Hardhat quantiles

.Rbuildignore

@@ -19,4 +19,5 @@
 ^DEVELOPMENT\.md$
 ^doc$
 ^Meta$
-^.lintr$
+^.lintr$
+^.venv$

DESCRIPTION

@@ -2,12 +2,13 @@ Package: epipredict
 Title: Basic epidemiology forecasting methods
 Version: 0.1.0
 Authors@R: c(
-    person("Daniel", "McDonald", , "daniel@stat.ubc.ca", role = c("aut", "cre")),
+    person("Daniel J.", "McDonald", , "daniel@stat.ubc.ca", role = c("aut", "cre")),
     person("Ryan", "Tibshirani", , "ryantibs@cmu.edu", role = "aut"),
+    person("Dmitry", "Shemetov", email = "dshemeto@andrew.cmu.edu", role = "aut"),
+    person("David", "Weber", email = "davidweb@andrew.cmu.edu", role = "aut"),
+    person("CMU's Delphi Research Group", role = c("cph", "fnd")),
     person("Logan", "Brooks", role = "aut"),
     person("Rachel", "Lobay", role = "aut"),
-    person("Dmitry", "Shemetov", email = "dshemeto@andrew.cmu.edu", role = "ctb"),
-    person("David", "Weber", email = "davidweb@andrew.cmu.edu", role = "ctb"),
     person("Maggie", "Liu", role = "ctb"),
     person("Ken", "Mawer", role = "ctb"),
     person("Chloe", "You", role = "ctb"),
@@ -23,7 +24,7 @@ URL: https://github.com/cmu-delphi/epipredict/,
     https://cmu-delphi.github.io/epipredict
 BugReports: https://github.com/cmu-delphi/epipredict/issues/
 Depends:
-    epiprocess (>= 0.7.12),
+    epiprocess (>= 0.9.0),
     parsnip (>= 1.0.0),
     R (>= 3.5.0)
 Imports:
@@ -34,10 +35,11 @@ Imports:
     generics,
     ggplot2,
     glue,
-    hardhat (>= 1.3.0),
+    hardhat (>= 1.4.0.9002),
+    lifecycle,
     magrittr,
     recipes (>= 1.0.4),
-    rlang (>= 1.0.0),
+    rlang (>= 1.1.0),
     stats,
     tibble,
     tidyr,
@@ -68,7 +70,8 @@ VignetteBuilder:
 Remotes:
     cmu-delphi/epidatr,
     cmu-delphi/epiprocess,
-    dajmcdon/smoothqr
+    dajmcdon/smoothqr,
+    tidymodels/hardhat
 Config/testthat/edition: 3
 Encoding: UTF-8
 LazyData: true

