public virtual bool Match(Context env, Concept check, GetValue propfunc, params object[] args)
{
// Apply propfunc now, and save for later
object value = propfunc(check, args);
bool matched = false;
if (value is Concept)
{
matched = IsMatch((Concept)value);
}
else if (value is IParsedPhrase)
{
matched = IsMatch((IParsedPhrase)value);
}
if (matched)
{
object propogate = new ThreeTuple <GetValue, object, object[]>(propfunc, check, args);
Propogate(env, propogate, 1.0);
return(true);
}
return(false);
}
static void Main(string[] args)
{
var personDetails = Console.ReadLine().Split();
string personName = personDetails[0] + " " + personDetails[1];
string personAdress = personDetails[2];
string town = personDetails[3];
ThreeTuple <string, string, string> personTuple = new ThreeTuple <string, string, string>(personName, personAdress, town);
var drunkInput = Console.ReadLine().Split();
string name = drunkInput[0];
int beer = int.Parse(drunkInput[1]);
bool drunkOrNot = drunkInput[2] == "drunk";
ThreeTuple <string, int, bool> drunkTuple = new ThreeTuple <string, int, bool>(name, beer, drunkOrNot);
var bankBalance = Console.ReadLine().Split();
string accountName = bankBalance[0];
double accountBalance = double.Parse(bankBalance[1]);
string bankName = bankBalance[2];
ThreeTuple <string, double, string> numTuple = new ThreeTuple <string, double, string>(accountName, accountBalance, bankName);
Console.WriteLine(personTuple);
Console.WriteLine(drunkTuple);
Console.WriteLine(numTuple);
}
ImputeEmotionalContentFromFile(string filename, uint column, uint repeats, string imputesave)
{
MemorySource <string, ThreeTuple <ContinuousDistribution, ContinuousDistribution, ContinuousDistribution> > imputed = new MemorySource <string, ThreeTuple <ContinuousDistribution, ContinuousDistribution, ContinuousDistribution> >();
ComboSource <string, ThreeTuple <ContinuousDistribution, ContinuousDistribution, ContinuousDistribution> > combo = new ComboSource <string, ThreeTuple <ContinuousDistribution, ContinuousDistribution, ContinuousDistribution> >(source, imputed);
// Check for existing imputed file
DataReader imputereader = new DataReader(imputesave);
uint kk = 0;
for (string[] row = imputereader.ReadRow(); row != null; row = imputereader.ReadRow())
{
kk++;
if (kk % 1000 == 0)
{
Console.WriteLine("#" + kk);
}
double meanv = double.Parse(row[1]), varv = double.Parse(row[2]), meana = double.Parse(row[3]), vara = double.Parse(row[4]), meand = double.Parse(row[5]), vard = double.Parse(row[6]);
ContinuousDistribution valence = new ClippedGaussianDistribution(meanv, varv, 0, 1);
ContinuousDistribution arousal = new ClippedGaussianDistribution(meana, vara, 0, 1);
ContinuousDistribution dominance = new ClippedGaussianDistribution(meand, vard, 0, 1);
imputed[row[0]] = new ThreeTuple <ContinuousDistribution, ContinuousDistribution, ContinuousDistribution>(valence, arousal, dominance);
}
imputereader.Close();
for (uint ii = 0; ii < repeats; ii++)
{
Dictionary <string, List <KeyValuePair <double, double> > >
sentencesV = new Dictionary <string, List <KeyValuePair <double, double> > >(),
sentencesA = new Dictionary <string, List <KeyValuePair <double, double> > >(),
sentencesD = new Dictionary <string, List <KeyValuePair <double, double> > >();
DataReader reader = new DataReader(filename);
uint jj = 0;
for (string[] row = reader.ReadRow(); row != null; row = reader.ReadRow())
{
jj++;
if (jj % 1000 == 0)
{
Console.WriteLine("#" + jj + ": " + sentencesV.Count + ", " + imputed.Count);
}
List <string> words = TwitterUtilities.SplitWords(row[column].ToLower());
AnalyzeWords(words, combo, sentencesV, sentencesA, sentencesD);
}
reader.Close();
AnalyzeSentences(imputed, sentencesV, sentencesA, sentencesD, imputesave);
}
source = combo;
