geom_georaster: 2d image of a geofield
In andrew-MET/harpVis: Visualisation functions for harp.

geom_georaster

R Documentation

2d image of a geofield

Description

This function visualises geofield data as a raster in 2D. It is built on top of geom_raster.

It requires data frames with a column containing geofields. This would normally be a geolist column, but a standard list column containing geofields will also work.

Smoothing can be achieved by upscaling the data before plotting. This can only be done using an integer scale factor and the methods can be any function that summarises a vector into a single value, for example "mean", "median", "min", "max", or "downsample". Downsampling is simply sampling a pixel within the upscaled pixel - by default this is the centre pixel. Downsampling is the fastest method and is probably sufficient, especially for faceted plots.

Usage

geom_georaster(
  mapping = NULL,
  data = NULL,
  position = "identity",
  ...,
  upscale_factor = 1,
  upscale_method = "mean",
  downsample_location = "centre",
  hjust = 0.5,
  vjust = 0.5,
  interpolate = FALSE,
  na.rm = FALSE,
  show.legend = NA,
  inherit.aes = TRUE
)

Arguments

`mapping`	Set of aesthetic mappings created by `aes()`. If specified and `inherit.aes = TRUE` (the default), it is combined with the default mapping at the top level of the plot. You must supply `mapping` if there is no plot mapping.
`data`	The data to be displayed in this layer. There are three options: If `NULL`, the default, the data is inherited from the plot data as specified in the call to `ggplot()`. A `data.frame`, or other object, will override the plot data. All objects will be fortified to produce a data frame. See `fortify()` for which variables will be created. A `function` will be called with a single argument, the plot data. The return value must be a `data.frame`, and will be used as the layer data. A `function` can be created from a `formula` (e.g. `~ head(.x, 10)`).
`position`	Position adjustment, either as a string naming the adjustment (e.g. `"jitter"` to use `position_jitter`), or the result of a call to a position adjustment function. Use the latter if you need to change the settings of the adjustment.
`...`	Other arguments passed on to `layer()`. These are often aesthetics, used to set an aesthetic to a fixed value, like `colour = "red"` or `size = 3`. They may also be parameters to the paired geom/stat.
`upscale_factor`	An integer by which to upscale the data before computing the contours. For example if this is 2, the upscaled grid will have 2 pixels in each direction from the grid before upscaling.
`upscale_method`	The method used for upscaling. See `geo_upscale` for more details.
`downsample_location`	When "downsample" is the chosen method, each pixel in the upscaled field is sampled from a pixel from the original field that is inside the upscaled pixel. The location of that pixel can be one of "bottom_left", "bottom_centre", "bottom_right", "left_centre", "centre", "right_centre", "top_right", "top_centre", "top_left" or "random".
`hjust, vjust`	horizontal and vertical justification of the grob. Each justification value should be a number between 0 and 1. Defaults to 0.5 for both, centering each pixel over its data location.
`interpolate`	If `TRUE` interpolate linearly, if `FALSE` (the default) don't interpolate.
`na.rm`	If `FALSE`, the default, missing values are removed with a warning. If `TRUE`, missing values are silently removed.
`show.legend`	logical. Should this layer be included in the legends? `NA`, the default, includes if any aesthetics are mapped. `FALSE` never includes, and `TRUE` always includes. It can also be a named logical vector to finely select the aesthetics to display.
`inherit.aes`	If `FALSE`, overrides the default aesthetics, rather than combining with them. This is most useful for helper functions that define both data and aesthetics and shouldn't inherit behaviour from the default plot specification, e.g. `borders()`.