R: Spectrogram fft

evolfft {RSEIS} | R Documentation

## Spectrogram fft

### Description

Spectrogram using simple fft (Gabor Transform)

### Usage

    evolfft(a, dt = 0, Nfft = 0, Ns = 0, Nov = 0, fl = 0, fh = 10, pcttap =
    0.05, adjust=TRUE )

### Arguments

`a` | signal
`dt` | sample rate interval (s)
`Nfft` | Number of points in fft
`Ns` | NUmber of sample in sub-window
`Nov` | number of sample to overlap
`fl` | low frequency to display
`fh` | high frequency to display
`pcttap` | Percent cosine taper for each window
`adjust` | logical, if TRUE adjust the parameters so the plot looks good (DEFAULT). If FALSE, keep user parameters.

### Details

This is a duplication of the spectrogram function in matlab which applies Welsh's Method. Each mini-window is tapered with a cosine window.

### Value

List

`sig` | input signal
`dt` | deltat
`wpars` | input parameters
`DSPEC` | spectrum image
`freqs` | output frequencies (y axis)
`tims` | output times (x-axis)

### Note

Parameter adjust is by default TRUE so that the choice of Ns, Nov, and kcol will be optimized, more or less. Set this logical to FALSE to force the function to use user input parameters.

### Author(s)

Jonathan M. Lees<jonathan.lees.edu>

### See Also

evolMTM, evolAR, MTM.drive

### Examples

    data(CE1)

    ####  plot signals
    plot(CE1$x, CE1$y, type='l')

    ###  set parameters
    Nfft<-1024   ###  fft length
    Ns<-250      ###  number of samples in a window
    Nov<-240     ###  number of samples of overlap per window
    fl<-0        ###  low frequency to return
    fh<-1/(2*CE1$dt)     ###  high frequency to return

    ########  calculate the evolutive fft (Gabor Transform)
    EV <- evolfft(CE1$y, dt =CE1$dt , Nfft = Nfft, Ns =Ns , Nov =Nov , fl =fl
    , fh = 25)

    ### plot image, but it does not look too interesting
    image(EV$DSPEC)

    ### plot Gabor transform with special function
    PE <- plotevol(EV, log=0, fl=0.01, fh=100, col=rainbow(100), ygrid=FALSE,
    STAMP="", STYLE="fft")

[Package RSEIS version 3.7-4 Index]