test_that("Coxph time column missing", {
  a <- c(0, 1, 2, 3, 4, 5, 6)
  b <- c(1, 2, 3, 4, 5, 6, 7)
  c <- c(0, 1, 0, 0, 0, 1, 0)
  d <- c(3, 4, 5, 6, 7, 8, 9)
  df <- data.table("a" = a, "b" = b, "c" = c, "d" = d)
  time1 <- "a_bad"
  time2 <- "b"
  event <- "c"
  names <- c("d")
  term_n <- c(0)
  tform <- c("loglin")
  keep_constant <- c(0)
  a_n <- c(-0.1)
  modelform <- "M"
  fir <- 0
  der_iden <- 0
  control <- list("ncores" = 2, "lr" = 0.75, "maxiter" = -1, "halfmax" = 5, "epsilon" = 1e-9, "deriv_epsilon" = 1e-9, "abs_max" = 1.0, "change_all" = TRUE, "dose_abs_max" = 100.0, "verbose" = 0, "ties" = "breslow", "double_step" = 1)
  expect_error(RunCoxRegression(df, time1, time2, event, names, term_n, tform, keep_constant, a_n, modelform, fir, der_iden, control))
})
test_that("Coxph no events", {
  a <- c(0, 1, 2, 3, 4, 5, 6)
  b <- c(1, 2, 3, 4, 5, 6, 7)
  c <- c(0, 0, 0, 0, 0, 0, 0)
  d <- c(3, 4, 5, 6, 7, 8, 9)
  df <- data.table("a" = a, "b" = b, "c" = c, "d" = d)
  time1 <- "a"
  time2 <- "b"
  event <- "c"
  names <- c("d", "d")
  term_n <- c(0, 1)
  tform <- c("loglin", "loglin")
  keep_constant <- c(0, 0)
  a_n <- c(-0.1, 0.1)
  modelform <- "M"
  fir <- 0
  der_iden <- 0
  control <- list("ncores" = 2, "lr" = 0.75, "maxiter" = -1, "halfmax" = 5, "epsilon" = 1e-9, "deriv_epsilon" = 1e-9, "abs_max" = 1.0, "change_all" = TRUE, "dose_abs_max" = 100.0, "verbose" = 0, "ties" = "breslow", "double_step" = 1)
  expect_error(RunCoxRegression(df, time1, time2, event, names, term_n, tform, keep_constant, a_n, modelform, fir, der_iden, control))
})

test_that("Coxph_strata time column missing", {
  a <- c(0, 1, 2, 3, 4, 5, 6)
  b <- c(1, 2, 3, 4, 5, 6, 7)
  c <- c(0, 1, 0, 0, 0, 1, 0)
  d <- c(3, 4, 5, 6, 7, 8, 9)
  e <- c(1, 1, 0, 0, 1, 0, 1)
  df <- data.table("a" = a, "b" = b, "c" = c, "d" = d, "e" = e)
  time1 <- "a_bad"
  time2 <- "b"
  event <- "c"
  names <- c("d")
  strat_col <- "e"
  term_n <- c(0)
  tform <- c("loglin")
  keep_constant <- c(0)
  a_n <- c(-0.1)
  modelform <- "M"
  fir <- 0
  der_iden <- 0
  control <- list("ncores" = 2, "lr" = 0.75, "maxiter" = -1, "halfmax" = 5, "epsilon" = 1e-9, "deriv_epsilon" = 1e-9, "abs_max" = 1.0, "change_all" = TRUE, "dose_abs_max" = 100.0, "verbose" = 0, "ties" = "breslow", "double_step" = 1)
  expect_error(RunCoxRegression_STRATA(df, time1, time2, event, names, term_n, tform, keep_constant, a_n, modelform, fir, der_iden, control, strat_col))
})
test_that("Coxph_strata no events", {
  a <- c(0, 1, 2, 3, 4, 5, 6)
  b <- c(1, 2, 3, 4, 5, 6, 7)
  c <- c(0, 0, 0, 0, 0, 0, 0)
  d <- c(3, 4, 5, 6, 7, 8, 9)
  e <- c(1, 1, 0, 0, 1, 0, 1)
  df <- data.table("a" = a, "b" = b, "c" = c, "d" = d, "e" = e)
  time1 <- "a"
  time2 <- "b"
  event <- "c"
  names <- c("d")
  strat_col <- "e"
  term_n <- c(0)
  tform <- c("loglin")
  keep_constant <- c(0)
  a_n <- c(-0.1)
  modelform <- "M"
  fir <- 0
