List of decompose() Examples

Examples of decompose()

cern.colt.matrix.linalg.LUDecompositionQuick.decompose()
Decomposes matrix A into L and U (in-place). Upon return A is overridden with the result LU, such that L*U = A. Uses a "left-looking", dot-product, Crout/Doolittle algorithm. @param A any matrix.
com.facebook.presto.jdbc.internal.netty.buffer.CompositeChannelBuffer.decompose()
Same with {@link #slice(int,int)} except that this method returns a list.
com.geophile.z.Space.decompose()
io.netty.buffer.CompositeByteBuf.decompose()
Same with {@link #slice(int,int)} except that this method returns a list.
mikera.matrixx.decompose.impl.eigen.SymmetricQRAlgorithmDecomposition.decompose()
Decomposes the matrix using the QR algorithm. Care was taken to minimize unnecessary memory copying and cache skipping. @param orig The matrix which is being decomposed. Not modified. @return true if it decomposed the matrix or false if an error was detected. This will not catch all errors.
mikera.matrixx.decompose.impl.hessenberg.TridiagonalDecompositionHouseholder.decompose()
Decomposes the provided symmetric matrix. @param A Symmetric matrix that is going to be decomposed. Not modified.
mikera.matrixx.decompose.impl.qr.HouseholderQR.decompose()

In order to decompose the matrix 'A' it must have full rank. 'A' is a 'm' by 'n' matrix. It requires about 2n*m²-2m²/3 flops.

The matrix provided here can be of different dimension than the one specified in the constructor. It just has to be smaller than or equal to it.
org.apache.cassandra.db.marshal.AbstractType.decompose()
org.apache.cassandra.db.marshal.CompositeType.decompose()
org.apache.cassandra.db.marshal.ListType.decompose()
Layout is: {@code ... }where: n is the number of elements s_i is the number of bytes composing the ith element b_i is the s_i bytes composing the ith element
org.apache.cassandra.db.marshal.MapType.decompose()
Layout is: {@code ... }where: n is the number of elements sk_i is the number of bytes composing the ith key k_i k_i is the sk_i bytes composing the ith key sv_i is the number of bytes composing the ith value v_i v_i is the sv_i bytes composing the ith value
org.apache.cassandra.db.marshal.SetType.decompose()
Layout is: {@code ... }where: n is the number of elements s_i is the number of bytes composing the ith element b_i is the s_i bytes composing the ith element
org.apache.cassandra.db.marshal.TimeUUIDType.decompose()
org.apache.cassandra.db.marshal.UTF8Type.decompose()
org.ejml.alg.block.decomposition.qr.BlockMatrix64HouseholderQR.decompose()
@inheritDoc
org.ejml.alg.dense.decomposition.bidiagonal.BidiagonalDecompositionRow.decompose()
Computes the decomposition of the provided matrix. If no errors are detected then true is returned, false otherwise. @param A The matrix that is being decomposed. Not modified. @return If it detects any errors or not.
org.ejml.alg.dense.decomposition.chol.CholeskyDecompositionInner.decompose()
org.ejml.alg.dense.decomposition.hessenberg.TridiagonalDecompositionHouseholder.decompose()
Decomposes the provided symmetric matrix. @param A Symmetric matrix that is going to be decomposed. Not modified.
org.ejml.alg.dense.decomposition.hessenberg.TridiagonalDecompositionHouseholderOrig.decompose()
Decomposes the provided symmetric matrix. @param A Symmetric matrix that is going to be decomposed. Not modified.
org.ejml.alg.dense.decomposition.lu.LUDecompositionAlt.decompose()
This is a modified version of what was found in the JAMA package. The order that it performs its permutations in is the primary difference from NR @param a The matrix that is to be decomposed. Not modified. @return true If the matrix can be decomposed and false if it can not.
org.ejml.alg.dense.decomposition.qr.QRDecompositionHouseholderTran.decompose()

To decompose the matrix 'A' it must have full rank. 'A' is a 'm' by 'n' matrix. It requires about 2n*m²-2m²/3 flops.

The matrix provided here can be of different dimension than the one specified in the constructor. It just has to be smaller than or equal to it.
org.ejml.factory.EigenDecomposition.decompose()
org.ejml.factory.LUDecomposition.decompose()
org.ejml.factory.QRDecomposition.decompose()
org.ejml.factory.SingularValueDecomposition.decompose()
org.jboss.netty.buffer.CompositeChannelBuffer.decompose()
Same with {@link #slice(int,int)} except that this method returns a list.
org.libreplan.business.workingday.EffortDuration.decompose()
ru.ifmo.diplom.kirilchuk.jawelet.core.dwt.transforms.DWTransform1D.decompose()
Performs dwt decomposition to maximal level. It means that data length would be extended(if need) to closest 2^N and decomposition result will have approximation vector with size=1 and list with N detail vectors. @param data input vector to decompose. @return result of decomposition. @deprecated
ru.ifmo.diplom.kirilchuk.jawelet.core.dwt.transforms.haar.impl.HaarWaveletTransform.decompose()
ru.ifmo.diplom.kirilchuk.jawelet.core.dwt.transforms.legall.impl.LeGallWaveletTransform.decompose()

Examples of cern.colt.matrix.linalg.LUDecompositionQuick.decompose()

      Assert.assertEquals(i+1, s.j_x[i],comparisonAccuracy);
    verifyAxb(s);
    
    // Test 2
    LUDecompositionQuick solver = new LUDecompositionQuick();
    solver.decompose(testMatrix);solver.setLU(testMatrix);
    solver.solve(x);
    for(int i=0;i<testMatrix.rows();++i)
      Assert.assertEquals(i+1, x.getQuick(i),comparisonAccuracy);
    verifyAxb(s);

