idx int64 0 41.2k | question stringlengths 73 5.81k | target stringlengths 5 918 |
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2,800 | private static void invokeMatlab ( File dataMatrixFile , File affMatrixFile , int dimensions , File outputFile ) throws IOException { String commandLine = "matlab -nodisplay -nosplash -nojvm" ; LOGGER . fine ( commandLine ) ; Process matlab = Runtime . getRuntime ( ) . exec ( commandLine ) ; String outputStr = "save " ... | Invokes Matlab to run the LPP script |
2,801 | private static void invokeOctave ( File dataMatrixFile , File affMatrixFile , int dimensions , File outputFile ) throws IOException { File octaveFile = File . createTempFile ( "octave-LPP" , ".m" ) ; String outputStr = "save(\"-ascii\", \"" + outputFile . getAbsolutePath ( ) + "\", \"projection\");\n" ; String octavePr... | Invokes Octave to run the LPP script |
2,802 | public static void setLevel ( Level outputLevel ) { Logger appRooLogger = Logger . getLogger ( "edu.ucla.sspace" ) ; Handler verboseHandler = new ConsoleHandler ( ) ; verboseHandler . setLevel ( outputLevel ) ; appRooLogger . addHandler ( verboseHandler ) ; appRooLogger . setLevel ( outputLevel ) ; appRooLogger . setUs... | Sets the output level of the S - Space package according to the desired level . |
2,803 | private void advance ( ) { try { while ( true ) { if ( curLine == null || ! matcher . find ( ) ) { String line = br . readLine ( ) ; if ( line == null ) { next = null ; br . close ( ) ; return ; } matcher = notWhiteSpace . matcher ( line ) ; curLine = line ; if ( ! matcher . find ( ) ) continue ; } next = curLine . sub... | Advances to the next word in the buffer . |
2,804 | private void checkIndices ( int row , int col , boolean expand ) { if ( row < 0 || col < 0 ) { throw new ArrayIndexOutOfBoundsException ( ) ; } if ( expand ) { int r = row + 1 ; int cur = 0 ; while ( r > ( cur = rows . get ( ) ) && ! rows . compareAndSet ( cur , r ) ) ; int c = col + 1 ; cur = 0 ; while ( c > ( cur = c... | Verify that the given row and column value is non - negative and optionally expand the size of the matrix if the row or column are outside the current bounds . |
2,805 | private static int index ( Object o ) { Integer i = TYPE_INDICES . get ( o ) ; if ( i == null ) { synchronized ( TYPE_INDICES ) { i = TYPE_INDICES . get ( o ) ; if ( i != null ) return i ; else { int j = TYPE_INDICES . size ( ) ; TYPE_INDICES . put ( o , j ) ; TYPES . add ( o ) ; return j ; } } } return i ; } | Returns the index for the given type creating a new index if necessary |
2,806 | private void addThread ( ) { Thread t = new WorkerThread ( workQueue ) ; threads . add ( t ) ; t . start ( ) ; } | Increases the number of concurrently processing threads by one . |
2,807 | public long getRemainingTasks ( Object taskGroupId ) { CountDownLatch latch = taskKeyToLatch . get ( taskGroupId ) ; return ( latch == null ) ? 0 : latch . getCount ( ) ; } | Returns the number of tasks that need to be completed before the group associated with the key is complete . Note that this number includes both those tasks running and not yet completed as well as tasks that have yet to be enqueued on behalf of this id . |
2,808 | public Object registerTaskGroup ( int numTasks ) { Object key = new Object ( ) ; taskKeyToLatch . putIfAbsent ( key , new CountDownLatch ( numTasks ) ) ; return key ; } | Registers a new task group with the specified number of tasks to execute and returns a task group identifier to use when registering its tasks . |
2,809 | public void run ( Collection < Runnable > tasks ) { int numTasks = tasks . size ( ) ; CountDownLatch latch = new CountDownLatch ( numTasks ) ; for ( Runnable r : tasks ) { if ( r == null ) throw new NullPointerException ( "Cannot run null tasks" ) ; workQueue . offer ( new CountingRunnable ( r , latch ) ) ; } try { lat... | Executes the tasks using a thread pool and returns once all tasks have finished . |
2,810 | @ SuppressWarnings ( "unchecked" ) public static < T > T getObjectInstance ( String className ) { try { Class clazz = Class . forName ( className ) ; return ( T ) clazz . newInstance ( ) ; } catch ( Exception e ) { throw new Error ( e ) ; } } | Returns an arbitrary object instance based on a class name . |
2,811 | public static < T extends Vector > double getSimilarity ( SimType similarityType , T a , T b ) { switch ( similarityType ) { case COSINE : return cosineSimilarity ( a , b ) ; case PEARSON_CORRELATION : return correlation ( a , b ) ; case EUCLIDEAN : return euclideanSimilarity ( a , b ) ; case SPEARMAN_RANK_CORRELATION ... | Calculates the similarity of the two vectors using the provided similarity measure . |
