putD.wd | R Documentation |
Makes a copy of the wd
object, replaces some mother wavelet coefficients data in the copy, and then returns the copy.
## S3 method for class 'wd' putD(wd, level, v, boundary=FALSE, index=FALSE, ...)
wd |
Wavelet decomposition object into which you wish to insert the mother wavelet coefficients. |
level |
the resolution level at which you wish to replace the mother wavelet coefficients. |
v |
the replacement data, this should be of the correct length. |
boundary |
If |
index |
If index is |
... |
any other arguments |
The function accessD
obtains the mother wavelet coefficients for a particular level. The function putD.wd
replaces father wavelet coefficients at a particular resolution level and returns a modified wd object reflecting the change.
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 vector. PutD.wd
obtains information about where the smoothed data appears from the fl.dbase
component of an wd.object
, in particular the array
fl.dbase$first.last.d
which gives a complete specification of index numbers and offsets for
wd.object$D
.
Note that this function is method for the generic function putD
. When the wd.object
is definitely a wd class object then you only need use the generic version of this function.
Note also that this function only puts information into wd
class objects. To extract coefficients from a wd
object you have to use the accessD
function (or more precisely, the accessD.wd
method).
A wd
class object containing the modified mother wavelet coefficients.
Version 3.5.3 Copyright Guy Nason 1994
G P Nason
putD
, wd.object
, wd
, accessD
,putD
, first.last
,
# # Generate an EMPTY wd object: # zero <- rep(0, 16) zerowd <- wd(zero) # # Put some random father wavelet coefficients into the object at # resolution level 2. For the decimated wavelet transform there # are always 2^i coefficients at resolution level i. So we have to # insert 4 coefficients # mod.zerowd <- putD( zerowd, level=2, v=rnorm(4)) # # If you plot mod.zerowd you will see that there are only # coefficients at resolution level 2 where you just put the coefficients. # # Now, for a time-ordered non-decimated wavelet transform object the # procedure is exactly the same EXCEPT that there are going to be # 16 coefficients at each resolution level. I.e. # # Create empty TIME-ORDERED NON-DECIMATED wavelet transform object # zerowdS <- wd(zero, type="station") # # Now insert 16 random coefficients at resolution level 2 # mod.zerowdS <- putD(zerowdS, level=2, v=rnorm(16)) # # Once more if you plot mod.zerowdS then there will only be # coefficients at resolution level 2.
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