# MixtComp version 4 - july 2019
# Copyright (C) Inria - Université de Lille - CNRS

# This program is free software: you can redistribute it and/or modify
# it under the terms of the GNU Affero General Public License as
# published by the Free Software Foundation, either version 3 of the
# License, or (at your option) any later version.
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
# GNU Affero General Public License for more details.
#
# You should have received a copy of the GNU Affero General Public License
# along with this program.  If not, see <https://www.gnu.org/licenses/>


# @author Quentin Grimonprez
context("Misc functions")


test_that("reduceRMixtCompOutput works in FALSE FALSE", {
  res <- list(variable = list(
    type = list(
      z_class = "LatentClass",
      var1 = "Gaussian",
      var2 = "Multinomial",
      var3 = "Poisson",
      var4 = "NegativeBinomial",
      var5 = "Weibull",
      var6 = "Rank_ISR",
      var7 = "Func_SharedAlpha_CS",
      var8 = "Func_CS"
    ),
    param = list(
      z_class = list(stat = 1, log = 1),
      var1 = list(stat = 1, log = 1),
      var2 = list(stat = 1, log = 1),
      var3 = list(stat = 1, log = 1),
      var4 = list(stat = 1, log = 1),
      var5 = list(stat = 1, log = 1),
      var6 = list(
        mu = list(stat = 1, log = 1),
        pi = list(stat = 1, log = 1)
      ),
      var7 = list(
        alpha = list(stat = 1, log = 1),
        beta = list(stat = 1, log = 1),
        sd = list(stat = 1, log = 1)
      ),
      var8 = list(
        alpha = list(stat = 1, log = 1),
        beta = list(stat = 1, log = 1),
        sd = list(stat = 1, log = 1)
      )
    ),
    data = list(
      z_class = list(completed = 1:10),
      var1 = list(completed = 1:10, a = 1),
      var2 = list(time = 1:10, data = 1, a = 1)
    )
  ))

  class(res) <- "MixtComp"


  resOut <- reduceRMixtCompOutput(res, completed = FALSE, log = FALSE)

  expect_equal(resOut, res)


  res2 <- list(variable = res$variable, nClass = 2:3, res = list(NULL, res, res))
  class(res2) <- "MixtCompLearn"

  resOut <- reduceRMixtCompOutput(res2, completed = FALSE, log = FALSE)

  expect_equal(resOut, res2)
})



test_that("reduceRMixtCompOutput works in TRUE TRUE", {
  res <- list(variable = list(
    type = list(
      z_class = "LatentClass",
      var1 = "Gaussian",
      var2 = "Multinomial",
      var3 = "Poisson",
      var4 = "NegativeBinomial",
      var5 = "Weibull",
      var6 = "Rank_ISR",
      var7 = "Func_SharedAlpha_CS",
      var8 = "Func_CS"
    ),
    param = list(
      z_class = list(stat = 1, log = 1),
      var1 = list(stat = 1, log = 1),
      var2 = list(stat = 1, log = 1),
      var3 = list(stat = 1, log = 1),
      var4 = list(stat = 1, log = 1),
      var5 = list(stat = 1, log = 1),
      var6 = list(
        mu = list(stat = 1, log = 1),
        pi = list(stat = 1, log = 1)
      ),
      var7 = list(
        alpha = list(stat = 1, log = 1),
        beta = list(stat = 1, log = 1),
        sd = list(stat = 1, log = 1)
      ),
      var8 = list(
        alpha = list(stat = 1, log = 1),
        beta = list(stat = 1, log = 1),
        sd = list(stat = 1, log = 1)
      )
    ),
    data = list(
      z_class = list(completed = 1:10),
      var1 = list(completed = 1:10, a = 1),
      var2 = list(time = 1:10, data = 1, a = 1)
    )
  ))

  class(res) <- "MixtComp"

