diffcumspec {seewave}R Documentation

Difference between two cumulative frequency spectra

Description

This function compares two distributions (e.g. two frequency spectra) by computing the difference between two cumulative frequency spectra

Usage

diffcumspec(spec1, spec2, f = NULL, mel = FALSE, 
plot = FALSE, type = "l", lty = c(1, 2), col = c(2, 4, 8),
flab = NULL, alab = "Cumulated amplitude",
flim = NULL, alim = NULL,
title = TRUE, legend = TRUE, ...)

Arguments

spec1

any distribution, especially a spectrum obtained with spec or meanspec (not in dB). This can be either a two-column matrix (col1 = frequency, col2 = amplitude) or a vector (amplitude).

spec2

any distribution, especially a spectrum obtained with spec or meanspec (not in dB). This can be either a two-column matrix (col1 = frequency, col2 = amplitude) or a vector (amplitude).

f

sampling frequency of waves used to obtain spec1 and spec2 (in Hz). Not necessary if spec1 and/or spec2 is a two columns matrix obtained with spec or meanspec.

mel

a logical, if TRUE the (htk-)mel scale is used.

plot

logical, if TRUE plots both cumulative spectra and their distance.

type

if plot is TRUE, type of plot that should be drawn. See plot for details (by default "l" for lines).

col

a vector of length 3 for the colour of spec1, spec2, and the difference between each of them.

lty

a vector of length 2 for the line type of spec1 and spec2 if type="l".

flab

title of the frequency axis.

alab

title of the amplitude axis.

flim

the range of frequency values.

alim

range of amplitude axis.

title

logical, if TRUE, adds a title with D and F values.

legend

logical, if TRUE adds a legend to the plot.

...

other plot graphical parameters.

Details

Both spectra are transformed into cumulative distribution functions (CDF).
Spectral difference is then computed according to:

D = 1/n * sum(abs(X-Y)), with X and Y the spectrum CDFs, and 0 < D < 1.

Value

A numeric vector of length 1 returning the difference between the two spectra. No unit.

Note

This metric is sensitive not only to the spectral overlap between but also to the mean frequential distance between the different frequency peaks.

Author(s)

Laurent Lellouch, Jerome Sueur

References

Lellouch L, Pavoine S, Jiguet F, Glotin H, Sueur J (2014) Monitoring temporal change of bird communities with dissimilarity acoustic indices. Methods in Ecology and Evolution, in press.

See Also

kl.dist, ks.dist, simspec, diffspec, logspec.dist, itakura.dist

Examples

## Hz scale
data(tico)
data(orni)
orni.hz <- meanspec(orni, plot=FALSE)
tico.hz <- meanspec(tico, plot=FALSE)
diffcumspec(orni.hz, tico.hz, plot=TRUE)
## mel scale
require(tuneR)
orni.mel <- melfcc(orni, nbands = 256, dcttype = "t3", fbtype = "htkmel", spec_out=TRUE)
orni.mel.mean <- apply(orni.mel$aspectrum, MARGIN=2, FUN=mean)
tico.mel <- melfcc(tico, nbands = 256, dcttype = "t3", fbtype = "htkmel", spec_out=TRUE)
tico.mel.mean <- apply(tico.mel$aspectrum, MARGIN=2, FUN=mean)
diffcumspec(orni.mel.mean, tico.mel.mean, f=22050, mel=TRUE, plot=TRUE)

[Package seewave version 2.1.6 Index]