Replacement of vars() with quos()

R/assertions.R

@@ -100,7 +100,7 @@ assert_inherits_class <- function(x, should_have) {
 #' Assert that variables not passed as strings are present in target dataset
 #'
 #' @param quo_list A variable that can be a string, variable, or combination of
-#' those using dplyr::vars
+#' those using rlang::quos
 #' @param vnames Variable names of the target dataset to check against
 #' @param envir Environment containing the dataset \code{target} from which names will be checked against
 #' @param allow_character Whether or not character strings are allows in an entry
@@ -114,10 +114,10 @@ assert_quo_var_present <- function(quo_list, vnames=NULL, envir=NULL, allow_char
 
  if (allow_character) {
  allow <- c('name', 'character')
- allow_str <- "`. Submit either a string, a variable name, or multiple variable names using `dplyr::vars`."
+ allow_str <- "`. Submit either a string, a variable name, or multiple variable names using `rlang::quos`."
  } else {
  allow <- "name"
- allow_str <- "`. Submit either a variable name or multiple variable names using `dplyr::vars`."
+ allow_str <- "`. Submit either a variable name or multiple variable names using `rlang::quos`."
  }
 
  # Global definition warning
@@ -155,7 +155,7 @@ assert_quo_var_present <- function(quo_list, vnames=NULL, envir=NULL, allow_char
 #' Assert that an argument is passed using vars as appropriate
 #'
 #' @param quo_list A variable that can be a string, variable, or combination of
-#' those using dplyr::vars
+#' those using rlang::quos
 #' @param allow_character Whether or not character strings are allows in an entry
 #'
 #' @return Unpacked quosure.
@@ -169,20 +169,20 @@ unpack_vars <- function(quo_list, allow_character=TRUE) {
  param <- enexpr(quo_list)
 
  if (allow_character) {
- allow_str <- "`. Submit either a string, a variable name, or multiple variable names using `dplyr::vars`."
+ allow_str <- "`. Submit either a string, a variable name, or multiple variable names using `rlang::quos`."
  } else {
- allow_str <- "`. Submit either a variable name or multiple variable names using `dplyr::vars`."
+ allow_str <- "`. Submit either a variable name or multiple variable names using `rlang::quos`."
  }
 
  # Unpack the `quo_list` group to ensure that the type is `list_of<quosures>`
  # It had to be a 1 item list, so check if that element is a `call`
- # The only valid use of a `call` is to provide multiple variables using `vars`
+ # The only valid use of a `call` is to provide multiple variables using `quos`
  c <- quo_get_expr(quo_list[[1]])
  if (is.call(c)) {
  # If it's a call, we need to pull it out a level
  quo_list <- tryCatch({
- # If it's in here, the call has to be to dplyr::vars
- if (call_name(c) != "vars") abort("Multiple variables should be using dplyr::vars")
+ # If it's in here, the call has to be to rlang::quos
+ if (call_name(c) != "quos") abort("Multiple variables should be using rlang::quos")
 
  # Evaluate the quosure sort_vars getting the expression
  eval(c, envir=caller_env())
@@ -192,7 +192,7 @@ unpack_vars <- function(quo_list, allow_character=TRUE) {
  abort(message = paste0("Invalid input to `", param, allow_str))
  })
  } else {
- if (is.null(c)) return(vars())
+ if (is.null(c)) return(quos())
  }
  quo_list
 }

R/count_bindings.R

@@ -576,6 +576,10 @@ set_outer_sort_position <- function(e, outer_sort_position) {
 set_denom_where <- function(e, denom_where) {
  denom_where <- enquo(denom_where)
 
+ if (!(inherits(e, 'tplyr_layer') | inherits(e, 'tplyr_table'))) {
+ stop('Object type should be either "tplyr_layer" or "tplyr_table"', call.=FALSE)
+ }
+
  assert_that(is_logical_or_call(denom_where),
  msg = "The `where` parameter must contain subsetting logic (enter without quotes)")
 
