Examples of edu.stanford.nlp.util.Timing.start()

edu.stanford.nlp.util.Timing.start()
Start timer.

    }


    System.err.printf("Tagging completed in %.2f sec.%n",
        timer.stop() / 1000.0);


    timer.start();


    int numSentences = 0;
    for (List<TaggedWord> taggedSentence : tagged) {
      GrammaticalStructure parse = predict(taggedSentence);

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    //!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!
    //!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!
    Timing total = new Timing();
    Timing current = new Timing();
    total.start();
    current.start();
    for (k = 0; k<maxIterations ; k++)  {
      try{
        boolean doEval = (k > 0 && evaluateIters > 0 && k % evaluateIters == 0);
        if (doEval) {
          doEvaluation(x);

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  Counter<K> lastUpdated = new ClassicCounter<K>();
  int timeStep = 0;


  Timing total = new Timing();
  total.start();


  for (int iter = 0; iter < numPasses; iter++) {
    double totalObjValue = 0;


    for (int j = 0; j < numBatches; j++) {

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    //!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!


    Timing total = new Timing();
    Timing current = new Timing();
    total.start();
    current.start();
    int t=t0;
    int iters = 0;
    for (int pass = 0; pass < numPasses; pass++)  {
      boolean doEval = (pass > 0 && evaluateIters > 0 && pass % evaluateIters == 0);
      if (doEval) {

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    //!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!


    Timing total = new Timing();
    Timing current = new Timing();
    total.start();
    current.start();
    int iters = 0;
    double gValue = 0;
    double wValue = 0;
    double currentRate = 0, testUpdate = 0, realUpdate = 0;

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      if(tokenizerFactory != null)
        pwErr.println("parseFiles: Tokenizer factory is: " + tokenizerFactory);
    }


    final Timing timer = new Timing();
    timer.start();


    //Loop over the files
    for (int i = argIndex; i < args.length; i++) {
      final String filename = args[i];

