check for mode first (#972)

because regression and classification models also have `$censor_probs` even though its just an empty list

Author: hfrick

DESCRIPTION

@@ -1,6 +1,6 @@
 Package: parsnip
 Title: A Common API to Modeling and Analysis Functions
-Version: 1.1.0.9002
+Version: 1.1.0.9003
 Authors@R: c(
     person("Max", "Kuhn", , "max@posit.co", role = c("aut", "cre")),
     person("Davis", "Vaughan", , "davis@posit.co", role = "aut"),

R/survival-censoring-weights.R

@@ -63,6 +63,11 @@ trunc_probs <- function(probs, trunc = 0.01) {
 }
 
 .check_censor_model <- function(x) {
+  if (x$spec$mode != "censored regression") {
+    cli::cli_abort(
+      "The model needs to be for mode 'censored regression', not for mode '{x$spec$mode}'."
+    )
+  }
   nms <- names(x)
   if (!any(nms == "censor_probs")) {
     rlang::abort("Please refit the model with parsnip version 1.0.4 or greater.")
@@ -245,14 +250,17 @@ add_graf_weights_vec <- function(object, .pred, surv_obj, trunc = 0.05, eps = 10
   num_times <- vctrs::list_sizes(.pred)
   y <- vctrs::list_unchop(.pred)
   y$surv_obj <- vctrs::vec_rep_each(surv_obj, times = num_times)
+
   names(y)[names(y) == ".time"] <- ".eval_time"   # Temporary
+
   # Compute the actual time of evaluation
   y$.weight_time <- graf_weight_time_vec(y$surv_obj, y$.eval_time, eps = eps)
   # Compute the corresponding probability of being censored
   y$.pred_censored <- predict(object$censor_probs, time = y$.weight_time, as_vector = TRUE)
   y$.pred_censored <- trunc_probs(y$.pred_censored, trunc = trunc)
   # Invert the probabilities to create weights
   y$.weight_censored = 1 / y$.pred_censored
+
   # Convert back the list column format
   y$surv_obj <- NULL
   vctrs::vec_chop(y, sizes = num_times)