
Analyze Wavelet from View object
analyze_wavelet.RdAnalyze Wavelet from View object
Usage
analyze_wavelet(
  obj,
  column,
  loess.span = 0,
  dj = 1/20,
  lowerPeriod = 2/obj$recording$fps,
  upperPeriod = 5,
  make.pval = TRUE,
  method = "white.noise",
  params = NULL,
  n.sim = 1,
  date.format = NULL,
  date.tz = NULL,
  verbose = TRUE
)Arguments
- obj
- View object. 
- column
- Column in view to analyse. 
- loess.span
- parameter alpha in loess controlling the degree of time series smoothing, if the time series is to be detrended; no detrending if loess.span = 0. Default: 0. 
- dj
- frequency resolution. Default 1/20. 
- lowerPeriod
- lower Fourier period in seconds. Defaults to 2/fps. 
- upperPeriod
- upper Fourier period in seconds. Defaults to 5s. 
- make.pval
- method
- params
- n.sim
- number of simulations (default 1). 
- date.format
- date.tz
- verbose
See also
Other wavelet functions: 
analyze_coherency(),
get_local_max_average_power(),
plot_average_coherency(),
plot_average_power(),
plot_cross_spectrum(),
plot_cwt_energy(),
plot_phase_difference(),
plot_power_spectrum(),
plot_roll_resultant_length(),
plot_sel_phases(),
plot_wt_energy()
Examples
r <- get_sample_recording()
rv <- get_raw_view(r, "Central", "", "Sitar")
pv <- get_processed_view(rv)
w <- analyze_wavelet(pv, "Nose_y")
#> Starting wavelet transformation...
#> ... and simulations... 
#> 
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#> Class attributes are accessible through following names:
#> series loess.span dt dj Wave Phase Ampl Power Power.avg Power.pval Power.avg.pval Ridge Period Scale nc nr coi.1 coi.2 axis.1 axis.2 date.format date.tz