💄 Start switching to base R pipe

Change-Id: I9a7cadb089e150deb1e58f33b8944ea789cd612f

Author: kupietz

R/collocationAnalysis.R

@@ -53,17 +53,17 @@ setGeneric("collocationAnalysis", function(kco, ...)  standardGeneric("collocati
 #' \dontrun{
 #'
 #'  # Find top collocates of "Packung" inside and outside the sports domain.
-#'  KorAPConnection(verbose = TRUE) %>%
+#'  KorAPConnection(verbose = TRUE) |>
 #'   collocationAnalysis("Packung", vc=c("textClass=sport", "textClass!=sport"),
-#'                       leftContextSize=1, rightContextSize=1, topCollocatesLimit=20) %>%
+#'                       leftContextSize=1, rightContextSize=1, topCollocatesLimit=20) |>
 #'   dplyr::filter(logDice >= 5)
 #' }
 #'
 #' \dontrun{
 #'
 #' # Identify the most prominent light verb construction with "in ... setzen".
 #' # Note that, currently, the use of focus function disallows exactFrequencies.
-#' KorAPConnection(verbose = TRUE) %>%
+#' KorAPConnection(verbose = TRUE) |>
 #'   collocationAnalysis("focus(in [tt/p=NN] {[tt/l=setzen]})",
 #'     leftContextSize=1, rightContextSize=0, exactFrequencies=FALSE, topCollocatesLimit=20)
 #' }
@@ -124,7 +124,7 @@ setMethod("collocationAnalysis", "KorAPConnection",
                                             localStopwords = localStopwords,
                                             seed = seed,
                                             expand = expand,
-                                            ...) ) %>%
+                                            ...) ) |>
                 bind_rows()
             } else {
               set.seed(seed)
@@ -142,8 +142,8 @@ setMethod("collocationAnalysis", "KorAPConnection",
               )
 
               if (nrow(candidates) > 0) {
-                candidates <- candidates %>%
-                  filter(frequency >= minOccur) %>%
+                candidates <- candidates |>
+                  filter(frequency >= minOccur) |>
                   slice_head(n=topCollocatesLimit)
                 collocationScoreQuery(
                   kco,
@@ -164,7 +164,7 @@ setMethod("collocationAnalysis", "KorAPConnection",
               }
             }
             if (maxRecurse > 0 & length(result) > 0 && any(!!thresholdScore >= threshold)) {
-              recurseWith <- result %>%
+              recurseWith <- result |>
                 filter(!!as.name(thresholdScore) >= threshold)
               result <- collocationAnalysis(
                 kco,
@@ -262,10 +262,10 @@ matches2FreqTable <- function(matches,
       )
     }
     log_info(verbose, paste("Aggregating", length(oldTable$word), "tokens\n"))
-    oldTable  %>%
-      group_by(word) %>%
-      mutate(word = dplyr::case_when(ignoreCollocateCase ~ tolower(word), TRUE ~ word)) %>%
-      summarise(frequency=sum(frequency), .groups = "drop") %>%
+    oldTable  |>
+      group_by(word) |>
+      mutate(word = dplyr::case_when(ignoreCollocateCase ~ tolower(word), TRUE ~ word)) |>
+      summarise(frequency=sum(frequency), .groups = "drop") |>
       arrange(desc(frequency))
   } else {
     stopwordsTable <- dplyr::tibble(word=stopwords)
@@ -281,11 +281,11 @@ matches2FreqTable <- function(matches,
     if(length(left) + length(right) == 0) {
       oldTable
     } else {
-      table(c(left, right)) %>%
-        dplyr::as_tibble(.name_repair = "minimal") %>%
-        dplyr::rename(word = 1, frequency = 2) %>%
-        dplyr::filter(str_detect(word, collocateFilterRegex)) %>%
-        dplyr::anti_join(stopwordsTable, by="word")  %>%
+      table(c(left, right)) |>
+        dplyr::as_tibble(.name_repair = "minimal") |>
+        dplyr::rename(word = 1, frequency = 2) |>
+        dplyr::filter(str_detect(word, collocateFilterRegex)) |>
+        dplyr::anti_join(stopwordsTable, by="word")  |>
         dplyr::bind_rows(oldTable)
     }
   }
@@ -323,10 +323,10 @@ snippet2FreqTable <- function(snippet,
       )
     }
     log_info(verbose, paste("Aggregating", length(oldTable$word), "tokens\n"))
-    oldTable  %>%
-      group_by(word) %>%
-      mutate(word = dplyr::case_when(ignoreCollocateCase ~ tolower(word), TRUE ~ word)) %>%
-      summarise(frequency=sum(frequency), .groups = "drop") %>%
+    oldTable  |>
+      group_by(word) |>
+      mutate(word = dplyr::case_when(ignoreCollocateCase ~ tolower(word), TRUE ~ word)) |>
+      summarise(frequency=sum(frequency), .groups = "drop") |>
       arrange(desc(frequency))
   } else {
     stopwordsTable <- dplyr::tibble(word=stopwords)
@@ -351,11 +351,11 @@ snippet2FreqTable <- function(snippet,
     if(is.na(left[1]) || is.na(right[1]) || length(left) + length(right) == 0) {
       oldTable
     } else {
-      table(c(left, right)) %>%
-        dplyr::as_tibble(.name_repair = "minimal") %>%
-        dplyr::rename(word = 1, frequency = 2) %>%
-        dplyr::filter(str_detect(word, collocateFilterRegex)) %>%
-        dplyr::anti_join(stopwordsTable, by="word")  %>%
+      table(c(left, right)) |>
+        dplyr::as_tibble(.name_repair = "minimal") |>
+        dplyr::rename(word = 1, frequency = 2) |>
+        dplyr::filter(str_detect(word, collocateFilterRegex)) |>
+        dplyr::anti_join(stopwordsTable, by="word")  |>
         dplyr::bind_rows(oldTable)
     }
   }
@@ -487,8 +487,8 @@ collocatesQuery <-
                         ignoreCollocateCase = ignoreCollocateCase,
                         stopwords = stopwords,
                         ...,
-                        verbose = kco@verbose) %>%
-        mutate(frequency = frequency * q@totalResults / min(q@totalResults, searchHitsSampleLimit)) %>%
+                        verbose = kco@verbose) |>
+        mutate(frequency = frequency * q@totalResults / min(q@totalResults, searchHitsSampleLimit)) |>
         filter(frequency >= minOccur)
     }
   }