NAMESPACE

@@ -2,8 +2,6 @@
 
 S3method(Add_model,epi_workflow)
 S3method(Add_model,workflow)
-S3method(Math,dist_quantiles)
-S3method(Ops,dist_quantiles)
 S3method(Remove_model,epi_workflow)
 S3method(Remove_model,workflow)
 S3method(Update_model,epi_workflow)
@@ -38,20 +36,14 @@ S3method(extract_frosting,default)
 S3method(extract_frosting,epi_workflow)
 S3method(extract_layers,frosting)
 S3method(extract_layers,workflow)
-S3method(extrapolate_quantiles,dist_default)
-S3method(extrapolate_quantiles,dist_quantiles)
-S3method(extrapolate_quantiles,distribution)
+S3method(extrapolate_quantiles,quantile_pred)
 S3method(fit,epi_workflow)
 S3method(flusight_hub_formatter,canned_epipred)
 S3method(flusight_hub_formatter,data.frame)
 S3method(forecast,epi_workflow)
-S3method(format,dist_quantiles)
-S3method(is.na,dist_quantiles)
-S3method(is.na,distribution)
 S3method(key_colnames,epi_workflow)
 S3method(key_colnames,recipe)
-S3method(mean,dist_quantiles)
-S3method(median,dist_quantiles)
+S3method(mean,quantile_pred)
 S3method(predict,epi_workflow)
 S3method(predict,flatline)
 S3method(prep,check_enough_train_data)
@@ -93,7 +85,7 @@ S3method(print,step_lag_difference)
 S3method(print,step_naomit)
 S3method(print,step_population_scaling)
 S3method(print,step_training_window)
-S3method(quantile,dist_quantiles)
+S3method(quantile,quantile_pred)
 S3method(recipe,epi_df)
 S3method(recipes::recipe,formula)
 S3method(refresh_blueprint,default_epi_recipe_blueprint)
@@ -112,19 +104,17 @@ S3method(slather,layer_residual_quantiles)
 S3method(slather,layer_threshold)
 S3method(slather,layer_unnest)
 S3method(snap,default)
-S3method(snap,dist_default)
-S3method(snap,dist_quantiles)
-S3method(snap,distribution)
+S3method(snap,quantile_pred)
 S3method(tidy,check_enough_train_data)
 S3method(tidy,frosting)
 S3method(tidy,layer)
 S3method(update,layer)
-S3method(vec_ptype_abbr,dist_quantiles)
-S3method(vec_ptype_full,dist_quantiles)
+S3method(vec_arith,quantile_pred)
+S3method(vec_arith.numeric,quantile_pred)
+S3method(vec_arith.quantile_pred,numeric)
+S3method(vec_math,quantile_pred)
 S3method(weighted_interval_score,default)
-S3method(weighted_interval_score,dist_default)
-S3method(weighted_interval_score,dist_quantiles)
-S3method(weighted_interval_score,distribution)
+S3method(weighted_interval_score,quantile_pred)
 export("%>%")
 export(Add_model)
 export(Remove_model)
@@ -142,6 +132,7 @@ export(arx_class_epi_workflow)
 export(arx_classifier)
 export(arx_fcast_epi_workflow)
 export(arx_forecaster)
+export(as_tibble)
 export(autoplot)
 export(bake)
 export(cdc_baseline_args_list)
@@ -150,7 +141,6 @@ export(check_enough_train_data)
 export(clean_f_name)
 export(default_epi_recipe_blueprint)
 export(detect_layer)
-export(dist_quantiles)
 export(epi_recipe)
 export(epi_workflow)
 export(extract_argument)
@@ -181,10 +171,10 @@ export(layer_quantile_distn)
 export(layer_residual_quantiles)
 export(layer_threshold)
 export(layer_unnest)
-export(nested_quantiles)
 export(pivot_quantiles_longer)
 export(pivot_quantiles_wider)
 export(prep)
+export(quantile_pred)
 export(quantile_reg)
 export(rand_id)
 export(recipe)
@@ -208,22 +198,18 @@ export(update_frosting)
 export(update_model)
 export(validate_layer)
 export(weighted_interval_score)
-import(distributional)
 import(epiprocess)
 import(parsnip)
 import(recipes)
-importFrom(checkmate,assert)
-importFrom(checkmate,assert_character)
 importFrom(checkmate,assert_class)
-importFrom(checkmate,assert_date)
-importFrom(checkmate,assert_function)
-importFrom(checkmate,assert_int)
-importFrom(checkmate,assert_integer)
-importFrom(checkmate,assert_integerish)
-importFrom(checkmate,assert_logical)
-importFrom(checkmate,assert_number)
 importFrom(checkmate,assert_numeric)
-importFrom(checkmate,assert_scalar)
+importFrom(checkmate,test_character)
+importFrom(checkmate,test_date)
+importFrom(checkmate,test_function)
+importFrom(checkmate,test_integerish)
+importFrom(checkmate,test_logical)
+importFrom(checkmate,test_numeric)
+importFrom(checkmate,test_scalar)
 importFrom(cli,cli_abort)
 importFrom(cli,cli_warn)
 importFrom(dplyr,across)
@@ -256,6 +242,7 @@ importFrom(ggplot2,geom_line)
 importFrom(ggplot2,geom_linerange)
 importFrom(ggplot2,geom_point)
 importFrom(ggplot2,geom_ribbon)
+importFrom(hardhat,quantile_pred)
 importFrom(hardhat,refresh_blueprint)
 importFrom(hardhat,run_mold)
 importFrom(magrittr,"%>%")
@@ -271,6 +258,7 @@ importFrom(rlang,":=")
 importFrom(rlang,abort)
 importFrom(rlang,arg_match)
 importFrom(rlang,as_function)
+importFrom(rlang,caller_arg)
 importFrom(rlang,caller_env)
 importFrom(rlang,enquo)
 importFrom(rlang,enquos)
@@ -283,24 +271,15 @@ importFrom(rlang,is_true)
 importFrom(rlang,set_names)
 importFrom(rlang,sym)
 importFrom(stats,as.formula)
-importFrom(stats,family)
 importFrom(stats,lm)
-importFrom(stats,median)
 importFrom(stats,model.frame)
 importFrom(stats,poly)
 importFrom(stats,predict)
-importFrom(stats,qnorm)
 importFrom(stats,quantile)
 importFrom(stats,residuals)
 importFrom(tibble,as_tibble)
 importFrom(tibble,tibble)
 importFrom(tidyr,crossing)
-importFrom(vctrs,as_list_of)
-importFrom(vctrs,field)
-importFrom(vctrs,new_rcrd)
-importFrom(vctrs,new_vctr)
-importFrom(vctrs,vec_cast)
-importFrom(vctrs,vec_data)
-importFrom(vctrs,vec_ptype_abbr)
-importFrom(vctrs,vec_ptype_full)
-importFrom(vctrs,vec_recycle_common)
+importFrom(vctrs,vec_arith)
+importFrom(vctrs,vec_arith.numeric)
+importFrom(vctrs,vec_math)

