Skip to contents

Automatic plots for objects generated in biometryassist

Source: R/autoplot.R
autoplot.Rd

These objects are imported from other packages. Follow the links below to see their documentation.

ggplot2

autoplot

Usage

# S3 method for mct
autoplot(
  object,
  size = 4,
  label_height = 0.1,
  rotation = 0,
  axis_rotation = rotation,
  label_rotation = rotation,
  ...
)

# S3 method for design
autoplot(
  object,
  rotation = 0,
  size = 4,
  margin = FALSE,
  palette = "default",
  row = NULL,
  col = NULL,
  block = NULL,
  ...
)

Arguments

object

An object to create a plot for. Currently objects from the multiple_comparisons() or design() functions with class "mct" or "design" respectively are supported.

size

Increase or decrease the text size within the plot for treatment labels. Numeric with default value of 4.

label_height

Height of the text labels above the upper error bar on the plot. Default is 0.1 (10%) of the difference between upper and lower error bars above the top error bar. Values > 1 are interpreted as the actual value above the upper error bar.

rotation

Rotate the x axis labels and the treatment group labels within the plot. Allows for easier reading of long axis or treatment labels. Number between 0 and 360 (inclusive) - default 0

axis_rotation

Enables rotation of the x axis independently of the group labels within the plot.

label_rotation

Enables rotation of the treatment group labels independently of the x axis labels within the plot.

...

Arguments passed to methods.

margin

Logical (default FALSE). A value of FALSE will expand the plot to the edges of the plotting area i.e. remove white space between plot and axes.

palette

A string specifying the colour scheme to use for plotting. Default is equivalent to "Spectral". Colour blind friendly palettes can also be provided via options "colour blind" (or "color blind", both equivalent to "viridis"), "magma", "inferno", "plasma" or "cividis". Other palettes from scales::brewer_pal() are also possible.

Value

A ggplot2 object.

See also

multiple_comparisons() and design()

Examples

dat.aov <- aov(Petal.Width ~ Species, data = iris)
output <- multiple_comparisons(dat.aov, classify = "Species")
autoplot(output, label_height = 0.5)

des.out <- design(type = "crd", treatments = c(1, 5, 10, 20),
                  reps = 5, nrows = 4, ncols = 5, seed = 42, plot = FALSE)
#> Source of Variation                     df
#>  =============================================
#>  treatments                              3
#>  Residual                                16
#>  =============================================
#>  Total                                   19
autoplot(des.out)


# Colour blind friendly colours
autoplot(des.out, palette = "colour-blind")


# Alternative colour scheme
autoplot(des.out, palette = "plasma")