return(imputed);
}
public bool TryGetWordOrStem(IDataSource <string, ThreeTuple <ContinuousDistribution, ContinuousDistribution, ContinuousDistribution> > source,
string word, out ThreeTuple <ContinuousDistribution, ContinuousDistribution, ContinuousDistribution> vad)
{
if (!source.TryGetValue(word, out vad))
{
// try stemmed word
string stem = stemmer.stemTerm(word);
if (stem == word || !source.TryGetValue(stem, out vad))
{
return(false);
}
}
return(true);
}
static void Main()
{
string[] inputRow1 = Console.ReadLine().Split();
ThreeTuple<string, string, string> t1= new ThreeTuple<string, string, string>(inputRow1[0]+" "+inputRow1[1],inputRow1[2],inputRow1[3]);
string[] inputRow2 = Console.ReadLine().Split();
bool arg = false;
if (inputRow2[2] == "drunk")
{
arg = true;
}
ThreeTuple<string, int, bool> t2 = new ThreeTuple<string, int, bool>(inputRow2[0], int.Parse(inputRow2[1]), arg );
string[] inputRow3 = Console.ReadLine().Split();
ThreeTuple<string, double, string> t3 = new ThreeTuple<string, double, string>(inputRow3[0], double.Parse(inputRow3[1]), inputRow3[2]);
Console.WriteLine($"{t1.Key} -> {t1.FirstValue} -> {t1.SecondValue}");
Console.WriteLine($"{t2.Key} -> {t2.FirstValue} -> {t2.SecondValue}");
Console.WriteLine("{0} -> {1:f1} -> {2}",t3.Key,t3.FirstValue,t3.SecondValue);
}
public void AnalyzeSentences(MemorySource <string, ThreeTuple <ContinuousDistribution, ContinuousDistribution, ContinuousDistribution> > inputed,
Dictionary <string, List <KeyValuePair <double, double> > > sentencesV,
Dictionary <string, List <KeyValuePair <double, double> > > sentencesA,
Dictionary <string, List <KeyValuePair <double, double> > > sentencesD, string imputesave)
{
using (var stream = File.CreateText(imputesave)) {
foreach (string stem in sentencesV.Keys)
{
double vmean = WeightedStatistics.Mean(sentencesV[stem]), amean = WeightedStatistics.Mean(sentencesA[stem]), dmean = WeightedStatistics.Mean(sentencesD[stem]);
ClippedGaussianDistribution valence = new ClippedGaussianDistribution(vmean, WeightedStatistics.Variance(sentencesV[stem], vmean, true), 0, 1);
ClippedGaussianDistribution arousal = new ClippedGaussianDistribution(amean, WeightedStatistics.Variance(sentencesA[stem], amean, true), 0, 1);
ClippedGaussianDistribution dominance = new ClippedGaussianDistribution(dmean, WeightedStatistics.Variance(sentencesD[stem], dmean, true), 0, 1);
inputed[stem] = new ThreeTuple <ContinuousDistribution, ContinuousDistribution, ContinuousDistribution>(valence, arousal, dominance);
stream.WriteLine(stem + "," + valence.InternalMean + "," + valence.InternalVariance + "," + arousal.InternalMean + "," + arousal.InternalVariance + "," + dominance.InternalMean + "," + dominance.InternalVariance);
}
}
}
public virtual bool Match(Context env, Concept check, GetValue propfunc, params object[] args)
{
// Apply propfunc now, and save for later
object value = propfunc(check, args);
bool matched = false;
if (value is Concept)
matched = IsMatch((Concept) value);
else if (value is IParsedPhrase)
matched = IsMatch((IParsedPhrase) value);
if (matched)
{
object propogate = new ThreeTuple<GetValue, object, object[]>(propfunc, check, args);
Propogate(env, propogate, 1.0);
return true;
}
return false;
}
public virtual IParsedPhrase Produce(Context env, POSTagger tagger, GrammarParser parser)
{
object var = env.LookupDefaulted <object>("$p$" + name, null);
if (var is ThreeTuple <GetValue, object, object[]> )
{
ThreeTuple <GetValue, object, object[]> tuple = (ThreeTuple <GetValue, object, object[]>)var;
var = tuple.one(tuple.two, tuple.three);
}
if (var is IParsedPhrase)
{
return((IParsedPhrase)var);
}
else if (var is Concept)
{
return(ConceptToPhrase(env, (Concept)var, tagger, parser));
}
return(null); // don't produce anything!
