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

In ggpmisc: Miscellaneous Extensions to 'ggplot2'

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.

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().

Returned and computed variables

x

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

y

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.

Note

These statistics check the scale of the x aesthetic and if it is Date or Datetime they correctly generate the labels by transforming the numeric x values to Date or POSIXct objects, respectively. In which case the x.label.fmt must follow the syntax supported by strftime() rather than by sprintf(). Overlap of labels with points can avoided by use of one of the nudge positions, possibly together with geometry geom_text_s from package ggpp, or with geom_text_repel or geom_label_repel from package ggrepel. To discard overlapping labels use check_overlap = TRUE as argument to geom_text or geom_text_s. By default the labels are character values suitable to be plotted as is, but with a suitable format passed as argument to label.fmt labels suitable for parsing by the geoms (e.g. into expressions containing Greek letters, super- or subscripts, maths symbols or maths constructs) can be also easily obtained.

Examples

# 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)

ggpmisc documentation built on June 28, 2024, 1:07 a.m.