Example usage for java.util Set size

Introduction

In this page you can find the example usage for java.util Set size.

Prototype

int size();

Source Link

Document

Returns the number of elements in this set (its cardinality).

Usage

From source file:Main.java

public static <T> Set<T> merge(Set<T> c1, Set<T> c2) {
    if (c1 == null || c1.size() == 0) {
        return c2;
    }// w ww.  j a v  a 2s .c  o  m
    if (c2 == null || c2.size() == 0) {
        return c1;
    }
    Set<T> all = new HashSet<T>(c1.size() + c2.size());
    all.addAll(c1);
    all.addAll(c2);
    return all;
}

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From source file:edu.stanford.muse.Main.java

public static GroupAssigner doGroups(AddressBook addressBook, Collection<EmailDocument> allDocs)
        throws CancelledException {
    Grouper<String> grouper = new Grouper<String>();
    // we'll ignore the one-sies
    int threshold = 1;
    Set<Contact> contactsToIgnore = GroupUtils.contactsAtOrBelowThreshold(addressBook, allDocs, threshold);
    log.info(contactsToIgnore.size() + " contacts will be ignored because they are below threshold of "
            + threshold);/*from   w  w  w .j a  va2  s  .co  m*/

    Map<Group<String>, Float> weightedInputMap = GroupUtils.convertEmailsToGroupsWeighted(addressBook, allDocs,
            contactsToIgnore);
    List<Pair<Group<String>, Float>> weightedInputList = Util.mapToListOfPairs(weightedInputMap);
    Util.sortPairsBySecondElement(weightedInputList);
    Map<String, Float> individualElementsValueMap = GroupUtils.getScoreForContacts(addressBook, allDocs,
            contactsToIgnore);
    individualElementsValueMap = Util.reorderMapByValue(individualElementsValueMap);
    //      hierarchy = grouper.findGroups(input, 25);
    try {
        grouper.setAffinityMap(GroupUtils.computeAffinityMap(addressBook.allContacts()));
        grouper.setIndividualElementsValueMap(individualElementsValueMap);
    } catch (Throwable t) {
        log.warn("Exception trying to compute grouper affinity map " + t);
        Util.print_exception(t, log);
    }

    float errWeight = 0.4f;
    int nGroups = 20;

    GroupAssigner ca = new GroupAssigner();

    GroupHierarchy<String> hierarchy = grouper.findGroupsWeighted(weightedInputList, nGroups - 1, errWeight); // err weight of 0.4 seems to work well.
    if (hierarchy != null) {
        List<SimilarGroup<String>> selectedGroups = SimilarGroupMethods.topGroups(hierarchy, nGroups - 1);
        ca.setupGroups(allDocs, selectedGroups, addressBook, 0);
    }
    return ca;
}

---

From source file:edu.wpi.checksims.algorithm.output.SimilarityMatrix.java

/**
 * Fill the results matrix/*from w ww.ja va 2s  . com*/
 *
 * NOTE that this is inefficient; we calculate twice for each pair, as (i,j) and (j,i).
 * If speed optimizations are required, recommend starting here.
 *
 * @param submissions Submissions to generate results matrix from
 * @param algorithm Algorithm to use when detecting plagiarism
 * @return Array of algorithm results, with results[i,j] being the results of comparing students i and j
 */
public static SimilarityMatrix generate(Set<Submission> submissions, SimilarityDetector algorithm) {
    checkNotNull(submissions);
    checkArgument(submissions.size() >= 2);
    checkNotNull(algorithm);

    Logger logs = LoggerFactory.getLogger(SimilarityMatrix.class);

    float[][] results = new float[submissions.size()][submissions.size()];
    logs.debug("Sorting submissions prior to algorithm pass...");
    List<Submission> submissionsSorted = Ordering
            .from((Submission a, Submission b) -> a.getName().compareTo(b.getName()))
            .immutableSortedCopy(submissions);

    // Generate all possible unordered pairs of submissions
    Set<Submission> submissionsAsSet = ImmutableSet.copyOf(submissions);
    Set<Pair<Submission, Submission>> pairs = PairGenerator.generatePairs(submissionsAsSet);

    // Get results for all possible pairs of submissions
    Set<AlgorithmResults> algorithmResults = AlgorithmRunner.runAlgorithm(pairs, algorithm);

    // First, zero the diagonal of the results array
    for (int i = 0; i < submissionsSorted.size(); i++) {
        results[i][i] = 0.00f; // Same submission, ignore
    }

