remove udpipe_accuracy for the time being

NAMESPACE

@@ -33,7 +33,6 @@ export(txt_previous)
 export(txt_recode)
 export(txt_sample)
 export(txt_show)
-export(udpipe_accuracy)
 export(udpipe_annotate)
 export(udpipe_download_model)
 export(udpipe_load_model)

NEWS.md

@@ -1,10 +1,10 @@
 # CHANGES IN udpipe VERSION 0.2.1
 
 - Added phrases to extract POS sequences more easily like noun phrases, verb phrases or any sequence of parts of speech tags and their corresponding words
-- Add udpipe_accuracy
 - Fix issue in txt_nextgram if n was larger than the number of elements in x
 - Fix heap-use-after-free address sanitiser issue
 - Fix runtime error: null pointer passed as argument 1, which is declared to never be null (e.g. udpipe.cpp: 3338)
+- Another stab at the Solaris compilation issue
 
 
 # CHANGES IN udpipe VERSION 0.2

R/RcppExports.R

@@ -13,10 +13,6 @@ udp_tokenise_tag_parse <- function(udmodel, x, docid, annotation_tokenizer, anno
     .Call('_udpipe_udp_tokenise_tag_parse', PACKAGE = 'udpipe', udmodel, x, docid, annotation_tokenizer, annotation_tagger, annotation_parser)
 }
 
-udp_evaluate <- function(udmodel, conllu_test_file, output_file, annotation_tokenizer, annotation_tagger, annotation_parser) {
-    .Call('_udpipe_udp_evaluate', PACKAGE = 'udpipe', udmodel, conllu_test_file, output_file, annotation_tokenizer, annotation_tagger, annotation_parser)
-}
-
 na_locf <- function(x) {
     .Call('_udpipe_na_locf', PACKAGE = 'udpipe', x)
 }

R/udpipe_train.R

@@ -38,7 +38,7 @@
 #'  \item{errors: }{Messages from the UDPipe process indicating possible errors for example when passing the wrong arguments to the 
 #'  annotation_tokenizer, annotation_tagger or annotation_parser}
 #' }
-#' @seealso \code{\link{udpipe_annotation_params}}, \code{\link{udpipe_annotate}}, \code{\link{udpipe_load_model}}, \code{\link{udpipe_accuracy}}
+#' @seealso \code{\link{udpipe_annotation_params}}, \code{\link{udpipe_annotate}}, \code{\link{udpipe_load_model}}
 #' @references \url{http://ufal.mff.cuni.cz/udpipe/users-manual}
 #' @details 
 #' In order to train a model, you need to provide files which are in CONLL-U format in argument \code{files_conllu_training}. 
@@ -133,59 +133,3 @@ udpipe_train <- function(file = file.path(getwd(), "my_annotator.udpipe"),
     class = "udpipe_trained_model"))
 }
 
-
-
-
-#' @title Evaluate the accuracy of your UDPipe model on holdout data
-#' @description Get precision, recall and F1 measures on finding words, sentences, 
-#' parts of speech tags (upos and xpos) and the grammatical annotated features.
-#' For the accuracy of the dependency parsing, the output shows 
-#' the LAS (labeled attachment score - the percentage of predicted dependencies
-#' where the arc and the label are assigned correctly) and 
-#' UAS (unlabeled attachment score – where the arc is assigned correctly) 
-#' dependency scores on holdout data in conllu format.
-#' @param object an object of class \code{udpipe_model} as returned by \code{\link{udpipe_load_model}}
-#' @param file_conllu the full path to a file on disk containing holdout data in conllu format
-#' @param tokenizer a character string of length 1, which is either 'default' or 'none'
-#' @param tagger a character string of length 1, which is either 'default' or 'none'
-#' @param parser a character string of length 1, which is either 'default' or 'none'
-#' @return a list with 3 elements
-#' \itemize{
-#'  \item{accuracy: }{A character vector with accuracy metrics.}
-#'  \item{error: }{A character string with possible errors when calculating the accuracy metrics}
-#' }
-#' @seealso \code{\link{udpipe_load_model}}
-#' @references \url{https://ufal.mff.cuni.cz/udpipe}, 
-#' \url{http://universaldependencies.org/format.html}
-#' @export
-#' @examples 
-#' x <- udpipe_download_model(language = "dutch-lassysmall")
-#' ud_dutch <- udpipe_load_model(x$file_model)
-#' 
-#' file_conllu <- system.file(package = "udpipe", "dummydata", "traindata.conllu")
-#' metrics <- udpipe_accuracy(ud_dutch, file_conllu, 
-#'                            tokenizer = "default", tagger = "none", parser = "none")
-#' metrics$accuracy
-#' 
-#' ## cleanup for CRAN only - you probably want to keep your model if you have downloaded it
-#' file.remove("dutch-lassysmall-ud-2.0-170801.udpipe")
-udpipe_accuracy <- function(object, 
-                            file_conllu, 
-                            tokenizer = c("default", "none"), 
-                            tagger = c("default", "none"), 
-                            parser = c("default", "none")) {
-  if(!inherits(object, "udpipe_model")){
-    stop("object should be of class udpipe_model as returned by the function ?udpipe_load_model")
-  }
-  stopifnot(file.exists(file_conllu))
-  tokenizer <- match.arg(tokenizer)
-  tagger <- match.arg(tagger)
-  parser <- match.arg(parser)
-
-  f <- tempfile()
-  out <- udp_evaluate(object$model, file_conllu, f, tokenizer, tagger, parser)
-  out$accuracy <- readLines(f)
-  class(out) <- "udpipe_accuracy"
-  out
-}
-

