ICLUST.graph: create control code for ICLUST graphical output

Description

Given a cluster structure determined by ICLUST, create dot code to describe the ICLUST output. To use the dot code, use either http://www.graphviz.org/ Graphviz or a commercial viewer (e.g., OmniGraffle). This function parallels ICLUST.rgraph which uses Rgraphviz.

Usage

ICLUST.graph(ic.results, out.file,min.size=1, short = FALSE,labels=NULL,
size = c(8, 6), node.font = c("Helvetica", 14), edge.font = c("Helvetica", 12), 
 rank.direction=c("RL","TB","LR","BT"), digits = 2, title = "ICLUST", ...)

Arguments

ic.results

output list from ICLUST

out.file

name of output file (defaults to console)

min.size

draw a smaller node (without all the information) for clusters < min.size -- useful for large problems

short

if short==TRUE, don't use variable names

labels

vector of text labels (contents) for the variables

size

size of output

node.font

Font to use for nodes in the graph

edge.font

Font to use for the labels of the arrows (edges)

rank.direction

LR or RL

digits

number of digits to show

title

any title

...

other options to pass

Value

Output is a set of dot commands written either to console or to the output file. These commands may then be used as input to any "dot" viewer, e.g., Graphviz.

Details

Will create (or overwrite) an output file and print out the dot code to show a cluster structure. This dot file may be imported directly into a dot viewer (e.g., http://www.graphviz.org/). The "dot" language is a powerful graphic description language that is particulary appropriate for viewing cluster output. Commercial graphics programs (e.g., OmniGraffle) can also read (and clean up) dot files. ICLUST.graph takes the output from ICLUST results and processes it to provide a pretty picture of the results. Original variables shown as rectangles and ordered on the left hand side (if rank direction is RL) of the graph. Clusters are drawn as ellipses and include the alpha, beta, and size of the cluster. Edges show the cluster intercorrelations.

It is possible to trim the output to not show all cluster information. Clusters < min.size are shown as small ovals without alpha, beta, and size information.

Although it would be nice to process the dot code directly in R, the Rgraphviz package is difficult to use on all platforms and thus the dot code is written directly.

References

ICLUST: http://personality-project.org/r/r.iclust.html

Examples

Run this code

test.data <- Harman74.cor$cov
ic.out <- ICLUST(test.data)
out.file <- file.choose(new=TRUE)   #create a new file to write the plot commands to 
ICLUST.graph(ic.out,out.file)   
now go to graphviz (outside of R) and open the out.file you created
print(ic.out,digits=2)

