LinkNexus/huoyi_deploy
20
0
Fork 0
Code Issues Pull Requests Actions Packages Projects Releases Wiki Activity

initial commit

Browse Source
This commit is contained in:
huangweifeng
2026-10-22 09:23:54 +08:00
commit 63f557a39f
4448 changed files with 584487 additions and 0 deletions
Download Patch File Download Diff File Expand all files Collapse all files
third_party/eigen/unsupported/test/sparse_extra.cpp
Vendored
+254
View File
@@ -0,0 +1,254 @@
// This file is part of Eigen, a lightweight C++ template library
// for linear algebra.
//
// Copyright (C) 2008-2010 Gael Guennebaud <g.gael@free.fr>
//
// This Source Code Form is subject to the terms of the Mozilla
// Public License v. 2.0. If a copy of the MPL was not distributed
// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
#include <cstdlib>
#include <string>
#include "sparse.h"
#ifdef min
#undef min
#endif
#ifdef max
#undef max
#endif
#include <Eigen/SparseExtra>
// Read from an environment variable TEST_TMPDIR, if available,
// and append the provided filename. Defaults to local directory.
std::string GetTestTempFilename(const char* filename) {
const char* test_tmpdir = std::getenv("TEST_TMPDIR");
if (test_tmpdir == nullptr) {
return std::string(filename);
}
return std::string(test_tmpdir) + std::string("/") + std::string(filename);
}
template <typename SetterType, typename DenseType, typename Scalar, int Options>
bool test_random_setter(SparseMatrix<Scalar, Options>& sm, const DenseType& ref,
const std::vector<Vector2i>& nonzeroCoords) {
{
sm.setZero();
SetterType w(sm);
std::vector<Vector2i> remaining = nonzeroCoords;
while (!remaining.empty()) {
int i = internal::random<int>(0, static_cast<int>(remaining.size()) - 1);
w(remaining[i].x(), remaining[i].y()) = ref.coeff(remaining[i].x(), remaining[i].y());
remaining[i] = remaining.back();
remaining.pop_back();
}
}
return sm.isApprox(ref);
}
template <typename SparseMatrixType>
void sparse_extra(const SparseMatrixType& ref) {
const Index rows = ref.rows();
const Index cols = ref.cols();
typedef typename SparseMatrixType::Scalar Scalar;
enum { Flags = SparseMatrixType::Flags };
double density = (std::max)(8. / (rows * cols), 0.01);
typedef Matrix<Scalar, Dynamic, Dynamic> DenseMatrix;
typedef Matrix<Scalar, Dynamic, 1> DenseVector;
Scalar eps = 1e-6;
SparseMatrixType m(rows, cols);
DenseMatrix refMat = DenseMatrix::Zero(rows, cols);
DenseVector vec1 = DenseVector::Random(rows);
std::vector<Vector2i> zeroCoords;
std::vector<Vector2i> nonzeroCoords;
initSparse<Scalar>(density, refMat, m, 0, &zeroCoords, &nonzeroCoords);
if (zeroCoords.size() == 0 || nonzeroCoords.size() == 0) return;
// test coeff and coeffRef
for (int i = 0; i < (int)zeroCoords.size(); ++i) {
VERIFY_IS_MUCH_SMALLER_THAN(m.coeff(zeroCoords[i].x(), zeroCoords[i].y()), eps);
if (internal::is_same<SparseMatrixType, SparseMatrix<Scalar, Flags> >::value)
VERIFY_RAISES_ASSERT(m.coeffRef(zeroCoords[0].x(), zeroCoords[0].y()) = 5);
}
VERIFY_IS_APPROX(m, refMat);
m.coeffRef(nonzeroCoords[0].x(), nonzeroCoords[0].y()) = Scalar(5);
refMat.coeffRef(nonzeroCoords[0].x(), nonzeroCoords[0].y()) = Scalar(5);
VERIFY_IS_APPROX(m, refMat);
// random setter
// {
// m.setZero();
// VERIFY_IS_NOT_APPROX(m, refMat);
