public virtual ClassicCounter <L> ScoresOf(RVFDatum <L, F> example)
{
ClassicCounter <L> scores = new ClassicCounter <L>();
Counters.AddInPlace(scores, priors);
if (addZeroValued)
{
Counters.AddInPlace(scores, priorZero);
}
foreach (L l in labels)
{
double score = 0.0;
ICounter <F> features = example.AsFeaturesCounter();
foreach (F f in features.KeySet())
{
int value = (int)features.GetCount(f);
score += Weight(l, f, int.Parse(value));
if (addZeroValued)
{
score -= Weight(l, f, zero);
}
}
scores.IncrementCount(l, score);
}
return(scores);
}
public virtual Edu.Stanford.Nlp.Stats.Dirichlet <E> GetPosteriorDistribution(ICounter <E> counts)
{
ICounter <E> newParameters = new ClassicCounter <E>(parameters);
Counters.AddInPlace(newParameters, counts);
return(new Edu.Stanford.Nlp.Stats.Dirichlet <E>(newParameters));
}
public virtual void AddAll(K1 key, ICounter <K2> c)
{
ClassicCounter <K2> myInner = GetCounter(key);
Counters.AddInPlace(myInner, c);
total += c.TotalCount();
}
public virtual ClassicCounter <OUT> LastRecall()
{
ClassicCounter <OUT> result = new ClassicCounter <OUT>();
Counters.AddInPlace(result, previousGoldCorrect);
Counters.DivideInPlace(result, previousGold);
return(result);
}
public virtual ClassicCounter <OUT> LastPrecision()
{
ClassicCounter <OUT> result = new ClassicCounter <OUT>();
Counters.AddInPlace(result, previousGuessedCorrect);
Counters.DivideInPlace(result, previousGuessed);
return(result);
}
public virtual void AddFeatures(ICollection <string> feat)
{
if (features == null)
{
features = new ClassicCounter <string>();
}
Counters.AddInPlace(features, feat);
}
public virtual void AddAll(ITwoDimensionalCounterInterface <K1, K2> c)
{
foreach (K1 key in c.FirstKeySet())
{
ICounter <K2> inner = c.GetCounter(key);
ClassicCounter <K2> myInner = GetCounter(key);
Counters.AddInPlace(myInner, inner);
total += inner.TotalCount();
}
}
public virtual void AddAll(Edu.Stanford.Nlp.Stats.TwoDimensionalIntCounter <K1, K2> c)
{
foreach (K1 key in c.FirstKeySet())
{
IntCounter <K2> inner = c.GetCounter(key);
IntCounter <K2> myInner = GetCounter(key);
Counters.AddInPlace(myInner, inner);
total += inner.TotalIntCount();
}
}
/// <summary>
/// Takes all the support vectors, and their corresponding alphas, and computes a weight
/// vector that can be used in a vanilla LinearClassifier.
/// </summary>
/// <remarks>
/// Takes all the support vectors, and their corresponding alphas, and computes a weight
/// vector that can be used in a vanilla LinearClassifier. This only works because
/// we are using a linear kernel. The Counter is over the feature indices (+1 cos for
/// some reason svm_light is 1-indexed), not features.
/// </remarks>
private static ClassicCounter <int> GetWeights(IList <Pair <double, ClassicCounter <int> > > supportVectors)
{
ClassicCounter <int> weights = new ClassicCounter <int>();
foreach (Pair <double, ClassicCounter <int> > sv in supportVectors)
{
ClassicCounter <int> c = new ClassicCounter <int>(sv.Second());
Counters.MultiplyInPlace(c, sv.First());
Counters.AddInPlace(weights, c);
}
return(weights);
}
public virtual void TestAddInPlaceCollection()
{
// initialize counter
SetUp();
IList <string> collection = new List <string>();
collection.Add("p");
collection.Add("p");
collection.Add("s");
Counters.AddInPlace(c1, collection);
NUnit.Framework.Assert.AreEqual(3.0, c1.GetCount("p"));
NUnit.Framework.Assert.AreEqual(5.0, c1.GetCount("s"));
}
/// <summary>
/// Use
/// <see cref="Edu.Stanford.Nlp.Trees.International.Spanish.SpanishXMLTreeReader"/>
/// to load the trees from the provided files,
/// and begin collecting some statistics to be used in later MWE cleanup.
