Speedups for epix_slide

NAMESPACE

@@ -66,7 +66,9 @@ importFrom(data.table,as.data.table)
 importFrom(data.table,between)
 importFrom(data.table,copy)
 importFrom(data.table,key)
+importFrom(data.table,rbindlist)
 importFrom(data.table,set)
+importFrom(data.table,setDF)
 importFrom(data.table,setkeyv)
 importFrom(dplyr,arrange)
 importFrom(dplyr,bind_rows)
@@ -114,6 +116,8 @@ importFrom(rlang,syms)
 importFrom(stats,cor)
 importFrom(stats,median)
 importFrom(tibble,as_tibble)
+importFrom(tibble,new_tibble)
+importFrom(tibble,validate_tibble)
 importFrom(tidyr,unnest)
 importFrom(tidyselect,eval_select)
 importFrom(tidyselect,starts_with)

R/archive.R

@@ -495,7 +495,10 @@ epi_archive =
                         version <= max_version, ] %>%
               unique(by = c("geo_value", "time_value", other_keys),
                      fromLast = TRUE) %>%
-              tibble::as_tibble() %>% 
+              tibble::as_tibble() %>%
+              # (`as_tibble` should de-alias the DT and its columns in any edge
+              # cases where they are aliased. We don't say we guarantee this
+              # though.)
               dplyr::select(-"version") %>%
               as_epi_df(geo_type = self$geo_type,
                         time_type = self$time_type,

R/epi_df.R

@@ -159,7 +159,13 @@ new_epi_df = function(x = tibble::tibble(), geo_type, time_type, as_of,
 
   # Reorder columns (geo_value, time_value, ...)
   if(sum(dim(x)) != 0){
-    x = dplyr::relocate(x, "geo_value", "time_value")
+    cols_to_put_first <- c("geo_value", "time_value")
+    x <- x[, c(
+      cols_to_put_first,
+      # All other columns
+      names(x)[!(names(x) %in% cols_to_put_first)]
+      )
+    ]
   }
 
   # Apply epi_df class, attach metadata, and return

R/grouped_epi_archive.R

@@ -185,7 +185,9 @@ grouped_epi_archive =
 #' @description Slides a given function over variables in a `grouped_epi_archive`
 #'   object. See the documentation for the wrapper function [`epix_slide()`] for
 #'   details.
-#' @importFrom data.table key address
+#' @importFrom data.table key address rbindlist setDF
+#' @importFrom tibble as_tibble new_tibble validate_tibble
+#' @importFrom dplyr group_by groups
 #' @importFrom rlang !! !!! enquo quo_is_missing enquos is_quosure sym syms
 #'  env missing_arg
           slide = function(f, ..., before, ref_time_values,
@@ -280,16 +282,19 @@ grouped_epi_archive =
               if (! (is.atomic(comp_value) || is.data.frame(comp_value))) {
                 Abort("The slide computation must return an atomic vector or a data frame.")
               }
+
+              # Label every result row with the `ref_time_value`
+              res <- list(time_value = ref_time_value)
+
               # Wrap the computation output in a list and unchop/unnest later if
               # `as_list_col = FALSE`. This approach means that we will get a
               # list-class col rather than a data.frame-class col when
               # `as_list_col = TRUE` and the computations outputs are data
               # frames.
-              comp_value <- list(comp_value)
-
-              # Label every result row with the `ref_time_value`:
-              return(tibble::tibble(time_value = .env$ref_time_value,
-                                    !!new_col := .env$comp_value))
+              res[[new_col]] <- list(comp_value)
+
+              # Convert the list to a tibble all at once for speed.
+              return(validate_tibble(new_tibble(res)))
             }
 
             # If `f` is missing, interpret ... as an expression for tidy evaluation
@@ -308,7 +313,7 @@ grouped_epi_archive =
             }
 
             f = as_slide_computation(f, ...)
-            x = purrr::map_dfr(ref_time_values, function(ref_time_value) {
+            x = lapply(ref_time_values, function(ref_time_value) {
               # Ungrouped as-of data; `epi_df` if `all_versions` is `FALSE`,
               # `epi_archive` if `all_versions` is `TRUE`:
               as_of_raw = private$ungrouped$as_of(ref_time_value, min_time_value = ref_time_value - before, all_versions = all_versions)
@@ -331,6 +336,13 @@ grouped_epi_archive =
                 # copies.
                 if (address(as_of_archive$DT) == address(private$ungrouped$DT)) {
                   # `as_of` aliased its the full `$DT`; copy before mutating:
+                  #
+                  # Note: this step is probably unneeded; we're fine with
+                  # aliasing of the DT or its columns: vanilla operations aren't
+                  # going to mutate them in-place if they are aliases, and we're
+                  # not performing mutation (unlike the situation with
+                  # `fill_through_version` where we do mutate a `DT` and don't
+                  # want aliasing).
                   as_of_archive$DT <- copy(as_of_archive$DT)
                 }
                 dt_key = data.table::key(as_of_archive$DT)
@@ -357,15 +369,20 @@ grouped_epi_archive =
               }
 
