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seewave (version 1.7.6)

simspec: Similarity between two frequency spectra

Description

This function estimates the similarity between two frequency spectra.

Usage

simspec(spec1, spec2, f = NULL, plot = FALSE, type = "l",
lty1 = 1, lty2 = 2,
lty3 = 3, col1 = 2, col2 = 4, col3 = 1, flab = "Frequency (kHz)",
alab = "Amplitude (percentage)", flim = c(0, f/2000),
alim = c(0, 100),
legend = TRUE, ...)

Arguments

spec1
a first data set resulting of a spectral analysis obtained with spec or meanspec (not in dB). This can be either a two-column matrix (col1 = frequency,
spec2
a first data set resulting of a spectral analysis obtained with spec or meanspec (not in dB). This can be either a two-column matrix (col1 = frequency,
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
plot
logical, if TRUE plots both spectra and similarity function (by default FALSE).
type
if plot is TRUE, type of plot that should be drawn. See plot for details (by default "l" for lines).
lty1
line type of spec1 if type="l".
lty2
line type of spec2 if type="l".
lty3
line type of the similarity function if type="l".
col1
colour of spec1.
col2
colour of spec2.
col3
colour of the similarity function.
flab
title of the frequency axis.
alab
title of the amplitude axis.
flim
the range of frequency values.
alim
range of amplitude axis.
legend
logical, if TRUE adds a legend to the plot.
...
other plot graphical parameters.

Value

  • The similarity index is returned. This value is in %. When plot is TRUE, both spectra and the similarity function are plotted on the same graph. The similarity index is the mean of this function.

Details

Spectra similarity is assessed according to: $$S = \frac{100/N} \times{\sum_{i=1}^N{\frac{\min{spec1(i),spec2(i)}} {\max{spec1(i),spec2(i)}}}}$$ with S in %.

References

Deecke, V. B. and Janik, V. M. 2006. Automated categorization of bioacoustic signals: avoiding perceptual pitfalls. Journal of the Acoustical Society of America, 119: 645-653.

See Also

spec, meanspec, corspec, diffspec, diffenv, kl.dist, ks.dist, logspec.dist, itakura.dist

Examples

Run this code
a<-noisew(f=8000,d=1)
b<-synth(f=8000,d=1,cf=2000)
c<-synth(f=8000,d=1,cf=1000)
d<-noisew(f=8000,d=1)
speca<-spec(a,f=8000,at=0.5,plot=FALSE)
specb<-spec(b,f=8000,at=0.5,plot=FALSE)
specc<-spec(c,f=8000,at=0.5,plot=FALSE)
specd<-spec(d,f=8000,at=0.5,plot=FALSE)
simspec(speca,speca)
simspec(speca,specb)
simspec(speca,specc,plot=TRUE)
simspec(specb,specc,plot=TRUE)
#[1] 12.05652
simspec(speca,specd,plot=TRUE)

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