public WordVector(WordVector orig) : this(modshogunPINVOKE.new_WordVector__SWIG_5(WordVector.getCPtr(orig)), true)
{
if (modshogunPINVOKE.SWIGPendingException.Pending)
{
throw modshogunPINVOKE.SWIGPendingException.Retrieve();
}
}
public CustomBitArray CalculateHashScore(WordVector vector)
{
CustomBitArray arr = new CustomBitArray(_hyperPlanes.Count);
for (int i = _hyperPlanes.Count - 1; i != -1; i--)
arr[i] = (_hyperPlanes[i] * vector) >= 0;
return arr;
}
public void TestVectorAverage()
{
var x = new WordVector("word1", new float[] { 1, 3, 4 });
var y = new WordVector("word2", new float[] { 1, 0, 0 });
var result = new[] { x, y }.Average();
CollectionAssert.AreEqual(new [] { 1, 1.5f, 2 }, result);
}
public void TestVectorSubtractionOperator()
{
var x = new WordVector("word1", new float[] { 1, 3, 4 });
var y = new WordVector("word2", new float[] { 1, 0, 0 });
var z = y + x - y;
Assert.IsNotNull(z);
CollectionAssert.AreEqual(new float[] { 1, 3, 4 }, z);
}
public CustomBitArray CalculateHashScore(WordVector vector, out bool anyTrue)
{
anyTrue = false;
CustomBitArray arr = new CustomBitArray(_hyperPlanes.Count);
for (int i = _hyperPlanes.Count - 1; i != -1; i--)
{
anyTrue |= (arr[i] = (_hyperPlanes[i] * vector) > 0);
}
return arr;
}
public TrainingAction(IPlan plan, ContextMaps maps)
: base(plan,maps)
{
_contextMap = maps.For(plan.Word);
_weights = _contextMap.NeuronWeights;
if (!plan.Output.HasValue) throw new ArgumentException("plan.Output must be set", "plan");
_wordVector = _vectors[plan.Word];
if (_outputArray == null)
{
_outputArray = OutputToArray(plan.Output.Value);
}
}
public static short[] get_vector(WordVector src) {
IntPtr ptr = modshogunPINVOKE.WordVector_get_vector__SWIG_1(WordVector.getCPtr(src));
if (modshogunPINVOKE.SWIGPendingException.Pending) throw modshogunPINVOKE.SWIGPendingException.Retrieve();
int[] size = new int[1];
Marshal.Copy(ptr, size, 0, 1);
int len = size[0];
short[] ret = new short[len];
Marshal.Copy(new IntPtr(ptr.ToInt64() + Marshal.SizeOf(typeof(int))), ret, 0, len);
return ret;
}
public void SendQuery(string query)
{
var n1GrammQuery = TextConvertor.TextToWordList(query);
var texts = TextSearcher.Search(query);
foreach (string text in texts)
{
var n1GrammText = TextConvertor.TextToWordList(text);
var vectorizedText = _word2VecModelDB.CreateWordVectorList(n1GrammText);
var vectorizedQuery = _word2VecModelDB.CreateWordVectorList(n1GrammQuery);
var score = Cluster.GetAccordance(WordVector.GetVectors(vectorizedText), WordVector.GetVectors(vectorizedQuery));
_view.ShowTextWithScore(text, score);
}
}
public void TestRandomExcluding()
{
_target = new WordVectors(10);
var wv1 = new WordVector {Name = "wv1" };
var wv2 = new WordVector { Name = "wv2" }; ;
var wv3 = new WordVector { Name = "wv3" }; ;
var wv4 = new WordVector { Name = "wv4" }; ;
_target.TryAdd("wv1", wv1);
_target.TryAdd("wv2", wv2);
_target.TryAdd("wv3", wv3);
_target.TryAdd("wv4", wv4);
var result = _target.RandomExcluding(new HashSet<WordVector> {wv1, wv2, wv3});
result.Should().Be(wv4);
}
public static short[] get_vector(WordVector src, bool own)
{
IntPtr ptr = modshogunPINVOKE.WordVector_get_vector__SWIG_0(WordVector.getCPtr(src), own);
if (modshogunPINVOKE.SWIGPendingException.Pending)
{
throw modshogunPINVOKE.SWIGPendingException.Retrieve();
}
int[] size = new int[1];
Marshal.Copy(ptr, size, 0, 1);
int len = size[0];
short[] ret = new short[len];
