21373593817

Committed 26 Jan 2026 08:52PM UTC coverage: 84.006%. First build

Build # 21373593817

Build Type

Pull #499

github

Committed by

Ravenwater

Commit Message

Add comprehensive BLAS regression tests for coverage

Convert generators.cpp and matrix_ops.cpp from demos to proper
regression tests with assertions:

generators.cpp:
- Add VerifyIdentityGenerator, VerifyRowOrderIndex, VerifyColumnOrderIndex
- Add VerifyLaplace2D, VerifyMinij, VerifyMagicSquare
- Add VerifyUniformRandom, VerifyGaussianRandom
- Add VerifyHilbert (scaled and unscaled), VerifyTridiag
- Test with double, float, posit<32,2>, posit<16,1>

matrix_ops.cpp:
- Add VerifyTranspose, VerifyMatrixVectorProduct, VerifyMatrixMatrixProduct
- Add VerifyFusedMatrixOps for posit fused operations
- Add VerifyOperators (eye, diag, tril, triu)
- Add VerifyNorm (1-norm, 2-norm, inf-norm)
- Add VerifyMatnorm (matrix 1-norm and inf-norm)
- Add VerifyVmath (sqrt, square, power, sin, cos, tan)
- Test with float, double, posit<32,2>, bfloat16

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>

Pull Request Pull Request #499: V3.93: UBSan fixes, image demo, and coverage workflow

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34.13

/linalg/data/test_matrices.cpp

// test_matrices.cpp: convert test matrix include files to data files
//
// Copyright (C) 2017 Stillwater Supercomputing, Inc.
// SPDX-License-Identifier: MIT
//
// This file is part of the universal numbers project, which is released under an MIT Open Source license.
#include <universal/utility/directives.hpp>
#include <cmath>
#include <iostream>
#include <iomanip>
#include <fstream>

// Serialization - test_matrix.hpp reads matrices from .dat files
#include <blas/serialization/datafile.hpp>
#include <blas/serialization/test_matrix.hpp>

#include <universal/verification/test_suite.hpp>
#include <blas/matrices/testsuite.hpp>

namespace sw { namespace blas {
        using namespace sw::numeric::containers;

        static void WriteMatrixDataFile(const std::string& filename, const matrix<double>& A) {
                std::ofstream fo;
                fo.open(filename);
                fo << A;
                fo.close();
        }

        static void GenerateMatrixDataFiles(const std::vector<std::string>& testMatrixNames) {
                for (auto matrixName : testMatrixNames) {
                        WriteMatrixDataFile(matrixName + std::string(".dat"), getTestMatrix(matrixName));
                }
        }

        ////////////////////////////////////////////////////////////////////////
        // Test global getTestMatrix() from testsuite.hpp
        int VerifyGlobalGetTestMatrix(bool reportTestCases) {
                int nrOfFailedTests = 0;

                // Test all available matrices from testsuite.hpp
                std::vector<std::pair<std::string, std::pair<size_t, size_t>>> expectedDimensions = {
                        {"lambers_well", {2, 2}},
                        {"lambers_ill", {2, 2}},
                        {"h3", {3, 3}},
                        {"q3", {3, 3}},
                        {"int3", {3, 3}},
                        {"faires74x3", {3, 3}},
                        {"q4", {4, 4}},
                        {"lu4", {4, 4}},
                        {"s4", {4, 4}},
                        {"rand4", {4, 4}},
                        {"q5", {5, 5}},
                        {"b1_ss", {7, 7}},
                        {"cage3", {5, 5}},
                        {"pores_1", {30, 30}},
                        {"Stranke94", {10, 10}},
                        {"Trefethen_20", {20, 20}}
                };

                for (const auto& entry : expectedDimensions) {
                        const std::string& name = entry.first;
                        size_t expectedRows = entry.second.first;
                        size_t expectedCols = entry.second.second;

                        // Use global getTestMatrix (from testsuite.hpp)
                        matrix<double> M = ::getTestMatrix(name);

                        if (num_rows(M) != expectedRows || num_cols(M) != expectedCols) {
                                ++nrOfFailedTests;
                                if (reportTestCases) std::cerr << "FAIL: global getTestMatrix(" << name << ") = "
                                                               << num_rows(M) << "x" << num_cols(M)
                                                               << " (expected " << expectedRows << "x" << expectedCols << ")\n";
                        }
                }

                // Test unknown matrix returns default (lu4)
                matrix<double> unknown = ::getTestMatrix("unknown_matrix_xyz");
                if (num_rows(unknown) != 4 || num_cols(unknown) != 4) {
                        ++nrOfFailedTests;
                        if (reportTestCases) std::cerr << "FAIL: global getTestMatrix(unknown) should return lu4 (4x4)\n";
                }

                return nrOfFailedTests;
        }

        ////////////////////////////////////////////////////////////////////////
        // Test global kappa() from testsuite.hpp
        int VerifyGlobalKappa(bool reportTestCases) {
                int nrOfFailedTests = 0;

                // Test known condition numbers
                std::vector<std::pair<std::string, double>> expectedKappa = {
                        {"lambers_well", 10.0},
                        {"lambers_ill", 1.869050824603144e+08},
                        {"h3", 1.8478e+11},
                        {"q3", 1.2857e+06},
                        {"int3", 43.6115},
                        {"faires74x3", 15999},
                        {"q4", 2.35},
                        {"lu4", 11.6810},
                        {"s4", 4.19},
                        {"rand4", 27.81},
                        {"q5", 1.1e+04},
                        {"b1_ss", 1.973732e+02},
                        {"cage3", 1.884547e+01},
                        {"pores_1", 1.812616e+06},
                        {"Stranke94", 5.173300e+01},
                        {"Trefethen_20", 6.308860e+01}
                };

                for (const auto& entry : expectedKappa) {
                        const std::string& name = entry.first;
                        double expected = entry.second;

                        // Use global kappa (from testsuite.hpp)
                        double k = ::kappa(name);

                        // Use relative tolerance for comparison
                        double relError = std::abs(k - expected) / expected;
                        if (relError > 0.001) {
                                ++nrOfFailedTests;
                                if (reportTestCases) std::cerr << "FAIL: global kappa(" << name << ") = " << k
                                                               << " (expected " << expected << ")\n";
                        }
                }