}
public ScatterDataPoint(ThreeTuple <float> coords, float value)
{
this.Coords = coords;
this.Value = value;
}
public void Populate()
{
#region Types of Keywords
FieldPublicDynamic = new { PropPublic1 = "A", PropPublic2 = 1, PropPublic3 = "B", PropPublic4 = "B", PropPublic5 = "B", PropPublic6 = "B", PropPublic7 = "B", PropPublic8 = "B", PropPublic9 = "B", PropPublic10 = "B", PropPublic11 = "B", PropPublic12 = new { PropSubPublic1 = 0, PropSubPublic2 = 1, PropSubPublic3 = 2 } };
FieldPublicObject = new StringBuilder("Object - StringBuilder");
FieldPublicInt32 = int.MaxValue;
FieldPublicInt64 = long.MaxValue;
FieldPublicULong = ulong.MaxValue;
FieldPublicUInt = uint.MaxValue;
FieldPublicDecimal = 100000.999999m;
FieldPublicDouble = 100000.999999d;
FieldPublicChar = 'A';
FieldPublicByte = byte.MaxValue;
FieldPublicBoolean = true;
FieldPublicSByte = sbyte.MaxValue;
FieldPublicShort = short.MaxValue;
FieldPublicUShort = ushort.MaxValue;
FieldPublicFloat = 100000.675555f;
FieldPublicInt32Nullable = int.MaxValue;
FieldPublicInt64Nullable = 2;
FieldPublicULongNullable = ulong.MaxValue;
FieldPublicUIntNullable = uint.MaxValue;
FieldPublicDecimalNullable = 100000.999999m;
FieldPublicDoubleNullable = 100000.999999d;
FieldPublicCharNullable = 'A';
FieldPublicByteNullable = byte.MaxValue;
FieldPublicBooleanNullable = true;
FieldPublicSByteNullable = sbyte.MaxValue;
FieldPublicShortNullable = short.MaxValue;
FieldPublicUShortNullable = ushort.MaxValue;
FieldPublicFloatNullable = 100000.675555f;
#endregion
#region System
FieldPublicDateTime = new DateTime(2000, 1, 1, 1, 1, 1);
FieldPublicTimeSpan = new TimeSpan(1, 10, 40);
FieldPublicEnumDateTimeKind = DateTimeKind.Local;
// Instantiate date and time using Persian calendar with years,
// months, days, hours, minutes, seconds, and milliseconds
FieldPublicDateTimeOffset = new DateTimeOffset(1387, 2, 12, 8, 6, 32, 545,
new System.Globalization.PersianCalendar(),
new TimeSpan(1, 0, 0));
FieldPublicIntPtr = new IntPtr(100);
FieldPublicTimeZone = TimeZone.CurrentTimeZone;
FieldPublicTimeZoneInfo = TimeZoneInfo.Utc;
FieldPublicTuple = Tuple.Create <string, int, decimal>("T-string\"", 1, 1.1m);
FieldPublicType = typeof(object);
FieldPublicUIntPtr = new UIntPtr(100);
FieldPublicUri = new Uri("http://www.site.com");
FieldPublicVersion = new Version(1, 0, 100, 1);
FieldPublicGuid = new Guid("d5010f5b-0cd1-44ca-aacb-5678b9947e6c");
FieldPublicSingle = Single.MaxValue;
FieldPublicException = new Exception("Test error", new Exception("inner exception"));
FieldPublicEnumNonGeneric = EnumTest.ValueA;
FieldPublicAction = () => true.Equals(true);
FieldPublicAction2 = (a, b) => true.Equals(true);
FieldPublicFunc = () => true;
FieldPublicFunc2 = (a, b) => true;
#endregion
#region Arrays and Collections
FieldPublicArrayUni = new string[2];
FieldPublicArrayUni[0] = "[0]";
FieldPublicArrayUni[1] = "[1]";
FieldPublicArrayTwo = new string[2, 2];
FieldPublicArrayTwo[0, 0] = "[0, 0]";
FieldPublicArrayTwo[0, 1] = "[0, 1]";
FieldPublicArrayTwo[1, 0] = "[1, 0]";
FieldPublicArrayTwo[1, 1] = "[1, 1]";
