tests/testthat/test-general-qc.R

In nationalparkservice/mojn-ds-rpackage: Desert Springs Protocol R Package

context("Completeness")
LoadDesertSprings(dir)


test_that("qcCompleteness works as expected", {
  
  actual_rows <- nrow(qcCompleteness(field.season = c("2016", "2017", "2018", "2019", "2020", "2021", "2022")))
  expect_equal(actual_rows, 57)
  
  actual_cols <- colnames(qcCompleteness())
  expected_cols <- c("Park", "FieldSeason", "SampleFrame", "MonitoringStatus", "Count", "Percent")
  expect_equal(actual_cols, expected_cols)
  
  actual_int <- qcCompleteness()
  expect_equal(class(actual_int$Count), "integer")
  
  actual_dbl <- qcCompleteness()
  expect_equal(typeof(actual_dbl$Percent), "double")
  
  actual_count <- (qcCompleteness() %>% dplyr::filter(Park == "DEVA", FieldSeason == "2018", SampleFrame == "3Yr", MonitoringStatus == "Sampled") %>% dplyr::select(Count))[1,]
  expected_count <- tibble::as_tibble(as.integer(59)) %>% dplyr::rename(Count = value)
  expect_equal(actual_count, expected_count)
  
  actual_percent <- (qcCompleteness() %>% dplyr::filter(Park == "DEVA", FieldSeason == "2018", SampleFrame == "3Yr", MonitoringStatus == "Sampled") %>% dplyr::select(Percent))[1,]
  expected_percent <- tibble::as_tibble(as.double(59*100/60)) %>% dplyr::rename(Percent = value)
  expect_equal(actual_count, expected_count)
  
})


test_that("qcDPLCheck returns correct number of rows and columns", {

  actual_rows <- nrow(qcDPLCheck() %>% dplyr::filter(FieldSeason == "2018"))
  expect_equal(actual_rows, 120)
  
  actual_cols <- colnames(qcDPLCheck())
  expected_cols <- c("Park", "SiteCode", "SiteName", "VisitDate", "FieldSeason", "SampleFrame", "VisitType", "Visit", "FlowCondition", "EstimatedDischarge", "VolumetricDischarge", "Disturbance", "FlowModification", "Wildlife", "Riparian", "Invasives", "Temperature", "pH", "SpCond", "DisOxygen")
  expect_equal(actual_cols, expected_cols)
    
})


test_that("qcSpringTypeDiscrepancies returns correct number of rows and columns", {

  actual_rows <- nrow(qcSpringTypeDiscrepancies(field.season = c("2016", "2017", "2018", "2019", "2020", "2021", "2022")))
  expect_equal(actual_rows, 81)
  
  actual_cols <- colnames(qcSpringTypeDiscrepancies())
  expected_cols <- c("Park", "SiteCode", "SiteName", "SpringType", "FieldSeasons")
  expect_equal(actual_cols, expected_cols)
    
})


test_that("qcVisitsBySite works as expected", {
  
  actual_rows <- nrow(qcVisitsBySite(field.season = c("2016", "2017", "2018", "2019", "2020", "2021", "2022")))
  expect_equal(actual_rows, 249)
  
  actual_cols <- colnames(qcVisitsBySite())
  expected_cols <- c("Park", "SiteCode", "SiteName", "SampleFrame", "VisitDates")
  expect_equal(actual_cols, expected_cols)
  
  actual_character <- qcVisitsBySite()
  expect_equal(class(actual_character$VisitDates), "character")
  
  actual_dates <- qcVisitsBySite() %>% dplyr::filter(SiteCode == "LAKE_P_HOR0042") %>% dplyr::select(VisitDates)
  expected_dates <- tibble::as_tibble(as.character("Oct 24 (2022), Oct 25 (2021), Oct 27 (2020), Oct 30 (2023), Nov 1 (2017), Nov 4 (2019), Nov 27 (2018), Apr 5 (2016)")) %>% dplyr::rename(VisitDates = value)
  expect_equal(actual_dates, expected_dates)
  
})


test_that("qcVisitsByDate works as expected", {
  
  actual_rows <- nrow(qcVisitsByDate(field.season = c("2016", "2017", "2018", "2019", "2020", "2021", "2022")))
  expect_equal(actual_rows, 156)
  
  actual_cols <- colnames(qcVisitsByDate())
  expected_cols <- c("Date", "WY2023", "WY2022", "WY2021", "WY2020", "WY2019", "WY2018", "WY2017", "WY2016")
  expect_equal(actual_cols, expected_cols)
  
  actual_character <- qcVisitsByDate()
  expect_equal(class(actual_character$Date), "character")
  expect_equal(class(actual_character$WY2021), "character")
  expect_equal(class(actual_character$WY2019), "character")
  
  actual_sites <- qcVisitsByDate() %>% dplyr::filter(Date == "Nov 1")
  expected_sites <- tibble::as_tibble_row(c(Date = "Nov 1",
                                            WY2023 = NA_character_,
                                            WY2022 = "DEVA_P_SIS0800, DEVA_P_BOT0781",
                                            WY2021 = "DEVA_P_JAC0189",
                                            WY2020 = NA_character_,
                                            WY2019 = NA_character_,
                                            WY2018 = NA_character_,
                                            WY2017 = "LAKE_P_HOR0042, LAKE_P_SUG0011",
                                            WY2016 = NA_character_))
  expect_equal(actual_sites, expected_sites)
  
})


test_that("qcNotSampled returns correct number of rows and columns", {
  
  actual_rows <- nrow(qcNotSampled(field.season = c("2016", "2017", "2018", "2019", "2020", "2021", "2022")))
  expect_equal(actual_rows, 82)
  
  actual_cols <- colnames(qcNotSampled())
  expected_cols <- c("Park", "SiteCode", "SiteName", "FieldSeason", "SampleFrame")
  expect_equal(actual_cols, expected_cols)
  
})


test_that("qcRepeatVisits returns correct number of rows and columns", {
  
  actual_rows <- nrow(qcRepeatVisits(field.season = c("2016", "2017", "2018", "2019", "2020", "2021", "2022")))
  expect_equal(actual_rows, 12)
  
  actual_cols <- colnames(qcRepeatVisits())
  expected_cols <- c("Park", "SiteCode", "SiteName", "VisitDate", "FieldSeason", "SampleFrame", "VisitType", "MonitoringStatus", "Notes")
  expect_equal(actual_cols, expected_cols)
  
  actual_date <- qcRepeatVisits()
  expect_equal(class(actual_date$VisitDate), "Date")
  
})