public static void VisualizeTree(IEnumerable <string> brtFiles, string luceneIndex = null, string[] keywords = null, bool isRemoveLeafNodes = true)
{
List <ITree> trees = new List <ITree>();
foreach (var brtFile in brtFiles)
{
//Read tree from file
TreeDataParser parser = new TreeDataParser(brtFile, isRemoveLeafNodes);
var tree = parser.GetTree();
Trace.WriteLine(tree.GetDepth(tree.Root));
if (luceneIndex != null)
{
var scheme = TreeNodeScheme.Get(tree.Graph.NodeTable);
scheme.SetIndexReader(LuceneOperations.GetIndexReader(luceneIndex));
scheme.SetBRTFileName(brtFile);
}
trees.Add(tree);
}
//Print analyze info
DoubleStatistics depthStat = new DoubleStatistics();
DoubleStatistics internalNodeStat = new DoubleStatistics();
foreach (var tree in trees)
{
depthStat.AddNumber(tree.BFS(tree.Root).Max(node =>
{
int depth = 0;
INode ancestor = node;
while ((ancestor = tree.GetParent(ancestor)) != null)
{
depth++;
}
return(depth);
}) + 1);
internalNodeStat.AddNumber(tree.BFS(tree.Root).Count());
}
Console.WriteLine(depthStat.ToString());
Console.WriteLine(internalNodeStat.ToString());
//Visualize tree
Thread NetServer = new Thread(new ThreadStart(() =>
{
TreeVisualization treeVis = new TreeVisualization(trees, keywords);
}));
NetServer.SetApartmentState(ApartmentState.STA);
NetServer.IsBackground = true;
NetServer.Start();
System.Windows.Threading.Dispatcher.Run();
}
public static void AnalyzeTreeStructure()
{
//string folder = @"D:\Project\StreamingRoseRiver\EbolaCaseStudyFinal\RoseRiver\Data\KddInfovisGraphicsIndex_Lucene_a=0.003_sm=1-test\";
string folder = @"D:\Project\StreamingRoseRiver\EbolaCaseStudyFinal\Trees3\";
int index = 0;
DoubleStatistics stat = new DoubleStatistics();
while (true)
{
var fileName = folder + index + ".gv";
if (!File.Exists(fileName))
{
break;
}
var tree = ReadTree(fileName);
stat.AddNumber(tree.Graph.NodeCount);
Console.WriteLine(tree.Graph.NodeCount);
//Console.WriteLine(index + "\t" + stat.ToStringShort());
//Console.Write(stat.GetAverage() + "\t");
index++;
}
}
public static void AnalyzeTwitterWordDistribution(string inputPath, TokenizeConfig tokenConfig)
{
var indexReader = LuceneOperations.GetIndexReader(inputPath);
var docNum = indexReader.NumDocs();
int[] docWordCnt = new int[docNum];
int[] docUniqWordCnt = new int[docNum];
Dictionary <string, int> wordDocCntDict = new Dictionary <string, int>();
Dictionary <string, int> wordOccCntDict = new Dictionary <string, int>();
var fieldWeights = tokenConfig.TokenizerType == TokenizerType.FeatureVector
? BingNewsFields.FeatureVectorFieldWeights
: BingNewsFields.NewsFieldWeights;
ProgramProgress progress = new ProgramProgress(docNum);
for (int iDoc = 0; iDoc < docNum; iDoc++)
{
var document = indexReader.Document(iDoc);
var content = LuceneOperations.GetContent(document, fieldWeights);
var words = NLPOperations.Tokenize(content, tokenConfig);
var uniqueWords = new HashSet <string>(words);
docWordCnt[iDoc] = words.Count;
docUniqWordCnt[iDoc] = uniqueWords.Count;
foreach (var word in uniqueWords)
{
if (!wordDocCntDict.ContainsKey(word))
{
wordDocCntDict.Add(word, 0);
}
wordDocCntDict[word]++;
}
foreach (var word in words)
{
if (!wordOccCntDict.ContainsKey(word))
{
wordOccCntDict.Add(word, 0);
}
wordOccCntDict[word]++;
}
progress.PrintIncrementExperiment();
}
progress.PrintTotalTime();
indexReader.Close();
//Statistics
DoubleStatistics statDocWordCnt = new DoubleStatistics();
DoubleStatistics statDocUniqWordCnt = new DoubleStatistics();
DoubleStatistics statWordDocCnt = new DoubleStatistics();
