code stringlengths 73 34.1k | label stringclasses 1
value |
|---|---|
private DependencyTreeNode getNextNode(DependencyRelation prev,
DependencyRelation cur) {
return (prev.headNode() == cur.headNode()
|| prev.dependentNode() == cur.headNode())
? cur.dependentNode()
: cur.headNode();
} | java |
private static double[] toArray(DoubleVector v, int length) {
double[] arr = new double[length];
for (int i = 0; i < arr.length; ++i) {
arr[i] = v.get(i);
}
return arr;
} | java |
private Collection<WordSimilarity> parse(File word353file) {
Collection<WordSimilarity> pairs = new LinkedList<WordSimilarity>();
try {
BufferedReader br = new BufferedReader(new FileReader(word353file));
// skip the first line
br.readLine();
... | java |
public Iterator<MatrixEntry> iterator() {
try {
return MatrixIO.getMatrixFileIterator(matrixFile, format);
} catch (IOException ioe) {
throw new IOError(ioe);
}
} | java |
private void loadFromFormat(InputStream is, SSpaceFormat format)
throws IOException {
// NOTE: Use a LinkedHashMap here because this will ensure that the
// words are returned in the same row-order as the matrix. This
// generates better disk I/O behavior for accessing the matrix si... | java |
public Graph<T> next() {
if (nextSubgraphs.isEmpty())
throw new NoSuchElementException();
Graph<T> next = nextSubgraphs.poll();
// If we've exhausted the current set of subgraphs, queue up more of
// them, generated from the remaining vertices
if (nextSubgra... | java |
private static void add(IntegerVector semantics, TernaryVector index) {
// Lock on the semantic vector to avoid a race condition with another
// thread updating its semantics. Use the vector to avoid a class-level
// lock, which would limit the concurrency.
synchronized(semantics) {
... | java |
public SimpleDependencyPath copy() {
SimpleDependencyPath copy = new SimpleDependencyPath();
copy.path.addAll(path);
copy.nodes.addAll(nodes);
return copy;
} | java |
public SimpleDependencyPath extend(DependencyRelation relation) {
SimpleDependencyPath copy = copy();
// Figure out which node is at the end of our path, and then add the new
// node to the end of our nodes
DependencyTreeNode last = last();
copy.nodes.add((relation.headNode().eq... | java |
public static Matrix create(int rows, int cols, boolean isDense) {
// Estimate the number of bytes that the matrix will take up based on
// its maximum dimensions and its sparsity.
long size = (isDense)
? (long)rows * (long)cols * BYTES_PER_DOUBLE
: (long)(rows * (long)co... | java |
public static Matrix copy(Matrix matrix) {
Matrix copiedMatrix = null;
if (matrix instanceof SparseMatrix)
copiedMatrix = Matrices.create(
matrix.rows(), matrix.columns(), Type.SPARSE_IN_MEMORY);
else
copiedMatrix = Matrices.create(
... | java |
public String next() {
if (next == null)
throw new NoSuchElementException();
String replacement = replacementMap.get(next);
replacement = (replacement == null) ? next : replacement;
advance();
return replacement;
} | java |
public Color next() {
int r = rand.nextInt(256);
int g = rand.nextInt(256);
int b = rand.nextInt(256);
return (seed == null)
? new Color(r, g, b)
: new Color((r + seed.getRed()) / 2,
(g + seed.getGreen()) / 2,
(b + s... | java |
public static synchronized void setProperties(Properties props) {
wordLimit = Integer.parseInt(
props.getProperty(TOKEN_COUNT_LIMIT_PROPERTY, "0"));
String filterProp =
props.getProperty(TOKEN_FILTER_PROPERTY);
filter = (filterProp != null)
? TokenFilter... | java |
private static Iterator<String> getBaseIterator(BufferedReader reader,
boolean keepOrdering) {
// The final iterator is how the stream will be tokenized after all the
// tokenizing options have been applied. This value is iteratively set
// a... | java |
@SuppressWarnings("unchecked")
private void updateSemantics(SemanticVector toUpdate,
String cooccurringWord,
TernaryVector iv) {
SemanticVector prevWordSemantics = getSemanticVector(cooccurringWord);
Integer occurrences = wor... | java |
private static void add(DoubleVector semantics,
TernaryVector index,
double percentage) {
for (int p : index.positiveDimensions())
semantics.add(p, percentage);
for (int n : index.negativeDimensions())
semantics.add(n, -perc... | java |
private static DoubleVector generateInitialVector(int length,
double mean,
double std) {
DoubleVector vector = new DenseVector(length);
for (int i = 0; i < length; ++i) {
double v = RA... | java |
private static double dotProduct(DoubleVector u,
DoubleVector v) {
double dot = 0;
for (int i = 0; i < u.length(); ++i) {
double a = u.get(i);
double b = v.get(i);
dot += u.get(i) * v.get(i);
