Function stable_norm

dependence/eigen-3.4.0/test/stable_norm.cpp:17–196

}

template<typename MatrixType> void stable_norm(const MatrixType& m)
{
  /* this test covers the following files:
     StableNorm.h
  */
  using std::sqrt;
  using std::abs;
  typedef typename MatrixType::Scalar Scalar;
  typedef typename NumTraits<Scalar>::Real RealScalar;
  
  bool complex_real_product_ok = true;

  // Check the basic machine-dependent constants.
  {
    int ibeta, it, iemin, iemax;

    ibeta = std::numeric_limits<RealScalar>::radix;         // base for floating-point numbers
    it    = std::numeric_limits<RealScalar>::digits;        // number of base-beta digits in mantissa
    iemin = std::numeric_limits<RealScalar>::min_exponent;  // minimum exponent
    iemax = std::numeric_limits<RealScalar>::max_exponent;  // maximum exponent

    VERIFY( (!(iemin > 1 - 2*it || 1+it>iemax || (it==2 && ibeta<5) || (it<=4 && ibeta <= 3 ) || it<2))
           && "the stable norm algorithm cannot be guaranteed on this computer");
    
    Scalar inf = std::numeric_limits<RealScalar>::infinity();
    if(NumTraits<Scalar>::IsComplex && (numext::isnan)(inf*RealScalar(1)) )
    {
      complex_real_product_ok = false;
      static bool first = true;
      if(first)
        std::cerr << "WARNING: compiler mess up complex*real product, " << inf << " * " << 1.0 << " = " << inf*RealScalar(1) << std::endl;
      first = false;
    }
  }


  Index rows = m.rows();
  Index cols = m.cols();

  // get a non-zero random factor
  Scalar factor = internal::random<Scalar>();
  while(numext::abs2(factor)<RealScalar(1e-4))
    factor = internal::random<Scalar>();
  Scalar big = factor * ((std::numeric_limits<RealScalar>::max)() * RealScalar(1e-4));
  
  factor = internal::random<Scalar>();
  while(numext::abs2(factor)<RealScalar(1e-4))
    factor = internal::random<Scalar>();
  Scalar small = factor * ((std::numeric_limits<RealScalar>::min)() * RealScalar(1e4));

  Scalar one(1);

  MatrixType  vzero = MatrixType::Zero(rows, cols),
              vrand = MatrixType::Random(rows, cols),
              vbig(rows, cols),
              vsmall(rows,cols);

  vbig.fill(big);