putD.mwd | R Documentation |
The wavelet coefficients from a multiple wavelet decomposition structure, mwd.object
, (e.g. returned from mwd
) are packed into a single matrix in that structure. This function copies the mwd.object
, replaces some wavelet coefficients in the copy, and then returns the copy.
## S3 method for class 'mwd'
putD(mwd, level, M, boundary = FALSE, index = FALSE, ...)
mwd |
Multiple wavelet decomposition structure whose coefficients you wish to replace. |
level |
The level that you wish to replace. |
M |
Matrix of replacement coefficients. |
boundary |
If |
index |
If index is |
... |
any other arguments |
The mwd
function produces a wavelet decomposition structure.
The need for this function is a consequence of the pyramidal structure of Mallat's algorithm and the memory efficiency gain achieved by storing the pyramid as a linear matrix of coefficients. PutD obtains information about where the wavelet coefficients appear from the fl.dbase component of mwd, in particular the array fl.dbase$first.last.d
which gives a complete specification of index numbers and offsets for mwd$D
.
Note also that this function only puts information into mwd class objects. To extract coefficients from mwd structures you have to use the accessD.mwd function.
See Downie and Silverman, 1998.
An object of class mwd.object
if index is FALSE
, otherwise the index numbers indicating where the M
matrix would have been inserted into the mwd$D
object are returned.
Version 3.9.6 (Although Copyright Tim Downie 1995-6).
Tim Downie
accessC.mwd
, accessD.mwd
, draw.mwd
, mfirst.last
, mfilter.select
, mwd
, mwd.object
, mwr
, plot.mwd
, print.mwd
, putC.mwd
, summary.mwd
, threshold.mwd
, wd
, wr.mwd
.
#
# Generate an mwd object
#
tmp <- mwd(rnorm(32))
#
# Now let's examine the finest resolution detail...
#
accessD(tmp, level=3)
# [,1] [,2] [,3] [,4] [,5] [,6]
#[1,] 0.8465672 0.4983564 0.3408087 0.1340325 0.5917774 -0.06804291
#[2,] 0.6699962 -0.2535760 -1.0344445 0.2068644 -0.4912086 1.16039885
# [,7] [,8]
#[1,] -0.6226445 0.2617596
#[2,] -0.4956576 -0.5555795
#
#
# A matrix. There are two rows one for each mother wavelet in this
# two-ple multiple wavelet transform and at level 3 there are 2^3 columns.
#
# Let's set the coefficients of the first mother wavelet all equal to zero
# for this examples
#
newdmat <- accessD(tmp, level=3)
newdmat[1,] <- 0
#
# Ok, let's insert it back at level 3
#
tmp2 <- putD(tmp, level=3, M=newdmat)
#
# And check it
#
accessD(tmp2, level=3)
# [,1] [,2] [,3] [,4] [,5] [,6] [,7]
#[1,] 0.0000000 0.000000 0.000000 0.0000000 0.0000000 0.000000 0.0000000
#[2,] 0.6699962 -0.253576 -1.034445 0.2068644 -0.4912086 1.160399 -0.4956576
# [,8]
#[1,] 0.0000000
#[2,] -0.5555795
#
#
# Yep, all the first mother wavelet coefficients at level 3 are now zero.
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