Stat_Contour with Data Labels on Lines

stat_contour with data labels on lines

using directlabels package and picking solution from this

# Basic plot
v <- ggplot(volcano3d, aes(x, y, z = z))
library(directlabels)
v2 <- v + stat_contour(aes(colour = ..level..))
direct.label(v2, method="bottom.pieces")

How to plot a contour with directlabels using two different dataframe

I am not 100% sure, but it seems that the problem is with how direct.label treats your first ggplot(NULL) call. Most likely it looks there for the required aesthetics, but not able to find them.

Here's how you can fix that:

pp0 <- ggplot(dat0, aes(x=x, y=y, z=z)) + geom_point()
pp <- pp0 + stat_contour(data=z.cubic, aes(x=x, y=y, z=z, colour=..level..))

and now both print(pp) and direct.label(pp) work as expected.

Update

Browsing the source, I found a way to fix the issue by adding the following line right before the last one in direct.label.ggplot: dlgeom$mapping <- c(dlgeom$mapping, L$mapping).

Update 2

Toby Hocking (package maintainer) answered my message and, as it turns out, the package has indeed been updated to version directlabels_2014.6.13 on R-Forge, which is correctly pointed out by @user3357659. In fact, the idea I'm proposing here as a workaround for an outdated version directlabels_2013.6.15 has been already implemented there.

Using directlabels with ggplot2 to label a second layer with data different from the primary layer

Use geom_dl to label additional layers:

WithLegend <- ggplot(volcano3d_1,aes(x, y, z=z, colour=..level..))+
  stat_contour()+
  stat_contour(data=volcano3d_2)
## direct.label labels the first colored layer.
SomeLabels <- direct.label(v)
## Additional labels can be added using geom_dl layers.
MoreLabels <- SomeLabels+
  geom_dl(aes(label=..level.., colour=..level..),
          data=volcano3d_2, method="top.pieces", stat="contour")

adding custom labels to ggplot geom_contour

I think that I have come to a workaround to show the labels using geom_dl:

library(lattice)
library(directlabels)
dat <- melt(volcano)
brks <- c(100, 120, 140, 160)
g <- ggplot(dat, aes(x = Var1, y = Var2, z = value)) +
     geom_contour(colour='black', breaks = brks)+
     geom_dl(aes(label=..level..), method="bottom.pieces", 
             stat="contour",breaks = brks)
g

Just indicate in geom_dl that you want to label the levels (aes(label=..levels..)) contained in the breaks (breaks=brks), so it knows the labels to be shown.

Drawing labels on flat section of contour lines in ggplot2

I created a function to calculate the flattest section using the method for contour() (from plot3d), created a data frame with just the flattest values with help from plyr, and added it manually to the plot with geom_text(). To exactly match the contour() output, the labels need to be rotated, sections of the contour lines need to be erased to make room for the labels, and corrections need to be made to ensure the labels don't fall off the edges of the contour lines. I will work on these over the next couple of months (this is all still a side project).

library(fields)
library(ggplot2)
library(reshape)

sumframe<-structure(list(Morph = c("LW", "LW", "LW", "LW", "LW", "LW", "LW", "LW", "LW", "LW", "LW", "LW", "LW", "SW", "SW", "SW", "SW", "SW", "SW", "SW", "SW", "SW", "SW", "SW", "SW", "SW"), xvalue = c(4, 8, 9, 9.75, 13, 14, 16.25, 17.25, 18, 23, 27, 28, 28.75, 4, 8, 9, 9.75, 13, 14, 16.25, 17.25, 18, 23, 27, 28, 28.75), yvalue = c(17, 34, 12, 21.75, 29, 7, 36.25, 14.25, 24, 19, 36, 14, 23.75, 17, 34, 12, 21.75, 29, 7, 36.25, 14.25, 24, 19, 36, 14, 23.75), zvalue = c(126.852666666667, 182.843333333333, 147.883333333333, 214.686666666667, 234.511333333333, 198.345333333333, 280.9275, 246.425, 245.165, 247.611764705882, 266.068, 276.744, 283.325, 167.889, 229.044, 218.447777777778, 207.393, 278.278, 203.167, 250.495, 329.54, 282.463, 299.825, 286.942, 372.103, 307.068)), .Names = c("Morph", "xvalue", "yvalue", "zvalue"), row.names = c(NA, -26L), class = "data.frame")