/// NB: Much of the important cleanup happens implicitly here; the XML tree reader triggers the
/// tree normalization routine.
/// </summary>
/// <exception cref="System.Exception"/>
/// <exception cref="System.IO.IOException"/>
/// <exception cref="Java.Util.Concurrent.ExecutionException"/>
private IList <Tree> LoadTrees()
{
bool ner = PropertiesUtils.GetBool(options, "ner", false);
string encoding = new SpanishTreebankLanguagePack().GetEncoding();
SpanishXMLTreeReaderFactory trf = new SpanishXMLTreeReaderFactory(true, true, ner, false);
IList <Tree> trees = new List <Tree>();
foreach (File file in inputFiles)
{
Pair <TwoDimensionalCounter <string, string>, IList <Tree> > ret = ProcessTreeFile(file, trf, encoding);
Counters.AddInPlace(unigramTagger, ret.First());
Sharpen.Collections.AddAll(trees, ret.Second());
}
return(trees);
}
/// <param name="guesses">Collection of guessed objects</param>
/// <param name="golds">Collection of gold-standard objects</param>
/// <param name="pw">
///
/// <see cref="Java.IO.PrintWriter"/>
/// to print eval stats
/// </param>
public virtual void Eval(ICollection <In> guesses, ICollection <In> golds, PrintWriter pw)
{
if (verbose)
{
System.Console.Out.WriteLine("evaluating precision...");
}
Pair <ClassicCounter <OUT>, ClassicCounter <OUT> > precision = EvalPrecision(guesses, golds);
previousGuessed = precision.First();
Counters.AddInPlace(guessed, previousGuessed);
previousGuessedCorrect = precision.Second();
Counters.AddInPlace(guessedCorrect, previousGuessedCorrect);
if (verbose)
{
System.Console.Out.WriteLine("evaluating recall...");
}
Pair <ClassicCounter <OUT>, ClassicCounter <OUT> > recall = EvalPrecision(golds, guesses);
previousGold = recall.First();
Counters.AddInPlace(gold, previousGold);
previousGoldCorrect = recall.Second();
Counters.AddInPlace(goldCorrect, previousGoldCorrect);
}
/// <exception cref="System.IO.IOException"/>
/// <exception cref="System.TypeLoadException"/>
private ICounter <CandidatePhrase> LearnNewPhrasesPrivate(string label, PatternsForEachToken patternsForEachToken, ICounter <E> patternsLearnedThisIter, ICounter <E> allSelectedPatterns, ICollection <CandidatePhrase> alreadyIdentifiedWords, CollectionValuedMap
<E, Triple <string, int, int> > matchedTokensByPat, ICounter <CandidatePhrase> scoreForAllWordsThisIteration, TwoDimensionalCounter <CandidatePhrase, E> terms, TwoDimensionalCounter <CandidatePhrase, E> wordsPatExtracted, TwoDimensionalCounter <E
, CandidatePhrase> patternsAndWords4Label, string identifier, ICollection <CandidatePhrase> ignoreWords, bool computeProcDataFreq)
{
ICollection <CandidatePhrase> alreadyLabeledWords = new HashSet <CandidatePhrase>();
if (constVars.doNotApplyPatterns)
{
// if want to get the stats by the lossy way of just counting without
// applying the patterns
ConstantsAndVariables.DataSentsIterator sentsIter = new ConstantsAndVariables.DataSentsIterator(constVars.batchProcessSents);
while (sentsIter.MoveNext())
{
