getpacket.wpst(wpst, level, index )
nlevels(wpst).
The coefficients at level $nlevels
are the data the created the wpst object.
r = nlevels - level.
Each packet of coefficients is obtained by chaining together the effect of the two packet operators DG and DH: these are the high and low pass quadrature mirror filters of the Mallat pyramid algorithm scheme followed by both even and odd decimation. For a full description of this algorithm and how coefficients are stored within see Nason, Sapatinas and Sawczenko, 1998.
Note that this function extracts packets. If you want to obtain the wavelet packet coefficients for each shift you need to use the accessD.wpst function. This function extracts particular wavelet packet coefficients for a particular shift. In particular, this function returns a number of coefficients dependent on the scale level requested whereas accessD.wpst always returns a vector of coefficients of length equal to the input data that created the wpst object initially.
# # Create some random data # myrand <- rnorm(16) myrand # [1] 0.19268626 -0.41737181 -0.30806613 0.07435407 0.99871757 # [6] -0.58935121 -1.38049759 -0.13346631 1.55555403 -1.60581265 #[11] 0.14353621 1.21277774 1.13762337 -1.08577934 -0.29745609 #[16] 0.50977512 # # Do the non-decimated wavelet packet transform # myrwpst <- wpst(myrand) # # Let's access what is a level nlevels(myrwpst) # getpacket(myrwpst, nlevels(myrwpst), index=0) # [1] 0.19268626 -0.41737181 -0.30806613 0.07435407 0.99871757 # [6] -0.58935121 -1.38049759 -0.13346631 1.55555403 -1.60581265 #[11] 0.14353621 1.21277774 1.13762337 -1.08577934 -0.29745609 #[16] 0.50977512 # # I.e. the data that created the object. # # How about extracting the 3rd (last) packet at level 3? # getpacket(myrwpst, 3, index=3) #[1] -2.660657144 0.688415755 -1.764060698 0.717267105 -0.206916242 #[6] -0.659983747 0.005836952 -0.196874007 # # Of course, there are only 8 coefficients at this level.