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    // Test simplified pattern with number
    TokenSequencePattern p = TokenSequencePattern.compile( "(?$dt \"atropine\") []{0,15} " +
            "(?$se  \"social\" \"avoidant\" \"behaviour\"|\"dysuria\"|\"hyperglycaemia\"| \"mental\" \"disorder\"|\"vertigo\"|\"flutter\"| \"chest\" \"pain\"| \"elevated\" \"blood\" \"pressure\"|\"mania\"| \"rash\" \"erythematous\"|\"manic\"| \"papular\" \"rash\"|\"death\"| \"atrial\" \"arrhythmia\"| \"dry\" \"eyes\"| \"loss\" \"of\" \"libido\"| \"rash\" \"papular\"|\"hypersensitivity\"| \"blood\" \"pressure\" \"increased\"|\"dyspepsia\"| \"accommodation\" \"disorder\"| \"reflexes\" \"increased\"|\"lesions\"|\"asthenia\"| \"gastrointestinal\" \"pain\"|\"excitement\"| \"breast\" \"feeding\"|\"hypokalaemia\"| \"cerebellar\" \"syndrome\"|\"nervousness\"| \"pulmonary\" \"oedema\"| \"inspiratory\" \"stridor\"| \"taste\" \"altered\"|\"paranoia\"| \"psychotic\" \"disorder\"| \"open\" \"angle\" \"glaucoma\"|\"photophobia\"| \"dry\" \"eye\"|\"osteoarthritis\"| \"keratoconjunctivitis\" \"sicca\"| \"haemoglobin\" \"increased\"| \"ventricular\" \"extrasystoles\"|\"hallucinations\"|\"conjunctivitis\"|\"paralysis\"| \"qrs\" \"complex\"|\"anxiety\"| \"conjunctival\" \"disorder\"|\"coma\"|\"strabismus\"|\"thirst\"|\"para\"| \"sicca\" \"syndrome\"| \"atrioventricular\" \"dissociation\"|\"desquamation\"|\"crusting\"| \"abdominal\" \"distension\"|\"blindness\"|\"hypotension\"|\"dermatitis\"| \"sinus\" \"tachycardia\"| \"abdominal\" \"distention\"| \"lacrimation\" \"decreased\"|\"sicca\"| \"paralytic\" \"ileus\"| \"urinary\" \"hesitation\"|\"withdrawn\"| \"erectile\" \"dysfunction\"|\"keratoconjunctivitis\"|\"anaphylaxis\"| \"psychiatric\" \"disorders\"| \"altered\" \"taste\"|\"somnolence\"|\"extrasystoles\"|\"ageusia\"| \"intraocular\" \"pressure\" \"increased\"| \"left\" \"ventricular\" \"failure\"|\"impotence\"|\"drowsiness\"|\"conjunctiva\"| \"delayed\" \"gastric\" \"emptying\"| \"gastrointestinal\" \"sounds\" \"abnormal\"| \"qt\" \"prolonged\"| \"supraventricular\" \"tachycardia\"|\"weakness\"|\"hypertonia\"| \"confusional\" \"state\"|\"anhidrosis\"|\"myopia\"|\"dyspnoea\"| \"speech\" \"impairment\" \"nos\"| \"rash\" \"maculo\" \"papular\"|\"petechiae\"|\"tachypnea\"| \"acute\" \"angle\" \"closure\" \"glaucoma\"| \"gastrooesophageal\" \"reflux\" \"disease\"|\"hypokalemia\"| \"left\" \"heart\" \"failure\"| \"myocardial\" \"infarction\"| \"site\" \"reaction\"| \"ventricular\" \"fibrillation\"|\"fibrillation\"| \"maculopapular\" \"rash\"| \"impaired\" \"gastric\" \"emptying\"|\"amnesia\"| \"labored\" \"respirations\"| \"decreased\" \"lacrimation\"|\"mydriasis\"|\"headache\"| \"dry\" \"mouth\"|\"scab\"| \"cardiac\" \"syncope\"| \"visual\" \"acuity\" \"reduced\"|\"tension\"| \"blurred\" \"vision\"| \"bloated\" \"feeling\"| \"labored\" \"breathing\"| \"stridor\" \"inspiratory\"| \"skin\" \"exfoliation\"| \"memory\" \"loss\"|\"syncope\"| \"rash\" \"scarlatiniform\"|\"hyperpyrexia\"| \"cardiac\" \"flutter\"|\"heartburn\"| \"bowel\" \"sounds\" \"decreased\"|\"blepharitis\"|\"tachycardia\"| \"excessive\" \"thirst\"|\"confusion\"| \"rash\" \"macular\"| \"taste\" \"loss\"| \"respiratory\" \"failure\"|\"hesitancy\"|\"dysmetria\"|\"disorientation\"| \"decreased\" \"hemoglobin\"| \"atrial\" \"fibrillation\"| \"urinary\" \"retention\"| \"dry\" \"skin\"|\"dehydration\"|\"hyponatraemia\"|\"dysgeusia\"|\"disorder\"| \"increased\" \"intraocular\" \"pressure\"| \"speech\" \"disorder\"| \"feeling\" \"abnormal\"|\"pain\"| \"anaphylactic\" \"shock\"|\"hallucination\"| \"abdominal\" \"pain\"| \"junctional\" \"tachycardia\"| \"bun\" \"increased\"| \"ventricular\" \"flutter\"| \"scarlatiniform\" \"rash\"|\"agitation\"| \"feeling\" \"hot\"|\"hyponatremia\"| \"decreased\" \"bowel\" \"sounds\"|\"cyanosis\"|\"dysarthria\"| \"heat\" \"intolerance\"|\"hyperglycemia\"|\"reflux\"| \"angle\" \"closure\" \"glaucoma\"| \"electrocardiogram\" \"qt\" \"prolonged\"| \"vision\" \"blurred\"| \"blood\" \"urea\" \"increased\"|\"dizziness\"|\"arrhythmia\"|\"erythema\"|\"vomiting\"| \"difficulty\" \"in\" \"micturition\"|\"infarction\"|\"laryngospasm\"|\"hypoglycaemia\"|\"hypoglycemia\"| \"elevated\" \"hemoglobin\"| \"skin\" \"warm\"| \"ventricular\" \"arrhythmia\"|\"dissociation\"| \"warm\" \"skin\"| \"follicular\" \"conjunctivitis\"|\"urticaria\"|\"fatigue\"| \"cardiac\" \"fibrillation\"| \"decreased\" \"sweating\"| \"decreased\" \"visual\" \"acuity\"|\"lethargy\"| \"acute\" \"angle\" \"closure\" \"glaucoma\"| \"nodal\" \"rhythm\"|\"borborygmi\"|\"hyperreflexia\"| \"respiratory\" \"depression\"|\"diarrhea\"|\"leukocytosis\"| \"speech\" \"disturbance\"|\"ataxia\"|\"cycloplegia\"|\"tachypnoea\"|\"eczema\"| \"supraventricular\" \"extrasystoles\"|\"ileus\"| \"cardiac\" \"arrest\"| \"ventricular\" \"tachycardia\"|\"laryngitis\"|\"delirium\"|\"lactation\"|\"glaucoma\"|\"obstruction\"|\"hypohidrosis\"|\"parity\"|\"palpitations\"| \"temperature\" \"intolerance\"|\"constipation\"|\"cyclophoria\"| \"acute\" \"coronary\" \"syndrome\"| \"arrhythmia\" \"supraventricular\"|\"arrest\"|\"lesion\"|\"nausea\"| \"sweating\" \"decreased\"|\"keratitis\"|\"dyskinesia\"| \"pulmonary\" \"function\" \"test\" \"decreased\"|\"stridor\"|\"swelling\"|\"dysphagia\"| \"haemoglobin\" \"decreased\"|\"diarrhoea\"| \"ileus\" \"paralytic\"|\"clonus\"|\"insomnia\"| \"electrocardiogram\" \"qrs\" \"complex\"| \"nasal\" \"congestion\"| \"nasal\" \"dryness\"|\"sweating\"|\"rash\"| \"nodal\" \"arrhythmia\"|\"irritability\"|\"hyperhidrosis\"| \"ventricular\" \"failure\")");


