seewave (version 2.2.3)

ACI: Acoustic Complexity Index

Description

This function computes the Acoustic Complexity Index (ACI) as described in Pieretti et al. (2011)

Usage

ACI(wave, f, channel = 1, wl = 512, ovlp = 0,  wn = "hamming", flim = NULL, nbwindows = 1)

Value

A vector of length 1 returning the ACI total.

Arguments

wave

an R object.

f

sampling frequency of wave (in Hz). Does not need to be specified if embedded in wave.

channel

channel of the R object, by default left channel (1).

wl

window length for the analysis (even number of points) (by default = 512).

ovlp

overlap between two successive windows (in %).

wn

window name, see ftwindow (by default "hanning").

flim

a numeric vector of length 2 to select a frequency band (in kHz).

nbwindows

a numeric vector of length 1 specifying the number of windows (by default 1, ie a single window including the complete wave object.

Author

Laurent Lellouch, improved by Amandine Gasc and Morgane Papin

Details

The function computes first a short-term Fourier transform and then the ACI index.
The function returns only the ACI total, ACI tot in Pieretti et al. (2010).
See the references for details on computation.

References

Pieretti N, Farina A, Morri FD (2011) A new methodology to infer the singing activity of an avian community: the Acoustic Complexity Index (ACI). Ecological Indicators, 11, 868-873.
Farina A, Pieretti N, Piccioli L (2011) The soundscape methodology for long-term bird monitoring: a Mediterranean Europe case-study. Ecological Informatics, 6, 354-363.

See Also

spectro, specflux

Examples

data(tico)
ACI(tico)
## dividing the sound sample into 4 windows of equal duration
ACI(tico, nbwindows=4)
## selection of a frequency band
ACI(tico, flim=c(2,6))