2,812 | public static double cosineSimilarity ( double [ ] a , double [ ] b ) { check ( a , b ) ; double dotProduct = 0.0 ; double aMagnitude = 0.0 ; double bMagnitude = 0.0 ; for ( int i = 0 ; i < b . length ; i ++ ) { double aValue = a [ i ] ; double bValue = b [ i ] ; aMagnitude += aValue * aValue ; bMagnitude += bValue * b... | Returns the cosine similarity of the two arrays . |
2,813 | public static double spearmanRankCorrelationCoefficient ( double [ ] a , double [ ] b ) { check ( a , b ) ; int N = a . length ; int NcubedMinusN = ( N * N * N ) - N ; double [ ] rankedA = rank ( a ) ; double [ ] rankedB = rank ( b ) ; double sumDiffs = 0 ; for ( int i = 0 ; i < rankedA . length - 1 ; ++ i ) { double d... | Computes the Spearman rank correlation coefficient for the two arrays . |
2,814 | public Set < T > types ( ) { Set < T > types = new HashSet < T > ( ) ; for ( Object o : edges . values ( ) ) { Set < T > s = ( Set < T > ) o ; types . addAll ( s ) ; } return types ; } | Returns the set of types contained within this set |
2,815 | public static double mean ( Collection < ? extends Number > values ) { double sum = 0d ; for ( Number n : values ) sum += n . doubleValue ( ) ; return sum / values . size ( ) ; } | Returns the mean value of the collection of numbers |
2,816 | public static double mean ( int [ ] values ) { double sum = 0d ; for ( int i : values ) sum += i ; return sum / values . length ; } | Returns the mean value of the array of ints |
2,817 | @ SuppressWarnings ( "unchecked" ) public static < T extends Number & Comparable > T median ( Collection < T > values ) { if ( values . isEmpty ( ) ) throw new IllegalArgumentException ( "No median in an empty collection" ) ; List < T > sorted = new ArrayList < T > ( values ) ; Collections . sort ( sorted ) ; return so... | Returns the median value of the collection of numbers |
2,818 | public static double median ( int [ ] values ) { if ( values . length == 0 ) throw new IllegalArgumentException ( "No median in an empty array" ) ; int [ ] sorted = Arrays . copyOf ( values , values . length ) ; Arrays . sort ( sorted ) ; return sorted [ sorted . length / 2 ] ; } | Returns the median value of the array of ints |
2,819 | public static < T extends Number > T mode ( Collection < T > values ) { if ( values . isEmpty ( ) ) throw new IllegalArgumentException ( "No mode in an empty collection" ) ; Counter < T > c = new ObjectCounter < T > ( ) ; for ( T n : values ) c . count ( n ) ; return c . max ( ) ; } | Returns the mode value of the collection of numbers |
2,820 | public static int mode ( int [ ] values ) { if ( values . length == 0 ) throw new IllegalArgumentException ( "No mode in an empty array" ) ; Counter < Integer > c = new ObjectCounter < Integer > ( ) ; for ( int i : values ) c . count ( i ) ; return c . max ( ) ; } | Returns the mode value of the array of ints |
2,821 | public static double mode ( double [ ] values ) { if ( values . length == 0 ) throw new IllegalArgumentException ( "No mode in an empty array" ) ; Counter < Double > c = new ObjectCounter < Double > ( ) ; for ( double d : values ) c . count ( d ) ; return c . max ( ) ; } | Returns the mode value of the array of doubles |
2,822 | public static double stddev ( Collection < ? extends Number > values ) { double mean = mean ( values ) ; double sum = 0d ; for ( Number n : values ) { double d = n . doubleValue ( ) - mean ; sum += d * d ; } return Math . sqrt ( sum / values . size ( ) ) ; } | Returns the standard deviation of the collection of numbers |
2,823 | public static double stddev ( int [ ] values ) { double mean = mean ( values ) ; double sum = 0d ; for ( int i : values ) { double d = i - mean ; sum += d * d ; } return Math . sqrt ( sum / values . length ) ; } | Returns the standard deviation of the values in the int array |
2,824 | public static double sum ( Collection < ? extends Number > values ) { double sum = 0d ; for ( Number n : values ) sum += n . doubleValue ( ) ; return sum ; } | Returns the sum of the collection of numbers |
2,825 | private < E extends Edge > double getConnectionSimilarity ( Graph < E > graph , Edge e1 , Edge e2 ) { int e1to = e1 . to ( ) ; int e1from = e1 . from ( ) ; int e2to = e2 . to ( ) ; int e2from = e2 . from ( ) ; if ( e1to == e2to ) return getConnectionSimilarity ( graph , e1to , e1from , e2from ) ; else if ( e1to == e2fr... | Computes the connection similarity for the two edges first calculating the impost and keystones nodes . If the edges are not connected returns 0 . |
