context("example post-processing")

expect_ggplot <- function(object, ...) {
  testthat::expect_true(is(object, "ggplot"), ...)
}

expect_loo <- function(object, ...) {
  testthat::expect_true(is(object, "psis_loo"), ...)
}

test_that("fitted() gives correct dimensions", {
  expect_equal(NROW(mvgam:::mvgam_examp_dat$data_train),
               NROW(fitted(mvgam:::mvgam_example1)))

  expect_equal(NROW(mvgam:::mvgam_examp_dat$data_train),
               NROW(fitted(mvgam:::mvgam_example2)))

  expect_equal(NROW(mvgam:::mvgam_examp_dat$data_train),
               NROW(fitted(mvgam:::mvgam_example3)))

  expect_equal(NROW(mvgam:::mvgam_examp_dat$data_train),
               NROW(fitted(mvgam:::mvgam_example4)))
})

test_that("variable extraction works correctly", {
  expect_true(inherits(as.matrix(mvgam:::mvgam_example4,
                                 'A', regex = TRUE),
                       'matrix'))
  expect_true(inherits(as.matrix(mvgam:::mvgam_example4,
                                 'Sigma', regex = TRUE),
                       'matrix'))
  expect_true(inherits(as.matrix(mvgam:::mvgam_example5,
                                 'rho_gp', regex = TRUE),
                       'matrix'))
})

test_that("hindcast() works correctly", {
  hc <- hindcast(mvgam:::mvgam_example1)
  expect_true(inherits(hc$hindcasts, 'list'))
  expect_equal(NROW(mvgam:::mvgam_examp_dat$data_train) /
                 NCOL(mvgam:::mvgam_example1$ytimes),
               NCOL(hc$hindcasts$series_1))

  hc <- hindcast(mvgam:::mvgam_example1, type = 'expected')
  expect_true(inherits(hc$hindcasts, 'list'))
  expect_equal(NROW(mvgam:::mvgam_examp_dat$data_train) /
                 NCOL(mvgam:::mvgam_example1$ytimes),
               NCOL(hc$hindcasts$series_1))

  hc <- hindcast(mvgam:::mvgam_example4)
  expect_true(inherits(hc$hindcasts, 'list'))
  expect_equal(NROW(mvgam:::mvgam_examp_dat$data_train) /
                 NCOL(mvgam:::mvgam_example4$ytimes),
               NCOL(hc$hindcasts$series_1))

  hc <- hindcast(mvgam:::mvgam_example4, type = 'expected')
  expect_true(inherits(hc$hindcasts, 'list'))
  expect_equal(NROW(mvgam:::mvgam_examp_dat$data_train) /
                 NCOL(mvgam:::mvgam_example4$ytimes),
               NCOL(hc$hindcasts$series_1))

  hc <- hindcast(mvgam:::mvgam_example5, type = 'trend')
  expect_true(inherits(hc$hindcasts, 'list'))
  expect_equal(NROW(mvgam:::mvgam_examp_dat$data_train) /
                 NCOL(mvgam:::mvgam_example5$ytimes),
               NCOL(hc$hindcasts$series_1))
})

test_that("predict() works correctly", {
  expect_equal(dim(predict(mvgam:::mvgam_example1, type = 'expected',
                           process_error = FALSE)),
               dim(predict(mvgam:::mvgam_example2, type = 'expected',
                           process_error = FALSE)))

  expect_equal(dim(predict(mvgam:::mvgam_example3, type = 'expected',
                           process_error = FALSE)),
               dim(predict(mvgam:::mvgam_example4, type = 'expected',
                           process_error = FALSE)))

  expect_equal(NROW(predict(mvgam:::mvgam_example1,
                           newdata = mvgam:::mvgam_examp_dat$data_test,
                           process_error = FALSE)),
               NROW(mvgam:::mvgam_examp_dat$data_test))
  expect_equal(NROW(predict(mvgam:::mvgam_example5,
                            newdata = mvgam:::mvgam_examp_dat$data_test,
                            process_error = FALSE)),
               NROW(mvgam:::mvgam_examp_dat$data_test))

  expect_equal(dim(predict(mvgam:::mvgam_example1,
                           newdata = mvgam:::mvgam_examp_dat$data_test,
                           process_error = FALSE)),
               dim(predict(mvgam:::mvgam_example2,
                           newdata = mvgam:::mvgam_examp_dat$data_test,
                           process_error = FALSE)))

