Package mikera.matrixx.impl

Examples of mikera.matrixx.impl.AStridedMatrix

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    Matrix m = (Matrix) Matrixx.newMatrix(4, 4);
    Vectorz.fillIndexes(m.asVector());

    // regression test
    {
      @SuppressWarnings("unused")
      AStridedMatrix tsm = m.subMatrix(1, 1, 1, 1);
    }

    AStridedMatrix sm = m.subMatrix(1, 2, 1, 2);
    assertEquals(2, sm.rowCount());
    assertEquals(2, sm.columnCount());
    assertTrue(sm.data == m.data);

    assertEquals(
        Matrixx.create(new double[][] { { 5.0, 6.0 }, { 9.0, 10.0 } }),
        sm);

    AStridedMatrix ssm = sm.subMatrix(1, 1, 1, 1);
    assertEquals(Matrixx.create(new double[][] { { 10.0 } }), ssm);

  }
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        qr.householder(w,A);

//        SimpleMatrix U = new SimpleMatrix(width,1, true, qr.getQR()[w]).extractMatrix(w,width,0,1);
        Matrix temp = Matrix.create(width,1);
        temp.setElements(qr.getQR()[w]);
        AStridedMatrix U = temp.subMatrix(w, width-w, 0, 1);
       
        U.set(0,0,1); // this is not explicity set and is assumed to be 1
        Matrix I = Matrix.createIdentity(width-w);
//        SimpleMatrix Q = I.minus(U.mult(U.transpose()).scale(qr.getGamma()));
        Matrix temp1 = Multiplications.multiply(U, U.getTranspose());
        temp1.scale(qr.getGamma());
        I.sub(temp1);
        Matrix Q = I;


        // check the expected properties of Q
        assertTrue(Q.epsilonEquals(Q.getTranspose(),1e-6));
        assertTrue(Q.epsilonEquals(Q.inverse(),1e-6));

//        SimpleMatrix result = Q.mult(A.extractMatrix(w,width,w,width));
        AStridedMatrix result = Multiplications.multiply(Q, A.subMatrix(w,width-w,w,width-w));

        for( int i = 1; i < width-w; i++ ) {
            assertEquals(0,result.get(i,0),1e-5);
        }
    }
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        // compute the results using standard matrix operations
        Matrix I = Matrix.createIdentity(width-w);

//        SimpleMatrix u_sub = U.extractMatrix(w,width,0,1);
        AStridedMatrix u_sub = U.subMatrix(w, width-w, 0, 1);
        u_sub.set(0,0,1);// assumed to be 1 in the algorithm
//        SimpleMatrix A_sub = A.extractMatrix(w,width,w,width);
        AStridedMatrix A_sub = A.subMatrix(w,width-w,w,width-w);
//        SimpleMatrix expected = I.minus(u_sub.mult(u_sub.transpose()).scale(gamma)).mult(A_sub);
        Matrix temp1 = Multiplications.multiply(u_sub, u_sub.getTranspose());
        temp1.scale(gamma);
        I.sub(temp1);
        Matrix expected = Multiplications.multiply(I, A_sub);
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        qr.householder(w,A);

//        SimpleMatrix U = new SimpleMatrix(width,1, true, qr.getU()).extractMatrix(w,width,0,1);
        Matrix temp = Matrix.create(width,1);
        temp.setElements(qr.getU());
        AStridedMatrix U = temp.subMatrix(w, width-w, 0, 1);

        Matrix I = Matrix.createIdentity(width-w);
//      SimpleMatrix Q = I.minus(U.mult(U.transpose()).scale(qr.getGamma()));
        Matrix temp1 = Multiplications.multiply(U, U.getTranspose());
        temp1.scale(qr.getGamma());
        I.sub(temp1);
        Matrix Q = I;


        // check the expected properties of Q
        assertTrue(Q.epsilonEquals(Q.getTranspose(),1e-6));
        assertTrue(Q.epsilonEquals(Q.inverse(),1e-6));

//        SimpleMatrix result = Q.mult(A.extractMatrix(w,width,w,width));
        AStridedMatrix result = Multiplications.multiply(Q, A.subMatrix(w,width-w,w,width-w));

        for( int i = 1; i < width-w; i++ ) {
            assertEquals(0,result.get(i,0),1e-5);
        }
    }
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        // compute the results using standard matrix operations
        Matrix I = Matrix.createIdentity(width-w);

//        SimpleMatrix u_sub = U.extractMatrix(w,width,0,1);
        AStridedMatrix u_sub = U.subMatrix(w, width-w, 0, 1);
//        SimpleMatrix A_sub = A.extractMatrix(w,width,w,width);
        AStridedMatrix A_sub = A.subMatrix(w,width-w,w,width-w);
//        SimpleMatrix expected = I.minus(u_sub.mult(u_sub.transpose()).scale(gamma)).mult(A_sub);
        Matrix temp1 = Multiplications.multiply(u_sub, u_sub.getTranspose());
        temp1.scale(gamma);
        I.sub(temp1);
        Matrix expected = Multiplications.multiply(I, A_sub);
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Related Classes of mikera.matrixx.impl.AStridedMatrix

  • mikera.matrixx.decompose.impl.qr.TestHouseholderColQR
  • mikera.matrixx.decompose.impl.qr.TestHouseholderQR
  • mikera.matrixx.TestMisc
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