Dominant frequency of a time wave
This function gives the dominant frequency (i. e. the frequency of highest amplitude) of a time wave.
dfreq(wave, f, channel = 1, wl = 512, wn = "hanning", ovlp = 0, fftw= FALSE, at = NULL, tlim = NULL, threshold = NULL, bandpass = NULL, clip = NULL, plot = TRUE, xlab = "Times (s)", ylab = "Frequency (kHz)", ylim = c(0, f/2000), ...)
wave |
an R object. |
f |
sampling frequency of |
channel |
channel of the R object, by default left channel (1). |
wl |
length of the window for the analysis (even number of points, by default = 512). |
wn |
window name, see |
ovlp |
overlap between two successive analysis windows (in % ). |
fftw |
if |
at |
time position where the dominant frequency has to be computed (in s.). |
tlim |
modifications of the time X-axis limits. |
threshold |
amplitude threshold for signal detection (in % ). |
bandpass |
a numeric vector of length two, giving the lower and upper limits of a frequency bandpass filter (in Hz). |
clip |
a numeric value to select dominant frequency values according to their amplitude in reference to a maximal value of 1 for the whole signal (has to be >0 & < 1). |
plot |
logical, if |
xlab |
title of the x axis. |
ylab |
title of the y axis. |
ylim |
the range of y values. |
... |
other |
When plot is FALSE, dfreq returns a two-column matrix, the first column corresponding to time in seconds (x-axis) and the second column corresponding to
to dominant frequency in kHz (y-axis).
NA corresponds to pause sections in wave (see threshold).
This function is based on fft.
Jerome Sueur sueur@mnhn.fr
data(tico) f <- 22050 # default dfreq(tico,f) # using the amplitude threshold and changing the graphical output dfreq(tico, f, ovlp=50,threshold=5, type="l", col=2) # using 'at' argument for specific positions along the time axis dfreq(tico, f, at=c(0.25, 0.75, 1.2, 1.6)) dfreq(tico, f, at=seq(0.5, 1.4, by=0.005), threshold=5) # a specific number of measures on a single note dfreq(tico, f, at=seq(0.5, 0.9, len=100), threshold=5, xlim=c(0.5,0.9)) # overlap on spectrogram # and use of 'clip' argument to better track the dominant frequency # in noisy conditions op <- par() ticon <- tico@left/max(tico@left) + noisew(d=length(tico@left)/f, f) spectro(ticon, f) res <- dfreq(ticon, f, clip=0.3, plot=FALSE) points(res, col=2, pch =13) par(op)
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