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

Description

stat_peaks finds at which x positions the global y maximun or local y maxima are located. stat_valleys finds at which x positions the global y minimum or local y minima located. They both support filtering of relevant peaks. Axis flipping is supported.

Usage

stat_peaks(
  mapping = NULL,
  data = NULL,
  geom = "point",
  position = "identity",
  ...,
  span = 5,
  global.threshold = 0,
  local.threshold = 0,
  local.reference = "median",
  strict = FALSE,
  label.fmt = NULL,
  x.label.fmt = NULL,
  y.label.fmt = NULL,
  extract.peaks = NULL,
  orientation = "x",
  na.rm = FALSE,
  show.legend = FALSE,
  inherit.aes = TRUE
)
stat_valleys(
  mapping = NULL,
  data = NULL,
  geom = "point",
  position = "identity",
  ...,
  span = 5,
  global.threshold = 0.01,
  local.threshold = NULL,
  local.reference = "median",
  strict = FALSE,
  label.fmt = NULL,
  x.label.fmt = NULL,
  y.label.fmt = NULL,
  extract.valleys = NULL,
  orientation = "x",
  na.rm = FALSE,
  show.legend = FALSE,
  inherit.aes = TRUE
)

Value

A data frame with one row for each peak (or valley) found in the data extracted from the input data or all rows in data. Added columns contain the labels.

Arguments

mapping: The aesthetic mapping, usually constructed with aes or 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
position: The position adjustment to use for overlapping points on this layer
...: other arguments passed on to layer. This can include aesthetics whose values you want to set, not map. See layer for more details.
span: odd positive integer A peak is defined as an element in a sequence which is greater than all other elements within a moving window of width span centred at that element. The default value is 5, meaning that a peak is taller than its four nearest neighbours. span = NULL extends the span to the whole length of x.
global.threshold: numeric A value belonging to class "AsIs" is interpreted as an absolute minimum height or depth expressed in data units. A bare numeric value (normally between 0.0 and 1.0), is interpreted as relative to the range of the data. In both cases it sets a global height (depth) threshold below which peaks (valleys) are ignored. A bare negative numeric value indicates the global height (depth) threshold below which peaks (valleys) are be ignored. If global.threshold = NULL, no threshold is applied and all peaks are returned.
local.threshold: numeric A value belonging to class "AsIs" is interpreted as an absolute minimum height (depth) expressed in data units relative to the within-window computed minimum (maximum) value. A bare numeric value (normally between 0.0 and 1.0), is interpreted as expressed in units relative to the range of the data. In both cases local.threshold sets a local height (depth) threshold below which peaks (valleys) are ignored. If local.threshold = NULL or if span spans the whole of x, no threshold is applied.
local.reference: character One of "minimum"/maximum or "median". The reference used to assess the height of the peak, either the minimum value within the window or the median of all values in the window.
strict: logical flag: if TRUE, an element must be strictly greater than all other values in its window to be considered a peak.
label.fmt, x.label.fmt, y.label.fmt: character strings giving a format definition for construction of character strings labels with function sprintf from x and/or y values.
extract.peaks, extract.valleys: If TRUE only the rows containing peaks or valleys are returned. If FALSE the whole of data is returned but with labels set to NA in rows not containing peaks or valleys. If NULL, the default, TRUE, is used unless the geom name passed as argument is "text_repel" or "label_repel".
orientation: character The orientation of the layer can be set to either "x", the default, or "y".
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.

Computed and copied variables in the returned data frame

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) formatted as character

y.label

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

Default aesthetics

Set by the statistic and available to geoms.

label: stat(x.label)
xintercept: stat(x)
yintercept: stat(y)

Required aesthetics

Required by the statistic and need to be set with aes().

x: numeric, wavelength in nanometres
y: numeric, a spectral quantity

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.

Two tests make it possible to ignore irrelevant peaks or valleys. One test controlled by (global.threshold) is based on the absolute height/depth of peaks/valleys and can be used in all cases to ignore globally low peaks and shallow valleys. A second test controlled by (local.threshold) is available when the window defined by `span` does not include all observations and can be used to ignore peaks/valleys that are not locally prominent. In this second approach the height/depth of each peak/valley is compared to a summary computed from other values within the window where it was found. In this second case, the reference value used is the summary indicated by local.reference. The values global.threshold and local.threshold if bare numeric are relative to the range of y. Thresholds for ignoring too small peaks are applied after peaks are searched for, and threshold values can in some cases result in no peaks being displayed.

Date time scales are recognized and labels formatted accordingly.

Examples

Run this code

# lynx and Nile are time.series objects recognized by
# ggpp::ggplot.ts() and converted on-the-fly with a default mapping

# numeric, date times and dates are supported with data frames

# using defaults
ggplot(Nile) +
  geom_line() +
  stat_peaks(colour = "red") +
  stat_valleys(colour = "blue")

# using wider window
ggplot(Nile) +
  geom_line() +
  stat_peaks(colour = "red", span = 11) +
  stat_valleys(colour = "blue", span = 11)

# global threshold for peak height
ggplot(Nile) +
  geom_line() +
  stat_peaks(colour = "red",
             global.threshold = 0.5) # half of data range

ggplot(Nile) +
  geom_line() +
  stat_peaks(colour = "red",
             global.threshold = I(1100)) + # data unit
             expand_limits(y = c(0, 1500))

# local (within window) threshold for peak height
# narrow peaks at the tip and locally tall

ggplot(Nile) +
  geom_line() +
  stat_peaks(colour = "red",
             span = 9,
             local.threshold = 0.3,
             local.reference = "farthest")

# with narrower window
ggplot(Nile) +
  geom_line() +
  stat_peaks(colour = "red",
             span = 5,
             local.threshold = 0.25,
             local.reference = "farthest")

ggplot(lynx) +
  geom_line() +
  stat_peaks(colour = "red",
             local.threshold = 1/5,
             local.reference = "median")

ggplot(Nile) +
  geom_line() +
  stat_valleys(colour = "blue",
               global.threshold = I(700))

# orientation is supported
ggplot(lynx, aes(lynx, time)) +
  geom_line(orientation = "y") +
  stat_peaks(colour = "red", orientation = "y") +
  stat_valleys(colour = "blue", orientation = "y")

# default aesthetic mapping supports additional geoms
ggplot(lynx) +
  geom_line() +
  stat_peaks(colour = "red") +
  stat_peaks(colour = "red", geom = "rug")

ggplot(lynx) +
  geom_line() +
  stat_peaks(colour = "red") +
  stat_peaks(colour = "red", geom = "text", hjust = -0.1, angle = 33)

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

# Force conversion of time series time into POSIXct date time
ggplot(lynx, as.numeric = FALSE) +
  geom_line() +
  stat_peaks(colour = "red") +
  stat_peaks(colour = "red",
             geom = "text",
             hjust = -0.1,
             x.label.fmt = "%Y",
             angle = 33)

ggplot(Nile, as.numeric = FALSE) +
  geom_line() +
  stat_peaks(colour = "red") +
  stat_peaks(colour = "red",
             geom = "text_s",
             position = position_nudge_keep(x = 0, y = 60),
             hjust = -0.1,
             x.label.fmt = "%Y",
             angle = 90) +
  expand_limits(y = 2000)

ggplot(lynx, as.numeric = FALSE) +
  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)

Run the code above in your browser using DataLab