Learn R Programming

base (version 3.6.2)

pretty: Pretty Breakpoints

Description

Compute a sequence of about n+1 equally spaced ‘round’ values which cover the range of the values in x. The values are chosen so that they are 1, 2 or 5 times a power of 10.

Usage

pretty(x, …)

# S3 method for default pretty(x, n = 5, min.n = n %/% 3, shrink.sml = 0.75, high.u.bias = 1.5, u5.bias = .5 + 1.5*high.u.bias, eps.correct = 0, …)

Arguments

x

an object coercible to numeric by as.numeric.

n

integer giving the desired number of intervals. Non-integer values are rounded down.

min.n

nonnegative integer giving the minimal number of intervals. If min.n == 0, pretty(.) may return a single value.

shrink.sml

positive number, a factor (smaller than one) by which a default scale is shrunk in the case when range(x) is very small (usually 0).

high.u.bias

non-negative numeric, typically \(> 1\). The interval unit is determined as {1,2,5,10} times b, a power of 10. Larger high.u.bias values favor larger units.

u5.bias

non-negative numeric multiplier favoring factor 5 over 2. Default and ‘optimal’: u5.bias = .5 + 1.5*high.u.bias.

eps.correct

integer code, one of {0,1,2}. If non-0, an epsilon correction is made at the boundaries such that the result boundaries will be outside range(x); in the small case, the correction is only done if eps.correct >= 2.

further arguments for methods.

Details

pretty ignores non-finite values in x.

Let d <- max(x) - min(x) \(\ge 0\). If d is not (very close) to 0, we let c <- d/n, otherwise more or less c <- max(abs(range(x)))*shrink.sml / min.n. Then, the 10 base b is \(10^{\lfloor{\log_{10}(c)}\rfloor}\) such that \(b \le c < 10b\).

Now determine the basic unit \(u\) as one of \(\{1,2,5,10\} b\), depending on \(c/b \in [1,10)\) and the two ‘bias’ coefficients, \(h =\)high.u.bias and \(f =\)u5.bias.

………

References

Becker, R. A., Chambers, J. M. and Wilks, A. R. (1988) The New S Language. Wadsworth & Brooks/Cole.

See Also

axTicks for the computation of pretty axis tick locations in plots, particularly on the log scale.

Examples

Run this code
# NOT RUN {
pretty(1:15)          # 0  2  4  6  8 10 12 14 16
pretty(1:15, h = 2)   # 0  5 10 15
pretty(1:15, n = 4)   # 0  5 10 15
pretty(1:15 * 2)      # 0  5 10 15 20 25 30
pretty(1:20)          # 0  5 10 15 20
pretty(1:20, n = 2)   # 0 10 20
pretty(1:20, n = 10)  # 0  2  4 ... 20

for(k in 5:11) {
  cat("k=", k, ": "); print(diff(range(pretty(100 + c(0, pi*10^-k)))))}

##-- more bizarre, when  min(x) == max(x):
pretty(pi)

add.names <- function(v) { names(v) <- paste(v); v}
utils::str(lapply(add.names(-10:20), pretty))
utils::str(lapply(add.names(0:20),   pretty, min.n = 0))
sapply(    add.names(0:20),   pretty, min.n = 4)

pretty(1.234e100)
pretty(1001.1001)
pretty(1001.1001, shrink = 0.2)
for(k in -7:3)
  cat("shrink=", formatC(2^k, width = 9),":",
      formatC(pretty(1001.1001, shrink.sml = 2^k), width = 6),"\n")
# }

Run the code above in your browser using DataLab