stat_peaks: Local maxima (peaks) or minima (valleys)

Description

stat_peaks finds at which x positions local y maxima are located and stat_valleys finds at which x positions local y minima are located. Both stats return a subset of data with rows matching for peaks or valleys with formatted character labels added. The formatting is determined by a format string compatible with sprintf() or strftime().

Usage

stat_peaks(
  mapping = NULL,
  data = NULL,
  geom = "point",
  span = 5,
  ignore_threshold = 0,
  strict = FALSE,
  label.fmt = NULL,
  x.label.fmt = NULL,
  y.label.fmt = NULL,
  orientation = "x",
  position = "identity",
  na.rm = FALSE,
  show.legend = FALSE,
  inherit.aes = TRUE,
  ...
)
stat_valleys(
  mapping = NULL,
  data = NULL,
  geom = "point",
  span = 5,
  ignore_threshold = 0,
  strict = FALSE,
  label.fmt = NULL,
  x.label.fmt = NULL,
  y.label.fmt = NULL,
  orientation = "x",
  position = "identity",
  na.rm = FALSE,
  show.legend = FALSE,
  inherit.aes = TRUE,
  ...
)

Arguments

mapping: The aesthetic mapping, usually constructed with aes. Only needs to be set at the layer level if you are overriding the plot defaults.
data: A layer specific dataset - only needed if you want to override the plot defaults.
geom: The geometric object to use display the data.
span: a peak is defined as an element in a sequence which is greater than all other elements within a window of width span centered at that element. The default value is 5, meaning that a peak is bigger than two consecutive neighbors on each side. A NULL value for span is taken as a span covering the whole of the data range.
ignore_threshold: numeric value between 0.0 and 1.0 indicating the size threshold below which peaks will be ignored.
strict: logical flag: if TRUE, an element must be strictly greater than all other values in its window to be considered a peak. Default: FALSE.
label.fmt: character string giving a format definition for converting values into character strings by means of function sprintf or strptime, its use is deprecated.
x.label.fmt: character string giving a format definition for converting $x$-values into character strings by means of function sprintf or strftime. The default argument varies depending on the scale in use.
y.label.fmt: character string giving a format definition for converting $y$-values into character strings by means of function sprintf.
orientation: character Either "x" or "y".
position: The position adjustment to use for overlapping points on this layer.
na.rm: a logical value indicating whether NA values should be stripped before the computation proceeds.
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.
inherit.aes: If FALSE, overrides the default aesthetics, rather than combining with them. This is most useful for helper functions that define both data and aesthetics and shouldn't inherit behaviour from the default plot specification, e.g. borders.
...: other arguments passed on to layer. This can include aesthetics whose values you want to set, not map. See layer for more details.

Returned and computed variables

x: x-value at the peak (or valley) as numeric

y-value at the peak (or valley) as numeric

x.label

x-value at the peak (or valley) as character

y.label

y-value at the peak (or valley) as character

Warning!

The current version of these statistics do not support passing nudge_x or nurge_y named parameters to the geometry. Use `position` and one of the position functions such as position_nudge_keep instead.

Details

These stats use geom_point by default as it is the geom most likely to work well in almost any situation without need of tweaking. The default aesthetics set by these stats allow their direct use with geom_text, geom_label, geom_line, geom_rug, geom_hline and geom_vline. The formatting of the labels returned can be controlled by the user.

The default for parameter strict is TRUE in functions splus2R::peaks() and find_peaks(), while the default is FALSE in stat_peaks() and in stat_valleys().

Examples

Run this code

# lynx is a time.series object
lynx_num.df <-
  try_tibble(lynx,
             col.names = c("year", "lynx"),
             as.numeric = TRUE) # years -> as numeric

ggplot(lynx_num.df, aes(year, lynx)) +
  geom_line() +
  stat_peaks(colour = "red") +
  stat_valleys(colour = "blue")

ggplot(lynx_num.df, aes(lynx, year)) +
  geom_line(orientation = "y") +
  stat_peaks(colour = "red", orientation = "y") +
  stat_valleys(colour = "blue", orientation = "y")

ggplot(lynx_num.df, aes(year, lynx)) +
  geom_line() +
  stat_peaks(colour = "red") +
  stat_peaks(colour = "red", geom = "rug")

ggplot(lynx_num.df, aes(year, lynx)) +
  geom_line() +
  stat_peaks(colour = "red") +
  stat_peaks(colour = "red", geom = "text", hjust = -0.1, angle = 33)

ggplot(lynx_num.df, aes(lynx, year)) +
  geom_line(orientation = "y") +
  stat_peaks(colour = "red", orientation = "y") +
  stat_peaks(colour = "red", orientation = "y",
             geom = "text", hjust = -0.1)

lynx_datetime.df <-
   try_tibble(lynx,
              col.names = c("year", "lynx")) # years -> POSIXct

ggplot(lynx_datetime.df, aes(year, lynx)) +
  geom_line() +
  stat_peaks(colour = "red") +
  stat_valleys(colour = "blue")

ggplot(lynx_datetime.df, aes(year, lynx)) +
  geom_line() +
  stat_peaks(colour = "red") +
  stat_peaks(colour = "red",
             geom = "text",
             hjust = -0.1,
             x.label.fmt = "%Y",
             angle = 33)

ggplot(lynx_datetime.df, aes(year, lynx)) +
  geom_line() +
  stat_peaks(colour = "red") +
  stat_peaks(colour = "red",
             geom = "text_s",
             position = position_nudge_keep(x = 0, y = 200),
             hjust = -0.1,
             x.label.fmt = "%Y",
             angle = 90) +
  expand_limits(y = 8000)

ggplot(lynx_datetime.df, aes(year, lynx)) +
  geom_line() +
  stat_peaks(colour = "red",
             geom = "text_s",
             position = position_nudge_to(y = 7600),
             arrow = arrow(length = grid::unit(1.5, "mm")),
             point.padding = 0.7,
             x.label.fmt = "%Y",
             angle = 90) +
  expand_limits(y = 9000)

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