stripePlot: Lattice plot methods for producing stripe plots

In SantanderMetGroup/visualizeR: Visualizing climate4R data and Communicating Uncertainty in Seasonal Climate Prediction

Lattice plot methods for producing stripe plots

Description

A wrapper for the lattice (trellis) plot methods for grid and station data.

Usage

stripePlot(
  grid,
  aggr.spatial = list(FUN = "mean", na.rm = TRUE),
  color.theme = "RdBu",
  rev.colors = FALSE,
  xlabels = NULL,
  ylabels = NULL,
  ...
)

Arguments

grid	Input grid (or station data), ideally multimember and with time dimension > 1.
aggr.spatial	list containing the function and the related arguments to perform spatial aggregation. Default is list(FUN = mean, na.rm = TRUE).
color.theme	A character string indicating the color theme to use in the map. Valid values are those available in the RColorBrewer themes. Additionally, the "jet.colors" palette can be used (the rainbow colors, in general not advised, though), for backwards compatibility. Default to the diverging, colorblind-friendly "RdYlBu" palette. NOTE: the color.theme argument will be overriden if the col.regions option from levelplot is used.
rev.colors	Should the chosen color theme be reversed? (default to FALSE, leaving the palette “as is”).
xlabels	Character string of the labels to be shown in the x axis (Default to NULL)
ylabels	Character string of the labels to be shown in the y axis (Default to NULL)
...	Additional arguments as passed to function levelplot.

Details

The function applies the levelplot method after computing spatial aggregation (parameter aggr.spatial) to the imput grids (or station data).

This function is appropriate for multimember grids, each row represents a member.

Controlling graphical parameters

Many different aspects of the plot can be controlled passing the relevant arguments to levelplot. Fine control of graphical parameters for the trellis display can be also controlled using trellis.par.set.

Value

A lattice plot of class “trellis”.

Author(s)

M. Iturbide

Examples

require(climate4R.datasets)
data("CFS_Iberia_pr")
stripePlot(CFS_Iberia_pr)

SantanderMetGroup/visualizeR documentation built on Oct. 28, 2023, 6:11 a.m.