Title:	Plotting Field Plans for Agricultural Experiments
Version:	1.10
Type:	Package
Description:	A function for plotting maps of agricultural field experiments that are laid out in grids. See Ryder (1981) <doi:10.1017/S0014479700011601>.
Imports:	ggplot2, grid, lattice, reshape2, rlang
Suggests:	agridat, knitr, rmarkdown, testthat
License:	GPL-3
URL:	https://kwstat.github.io/desplot/
BugReports:	https://github.com/kwstat/desplot/issues
VignetteBuilder:	knitr
RoxygenNote:	7.2.2
Encoding:	UTF-8
Language:	en-US
NeedsCompilation:	no
Packaged:	2023-03-09 22:45:26 UTC; wrightkevi
Author:	Kevin Wright [aut, cre]
Maintainer:	Kevin Wright <kw.stat@gmail.com>
Repository:	CRAN
Date/Publication:	2023-03-09 23:20:06 UTC

Function to create a Red-Gray-Blue palette

Description

A function to create a Red-Gray-Blue palette.

Usage

RedGrayBlue(n)

Arguments

Details

Using gray instead of white allows missing values to appear as white (actually, transparent).

Value

A vector of n colors.

Author(s)

Kevin Wright

Examples

pie(rep(1,11), col=RedGrayBlue(11))
title("RedGrayBlue(11)")

Plot the layout/data of a field experiment.

Description

Use this function to plot the layout of a rectangular lattice field experiment and also the observed data values.

Usage

desplot(
  data,
  form = formula(NULL ~ x + y),
  num = NULL,
  num.string = NULL,
  col = NULL,
  col.string = NULL,
  text = NULL,
  text.string = NULL,
  out1 = NULL,
  out1.string = NULL,
  out2 = NULL,
  out2.string = NULL,
  dq = NULL,
  dq.string = NULL,
  col.regions = RedGrayBlue,
  col.text = NULL,
  text.levels = NULL,
  out1.gpar = list(col = "black", lwd = 3),
  out2.gpar = list(col = "yellow", lwd = 1, lty = 1),
  at,
  midpoint = "median",
  ticks = FALSE,
  flip = FALSE,
  main = NULL,
  xlab,
  ylab,
  shorten = "abb",
  show.key = TRUE,
  key.cex,
  cex = 0.4,
  strip.cex = 0.75,
  subset = TRUE,
  gg = FALSE,
  ...
)

ggdesplot(
  data,
  form = formula(NULL ~ x + y),
  num = NULL,
  num.string = NULL,
  col = NULL,
  col.string = NULL,
  text = NULL,
  text.string = NULL,
  out1 = NULL,
  out1.string = NULL,
  out2 = NULL,
  out2.string = NULL,
  dq = NULL,
  dq.string = NULL,
  col.regions = RedGrayBlue,
  col.text = NULL,
  text.levels = NULL,
  out1.gpar = list(col = "black", lwd = 3),
  out2.gpar = list(col = "yellow", lwd = 1, lty = 1),
  at,
  midpoint = "median",
  ticks = FALSE,
  flip = FALSE,
  main = NULL,
  xlab,
  ylab,
  shorten = "abb",
  show.key = TRUE,
  key.cex,
  cex = 0.4,
  strip.cex = 0.75,
  subset = TRUE,
  gg = FALSE,
  ...
)

Arguments

Details

To create the plot using lattice graphics: 1. desplot(...).

To create the plot using ggplot2 graphics, use one of the following: 1. ggdesplot(...). 2. desplot(..., gg=TRUE). 3. options(desplot.gg=TRUE); desplot(...). Method 3 is useful to modify all results from existing scripts.

The lattice version is complete, mature, and robust. The ggplot2 version is incomplete. The legend can only show colors, and some function arguments are ignored. In general, lattice graphics are about 4-5 times faster than ggplot2 graphics. Not all lattice parameters are passed down to xyplot, but it is possible to make almost any change to the plot by assigning the desplot object to a variable and then edit the object by hand or use update to modify the object. Then print it manually. See the first example below.

