tests/testthat/test-cpp_data.R

In tlverse/sl3: Pipelines for Machine Learning and Super Learning

context("test-cpp_data.R -- cpp data and subsets")

if (FALSE) {
  setwd("..")
  setwd("..")
  getwd()
  library("devtools")
  document()
  load_all("./") # load all R files in /R and datasets in /data. Ignores NAMESPACE:
  setwd("..")
  install("sl3", build_vignettes = FALSE, dependencies = FALSE) # INSTALL W/ devtools:
}

notrun.save.cpp.data <- function() {
  library("hbgd")
  data(cpp)
  cpp <- cpp[, names(cpp)[!names(cpp) %in% c("geniq", "sysbp", "diabp", "preeclmp")]]
  cpp_1yr <- cpp[cpp[["agedays"]] == 366, ]
  # --------------------------------
  # save as compressed R file
  # --------------------------------
  require("tools")
  save(cpp, compress = TRUE, file = "./data/cpp.rda", compression_level = 9)
  resaveRdaFiles("./data/cpp.rda", compress = "bzip2")

  save(cpp_1yr, compress = TRUE, file = "./data/cpp_1yr.rda", compression_level = 9)
  resaveRdaFiles("./data/cpp_1yr.rda", compress = "bzip2")

  cpp_imputed <- cpp[!is.na(cpp[, "haz"]), ]
  covars <- c("apgar1", "apgar5", "parity", "gagebrth", "mage", "meducyrs", "sexn")
  cpp_imputed[is.na(cpp_imputed)] <- 0
  save(cpp_imputed, compress = TRUE, file = "./data/cpp_imputed.rda", compression_level = 9)
  resaveRdaFiles("./data/cpp_imputed.rda", compress = "bzip2")
}

data(cpp)
data(cpp_1yr)

cpp <- cpp[!is.na(cpp[, "haz"]), ]
covars <- c("apgar1", "apgar5", "parity", "gagebrth", "mage", "meducyrs", "sexn")
cpp[is.na(cpp)] <- 0
outcome <- "haz"
cpp <- cpp[1:150, ]