Description Usage Arguments Details Author(s) Examples
Plots an object inheriting from the Spectra class
1 2 3 4 5 6 7 8 | ## S3 method for class 'Spectra'
plot(x, gg=FALSE, gaps=TRUE, attr=NULL, ...)
## S4 method for signature 'Spectra'
plot_summary(x, fun=mean, se=TRUE, ...)
## S4 method for signature 'Spectra'
plot_stack(x)
## S4 method for signature 'Spectra'
plot_offset(x, offset=1)
|
x |
an object of class |
gg |
if TRUE, uses the |
gaps |
if TRUE, gaps in the spectra are not plotted |
attr |
attribute against which lines are coloured (only for |
fun |
an aggregation function |
se |
if TRUE, plots the standard deviation around the summary spectra (computed by function as given by |
offset |
Offset between spectra |
... |
options to be passed to |
The philosophy of this plotting routine is to provide a "quick'n'dirty" way to plot your spectra collection. For advanced visualisations, the use of melt_spectra
alongside with ggplot2 or lattice is encouraged.
Pierre Roudier pierre.roudier@gmail.com
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 | # Loading example data
data(australia)
spectra(australia) <- sr_no ~ ... ~ 350:2500
# Default plotting method
plot(australia)
# Default plot using ggplot2
plot(australia, gg = TRUE)
# Managing gaps in the spectra
s <- cut(australia, wl =c(-1*450:500, -1*1800:2050))
plot(s, gaps = TRUE)
plot(s, gaps = FALSE)
# passing various options to matplot
plot(australia, lty = 1:5, col = 'blue', xlab = 'foo', ylab = 'bar', ylim = c(0.4,0.6), main = 'my plot')
# Using colour ramps
plot(australia, lty = 1, col = rainbow(10), main = "It is possible to create really ugly visualisations")
## Not run:
# Example using colours given by ColorBrewer (http://colorbrewer2.org/)
library(RColorBrewer)
plot(australia, lty = 1, col = brewer.pal(n = 8, name = "Set2"))
## End(Not run)
# Using an attribute to group spectra
australia$fact <- sample(LETTERS[1:3], size = nrow(australia), replace = TRUE) # Generate some kind of factor
s <- aggregate_spectra(australia, fun = mean, id = 'fact')
plot(s, gg = TRUE, attr = 'fact')
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