  expectedRes <- list(variable = list(
    type = list(
      z_class = "LatentClass",
      var1 = "Gaussian",
      var2 = "Multinomial",
      var3 = "Poisson",
      var4 = "NegativeBinomial",
      var5 = "Weibull",
      var6 = "Rank_ISR",
      var7 = "Func_SharedAlpha_CS",
      var8 = "Func_CS"
    ),
    param = list(
      z_class = list(stat = 1),
      var1 = list(stat = 1),
      var2 = list(stat = 1),
      var3 = list(stat = 1),
      var4 = list(stat = 1),
      var5 = list(stat = 1),
      var6 = list(
        mu = list(stat = 1),
        pi = list(stat = 1)
      ),
      var7 = list(
        alpha = list(stat = 1),
        beta = list(stat = 1),
        sd = list(stat = 1)
      ),
      var8 = list(
        alpha = list(stat = 1),
        beta = list(stat = 1),
        sd = list(stat = 1)
      )
    ),
    data = list(
      z_class = list(completed = 1:10),
      var1 = list(a = 1),
      var2 = list(a = 1)
    )
  ))

  class(expectedRes) <- "MixtComp"

  resOut <- reduceRMixtCompOutput(res, completed = TRUE, log = TRUE)

  expect_equal(resOut, expectedRes)


  res2 <- list(variable = res$variable, nClass = 2:3, res = list(NULL, res, res))
  class(res2) <- "MixtCompLearn"

  expectedRes2 <- list(variable = expectedRes$variable, nClass = 2:3, res = list(NULL, expectedRes, expectedRes))
  resOut <- reduceRMixtCompOutput(res2, completed = TRUE, log = TRUE)

  expect_equivalent(resOut, expectedRes2)
})

test_that("reduceRMixtCompOutput works in TRUE FALSE", {
  res <- list(variable = list(
    type = list(
      z_class = "LatentClass",
      var1 = "Gaussian",
      var2 = "Multinomial",
      var3 = "Poisson",
      var4 = "NegativeBinomial",
      var5 = "Weibull",
      var6 = "Rank_ISR",
      var7 = "Func_SharedAlpha_CS",
      var8 = "Func_CS"
    ),
    param = list(
      z_class = list(stat = 1, log = 1),
      var1 = list(stat = 1, log = 1),
      var2 = list(stat = 1, log = 1),
      var3 = list(stat = 1, log = 1),
      var4 = list(stat = 1, log = 1),
      var5 = list(stat = 1, log = 1),
      var6 = list(
        mu = list(stat = 1, log = 1),
        pi = list(stat = 1, log = 1)
      ),
      var7 = list(
        alpha = list(stat = 1, log = 1),
        beta = list(stat = 1, log = 1),
        sd = list(stat = 1, log = 1)
      ),
      var8 = list(
        alpha = list(stat = 1, log = 1),
        beta = list(stat = 1, log = 1),
        sd = list(stat = 1, log = 1)
      )
    ),
    data = list(
      z_class = list(completed = 1:10),
      var1 = list(completed = 1:10, a = 1),
      var2 = list(time = 1:10, data = 1, a = 1)
    )
  ))

  class(res) <- "MixtComp"

  expectedRes <- list(variable = list(
    type = list(
      z_class = "LatentClass",
      var1 = "Gaussian",
      var2 = "Multinomial",
      var3 = "Poisson",
      var4 = "NegativeBinomial",
      var5 = "Weibull",
      var6 = "Rank_ISR",
      var7 = "Func_SharedAlpha_CS",
      var8 = "Func_CS"
    ),
    param = list(
      z_class = list(stat = 1, log = 1),
      var1 = list(stat = 1, log = 1),
      var2 = list(stat = 1, log = 1),
      var3 = list(stat = 1, log = 1),
      var4 = list(stat = 1, log = 1),
      var5 = list(stat = 1, log = 1),
      var6 = list(
        mu = list(stat = 1, log = 1),
        pi = list(stat = 1, log = 1)
      ),
      var7 = list(
        alpha = list(stat = 1, log = 1),
        beta = list(stat = 1, log = 1),
        sd = list(stat = 1, log = 1)
      ),
      var8 = list(
        alpha = list(stat = 1, log = 1),
        beta = list(stat = 1, log = 1),
        sd = list(stat = 1, log = 1)
      )
    ),
    data = list(
      z_class = list(completed = 1:10),
      var1 = list(a = 1),
      var2 = list(a = 1)
    )
  ))

  class(expectedRes) <- "MixtComp"

  resOut <- reduceRMixtCompOutput(res, completed = TRUE, log = FALSE)

  expect_equal(resOut, expectedRes)


