| 1 | computeCoeffs = function(data, index, nb_series_per_chunk, wf) |
| 2 | { |
| 3 | coeffs_chunk = NULL |
| 4 | if (is.data.frame(data) && index < nrow(data)) |
| 5 | { |
| 6 | #full data matrix |
| 7 | coeffs_chunk = curvesToCoeffs( |
| 8 | data[index:(min(index+nb_series_per_chunk-1,nrow(data))),], wf) |
| 9 | } |
| 10 | else if (is.function(data)) |
| 11 | { |
| 12 | #custom user function to retrieve next n curves, probably to read from DB |
| 13 | coeffs_chunk = curvesToCoeffs( data(rank=(index-1)+seq_len(nb_series_per_chunk)), wf ) |
| 14 | } |
| 15 | else if (exists(data_con)) |
| 16 | { |
| 17 | #incremental connection ; TODO: more efficient way to parse than using a temp file |
| 18 | ascii_lines = readLines(data_con, nb_series_per_chunk) |
| 19 | if (length(ascii_lines > 0)) |
| 20 | { |
| 21 | series_chunk_file = ".series_chunk" |
| 22 | writeLines(ascii_lines, series_chunk_file) |
| 23 | coeffs_chunk = curvesToCoeffs( read.csv(series_chunk_file), wf ) |
| 24 | unlink(series_chunk_file) |
| 25 | } |
| 26 | } |
| 27 | coeffs_chunk |
| 28 | } |
| 29 | |
| 30 | curvesToCoeffs = function(series, wf) |
| 31 | { |
| 32 | if (!require(wavelets, quietly=TRUE)) |
| 33 | stop("Couldn't load wavelets library") |
| 34 | L = length(series[1,]) |
| 35 | D = ceiling( log2(L) ) |
| 36 | nb_sample_points = 2^D |
| 37 | #TODO: parallel::parApply() ?! |
| 38 | as.data.frame( apply(series, 1, function(x) { |
| 39 | interpolated_curve = spline(1:L, x, n=nb_sample_points)$y |
| 40 | W = wavelets::dwt(interpolated_curve, filter=wf, D)@W |
| 41 | rev( sapply( W, function(v) ( sqrt( sum(v^2) ) ) ) ) |
| 42 | }) ) |
| 43 | } |