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Add test coverage for matrix lpNorm, RowMajor partial reductions, selfadjoint boundaries

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libeigen/eigen!2289

Co-authored-by: Rasmus Munk Larsen <rmlarsen@gmail.com>
This commit is contained in:
Rasmus Munk Larsen
2026-03-12 14:45:51 -07:00
parent 15cae83485
commit 356a9ba1da
3 changed files with 177 additions and 0 deletions
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68
test/product_selfadjoint.cpp
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@@ -63,6 +63,70 @@ void product_selfadjoint(const MatrixType& m) {
VERIFY_IS_APPROX(m1 * m4, m2.template selfadjointView<Lower>() * m4);
}
// Test selfadjoint products at blocking boundary sizes.
// The existing test uses random sizes; this tests deterministic sizes
// at transitions (especially around the GEBP early-return threshold of 48).
template <int>
void product_selfadjoint_boundary() {
typedef double Scalar;
typedef Matrix<Scalar, Dynamic, Dynamic> Mat;
typedef Matrix<Scalar, Dynamic, 1> Vec;
const int sizes[] = {1, 2, 3, 4, 8, 16, 47, 48, 49, 64, 96, 128};
for (int si = 0; si < 12; ++si) {
int n = sizes[si];
Mat m1 = Mat::Random(n, n);
m1 = (m1 + m1.transpose()).eval(); // make symmetric
Vec v1 = Vec::Random(n);
Mat rhs = Mat::Random(n, 5);
// Lower selfadjointView * vector
Mat m2 = m1.triangularView<Lower>();
VERIFY_IS_APPROX(m2.selfadjointView<Lower>() * v1, m1 * v1);
// Upper selfadjointView * vector
m2 = m1.triangularView<Upper>();
VERIFY_IS_APPROX(m2.selfadjointView<Upper>() * v1, m1 * v1);
// selfadjointView * matrix
m2 = m1.triangularView<Lower>();
VERIFY_IS_APPROX(m2.selfadjointView<Lower>() * rhs, m1 * rhs);
// rankUpdate
Vec v2 = Vec::Random(n);
m2 = m1.triangularView<Lower>();
m2.selfadjointView<Lower>().rankUpdate(v1, v2);
VERIFY_IS_APPROX(m2, (m1 + v1 * v2.transpose() + v2 * v1.transpose()).triangularView<Lower>().toDenseMatrix());
}
}
// Same test for complex type (tests conjugation logic).
template <int>
void product_selfadjoint_boundary_complex() {
typedef std::complex<float> Scalar;
typedef Matrix<Scalar, Dynamic, Dynamic> Mat;
typedef Matrix<Scalar, Dynamic, 1> Vec;
const int sizes[] = {1, 8, 47, 48, 49, 64};
for (int si = 0; si < 6; ++si) {
int n = sizes[si];
Mat m1 = Mat::Random(n, n);
m1 = (m1 + m1.adjoint()).eval(); // make Hermitian
m1.diagonal() = m1.diagonal().real().template cast<Scalar>(); // real diagonal
Vec v1 = Vec::Random(n);
Mat rhs = Mat::Random(n, 3);
Mat m2 = m1.triangularView<Lower>();
VERIFY_IS_APPROX(m2.selfadjointView<Lower>() * v1, m1 * v1);
VERIFY_IS_APPROX(m2.selfadjointView<Lower>() * rhs, m1 * rhs);
m2 = m1.triangularView<Upper>();
VERIFY_IS_APPROX(m2.selfadjointView<Upper>() * v1, m1 * v1);
}
}
EIGEN_DECLARE_TEST(product_selfadjoint) {
int s = 0;
for (int i = 0; i < g_repeat; i++) {
@@ -86,4 +150,8 @@ EIGEN_DECLARE_TEST(product_selfadjoint) {
CALL_SUBTEST_7(product_selfadjoint(Matrix<float, Dynamic, Dynamic, RowMajor>(s, s)));
TEST_SET_BUT_UNUSED_VARIABLE(s)
}
// Deterministic blocking boundary tests (outside g_repeat).
CALL_SUBTEST_8(product_selfadjoint_boundary<0>());
CALL_SUBTEST_9(product_selfadjoint_boundary_complex<0>());
}