code/draft_R_pkg/R/main.R

   1 #TODO: setRefClass... to avoid copy data !!
   2 #http://stackoverflow.com/questions/2603184/r-pass-by-reference
   3
   4 #fields: data (can be NULL or provided by user), coeffs (will be computed
   5 #con can be a character string naming a file; see readLines()
   6 #data can be in DB format, on one column : TODO: guess (from header, or col. length...)
   7
   8
   9 writeTmp(curves [uncompressed coeffs, limited number - nbSeriesPerChunk], last=FALSE) #if last=TRUE, close the conn
  10 readTmp(..., from index, n curves) #careful: connection must remain open
  11 #TODO: write read/write tmp reference ( on file in .tmp/ folder ... )
  12
  13 epclust = function(data=NULL, K, nbPerChunk, ..., writeTmp=ref_writeTmp, readTmp=ref_readTmp) #where to put/retrieve intermediate results; if not provided, use file on disk
  14 {
  15
  16
  17     #on input: can be data or con; data handled by writing it to file (ascii or bin ?!),
  18 #data: con or matrix or DB
  19
  20     #1) acquire data (process curves, get as coeffs)
  21     if (is.numeric(data))
  22     {
  23         #full data matrix
  24         index = 1
  25         n = nrow(data)
  26         while (index < n)
  27         {
  28             writeTmp( getCoeffs(data) )
  29             index = index + nbSeriesPerChunk
  30         }
  31     } else if (is.function(data))
  32     {
  33         #custom user function to retrieve next n curves, probably to read from DB
  34         writeTmp( getCoeffs( data(nbPerChunk) ) )
  35     } else
  36     {
  37         #incremental connection
  38         #read it one by one and get coeffs until nbSeriesPerChunk
  39         #then launch a clustering task............
  40         ascii_lines = readLines(data, nbSeriesPerChunk)
  41         seriesChunkFile = ".tmp/seriesChunk" #TODO: find a better way
  42         writeLines(ascii_lines, seriesChunkFile)
  43         writeTmp( getCoeffs( read.csv(seriesChunkFile) ) )
  44     } else
  45         stop("Unrecognizable 'data' argument (must be numeric, functional or connection)")
  46
  47     #2) process coeffs (by nbSeriesPerChunk) and cluster in parallel (just launch async task, wait for them to complete, and re-do if necessary)
  48
  49
  50     #3) apply stage 2 (in parallel ? inside task 2) ?)
  51 }
  52
  53 getCoeffs = function(series)
  54 {
  55     #... return wavelets coeffs : compute in parallel !
  56 }