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)))
# }