Simplify&flatten epi_slide data mask implementation

and add some unrelated comments regarding time value counting details.

Since we're not potentially dealing with R6 objects, we can just us
`as_data_mask(.x)`. We can also flatten the data mask by installing the `.x`,
`.group_key` and `.ref_time_value` in the same way as that pronouns are
installed (except keeping their original classes, not converting to pronouns),
rather than using another level in the environment chain for the data mask.

Author: brookslogan

R/slide.R

@@ -299,7 +299,9 @@ epi_slide = function(x, f, ..., before, after, ref_time_values,
     o = .data_group$time_value %in% time_values
     num_ref_rows = sum(o)
 
-    # Count the number of appearances of each reference time value
+    # 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$time_value %in% time_values) %>%
       dplyr::count(.data$time_value) %>%
@@ -386,14 +388,12 @@ epi_slide = function(x, f, ..., before, after, ref_time_values,
       .ref_time_value = min(.x$time_value) + before
       .x <- .x[.x$.real,]
       .x$.real <- NULL
-      data_parent_env = rlang::as_environment(.x)
-      data_env = env(data_parent_env,
-                     .x = .x, .group_key = .group_key,
-                     .ref_time_value = .ref_time_value)
-      # `as_data_mask()` appears to strip off ancestors. We'll need to
-      # do some more work with `new_data_mask()`:
-      data_mask = rlang::new_data_mask(data_env, top = data_parent_env)
-      data_mask$.data <- rlang::as_data_pronoun(.x)
+      data_mask = rlang::as_data_mask(.x)
+      # We'll also install `.x` directly, not as an `rlang_data_pronoun`, so
+      # that we can, e.g., use more dplyr and epiprocess operations.
+      data_mask$.x = .x
+      data_mask$.group_key = .group_key
+      data_mask$.ref_time_value = .ref_time_value
       rlang::eval_tidy(quo, data_mask)
     }
     new_col = sym(names(rlang::quos_auto_name(quos)))