Package no.uib.cipr.matrix

Examples of no.uib.cipr.matrix.DenseMatrix.numRows()

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        for (int i = 0; i < Al.size() - 1; ++i)
            this.A[i] = Al.get(i);

        // Create a LU decomposition of the smallest Galerkin matrix
        DenseMatrix Ac = new DenseMatrix(Al.get(Al.size() - 1));
        lu = new DenseLU(Ac.numRows(), Ac.numColumns());
        lu.factor(Ac);

        // Allocate vectors at each level
        u = new DenseVector[m];
        f = new DenseVector[m];
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    File matrixFile = new File("TestMatrixFile");
    BufferedWriter out = new BufferedWriter(new FileWriter(matrixFile));
    MatrixVectorWriter writer = new MatrixVectorWriter(out);
    MatrixInfo mi = new MatrixInfo(false, MatrixInfo.MatrixField.Real, MatrixInfo.MatrixSymmetry.General);
    writer.printMatrixInfo(mi);
    writer.printMatrixSize(new MatrixSize(mat.numRows(), mat.numColumns(), mat.numColumns() * mat.numRows()), mi);
    writer.printArray(mat.getData());
    writer.close();
    Matrix newMat = new DenseMatrix(new MatrixVectorReader(new FileReader(matrixFile)));

    MatrixTestAbstract.assertEquals(mat, newMat);
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    File matrixFile = new File("TestMatrixFile");
    BufferedWriter out = new BufferedWriter(new FileWriter(matrixFile));
    MatrixVectorWriter writer = new MatrixVectorWriter(out);
    MatrixInfo mi = new MatrixInfo(false, MatrixInfo.MatrixField.Real, MatrixInfo.MatrixSymmetry.General);
    writer.printMatrixInfo(mi);
    writer.printMatrixSize(new MatrixSize(mat.numRows(), mat.numColumns(), mat.numColumns() * mat.numRows()), mi);
    writer.printArray(mat.getData());
    writer.close();
    Matrix newMat = new DenseMatrix(new MatrixVectorReader(new FileReader(matrixFile)));

    MatrixTestAbstract.assertEquals(mat, newMat);
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  }

  public void ignoredTimedMult() {
    Stopwatch watch = Stopwatch.createUnstarted();
    DenseMatrix dense = new DenseMatrix(1000, 1000);
    int[][] nz = Utilities.getRowPattern(dense.numRows(), dense.numColumns(), 100);
    Utilities.rowPopulate(dense, nz);
    log.info("created matrices");
    Matrix sparse = new LinkedSparseMatrix(dense.numRows(), dense.numColumns());
    sparse.set(dense);
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    Stopwatch watch = Stopwatch.createUnstarted();
    DenseMatrix dense = new DenseMatrix(1000, 1000);
    int[][] nz = Utilities.getRowPattern(dense.numRows(), dense.numColumns(), 100);
    Utilities.rowPopulate(dense, nz);
    log.info("created matrices");
    Matrix sparse = new LinkedSparseMatrix(dense.numRows(), dense.numColumns());
    sparse.set(dense);

    for (Matrix m : Lists.newArrayList(dense, sparse)) {
      log.info("starting " + m.getClass());
      Matrix t = new DenseMatrix(m);
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  }

  public void ignoredTimedTransMult() {
    Stopwatch watch = Stopwatch.createUnstarted();
    DenseMatrix dense = new DenseMatrix(1000, 1000);
    int[][] nz = Utilities.getRowPattern(dense.numRows(), dense.numColumns(), 100);
    Utilities.rowPopulate(dense, nz);
    log.info("created matrices");
    Matrix sparse = new LinkedSparseMatrix(dense.numRows(), dense.numColumns());
    sparse.set(dense);
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    Stopwatch watch = Stopwatch.createUnstarted();
    DenseMatrix dense = new DenseMatrix(1000, 1000);
    int[][] nz = Utilities.getRowPattern(dense.numRows(), dense.numColumns(), 100);
    Utilities.rowPopulate(dense, nz);
    log.info("created matrices");
    Matrix sparse = new LinkedSparseMatrix(dense.numRows(), dense.numColumns());
    sparse.set(dense);

    for (Matrix m : Lists.newArrayList(dense, sparse)) {
      log.info("starting " + m.getClass());
      Matrix t = new DenseMatrix(m);
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