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63c7a023ee Improved on old unit tests
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Merge-Checker / build_and_test (pull_request) Failing after 24s
2025-06-05 15:02:42 -04:00
5 changed files with 133 additions and 101 deletions

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@@ -2,11 +2,8 @@
This matrix math library is focused on embedded development and avoids any heap memory allocation unless you explicitly ask for it. This matrix math library is focused on embedded development and avoids any heap memory allocation unless you explicitly ask for it.
It uses templates to pre-allocate matrices on the stack. It uses templates to pre-allocate matrices on the stack.
# Building There are still several operations that are works in progress such as:
1. Initialize the repositiory with the command: - Add a function to calculate eigenvalues/vectors
```bash - Add a function to compute RREF
cmake -S . -B build -G Ninja - Add a function for SVD decomposition
``` - Add a function for LQ decomposition
2. Go into the build folder and run `ninja`
3. That's it. You can test out the build by running `./unit-tests/matrix-tests`

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

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@@ -415,6 +415,7 @@ TEST_CASE("Identity Matrix", "Matrix") {
SECTION("Tall Matrix") { SECTION("Tall Matrix") {
Matrix<5, 2> matrix = Matrix<5, 2>::Identity(); Matrix<5, 2> matrix = Matrix<5, 2>::Identity();
printLabeledMatrix("Identity Matrix", matrix);
uint32_t oneColumnIndex{0}; uint32_t oneColumnIndex{0};
for (uint32_t row = 0; row < 5; row++) { for (uint32_t row = 0; row < 5; row++) {
for (uint32_t column = 0; column < 2; column++) { for (uint32_t column = 0; column < 2; column++) {
@@ -539,13 +540,13 @@ TEST_CASE("QR Decompositions", "Matrix") {
} }
// Check that Qᵀ * Q ≈ I // Check that Qᵀ * Q ≈ I
// Since the rank of this matrix is 2, only the top left 2x2 sub-matrix will // This MUST be true even if the rank of A is 2 because without this,
// equal I. // calculating eigenvalues/vectors will not work.
Matrix<3, 3> Qt = Q.Transpose(); Matrix<3, 3> Qt = Q.Transpose();
Matrix<3, 3> QtQ{}; Matrix<3, 3> QtQ{};
QtQ = Qt * Q; QtQ = Qt * Q;
for (int i = 0; i < 2; ++i) { for (int i = 0; i < 3; ++i) {
for (int j = 0; j < 2; ++j) { for (int j = 0; j < 3; ++j) {
if (i == j) if (i == j)
REQUIRE_THAT(QtQ[i][j], Catch::Matchers::WithinRel(1.0f, 1e-4f)); REQUIRE_THAT(QtQ[i][j], Catch::Matchers::WithinRel(1.0f, 1e-4f));
else else
@@ -559,6 +560,28 @@ TEST_CASE("QR Decompositions", "Matrix") {
REQUIRE(std::fabs(R[i][j]) < 1e-4f); 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") { SECTION("4x2 QRDecomposition") {
@@ -600,41 +623,42 @@ TEST_CASE("QR Decompositions", "Matrix") {
} }
} }
TEST_CASE("Eigenvalues and Vectors", "Matrix") { // TEST_CASE("Eigenvalues and Vectors", "Matrix") {
SECTION("2x2 Eigen") { // SECTION("2x2 Eigen") {
Matrix<2, 2> A{1.0f, 2.0f, 3.0f, 4.0f}; // Matrix<2, 2> A{1.0f, 2.0f, 3.0f, 4.0f};
Matrix<2, 2> vectors{}; // Matrix<2, 2> vectors{};
Matrix<2, 1> values{}; // 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[0][0], Catch::Matchers::WithinRel(0.41597f, 1e-4f));
REQUIRE_THAT(vectors[1][0], Catch::Matchers::WithinRel(0.90938f, 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[0][0], Catch::Matchers::WithinRel(5.372282f, 1e-4f));
REQUIRE_THAT(values[1][0], Catch::Matchers::WithinRel(-0.372281f, 1e-4f)); // REQUIRE_THAT(values[1][0], Catch::Matchers::WithinRel(-0.372281f,
} // 1e-4f));
// }
SECTION("3x3 Rank Defficient Eigen") { // SECTION("3x3 Eigen") {
SKIP("Skipping this because QR decomposition isn't ready for it"); // // this symmetrix tridiagonal matrix is well behaved for testing
// 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> A{1, 2, 3, 4, 5, 6, 7, 8, 9};
Matrix<3, 3> vectors{}; // Matrix<3, 3> vectors{};
Matrix<3, 1> values{}; // Matrix<3, 1> values{};
A.EigenQR(vectors, values, 1000000, 1e-8f); // A.EigenQR(vectors, values, 1000000, 1e-8f);
std::string strBuf1 = ""; // std::string strBuf1 = "";
vectors.ToString(strBuf1); // vectors.ToString(strBuf1);
std::cout << "Vectors:\n" << strBuf1 << std::endl; // std::cout << "Vectors:\n" << strBuf1 << std::endl;
strBuf1 = ""; // strBuf1 = "";
values.ToString(strBuf1); // values.ToString(strBuf1);
std::cout << "Values:\n" << strBuf1 << std::endl; // std::cout << "Values:\n" << strBuf1 << std::endl;
REQUIRE_THAT(vectors[0][0], Catch::Matchers::WithinRel(0.23197f, 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[1][0], Catch::Matchers::WithinRel(0.525322f,
REQUIRE_THAT(vectors[2][0], Catch::Matchers::WithinRel(0.81867f, 1e-4f)); // 1e-4f)); REQUIRE_THAT(vectors[2][0], Catch::Matchers::WithinRel(0.81867f,
REQUIRE_THAT(values[0][0], Catch::Matchers::WithinRel(-1.11684f, 1e-4f)); // 1e-4f)); REQUIRE_THAT(values[0][0], Catch::Matchers::WithinRel(-1.11684f,
REQUIRE_THAT(values[1][0], Catch::Matchers::WithinRel(0.0f, 1e-4f)); // 1e-4f)); REQUIRE_THAT(values[1][0], Catch::Matchers::WithinRel(0.0f,
REQUIRE_THAT(values[2][0], Catch::Matchers::WithinRel(16.1168f, 1e-4f)); // 1e-4f)); REQUIRE_THAT(values[2][0], Catch::Matchers::WithinRel(16.1168f,
} // 1e-4f));
} // }
// }

