Produce a graph of design layout, skeletal ANOVA table and data frame with complete design

Usage

des_info(
  design.obj,
  nrows,
  ncols,
  brows = NA,
  bcols = NA,
  byrow = TRUE,
  fac.names = NULL,
  fac.sep = c("", " "),
  plot = TRUE,
  rotation = 0,
  size = 4,
  margin = FALSE,
  save = FALSE,
  savename = paste0(design.obj$parameters$design, "_design"),
  plottype = "pdf",
  return.seed = TRUE,
  quiet = FALSE,
  ...
)

Arguments

design.obj: An agricolae design object.
nrows: The number of rows in the design.
ncols: The number of columns in the design.
brows: For RCBD only. The number of rows in a block.
bcols: For RCBD only. The number of columns in a block.
byrow: For split-plot only. Logical (default: TRUE). Provides a way to arrange plots within whole-plots when there are multiple possible arrangements.
fac.names: Allows renaming of the A level of factorial designs (i.e. those using agricolae::design.ab()) by passing (optionally named) vectors of new labels to be applied to the factors within a list. See examples and details for more information.
fac.sep: The separator used by fac.names. Used to combine factorial design levels. If a vector of 2 levels is supplied, the first separates factor levels and label, and the second separates the different factors.
plot: Logical (default TRUE). If TRUE, display a plot of the generated design. A plot can always be produced later using autoplot().
rotation: Rotate the text output as Treatments within the plot. Allows for easier reading of long treatment labels. Takes positive and negative values being number of degrees of rotation from horizontal.
size: Increase or decrease the text size within the plot for treatment labels. Numeric with default value of 4.
margin: Logical (default FALSE). Setting to TRUE will add a margin (white space) between plot and axes.
save: One of FALSE (default)/"none", TRUE/"both", "plot" or "workbook". Specifies which output to save.
savename: A filename for the design to be saved to. Default is the type of the design combined with "_design".
plottype: The type of file to save the plot as. Usually one of "pdf", "png", or "jpg". See ggplot2::ggsave() for all possible options.
return.seed: Logical (default TRUE). Output the seed used in the design?
quiet: Logical (default FALSE). Return the objects without printing output.
...: Additional parameters passed to ggplot2::ggsave() for saving the plot.

Value

A list containing a data frame with the complete design, a ggplot object with plot layout, the seed (if return.seed = TRUE), and the satab object, allowing repeat output of the satab table via cat(output$satab).

Details

If save = TRUE (or "both"), both the plot and the workbook will be saved to the current working directory, with filename given by savename. If one of either "plot" or "workbook" is specified, only that output is saved. If save = FALSE (the default, or equivalently "none"), nothing will be output.

fac.names can be supplied to provide more intuitive names for factors and their levels in factorial designs. They should be specified in a list format, for example fac.names = list(A_names = c("a", "b", "c"), B_names = c("x", "y", "z")). This will result a design output with a column named A_names with levels a, b, c and another named B_names with levels x, y, z. Only the first two elements of the list will be used.

If fac.sep is a single element (e.g. ""), this is used to separate all factor labels (e.g. A_1_B_1). If it is two elements (e.g. c("", "")), the first element separates the factor names and their levels, and the second level separates the two factors (e.g. A1_B1).

... allows extra arguments to be passed to ggsave for output of the plot. The details of possible arguments can be found in ggplot2::ggsave().

Examples

library(agricolae)

# Completely Randomised Design
trt <- c(1, 5, 10, 20)
rep <- 5
outdesign <- design.crd(trt = trt, r = rep, seed = 42)
des.out <- des_info(design.obj = outdesign, nrows = 4, ncols = 5)
#> Source of Variation                     df
#>  =============================================
#>  trt                                     3
#>  Residual                                16
#>  =============================================
#>  Total                                   19


# Randomised Complete Block Design
trt <- LETTERS[1:11]
rep <- 4
outdesign <- design.rcbd(trt = trt, r = rep, seed = 42)
des.out <- des_info(
  design.obj = outdesign, nrows = 11,
  ncols = 4, brows = 11, bcols = 1
)
#> Source of Variation                     df
#>  =============================================
#>  Block stratum                           3
#>  ---------------------------------------------
#>  trt                                     10
#>  Residual                                30
#>  =============================================
#>  Total                                   43


# Latin Square Design
trt <- c("S1", "S2", "S3", "S4")
outdesign <- design.lsd(trt)
des.out <- des_info(design.obj = outdesign, nrows = 4, ncols = 4)
#> Source of Variation                     df
#>  =============================================
#>  Row                                     3
#>  Column                                  3
#>  trt                                     3
#>  Residual                                6
#>  =============================================
#>  Total                                   15


# Factorial Design (Crossed, Completely Randomised)
trt <- c(3, 2) # Factorial 3 x 2
rep <- 3
outdesign <- design.ab(trt, r = rep, design = "crd")
des.out <- des_info(design.obj = outdesign, nrows = 6, ncols = 3)
#> Source of Variation                     df
#>  =============================================
#>  A                                       2
#>  B                                       1
#>  A:B                                     2
#>  Residual                                12
#>  =============================================
#>  Total                                   17


# Factorial Design (Crossed, Completely Randomised), renaming factors
trt <- c(3, 2) # Factorial 3 x 2
rep <- 3
outdesign <- design.ab(trt, r = rep, design = "crd")
des.out <- des_info(design.obj = outdesign, nrows = 6, ncols = 3,
                    fac.names = list(N = c(50, 100, 150),
                                     Water = c("Irrigated", "Rain-fed")))
#> Source of Variation                     df
#>  =============================================
#>  N                                       2
#>  Water                                   1
#>  N:Water                                 2
#>  Residual                                12
#>  =============================================
#>  Total                                   17


# Factorial Design (Nested, Latin Square)
trt <- c("A1", "A2", "A3", "A4", "B1", "B2", "B3")
outdesign <- design.lsd(trt)
des.out <- des_info(design.obj = outdesign, nrows = 7, ncols = 7)
#> Source of Variation                     df
#>  =============================================
#>  Row                                     6
#>  Column                                  6
#>  trt                                     6
#>  Residual                                30
#>  =============================================
#>  Total                                   48


# Split plot design
trt1 <- c("A", "B")
trt2 <- 1:4
rep <- 4
outdesign <- design.split(trt1, trt2, r = rep)
des.out <- des_info(design.obj = outdesign, nrows = 8, ncols = 4, brows = 4, bcols = 2)
#> Source of Variation                          df
#>  ==================================================
#>  Block stratum                                3
#>  --------------------------------------------------
#>  Whole plot stratum
#>           trt1                                1
#>  Whole plot Residual                          3
#>  ==================================================
#>  Subplot stratum
#>           trt2                                3
#>           trt1:trt2                           3
#>           Subplot Residual                   18
#>  ==================================================
#>  Total                                       31