@@ -587,7 +591,7 @@ set_denom_where <- function(e, denom_where) {
 #' @export
 #' @noRd
 set_denoms_by.count_layer <- function(e, ...) {
- dots <- vars(...)
+ dots <- quos(...)
  dots_chr <- map_chr(dots, as_name)
 
  # Pull these variables to make sure the denoms used make sense

R/denom.R

@@ -65,7 +65,7 @@ this_denom <- function(.data, header_n, treat_var) {
 #' @examples
 #' library(dplyr)
 #'
-#' t <- tplyr_table(mtcars, gear, cols = vars(cyl, am))
+#' t <- tplyr_table(mtcars, gear, cols = quos(cyl, am))
 #'
 #' get_header_n_value(t, 3, 6, 0)
 #' # Returns the number of cars that have 3 gears, 6 cylinders, and auto transmission

R/desc.R

@@ -139,15 +139,15 @@ process_formatting.desc_layer <- function(x, ...) {
  if (stats_as_columns) {
  form_sums[[i]] <- trans_sums[[i]] %>%
  pivot_wider(id_cols=c(!!treat_var, match_exact(by)), # Keep row_label and the by variables
- names_from = match_exact(vars(row_label, !!!cols)), # Pull the names from treatment and cols argument
+ names_from = match_exact(quos(row_label, !!!cols)), # Pull the names from treatment and cols argument
  names_prefix = paste0('var', i, "_"), # Prefix with the name of the target variable
  values_from = display_string # Use the created display_string variable for values
  )
 
  } else {
  form_sums[[i]] <- trans_sums[[i]] %>%
  pivot_wider(id_cols=c('row_label', match_exact(by)), # Keep row_label and the by variables
- names_from = match_exact(vars(!!treat_var, !!!cols)), # Pull the names from treatment and cols argument
+ names_from = match_exact(quos(!!treat_var, !!!cols)), # Pull the names from treatment and cols argument
  names_prefix = paste0('var', i, "_"), # Prefix with the name of the target variable
  values_from = display_string # Use the created display_string variable for values
  )
@@ -173,7 +173,7 @@ process_formatting.desc_layer <- function(x, ...) {
  # formatted_data <- formatted_data %>%
  # rowwise() %>%
  # # Replace NA values with the proper empty strings
- # mutate_at(vars(starts_with('var')), ~ replace_na(.x, format_strings[[row_label]]$empty))
+ # mutate_at(quos(starts_with('var')), ~ replace_na(.x, format_strings[[row_label]]$empty))
 
 
  # Clean up

R/layer.R

@@ -26,7 +26,7 @@
 #' either "counts" for categorical counts, "desc" for descriptive statistics,
 #' or "shift" for shift table counts
 #' @param by A string, a variable name, or a list of variable names supplied
-#' using \code{dplyr::vars}
+#' using \code{rlang::quos}
 #' @param target_var Symbol. Required, The variable name on which the summary is
 #' to be performed. Must be a variable within the target dataset. Enter
 #' unquoted - i.e. target_var = AEBODSYS.
@@ -63,7 +63,7 @@
 #' @examples
 #' tab <- tplyr_table(iris, Sepal.Width)
 #'
-#' l <- group_count(tab, by=vars('Label Text', Species),
+#' l <- group_count(tab, by=quos('Label Text', Species),
 #' target_var=Species, where= Sepal.Width < 5.5,
 #' cols = Species)
 #'

R/layer_bindings.R

@@ -50,13 +50,13 @@ set_target_var <- function(layer, target_var) {
 #' iris$Species2 <- iris$Species
 #' lay <- tplyr_table(iris, Species) %>%
 #' group_count(Species) %>%
-#' set_by(vars(Species2, Sepal.Width))
+#' set_by(quos(Species2, Sepal.Width))
 get_by <- function(layer) {
  env_get(layer, "by")
 }
 