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Examples of cern.colt.matrix.linalg.LUDecompositionQuick.decompose()

    }, IllegalArgumentException.class,"singular");    


    checkForCorrectException(new whatToRun() {
      public void run() throws NumberFormatException {
        LUDecompositionQuick coltSolver = new LUDecompositionQuick();
        coltSolver.decompose(matrix);coltSolver.setLU(matrix);
        coltSolver.solve(x);
      }
    }, IllegalArgumentException.class,"singular");    


    checkForCorrectException(new whatToRun() {

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Examples of cern.colt.matrix.linalg.LUDecompositionQuick.decompose()

    b.assign(randomGenerator);


    final LSolver solver = new LSolver(matrix,b);
    long tmStarted = new Date().getTime();
    LUDecompositionQuick coltSolver = new LUDecompositionQuick();
    coltSolver.decompose(matrix);coltSolver.setLU(matrix);
    
    DoubleMatrix1D vector = b.copy();
    coltSolver.solve(vector);
    long tmFinished = new Date().getTime();
    System.out.println(" time taken: "+((double)tmFinished-tmStarted)/1000);

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Examples of cern.colt.matrix.linalg.LUDecompositionQuick.decompose()

    
    if (!singular)
      TestSolver.verifyAxb(solver);
    
    LUDecompositionQuick coltSolver = new LUDecompositionQuick();
    coltSolver.decompose(matrix);coltSolver.setLU(matrix);
    DoubleMatrix1D vector = DoubleFactory1D.dense.make(matrix.rows(), 0);
    
    try
    {
      coltSolver.solve(vector);

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Examples of cern.colt.matrix.linalg.LUDecompositionQuick.decompose()

   */  
  public void solveUsingColt()
  {
    LUDecompositionQuick solver = new LUDecompositionQuick();
    DoubleMatrix2D matrix = toDoubleMatrix2D();
    solver.decompose(matrix);solver.setLU(matrix);
    DoubleMatrix1D result = toDoubleMatrix1D();
    solver.solve(result);result.toArray(j_x);    
  }
  
  /** The following two variables are not currently in use.

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Examples of com.facebook.presto.jdbc.internal.netty.buffer.CompositeChannelBuffer.decompose()

            // Make sure the resulting cumulation buffer has no more than the configured components.
            CompositeChannelBuffer composite = (CompositeChannelBuffer) cumulation;
            if (composite.numComponents() >= maxCumulationBufferComponents) {
                currentMessage.setContent(ChannelBuffers.wrappedBuffer(composite.copy(), input));
            } else {
                List<ChannelBuffer> decomposed = composite.decompose(0, composite.readableBytes());
                ChannelBuffer[] buffers = decomposed.toArray(new ChannelBuffer[decomposed.size() + 1]);
                buffers[buffers.length - 1] = input;


                currentMessage.setContent(ChannelBuffers.wrappedBuffer(buffers));
            }

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Examples of com.geophile.z.Space.decompose()

                    SpatialObject box = BoxLatLon.newBox(lat.subtract(r).doubleValue(),
                                                         lat.add(r).doubleValue(),
                                                         lon.subtract(r).doubleValue(),
                                                         lon.add(r).doubleValue());
                    long[] zValues = new long[box.maxZ()];
                    space.decompose(box, zValues);
                    for (int i = 0; i < box.maxZ(); i++) {
                        long z = zValues[i];
                        if (z != -1L) {
                            ExpressionNode lo = new ConstantExpression(Space.zLo(z), InternalIndexTypes.LONG.instance(true));
                            ExpressionNode hi =  new ConstantExpression(Space.zHi(z), InternalIndexTypes.LONG.instance(true));

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Examples of io.netty.buffer.CompositeByteBuf.decompose()

    }


    private static void checkContentBuffer(FullHttpRequest aggregatedMessage) {
        CompositeByteBuf buffer = (CompositeByteBuf) aggregatedMessage.content();
        assertEquals(2, buffer.numComponents());
        List<ByteBuf> buffers = buffer.decompose(0, buffer.capacity());
        assertEquals(2, buffers.size());
        for (ByteBuf buf: buffers) {
            // This should be false as we decompose the buffer before to not have deep hierarchy
            assertFalse(buf instanceof CompositeByteBuf);
        }

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Examples of mikera.matrixx.decompose.impl.eigen.SymmetricQRAlgorithmDecomposition.decompose()

     * @param computeVectors Should it compute the eigenvectors or just eigenvalues.
     * @return an IEigenResult object that represents the solution to the decomposition.
     */
    public static IEigenResult decomposeSymmetric(AMatrix A, boolean computeVectors) {
        SymmetricQRAlgorithmDecomposition alg = new SymmetricQRAlgorithmDecomposition(computeVectors);
        return alg.decompose(A);
    }
    /**
     * <p>
     * Computes the eigenvalues and eigenvectors of a real symmetric matrix. Returns an object that represents
     * the solution of the decomposition.

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Examples of mikera.matrixx.decompose.impl.hessenberg.TridiagonalDecompositionHouseholder.decompose()

                {-0.397037, 0.623341, 3.571302, -0.239631, -0.264573},
                {0.367426, 0.624798, -0.239631, 3.625034, -0.162896},
                {-0.208338, 0.401906, -0.264573, -0.162896, 3.835783}});


        TridiagonalDecompositionHouseholder tridiag = new TridiagonalDecompositionHouseholder();
        tridiag.decompose(A);


        double diag[] = new double[5];
        double off[] = new double[4];


        tridiag.getDiagonal(diag,off);

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