}
return dot;
} | java |
private void updateTypeCounts(T type, int delta) {
if (!typeCounts.containsKey(type)) {
assert delta > 0
: "removing edge type that was not originally present";
typeCounts.put(type, delta);
}
else {
int curCount = typeCounts.get(type);
... | java |
private static File getTempMatrixFile() {
File tmp = null;
try {
tmp = File.createTempFile("matlab-sparse-matrix", ".dat");
} catch (IOException ioe) {
throw new IOError(ioe);
}
tmp.deleteOnExit();
return tmp;
} | java |
private IntegerVector getSemanticVector(String word) {
IntegerVector v = wordSpace.get(word);
if (v == null) {
// lock on the word in case multiple threads attempt to add it at
// once
synchronized(this) {
// recheck in case another thread added it whi... | java |
public static void shuffle(int[] arr, Random rand) {
int size = arr.length;
for (int i = size; i > 1; i--) {
int tmp = arr[i-1];
int r = rand.nextInt(i);
arr[i-1] = arr[r];
arr[r] = tmp;
}
} | java |
private void addInitial(G g) {
Set<T> typeCounts = g.edgeTypes();
LinkedList<Map.Entry<G,Integer>> graphs = typesToGraphs.get(typeCounts);
if (graphs == null) {
graphs = new LinkedList<Map.Entry<G,Integer>>();
typesToGraphs.put(new HashSet<T>(typeCounts), graphs);
... | java |
private static void usage(ArgOptions options) {
System.out.println(
"Fanmod 1.0, " +
"usage: java -jar fanmod.jar [options] input.graph output.serialized \n\n"
+ options.prettyPrint() +
"\nThe edge file format is:\n" +
" vertex1 vertex2 [edge_label]... | java |
private static double entropy(double count, double sum) {
double p = count / sum;
return Math.log(p) * p;
} | java |
public int getCount(T obj) {
int objIndex = (allowNewIndices)
? objectIndices.index(obj)
: objectIndices.find(obj);
return (objIndex < 0) ? 0 : indexToCount.get(objIndex);
} | java |
public static int log2 (int n){
int log = 0;
for(int k=1; k < n; k *= 2, log++);
if (n != (1 << log))
return -1 ; /* n is not a power of 2 */
return log; } | java |
public static double sum(DoubleVector v) {
double sum = 0;
if (v instanceof SparseVector) {
for (int nz : ((SparseVector)v).getNonZeroIndices())
sum += v.get(nz);
}
else {
int len = v.length();
for (int i = 0; i < len; ++i)
... | java |
private static void execute(File dataMatrixFile,
File affMatrixFile,
int dims, File outputMatrix)
throws IOException {
// Decide whether to use Matlab or Octave
if (isMatlabAvailable())
invokeMatlab(dataMatrixFile,... | java |
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.getRun... | java |
private static void invokeOctave(File dataMatrixFile, File affMatrixFile,
int dimensions, File outputFile)
throws IOException {
// Create the octave file for executing
File octaveFile = File.createTempFile("octave-LPP",".m");
// Create the Matl... | java |
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);
ap... | java |
private void advance() {
try {
// loop until we find a word in the reader, or there are no more
// words
while (true) {
// if we haven't looked at any lines yet, or if the index into
// the current line is already at the end
if... | java |
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))
... | java |
private static int index(Object o) {
Integer i = TYPE_INDICES.get(o);
if (i == null) {
synchronized (TYPE_INDICES) {
// check that another thread did not already update the index
i = TYPE_INDICES.get(o);
if (i != null)
retur... | java |
private void addThread() {
Thread t = new WorkerThread(workQueue);
threads.add(t);
t.start();
} | java |
public long getRemainingTasks(Object taskGroupId) {
CountDownLatch latch = taskKeyToLatch.get(taskGroupId);
return (latch == null)
? 0
: latch.getCount();
} | java |
public Object registerTaskGroup(int numTasks) {
Object key = new Object();
taskKeyToLatch.putIfAbsent(key, new CountDownLatch(numTasks));
return key;
} | java |
public void run(Collection<Runnable> tasks) {
// Create a semphore that the wrapped runnables will execute
int numTasks = tasks.size();
CountDownLatch latch = new CountDownLatch(numTasks);
for (Runnable r : tasks) {
if (r == null)
throw new NullPointerExceptio... | java |
@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);
}
} | java |
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:
... | java |
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 ... | java |
public static double spearmanRankCorrelationCoefficient(double[] a,
double[] b) {
check(a, b);
int N = a.length;
int NcubedMinusN = (N * N * N) - N;
// Convert a and b into rankings. The last value of this array is the
... | java |
public Set<T> types() {
// NOTE: purely unoptimized!
