View source: R/rendering_and_plotting.R
HHSpecPlot | R Documentation |
This function displays the Hilbert periodogram, with options to plot individual IMFs and also the Fourier periodogram for comparison.
HHSpecPlot(hspec, freq.span = NULL, scaling = "none", imf.list = NULL,
show.total = TRUE, show.fourier = FALSE, scale.fourier = FALSE,
show.imfs = FALSE, legend = TRUE, ...)
hspec |
Data structure returned by |
freq.span |
Frequency range to plot, |
scaling |
Amplitude scaling, can be |
imf.list |
Which IMFs to plot, requires |
show.total |
Show the ensemble Hilbert spectrogram |
show.fourier |
Show the Fourier periodogram |
scale.fourier |
Scale Fourier and Hilbert spectra to each other for easier comparison |
show.imfs |
Plot individual IMF spectra |
legend |
Determines whether or not a legend is shown |
... |
This function supports some optional parameters as well:
|
This function plots the Hilbert periodogram of a signal, with options to show periodograms of individual IMFs. You can also plot a simple Fourier periodogram for comparison.
Daniel Bowman danny.c.bowman@gmail.com
HHSpectrum
, HHGramImage
#Here we see how the EMD produces a dyadic filter bank for uniform random noise
#The frequency distributions of all but the first IMF display a Chi-Square distribution
#See Huang, N. E. & Wu, Z.
#A review on Hilbert-Huang Transform: Method and its applications to geophysical studies.
#Reviews of Geophysics, 2008, 46, RG2006
#The EMD of this signal may take a couple of minutes to run
set.seed(628)
sig <- runif(10000)
tt <- seq_len(length(sig)) * 0.01
## Not run: emd.result <- Sig2IMF(sig, tt)
dfreq <- 0.1
## Not run: hspec <- HHSpectrum(emd.result, dfreq)
## Not run: HHSpecPlot(hspec, show.imfs = TRUE,
imf.list = 1:10, show.total = TRUE, scaling = "sqrt",
imf.lwd = rep(2, 10), total.lty = 3)
## End(Not run)
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