Fix #370

R/tmb-sim.R

@@ -268,24 +268,25 @@ sdmTMB_simulate <- function(formula,
   if (!is.null(fit$time)) d[[fit$time]] <- data[[fit$time]]
   d[[mesh$xy_cols[1]]] <- data[[mesh$xy_cols[1]]]
   d[[mesh$xy_cols[2]]] <- data[[mesh$xy_cols[2]]]
-  d[["omega_s"]] <- if (all(s$omega_s_A != 0)) s$omega_s_A
-  d[["epsilon_st"]] <- if (all(s$epsilon_st_A_vec != 0)) s$epsilon_st_A_vec
-  d[["zeta_s"]] <- if (all(s$zeta_s_A != 0)) s$zeta_s_A
-
-    # Warnings for pieces collapsing to 0. The sum() > 0 piece is needed because parameters that are input are turned to 0x0 matrices
-  if (sum(sigma_O) > 0) {
-    if(is.null(d[["omega_s"]])) cli::cli_alert_info(paste("Warning: spatial field is collapsing to 0 but sigma_O was specified.",
-                                                        "Please check the spatial range and cutoff distance used to construct the mesh."))
-  }
-  if (sum(sigma_E) > 0) {
-    if(is.null(d[["epsilon_st"]])) cli::cli_alert_info(paste("Warning: spatiotemporal field is collapsing to 0 but sigma_E was specified.",
-                                                        "Please check the spatial range and cutoff distance used to construct the mesh."))
-  }
-  if (sum(sigma_Z) > 0) {
-    if(is.null(d[["zeta_s"]])) cli::cli_alert_info(paste("Warning: spatially varying coefficient field is collapsing to 0 but sigma_Z was specified.",
-                                                               "Please check the spatial range and cutoff distance used to construct the mesh."))
-  }
-
+
+  d[["omega_s"]] <- if (sum(sigma_O) > 0) s$omega_s_A
+  d[["epsilon_st"]] <- if (sum(sigma_E) > 0) s$epsilon_st_A_vec
+  d[["zeta_s"]] <- if (sum(sigma_Z) > 0) s$zeta_s_A
+
+  # # Warnings for fields collapsing to 0
+  # info_collapse <- function(sig, vec, .par, .name) {
+  #   if (sum(sig) > 0 && all (vec == 0)) {
+  #     msg <- paste0("The ", .name, " has been returned as all zeros although ", .par,
+  #       " was specified as > 0. Try making your mesh finer, e.g., with a lower ",
+  #       "`cutoff` or a higher number of knots. Triangle edge length needs to be ",
+  #       "lower than the range size (distance correlation is effectively independent.")
+  #     cli::cli_alert_info(msg)
+  #   }
+  # }
+  # info_collapse(sigma_O, s$omega_s_A, "sigma_O", "spatial field")
+  # info_collapse(sigma_E, s$epsilon_st_A_vec, "sigma_E", "spatiotemporal field")
+  # info_collapse(sigma_Z, s$zeta_s_A, "sigma_Z", "spatially varying coefficient field")
+
   if (any(family$family %in% c("truncated_nbinom1", "truncated_nbinom2"))) {
     d[["mu"]] <- family$linkinv(s$eta_i, phi = phi)
   } else {

tests/testthat/test-tmb-simulation.R

@@ -183,3 +183,28 @@ test_that("simulate.sdmTMB returns the right length", {
   s <- simulate(m, nsim = 2)
   expect_equal(nrow(s), nrow(pcod))
 })
+
+test_that("coarse meshes with zeros in simulation still return fields #370", {
+  set.seed(123)
+  predictor_dat <- data.frame(
+    X = runif(100), Y = runif(100),
+    a1 = rnorm(100), year = rep(1:2, each = 50))
+  mesh <- sdmTMB::make_mesh(predictor_dat, xy_cols = c("X", "Y"), n_knots = 30)
+  sim_dat <- sdmTMB::sdmTMB_simulate(
+    formula = ~ 1 + a1,
+    data = predictor_dat,
+    time = "year",
+    mesh = mesh,
+    family = gaussian(),
+    range = 0.5,
+    sigma_E = 0.1,
+    phi = 0.1,
+    sigma_O = 0.2,
+    seed = 42,
+    B = c(0.2, -0.4) # B0 = intercept, B1 = a1 slope
+  )
+  nm <- names(sim_dat)
+  expect_true("omega_s" %in% nm)
+  expect_true("epsilon_st" %in% nm)
+  expect_false("zeta_s" %in% nm)
+})