 #' @param by A string, a variable name, or a list of variable names supplied
-#' using \code{dplyr::vars}.
+#' using \code{rlang::quos}.
 #'
 #' @export
 #' @rdname by
@@ -111,15 +111,15 @@ set_where.tplyr_layer <- function(obj, where) {
 #' library(magrittr)
 #' lay <- tplyr_table(mtcars, gear) %>%
 #' add_layer(
-#' group_desc(mpg, by=vars(carb, am)) %>%
+#' group_desc(mpg, by=quos(carb, am)) %>%
 #' set_precision_by(carb)
 #' )
 get_precision_by <- function(layer) {
  env_get(layer, "precision_by")
 }
 
 #' @param precision_by A string, a variable name, or a list of variable names supplied
-#' using \code{dplyr::vars}.
+#' using \code{rlang::quos}.
 #'
 #' @export
 #' @rdname precision_by
@@ -155,15 +155,15 @@ set_precision_by <- function(layer, precision_by) {
 #' library(magrittr)
 #' lay <- tplyr_table(mtcars, gear) %>%
 #' add_layer(
-#' group_desc(vars(mpg, disp), by=vars(carb, am)) %>%
+#' group_desc(quos(mpg, disp), by=quos(carb, am)) %>%
 #' set_precision_on(disp)
 #' )
 get_precision_on <- function(layer) {
  env_get(layer, "precision_on")
 }
 
 #' @param precision_on A string, a variable name, or a list of variable names
-#' supplied using \code{dplyr::vars}.
+#' supplied using \code{rlang::quos}.
 #'
 #' @export
 #' @rdname precision_on
@@ -229,7 +229,7 @@ set_precision_data <- function(layer, prec, default = c("error", "auto")) {
  precision_by_syms <- map(precision_by, sym)
 
  # Insert the by variables in the layer and let set_precision_by validate
- set_precision_by(layer, vars(!!!precision_by_syms))
+ set_precision_by(layer, quos(!!!precision_by_syms))
 
  # Checks
  # max_int and max_dec are both on precision dataset

R/layering.R

@@ -135,7 +135,7 @@ add_layers <- function(parent, ...) {
 #' Count layers are also capable of producing counts of nested relationships.
 #' For example, if you want to produce counts of an overall outside group, and
 #' then the subgroup counts within that group, you can specify the target
-#' variable as vars(OutsideVariable, InsideVariable). This allows you to do
+#' variable as quos(OutsideVariable, InsideVariable). This allows you to do
 #' tables like Adverse Events where you want to see the Preferred Terms within
 #' Body Systems, all in one layer. Further control over denominators is
 #' available using the function \code{\link{set_denoms_by}} and distinct
@@ -153,7 +153,7 @@ add_layers <- function(parent, ...) {
 #' shift layer displays an endpoint's 'shift' throughout the duration of the
 #' study. It is an abstraction over the count layer, however we have provided
 #' an interface that is more efficient and intuitive. Targets are passed as
-#' named symbols using \code{dplyr::vars}. Generally the baseline is passed
+#' named symbols using \code{rlang::quos}. Generally the baseline is passed
 #' with the name 'row' and the shift is passed with the name 'column'. Both
 #' counts (n) and percentages (pct) are supported and can be specified with
 #' the \code{\link{set_format_strings}} function. To allow for flexibility
@@ -190,22 +190,22 @@ add_layers <- function(parent, ...) {
 #'
 #' t <- tplyr_table(mtcars, am) %>%
 #' add_layer(
-#' group_shift(vars(row=gear, column=carb), by=cyl)
+#' group_shift(quos(row=gear, column=carb), by=cyl)
 #' )
-group_count <- function(parent, target_var, by=vars(), where=TRUE, ...) {
+group_count <- function(parent, target_var, by=quos(), where=TRUE, ...) {
  tplyr_layer(parent, type='count', by=enquos(by), target_var=enquos(target_var), where=enquo(where), ...)
 }
 