  der_iden <- 0
  control <- list("ncores" = 2, "lr" = 0.75, "maxiter" = -1, "halfmax" = 5, "epsilon" = 1e-9, "deriv_epsilon" = 1e-9, "abs_max" = 1.0, "change_all" = TRUE, "dose_abs_max" = 100.0, "verbose" = 0, "ties" = "breslow", "double_step" = 1)
  expect_error(RunCoxRegression_STRATA(df, time1, time2, event, names, term_n, tform, keep_constant, a_n, modelform, fir, der_iden, control, strat_col))
  #
  a <- c(0, 1, 2, 3, 4, 5, 6)
  b <- c(1, 2, 3, 4, 5, 6, 7)
  c <- c(1, 0, 0, 0, 0, 0, 0)
  d <- c(3, 4, 5, 6, 7, 8, 9)
  e <- c(1, 1, 0, 0, 1, 0, 1)
  df <- data.table("a" = a, "b" = b, "c" = c, "d" = d, "e" = e)
  expect_no_error(RunCoxRegression_STRATA(df, time1, time2, event, names, term_n, tform, keep_constant, a_n, modelform, fir, der_iden, control, strat_col))
})
test_that("Coxph_strata no strata", {
  a <- c(0, 1, 2, 3, 4, 5, 6)
  b <- c(1, 2, 3, 4, 5, 6, 7)
  c <- c(0, 1, 0, 0, 0, 1, 0)
  d <- c(3, 4, 5, 6, 7, 8, 9)
  e <- c(1, 1, 0, 0, 1, 0, 1)
  df <- data.table("a" = a, "b" = b, "c" = c, "d" = d, "e" = e)
  time1 <- "a"
  time2 <- "b"
  event <- "c"
  names <- c("d")
  strat_col <- "e_bad"
  term_n <- c(0)
  tform <- c("loglin")
  keep_constant <- c(0)
  a_n <- c(-0.1)
  modelform <- "M"
  fir <- 0
  der_iden <- 0
  control <- list("ncores" = 2, "lr" = 0.75, "maxiter" = -1, "halfmax" = 5, "epsilon" = 1e-9, "deriv_epsilon" = 1e-9, "abs_max" = 1.0, "change_all" = TRUE, "dose_abs_max" = 100.0, "verbose" = 0, "ties" = "breslow", "double_step" = 1)
  expect_error(RunCoxRegression_STRATA(df, time1, time2, event, names, term_n, tform, keep_constant, a_n, modelform, fir, der_iden, control, strat_col))
})
test_that("Coxph_strata strata with no error", {
  a <- c(0, 1, 2, 3, 4, 5, 6)
  b <- c(1, 2, 3, 4, 5, 6, 7)
  c <- c(1, 1, 0, 0, 0, 0, 0)
  d <- c(3, 4, 5, 6, 7, 8, 9)
  e <- c(1, 1, 0, 0, 1, 0, 1)
  df <- data.table("a" = a, "b" = b, "c" = c, "d" = d, "e" = e)
  time1 <- "a"
  time2 <- "b"
  event <- "c"
  names <- c("d")
  strat_col <- "e_bad"
  term_n <- c(0)
  tform <- c("loglin")
  keep_constant <- c(0)
  a_n <- c(-0.1)
  modelform <- "M"
  fir <- 0
  der_iden <- 0
  control <- list("ncores" = 2, "lr" = 0.75, "maxiter" = -1, "halfmax" = 5, "epsilon" = 1e-9, "deriv_epsilon" = 1e-9, "abs_max" = 1.0, "change_all" = TRUE, "dose_abs_max" = 100.0, "verbose" = 0, "ties" = "breslow", "double_step" = 1)
  expect_error(RunCoxRegression_STRATA(df, time1, time2, event, names, term_n, tform, keep_constant, a_n, modelform, fir, der_iden, control, strat_col))
})

test_that("Coxph null time column missing", {
  a <- c(0, 1, 2, 3, 4, 5, 6)
  b <- c(1, 2, 3, 4, 5, 6, 7)
  c <- c(0, 1, 0, 0, 0, 1, 0)
  d <- c(3, 4, 5, 6, 7, 8, 9)
  df <- data.table("a" = a, "b" = b, "c" = c, "d" = d)
  time1 <- "a_bad"
  time2 <- "b"
  event <- "c"
  control <- list("ncores" = 2, "lr" = 0.75, "maxiter" = -1, "halfmax" = 5, "epsilon" = 1e-9, "deriv_epsilon" = 1e-9, "abs_max" = 1.0, "change_all" = TRUE, "dose_abs_max" = 100.0, "verbose" = 0, "ties" = "breslow", "double_step" = 1)
