EXAMPLE:Systematic joint best-basis selection and bit allocation forone dimensional data at 2 bits per sample.Given five training images are 512X512 in dimension, output, asdoubles, the wavelet coefficients from a one-dimensional two levelwavelet packet transform into files (subband, subband.1, subband.2,subband.1.1, subband.1.2, subband.2.1, and subband.2.2) where subbandis the original data, subband.1 (subband.2) is the lowpass (highpass)subband, subband.1.1 is the lowpass subband of the lowpass subband,and so on.Use block and tsvq, both compiled to handle double DATATYPE, to makeTSVQ codebooks for each training data file, and then make PTSVQ's.  Ashell script is recommended to make this much easier to handle.e.g.	block -i subband.1.2 -o train.1.2 -r 640 -l 128 -h 2 -w 2	tsvq -t train.1.2 -c codebook.1.2 -s statfile.1.2 -d 4 -r 8 > tsvq.out	prune -c codebook.1.2 -s statfile.1.2 -o nested.1.2 >& prune.out.1.2Note that the image subband dimension for the second level ofdecomposition is 128 by 128, but as there were 5 training images,there are 5*128 = 640 rows.Once the above step is done there should be files (prune.out,prune.out.1, prune.out.2, prune.out.1.1, prune.out.1.2, prune.out.2.1,and prune.out.2.2).  These contain all of the rate-distortioncharacteristics of all the PTSVQ's.  Systematic joint best-basisselection and bit allocation is done as:wpt_bitalloc -c prune.out -l 2 -d 2 -r 2 > wpt_bitalloc.outThe output of wpt_bitalloc consist of several scripts to assistencoding and reconstruction of actual test data.  These are examples,and should be modified as needed.  For more details, see thedocumentation in the code and the tsvq code.Questions and comments should be sent toJill R. Goldschneiderjrgold@isdl.ee.washington.edu