data_bin_file = ".epclust_test_m.bin"
unlink(data_bin_file)
- #dataset 200 cols / 30 rows
+ # Dataset 200 cols / 30 rows
data_ascii = matrix(runif(200*30,-10,10),nrow=30)
nbytes = 4 #lead to a precision of 1e-7 / 1e-8
endian = "little"
- #Simulate serialization in one single call
+ # Simulate serialization in one single call
binarize(data_ascii, data_bin_file, 500, ",", nbytes, endian)
expect_equal(file.info(data_bin_file)$size, length(data_ascii)*nbytes+8)
for (indices in list(c(1,3,5), 3:13, c(5,20,50), c(75,130:135), 196:200))
}
unlink(data_bin_file)
- #...in several calls (last call complete, next call NULL)
+ # Serialization in several calls (last call complete, next call NULL)
for (i in 1:20)
- binarize(data_ascii[((i-1)*10+1):(i*10),], data_bin_file, 20, ",", nbytes, endian)
+ binarize(data_ascii[,((i-1)*10+1):(i*10)], data_bin_file, 20, ",", nbytes, endian)
expect_equal(file.info(data_bin_file)$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_bin_file = ".epclust_test_t.bin"
unlink(data_bin_file)
- #dataset 200 cols / 30 rows
+ # Dataset 200 cols / 30 rows
data_ascii = matrix(runif(200*30,-10,10),nrow=30)
nbytes = 8
endian = "little"
binarizeTransform(getSeries, function(series) apply(series, 2, range),
trans_bin_file, 250, nbytes, endian)
unlink(data_bin_file)
- expect_equal(file.info(trans_bin_file)$size, 2*nrow(data_ascii)*nbytes+8)
+ expect_equal(file.info(trans_bin_file)$size, 2*ncol(data_ascii)*nbytes+8)
for (indices in list(c(1,3,5), 3:13, c(5,20,50), c(75,130:135), 196:200))
{
trans_cols = getDataInFile(indices, trans_bin_file, nbytes, endian)
- expect_equal(trans_cols, apply(data_ascii[indices,],2,range), tolerance=1e-6)
+ expect_equal(trans_cols, apply(data_ascii[,indices],2,range), tolerance=1e-6)
}
unlink(trans_bin_file)
})
data_bin_file = ".epclust_test_c.bin"
unlink(data_bin_file)
- #dataset 300 cols / 50 rows
+ # Dataset 300 cols / 50 rows
data_csv = system.file("testdata","de_serialize.csv",package="epclust")
nbytes = 8
endian = "big"
- data_ascii = as.matrix(read.csv(data_csv, sep=";", header=FALSE)) #for ref
+ data_ascii = t( as.matrix(read.table(data_csv, sep=";", header=FALSE)) ) #for ref
- #Simulate serialization in one single call
+ # Simulate serialization in one single call
binarize(data_csv, data_bin_file, 350, ";", nbytes, endian)
expect_equal(file.info(data_bin_file)$size, 300*50*8+8)
for (indices in list(c(1,3,5), 3:13, c(5,20,50), c(75,130:135), 196:200))
{
- #HACK: as.matrix(as.data.frame( )) required to match (ref) data structure
- data_cols = as.matrix(as.data.frame( getDataInFile(indices,data_bin_file,nbytes,endian) ))
+ data_cols = getDataInFile(indices,data_bin_file,nbytes,endian)
+ #HACK: rows naming required to match (ref) data structure
+ rownames(data_cols) <- paste("V",seq_len(nrow(data_ascii)), sep="")
expect_equal(data_cols, data_ascii[,indices])
}
unlink(data_bin_file)
- #...in several calls / chunks of 29 --> 29*10 + 10, incomplete last
+ # Serialization in several calls / chunks of 29 --> 29*10 + 10, incomplete last
data_con = file(data_csv, "r")
binarize(data_con, data_bin_file, 29, ";", nbytes, endian)
expect_equal(file.info(data_bin_file)$size, 300*50*8+8)
for (indices in list(c(1,3,5), 3:13, c(5,20,50), c(75,130:135), 196:200))
{
- data_cols = as.matrix(as.data.frame( getDataInFile(indices,data_bin_file,nbytes,endian) ))
+ data_cols = getDataInFile(indices,data_bin_file,nbytes,endian)
+ rownames(data_cols) <- paste("V",seq_len(nrow(data_ascii)), sep="")
expect_equal(data_cols, data_ascii[,indices])
}
unlink(data_bin_file)