    // For each result, fill corresponding spots in the results matrix
    algorithmResults.stream().forEach((result) -> {
        int indexFirst = submissionsSorted.indexOf(result.a);
        int indexSecond = submissionsSorted.indexOf(result.b);

        if (indexFirst == -1) {
            throw new RuntimeException("Could not find index of submission " + result.a.getName());
        } else if (indexSecond == -1) {
            throw new RuntimeException("Could not find index of submission " + result.b.getName());
        }

        results[indexFirst][indexSecond] = result.percentMatchedA();
        results[indexSecond][indexFirst] = result.percentMatchedB();
    });

    logs.info("Done performing similarity detection");

    return new SimilarityMatrix(submissionsSorted, results);
}

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From source file:Main.java

/**
 * As {@link #getAllFields(Class)} but acts on a list of {@link Class}s and
 * uses only {@link Class#getDeclaredFields()}.
 *
 * @param classes The list of classes to reflect on
 * @return The complete list of fields//from w ww  .j  a  v  a  2s.  c  o  m
 */
private static Field[] getAllFields(List<Class<?>> classes) {
    Set<Field> fields = new HashSet<Field>();
    for (Class<?> clazz : classes) {
        fields.addAll(Arrays.asList(clazz.getDeclaredFields()));
    }

    return fields.toArray(new Field[fields.size()]);
}

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From source file:io.cortical.rest.model.TestDataMother.java

/**
 * Create dummy  {@link Fingerprint}.//from ww  w  .j  a  va2  s  .c o m
 * 
 * @return dummy fingerprint.
 */
public static Fingerprint createFingerprint() {
    Random random = new Random();
    Set<Integer> positionSet = new HashSet<>();
    while (positionSet.size() <= FINGERPRINT_LENGTH) {
        positionSet.add(random.nextInt(MAX_POSITION));
    }

    Integer[] positionsInteger = new Integer[FINGERPRINT_LENGTH];
    positionsInteger = positionSet.toArray(positionsInteger);
    sort(positionsInteger);
    return new Fingerprint(ArrayUtils.toPrimitive(positionsInteger));
}

---

From source file:TwitterClustering.java

public static float jaccardDistance(Set<String> a, Set<String> b) {

    if (a.size() == 0 || b.size() == 0) {
        return 0;
    }//from   w  w w .  j  av  a  2  s  .  c o  m

    Set<String> unionXY = new HashSet<String>(a);
    unionXY.addAll(b);

    Set<String> intersectionXY = new HashSet<String>(a);
    intersectionXY.retainAll(b);
    float retValue = (float) intersectionXY.size() / (float) unionXY.size();
    return retValue;

}

---

From source file:mml.handler.scratch.Scratch.java

/**
 * Get a version that may or may not be in scratch. If not put it there.
 * @param docid the docid //from w  w w . j av a 2 s  .co m
 * @param version the desired single version or null if default
 * @param dbase the database it is in
 * @return a ScratchVersion object or null
 * @throws MMLException 
 */
public static ScratchVersion getVersion(String docid, String version, String dbase) throws MMLException {
    try {
        ScratchVersion sv = null;
        if (version != null)
            sv = getScratchVersion(docid, version, dbase);
        if (sv == null) {
            EcdosisMVD mvd = doGetMVD(dbase, docid);
            if (mvd != null) {
                if (version == null)
                    version = mvd.getVersion1();
                String base = Layers.stripLayer(version);
                HashMap<String, char[]> layers = new HashMap<String, char[]>();
                int numVersions = mvd.numVersions();
                for (int i = 1; i <= numVersions; i++) {
                    String vName = mvd.getVersionId((short) i);
                    if (vName.lastIndexOf(base) == 0)
                        layers.put(vName, mvd.getVersion(i));
                }
                if (!layers.isEmpty()) {
                    Set<String> keys = layers.keySet();
                    String[] arr = new String[keys.size()];
                    keys.toArray(arr);
                    Arrays.sort(arr);
                    String[] all = mvd.getAllVersions();
                    short id = mvd.getVersionId(version);
                    String longName = mvd.getVersionLongName(id);
                    sv = new ScratchVersion(base, longName, docid, dbase, null, false);
                    for (int i = 0; i < arr.length; i++) {
                        String updatedName = Layers.upgradeLayerName(all, arr[i]);
                        sv.addLayer(layers.get(arr[i]), ScratchVersion.layerNumber(updatedName));
                    }
                    // save it for next time
                    Connection conn = Connector.getConnection();
                    conn.putToDb(Database.SCRATCH, dbase, docid, version, sv.toJSON());
                    return sv;
                }
            }
            return null;
        } else
            return sv;
    } catch (DbException e) {
        throw new MMLException(e);
    }
}

---

From source file:bayesGame.ui.painter.OrNodePainter.java

public static Image paintPercentage(Color gridColor, Color falseColor, int size, int squaresize, BayesNode node,
        Fraction parentNode1Probability, Fraction parentNode2Probability) {

    BufferedImage img = new BufferedImage(size, size, BufferedImage.TYPE_INT_RGB);
    Graphics g = img.getGraphics();

    NodePainter.graphicBackgroundPainter(g, 0, 0, size, size);