  expect_error(RunCoxNull(df, time1, time2, event, control))
})
test_that("Coxph null no events", {
  a <- c(0, 1, 2, 3, 4, 5, 6)
  b <- c(1, 2, 3, 4, 5, 6, 7)
  c <- c(0, 0, 0, 0, 0, 0, 0)
  d <- c(3, 4, 5, 6, 7, 8, 9)
  df <- data.table("a" = a, "b" = b, "c" = c, "d" = d)
  time1 <- "a"
  time2 <- "b"
  event <- "c"
  control <- list("ncores" = 2, "lr" = 0.75, "maxiter" = -1, "halfmax" = 5, "epsilon" = 1e-9, "deriv_epsilon" = 1e-9, "abs_max" = 1.0, "change_all" = TRUE, "dose_abs_max" = 100.0, "verbose" = 0, "ties" = "breslow", "double_step" = 1)
  expect_error(RunCoxNull(df, time1, time2, event, control))
})

test_that("Coxph loglin_M", {
  fname <- "ll_0.csv"
  colTypes <- c("double", "double", "double", "integer", "integer")
  df <- fread(fname, nThread = min(c(detectCores(), 2)), data.table = TRUE, header = TRUE, colClasses = colTypes, verbose = FALSE, fill = TRUE)
  time1 <- "t0"
  time2 <- "t1"
  event <- "lung"
  names <- c("dose", "fac")
  term_n <- c(0, 0)
  tform <- c("loglin", "loglin")
  keep_constant <- c(0, 0)
  a_n <- c(0.01, 0.1)
  modelform <- "M"
  fir <- 0
  der_iden <- 0
  control <- list("ncores" = 2, "lr" = 0.75, "maxiter" = 20, "halfmax" = 5, "epsilon" = 1e-6, "deriv_epsilon" = 1e-6, "abs_max" = 1.0, "change_all" = TRUE, "dose_abs_max" = 100.0, "verbose" = 0, "ties" = "breslow", "double_step" = 1)
  e <- RunCoxRegression(df, time1, time2, event, names, term_n, tform, keep_constant, a_n, modelform, fir, der_iden, control)
  expect_equal(e$beta_0, c(-0.0996, -0.05697), tolerance = 1e-2)
})
test_that("Coxph loglin_plin_M", {
  fname <- "l_pl_0.csv"
  colTypes <- c("double", "double", "double", "integer", "integer")
  df <- fread(fname, nThread = min(c(detectCores(), 2)), data.table = TRUE, header = TRUE, colClasses = colTypes, verbose = FALSE, fill = TRUE)
  time1 <- "t0"
  time2 <- "t1"
  event <- "lung"
  names <- c("dose", "fac")
  term_n <- c(0, 0)
  tform <- c("loglin", "plin")
  keep_constant <- c(0, 0)
  a_n <- c(0.01, 0.5)
  modelform <- "M"
  fir <- 0
  der_iden <- 0
  control <- list("ncores" = 2, "lr" = 0.75, "maxiter" = 20, "halfmax" = 5, "epsilon" = 1e-6, "deriv_epsilon" = 1e-6, "abs_max" = 1.0, "change_all" = TRUE, "dose_abs_max" = 100.0, "verbose" = 0, "ties" = "breslow", "double_step" = 1)
  e <- RunCoxRegression(df, time1, time2, event, names, term_n, tform, keep_constant, a_n, modelform, fir, der_iden, control)
  expect_equal(e$beta_0, c(0.1747772, 0.75), tolerance = 1e-2)
})
test_that("Coxph loglin_plin_A", {
  fname <- "l_pl_A_0.csv"
  colTypes <- c("double", "double", "double", "integer", "integer")
  df <- fread(fname, nThread = min(c(detectCores(), 2)), data.table = TRUE, header = TRUE, colClasses = colTypes, verbose = FALSE, fill = TRUE)
  time1 <- "t0"
  time2 <- "t1"
  event <- "lung"
