Drawing a contour line around connected cells in a heatmap in R
I have data with two time axes and measurements for each cell. From this I create a heatmap. I also know for each cell whether the measurement is significant.
My problem is to draw a contour line around all cells that are significant. If cells form clusters with the same significance value, I need to draw the contour around the cluster and not around each individual cell.
The data are in this format:
x_time y_time metric signif
1 1 1 0.3422285 FALSE
2 2 1 0.6114085 FALSE
3 3 1 0.5381621 FALSE
4 4 1 0.5175120 FALSE
5 1 2 0.6997991 FALSE
6 2 2 0.3054885 FALSE
7 3 2 0.8353888 TRUE
8 4 2 0.3991566 TRUE
9 1 3 0.7522728 TRUE
10 2 3 0.5311418 TRUE
11 3 3 0.4972816 TRUE
12 4 3 0.4330033 TRUE
13 1 4 0.5157972 TRUE
14 2 4 0.6324151 TRUE
15 3 4 0.4734126 TRUE
16 4 4 0.4315119 TRUE
The code below generates this data, where the measurements are random (dt$metrics) and the significance is logical (dt$signif).
# data example
dt <- data.frame(x_time=rep(seq(1, 4), 4),
y_time=rep(seq(1, 4), each=4),
metric=(rnorm(16, 0.5, 0.2)),
signif=c(rep(FALSE, 6), rep(TRUE, 10)))
The heatmap alone can be generated using ggplot2's geom_tile
# Generate heatmap using ggplot2's geom_tile
library(ggplot2)
p <- ggplot(data = dt, aes(x = x_time, y = y_time))
p <- p + geom_tile(aes(fill = metric))
Based on this question, I managed to draw contours with different colors around each cell according to the significance value.
# Heatmap with lines around each significant cell
p <- ggplot(data = dt, aes(x = x_time, y = y_time))
p <- p + geom_tile(aes(fill = metric, color = signif), size = 2)
p <- p + scale_color_manual(values = c("black", "white"))
However, this approach does not group adjacent significant cells together by drawing a contour around the entire group (as is also discussed in the question I linked to).
As this question shows, it is possible to draw boxes around specified areas, but I do not think this can be extended to all possible clusters of cells.
This answer is based on How to get contour lines around the grids in R-raster?.
library(data.table)
library(raster)
Also note that clump requires that igraph package is installed, and dissolve = TRUE in rasterToPolygons requires rgeos.
# convert data.frame to data.table
# not strictly necessary, but enables use of convenient functions: dcast and rbindlist.
setDT(d)
# reshape to wide
d2 <- dcast(d, y ~ x, value.var = "sig")
# reverse order of rows to match raster order
# remove first column
# convert to matrix and then to raster
r <- raster(as.matrix(d2[ , .SD[.N:1, -1]]),
xmn = 0, xmx = ncol(d2) - 1, ymn = 0, ymx = ncol(d2) - 1)
# detect clumps of connected cells of the value TRUE
# convert raster to polygons
# dissolve polygons into multi-polygons
polys <- rasterToPolygons(clump(r), dissolve = TRUE)
# grab coordinates of individual polygons and convert to a data.table
# use idcol = TRUE to enable grouping of paths when plotting
d_poly <- rbindlist(lapply(polys@polygons,
function(x) as.data.table(x@Polygons[[1]]@coords)),
idcol = TRUE)
# plot an outline around each 'patch of significant values' using geom_path
ggplot(d, aes(x = x, y = y)) +
geom_tile(aes(fill = z)) +
geom_path(data = d_poly, aes(x = x + 0.5, y = y + 0.5, group = .id),
size = 2, color = "red")
Data:
d <- structure(list(x = c(1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L,
3L, 3L, 3L, 3L, 4L, 4L, 4L, 4L),
y = c(1L, 2L, 3L, 4L, 1L, 2L, 3L, 4L,
1L, 2L, 3L, 4L, 1L, 2L, 3L, 4L),
sig = c(FALSE, FALSE, FALSE, TRUE, FALSE, FALSE, TRUE, TRUE,
TRUE, FALSE, FALSE, FALSE, TRUE, FALSE, FALSE, TRUE),
z = c(0.96, 0.76, 0.14, 0.93, 0.39, 0.06, 0.99, 0.77,
0.7, 0.72, 0.08, 0.94, 0.98, 0.83, 0.12, 0.42)),
row.names = c(NA, -16L), class = "data.frame")