FieldPublicArrayThree = new string[1, 1, 2];
FieldPublicArrayThree[0, 0, 0] = "[0, 0, 0]";
FieldPublicArrayThree[0, 0, 1] = "[0, 0, 1]";
FieldPublicJaggedArrayTwo = new string[2][];
FieldPublicJaggedArrayTwo[0] = new string[5] {
"a", "b", "c", "d", "e"
};
FieldPublicJaggedArrayTwo[1] = new string[4] {
"a1", "b1", "c1", "d1"
};
FieldPublicJaggedArrayThree = new string[1][][];
FieldPublicJaggedArrayThree[0] = new string[1][];
FieldPublicJaggedArrayThree[0][0] = new string[2];
FieldPublicJaggedArrayThree[0][0][0] = "[0][0][0]";
FieldPublicJaggedArrayThree[0][0][1] = "[0][0][1]";
FieldPublicMixedArrayAndJagged = new int[3][, ]
{
new int[, ] {
{ 1, 3 }, { 5, 7 }
},
new int[, ] {
{ 0, 2 }, { 4, 6 }, { 8, 10 }
},
new int[, ] {
{ 11, 22 }, { 99, 88 }, { 0, 9 }
}
};
FieldPublicDictionary = new System.Collections.Generic.Dictionary <string, string>();
FieldPublicDictionary.Add("Key1", "Value1");
FieldPublicDictionary.Add("Key2", "Value2");
FieldPublicDictionary.Add("Key3", "Value3");
FieldPublicDictionary.Add("Key4", "Value4");
FieldPublicList = new System.Collections.Generic.List <int>();
FieldPublicList.Add(0);
FieldPublicList.Add(1);
FieldPublicList.Add(2);
FieldPublicQueue = new System.Collections.Generic.Queue <int>();
FieldPublicQueue.Enqueue(10);
FieldPublicQueue.Enqueue(11);
FieldPublicQueue.Enqueue(12);
FieldPublicHashSet = new System.Collections.Generic.HashSet <string>();
FieldPublicHashSet.Add("HashSet1");
FieldPublicHashSet.Add("HashSet2");
FieldPublicSortedSet = new System.Collections.Generic.SortedSet <string>();
FieldPublicSortedSet.Add("SortedSet1");
FieldPublicSortedSet.Add("SortedSet2");
FieldPublicSortedSet.Add("SortedSet3");
FieldPublicStack = new System.Collections.Generic.Stack <string>();
FieldPublicStack.Push("Stack1");
FieldPublicStack.Push("Stack2");
FieldPublicStack.Push("Stack3");
FieldPublicLinkedList = new System.Collections.Generic.LinkedList <string>();
FieldPublicLinkedList.AddFirst("LinkedList1");
FieldPublicLinkedList.AddLast("LinkedList2");
FieldPublicLinkedList.AddAfter(FieldPublicLinkedList.Find("LinkedList1"), "LinkedList1.1");
FieldPublicObservableCollection = new System.Collections.ObjectModel.ObservableCollection <string>();
FieldPublicObservableCollection.Add("ObservableCollection1");
FieldPublicObservableCollection.Add("ObservableCollection2");
FieldPublicKeyedCollection = new MyDataKeyedCollection();
FieldPublicKeyedCollection.Add(new MyData()
{
Data = "data1", Id = 0
});
FieldPublicKeyedCollection.Add(new MyData()
{
Data = "data2", Id = 1
});
var list = new List <string>();
list.Add("list1");
list.Add("list2");
list.Add("list3");
FieldPublicReadOnlyCollection = new ReadOnlyCollection <string>(list);
FieldPublicReadOnlyDictionary = new ReadOnlyDictionary <string, string>(FieldPublicDictionary);
FieldPublicReadOnlyObservableCollection = new ReadOnlyObservableCollection <string>(FieldPublicObservableCollection);
FieldPublicCollection = new Collection <string>();
FieldPublicCollection.Add("collection1");
FieldPublicCollection.Add("collection2");
FieldPublicCollection.Add("collection3");