Use col.regions to specify fill colors. This can either be a vector of colors or a function that produces a vector of colors. If the response variable is a factor and col.regions is a function, it will be ignored and the cells are filled with default light-colored backgrounds and a key is placed on the left. If the response variable is numeric, the cells are colored according to col.regions, and a ribbon key is placed on the right.

Use shorten='abb' (this is default) to shorten the cell text to 2 characters using the abbreviate function Use shorten='sub' to use a 3-character substring. Use shorten='no' or shorten=FALSE for no shortening.

Note that two sub-plots with identical levels of the split-plot factor can be adjacent to each other by virtue of appearing in different whole-plots. To correctly outline the split-plot factor, simply concatenate the whole-plot factor and sub-plot factor together.

To get a map of a field with a true aspect ratio (lattice version only), include 'aspect=ylen/xlen' in the call, where 'ylen' is the vertical length of the field and 'xlen' is the horizontal length of the field.

To call this function inside another function, you can hack like this: vr <- "yield"; vx <- "x"; vy <- "y"; eval(parse(text=paste("desplot(", vr, "~", vx, "*", vy, ", data=yates.oats)")))

Value

A lattice or ggplot2 object

Author(s)

Kevin Wright

References

K. Ryder (1981). Field plans: why the biometrician finds them useful. Experimental Agriculture, 17, 243–256.

Examples

if(require(agridat)){

# Show how to customize any feature.  Here: make the strips bigger.
data(besag.met)
d1 <- desplot(besag.met, 
              yield ~ col*row|county, 
              main="besag.met",
              out1=rep, out2=block, out2.gpar=list(col="white"), strip.cex=2)
d1 <- update(d1, par.settings = list(layout.heights=list(strip=2)))
print(d1)

# Show experiment layout
data(yates.oats)
desplot(yates.oats, 
        yield ~ col+row, 
        out1=block, out2=gen)

desplot(yates.oats, 
        block ~ col+row, 
        col=nitro, text=gen, cex=1, out1=block,
        out2=gen, out2.gpar=list(col = "gray50", lwd = 1, lty = 1))

}

Borders between tiles

Description

'geom_tileborder' draws a border between tiles of different classes. The required aesthetics are 'aes(x,y,grp)', where 'grp' is the grouping classification that separates tiles.

Usage

geom_tileborder(
  mapping = NULL,
  data = NULL,
  geom = "segment",
  position = "identity",
  na.rm = TRUE,
  show.legend = NA,
  inherit.aes = TRUE,
  ...
)

Arguments

Details

Note, we cannot use 'aes(group)' because it groups the interaction of ALL discrete variables including facets. Since we do not want to draw a border between facets, we had to define a new aesthetic. See: # http://ggplot2.tidyverse.org/reference/aes_group_order.html

Also, we do not want to split the data into separate groups for each level of 'grp', so we need to include 'aes(group=1)'.

Examples

dd <- data.frame(
  x=c(1,2,1,2,3,1,2,1,2,3),
  y=c(2,2,2,2,2,1,1,1,1,1),
  loc=factor(c(1,1,2,2,2,1,1,2,2,2)),
  rep=factor(c(2,2,1,2,3,1,1,1,2,3)))
library(ggplot2)
ggplot(dd, aes(x=x, y=y)) +
  facet_wrap( ~ loc) +
  geom_tile(aes(fill=rep)) +
  geom_tileborder(aes(group=1, grp=rep), lwd=1.5)
# Compare to lattice version of desplot
# desplot::desplot(rep ~ x*y|loc, data=dd, out1=rep)

Panel Function for desplot

Description

This is a panel function for desplot which fills cells with a background color and adds outlines around blocks of cells.

Usage

panel.outlinelevelplot(
  x,
  y,
  z,
  subscripts,
  at,
  ...,
  alpha.regions = 1,
  out1f,
  out1g,
  out2f,
  out2g,
  dq
)

Arguments

Details

It does not add the text labels, numbers, or colors.

The rule for determining where to draw outlines is to compare the levels of the factor used for outlining. If bordering cells have different levels of the factor, then a border is drawn. 'NA' values are ignored (otherwise, too many lines would be drawn).

The code works, but is probably overkill and has not been streamlined.

References

None