cleanup

DESCRIPTION

@@ -1,6 +1,6 @@
 Package: AMR
-Version: 1.8.2.9031
-Date: 2022-10-21
+Version: 1.8.2.9032
+Date: 2022-10-22
 Title: Antimicrobial Resistance Data Analysis
 Description: Functions to simplify and standardise antimicrobial resistance (AMR)
   data analysis and to work with microbial and antimicrobial properties by

NEWS.md

@@ -1,4 +1,4 @@
-# AMR 1.8.2.9031
+# AMR 1.8.2.9032
 
 This version will eventually become v2.0! We're happy to reach a new major milestone soon!
 

R/aa_globals.R

@@ -94,6 +94,8 @@ globalVariables(c(
   "atc_group1",
   "atc_group2",
   "base_ab",
+  "ci_min",
+  "ci_max",
   "code",
   "cols",
   "count",

R/add_custom_antimicrobials.R

@@ -112,9 +112,6 @@ add_custom_antimicrobials <- function(x) {
   AMR_env$custom_ab_codes <- c(AMR_env$custom_ab_codes, x$ab)
   class(AMR_env$AB_lookup$ab) <- "character"
   
-  bind_rows <- import_fn("bind_rows", "dplyr", error_on_fail = FALSE)
-  if (is.null(bind_rows)) {
-    # do the binding in base R
   new_df <- AMR_env$AB_lookup[0, , drop = FALSE][seq_len(NROW(x)), , drop = FALSE]
   rownames(new_df) <- NULL
   list_cols <- vapply(FUN.VALUE = logical(1), new_df, is.list)
@@ -127,10 +124,6 @@ add_custom_antimicrobials <- function(x) {
     new_df[, col] <- x[, col, drop = TRUE]
   }
   AMR_env$AB_lookup <- unique(rbind(AMR_env$AB_lookup, new_df))
-  } else {
-    # otherwise use dplyr
-    AMR_env$AB_lookup <- unique(bind_rows(AMR_env$AB_lookup, x))
-  }
   class(AMR_env$AB_lookup$ab) <- c("ab", "character")
   message_("Added ", nr2char(nrow(x)), " record", ifelse(nrow(x) > 1, "s", ""), " to the internal `antibiotics` data set.")
 }

R/rsi_calc.R

@@ -279,7 +279,6 @@ rsi_calc_df <- function(type, # "proportion", "count" or "both"
       col_results <- as.data.frame(as.matrix(table(values)), stringsAsFactors = FALSE)
       col_results$interpretation <- rownames(col_results)
       col_results$isolates <- col_results[, 1, drop = TRUE]
-      ddf <<- col_results
       if (NROW(col_results) > 0 && sum(col_results$isolates, na.rm = TRUE) > 0) {
         if (sum(col_results$isolates, na.rm = TRUE) >= minimum) {
           col_results$value <- col_results$isolates / sum(col_results$isolates, na.rm = TRUE)

inst/tinytest/test-zzz.R

@@ -34,7 +34,6 @@
 import_functions <- c(
   "%chin%" = "data.table",
   "anti_join" = "dplyr",
-  "bind_rows" = "dplyr",
   "chmatch" = "data.table",
   "cur_column" = "dplyr",
   "full_join" = "dplyr",