NEWS.md

@@ -57,3 +57,7 @@ Pre-1.0.0 numbering scheme: 0.x will indicate releases, while 0.0.x will indicat
 - Add `step_epi_slide` to produce generic sliding computations over an `epi_df`
 - Add quantile random forests (via `{grf}`) as a parsnip engine
 - Replace `epi_keys()` with `epiprocess::key_colnames()`, #352
+- More descriptive error messages from `arg_is_*()`, #287
+- Fix bug where `fit()` drops the `epi_workflow` class (also error if
+  non-`epi_df` data is given to `epi_recipe()`), #363
+- Try to retain the `epi_df` class during baking to the extent possible, #376

R/autoplot.R

@@ -131,7 +131,7 @@ autoplot.epi_workflow <- function(
   if (length(extra_keys) == 0L) extra_keys <- NULL
   edf <- as_epi_df(edf,
     as_of = object$fit$meta$as_of,
-    additional_metadata = list(other_keys = extra_keys)
+    other_keys = extra_keys %||% character()
   )
   if (is.null(predictions)) {
     return(autoplot(
@@ -248,7 +248,7 @@ plot_bands <- function(
   ntarget_dates <- dplyr::n_distinct(predictions$time_value)
 
   predictions <- predictions %>%
-    mutate(.pred_distn = dist_quantiles(quantile(.pred_distn, l), l)) %>%
+    mutate(.pred_distn = quantile_pred(quantile(.pred_distn, l), l)) %>%
     pivot_quantiles_wider(.pred_distn)
   qnames <- setdiff(names(predictions), innames)
 

R/cdc_baseline_forecaster.R

@@ -29,11 +29,11 @@
 #'   mutate(deaths = pmax(death_rate / 1e5 * pop * 7, 0)) %>%
 #'   select(-pop, -death_rate) %>%
 #'   group_by(geo_value) %>%
-#'   epi_slide(~ sum(.$deaths), before = 6, new_col_name = "deaths") %>%
+#'   epi_slide(~ sum(.$deaths), .window_size = 7, .new_col_name = "deaths_7dsum") %>%
 #'   ungroup() %>%
 #'   filter(weekdays(time_value) == "Saturday")
 #'
-#' cdc <- cdc_baseline_forecaster(weekly_deaths, "deaths")
+#' cdc <- cdc_baseline_forecaster(weekly_deaths, "deaths_7dsum")
 #' preds <- pivot_quantiles_wider(cdc$predictions, .pred_distn)
 #'
 #' library(ggplot2)