`multi_predict(type = "survival")` is missing `penalty` column for single penalty value

[hfrick]

library(censored)
#> Loading required package: parsnip
#> Loading required package: survival
lung2 <- lung[-14, ]

set.seed(14)
f_fit <- proportional_hazards(penalty = 0.123) %>%
  set_mode("censored regression") %>%
  set_engine("glmnet") %>%
  fit(Surv(time, status) ~ age + ph.ecog, data = lung2)

pred_multi <- multi_predict(f_fit,new_data = lung2[1:3, ], type = "survival",
  eval_time = c(100, 200), penalty = 0.1)

# this should have a penalty column
pred_multi$.pred[[1]]
#> # A tibble: 2 × 2
#>   .eval_time .pred_survival
#>        <dbl>          <dbl>
#> 1        100          0.868
#> 2        200          0.680

^{Created on 2023-05-04 with reprex v2.0.2}

[hfrick]

This currently doesn't work because survival_prob_coxnet() reconstructs multi from the length of the penalty, which does not allow us to specify multi = TRUE and a penalty with a single value.

The plan is to give survival_prob_coxnet() its own multi arg and call it directly from multi_predict(). We can't go through predict() as we do now because predict() won't let us pass the multi argument through. We will need to add to multi_predict() any checks on the type (and the like) that are carried out by predict().

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