# Subdivide, calculate surfaces, recombine for ggplot:
sumframeLW<-subset(sumframe, Morph=="LW")
sumframeSW<-subset(sumframe, Morph="SW")

surf.teLW<-Tps(cbind(sumframeLW$xvalue, sumframeLW$yvalue), sumframeLW$zvalue, lambda=0.01)
surf.te.outLW<-predict.surface(surf.teLW)

surf.teSW<-Tps(cbind(sumframeSW$xvalue, sumframeSW$yvalue), sumframeSW$zvalue, lambda=0.01)
surf.te.outSW<-predict.surface(surf.teSW)

sumframe$Morph<-as.numeric(as.factor(sumframe$Morph))

LWsurfm<-melt(surf.te.outLW)
LWsurfm<-rename(LWsurfm, c("value"="z", "X1"="x", "X2"="y"))
LWsurfms<-na.omit(LWsurfm)
LWsurfms[,"Morph"]<-c("LW")

SWsurfm<-melt(surf.te.outSW)
SWsurfm<-rename(SWsurfm, c("value"="z", "X1"="x", "X2"="y"))
SWsurfms<-na.omit(SWsurfm)
SWsurfms[,"Morph"]<-c("SW")

LWSWsurf<-rbind(LWsurfms, SWsurfms)
# Note that I've lost my units - things have been rescaled to be between 0 and 80.

LWSWc<-ggplot(LWSWsurf, aes(x,y,z=z))+facet_wrap(~Morph)+geom_contour(colour="black", size=0.6)
LWSWc
# Create data frame from data used to generate this contour plot:
tmp3<-ggplot_build(LWSWc)$data[[1]]

In a nutshell, the tmp3 data frame contains a vector, tmp3$group, which was used as a grouping variable for subsequent calculations. Within each level of tmp3$group, the variances were calculated with flattenb. A new data frame was generated, and the values from that data frame were added to the plot with geom_text().

flattenb <- function (tmp3){
    counts = length(tmp3$group)
    xdiffs = diff(tmp3$x)
    ydiffs = diff(tmp3$y)
    avgGradient = ydiffs/xdiffs
    squareSum = avgGradient * avgGradient
    variance = (squareSum - (avgGradient * avgGradient) / counts / counts)
    data.frame(variance = c(9999999, variance) #99999 pads this so the length is same as original and the first values are not selected
    )
}

tmp3<-cbind(tmp3, ddply(tmp3, 'group', flattenb))
tmp3l<-ddply(tmp3, 'group', subset, variance==min(variance))
tmp3l[,"Morph"]<-c(rep("LW", times=8), rep("SW", times=8))

LWSWpp<-ggplot(LWSWsurf, aes(x,y,z=z))
LWSWpp<-LWSWpp+geom_tile(aes(fill=z))+stat_contour(aes(x,y,z=z, colour=..level..), colour="black", size=0.6)
LWSWpp<-LWSWpp+scale_fill_gradientn(colours=tim.colors(128))
LWSWpp<-LWSWpp+geom_text(data=tmp3l, aes(z=NULL, label=level))+facet_wrap(~Morph)
LWSWpp

Change contour colours using directlabels

I spotted a similar post and thought this would be easy, something along the lines of direct.label(p, list("last.points", colour = "black"). I could not make it work, unfortunately; I believe, this is not directly supproted.

I then decided to use black magic and managed to do the trick by manually overriding the colour scale:

direct.label(plotDF + 
             scale_colour_gradient(low="black", high="black"))

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