R: geom_scattermore

geom_scattermore {scattermore} | R Documentation

## geom_scattermore

### Description

`ggplot2::ggplot()` integration. This cooperates with the rest of ggplot (so you can use it to e.g. add rasterized scatterplots to vector output in order to reduce PDF size). Note that the ggplot processing overhead still dominates the plotting time. Use `geom_scattermost()` to tradeoff some niceness and circumvent ggplot logic to gain speed.

### Usage

    geom_scattermore(
      mapping = NULL,
      data = NULL,
      stat = "identity",
      position = "identity",
      ...,
      na.rm = FALSE,
      show.legend = NA,
      inherit.aes = TRUE,
      interpolate = FALSE,
      pointsize = 0,
      pixels = c(512, 512)
    )

### Arguments

`mapping, data, stat, position, inherit.aes, show.legend, ...` | passed to `ggplot2::layer()`
`na.rm` | Remove NA values, just as with `ggplot2::geom_point()`.
`interpolate` | Default FALSE, passed to `grid::rasterGrob()`.
`pointsize` | Radius of rasterized point. Use `0` for single pixels (fastest).
`pixels` | Vector with X and Y resolution of the raster, default `c(512,512)`.

### Details

Accepts aesthetics `x`, `y`, `colour` and `alpha`. Point size is fixed for all points. Due to rasterization properties it is often beneficial to try non-integer point sizes, e.g. `3.2` looks much better than `3`.

### Examples

    library(ggplot2)
    library(scattermore)
    ggplot(data.frame(x=rnorm(100000), y=rexp(100000))) +
      geom_scattermore(aes(x,y,color=x),
                       pointsize=3,
                       alpha=0.1,
                       pixels=c(1000,1000),
                       interpolate=TRUE) +
      scale_color_viridis_c()

[Package scattermore version 0.7 Index]