Set<T> types = new HashSet<T>();
for (Object o : edges.values()) {
Set<T> s = (Set<T>)o;
types.addAll(s);
}
return types;
} | java |
public static double mean(Collection<? extends Number> values) {
double sum = 0d;
for (Number n : values)
sum += n.doubleValue();
return sum / values.size();
} | java |
public static double mean(int[] values) {
double sum = 0d;
for (int i : values)
sum += i;
return sum / values.length;
} | java |
@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);
Collect... | java |
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];
} | java |
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();
} | java |
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();
} | java |
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();
} | java |
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());
} | java |
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);
} | java |
public static double sum(Collection<? extends Number> values) {
double sum = 0d;
for (Number n : values)
sum += n.doubleValue();
return sum;
} | java |
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, e2fro... | java |
private void addIntermediateNode(Node<V> original,
int numOverlappingCharacters,
String key,
int indexOfStartOfOverlap,
V value) {
// get the current prefix for the node
char[] originalPrefix = original.prefix;
// create the new prefix for the original node, which will ... | java |
public <E extends Edge> double[] compute(Graph<E> g) {
// Perform a quick test for whether the vertices of g are a contiguous
// sequence starting at 0, which makes the vertex mapping trivial
if (!hasContiguousVertices(g))
throw new IllegalArgumentException(
"Vertices... | java |
private Matrix getEdgeSimMatrix(List<Edge> edgeList, SparseMatrix sm,
boolean keepSimilarityMatrixInMemory) {
return (keepSimilarityMatrixInMemory)
? calculateEdgeSimMatrix(edgeList, sm)
: new LazySimilarityMatrix(edgeList, sm);
} | java |
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.re... | java |
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... | java |
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;
} | java |
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 Ille... | java |
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 Illega... | java |
public static Matrix average(Matrix m, Dimension dim) {
Matrix averageMatrix = null;
if (dim == Dimension.ALL) {
// Compute the average of all values in the matrix.
