Compute 'multitaper' spectral densities of time-series data

Compute 'multitaper' spectral densities of time-series data

Usage

multitaper_config(
  data_length,
  fs,
  frequency_range = NULL,
  time_bandwidth = 5,
  num_tapers = NULL,
  window_params = c(5, 1),
  nfft = NA,
  detrend_opt = "linear"
)

multitaper(
  data,
  fs,
  frequency_range = NULL,
  time_bandwidth = 5,
  num_tapers = NULL,
  window_params = c(5, 1),
  nfft = NA,
  detrend_opt = "linear"
)

Arguments

data_length

length of data

fs

sampling frequency in 'Hz'

frequency_range

frequency range to look at; length of two

time_bandwidth

a number indicating time-half bandwidth product; i.e. the window duration times the half bandwidth of main lobe; default is 5

num_tapers

number of 'DPSS' tapers to use; default is NULL and will be automatically computed from floor(2*time_bandwidth - 1)

window_params

vector of two numbers; the first number is the window size in seconds; the second number if the step size; default is c(5, 1)

nfft

'NFFT' size, positive; see 'Details'

detrend_opt

how you want to remove the trend from data window; options are 'linear' (default), 'constant', and 'off'

data

numerical vector, signal traces

Value

multitaper_config returns a list of configuration parameters for the filters; multitaper also returns the time, frequency and corresponding spectral power.

Details

The original source code comes from 'Prerau' Lab (see 'Github' repository 'multitaper_toolbox' under user 'preraulab'). The results tend to agree with their 'Python' implementation with precision on the order of at 1E-7 with standard deviation at most 1E-5. The original copy was licensed under a Creative Commons Attribution 'NC'-'SA' 4.0 International License (https://creativecommons.org/licenses/by-nc-sa/4.0/).

This package ('ravetools') redistributes the multitaper function under minor modifications on nfft. In the original copy there is no parameter to control the exact numbers of nfft, and the nfft is always the power of 2. While choosing nfft to be the power of 2 is always recommended, the modified code allows other choices.

Examples

# \donttest{

# Takes long to run

time <- seq(0, 3, by = 0.001)
x <- sin(time * 20*pi) + exp(-time^2) * cos(time * 10*pi)

res <- multitaper(
  x, 1000, frequency_range = c(0,15),
  time_bandwidth=1.5,
  window_params=c(2,0.01)
)


image(
  x = res$time,
  y = res$frequency,
  z = 10 * log10(res$spec),
  xlab = "Time (s)",
  ylab = 'Frequency (Hz)',
  col = matlab_palette()
)


# }