Pair <IDictionary <string, DataInstance>, File> sentsf = sentsIter.Current;
this.StatsWithoutApplyingPatterns(sentsf.First(), patternsForEachToken, patternsLearnedThisIter, wordsPatExtracted);
}
}
else
{
if (patternsLearnedThisIter.Size() > 0)
{
this.ApplyPats(patternsLearnedThisIter, label, wordsPatExtracted, matchedTokensByPat, alreadyLabeledWords);
}
}
if (computeProcDataFreq)
{
if (!phraseScorer.wordFreqNorm.Equals(PhraseScorer.Normalization.None))
{
Redwood.Log(Redwood.Dbg, "computing processed freq");
foreach (KeyValuePair <CandidatePhrase, double> fq in Data.rawFreq.EntrySet())
{
double @in = fq.Value;
if (phraseScorer.wordFreqNorm.Equals(PhraseScorer.Normalization.Sqrt))
{
@in = Math.Sqrt(@in);
}
else
{
if (phraseScorer.wordFreqNorm.Equals(PhraseScorer.Normalization.Log))
{
@in = 1 + Math.Log(@in);
}
else
{
throw new Exception("can't understand the normalization");
}
}
System.Diagnostics.Debug.Assert(!double.IsNaN(@in), "Why is processed freq nan when rawfreq is " + @in);
Data.processedDataFreq.SetCount(fq.Key, @in);
}
}
else
{
Data.processedDataFreq = Data.rawFreq;
}
}
if (constVars.wordScoring.Equals(GetPatternsFromDataMultiClass.WordScoring.Weightednorm))
{
foreach (CandidatePhrase en in wordsPatExtracted.FirstKeySet())
{
if (!constVars.GetOtherSemanticClassesWords().Contains(en) && (en.GetPhraseLemma() == null || !constVars.GetOtherSemanticClassesWords().Contains(CandidatePhrase.CreateOrGet(en.GetPhraseLemma()))) && !alreadyLabeledWords.Contains(en))
{
terms.AddAll(en, wordsPatExtracted.GetCounter(en));
}
}
RemoveKeys(terms, ConstantsAndVariables.GetStopWords());
ICounter <CandidatePhrase> phraseScores = phraseScorer.ScorePhrases(label, terms, wordsPatExtracted, allSelectedPatterns, alreadyIdentifiedWords, false);
System.Console.Out.WriteLine("count for word U.S. is " + phraseScores.GetCount(CandidatePhrase.CreateOrGet("U.S.")));
ICollection <CandidatePhrase> ignoreWordsAll;
if (ignoreWords != null && !ignoreWords.IsEmpty())
{
ignoreWordsAll = CollectionUtils.UnionAsSet(ignoreWords, constVars.GetOtherSemanticClassesWords());
}
else
{
ignoreWordsAll = new HashSet <CandidatePhrase>(constVars.GetOtherSemanticClassesWords());
}
Sharpen.Collections.AddAll(ignoreWordsAll, constVars.GetSeedLabelDictionary()[label]);
Sharpen.Collections.AddAll(ignoreWordsAll, constVars.GetLearnedWords(label).KeySet());
System.Console.Out.WriteLine("ignoreWordsAll contains word U.S. is " + ignoreWordsAll.Contains(CandidatePhrase.CreateOrGet("U.S.")));
ICounter <CandidatePhrase> finalwords = ChooseTopWords(phraseScores, terms, phraseScores, ignoreWordsAll, constVars.thresholdWordExtract);
phraseScorer.PrintReasonForChoosing(finalwords);
scoreForAllWordsThisIteration.Clear();
Counters.AddInPlace(scoreForAllWordsThisIteration, phraseScores);
Redwood.Log(ConstantsAndVariables.minimaldebug, "\n\n## Selected Words for " + label + " : " + Counters.ToSortedString(finalwords, finalwords.Size(), "%1$s:%2$.2f", "\t"));
if (constVars.goldEntities != null)
{
IDictionary <string, bool> goldEntities4Label = constVars.goldEntities[label];
