tests/testthat/test-vollenweider_etr_I.R

In pam: Fast and Efficient Processing of PAM Data

test_that("test-vollenweider_etr_I generate regression 20240925.csv - linux", {
  skip_if_not(is_reference_platform())

  test_data_file <- testthat::test_path("data", "dual_pam_data", "20240925.csv")
  data <- read_dual_pam_data(test_data_file)
  model_result <- vollenweider_generate_regression_ETR_I(data)

  expect_equal(model_result[["residual_sum_of_squares"]], 57.4443325)
  expect_equal(model_result[["pmax"]], 165.4671070)
  # expect_equal(model_result[["a"]], 0.001864811)
  # expect_equal(model_result[["alpha"]], 0.00001772)
  expect_equal(model_result[["n"]], 70.3820335)
  expect_equal(model_result[["ik"]], 536.2487)
  expect_equal(model_result[["popt"]], 153.098976)
  expect_equal(model_result[["iik"]], 496.165847)
  expect_equal(model_result[["pmax_popt_and_ik_iik_ratio"]], 1.08078520)
})

test_that("test-vollenweider_etr_I generate regression 20240925.csv", {
  test_data_file <- testthat::test_path("data", "dual_pam_data", "20240925.csv")
  data <- read_dual_pam_data(test_data_file)
  model_result <- vollenweider_generate_regression_ETR_I(data)
  expect_no_error(validate_model_result(model_result))
})

test_that("test-vollenweider_etr_I control plot 20240925.csv", {
  test_data_file <- testthat::test_path("data", "dual_pam_data", "20240925.csv")
  data <- read_dual_pam_data(test_data_file)
  model_result <- vollenweider_generate_regression_ETR_I(data)

  plot <- plot_control(
    data,
    model_result,
    "vollenweider ETR I 20240925.csv",
    color_vollenweider
  )
  expect_s3_class(plot, "ggplot")
  expect_gt(length(plot$layers), 0)

  out <- file.path("results", "test-vollenweider_etr_I control plot 20240925.jpg")
  ggplot2::ggsave(out, create.dir = TRUE, plot = plot, units = "px", width = 1000, height = 1000, dpi = 100, limitsize = FALSE)
  expect_true(file.exists(out))
})

test_that("test-vollenweider_etr_I generate regression modified 20240925.csv - linux", {
  skip_if_not(is_reference_platform())

  test_data_file <- testthat::test_path("data", "dual_pam_data", "20240925.csv")
  data <- read_dual_pam_data(test_data_file)
  model_result <- vollenweider_generate_regression_ETR_I(data)
  model_result <- vollenweider_modified(model_result)

  expect_equal(model_result[["residual_sum_of_squares"]], 57.4443325)
  expect_equal(model_result[["a"]], 165.4671070)
  # expect_equal(model_result[["b"]], 0.001864811)
  # expect_equal(model_result[["c"]], 0.00001772)
  expect_equal(model_result[["d"]], 70.3820335)
  expect_equal(model_result[["alpha"]], 0.308564116)
  expect_equal(model_result[["beta"]], NA_real_)
  expect_equal(model_result[["etrmax_with_photoinhibition"]], 153.098976)
  expect_equal(model_result[["etrmax_without_photoinhibition"]], 165.4671070)
  expect_equal(model_result[["ik_with_photoinhibition"]], 496.165847)
  expect_equal(model_result[["ik_without_photoinhibition"]], 536.2487)
  expect_equal(model_result[["im_with_photoinhibition"]], 1420)
  expect_equal(model_result[["w"]], NA_real_)
  expect_equal(model_result[["ib"]], NA_real_)
  expect_equal(model_result[["etrmax_without_with_ratio"]], 1.08078520)
  expect_equal(model_result[["saturation"]], FALSE)
})

test_that("test-vollenweider_etr_I generate regression modified 20240925.csv", {
  test_data_file <- testthat::test_path("data", "dual_pam_data", "20240925.csv")
  data <- read_dual_pam_data(test_data_file)
  model_result <- vollenweider_generate_regression_ETR_I(data)
  expect_no_error(validate_model_result(model_result))

  model_result <- vollenweider_modified(model_result)
  expect_no_error(validate_modified_model_result(model_result))
})

test_that("test-vollenweider_etr_I modified control plot 20240925.csv", {
  test_data_file <- testthat::test_path("data", "dual_pam_data", "20240925.csv")
  data <- read_dual_pam_data(test_data_file)
  model_result <- vollenweider_generate_regression_ETR_I(data)
  model_result <- vollenweider_modified(model_result)

  plot <- plot_control(
    data,
    model_result,
    "vollenweider ETR I modified 20240925.csv",
    color_vollenweider
  )
  expect_s3_class(plot, "ggplot")
  expect_gt(length(plot$layers), 0)

  out <- file.path("results", "test-vollenweider_etr_I modified control plot 20240925.jpg")
  ggplot2::ggsave(out, create.dir = TRUE, plot = plot, units = "px", width = 1000, height = 1000, dpi = 100, limitsize = FALSE)
  expect_true(file.exists(out))
})