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@@ -8,7 +8,6 @@
// any other libraries // any other libraries
#include <array> #include <array>
#include <cmath> #include <cmath>
#include <cstdint>
// basically re-run all of the matrix tests with huge matrices and time the // basically re-run all of the matrix tests with huge matrices and time the
// results. // results.
@@ -30,13 +29,13 @@ TEST_CASE("Timing Tests", "Matrix") {
Matrix<4, 4> mat5{}; Matrix<4, 4> mat5{};
SECTION("Addition") { SECTION("Addition") {
for (uint32_t i{0}; i < 100000; i++) { for (uint32_t i{0}; i < 10000; i++) {
mat3 = mat1 + mat2; mat3 = mat1 + mat2;
} }
} }
SECTION("Subtraction") { SECTION("Subtraction") {
for (uint32_t i{0}; i < 100000; i++) { for (uint32_t i{0}; i < 10000; i++) {
mat3 = mat1 - mat2; mat3 = mat1 - mat2;
} }
} }
@@ -48,19 +47,19 @@ TEST_CASE("Timing Tests", "Matrix") {
} }
SECTION("Scalar Multiplication") { SECTION("Scalar Multiplication") {
for (uint32_t i{0}; i < 100000; i++) { for (uint32_t i{0}; i < 10000; i++) {
mat3 = mat1 * 3; mat3 = mat1 * 3;
} }
} }
SECTION("Element Multiply") { SECTION("Element Multiply") {
for (uint32_t i{0}; i < 100000; i++) { for (uint32_t i{0}; i < 10000; i++) {
mat1.ElementMultiply(mat2, mat3); mat1.ElementMultiply(mat2, mat3);
} }
} }
SECTION("Element Divide") { SECTION("Element Divide") {
for (uint32_t i{0}; i < 100000; i++) { for (uint32_t i{0}; i < 10000; i++) {
mat1.ElementDivide(mat2, mat3); mat1.ElementDivide(mat2, mat3);
} }
} }
@@ -69,59 +68,52 @@ TEST_CASE("Timing Tests", "Matrix") {
// what about matrices of 0,0 or 1,1? // what about matrices of 0,0 or 1,1?
// minor matrix for 2x2 matrix // minor matrix for 2x2 matrix
Matrix<49, 49> minorMat1{}; Matrix<49, 49> minorMat1{};
for (uint32_t i{0}; i < 100000; i++) { for (uint32_t i{0}; i < 10000; i++) {
mat1.MinorMatrix(minorMat1, 0, 0); mat1.MinorMatrix(minorMat1, 0, 0);
} }
} }
SECTION("Determinant") { SECTION("Determinant") {
for (uint32_t i{0}; i < 1000000; i++) { for (uint32_t i{0}; i < 100000; i++) {
float det1 = mat4.Det(); float det1 = mat4.Det();
} }
} }
SECTION("Matrix of Minors") { SECTION("Matrix of Minors") {
for (uint32_t i{0}; i < 1000000; i++) { for (uint32_t i{0}; i < 100000; i++) {
mat4.MatrixOfMinors(mat5); mat4.MatrixOfMinors(mat5);
} }
} }
SECTION("Invert") { SECTION("Invert") {
for (uint32_t i{0}; i < 1000000; i++) { for (uint32_t i{0}; i < 100000; i++) {
mat5 = mat4.Invert(); mat5 = mat4.Invert();
} }
}; };
SECTION("Transpose") { SECTION("Transpose") {
for (uint32_t i{0}; i < 100000; i++) { for (uint32_t i{0}; i < 10000; i++) {
mat3 = mat1.Transpose(); mat3 = mat1.Transpose();
} }
} }
SECTION("Normalize") { SECTION("Normalize") {
for (uint32_t i{0}; i < 100000; i++) { for (uint32_t i{0}; i < 10000; i++) {
mat3 = mat1 / mat1.EuclideanNorm(); mat3 = mat1 / mat1.EuclideanNorm();
} }
} }
SECTION("GET ROW") { SECTION("GET ROW") {
Matrix<1, 50> mat1Rows{}; Matrix<1, 50> mat1Rows{};
for (uint32_t i{0}; i < 100000000; i++) { for (uint32_t i{0}; i < 1000000; i++) {
mat1.GetRow(0, mat1Rows); mat1.GetRow(0, mat1Rows);
} }
} }
SECTION("GET COLUMN") { SECTION("GET COLUMN") {
Matrix<50, 1> mat1Columns{}; Matrix<50, 1> mat1Columns{};
for (uint32_t i{0}; i < 100000000; i++) { for (uint32_t i{0}; i < 1000000; i++) {
mat1.GetColumn(0, mat1Columns); mat1.GetColumn(0, mat1Columns);
} }
} }
SECTION("QR Decomposition") {
Matrix<50, 50> Q, R{};
for (uint32_t i{0}; i < 500; i++) {
mat1.QRDecomposition(Q, R);
}
}
} }

