require(testthat)
context("read ESDFL")
options(width = 500)
options(useFancyQuotes = FALSE)
source("REF-2-esdfl.R") # has REF output in it

# ideally this wouldn't trip up any of the scope fixes below
dsex <- "should not be used"

test_that("read ESDFL", {
  sdf <<- readNAEP(system.file("extdata/data", "M36NT2PM.dat", package = "NAEPprimer"))
  sdfA <<- subset(sdf, scrpsu %in% c(5, 45, 56))
  sdfB <- subset(sdf, scrpsu %in% c(75, 76, 78))
  sdfC <- subset(sdf, scrpsu %in% 100:200)
  sdfD <<- subset(sdf, scrpsu %in% 201:300)

  sdfB$year <- 2002
  sdfC$year <- 2003

  sdfB <<- sdfB
  sdfC <<- sdfC
  # construct an edsurvey.data.frame.list from these four data sets
  sdfl <<- edsurvey.data.frame.list(list(sdfA, sdfB, sdfC, sdfD),
    labels = c(
      "A locations",
      "B locations",
      "C locations",
      "D locations"
    )
  )
  expect_is(sdfl, "edsurvey.data.frame.list")
})


# for subset test
i <- "invalid level: outside"
context("ESDFL subset and scope")
test_that("ESDFL subset and scope", {
  yes <- "Yes"
  g1 <- subset(sdfl, ell3 == "Yes")
  g2 <- subset(sdfl, ell3 == yes)
  expect_equal(dim(g1), dim(g2))
  i <- "invalid level: inside"
  ssfun <- function(data) {
    i <- "Yes"
    subset(data, ell3 == i)
  }
  g3 <- ssfun(sdfl)
  expect_equal(dim(g1), dim(g3))
})


context("ESDFL achievementLevels")
test_that("ESDFL achievementLevels", {
  expect_known_value(test8 <- achievementLevels(data = sdfl), file = "aLevels_test8.rds", update = FALSE)
})

context("ESDFL cor")
test_that("ESDFL cor", {
  skip_on_cran()
  c1 <- cor.sdf("b017451", "b003501", sdfA,
    method = "Pearson",
    weightVar = "origwt"
  )
  c3 <- cor.sdf("b017451", "b003501", sdfC,
    method = "Pearson",
    weightVar = "origwt"
  )
  c1234 <- cor.sdf("b017451", "b003501", sdfl,
    method = "Pearson",
    weightVar = "origwt"
  )
  expect_equal(c1, c1234[[1]])
  expect_equal(c3, c1234[[3]])
})
skip_on_cran()

context("ESDFL edsurveyTable")
test_that("ESDFL edsurveyTable", {
  skip_on_cran()
  et1 <- edsurveyTable(composite ~ b017451 + dsex, sdfl)
  et1c <- withr::with_options(list(digits = 7), capture.output(et1))
  expect_equal(et1c, et1REF)

  etB <- edsurveyTable(composite ~ b017451 + dsex, sdfB)
  # row names will not agree, homogenize them
  row.names(et1$data) <- paste(rep(LETTERS[1:4], each = nrow(etB$data)), rep(1:nrow(etB$data), 4))
  row.names(etB$data) <- paste("B", 1:nrow(etB$data))
  # remove "labels" because it is only on the edsurveyTableList
  ss <- subset(et1$data, labels == "B locations")[, 2:ncol(et1$data)]
  for (i in 1:ncol(ss)) {
    mostattributes(ss[, i]) <- attributes(et1$data[, i + 1])
  }
  coetB <- withr::with_options(list(digits = 7), capture.output(etB$data))
  coss <- withr::with_options(list(digits = 7), capture.output(ss))
  expect_equal(coetB, coss)
})

context("ESDFL edsurveyTable error handling")
test_that("ESDFL error handling", {
  skip_on_cran()
  expect_warning(
    edsurveyTable(composite ~ b017451, sdfl,
      returnMeans = TRUE, returnSepct = FALSE,
      pctAggregationLevel = 6
    ),
    paste0("Warnings from datasets \"A locations\"")
  )
  sdfE <- "String"
  sdfl_error <- edsurvey.data.frame.list(list(sdfE, sdfB, sdfC, sdfE),
    labels = c(
      "first E locations",
      "B locations",
      "C locations",
      "second E locations"
    )
  )
  expect_warning(
    edsurveyTable(composite ~ b017451,
      sdfl_error,
      returnMeans = FALSE,
      returnSepct = FALSE
    ),
    "E locations"
  )

  suppressWarnings(et2 <- edsurveyTable(composite ~ b017451, sdfl_error, returnMeans = FALSE, returnSepct = FALSE))
  withr::with_options(
    list(digits = 1),
    et2c <- capture.output(et2)
  )

