added function to summarize MetaNLP-objects

DESCRIPTION

@@ -48,6 +48,7 @@ Collate:
     util.R
     delete_functions.R
     feature_selection.R
+    useful_functions.R
 Encoding: UTF-8
 LazyData: true
 RoxygenNote: 7.3.1

NAMESPACE

@@ -7,4 +7,5 @@ export(select_features)
 exportMethods(delete_stop_words)
 exportMethods(delete_words)
 exportMethods(select_features)
+exportMethods(summary)
 import(methods)

R/useful_functions.R

@@ -0,0 +1,78 @@
+#' Summary of MetaNLP-objects
+#'
+#' Returns a quick overview over the \eqn{n} most frequent word stems structured
+#' into included and excluded papers.
+#'
+#' @param object An object of class MetaNLP.
+#' @param n Number of most frequent words to be displayed.
+#' @param stop_words Boolean to decide wether stop words shall be included in
+#' the summary. \code{stop_words = TRUE} means, that stop words are included.
+#' @param ... Additional parameters for \code{delete_stop_words} (e.g. language
+#' of the stop words).
+#'
+#' @return A list of most frequent words.
+#'
+#' @examples
+#' \dontrun{
+#' obj <- MetaNLP("test_data.csv")
+#' summary(obj, n = 8)
+#' }
+#'
+#' @rdname summary
+#' @export
+setMethod("summary", signature("MetaNLP"),
+          function(object, n = 5, stop_words = FALSE, ...) {
+            decision <- NULL
+
+            # delete stop words
+            if(!stop_words) {
+              wcm <- delete_stop_words(object, ...)@data_frame
+            } else {
+              wcm <- object@data_frame
+            }
+
+            # get n most frequent words
+            wcm |>
+              (`[`)(-c(1, 2)) |>
+              colSums() |>
+              sort(decreasing = TRUE) |>
+              (`[`)(1:n) -> total
+
+            # get n most frequent words from "exclude"
+            wcm |>
+              subset(decision == "no") |>
+              (`[`)(-c(1, 2)) |>
+              colSums() |>
+              sort(decreasing = TRUE) |>
+              (`[`)(1:n) -> exclude
+
+            # get n most frequent words from "include"
+            wcm |>
+              subset(decision == "yes") |>
+              (`[`)(-c(1, 2)) |>
+              colSums() |>
+              sort(decreasing = TRUE) |>
+              (`[`)(1:n) -> include
+
+            # relative frequency of words
+            denom_total <- sum(colSums(wcm[-c(1, 2)]))
+            denom_ex <- sum(colSums(subset(wcm, decision == "no")[-c(1, 2)]))
+            denom_in <- sum(colSums(subset(wcm, decision == "yes")[-c(1, 2)]))
+
+            rel_total <- paste(round(total / denom_total * 100,
+                               digits = 2), "%")
+            rel_exclude <- paste(round(exclude /  denom_ex * 100,
+                                       digits = 2), "%")
+            rel_include <- paste(round(include / denom_in * 100,
+                                       digits = 2), "%")
+
+            # return list with all information
+            list("Total" = noquote(rbind("Absolute" = total,
+                                         "Relative" = rel_total)),
+                 "Exclude" = noquote(rbind("Absolute" = exclude,
+                                           "Relative" = rel_exclude)),
+                 "Include" = noquote(rbind("Absolute" = include,
+                                           "Relative" = rel_include)))
+
+
+          })