 #' @rdname layer_constructors
 #' @family Layer Construction Functions
 #' @export
-group_desc <- function(parent, target_var, by=vars(), where=TRUE, ...) {
+group_desc <- function(parent, target_var, by=quos(), where=TRUE, ...) {
  tplyr_layer(parent, type='desc', by=enquos(by), target_var=enquos(target_var), where=enquo(where), ...)
 }
 
 #' @rdname layer_constructors
 #' @family Layer Construction Functions
 #' @export
-group_shift <- function(parent, target_var, by=vars(), where=TRUE, ...) {
+group_shift <- function(parent, target_var, by=quos(), where=TRUE, ...) {
  tplyr_layer(parent, type='shift', by=enquos(by), target_var=enquos(target_var), where=enquo(where), ...)
 }

R/meta_utils.R

@@ -126,25 +126,25 @@ get_meta_result.data.frame <- function(x, row_id, column, ...) {
 #'
 #' dat <- t %>% build(metadata = TRUE)
 #'
-#' get_meta_subset(t, 'd1_1', 'var1_4', add_cols = dplyr::vars(carb))
+#' get_meta_subset(t, 'd1_1', 'var1_4', add_cols = rlang::quos(carb))
 #'
 #' m <- t$metadata
 #' dat <- t$target
 #'
-#' get_meta_subset(t, 'd1_1', 'var1_4', add_cols = dplyr::vars(carb), target = target)
-get_meta_subset <- function(x, row_id, column, add_cols = vars(USUBJID), ...) {
+#' get_meta_subset(t, 'd1_1', 'var1_4', add_cols = rlang::quos(carb), target = target)
+get_meta_subset <- function(x, row_id, column, add_cols = quos(USUBJID), ...) {
  UseMethod("get_meta_subset")
 }
 
 #' @export
 #' @rdname get_meta_subset
 get_meta_subset.data.frame <- function(x, row_id, column,
- add_cols = vars(USUBJID), target = NULL, ...) {
+ add_cols = quos(USUBJID), target = NULL, ...) {
  # Get the metadata object ready
  m <- get_meta_result(x, row_id, column)
 
  if (!inherits(add_cols, 'quosures')) {
- stop("add_cols must be provided using `dplyr::vars()`", call.=FALSE)
+ stop("add_cols must be provided using `rlang::quos()`", call.=FALSE)
  }
 
  # Subset and return the data
@@ -159,13 +159,13 @@ get_meta_subset.data.frame <- function(x, row_id, column,
 
 #' @export
 #' @rdname get_meta_subset
-get_meta_subset.tplyr_table <- function(x, row_id, column, add_cols = vars(USUBJID), ...) {
+get_meta_subset.tplyr_table <- function(x, row_id, column, add_cols = quos(USUBJID), ...) {
 
  # Get the metadata object ready
  m <- get_meta_result(x, row_id, column)
 
  if (!inherits(add_cols, 'quosures')) {
- stop("add_cols must be provided using `dplyr::vars()`", call.=FALSE)
+ stop("add_cols must be provided using `rlang::quos()`", call.=FALSE)
  }
 
  # Subset and return the data

R/nested.R

@@ -41,10 +41,10 @@ process_nested_count_target <- function(x) {
  }
 
  first_layer <- process_summaries(group_count(current_env(), target_var = !!target_var[[1]],
- by = vars(!!!by), where = !!where))
+ by = quos(!!!by), where = !!where))
 
  second_layer <- process_summaries(group_count(current_env(), target_var = !!target_var[[2]],
- by = vars(!!target_var[[1]], !!!by), where = !!where) %>%
+ by = quos(!!target_var[[1]], !!!by), where = !!where) %>%
  set_count_row_prefix(indentation) %>%
  set_denoms_by(!!!second_denoms_by))
 
@@ -82,8 +82,8 @@ process_nested_count_target <- function(x) {
  target_var_saved <- target_var
  is_built_nest <- TRUE
 
