figure108.wt.filter {wavelets} | R Documentation |
Plots multiple DWT Wavelet or Scaling Filters similar to Figure 108 in Wavelet Methods for Time Series Analysis by Percival and Walden (2000).
figure108.wt.filter(filter.objects, level = 1, l = NULL, wavelet = TRUE)
filter.objects |
List containing 'wt.filter' objects, character strings specifying a wavelet filter, or numeric vectors of wavelet coefficients. The list can contain a combination of 'wt.filter' objects, character strings, and numeric vectors. If only one filter is to be plotted, a single 'wt.filter' object, character string, or numeric vector may be supplied. See 'help(wt.filter)' for acceptable filter names. |
level |
If |
l |
Single integer representing the right hand limit of the
horizontal axis. If unspecified, it will default to the length
of the filter of greatest length given in
|
wavelet |
A logical flag indicating whether to plot the wavelet (high pass) or scaling (low pass) filter. |
The plotting space available for each filter is dictated by the value of greatest magnitude of all the filters plotted. The vertical plotting space for each level will then be 2 times the absolute value of this magnitude.
The filters are successively plotted in the order given in
filter.object
, where the first filter in filter.object
is drawn at the top of the plot region, and the successive filters
are plotted below.
Kelvin Ma, kkym@u.washington.edu
Percival, D. B. and A. T. Walden (2000) Wavelet Methods for Time Series Analysis, Cambridge University Press.
# Plotting the LA8 Wavelet Filter filter <- wt.filter() figure108.wt.filter(filter) # Alternatively figure108.wt.filter("la8") # Plotting the Haar, D4, D6 Wavelet Filters figure108.wt.filter(list("haar", "d4", "d6")) # Plotting the Haar, D4, D6 Scaling Filters figure108.wt.filter(list("haar", "d4", "d6"), wavelet = FALSE) # Alternatively haar <- wt.filter("haar") d6 <- wt.filter("d6") figure108.wt.filter(list(haar, "d4", d6), wavelet = FALSE) # Adding an "made up" filter (represented by c(1,-1,1,-1) figure108.wt.filter(list(haar, "d4", d6, c(1,-1,1,-1)), wavelet = FALSE)