This position adjustment is able to select a meaningful jitter of the data based on the combination of positional scale types. IT behaves differently depending on if none, one, or both the x and y scales are discrete. If both are discrete it will jitter the datapoints evenly inside a disc, if one of them is discrete it will jitter the discrete dimension to follow the density along the other dimension (like a sina plot). If neither are discrete it will not do any jittering.

`position_auto(jitter.width = 0.75, bw = "nrd0", scale = TRUE, seed = NA)`

- jitter.width
The maximal width of the jitter

- bw
The smoothing bandwidth to use in the case of sina jittering. See the

`bw`

argument in stats::density- scale
Should the width of jittering be scaled based on the number of points in the group

- seed
A seed to supply to make the jittering reproducible across layers

geom_autopoint for a point geom that uses auto-position by default

```
# Continuous vs continuous: No jitter
ggplot(mpg) + geom_point(aes(cty, hwy), position = 'auto')
# Continuous vs discrete: sina jitter
ggplot(mpg) + geom_point(aes(cty, drv), position = 'auto')
# Discrete vs discrete: disc-jitter
ggplot(mpg) + geom_point(aes(fl, drv), position = 'auto')
# Don't scale the jitter based on group size
ggplot(mpg) + geom_point(aes(cty, drv), position = position_auto(scale = FALSE))
ggplot(mpg) + geom_point(aes(fl, drv), position = position_auto(scale = FALSE))
```