# pretty

##### Pretty Breakpoints

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.

- Keywords
- dplot

##### 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

`library(base)`

```
# 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")
# }
```

*Documentation reproduced from package base, version 3.5.3, License: Part of R 3.5.3*