save intermediate

[epclust.git] / epclust / tests / testthat / test.computeMedoidsIndices.R

diff --git a/epclust/tests/testthat/test.computeMedoidsIndices.R b/epclust/tests/testthat/test.computeMedoidsIndices.R
new file mode 100644 (file)
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+++ b/epclust/tests/testthat/test.computeMedoidsIndices.R
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+context("computeMedoidsIndices")
+
+test_that("serialization + getDataInFile retrieve original data / from matrix",
+{
+       data_bin_file = "/tmp/epclust_test_m.bin"
+       unlink(data_bin_file)
+
+       #dataset 200 lignes / 30 columns
+       data_ascii = matrix(runif(200*30,-10,10),ncol=30)
+       nbytes = 4 #lead to a precision of 1e-7 / 1e-8
+       endian = "little"
+
+       #Simulate serialization in one single call
+       binarize(data_ascii, data_bin_file, 500, ",", nbytes, endian)
+       expect_equal(file.info(data_bin_file)$size, length(data_ascii)*nbytes+8)
+       for (indices in list(c(1,3,5), 3:13, c(5,20,50), c(75,130:135), 196:200))
+       {
+               data_lines = getDataInFile(indices, data_bin_file, nbytes, endian)
+               expect_equal(data_lines, data_ascii[indices,], tolerance=1e-6)
+       }
+       unlink(data_bin_file)
+
+       #...in several calls (last call complete, next call NULL)
+       for (i in 1:20)
+               binarize(data_ascii[((i-1)*10+1):(i*10),], data_bin_file, 20, ",", nbytes, endian)
+       expect_equal(file.info(data_bin_file)$size, length(data_ascii)*nbytes+8)
+       for (indices in list(c(1,3,5), 3:13, c(5,20,50), c(75,130:135), 196:200))
+       {
+               data_lines = getDataInFile(indices, data_bin_file, nbytes, endian)
+               expect_equal(data_lines, data_ascii[indices,], tolerance=1e-6)
+       }
+       unlink(data_bin_file)
+})
+
+TODO: test computeMedoids + filter
+#              #R-equivalent, requiring a matrix (thus potentially breaking "fit-in-memory" hope)
+#              mat_meds = medoids[,]
+#              mi = rep(NA,nb_series)
+#              for (i in 1:nb_series)
+#                      mi[i] <- which.min( rowSums( sweep(mat_meds, 2, ref_series[i,], '-')^2 ) )
+#              rm(mat_meds); gc()
+