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Correct unittest input error

release/4.3a0
jingwuOUO 2020-10-22 14:19:23 -04:00
parent 5f50e740b7
commit f86ad95582
2 changed files with 33 additions and 39 deletions
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37
gtsam/linear/tests/testAcceleratedPowerMethod.cpp
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@ -42,26 +42,24 @@ TEST(AcceleratedPowerMethod, acceleratedPowerIteration) {
// test power iteration, beta is set to 0 // test power iteration, beta is set to 0
Sparse A(6, 6); Sparse A(6, 6);
A.coeffRef(0, 0) = 6; A.coeffRef(0, 0) = 6;
A.coeffRef(0, 0) = 5; A.coeffRef(1, 1) = 5;
A.coeffRef(0, 0) = 4; A.coeffRef(2, 2) = 4;
A.coeffRef(0, 0) = 3; A.coeffRef(3, 3) = 3;
A.coeffRef(0, 0) = 2; A.coeffRef(4, 4) = 2;
A.coeffRef(0, 0) = 1; A.coeffRef(5, 5) = 1;
Vector initial = Vector6::Zero(); Vector initial = Vector6::Random();
const Vector6 x1 = (Vector(6) << 1.0, 0.0, 0.0, 0.0, 0.0, 0.0).finished(); const Vector6 x1 = (Vector(6) << 1.0, 0.0, 0.0, 0.0, 0.0, 0.0).finished();
const double ev1 = 1.0; const double ev1 = 6.0;
// test accelerated power iteration // test accelerated power iteration
AcceleratedPowerMethod<Sparse> apf(A, initial); AcceleratedPowerMethod<Sparse> apf(A, initial);
apf.compute(20, 1e-4); apf.compute(50, 1e-4);
EXPECT_LONGS_EQUAL(1, apf.eigenvectors().cols()); EXPECT_LONGS_EQUAL(6, apf.eigenvector().rows());
EXPECT_LONGS_EQUAL(6, apf.eigenvectors().rows());
Vector6 actual1 = apf.eigenvectors(); Vector6 actual1 = apf.eigenvector();
// actual1(0) = abs (actual1(0)); EXPECT(assert_equal(x1, actual1, 1e-4));
EXPECT(assert_equal(x1, actual1));
EXPECT_DOUBLES_EQUAL(ev1, apf.eigenvalues(), 1e-5); EXPECT_DOUBLES_EQUAL(ev1, apf.eigenvalue(), 1e-5);
} }
/* ************************************************************************* */ /* ************************************************************************* */
@ -76,10 +74,7 @@ TEST(AcceleratedPowerMethod, useFactorGraph) {
// Get eigenvalues and eigenvectors with Eigen // Get eigenvalues and eigenvectors with Eigen
auto L = fg.hessian(); auto L = fg.hessian();
cout << L.first << endl;
Eigen::EigenSolver<Matrix> solver(L.first); Eigen::EigenSolver<Matrix> solver(L.first);
cout << solver.eigenvalues() << endl;
cout << solver.eigenvectors() << endl;
// Check that we get zero eigenvalue and "constant" eigenvector // Check that we get zero eigenvalue and "constant" eigenvector
EXPECT_DOUBLES_EQUAL(0.0, solver.eigenvalues()[0].real(), 1e-9); EXPECT_DOUBLES_EQUAL(0.0, solver.eigenvalues()[0].real(), 1e-9);
@ -95,11 +90,11 @@ TEST(AcceleratedPowerMethod, useFactorGraph) {
const auto ev1 = solver.eigenvalues()(maxIdx).real(); const auto ev1 = solver.eigenvalues()(maxIdx).real();
auto ev2 = solver.eigenvectors().col(maxIdx).real(); auto ev2 = solver.eigenvectors().col(maxIdx).real();
Vector initial = Vector4::Zero(); Vector initial = Vector4::Random();
AcceleratedPowerMethod<Matrix> apf(L.first, initial); AcceleratedPowerMethod<Matrix> apf(L.first, initial);
apf.compute(20, 1e-4); apf.compute(50, 1e-4);
EXPECT_DOUBLES_EQUAL(ev1, apf.eigenvalues(), 1e-8); EXPECT_DOUBLES_EQUAL(ev1, apf.eigenvalue(), 1e-8);
EXPECT(assert_equal(ev2, apf.eigenvectors(), 3e-5)); EXPECT(assert_equal(-ev2, apf.eigenvector(), 3e-5));
} }
/* ************************************************************************* */ /* ************************************************************************* */