// SparseSetter<SparseMatrixType, RandomAccessPattern> w(m);
// std::vector<Vector2i> remaining = nonzeroCoords;
// while(!remaining.empty())
// {
// int i = internal::random<int>(0,remaining.size()-1);
// w->coeffRef(remaining[i].x(),remaining[i].y()) = refMat.coeff(remaining[i].x(),remaining[i].y());
// remaining[i] = remaining.back();
// remaining.pop_back();
// }
// }
// VERIFY_IS_APPROX(m, refMat);
VERIFY((test_random_setter<RandomSetter<SparseMatrixType, StdMapTraits> >(m, refMat, nonzeroCoords)));
VERIFY((test_random_setter<RandomSetter<SparseMatrixType, StdUnorderedMapTraits> >(m, refMat, nonzeroCoords)));
#ifdef EIGEN_GOOGLEHASH_SUPPORT
VERIFY((test_random_setter<RandomSetter<SparseMatrixType, GoogleDenseHashMapTraits> >(m, refMat, nonzeroCoords)));
VERIFY((test_random_setter<RandomSetter<SparseMatrixType, GoogleSparseHashMapTraits> >(m, refMat, nonzeroCoords)));
#endif
// test RandomSetter
/*{
SparseMatrixType m1(rows,cols), m2(rows,cols);
DenseMatrix refM1 = DenseMatrix::Zero(rows, rows);
initSparse<Scalar>(density, refM1, m1);
{
Eigen::RandomSetter<SparseMatrixType > setter(m2);
for (int j=0; j<m1.outerSize(); ++j)
for (typename SparseMatrixType::InnerIterator i(m1,j); i; ++i)
setter(i.index(), j) = i.value();
}
VERIFY_IS_APPROX(m1, m2);
}*/
}
template <typename SparseMatrixType>
void check_marketio() {
typedef Matrix<typename SparseMatrixType::Scalar, Dynamic, Dynamic> DenseMatrix;
Index rows = internal::random<Index>(1, 100);
Index cols = internal::random<Index>(1, 100);
SparseMatrixType m1, m2;
m1 = DenseMatrix::Random(rows, cols).sparseView();
std::string filename = GetTestTempFilename("sparse_extra.mtx");
saveMarket(m1, filename);
loadMarket(m2, filename);
VERIFY_IS_EQUAL(DenseMatrix(m1), DenseMatrix(m2));
}
template <typename VectorType>
void check_marketio_vector() {
Index size = internal::random<Index>(1, 100);
VectorType v1, v2;
v1 = VectorType::Random(size);
std::string filename = GetTestTempFilename("vector_extra.mtx");
saveMarketVector(v1, filename);
loadMarketVector(v2, filename);
VERIFY_IS_EQUAL(v1, v2);
}
template <typename DenseMatrixType>
void check_marketio_dense() {
Index rows = DenseMatrixType::MaxRowsAtCompileTime;
if (DenseMatrixType::MaxRowsAtCompileTime == Dynamic) {
rows = internal::random<Index>(1, 100);
} else if (DenseMatrixType::RowsAtCompileTime == Dynamic) {
rows = internal::random<Index>(1, DenseMatrixType::MaxRowsAtCompileTime);
}
Index cols = DenseMatrixType::MaxColsAtCompileTime;
if (DenseMatrixType::MaxColsAtCompileTime == Dynamic) {
cols = internal::random<Index>(1, 100);
} else if (DenseMatrixType::ColsAtCompileTime == Dynamic) {
cols = internal::random<Index>(1, DenseMatrixType::MaxColsAtCompileTime);
}
DenseMatrixType m1, m2;
m1 = DenseMatrixType::Random(rows, cols);
std::string filename = GetTestTempFilename("dense_extra.mtx");
saveMarketDense(m1, filename);
loadMarketDense(m2, filename);
VERIFY_IS_EQUAL(m1, m2);
}
template <typename Scalar>
void check_sparse_inverse() {
typedef SparseMatrix<Scalar> MatrixType;
Matrix<Scalar, -1, -1> A;
A.resize(1000, 1000);
A.fill(0);
A.setIdentity();
A.col(0).array() += 1;
A.row(0).array() += 2;
A.col(2).array() += 3;
A.row(7).array() += 3;
A.col(9).array() += 3;