if (goldEntities4Label != null)
{
StringBuilder s = new StringBuilder();
finalwords.KeySet().Stream().ForEach(null);
Redwood.Log(ConstantsAndVariables.minimaldebug, "\n\n## Gold labels for selected words for label " + label + " : " + s.ToString());
}
else
{
Redwood.Log(Redwood.Dbg, "No gold entities provided for label " + label);
}
}
if (constVars.outDir != null && !constVars.outDir.IsEmpty())
{
string outputdir = constVars.outDir + "/" + identifier + "/" + label;
IOUtils.EnsureDir(new File(outputdir));
TwoDimensionalCounter <CandidatePhrase, CandidatePhrase> reasonForWords = new TwoDimensionalCounter <CandidatePhrase, CandidatePhrase>();
foreach (CandidatePhrase word in finalwords.KeySet())
{
foreach (E l in wordsPatExtracted.GetCounter(word).KeySet())
{
foreach (CandidatePhrase w2 in patternsAndWords4Label.GetCounter(l))
{
reasonForWords.IncrementCount(word, w2);
}
}
}
Redwood.Log(ConstantsAndVariables.minimaldebug, "Saving output in " + outputdir);
string filename = outputdir + "/words.json";
// the json object is an array corresponding to each iteration - of list
// of objects,
// each of which is a bean of entity and reasons
IJsonArrayBuilder obj = Javax.Json.Json.CreateArrayBuilder();
if (writtenInJustification.Contains(label) && writtenInJustification[label])
{
IJsonReader jsonReader = Javax.Json.Json.CreateReader(new BufferedInputStream(new FileInputStream(filename)));
IJsonArray objarr = jsonReader.ReadArray();
foreach (IJsonValue o in objarr)
{
obj.Add(o);
}
jsonReader.Close();
}
IJsonArrayBuilder objThisIter = Javax.Json.Json.CreateArrayBuilder();
foreach (CandidatePhrase w in reasonForWords.FirstKeySet())
{
IJsonObjectBuilder objinner = Javax.Json.Json.CreateObjectBuilder();
IJsonArrayBuilder l = Javax.Json.Json.CreateArrayBuilder();
foreach (CandidatePhrase w2 in reasonForWords.GetCounter(w).KeySet())
{
l.Add(w2.GetPhrase());
}
IJsonArrayBuilder pats = Javax.Json.Json.CreateArrayBuilder();
foreach (E p in wordsPatExtracted.GetCounter(w))
{
pats.Add(p.ToStringSimple());
}
objinner.Add("reasonwords", l);
objinner.Add("patterns", pats);
objinner.Add("score", finalwords.GetCount(w));
objinner.Add("entity", w.GetPhrase());
objThisIter.Add(objinner.Build());
}
obj.Add(objThisIter);
// Redwood.log(ConstantsAndVariables.minimaldebug, channelNameLogger,
// "Writing justification at " + filename);
IOUtils.WriteStringToFile(StringUtils.Normalize(StringUtils.ToAscii(obj.Build().ToString())), filename, "ASCII");
writtenInJustification[label] = true;
}
if (constVars.justify)
{
Redwood.Log(Redwood.Dbg, "\nJustification for phrases:\n");
foreach (CandidatePhrase word in finalwords.KeySet())
{
Redwood.Log(Redwood.Dbg, "Phrase " + word + " extracted because of patterns: \t" + Counters.ToSortedString(wordsPatExtracted.GetCounter(word), wordsPatExtracted.GetCounter(word).Size(), "%1$s:%2$f", "\n"));
}
}
// if (usePatternResultAsLabel)
// if (answerLabel != null)
// labelWords(sents, commonEngWords, finalwords.keySet(),
