image.plot in R not displaying colorscale values at the edges of color scale

Question

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Notice the diff in color scale label on two images. top image is the output from R 3.2.5, same code produces bottom image in R 2.15.2. I want to resolve the 'shift' of labels in the top plot to match the bottom one. Sample code given in this query was used to generate both plots.

I am trying to plot a map using image.plot but the min and max value of colorscale are not displayed exactly at the tips. I am facing this issue in R version 3.2.5 (2016-04-14); Platform: x86_64-w64-mingw32/x64 (64-bit) and library package 'fields' Spam version 1.4-0 (2016-08-29)

In contrast, the same commands could be correctly displayed the min and max values at the edges of color scale in R version 2.15.2 (2012-10-26), Platform: x86_64-w64-mingw32/x64 (64-bit) and 'fields' package 0.41-0 (2014-02-26). Here is sample code:

library(fields)
temp <- matrix(data=rexp(200, rate=10), nrow=180, ncol=360)
min(temp)
max(temp)
color_plate <- c("#FF0000", "#FF4D00", "#FF7000", "#FF8A00", "#FFA800", "#FFBF00", "#FFF000", "#FFFF54", "#AAFFFF","#7FFFFF", "#55FFFF", "#2AFFFF", "#00CFFF", "#20BFFF", "#209FFF", "#2060FF")

zlim <- seq(0.08,0.40,by=0.04)
temp[temp<min(zlim)] <- min(zlim)
temp[temp>max(zlim)] <- max(zlim)

image.plot(temp,col=color_plate, 
           axis.args=list(cex.axis =1,at=zlim, labels=zlim,mgp=c(1, 0, 0),tck=0.1))

Answer 1

The best I could do to answer this question was to escape the confines of image.plot()and recode the heat map in ggplot2. The code I wrote should relocate your tick marks to the appropriate locations. Note that "Var1" and "Var2" in the ggplot object p can be switched depending on how you want the data displayed. I used melt() to transform the temp object which means that the original row/column designation is lost. I wasn't sure which plotted on the x/y axis in the image.plot() function, so if I chose the wrong one be sure to switch "Var1" and "Var2".

I hope this helps!

library(fields)
library(reshape2)
library(ggplot2)
library(grid)

temp <- matrix(data=rexp(200, rate=10), nrow=180, ncol=360)

color_palette <- c("#FF0000", "#FF4D00", "#FF7000", "#FF8A00",
        "#FFA800", "#FFBF00", "#FFF000", "#FFFF54", "#AAFFFF","#7FFFFF",
        "#55FFFF", "#2AFFFF", "#00CFFF", "#20BFFF", "#209FFF", "#2060FF")

zlim <- seq(0.08,0.40,by=0.04)
zlim2 <- seq(0.08,0.40,by=0.02)

temp[temp<min(zlim)] <- min(zlim)
temp[temp>max(zlim)] <- max(zlim)
rownames(temp) <- seq(0,1,1/(length(temp[,1])-1))
colnames(temp) <- seq(0,1,1/(length(temp[1,])-1))

tdm <- melt(temp)

tdm$val_for_color <- NA
##can change this as long as you end up with 17 classes (labeled 1-17) for color assignment
for(i in 1:(length(zlim2)-1)){
    tdm$val_for_color[which(tdm$value >= zlim2[[i]] & tdm$value <= zlim2[[i+1]] )] <- i
}

p <- ggplot(tdm, aes(x = Var1, y = Var2, fill = val_for_color)) +
        geom_raster() + scale_fill_gradientn(breaks=seq(1,length(zlim),1),colors=color_palette, labels=zlim)+ 
        scale_x_continuous(expand=c(0,0)) +
        scale_y_continuous(expand=c(0,0)) +
        guides(fill = guide_colorbar(draw.ulim = TRUE,draw.llim = FALSE,
                        barwidth = 0.7, barheight = 10, limits=c(min(zlim),max(zlim)), raster=FALSE,
                        ticks=FALSE,
                        title=NULL))+
        ylab(NULL)+
        xlab(NULL)+
        theme_bw()

g <- ggplotGrob(p)

#this shifts and spreads the labels
d <-g$grobs[[15]][[1]][[1]]$grobs[[3]]$y[[1]]
g$grobs[[15]][[1]][[1]]$grobs[[3]]$y[[1]] <- g$grobs[[15]][[1]][[1]]$grobs[[3]]$y[[1]]-d
for(i in 2:length(g$grobs[[15]][[1]][[1]]$grobs[[3]]$y)){
    g$grobs[[15]][[1]][[1]]$grobs[[3]]$y[[i]] <- d*5*(i-1)
}

grid.draw(g)

Answer 2

I got the answer from package creator of fields package. Pasting the sample code here for others..

library(fields)

temp <- matrix( seq( 0,.5,,80), 8,10)

colTab <- c("#FF0000", "#FF4D00","#FF7000", "#FF8A00", "#FF7000")

N<- length( colTab)

breaks <- seq(0.08, 0.40,  length.out= N+1 )

image.plot(temp, col=colTab, breaks=breaks,
           axis.args=list(cex.axis =1, at=breaks, labels= breaks, mgp=c(1, 0, 0), tck=0.1)
     )