2,826 | private void addIntermediateNode ( Node < V > original , int numOverlappingCharacters , String key , int indexOfStartOfOverlap , V value ) { char [ ] originalPrefix = original . prefix ; char distinguishing = originalPrefix [ numOverlappingCharacters ] ; char [ ] remainingPrefix = Arrays . copyOfRange ( originalPrefix ... | Creates a series of children under the provided node moving the value that was mapped to this node to the appropriate terminal node in the series and finally creating a new node at the end to hold the new key - value mapping . |
2,827 | public < E extends Edge > double [ ] compute ( Graph < E > g ) { if ( ! hasContiguousVertices ( g ) ) throw new IllegalArgumentException ( "Vertices must be in continugous order" ) ; double [ ] centralities = new double [ g . order ( ) ] ; IntIterator vertexIter = g . vertices ( ) . iterator ( ) ; while ( vertexIter . ... | Returns a mapping from each vertex to its betweenness centrality measure . |
2,828 | private Matrix getEdgeSimMatrix ( List < Edge > edgeList , SparseMatrix sm , boolean keepSimilarityMatrixInMemory ) { return ( keepSimilarityMatrixInMemory ) ? calculateEdgeSimMatrix ( edgeList , sm ) : new LazySimilarityMatrix ( edgeList , sm ) ; } | Returns the edge similarity matrix for the edges in the provided sparse matrix . |
2,829 | private Matrix calculateEdgeSimMatrix ( final List < Edge > edgeList , final SparseMatrix sm ) { final int numEdges = edgeList . size ( ) ; final Matrix edgeSimMatrix = new SparseSymmetricMatrix ( new SparseHashMatrix ( numEdges , numEdges ) ) ; Object key = workQueue . registerTaskGroup ( numEdges ) ; for ( int i = 0 ... | Calculates the similarity matrix for the edges . The similarity matrix is symmetric . |
2,830 | private static MultiMap < Integer , Integer > convertMergesToAssignments ( List < Merge > merges , int numOriginalClusters ) { MultiMap < Integer , Integer > clusterToElements = new HashMultiMap < Integer , Integer > ( ) ; for ( int i = 0 ; i < numOriginalClusters ; ++ i ) clusterToElements . put ( i , i ) ; for ( Merg... | Converts a series of merges to cluster assignments . Cluster assignments are assumed to start at 0 . |
2,831 | private static int [ ] getImpostNeighbors ( SparseMatrix sm , int rowIndex ) { int [ ] impost1edges = sm . getRowVector ( rowIndex ) . getNonZeroIndices ( ) ; int [ ] neighbors = Arrays . copyOf ( impost1edges , impost1edges . length + 1 ) ; neighbors [ neighbors . length - 1 ] = rowIndex ; return neighbors ; } | Returns an array containing the row indices of the neighbors of the impost node and the row index of the impost node itself . |
2,832 | public double getSolutionDensity ( int solutionNum ) { if ( solutionNum < 0 || solutionNum >= mergeOrder . size ( ) ) { throw new IllegalArgumentException ( "not a valid solution: " + solutionNum ) ; } if ( mergeOrder == null || edgeList == null ) { throw new IllegalStateException ( "initial clustering solution is not ... | Returns the partition density of the clustering solution . |
2,833 | public Assignments getSolution ( int solutionNum ) { if ( solutionNum < 0 || solutionNum >= mergeOrder . size ( ) ) { throw new IllegalArgumentException ( "not a valid solution: " + solutionNum ) ; } if ( mergeOrder == null || edgeList == null ) { throw new IllegalStateException ( "initial clustering solution is not va... | Returns the clustering solution after the specified number of merge steps . |
2,834 | public static Matrix average ( Matrix m , Dimension dim ) { Matrix averageMatrix = null ; if ( dim == Dimension . ALL ) { double average = 0 ; for ( int i = 0 ; i < m . rows ( ) ; ++ i ) { for ( int j = 0 ; j < m . columns ( ) ; ++ j ) average += m . get ( i , j ) ; } averageMatrix = new ArrayMatrix ( 1 , 1 ) ; average... | Return a matrix containing the averages for the dimension specificed . |
2,835 | public void processFile ( File blogFile ) throws IOException { BufferedReader br = new BufferedReader ( new FileReader ( blogFile ) ) ; String line = null ; String date = null ; String id = null ; StringBuilder content = new StringBuilder ( ) ; boolean needMoreContent = false ; while ( ( line = br . readLine ( ) ) != n... | Given a blog file read through each line and extract the content and updated date printing these as one line to the result file . |
2,836 | private Collection < Multigraph < T , E > > enumerateSimpleGraphs ( Multigraph < T , E > input , List < IntPair > connected , int curPair , Multigraph < T , E > toCopy ) { List < Multigraph < T , E > > simpleGraphs = new LinkedList < Multigraph < T , E > > ( ) ; IntPair p = connected . get ( curPair ) ; Set < E > edges... | Recursively enumerates the parallel edge permutations of the input graph building up the graphs and returning the entire set of graphs . |
2,837 | public Multigraph < T , E > next ( ) { if ( ! hasNext ( ) ) throw new NoSuchElementException ( ) ; Multigraph < T , E > cur = next . poll ( ) ; if ( next . isEmpty ( ) ) advance ( ) ; return cur ; } | Returns the next simple graph from the multigraph . |