// patterns.keySet(), outFile);
// else
// throw new RuntimeException("why is the answer label null?");
return(finalwords);
}
else
{
if (constVars.wordScoring.Equals(GetPatternsFromDataMultiClass.WordScoring.Bpb))
{
Counters.AddInPlace(terms, wordsPatExtracted);
ICounter <CandidatePhrase> maxPatWeightTerms = new ClassicCounter <CandidatePhrase>();
IDictionary <CandidatePhrase, E> wordMaxPat = new Dictionary <CandidatePhrase, E>();
foreach (KeyValuePair <CandidatePhrase, ClassicCounter <E> > en in terms.EntrySet())
{
ICounter <E> weights = new ClassicCounter <E>();
foreach (E k in en.Value.KeySet())
{
weights.SetCount(k, patternsLearnedThisIter.GetCount(k));
}
maxPatWeightTerms.SetCount(en.Key, Counters.Max(weights));
wordMaxPat[en.Key] = Counters.Argmax(weights);
}
Counters.RemoveKeys(maxPatWeightTerms, alreadyIdentifiedWords);
double maxvalue = Counters.Max(maxPatWeightTerms);
ICollection <CandidatePhrase> words = Counters.KeysAbove(maxPatWeightTerms, maxvalue - 1e-10);
CandidatePhrase bestw = null;
if (words.Count > 1)
{
double max = double.NegativeInfinity;
foreach (CandidatePhrase w in words)
{
if (terms.GetCount(w, wordMaxPat[w]) > max)
{
max = terms.GetCount(w, wordMaxPat[w]);
bestw = w;
}
}
}
else
{
if (words.Count == 1)
{
bestw = words.GetEnumerator().Current;
}
else
{
return(new ClassicCounter <CandidatePhrase>());
}
}
Redwood.Log(ConstantsAndVariables.minimaldebug, "Selected Words: " + bestw);
return(Counters.AsCounter(Arrays.AsList(bestw)));
}
else
{
throw new Exception("wordscoring " + constVars.wordScoring + " not identified");
}
}
}
/// <summary>
/// <inheritDoc/>
///
/// </summary>
public virtual void AddAll(ICounter <E> counter)
{
Counters.AddInPlace(this, counter);
}
/// <summary>Constructs a new Counter with the contents of the given Counter.</summary>
/// <remarks>
/// Constructs a new Counter with the contents of the given Counter.
/// <i>Implementation note:</i> A new Counter is allocated with its
/// own counts, but keys will be shared and should be an immutable class.
/// </remarks>
/// <param name="c">The Counter which will be copied.</param>
public ClassicCounter(ICounter <E> c)
: this()
{
Counters.AddInPlace(this, c);
SetDefaultReturnValue(c.DefaultReturnValue());
}
public virtual void TestClassicCounterHistoricalMain()
{
c.SetCount("p", 0);
c.SetCount("q", 2);
ClassicCounter <string> small_c = new ClassicCounter <string>(c);
ICounter <string> c7 = c.GetFactory().Create();
c7.AddAll(c);
NUnit.Framework.Assert.AreEqual(c.TotalCount(), 2.0);
c.IncrementCount("p");
NUnit.Framework.Assert.AreEqual(c.TotalCount(), 3.0);
c.IncrementCount("p", 2.0);
NUnit.Framework.Assert.AreEqual(Counters.Min(c), 2.0);
NUnit.Framework.Assert.AreEqual(Counters.Argmin(c), "q");
// Now p is p=3.0, q=2.0
c.SetCount("w", -5.0);
c.SetCount("x", -4.5);
IList <string> biggestKeys = new List <string>(c.KeySet());
NUnit.Framework.Assert.AreEqual(biggestKeys.Count, 4);
biggestKeys.Sort(Counters.ToComparator(c, false, true));
NUnit.Framework.Assert.AreEqual("w", biggestKeys[0]);