double average = 0;
for (int i = 0; i < m.rows(); ++i) {
for (int j = 0; j < m.columns... | java |
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()) ... | java |
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);
// Get th... | java |
public Multigraph<T,E> next() {
if (!hasNext())
throw new NoSuchElementException();
Multigraph<T,E> cur = next.poll();
if (next.isEmpty())
advance();
return cur;
} | java |
private void addRelation(String object, String attribute) {
double val;
int row, col;
object = object.toLowerCase();
attribute = attribute.toLowerCase();
// get row in matrix
if( objectTable.containsKey(object) ) {
// if the object already exists in matrix, ... | java |
private boolean inStartSet(String tag) {
return
// noun
tag.startsWith("NN") ||
// adjective
tag.startsWith("JJ") ||
// adverb
tag.startsWith("RB") ||
// cardinal number
tag.startsWith("CD");
} | java |
private boolean isPhraseOrClause(String tag) {
// find out why adding more reduced the number of relations
return
(!tag.equals("SYM") &&
tag.startsWith("S")) ||
tag.equals("ADJP") ||
tag.equals("ADVP") ||
tag.equals("CONJP") ||
tag... | java |
private String getNextTag(String str) {
String tag;
int endIndex;
int tagIndex = str.indexOf("(");
if( tagIndex < 0 ) {
return null;
}
// in case there's nothing in the sentence
endIndex = str.indexOf(" ", tagIndex);
if( endIndex < 0 ) {
... | java |
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;
... | java |
public void process(Iterator<String> text) {
String nextToken = null, curToken = null;
// Base case for the next token buffer to ensure we always have two
// valid tokens present
if (text.hasNext())
nextToken = text.next();
while (text.hasNext()) {
curToke... | java |
private void processBigram(String left, String right) {
TokenStats leftStats = getStatsFor(left);
TokenStats rightStats = getStatsFor(right);
// mark that both appeared
leftStats.count++;
rightStats.count++;
// Mark the respective positions of each
leftS... | java |
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.... | java |
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);
defa... | java |
private double logLikelihood(int[] contingencyTable) {
// Rename for short-hand convenience
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;
... | java |
public int getDimension(DependencyPath path) {
String endToken = path.last().word();
// Extract out how the current word is related to the last word in the
// path.
String relation = path.getRelation(path.length() - 1);
return getDimensionInternal(endToken + "+" + relation);
... | java |
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;
} | java |
protected void addContextTerms(SparseDoubleVector meaning,
Queue<String> words,
int distance) {
// Iterate through each of the context words.
for (String term : words) {
if (!term.equals(IteratorFactory.EMPTY_TOKEN)) {
... | java |
@SuppressWarnings("unchecked")
private void processSpace() throws IOException {
compressedDocumentsWriter.close();
// Generate the reverse index-to-term mapping. We will need this for
// assigning specific senses to each term
String[] indexToTerm = new String[termToIndex.si... | java |
private void senseInduce(String term, Matrix contexts) throws IOException {
LOGGER.fine("Clustering " + contexts.rows() + " contexts for " + term);
// For terms with fewer than seven contexts, set the number of potential
// clusters lower
int numClusters = Math.min(7, contexts.rows());
... | java |
private int processIntDocument(int termIndex, int[] document,
Matrix contextMatrix,
int rowStart,
BitSet featuresForTerm) {
int contexts = 0;
for (int i = 0; i < document.length; ++i) {
... | java |
private static double logLikelihood(double a, double b,
double c, double d) {
// Table set up as:
// a b
// c d
double col1sum = a + c;
double col2sum = b + d;
double row1sum = a + b;
double row2sum = c + d;
d... | java |
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);
} | java |
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.contains... | java |
public DoubleVector centerOfMass() {
// Handle lazy initialization
if (centroid == null) {
if (indices.size() == 1)
centroid = sumVector;
else {
// Update the centroid by normalizing by the number of elements.
// We expect that the ... | java |
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 Den... | java |
public void merge(CandidateCluster other) {
indices.addAll(other.indices);
VectorMath.add(sumVector, other.sumVector);
centroid = null;
} | java |
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,
... | java |
private void updateTemporalSemantics(long currentSemanticPartitionStartTime,
SemanticSpace semanticPartition) {
// Pre-allocate the zero vector so that if multiple interesting words
// are not present in the space, they all point to the same zero
... | java |
private void printShiftRankings(String dateString,
long startOfMostRecentPartition,
TimeSpan partitionDuration)
throws IOException {
SortedMultiMap<Double,String> shiftToWord =
new TreeMultiMap<Double,String>();
... | java |
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 s... | java |
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);
} | java |
public int size() {
// Since the sets are disjoint, we can simple sum their sizes
int size = 0;
for (Set<T> s : sets)
size += s.size();
return size;
} | java |
public void readFields(DataInput in) throws IOException {
t.readFields(in);
position = in.readInt();
} | java |
public void write(DataOutput out) throws IOException {
t.write(out);
out.writeInt(position);
} | java |
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,... | java |
private DoubleVector groupConvolution(Queue<String> prevWords,
Queue<String> nextWords) {
// Generate an empty DoubleVector to hold the convolution.
DoubleVector result = new DenseVector(indexVectorSize);
// Do the convolutions starting at index 0.
... | java |
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