DoubleStatistics statWordOccCnt = new DoubleStatistics();
for (int iDoc = 0; iDoc < docNum; iDoc++)
{
statDocWordCnt.AddNumber(docWordCnt[iDoc]);
statDocUniqWordCnt.AddNumber(docUniqWordCnt[iDoc]);
}
foreach (var kvp in wordDocCntDict)
{
statWordDocCnt.AddNumber(kvp.Value);
}
foreach (var kvp in wordOccCntDict)
{
statWordOccCnt.AddNumber(kvp.Value);
}
Console.WriteLine(statDocWordCnt.ToString("statDocWordCnt"));
Console.WriteLine(statDocUniqWordCnt.ToString("statDocUniqWordCnt"));
Console.WriteLine(statWordDocCnt.ToString("statWordDocCnt"));
Console.WriteLine(statWordOccCnt.ToString("wordOccCnt"));
//Hist
var docWordCntHist = new DoubleHistogram(docWordCnt.Select(i => (double)i), (double)1);
var docUniqueWordCntList = new DoubleHistogram(docUniqWordCnt.Select(i => (double)i), (double)1);
var wordDocCntHist = new DoubleHistogram(wordDocCntDict.Select(kvp => (double)kvp.Value), 1000);
var wordDocCntHist2 = new DoubleHistogram(wordDocCntDict.Select(kvp => (double)kvp.Value), (double)1);
docWordCntHist.PrintToFile(StringOperations.EnsureFolderEnd(inputPath) + "docWordCntHist.csv");
docUniqueWordCntList.PrintToFile(StringOperations.EnsureFolderEnd(inputPath) + "docUniqueWordCntList.csv");
wordDocCntHist.PrintToFile(StringOperations.EnsureFolderEnd(inputPath) + "wordDocCntHist.csv");
wordDocCntHist2.PrintToFile(StringOperations.EnsureFolderEnd(inputPath) + "wordDocCntHist2.csv");
Console.Read();
}
public void AnalyzeResultsTreeCounts()
{
bool isAddVisTime = true;
var folders = new[]
{
@"D:\Project\StreamingRoseRiver\ScalabilityExperiment\Results\RunTimeExperiment-TreeCountExp2\",
//@"D:\Project\StreamingRoseRiver\ScalabilityExperiment\Results\RunTimeExperiment-supp\",
//@"D:\Project\StreamingRoseRiver\ScalabilityExperiment\Results\RunTimeExperiment-TreeCount\",
//@"D:\Project\StreamingRoseRiver\ScalabilityExperiment\Results\RunTimeExperiment-TreeCountStart19\",
//@"D:\Project\StreamingRoseRiver\ScalabilityExperiment\Results\RunTimeExperiment-treeCount21End\",
};
//Dictionary<int, Dictionary<int, DoubleStatistics[]>> statDictionary = new Dictionary<int, Dictionary<int, DoubleStatistics[]>>();
Dictionary <Tuple <int, int, int>, Dictionary <int, double> > statDictionary =
new Dictionary <Tuple <int, int, int>, Dictionary <int, double> >();
HashSet <int> copyFactors = new HashSet <int>();
HashSet <int> focusCounts = new HashSet <int>();
HashSet <int> treeCounts = new HashSet <int>();
HashSet <int> focusSeeds = new HashSet <int>();
foreach (var folder in folders)
{
foreach (var file in Directory.GetFiles(folder))
{
var result = new TopicStreamResult(file);
var key = Tuple.Create(result.CopyFactor, result.FocusCount, result.TreeCount);
Dictionary <int, double> value;
if (!statDictionary.TryGetValue(key, out value))
{
value = new Dictionary <int, double>();
statDictionary.Add(key, value);
}
value.Add(result.DefaultTreeCutRandomSeed,
(result.TreeCutTime + (isAddVisTime ? result.VisTime : 0.0) + result.DAGTime +
result.SedimentationTime));
focusSeeds.Add(result.DefaultTreeCutRandomSeed);
copyFactors.Add(result.CopyFactor);
focusCounts.Add(result.FocusCount);
treeCounts.Add(result.TreeCount);
}
}
if (copyFactors.Count != 1)
{
throw new ArgumentException();
}
var treeCountList = new List <int>(treeCounts);
treeCountList.Sort();
var focusCountList = new List <int>(focusCounts);
focusCountList.Sort();
var focusSeedList = new List <int>(focusSeeds);
focusSeedList.Sort();
var singleCopyFactor = copyFactors.First();
double[,] matrices = new double[treeCountList.Count - 1, focusCountList.Count];
