ggspectra (version 0.3.13)

stat_spikes: Find spikes

Description

stat_spikes finds at which x positions spikes are located. Spikes can be either upwards or downwards from the baseline.

Usage

stat_spikes(
  mapping = NULL,
  data = NULL,
  geom = "point",
  position = "identity",
  ...,
  z.threshold = 9,
  max.spike.width = 8,
  chroma.type = "CMF",
  label.fmt = "%.3g",
  x.label.fmt = label.fmt,
  y.label.fmt = label.fmt,
  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.

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.

z.threshold

numeric Modified Z values larger than z.threshold are considered to be spikes.

max.spike.width

integer Wider regions with high Z values are not detected as spikes.

chroma.type

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

label.fmt

character string giving a format definition for converting values into character strings by means of function sprintf.

x.label.fmt

character string giving a format definition for converting $x$-values into character strings by means of function sprintf.

y.label.fmt

character string giving a format definition for converting $y$-values into character strings by means of function sprintf.

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 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 that either "black" or "white", 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

Details

This stat uses 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 this stat allows its 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.

See Also

find_spikes, which is used internally, for a description of the algorithm used.

Other stats functions: stat_color(), stat_find_qtys(), stat_find_wls(), stat_label_peaks(), stat_peaks(), 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.

# two spurious(?) spikes
ggplot(sun.spct) +
  geom_line() +
  stat_spikes(colour = "red", alpha = 0.3)

# no spikes detected
ggplot(sun.spct) +
  geom_line() +
  stat_spikes(colour = "red", alpha = 0.3,
              max.spike.width = 3,
              z.threshold = 12)

# small noise spikes detected
ggplot(white_led.raw_spct) +
  geom_line() +
  stat_spikes(colour = "red", alpha = 0.3)

ggplot(white_led.raw_spct) +
  geom_line() +
  stat_spikes(colour = "red", alpha = 0.3) +
  stat_spikes(geom = "text", colour = "red", check_overlap = TRUE,
             vjust = -0.5, label.fmt = "%3.0f nm")

ggplot(white_led.raw_spct, aes(w.length, counts_2)) +
  geom_line() +
  stat_spikes(colour = "red", alpha = 0.3,
              max.spike.width = 3,
              z.threshold = 12)