ground/gcs/src/libs/eigen/doc/tutorial.cpp

   1 #include <Eigen/Array>
   2
   3 int main(int argc, char *argv[])
   4 {
   5   std::cout.precision(2);
   6
   7   // demo static functions
   8   Eigen::Matrix3f m3 = Eigen::Matrix3f::Random();
   9   Eigen::Matrix4f m4 = Eigen::Matrix4f::Identity();
  10
  11   std::cout << "*** Step 1 ***\nm3:\n" << m3 << "\nm4:\n" << m4 << std::endl;
  12
  13   // demo non-static set... functions
  14   m4.setZero();
  15   m3.diagonal().setOnes();
  16
  17   std::cout << "*** Step 2 ***\nm3:\n" << m3 << "\nm4:\n" << m4 << std::endl;
  18
  19   // demo fixed-size block() expression as lvalue and as rvalue
  20   m4.block<3,3>(0,1) = m3;
  21   m3.row(2) = m4.block<1,3>(2,0);
  22
  23   std::cout << "*** Step 3 ***\nm3:\n" << m3 << "\nm4:\n" << m4 << std::endl;
  24
  25   // demo dynamic-size block()
  26   {
  27     int rows = 3, cols = 3;
  28     m4.block(0,1,3,3).setIdentity();
  29     std::cout << "*** Step 4 ***\nm4:\n" << m4 << std::endl;
  30   }
  31
  32   // demo vector blocks
  33   m4.diagonal().block(1,2).setOnes();
  34   std::cout << "*** Step 5 ***\nm4.diagonal():\n" << m4.diagonal() << std::endl;
  35   std::cout << "m4.diagonal().start(3)\n" << m4.diagonal().start(3) << std::endl;
  36
  37   // demo coeff-wise operations
  38   m4 = m4.cwise()*m4;
  39   m3 = m3.cwise().cos();
  40   std::cout << "*** Step 6 ***\nm3:\n" << m3 << "\nm4:\n" << m4 << std::endl;
  41
  42   // sums of coefficients
  43   std::cout << "*** Step 7 ***\n m4.sum(): " << m4.sum() << std::endl;
  44   std::cout << "m4.col(2).sum(): " << m4.col(2).sum() << std::endl;
  45   std::cout << "m4.colwise().sum():\n" << m4.colwise().sum() << std::endl;
  46   std::cout << "m4.rowwise().sum():\n" << m4.rowwise().sum() << std::endl;
  47
  48   // demo intelligent auto-evaluation
  49   m4 = m4 * m4; // auto-evaluates so no aliasing problem (performance penalty is low)
  50   Eigen::Matrix4f other = (m4 * m4).lazy(); // forces lazy evaluation
  51   m4 = m4 + m4; // here Eigen goes for lazy evaluation, as with most expressions
  52   m4 = -m4 + m4 + 5 * m4; // same here, Eigen chooses lazy evaluation for all that.
  53   m4 = m4 * (m4 + m4); // here Eigen chooses to first evaluate m4 + m4 into a temporary.
  54                        // indeed, here it is an optimization to cache this intermediate result.
  55   m3 = m3 * m4.block<3,3>(1,1); // here Eigen chooses NOT to evaluate block() into a temporary
  56     // because accessing coefficients of that block expression is not more costly than accessing
  57     // coefficients of a plain matrix.
  58   m4 = m4 * m4.transpose(); // same here, lazy evaluation of the transpose.
  59   m4 = m4 * m4.transpose().eval(); // forces immediate evaluation of the transpose
  60
  61   std::cout << "*** Step 8 ***\nm3:\n" << m3 << "\nm4:\n" << m4 << std::endl;
  62 }