  names <- c("dose", "fac")
  term_n <- c(0, 1)
  tform <- c("loglin", "plin")
  keep_constant <- c(0, 0)
  a_n <- c(0.01, 0.5)
  modelform <- "A"
  fir <- 0
  der_iden <- 0
  control <- list("ncores" = 2, "lr" = 0.75, "maxiter" = 100, "halfmax" = 5, "epsilon" = 1e-6, "deriv_epsilon" = 1e-6, "abs_max" = 1.0, "change_all" = TRUE, "dose_abs_max" = 100.0, "verbose" = 0, "ties" = "breslow", "double_step" = 1)
  e <- RunCoxRegression(df, time1, time2, event, names, term_n, tform, keep_constant, a_n, modelform, fir, der_iden, control)
  expect_equal(e$beta_0, c(0.11, 1.01), tolerance = 1e-2)
})
#
test_that("Coxph dose list", {
  fname <- "dose.csv"
  colTypes <- c("double", "double", "double", "integer")
  df <- fread(fname, nThread = min(c(detectCores(), 2)), data.table = TRUE, header = TRUE, colClasses = colTypes, verbose = FALSE, fill = TRUE)
  time1 <- "t0"
  time2 <- "t1"
  event <- "lung"
  names <- c("dose", "dose", "dose", "dose", "dose", "dose", "dose", "dose", "dose", "dose", "dose")
  term_n <- c(0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0)
  tform <- c("loglin_top", "lin_slope", "lin_int", "quad_slope", "step_slope", "step_int", "lin_quad_slope", "lin_quad_int", "lin_exp_slope", "lin_exp_int", "lin_exp_exp_slope")
  keep_constant <- c(0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0)
  tform <- c("loglin_top", "lin_slope", "lin_int", "quad_slope", "step_slope", "step_int", "lin_quad_slope", "lin_quad_int", "lin_exp_slope", "lin_exp_int", "lin_exp_exp_slope")
  a_n <- c(-0.1, -0.1, 1, -0.1, 1, 2, 0.3, 1.5, 0.2, 0.7, 1)
  modelform <- "M"
  fir <- 0
  der_iden <- 0
  control <- list("ncores" = 2, "lr" = 0.75, "maxiter" = 20, "halfmax" = 5, "epsilon" = 1e-6, "deriv_epsilon" = 1e-6, "abs_max" = 1.0, "change_all" = TRUE, "dose_abs_max" = 100.0, "verbose" = 0, "ties" = "breslow", "double_step" = 1)
  e <- RunCoxRegression(df, time1, time2, event, names, term_n, tform, keep_constant, a_n, modelform, fir, der_iden, control)
  expect_equal(e$beta_0, c(-0.10396225, -0.09955731, 1.00377389, -0.10537894, 1.01629097, 2.15102759, 0.29434874, 1.57836844, 0.20994531, 0.87551440, 1.00908073), tolerance = 1e-2)
})

test_that("Coxph fixed intercept", {
  fname <- "dose.csv"
  colTypes <- c("double", "double", "double", "integer")
  df <- fread(fname, nThread = min(c(detectCores(), 2)), data.table = TRUE, header = TRUE, colClasses = colTypes, verbose = FALSE, fill = TRUE)
  time1 <- "t0"
  time2 <- "t1"
  event <- "lung"
  names <- c("dose", "dose", "dose", "dose", "dose")
  term_n <- c(0, 0, 0, 0, 0)
  tform <- c("loglin", "lin_slope", "lin_int", "step_slope", "step_int")
  keep_constant <- c(0, 0, 1, 0, 1)
  a_n <- c(-0.1, 0.1, -1, 0.1, -1)
  modelform <- "M"
  fir <- 0
  der_iden <- 0
  control <- list("ncores" = 2, "lr" = 0.75, "maxiter" = 20, "halfmax" = 5, "epsilon" = 1e-6, "deriv_epsilon" = 1e-6, "abs_max" = 1.0, "change_all" = TRUE, "dose_abs_max" = 100.0, "verbose" = 0, "ties" = "breslow", "double_step" = 1)