2,838 | private void addRelation ( String object , String attribute ) { double val ; int row , col ; object = object . toLowerCase ( ) ; attribute = attribute . toLowerCase ( ) ; if ( objectTable . containsKey ( object ) ) { row = objectTable . get ( object ) ; } else { row = Integer . valueOf ( objectCounter . getAndIncrement... | Adds a relation pair to the matrix |
2,839 | private boolean inStartSet ( String tag ) { return tag . startsWith ( "NN" ) || tag . startsWith ( "JJ" ) || tag . startsWith ( "RB" ) || tag . startsWith ( "CD" ) ; } | Checks to see if the tag can modify another word |
2,840 | private boolean isPhraseOrClause ( String tag ) { return ( ! tag . equals ( "SYM" ) && tag . startsWith ( "S" ) ) || tag . equals ( "ADJP" ) || tag . equals ( "ADVP" ) || tag . equals ( "CONJP" ) || tag . equals ( "FRAG" ) || tag . equals ( "INTJ" ) || tag . equals ( "LST" ) || tag . equals ( "NAC" ) || tag . equals ( ... | Checks to see if tag marks a phrase or clause |
2,841 | private String getNextTag ( String str ) { String tag ; int endIndex ; int tagIndex = str . indexOf ( "(" ) ; if ( tagIndex < 0 ) { return null ; } endIndex = str . indexOf ( " " , tagIndex ) ; if ( endIndex < 0 ) { return null ; } tag = str . substring ( tagIndex + 1 , endIndex ) ; if ( tag . length ( ) > 0 ) { return... | Returns the next tag in the sentence or null if there are no more tags |
2,842 | public double [ ] vectorize ( List < String > phonemes ) { int nextConsonantIndex = 0 ; int nextVowelIndex = 0 ; double [ ] result = new double [ ( vowelIndices . length + consonantIndices . length ) * 3 ] ; for ( String phoneme : phonemes ) { int offset = 3 ; if ( VOWELS . contains ( phoneme ) ) offset *= vowelIndices... | Returns a left - justified syllablilic template representation of the given list of phonemes . Every three values correspond to a single phoneme representation . If six syllables are used a vector of 99 values is returned otherwise a vector of 54 values is returned . |
2,843 | public void process ( Iterator < String > text ) { String nextToken = null , curToken = null ; if ( text . hasNext ( ) ) nextToken = text . next ( ) ; while ( text . hasNext ( ) ) { curToken = nextToken ; nextToken = text . next ( ) ; if ( ! ( excludeToken ( curToken ) || excludeToken ( nextToken ) ) ) processBigram ( ... | Processes the tokens in the iterator to gather statistics for any bigrams contained therein |
2,844 | private void processBigram ( String left , String right ) { TokenStats leftStats = getStatsFor ( left ) ; TokenStats rightStats = getStatsFor ( right ) ; leftStats . count ++ ; rightStats . count ++ ; leftStats . leftCount ++ ; rightStats . rightCount ++ ; numBigramsInCorpus ++ ; long bigram = ( ( ( long ) leftStats . ... | Updates the statistics for the bigram formed from the provided left and right token . |
2,845 | public void printBigrams ( PrintWriter output , SignificanceTest test , int minOccurrencePerToken ) { String [ ] indexToToken = new String [ tokenCounts . size ( ) ] ; for ( Map . Entry < String , TokenStats > e : tokenCounts . entrySet ( ) ) indexToToken [ e . getValue ( ) . index ] = e . getKey ( ) . toString ( ) ; L... | Prints all of the known bigrams where each token in the bigram must occur at least the number of specified time . |
2,846 | private double getScore ( int [ ] contingencyTable , SignificanceTest test ) { switch ( test ) { case PMI : return pmi ( contingencyTable ) ; case CHI_SQUARED : return chiSq ( contingencyTable ) ; case LOG_LIKELIHOOD : return logLikelihood ( contingencyTable ) ; default : throw new Error ( test + " not implemented yet"... | Returns the score of the contingency table using the specified significance test |
2,847 | private double logLikelihood ( int [ ] contingencyTable ) { int [ ] t = contingencyTable ; int col1sum = t [ 0 ] + t [ 2 ] ; int col2sum = t [ 1 ] + t [ 3 ] ; int row1sum = t [ 0 ] + t [ 1 ] ; int row2sum = t [ 2 ] + t [ 3 ] ; double sum = row1sum + row2sum ; double aExp = ( row1sum / sum ) * col1sum ; double bExp = ( ... | Returns the log - likelihood score of the contingency table |
2,848 | public int getDimension ( DependencyPath path ) { String endToken = path . last ( ) . word ( ) ; String relation = path . getRelation ( path . length ( ) - 1 ) ; return getDimensionInternal ( endToken + "+" + relation ) ; } | Returns the dimension number corresponding to the term at the end of the provided path . |
2,849 | public synchronized DoubleVector generate ( ) { DoubleVector termVector = new DenseVector ( indexVectorLength ) ; for ( int i = 0 ; i < indexVectorLength ; i ++ ) termVector . set ( i , mean + ( randomGenerator . nextGaussian ( ) * stdev ) ) ; return termVector ; } | Generate a new random vector using a guassian distribution for each value . |