src/RcppExports.cpp

@@ -45,22 +45,6 @@ BEGIN_RCPP
     return rcpp_result_gen;
 END_RCPP
 }
-// udp_evaluate
-Rcpp::List udp_evaluate(SEXP udmodel, Rcpp::CharacterVector conllu_test_file, Rcpp::CharacterVector output_file, std::string annotation_tokenizer, std::string annotation_tagger, std::string annotation_parser);
-RcppExport SEXP _udpipe_udp_evaluate(SEXP udmodelSEXP, SEXP conllu_test_fileSEXP, SEXP output_fileSEXP, SEXP annotation_tokenizerSEXP, SEXP annotation_taggerSEXP, SEXP annotation_parserSEXP) {
-BEGIN_RCPP
-    Rcpp::RObject rcpp_result_gen;
-    Rcpp::RNGScope rcpp_rngScope_gen;
-    Rcpp::traits::input_parameter< SEXP >::type udmodel(udmodelSEXP);
-    Rcpp::traits::input_parameter< Rcpp::CharacterVector >::type conllu_test_file(conllu_test_fileSEXP);
-    Rcpp::traits::input_parameter< Rcpp::CharacterVector >::type output_file(output_fileSEXP);
-    Rcpp::traits::input_parameter< std::string >::type annotation_tokenizer(annotation_tokenizerSEXP);
-    Rcpp::traits::input_parameter< std::string >::type annotation_tagger(annotation_taggerSEXP);
-    Rcpp::traits::input_parameter< std::string >::type annotation_parser(annotation_parserSEXP);
-    rcpp_result_gen = Rcpp::wrap(udp_evaluate(udmodel, conllu_test_file, output_file, annotation_tokenizer, annotation_tagger, annotation_parser));
-    return rcpp_result_gen;
-END_RCPP
-}
 // na_locf
 Rcpp::CharacterVector na_locf(Rcpp::CharacterVector x);
 RcppExport SEXP _udpipe_na_locf(SEXP xSEXP) {
@@ -93,7 +77,6 @@ static const R_CallMethodDef CallEntries[] = {
     {"_udpipe_phrases_regex_locate", (DL_FUNC) &_udpipe_phrases_regex_locate, 3},
     {"_udpipe_udp_load_model", (DL_FUNC) &_udpipe_udp_load_model, 1},
     {"_udpipe_udp_tokenise_tag_parse", (DL_FUNC) &_udpipe_udp_tokenise_tag_parse, 6},
-    {"_udpipe_udp_evaluate", (DL_FUNC) &_udpipe_udp_evaluate, 6},
     {"_udpipe_na_locf", (DL_FUNC) &_udpipe_na_locf, 1},
     {"_udpipe_udp_train", (DL_FUNC) &_udpipe_udp_train, 6},
     {NULL, NULL, 0}

src/rcpp_udpipe.cpp

@@ -71,50 +71,6 @@ Rcpp::List udp_tokenise_tag_parse(SEXP udmodel, Rcpp::StringVector x, Rcpp::Stri
 
 
 
-// [[Rcpp::export]]
-Rcpp::List udp_evaluate(SEXP udmodel, 
-                        Rcpp::CharacterVector conllu_test_file, 
-                        Rcpp::CharacterVector output_file, 
-                        std::string annotation_tokenizer,
-                        std::string annotation_tagger,
-                        std::string annotation_parser) {
-  Rcpp::XPtr<ufal::udpipe::model> languagemodel(udmodel);
-
-  // Handle default and none input to tokenizer, tagger, parser
-  std::string pipeline_tokenizer = annotation_tokenizer;
-  std::string pipeline_tagger = annotation_tagger;
-  std::string pipeline_parser = annotation_parser;
-  if (pipeline_tagger.compare("none") == 0){
-    pipeline_tagger = ufal::udpipe::pipeline::NONE;
-  }else if (pipeline_tagger.compare("default") == 0){
-    pipeline_tagger = ufal::udpipe::pipeline::DEFAULT;
-  }
-  if (pipeline_parser.compare("none") == 0){
-    pipeline_parser = ufal::udpipe::pipeline::NONE;
-  }else if (pipeline_parser.compare("default") == 0){
-    pipeline_parser = ufal::udpipe::pipeline::DEFAULT;
-  }
-
-  // Set up evaluator
-  ufal::udpipe::evaluator modelevaluator = ufal::udpipe::evaluator(languagemodel, pipeline_tokenizer, pipeline_tagger, pipeline_parser);
-
-  // Input CONLLU filestream and output file containing the evaluation
-  std::string path;
-  path = conllu_test_file[0];
-  std::ifstream infile(path.c_str());
-  path = output_file[0];
-  std::ofstream outfile(path.c_str());
-
-  // Evaluate the model
-  std::string error;
-  modelevaluator.evaluate(infile, outfile, error);
-
-  // Return the file and the error
-  Rcpp::List output = Rcpp::List::create(Rcpp::Named("error") = error);
-  return output;
-}
-
-
 // [[Rcpp::export]]
 Rcpp::CharacterVector na_locf(Rcpp::CharacterVector x) {
   int i;

src/udpipe.cpp

@@ -19767,8 +19767,10 @@ void multiword_splitter::append_token(string_piece token, string_piece misc, sen
   }
 
   // Determine casing
-  enum casing_t { UC_FIRST, UC_ALL, OTHER };
-  casing_t casing = OTHER;
+  int UC_FIRST=0, UC_ALL=1, OTHER=2;
+  int casing=OTHER;
+  //enum casing_t { UC_FIRST, UC_ALL, OTHER };
+  //casing_t casing = OTHER;
   //enum { UC_FIRST, UC_ALL, OTHER } casing = OTHER;
 
   if (unicode::category(utf8::first(token.str, token.len)) & unicode::Lut) {