  expect_equal(dim(predict(mvgam:::mvgam_example3,
                           newdata = mvgam:::mvgam_examp_dat$data_test,
                           process_error = FALSE)),
               dim(predict(mvgam:::mvgam_example4,
                           newdata = mvgam:::mvgam_examp_dat$data_test,
                           process_error = FALSE)))
})

test_that("mcmc_plot() works correctly", {
  expect_ggplot(mcmc_plot(mvgam:::mvgam_example1))
  expect_ggplot(mcmc_plot(mvgam:::mvgam_example2))
  expect_ggplot(mcmc_plot(mvgam:::mvgam_example3))
  expect_ggplot(mcmc_plot(mvgam:::mvgam_example4))

  expect_ggplot(mcmc_plot(mvgam:::mvgam_example1, variable = 'trend_params'))
  expect_ggplot(mcmc_plot(mvgam:::mvgam_example2, variable = 'trend_params'))
  expect_ggplot(mcmc_plot(mvgam:::mvgam_example3, variable = 'trend_params'))
  expect_ggplot(mcmc_plot(mvgam:::mvgam_example4, variable = 'trend_params'))
  expect_ggplot(mcmc_plot(mvgam:::mvgam_example5, variable = 'trend_params'))
})

test_that("marginaleffects works correctly", {
  expect_ggplot(plot_slopes(mvgam:::mvgam_example1,
                            variables = 'season',
                            condition = 'season',
                            type = 'link'))
  expect_ggplot(plot_slopes(mvgam:::mvgam_example2,
                            variables = 'season',
                            condition = 'season',
                            type = 'link'))
  expect_ggplot(plot_slopes(mvgam:::mvgam_example3,
                            variables = 'season',
                            condition = 'season',
                            type = 'link'))
  expect_ggplot(plot_slopes(mvgam:::mvgam_example4,
                            variables = 'season',
                            condition = 'season',
                            type = 'link'))
  expect_ggplot(plot_slopes(mvgam:::mvgam_example5,
                            variables = 'season',
                            condition = 'season',
                            type = 'link'))

  expect_ggplot(plot_predictions(mvgam:::mvgam_example1,
                                 condition = 'season',
                                 type = 'link'))
  expect_ggplot(plot_predictions(mvgam:::mvgam_example2,
                                 condition = 'season',
                                 type = 'link'))
  expect_ggplot(plot_predictions(mvgam:::mvgam_example3,
                                 condition = 'season',
                                 type = 'link'))
  expect_ggplot(plot_predictions(mvgam:::mvgam_example4,
                                 condition = 'season',
                                 type = 'link'))
  expect_ggplot(plot_predictions(mvgam:::mvgam_example5,
                                 condition = 'season',
                                 type = 'link'))
})

test_that("plot_mvgam... functions work properly", {
  expect_no_error(plot_mvgam_fc(mvgam:::mvgam_example1))
  expect_no_error(plot_mvgam_fc(mvgam:::mvgam_example2))
  expect_no_error(plot(mvgam:::mvgam_example4, type = 'forecast'))
  expect_no_error(SW(plot(mvgam:::mvgam_example3, type = 'smooths')))
  expect_no_error(SW(plot(mvgam:::mvgam_example3, type = 'smooths',
                       realisations = TRUE)))
  expect_no_error(plot_mvgam_smooth(mvgam:::mvgam_example1,
                                    smooth = 1,
                                    derivatives = TRUE))
  expect_no_error(plot_mvgam_smooth(mvgam:::mvgam_example1,
                                    smooth = 1,
                                    residuals = TRUE))
  expect_no_error(plot_mvgam_smooth(mvgam:::mvgam_example1,
                                    smooth = 1,
                                    realisations = TRUE))
  expect_error(plot_mvgam_smooth(mvgam:::mvgam_example4,
                                    smooth = 1))
  expect_no_error(plot_mvgam_smooth(mvgam:::mvgam_example4,
                                         smooth = 1,
                                         trend_effects = TRUE))
  expect_no_error(plot_mvgam_smooth(mvgam:::mvgam_example4,
                                    smooth = 1,
                                    derivatives = TRUE,
                                    trend_effects = TRUE))
  expect_message(plot(mvgam:::mvgam_example3, type = 'pterms'),
                 'No parametric terms in model formula')
  expect_message(plot(mvgam:::mvgam_example1, type = 're'))
  expect_error(plot(mvgam:::mvgam_example1, type = 'factors'))
  expect_no_error(plot(mvgam:::mvgam_example5, type = 'factors'))
  expect_no_error(plot_mvgam_trend(mvgam:::mvgam_example1))
  expect_no_error(plot_mvgam_trend(mvgam:::mvgam_example4))
  expect_no_error(plot_mvgam_series(object = mvgam:::mvgam_example4))
})