2,850 | protected void addContextTerms ( SparseDoubleVector meaning , Queue < String > words , int distance ) { for ( String term : words ) { if ( ! term . equals ( IteratorFactory . EMPTY_TOKEN ) ) { int dimension = basis . getDimension ( term ) ; if ( dimension == - 1 ) continue ; meaning . set ( dimension , weighting . weig... | Adds a feature for each word in the context that has a valid dimension . Feature are scored based on the context word s distance from the focus word . |
2,851 | @ SuppressWarnings ( "unchecked" ) private void processSpace ( ) throws IOException { compressedDocumentsWriter . close ( ) ; String [ ] indexToTerm = new String [ termToIndex . size ( ) ] ; for ( Map . Entry < String , Integer > e : termToIndex . entrySet ( ) ) indexToTerm [ e . getValue ( ) ] = e . getKey ( ) ; int c... | Calculates the first order co - occurrence statics to determine the feature set for each term then clusters the feature vectors for each terms contexts and finally induces the sense - specific vectors for each term . |
2,852 | private void senseInduce ( String term , Matrix contexts ) throws IOException { LOGGER . fine ( "Clustering " + contexts . rows ( ) + " contexts for " + term ) ; int numClusters = Math . min ( 7 , contexts . rows ( ) ) ; if ( ! ( term . matches ( "[a-zA-z]+" ) && numClusters > 6 ) ) { SparseDoubleVector meanSenseVector... | Given a matrix for the term where each row is a different context clusters the rows to identify how many senses the word has . |
2,853 | private int processIntDocument ( int termIndex , int [ ] document , Matrix contextMatrix , int rowStart , BitSet featuresForTerm ) { int contexts = 0 ; for ( int i = 0 ; i < document . length ; ++ i ) { int curToken = document [ i ] ; if ( curToken != termIndex ) continue ; SparseArray < Integer > contextCounts = new S... | Processes the compressed version of a document where each integer indicates that token s index and identifies all the contexts for the target word adding them as new rows to the context matrix . |
2,854 | private static double logLikelihood ( double a , double b , double c , double d ) { double col1sum = a + c ; double col2sum = b + d ; double row1sum = a + b ; double row2sum = c + d ; double sum = row1sum + row2sum ; double aExp = ( row1sum / sum ) * col1sum ; double bExp = ( row1sum / sum ) * col2sum ; double cExp = (... | Returns the log - likelihood of the contingency table made up of the four values . |
2,855 | private void checkIndices ( int row , int col ) { if ( row < 0 || row >= rows ) throw new ArrayIndexOutOfBoundsException ( "row: " + row ) ; else if ( col < 0 || col >= cols ) throw new ArrayIndexOutOfBoundsException ( "column: " + col ) ; } | Check that the indices of a requested cell are within bounds . |
2,856 | public boolean add ( WeightedEdge e ) { int toAdd = - 1 ; if ( e . from ( ) == rootVertex ) toAdd = e . to ( ) ; else if ( e . to ( ) == rootVertex ) toAdd = e . from ( ) ; else { return false ; } double w = e . weight ( ) ; if ( edges . containsKey ( toAdd ) ) { double w2 = edges . put ( toAdd , w ) ; return false ; }... | Adds the edge to this set if one of the vertices is the root vertex . |
2,857 | public DoubleVector centerOfMass ( ) { if ( centroid == null ) { if ( indices . size ( ) == 1 ) centroid = sumVector ; else { int length = sumVector . length ( ) ; double d = 1d / indices . size ( ) ; if ( sumVector instanceof SparseVector ) { centroid = new SparseHashDoubleVector ( length ) ; SparseVector sv = ( Spars... | Returns the average data point assigned to this candidate cluster |
2,858 | public void add ( int index , DoubleVector v ) { boolean added = indices . add ( index ) ; assert added : "Adding duplicate indices to candidate facility" ; if ( sumVector == null ) { sumVector = ( v instanceof SparseVector ) ? new SparseHashDoubleVector ( v ) : new DenseVector ( v ) ; } else { VectorMath . add ( sumVe... | Adds the data point with the specified index to the facility |
2,859 | public void merge ( CandidateCluster other ) { indices . addAll ( other . indices ) ; VectorMath . add ( sumVector , other . sumVector ) ; centroid = null ; } | Merges the elements assigned to the other cluster into this one . |
2,860 | private void printSpace ( SemanticSpace sspace , String tag ) { try { String EXT = ".sspace" ; File output = ( overwrite ) ? new File ( outputDir , sspace . getSpaceName ( ) + tag + EXT ) : File . createTempFile ( sspace . getSpaceName ( ) + tag , EXT , outputDir ) ; long startTime = System . currentTimeMillis ( ) ; Se... | Prints the semantic space to file inserting the tag into the . sspace file name |
