public override int CompareTo(IPokerHand other)
{
if (other is null)
{
return(1);
}
if (HandRank > other.HandRank)
{
return(1);
}
if (HandRank < other.HandRank)
{
return(-1);
}
var otherHand = (ThreeOfAkind)ConvertToThisType(other);
if (Triple.First().Rank > otherHand.Triple.First().Rank)
{
return(1);
}
if (Triple.First().Rank < otherHand.Triple.First().Rank)
{
return(-1);
}
return(Utils.ComapreCards(Kickers, otherHand.Kickers));
}
protected internal override double[] TrainWeights(int[][][][] data, int[][] labels, IEvaluator[] evaluators, int pruneFeatureItr, double[][][][] featureVals)
{
if (flags.secondOrderNonLinear)
{
CRFNonLinearSecondOrderLogConditionalObjectiveFunction func = new CRFNonLinearSecondOrderLogConditionalObjectiveFunction(data, labels, windowSize, classIndex, labelIndices, map, flags, nodeFeatureIndicesMap.Size(), edgeFeatureIndicesMap.Size
());
cliquePotentialFunctionHelper = func;
double[] allWeights = TrainWeightsUsingNonLinearCRF(func, evaluators);
Quadruple <double[][], double[][], double[][], double[][]> @params = func.SeparateWeights(allWeights);
this.inputLayerWeights4Edge = @params.First();
this.outputLayerWeights4Edge = @params.Second();
this.inputLayerWeights = @params.Third();
this.outputLayerWeights = @params.Fourth();
}
else
{
CRFNonLinearLogConditionalObjectiveFunction func = new CRFNonLinearLogConditionalObjectiveFunction(data, labels, windowSize, classIndex, labelIndices, map, flags, nodeFeatureIndicesMap.Size(), edgeFeatureIndicesMap.Size(), featureVals);
if (flags.useAdaGradFOBOS)
{
func.gradientsOnly = true;
}
cliquePotentialFunctionHelper = func;
double[] allWeights = TrainWeightsUsingNonLinearCRF(func, evaluators);
Triple <double[][], double[][], double[][]> @params = func.SeparateWeights(allWeights);
this.linearWeights = @params.First();
this.inputLayerWeights = @params.Second();
this.outputLayerWeights = @params.Third();
}
return(null);
}
private string GetConllEvalString(IList <L> orderedLabels, bool ignoreNegLabel)
{
StringBuilder sb = new StringBuilder();
int correctPhrases = GetCorrect() - GetCorrect(negLabel);
Triple <double, int, int> accuracyInfo = GetAccuracyInfo();
int totalCount = accuracyInfo.Second() + accuracyInfo.Third();
sb.Append("processed " + totalCount + " tokens with " + GetRelevant() + " phrases; ");
sb.Append("found: " + GetRetrieved() + " phrases; correct: " + correctPhrases + "\n");
Formatter formatter = new Formatter(sb, Locale.Us);
formatter.Format("accuracy: %6.2f%%; ", accuracyInfo.First() * 100);
formatter.Format("precision: %6.2f%%; ", GetPrecision() * 100);
formatter.Format("recall: %6.2f%%; ", GetRecall() * 100);
formatter.Format("FB1: %6.2f\n", GetFMeasure() * 100);
foreach (L label in orderedLabels)
{
if (ignoreNegLabel && label.Equals(negLabel))
{
continue;
}
formatter.Format("%17s: ", label);
formatter.Format("precision: %6.2f%%; ", GetPrecision(label) * 100);
formatter.Format("recall: %6.2f%%; ", GetRecall(label) * 100);
formatter.Format("FB1: %6.2f %d\n", GetFMeasure(label) * 100, GetRetrieved(label));
}
return(sb.ToString());
}
public override Triple<int[][][], int[], double[][][]> DocumentToDataAndLabels(IList<In> document)
{
Triple<int[][][], int[], double[][][]> result = base.DocumentToDataAndLabels(document);
int[][][] data = result.First();
data = TransformDocData(data);
return new Triple<int[][][], int[], double[][][]>(data, result.Second(), result.Third());
}
/// <summary>Returns a String summarizing overall accuracy that will print nicely.</summary>
public virtual string GetAccuracyDescription(int numDigits)
{
NumberFormat nf = NumberFormat.GetNumberInstance();
nf.SetMaximumFractionDigits(numDigits);
Triple <double, int, int> accu = GetAccuracyInfo();
return(nf.Format(accu.First()) + " (" + accu.Second() + "/" + (accu.Second() + accu.Third()) + ")");
}
public virtual string GetRecallDescription(int numDigits, L label)
{
NumberFormat nf = NumberFormat.GetNumberInstance();
nf.SetMaximumFractionDigits(numDigits);
Triple <double, int, int> recall = GetRecallInfo(label);
return(nf.Format(recall.First()) + " (" + recall.Second() + "/" + (recall.Second() + recall.Third()) + ")");
