with parallel::export

[epclust.git] / epclust / R / computeCoeffs.R

diff --git a/epclust/R/computeCoeffs.R b/epclust/R/computeCoeffs.R
deleted file mode 100644 (file)
index fca3b91..0000000
--- a/epclust/R/computeCoeffs.R
+++ /dev/null
@@ -1,43 +0,0 @@
-computeCoeffs = function(data, index, nb_series_per_chunk, wf)
-{
-       coeffs_chunk = NULL
-       if (is.data.frame(data) && index < nrow(data))
-       {
-               #full data matrix
-               coeffs_chunk = curvesToCoeffs(
-                       data[index:(min(index+nb_series_per_chunk-1,nrow(data))),], wf)
-       }
-       else if (is.function(data))
-       {
-               #custom user function to retrieve next n curves, probably to read from DB
-               coeffs_chunk = curvesToCoeffs( data(rank=(index-1)+seq_len(nb_series_per_chunk)), wf )
-       }
-       else if (exists(data_con))
-       {
-               #incremental connection ; TODO: more efficient way to parse than using a temp file
-               ascii_lines = readLines(data_con, nb_series_per_chunk)
-               if (length(ascii_lines > 0))
-               {
-                       series_chunk_file = ".series_chunk"
-                       writeLines(ascii_lines, series_chunk_file)
-                       coeffs_chunk = curvesToCoeffs( read.csv(series_chunk_file), wf )
-                       unlink(series_chunk_file)
-               }
-       }
-       coeffs_chunk
-}
-
-curvesToCoeffs = function(series, wf)
-{
-       if (!require(wavelets, quietly=TRUE))
-               stop("Couldn't load wavelets library")
-       L = length(series[1,])
-       D = ceiling( log2(L) )
-       nb_sample_points = 2^D
-       #TODO: parallel::parApply() ?!
-       as.data.frame( apply(series, 1, function(x) {
-               interpolated_curve = spline(1:L, x, n=nb_sample_points)$y
-               W = wavelets::dwt(interpolated_curve, filter=wf, D)@W
-               rev( sapply( W, function(v) ( sqrt( sum(v^2) ) ) ) )
-       }) )
-}