2,861 | private void updateTemporalSemantics ( long currentSemanticPartitionStartTime , SemanticSpace semanticPartition ) { double [ ] zeroVector = new double [ semanticPartition . getVectorLength ( ) ] ; for ( String word : interestingWords ) { SortedMap < Long , double [ ] > temporalSemantics = wordToTemporalSemantics . get ... | Adds the temporal semantics for each interesting word using the provided semantic partition . |
2,862 | private void printShiftRankings ( String dateString , long startOfMostRecentPartition , TimeSpan partitionDuration ) throws IOException { SortedMultiMap < Double , String > shiftToWord = new TreeMultiMap < Double , String > ( ) ; TimeSpan twoPartitions = new TimeSpan ( partitionDuration . getYears ( ) * 2 , partitionDu... | Computes the ranking of which words underwent the most dramatic shifts in the most recent partition and then prints the ranking list of a file . |
2,863 | protected void usage ( ) { System . out . println ( "usage: java FixedDurationTemporalRandomIndexingMain [options] " + "<output-dir>\n\n" + argOptions . prettyPrint ( ) + "\nFixed-Duration TRI provides four main output options:\n\n" + " 1) Outputting each semantic partition as a separate .sspace file. " + "Each file\... | Prints the instructions on how to execute this program to standard out . |
2,864 | public Iterator < T > iterator ( ) { List < Iterator < T > > iters = new ArrayList < Iterator < T > > ( sets . size ( ) ) ; for ( Set < T > s : sets ) iters . add ( s . iterator ( ) ) ; return new CombinedIterator < T > ( iters ) ; } | Returns an iterator over all the unique items across all sets . |
2,865 | public int size ( ) { int size = 0 ; for ( Set < T > s : sets ) size += s . size ( ) ; return size ; } | Returns the number of unique items across all sets . |
2,866 | public void readFields ( DataInput in ) throws IOException { t . readFields ( in ) ; position = in . readInt ( ) ; } | Deserializes the internal data from the provided stream . |
2,867 | public void write ( DataOutput out ) throws IOException { t . write ( out ) ; out . writeInt ( position ) ; } | Serailizes the internsal data to the provided stream |
2,868 | private void normalize ( DoubleVector v ) { double magnitude = 0 ; for ( int i = 0 ; i < v . length ( ) ; ++ i ) magnitude += Math . pow ( v . get ( i ) , 2 ) ; if ( magnitude == 0 ) return ; magnitude = Math . sqrt ( magnitude ) ; for ( int i = 0 ; i < v . length ( ) ; ++ i ) v . set ( i , v . get ( i ) / magnitude ) ... | Performs l2 - normalization on the vector in place . If the magnitude of the vector is 0 the values are left unchanged . |
2,869 | private DoubleVector groupConvolution ( Queue < String > prevWords , Queue < String > nextWords ) { DoubleVector result = new DenseVector ( indexVectorSize ) ; String prevWord = prevWords . peek ( ) ; DoubleVector tempConvolution ; if ( ! prevWord . equals ( IteratorFactory . EMPTY_TOKEN ) ) { tempConvolution = convolu... | Generate the circular convoltion of n - grams composed of words in the given context . The result of this convolution is returned as a DoubleVector . |
2,870 | protected void setup ( Mapper . Context context ) { Configuration conf = context . getConfiguration ( ) ; extractor = new CooccurrenceExtractor ( conf ) ; Properties props = new Properties ( ) ; for ( String property : ITERATOR_FACTORY_PROPERTIES ) { String propVal = conf . get ( property ) ; if ( propVal != null ) pro... | Initializes all the properties for this particular mapper . This process includes setting up the window size and configuring how the input documents will be tokenized . |
2,871 | public DependencyPath next ( ) { if ( next == null ) throw new NoSuchElementException ( "No further paths to return" ) ; DependencyPath p = next ; advance ( ) ; return p ; } | Returns the next path that meets the requirements . |
2,872 | public long getPrimitive ( int index ) { if ( index < 0 || index >= maxLength ) { throw new ArrayIndexOutOfBoundsException ( "invalid index: " + index ) ; } int pos = Arrays . binarySearch ( indices , index ) ; long value = ( pos >= 0 ) ? values [ pos ] : 0 ; return value ; } | Retrieve the value at specified index or 0 if no value had been specified . |
2,873 | public long [ ] toPrimitiveArray ( long [ ] array ) { for ( int i = 0 , j = 0 ; i < array . length ; ++ i ) { int index = - 1 ; if ( j < indices . length && ( index = indices [ j ] ) == i ) { array [ i ] = values [ j ] ; j ++ ; } else array [ i ] = 0 ; } return array ; } | Sets the values of the provided array using the contents of this array . If the provided array is longer than this array the additional values are left unchanged . |
