stat_peaks {ggspectra} | R Documentation |
Find peaks and valleys.
Description
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,
global.threshold = ignore_threshold,
local.threshold = NULL,
local.reference = "median",
strict = FALSE,
refine.wl = FALSE,
method = "spline",
chroma.type = "CMF",
label.fmt = "%.3g",
x.label.fmt = label.fmt,
y.label.fmt = label.fmt,
x.label.transform = function(x) {
x
},
y.label.transform = function(x) {
x
},
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,
global.threshold = ignore_threshold,
local.threshold = NULL,
local.reference = "median",
strict = FALSE,
refine.wl = FALSE,
method = "spline",
chroma.type = "CMF",
label.fmt = "%.3g",
x.label.fmt = label.fmt,
y.label.fmt = label.fmt,
x.label.transform = function(x) {
x
},
y.label.transform = function(x) {
x
},
x.colour.transform = x.label.transform,
na.rm = FALSE,
show.legend = FALSE,
inherit.aes = TRUE
)
Arguments
mapping |
The aesthetic mapping, usually constructed with
|
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 |
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 |
ignore_threshold |
Deprecated synonym for |
global.threshold |
numeric A value belonging to class
|
local.threshold |
numeric A value belonging to class |
local.reference |
character One of |
strict |
logical flag: if |
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 |
label.fmt , x.label.fmt , y.label.fmt |
character strings giving a format
definition for construction of character strings labels with function
|
x.label.transform , y.label.transform , x.colour.transform |
function Applied
to |
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?
|
inherit.aes |
If |
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.
Value
A data frame with one row for each peak (or valley) found in the
data. If refine.wl = FALSE
, the returned rows have x
and
y
matching those in a row in the input data
. If
refine.wl = TRUE
, interpolation based on a fitted spline is used to
compute new x
and y
values.
Computed and copied variables in the returned data frame
- 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
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.
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.
# PEAKS
ggplot(sun.spct) +
geom_line() +
stat_peaks()
# threshold relative to data range [0..1]
ggplot(sun.spct) +
geom_line() +
stat_peaks(global.threshold = 0.6) # 0.6 * range of data
# threshold in data units
ggplot(sun.spct) +
geom_line() +
stat_peaks(global.threshold = I(0.4))
# threshold in data units
ggplot(sun.spct, unit.out = "photon") +
geom_line() +
stat_peaks(global.threshold = I(2e-6)) # Q in mol m-2 s-1
# VALLEYS
ggplot(sun.spct) +
geom_line() +
stat_valleys()
# discard multiple maxima or minima
ggplot(sun.spct) +
geom_line() +
stat_valleys(strict = TRUE)
# threshold relative to data range [0..1]
ggplot(sun.spct) +
geom_line() +
stat_valleys(global.threshold = 0.6)
# reverse threshold relative to data range [-1..0]
ggplot(sun.spct) +
geom_line() +
stat_valleys(global.threshold = -0.9)
# threshold in data units using I()
ggplot(sun.spct) +
geom_line() +
stat_valleys(global.threshold = I(0.6), strict = TRUE)
# USING OTHER COMPUTED VALUES
# colours matching the wavelength at peaks
ggplot(sun.spct) +
geom_line() +
stat_peaks(span = 51, size = 2.7,
mapping = aes(colour = after_stat(wl.colour))) +
scale_color_identity()
# labels for local maxima
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")
# labels for local fitted peaks
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)
# fitted peaks and valleys
ggplot(sun.spct) +
geom_line() +
stat_peaks(span = 31, geom = "point", colour = "red", refine.wl = TRUE) +
stat_peaks(mapping = aes(fill = after_stat(wl.colour), color = after_stat(BW.colour)),
span = 31, geom = "label",
size = 3, vjust = -0.2, label.fmt = "%.4g nm",
refine.wl = TRUE) +
stat_valleys(span = 51, geom = "point", colour = "blue", refine.wl = TRUE) +
stat_valleys(mapping = aes(fill = after_stat(wl.colour), color = after_stat(BW.colour)),
span = 51, geom = "label",
size = 3, vjust = 1.2, label.fmt = "%.4g nm",
refine.wl = TRUE) +
expand_limits(y = 0.85) + # make room for label
scale_fill_identity() +
scale_color_identity()