  expect_message(expect_error(g1 <- gap("composite", sdfl_error, groupA = dsex == "Male"), "reference"), "E locations")
  sdfl_errorB <- edsurvey.data.frame.list(list(sdfA, sdfB, sdfE, sdfC),
    labels = c(
      "A locations",
      "B locations",
      "E locations",
      "C locations"
    )
  )
  expect_message(
    g2 <- gap("composite", sdfl_errorB, groupA = dsex == "Male"),
    "An error occurred while working on a dataset \"E locations\". The results from that dataset will be excluded. Error message:"
  )
  g3 <- gap("composite", sdfl, groupA = dsex == "Male")
  expect_equivalent(g2$results[2, ], g3$results[2, ])
  expect_equal(et2c, et2REF)
})

context("ESDFL gap")
test_that("ESDFL gap", {
  skip_on_cran()
  g1 <- gap("composite", sdfl, dsex == "Male", dsex == "Female", returnSimpleDoF = TRUE)
  mle <- "Male"
  g1p <- gap("composite", sdfl, dsex == mle, dsex == "Female", returnSimpleDoF = TRUE)
  expect_equal(g1$results, g1p$results)
  # check that the columns output for just one agree between esdfl and sdf
  g2 <- gap("composite", sdfC, dsex == "Male", dsex == "Female", returnSimpleDoF = TRUE)
  mnames <- names(g2$results)
  mnames <- mnames[mnames %in% names(g1$results)]
  expect_equal(unlist(g2$results[mnames]), unlist(g1$results[3, mnames]))
  # also check that the overall output has not changed.targetLevel="Male"
  expect_known_value(g1, "gap_esdfl_mean.rds", update = FALSE)
  # percentile
  expect_known_value(g_pct <- gap("composite", sdfl, dsex == "Male", percentiles = c(2, 50), pctMethod = "symmetric"), "gap_esdfl_pct.rds", update = FALSE)
  # achievement level
  expect_known_value(g_al <- gap("composite", sdfl, dsex == "Male", achievementLevel = "Proficient"), "gap_esdfl_al.rds", update = FALSE)
  # percent
  expect_known_value(g_per <- gap("dsex", sdfl, dsex == "Male", targetLevel = "Male"), "gap_esdfl_perct.rds", update = FALSE)
})

context("ESDFL helper functions")
test_that("ESDFL helper functions", {
  skip_on_cran()
  d1 <- dim(sdfl)
  expect_equal(d1$nrow[1], nrow(sdfA))
  expect_equal(d1$ncol[3], ncol(sdfC))
  pv1 <- getPlausibleValue("composite", sdfl)
  expect_equal(pv1[[2]], getPlausibleValue("composite", sdfB))
  wr1 <- getWeightJkReplicates("origwt", sdfl)
  expect_equal(wr1[[4]], getWeightJkReplicates("origwt", sdfD))
  hpv1 <- hasPlausibleValue("algebra", sdfl)
  expect_equal(hpv1[[1]], hasPlausibleValue("algebra", sdfA))
  hpv2 <- hasPlausibleValue("dsex", sdfl)
  expect_equal(hpv2[[2]], hasPlausibleValue("dsex", sdfB))
  iw1 <- isWeight("origwt", sdfl)
  expect_equal(iw1[[3]], TRUE)
  iw2 <- isWeight("composite", sdfl)
  expect_equal(iw2[[4]], FALSE)
  l1 <- levelsSDF("sdracem", sdfl)
  expect_equal(l1[[1]], levelsSDF("sdracem", sdfA))
  l2 <- levelsSDF("dsex", sdfl)
  expect_equal(l2[[2]], levelsSDF("dsex", sdfB))
  n1 <- colnames(sdfl)
  expect_equal(n1[[3]], colnames(sdfC))
  spvo1 <- capture.output(showPlausibleValues(sdfl))
  spvoD <- capture.output(showPlausibleValues(sdfD))
  expect_equal(rev(spvo1)[1:length(spvoD)], rev(spvoD))
  sw1 <- capture.output(showWeights(sdfl, verbose = TRUE))
  swA <- capture.output(showWeights(sdfA, verbose = TRUE))
  swB <- capture.output(showWeights(sdfB, verbose = TRUE))
  swC <- capture.output(showWeights(sdfC, verbose = TRUE))
  swD <- capture.output(showWeights(sdfD, verbose = TRUE))
  expect_equal(sw1, c(swA, swB, swC, swD))
})


context("ESDFL cor")
test_that("ESDFL cor", {
  skip_on_cran()
  c1 <- cor.sdf("b017451", "b003501", sdfA,
    method = "Pearson",
    weightVar = "origwt"
  )
  c3 <- cor.sdf("b017451", "b003501", sdfC,
    method = "Pearson",
    weightVar = "origwt"
  )
  c1234 <- cor.sdf("b017451", "b003501", sdfl,
    method = "Pearson",
    weightVar = "origwt"
  )
  expect_equal(c1, c1234[[1]])
  expect_equal(c3, c1234[[3]])
})


context("ESDFL subset and print")
test_that("ESDFL subset and print", {
  skip_on_cran()
  sdfl2 <- subset(sdfl, dsex == "Male")
  expect_equal(capture.output(print(sdfl2)), printREF)
  d1 <- dim(sdfl2)
  expect_equal(d1$nrow[1], nrow(subset(sdfA, dsex == "Male")))
  expect_equal(d1$ncol[3], ncol(subset(sdfC, dsex == "Female")))