R/collocationScoreQuery.R

@@ -33,13 +33,13 @@ utils::globalVariables(c("."))
 #' @examples
 #' \dontrun{
 #'
-#' KorAPConnection(verbose = TRUE) %>%
+#' KorAPConnection(verbose = TRUE) |>
 #'   collocationScoreQuery("Grund", "triftiger")
 #' }
 #'
 #' \dontrun{
 #'
-#' KorAPConnection(verbose = TRUE) %>%
+#' KorAPConnection(verbose = TRUE) |>
 #' collocationScoreQuery("Grund", c("guter", "triftiger"),
 #'    scoreFunctions = list(localMI = function(O1, O2, O, N, E, window_size) { O * log2(O/E) }) )
 #' }
@@ -48,11 +48,11 @@ utils::globalVariables(c("."))
 #'
 #' library(highcharter)
 #' library(tidyr)
-#' KorAPConnection(verbose = TRUE) %>%
+#' KorAPConnection(verbose = TRUE) |>
 #'   collocationScoreQuery("Team", "agil", vc = paste("pubDate in", c(2014:2018)),
-#'                         lemmatizeNodeQuery = TRUE, lemmatizeCollocateQuery = TRUE) %>%
-#'                          pivot_longer(14:last_col(), names_to = "measure", values_to = "score") %>%
-#'   hchart(type="spline", hcaes(label, score, group=measure)) %>%
+#'                         lemmatizeNodeQuery = TRUE, lemmatizeCollocateQuery = TRUE) |>
+#'                          pivot_longer(14:last_col(), names_to = "measure", values_to = "score") |>
+#'   hchart(type="spline", hcaes(label, score, group=measure)) |>
 #'   hc_add_onclick_korap_search()
 #' }
 #'
@@ -202,8 +202,8 @@ mergeDuplicateCollocates <- function(..., smoothingConstant = .5) {
   korapUrl <- combined_df$webUIRequestUrl[1] |> httr2::url_modify(query="")
 
