# Produce a graph of design layout, skeletal ANOVA table and data frame with complete design ```r des_info( design.obj, nrows, ncols, brows = NA, bcols = NA, byrow = TRUE, fac.names = NULL, fac.sep = c("", " "), buffer = NULL, 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. - `buffer`: The type of buffer. One of edge, row, column, double row, double column, or block (coming soon). - `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. ## Returns 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 ```r 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) # 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 ) # Latin Square Design trt <- c("S1", "S2", "S3", "S4") outdesign <- design.lsd(trt) des.out <- des_info(design.obj = outdesign, nrows = 4, ncols = 4) # 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) # 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"))) # 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) # 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) ```

des_info function