How to use

times

method

in

gov.sandia.cognition.math.matrix.custom.DiagonalMatrix

@Override
public final Vector preTimes(
  final DenseVector vector)
{
  // Only true for diagonal (and symmetric) matrices: pre-mult vector is the same as post-mult
  // vector
  return times(vector);
}

@Override
Vector precondition(Vector v)
{
  return Minv.times(v);
}

@Override
public final Vector preTimes(
  final DenseVector vector)
{
  // Only true for diagonal (and symmetric) matrices: pre-mult vector is the same as post-mult
  // vector
  return times(vector);
}

@Override
public final Vector preTimes(
  final DenseVector vector)
{
  // Only true for diagonal (and symmetric) matrices: pre-mult vector is the same as post-mult
  // vector
  return times(vector);
}

@Override
Vector precondition(Vector v)
{
  return Minv.times(v);
}

@Override
Vector precondition(Vector v)
{
  return Minv.times(v);
}

/**
 * Overrides the default implementation so that L_tilde can be raised to a
 * power and the diagonal weights can be added implicitly (which is much
 * faster and memory efficient than the explicit representation).
 *
 * @param input The vector to multiply by the implicit represetation of the
 * matrix
 * @return The result of the function.
 */
@Override
public Vector evaluate(Vector input)
{
  Vector v = input;
  for (int i = 0; i < power; ++i)
  {
    v = m.times(v);
  }
  Vector plusV = additional.times(input);
  return v.plus(plusV);
}

/**
 * Overrides the default implementation so that L_tilde can be raised to a
 * power and the diagonal weights can be added implicitly (which is much
 * faster and memory efficient than the explicit representation).
 *
 * @param input The vector to multiply by the implicit represetation of the
 * matrix
 * @return The result of the function.
 */
@Override
public Vector evaluate(Vector input)
{
  Vector v = input;
  for (int i = 0; i < power; ++i)
  {
    v = m.times(v);
  }
  Vector plusV = additional.times(input);
  return v.plus(plusV);
}

/**
 * Overrides the default implementation so that L_tilde can be raised to a
 * power and the diagonal weights can be added implicitly (which is much
 * faster and memory efficient than the explicit representation).
 *
 * @param input The vector to multiply by the implicit represetation of the
 * matrix
 * @return The result of the function.
 */
@Override
public Vector evaluate(Vector input)
{
  Vector v = input;
  for (int i = 0; i < power; ++i)
  {
    v = m.times(v);
  }
  Vector plusV = additional.times(input);
  return v.plus(plusV);
}

Matrix tmp = diag.times(multipartiteAdjacency);
Matrix DAD = tmp.times(diag);
Matrix minusDAD = DAD.scale(-1);

Matrix tmp = diag.times(multipartiteAdjacency);
Matrix DAD = tmp.times(diag);
Matrix minusDAD = DAD.scale(-1);

Matrix tmp = diag.times(multipartiteAdjacency);
Matrix DAD = tmp.times(diag);
Matrix minusDAD = DAD.scale(-1);