35
gtsam/linear/tests/testPowerMethod.cpp
View File

@ -42,23 +42,22 @@ TEST(PowerMethod, powerIteration) {
// test power iteration, beta is set to 0 // test power iteration, beta is set to 0
Sparse A(6, 6); Sparse A(6, 6);
A.coeffRef(0, 0) = 6; A.coeffRef(0, 0) = 6;
A.coeffRef(0, 0) = 5; A.coeffRef(1, 1) = 5;
A.coeffRef(0, 0) = 4; A.coeffRef(2, 2) = 4;
A.coeffRef(0, 0) = 3; A.coeffRef(3, 3) = 3;
A.coeffRef(0, 0) = 2; A.coeffRef(4, 4) = 2;
A.coeffRef(0, 0) = 1; A.coeffRef(5, 5) = 1;
Vector initial = Vector6::Zero(); Vector initial = Vector6::Random();
PowerMethod<Sparse> pf(A, initial); PowerMethod<Sparse> pf(A, initial);
pf.compute(20, 1e-4); pf.compute(50, 1e-4);
EXPECT_LONGS_EQUAL(1, pf.eigenvectors().cols()); EXPECT_LONGS_EQUAL(6, pf.eigenvector().rows());
EXPECT_LONGS_EQUAL(6, pf.eigenvectors().rows());
const Vector6 x1 = (Vector(6) << 1.0, 0.0, 0.0, 0.0, 0.0, 0.0).finished(); const Vector6 x1 = (Vector(6) << 1.0, 0.0, 0.0, 0.0, 0.0, 0.0).finished();
Vector6 actual0 = pf.eigenvectors(); Vector6 actual0 = pf.eigenvector();
EXPECT(assert_equal(x1, actual0)); EXPECT(assert_equal(x1, actual0, 1e-4));
const double ev1 = 1.0; const double ev1 = 6.0;
EXPECT_DOUBLES_EQUAL(ev1, pf.eigenvalues(), 1e-5); EXPECT_DOUBLES_EQUAL(ev1, pf.eigenvalue(), 1e-5);
} }
/* ************************************************************************* */ /* ************************************************************************* */
@ -89,12 +88,12 @@ TEST(PowerMethod, useFactorGraph) {
const auto ev1 = solver.eigenvalues()(maxIdx).real(); const auto ev1 = solver.eigenvalues()(maxIdx).real();
auto ev2 = solver.eigenvectors().col(maxIdx).real(); auto ev2 = solver.eigenvectors().col(maxIdx).real();
Vector initial = Vector4::Zero(); Vector initial = Vector4::Random();
PowerMethod<Matrix> pf(L.first, initial); PowerMethod<Matrix> pf(L.first, initial);
pf.compute(20, 1e-4); pf.compute(50, 1e-4);
EXPECT_DOUBLES_EQUAL(ev1, pf.eigenvalues(), 1e-8); EXPECT_DOUBLES_EQUAL(ev1, pf.eigenvalue(), 1e-8);
// auto actual2 = pf.eigenvectors(); auto actual2 = pf.eigenvector();
// EXPECT(assert_equal(ev2, actual2, 3e-5)); EXPECT(assert_equal(-ev2, actual2, 3e-5));
} }
/* ************************************************************************* */ /* ************************************************************************* */