  expect_no_error(RunCoxRegression(df, time1, time2, event, names, term_n, tform, keep_constant, a_n, modelform, fir, der_iden, control))
})

test_that("Coxph loglin_M Strata", {
  fname <- "ll_0.csv"
  colTypes <- c("double", "double", "double", "integer", "integer")
  df <- fread(fname, nThread = min(c(detectCores(), 2)), data.table = TRUE, header = TRUE, colClasses = colTypes, verbose = FALSE, fill = TRUE)
  time1 <- "t0"
  time2 <- "t1"
  event <- "lung"
  names <- c("dose")
  term_n <- c(0)
  tform <- c("loglin")
  keep_constant <- c(0)
  a_n <- c(0.01)
  modelform <- "M"
  fir <- 0
  der_iden <- 0
  control <- list("ncores" = 2, "lr" = 0.75, "maxiter" = 20, "halfmax" = 5, "epsilon" = 1e-6, "deriv_epsilon" = 1e-6, "abs_max" = 1.0, "change_all" = TRUE, "dose_abs_max" = 100.0, "verbose" = 0, "ties" = "breslow", "double_step" = 1)
  e <- RunCoxRegression_STRATA(df, time1, time2, event, names, term_n, tform, keep_constant, a_n, modelform, fir, der_iden, control, "fac")
  expect_equal(e$beta_0, c(-0.106), tolerance = 1e-2)
})
test_that("Coxph loglin_M Single", {
  fname <- "ll_0.csv"
  colTypes <- c("double", "double", "double", "integer", "integer")
  df <- fread(fname, nThread = min(c(detectCores(), 2)), data.table = TRUE, header = TRUE, colClasses = colTypes, verbose = FALSE, fill = TRUE)
  time1 <- "t0"
  time2 <- "t1"
  event <- "lung"
  names <- c("dose", "fac")
  term_n <- c(0, 0)
  tform <- c("loglin", "loglin")
  keep_constant <- c(0, 0)
  a_n <- c(0.01, 0.1)
  modelform <- "M"
  fir <- 0
  der_iden <- 0
  control <- list("ncores" = 2, "lr" = 0.75, "maxiter" = 20, "halfmax" = 5, "epsilon" = 1e-6, "deriv_epsilon" = 1e-6, "abs_max" = 1.0, "change_all" = TRUE, "dose_abs_max" = 100.0, "verbose" = 0, "ties" = "breslow", "double_step" = 1)
  e <- RunCoxRegression_Single(df, time1, time2, event, names, term_n, tform, keep_constant, a_n, modelform, fir, control)
  expect_equal(e$AIC, 1056.299, tolerance = 1e-2)
})
test_that("Coxph loglin_M Null", {
  fname <- "ll_0.csv"
  colTypes <- c("double", "double", "double", "integer", "integer")
  df <- fread(fname, nThread = min(c(detectCores(), 2)), data.table = TRUE, header = TRUE, colClasses = colTypes, verbose = FALSE, fill = TRUE)
  time1 <- "t0"
  time2 <- "t1"
  event <- "lung"
  names <- c("dose", "fac")
  term_n <- c(0, 0)
  tform <- c("loglin", "loglin")
  keep_constant <- c(0, 0)
  a_n <- c(0.01, 0.1)
  modelform <- "M"
  fir <- 0
  der_iden <- 0
  control <- list("ncores" = 2, "lr" = 0.75, "maxiter" = 20, "halfmax" = 5, "epsilon" = 1e-6, "deriv_epsilon" = 1e-6, "abs_max" = 1.0, "change_all" = TRUE, "dose_abs_max" = 100.0, "verbose" = 0, "ties" = "breslow", "double_step" = 1)
  e <- RunCoxNull(df, time1, time2, event, control)
  expect_equal(e$AIC, 1052, tolerance = 1e-2)
})

test_that("Coxph loglin_M CENSOR", {
