test_that("Poisson 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"
  pyr <- "a_bad"
  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" = 0.95, "maxiter" = -1, "halfmax" = 1, "epsilon" = 1e-9, "deriv_epsilon" = 1e-9, "abs_max" = 1.0, "change_all" = TRUE, "dose_abs_max" = 1.0, "verbose" = 0, "double_step" = 1)
  expect_error(RunPoissonRegression(df, pyr, event, names, term_n, tform, keep_constant, a_n, modelform, fir, der_iden, control))
})
test_that("Poisson 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"
  pyr <- "a"
  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" = 0.95, "maxiter" = -1, "halfmax" = 1, "epsilon" = 1e-9, "deriv_epsilon" = 1e-9, "abs_max" = 1.0, "change_all" = TRUE, "dose_abs_max" = 1.0, "verbose" = 0, "double_step" = 1)
  expect_error(RunPoissonRegression(df, pyr, event, names, term_n, tform, keep_constant, a_n, modelform, fir, der_iden, control))
})
test_that("Poisson 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)
  fac <- c(0, 0, 0, 0, 1, 0, 0)
  df <- data.table("a" = a, "b" = b, "c" = c, "d" = d)
  time1 <- "a"
  time2 <- "b"
  event <- "c"
  pyr <- "a"
  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" = 0.95, "maxiter" = -1, "halfmax" = 1, "epsilon" = 1e-9, "deriv_epsilon" = 1e-9, "abs_max" = 1.0, "change_all" = TRUE, "dose_abs_max" = 1.0, "verbose" = 0, "double_step" = 1)
  expect_error(RunPoissonRegression(df, pyr, event, names, term_n, tform, keep_constant, a_n, modelform, fir, der_iden, control))
  #
  a <- c(0, 1, 2, 3, 4, 5, 6)
  b <- c(1, 2, 3, 4, 5, 6, 7)
  c <- c(0, 1, 1, 1, 0, 0, 1)
  d <- c(3, 4, 5, 6, 7, 8, 9)
  fac <- c(0, 0, 0, 0, 1, 0, 0)
  df <- data.table("a" = a, "b" = b, "c" = c, "d" = d, "fac" = fac)
  expect_no_error(RunPoissonRegression_STRATA(df, pyr, event, names, term_n, tform, keep_constant, a_n, modelform, fir, der_iden, control, c("fac")))
})

test_that("Pois 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"
  df$pyr <- df$t1 - df$t0
  pyr <- "pyr"
  event <- "lung"
  names <- c("dose", "fac")
  term_n <- c(0, 0)
  tform <- c("loglin", "loglin")
  keep_constant <- c(0, 0)
  a_n <- c(0.01, 0.1)
  modelform <- "M"
  fir <- 0
  der_iden <- 0
  control <- list("ncores" = 2, "lr" = 0.75, "maxiter" = 20, "halfmax" = 5, "epsilon" = 1e-6, "deriv_epsilon" = 1e-6, "abs_max" = 1.0, "change_all" = TRUE, "dose_abs_max" = 100.0, "verbose" = 0, "ties" = "breslow", "double_step" = 1)
  e <- RunPoissonRegression(df, pyr, event, names, term_n, tform, keep_constant, a_n, modelform, fir, der_iden, control)
  expect_equal(e$beta_0, c(-0.727884, -1.514085), tolerance = 1e-2)
})
test_that("Pois 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"
  df$pyr <- df$t1 - df$t0
  pyr <- "pyr"
  event <- "lung"
  names <- c("dose", "fac")
  term_n <- c(0, 0)
  tform <- c("loglin", "plin")
  keep_constant <- c(0, 0)
  a_n <- c(0.01, 0.5)
  modelform <- "M"
  fir <- 0
  der_iden <- 0
  control <- list("ncores" = 2, "lr" = 0.75, "maxiter" = 20, "halfmax" = 5, "epsilon" = 1e-6, "deriv_epsilon" = 1e-6, "abs_max" = 1.0, "change_all" = TRUE, "dose_abs_max" = 100.0, "verbose" = 0, "ties" = "breslow", "double_step" = 1)
  e <- RunPoissonRegression(df, pyr, event, names, term_n, tform, keep_constant, a_n, modelform, fir, der_iden, control)
  expect_equal(e$beta_0, c(-0.32, -0.6), tolerance = 1e-2)
})
test_that("Pois 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"
  df$pyr <- df$t1 - df$t0
  pyr <- "pyr"
  event <- "lung"
  names <- c("dose", "fac")
  term_n <- c(0, 1)
  tform <- c("loglin", "plin")
  keep_constant <- c(0, 0)
  a_n <- c(0.01, 0.5)
  modelform <- "A"
  fir <- 0
  der_iden <- 0
  control <- list("ncores" = 2, "lr" = 0.75, "maxiter" = 100, "halfmax" = 5, "epsilon" = 1e-6, "deriv_epsilon" = 1e-6, "abs_max" = 1.0, "change_all" = TRUE, "dose_abs_max" = 100.0, "verbose" = 0, "ties" = "breslow", "double_step" = 1)
  e <- RunPoissonRegression(df, pyr, event, names, term_n, tform, keep_constant, a_n, modelform, fir, der_iden, control)
  expect_equal(e$beta_0, c(-0.1585696, -1.4945955), tolerance = 1e-2)
})

test_that("Pois 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"
  df$pyr <- df$t1 - df$t0
  pyr <- "pyr"
  event <- "lung"
  names <- c("dose", "fac")
  term_n <- c(0, 0)
  tform <- c("loglin", "loglin")
  keep_constant <- c(0, 0)
  a_n <- c(0.01, 0.1)
  modelform <- "M"
  fir <- 0
  der_iden <- 0
  control <- list("ncores" = 2, "lr" = 0.75, "maxiter" = 20, "halfmax" = 5, "epsilon" = 1e-6, "deriv_epsilon" = 1e-6, "abs_max" = 1.0, "change_all" = TRUE, "dose_abs_max" = 100.0, "verbose" = 0, "ties" = "breslow", "double_step" = 1)
  e <- RunPoissonRegression_Single(df, pyr, event, names, term_n, tform, a_n, modelform, fir, control)
  expect_equal(e$AIC, 2354.055, tolerance = 1e-2)
})
test_that("Pois 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"
  df$pyr <- df$t1 - df$t0
  pyr <- "pyr"
  event <- "lung"
  names <- c("dose")
  term_n <- c(0)
  tform <- c("loglin")
  keep_constant <- c(0)
  a_n <- c(0.01)
  modelform <- "M"
  fir <- 0
  der_iden <- 0
  control <- list("ncores" = 2, "lr" = 0.75, "maxiter" = 20, "halfmax" = 5, "epsilon" = 1e-6, "deriv_epsilon" = 1e-6, "abs_max" = 1.0, "change_all" = TRUE, "dose_abs_max" = 100.0, "verbose" = 0, "ties" = "breslow", "double_step" = 1)
  e <- RunPoissonRegression_STRATA(df, pyr, event, names, term_n, tform, keep_constant, a_n, modelform, fir, der_iden, control, c("fac"))
  expect_equal(e$beta_0, c(0.05476188), tolerance = 1e-1)
})