Examples of org.apache.commons.math3.stat.descriptive.AggregateSummaryStatistics

Package org.apache.commons.math3.stat.descriptive

Examples of org.apache.commons.math3.stat.descriptive.AggregateSummaryStatistics

org.apache.commons.math3.exception.MathIllegalArgumentException

An aggregator for {@code SummaryStatistics} from several data sets ordata set partitions. In its simplest usage mode, the client creates an instance via the zero-argument constructor, then uses {@link #createContributingStatistics()} to obtain a {@code SummaryStatistics}for each individual data set / partition. The per-set statistics objects are used as normal, and at any time the aggregate statistics for all the contributors can be obtained from this object.
Clients with specialized requirements can use alternative constructors to control the statistics implementations and initial values used by the contributing and the internal aggregate {@code SummaryStatistics} objects.
A static {@link #aggregate(Collection)} method is also included that computesaggregate statistics directly from a Collection of SummaryStatistics instances.
When {@link #createContributingStatistics()} is used to create SummaryStatisticsinstances to be aggregated concurrently, the created instances' {@link SummaryStatistics#addValue(double)} methods must synchronize on the aggregatinginstance maintained by this class. In multithreaded environments, if the functionality provided by {@link #aggregate(Collection)} is adequate, that method should be usedto avoid unnecessary computation and synchronization delays.
@since 2.0

     */
    public double correlation(final double[] xArray, final double[] yArray)
            throws DimensionMismatchException {


        if (xArray.length != yArray.length) {
            throw new DimensionMismatchException(xArray.length, yArray.length);
        }


        final int n = xArray.length;
        final long numPairs = sum(n - 1);

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     * @throws DimensionMismatchException if {@link #target} and
     * {@link #weightMatrix} have inconsistent dimensions.
     */
    private void checkParameters() {
        if (target.length != weightMatrix.getColumnDimension()) {
            throw new DimensionMismatchException(target.length,
                                                 weightMatrix.getColumnDimension());
        }
    }

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    public void increment(final double[] data)
        throws DimensionMismatchException {


        int length = data.length;
        if (length != dimension) {
            throw new DimensionMismatchException(length, dimension);
        }


        // only update the upper triangular part of the covariance matrix
        // as only these parts are actually stored
        for (int i = 0; i < length; i++){

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     * @throws DimensionMismatchException if the dimension of sc does not match this
     * @since 3.3
     */
    public void append(StorelessCovariance sc) throws DimensionMismatchException {
        if (sc.dimension != dimension) {
            throw new DimensionMismatchException(sc.dimension, dimension);
        }


        // only update the upper triangular part of the covariance matrix
        // as only these parts are actually stored
        for (int i = 0; i < dimension; i++) {

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            if (m.getColumnDimension() != m.getRowDimension()) {
                throw new NonSquareOperatorException(m.getColumnDimension(),
                                                     m.getRowDimension());
            }
            if (m.getRowDimension() != a.getRowDimension()) {
                throw new DimensionMismatchException(m.getRowDimension(),
                                                     a.getRowDimension());
            }
        }
    }

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     * length.
     */
    protected double[] computeResiduals(double[] objectiveValue) {
        final double[] target = getTarget();
        if (objectiveValue.length != target.length) {
            throw new DimensionMismatchException(target.length,
                                                 objectiveValue.length);
        }


        final double[] residuals = new double[target.length];
        for (int i = 0; i < target.length; i++) {

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   */
  public Rotation(Vector3D u, Vector3D v) throws MathArithmeticException {


    double normProduct = u.getNorm() * v.getNorm();
    if (normProduct == 0) {
        throw new MathArithmeticException(LocalizedFormats.ZERO_NORM_FOR_ROTATION_DEFINING_VECTOR);
    }


    double dot = u.dotProduct(v);


    if (dot < ((2.0e-15 - 1.0) * normProduct)) {

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     * @return the smallest prime greater than or equal to n.
     * @throws MathIllegalArgumentException if n &lt; 0.
     */
    public static int nextPrime(int n) {
        if (n < 0) {
            throw new MathIllegalArgumentException(LocalizedFormats.NUMBER_TOO_SMALL, n, 0);
        }
        if (n == 2) {
            return 2;
        }
        n |= 1;//make sure n is odd

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     * @throws MathIllegalArgumentException if n &lt; 2.
     */
    public static List<Integer> primeFactors(int n) {


        if (n < 2) {
            throw new MathIllegalArgumentException(LocalizedFormats.NUMBER_TOO_SMALL, n, 2);
        }
        // slower than trial div unless we do an awful lot of computation
        // (then it finally gets JIT-compiled efficiently
        // List<Integer> out = PollardRho.primeFactors(n);
        return SmallPrimes.trialDivision(n);

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   */
  public Rotation(Vector3D axis, double angle) throws MathIllegalArgumentException {


    double norm = axis.getNorm();
    if (norm == 0) {
      throw new MathIllegalArgumentException(LocalizedFormats.ZERO_NORM_FOR_ROTATION_AXIS);
    }


    double halfAngle = -0.5 * angle;
    double coeff = FastMath.sin(halfAngle) / norm;

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