  res2 <- list(variable = res$variable, nClass = 2:3, res = list(NULL, res, res))
  class(res2) <- "MixtCompLearn"

  expectedRes2 <- list(variable = expectedRes$variable, nClass = 2:3, res = list(NULL, expectedRes, expectedRes))
  resOut <- reduceRMixtCompOutput(res2, completed = TRUE, log = FALSE)

  expect_equivalent(resOut, expectedRes2)
})




test_that("reduceRMixtCompOutput works in FALSE TRUE", {
  res <- list(variable = list(
    type = list(
      z_class = "LatentClass",
      var1 = "Gaussian",
      var2 = "Multinomial",
      var3 = "Poisson",
      var4 = "NegativeBinomial",
      var5 = "Weibull",
      var6 = "Rank_ISR",
      var7 = "Func_SharedAlpha_CS",
      var8 = "Func_CS"
    ),
    param = list(
      z_class = list(stat = 1, log = 1),
      var1 = list(stat = 1, log = 1),
      var2 = list(stat = 1, log = 1),
      var3 = list(stat = 1, log = 1),
      var4 = list(stat = 1, log = 1),
      var5 = list(stat = 1, log = 1),
      var6 = list(
        mu = list(stat = 1, log = 1),
        pi = list(stat = 1, log = 1)
      ),
      var7 = list(
        alpha = list(stat = 1, log = 1),
        beta = list(stat = 1, log = 1),
        sd = list(stat = 1, log = 1)
      ),
      var8 = list(
        alpha = list(stat = 1, log = 1),
        beta = list(stat = 1, log = 1),
        sd = list(stat = 1, log = 1)
      )
    ),
    data = list(
      z_class = list(completed = 1:10),
      var1 = list(completed = 1:10, a = 1),
      var2 = list(time = 1:10, data = 1, a = 1)
    )
  ))

  class(res) <- "MixtComp"

  expectedRes <- list(variable = list(
    type = list(
      z_class = "LatentClass",
      var1 = "Gaussian",
      var2 = "Multinomial",
      var3 = "Poisson",
      var4 = "NegativeBinomial",
      var5 = "Weibull",
      var6 = "Rank_ISR",
      var7 = "Func_SharedAlpha_CS",
      var8 = "Func_CS"
    ),
    param = list(
      z_class = list(stat = 1),
      var1 = list(stat = 1),
      var2 = list(stat = 1),
      var3 = list(stat = 1),
      var4 = list(stat = 1),
      var5 = list(stat = 1),
      var6 = list(
        mu = list(stat = 1),
        pi = list(stat = 1)
      ),
      var7 = list(
        alpha = list(stat = 1),
        beta = list(stat = 1),
        sd = list(stat = 1)
      ),
      var8 = list(
        alpha = list(stat = 1),
        beta = list(stat = 1),
        sd = list(stat = 1)
      )
    ),
    data = list(
      z_class = list(completed = 1:10),
      var1 = list(completed = 1:10, a = 1),
      var2 = list(time = 1:10, data = 1, a = 1)
    )
  ))

  class(expectedRes) <- "MixtComp"

  resOut <- reduceRMixtCompOutput(res, completed = FALSE, log = TRUE)

  expect_equal(resOut, expectedRes)


  res2 <- list(variable = res$variable, nClass = 2:3, res = list(NULL, res, res))
  class(res2) <- "MixtCompLearn"

  expectedRes2 <- list(variable = expectedRes$variable, nClass = 2:3, res = list(NULL, expectedRes, expectedRes))
  resOut <- reduceRMixtCompOutput(res2, completed = FALSE, log = TRUE)

  expect_equivalent(resOut, expectedRes2)
})


test_that("computeDiscrimPowerVar works", {
  output <- list(mixture = list(
    IDClass = matrix(1:10, nrow = 2),
    IDClassBar = matrix(1:10, nrow = 2)[2:1, ]
  ))

  out <- computeDiscrimPowerVar(output)
  expect_equal(out, c(-2, -6, -10, -14, -18))

  out <- computeDiscrimPowerVar(output, 1)
  expect_equal(out, 1 - output$mixture$IDClass[1, ] - output$mixture$IDClass[2, ])

  expect_error(out <- computeDiscrimPowerVar(output, 10))
})