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Find peaks and valleys.

Source: R/stat-peaks.R
stat_peaks.Rd

stat_peaks finds at which x positions local maxima are located. If you want find local minima, you can use stat_valleys instead. Axis flipping is currently not supported.

Usage

stat_peaks(
  mapping = NULL,
  data = NULL,
  geom = "point",
  position = "identity",
  ...,
  span = 5,
  ignore_threshold = 0.01,
  strict = is.null(span),
  refine.wl = FALSE,
  method = "spline",
  chroma.type = "CMF",
  label.fmt = "%.3g",
  x.label.fmt = label.fmt,
  y.label.fmt = label.fmt,
  x.label.transform = I,
  y.label.transform = I,
  x.colour.transform = x.label.transform,
  na.rm = FALSE,
  show.legend = FALSE,
  inherit.aes = TRUE
)

stat_valleys(
  mapping = NULL,
  data = NULL,
  geom = "point",
  position = "identity",
  ...,
  span = 5,
  ignore_threshold = -0.01,
  strict = is.null(span),
  refine.wl = FALSE,
  method = "spline",
  chroma.type = "CMF",
  label.fmt = "%.3g",
  x.label.fmt = label.fmt,
  y.label.fmt = label.fmt,
  x.label.transform = I,
  y.label.transform = I,
  x.colour.transform = x.label.transform,
  na.rm = FALSE,
  show.legend = FALSE,
  inherit.aes = TRUE
)

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

integer 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. Use NULL for the global peak. Valleys are the reverse.

ignore_threshold

numeric For peaks, value between 0.0 and 1.0 indicating the relative size of peaks compared to tallest peak threshold below which peaks will be ignored, while negative values between 0.0 and -1.0 set a threshold so that the tallest peaks are ignored, instead of the shortest. For valleys, value between 0.0 and 1.0 indicating the relative depth of valleys below which valleys will be ignored, while negative values between 0.0 and -1.0 set a threshold so that the deeper valleys are ignored, instead of the shallower ones.

strict

logical If TRUE, an element must be strictly greater than all other values in its window to be considered a peak.

refine.wl

logical Flag indicating if peak or valleys locations should be refined by fitting a function.

method

character String with the name of a method used for peak fitting. Currently only spline interpolation is implemented.

chroma.type

character one of "CMF" (color matching function) or "CC" (color coordinates) or a chroma_spct object.

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.

x.label.transform, y.label.transform, x.colour.transform

function Applied to x or y values when constructing the character labels or computing matching colours.

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.

Value

A data frame with one row for each peak (or valley) found in the data.

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.

Note

These stats work nicely together with geoms geom_text_repel and geom_label_repel from package ggrepel to solve the problem of overlapping labels by displacing them. To discard overlapping labels use check_overlap = TRUE as argument to geom_text. By default the labels are character values suitable to be plotted as is, but with a suitable label.fmt labels suitable for parsing by the geoms (e.g. into expressions containing greek letters or super or subscripts) can be also easily obtained.

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) formatted as character

y.label

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

wl.color

color definition calculated by assuming that x-values are wavelengths expressed in nanometres.

BW.color

color definition, either "black" or "white", as needed to ensure high contrast to wl.color.

Default aesthetics

Set by the statistic and available to geoms.

label

stat(x.label)

xintercept

stat(x)

yintercept

stat(y)

fill

stat(wl.color)

Required aesthetics

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

x

numeric, wavelength in nanometres

y

numeric, a spectral quantity

See also

find_peaks, which is used internally.

Other stats functions: stat_color(), stat_find_qtys(), stat_find_wls(), stat_label_peaks(), stat_spikes(), stat_wb_box(), stat_wb_column(), stat_wb_contribution(), stat_wb_hbar(), stat_wb_irrad(), stat_wb_label(), stat_wb_mean(), stat_wb_relative(), stat_wb_sirrad(), stat_wb_total(), stat_wl_strip(), stat_wl_summary()

Examples


# ggplot() methods for spectral objects set a default mapping for x and y.
ggplot(sun.spct) +
  geom_line() +
  stat_peaks()


ggplot(sun.spct) +
  geom_line() +
  stat_valleys()


ggplot(sun.spct) +
  geom_line() +
  stat_peaks(span = 51, geom = "point", colour = "red") +
  stat_peaks(span = 51, geom = "text", colour = "red",
             vjust = -0.4, label.fmt = "%3.2f nm")


ggplot(sun.spct) +
  geom_line() +
  stat_peaks(span = 51, geom = "point", colour = "red", refine.wl = TRUE) +
  stat_peaks(span = 51, geom = "text", colour = "red",
             vjust = -0.4, label.fmt = "%3.2f nm",
             refine.wl = TRUE)


ggplot(sun.spct) +
  geom_line() +
  stat_peaks(span = 51, geom = "point", colour = "red", refine.wl = TRUE) +
  stat_peaks(mapping = aes(fill = after_stat(wl.colour), color = after_stat(BW.colour)),
             span = 51, geom = "label",
             size = 3, vjust = -0.2, label.fmt = "%.3g nm",
             refine.wl = TRUE) +
  stat_valleys(span = 71, geom = "point", colour = "blue", refine.wl = TRUE) +
  stat_valleys(mapping = aes(fill = after_stat(wl.colour), color = after_stat(BW.colour)),
               span = 71, geom = "label",
               size = 3, vjust = 1.2, label.fmt = "%.3g nm",
               refine.wl = TRUE) +
  expand_limits(y = 0.85) + # make room for label
  scale_fill_identity() +
  scale_color_identity()