test_that("dynamic factor investigations work", {
  lvcors <- lv_correlations(mvgam:::mvgam_example5)
  expect_true(inherits(lvcors, 'list'))
  expect_true(all.equal(dim(lvcors$mean_correlations),
                        c(nlevels(mvgam:::mvgam_example5$obs_data$series),
                          nlevels(mvgam:::mvgam_example5$obs_data$series))))
  expect_true(mvgam:::mvgam_example5$use_lv)
})

# Skip forecast and loo testing as they are a bit time-consuming
test_that("evaluate() functions working", {
  skip_on_cran()
  mod <- mvgam:::mvgam_example1
  out <- eval_mvgam(mod,
                    fc_horizon = 6,
                    n_samples = 100,
                    n_cores = 1)
  expect_true(inherits(out, 'list'))
  expect_true(all(names(out) ==
                    levels(mod$obs_data$series)))
  expect_true(NROW(out[[1]]) == 6)

  mod <- mvgam:::mvgam_example4
  out <- eval_mvgam(mod,
                    fc_horizon = 2,
                    n_samples = 100,
                    n_cores = 1)
  expect_true(inherits(out, 'list'))
  expect_true(all(names(out) ==
                    levels(mod$obs_data$series)))
  expect_true(NROW(out[[1]]) == 2)

  mod <- mvgam:::mvgam_example5
  out <- eval_mvgam(mod,
                    fc_horizon = 2,
                    n_samples = 100,
                    n_cores = 1)
  expect_true(inherits(out, 'list'))
  expect_true(all(names(out) ==
                    levels(mod$obs_data$series)))
  expect_true(NROW(out[[1]]) == 2)

  expect_no_error(compare_mvgams(mvgam:::mvgam_example2,
                                 mvgam:::mvgam_example4,
                                 n_samples = 100,
                                 n_evaluations = 2,
                                 n_cores = 1))
})

test_that("forecast() works correctly", {
  skip_on_cran()
  fc <- forecast(mvgam:::mvgam_example1,
                 newdata = mvgam:::mvgam_examp_dat$data_test)
  expect_true(inherits(fc$hindcasts, 'list'))
  expect_true(inherits(fc$forecasts, 'list'))
  expect_equal(NROW(mvgam:::mvgam_examp_dat$data_test) /
                 NCOL(mvgam:::mvgam_example1$ytimes),
               NCOL(fc$forecasts$series_1),
               length(fc$test_observations$series_1))

  sc <- score(fc)
  expect_true(inherits(sc, 'list'))
  expect_true(all.equal(names(sc),
                        c(levels(mvgam:::mvgam_examp_dat$data_test$series),
                          'all_series')))
  expect_error(score(fc, score = 'elpd'))

  fc <- forecast(mvgam:::mvgam_example1,
                 newdata = mvgam:::mvgam_examp_dat$data_test,
                 type = 'expected')
  expect_true(inherits(fc$hindcasts, 'list'))
  expect_true(inherits(fc$forecasts, 'list'))
  expect_equal(NROW(mvgam:::mvgam_examp_dat$data_test) /
                 NCOL(mvgam:::mvgam_example1$ytimes),
               NCOL(fc$forecasts$series_1),
               length(fc$test_observations$series_1))

  fc <- forecast(mvgam:::mvgam_example2,
                 newdata = mvgam:::mvgam_examp_dat$data_test,
                 type = 'link')
  expect_true(inherits(fc$hindcasts, 'list'))
  expect_true(inherits(fc$forecasts, 'list'))
  expect_equal(NROW(mvgam:::mvgam_examp_dat$data_test) /
                 NCOL(mvgam:::mvgam_example2$ytimes),
               NCOL(fc$forecasts$series_1),
               length(fc$test_observations$series_1))
  sc <- score(fc, score = 'elpd')
  expect_true(inherits(sc, 'list'))
  expect_true(all.equal(names(sc),
                        c(levels(mvgam:::mvgam_examp_dat$data_test$series),
                          'all_series')))

