train_test_filesystem: Organise files into a train-test filesystem

In MIC: Analysis of Antimicrobial Minimum Inhibitory Concentration Data

Organise files into a train-test filesystem

Description

Organise files into a train-test filesystem

Usage

train_test_filesystem(
  path_to_files,
  file_ext,
  split = 0.8,
  train_folder = "train",
  test_folder = "test",
  shuffle = TRUE,
  overwrite = FALSE
)

Arguments

path_to_files	directory containing files
file_ext	file extension to filter
split	training data split
train_folder	name of training folder (subdirectory), will be created if does not exist
test_folder	name of testing folder (subdirectory), will be created if does not exist
shuffle	randomise files when splitting (if FALSE, files will be sorted by filename prior to splitting)
overwrite	force overwrite of files that already exist

Value

named vector of train and test directories

Examples

set.seed(123)
# create 10 random DNA files
tmp_dir <- tempdir()
# remove any existing .fna files
file.remove(
  list.files(tmp_dir, pattern = "*.fna", full.names = TRUE)
)

for (i in 1:10) {
 writeLines(paste0(">", i, "\n", paste0(sample(c("A", "T", "C", "G"),
 100, replace = TRUE), collapse = "")), file.path(tmp_dir, paste0(i, ".fna")))
}

# split files into train and test directories
paths <- train_test_filesystem(tmp_dir,
                               file_ext = "fna",
                               split = 0.8,
                               shuffle = TRUE,
                               overwrite = TRUE)

list.files(paths[["train"]])
list.files(paths[["test"]])

MIC documentation built on April 12, 2025, 2:26 a.m.