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Improve test coverage for inner product, fill, reductions, and IO

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libeigen/eigen!2286

Co-authored-by: Rasmus Munk Larsen <rmlarsen@gmail.com>
This commit is contained in:
Rasmus Munk Larsen
2026-03-12 12:48:45 -07:00
parent 5e478d3285
commit c93116b43d
5 changed files with 209 additions and 1 deletions
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88
test/vectorwiseop.cpp
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@@ -91,6 +91,16 @@ void vectorwiseop_array(const ArrayType& m) {
VERIFY((mb.col(c) == (m1.real().col(c) >= 0.7).any()).all());
mb = (m1.real() >= 0.7).rowwise().any();
VERIFY((mb.row(r) == (m1.real().row(r) >= 0.7).any()).all());
// test count()
{
Array<Index, 1, ArrayType::ColsAtCompileTime> colcounts(cols);
Array<Index, ArrayType::RowsAtCompileTime, 1> rowcounts(rows);
colcounts = (m1.real() >= 0).colwise().count();
for (Index k = 0; k < cols; ++k) VERIFY_IS_EQUAL(colcounts(k), (m1.real().col(k) >= 0).count());
rowcounts = (m1.real() >= 0).rowwise().count();
for (Index k = 0; k < rows; ++k) VERIFY_IS_EQUAL(rowcounts(k), (m1.real().row(k) >= 0).count());
}
}
template <typename MatrixType>
@@ -206,6 +216,15 @@ void vectorwiseop_matrix(const MatrixType& m) {
VERIFY_EVALUATION_COUNT(m2 = (m1.rowwise() - m1.colwise().sum() / RealScalar(m1.rows())),
(MatrixType::RowsAtCompileTime != 1 ? 1 : 0));
// test colwise/rowwise reverse
{
MatrixType m_rev(rows, cols);
m_rev = m1.colwise().reverse();
for (Index k = 0; k < cols; ++k) VERIFY_IS_APPROX(m_rev.col(k), m1.col(k).reverse());
m_rev = m1.rowwise().reverse();
for (Index k = 0; k < rows; ++k) VERIFY_IS_APPROX(m_rev.row(k), m1.row(k).reverse());
}
// test empty expressions
VERIFY_IS_APPROX(m1.matrix().middleCols(0, 0).rowwise().sum().eval(), MatrixX::Zero(rows, 1));
VERIFY_IS_APPROX(m1.matrix().middleRows(0, 0).colwise().sum().eval(), MatrixX::Zero(1, cols));
@@ -224,6 +243,73 @@ void vectorwiseop_matrix(const MatrixType& m) {
VERIFY_IS_EQUAL(m1.real().middleCols(0, fix<0>).colwise().maxCoeff().eval().cols(), 0);
}
// Integer-safe subset of vectorwiseop_array: tests +, -, all/any, count only.
// Skips *, / which cause integer overflow or division-by-zero with full-range random ints.
template <typename ArrayType>
void vectorwiseop_array_integer(const ArrayType& m) {
typedef typename ArrayType::Scalar Scalar;
typedef Array<Scalar, ArrayType::RowsAtCompileTime, 1> ColVectorType;
typedef Array<Scalar, 1, ArrayType::ColsAtCompileTime> RowVectorType;
Index rows = m.rows();
Index cols = m.cols();
Index r = internal::random<Index>(0, rows - 1), c = internal::random<Index>(0, cols - 1);
ArrayType m1 = ArrayType::Random(rows, cols), m2(rows, cols);
// Clamp to avoid overflow even in addition/subtraction.
for (Index j = 0; j < cols; ++j)
for (Index i = 0; i < rows; ++i) m1(i, j) = m1(i, j) % Scalar(10000);
ColVectorType colvec = ColVectorType::Random(rows);
for (Index i = 0; i < rows; ++i) colvec(i) = colvec(i) % Scalar(10000);
RowVectorType rowvec = RowVectorType::Random(cols);
for (Index j = 0; j < cols; ++j) rowvec(j) = rowvec(j) % Scalar(10000);
// test addition
m2 = m1;
m2.colwise() += colvec;
VERIFY_IS_APPROX(m2, m1.colwise() + colvec);
VERIFY_IS_APPROX(m2.col(c), m1.col(c) + colvec);
m2 = m1;
m2.rowwise() += rowvec;
VERIFY_IS_APPROX(m2, m1.rowwise() + rowvec);
VERIFY_IS_APPROX(m2.row(r), m1.row(r) + rowvec);
// test subtraction
m2 = m1;
m2.colwise() -= colvec;
VERIFY_IS_APPROX(m2, m1.colwise() - colvec);
VERIFY_IS_APPROX(m2.col(c), m1.col(c) - colvec);
m2 = m1;
m2.rowwise() -= rowvec;
VERIFY_IS_APPROX(m2, m1.rowwise() - rowvec);
VERIFY_IS_APPROX(m2.row(r), m1.row(r) - rowvec);
// all/any
Array<bool, Dynamic, Dynamic> mb(rows, cols);
mb = (m1 <= Scalar(0)).colwise().all();
VERIFY((mb.col(c) == (m1.col(c) <= Scalar(0)).all()).all());
mb = (m1 <= Scalar(0)).rowwise().all();
VERIFY((mb.row(r) == (m1.row(r) <= Scalar(0)).all()).all());
mb = (m1 >= Scalar(0)).colwise().any();
VERIFY((mb.col(c) == (m1.col(c) >= Scalar(0)).any()).all());
mb = (m1 >= Scalar(0)).rowwise().any();
VERIFY((mb.row(r) == (m1.row(r) >= Scalar(0)).any()).all());
// test count()
{
Array<Index, 1, ArrayType::ColsAtCompileTime> colcounts(cols);
Array<Index, ArrayType::RowsAtCompileTime, 1> rowcounts(rows);
colcounts = (m1 >= Scalar(0)).colwise().count();
for (Index k = 0; k < cols; ++k) VERIFY_IS_EQUAL(colcounts(k), (m1.col(k) >= Scalar(0)).count());
rowcounts = (m1 >= Scalar(0)).rowwise().count();
for (Index k = 0; k < rows; ++k) VERIFY_IS_EQUAL(rowcounts(k), (m1.row(k) >= Scalar(0)).count());
}
}
void vectorwiseop_mixedscalar() {
Matrix4cd a = Matrix4cd::Random();
Vector4cd b = Vector4cd::Random();
@@ -248,4 +334,6 @@ EIGEN_DECLARE_TEST(vectorwiseop) {
CALL_SUBTEST_7(vectorwiseop_matrix(VectorXd(internal::random<int>(1, EIGEN_TEST_MAX_SIZE))));
CALL_SUBTEST_7(vectorwiseop_matrix(RowVectorXd(internal::random<int>(1, EIGEN_TEST_MAX_SIZE))));
CALL_SUBTEST_8(vectorwiseop_mixedscalar());
CALL_SUBTEST_9(vectorwiseop_array_integer(
ArrayXXi(internal::random<int>(1, EIGEN_TEST_MAX_SIZE), internal::random<int>(1, EIGEN_TEST_MAX_SIZE))));
}