These functions create layers that display lines described i various ways. Unlike most of the plotting functions in ggformula, these functions do not take a formula as input for describing positional attributes of the plot.

gf_abline(
  object = NULL,
  gformula = NULL,
  data = NULL,
  ...,
  slope,
  intercept,
  color,
  linetype,
  linewidth,
  alpha,
  xlab,
  ylab,
  title,
  subtitle,
  caption,
  show.legend = NA,
  show.help = NULL,
  inherit = FALSE,
  environment = parent.frame()
)

gf_hline(
  object = NULL,
  gformula = NULL,
  data = NULL,
  ...,
  yintercept,
  color,
  linetype,
  linewidth,
  alpha,
  xlab,
  ylab,
  title,
  subtitle,
  caption,
  show.legend = NA,
  show.help = NULL,
  inherit = FALSE,
  environment = parent.frame()
)

gf_vline(
  object = NULL,
  gformula = NULL,
  data = NULL,
  ...,
  xintercept,
  color,
  linetype,
  linewidth,
  alpha,
  xlab,
  ylab,
  title,
  subtitle,
  caption,
  show.legend = NA,
  show.help = NULL,
  inherit = FALSE,
  environment = parent.frame()
)

gf_coefline(object = NULL, coef = NULL, model = NULL, ...)

Arguments

object

When chaining, this holds an object produced in the earlier portions of the chain. Most users can safely ignore this argument. See details and examples.

gformula

Must be NULL.

data

The data to be displayed in this layer. There are three options:

If NULL, the default, the data is inherited from the plot data as specified in the call to ggplot().

A data.frame, or other object, will override the plot data. All objects will be fortified to produce a data frame. See fortify() for which variables will be created.

A function will be called with a single argument, the plot data. The return value must be a data.frame, and will be used as the layer data. A function can be created from a formula (e.g. ~ head(.x, 10)).

...

Additional arguments. Typically these are (a) ggplot2 aesthetics to be set with attribute = value, (b) ggplot2 aesthetics to be mapped with attribute = ~ expression, or (c) attributes of the layer as a whole, which are set with attribute = value.

color

A color or a formula used for mapping color.

linetype

A linetype (numeric or "dashed", "dotted", etc.) or a formula used for mapping linetype.

linewidth

A numerical line width or a formula used for mapping linewidth.

alpha

Opacity (0 = invisible, 1 = opaque).

xlab

Label for x-axis. See also gf_labs().

ylab

Label for y-axis. See also gf_labs().

title, subtitle, caption

Title, sub-title, and caption for the plot. See also gf_labs().

show.legend

logical. Should this layer be included in the legends? NA, the default, includes if any aesthetics are mapped. FALSE never includes, and TRUE always includes. It can also be a named logical vector to finely select the aesthetics to display.

show.help

If TRUE, display some minimal help.

inherit

A logical indicating whether default attributes are inherited.

environment

An environment in which to look for variables not found in data.

xintercept, yintercept, slope, intercept

Parameters that control the position of the line. If these are set, data, mapping and show.legend are overridden.

coef

A numeric vector of coefficients.

model

A model from which to extract coefficients.

Examples

mtcars2 <- df_stats(wt ~ cyl, data = mtcars, median_wt = median)
gf_point(wt ~ hp, size = ~wt, color = ~cyl, data = mtcars) |>
  gf_abline(slope = ~0, intercept = ~median_wt, color = ~cyl, data = mtcars2)


gf_point(wt ~ hp, size = ~wt, color = ~cyl, data = mtcars) |>
  gf_abline(slope = 0, intercept = 3, color = "green")


# avoid warnings by using formulas:

gf_point(wt ~ hp, size = ~wt, color = ~cyl, data = mtcars) |>
  gf_abline(slope = ~0, intercept = ~3, color = "green")


gf_point(wt ~ hp, size = ~wt, color = ~cyl, data = mtcars) |>
  gf_hline(yintercept = ~median_wt, color = ~cyl, data = mtcars2)


gf_point(mpg ~ hp, color = ~cyl, size = ~wt, data = mtcars) |>
  gf_abline(color = "red", slope = ~ - 0.10, intercept = ~ 35)


gf_point(mpg ~ hp, color = ~cyl, size = ~wt, data = mtcars) |>
  gf_abline(
    color = "red", slope = ~slope, intercept = ~intercept,
    data = data.frame(slope = -0.10, intercept = 33:35)
  )


# We can set the color of the guidelines while mapping color in other layers
gf_point(mpg ~ hp, color = ~cyl, size = ~ wt, data = mtcars) |>
  gf_hline(color = "navy", yintercept = ~ c(20, 25), data = NA) |>
  gf_vline(color = "brown", xintercept = ~ c(200, 300), data = NA)


# If we want to map the color of the guidelines, it must work with the
# scale of the other colors in the plot.
gf_point(mpg ~ hp, size = ~wt, data = mtcars, alpha = 0.3) |>
  gf_hline(color = ~"horizontal", yintercept = ~ c(20, 25), data = NA) |>
  gf_vline(color = ~"vertical", xintercept = ~ c(100, 200, 300), data = NA)


gf_point(mpg ~ hp, size = ~wt, color = ~ factor(cyl), data = mtcars, alpha = 0.3) |>
  gf_hline(color = "orange", yintercept = ~ 20) |>
  gf_vline(color = ~ c("4", "6", "8"), xintercept = ~ c(80, 120, 250), data = NA)


gf_point(mpg ~ hp, size = ~wt, color = ~ factor(cyl), data = mtcars, alpha = 0.3) |>
  gf_hline(color = "orange", yintercept = ~ 20) |>
  gf_vline(color = c("green", "red", "blue"), xintercept = ~ c(80, 120, 250),
    data = NA)


# reversing the layers requires using inherit = FALSE
gf_hline(color = "orange", yintercept = ~ 20) |>
  gf_vline(color = ~ c("4", "6", "8"), xintercept = ~ c(80, 120, 250), data = NA) |>
  gf_point(mpg ~ hp,
    size = ~wt, color = ~ factor(cyl), data = mtcars, alpha = 0.3,
    inherit = FALSE
  )