                // Test unknown matrix returns default (lu4's kappa)
                double unknownK = ::kappa("unknown_matrix_xyz");
                if (std::abs(unknownK - 11.6810) > 0.01) {
                        ++nrOfFailedTests;
                        if (reportTestCases) std::cerr << "FAIL: global kappa(unknown) should return 11.6810\n";
                }

                return nrOfFailedTests;
        }

        ////////////////////////////////////////////////////////////////////////
        // Test matrix data values (not just dimensions)
        int VerifyMatrixValues(bool reportTestCases) {
                int nrOfFailedTests = 0;

                // Test lambers_well matrix values
                // lambers_well = [[1, 2], [3, 4]] or similar known values
                {
                        matrix<double> A = ::getTestMatrix("lambers_well");
                        if (num_rows(A) >= 2 && num_cols(A) >= 2) {
                                // Just verify the matrix has non-zero values
                                bool hasNonZero = false;
                                for (size_t i = 0; i < num_rows(A) && !hasNonZero; ++i) {
                                        for (size_t j = 0; j < num_cols(A) && !hasNonZero; ++j) {
                                                if (A[i][j] != 0.0) hasNonZero = true;
                                        }
                                }
                                if (!hasNonZero) {
                                        ++nrOfFailedTests;
                                        if (reportTestCases) std::cerr << "FAIL: lambers_well has all zero values\n";
                                }
                        }
                }

                // Test lu4 matrix values
                {
                        matrix<double> A = ::getTestMatrix("lu4");
                        if (num_rows(A) == 4 && num_cols(A) == 4) {
                                // Verify diagonal has non-zero values (for LU decomposition test matrices)
                                bool diagonalOK = true;
                                for (size_t i = 0; i < 4; ++i) {
                                        if (A[i][i] == 0.0) diagonalOK = false;
                                }
                                if (!diagonalOK) {
                                        ++nrOfFailedTests;
                                        if (reportTestCases) std::cerr << "FAIL: lu4 diagonal should be non-zero\n";
                                }
                        }
                }

                return nrOfFailedTests;
        }

        ////////////////////////////////////////////////////////////////////////
        // Test WriteMatrixDataFile function
        int VerifyWriteMatrixDataFile(bool reportTestCases) {
                int nrOfFailedTests = 0;

                // Create a small test matrix
                matrix<double> A(3, 3);
                A[0][0] = 1.0; A[0][1] = 2.0; A[0][2] = 3.0;
                A[1][0] = 4.0; A[1][1] = 5.0; A[1][2] = 6.0;
                A[2][0] = 7.0; A[2][1] = 8.0; A[2][2] = 9.0;

                // Write to temporary file
                std::string tempFile = "/tmp/test_matrix_write.dat";
                WriteMatrixDataFile(tempFile, A);

                // Read back and verify
                matrix<double> B;
                std::ifstream fi(tempFile);
                if (fi.good()) {
                        fi >> B;
                        fi.close();

                        if (num_rows(B) != 3 || num_cols(B) != 3) {
                                ++nrOfFailedTests;
                                if (reportTestCases) std::cerr << "FAIL: read back matrix has wrong dimensions\n";
                        } else {
                                // Verify values
                                for (size_t i = 0; i < 3; ++i) {
                                        for (size_t j = 0; j < 3; ++j) {
                                                if (std::abs(A[i][j] - B[i][j]) > 0.0001) {
                                                        ++nrOfFailedTests;
                                                        if (reportTestCases) std::cerr << "FAIL: matrix value mismatch at [" << i << "][" << j << "]\n";
                                                }
                                        }
                                }
                        }
                } else {
                        ++nrOfFailedTests;
                        if (reportTestCases) std::cerr << "FAIL: could not read back written matrix file\n";
                }

                // Clean up
                std::remove(tempFile.c_str());

                return nrOfFailedTests;
        }

        ////////////////////////////////////////////////////////////////////////
        // Compare file-loaded matrix with header-defined matrix
        int VerifyFileVsHeaderMatrices(bool reportTestCases) {
                int nrOfFailedTests = 0;

                // Compare matrices that are available in both formats
                std::vector<std::string> matricesToCompare = {
                        "lambers_well",
                        "lambers_ill",
                        "lu4",
                        "q4"
                };

                for (const auto& name : matricesToCompare) {
                        // Get from header (global function)
                        matrix<double> fromHeader = ::getTestMatrix(name);

                        // Get from file (sw::blas function)
                        matrix<double> fromFile = sw::blas::getTestMatrix(name);

                        if (num_rows(fromFile) == 0 || num_cols(fromFile) == 0) {
                                // File doesn't exist, skip comparison
                                continue;
                        }

                        if (num_rows(fromHeader) != num_rows(fromFile) || num_cols(fromHeader) != num_cols(fromFile)) {
                                ++nrOfFailedTests;
                                if (reportTestCases) std::cerr << "FAIL: " << name << " dimension mismatch between header and file\n";
                                continue;
                        }

                        // Compare values
                        double maxError = 0.0;
                        for (size_t i = 0; i < num_rows(fromHeader); ++i) {
                                for (size_t j = 0; j < num_cols(fromHeader); ++j) {
                                        double err = std::abs(fromHeader[i][j] - fromFile[i][j]);
                                        if (err > maxError) maxError = err;
                                }
                        }

                        // Allow for floating-point serialization differences (file stores limited precision)
                        if (maxError > 1e-5) {
                                ++nrOfFailedTests;
                                if (reportTestCases) std::cerr << "FAIL: " << name << " value mismatch (max error: " << maxError << ")\n";
                        }
                }

                return nrOfFailedTests;
        }

} }

// This is a program that we ran once to get the test matrices converted to data files
// 
// We have no code in the regression side of the test so CI is a NOP


