Delete forcing compare eigenvector in unittest
parent
4ee4014d7a
commit
f604a9784d
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@ -76,11 +76,6 @@ TEST(AcceleratedPowerMethod, useFactorGraph) {
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auto L = fg.hessian();
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Eigen::EigenSolver<Matrix> solver(L.first);
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// Check that we get zero eigenvalue and "constant" eigenvector
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EXPECT_DOUBLES_EQUAL(0.0, solver.eigenvalues()[0].real(), 1e-9);
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auto v0 = solver.eigenvectors().col(0);
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for (size_t j = 0; j < 3; j++) EXPECT_DOUBLES_EQUAL(-0.5, v0[j].real(), 1e-9);
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// find the index of the max eigenvalue
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size_t maxIdx = 0;
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for (auto i = 0; i < solver.eigenvalues().rows(); ++i) {
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@ -105,7 +100,6 @@ TEST(AcceleratedPowerMethod, useFactorGraph) {
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const double ritzValue = actual1.dot(L.first * actual1);
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const double ritzResidual = (L.first * actual1 - ritzValue * actual1).norm();
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EXPECT_DOUBLES_EQUAL(0, ritzResidual, 1e-5);
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// Check
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}
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/* ************************************************************************* */
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@ -74,11 +74,6 @@ TEST(PowerMethod, useFactorGraph) {
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auto L = fg.hessian();
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Eigen::EigenSolver<Matrix> solver(L.first);
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// Check that we get zero eigenvalue and "constant" eigenvector
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EXPECT_DOUBLES_EQUAL(0.0, solver.eigenvalues()[0].real(), 1e-9);
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auto v0 = solver.eigenvectors().col(0);
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for (size_t j = 0; j < 3; j++) EXPECT_DOUBLES_EQUAL(-0.5, v0[j].real(), 1e-9);
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// find the index of the max eigenvalue
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size_t maxIdx = 0;
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for (auto i = 0; i < solver.eigenvalues().rows(); ++i) {
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