Merge pull request #88 from cmu-delphi/add-distn

Add distn

Author: dajmcdon

DESCRIPTION

@@ -15,40 +15,39 @@ Depends:
 Imports: 
     assertthat,
     cli,
+    distributional,
     dplyr,
     epiprocess,
     fs,
     generics,
     glue,
-    hardhat (>= 1.1.0.9000),
+    hardhat (>= 1.2.0),
     magrittr,
     purrr,
-    recipes (>= 0.2.0.9001),
+    recipes (>= 1.0.0),
     rlang,
     stats,
     tensr,
     tibble,
     tidyr,
     tidyselect,
     usethis,
+    vctrs,
     workflows
 Suggests: 
     covidcast,
     data.table,
     ggplot2,
     knitr,
     lubridate,
-    parsnip (>= 0.2.1.9001),
+    parsnip (>= 1.0.0),
     RcppRoll,
     rmarkdown,
     testthat (>= 3.0.0)
 VignetteBuilder: 
     knitr
 Remotes:
-    dajmcdon/epiprocess,
-    tidymodels/hardhat,
-    tidymodels/parsnip,
-    tidymodels/recipes
+    dajmcdon/epiprocess
 Config/testthat/edition: 3
 Encoding: UTF-8
 Roxygen: list(markdown = TRUE)

NAMESPACE

@@ -1,5 +1,7 @@
 # Generated by roxygen2: do not edit by hand
 
+S3method(Math,dist_quantiles)
+S3method(Ops,dist_quantiles)
 S3method(apply_frosting,default)
 S3method(apply_frosting,epi_workflow)
 S3method(augment,epi_workflow)
@@ -20,6 +22,11 @@ S3method(extract_argument,recipe)
 S3method(extract_argument,step)
 S3method(extract_layers,frosting)
 S3method(extract_layers,workflow)
+S3method(extrapolate_quantiles,dist_default)
+S3method(extrapolate_quantiles,dist_quantiles)
+S3method(extrapolate_quantiles,distribution)
+S3method(format,dist_quantiles)
+S3method(median,dist_quantiles)
 S3method(predict,epi_workflow)
 S3method(prep,epi_recipe)
 S3method(prep,step_epi_ahead)
@@ -28,12 +35,20 @@ S3method(print,epi_workflow)
 S3method(print,frosting)
 S3method(print,step_epi_ahead)
 S3method(print,step_epi_lag)
+S3method(quantile,dist_quantiles)
 S3method(refresh_blueprint,default_epi_recipe_blueprint)
 S3method(run_mold,default_epi_recipe_blueprint)
 S3method(slather,layer_naomit)
 S3method(slather,layer_predict)
-S3method(slather,layer_residual_quantile)
+S3method(slather,layer_predictive_distn)
+S3method(slather,layer_residual_quantiles)
 S3method(slather,layer_threshold)
+S3method(snap,default)
+S3method(snap,dist_default)
+S3method(snap,dist_quantiles)
+S3method(snap,distribution)
+S3method(vec_ptype_abbr,dist_quantiles)
+S3method(vec_ptype_full,dist_quantiles)
 export("%>%")
 export(add_epi_recipe)
 export(add_frosting)
@@ -46,12 +61,14 @@ export(create_layer)
 export(default_epi_recipe_blueprint)
 export(detect_layer)
 export(df_mat_mul)
+export(dist_quantiles)
 export(epi_keys)
 export(epi_recipe)
 export(epi_recipe_blueprint)
 export(epi_workflow)
 export(extract_argument)
 export(extract_layers)
+export(extrapolate_quantiles)
 export(frosting)
 export(get_precision)
 export(get_test_data)
@@ -66,8 +83,10 @@ export(knnarx_forecaster)
 export(layer)
 export(layer_naomit)
 export(layer_predict)
-export(layer_residual_quantile)
+export(layer_predictive_distn)
+export(layer_residual_quantiles)
 export(layer_threshold)
+export(nested_quantiles)
 export(new_default_epi_recipe_blueprint)
 export(new_epi_recipe_blueprint)
 export(remove_frosting)
@@ -78,7 +97,9 @@ export(step_epi_ahead)
 export(step_epi_lag)
 export(step_epi_naomit)
 export(validate_layer)
+import(distributional)
 import(recipes)
+import(vctrs)
 importFrom(generics,augment)
 importFrom(generics,fit)
 importFrom(hardhat,refresh_blueprint)
@@ -91,10 +112,13 @@ importFrom(rlang,abort)
 importFrom(rlang,caller_env)
 importFrom(rlang,is_null)
 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(stats,setNames)

R/arx_forecaster_mod.R

@@ -0,0 +1,29 @@
+arx_epi_forecaster <- function(epi_data, response,
+                               ...,
+                               trainer = parsnip::linear_reg(),
+                               args_list = arx_args_list()) {
+
+  r <- epi_recipe(epi_data) %>%
+    step_epi_lag(..., lag = args_list$lags) %>% # hmmm, same for all predictors
+    step_epi_ahead(response, ahead = args_list$ahead) %>%
+  # should use the internal function (in an open PR)
+    recipes::step_naomit(recipes::all_predictors()) %>%
+    recipes::step_naomit(recipes::all_outcomes(), skip = TRUE)
+  # should limit the training window here (in an open PR)
+  # What to do if insufficient training data? Add issue.
+  # remove intercept? not sure how this is implemented in tidymodels
+  f <- frosting() %>%
+    layer_predict() %>%
+    layer_naomit(.pred) %>%
+    layer_residual_quantile(
+      probs = args_list$levels,
+      symmetrize = args_list$symmetrize) %>%
+    layer_threshold(.pred, dplyr::starts_with("q")) #, .flag = args_list$nonneg) in open PR
+  # need the target date processing here
+
+  latest <- get_test_data(r, epi_data)
+
+  epi_workflow(r, trainer) %>% # bug, issue 72
+    add_frosting(f)
+
+}

R/compat-purrr.R

@@ -2,7 +2,7 @@
 
 
 map <- function(.x, .f, ...) {
-  .f <- rlang::as_function(.f, env = global_env())
+  .f <- rlang::as_function(.f, env = rlang::global_env())
   lapply(.x, .f, ...)
 }
 walk <- function(.x, .f, ...) {
@@ -23,7 +23,7 @@ map_chr <- function(.x, .f, ...) {
   .rlang_purrr_map_mold(.x, .f, character(1), ...)
 }
 .rlang_purrr_map_mold <- function(.x, .f, .mold, ...) {
-  .f <- rlang::as_function(.f, env = global_env())
+  .f <- rlang::as_function(.f, env = rlang::global_env())
   out <- vapply(.x, .f, .mold, ..., USE.NAMES = FALSE)
   names(out) <- names(.x)
   out
@@ -41,12 +41,12 @@ map_chr <- function(.x, .f, ...) {
 }
 
 map2 <- function(.x, .y, .f, ...) {
-  .f <- as_function(.f, env = global_env())
+  .f <- rlang::as_function(.f, env = rlang::global_env())
   out <- mapply(.f, .x, .y, MoreArgs = list(...), SIMPLIFY = FALSE)
   if (length(out) == length(.x)) {
-    set_names(out, names(.x))
+    rlang::set_names(out, names(.x))
   } else {
-    set_names(out, NULL)
+    rlang::set_names(out, NULL)
   }
 }
 map2_lgl <- function(.x, .y, .f, ...) {