// Regression testing guards: typically set by the cmake configuration, but MANUAL_TESTING is an override
#define MANUAL_TESTING 0
// REGRESSION_LEVEL_OVERRIDE is set by the cmake file to drive a specific regression intensity
// It is the responsibility of the regression test to organize the tests in a quartile progression.
//#undef REGRESSION_LEVEL_OVERRIDE
#ifndef REGRESSION_LEVEL_OVERRIDE
#undef REGRESSION_LEVEL_1
#undef REGRESSION_LEVEL_2
#undef REGRESSION_LEVEL_3
#undef REGRESSION_LEVEL_4
#define REGRESSION_LEVEL_1 1
#define REGRESSION_LEVEL_2 1
#define REGRESSION_LEVEL_3 1
#define REGRESSION_LEVEL_4 1
#endif

int main()
try {
        using namespace sw::universal;
        using namespace sw::blas;

        std::string test_suite  = "test matrices serialization";
        std::string test_tag    = "test_matrices";
        bool reportTestCases    = true;
        int nrOfFailedTestCases = 0;

        ReportTestSuiteHeader(test_suite, reportTestCases);

#if MANUAL_TESTING

        // set up the set of test matrices
        std::vector<std::string> allTestMatrices = {
                "lambers_well",  //   2 x   2 well-conditioned matrix, K = 10.0
                "lambers_ill",   //   2 x   2 ill-conditioned matrix, K = 1.869050824603144e+08
                "h3",            //   3 x   3 test matrix, K = 1.8478e+11
                "int3",          //   3 x   3 integer test matrix (low condition number), K = 43.6115
                "faires74x3",    //   3 x   3 Burden Faires Ill-conditioned, K = 15999
                "q3",            //   3 x   3 Variable test matrix (edit entries), K = 1.2857e+06
                "q4",            //   4 x   4 test matrix, K = 2.35
                "q5",            //   5 x   5 test matrix, K = 1.1e+04
                "lu4",           //   4 x   4 test matrix, K = 11.6810
                "s4",            //   4 x   4 test matrix, K = 4.19
                "rand4",         //   4 x   4 random (low condition), K = 27.81
                "cage3",         //   5 x   5 Directed Weighted Graph, K = 1.884547e+01
                "b1_ss",         //   7 x   7 Chemical Process Simulation Problem, K = 1.973732e+02

                "west0132",      // 132 x 132 Chem. Simulation Process, K = 4.2e+11 
                "west0167",      // 167 x 167 Chemical Simulation Process, K = 2.827e+07
                "steam1",        // 240 x 240 Computational Fluid Dynamics, K = 2.827501e+07
                "steam3",        //  83 x  83 Computational Fluid Dynamics, K = 5.51e+10
                "fs_183_1",      // 183 x 183 2D/3D Problem Sequence, K = 1.5129e+13
                "fs_183_3",      // 183 x 183 2D/3D Problem Sequence, K = 1.5129e+13
                "bwm200",        // 200 x 200 Chemical simulation, K = 2.412527e+03
                "gre_343",       // 343 x 343 Directed Weighted Graph, K = 1.119763e+02
                "pores_1",       //  30 x  30 Computational Fluid Dynamics, K = 1.812616e+06
                "Stranke94",     //  10 x  10 Undirected Weighted Graph, K = 5.173300e+01
                "Trefethen_20",  //  20 x  20 Combinatorial Problem, K = 6.308860e+01
                "bcsstk01",      //  48 x  48 Structural Engineering, K = 8.8234e+05
                "bcsstk03",      // 112 x 112 Structural Engineering, K = 6.791333e+06
                "bcsstk04",      // 132 x 132 Structural Engineering, K = 2.292466e+06
                "bcsstk05",      // 153 x 153 Structural Engineering, K = 1.428114e+04
                "bcsstk22",      // 138 x 138 Structural Engineering, K = 1.107165e+05
                "lund_a",        // 147 x 147 Structural Engineering, K = 2.796948e+06
                "nos1",          // 237 x 237 Structural Engineering K = 1.991546e+07
                "arc130",        // 130 x 130    K = 6.0542e+10
                "saylr1",        // 238 x 238 Computational Fluid Dynamics, K = 7.780581e+08
                "tumorAntiAngiogenesis_2" // , K 1.9893e+10
        };
        GenerateMatrixDataFiles(allTestMatrices);

        ReportTestSuiteResults(test_suite, nrOfFailedTestCases);
        return EXIT_SUCCESS;
#else
        // Test the serialization/test_matrix.hpp functionality
        // Note: sw::blas::getTestMatrix() reads from .dat files (different from global getTestMatrix())
#if REGRESSION_LEVEL_1
        {
                // Test dataDirectory()
                std::string dataDir = sw::blas::dataDirectory();
                if (dataDir.empty()) {
                        ++nrOfFailedTestCases;
                        if (reportTestCases) std::cout << "FAIL: dataDirectory() returned empty\n";
                } else {
                        if (reportTestCases) std::cout << "PASS: dataDirectory() = " << dataDir << "\n";
                }

                // Test TestMatrixList is populated
                if (sw::blas::TestMatrixList.empty()) {
                        ++nrOfFailedTestCases;
                        if (reportTestCases) std::cout << "FAIL: TestMatrixList is empty\n";
                } else {
                        if (reportTestCases) std::cout << "PASS: TestMatrixList has " << sw::blas::TestMatrixList.size() << " matrices\n";
                }

                // Test ConditionNumber map is populated
                if (sw::blas::ConditionNumber.empty()) {
                        ++nrOfFailedTestCases;
                        if (reportTestCases) std::cout << "FAIL: ConditionNumber map is empty\n";
                } else {
                        if (reportTestCases) std::cout << "PASS: ConditionNumber map has " << sw::blas::ConditionNumber.size() << " entries\n";
                }

                // Test kappa() for known matrices (from serialization module)
                double k = sw::blas::kappa("lambers_well");
                if (std::abs(k - 10.0) < 0.001) {
                        if (reportTestCases) std::cout << "PASS: kappa(lambers_well) = " << k << "\n";
                } else {
                        ++nrOfFailedTestCases;
                        if (reportTestCases) std::cout << "FAIL: kappa(lambers_well) = " << k << " (expected 10.0)\n";
                }

                // Test kappa() for unknown matrix (should return 0.0 and print error)
                double unknownK = sw::blas::kappa("nonexistent_matrix");
                if (unknownK == 0.0) {
                        if (reportTestCases) std::cout << "PASS: kappa(unknown) = 0.0 (expected)\n";
                } else {
                        ++nrOfFailedTestCases;
                        if (reportTestCases) std::cout << "FAIL: kappa(unknown) = " << unknownK << " (expected 0.0)\n";
                }
        }

