r - ggplot2: Automatic scaling to include complete contour lines in geom_density_2d -

hopefully quick.

i have plotted following chart using ggplot.

with code:

ggplot(contourdummy,aes(x=measure.name1,y=measure.name2,colour=category.name)) +geom_density_2d() 

my issue of contour lines not complete.

now if scale axis adding following...

+ scale_x_continuous(minor_breaks=0, breaks=seq(14,26,12),limits=c(14,26))  + scale_y_continuous(minor_breaks=0, breaks=seq(50,100,50),limits=c(50,100) 

i desired output.

but there way of automatically setting limits? want able replicate chart type automatically switching data source, x, y , colour.

i don't particularly want fiddling around scales every time.

here's function expands x , y ranges include maximum extent of density contours. function works follows:

1. create plot object x , y ranges expanded beyond data range, can sure plot include complete contour lines.

2. use ggplot_build determine min , max x , y values among density contours.

3. set x , y ranges of plot min , max x , y values determined in step 2.

the exp parameter there expand final range tiny amount (1% default) because small piece of contour line can still cut off without small bit of padding (in example below, try plotting mtcars data frame exp=0 , you'll see mean).

d2d = function(data, var1, var2, col, exp=0.005) {    # if colour variable numeric, convert factor   if(is.numeric(data[,col])) {     data[,col] = as.factor(data[,col])   }    # create plot, expand x , y ranges beyond data   p=ggplot(data, aes_string(var1, var2, colour=col)) +     geom_density_2d() +     scale_x_continuous(limits=c(min(data[,var1]) - 2*diff(range(data[,var1])),                                 max(data[,var1]) + 2*diff(range(data[,var1])))) +     scale_y_continuous(limits=c(min(data[,var2]) - 2*diff(range(data[,var2])),                                 max(data[,var2]) + 2*diff(range(data[,var2]))))    # min , max x , y values among density contours   pb = ggplot_build(p)    xyscales = lapply(pb$data[[1]][,c("x","y")], function(var) {     rng = range(var)     rng + c(-exp*diff(rng), exp*diff(rng))   })    # set x , y ranges include complete density contours   ggplot(data, aes_string(var1, var2, colour=col)) +     geom_density_2d() +     scale_x_continuous(limits=xyscales[[1]]) +     scale_y_continuous(limits=xyscales[[2]])  } 

try out function on 2 built-in data sets:

d2d(mtcars, "wt","mpg", "cyl") d2d(iris, "petal.width", "petal.length", "species") 

here's plots default x , y ranges:

ggplot(mtcars, aes(wt, mpg, colour=factor(cyl))) + geom_density_2d()  ggplot(iris, aes(petal.width, petal.length, colour=species)) + geom_density_2d() 

if want control number of axis tick marks well, can, example, this:

d2d = function(data, var1, var2, col, nx=5, ny=5, exp=0.01) {    require(scales)    # if colour variable numeric, convert factor   if(is.numeric(data[,col])) {     data[,col] = as.factor(data[,col])   }    # create plot, expand x , y ranges beyond data   p=ggplot(data, aes_string(var1, var2, colour=col)) +     geom_density_2d() +     scale_x_continuous(limits=c(min(data[,var1]) - 2*diff(range(data[,var1])),                                 max(data[,var1]) + 2*diff(range(data[,var1])))) +     scale_y_continuous(limits=c(min(data[,var2]) - 2*diff(range(data[,var2])),                                 max(data[,var2]) + 2*diff(range(data[,var2]))))    # min , max x , y values among density curves   pb = ggplot_build(p)    xyscales = lapply(pb$data[[1]][,c("x","y")], function(var) {     rng = range(var)     rng + c(-exp*diff(rng), exp*diff(rng))   })    # set x , y ranges include of outer density curves   ggplot(data, aes_string(var1, var2, colour=col)) +     geom_density_2d() +     scale_x_continuous(limits=xyscales[[1]], breaks=pretty_breaks(n=nx)) +     scale_y_continuous(limits=xyscales[[2]], breaks=pretty_breaks(n=ny))  }