chaning parameter name dataset_to_merge_assessments

R/2_4_0_textPredict_Assess_Classify.R

@@ -43,7 +43,7 @@
 #' @param story_id (vector; only for "texttrained"-model_type) Vector of story-ids. Specify this to get story level scores (i.e., summed sentence
 #' probabilities corrected for word count). When there is both story_id and participant_id indicated, the function
 #' returns a list including both story level and person level prediction corrected for word count. (default = NULL)
-#' @param dataset_to_merge_predictions (R-object, tibble; only for "texttrained"-model_type) Insert your data here to integrate predictions to your dataset,
+#' @param dataset_to_merge_assessments (R-object, tibble; only for "texttrained"-model_type) Insert your data here to integrate predictions to your dataset,
 #'  (default = NULL).
 #' @param save_embeddings (boolean; only for "texttrained"-model_type) If set to TRUE, embeddings will be saved with a unique identifier, and
 #' will be automatically opened next time textPredict is run with the same text. (default = TRUE)
@@ -110,7 +110,7 @@
 #'   texts = implicit_motive_data$satisfactiontexts,
 #'   model_info = "implicit_power_roberta_large_L23_v1",
 #'   participant_id = implicit_motive_data$participant_id,
-#'   dataset_to_merge_predictions = implicit_motive_data
+#'   dataset_to_merge_assessments = implicit_motive_data
 #' )
 #'
 #' # Examine results
@@ -159,7 +159,7 @@ textPredict <- function(
     save_dir = "wd",
     save_name = "textPredict",
     story_id = NULL,
-    dataset_to_merge_predictions = NULL,
+    dataset_to_merge_assessments = NULL,
     previous_sentence = FALSE,
     ## fine-tuned model specific parameters ##
     tokenizer_parallelism = FALSE,
@@ -270,7 +270,7 @@ textPredict <- function(
         save_dir = save_dir,
         save_name = save_name,
         story_id = story_id,
-        dataset_to_merge_predictions = dataset_to_merge_predictions,
+        dataset_to_merge_assessments = dataset_to_merge_assessments,
         previous_sentence = previous_sentence,
         ...)
 
@@ -317,7 +317,7 @@ textPredict <- function(
         show_texts = show_texts,
         participant_id = participant_id,
         story_id = story_id,
-        dataset_to_merge_predictions = dataset_to_merge_predictions,
+        dataset_to_merge_assessments = dataset_to_merge_assessments,
         previous_sentence = previous_sentence,
         device = device,
       )

R/2_4_1_textPredictTextTrained.R

@@ -342,7 +342,7 @@ textReturnEmbedding <- function(
 #' @param story_id (vector; only works for implicit motives models) Vector of story-ids. Specify this to get story level scores (i.e., summed sentence
 #' probabilities corrected for word count). When there is both story_id and participant_id indicated, the function
 #' returns a list including both story level and person level prediction corrected for word count. (default = NULL)
-#' @param dataset_to_merge_predictions (tibble; only works for implicit motives models) Insert your data here to integrate predictions to your dataset,
+#' @param dataset_to_merge_assessments (tibble; only works for implicit motives models) Insert your data here to integrate predictions to your dataset,
 #'  (default = NULL).
 #' @param previous_sentence (Boolean; only works for implicit motives models) If set to TRUE, word-embeddings will be averaged over the current and previous
 #' sentence per story-id. For this, both participant-id and story-id must be specified.
@@ -394,7 +394,7 @@ textReturnEmbedding <- function(
 #'   texts = implicit_motive_data$satisfactiontexts,
 #'   model_info = "implicit_power_roberta_large_L23_v1",
 #'   participant_id = implicit_motive_data$participant_id,
-#'   dataset_to_merge_predictions = implicit_motive_data
+#'   dataset_to_merge_assessments = implicit_motive_data
 #' )
 #'
 #' # Examine results
@@ -436,7 +436,7 @@ textPredictTextTrained <- function(
     show_texts = FALSE,
     participant_id = NULL,
     story_id = NULL,
-    dataset_to_merge_predictions = NULL,
+    dataset_to_merge_assessments = NULL,
     previous_sentence = FALSE,
     device = "cpu",
     ...) {

R/2_4_2_textPredictImplicitMotives.R

@@ -348,7 +348,7 @@ implicit_motives_results <- function(
       # If no merge was successful, show the message
       if (!merge_success) {
         message(colourise(
-          "Note: dataset_to_merge_predictions does not have the same number of rows as the predictions and cannot be merged.\n",
+          "Note: dataset_to_merge_assessments does not have the same number of rows as the predictions and cannot be merged.\n",
           "brown"
         ))
       }
@@ -509,7 +509,7 @@ get_implicit_model_info <- function(
 #' @param story_id (vector; only works for implicit motives models) Vector of story-ids. Specify this to get story level scores (i.e., summed sentence
 #' probabilities corrected for word count). When there is both story_id and participant_id indicated, the function
 #' returns a list including both story level and person level prediction corrected for word count. (default = NULL)
-#' @param dataset_to_merge_predictions (tibble; only works for implicit motives models) Insert your data here to integrate predictions to your dataset,
+#' @param dataset_to_merge_assessments (tibble; only works for implicit motives models) Insert your data here to integrate predictions to your dataset,
 #'  (default = NULL).
 #' @param previous_sentence (Boolean; only works for implicit motives models) If set to TRUE, word-embeddings will be averaged over the current and previous
 #' sentence per story-id. For this, both participant-id and story-id must be specified.
@@ -561,7 +561,7 @@ get_implicit_model_info <- function(
 #'   texts = implicit_motive_data$satisfactiontexts,
 #'   model_info = "implicit_power_roberta_large_L23_v1",
 #'   participant_id = implicit_motive_data$participant_id,
-#'   dataset_to_merge_predictions = implicit_motive_data
+#'   dataset_to_merge_assessments = implicit_motive_data
 #' )
 #'
 #' # Examine results
@@ -604,7 +604,7 @@ textPredictImplicitMotives <- function(
     show_texts = FALSE,
     participant_id = NULL,
     story_id = NULL,
-    dataset_to_merge_predictions = NULL,
+    dataset_to_merge_assessments = NULL,
     previous_sentence = FALSE,
     device = "cpu",
     ...) {
@@ -628,10 +628,10 @@ textPredictImplicitMotives <- function(
   model_name <- model_info
   lower_case_model <- as.character(tolower(model_name))
 
