\name{ICLUST.graph}
\alias{ICLUST.graph}
\alias{iclust.graph}
\title{ create control code for ICLUST graphical output}
\description{Given a cluster structure determined by \code{\link{ICLUST}}, create dot code to describe the \code{\link{ICLUST}} output.  To use the dot code, use either https://www.graphviz.org/ Graphviz or a commercial viewer (e.g., OmniGraffle).  This function parallels \code{\link{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", ...)
}
%- maybe also 'usage' for other objects documented here.
\arguments{
  \item{ic.results}{output list from ICLUST }
  \item{out.file}{ name of output file (defaults to console) }
  \item{min.size}{draw a smaller node (without all the information) for clusters < min.size -- useful for large problems}
  \item{short}{if short==TRUE, don't use variable names}
  \item{labels}{vector of text labels (contents) for the variables}
  \item{size}{size of output }
  \item{node.font}{ Font to use for nodes in the graph }
  \item{edge.font}{ Font to use for the labels of the arrows (edges)}
  \item{rank.direction}{LR or RL  }
  \item{digits}{ number of digits to show }
  \item{title}{ any title }
  \item{\dots}{ other options to pass }
}
\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.,  https://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 \code{\link{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.

}

\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.
}
\references{ ICLUST: \url{https://personality-project.org/r/r.ICLUST.html}}
\author{
 \email{revelle@northwestern.edu } \cr
 \url{https://personality-project.org/revelle.html}}

\seealso{  \code{\link{VSS.plot}},  \code{\link{ICLUST}}}
\examples{
\dontrun{
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{https://personality-project.org/r/r.ICLUST.html} for an example.

}

\keyword{multivariate }%
\keyword{cluster}% 
\keyword{hplot}