NUnit.Framework.Assert.AreEqual("x", biggestKeys[1]);
NUnit.Framework.Assert.AreEqual("p", biggestKeys[2]);
NUnit.Framework.Assert.AreEqual("q", biggestKeys[3]);
NUnit.Framework.Assert.AreEqual(Counters.Min(c), -5.0, Tolerance);
NUnit.Framework.Assert.AreEqual(Counters.Argmin(c), "w");
NUnit.Framework.Assert.AreEqual(Counters.Max(c), 3.0, Tolerance);
NUnit.Framework.Assert.AreEqual(Counters.Argmax(c), "p");
if (integral)
{
NUnit.Framework.Assert.AreEqual(Counters.Mean(c), -1.0);
}
else
{
NUnit.Framework.Assert.AreEqual(Counters.Mean(c), -1.125, Tolerance);
}
if (!integral)
{
// only do this for floating point counters. Too much bother to rewrite
c.SetCount("x", -2.5);
ClassicCounter <string> c2 = new ClassicCounter <string>(c);
NUnit.Framework.Assert.AreEqual(3.0, c2.GetCount("p"));
NUnit.Framework.Assert.AreEqual(2.0, c2.GetCount("q"));
NUnit.Framework.Assert.AreEqual(-5.0, c2.GetCount("w"));
NUnit.Framework.Assert.AreEqual(-2.5, c2.GetCount("x"));
ICounter <string> c3 = c.GetFactory().Create();
foreach (string str in c2.KeySet())
{
c3.IncrementCount(str);
}
NUnit.Framework.Assert.AreEqual(1.0, c3.GetCount("p"));
NUnit.Framework.Assert.AreEqual(1.0, c3.GetCount("q"));
NUnit.Framework.Assert.AreEqual(1.0, c3.GetCount("w"));
NUnit.Framework.Assert.AreEqual(1.0, c3.GetCount("x"));
Counters.AddInPlace(c2, c3, 10.0);
NUnit.Framework.Assert.AreEqual(13.0, c2.GetCount("p"));
NUnit.Framework.Assert.AreEqual(12.0, c2.GetCount("q"));
NUnit.Framework.Assert.AreEqual(5.0, c2.GetCount("w"));
NUnit.Framework.Assert.AreEqual(7.5, c2.GetCount("x"));
c3.AddAll(c);
NUnit.Framework.Assert.AreEqual(4.0, c3.GetCount("p"));
NUnit.Framework.Assert.AreEqual(3.0, c3.GetCount("q"));
NUnit.Framework.Assert.AreEqual(-4.0, c3.GetCount("w"));
NUnit.Framework.Assert.AreEqual(-1.5, c3.GetCount("x"));
Counters.SubtractInPlace(c3, c);
NUnit.Framework.Assert.AreEqual(1.0, c3.GetCount("p"));
NUnit.Framework.Assert.AreEqual(1.0, c3.GetCount("q"));
NUnit.Framework.Assert.AreEqual(1.0, c3.GetCount("w"));
NUnit.Framework.Assert.AreEqual(1.0, c3.GetCount("x"));
foreach (string str_1 in c.KeySet())
{
c3.IncrementCount(str_1);
}
NUnit.Framework.Assert.AreEqual(2.0, c3.GetCount("p"));
NUnit.Framework.Assert.AreEqual(2.0, c3.GetCount("q"));
NUnit.Framework.Assert.AreEqual(2.0, c3.GetCount("w"));
NUnit.Framework.Assert.AreEqual(2.0, c3.GetCount("x"));
Counters.DivideInPlace(c2, c3);
NUnit.Framework.Assert.AreEqual(6.5, c2.GetCount("p"));
NUnit.Framework.Assert.AreEqual(6.0, c2.GetCount("q"));
NUnit.Framework.Assert.AreEqual(2.5, c2.GetCount("w"));
NUnit.Framework.Assert.AreEqual(3.75, c2.GetCount("x"));
Counters.DivideInPlace(c2, 0.5);
NUnit.Framework.Assert.AreEqual(13.0, c2.GetCount("p"));
NUnit.Framework.Assert.AreEqual(12.0, c2.GetCount("q"));
NUnit.Framework.Assert.AreEqual(5.0, c2.GetCount("w"));
NUnit.Framework.Assert.AreEqual(7.5, c2.GetCount("x"));
Counters.MultiplyInPlace(c2, 2.0);
NUnit.Framework.Assert.AreEqual(26.0, c2.GetCount("p"));
NUnit.Framework.Assert.AreEqual(24.0, c2.GetCount("q"));