FieldPublicArrayListNonGeneric = new System.Collections.ArrayList();
FieldPublicArrayListNonGeneric.Add(1);
FieldPublicArrayListNonGeneric.Add("a");
FieldPublicArrayListNonGeneric.Add(10.0m);
FieldPublicArrayListNonGeneric.Add(new DateTime(2000, 01, 01));
FieldPublicBitArray = new System.Collections.BitArray(3);
FieldPublicBitArray[2] = true;
FieldPublicSortedList = new System.Collections.SortedList();
FieldPublicSortedList.Add("key1", 1);
FieldPublicSortedList.Add("key2", 2);
FieldPublicSortedList.Add("key3", 3);
FieldPublicSortedList.Add("key4", 4);
FieldPublicHashtableNonGeneric = new System.Collections.Hashtable();
FieldPublicHashtableNonGeneric.Add("key1", 1);
FieldPublicHashtableNonGeneric.Add("key2", 2);
FieldPublicHashtableNonGeneric.Add("key3", 3);
FieldPublicHashtableNonGeneric.Add("key4", 4);
FieldPublicQueueNonGeneric = new System.Collections.Queue();
FieldPublicQueueNonGeneric.Enqueue("QueueNonGeneric1");
FieldPublicQueueNonGeneric.Enqueue("QueueNonGeneric2");
FieldPublicQueueNonGeneric.Enqueue("QueueNonGeneric3");
FieldPublicStackNonGeneric = new System.Collections.Stack();
FieldPublicStackNonGeneric.Push("StackNonGeneric1");
FieldPublicStackNonGeneric.Push("StackNonGeneric2");
FieldPublicIEnumerable = FieldPublicSortedList;
FieldPublicBlockingCollection = new System.Collections.Concurrent.BlockingCollection <string>();
FieldPublicBlockingCollection.Add("BlockingCollection1");
FieldPublicBlockingCollection.Add("BlockingCollection2");
FieldPublicConcurrentBag = new System.Collections.Concurrent.ConcurrentBag <string>();
FieldPublicConcurrentBag.Add("ConcurrentBag1");
FieldPublicConcurrentBag.Add("ConcurrentBag2");
FieldPublicConcurrentBag.Add("ConcurrentBag3");
FieldPublicConcurrentDictionary = new System.Collections.Concurrent.ConcurrentDictionary <string, int>();
FieldPublicConcurrentDictionary.GetOrAdd("ConcurrentDictionary1", 0);
FieldPublicConcurrentDictionary.GetOrAdd("ConcurrentDictionary2", 0);
FieldPublicConcurrentQueue = new System.Collections.Concurrent.ConcurrentQueue <string>();
FieldPublicConcurrentQueue.Enqueue("ConcurrentQueue1");
FieldPublicConcurrentQueue.Enqueue("ConcurrentQueue2");
FieldPublicConcurrentStack = new System.Collections.Concurrent.ConcurrentStack <string>();
FieldPublicConcurrentStack.Push("ConcurrentStack1");
FieldPublicConcurrentStack.Push("ConcurrentStack2");
// FieldPublicOrderablePartitioner = new OrderablePartitioner();
// FieldPublicPartitioner;
// FieldPublicPartitionerNonGeneric;
FieldPublicHybridDictionary = new System.Collections.Specialized.HybridDictionary();
FieldPublicHybridDictionary.Add("HybridDictionaryKey1", "HybridDictionary1");
FieldPublicHybridDictionary.Add("HybridDictionaryKey2", "HybridDictionary2");
FieldPublicListDictionary = new System.Collections.Specialized.ListDictionary();
FieldPublicListDictionary.Add("ListDictionaryKey1", "ListDictionary1");
FieldPublicListDictionary.Add("ListDictionaryKey2", "ListDictionary2");
FieldPublicNameValueCollection = new System.Collections.Specialized.NameValueCollection();