2,874 | private Function getFunction ( int exponent , int dimensions ) { if ( exponent == 0 ) { int [ ] func = new int [ dimensions ] ; for ( int i = 0 ; i < dimensions ; ++ i ) { func [ i ] = i ; } return new Function ( func , func ) ; } exponent = Math . abs ( exponent ) ; Function function = permutationToReordering . get ( ... | Returns the bijective mapping for each integer in the form of an array based on the the current exponent of the permutation . |
2,875 | public V put ( K key , V value ) { V old = super . put ( key , value ) ; if ( size ( ) > bound ) { remove ( firstKey ( ) ) ; } return old ; } | Adds the key - value mapping to this map and if the total number of mappings exceeds the bounds removes either the currently lowest element or if reversed the currently highest element . |
2,876 | private void updateTimeRange ( long timestamp ) { if ( timestamp < startTime ) { startTime = timestamp ; } if ( timestamp > endTime ) { endTime = timestamp ; } } | Updates the start and end times if this time stamp exceeds either . |
2,877 | public String getDimensionDescription ( int dimension ) { if ( dimension < 0 || dimension >= basisMapping . numDimensions ( ) ) throw new IllegalArgumentException ( "Invalid dimension: " + dimension ) ; return basisMapping . getDimensionDescription ( dimension ) ; } | Returns a description of the dependency path feature to which the provided dimension is mapped . |
2,878 | private boolean acceptWord ( String word ) { return ! word . equals ( EMPTY_STRING ) && ( semanticFilter . isEmpty ( ) || semanticFilter . contains ( word ) ) ; } | Returns true if there is no semantic filter list or the word is in the filter list . |
2,879 | private void removeHtmlComments ( StringBuilder article ) { int htmlCommentStart = article . indexOf ( "<!--" ) ; while ( htmlCommentStart >= 0 ) { int htmlCommentEnd = article . indexOf ( " , htmlCommentStart ) ; if ( htmlCommentEnd > htmlCommentStart ) article . delete ( htmlCommentStart , htmlCommentEnd + 3 ) ; else... | Removes HTML comments from the article text |
2,880 | private int getTokenCount ( String article ) { Pattern notWhiteSpace = Pattern . compile ( "\\S+" ) ; Matcher matcher = notWhiteSpace . matcher ( article ) ; int tokens = 0 ; while ( matcher . find ( ) ) tokens ++ ; return tokens ; } | Returns the number of tokens in the article . |
2,881 | private long getIndex ( T x , T y ) { int i = elementIndices . index ( x ) ; int j = elementIndices . index ( y ) ; long index = ( ( ( long ) i ) << 32 ) | j ; return index ; } | Returns the concatenated index of the two elements . |
2,882 | public int getCount ( T x , T y ) { return counts . get ( getIndex ( x , y ) ) ; } | Returns the number of times the specified pair of objects has been seen by this counter . |
2,883 | public void reset ( ) { data . rewind ( ) ; data . getInt ( ) ; data . getInt ( ) ; data . getInt ( ) ; curCol = 0 ; entry = 0 ; try { advance ( ) ; } catch ( IOException ioe ) { throw new IOError ( ioe ) ; } } | Resets the iterator to the start of the file s data . |
2,884 | public static void save ( Object o , File file ) { try { FileOutputStream fos = new FileOutputStream ( file ) ; ObjectOutputStream outStream = new ObjectOutputStream ( new BufferedOutputStream ( fos ) ) ; outStream . writeObject ( o ) ; outStream . close ( ) ; } catch ( IOException ioe ) { throw new IOError ( ioe ) ; }... | Serializes the object to the provided file . |
2,885 | public static void save ( Object o , OutputStream stream ) { try { ObjectOutputStream outStream = ( stream instanceof ObjectOutputStream ) ? ( ObjectOutputStream ) stream : new ObjectOutputStream ( stream ) ; outStream . writeObject ( o ) ; } catch ( IOException ioe ) { throw new IOError ( ioe ) ; } } | Serializes the object to the provided stream . This method does not close the stream after writing . |
2,886 | @ SuppressWarnings ( "unchecked" ) public static < T > T load ( InputStream stream ) { try { ObjectInputStream inStream = ( stream instanceof ObjectInputStream ) ? ( ObjectInputStream ) stream : new ObjectInputStream ( stream ) ; T object = ( T ) inStream . readObject ( ) ; return object ; } catch ( IOException ioe ) {... | Loads a serialized object of the specifed type from the stream . This method does not close the stream after reading |
2,887 | public static < T > Iterator < T > join ( Collection < Iterable < T > > iterables ) { Queue < Iterator < T > > iters = new ArrayDeque < Iterator < T > > ( iterables . size ( ) ) ; for ( Iterable < T > i : iterables ) iters . add ( i . iterator ( ) ) ; return new CombinedIterator < T > ( iters ) ; } | Joins the iterators of all the provided iterables as one unified iterator . |
