Nothing
cutforest <- function(b, k = NULL, h = NULL)
{
if (is.null(k) && is.null(h))
stop("either 'k' or 'h' must be specified")
rdend<-list( "merge"=b$merge[b$row_col==0,],
"height"=b$height[b$row_col==0],
"order"= b$row_order,
"method"="ward",
"dist.method"="euclidean");
class(rdend)<-"hclust";
#cutree(rdend, k=3)
#rdend<- as.dendrogram(rdend)
#b$row_order<- order.dendrogram(rdend)
cdend<-list( "merge"=b$merge[b$row_col==1,],
"height"=b$height[b$row_col==1],
"order"= b$col_order,
"method"="ward",
"dist.method"="euclidean");
class(cdend)<-"hclust";
# cdend<- as.dendrogram(cdend)
# b$col_order<- order.dendrogram(cdend)
if ( is.null(h) )
{
i=1
trow=b$dim[1];
tcol=b$dim[2];
while((trow*tcol)>k)
{
if((b$row_col[i]==0) && (trow>1))
trow=trow-1;
if((b$row_col[i]==1) && (tcol>1))
tcol=tcol-1;
i=i+1
}
rind=cutree(rdend, k=trow)
cind=cutree(cdend, k=tcol)
}
else
{
rind=cutree(rdend, h=h)
cind=cutree(cdend, h=h)
}
if(is.null(b$row_name))
row.group <- rind
else
row.group <- data.frame(b$row_name, rind)
if(is.null(b$col_name))
col.group <- cind
else
col.group <- data.frame(b$col_name, cind)
#CIL=clusterimpBF(b, rind, cind)
#CIB=clusterimpact(b, rind, cind)
groups <- list("Row_grouping"=row.group, "Col_grouping"= col.group)
#######################
# par(mfrow=c(2,2))
# barplot(CIL$row_likelihood[1,], col = heat.colors(length(rind)), main = "rows impact", ylab = "Log Bayes factor")
# barplot(CIL$row_likelihood[2,], col = heat.colors(length(rind)), main = "row clusters impact", ylab = "Log Bayes factor")
# barplot(CIB$row_likelihood[1,]/sum(CIB$row_likelihood[1,]), col = heat.colors(length(rind)), main = "rows impact", ylab = "between sum of square")
# barplot(CIB$row_likelihood[2,]/sum(unique(CIB$row_likelihood[2,])), col = heat.colors(length(rind)), main = "row clusters impact", ylab = "between sum of square")
# dev.new()
# par(mfrow=c(2,2))
# barplot(CIL$col_likelihood[1,], col = heat.colors(length(cind)), main = "cols impact", ylab = "Log Bayes factor")
# barplot(CIL$col_likelihood[2,], col = heat.colors(length(cind)), main = "col clusters impact", ylab = "Log Bayes factor")
# barplot(CIB$col_likelihood[1,]/sum(CIB$col_likelihood[1,]), col = heat.colors(length(cind)), main = "cols impact", ylab = "between sum of square")
# barplot(CIB$col_likelihood[2,]/sum(unique(CIB$col_likelihood[2,])), col = heat.colors(length(cind)), main = "col clusters impact", ylab = "between sum of square")
#######################
#dev.new()
# strl=sort(CI$row_likelihood[1,], method = "shell", index.return = TRUE)
# rname = b$row_name[strl$ix]
# strlnew=sort(CInew$row_likelihood[1,], method = "shell", index.return = TRUE)
# rnamenew = b$row_name[strlnew$ix]
# if(is.null(rname))
# rname = strl$ix
# barplot(strl$x, names.arg = rname, las=2, col = heat.colors(length(strl$x)), main = "rows impact", xlab = "row names", ylab = "Log Bayes factor")
# if(is.null(rnamenew))
# rname = strlnew$ix
# barplot(strlnew$x, names.arg = rnamenew, las=2, col = heat.colors(length(strl$x)), main = "rows impact", xlab = "row names", ylab = "Log Bayes factor")
##################################################################################################################################
# stcl=sort(CI$col_likelihood[1,], method = "shell", index.return = TRUE)
# cname = b$col_name[stcl$ix]
# if(is.null(cname))
# cname = stcl$ix
# barplot(stcl$x, names.arg = cname, las=2, col = heat.colors(length(stcl$x)), main = "columns impact", xlab = "column names", ylab = "Log Bayes factor")
class(groups) <- "bigroup";
return(groups)
}
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