Question

I am plotting a scatter plot(x, y) and want it to be log-valued, so I do: plot(log(x), log(y)). I’d like to deal with cases where some value in x is 0, and thus not on the plot, while the corresponding y value is nonzero.

I’d like to display the scatter with log ticks but natural number values, meaning if in log2 then the ticks should be 2^0, 2^1, 2^2, ... that would allow me to plot 0 values on the scale as well so as to not miss these points.

Here’s an example:

> x = c(0, 1, 20, 100, 200, 500)
> y = c(1, 16, 32, 105, 300, 50)
> plot(x, y)

There are six points. If I use:

> plot(log2(x), log2(y))

There are only 5 plotted, since x[0], y[0] is omitted (the x-value is 0). Therefore, I’d like to plot the log values but have tick labels to be natural numbers that are simply marked on a log scale. Then you can easily have on the same axis, 0, 2^0 (which is 1 of course), 2^1, 2^2, etc. and so on. Then the point (x[0], y[0]) will still be plotted, while keeping the log scale.

Side note: I don’t think it’s fair to downvote a post asking something very reasonable with an example. This is clearly on topic and relevant, and will come up for virtually everyone who is plotting things on a log value and cares about boundary / edge cases.

(I know some people deal with this by adding an arbitrary small constant to all points but I’d like to avoid that as it is messy.) thanks

Answer 1

If I understand you want to plot x versus y in the log scale?

Here and example using lattice and latticeExtra

# Some reproducible data
tm <- data.frame(x=seq(0,10,1),y=seq(0,10,1))
library(lattice) 
library(latticeExtra) 
xyplot(x ~ y , data=tm, 
       scales= list(x=list(log=2), 
                    y=list(log=2)), 
       xscale.components = xscale.components.logpower, ## to get pretty scales
        yscale.components = yscale.components.logpower 
)