1 #include <Eigen/Array>
2
main(int argc,char * argv[])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 }
63