Drop most skip_on_ci

.github/workflows/R-CMD-check.yaml

@@ -22,7 +22,7 @@ jobs:
           - {os: windows-latest, r: 'release'}
           - {os: macOS-latest, r: 'release'}
           - {os: ubuntu-latest,   r: 'devel', http-user-agent: 'release'}
-          - {os: ubuntu-latest,   r: 'release'}
+        #  - {os: ubuntu-latest,   r: 'release'}
         # - {os: ubuntu-latest,   r: 'oldrel-1'}
 
     env:
@@ -72,6 +72,7 @@ jobs:
           remotes::install_cran("sf")
           remotes::install_cran("rcmdcheck")
           remotes::install_cran("textshaping")
+          remotes::install_github("pbs-assess/sdmTMBextra")
           install.packages("Matrix", type = "source")
           install.packages("TMB", type = "source")
         shell: Rscript {0}
@@ -83,6 +84,7 @@ jobs:
           remotes::install_cran("knitr")
           remotes::install_cran("rmarkdown")
           remotes::install_cran("rcmdcheck")
+          remotes::install_github("pbs-assess/sdmTMBextra")
           install.packages("Matrix", type = "source")
           install.packages("TMB", type = "source")
         shell: Rscript {0}
@@ -94,6 +96,7 @@ jobs:
           remotes::install_cran("knitr")
           remotes::install_cran("rmarkdown")
           remotes::install_cran("rcmdcheck")
+          remotes::install_github("pbs-assess/sdmTMBextra")
           install.packages("Matrix", type = "source")
           install.packages("TMB", type = "source")
         shell: Rscript {0}

tests/testthat/test-1-fit-basic.R

@@ -125,7 +125,6 @@ test_that("sdmTMB model fit with a covariate beta", {
 })
 
 test_that("Anisotropy fits and plots", {
-  skip_on_ci()
   skip_on_cran()
   local_edition(2)
   m <- sdmTMB(
@@ -176,7 +175,6 @@ test_that("A spatiotemporal version works with predictions on new data points",
 
 test_that("Predictions on the original data set as `newdata`` return the same predictions", {
   skip_on_cran()
-  skip_on_ci()
   local_edition(2)
   set.seed(1)
   x <- stats::runif(500, -1, 1)
@@ -219,7 +217,6 @@ test_that("Predictions on the original data set as `newdata`` return the same pr
 
 test_that("poly() works on newdata", {
   skip_on_cran()
-  skip_on_ci()
 
   # https://github.com/pbs-assess/sdmTMB/issues/77
   d <- pcod_2011

tests/testthat/test-2-fit-less-basic.R

@@ -1,6 +1,5 @@
 test_that("Regularization works", {
   skip_on_cran()
-  skip_on_ci()
   local_edition(2)
   d <- subset(pcod, year >= 2015)
   d$depth_scaled <- as.numeric(scale(d$depth_scaled))
@@ -31,7 +30,6 @@ test_that("Regularization works", {
 
 test_that("A time-varying model fits and predicts appropriately", {
   skip_on_cran()
-  skip_on_ci()
   local_edition(2)
   # SEED <- 42
   # set.seed(SEED)
@@ -84,7 +82,6 @@ test_that("Year indexes get created correctly", {
 
 test_that("A spatially varying coefficient model fits", {
   skip_on_cran()
-  skip_on_ci()
   d <- subset(pcod, year >= 2011) # subset for speed
   pcod_spde <- make_mesh(d, c("X", "Y"), cutoff = 30)
   d$scaled_year <- (d$year - mean(d$year)) / sd(d$year)
@@ -101,7 +98,6 @@ test_that("A spatially varying coefficient model fits", {
 test_that("SPDE as generated by make_mesh is consistent", {
   set.seed(42)
   skip_on_cran()
-  skip_on_ci()
   set.seed(1)
   local_edition(2)
   x <- stats::runif(70, -1, 1)
@@ -173,7 +169,6 @@ test_that("SPDE as generated by make_mesh is consistent", {
 
 test_that("profile option works", {
   skip_on_cran()
-  skip_on_ci()
   d <- subset(pcod, year == 2013)
   pcod_spde <- make_mesh(d, c("X", "Y"), cutoff = 10)
   mp <- sdmTMB(density ~ depth_scaled + depth_scaled2,
@@ -192,7 +187,6 @@ test_that("profile option works", {
 
 test_that("The mapping off spatial and spatiotemporal fields works.", {
   skip_on_cran()
-  skip_on_ci()
   d <- subset(pcod, year >= 2013)
   pcod_spde <- make_mesh(d, c("X", "Y"), cutoff = 50)
   m <- sdmTMB(density ~ 0 + as.factor(year),
@@ -251,7 +245,6 @@ test_that("Large coordinates cause a warning.", {
 
 test_that("Random walk fields work", {
   skip_on_cran()
-  skip_on_ci()
   d <- subset(pcod, year >= 2013)
   pcod_spde <- make_mesh(d, c("X", "Y"), cutoff = 15)
   m_rw <- sdmTMB(density ~ 1,
@@ -281,7 +274,6 @@ test_that("Random walk fields work", {
 
 test_that("start works", {
   skip_on_cran()
-  skip_on_ci()
 
     expect_error({
       m2 <- sdmTMB(density ~ poly(depth, 2),
@@ -300,7 +292,6 @@ test_that("start works", {
 
 test_that("Multiple SVC works", {
   skip_on_cran()
-  skip_on_ci()
 
   mesh <- make_mesh(pcod, c("X", "Y"), cutoff = 15)
 