NUnit.Framework.Assert.AreEqual(10.0, c2.GetCount("w"));
NUnit.Framework.Assert.AreEqual(15.0, c2.GetCount("x"));
Counters.DivideInPlace(c2, 2.0);
NUnit.Framework.Assert.AreEqual(13.0, c2.GetCount("p"));
NUnit.Framework.Assert.AreEqual(12.0, c2.GetCount("q"));
NUnit.Framework.Assert.AreEqual(5.0, c2.GetCount("w"));
NUnit.Framework.Assert.AreEqual(7.5, c2.GetCount("x"));
foreach (string str_2 in c2.KeySet())
{
c2.IncrementCount(str_2);
}
NUnit.Framework.Assert.AreEqual(14.0, c2.GetCount("p"));
NUnit.Framework.Assert.AreEqual(13.0, c2.GetCount("q"));
NUnit.Framework.Assert.AreEqual(6.0, c2.GetCount("w"));
NUnit.Framework.Assert.AreEqual(8.5, c2.GetCount("x"));
foreach (string str_3 in c.KeySet())
{
c2.IncrementCount(str_3);
}
NUnit.Framework.Assert.AreEqual(15.0, c2.GetCount("p"));
NUnit.Framework.Assert.AreEqual(14.0, c2.GetCount("q"));
NUnit.Framework.Assert.AreEqual(7.0, c2.GetCount("w"));
NUnit.Framework.Assert.AreEqual(9.5, c2.GetCount("x"));
c2.AddAll(small_c);
NUnit.Framework.Assert.AreEqual(15.0, c2.GetCount("p"));
NUnit.Framework.Assert.AreEqual(16.0, c2.GetCount("q"));
NUnit.Framework.Assert.AreEqual(7.0, c2.GetCount("w"));
NUnit.Framework.Assert.AreEqual(9.5, c2.GetCount("x"));
NUnit.Framework.Assert.AreEqual(new HashSet <string>(Arrays.AsList("p", "q")), Counters.KeysAbove(c2, 14));
NUnit.Framework.Assert.AreEqual(new HashSet <string>(Arrays.AsList("q")), Counters.KeysAt(c2, 16));
NUnit.Framework.Assert.AreEqual(new HashSet <string>(Arrays.AsList("x", "w")), Counters.KeysBelow(c2, 9.5));
Counters.AddInPlace(c2, small_c, -6);
NUnit.Framework.Assert.AreEqual(15.0, c2.GetCount("p"));
NUnit.Framework.Assert.AreEqual(4.0, c2.GetCount("q"));
NUnit.Framework.Assert.AreEqual(7.0, c2.GetCount("w"));
NUnit.Framework.Assert.AreEqual(9.5, c2.GetCount("x"));
Counters.SubtractInPlace(c2, small_c);
Counters.SubtractInPlace(c2, small_c);
Counters.RetainNonZeros(c2);
NUnit.Framework.Assert.AreEqual(15.0, c2.GetCount("p"));
NUnit.Framework.Assert.IsFalse(c2.ContainsKey("q"));
NUnit.Framework.Assert.AreEqual(7.0, c2.GetCount("w"));
NUnit.Framework.Assert.AreEqual(9.5, c2.GetCount("x"));
}
// serialize to Stream
if (c is ISerializable)
{
try
{
ByteArrayOutputStream baos = new ByteArrayOutputStream();
ObjectOutputStream @out = new ObjectOutputStream(new BufferedOutputStream(baos));
@out.WriteObject(c);
@out.Close();
// reconstitute
byte[] bytes = baos.ToByteArray();
ObjectInputStream @in = new ObjectInputStream(new BufferedInputStream(new ByteArrayInputStream(bytes)));
c = IOUtils.ReadObjectFromObjectStream(@in);
@in.Close();
if (!this.integral)
{
NUnit.Framework.Assert.AreEqual(-2.5, c.TotalCount());
NUnit.Framework.Assert.AreEqual(-5.0, Counters.Min(c));
NUnit.Framework.Assert.AreEqual("w", Counters.Argmin(c));
}
c.Clear();
if (!this.integral)
{
NUnit.Framework.Assert.AreEqual(0.0, c.TotalCount());
}
}
catch (IOException ioe)
{
Fail("IOException: " + ioe);
}
catch (TypeLoadException cce)
{
Fail("ClassNotFoundException: " + cce);
}
}
}