```/* <![CDATA[ */
function get_sym_list(){return [["Function","xf",[["main",3]]]];} /* ]]> */1#include <Eigen/Array>
2
3int 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}
63```