        // Test global getTestMatrix() from testsuite.hpp
        nrOfFailedTestCases += ReportTestResult(sw::blas::VerifyGlobalGetTestMatrix(reportTestCases), "testsuite.hpp", "getTestMatrix");

        // Test global kappa() from testsuite.hpp
        nrOfFailedTestCases += ReportTestResult(sw::blas::VerifyGlobalKappa(reportTestCases), "testsuite.hpp", "kappa");

        // Test matrix data values
        nrOfFailedTestCases += ReportTestResult(sw::blas::VerifyMatrixValues(reportTestCases), "matrices", "value verification");
#endif

#if REGRESSION_LEVEL_2
        {
                using namespace sw::numeric::containers;

                // Test loading a small matrix from file using sw::blas::getTestMatrix
                matrix<double> A = sw::blas::getTestMatrix("lambers_well");
                if (num_rows(A) == 2 && num_cols(A) == 2) {
                        if (reportTestCases) std::cout << "PASS: getTestMatrix(lambers_well) = 2x2\n";
                } else {
                        ++nrOfFailedTestCases;
                        if (reportTestCases) std::cout << "FAIL: getTestMatrix(lambers_well) = " << num_rows(A) << "x" << num_cols(A) << "\n";
                }

                // Test loading another matrix
                matrix<double> B = sw::blas::getTestMatrix("lu4");
                if (num_rows(B) == 4 && num_cols(B) == 4) {
                        if (reportTestCases) std::cout << "PASS: getTestMatrix(lu4) = 4x4\n";
                } else {
                        ++nrOfFailedTestCases;
                        if (reportTestCases) std::cout << "FAIL: getTestMatrix(lu4) = " << num_rows(B) << "x" << num_cols(B) << "\n";
                }

                // Test loading non-existent matrix (should return empty matrix)
                matrix<double> C = sw::blas::getTestMatrix("nonexistent_matrix");
                if (num_rows(C) == 0 && num_cols(C) == 0) {
                        if (reportTestCases) std::cout << "PASS: getTestMatrix(unknown) = 0x0 (expected)\n";
                } else {
                        ++nrOfFailedTestCases;
                        if (reportTestCases) std::cout << "FAIL: getTestMatrix(unknown) = " << num_rows(C) << "x" << num_cols(C) << "\n";
                }
        }

        // Test WriteMatrixDataFile function
        nrOfFailedTestCases += ReportTestResult(sw::blas::VerifyWriteMatrixDataFile(reportTestCases), "serialization", "WriteMatrixDataFile");

        // Compare file-loaded vs header-defined matrices
        nrOfFailedTestCases += ReportTestResult(sw::blas::VerifyFileVsHeaderMatrices(reportTestCases), "matrices", "file vs header comparison");
#endif

#if REGRESSION_LEVEL_3
        {
                using namespace sw::numeric::containers;

                // Test loading all matrices in TestMatrixList
                int loadedCount = 0;
                for (const auto& matrixName : sw::blas::TestMatrixList) {
                        matrix<double> M = sw::blas::getTestMatrix(matrixName);
                        if (num_rows(M) > 0 && num_cols(M) > 0) {
                                ++loadedCount;
                        } else {
                                ++nrOfFailedTestCases;
                                if (reportTestCases) std::cout << "FAIL: getTestMatrix(" << matrixName << ") load failed\n";
                        }
                }
                if (reportTestCases) std::cout << "Loaded " << loadedCount << "/" << sw::blas::TestMatrixList.size() << " matrices\n";
        }
#endif

#if REGRESSION_LEVEL_4
        {
                // Verify condition numbers are available for all matrices in TestMatrixList
                int kappaCount = 0;
                for (const auto& matrixName : sw::blas::TestMatrixList) {
                        double k = sw::blas::kappa(matrixName);
                        if (k > 0.0) {
                                ++kappaCount;
                        } else {
                                ++nrOfFailedTestCases;
                                if (reportTestCases) std::cout << "FAIL: kappa(" << matrixName << ") not found\n";
                        }
                }
                if (reportTestCases) std::cout << "Found kappa for " << kappaCount << "/" << sw::blas::TestMatrixList.size() << " matrices\n";
        }
#endif

        ReportTestSuiteResults(test_suite, nrOfFailedTestCases);
        return (nrOfFailedTestCases > 0 ? EXIT_FAILURE : EXIT_SUCCESS);
#endif
}
catch (char const* msg) {
        std::cerr << msg << std::endl;
        return EXIT_FAILURE;
}
catch (const sw::universal::universal_arithmetic_exception& err) {
        std::cerr << "Uncaught universal arithmetic exception: " << err.what() << std::endl;
        return EXIT_FAILURE;
}
catch (const sw::universal::universal_internal_exception& err) {
        std::cerr << "Uncaught universal internal exception: " << err.what() << std::endl;
        return EXIT_FAILURE;
}
catch (const std::runtime_error& err) {
        std::cerr << "Uncaught runtime exception: " << err.what() << std::endl;
        return EXIT_FAILURE;
}
catch (...) {
        std::cerr << "Caught unknown exception" << std::endl;
        return EXIT_FAILURE;
}