2,888 | private void advance ( ) { if ( current == null || ! current . hasNext ( ) ) { do { current = iters . poll ( ) ; } while ( current != null && ! current . hasNext ( ) ) ; } } | Moves to the next iterator in the queue if the current iterator is out of elements . |
2,889 | public synchronized T next ( ) { if ( current == null ) { throw new NoSuchElementException ( ) ; } T t = current . next ( ) ; if ( toRemoveFrom != current ) toRemoveFrom = current ; advance ( ) ; return t ; } | Returns the next element from some iterator . |
2,890 | public DoubleVector buildVector ( BufferedReader document , DoubleVector documentVector ) { Map < String , Integer > termCounts = new HashMap < String , Integer > ( ) ; Iterator < String > articleTokens = IteratorFactory . tokenize ( document ) ; while ( articleTokens . hasNext ( ) ) { String term = articleTokens . nex... | Represent a document as the summation of term Vectors . |
2,891 | public Graph < Edge > readUndirectedFromWeighted ( File f , Indexer < String > vertexIndexer , double minWeight ) throws IOException { BufferedReader br = new BufferedReader ( new FileReader ( f ) ) ; Graph < Edge > g = new SparseUndirectedGraph ( ) ; int lineNo = 0 ; for ( String line = null ; ( line = br . readLine (... | Reads in an undirected network from a file containing weighted edges only keeping those undirected edges whose weight was above the specified threshold |
2,892 | private static void clusterIteration ( Matrix matrix , int numClusters , KMeansSeed seedType , CriterionFunction criterion ) { DoubleVector [ ] centers = seedType . chooseSeeds ( numClusters , matrix ) ; int [ ] initialAssignments = new int [ matrix . rows ( ) ] ; if ( numClusters != 1 ) { int nc = 0 ; for ( int i = 0 ... | Performs one iteration of Direct Clustering over the data set . |
2,893 | protected static Set < String > loadValidTermSet ( String validTermsFileName ) throws IOException { Set < String > validTerms = new HashSet < String > ( ) ; BufferedReader br = new BufferedReader ( new FileReader ( validTermsFileName ) ) ; for ( String line = null ; ( line = br . readLine ( ) ) != null ; ) { validTerms... | Returns a set of terms based on the contents of the provided file . Each word is expected to be on its own line . |
2,894 | private void retainOnly ( int columns ) { LOGGER . info ( "Sorting the columns by entropy and computing the top " + columns + " columns to retain" ) ; int words = termToIndex . numDimensions ( ) ; MultiMap < Double , Integer > entropyToIndex = new BoundedSortedMultiMap < Double , Integer > ( columns , false , true , tr... | Drops all but the specified number of columns retaining those that have the highest information theoretic entropy . |
2,895 | private void processWordsInNP ( ArrayList < Pair < String > > wordsInPhrase ) { if ( wordsInPhrase . size ( ) > 1 ) { for ( int i = 0 ; i < wordsInPhrase . size ( ) - 1 ; i ++ ) { if ( inStartSet ( wordsInPhrase . get ( i ) . x ) ) { for ( int j = i + 1 ; j < wordsInPhrase . size ( ) ; j ++ ) { if ( inReceiveSet ( word... | Creates relations between words in a noun phrase |
2,896 | protected Double computeAssociation ( SemanticSpace sspace , String word1 , String word2 ) { Vector v1 = sspace . getVector ( word1 ) ; Vector v2 = sspace . getVector ( word2 ) ; if ( v1 == null || v2 == null ) return null ; double rank1 = findRank ( sspace , word1 , word2 ) ; double rank2 = findRank ( sspace , word2 ,... | Returns the association of the two words on a scale of 0 to 1 . |
2,897 | protected double computeScore ( double [ ] humanScores , double [ ] compScores ) { double average = 0 ; for ( double score : compScores ) average += score ; return average / compScores . length ; } | Returns the average computer generated score on the Deese Antonymy test . |
2,898 | public static void bitreverse ( DoubleVector data , int i0 , int stride ) { int n = data . length ( ) ; for ( int i = 0 , j = 0 ; i < n - 1 ; i ++ ) { int k = n / 2 ; if ( i < j ) { double tmp = data . get ( i0 + stride * i ) ; data . set ( i0 + stride * i , data . get ( i0 + stride * j ) ) ; data . set ( i0 + stride *... | This is the Gold rader bit - reversal algorithm |
2,899 | protected int getIndexFromMap ( int [ ] maskMap , int index ) { if ( index < 0 || index >= maskMap . length ) throw new IndexOutOfBoundsException ( "The given index is beyond the bounds of the matrix" ) ; int newIndex = maskMap [ index ] ; if ( newIndex < 0 || maskMap == rowMaskMap && newIndex >= matrix . rows ( ) || m... | Returns the new index value for a given index from a given mapping . Returns - 1 if no mapping is found for the requested row . |
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