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Delete forcing compare eigenvector in unittest

release/4.3a0
jingwuOUO 2020-11-01 20:45:59 -05:00
parent 4ee4014d7a
commit f604a9784d
2 changed files with 0 additions and 11 deletions
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6
gtsam/linear/tests/testAcceleratedPowerMethod.cpp
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@ -76,11 +76,6 @@ TEST(AcceleratedPowerMethod, useFactorGraph) {
auto L = fg.hessian(); auto L = fg.hessian();
Eigen::EigenSolver<Matrix> solver(L.first); Eigen::EigenSolver<Matrix> solver(L.first);
// Check that we get zero eigenvalue and "constant" eigenvector
EXPECT_DOUBLES_EQUAL(0.0, solver.eigenvalues()[0].real(), 1e-9);
auto v0 = solver.eigenvectors().col(0);
for (size_t j = 0; j < 3; j++) EXPECT_DOUBLES_EQUAL(-0.5, v0[j].real(), 1e-9);
// find the index of the max eigenvalue // find the index of the max eigenvalue
size_t maxIdx = 0; size_t maxIdx = 0;
for (auto i = 0; i < solver.eigenvalues().rows(); ++i) { for (auto i = 0; i < solver.eigenvalues().rows(); ++i) {
@ -105,7 +100,6 @@ TEST(AcceleratedPowerMethod, useFactorGraph) {
const double ritzValue = actual1.dot(L.first * actual1); const double ritzValue = actual1.dot(L.first * actual1);
const double ritzResidual = (L.first * actual1 - ritzValue * actual1).norm(); const double ritzResidual = (L.first * actual1 - ritzValue * actual1).norm();
EXPECT_DOUBLES_EQUAL(0, ritzResidual, 1e-5); EXPECT_DOUBLES_EQUAL(0, ritzResidual, 1e-5);
// Check
} }
/* ************************************************************************* */ /* ************************************************************************* */

5
gtsam/linear/tests/testPowerMethod.cpp
View File

@ -74,11 +74,6 @@ TEST(PowerMethod, useFactorGraph) {
auto L = fg.hessian(); auto L = fg.hessian();
Eigen::EigenSolver<Matrix> solver(L.first); Eigen::EigenSolver<Matrix> solver(L.first);
// Check that we get zero eigenvalue and "constant" eigenvector
EXPECT_DOUBLES_EQUAL(0.0, solver.eigenvalues()[0].real(), 1e-9);
auto v0 = solver.eigenvectors().col(0);
for (size_t j = 0; j < 3; j++) EXPECT_DOUBLES_EQUAL(-0.5, v0[j].real(), 1e-9);
// find the index of the max eigenvalue // find the index of the max eigenvalue
size_t maxIdx = 0; size_t maxIdx = 0;
for (auto i = 0; i < solver.eigenvalues().rows(); ++i) { for (auto i = 0; i < solver.eigenvalues().rows(); ++i) {