Update f documentation in epi_slide

.Rbuildignore

@@ -8,3 +8,5 @@
 ^data-raw$
 ^_pkgdown\.yml$
 ^pkgdown$
+^doc$
+^Meta$

.gitignore

@@ -5,3 +5,6 @@
 *.Rproj
 inst/doc
 docs
+/doc/
+/Meta/
+*.DS_Store

NAMESPACE

@@ -1,5 +1,6 @@
 # Generated by roxygen2: do not edit by hand
 
+S3method("[",epi_df)
 S3method(arrange,epi_df)
 S3method(as_epi_df,data.frame)
 S3method(as_epi_df,epi_df)
@@ -79,5 +80,3 @@ importFrom(tidyr,unnest)
 importFrom(tidyselect,eval_select)
 importFrom(tidyselect,starts_with)
 importFrom(tsibble,as_tsibble)
-importFrom(utils,head)
-importFrom(utils,tail)

R/methods-epi_df.R

@@ -99,19 +99,14 @@ summary.epi_df = function(object, ...) {
 
   cn <- names(res)
   nr <- vctrs::vec_size(x) 
-  not_epi_df <- (!("time_value" %in% cn) || !("geo_value" %in% cn)
-                 || vctrs::vec_size(res) > nr || any(i > nr))
+  not_epi_df <- (!("time_value" %in% cn) || !("geo_value" %in% cn) || vctrs::vec_size(res) > nr || any(i > nr))
 
   if (not_epi_df) return(tibble::as_tibble(res))
 
   # Case when i is numeric and there are duplicate values in it
   if (is.numeric(i) && vctrs::vec_duplicate_any(i) > 0) 
     return(tibble::as_tibble(res))
 
-  # Column subsetting only, then return res as tibble
-  if (rlang::is_null(i) && !rlang::is_null(j)) 
-    return(tibble::as_tibble(res))
-
   att_x = attr(x, "metadata")
   new_epi_df(tibble::as_tibble(res), 
              geo_type = att_x$geo_type, 

R/slide.R

@@ -8,11 +8,14 @@
 #' @param f Function or formula to slide over variables in `x`. To "slide" means
 #'   to apply a function or formula over a running window of `n` time steps
 #'   (where one time step is typically one day or one week; see details for more
-#'   explanation). If a function, `f` must take `x`, a data frame with the same
-#'   column names as the original object; followed by any number of named
-#'   arguments; and ending with `...`. If a formula, `f` can operate directly on
-#'   columns accessed via `.x$var`, as in `~ mean(.x$var)` to compute a mean of
-#'   a column `var` over a sliding window of `n` time steps.
+#'   explanation). If a function, `f` should take `x`, an `epi_df` with the same 
+#'   names as the non-grouping columns, followed by `g` to refer to the one row 
+#'   tibble with one column per grouping variable that identifies the group, 
+#'   and any number of named arguments (which will be taken from `...`). If a 
+#'   formula, `f` can operate directly on columns accessed via `.x$var`, as 
+#'   in `~ mean(.x$var)` to compute a mean of a column var over a sliding 
+#'   window of n time steps. As well, `.y` may be used in the formula to refer 
+#'   to the groupings that would be described by `g` if `f` was a function.
 #' @param ... Additional arguments to pass to the function or formula specified
 #'   via `f`. Alternatively, if `f` is missing, then the current argument is
 #'   interpreted as an expression for tidy evaluation. See details.  
@@ -85,26 +88,6 @@
 #'   inferred from the given expression and overrides any name passed explicitly 
 #'   through the `new_col_name` argument.
 #'   
-#' When `f` is a named function with arguments, if a tibble with an unnamed 
-#'   grouping variable is passed in as the method argument to `f`, include a 
-#'   parameter for the grouping-variable in `function()` just prior to 
-#'   specifying the method to prevent that from being overridden. For example:
-#'   ```
-#'   # Construct an tibble with an unnamed grouping variable
-#'   edf = bind_rows(tibble(geo_value = "ak", time_value = as.Date("2020-01-01") 
-#'             + 1:10, x1=1:10, y=1:10 + rnorm(10L))) %>% 
-#'     as_epi_df()
-#'   
-#'   # Now, include a row parameter for the grouping variable in the tibble, 
-#'   # which we denote as g, just prior to method = "qr"
-#'   # Note that if g was not included below, then the method = "qr" would be 
-#'   # overridden, as described above
-#'   edf %>%
-#'   group_by(geo_value) %>%
-#'   epi_slide(function(x, g, method="qr", ...) tibble(model=list(
-#'             lm(y ~ x1, x, method=method))), n=7L) 
-#'   ```
-#'   
 #' @importFrom lubridate days weeks
 #' @importFrom rlang .data .env !! enquo enquos sym
 #' @export

tests/testthat/test-epi_slide.R

@@ -27,8 +27,8 @@ test_that("`ref_time_values` + `align` that have some slide data, but generate t
 test_that("these doesn't produce an error; the error appears only if the ref time values are out of the range for every group", {
   expect_identical(edf %>% group_by(geo_value) %>% epi_slide(f, n=3L, ref_time_values=as.Date("2020-01-01")+200L) %>% 
                      dplyr::select("geo_value","slide_value_value"), 
-                   dplyr::tibble(geo_value = "ak", slide_value_value = 199) %>% group_by(geo_value)) # out of range for one group
+                   dplyr::tibble(geo_value = "ak", slide_value_value = 199)) # out of range for one group
   expect_identical(edf %>% group_by(geo_value) %>% epi_slide(f, n=3L, ref_time_values=as.Date("2020-01-04")) %>% 
                      dplyr::select("geo_value","slide_value_value"), 
-                   dplyr::tibble(geo_value = c("ak", "al"), slide_value_value = c(2, -2)) %>% group_by(geo_value)) # not out of range for either group
+                   dplyr::tibble(geo_value = c("ak", "al"), slide_value_value = c(2, -2))) # not out of range for either group
 })