Assemble label and map it

Assemble model-fit-derived text or expressions and map them to the label aesthetic.

Usage

use_label(..., labels = NULL, other.mapping = NULL, sep = "*\", \"*")

f_use_label(..., labels = NULL, other.mapping = NULL, format = NULL)

Arguments

...: character Strings giving the names of at most six label components in the order they will be included in the combined label.
labels: character A vector with the name of at most six label components. If provided, values passed through ... are ignored.
other.mapping: An unevaluated expression constructed with function aes() to be included in the returned value.
sep: character A string used as separator when pasting the label components together.
format: character A string with as many labels being mapped. The format string must have mark-up matching the output.type used! With the default geometries, output.type = "expression" requiring that the character string can

Value

A mapping to the label aesthetic and optionally additional mappings as an unevaluated R expression, built using function aes(), ready to be passed as argument to the mapping parameter of the supported statistics.

Details

Statistics stat_poly_eq(), stat_ma_eq(), stat_quant_eq() and stat_correlation() return multiple text strings to be used individually or assembled into longer character strings depending on the labels actually desired. Assembling and mapping them requires verbose R code and familiarity with R expression syntax. Function use_label() automates these two tasks and accepts abbreviated familiar names for the parameters in addition to the name of the columns in the data object returned by the statistics. The default separator is suitable for plotmath expressions.

These four statistics return several character variables with names ending in .label. This ending can be omitted, as well as .value for f.value.label, t.value.label, z.value.label, S.value.label and p.value.label. R2 can be used in place of rr. Furthermore, case is ignored. Thus, use_label("eq", "R2") is equivalent to aes(label = paste(after_stat(eq.label), after_stat(rr.label), sep = ", "))

Function use_label() calls aes() to create a mapping for the label aesthetic to a text string assembled by calling paste(). Function f_use_label() uses sprintf() instead of paste() and expects a format string with the correct number of place-holders for the strings. Both functions can, when needed, combine this mapping to the label aesthetic with other mappings created with aes().

Examples

# generate artificial data
set.seed(4321)
x <- 1:100
y <- (x + x^2 + x^3) + rnorm(length(x), mean = 0, sd = mean(x^3) / 4)
my.data <- data.frame(x = x,
                      y = y * 1e-5,
                      group = c("A", "B"),
                      y2 = y * 1e-5 + c(2, 0))

# give a name to a formula
formula <- y ~ poly(x, 3, raw = TRUE)

# default label constructed by use_label()
ggplot(data = my.data,
       mapping = aes(x = x, y = y2, colour = group)) +
  geom_point() +
  stat_poly_line(formula = formula) +
  stat_poly_eq(mapping = use_label(),
               formula = formula)


# user specified label components and default for sep
ggplot(data = my.data,
       mapping = aes(x = x, y = y2, colour = group)) +
  geom_point() +
  stat_poly_line(formula = formula) +
  stat_poly_eq(mapping = use_label("eq", "F"),
               formula = formula)


# user specified label components and separator
ggplot(data = my.data,
       mapping = aes(x = x, y = y2, colour = group)) +
  geom_point() +
  stat_poly_line(formula = formula) +
  stat_poly_eq(mapping = use_label("R2", "F", sep = "*\" with \"*"),
               formula = formula)


# user specified label components and format string
ggplot(data = my.data,
       mapping = aes(x = x, y = y2, colour = group)) +
  geom_point() +
  stat_poly_line(formula = formula) +
  stat_poly_eq(mapping =
                 f_use_label("R2", "F",
                             format = "\"Estimates: \"*%s*\" with \"*%s*\" works!\""),
               formula = formula)


# combine the mapping to the label aesthetic with other mappings
ggplot(data = my.data,
       mapping = aes(x = x, y = y2)) +
  geom_point(mapping = aes(colour = group)) +
  stat_poly_line(mapping = aes(colour = group), formula = formula) +
  stat_poly_eq(mapping = use_label("grp", "eq", "F",
                                   aes(grp.label = group)),
              formula = formula)


# combine other mappings with default labels
ggplot(data = my.data,
       mapping = aes(x = x, y = y2)) +
  geom_point(mapping = aes(colour = group)) +
  stat_poly_line(mapping = aes(colour = group), formula = formula) +
  stat_poly_eq(mapping = use_label(aes(colour = group)),
              formula = formula)


# example with other available components
ggplot(data = my.data,
       mapping = aes(x = x, y = y2, colour = group)) +
  geom_point() +
  stat_poly_line(formula = formula) +
  stat_poly_eq(mapping = use_label("eq", "adj.R2", "n"),
               formula = formula)


# multiple labels
ggplot(data = my.data,
       mapping = aes(x, y2, colour = group)) +
  geom_point() +
  stat_poly_line(formula = formula) +
  stat_poly_eq(mapping = use_label("R2", "F", "P", "AIC", "BIC"),
               formula = formula) +
  stat_poly_eq(mapping = use_label(c("eq", "n")),
               formula = formula,
               label.y = "bottom",
               label.x = "right")


# quantile regression
ggplot(data = my.data,
       mapping = aes(x, y)) +
  stat_quant_band(formula = formula) +
  stat_quant_eq(mapping = use_label("eq", "n"),
                formula = formula) +
  geom_point()


# major axis regression
ggplot(data = my.data, aes(x = x, y = y)) +
  stat_ma_line() +
  stat_ma_eq(mapping = use_label("eq", "n")) +
  geom_point()


# correlation
ggplot(data = my.data,
       mapping = aes(x = x, y = y)) +
  stat_correlation(mapping = use_label("r", "t", "p")) +
  geom_point()

Usage

Arguments

Value

Details

See also

Examples