# ---------------------------------------------------------
# formula must be a formula
# ---------------------------------------------------------

test_that("nonlinear mixed model validates formula", {
  
  skip_if_not_installed("nlme")
  
  dat <- data.frame(
    id = factor(1:10),
    x = 1:10,
    y = 1:10
  )
  
  expect_error(
    fit_nlme_biomix(
      formula = "y ~ x",
      data = dat,
      fixed = a ~ 1,
      random = a ~ 1 | id,
      start = c(a = 1)
    ),
    "formula must be a formula"
  )
})


# ---------------------------------------------------------
# data must be a data frame or groupedData object
# ---------------------------------------------------------

test_that("nonlinear mixed model validates data", {
  
  skip_if_not_installed("nlme")
  
  expect_error(
    fit_nlme_biomix(
      formula = y ~ x,
      data = list(
        y = 1:10,
        x = 1:10
      ),
      fixed = a ~ 1,
      random = a ~ 1,
      start = c(a = 1)
    ),
    "data must be a data frame or groupedData object"
  )
})


# ---------------------------------------------------------
# fixed must be supplied
# ---------------------------------------------------------

test_that("nonlinear mixed model requires fixed effects", {
  
  skip_if_not_installed("nlme")
  
  dat <- data.frame(
    id = factor(1:10),
    x = 1:10,
    y = 1:10
  )
  
  expect_error(
    fit_nlme_biomix(
      formula = y ~ x,
      data = dat,
      random = a ~ 1 | id,
      start = c(a = 1)
    ),
    "The 'fixed' argument must be supplied"
  )
})


# ---------------------------------------------------------
# random must be supplied
# ---------------------------------------------------------

test_that("nonlinear mixed model requires random effects", {
  
  skip_if_not_installed("nlme")
  
  dat <- data.frame(
    id = factor(1:10),
    x = 1:10,
    y = 1:10
  )
  
  expect_error(
    fit_nlme_biomix(
      formula = y ~ x,
      data = dat,
      fixed = a ~ 1,
      start = c(a = 1)
    ),
    "The 'random' argument must be supplied"
  )
})


# ---------------------------------------------------------
# start must be supplied
# ---------------------------------------------------------

test_that("nonlinear mixed model requires starting values", {
  
  skip_if_not_installed("nlme")
  
  dat <- data.frame(
    id = factor(1:10),
    x = 1:10,
    y = 1:10
  )
  
  expect_error(
    fit_nlme_biomix(
      formula = y ~ x,
      data = dat,
      fixed = a ~ 1,
      random = a ~ 1 | id
    ),
    "Starting values must be supplied through 'start'"
  )
})


# ---------------------------------------------------------
# start must be numeric
# ---------------------------------------------------------

test_that("nonlinear mixed model validates numeric starting values", {
  
  skip_if_not_installed("nlme")
  
  dat <- data.frame(
    id = factor(1:10),
    x = 1:10,
    y = 1:10
  )
  
  expect_error(
    fit_nlme_biomix(
      formula = y ~ x,
      data = dat,
      fixed = a ~ 1,
      random = a ~ 1 | id,
      start = "1"
    ),
    "'start' must be a named numeric vector"
  )
})


# ---------------------------------------------------------
# start must have names
# ---------------------------------------------------------

test_that("nonlinear mixed model validates named starting values", {
  
  skip_if_not_installed("nlme")
  
  dat <- data.frame(
    id = factor(1:10),
    x = 1:10,
    y = 1:10
  )
  
  expect_error(
    fit_nlme_biomix(
      formula = y ~ x,
      data = dat,
      fixed = a ~ 1,
      random = a ~ 1 | id,
      start = c(1)
    ),
    "'start' must be a named numeric vector"
  )
})