}
public virtual string GetPrecisionDescription(int numDigits, L label)
{
NumberFormat nf = NumberFormat.GetNumberInstance();
nf.SetMaximumFractionDigits(numDigits);
Triple <double, int, int> prec = GetPrecisionInfo(label);
return(nf.Format(prec.First()) + " (" + prec.Second() + "/" + (prec.Second() + prec.Third()) + ")");
}
private static void EmitSortedTrees(PriorityQueue <Triple <double, Tree, Tree> > queue, int worstKTreesToEmit, string filePrefix)
{
if (queue == null)
{
log.Info("Queue was not initialized properly");
}
try
{
PrintWriter guessPw = new PrintWriter(new BufferedWriter(new OutputStreamWriter(new FileOutputStream(filePrefix + ".kworst.guess"), "UTF-8")));
PrintWriter goldPw = new PrintWriter(new BufferedWriter(new OutputStreamWriter(new FileOutputStream(filePrefix + ".kworst.gold"), "UTF-8")));
IConstituentFactory cFact = new LabeledScoredConstituentFactory();
PrintWriter guessDepPw = new PrintWriter(new BufferedWriter(new OutputStreamWriter(new FileOutputStream(filePrefix + ".kworst.guess.deps"), "UTF-8")));
PrintWriter goldDepPw = new PrintWriter(new BufferedWriter(new OutputStreamWriter(new FileOutputStream(filePrefix + ".kworst.gold.deps"), "UTF-8")));
System.Console.Out.Printf("F1s of %d worst trees:\n", worstKTreesToEmit);
for (int i = 0; queue.Peek() != null && i < worstKTreesToEmit; i++)
{
Triple <double, Tree, Tree> trees = queue.Poll();
System.Console.Out.WriteLine(trees.First());
//Output the trees
goldPw.Println(trees.Second().ToString());
guessPw.Println(trees.Third().ToString());
//Output the set differences
ICollection <Constituent> goldDeps = Generics.NewHashSet();
Sharpen.Collections.AddAll(goldDeps, trees.Second().Constituents(cFact));
goldDeps.RemoveAll(trees.Third().Constituents(cFact));
foreach (Constituent c in goldDeps)
{
goldDepPw.Print(c.ToString() + " ");
}
goldDepPw.Println();
ICollection <Constituent> guessDeps = Generics.NewHashSet();
Sharpen.Collections.AddAll(guessDeps, trees.Third().Constituents(cFact));
guessDeps.RemoveAll(trees.Second().Constituents(cFact));
foreach (Constituent c_1 in guessDeps)
{
guessDepPw.Print(c_1.ToString() + " ");
}
guessDepPw.Println();
}
guessPw.Close();
goldPw.Close();
goldDepPw.Close();
guessDepPw.Close();
}
catch (UnsupportedEncodingException e)
{
Sharpen.Runtime.PrintStackTrace(e);
}
catch (FileNotFoundException e)
{
Sharpen.Runtime.PrintStackTrace(e);
}
}
public virtual int Compare(Triple <double, Tree, Tree> o1, Triple <double, Tree, Tree> o2)
{
double firstF1 = o1.First();
double secondF1 = o2.First();
if (firstF1 < secondF1)
{
return(-1);
}
else
{
if (firstF1 == secondF1)
{
return(0);
}
}
return(1);
}
public virtual void InitMC(List <Triple <double, int, int> > dataScores)
{
IPriorityQueue <Pair <int, Triple <double, int, int> > > q = new BinaryHeapPriorityQueue <Pair <int, Triple <double, int, int> > >();
for (int i = 0; i < dataScores.Count; i++)
{
q.Add(new Pair <int, Triple <double, int, int> >(int.Parse(i), dataScores[i]), -dataScores[i].First());
}
IList <Pair <int, Triple <double, int, int> > > sorted = q.ToSortedList();
scores = new double[sorted.Count];
classes = new int[sorted.Count];
guesses = new int[sorted.Count];
logger.Info("incoming size " + dataScores.Count + " resulting " + sorted.Count);
for (int i_1 = 0; i_1 < sorted.Count; i_1++)
{
Triple <double, int, int> next = sorted[i_1].Second();
scores[i_1] = next.First();
classes[i_1] = next.Second();
guesses[i_1] = next.Third();
}
Init();
}
private void RunParallelApplyPats(IDictionary <string, DataInstance> sents, string label, E pattern, TwoDimensionalCounter <CandidatePhrase, E> wordsandLemmaPatExtracted, CollectionValuedMap <E, Triple <string, int, int> > matchedTokensByPat, ICollection
<CandidatePhrase> alreadyLabeledWords)
{
Redwood.Log(Redwood.Dbg, "Applying pattern " + pattern + " to a total of " + sents.Count + " sentences ");
IList <string> notAllowedClasses = new List <string>();
IList <string> sentids = CollectionUtils.ToList(sents.Keys);
if (constVars.doNotExtractPhraseAnyWordLabeledOtherClass)
{
foreach (string l in constVars.GetAnswerClass().Keys)
{
if (!l.Equals(label))