- by <- vars(!!target_var[[1]], !!!by)
- target_var <- vars(!!target_var[[2]])
+ by <- quos(!!target_var[[1]], !!!by)
+ target_var <- quos(!!target_var[[2]])
 
 
  }, envir = x)

R/process_metadata.R

@@ -34,14 +34,14 @@ process_metadata.desc_layer <- function(x, ...) {
  # Transpose the metadata identical to the summary
  form_meta[[i]] <- meta_sums[[i]] %>%
  pivot_wider(id_cols=c(!!treat_var, match_exact(by)),
- names_from = match_exact(vars(row_label, !!!cols)),
+ names_from = match_exact(quos(row_label, !!!cols)),
  names_prefix = paste0('var', i, "_"),
  values_from = meta
  )
  } else {
  form_meta[[i]] <- meta_sums[[i]] %>%
  pivot_wider(id_cols=c('row_label', match_exact(by)),
- names_from = match_exact(vars(!!treat_var, !!!cols)),
+ names_from = match_exact(quos(!!treat_var, !!!cols)),
  names_prefix = paste0('var', i, "_"),
  values_from = meta
  )

R/set_format_strings.R

@@ -82,7 +82,7 @@
 #' # In a shift layer
 #' tplyr_table(mtcars, am) %>%
 #' add_layer(
-#' group_shift(vars(row=gear, column=carb), by=cyl) %>%
+#' group_shift(quos(row=gear, column=carb), by=cyl) %>%
 #' set_format_strings(f_str("xxx (xx.xx%)", n, pct))
 #' ) %>%
 #' build()
@@ -157,9 +157,9 @@ set_format_strings.desc_layer <- function(e, ..., cap=getOption('tplyr.precision
 
  env_bind(e,
  format_strings = format_strings,
- summary_vars = vars(!!!summary_vars),
- keep_vars = vars(!!!keep_vars),
- trans_vars = vars(!!!trans_vars),
+ summary_vars = quos(!!!summary_vars),
+ keep_vars = quos(!!!keep_vars),
+ trans_vars = quos(!!!trans_vars),
  row_labels = row_labels,
  max_length = max_format_length,
  need_prec_table = need_prec_table,

R/shift_bindings.R

@@ -19,22 +19,22 @@
 #' # and by variables sum to 1
 #' tplyr_table(mtcars, am) %>%
 #' add_layer(
-#' group_shift(vars(row=gear, column=carb), by=cyl) %>%
+#' group_shift(quos(row=gear, column=carb), by=cyl) %>%
 #' set_format_strings(f_str("xxx (xx.xx%)", n, pct))
 #' ) %>%
 #' build()
 #'
 #' tplyr_table(mtcars, am) %>%
 #' add_layer(
-#' group_shift(vars(row=gear, column=carb), by=cyl) %>%
+#' group_shift(quos(row=gear, column=carb), by=cyl) %>%
 #' set_format_strings(f_str("xxx (xx.xx%)", n, pct)) %>%
 #' set_denoms_by(cyl, gear) # Row % sums to 1
 #' ) %>%
 #' build()
 #'
 #' tplyr_table(mtcars, am) %>%
 #' add_layer(
-#' group_shift(vars(row=gear, column=carb), by=cyl) %>%
+#' group_shift(quos(row=gear, column=carb), by=cyl) %>%
 #' set_format_strings(f_str("xxx (xx.xx%)", n, pct)) %>%
 #' set_denoms_by(cyl, gear, am) # % within treatment group sums to 1
 #' ) %>%
@@ -47,7 +47,7 @@ set_denoms_by <- function(e, ...) {
 #' @noRd
 set_denoms_by.shift_layer <- function(e, ...) {
 
- dots <- vars(...)
+ dots <- quos(...)
  dots_chr <- map_chr(dots, as_name)
 
  # Pull these variables to make sure the denoms used make sense