FieldPublicNameValueCollection.Add("Key1", "Value1");
FieldPublicNameValueCollection.Add("Key2", "Value2");
FieldPublicOrderedDictionary = new System.Collections.Specialized.OrderedDictionary();
FieldPublicOrderedDictionary.Add(1, "OrderedDictionary1");
FieldPublicOrderedDictionary.Add(2, "OrderedDictionary1");
FieldPublicOrderedDictionary.Add("OrderedDictionaryKey2", "OrderedDictionary2");
FieldPublicStringCollection = new System.Collections.Specialized.StringCollection();
FieldPublicStringCollection.Add("StringCollection1");
FieldPublicStringCollection.Add("StringCollection2");
#endregion
#region Several
PropXmlDocument = new XmlDocument();
PropXmlDocument.LoadXml("<xml>something</xml>");
var tr = new StringReader("<Root>Content</Root>");
PropXDocument = XDocument.Load(tr);
PropStream = GenerateStreamFromString("Stream");
PropBigInteger = new System.Numerics.BigInteger(100);
PropStringBuilder = new StringBuilder("StringBuilder");
FieldPublicIQueryable = new List <string>()
{
"IQueryable"
}.AsQueryable();
#endregion
#region Custom
FieldPublicMyCollectionPublicGetEnumerator = new MyCollectionPublicGetEnumerator("a b c", new char[] { ' ' });
FieldPublicMyCollectionInheritsPublicGetEnumerator = new MyCollectionInheritsPublicGetEnumerator("a b c", new char[] { ' ' });
FieldPublicMyCollectionExplicitGetEnumerator = new MyCollectionExplicitGetEnumerator("a b c", new char[] { ' ' });
FieldPublicMyCollectionInheritsExplicitGetEnumerator = new MyCollectionInheritsExplicitGetEnumerator("a b c", new char[] { ' ' });
FieldPublicMyCollectionInheritsTooIEnumerable = new MyCollectionInheritsTooIEnumerable("a b c", new char[] { ' ' });
FieldPublicEnumSpecific = EnumTest.ValueB;
MyDelegate = MethodDelegate;
EmptyClass = new EmptyClass();
StructGeneric = new ThreeTuple <int>(0, 1, 2);
StructGenericNullable = new ThreeTuple <int>(0, 1, 2);
FieldPublicNullable = new Nullable <ThreeTuple <int> >(StructGeneric);
#endregion
}
public bool TryGetWordOrStem(IDataSource<string, ThreeTuple<ContinuousDistribution, ContinuousDistribution, ContinuousDistribution>> source,
string word, out ThreeTuple<ContinuousDistribution, ContinuousDistribution, ContinuousDistribution> vad)
{
if (!source.TryGetValue(word, out vad)) {
// try stemmed word
string stem = stemmer.stemTerm(word);
if (stem == word || !source.TryGetValue(stem, out vad))
return false;
}
return true;
}
public IDataSource<string, ThreeTuple<ContinuousDistribution, ContinuousDistribution, ContinuousDistribution>> ImputeEmotionalContentFromFile(string filename, uint column, uint repeats, string imputesave)
{
MemorySource<string, ThreeTuple<ContinuousDistribution, ContinuousDistribution, ContinuousDistribution>> imputed = new MemorySource<string, ThreeTuple<ContinuousDistribution, ContinuousDistribution, ContinuousDistribution>>();
ComboSource<string, ThreeTuple<ContinuousDistribution, ContinuousDistribution, ContinuousDistribution>> combo = new ComboSource<string, ThreeTuple<ContinuousDistribution, ContinuousDistribution, ContinuousDistribution>>(source, imputed);
// Check for existing imputed file