1	// test_matrices.cpp: convert test matrix include files to data files
2	//
3	// Copyright (C) 2017 Stillwater Supercomputing, Inc.
4	// SPDX-License-Identifier: MIT
5	//
6	// This file is part of the universal numbers project, which is released under an MIT Open Source license.
7	#include <universal/utility/directives.hpp>
8	#include <cmath>
9	#include <iostream>
10	#include <iomanip>
11	#include <fstream>
12
13	// Serialization - test_matrix.hpp reads matrices from .dat files
14	#include <blas/serialization/datafile.hpp>
15	#include <blas/serialization/test_matrix.hpp>
16
17	#include <universal/verification/test_suite.hpp>
18	#include <blas/matrices/testsuite.hpp>
19
20	namespace sw { namespace blas {
21	using namespace sw::numeric::containers;
22
23	static void WriteMatrixDataFile(const std::string& filename, const matrix<double>& A) {	×
24	std::ofstream fo;	×
25	fo.open(filename);	×
26	fo << A;	×
27	fo.close();	×
28	}	×
29
30	static void GenerateMatrixDataFiles(const std::vector<std::string>& testMatrixNames) {	×
31	for (auto matrixName : testMatrixNames) {	×
32	WriteMatrixDataFile(matrixName + std::string(".dat"), getTestMatrix(matrixName));	×
33	}	×
34	}	×
35
36	////////////////////////////////////////////////////////////////////////
37	// Test global getTestMatrix() from testsuite.hpp
38	int VerifyGlobalGetTestMatrix(bool reportTestCases) {	1✔
39	int nrOfFailedTests = 0;	1✔
40
41	// Test all available matrices from testsuite.hpp
42	std::vector<std::pair<std::string, std::pair<size_t, size_t>>> expectedDimensions = {
NEW 43	{"lambers_well", {2, 2}},	×
NEW 44	{"lambers_ill", {2, 2}},	×
NEW 45	{"h3", {3, 3}},	×
NEW 46	{"q3", {3, 3}},	×
NEW 47	{"int3", {3, 3}},	×
NEW 48	{"faires74x3", {3, 3}},	×
NEW 49	{"q4", {4, 4}},	×
NEW 50	{"lu4", {4, 4}},	×
NEW 51	{"s4", {4, 4}},	×
NEW 52	{"rand4", {4, 4}},	×
NEW 53	{"q5", {5, 5}},	×
NEW 54	{"b1_ss", {7, 7}},	×
NEW 55	{"cage3", {5, 5}},	×
NEW 56	{"pores_1", {30, 30}},	×
NEW 57	{"Stranke94", {10, 10}},	×
NEW 58	{"Trefethen_20", {20, 20}}	×
59	};	19✔
60
61	for (const auto& entry : expectedDimensions) {	17✔
62	const std::string& name = entry.first;	16✔
63	size_t expectedRows = entry.second.first;	16✔
64	size_t expectedCols = entry.second.second;	16✔
65
66	// Use global getTestMatrix (from testsuite.hpp)
67	matrix<double> M = ::getTestMatrix(name);	16✔
68
69	if (num_rows(M) != expectedRows \|\| num_cols(M) != expectedCols) {	16✔
NEW 70	++nrOfFailedTests;	×
NEW 71	if (reportTestCases) std::cerr << "FAIL: global getTestMatrix(" << name << ") = "	×
NEW 72	<< num_rows(M) << "x" << num_cols(M)	×
NEW 73	<< " (expected " << expectedRows << "x" << expectedCols << ")\n";	×
74	}
75	}	16✔
76
77	// Test unknown matrix returns default (lu4)
78	matrix<double> unknown = ::getTestMatrix("unknown_matrix_xyz");	1✔
79	if (num_rows(unknown) != 4 \|\| num_cols(unknown) != 4) {	1✔
NEW 80	++nrOfFailedTests;	×
NEW 81	if (reportTestCases) std::cerr << "FAIL: global getTestMatrix(unknown) should return lu4 (4x4)\n";	×
82	}
83
84	return nrOfFailedTests;	1✔
85	}	5✔
86
87	////////////////////////////////////////////////////////////////////////
88	// Test global kappa() from testsuite.hpp
89	int VerifyGlobalKappa(bool reportTestCases) {	1✔
90	int nrOfFailedTests = 0;	1✔
91
92	// Test known condition numbers
93	std::vector<std::pair<std::string, double>> expectedKappa = {
NEW 94	{"lambers_well", 10.0},	×
NEW 95	{"lambers_ill", 1.869050824603144e+08},	×
NEW 96	{"h3", 1.8478e+11},	×
NEW 97	{"q3", 1.2857e+06},	×
NEW 98	{"int3", 43.6115},	×
NEW 99	{"faires74x3", 15999},	×
NEW 100	{"q4", 2.35},	×
NEW 101	{"lu4", 11.6810},	×
NEW 102	{"s4", 4.19},	×
NEW 103	{"rand4", 27.81},	×
NEW 104	{"q5", 1.1e+04},	×
NEW 105	{"b1_ss", 1.973732e+02},	×
NEW 106	{"cage3", 1.884547e+01},	×
NEW 107	{"pores_1", 1.812616e+06},	×
NEW 108	{"Stranke94", 5.173300e+01},	×
NEW 109	{"Trefethen_20", 6.308860e+01}	×
110	};	18✔
111
112	for (const auto& entry : expectedKappa) {	17✔
113	const std::string& name = entry.first;	16✔
114	double expected = entry.second;	16✔
115
116	// Use global kappa (from testsuite.hpp)
117	double k = ::kappa(name);	16✔
118
119	// Use relative tolerance for comparison
120	double relError = std::abs(k - expected) / expected;	16✔
121	if (relError > 0.001) {	16✔
NEW 122	++nrOfFailedTests;	×
NEW 123	if (reportTestCases) std::cerr << "FAIL: global kappa(" << name << ") = " << k	×
NEW 124	<< " (expected " << expected << ")\n";	×
125	}
126	}
127
128	// Test unknown matrix returns default (lu4's kappa)
129	double unknownK = ::kappa("unknown_matrix_xyz");	1✔
130	if (std::abs(unknownK - 11.6810) > 0.01) {	1✔
NEW 131	++nrOfFailedTests;	×
NEW 132	if (reportTestCases) std::cerr << "FAIL: global kappa(unknown) should return 11.6810\n";	×
133	}
134
135	return nrOfFailedTests;	1✔
136	}	2✔
137
138	////////////////////////////////////////////////////////////////////////
139	// Test matrix data values (not just dimensions)
140	int VerifyMatrixValues(bool reportTestCases) {	1✔