   # Group by collocate and summarize
-  combined_df %>%
-    group_by(collocate, O2, N) %>%
+  combined_df |>
+    group_by(collocate, O2, N) |>
     summarise(
       O = sum(O) - smoothingConstant * (n()-1),
       O1 = sum(O1) - smoothingConstant * (n()-1),
@@ -219,7 +219,7 @@ mergeDuplicateCollocates <- function(..., smoothingConstant = .5) {
       query = paste(query, collapse = " | "),
       webUIRequestUrl = buildWebUIRequestUrlFromString(korapUrl, query = paste(query, collapse = " | "), vc = first(vc)),
       across(everything(), first),
-    ) %>%
+    ) |>
     ungroup()
 }
 

Readme.md

@@ -21,7 +21,7 @@ R client package to access the [web service API](https://github.com/KorAP/Kustva
 
 ```R
 library(RKorAPClient)
-KorAPConnection(verbose=TRUE) %>% corpusQuery("Hello world") %>% fetchAll()
+KorAPConnection(verbose=TRUE) |> corpusQuery("Hello world") |> fetchAll()
 ```
 
 ### Frequencies over time and domains using ggplot2
@@ -49,8 +49,8 @@ query = c("macht []{0,3} Sinn", "ergibt []{0,3} Sinn")
 years = c(1980:2010)
 as.alternatives = TRUE
 vc = "textType = /Zeit.*/ & pubDate in"
-KorAPConnection(verbose=T) %>%
-  frequencyQuery(query, paste(vc, years), as.alternatives = as.alternatives) %>%
+KorAPConnection(verbose=T) |>
+  frequencyQuery(query, paste(vc, years), as.alternatives = as.alternatives) |>
   hc_freq_by_year_ci(as.alternatives)
 ```
 
@@ -62,18 +62,18 @@ KorAPConnection(verbose=T) %>%
 ```r
 library(RKorAPClient)
 library(knitr)
-KorAPConnection(verbose = TRUE) %>% auth() %>%
+KorAPConnection(verbose = TRUE) |> auth() |>
   collocationAnalysis(
     "focus(in [tt/p=NN] {[tt/l=setzen]})",
     leftContextSize = 1,
     rightContextSize = 0,
     exactFrequencies = FALSE,
     searchHitsSampleLimit = 1000,
     topCollocatesLimit = 20
-  ) %>%
-  mutate(LVC = sprintf("[in %s setzen](%s)", collocate, webUIRequestUrl)) %>%
-  select(LVC, logDice, pmi, ll) %>%
-  head(10) %>%
+  ) |>
+  mutate(LVC = sprintf("[in %s setzen](%s)", collocate, webUIRequestUrl)) |>
+  select(LVC, logDice, pmi, ll) |>
+  head(10) |>
   kable(format="pipe", digits=2)
 ```
 
@@ -101,7 +101,7 @@ In the case of DeReKo, this can be done in three different ways.
 Authorize your RKorAPClient application via the usual OAuth browser flow *using the default application id* and the `auth` method:
 
 ```R
-kco <- KorAPConnection() %>% auth()
+kco <- KorAPConnection() |> auth()
 ```
 
 #### 2. The old way: Authorize your RKorAPClient application manually
@@ -131,7 +131,7 @@ Authorize your RKorAPClient application via the usual OAuth browser flow, using
 2. Click on the copy symbol ⎘ behind the ID of your client application.
 3. Paste your clipboard content overwriting `<application ID>` in the following example code:
    ```R
-   kco <- KorAPConnection() %>% auth(app_id = "<application ID>")
+   kco <- KorAPConnection() |> auth(app_id = "<application ID>")
    ```
 
 #### Storing and testing your authorized access
@@ -150,7 +150,7 @@ Piping the result through the `auth()` function `kco <- KorAPConnection() |> aut
 To use the access token for simple corpus queries, i.e. to make `corpusQuery` return KWIC snippets, the `metadataOnly` parameter must be set to `FALSE`, for example:
 
 ```R
-corpusQuery(kco, "Ameisenplage", metadataOnly = FALSE) %>% fetchAll()
+corpusQuery(kco, "Ameisenplage", metadataOnly = FALSE) |> fetchAll()
 ```
 
 should return KWIC snippets, if you have authorized your application successfully.