accessC.mwd            package:wavethresh            R Documentation

_G_e_t _S_m_o_o_t_h_e_d _D_a_t_a _f_r_o_m _W_a_v_e_l_e_t _S_t_r_u_c_t_u_r_e

_D_e_s_c_r_i_p_t_i_o_n:

     The smoothed and original data from a multiple wavelet
     decomposition structure, 'mwd.object'  ect  (e.g. returned from
     'mwd') are packed into a single matrix in that structure.  TRUE 
     his function extracts the data corresponding to a particular
     resolution level.

_U_s_a_g_e:

     accessC.mwd(mwd, level = mwd$nlevels, ...)

_A_r_g_u_m_e_n_t_s:

     mwd: Multiple wavelet decomposition structure from which you wish
          to extract the smoothed or original data if the structure is
          from a wavelet decomposition, or the reconstructed data if
          the structure is from a wavelet reconstruction.

   level: The level that you wish to extract. By default, this is the
          level with most detail (in the case of structures from a
          decomposition this is the original data, in the case of
          structures from a reconstruction this is the top-level
          reconstruction).

     ...: any other arguments

_D_e_t_a_i_l_s:

     The mwd function produces a wavelet decomposition structure.

     For decomposition, the top level contains the original data, and
     subsequent lower levels contain the successively smoothed data. So
     if there are 'mwd$filter$npsi*2^m' original data points
     ('mwd$filter$npsi' is the multiplicity of wavelets), there will be
     'm+1' levels indexed 0,1,...,m. So 

     'accessC.mwd(Mwd, level=m)'

     pulls out the original data, as does

     'accessC.mwd(mwd)'

     To get hold of lower levels just specify the level that you're
     interested in, e.g. 

     'accessC.mwd(mwd, level=2)'

     Gets hold of the second level.

     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. AccessC obtains information about where the smoothed
     data appears from the fl.dbase component of mwd, in particular the
     array 'fl.dbase$first.last.c' which gives a complete specification
     of index numbers and offsets for 'mwd$C'. 

     Note also that this function only gets information from mwd class
     objects. To _put_ coefficients into mwd structures you have to use
     the putC.mwd function. 

     See Downie and Silverman, 1998.

_V_a_l_u_e:

     A matrix with 'mwd$filter$npsi' rows containing the extracted data
     of all the coefficients at that level.

_R_E_L_E_A_S_E:

     Version 3.9.6 (Although Copyright Tim Downie 1995-6.)

_S_e_e _A_l_s_o:

     'accessD.mwd', 'draw.mwd', 'mfirst.last', 'mfilter.select', 'mwd',
     'mwd.object', 'mwr', 'plot.mwd', 'print.mwd', 'putC.mwd',
     'putD.mwd', 'summary.mwd', 'threshold.mwd', 'wd'

_E_x_a_m_p_l_e_s:

     #
     # Get the 3rd level of smoothed data from a decomposition
     #
     #accessC.mwd(mwd(data), level=3)