DataReader imputereader = new DataReader(imputesave);
uint kk = 0;
for (string[] row = imputereader.ReadRow(); row != null; row = imputereader.ReadRow()) {
kk++;
if (kk % 1000 == 0)
Console.WriteLine("#" + kk);
double meanv = double.Parse(row[1]), varv = double.Parse(row[2]), meana = double.Parse(row[3]), vara = double.Parse(row[4]), meand = double.Parse(row[5]), vard = double.Parse(row[6]);
ContinuousDistribution valence = new ClippedGaussianDistribution(meanv, varv, 0, 1);
ContinuousDistribution arousal = new ClippedGaussianDistribution(meana, vara, 0, 1);
ContinuousDistribution dominance = new ClippedGaussianDistribution(meand, vard, 0, 1);
imputed[row[0]] = new ThreeTuple<ContinuousDistribution, ContinuousDistribution, ContinuousDistribution>(valence, arousal, dominance);
}
imputereader.Close();
for (uint ii = 0; ii < repeats; ii++) {
Dictionary<string, List<KeyValuePair<double, double>>>
sentencesV = new Dictionary<string, List<KeyValuePair<double, double>>>(),
sentencesA = new Dictionary<string, List<KeyValuePair<double, double>>>(),
sentencesD = new Dictionary<string, List<KeyValuePair<double, double>>>();
DataReader reader = new DataReader(filename);
uint jj = 0;
for (string[] row = reader.ReadRow(); row != null; row = reader.ReadRow()) {
jj++;
if (jj % 1000 == 0)
Console.WriteLine("#" + jj + ": " + sentencesV.Count + ", " + imputed.Count);
List<string> words = TwitterUtilities.SplitWords(row[column].ToLower());
AnalyzeWords(words, combo, sentencesV, sentencesA, sentencesD);
}
reader.Close();
AnalyzeSentences(imputed, sentencesV, sentencesA, sentencesD, imputesave);
}
source = combo;
return imputed;
}
public void AnalyzeSentences(MemorySource<string, ThreeTuple<ContinuousDistribution, ContinuousDistribution, ContinuousDistribution>> inputed,
Dictionary<string, List<KeyValuePair<double, double>>> sentencesV,
Dictionary<string, List<KeyValuePair<double, double>>> sentencesA,
Dictionary<string, List<KeyValuePair<double, double>>> sentencesD, string imputesave)
{
using (var stream = File.CreateText(imputesave)) {
foreach (string stem in sentencesV.Keys) {
double vmean = WeightedStatistics.Mean(sentencesV[stem]), amean = WeightedStatistics.Mean(sentencesA[stem]), dmean = WeightedStatistics.Mean(sentencesD[stem]);
ClippedGaussianDistribution valence = new ClippedGaussianDistribution(vmean, WeightedStatistics.Variance(sentencesV[stem], vmean, true), 0, 1);
ClippedGaussianDistribution arousal = new ClippedGaussianDistribution(amean, WeightedStatistics.Variance(sentencesA[stem], amean, true), 0, 1);
ClippedGaussianDistribution dominance = new ClippedGaussianDistribution(dmean, WeightedStatistics.Variance(sentencesD[stem], dmean, true), 0, 1);
inputed[stem] = new ThreeTuple<ContinuousDistribution, ContinuousDistribution, ContinuousDistribution>(valence, arousal, dominance);
stream.WriteLine(stem + "," + valence.InternalMean + "," + valence.InternalVariance + "," + arousal.InternalMean + "," + arousal.InternalVariance + "," + dominance.InternalMean + "," + dominance.InternalVariance);
}
}
}