int copyFactorIndex = 0;
int minTreeCnt = treeCountList.First();
var deltaTreeCount = treeCountList[1] - treeCountList[0];
foreach (var treeCount in treeCountList)
{
if (treeCount == minTreeCnt)
{
continue;
}
int focusCountIndex = 0;
foreach (var focusCount in focusCountList)
{
var tuple1 = Tuple.Create(singleCopyFactor, focusCount, treeCount - deltaTreeCount);
var tuple2 = Tuple.Create(singleCopyFactor, focusCount, treeCount);
DoubleStatistics stat = new DoubleStatistics();
var dict1 = statDictionary[tuple1];
var dict2 = statDictionary[tuple2];
//if (dict1.Count != 50 || dict2.Count != 50)
//{
// throw new ArgumentException();
//}
foreach (var focusSeed in focusSeedList)
{
double time1, time2;
if (dict1.TryGetValue(focusSeed, out time1) & dict2.TryGetValue(focusSeed, out time2))
{
stat.AddNumber(Math.Max(time2 - time1, 0));
}
}
matrices[copyFactorIndex, focusCountIndex] = stat.GetAverage();
focusCountIndex++;
}
copyFactorIndex++;
}
Console.Write("[");
for (int j = 0; j < treeCountList.Count - 1; j++)
{
for (int k = 0; k < focusCountList.Count; k++)
{
Console.Write(matrices[j, k] + (k == focusCountList.Count - 1 ? ";" : ","));
}
if (j == treeCountList.Count - 1)
{
Console.WriteLine("]/1000;");
}
else
{
Console.WriteLine("...");
}
}
Console.WriteLine();
}
List <int> GetLanguageErrorDocuments(IndexReader indexreader, string outputfile)
{
Console.WriteLine("==========Remove language error documents!==========");
StreamWriter sw = IsPrintTextFiles ? new StreamWriter(outputfile) : null;
List <int> removedDocuments = new List <int>();
var stopWords = IsEnglish ?
FileOperations.LoadKeyWordFile(StopWordsFile.EN, true) :
FileOperations.LoadKeyWordFile(StopWordsFile.CH, false);
var stopHash = Util.GetHashSet(stopWords);
int docNum = indexreader.NumDocs();
string titlefield = this.TitleField;
string bodyfield = this.BodyField;
int removedDocNum = 0;
Console.WriteLine("Total documents: {0}", docNum);
var tokenConfig = new TokenizeConfig(IsEnglish ? TokenizerType.Standard : TokenizerType.ICTCLAS, StopWordsFile.NO);
DoubleStatistics stat_percent = new DoubleStatistics();
DoubleStatistics stat_absolute = new DoubleStatistics();
for (int idoc = 0; idoc < docNum; idoc++)
{
if (idoc % 10000 == 0)
{
if (idoc == 0)
{
continue;
}
Console.WriteLine("Process " + idoc + "th document!");
Console.WriteLine("Remove {0} out of {1}: {2}%", removedDocNum, idoc, 100 * removedDocNum / idoc);
if (IsPrintTextFiles)
{
sw.Flush();
}
}
Document document = indexreader.Document(idoc);
string content = document.Get(titlefield) + " " + document.Get(bodyfield);
if (IsEnglish)
{
content = content.ToLower();
}
var words = NLPOperations.Tokenize(content, tokenConfig);
var termCnt0 = words.Count;
var termCnt1 = 0;
foreach (var word in words)
{
if (!stopHash.Contains(word))
{
termCnt1++;
}
}
if (((double)termCnt0 - termCnt1) / termCnt0 < MinLanguageCorrectRatio)
{
if (IsPrintTextFiles)
{
sw.WriteLine(DocumentToString(document));
}
removedDocuments.Add(idoc);
removedDocNum++;
}
else
{
stat_absolute.AddNumber(termCnt0 - termCnt1);
stat_percent.AddNumber((100.0) * (termCnt0 - termCnt1) / termCnt0);
}
}
Console.WriteLine("Remove {0} out of {1}: {2}%", removedDocNum, docNum, 100 * removedDocNum / docNum);
if (IsPrintTextFiles)
{
sw.WriteLine("Remove {0} out of {1}: {2}%", removedDocNum, docNum, 100 * removedDocNum / docNum);
sw.Flush();
sw.Close();
}
Console.WriteLine(stat_percent.ToString("stat_percent"));
Console.WriteLine(stat_absolute.ToString("stat_absolute"));
return(removedDocuments);
}