stat_spikes | R Documentation |
stat_spikes
finds at which x
positions spikes are located.
Spikes can be either upwards or downwards from the baseline.
Axis flipping is currently not supported.
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,
x.label.transform = I,
y.label.transform = I,
x.colour.transform = x.label.transform,
na.rm = FALSE,
show.legend = FALSE,
inherit.aes = TRUE
)
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 |
z.threshold |
numeric Modified Z values larger than |
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 |
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 |
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.
A data frame with one row for each peak (or valley) found in the data.
x-value at the peak (or valley) as numeric
y-value at the peak (or valley) as numeric
x-value at the peak (or valley) formatted as character
y-value at the peak (or valley) formatted as character
color definition calculated by assuming that x-values are wavelengths expressed in nanometres.
color definition that either "black" or "white", to ensure
high contrast to wl.color
.
Set by the statistic and available to geoms.
stat(x.label)
stat(x)
stat(y)
stat(wl.color)
Required by the statistic and need to be set with aes()
.
numeric, wavelength in nanometres
numeric, a spectral quantity
This stat works 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.
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()
# 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)
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