Quantile predictions output constructor #1191
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Merge branch 'quantile-mode' of https://github.com/dajmcdon/parsnip into quantile-mode # Conflicts: # R/predict.R
…nto quantile-mode
Co-authored-by: Simon P. Couch <[email protected]>
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@simonpcouch Thanks! |
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Can we call it |
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Thanks for making this
Nope, I'm good with using this class! |
Co-authored-by: Max Kuhn <[email protected]>
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One other small thing... let's remove row and column names from |
| expect_s3_class(one_quant_pred$.pred_quantile[[1]], c("tbl_df", "tbl", "data.frame")) | ||
| expect_named(one_quant_pred$.pred_quantile[[1]], c(".pred_quantile", ".quantile_level")) | ||
| expect_true(nrow(one_quant_pred$.pred_quantile[[1]]) == 1L) | ||
| expect_s3_class( |
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testthat has expect_vector() specifically for testing vctrs vectors, that seems relevant here.
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The output is a vector but the prototype for expect_vector() has matrix and vector inputs whose sizes must match and cannot be zero. It's not very straightforward to do that; It's a quare peg in a round hole. I think that the complexity there is not really worth it.
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@dajmcdon Merge time! One note... after looking into performance metrics, we realized that For these cases, we move infrastructure to hardhat (which everyone depends on at some level). After I merge this, I’ll PR into hardhat to put the functions there, and then PR to parsnip to remove them. |
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@topepo
quantile_levels).rq()predictions (1 or moretau/quantile_levels).I added a test for the constructor and adjusted your tests for the
quantregengine.Don't hesitate to ask for more changes! Or we can revisit if you'd really prefer the tibble list-col version.