  fname <- "ll_cens_0.csv"
  colTypes <- c("double", "double", "double", "integer", "integer")
  df <- fread(fname, nThread = min(c(detectCores(), 2)), data.table = TRUE, header = TRUE, colClasses = colTypes, verbose = FALSE, fill = TRUE)
  time1 <- "t0"
  time2 <- "t1"
  event <- "lung"
  names <- c("dose", "fac")
  term_n <- c(0, 0)
  tform <- c("loglin", "loglin")
  keep_constant <- c(0, 0)
  a_n <- c(0.01, 0.1)
  modelform <- "M"
  fir <- 0
  der_iden <- 0
  control <- list("ncores" = 2, "lr" = 0.75, "maxiter" = 20, "halfmax" = 5, "epsilon" = 1e-6, "deriv_epsilon" = 1e-6, "abs_max" = 1.0, "change_all" = TRUE, "dose_abs_max" = 100.0, "verbose" = 0, "ties" = "breslow", "double_step" = 1)
  e <- RunCoxRegression(df, time1, time2, event, names, term_n, tform, keep_constant, a_n, modelform, fir, der_iden, control)
  expect_equal(e$beta_0, c(-1.19, 0.08), tolerance = 1e-2)
})
test_that("Coxph loglin_M CENSOR Adjusted", {
  fname <- "ll_cens_0.csv"
  colTypes <- c("double", "double", "double", "integer", "integer")
  df <- fread(fname, nThread = min(c(detectCores(), 2)), data.table = TRUE, header = TRUE, colClasses = colTypes, verbose = FALSE, fill = TRUE)
  time1 <- "t0"
  time2 <- "t1"
  event <- "lung"
  names <- c("dose", "fac")
  term_n <- c(0, 0)
  tform <- c("loglin", "loglin")
  keep_constant <- c(0, 0)
  a_n <- c(-1.1169, -0.04558)
  modelform <- "M"
  fir <- 0
  der_iden <- 0
  control <- list("ncores" = 2, "lr" = 0.75, "maxiter" = 20, "halfmax" = 5, "epsilon" = 1e-6, "deriv_epsilon" = 1e-6, "abs_max" = 1.0, "change_all" = TRUE, "dose_abs_max" = 100.0, "verbose" = 0, "ties" = "breslow", "double_step" = 1)
  plot_options <- list("name" = paste(tempfile(), "run", sep = ""), "verbose" = FALSE, "studyid" = "studyid", "age_unit" = "years")
  dft <- GetCensWeight(df, time1, time2, event, names, term_n, tform, keep_constant, a_n, modelform, fir, control, plot_options)
  #
  #
  expect_equal(sum(dft$ch), 336410, tolerance = 1e-2)
})
test_that("Coxph loglin_M CENSOR Default", {
  fname <- "ll_cens_0.csv"
  colTypes <- c("double", "double", "double", "integer", "integer")
  df <- fread(fname, nThread = min(c(detectCores(), 2)), data.table = TRUE, header = TRUE, colClasses = colTypes, verbose = FALSE, fill = TRUE)
  time1 <- "t0"
  time2 <- "t1"
  event <- "lung"
  names <- c("dose", "fac")
  term_n <- c(0, 0)
  tform <- c("loglin", "loglin")
  keep_constant <- c(0, 0)
  a_n <- c(0, 0)
  modelform <- "M"
  fir <- 0
  der_iden <- 0
  control <- list("ncores" = 2, "lr" = 0.75, "maxiter" = -1, "halfmax" = -1, "epsilon" = 1e-6, "deriv_epsilon" = 1e-6, "abs_max" = 1.0, "change_all" = TRUE, "dose_abs_max" = 100.0, "verbose" = 0, "ties" = "breslow", "double_step" = 1)
  plot_options <- list("name" = paste(tempfile(), "run", sep = ""), "verbose" = FALSE, "studyid" = "studyid", "age_unit" = "years")
