warbleR (version 1.1.1)

xcorr: Spectrogram cross-correlation

Description

xcorr Estimates the similarity of two spectrograms by means of cross-correlation

Usage

xcorr(X, wl =512, frange= NULL, ovlp=90, dens=0.9, bp= NULL, wn='hanning', 
cor.method = "pearson", parallel = 1)

Arguments

X

Data frame containing columns for sound files (sound.files), selection number (selec), and start and end time of signal (start and end).

wl

A numeric vector of length 1 specifying the window length of the spectrogram, default is 512.

frange

A numeric vector of length 2 setting the upper and lower frequency limits (in kHz) in which to compare the signals. If not provided (NULL) the dfts function is used internally to define the highe

ovlp

Numeric vector of length 1 specifying % of overlap between two consecutive windows, as in spectro. Default is 90. High values of ovlp slow down the function but produce more accurate results.

dens

Numeric vector of length 1 specifying the approximate density of points in which to sample amplitude. See makeTemplate. Deafult is 0.9.

bp

A numeric vector of length 2 for the lower and upper limits of a frequency bandpass filter (in kHz) in which to detect dominant frequency. Only applied when frange is NULL. Default is NULL.

wn

A character vector of length 1 specifying the window name as in ftwindow.

cor.method

A character vector of length 1 specifying the correlation method as in cor.

parallel

Numeric. Controls whether parallel computing is applied. It specifies the number of cores to be used. Default is 1 (e.i. no parallel computing). For windows OS the warbleR from github to run parallel.

Value

• A list that includes 1) a data frame with the correlation statistic for each "sliding" step, 2) a matrix with the maximum (peak) correlation for each pairwise comparison, and 3) the frequency range.

source

H. Khanna, S.L.L. Gaunt & D.A. McCallum (1997). Digital spectrographic cross-correlation: tests of sensitivity. Bioacoustics 7(3): 209-234

Details

This function calculates the pairwise similarity of multiple signals by means of spectrogram cross-correlation. This method "slides" one spectrogram over the other calculating a correlation of the amplitude values at each step. The function runs pairwise cross-correlations on several signals and returns a list including the correlation statistic for each "sliding" step as well as the maximum (peak) correlation for each pairwise comparison. To accomplish this the margins of the signals are expanded by half the duration of the signal both before and after the provided time coordinates. This function is a modified version of the corMatch and makeTemplate from the awesome R package `monitoR`.

See Also

xcorr.graph

Examples

#First set temporal working directory
setwd(tempdir())

#load data
data(list = c("Phae.long1", "Phae.long2", "Phae.long3", "Phae.long4","manualoc.df"))
writeWave(Phae.long1, "Phae.long1.wav") #save sound files
writeWave(Phae.long2, "Phae.long2.wav")
writeWave(Phae.long3, "Phae.long3.wav")
writeWave(Phae.long4, "Phae.long4.wav")

xcor<-xcorr(X = manualoc.df, wl =300, frange= c(2, 9), ovlp=90, 
dens=1, wn='hanning', cor.method = "pearson")