Description Usage Arguments Details Author(s) References See Also Examples
View source: R/plot.dwt.multiple.R
Plot wavelet and scaling coefficients of multiple DWT objects.
1 2 3 |
x |
A list of |
levels |
Number, vector, or list of two vectors indicating range of levels to plot. See details. |
ylim |
Vector specifying the lower and upper limits of the vertical y-axis of each plot. |
draw.dashed.lines |
Boolean indicating whether dashed lines should be drawn between levels of wavelet and scaling coefficients. |
draw.level.labels |
Boolean indicating whether the labels for the levels of wavelet and scaling coefficients should be drawn. |
col |
Vector of length 2 for the alternating colors of the coefficients to be drawn. The colors alternate by level of the wavelet or scaling coefficients drawn. The first element of the vector is the color of the coefficients of the first level drawn. |
... |
Additional paramters that are acceptable arguments to the
generic |
If a single number is specified for levels
, then the wavelet
coefficients of levels 1 through levels
will be plotted.
Otherwise, a vector or the first element of a list will specify
which levels of the wavelet coefficients will be plotted.
Unless specified in the second element of a list, only one level
of scaling coefficients will be plotted and this level is equal
to the highest level of the wavelet coefficients plotted. If a DWT
object is defined for multiple time series, only the data pertaining
to the first time series of the DWT object is plotted. Thus, only
the wavelet coefficients and scaling coefficients of the first time
series of the DWT objects will be plotted.
For each dwt
object in the list of x
,
plot.dwt.multiple
takes the coefficients of the dwt
object and concatenates wavelet coefficients and scaling
coefficients by levels specified in levels
. The wavelet
coefficients will always be plotted preceding the scaling
coefficients.
This function allows users to visually examine differences in the
DWT transform of a time series using different filters (different
dwt
objects).
For an example, see Figure 126 of Wavelet Methods for Time Series Analysis by Percival and Walden (2000).
Kelvin Ma, kkym@u.washington.edu
Percival, D. B. and A. T. Walden (2000) Wavelet Methods for Time Series Analysis, Cambridge University Press.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 | X <- rnorm(2048)
# Create DWT Object of X with the "la8" filter.
dwtobj1 <- dwt(X, filter = "la8")
# Create DWT Object of X with the "d4" filter.
dwtobj2 <- dwt(X, filter = "d4")
# Create DWT Object of X with the "haar" filter
dwtobj3 <- dwt(X, filter = "haar")
# Create DWT Object of X with the "c6" filter
dwtobj4 <- dwt(X, filter = "c6")
#Create list of dwt objects
dwtlist <- list(dwtobj1, dwtobj2, dwtobj3, dwtobj4)
# Plot the dwt objects and the wavelet coefficients of level 1 through 6
# and the scaling coefficients of level 6. The first level drawn will
# be purple and the next level drawn will be gold.
plot.dwt.multiple(dwtlist, levels = 6, col = c("purple", "gold"))
# Plot the dwt objects and the wavelet coefficients of level 1, 3, and 5
# and scaling coefficients of level 2, and 4.
plot.dwt.multiple(dwtlist, levels = list(c(1,3,5), c(2,4)))
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