tests/testthat/test_filter.R

In neotoma2: Working with the Neotoma Paleoecology Database

test_that("filter runs as expected. filters datasettype", {

  ## we don't want this to run on CRAN
  skip_on_cran()
  brazil <- '{"type": "Polygon",
            "coordinates": [[
                [-73.125, -9.102],
                [-56.953, -33.138],
                [-36.563, -7.711],
                [-68.203, 13.923],
                [-73.125, -9.102]
              ]]}'

  brazil_sf <- geojsonsf::geojson_sf(brazil)
  brazil_datasets <- get_datasets(loc = brazil[1])
  brazil_pollen <- neotoma2::filter(brazil_datasets, datasettype == "pollen")
  brazil_summary <- summary(brazil_pollen)
  brazil_datatype <- unique(brazil_summary$types)

  expect_equal(brazil_datatype, "pollen")

})

test_that("filter works as expected. filter by lat.", {

  ## we don't want this to run on CRAN
  skip_on_cran()
  brazil <- '{"type": "Polygon",
            "coordinates": [[
                [-73.125, -9.102],
                [-56.953, -33.138],
                [-36.563, -7.711],
                [-68.203, 13.923],
                [-73.125, -9.102]
              ]]}'

  brazil_sf <- geojsonsf::geojson_sf(brazil)
  brazil_datasets <- get_datasets(loc = brazil[1])
  brazil_lat <- neotoma2::filter(brazil_datasets, lat > 0 & lat < 50)
  ds.0.50 <- as.data.frame(brazil_lat)
  latitudes <- ds.0.50$lat

  expect_true(all(latitudes < 50))
  expect_true(all(latitudes > 0))
})

test_that("filter works as expected. filter by long.", {

  ## we don't want this to run on CRAN
  skip_on_cran()
  brazil <- '{"type": "Polygon",
            "coordinates": [[
                [-73.125, -9.102],
                [-56.953, -33.138],
                [-36.563, -7.711],
                [-68.203, 13.923],
                [-73.125, -9.102]
              ]]}'

  brazil_sf <- geojsonsf::geojson_sf(brazil)

  brazil_datasets <- get_datasets(loc = brazil[1])

  # These bounds are beyond the range of the Brazil polygon.
  brazil_long <- neotoma2::filter(brazil_datasets, long > 0 & long < 50)

  expect_length(brazil_long, 0)

})

test_that("filter works as expected. filter by multiple arguments", {

  ## we don't want this to run on CRAN
  skip_on_cran()
  brazil <- '{"type": "Polygon",
            "coordinates": [[
                [-73.125, -9.102],
                [-56.953, -33.138],
                [-36.563, -7.711],
                [-68.203, 13.923],
                [-73.125, -9.102]
              ]]}'

  brazil_sf <- geojsonsf::geojson_sf(brazil)

  brazil_datasets <- get_datasets(loc = brazil[1])

  brazil <- neotoma2::filter(brazil_datasets,
                             datasettype == "pollen" &
                             long > -60 & long < -40 &
                             lat > -20 & lat < 0)

  df <- as.data.frame(brazil)
  longitudes <- df$long
  latitudes <- df$lat

  expect_true(all(longitudes < -40))
  expect_true(all(longitudes > -60))
  expect_true(all(latitudes > -20))
  expect_true(all(longitudes < 0))

  dst <- datasets(brazil) %>% as.data.frame() %>% select(datasettype)

  expect_true(all(dst == "pollen"))

