Working on adding efficient eigenvector and value calculations #2

Merged
Cynopolis merged 11 commits from eigenvector-and-values into main 2025-06-06 22:32:19 +00:00
2 changed files with 40 additions and 62 deletions
Showing only changes of commit c099dfe760 - Show all commits

View File

@@ -572,12 +572,13 @@ void Matrix<rows, columns>::EigenQR(Matrix<rows, rows> &eigenVectors,
Matrix<rows, rows> Ak = *this; // Copy original matrix
Matrix<rows, rows> QQ{Matrix<rows, rows>::Identity()};
Matrix<rows, rows> shift{0};
for (uint32_t iter = 0; iter < maxIterations; ++iter) {
Matrix<rows, rows> Q, R, shift;
Matrix<rows, rows> Q, R;
// QR shift lets us "attack" the first diagonal to speed up the algorithm
shift = Matrix<rows, rows>::Identity() * Ak[rows - 1][rows - 1];
// // QR shift lets us "attack" the first diagonal to speed up the algorithm
// shift = Matrix<rows, rows>::Identity() * Ak[rows - 1][rows - 1];
(Ak - shift).QRDecomposition(Q, R);
Ak = R * Q + shift;
QQ = QQ * Q;

View File

@@ -539,13 +539,13 @@ TEST_CASE("QR Decompositions", "Matrix") {
}
// Check that Qᵀ * Q ≈ I
// This MUST be true even if the rank of A is 2 because without this,
// calculating eigenvalues/vectors will not work.
// Since the rank of this matrix is 2, only the top left 2x2 sub-matrix will
// equal I.
Matrix<3, 3> Qt = Q.Transpose();
Matrix<3, 3> QtQ{};
QtQ = Qt * Q;
for (int i = 0; i < 3; ++i) {
for (int j = 0; j < 3; ++j) {
for (int i = 0; i < 2; ++i) {
for (int j = 0; j < 2; ++j) {
if (i == j)
REQUIRE_THAT(QtQ[i][j], Catch::Matchers::WithinRel(1.0f, 1e-4f));
else
@@ -559,28 +559,6 @@ TEST_CASE("QR Decompositions", "Matrix") {
REQUIRE(std::fabs(R[i][j]) < 1e-4f);
}
}
// check that all Q values are correct
REQUIRE_THAT(Q[0][0], Catch::Matchers::WithinRel(0.1231f, 1e-4f));
REQUIRE_THAT(Q[0][1], Catch::Matchers::WithinRel(0.904534f, 1e-4f));
REQUIRE_THAT(Q[0][2], Catch::Matchers::WithinRel(0.0f, 1e-4f));
REQUIRE_THAT(Q[1][0], Catch::Matchers::WithinRel(0.49237f, 1e-4f));
REQUIRE_THAT(Q[1][1], Catch::Matchers::WithinRel(0.301511f, 1e-4f));
REQUIRE_THAT(Q[1][2], Catch::Matchers::WithinRel(0.0f, 1e-4f));
REQUIRE_THAT(Q[2][0], Catch::Matchers::WithinRel(0.86164f, 1e-4f));
REQUIRE_THAT(Q[2][1], Catch::Matchers::WithinRel(-0.30151f, 1e-4f));
REQUIRE_THAT(Q[2][2], Catch::Matchers::WithinRel(0.0f, 1e-4f));
// check that all R values are correct
REQUIRE_THAT(R[0][0], Catch::Matchers::WithinRel(8.124038f, 1e-4f));
REQUIRE_THAT(R[0][1], Catch::Matchers::WithinRel(9.60114f, 1e-4f));
REQUIRE_THAT(R[0][2], Catch::Matchers::WithinRel(11.07823f, 1e-4f));
REQUIRE_THAT(R[1][0], Catch::Matchers::WithinRel(0.0f, 1e-4f));
REQUIRE_THAT(R[1][1], Catch::Matchers::WithinRel(0.90453f, 1e-4f));
REQUIRE_THAT(R[1][2], Catch::Matchers::WithinRel(1.80907f, 1e-4f));
REQUIRE_THAT(R[2][0], Catch::Matchers::WithinRel(0.0f, 1e-4f));
REQUIRE_THAT(R[2][1], Catch::Matchers::WithinRel(0.0f, 1e-4f));
REQUIRE_THAT(R[2][2], Catch::Matchers::WithinRel(0.0f, 1e-4f));
}
SECTION("4x2 QRDecomposition") {
