Refactor, update README.Rmd/.md

DESCRIPTION

@@ -25,3 +25,4 @@ Config/testthat/edition: 3
 RoxygenNote: 7.2.3
 VignetteBuilder: knitr
 Encoding: UTF-8
+Language: en-US

R/bleu.R

@@ -2,7 +2,7 @@ library(checkmate)
 
 
 
-#' Validate Arguemnts
+#' Validate Arguments
 #'
 #' @param weights Weight vector for `bleu_corpus_ids` and `bleu_sentence_ids` functions
 #' @param smoothing Smoothing method for `bleu_corpus_ids` and `bleu_sentence_ids` functions
@@ -40,9 +40,9 @@ validate_references <- function(references, target) {
 #'
 #' `bleu_sentence_ids` computes the BLEU score for a single candidate sentence and a list of reference sentences.
 #' The sentences must be tokenized before so they are represented as integer vectors.
-#' Akin to sacreBLEU, the function allows the application of different smoothing methods.
+#' Akin to sacrebleu (Python), the function allows the application of different smoothing methods.
 #' Epsilon- and add-k-smoothing are available. Epsilon-smoothing is equivalent to 'floor'
-#' smoothing in the sacreBLEU implementation.
+#' smoothing in the sacrebleu implementation.
 #' The different smoothing techniques are described in Chen et al., 2014
 #' (https://aclanthology.org/W14-3346/).
 #'
@@ -128,7 +128,7 @@ bleu_corpus_ids <- function(references, candidates, n = 4, weights = NULL, smoot
 # Compute BLEU for a Corpus with Tokenization
 #
 #' This function applies tokenization based on the 'tok' library and computes the BLEU score.
-#' An already initializied tokenizer can be provided using the `tokenizer`argument or
+#' An already initialized tokenizer can be provided using the `tokenizer`argument or
 #' a valid huggingface identifier (string) can be passed. If the identifier is used only,
 #' the tokenizer is newly initialized on every call.
 #' @param references A list of a list of reference sentences (`list(list(c(1,2,...)), list(c(3,5,...)))`).

README.Rmd

@@ -13,13 +13,13 @@ knitr::opts_chunk$set(
 )
 ```
 
-# sac :registered: eBLEU
+# sacReBLEU
 
 <!-- badges: start -->
 <!-- badges: end -->
 
-The goal of sacReBLEU is to provide a simple interface to the BLEU score, a metric for evaluating the quality of machine-translated text.
-This package is inspired by the NLTK and sacrebleu implementations of the BLEU score, and is based on a high-performance C++ implementation for the R programming language.
+The goal of sacReBLEU is to provide a simple interface to the BLEU score, a metric for evaluating the quality of generated text.
+This package is inspired by the NLTK and sacrebleu implementations of the BLEU score, and is implemented in C++ for the R programming language.
 
 ## Installation
 
@@ -32,12 +32,10 @@ devtools::install_github("LazerLambda/sacReBLEU")
 
 ## Example
 
-This is a basic example which shows you how to solve a common problem:
-
 ```{r example}
 library(sacReBLEU)
-ref_corpus <- list(c(1,2,3,4))
-cand_corpus <- c(1,2,3,5)
-bleu_standard <- bleu_sentence_ids(ref_corpus, cand_corpus)
+cand_corpus <- list("This is good", "This is not good")
+ref_corpus <- list(list("Perfect outcome!", "Excellent!"), list("Not sufficient.", "Horrible."))
+bleu_corpus <- bleu_corpus(ref_corpus, cand_corpus)
 ```
 

README.md

@@ -1,16 +1,15 @@
 
 <!-- README.md is generated from README.Rmd. Please edit that file -->
 
-# sac :registered: eBLEU
+# sacReBLEU
 
 <!-- badges: start -->
 <!-- badges: end -->
 
 The goal of sacReBLEU is to provide a simple interface to the BLEU
-score, a metric for evaluating the quality of machine-translated text.
-This package is inspired by the NLTK and sacrebleu implementations of
-the BLEU score, and is based on a high-performance C++ implementation
-for the R programming language.
+score, a metric for evaluating the quality of generated text. This
+package is inspired by the NLTK and sacrebleu implementations of the
+BLEU score, and is implemented in C++ for the R programming language.
 
 ## Installation
 
@@ -24,11 +23,9 @@ devtools::install_github("LazerLambda/sacReBLEU")
 
 ## Example
 
-This is a basic example which shows you how to solve a common problem:
-
 ``` r
 library(sacReBLEU)
-ref_corpus <- list(c(1,2,3,4))
-cand_corpus <- c(1,2,3,5)
-bleu_standard <- bleu_sentence_ids(ref_corpus, cand_corpus)
+cand_corpus <- list("This is good", "This is not good")
+ref_corpus <- list(list("Perfect outcome!", "Excellent!"), list("Not sufficient.", "Horrible."))
+bleu_corpus <- bleu_corpus(ref_corpus, cand_corpus)
 ```

src/Fraction.h

@@ -9,4 +9,4 @@ class Fraction {
         long double get_value();
     };
 
-#endif
+#endif