TRegexTreeVisitor(TregexPattern p, String[] handles, String encoding) { this.p = p; this.handles = handles; try { pw = new PrintWriter(new OutputStreamWriter(System.out, encoding),true); } catch (UnsupportedEncodingException e) { log.info("Error -- encoding " + encoding + " is unsupported. Using platform default PrintWriter instead."); pw = new PrintWriter(System.out,true); } }
/** * Set up shared random generator to use the given seed. * * @return Shared random generator object */ private static Random getRandom(long seed) { random = new Random(seed); log.info(String.format("Random generator initialized with seed %d%n", seed)); return random; }
public double evaluate(double[] x) { StringBuilder sb = new StringBuilder("Memory Usage: "); sb.append(" used(KB):").append(memMonitor.getUsedMemory(false)); sb.append(" maxAvailable(KB):").append(memMonitor.getMaxAvailableMemory(false)); sb.append(" max(KB):").append(memMonitor.getMaxMemory()); String memString = sb.toString(); log.info(memString); return 0; } }
public static double[] getWeights(String loadPath) throws IOException, ClassCastException, ClassNotFoundException { log.info("Loading weights from " + loadPath + "..."); double[] wt; Weights w; w = IOUtils.readObjectFromFile(loadPath); wt = w.w; return wt; }
/** * */ public static boolean acronymMatch(String s1, String s2, HashMap stemmedAcronymIndex) { log.info("Testing match:" + s1 + " : " + s2); String stem1 = (String) stemmedAcronymIndex.get(s1); String stem2 = (String) stemmedAcronymIndex.get(s2); log.info("Got stems:" + s1 + " : " + s2); return stem1.equals(stem2); } /**
private ScoredParsesIterator(String inputDesc, BufferedReader br) { this.inputDesc = inputDesc; this.br = br; logger.info("Reading cached parses from " + inputDesc); timing = new Timing(); timing.start(); next = getNext(); done = next == null; }
private void verbose(String s) { if (verbose) { log.info(s); } }
protected void say(String s) { if (!quiet) { log.info(s); } }
public static void main(String[] args) { List<Font> fonts = supportedFonts(ARABIC); log.info("Has MS Mincho? " + hasFont("MS Mincho")); for (Font font : fonts) { System.out.println(font.getName()); } }
/** * Print the timing done message with elapsed time in x.y seconds. * Restart the timer too. */ public void end(String msg) { long elapsed = System.nanoTime() - start; log.info(msg + " done [" + nf.format(((double) elapsed) / SECOND_DIVISOR) + " sec]."); this.start(); }
protected void sayln(String s) { if (!quiet) { log.info(s); } } }
private void sayln(String s) { if (!quiet) { log.info(s); } }
public static void main(String[] args) throws Exception { if (args.length != 2) { log.info("usage: java TaggerDemo modelFile fileToTag"); return; } MaxentTagger tagger = new MaxentTagger(args[0]); List<List<HasWord>> sentences = MaxentTagger.tokenizeText(new BufferedReader(new FileReader(args[1]))); for (List<HasWord> sentence : sentences) { List<TaggedWord> tSentence = tagger.tagSentence(sentence); System.out.println(SentenceUtils.listToString(tSentence, false)); } }
private synchronized void createOutDict() { if (outDict == null) { logger.info("reading "+flags.outDict2+" as a seen lexicon"); outDict = new CorpusDictionary(flags.outDict2); } }
public static Set<String> setLabels(List<Tree> trees, Map<String, String> labelMap, MissingLabels missing, String defaultLabel) { logger.info("Setting labels"); Set<String> unknowns = new HashSet<>(); for (Tree tree : trees) { setLabels(tree, labelMap, missing, defaultLabel, unknowns); } return unknowns; }
private static DiskTreebank makeSecondaryTreebank(String treebankPath, Options op, FileFilter filt) { log.info("Additionally training using secondary disk treebank: " + treebankPath + ' ' + filt); DiskTreebank trainTreebank = op.tlpParams.diskTreebank(); log.info("Reading trees..."); if (filt == null) { trainTreebank.loadPath(treebankPath); } else { trainTreebank.loadPath(treebankPath, filt); } Timing.tick("done [read " + trainTreebank.size() + " trees]."); return trainTreebank; }
public static void main(String[] args) { if (args.length >= 2) { EditDistance d = new EditDistance(); System.out.println(d.score(args[0], args[1])); } else { log.info("usage: java EditDistance str1 str2"); } }
public void averageScoredModels(Collection<ScoredObject<PerceptronModel>> scoredModels) { if (scoredModels.isEmpty()) { throw new IllegalArgumentException("Cannot average empty models"); } log.info("Averaging " + scoredModels.size() + " models with scores"); for (ScoredObject<PerceptronModel> model : scoredModels) { log.info(" " + NF.format(model.score())); } log.info(); List<PerceptronModel> models = CollectionUtils.transformAsList(scoredModels, ScoredObject::object); averageModels(models); }