Pretty ticks for log normal scale using ggplot2 (dynamic not manual)

ggplot2, plot, r

Solution

The base graphics behaviour can be reproduced using a custom breaks function:

base_breaks <- function(n = 10){
    function(x) {
        axisTicks(log10(range(x, na.rm = TRUE)), log = TRUE, n = n)
    }
}

Applying this to the example data gives the same result as using `trans_breaks('log10', function(x) 10^x)`:

ggplot(M, aes(x = X, y = Y)) + geom_line() +
    scale_y_continuous(trans = log_trans(), breaks = base_breaks()) + 
    theme(panel.grid.minor = element_blank())

However we can use the same function on a subset of the data, with y values between 50 and 600:

M2 <- subset(M, Y > 50 & Y < 600)
ggplot(M2, aes(x = X, y = Y)) + geom_line() +
    scale_y_continuous(trans = log_trans(), breaks = base_breaks()) + 
    theme(panel.grid.minor = element_blank())

As powers of ten are no longer suitable here, `base_breaks` produces alternative pretty breaks:

Note that I have turned off minor grid lines: in some cases it will make sense to have grid lines halfway between the major gridlines on the y-axis, but not always.

Edit

Suppose we modify M so that the minimum value is 0.1:

M <- M - min(M) + 0.1

The base_breaks() function still selects pretty breaks, but the labels are in scientific notation, which may not be seen as "pretty":

ggplot(M, aes(x = X, y = Y)) + geom_line() +
    scale_y_continuous(trans = log_trans(), breaks = base_breaks()) + 
    theme(panel.grid.minor = element_blank())

We can control the text formatting by passing a text formatting function to the `labels` argument of `scale_y_continuous`. In this case `prettyNum` from the base package does the job nicely:

ggplot(M, aes(x = X, y = Y)) + geom_line() +
scale_y_continuous(trans = log_trans(), breaks = base_breaks(),
                   labels = prettyNum) + 
theme(panel.grid.minor = element_blank())

Problem

I am trying to use ggplot2 to create a performance chart with a log normal y scale. Unfortunately I'm not able to produce nice ticks as for the base plot function. Here my example: ``` library(ggplot2) library(scales) # fix RNG set.seed(seed = 1) # simulate returns y=rnorm(999, 0.02, 0.2) # M$Y are the cummulative returns (like an index) M = data.frame(X = 1:1000, Y=100) for (i in 2:1000) M[i, "Y"] = M[i-1, "Y"] * (1 + y[i-1]) ggplot(M, aes(x = X, y = Y)) + geom_line() + scale_y_continuous(trans = log_trans()) ``` produces ugly ticks: I also tried: ``` ggplot(M, aes(x = X, y = Y)) + geom_line() + scale_y_continuous(trans = log_trans(), breaks = pretty_breaks()) ``` How can I get the same breaks/ticks as in the default plot function: ``` plot(M, type = "l", log = "y") ``` The result should look like this but not with hard-typing the breaks but dynamic. I tried functions like `axisTicks()` but was not successful: ``` ggplot(M, aes(x = X,y = Y)) + geom_line() + scale_y_continuous(trans = log_trans(), breaks = c(1, 10, 100, 10000)) ``` Thanks! edit: inserted pictures

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