@@ -324,7 +315,6 @@ test_that("Multiple SVC works", {
 
 test_that("More esoteric prediction options work", {
   skip_on_cran()
-  skip_on_ci()
   fit <- sdmTMB(
     density ~ depth_scaled,
     data = pcod_2011, mesh = pcod_mesh_2011,
@@ -369,7 +359,6 @@ test_that("More esoteric prediction options work", {
 
 test_that("update() works", {
   skip_on_cran()
-  skip_on_ci()
   fit <- sdmTMB(
     density ~ depth_scaled,
     data = pcod_2011, mesh = pcod_mesh_2011,

tests/testthat/test-2-print-anisotropy.R

@@ -1,6 +1,6 @@
 test_that("Print anisotropy prints correctly", {
   skip_on_cran()
-  skip_on_ci()
+  skip_on_ci() # slow
 
   # No anisotropy
   fit1 <- sdmTMB(

tests/testthat/test-3-families.R

@@ -36,7 +36,6 @@ loc <- data.frame(x = x, y = y)
 spde <- make_mesh(loc, c("x", "y"), n_knots = 50, type = "kmeans")
 
 test_that("Student family fits", {
-  skip_on_ci()
   skip_on_cran()
   set.seed(3)
   initial_betas <- 0.5
@@ -57,7 +56,6 @@ test_that("Student family fits", {
 })
 
 test_that("Lognormal fits", {
-  skip_on_ci()
   skip_on_cran()
   range <- 1
   x <- stats::runif(500, -1, 1)
@@ -77,7 +75,6 @@ test_that("Lognormal fits", {
 })
 
 test_that("NB2 fits", {
-  skip_on_ci()
   skip_on_cran()
   set.seed(1)
   x <- stats::runif(300, -1, 1)
@@ -93,7 +90,6 @@ test_that("NB2 fits", {
 })
 
 test_that("Truncated NB2, truncated NB1, and regular NB1 fit", {
-  skip_on_ci()
   skip_on_cran()
   set.seed(1)
   x <- stats::runif(300, -1, 1)
@@ -129,7 +125,6 @@ test_that("Truncated NB2, truncated NB1, and regular NB1 fit", {
 })
 
 test_that("Poisson fits", {
-  skip_on_ci()
   skip_on_cran()
   d <- pcod
   spde <- make_mesh(pcod, c("X", "Y"), cutoff = 10)
@@ -144,7 +139,6 @@ test_that("Poisson fits", {
 })
 
 test_that("Binomial fits", {
-  skip_on_ci()
   skip_on_cran()
   d <- pcod[pcod$year == 2017, ]
   d$density <- round(d$density)
@@ -158,7 +152,6 @@ test_that("Binomial fits", {
 })
 
 test_that("Gamma fits", {
-  skip_on_ci()
   skip_on_cran()
   d <- pcod[pcod$year == 2017 & pcod$density > 0, ]
   spde <- make_mesh(d, c("X", "Y"), cutoff = 10)
@@ -176,7 +169,6 @@ test_that("Gamma fits", {
 })
 
 test_that("Beta fits", {
-  skip_on_ci()
   skip_on_cran()
   set.seed(1)
   x <- stats::runif(400, -1, 1)
@@ -200,7 +192,6 @@ test_that("Beta fits", {
 })
 
 test_that("Censored Poisson fits", {
-  skip_on_ci()
   skip_on_cran()
   set.seed(1)
 
@@ -434,7 +425,6 @@ test_that("Binomial simulation/residuals works with weights argument or cbind()"
 
 test_that("Generalized gamma works", {
   skip_on_cran()
-  skip_on_ci()
   d <- subset(pcod_2011, density > 0)
   fit1 <- sdmTMB(
     density ~ 1 + depth_scaled,
@@ -480,7 +470,6 @@ test_that("Generalized gamma works", {
 
 test_that("Generalized gamma matches Gamma when Q = sigma", {
   skip_on_cran()
-  skip_on_ci()
 