})

test_that("filter runs as expected. filters 2 datasettypes", {

  ## we don't want this to run on CRAN
  skip_on_cran()
  brazil <- '{"type": "Polygon",
            "coordinates": [[
                [-73.125, -9.102],
                [-56.953, -33.138],
                [-36.563, -7.711],
                [-68.203, 13.923],
                [-73.125, -9.102]
              ]]}'

  brazil_sf <- geojsonsf::geojson_sf(brazil)

  brazil_datasets <- get_datasets(loc = brazil) %>%
    neotoma2::filter(datasettype == "pollen" | datasettype == "charcoal")

  dst <- datasets(brazil_datasets) %>%
    as.data.frame() %>%
    select(datasettype) %>%
    unlist()

  expect_true(all(dst %in% c("pollen", "charcoal")))
})


test_that("filter on datasettype runs as expected. count unique sites", {

  ## we don't want this to run on CRAN
  skip_on_cran()
  brazil <- '{"type": "Polygon",
            "coordinates": [[
                [-73.125, -9.102],
                [-56.953, -33.138],
                [-36.563, -7.711],
                [-68.203, 13.923],
                [-73.125, -9.102]
              ]]}'

  brazil_datasets <- get_datasets(loc = brazil) %>%
    neotoma2::filter(datasettype == "pollen" | datasettype == "charcoal")

  brazil_ids <- getids(brazil_datasets) %>%
    select(siteid) %>%
    unlist() %>%
    unique()

  brazil_length <- length(brazil_datasets)

  expect_equal(length(brazil_ids), brazil_length)
  expect_lte(brazil_length, nrow(summary(brazil_datasets)))

})

test_that("filter on lat runs as expected. count unique sites", {

  ## we don't want this to run on CRAN
  skip_on_cran()
  brazil <- '{"type": "Polygon",
            "coordinates": [[
                [-73.125, -9.102],
                [-56.953, -33.138],
                [-36.563, -7.711],
                [-68.203, 13.923],
                [-73.125, -9.102]
              ]]}'

  brazil_sf <- geojsonsf::geojson_sf(brazil)

  brazil_datasets <- get_datasets(loc = brazil_sf[1])

  brasil_space <- brazil_datasets %>% neotoma2::filter(lat > -18 & lat < -16)

  brazil_ids <- length(unique(getids(brasil_space)$siteid))
  brazil_length <- length(brasil_space)

  expect_equal(brazil_ids, brazil_length)

})

test_that("filtering by collunitid removes samples", {

  ## we don't want this to run on CRAN
  skip_on_cran()
  meer <- get_sites(sitename = "meerfeld%") %>%
    get_downloads()

  meerDS42510 <- meer %>%
    neotoma2::filter(collunitid == 29576) %>%
    samples()

  expect_true(all(meerDS42510$collectionunitid == 29576))

})

test_that("filtering by datasetid keeps all other collection units
          where the dataset does not belong", {

  ## we don't want this to run on CRAN
  skip_on_cran()
  meer <- get_sites(sitename = "meerfeld%") %>%
    get_downloads()

  meerDS42510 <- meer %>%
    neotoma2::filter(datasetid == 42510)

  meerId <-  as.data.frame(collunits(meerDS42510))$collectionunitid

  expect_equal(meerId, 29576)

})


 test_that("filter works regardless of before/after get_downloads", {
  skip_on_cran()
  core_sites <- c(13949, 11904, 13319, 728, 13248, 2625, 2806,
    13280, 519, 11745, 273, 13956,
    11880, 13321, 9801, 13698, 11816,
    13909, 13921)

  core_wc_dl_f <- get_sites(core_sites) %>%
    get_datasets() %>%
    get_downloads() %>%
    neotoma2::filter(datasettype == "water chemistry")

  core_wc_f_dl <- get_sites(core_sites) %>%
    get_datasets() %>%
    neotoma2::filter(datasettype == "water chemistry") %>%
    get_downloads()

  core_dl_f_ids <- getids(core_wc_dl_f)
  core_f_dl_ids <- getids(core_wc_f_dl)

  expect_setequal(core_dl_f_ids$siteid, core_f_dl_ids$siteid)
  expect_setequal(core_dl_f_ids$collunitid, core_f_dl_ids$collunitid)
  expect_setequal(core_dl_f_ids$datasetid, core_f_dl_ids$datasetid)

 })