 
#test.data <- Harman74.cor$cov 
#my.iclust <- ICLUST(test.data)
#ICLUST.graph(my.iclust)
#
#
#digraph ICLUST {
#  rankdir=RL;
#  size="8,8";
#  node [fontname="Helvetica" fontsize=14 shape=box, width=2];
#  edge [fontname="Helvetica" fontsize=12];
# label = "ICLUST";
#	fontsize=20;
#V1  [label = VisualPerception];
#V2  [label = Cubes];
#V3  [label = PaperFormBoard];
#V4  [label = Flags];
#V5  [label = GeneralInformation];
#V6  [label = PargraphComprehension];
#V7  [label = SentenceCompletion];
#V8  [label = WordClassification];
#V9  [label = WordMeaning];
#V10  [label = Addition];
#V11  [label = Code];
#V12  [label = CountingDots];
#V13  [label = StraightCurvedCapitals];
#V14  [label = WordRecognition];
#V15  [label = NumberRecognition];
#V16  [label = FigureRecognition];
#V17  [label = ObjectNumber];
#V18  [label = NumberFigure];
#V19  [label = FigureWord];
#V20  [label = Deduction];
#V21  [label = NumericalPuzzles];
#V22  [label = ProblemReasoning];
#V23  [label = SeriesCompletion];
#V24  [label = ArithmeticProblems];
#node [shape=ellipse, width ="1"];
#C1-> V9 [ label = 0.78 ];
#C1-> V5 [ label = 0.78 ];
#C2-> V12 [ label = 0.66 ];
#C2-> V10 [ label = 0.66 ];
#C3-> V18 [ label = 0.53 ];
#C3-> V17 [ label = 0.53 ];
#C4-> V23 [ label = 0.59 ];
#C4-> V20 [ label = 0.59 ];
#C5-> V13 [ label = 0.61 ];
#C5-> V11 [ label = 0.61 ];
#C6-> V7 [ label = 0.78 ];
#C6-> V6 [ label = 0.78 ];
#C7-> V4 [ label = 0.55 ];
#C7-> V1 [ label = 0.55 ];
#C8-> V16 [ label = 0.5 ];
#C8-> V14 [ label = 0.49 ];
#C9-> C1 [ label = 0.86 ];
#C9-> C6 [ label = 0.86 ];
#C10-> C4 [ label = 0.71 ];
#C10-> V22 [ label = 0.62 ];
#C11-> V21 [ label = 0.56 ];
#C11-> V24 [ label = 0.58 ];
#C12-> C10 [ label = 0.76 ];
#C12-> C11 [ label = 0.67 ];
#C13-> C8 [ label = 0.61 ];
#C13-> V15 [ label = 0.49 ];
#C14-> C2 [ label = 0.74 ];
#C14-> C5 [ label = 0.72 ];
#C15-> V3 [ label = 0.48 ];
#C15-> C7 [ label = 0.65 ];
#C16-> V19 [ label = 0.48 ];
#C16-> C3 [ label = 0.64 ];
#C17-> V8 [ label = 0.62 ];
#C17-> C12 [ label = 0.8 ];
#C18-> C17 [ label = 0.82 ];
#C18-> C15 [ label = 0.68 ];
#C19-> C16 [ label = 0.66 ];
#C19-> C13 [ label = 0.65 ];
#C20-> C19 [ label = 0.72 ];
#C20-> C18 [ label = 0.83 ];
#C21-> C20 [ label = 0.87 ];
#C21-> C9 [ label = 0.76 ];
#C22-> 0 [ label = 0 ];
#C22-> 0 [ label = 0 ];
#C23-> 0 [ label = 0 ];
#C23-> 0 [ label = 0 ];
#C1  [label =   "C1\n  alpha= 0.84\n beta=  0.84\nN= 2"] ;
#C2  [label =   "C2\n  alpha= 0.74\n beta=  0.74\nN= 2"] ;
#C3  [label =   "C3\n  alpha= 0.62\n beta=  0.62\nN= 2"] ;
#C4  [label =   "C4\n  alpha= 0.67\n beta=  0.67\nN= 2"] ;
#C5  [label =   "C5\n  alpha= 0.7\n beta=  0.7\nN= 2"] ;
#C6  [label =   "C6\n  alpha= 0.84\n beta=  0.84\nN= 2"] ;
#C7  [label =   "C7\n  alpha= 0.64\n beta=  0.64\nN= 2"] ;
#C8  [label =   "C8\n  alpha= 0.58\n beta=  0.58\nN= 2"] ;
#C9  [label =   "C9\n  alpha= 0.9\n beta=  0.87\nN= 4"] ;
#C10  [label =   "C10\n  alpha= 0.74\n beta=  0.71\nN= 3"] ;
#C11  [label =   "C11\n  alpha= 0.62\n beta=  0.62\nN= 2"] ;
#C12  [label =   "C12\n  alpha= 0.79\n beta=  0.74\nN= 5"] ;
#C13  [label =   "C13\n  alpha= 0.64\n beta=  0.59\nN= 3"] ;
#C14  [label =   "C14\n  alpha= 0.79\n beta=  0.74\nN= 4"] ;
#C15  [label =   "C15\n  alpha= 0.66\n beta=  0.58\nN= 3"] ;
#C16  [label =   "C16\n  alpha= 0.65\n beta=  0.57\nN= 3"] ;
#C17  [label =   "C17\n  alpha= 0.81\n beta=  0.71\nN= 6"] ;
#C18  [label =   "C18\n  alpha= 0.84\n beta=  0.75\nN= 9"] ;
#C19  [label =   "C19\n  alpha= 0.74\n beta=  0.65\nN= 6"] ;
#C20  [label =   "C20\n  alpha= 0.87\n beta=  0.74\nN= 15"] ;
#C21  [label =   "C21\n  alpha= 0.9\n beta=  0.77\nN= 19"] ;
#C22  [label =   "C22\n  alpha= 0\n beta=  0\nN= 0"] ;
#C23  [label =   "C23\n  alpha= 0\n beta=  0\nN= 0"] ;
#{ rank=same;
#V1;V2;V3;V4;V5;V6;V7;V8;V9;V10;V11;V12;V13;V14;V15;V16;V17;V18;V19;V20;V21;V22;V23;V24;}}
#
#copy the above output to Graphviz and draw it
#see \url{http://personality-project.org/r/r.ICLUST.html} for an example.

Run the code above in your browser using DataLab

Get 50% off unlimited learning