From 4b785e06e845e48f6390bf87e64414c061323e31 Mon Sep 17 00:00:00 2001
From: Sean Anderson <sean@seananderson.ca>
Date: Fri, 20 Sep 2024 13:34:34 -0700
Subject: [PATCH] Fix offset prediction in cross validation #372

---
 DESCRIPTION                  |  2 +-
 NEWS.md                      |  3 +++
 R/cross-val.R                | 10 ++++++----
 tests/testthat/test-offset.R | 22 ++++++++++++++++++++++
 4 files changed, 32 insertions(+), 5 deletions(-)

diff --git a/DESCRIPTION b/DESCRIPTION
index 7cc976e50..c69e2f1d4 100644
--- a/DESCRIPTION
+++ b/DESCRIPTION
@@ -1,7 +1,7 @@
 Type: Package
 Package: sdmTMB
 Title: Spatial and Spatiotemporal SPDE-Based GLMMs with 'TMB'
-Version: 0.6.0.9004
+Version: 0.6.0.9005
 Authors@R: c(
     person(c("Sean", "C."), "Anderson", , "sean@seananderson.ca",
            role = c("aut", "cre"),
diff --git a/NEWS.md b/NEWS.md
index b3db0f703..18375ff40 100644
--- a/NEWS.md
+++ b/NEWS.md
@@ -1,5 +1,8 @@
 # sdmTMB (development version)
 
+* Fix passing of `offset` argument through in `sdmTMB_cv()`. Before it was being
+  omitted in the prediction (i.e., set to 0). #372
+
 * Fig bug in `exponentiate` argument for `tidy()`. Set `conf.int = TRUE` as
   default. #353
 
diff --git a/R/cross-val.R b/R/cross-val.R
index 06abe9af1..6e871f13c 100644
--- a/R/cross-val.R
+++ b/R/cross-val.R
@@ -287,10 +287,10 @@ sdmTMB_cv <- function(
     cli_abort("`weights` cannot be specified within sdmTMB_cv().")
   }
   if ("offset" %in% names(dot_args)) {
-    .offset <- eval(dot_args$offset)
-    if (parallel && !is.character(.offset) && !is.null(.offset)) {
-      cli_abort("We recommend using a character value for 'offset' (indicating the column name) when applying parallel cross validation.")
+    if (!is.character(dot_args$offset)) {
+      cli_abort("Please use a character value for 'offset' (indicating the column name) for cross validation.")
     }
+    .offset <- eval(dot_args$offset)
   } else {
     .offset <- NULL
   }
@@ -369,7 +369,9 @@ sdmTMB_cv <- function(
 
     # FIXME: only use TMB report() below to be faster!
     # predict for withheld data:
-    predicted <- predict(object, newdata = cv_data, type = "response")
+    predicted <- predict(object, newdata = cv_data, type = "response",
+      offset = if (!is.null(.offset)) cv_data[[.offset]] else rep(0, nrow(cv_data)))
+
     cv_data$cv_predicted <- predicted$est
     response <- get_response(object$formula[[1]])
     withheld_y <- predicted[[response]]
diff --git a/tests/testthat/test-offset.R b/tests/testthat/test-offset.R
index aa6a636f2..d19420d70 100644
--- a/tests/testthat/test-offset.R
+++ b/tests/testthat/test-offset.R
@@ -138,6 +138,28 @@ test_that("Offset prediction matches glm()", {
   # p_glmmTMB <- predict(fit_glmmTMB, newdata = dat)
   # expect_equal(p$est, unname(p_glmmTMB))
 })
+
+test_that("offset gets passed through cross validation as expected #372", {
+  dat <- subset(dogfish, catch_weight > 0)
+  expect_error(
+    x <- sdmTMB_cv(catch_weight ~ 1,
+      data = dat,
+      family = Gamma("log"), offset = log(dat$area_swept), spatial = "off"
+    ),
+    "offset"
+  )
+  set.seed(1)
+  x <- sdmTMB_cv(catch_weight ~ 1,
+    data = dat, family = Gamma("log"),
+    offset = "area_swept", spatial = "off",
+    mesh = make_mesh(dat, c("X", "Y"), cutoff = 10), k_folds = 2
+  )
+  y <- x$data[, c("catch_weight", "cv_predicted")]
+  # plot(y$catch_weight, y$cv_predicted)
+  # if offset is applied, will have unique values because an intercept-only model:
+  expect_true(length(unique(y$cv_predicted)) == 684L)
+})
+
 # #
 # # offset/prediction setting checks:
 #