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@@ -1,36 +1,56 @@
Running matrix-timing-tests with timing Randomness seeded to: 2444679151
Randomness seeded to: 3567651885 0.180 s: Addition
1.857 s: Addition 0.180 s: Timing Tests
1.857 s: Timing Tests 0.177 s: Subtraction
1.788 s: Subtraction 0.177 s: Timing Tests
1.788 s: Timing Tests 1.868 s: Multiplication
1.929 s: Multiplication 1.868 s: Timing Tests
1.929 s: Timing Tests 0.127 s: Scalar Multiplication
1.268 s: Scalar Multiplication 0.127 s: Timing Tests
1.268 s: Timing Tests 0.173 s: Element Multiply
1.798 s: Element Multiply 0.173 s: Timing Tests
1.798 s: Timing Tests 0.178 s: Element Divide
1.802 s: Element Divide 0.178 s: Timing Tests
1.803 s: Timing Tests 0.172 s: Minor Matrix
1.553 s: Minor Matrix 0.172 s: Timing Tests
1.554 s: Timing Tests 0.103 s: Determinant
1.009 s: Determinant 0.103 s: Timing Tests
1.009 s: Timing Tests 0.411 s: Matrix of Minors
4.076 s: Matrix of Minors 0.411 s: Timing Tests
4.076 s: Timing Tests 0.109 s: Invert
1.066 s: Invert 0.109 s: Timing Tests
1.066 s: Timing Tests 0.122 s: Transpose
1.246 s: Transpose 0.122 s: Timing Tests
1.246 s: Timing Tests 0.190 s: Normalize
2.284 s: Normalize 0.190 s: Timing Tests
2.284 s: Timing Tests 0.006 s: GET ROW
0.606 s: GET ROW 0.006 s: Timing Tests
0.606 s: Timing Tests 0.235 s: GET COLUMN
24.629 s: GET COLUMN 0.235 s: Timing Tests
24.630 s: Timing Tests
3.064 s: QR Decomposition
3.064 s: Timing Tests
=============================================================================== ===============================================================================
test cases: 1 | 1 passed test cases: 1 | 1 passed
assertions: - none - assertions: - none -
Command being timed: "build/unit-tests/matrix-timing-tests -d yes"
User time (seconds): 4.05
System time (seconds): 0.00
Percent of CPU this job got: 100%
Elapsed (wall clock) time (h:mm:ss or m:ss): 0:04.05
Average shared text size (kbytes): 0
Average unshared data size (kbytes): 0
Average stack size (kbytes): 0
Average total size (kbytes): 0
Maximum resident set size (kbytes): 3200
Average resident set size (kbytes): 0
Major (requiring I/O) page faults: 184
Minor (reclaiming a frame) page faults: 171
Voluntary context switches: 1
Involuntary context switches: 26
Swaps: 0
File system inputs: 12
File system outputs: 1
Socket messages sent: 0
Socket messages received: 0
Signals delivered: 0
Page size (bytes): 4096
Exit status: 0