Package 'ggbumpribbon'

Description

geom_bump_line() renders smooth curves connecting discrete rank positions across time periods. It is the line counterpart to geom_bump_ribbon(), producing stroked paths instead of filled areas.

Usage

geom_bump_line(
  mapping = NULL,
  data = NULL,
  position = "identity",
  ...,
  smooth = 8,
  n = 100,
  method = "sigmoid",
  na.rm = FALSE,
  show.legend = NA,
  inherit.aes = TRUE
)

Arguments

Value

A ggplot2 layer that can be added to a plot.

Aesthetics

geom_bump_line() understands the following aesthetics (required aesthetics are in bold):

• x

• y

• alpha

• colour

• group

• linetype

• linewidth

Computed variables

avg_y

Mean of y values in the group, inverse-transformed to original data space. Works correctly with scale_y_reverse(). Map to colour via after_stat(avg_y).

Multi-bend curves

The number of bends is controlled by the data, not by parameters. Two x-values produce one sigmoid. Four x-values (with the two middle points holding the start/end y positions) produce three sigmoids that mimic the "exit–channel–enter" pattern common in infographics:

df <- data.frame(
  x     = rep(c(1, 1.4, 1.6, 2), each = 5),
  y     = c(from, from, to, to),
  group = rep(groups, 4)
)

See Also

geom_bump_ribbon(), ggplot2::geom_path()

Other bump geoms: geom_bump_ribbon()

Examples

library(ggplot2)

# basic 2-point line bump
df <- data.frame(
  x     = rep(1:2, each = 5),
  y     = c(1, 2, 3, 4, 5, 3, 1, 5, 2, 4),
  group = rep(LETTERS[1:5], 2)
)
ggplot(df, aes(x, y, group = group, colour = after_stat(avg_y))) +
  geom_bump_line(linewidth = 1) +
  scale_colour_viridis_c() +
  scale_y_reverse()

# 3-bend pattern (exit-channel-enter)
df3 <- data.frame(
  x     = rep(c(1, 1.4, 1.6, 2), each = 5),
  y     = c(1,2,3,4,5, 1,2,3,4,5, 3,1,5,2,4, 3,1,5,2,4),
  group = rep(LETTERS[1:5], 4)
)
ggplot(df3, aes(x, y, group = group, colour = after_stat(avg_y))) +
  geom_bump_line(linewidth = 1.2) +
  scale_colour_viridis_c() +
  scale_y_reverse()

Description

geom_bump_ribbon() renders filled ribbons that follow smooth curves between discrete rank positions. It is the filled-area counterpart to ggbump's geom_bump() (https://github.com/davidsjoberg/ggbump).

Usage

geom_bump_ribbon(
  mapping = NULL,
  data = NULL,
  position = "identity",
  ...,
  smooth = 8,
  n = 100,
  width = 0.8,
  method = "sigmoid",
  na.rm = FALSE,
  show.legend = NA,
  inherit.aes = TRUE
)

Arguments

Value

A ggplot2 layer that can be added to a plot.

Aesthetics

geom_bump_ribbon() understands the following aesthetics (required aesthetics are in bold):

• x

• y

• alpha

• colour

• fill

• group

• linetype

• linewidth

Computed variables

ymin

Lower ribbon boundary.

ymax

Upper ribbon boundary.

avg_y

Mean of y values in the group, inverse-transformed to original data space. Works correctly with scale_y_reverse() and other scale transforms. Map to fill via after_stat(avg_y).

Interpolation methods

When a group has 3 or more time points, adjacent segments must be joined.

"sigmoid" (default)

Each segment follows a logistic sigmoid $\sigma(t) = 1/(1+e^{-t})$ on $t \in [-s, s]$ where $s$ is the smooth parameter. Endpoints are clamped to exact knot values by rescaling $\sigma$ to $[0, 1]$, and a Hermite-basis derivative correction drives the slope to zero at every interior knot, guaranteeing C1 (first-derivative) continuity across segments. The smooth parameter controls steepness: lower values (e.g. 2–3) give gentle S-curves, higher values (e.g. 12–15) give near-step-function transitions.

