combining two plots in r

Question

Here are two plots I intend to combine:

First is half matrix of heatmap plot. ..............................

# plot 1 , heatmap plot
set.seed (123)
 myd <- data.frame ( matrix(sample (c(1, 0, -1), 500, replace = "T"), 50))

mmat <-  cor(myd)
diag(mmat) <- NA
mmat[upper.tri (mmat)] <- NA
heatmap (mmat, keep.dendro = F, Rowv = NA, Colv = NA)

I need to suppress the names in x and y columns and put them in diagonal.

The second plot, please note that names / labels in first plot corresponds name in second plot (x1 to X10):

  vard <- data.frame ( position = c(1, 10, 15, 18, 20, 23, 24, 30, 35, 40), 
          Names =paste ("X", 1:10, sep = ""))
    plot(vard$position, vard$position - vard$position,
                type = "n", axes = FALSE, xlab = "", ylab = NULL, yaxt = "n")
    polygon(c(0, max(vard$position + 0.08 * max(vard$position)),
                max(vard$position) + 0.08 * max(vard$position),
                0), 0.2 * c(-0.3, -0.3, 0.3, 0.3), col = "green4")
    segments(vard$position, -0.3, vard$position,                0.3)
    text(vard$position, 0.7, vard$position,
                    srt = 90)
    text(vard$position, -0.7, vard$Names)

I intend rotate the first plot so that X1 to X10 should correspond to the same in the second plot and there is connection between labels in second plot to first plot. The output would look like:

How can I do this ?

Edits: based on comments about add = TRUE....I am trying to add polygon to the heatmap plot, the like follows. But I could not find coordinates ..The strategy plot this way and flip the actual figure later...help much appreciated...

Answer 1

Here's a fully grid-based solution. The only really involved bit is the function convertToColors(); it takes a numeric matrix (possibly including NAs) and converts it to sRGB color strings (e.g. "#FFFFFF) representing colors on a red-to-white heat.colors() scale. Red corresponds to the minimum value in the matrix, white corresponds to the maximum value, and NAs are transparent.

Other than that, I think the code does a decent job of showing how many grid functions are no more complicated, and considerably more consistent and flexible, than the low-level base graphics functions.

library(grid)

## Data: heatmap
set.seed (123)
myd <- data.frame ( matrix(sample (c(1, 0, -1), 500, replace = "T"), 50))
mmat <-  cor(myd)
diag(mmat) <- NA
mmat[upper.tri (mmat)] <- NA
## Data: Positions
vard <- c(1, 10, 15, 18, 20, 23, 24, 30, 35, 40)

## Construct a function to convert a numeric matrix to a matrix of color names.
## The lowest value in the matrix maps to red, the highest to white,
## and the NAs to "transparent".
convertToColors <- function(mat) {
    # Produce 'normalized' version of matrix, with values ranging from 0 to 1
    rng <- range(mat, na.rm = TRUE)
    m <- (mat - rng[1])/diff(rng)
    # Convert to a matrix of sRGB color strings
    m2 <- m; class(m2) <- "character"
    m2[!is.na(m2)] <- rgb(colorRamp(heat.colors(10))(m[!is.na(m)]), max = 255)
    m2[is.na(m2)] <- "transparent"
    return(m2)
}

## Initialize plot and prepare two viewports
grid.newpage()
heatmapViewport <- viewport(height=1/sqrt(2), width=1/sqrt(2), angle = -135) 
annotationViewport <- viewport(y = 0.7, height = 0.4)

## Plot heat map
pushViewport(heatmapViewport)
    grid.raster(t(convertToColors(mmat)), interpolate = FALSE)
upViewport()

## Precompute x-locations of text and segment elements
n <- nrow(mmat)
v_x <- vard/max(vard)
X_x <- seq(0, 1, len=n)

## Plot the annotated green bar and line segments
pushViewport(annotationViewport)
    ## Green rectangle
    grid.polygon(x = c(0,0,1,1,0), y = c(.45,.55,.55,.45,.45),
                 gp = gpar(fill = "green4"))
    pushViewport(viewport(width = (n-1)/n))
        ## Segments and text marking vard values
        grid.segments(x0 = v_x, x1 = v_x, y0 = 0.3, y1 = 0.7)
        grid.text(label = vard, x = v_x, y = 0.75, rot = 90)
        ## Text marking heatmap column names (X1-X10)
        grid.text(paste0("X", seq_along(X_x)), x = X_x, y=0.05,
                  gp = gpar(fontface="bold"))
        ## Angled lines
        grid.segments(x0 = v_x, x1 = X_x, y0 = 0.29, y1 = 0.09)
    upViewport()
upViewport()