windows absurdly slow; skip damn near everything

tests/testthat/test-dynamic.R

@@ -1,5 +1,7 @@
 context("dynamic")
 
+skip_on_cran()
+
 test_that("dynamic to gp spline is working properly", {
   expect_match(attr(terms(mvgam:::interpret_mvgam(formula = y ~ dynamic(covariate, rho = 1,
                                                                         stationary = FALSE),
@@ -76,7 +78,6 @@ test_that("rho argument cannot be larger than N - 1", {
 })
 
 test_that("dynamic to spline works for trend_formulas", {
-  skip_on_cran()
   beta_data$data_train$random <- rnorm(NROW(beta_data$data_train))
   mod <- mvgam(y ~ dynamic(random, rho = 5),
                trend_formula = ~ dynamic(random, rho = 15),
@@ -92,7 +93,6 @@ test_that("dynamic to spline works for trend_formulas", {
 })
 
 test_that("dynamic to Hilbert works for trend_formulas", {
-  skip_on_cran()
   beta_data$data_train$random <- rnorm(NROW(beta_data$data_train))
   mod <- mvgam(y ~ dynamic(random),
                trend_formula = ~ dynamic(random, k = 22),

tests/testthat/test-gp.R

@@ -1,5 +1,7 @@
 context("gp")
 
+skip_on_cran()
+
 test_that("gp_to_s is working properly", {
   # All true gp() terms should be changed to s() with k = k+1
   formula <- y ~ s(series) + gp(banana) +

tests/testthat/test-marginaleffects.R

@@ -1,5 +1,7 @@
 context("marginaleffects")
 
+skip_on_cran()
+
 test_that("data_grid gives expected output structure", {
   # Dataframe example
   simdat <- sim_mvgam(n_series = 3, prop_trend = 1,
@@ -42,7 +44,6 @@ test_that("get_data gives expected output structure", {
 })
 
 test_that("get_predict gives expected output structure", {
-  skip_on_cran()
   preds <- get_predict(mvgam:::mvgam_example4)
   expect_equal(NROW(preds), NROW(mvgam:::mvgam_example4$obs_data))
 
@@ -51,7 +52,6 @@ test_that("get_predict gives expected output structure", {
 })
 
 test_that("averages give expected output structures", {
-  skip_on_cran()
   ems <- avg_predictions(mvgam:::mvgam_example3)
   expect_equal(NROW(ems), 1)
   expect_true(all(c("estimate", "conf.low", "conf.high") %in% colnames(ems)))

tests/testthat/test-mvgam.R

@@ -1,8 +1,8 @@
 context("mvgam")
 
+skip_on_cran()
+
 # JAGS setup should work, whether installed or not
-test_that("JAGS setups work", {
-  skip_on_cran()
   simdat <- sim_mvgam()
   mod <- mvgam(y ~ s(season),
                trend_model = 'RW',
@@ -100,7 +100,6 @@ test_that("response variable must be specified", {
 })
 
 test_that("prior_only works", {
-  skip_on_cran()
   mod <- mvgam(y ~ s(season),
                trend_model = AR(p = 2),
                drift = TRUE,
@@ -308,7 +307,6 @@ test_that("series levels must match unique entries in series", {
 })
 
 test_that("share_obs_params working", {
-  skip_on_cran()
   # Standard beta
   mod <- mvgam(y ~ s(season, by = series),
                trend_model = RW(cor = TRUE),
@@ -447,7 +445,6 @@ test_that("share_obs_params working", {
 })
 
 test_that("trend_map is behaving propoerly", {
-  skip_on_cran()
   sim <- sim_mvgam(n_series = 3)
   mod_data <- sim$data_train
   trend_map <- data.frame(series = unique(mod_data$series),
@@ -475,7 +472,6 @@ test_that("trend_map is behaving propoerly", {
 })
 
 test_that("models with only random effects should work without error", {
-  skip_on_cran()
   sim <- sim_mvgam(n_series = 3)
   mod_data <- sim$data_train
   mod_map <- mvgam(y ~ s(series, bs = 're'),
@@ -485,7 +481,6 @@ test_that("models with only random effects should work without error", {
 })
 
 test_that("models with only fs smooths should work without error", {
-  skip_on_cran()
   sim <- sim_mvgam(n_series = 3)
   mod_data <- sim$data_train
   mod_map <- mvgam(y ~ s(season, series, bs = 'fs'),
@@ -495,7 +490,6 @@ test_that("models with only fs smooths should work without error", {
 })
 
 test_that("trend_formula setup is working properly", {
-  skip_on_cran()
   sim <- sim_mvgam(n_series = 3)
   mod_data <- sim$data_train
   mod_map <- mvgam(y ~ s(series, bs = 're'),
@@ -536,7 +530,6 @@ test_that("trend_formula setup is working properly", {
 # Check that parametric effect priors are properly incorporated in the
 # model for a wide variety of model forms
 test_that("parametric effect priors correctly incorporated in models", {
-  skip_on_cran()
   mod_data <- mvgam:::mvgam_examp_dat
   mod_data$data_train$x1 <-
     rnorm(NROW(mod_data$data_train))

tests/testthat/test-piecewise.R

@@ -80,6 +80,7 @@ df <- rbind(data.frame(y = y,
                        fake = rnorm(100)))
 
 test_that("logistic caps should be included in the correct order", {
+  skip_on_cran()
   mod <- mvgam(formula = y ~ 0,
                      data = df,
                      trend_model = PW(growth = 'logistic',