"hermite"

Uses stats::splinefunH() with zero slopes at all knots (the cubic Hermite "smoothstep"). This is mathematically simpler: a single spline is evaluated across all knots, with C1 continuity guaranteed by construction. The smooth parameter is ignored. The visual shape is similar to "sigmoid" but not identical — the cubic polynomial $3t^2 - 2t^3$ has slightly different curvature distribution than the logistic function.

Both methods produce identical results for 2-point groups (a single segment has no join to worry about).

See Also

geom_bump_line(), ggplot2::geom_ribbon()

Other bump geoms: geom_bump_line()

Examples

library(ggplot2)

# basic: 5 items, 2 time points
df <- data.frame(
  x     = rep(1:2, each = 5),
  y     = c(1, 2, 3, 4, 5, 3, 1, 5, 2, 4),
  group = rep(LETTERS[1:5], 2)
)
ggplot(df, aes(x, y, group = group, fill = after_stat(avg_y))) +
  geom_bump_ribbon() +
  scale_fill_viridis_c() +
  scale_y_reverse()

# multi-period: 3 time points
df3 <- data.frame(
  x     = rep(1:3, each = 4),
  y     = c(1,2,3,4, 3,1,4,2, 2,4,1,3),
  group = rep(LETTERS[1:4], 3)
)
ggplot(df3, aes(x, y, group = group, fill = after_stat(avg_y))) +
  geom_bump_ribbon(alpha = 0.7) +
  scale_fill_viridis_c() +
  scale_y_reverse()

# Hermite method
ggplot(df3, aes(x, y, group = group, fill = after_stat(avg_y))) +
  geom_bump_ribbon(method = "hermite", alpha = 0.7) +
  scale_fill_viridis_c() +
  scale_y_reverse()

# mtcars: MPG rank vs HP rank
mt <- mtcars[1:10, ]
mt$car   <- rownames(mt)
mt_long  <- data.frame(
  x     = rep(1:2, each = 10),
  y     = c(rank(-mt$mpg), rank(-mt$hp)),
  group = rep(mt$car, 2)
)
ggplot(mt_long, aes(x, y, group = group, fill = after_stat(avg_y))) +
  geom_bump_ribbon() +
  scale_fill_gradientn(colours = c("#2ecc71", "#f7dc6f", "#eb4d4b"),
                       guide = "none") +
  scale_y_reverse() +
  theme_void()

Description

A convenience wrapper around ggplot2::scale_fill_gradientn() with defaults suited to rank comparison charts (green = best, red = worst).

Usage

scale_fill_rank(
  colors = c("#2ecc71", "#a8e063", "#f7dc6f", "#f0932b", "#eb4d4b", "#c0392b"),
  limits = NULL,
  ...
)

Arguments

Value

A ggplot2 scale object.

See Also

ggplot2::scale_fill_gradientn(), geom_bump_ribbon()

Other bump scales: theme_bump()

Examples

library(ggplot2)
df <- data.frame(
  x     = rep(1:2, each = 5),
  y     = c(1,2,3,4,5, 3,1,5,2,4),
  group = rep(LETTERS[1:5], 2)
)
ggplot(df, aes(x, y, group = group, fill = after_stat(avg_y))) +
  geom_bump_ribbon() +
  scale_fill_rank() +
  scale_y_reverse()

Description

These ggproto objects implement the statistical transformations for bump ribbon and line charts. They are exported for extensibility but should typically be used through geom_bump_ribbon() and geom_bump_line().

Value

ggproto objects that should not be called directly.

See Also

ggplot2::Stat, ggplot2::ggproto()

Description

A minimal dark theme based on ggplot2::theme_void() with a dark background and light text, suited to rank comparison infographics.

Usage

theme_bump(bg = "#1a1a2e", title_color = "#e74c3c", base_size = 10)

Arguments

Value

A ggplot2 theme object.

See Also

ggplot2::theme_void(), geom_bump_ribbon()

Other bump scales: scale_fill_rank()

Examples

library(ggplot2)
ggplot(mtcars, aes(wt, mpg)) +
  geom_point(colour = "white") +
  labs(title = "Motor Trend Cars") +
  theme_bump()