### Name: heatmap
### Title: Draw a Heat Map
### Aliases: heatmap
### Keywords: hplot

### ** Examples

require(graphics); require(grDevices)
x  <- as.matrix(mtcars)
rc <- rainbow(nrow(x), start=0, end=.3)
cc <- rainbow(ncol(x), start=0, end=.3)
hv <- heatmap(x, col = cm.colors(256), scale="column",
              RowSideColors = rc, ColSideColors = cc, margins=c(5,10),
              xlab = "specification variables", ylab= "Car Models",
              main = "heatmap(<Mtcars data>, ..., scale = \"column\")")
utils::str(hv) # the two re-ordering index vectors

## no column dendrogram (nor reordering) at all:
heatmap(x, Colv = NA, col = cm.colors(256), scale="column",
        RowSideColors = rc, margins=c(5,10),
        xlab = "specification variables", ylab= "Car Models",
        main = "heatmap(<Mtcars data>, ..., scale = \"column\")")
## Don't show:
## no row dendrogram (nor reordering) at all:
heatmap(x, Rowv = NA, col = cm.colors(256), scale="column",
        ColSideColors = cc, margins=c(5,10),
        xlab = "xlab", ylab= "ylab")# no main
## End Don't show
## "no nothing"
heatmap(x, Rowv = NA, Colv = NA, scale="column",
        main = "heatmap(*, NA, NA) ~= image(t(x))")

round(Ca <- cor(attitude), 2)
symnum(Ca) # simple graphic
heatmap(Ca,             symm = TRUE, margins=c(6,6))# with reorder()
heatmap(Ca, Rowv=FALSE, symm = TRUE, margins=c(6,6))# _NO_ reorder()

## For variable clustering, rather use distance based on cor():
symnum( cU <- cor(USJudgeRatings) )

hU <- heatmap(cU, Rowv = FALSE, symm = TRUE, col = topo.colors(16),
             distfun = function(c) as.dist(1 - c), keep.dendro = TRUE)
## The Correlation matrix with same reordering:
round(100 * cU[hU[[1]], hU[[2]]])
## The column dendrogram:
utils::str(hU$Colv)