141	int nrOfFailedTests = 0;	1✔
142
143	// Test lambers_well matrix values
144	// lambers_well = [[1, 2], [3, 4]] or similar known values
145	{
146	matrix<double> A = ::getTestMatrix("lambers_well");	1✔
147	if (num_rows(A) >= 2 && num_cols(A) >= 2) {	1✔
148	// Just verify the matrix has non-zero values
149	bool hasNonZero = false;	1✔
150	for (size_t i = 0; i < num_rows(A) && !hasNonZero; ++i) {	2✔
151	for (size_t j = 0; j < num_cols(A) && !hasNonZero; ++j) {	2✔
152	if (A[i][j] != 0.0) hasNonZero = true;	1✔
153	}
154	}
155	if (!hasNonZero) {	1✔
NEW 156	++nrOfFailedTests;	×
NEW 157	if (reportTestCases) std::cerr << "FAIL: lambers_well has all zero values\n";	×
158	}
159	}
160	}	1✔
161
162	// Test lu4 matrix values
163	{
164	matrix<double> A = ::getTestMatrix("lu4");	1✔
165	if (num_rows(A) == 4 && num_cols(A) == 4) {	1✔
166	// Verify diagonal has non-zero values (for LU decomposition test matrices)
167	bool diagonalOK = true;	1✔
168	for (size_t i = 0; i < 4; ++i) {	5✔
169	if (A[i][i] == 0.0) diagonalOK = false;	4✔
170	}
171	if (!diagonalOK) {	1✔
NEW 172	++nrOfFailedTests;	×
NEW 173	if (reportTestCases) std::cerr << "FAIL: lu4 diagonal should be non-zero\n";	×
174	}
175	}
176	}	1✔
177
178	return nrOfFailedTests;	1✔
179	}
180
181	////////////////////////////////////////////////////////////////////////
182	// Test WriteMatrixDataFile function
NEW 183	int VerifyWriteMatrixDataFile(bool reportTestCases) {	×
NEW 184	int nrOfFailedTests = 0;	×
185
186	// Create a small test matrix
NEW 187	matrix<double> A(3, 3);	×
NEW 188	A[0][0] = 1.0; A[0][1] = 2.0; A[0][2] = 3.0;	×
NEW 189	A[1][0] = 4.0; A[1][1] = 5.0; A[1][2] = 6.0;	×
NEW 190	A[2][0] = 7.0; A[2][1] = 8.0; A[2][2] = 9.0;	×
191
192	// Write to temporary file
NEW 193	std::string tempFile = "/tmp/test_matrix_write.dat";	×
NEW 194	WriteMatrixDataFile(tempFile, A);	×
195
196	// Read back and verify
NEW 197	matrix<double> B;	×
NEW 198	std::ifstream fi(tempFile);	×
NEW 199	if (fi.good()) {	×
NEW 200	fi >> B;	×
NEW 201	fi.close();	×
202
NEW 203	if (num_rows(B) != 3 \|\| num_cols(B) != 3) {	×
NEW 204	++nrOfFailedTests;	×
NEW 205	if (reportTestCases) std::cerr << "FAIL: read back matrix has wrong dimensions\n";	×
206	} else {
207	// Verify values
NEW 208	for (size_t i = 0; i < 3; ++i) {	×
NEW 209	for (size_t j = 0; j < 3; ++j) {	×
NEW 210	if (std::abs(A[i][j] - B[i][j]) > 0.0001) {	×
NEW 211	++nrOfFailedTests;	×
NEW 212	if (reportTestCases) std::cerr << "FAIL: matrix value mismatch at [" << i << "][" << j << "]\n";	×
213	}
214	}
215	}
216	}
217	} else {
NEW 218	++nrOfFailedTests;	×
NEW 219	if (reportTestCases) std::cerr << "FAIL: could not read back written matrix file\n";	×
220	}
221
222	// Clean up
NEW 223	std::remove(tempFile.c_str());	×
224
NEW 225	return nrOfFailedTests;	×
NEW 226	}	×
227
228	////////////////////////////////////////////////////////////////////////
229	// Compare file-loaded matrix with header-defined matrix
NEW 230	int VerifyFileVsHeaderMatrices(bool reportTestCases) {	×
NEW 231	int nrOfFailedTests = 0;	×
232
233	// Compare matrices that are available in both formats
234	std::vector<std::string> matricesToCompare = {
235	"lambers_well",
236	"lambers_ill",
237	"lu4",
238	"q4"
NEW 239	};	×
240
NEW 241	for (const auto& name : matricesToCompare) {	×
242	// Get from header (global function)
NEW 243	matrix<double> fromHeader = ::getTestMatrix(name);	×
244
245	// Get from file (sw::blas function)
NEW 246	matrix<double> fromFile = sw::blas::getTestMatrix(name);	×
247
NEW 248	if (num_rows(fromFile) == 0 \|\| num_cols(fromFile) == 0) {	×
249	// File doesn't exist, skip comparison
NEW 250	continue;	×
251	}
252
NEW 253	if (num_rows(fromHeader) != num_rows(fromFile) \|\| num_cols(fromHeader) != num_cols(fromFile)) {	×
NEW 254	++nrOfFailedTests;	×
NEW 255	if (reportTestCases) std::cerr << "FAIL: " << name << " dimension mismatch between header and file\n";	×
NEW 256	continue;	×
257	}
258
259	// Compare values
NEW 260	double maxError = 0.0;	×
NEW 261	for (size_t i = 0; i < num_rows(fromHeader); ++i) {	×
NEW 262	for (size_t j = 0; j < num_cols(fromHeader); ++j) {	×
NEW 263	double err = std::abs(fromHeader[i][j] - fromFile[i][j]);	×
NEW 264	if (err > maxError) maxError = err;	×
265	}
266	}
267
268	// Allow for floating-point serialization differences (file stores limited precision)
NEW 269	if (maxError > 1e-5) {	×
NEW 270	++nrOfFailedTests;	×
NEW 271	if (reportTestCases) std::cerr << "FAIL: " << name << " value mismatch (max error: " << maxError << ")\n";	×
272	}
NEW 273	}	×
274
NEW 275	return nrOfFailedTests;	×
NEW 276	}	×
277
278	} }
279
280	// This is a program that we ran once to get the test matrices converted to data files
281	//
282	// We have no code in the regression side of the test so CI is a NOP
283
284
285	// Regression testing guards: typically set by the cmake configuration, but MANUAL_TESTING is an override
286	#define MANUAL_TESTING 0
287	// REGRESSION_LEVEL_OVERRIDE is set by the cmake file to drive a specific regression intensity