-  if (is.null(participant_id) & is.null(story_id) & !is.null(dataset_to_merge_predictions)){
-      message(colourise(paste("Note: The 'texts' were not at the sentence level, and while dataset_to_merge_predictions",
+  if (is.null(participant_id) & is.null(story_id) & !is.null(dataset_to_merge_assessments)){
+      message(colourise(paste("Note: The 'texts' were not at the sentence level, and while dataset_to_merge_assessments",
       " was provided, participant_id and story_id were missing. ",
-      "The function treated each row_id as a participant_id when merging assessments into dataset_to_merge_predictions. \n", sep=""),
+      "The function treated each row_id as a participant_id when merging assessments into dataset_to_merge_assessments. \n", sep=""),
        "purple"))
 
     use_row_id_name <- TRUE
@@ -681,7 +681,7 @@ textPredictImplicitMotives <- function(
         show_texts = show_texts,
         participant_id = participant_id,
         story_id = story_id,
-        dataset_to_merge_predictions = dataset_to_merge_predictions,
+        dataset_to_merge_assessments = dataset_to_merge_assessments,
         previous_sentence = previous_sentence,
         device = device
       )
@@ -731,7 +731,7 @@ textPredictImplicitMotives <- function(
       story_id = story_id,
       predicted_scores2 = predicted_scores2,
       texts = texts,
-      dataset = dataset_to_merge_predictions,
+      dataset = dataset_to_merge_assessments,
       lower_case_model = lower_case_model
     )
 

tests/testthat/test_2_6_textPredict_implicitmotives.R

@@ -126,7 +126,7 @@ test_that("textPredict Implicit motives", {
     texts = PSE_stories_participant_level$stories,
     model_info = "implicitpower_roberta23_nilsson2024",
     participant_id = PSE_stories_participant_level$Participant_ID,
-    dataset_to_merge_predictions = PSE_stories_participant_level
+    dataset_to_merge_assessments = PSE_stories_participant_level
   )
   testthat::expect_that(predictions_participant_1, testthat::is_a("list"))
   testthat::expect_equal(length(predictions_participant_1), 3)
@@ -144,7 +144,7 @@ test_that("textPredict Implicit motives", {
     model_info = "implicitpower_roberta23_nilsson2024",
     show_texts = T
     # participant_id = PSE_stories_participant_level$Participant_ID,
-    # dataset_to_merge_predictions = PSE_stories_participant_level
+    # dataset_to_merge_assessments = PSE_stories_participant_level
   )
   testthat::expect_that(predictions_participant_2, testthat::is_a("tbl_df"))
   testthat::expect_equal(length(predictions_participant_2), 4)
@@ -156,7 +156,7 @@ test_that("textPredict Implicit motives", {
     model_info = "implicitachievement_roberta23_nilsson2024",
     participant_id = PSE_stories_story_level$Participant_ID,
     story_id = PSE_stories_story_level$story_id,
-    dataset_to_merge_predictions = PSE_stories_story_level
+    dataset_to_merge_assessments = PSE_stories_story_level
   )
   testthat::expect_that(predictions_story_1, testthat::is_a("list"))
   testthat::expect_equal(length(predictions_story_1), 4)
@@ -170,7 +170,7 @@ test_that("textPredict Implicit motives", {
     model_info = "implicitachievement_roberta23_nilsson2024",
     #participant_id = PSE_stories_story_level$Participant_ID,
     #story_id = PSE_stories_story_level$story_id,
-    dataset_to_merge_predictions = PSE_stories_story_level
+    dataset_to_merge_assessments = PSE_stories_story_level
   )
   testthat::expect_that(predictions_story_2, testthat::is_a("list"))
   testthat::expect_equal(length(predictions_story_2), 3)
@@ -182,7 +182,7 @@ test_that("textPredict Implicit motives", {
     model_info = "implicitaffiliation_roberta23_nilsson2024",
     participant_id = PSE_stories_sentence_level$Participant_ID,
     story_id = PSE_stories_sentence_level$story_id,
-    dataset_to_merge_predictions = PSE_stories_sentence_level
+    dataset_to_merge_assessments = PSE_stories_sentence_level
   )
   testthat::expect_that(predictions_sentence_1, testthat::is_a("list"))
   testthat::expect_equal(length(predictions_sentence_1), 4)
@@ -195,7 +195,7 @@ test_that("textPredict Implicit motives", {
     model_info = "implicitaffiliation_roberta23_nilsson2024",
     #participant_id = PSE_stories_sentence_level$Participant_ID,
     #story_id = PSE_stories_sentence_level$story_id,
-    dataset_to_merge_predictions = PSE_stories_sentence_level
+    dataset_to_merge_assessments = PSE_stories_sentence_level
   )
   testthat::expect_that(predictions_sentence_2, testthat::is_a("list"))
   testthat::expect_equal(length(predictions_sentence_2), 3)