seewave (version 1.4.3)

simspec: Similarity between two frequency spectra

Description

This function estimates the similarity between two frequency spectra.

Usage

simspec(spec1, spec2, f, 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), ...)

Arguments

spec1

a first data set resulting of a spectral analysis obtained with spec or meanspec (not in dB).

spec2

a second data set resulting of a spectral analysis obtained with spec or meanspec (not in dB).

f

sampling frequency of waves used to obtain spec1 and spec2 (in Hz).

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.

...

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 index is the mean of this function.

Details

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

Examples

a<-noise(f=8000,d=1)
b<-synth(f=8000,d=1,cf=2000)
c<-synth(f=8000,d=1,cf=1000)
d<-noise(f=8000,d=1)
speca<-spec(a,f=8000,wl=512,at=0.5,plot=FALSE)
specb<-spec(b,f=8000,wl=512,at=0.5,plot=FALSE)
specc<-spec(c,f=8000,wl=512,at=0.5,plot=FALSE)
specd<-spec(d,f=8000,wl=512,at=0.5,plot=FALSE)
simspec(speca,speca,f=8000)
#[1] 100 => similar spectra of course!
simspec(speca,specb,f=8000)
#[1] 0.3873278
simspec(speca,specc,f=8000,plot=TRUE)
#[1] 0.5920857
# two pure tone at different frequency are...
simspec(specb,specc,f=8000,plot=TRUE)
#[1] 12.05652
#... less similar than two noises
simspec(speca,specd,f=8000,plot=TRUE)
#[1] 57.40742