    // get non-zero truth table entries from the node
    List<Map<Object, Boolean>> nonZeroEntries = node.getNonZeroProbabilities();

    // get the identities of its parents by taking the first map and querying it 
    // for KeySet, subtracting the object representing the node itself
    Set<Object> nodeParents = nonZeroEntries.get(0).keySet();
    nodeParents.remove(node.type);//  ww w. ja  v  a  2  s  .  c o  m

    if (nodeParents.size() > 2) {
        throw new IllegalArgumentException("OR node with more than 2 parents not yet implemented");
    }

    Object[] nodeParentsArray = nodeParents.toArray();
    Object parent1 = nodeParentsArray[0];
    Object parent2 = nodeParentsArray[1];

    // for each map, check the truth table entry it corresponds to and color
    // those appropriately
    boolean p1true_p2true = false;
    boolean p1true_p2false = false;
    boolean p1false_p2true = false;
    boolean p1false_p2false = false;

    for (Map<Object, Boolean> map : nonZeroEntries) {
        Boolean parent1truth = map.get(parent1);
        Boolean parent2truth = map.get(parent2);

        if (parent1truth && parent2truth) {
            p1true_p2true = true;
        } else if (parent1truth && !parent2truth) {
            p1true_p2false = true;
        } else if (!parent1truth && parent2truth) {
            p1false_p2true = true;
        } else if (!parent1truth && !parent2truth) {
            p1false_p2false = true;
        }
    }

    int XSize = parentNode1Probability.multiply(size).intValue();
    int X_Size = size - XSize;
    int YSize = parentNode2Probability.multiply(size).intValue();
    int Y_Size = size - YSize;

    if (p1true_p2true) {
        NodePainter.squarePainter(g, 0, 0, XSize, YSize, gridColor, Color.BLACK);
    } else {
        NodePainter.squarePainter(g, 0, 0, XSize, YSize, NodePainter.RECTANGLE_BOX_BACKGROUND_COLOR,
                Color.BLACK);
    }

    NodePainter.squarePainter(g, XSize, 0, X_Size, YSize, gridColor, Color.BLACK);
    NodePainter.squarePainter(g, 0, YSize, XSize, Y_Size, gridColor, Color.BLACK);

    if (p1false_p2false) {
        NodePainter.squarePainter(g, XSize, YSize, X_Size, Y_Size, falseColor, Color.BLACK);
    } else {
        NodePainter.squarePainter(g, XSize, YSize, X_Size, Y_Size, NodePainter.RECTANGLE_BOX_BACKGROUND_COLOR,
                Color.BLACK);
    }

    return img;
}

---

From source file:Main.java

/**
 * Get a process definitions string like "1,2,3".
 *///from ww  w. j  a  v a2s . co m
private static String getProcessDefinitions(Set<Long> processDefinitions) {
    StringBuilder processDefs = new StringBuilder();
    int count = 0;
    for (Long pd : processDefinitions) {
        processDefs.append(pd);
        count++;
        if (count < processDefinitions.size()) {
            processDefs.append(",");
        }
    }

    return processDefs.toString();
}

---

From source file:cooccurrence.Omer_Levy.java

/**
 * Method that will extract top D singular values from CoVariance Matrix 
 * It will then identify the corresponding columns from U and V and add it to new matrices 
 * @param U//  w  w  w  . j  av  a 2 s  . c  o m
 * @param V
 * @param coVariance
 * @param matrixUd
 * @param matrixVd
 * @param coVarD
 * @param indicesD 
 */
private static void getTopD(RealMatrix U, RealMatrix V, RealMatrix coVariance, RealMatrix matrixUd,
        RealMatrix matrixVd, RealMatrix coVarD, ArrayList<Integer> indicesD) {
    TreeMap<Double, Set<Integer>> tmap = new TreeMap<>();
    for (int i = 0; i < coVariance.getRowDimension(); i++) {
        double val = coVariance.getEntry(i, i);
        if (tmap.containsKey(val)) {
            Set<Integer> temp = tmap.get(val);
            temp.add(i);
        } else {
            Set<Integer> temp = new HashSet<>();
            temp.add(i);
            tmap.put(val, temp);
        }
    }
    Iterator iter = tmap.keySet().iterator();
    while (iter.hasNext()) {
        Double val = (Double) iter.next();
        Set<Integer> indices = tmap.get(val);
        for (int i = 0; i < indices.size(); i++) {
            Iterator iterIndices = indices.iterator();
            while (iterIndices.hasNext()) {
                int index = (Integer) iterIndices.next();
                indicesD.add(index);
                coVarD.addToEntry(index, index, val);
                matrixUd.setColumnVector(index, U.getColumnVector(index));
                matrixVd.setColumnVector(index, V.getColumnVector(index));
            }
        }
    }

}

---

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