / use KDEOut read all varRoomBd
density close KDEOut / overlay on existing
Histogram of RoomBd / hist.DrawUseDataCoordinates
() hist.DrawLine( RoomBd, density )
Demo
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Add Kernel Density Estimation to Histogram
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Add Nonparametric Smoother to ScatterPlot
/ TPSpline.iml / / set up libref to data
set directory / run GetPersonalFilesDirectory(
dir ) dir dir "Data Sets" dir
"d\Charlie\IML Workshop" libname dataDir
(dir) / pred thin plate spline and ask for
95 confidence limits for the predicted mean.
/ submit ods exclude DataSummary FitSummary
FitStatistics proc tpspline
datadataDir.Colleges(where(PubPriv1))
model PctPhD(SAT) output outpred predicted
lclm uclm quit endsubmit / read work.pred
/ declare DataObject dobj dobj
DataObject.CreateFromServerDataSet( "work.pred" )
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Add Nonparametric Smoother to ScatterPlot
/ manufacture names output by proc / xVar
"SAT" yVar "PctPhD" predName "p_"
yVar lclName "lclm_" yVar uclName "uclm_"
yVar / create scatter plot of Y versus X
/ declare ScatterPlot plot plot
ScatterPlot.Create( dobj, xVar, yVar
) plot.SetAxisViewRange(YAXIS, 0, 100) / get
predicted values and confidence limits
/ dobj.Sort( xVar ) dobj.GetVarData( xVar, x
) dobj.GetVarData( predName, pred
) dobj.GetVarData( lclName, lower95
) dobj.GetVarData( uclName, upper95 )
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Add Nonparametric Smoother to ScatterPlot
/ plot the predicted pred in red
/ plot.DrawUseDataCoordinates() plot.DrawSetPenC
olor( RED ) plot.DrawLine( x, pred ) / plot
the confidence limits in blue / plot.DrawSetPenCo
lor( BLUE ) plot.DrawLine( x, lower95
) plot.DrawLine( x, upper95 ) / Add legend at
Inside Right Bottom position / labels
"Predicted" "95 Lower CLM" "95 Upper CLM"
colors RED BLUE BLUE run
DrawLegend( plot, labels, 14, colors,
SOLID, NULL, -1, "IRB" )
Demo
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Add Nonparametric Smoother to ScatterPlot