Examples of no.uib.cipr.matrix.Vector

no.uib.cipr.matrix.Vector
Basic vector interface. It holds doubles in an array, and is used alongside Matrix in numerical computations. Implementing classes decides on the actual storage.
Basic operations

Use size to get the vector size. get(int) gets an element, and there are corresponding set(int,double) and add(int,double) methods as well. Note that vector indices are zero-based (typical for Java and C). This means that they range from 0 to size-1. It is legal to have size equal zero.

Other basic operations are zero which zeros all the entries of the vector, which can be cheaper than either zeroing the vector manually, or creating a new vector, and the operation copy which creates a deep copy of the vector. This copy has separate storage, but starts with the same contents as the current vector.

Iterators

The vector interface extends Iterable, and the iterator returns a VectorEntry which contains current index and entry value. Note that the iterator may skip non-zero entries. Using an iterator, many simple and efficient algorithms can be created. The iterator also permits changing values in the vector, however only non-zero entries can be changed.

Basic linear algebra

A selection of basic linear algebra operations are available. To ensure high efficiency, little or no internal memory allocation is done, and the user is required to supply the output arguments.

The operations available include:

Additions

Vectors can be added to each other, even if their underlying vector structures are incompatible

Scaling

Scalar multiplication (scaling) of a whole vector

Norms

Both innerproducts and norms can be computed. Several common norms are supported

    }


    public void testPentaDiagonal() {
        int n = Utilities.getInt(1, 10);
        Matrix A = new DenseMatrix(n, n);
        Vector x = new DenseVector(n);


        for (int i = 0; i < n; ++i) {
            A.set(i, i, 4);
            x.set(i, 1);
        }
        for (int i = 0; i < n - 1; ++i) {
            A.set(i, i + 1, -1);
            A.set(i + 1, i, -1);
        }

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 */
public class ICCTest extends IncompleteFactorizationTestAbstract {


    @Override
    void testFactorization(Matrix A, Vector x) {
        Vector b = A.mult(x, x.copy());


        ICC icc = new ICC(new CompRowMatrix(A));
        icc.setMatrix(A);
        icc.apply(b, x);


        Vector r = A.multAdd(-1, x, b.copy());


        assertEquals(0, r.norm(Vector.Norm.TwoRobust), 1e-5);
    }

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 */
public class ILUTest extends IncompleteFactorizationTestAbstract {


    @Override
    void testFactorization(Matrix A, Vector x) {
        Vector b = A.mult(x, x.copy());


        ILU ilu = new ILU(new CompRowMatrix(A));
        ilu.setMatrix(A);
        ilu.apply(b, x);


        Vector r = A.multAdd(-1, x, b.copy());


        assertEquals(0, r.norm(Vector.Norm.TwoRobust), 1e-5);
    }

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  @Override
  public Vector getVector(String aTerm)
    throws SimilarityException
  {
    Vector vec1 = new SparseVector(getConceptCount());
    builder.buildVector(asList(aTerm), VectorAdapter.create(vec1));
    return vec1;
  }

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Related Classes of no.uib.cipr.matrix.Vector

cc.mallet.grmm.test.TestNormalFactor

no.uib.cipr.matrix.distributed.DistVector

no.uib.cipr.matrix.MatrixTestAbstract

no.uib.cipr.matrix.sparse.ICCTest

no.uib.cipr.matrix.sparse.ILUTest

no.uib.cipr.matrix.sparse.ILUTTest

no.uib.cipr.matrix.sparse.IncompleteFactorizationTestAbstract

no.uib.cipr.matrix.sparse.SparseVectorTest

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Examples of no.uib.cipr.matrix.Vector

Basic operations

Iterators

Basic linear algebra

Related Classes of no.uib.cipr.matrix.Vector