rasterize_points: rasterize_points

In plotly/rasterly: Easily and Rapidly Generate Raster Image Data with Support for 'Plotly.js'

Description

Points layer for "rasterly". Deprecated now, please use rasterly_points instead.

Usage

rasterize_points(
  rastObj,
  data = NULL,
  mapping = aes(),
  ...,
  xlim = NULL,
  ylim = NULL,
  max_size = NULL,
  reduction_func = NULL,
  layout = NULL,
  glyph = NULL,
  group_by_data_table = NULL,
  inherit.aes = TRUE
)

Arguments

rastObj	A rasterly object.
data	A data.frame or function with an argument x, specifying the dataset to use for plotting. If data is NULL, the data argument provided to rasterly may be passed through.
mapping	Default list of aesthetic mappings to use for plot. If provided and inherit.aes = TRUE, it will be stacked on top of the mappings passed to rasterly.
...	Pass-through arguments provided by rasterly.
xlim	Vector of type numeric. X limits in this layer.
ylim	Vector of type numeric. Y limits in this layer.
max_size	Numeric. When size changes, the upper bound of the number of pixels over which to spread a single observation.
reduction_func	Function. A reduction function is used to aggregate data points into their pixel representations. Currently supported reduction operators are sum, any, mean, m2, first, last, min and max. Default is sum. See details.
layout	Character. The method used to generate layouts for multiple images. The default is weighted. Useful for categorical data (i.e. "color" is provided via aes()). weighted specifies that the final raster should be a weighted combination of each (categorical) aggregation matrix. Conversely, cover indicates that the afterwards objects will be drawn on top of the previous ones.
glyph	Character. Currently, only "circle" and "square" are supported; as the size of the pixels increases, how should they spread out – should the pattern be circular or square? Other glyphs may be added in the future.
group_by_data_table	Logical. Default is TRUE; when "color" is provided via aes(), the "group by" operation may be perfromed within data.table or natively within rasterly. Generally, group_by_data_table = TRUE is faster, but for very large datasets grouping within rasterly may offer better performance.
inherit.aes	If FALSE, overrides the default aesthetics, rather than combining with them.

See Also

rasterly_points

plotly/rasterly documentation built on June 9, 2020, 1:21 p.m.