  # inside = TRUE
  expect_equal(d1, dim(subset(sdfl, eval("dsex == \"Male\""), inside = TRUE)))

  # expected message and error
  expect_warning(sdfl_e <- subset(sdfl, dsex1 == "Male"))
  expect_equal(sdfl_e, NULL)

  sdfE <- "String"
  sdfl_error <- edsurvey.data.frame.list(list(sdfE, sdfB, sdfC, sdfE),
    labels = c(
      "first E locations",
      "B locations",
      "C locations",
      "second E locations"
    )
  )
  sdfl_ref <- subset(edsurvey.data.frame.list(list(sdfB, sdfC), labels = c("B locations", "C locations")), dsex == "Male")
  expect_warning(sdfl_error_subset <- subset(sdfl_error, dsex == "Male"))
  expect_equal(dim(sdfl_error_subset), dim(sdfl_ref))
  expect_equal(sdfl_error_subset$covs, sdfl_ref$covs)
})


context("ESDFL lm.sdf")
test_that("ESDFL lm.sdf", {
  skip_on_cran()
  # jrrIMax is required to make sure U isn't singular
  et1 <- lm.sdf(composite ~ b017451 + dsex, sdfl, jrrIMax = Inf)
  # lm maps to lm.sdf when data is an edsurvey.data.frame.list
  # et1b <- lm.sdf(composite ~ b017451 + dsex, sdfl)
  # expect_equal(et1, et1b)
  et1D <- lm.sdf(composite ~ b017451 + dsex, sdfD, jrrIMax = Inf)
  # summary output should be the same
  et1s <- capture.output(summary(et1))
  et1Ds <- capture.output(summary(et1D))
  expect_equal(rev(et1s)[1:length(et1Ds)], rev(et1Ds))
  # check coefs are equal
  expect_equal(coef(et1)[, 4], coef(et1D))
  # check print results
  et1p <- capture.output(print(et1))
  et1Dp <- capture.output(print(et1D))
  expect_equal(rev(et1p)[1:2], rev(et1Dp))
})

context("ESDFL percentile")
test_that("ESDFL percentile", {
  skip_on_cran()
  expect_known_value(pct3 <- percentile("composite", 50, sdfl, pctMethod = "unbiased"), "pct3.rds", update = FALSE)
  pct3C <- percentile("composite", 50, sdfC, pctMethod = "unbiased")
  expect_equal(unlist(pct3C[, , drop = TRUE]), unlist(pct3[3, names(pct3C), drop = TRUE]))
})

context("ESDFL same survey")
test_that("ESDFL same survey", {
  skip_on_cran()
  expect_true(!EdSurvey:::sameSurvey(sdfA, sdfB))
  expect_true(EdSurvey:::sameSurvey(sdf, sdfA))
  expect_true(EdSurvey:::sameSurvey(sdfl[[1]][[4]], sdfD))
})

context("ESDFL append")
test_that("ESDFL append", {
  skip_on_cran()
  sdfl1a <- edsurvey.data.frame.list(list(sdfA, sdfB),
    labels = c(
      "A locations",
      "B locations"
    )
  )

  sdfl1b <- edsurvey.data.frame.list(list(sdfC, sdfD),
    labels = c(
      "C locations",
      "D locations"
    )
  )

  sdfl1a_rev <- edsurvey.data.frame.list(list(sdfB, sdfA),
    labels = c(
      "B locations",
      "A locations"
    )
  )

  sdfl1b_rev <- edsurvey.data.frame.list(list(sdfD, sdfC),
    labels = c(
      "D locations",
      "C locations"
    )
  )

  sdfl2 <- edsurvey.data.frame.list(list(sdfA, sdfB, sdfC, sdfD),
    labels = c(
      "A locations",
      "B locations",
      "C locations",
      "D locations"
    )
  )

  sdfl2_rev <- edsurvey.data.frame.list(list(sdfD, sdfC, sdfB, sdfA),
    labels = c(
      "D locations",
      "C locations",
      "B locations",
      "A locations"
    )
  )
  sdfl3 <- append.edsurvey.data.frame.list(
    append.edsurvey.data.frame.list(sdfl1a, sdfC, labelsB = "C locations"),
    sdfD,
    labelsB = "D locations"
  )

  sdfl4 <- append.edsurvey.data.frame.list(sdfl1a, sdfl1b)

  sdfl5 <- append.edsurvey.data.frame.list(sdfl1b_rev, sdfl1a_rev)

  expect_true(identical(sdfl2, sdfl3))
  expect_true(identical(sdfl2, sdfl4))
  expect_true(identical(sdfl2_rev, sdfl5))
})