    Timing timing = new Timing();
    timing.start();
    for (int i = 0; i < 100; i++) {
      TokenSequenceMatcher m = p.getMatcher(doc.get(CoreAnnotations.TokensAnnotation.class));
      boolean match = m.find();
      assertTrue(match);
      assertEquals("atropine we need to have many many words here but we do n't sweating", m.group(0));

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    }
    timing.stop("testTokenSequenceOptimizeOrString matched");




    CoreMap docNoMatch = createDocument("atropine we need to have many many words here but we don't, many many many words but still no match");
    timing.start();
    for (int i = 0; i < 100; i++) {
      TokenSequenceMatcher m = p.getMatcher(docNoMatch.get(CoreAnnotations.TokensAnnotation.class));
      boolean match = m.find();
      assertFalse(match);
    }

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    // make a clique tree for this document
    CRFCliqueTree cliqueTree = CRFCliqueTree.getCalibratedCliqueTree(docData, labelIndices, numClasses, classIndex, backgroundSymbol, cliquePotentialFunc, featureVal3DArr);


    if (!skipValCalc) {
      if (TIMED)
        timer.start();
      // compute the log probability of the document given the model with the parameters x
      int[] given = new int[window - 1];
      Arrays.fill(given, classIndex.indexOf(backgroundSymbol));
      if (docLabels.length>docData.length) { // only true for self-training
        // fill the given array with the extra docLabels

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      EForADocPos = new ArrayList<Map<Integer, double[]>>(docData.length);
    }


    if (!skipExpectedCountCalc) {
      if (TIMED)
        timer.start();
      // compute the expected counts for this document, which we will need to compute the derivative
      // iterate over the positions in this document
      double fVal = 1.0;
      for (int i = 0; i < docData.length; i++) {
        Set<Integer> docDataHashI = docDataHash.get(i);

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