               return(
-                dplyr::group_by(as_of_df, dplyr::across(tidyselect::all_of(private$vars)),
-                                .drop=private$drop) %>%
-                  dplyr::group_modify(group_modify_fn,
-                                      f = f, ...,
-                                      ref_time_value = ref_time_value,
-                                      new_col = new_col,
-                                      .keep = TRUE)
+                  dplyr::group_modify(
+                    dplyr::group_by(as_of_df, !!!syms(private$vars), .drop=private$drop),
+                    group_modify_fn,
+                    f = f, ...,
+                    ref_time_value = ref_time_value,
+                    new_col = new_col,
+                    .keep = TRUE
+                  )
               )
             })
+            # Combine output into a single tibble
+            x <- as_tibble(setDF(rbindlist(x)))
+            # Reconstruct groups
+            x <- group_by(x, !!!syms(private$vars), .drop=private$drop)
 
             # Unchop/unnest if we need to
             if (!as_list_col) {

R/methods-epi_archive.R

@@ -32,13 +32,18 @@
 #'   x$as_of(max_version = v)
 #'   ```
 #'
-#' @export
+#' Mutation and aliasing: `epix_as_of` and `$as_of` will not mutate the input
+#' archives, but may in some edge cases alias parts of the inputs, so copy the
+#' outputs if needed before using mutating operations like `data.table`'s `:=`
+#' operator. Currently, the only situation where there is potentially aliasing
+#' is of the `DT` in edge cases with `all_versions = TRUE`, but this may change
+#' in the future.
+#'
 #' @examples
 #' # warning message of data latency shown
 #' epix_as_of(x = archive_cases_dv_subset,
 #'            max_version = max(archive_cases_dv_subset$DT$version))
 #' 
-#' @export 
 #' @examples
 #'
 #' range(archive_cases_dv_subset$DT$version) # 2020-06-02 -- 2021-12-01
@@ -60,6 +65,8 @@
 #' }, epiprocess__snapshot_as_of_clobberable_version = function(wrn) invokeRestart("muffleWarning"))
 #' # Since R 4.0, there is a `globalCallingHandlers` function that can be used
 #' # to globally toggle these warnings.
+#'
+#' @export
 epix_as_of = function(x, max_version, min_time_value = -Inf, all_versions = FALSE) {
   if (!inherits(x, "epi_archive")) Abort("`x` must be of class `epi_archive`.")
   return(x$as_of(max_version, min_time_value, all_versions = all_versions))
@@ -798,6 +805,14 @@ group_by.epi_archive = function(.data, ..., .add=FALSE, .drop=dplyr::group_by_dr
 #'   x$slide(new_var = comp(old_var), before = 119)
 #'   ```
 #'
+#' Mutation and aliasing: `epix_slide` and `$slide` will not perform in-place
+#' mutation of the input archives on their own. In some edge cases the inputs it
+#' feeds to the slide computations may alias parts of the input archive, so copy
+#' the slide computation inputs if needed before using mutating operations like
+#' `data.table`'s `:=` operator. Similarly, in some edge cases, the output of
+#' the slide operation may alias parts of the input archive, so similarly, make
+#' sure to clone and/or copy appropriately before using in-place mutation.
+#'
 #' @examples
 #' library(dplyr)
 #'

R/slide.R

@@ -300,8 +300,7 @@ epi_slide = function(x, f, ..., before, after, ref_time_values,
     # Count the number of appearances of each reference time value (these
     # appearances should all be real for now, but if we allow ref time values
     # outside of .data_group's time values):
-    counts = .data_group %>%
-      dplyr::filter(.data$time_value %in% time_values) %>%
+    counts =  dplyr::filter(.data_group, .data$time_value %in% time_values) %>%
       dplyr::count(.data$time_value) %>%
       dplyr::pull(n)
 
@@ -375,8 +374,7 @@ epi_slide = function(x, f, ..., before, after, ref_time_values,
     .x$.real <- NULL
     f(.x, .group_key, .ref_time_value, ...)
   }
-  x = x %>%
-    group_modify(slide_one_grp,
+  x = group_modify(x, slide_one_grp,
                  f = f_wrapper, ...,
                  starts = starts,
                  stops = stops,