Combines and plots spectra (by taking the average and the standard deviation, for example) according to an index or a vector of identities.

aggplot(rspecdata, by = NULL, FUN.center = mean, FUN.error = sd,
  lcol = NULL, shadecol = NULL, alpha = 0.2, legend = FALSE, ...)

Arguments

rspecdata

(required) data frame containing the spectra to be manipulated and plotted.

by

(required) either a single value specifying the range of spectra within the data frame to be combined (for example, by = 3 indicates the function will be applied to groups of 3 consecutive columns in the spectra data frame) or a vector containing identifications for the columns in the spectra data frame (in which case the function will be applied to each group of spectra sharing the same identification).

FUN.center

the function to be applied to the groups of spectra, calculating a measure of central tendency (defaults to mean).

FUN.error

the function to be applied to the groups of spectra, calculating a measure of variation (defaults to sd).

lcol

color of plotted lines indicating central tendency.

shadecol

color of shaded areas indicating variance measure.

alpha

transparency of the shaded areas.

legend

automatically add a legend.

...

additional graphical parameters to be passed to plot.

Value

Plot containing the lines and shaded areas of the groups of spectra.

References

Montgomerie R (2006) Analyzing colors. In: Hill G, McGraw K (eds) Bird coloration. Harvard University Press, Cambridge, pp 90-147.

Examples

# NOT RUN {
# Load reflectance data
data(sicalis)

# Create grouping variable based on spec names
bysic <- gsub("^ind[0-9].",'', names(sicalis)[-1])

# Plot using various error functions and options
aggplot(sicalis, bysic)
aggplot(sicalis, bysic, FUN.error=function(x) quantile(x, c(0.0275,0.975)))
aggplot(sicalis, bysic, shade = spec2rgb(sicalis), lcol = 1)
aggplot(sicalis, bysic, lcol = 1, FUN.error = function(x) sd(x)/sqrt(length(x)))
# }