This is how benchmark results would change (along with a 95% confidence interval in relative change) if eca0fae is merged into master:

•   :ballot_box_with_check:as_draws_array: 136ms -> 136ms [-0.51%, +0.83%]
•   :rocket:as_draws_df: 64.6ms -> 61ms [-6.83%, -4.58%]
•   :ballot_box_with_check:as_draws_list: 157ms -> 156ms [-1.13%, +0.17%]
•   :ballot_box_with_check:as_draws_matrix: 58.8ms -> 58.7ms [-0.97%, +0.57%]
•   :ballot_box_with_check:as_draws_rvars: 80ms -> 80.4ms [-0.49%, +1.55%]
• ❗🐌summarise_draws_100_variables: 706ms -> 715ms [+0.92%, +1.51%]
• ❗🐌summarise_draws_10_variables: 105ms -> 107ms [+0.93%, +2.1%]
  Further explanation regarding interpretation and methodology can be found in the documentation.

Looks like a >1% increase to summarise_draws times, which I don't think is acceptable

How much increase exactly? 1% would barely matter I think

Codecov Report

Attention: Patch coverage is 93.75000% with 1 lines in your changes are missing coverage. Please review.

Project coverage is 95.33%. Comparing base (9de9857) to head (a28483f).

❗ Current head a28483f differs from pull request most recent head ded8b04. Consider uploading reports for the commit ded8b04 to get more accurate results

@@           Coverage Diff           @@
##           master     #356   +/-   ##
=======================================
  Coverage   95.33%   95.33%           
=======================================
  Files          50       50           
  Lines        3855     3860    +5     
=======================================
+ Hits         3675     3680    +5     
  Misses        180      180           

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• ❗🐌summarise_draws_100_variables: 706ms -> 715ms [+0.92%, +1.51%]

• ❗🐌summarise_draws_10_variables: 105ms -> 107ms [+0.93%, +2.1%]

Based on these ^

This is how benchmark results would change (along with a 95% confidence interval in relative change) if a28483f is merged into master:

•   :ballot_box_with_check:as_draws_array: 137ms -> 138ms [-0.57%, +1.33%]
• ❗🐌as_draws_df: 64.7ms -> 66.8ms [+1.45%, +5.05%]
•   :ballot_box_with_check:as_draws_list: 163ms -> 164ms [-0.39%, +2%]
• ❗🐌as_draws_matrix: 60.5ms -> 63.6ms [+3.63%, +6.84%]
•   :ballot_box_with_check:as_draws_rvars: 81.6ms -> 81.1ms [-1.61%, +0.46%]
• ❗🐌summarise_draws_100_variables: 709ms -> 719ms [+0.98%, +1.77%]
• ❗🐌summarise_draws_10_variables: 108ms -> 110ms [+0.75%, +2.83%]
  Further explanation regarding interpretation and methodology can be found in the documentation.

I've now added tests checking that the column types are as expected, and if the speed is ok, this is ready for review

FWIW, I think the unnesting / flattening might be doable as a cbind on row vectors (or maybe vec_cbind / vec_rbind for safety) to create a 1-row data frame. Dunno if that helps at all.

This is how benchmark results would change (along with a 95% confidence interval in relative change) if e175ba8 is merged into master:

•   :ballot_box_with_check:as_draws_array: 156ms -> 155ms [-1.35%, +0.57%]
•   :rocket:as_draws_df: 71.3ms -> 68.4ms [-5.59%, -2.54%]
•   :ballot_box_with_check:as_draws_list: 176ms -> 175ms [-1.7%, +0.47%]
•   :ballot_box_with_check:as_draws_matrix: 71ms -> 70.5ms [-1.68%, +0.53%]
•   :ballot_box_with_check:as_draws_rvars: 84ms -> 84.3ms [-0.89%, +1.65%]
• ❗🐌summarise_draws_100_variables: 724ms -> 733ms [+0.35%, +1.98%]
• ❗🐌summarise_draws_10_variables: 112ms -> 114ms [+1.05%, +2.91%]
  Further explanation regarding interpretation and methodology can be found in the documentation.

Speed is okay. Still, is this already the best way to implement the flattening?

unnesting / flattening might be doable as a cbind on row vectors (or maybe vec_cbind / vec_rbind for safety) to create a 1-row data frame.

Thanks for the tip! Simplifying this unnesting/flattening would, I think, be beneficial. However, I can't quite get the right structure with rbind or vec_rbind as the quantile2 column ends up with vectors of length 2 (as opposed to separate columns as in unlist). Looks like it would still need some kind of column splitting (e.g. tidyr::unnest_wider)

create_summary_list(example_draws(), 3, list(rhat = rhat_basic, quantile2 = quantile2), NULL) |>
   vec_rbind()

##       rhat            quantile2
## 1 1.014967 -1.231353, 18.874003

create_summary_list(example_draws(), 3, list(rhat = rhat_basic, quantile2 = quantile2), NULL) |>
   unlist()

##         rhat  quantile2.q5 quantile2.q95
##     1.014967     -1.231353     18.874003

Ah right... you might be able to use cbind if you conditionally transpose (or rbind) vectors of length > 1 to turn them into row vectors (not on a computer atm so I can't try it)

is this already the best way to implement the flattening

I don't think the issue is so critical that the fix is needed right away, so perhaps it's better to leave this open in case some other ideas come up (e.g. if @mjskay's method works out). However, I won't spend more time on this now