signal_spectrum: Calculate the spectrum of a time series

In coffeemuggler/eseis: Environmental Seismology Toolbox

Calculate the spectrum of a time series

Description

The power spectral density estimate of the time series is calculated using different approaches.

Usage

signal_spectrum(data, dt, method = "periodogram", n, res, log = FALSE, ...)

Arguments

data	eseis object, numeric vector or list of objects, data set to be processed.
dt	Numeric value, sampling period. If omitted, dt is set to 1/200. Only needed if data is no eseis object.
method	Character value, calculation method. One out of "periodogram" and "autoregressive". default is "periodogram".
n	Numeric value, optional number of samples in running window used for smoothing the spectrogram. Only applied if a number is provided. Smoothing is performed as running mean.
res	Numeric value, optional resolution of the spectrum, i.e. the number of power and frequency values. If omitted, the full resolution is returned. If used, a spline interpolation is performed.
log	Logical value, option to interpolate the spectrum with log spaced frequency values. Default is FALSE.
...	Additional arguments passed to the function.

Details

If the res option is used, the frequency and power vectors will be interpolated using a spline interpolator, using equally spaced frequency values. If desired, the additional option log = TRUE can be used to interpolate with log spaced frequency values.

Value

Data frame with frequency and power vector

Author(s)

Michael Dietze

Examples

## load example data set
data(rockfall)

## calculate spectrum with standard setup
s <- signal_spectrum(data = rockfall_eseis)

## plot spectrum
plot_spectrum(data = s)

coffeemuggler/eseis documentation built on Nov. 25, 2024, 8:31 p.m.