288	// It is the responsibility of the regression test to organize the tests in a quartile progression.
289	//#undef REGRESSION_LEVEL_OVERRIDE
290	#ifndef REGRESSION_LEVEL_OVERRIDE
291	#undef REGRESSION_LEVEL_1
292	#undef REGRESSION_LEVEL_2
293	#undef REGRESSION_LEVEL_3
294	#undef REGRESSION_LEVEL_4
295	#define REGRESSION_LEVEL_1 1
296	#define REGRESSION_LEVEL_2 1
297	#define REGRESSION_LEVEL_3 1
298	#define REGRESSION_LEVEL_4 1
299	#endif
300
301	int main()	1✔
302	try {
303	using namespace sw::universal;
304	using namespace sw::blas;
305
306	std::string test_suite = "test matrices serialization";	2✔
307	std::string test_tag = "test_matrices";	1✔
308	bool reportTestCases = true;	1✔
309	int nrOfFailedTestCases = 0;	1✔
310
311	ReportTestSuiteHeader(test_suite, reportTestCases);	1✔
312
313	#if MANUAL_TESTING
314
315	// set up the set of test matrices
316	std::vector<std::string> allTestMatrices = {
317	"lambers_well", // 2 x 2 well-conditioned matrix, K = 10.0
318	"lambers_ill", // 2 x 2 ill-conditioned matrix, K = 1.869050824603144e+08
319	"h3", // 3 x 3 test matrix, K = 1.8478e+11
320	"int3", // 3 x 3 integer test matrix (low condition number), K = 43.6115
321	"faires74x3", // 3 x 3 Burden Faires Ill-conditioned, K = 15999
322	"q3", // 3 x 3 Variable test matrix (edit entries), K = 1.2857e+06
323	"q4", // 4 x 4 test matrix, K = 2.35
324	"q5", // 5 x 5 test matrix, K = 1.1e+04
325	"lu4", // 4 x 4 test matrix, K = 11.6810
326	"s4", // 4 x 4 test matrix, K = 4.19
327	"rand4", // 4 x 4 random (low condition), K = 27.81
328	"cage3", // 5 x 5 Directed Weighted Graph, K = 1.884547e+01
329	"b1_ss", // 7 x 7 Chemical Process Simulation Problem, K = 1.973732e+02
330
331	"west0132", // 132 x 132 Chem. Simulation Process, K = 4.2e+11
332	"west0167", // 167 x 167 Chemical Simulation Process, K = 2.827e+07
333	"steam1", // 240 x 240 Computational Fluid Dynamics, K = 2.827501e+07
334	"steam3", // 83 x 83 Computational Fluid Dynamics, K = 5.51e+10
335	"fs_183_1", // 183 x 183 2D/3D Problem Sequence, K = 1.5129e+13
336	"fs_183_3", // 183 x 183 2D/3D Problem Sequence, K = 1.5129e+13
337	"bwm200", // 200 x 200 Chemical simulation, K = 2.412527e+03
338	"gre_343", // 343 x 343 Directed Weighted Graph, K = 1.119763e+02
339	"pores_1", // 30 x 30 Computational Fluid Dynamics, K = 1.812616e+06
340	"Stranke94", // 10 x 10 Undirected Weighted Graph, K = 5.173300e+01
341	"Trefethen_20", // 20 x 20 Combinatorial Problem, K = 6.308860e+01
342	"bcsstk01", // 48 x 48 Structural Engineering, K = 8.8234e+05
343	"bcsstk03", // 112 x 112 Structural Engineering, K = 6.791333e+06
344	"bcsstk04", // 132 x 132 Structural Engineering, K = 2.292466e+06
345	"bcsstk05", // 153 x 153 Structural Engineering, K = 1.428114e+04
346	"bcsstk22", // 138 x 138 Structural Engineering, K = 1.107165e+05
347	"lund_a", // 147 x 147 Structural Engineering, K = 2.796948e+06
348	"nos1", // 237 x 237 Structural Engineering K = 1.991546e+07
349	"arc130", // 130 x 130 K = 6.0542e+10
350	"saylr1", // 238 x 238 Computational Fluid Dynamics, K = 7.780581e+08
351	"tumorAntiAngiogenesis_2" // , K 1.9893e+10
352	};
353	GenerateMatrixDataFiles(allTestMatrices);
354
355	ReportTestSuiteResults(test_suite, nrOfFailedTestCases);
356	return EXIT_SUCCESS;
357	#else
358	// Test the serialization/test_matrix.hpp functionality
359	// Note: sw::blas::getTestMatrix() reads from .dat files (different from global getTestMatrix())
360	#if REGRESSION_LEVEL_1
361	{
362	// Test dataDirectory()
363	std::string dataDir = sw::blas::dataDirectory();	1✔
364	if (dataDir.empty()) {	1✔
NEW 365	++nrOfFailedTestCases;	×
NEW 366	if (reportTestCases) std::cout << "FAIL: dataDirectory() returned empty\n";	×
367	} else {
368	if (reportTestCases) std::cout << "PASS: dataDirectory() = " << dataDir << "\n";	1✔
369	}
370
371	// Test TestMatrixList is populated
372	if (sw::blas::TestMatrixList.empty()) {	1✔
NEW 373	++nrOfFailedTestCases;	×
NEW 374	if (reportTestCases) std::cout << "FAIL: TestMatrixList is empty\n";	×
375	} else {
376	if (reportTestCases) std::cout << "PASS: TestMatrixList has " << sw::blas::TestMatrixList.size() << " matrices\n";	1✔
377	}
378
379	// Test ConditionNumber map is populated
380	if (sw::blas::ConditionNumber.empty()) {	1✔
NEW 381	++nrOfFailedTestCases;	×
NEW 382	if (reportTestCases) std::cout << "FAIL: ConditionNumber map is empty\n";	×
383	} else {
384	if (reportTestCases) std::cout << "PASS: ConditionNumber map has " << sw::blas::ConditionNumber.size() << " entries\n";	1✔
385	}
386
387	// Test kappa() for known matrices (from serialization module)
388	double k = sw::blas::kappa("lambers_well");	1✔
389	if (std::abs(k - 10.0) < 0.001) {	1✔
390	if (reportTestCases) std::cout << "PASS: kappa(lambers_well) = " << k << "\n";	1✔
391	} else {
NEW 392	++nrOfFailedTestCases;	×
NEW 393	if (reportTestCases) std::cout << "FAIL: kappa(lambers_well) = " << k << " (expected 10.0)\n";	×
394	}
395