  fc <- forecast(mvgam:::mvgam_example2,
                 newdata = mvgam:::mvgam_examp_dat$data_test,
                 type = 'expected')
  expect_true(inherits(fc$hindcasts, 'list'))
  expect_true(inherits(fc$forecasts, 'list'))
  expect_equal(NROW(mvgam:::mvgam_examp_dat$data_test) /
                 NCOL(mvgam:::mvgam_example2$ytimes),
               NCOL(fc$forecasts$series_1),
               length(fc$test_observations$series_1))

  fc <- forecast(mvgam:::mvgam_example3,
                 newdata = mvgam:::mvgam_examp_dat$data_test)
  expect_true(inherits(fc$hindcasts, 'list'))
  expect_true(inherits(fc$forecasts, 'list'))
  expect_equal(NROW(mvgam:::mvgam_examp_dat$data_test) /
                 NCOL(mvgam:::mvgam_example3$ytimes),
               NCOL(fc$forecasts$series_1),
               length(fc$test_observations$series_1))

  fc <- forecast(mvgam:::mvgam_example3,
                 newdata = mvgam:::mvgam_examp_dat$data_test,
                 type = 'expected')
  expect_true(inherits(fc$hindcasts, 'list'))
  expect_true(inherits(fc$forecasts, 'list'))
  expect_equal(NROW(mvgam:::mvgam_examp_dat$data_test) /
                 NCOL(mvgam:::mvgam_example3$ytimes),
               NCOL(fc$forecasts$series_1),
               length(fc$test_observations$series_1))

  fc <- forecast(mvgam:::mvgam_example4,
                 newdata = mvgam:::mvgam_examp_dat$data_test)
  expect_true(inherits(fc$hindcasts, 'list'))
  expect_true(inherits(fc$forecasts, 'list'))
  expect_equal(NROW(mvgam:::mvgam_examp_dat$data_test) /
                 NCOL(mvgam:::mvgam_example4$ytimes),
               NCOL(fc$forecasts$series_1),
               length(fc$test_observations$series_1))

  fc <- forecast(mvgam:::mvgam_example4,
                 newdata = mvgam:::mvgam_examp_dat$data_test,
                 type = 'expected')
  expect_true(inherits(fc$hindcasts, 'list'))
  expect_true(inherits(fc$forecasts, 'list'))
  expect_equal(NROW(mvgam:::mvgam_examp_dat$data_test) /
                 NCOL(mvgam:::mvgam_example4$ytimes),
               NCOL(fc$forecasts$series_1),
               length(fc$test_observations$series_1))

  fc <- forecast(mvgam:::mvgam_example5,
                 newdata = mvgam:::mvgam_examp_dat$data_test,
                 type = 'expected')
  expect_true(inherits(fc$hindcasts, 'list'))
  expect_true(inherits(fc$forecasts, 'list'))
  expect_equal(NROW(mvgam:::mvgam_examp_dat$data_test) /
                 NCOL(mvgam:::mvgam_example5$ytimes),
               NCOL(fc$forecasts$series_1),
               length(fc$test_observations$series_1))
})

test_that("loo() works correctly", {
  skip_on_cran()
  expect_loo(suppressWarnings(loo(mvgam:::mvgam_example1)))
  expect_loo(suppressWarnings(loo(mvgam:::mvgam_example2)))
  expect_loo(suppressWarnings(loo(mvgam:::mvgam_example3)))
  expect_loo(suppressWarnings(loo(mvgam:::mvgam_example4)))
  expect_loo(suppressWarnings(loo(mvgam:::mvgam_example5)))

  p <- SW(loo_compare(mvgam:::mvgam_example1,
                      mvgam:::mvgam_example2,
                      model_names = c('banana')))
  expect_true(inherits(p, 'compare.loo'))
  expect_true(all(is.na(dimnames(p)[[1]]) == c(FALSE, TRUE)))

  p <- SW(loo_compare(mvgam:::mvgam_example1,
                      mvgam:::mvgam_example2,
                      mvgam:::mvgam_example3,
                      mvgam:::mvgam_example4,
                      mvgam:::mvgam_example5))
  expect_true(inherits(p, 'compare.loo'))
})