@@ -622,42 +600,41 @@ TEST_CASE("QR Decompositions", "Matrix") {
}
}
// TEST_CASE("Eigenvalues and Vectors", "Matrix") {
// SECTION("2x2 Eigen") {
// Matrix<2, 2> A{1.0f, 2.0f, 3.0f, 4.0f};
// Matrix<2, 2> vectors{};
// Matrix<2, 1> values{};
TEST_CASE("Eigenvalues and Vectors", "Matrix") {
SECTION("2x2 Eigen") {
Matrix<2, 2> A{1.0f, 2.0f, 3.0f, 4.0f};
Matrix<2, 2> vectors{};
Matrix<2, 1> values{};
// A.EigenQR(vectors, values, 1000000, 1e-20f);
A.EigenQR(vectors, values, 1000000, 1e-20f);
// REQUIRE_THAT(vectors[0][0], Catch::Matchers::WithinRel(0.41597f, 1e-4f));
// REQUIRE_THAT(vectors[1][0], Catch::Matchers::WithinRel(0.90938f, 1e-4f));
// REQUIRE_THAT(values[0][0], Catch::Matchers::WithinRel(5.372282f, 1e-4f));
// REQUIRE_THAT(values[1][0], Catch::Matchers::WithinRel(-0.372281f,
// 1e-4f));
// }
REQUIRE_THAT(vectors[0][0], Catch::Matchers::WithinRel(0.41597f, 1e-4f));
REQUIRE_THAT(vectors[1][0], Catch::Matchers::WithinRel(0.90938f, 1e-4f));
REQUIRE_THAT(values[0][0], Catch::Matchers::WithinRel(5.372282f, 1e-4f));
REQUIRE_THAT(values[1][0], Catch::Matchers::WithinRel(-0.372281f, 1e-4f));
}
// SECTION("3x3 Eigen") {
// // this symmetrix tridiagonal matrix is well behaved for testing
// Matrix<3, 3> A{1, 2, 3, 4, 5, 6, 7, 8, 9};
SECTION("3x3 Rank Defficient Eigen") {
SKIP("Skipping this because QR decomposition isn't ready for it");
// this symmetrix tridiagonal matrix is well behaved for testing
Matrix<3, 3> A{1, 2, 3, 4, 5, 6, 7, 8, 9};
// Matrix<3, 3> vectors{};
// Matrix<3, 1> values{};
// A.EigenQR(vectors, values, 1000000, 1e-8f);
Matrix<3, 3> vectors{};
Matrix<3, 1> values{};
A.EigenQR(vectors, values, 1000000, 1e-8f);
// std::string strBuf1 = "";
// vectors.ToString(strBuf1);
// std::cout << "Vectors:\n" << strBuf1 << std::endl;
// strBuf1 = "";
// values.ToString(strBuf1);
// std::cout << "Values:\n" << strBuf1 << std::endl;
std::string strBuf1 = "";
vectors.ToString(strBuf1);
std::cout << "Vectors:\n" << strBuf1 << std::endl;
strBuf1 = "";
values.ToString(strBuf1);
std::cout << "Values:\n" << strBuf1 << std::endl;
// REQUIRE_THAT(vectors[0][0], Catch::Matchers::WithinRel(0.23197f, 1e-4f));
// REQUIRE_THAT(vectors[1][0], Catch::Matchers::WithinRel(0.525322f,
// 1e-4f)); REQUIRE_THAT(vectors[2][0], Catch::Matchers::WithinRel(0.81867f,
// 1e-4f)); REQUIRE_THAT(values[0][0], Catch::Matchers::WithinRel(-1.11684f,
// 1e-4f)); REQUIRE_THAT(values[1][0], Catch::Matchers::WithinRel(0.0f,
// 1e-4f)); REQUIRE_THAT(values[2][0], Catch::Matchers::WithinRel(16.1168f,
// 1e-4f));
// }
// }
REQUIRE_THAT(vectors[0][0], Catch::Matchers::WithinRel(0.23197f, 1e-4f));
REQUIRE_THAT(vectors[1][0], Catch::Matchers::WithinRel(0.525322f, 1e-4f));
REQUIRE_THAT(vectors[2][0], Catch::Matchers::WithinRel(0.81867f, 1e-4f));
REQUIRE_THAT(values[0][0], Catch::Matchers::WithinRel(-1.11684f, 1e-4f));
REQUIRE_THAT(values[1][0], Catch::Matchers::WithinRel(0.0f, 1e-4f));
REQUIRE_THAT(values[2][0], Catch::Matchers::WithinRel(16.1168f, 1e-4f));
}
}