   # Generate values drawn from generaliased gamma distribution given the mean of those values
   rgengamma <- function(n, mean, sigma, Q) {

tests/testthat/test-3-spatial-varying.R

@@ -1,6 +1,5 @@
 test_that("SVC are estimated correctly for binomial and delta models", {
   skip_on_cran()
-  skip_on_ci()
   local_edition(2)
   d <- pcod
   d$year_scaled <- as.numeric(scale(d$year))
@@ -93,7 +92,6 @@ test_that("SVC are estimated correctly for binomial and delta models", {
 test_that("Delta model with spatially varying factor predictor and no spatiotemporal field works #237", {
   # https://github.com/pbs-assess/sdmTMB/issues/237
   skip_on_cran()
-  skip_on_ci()
   pcod_q2 <- pcod_2011
   pcod_q1 <- pcod_2011
   pcod_q1$quarter <- as.factor(1)
@@ -119,7 +117,6 @@ test_that("Delta model with spatially varying factor predictor and no spatiotemp
 
 test_that("Factor handling for SVC models works #269", {
   skip_on_cran()
-  skip_on_ci()
   set.seed(1)
   pcod_2011$vessel <- sample(c("A", "B"), size = nrow(pcod_2011), replace = TRUE)
   pcod_2011$vessel <- as.factor(pcod_2011$vessel)
@@ -140,7 +137,6 @@ test_that("Factor handling for SVC models works #269", {
 
 test_that("SVC throws a warning if character class #269", {
   skip_on_cran()
-  skip_on_ci()
   pcod_2011$vessel <- sample(c("A", "B"), size = nrow(pcod_2011), replace = TRUE)
   expect_warning({
     fit <- sdmTMB(present ~ vessel,

tests/testthat/test-4-index-calculation.R

@@ -1,6 +1,5 @@
 test_that("get_index(), get_index_sims(), and get_cog() work", {
   local_edition(3)
-  skip_on_ci()
   skip_on_cran()
   pcod_spde <- make_mesh(pcod, c("X", "Y"), cutoff = 20)
   m <- sdmTMB(
@@ -56,7 +55,6 @@ test_that("get_index(), get_index_sims(), and get_cog() work", {
 })
 
 test_that("index errors are returned as needed", {
-  skip_on_ci()
   skip_on_cran()
 
   g <- replicate_df(qcs_grid, "year", unique(pcod_2011$year))

tests/testthat/test-5-residuals.R

@@ -1,6 +1,5 @@
 # test_that("Simulated residuals work", {
 #   skip_on_cran()
-#   skip_on_ci()
 #   skip_if_not_installed("INLA")
 #   fit <- sdmTMB(density ~ as.factor(year) + poly(depth, 2),
 #     data = pcod_2011, time = "year", mesh = pcod_mesh_2011,
@@ -19,7 +18,6 @@
 
 test_that("randomized quantile residuals work,", {
   skip_on_cran()
-  skip_on_ci()
 
   set.seed(1)
   predictor_dat <- data.frame(X = runif(2000), Y = runif(2000))
@@ -298,7 +296,6 @@ test_that("MCMC residuals work with sdmTMBextra", {
   skip_on_cran()
   skip_if_not_installed("sdmTMBextra")
   skip_if_not_installed("rstan")
-  skip_on_ci()
   d <- pcod_2011
   set.seed(1)
   d$offset <- rnorm(nrow(d))
@@ -339,7 +336,6 @@ test_that("predict_mle_mcmc() works with extra_time #297", {
   skip_on_cran()
   skip_if_not_installed("sdmTMBextra")
   skip_if_not_installed("rstan")
-  skip_on_ci()
   fit <- sdmTMB(
     density ~ 1,
     time = "year",
@@ -357,7 +353,6 @@ test_that("predict_mle_mcmc() works with extra_time #297", {
 
 test_that("all residuals work with extra time and offsets #326", {
   skip_on_cran()
-  skip_on_ci()
   skip_if_not_installed("sdmTMBextra")
   mesh <- make_mesh(pcod, c("X", "Y"), cutoff = 30)
   pcod$os <- rep(log(0.01), nrow(pcod)) # offset

tests/testthat/test-6-tmb-simulation.R

@@ -1,5 +1,4 @@
 test_that("TMB IID simulation works", {
-  skip_on_ci()
   skip_on_cran()
 
   set.seed(1)
@@ -32,7 +31,6 @@ test_that("TMB IID simulation works", {
 })
 
 test_that("TMB AR1 simulation works", {
-  skip_on_ci()
   skip_on_cran()
 
   set.seed(1)
@@ -68,7 +66,6 @@ test_that("TMB AR1 simulation works", {
 })
 
 test_that("TMB RW simulation works", {
-  skip_on_ci()
   skip_on_cran()
 
   set.seed(1)
@@ -121,7 +118,6 @@ test_that("TMB RW simulation works", {
 
 test_that("TMB (custom) AR1 simulation is unbiased", {
   # run many times; check for bias
-  skip_on_ci()
   skip_on_cran()
 
   do_sim_fit <- function(i) {
@@ -165,7 +161,6 @@ test_that("TMB (custom) AR1 simulation is unbiased", {
 
 
 # test_that("TMB Delta simulation works", {
-#   skip_on_ci()
 #   skip_on_cran()
 #   skip_if_not_installed("INLA")
 #

tests/testthat/test-7-visreg.R

@@ -1,6 +1,5 @@
 test_that("visreg works", {
   skip_on_cran()
-  skip_on_ci()
   skip_if_not_installed("visreg")
 
   # first test against glmmTMB outputs