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Add boundary test coverage: stableNorm, LinSpaced, complex GEMV, triangular solve

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libeigen/eigen!2291

Co-authored-by: Rasmus Munk Larsen <rmlarsen@gmail.com>
This commit is contained in:
Rasmus Munk Larsen
2026-03-12 18:15:30 -07:00
parent 6b9275d1a8
commit c1faa74738
4 changed files with 401 additions and 0 deletions
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69
test/stable_norm.cpp
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@@ -236,6 +236,71 @@ void test_hypot() {
VERIFY((numext::isnan)(numext::hypot(a, nan)));
}
// Test stableNorm at the 4096-element block boundary.
// stable_norm_impl_inner_step processes vectors in blocks of 4096.
// Sizes near this boundary exercise the transition between full blocks
// and the remainder tail, including scale propagation across blocks.
template <typename Scalar>
void stable_norm_block_boundary() {
using std::abs;
using std::sqrt;
typedef typename NumTraits<Scalar>::Real RealScalar;
typedef Matrix<Scalar, Dynamic, 1> VecType;
// Test sizes around the 4096 block boundary.
const Index sizes[] = {4095, 4096, 4097, 8191, 8192, 8193, 12288};
for (int si = 0; si < 7; ++si) {
Index n = sizes[si];
VecType v = VecType::Random(n);
VERIFY_IS_APPROX(v.stableNorm(), v.norm());
VERIFY_IS_APPROX(v.blueNorm(), v.norm());
}
// Test scale transitions across blocks: first block has tiny values,
// second block has huge values. This exercises the scale/invScale
// update logic when maxCoeff > scale in stable_norm_kernel.
{
RealScalar tiny = (std::numeric_limits<RealScalar>::min)() * RealScalar(1e4);
RealScalar huge_val = (std::numeric_limits<RealScalar>::max)() * RealScalar(1e-4);
Index n = 8192;
VecType v(n);
// First 4096 elements: tiny. Second 4096 elements: huge.
v.head(4096).setConstant(Scalar(tiny));
v.tail(4096).setConstant(Scalar(huge_val));
// The huge part dominates, so the expected norm is sqrt(4096)*huge_val.
RealScalar expected = sqrt(RealScalar(4096)) * abs(huge_val);
VERIFY_IS_APPROX(v.stableNorm(), expected);
VERIFY_IS_APPROX(v.blueNorm(), expected);
}
// Reverse: first block huge, second block tiny.
{
RealScalar tiny = (std::numeric_limits<RealScalar>::min)() * RealScalar(1e4);
RealScalar huge_val = (std::numeric_limits<RealScalar>::max)() * RealScalar(1e-4);
Index n = 8192;
VecType v(n);
v.head(4096).setConstant(Scalar(huge_val));
v.tail(4096).setConstant(Scalar(tiny));
RealScalar expected = sqrt(RealScalar(4096)) * abs(huge_val);
VERIFY_IS_APPROX(v.stableNorm(), expected);
VERIFY_IS_APPROX(v.blueNorm(), expected);
}
// Matrix version: columns with different magnitudes.
// Scale must propagate correctly across columns.
{
RealScalar tiny = (std::numeric_limits<RealScalar>::min)() * RealScalar(1e4);
RealScalar huge_val = (std::numeric_limits<RealScalar>::max)() * RealScalar(1e-4);
typedef Matrix<Scalar, Dynamic, Dynamic> MatType;
MatType m(100, 2);
m.col(0).setConstant(Scalar(tiny));
m.col(1).setConstant(Scalar(huge_val));
RealScalar expected = sqrt(RealScalar(100)) * abs(huge_val);
VERIFY_IS_APPROX(m.stableNorm(), expected);
VERIFY_IS_APPROX(m.blueNorm(), expected);
}
}
EIGEN_DECLARE_TEST(stable_norm) {
CALL_SUBTEST_1(test_empty());
@@ -253,4 +318,8 @@ EIGEN_DECLARE_TEST(stable_norm) {
CALL_SUBTEST_5(stable_norm(VectorXcd(internal::random<int>(10, 2000))));
CALL_SUBTEST_6(stable_norm(VectorXcf(internal::random<int>(10, 2000))));
}
// Block boundary and scale transition tests (deterministic, outside g_repeat).
CALL_SUBTEST_7(stable_norm_block_boundary<float>());
CALL_SUBTEST_7(stable_norm_block_boundary<double>());
}