happy path for sparse matrix passed to fit()

Author: EmilHvitfeldt

R/fit.R

@@ -138,13 +138,7 @@ fit.model_spec <-
     }
 
     if (is_sparse_matrix(data)) {
-      outcome_names <- all.names(rlang::f_lhs(formula))
-      outcome_ind <- match(outcome_names, colnames(data))
-
-      y <- data[, outcome_ind]
-      x <- data[, -outcome_ind, drop = TRUE]
-
-      return(fit_xy(object, x, y, case_weights, control, ...))
+      data <- sparsevctrs::coerce_to_sparse_tibble(data)
     }
 
     dots <- quos(...)

tests/testthat/_snaps/sparsevctrs.md

@@ -11,8 +11,8 @@
     Code
       lm_fit <- fit(spec, avg_price_per_room ~ ., data = hotel_data[1:100, ])
     Condition
-      Error in `fit_xy()`:
-      ! `x` is a sparse matrix, but `linear_reg()` with engine "lm" doesn't accept that.
+      Warning:
+      `data` is a sparse tibble, but `linear_reg()` with engine "lm" doesn't accept that. Converting to non-sparse.
 
 # sparse tibble can be passed to `fit_xy()
 

tests/testthat/test-sparsevctrs.R

@@ -39,7 +39,6 @@ test_that("sparse matrix can be passed to `fit()", {
     set_engine("lm")
 
   expect_snapshot(
-    error = TRUE,
     lm_fit <- fit(spec, avg_price_per_room ~ ., data = hotel_data[1:100, ])
   )
 })