  dft <- GetCensWeight(df, time1, time2, event, names, term_n, tform, keep_constant, a_n, modelform, fir, control, plot_options)
  #
  #
  expect_equal(sum(dft$ch), 699, tolerance = 1e-2)
})

test_that("Coxph loglin_M Basic", {
  fname <- "ll_0.csv"
  colTypes <- c("double", "double", "double", "integer", "integer")
  df <- fread(fname, nThread = min(c(detectCores(), 2)), data.table = TRUE, header = TRUE, colClasses = colTypes, verbose = FALSE, fill = TRUE)
  time1 <- "t0"
  time2 <- "t1"
  event <- "lung"
  names <- c("dose", "fac")
  term_n <- c(0, 0)
  tform <- c("loglin", "loglin")
  keep_constant <- c(0, 0)
  a_n <- c(0.01, 0.1)
  modelform <- "M"
  fir <- 0
  der_iden <- 0
  control <- list("ncores" = 2, "lr" = 0.75, "maxiter" = 20, "halfmax" = 5, "epsilon" = 1e-6, "deriv_epsilon" = 1e-6, "abs_max" = 1.0, "change_all" = TRUE, "dose_abs_max" = 100.0, "verbose" = 0, "ties" = "breslow", "double_step" = 1)
  e <- RunCoxRegression_Basic(df, time1, time2, event, names, keep_constant, a_n, der_iden, control)
  expect_equal(e$beta_0, c(-0.09962, -0.05698), tolerance = 1e-2)
})

test_that("Coxph censoring weight", {
  fname <- "ll_comp_0.csv"
  colTypes <- c("double", "double", "double", "integer", "integer")
  df <- fread(fname, nThread = min(c(detectCores(), 2)), data.table = TRUE, header = TRUE, colClasses = colTypes, verbose = FALSE, fill = TRUE)
  time1 <- "t0"
  time2 <- "t1"
  df$censor <- (df$lung == 0)
  event <- "censor"
  names <- c("dose", "fac")
  term_n <- c(0, 0)
  tform <- c("loglin", "loglin")
  keep_constant <- c(1, 0)
  a_n <- c(0, 0)
  modelform <- "M"
  fir <- 0
  der_iden <- 0
  control <- list("ncores" = 2, "lr" = 0.75, "maxiter" = -1, "halfmax" = -1, "epsilon" = 1e-6, "deriv_epsilon" = 1e-6, "abs_max" = 1.0, "change_all" = TRUE, "dose_abs_max" = 100.0, "verbose" = 0, "ties" = "breslow", "double_step" = 1)
  plot_options <- list("name" = paste(tempfile(), "run", sep = ""), "verbose" = TRUE, "studyid" = "studyid", "age_unit" = "years")
  dft <- GetCensWeight(df, time1, time2, event, names, term_n, tform, keep_constant, a_n, modelform, fir, control, plot_options)
  #
  #
  t_ref <- dft$t
  surv_ref <- dft$surv
  t_c <- df$t1
  cens_weight <- approx(t_ref, surv_ref, t_c, rule = 2)$y
  df$weighting <- cens_weight
  # message(sum(cens_weight))
  #
  event <- "lung"
  a_n <- c(-0.1, -0.1)
  keep_constant <- c(0, 0)
  e0 <- RunCoxRegression_CR(df, time1, time2, event, names, term_n, tform, keep_constant, a_n, modelform, fir, der_iden, control, "weighting")
  a_n <- c(-0.1, -0.1)
  keep_constant <- c(0, 0)
  e1 <- RunCoxRegression(df, time1, time2, event, names, term_n, tform, keep_constant, a_n, modelform, fir, der_iden, control)
  #
  expect_equal(e0$LogLik - e1$LogLik, -2.909427, tolerance = 1e-2)
  #
  expect_error(RunCoxRegression_CR(df, time1, time2, event, names, term_n, tform, keep_constant, a_n, modelform, fir, der_iden, control, "bad_weighting"))
})