tests/testthat/test-geoknife_output_parser.R

context("Test output file parsing")



test_that("timeseries parser works on multi feature, single variable", {
  local_file <- system.file('extdata','tsv_multi_feature.tsv', package = 'geoknife')
  output <- parseTimeseries(local_file, delim = '\t', with.units = T)
  expect_is(output, "data.frame")
  expect_true('units' %in% names(output))
  output <- parseTimeseries(local_file, delim = '\t', with.units = F)
  expect_false('units' %in% names(output))
})

test_that("timeseries parser works on linear ring, single variable", {
  local_file <- system.file('extdata','tsv_linear_ring.tsv', package = 'geoknife')
  output <- parseTimeseries(local_file, delim = '\t')
  expect_is(output, "data.frame")
})

test_that("timeseries parser works on linear ring, comma delimited", {
  local_file <- system.file('extdata','csv_linear_ring.csv', package = 'geoknife')
  output <- parseTimeseries(local_file, delim = ',')
  expect_is(output, "data.frame")
  expect_error(parseTimeseries(local_file, delim = '\t'))
})

test_that("timeseries parser works on complex output tsv", {
  local_file <- system.file('extdata','tsv_multi_var_feature_stat.tsv', package = 'geoknife')
  output <- parseTimeseries(local_file, delim = '\t')
  expect_is(output, "data.frame")
  expect_error(parseTimeseries(local_file, delim = ','))
  expect_equal(output$Alabama[output$variable == 'Prcp' & output$statistic == 'MEAN'][6], 25.76490800)
  expect_equal(output$Connecticut[output$variable == 'Prcp' & output$statistic == 'MEAN'][6], 12.5118475)
  expect_equal(output$Alabama[output$variable == 'Tmin' & output$statistic == 'MEAN'][1], 7.776923)
  expect_equal(output$Idaho[output$variable == 'Wind' & output$statistic == 'VARIANCE'][2], 1.8166552)
  expect_equal(output$DateTime[output$variable == 'Wind' & output$statistic == 'VARIANCE'][2], as.POSIXct('1950-01-02 00:00', tz = 'UTC'))
})

test_that("timeseries parser works on complex output csv", {
  local_file <- system.file('extdata','csv_multi_feature_stat.csv', package = 'geoknife')
  output <- parseTimeseries(local_file, delim = ',')
  expect_is(output, "data.frame")
  expect_error(parseTimeseries(local_file, delim = ' '))
})

test_that("timeseries parser works on multi var multi feature", {
  local_file <- system.file('extdata','tsv_multi_feature_var.tsv', package = 'geoknife')
  output <- parseTimeseries(local_file, delim = '\t')
  expect_is(output, "data.frame")
  expect_error(parseTimeseries(local_file, delim = ' '))
})

test_that("timeseries parser works on multi threshold output",{
  local_file <- system.file('extdata','csv_multi_threshold.csv', package = 'geoknife')
  output <- parseTimeseries(local_file, delim = ',')
  expect_is(output, "data.frame")
  expect_equivalent(names(output)[1],'DateTime')
  expect_equivalent(names(output)[length(output)],'threshold(C)')
  expect_equal(output[['threshold(C)']][1],32)
  expect_equivalent(output$variable[1],'MIROC-ESM-CHEM_rcp26_r1i1p1-longest_run_tmax_abv')
})

test_that("timeseries parser works on multi feature w/ second time dimension", {
  local_file <- system.file('extdata','csv_time_dimension_parse.csv', package = 'geoknife')
  output <- parseTimeseries(local_file, delim = ',')
  expect_is(output, "data.frame")
})
USGS-R/geoknife documentation built on April 17, 2023, 8:26 p.m.