| 1 | context("computeMedoidsIndices") |
| 2 | |
| 3 | test_that("serialization + getDataInFile retrieve original data / from matrix", |
| 4 | { |
| 5 | data_bin_file = "/tmp/epclust_test_m.bin" |
| 6 | unlink(data_bin_file) |
| 7 | |
| 8 | #dataset 200 lignes / 30 columns |
| 9 | data_ascii = matrix(runif(200*30,-10,10),ncol=30) |
| 10 | nbytes = 4 #lead to a precision of 1e-7 / 1e-8 |
| 11 | endian = "little" |
| 12 | |
| 13 | #Simulate serialization in one single call |
| 14 | binarize(data_ascii, data_bin_file, 500, ",", nbytes, endian) |
| 15 | expect_equal(file.info(data_bin_file)$size, length(data_ascii)*nbytes+8) |
| 16 | for (indices in list(c(1,3,5), 3:13, c(5,20,50), c(75,130:135), 196:200)) |
| 17 | { |
| 18 | data_lines = getDataInFile(indices, data_bin_file, nbytes, endian) |
| 19 | expect_equal(data_lines, data_ascii[indices,], tolerance=1e-6) |
| 20 | } |
| 21 | unlink(data_bin_file) |
| 22 | |
| 23 | #...in several calls (last call complete, next call NULL) |
| 24 | for (i in 1:20) |
| 25 | binarize(data_ascii[((i-1)*10+1):(i*10),], data_bin_file, 20, ",", nbytes, endian) |
| 26 | expect_equal(file.info(data_bin_file)$size, length(data_ascii)*nbytes+8) |
| 27 | for (indices in list(c(1,3,5), 3:13, c(5,20,50), c(75,130:135), 196:200)) |
| 28 | { |
| 29 | data_lines = getDataInFile(indices, data_bin_file, nbytes, endian) |
| 30 | expect_equal(data_lines, data_ascii[indices,], tolerance=1e-6) |
| 31 | } |
| 32 | unlink(data_bin_file) |
| 33 | }) |
| 34 | |
| 35 | TODO: test computeMedoids + filter |
| 36 | # #R-equivalent, requiring a matrix (thus potentially breaking "fit-in-memory" hope) |
| 37 | # mat_meds = medoids[,] |
| 38 | # mi = rep(NA,nb_series) |
| 39 | # for (i in 1:nb_series) |
| 40 | # mi[i] <- which.min( rowSums( sweep(mat_meds, 2, ref_series[i,], '-')^2 ) ) |
| 41 | # rm(mat_meds); gc() |
| 42 | |