{
notAllowedClasses.Add(l);
}
}
notAllowedClasses.Add("OTHERSEM");
}
IDictionary <TokenSequencePattern, E> surfacePatternsLearnedThisIterConverted = null;
IDictionary <SemgrexPattern, E> depPatternsLearnedThisIterConverted = null;
if (constVars.patternType.Equals(PatternFactory.PatternType.Surface))
{
surfacePatternsLearnedThisIterConverted = new Dictionary <TokenSequencePattern, E>();
string patternStr = null;
try
{
patternStr = pattern.ToString(notAllowedClasses);
TokenSequencePattern pat = ((TokenSequencePattern)TokenSequencePattern.Compile(constVars.env[label], patternStr));
surfacePatternsLearnedThisIterConverted[pat] = pattern;
}
catch (Exception e)
{
log.Info("Error applying pattern " + patternStr + ". Probably an ill formed pattern (can be because of special symbols in label names). Contact the software developer.");
throw;
}
}
else
{
if (constVars.patternType.Equals(PatternFactory.PatternType.Dep))
{
depPatternsLearnedThisIterConverted = new Dictionary <SemgrexPattern, E>();
SemgrexPattern pat = SemgrexPattern.Compile(pattern.ToString(notAllowedClasses), new Env(constVars.env[label].GetVariables()));
depPatternsLearnedThisIterConverted[pat] = pattern;
}
else
{
throw new NotSupportedException();
}
}
//Apply the patterns and extract candidate phrases
int num;
int numThreads = constVars.numThreads;
//If number of sentences is less, do not create so many threads
if (sents.Count < 50)
{
numThreads = 1;
}
if (numThreads == 1)
{
num = sents.Count;
}
else
{
num = sents.Count / (numThreads - 1);
}
IExecutorService executor = Executors.NewFixedThreadPool(constVars.numThreads);
IList <IFuture <Triple <TwoDimensionalCounter <CandidatePhrase, E>, CollectionValuedMap <E, Triple <string, int, int> >, ICollection <CandidatePhrase> > > > list = new List <IFuture <Triple <TwoDimensionalCounter <CandidatePhrase, E>, CollectionValuedMap <E
, Triple <string, int, int> >, ICollection <CandidatePhrase> > > >();
for (int i = 0; i < numThreads; i++)
{
ICallable <Triple <TwoDimensionalCounter <CandidatePhrase, E>, CollectionValuedMap <E, Triple <string, int, int> >, ICollection <CandidatePhrase> > > task = null;
if (pattern.type.Equals(PatternFactory.PatternType.Surface))
{
//Redwood.log(Redwood.DBG, "Applying pats: assigning sentences " + i*num + " to " +Math.min(sentids.size(), (i + 1) * num) + " to thread " + (i+1));
task = new ApplyPatterns(sents, num == sents.Count ? sentids : sentids.SubList(i * num, Math.Min(sentids.Count, (i + 1) * num)), surfacePatternsLearnedThisIterConverted, label, constVars.removeStopWordsFromSelectedPhrases, constVars.removePhrasesWithStopWords
, constVars);
}
else
{
task = new ApplyDepPatterns(sents, num == sents.Count ? sentids : sentids.SubList(i * num, Math.Min(sentids.Count, (i + 1) * num)), depPatternsLearnedThisIterConverted, label, constVars.removeStopWordsFromSelectedPhrases, constVars.removePhrasesWithStopWords
, constVars);
}
IFuture <Triple <TwoDimensionalCounter <CandidatePhrase, E>, CollectionValuedMap <E, Triple <string, int, int> >, ICollection <CandidatePhrase> > > submit = executor.Submit(task);
list.Add(submit);
}
// Now retrieve the result
foreach (IFuture <Triple <TwoDimensionalCounter <CandidatePhrase, E>, CollectionValuedMap <E, Triple <string, int, int> >, ICollection <CandidatePhrase> > > future in list)
{
try
{
Triple <TwoDimensionalCounter <CandidatePhrase, E>, CollectionValuedMap <E, Triple <string, int, int> >, ICollection <CandidatePhrase> > result = future.Get();
Redwood.Log(ConstantsAndVariables.extremedebug, "Pattern " + pattern + " extracted phrases " + result.First());
wordsandLemmaPatExtracted.AddAll(result.First());
matchedTokensByPat.AddAll(result.Second());
Sharpen.Collections.AddAll(alreadyLabeledWords, result.Third());
}
catch (Exception e)
{
executor.ShutdownNow();
throw new Exception(e);
}
}
executor.Shutdown();
}
public static Pair <string, IFileFilter> GetTreebankDescription(string[] args, int argIndex, string flag)
{
Triple <string, IFileFilter, double> description = GetWeightedTreebankDescription(args, argIndex, flag);
return(Pair.MakePair(description.First(), description.Second()));
}
