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Label peaks and valleys.

Source: R/stat-label-peaks.R
stat_label_peaks.Rd

stat_labels_peaks finds at which x positions local maxima are located, and adds labels and colors to the data without subsetting. To find local minima, you can use stat_labels_valleys instead. The variable mapped to the x aesthetic is expected to contain wavelength values expressed in nanometres. Axis flipping is currently not supported.

Usage

stat_label_peaks(
  mapping = NULL,
  data = NULL,
  geom = "text",
  position = "identity",
  ...,
  span = 5,
  ignore_threshold = 0,
  strict = TRUE,
  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,
  label.fill = "",
  na.rm = TRUE,
  show.legend = FALSE,
  inherit.aes = TRUE
)

stat_label_valleys(
  mapping = NULL,
  data = NULL,
  geom = "text",
  position = "identity",
  ...,
  span = 5,
  ignore_threshold = 0,
  strict = TRUE,
  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,
  label.fill = "",
  na.rm = TRUE,
  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

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 consequtive neighbors on each side. Default: 5.

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.

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.

label.fill

character string to use for labels not at peaks or valleys being highlighted.

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

The original data with additional computed variables added.

Details

These statistics assemble text labels for each peak or valley and compute the colour corresponding to the wavelength of the peaks and valleys. Defaults work as long as the variable mapped to the x aesthetic contains wavelengths expressed in nanometres and the plot has an x-scale that does not apply a transformation. The three transform parameters can be used to back-transform the values when scales apply transformations so that peak/valley labels and axis labels match. Of course, x.label.transform and y.label.transform make also possible to scale the values in the labels.

Both statistics use geom_text by default as it is the geom most likely to work well in almost any situation without need of tweaking. These statistics work best with geom_text_repel and geom_label_repel from package 'ggrepel' as they are designed so that peak or valley labels will not overlap any observation in the whole data set. Default aesthetics set by these statistics 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.label

x-value at a peak (or valley) formatted as character or otherwise the value passed to label.fill which defaults to an empty string ("").

y.label

y-value at the peak (or valley) formatted as character or otherwise the value passed to label.fill which defaults to an empty string ("").

wl.color

At peaks and valleys, color definition calculated by assuming that x-values are wavelengths expressed in nanometres, otherwise, rgb(1, 1, 1, 0) (transparent white).

Default aesthetics

Set by the statistic and available to geoms.

label

..x.label..

xintercept

..x..

yintercept

..y..

color

black_or_white(..wl.color..)

fill

..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

stat_peaks, stat_valleys and find_peaks, which is used internally.

Other stats functions: stat_color(), stat_find_qtys(), stat_find_wls(), stat_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_label_peaks(hjust = "left", span = 31, angle = 90, color = "red")


ggplot(sun.spct) +
  geom_line() +
  stat_label_valleys(hjust = "right", span = 21, angle = 90, color = "blue")


# using transformed scales requires the user to pass functions as arguments
ggplot(sun.spct) +
  geom_line() +
  stat_label_peaks(hjust = "left", span = 31, angle = 90, color = "red",
                   x.label.transform = abs) +
  scale_x_reverse()


ggplot(sun.spct) +
  geom_line() +
  stat_label_peaks(hjust = "left", span = 31, angle = 90, color = "red",
                   x.label.transform = function(x) {10^x}) +
  scale_x_log10()


# geom_label
ggplot(sun.spct) +
  geom_line() +
  stat_peaks(span = 41, shape = 21, size = 3) +
  stat_label_peaks(span = 41, geom = "label", label.fmt = "%3.0f nm") +
  scale_fill_identity() +
  scale_color_identity() +
  expand_limits(y = c(NA, 1))


# using 'ggrepel' to avoid overlaps
# too slow for CRAN checks
if (FALSE) { # \dontrun{
library(ggrepel)

ggplot(sun.spct) + geom_line() +
  stat_peaks(span = 41, shape = 21, size = 3) +
  stat_label_peaks(span = 41, geom = "label_repel", segment.colour = "red",
                   nudge_y = 0.12, label.fmt = "%3.0f nm",
                   max.overlaps = Inf, min.segment.length = 0) +
  scale_fill_identity() +
  scale_color_identity() +
  expand_limits(y = c(NA, 1))
} # }