1c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath#include <Eigen/Array> 2c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 3c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamathint main(int argc, char *argv[]) 4c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath{ 5c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath std::cout.precision(2); 6c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 7c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath // demo static functions 8c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath Eigen::Matrix3f m3 = Eigen::Matrix3f::Random(); 9c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath Eigen::Matrix4f m4 = Eigen::Matrix4f::Identity(); 10c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 11c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath std::cout << "*** Step 1 ***\nm3:\n" << m3 << "\nm4:\n" << m4 << std::endl; 12c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 13c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath // demo non-static set... functions 14c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath m4.setZero(); 15c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath m3.diagonal().setOnes(); 16c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 17c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath std::cout << "*** Step 2 ***\nm3:\n" << m3 << "\nm4:\n" << m4 << std::endl; 18c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 19c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath // demo fixed-size block() expression as lvalue and as rvalue 20c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath m4.block<3,3>(0,1) = m3; 21c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath m3.row(2) = m4.block<1,3>(2,0); 22c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 23c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath std::cout << "*** Step 3 ***\nm3:\n" << m3 << "\nm4:\n" << m4 << std::endl; 24c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 25c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath // demo dynamic-size block() 26c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath { 27c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath int rows = 3, cols = 3; 28c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath m4.block(0,1,3,3).setIdentity(); 29c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath std::cout << "*** Step 4 ***\nm4:\n" << m4 << std::endl; 30c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath } 31c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 32c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath // demo vector blocks 33c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath m4.diagonal().block(1,2).setOnes(); 34c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath std::cout << "*** Step 5 ***\nm4.diagonal():\n" << m4.diagonal() << std::endl; 35c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath std::cout << "m4.diagonal().start(3)\n" << m4.diagonal().start(3) << std::endl; 36c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 37c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath // demo coeff-wise operations 38c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath m4 = m4.cwise()*m4; 39c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath m3 = m3.cwise().cos(); 40c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath std::cout << "*** Step 6 ***\nm3:\n" << m3 << "\nm4:\n" << m4 << std::endl; 41c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 42c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath // sums of coefficients 43c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath std::cout << "*** Step 7 ***\n m4.sum(): " << m4.sum() << std::endl; 44c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath std::cout << "m4.col(2).sum(): " << m4.col(2).sum() << std::endl; 45c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath std::cout << "m4.colwise().sum():\n" << m4.colwise().sum() << std::endl; 46c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath std::cout << "m4.rowwise().sum():\n" << m4.rowwise().sum() << std::endl; 47c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 48c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath // demo intelligent auto-evaluation 49c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath m4 = m4 * m4; // auto-evaluates so no aliasing problem (performance penalty is low) 50c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath Eigen::Matrix4f other = (m4 * m4).lazy(); // forces lazy evaluation 51c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath m4 = m4 + m4; // here Eigen goes for lazy evaluation, as with most expressions 52c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath m4 = -m4 + m4 + 5 * m4; // same here, Eigen chooses lazy evaluation for all that. 53c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath m4 = m4 * (m4 + m4); // here Eigen chooses to first evaluate m4 + m4 into a temporary. 54c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath // indeed, here it is an optimization to cache this intermediate result. 55c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath m3 = m3 * m4.block<3,3>(1,1); // here Eigen chooses NOT to evaluate block() into a temporary 56c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath // because accessing coefficients of that block expression is not more costly than accessing 57c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath // coefficients of a plain matrix. 58c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath m4 = m4 * m4.transpose(); // same here, lazy evaluation of the transpose. 59c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath m4 = m4 * m4.transpose().eval(); // forces immediate evaluation of the transpose 60c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath 61c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath std::cout << "*** Step 8 ***\nm3:\n" << m3 << "\nm4:\n" << m4 << std::endl; 62c981c48f5bc9aefeffc0bcb0cc3934c2fae179ddNarayan Kamath} 63