Marshal.Copy(new IntPtr(ptr.ToInt64() + Marshal.SizeOf(typeof(int))), ret, 0, len);
return(ret);
}
public void TestNetwork()
{
var wordVector = new WordVector() {Name = "test"};
var elements = new[] {0.1, 0.2, 0.3};
elements.CopyTo(wordVector.Elements,0);
var context = new[] {0.4, 0.5};
var factory = new NeuralNetworkFactory();
var network = factory.CreateNeuralNetwork(2, 2);
var examples = new[]
{
new Example {Input = new [] {1.0, 0.0}, ExpectedResult = new []{1.0}},
new Example {Input = new [] {0.0, 1.0}, ExpectedResult = new []{1.0}},
new Example {Input = new [] {1.0, 1.0}, ExpectedResult = new []{0.0}},
new Example {Input = new [] {0.0, 0.0}, ExpectedResult = new []{0.0}}
};
var error = network.Train(examples,0.1);
var result = network.Run(new[] {0.0, 0.0});
result[0].Should().BeLessOrEqualTo(error + 0.1);
}
protected WordVector ParseLine(string line)
{
var fields = line.Split(' ');
var name = fields[0];
var elements = new List<double>();
//skip first (name) and last (blank)
for (int i = 1; i < fields.Length-1; i++)
{
var element = fields[i];
try
{
elements.Add(double.Parse(element));
}
catch (FormatException fe)
{
_trace.TraceData(System.Diagnostics.TraceEventType.Error, 1, "could not parse element: " + element);
throw new LoaderException("could not parse element", fe);
}
}
var wv = new WordVector
{
Name = name,
};
elements.CopyTo(wv.Elements);
return wv;
}
internal static HandleRef getCPtr(WordVector obj)
{
return((obj == null) ? new HandleRef(null, IntPtr.Zero) : obj.swigCPtr);
}
public bool TryAdd(string key, WordVector value)
{
return _wordVectorDictionary.TryAdd(key, value);
}
public SimpleTweetCluster()
{
Vector = new WordVector();
}
public static double Distance(this float[] word1, WordVector word2)
{
return(word1.Distance(word2.Vector));
}
public static float[] Subtract(this float[] word1, WordVector word2)
{
return(word1.Subtract(word2.Vector));
}
public static float[] Add(this float[] word1, WordVector word2)
{
return(word1.Add(word2.Vector));
}
public static List <WordDistance> DistanceList(this List <WordVector> wordList, WordVector currentWord)
{
var distanceList = new List <WordDistance>();
foreach (WordVector word in wordList)
{
distanceList.Add(new WordDistance(word.Word, word.Distance(currentWord), currentWord.Word));
}
return(distanceList);
}
LSHashFunction GetNewHashFunction()
{
//Generate hyper planes
List<WordVector> planes = new List<WordVector>();
for (int j = 0; j < Settings.TweetClusterer_TCW_HyperPlaneCount; j++)
{
WordVector plane = new WordVector();
List<long> wordIDs = GetRandomWordIDs(_wordsPerHyperPlane);
foreach (long id in wordIDs)
plane.AddItem(id, Helpers.NextGaussian());
planes.Add(plane);
Console.Write('.');
}
return new LSHashFunction(planes);
}
public SimpleStory()
{
Vector = new WordVector();
}
internal static HandleRef getCPtr(WordVector obj) {
return (obj == null) ? new HandleRef(null, IntPtr.Zero) : obj.swigCPtr;
}
public Example(WordVector word, MorphoSyntacticContext context, double[] target )
{
Input = new double[WordVector.VectorLength + MorphoSyntacticContext.VectorLength];
word.Elements.CopyTo(Input,0);
context.Elements.CopyTo(Input, WordVector.VectorLength);
ExpectedResult = target;
}
public WordVector(WordVector orig) : this(modshogunPINVOKE.new_WordVector__SWIG_5(WordVector.getCPtr(orig)), true) {
if (modshogunPINVOKE.SWIGPendingException.Pending) throw modshogunPINVOKE.SWIGPendingException.Retrieve();
}