A.block(3, 4, 4, 2).array() += 9;
A.middleRows(10, 50).array() += 3;
A.middleCols(50, 50).array() += 40;
A.block(500, 300, 40, 20).array() += 10;
A.transposeInPlace();
Eigen::SparseLU<MatrixType> slu;
slu.compute(A.sparseView());
Matrix<Scalar, -1, -1> Id(A.rows(), A.cols());
Id.setIdentity();
Matrix<Scalar, -1, -1> inv = slu.solve(Id);
const MatrixType sparseInv = Eigen::SparseInverse<Scalar>().compute(A.sparseView()).inverse();
Scalar sumdiff = 0; // Check the diff only of the non-zero elements
for (Eigen::Index j = 0; j < A.cols(); j++) {
for (typename MatrixType::InnerIterator iter(sparseInv, j); iter; ++iter) {
const Scalar diff = std::abs(inv(iter.row(), iter.col()) - iter.value());
VERIFY_IS_APPROX_OR_LESS_THAN(diff, 1e-11);
if (iter.value() != 0) {
sumdiff += diff;
}
}
}
VERIFY_IS_APPROX_OR_LESS_THAN(sumdiff, 1e-10);
}
EIGEN_DECLARE_TEST(sparse_extra) {
for (int i = 0; i < g_repeat; i++) {
int s = Eigen::internal::random<int>(1, 50);
CALL_SUBTEST_1(sparse_extra(SparseMatrix<double>(8, 8)));
CALL_SUBTEST_2(sparse_extra(SparseMatrix<std::complex<double> >(s, s)));
CALL_SUBTEST_1(sparse_extra(SparseMatrix<double>(s, s)));
CALL_SUBTEST_3((check_marketio<SparseMatrix<float, ColMajor, int> >()));
CALL_SUBTEST_3((check_marketio<SparseMatrix<double, ColMajor, int> >()));
CALL_SUBTEST_3((check_marketio<SparseMatrix<std::complex<float>, ColMajor, int> >()));
CALL_SUBTEST_3((check_marketio<SparseMatrix<std::complex<double>, ColMajor, int> >()));
CALL_SUBTEST_3((check_marketio<SparseMatrix<float, ColMajor, long int> >()));
CALL_SUBTEST_3((check_marketio<SparseMatrix<double, ColMajor, long int> >()));
CALL_SUBTEST_3((check_marketio<SparseMatrix<std::complex<float>, ColMajor, long int> >()));
CALL_SUBTEST_3((check_marketio<SparseMatrix<std::complex<double>, ColMajor, long int> >()));
CALL_SUBTEST_4((check_marketio_dense<Matrix<float, Dynamic, Dynamic> >()));
CALL_SUBTEST_4((check_marketio_dense<Matrix<float, Dynamic, Dynamic, RowMajor> >()));
CALL_SUBTEST_4((check_marketio_dense<Matrix<double, Dynamic, Dynamic> >()));
CALL_SUBTEST_4((check_marketio_dense<Matrix<std::complex<float>, Dynamic, Dynamic> >()));
CALL_SUBTEST_4((check_marketio_dense<Matrix<std::complex<double>, Dynamic, Dynamic> >()));
CALL_SUBTEST_4((check_marketio_dense<Matrix<float, Dynamic, 3> >()));
CALL_SUBTEST_4((check_marketio_dense<Matrix<double, 3, Dynamic> >()));
CALL_SUBTEST_4((check_marketio_dense<Matrix<double, 3, 4> >()));
CALL_SUBTEST_4((check_marketio_dense<Matrix<double, Dynamic, Dynamic, ColMajor, 5, 5> >()));
CALL_SUBTEST_5((check_marketio_vector<Matrix<float, 1, Dynamic> >()));
CALL_SUBTEST_5((check_marketio_vector<Matrix<double, 1, Dynamic> >()));
CALL_SUBTEST_5((check_marketio_vector<Matrix<std::complex<float>, 1, Dynamic> >()));
CALL_SUBTEST_5((check_marketio_vector<Matrix<std::complex<double>, 1, Dynamic> >()));
CALL_SUBTEST_5((check_marketio_vector<Matrix<float, Dynamic, 1> >()));
CALL_SUBTEST_5((check_marketio_vector<Matrix<double, Dynamic, 1> >()));
CALL_SUBTEST_5((check_marketio_vector<Matrix<std::complex<float>, Dynamic, 1> >()));
CALL_SUBTEST_5((check_marketio_vector<Matrix<std::complex<double>, Dynamic, 1> >()));
CALL_SUBTEST_6((check_sparse_inverse<double>()));
TEST_SET_BUT_UNUSED_VARIABLE(s);
}
}