396	// Test kappa() for unknown matrix (should return 0.0 and print error)
397	double unknownK = sw::blas::kappa("nonexistent_matrix");	1✔
398	if (unknownK == 0.0) {	1✔
399	if (reportTestCases) std::cout << "PASS: kappa(unknown) = 0.0 (expected)\n";	1✔
400	} else {
NEW 401	++nrOfFailedTestCases;	×
NEW 402	if (reportTestCases) std::cout << "FAIL: kappa(unknown) = " << unknownK << " (expected 0.0)\n";	×
403	}
404	}	1✔
405
406	// Test global getTestMatrix() from testsuite.hpp
407	nrOfFailedTestCases += ReportTestResult(sw::blas::VerifyGlobalGetTestMatrix(reportTestCases), "testsuite.hpp", "getTestMatrix");	4✔
408
409	// Test global kappa() from testsuite.hpp
410	nrOfFailedTestCases += ReportTestResult(sw::blas::VerifyGlobalKappa(reportTestCases), "testsuite.hpp", "kappa");	4✔
411
412	// Test matrix data values
413	nrOfFailedTestCases += ReportTestResult(sw::blas::VerifyMatrixValues(reportTestCases), "matrices", "value verification");	3✔
414	#endif
415
416	#if REGRESSION_LEVEL_2
417	{
418	using namespace sw::numeric::containers;
419
420	// Test loading a small matrix from file using sw::blas::getTestMatrix
421	matrix<double> A = sw::blas::getTestMatrix("lambers_well");
422	if (num_rows(A) == 2 && num_cols(A) == 2) {
423	if (reportTestCases) std::cout << "PASS: getTestMatrix(lambers_well) = 2x2\n";
424	} else {
425	++nrOfFailedTestCases;
426	if (reportTestCases) std::cout << "FAIL: getTestMatrix(lambers_well) = " << num_rows(A) << "x" << num_cols(A) << "\n";
427	}
428
429	// Test loading another matrix
430	matrix<double> B = sw::blas::getTestMatrix("lu4");
431	if (num_rows(B) == 4 && num_cols(B) == 4) {
432	if (reportTestCases) std::cout << "PASS: getTestMatrix(lu4) = 4x4\n";
433	} else {
434	++nrOfFailedTestCases;
435	if (reportTestCases) std::cout << "FAIL: getTestMatrix(lu4) = " << num_rows(B) << "x" << num_cols(B) << "\n";
436	}
437
438	// Test loading non-existent matrix (should return empty matrix)
439	matrix<double> C = sw::blas::getTestMatrix("nonexistent_matrix");
440	if (num_rows(C) == 0 && num_cols(C) == 0) {
441	if (reportTestCases) std::cout << "PASS: getTestMatrix(unknown) = 0x0 (expected)\n";
442	} else {
443	++nrOfFailedTestCases;
444	if (reportTestCases) std::cout << "FAIL: getTestMatrix(unknown) = " << num_rows(C) << "x" << num_cols(C) << "\n";
445	}
446	}
447
448	// Test WriteMatrixDataFile function
449	nrOfFailedTestCases += ReportTestResult(sw::blas::VerifyWriteMatrixDataFile(reportTestCases), "serialization", "WriteMatrixDataFile");
450
451	// Compare file-loaded vs header-defined matrices
452	nrOfFailedTestCases += ReportTestResult(sw::blas::VerifyFileVsHeaderMatrices(reportTestCases), "matrices", "file vs header comparison");
453	#endif
454
455	#if REGRESSION_LEVEL_3
456	{
457	using namespace sw::numeric::containers;
458
459	// Test loading all matrices in TestMatrixList
460	int loadedCount = 0;
461	for (const auto& matrixName : sw::blas::TestMatrixList) {
462	matrix<double> M = sw::blas::getTestMatrix(matrixName);
463	if (num_rows(M) > 0 && num_cols(M) > 0) {
464	++loadedCount;
465	} else {
466	++nrOfFailedTestCases;
467	if (reportTestCases) std::cout << "FAIL: getTestMatrix(" << matrixName << ") load failed\n";
468	}
469	}
470	if (reportTestCases) std::cout << "Loaded " << loadedCount << "/" << sw::blas::TestMatrixList.size() << " matrices\n";
471	}
472	#endif
473
474	#if REGRESSION_LEVEL_4
475	{
476	// Verify condition numbers are available for all matrices in TestMatrixList
477	int kappaCount = 0;
478	for (const auto& matrixName : sw::blas::TestMatrixList) {
479	double k = sw::blas::kappa(matrixName);
480	if (k > 0.0) {
481	++kappaCount;
482	} else {
483	++nrOfFailedTestCases;
484	if (reportTestCases) std::cout << "FAIL: kappa(" << matrixName << ") not found\n";
485	}
486	}
487	if (reportTestCases) std::cout << "Found kappa for " << kappaCount << "/" << sw::blas::TestMatrixList.size() << " matrices\n";
488	}
489	#endif
490
491	ReportTestSuiteResults(test_suite, nrOfFailedTestCases);	1✔
492	return (nrOfFailedTestCases > 0 ? EXIT_FAILURE : EXIT_SUCCESS);	1✔
493	#endif
494	}	1✔
495	catch (char const* msg) {	×
496	std::cerr << msg << std::endl;	×
497	return EXIT_FAILURE;	×
498	}	×
499	catch (const sw::universal::universal_arithmetic_exception& err) {	×
500	std::cerr << "Uncaught universal arithmetic exception: " << err.what() << std::endl;	×
501	return EXIT_FAILURE;	×
502	}	×
503	catch (const sw::universal::universal_internal_exception& err) {	×
504	std::cerr << "Uncaught universal internal exception: " << err.what() << std::endl;	×
505	return EXIT_FAILURE;	×
506	}	×
507	catch (const std::runtime_error& err) {	×
508	std::cerr << "Uncaught runtime exception: " << err.what() << std::endl;	×
509	return EXIT_FAILURE;	×
510	}	×
511	catch (...) {	×
512	std::cerr << "Caught unknown exception" << std::endl;	×
513	return EXIT_FAILURE;	×
514	}	×

stillwater-sc / universal / 21373593817

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