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ADD: added other eigen lib

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This commit is contained in:
Henry Winkel
2022-12-21 16:19:04 +01:00
parent a570766dc6
commit 9e56c7f2c0
832 changed files with 36586 additions and 20006 deletions
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140
libs/eigen/unsupported/test/NonLinearOptimization.cpp
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@@ -12,14 +12,10 @@
// It is intended to be done for this test only.
#include <Eigen/src/Core/util/DisableStupidWarnings.h>
// tolerance for chekcing number of iterations
#define LM_EVAL_COUNT_TOL 4/3
// tolerance for checking number of iterations
#define LM_EVAL_COUNT_TOL 2
#define LM_CHECK_N_ITERS(SOLVER,NFEV,NJEV) { \
++g_test_level; \
VERIFY_IS_EQUAL(SOLVER.nfev, NFEV); \
VERIFY_IS_EQUAL(SOLVER.njev, NJEV); \
--g_test_level; \
VERIFY(SOLVER.nfev <= NFEV * LM_EVAL_COUNT_TOL); \
VERIFY(SOLVER.njev <= NJEV * LM_EVAL_COUNT_TOL); \
}
@@ -113,10 +109,10 @@ void testChkder()
}
// Generic functor
template<typename _Scalar, int NX=Dynamic, int NY=Dynamic>
template<typename Scalar_, int NX=Dynamic, int NY=Dynamic>
struct Functor
{
typedef _Scalar Scalar;
typedef Scalar_ Scalar;
enum {
InputsAtCompileTime = NX,
ValuesAtCompileTime = NY
@@ -186,9 +182,10 @@ void testLmder1()
lmder_functor functor;
LevenbergMarquardt<lmder_functor> lm(functor);
info = lm.lmder1(x);
EIGEN_UNUSED_VARIABLE(info)
// check return value
VERIFY_IS_EQUAL(info, 1);
// VERIFY_IS_EQUAL(info, 1);
LM_CHECK_N_ITERS(lm, 6, 5);
// check norm
@@ -214,9 +211,10 @@ void testLmder()
lmder_functor functor;
LevenbergMarquardt<lmder_functor> lm(functor);
info = lm.minimize(x);
EIGEN_UNUSED_VARIABLE(info)
// check return values
VERIFY_IS_EQUAL(info, 1);
// VERIFY_IS_EQUAL(info, 1);
LM_CHECK_N_ITERS(lm, 6, 5);
// check norm
@@ -298,9 +296,10 @@ void testHybrj1()
hybrj_functor functor;
HybridNonLinearSolver<hybrj_functor> solver(functor);
info = solver.hybrj1(x);
EIGEN_UNUSED_VARIABLE(info)
// check return value
VERIFY_IS_EQUAL(info, 1);
// VERIFY_IS_EQUAL(info, 1);
LM_CHECK_N_ITERS(solver, 11, 1);
// check norm
@@ -332,9 +331,10 @@ void testHybrj()
solver.diag.setConstant(n, 1.);
solver.useExternalScaling = true;
info = solver.solve(x);
EIGEN_UNUSED_VARIABLE(info)
// check return value
VERIFY_IS_EQUAL(info, 1);
// VERIFY_IS_EQUAL(info, 1);
LM_CHECK_N_ITERS(solver, 11, 1);
// check norm
@@ -385,10 +385,11 @@ void testHybrd1()
hybrd_functor functor;
HybridNonLinearSolver<hybrd_functor> solver(functor);
info = solver.hybrd1(x);
EIGEN_UNUSED_VARIABLE(info)
// check return value
VERIFY_IS_EQUAL(info, 1);
VERIFY_IS_EQUAL(solver.nfev, 20);
// VERIFY_IS_EQUAL(info, 1);
VERIFY(solver.nfev <= 20*LM_EVAL_COUNT_TOL);
// check norm
VERIFY_IS_APPROX(solver.fvec.blueNorm(), 1.192636e-08);
@@ -416,10 +417,11 @@ void testHybrd()
solver.diag.setConstant(n, 1.);
solver.useExternalScaling = true;
info = solver.solveNumericalDiff(x);
EIGEN_UNUSED_VARIABLE(info)
// check return value
VERIFY_IS_EQUAL(info, 1);
VERIFY_IS_EQUAL(solver.nfev, 14);
// VERIFY_IS_EQUAL(info, 1);
VERIFY(solver.nfev <= 14*LM_EVAL_COUNT_TOL);
// check norm
VERIFY_IS_APPROX(solver.fvec.blueNorm(), 1.192636e-08);
@@ -487,9 +489,10 @@ void testLmstr1()
lmstr_functor functor;
LevenbergMarquardt<lmstr_functor> lm(functor);
info = lm.lmstr1(x);
EIGEN_UNUSED_VARIABLE(info)
// check return value
VERIFY_IS_EQUAL(info, 1);
// VERIFY_IS_EQUAL(info, 1);
LM_CHECK_N_ITERS(lm, 6, 5);
// check norm
@@ -515,9 +518,10 @@ void testLmstr()
lmstr_functor functor;
LevenbergMarquardt<lmstr_functor> lm(functor);
info = lm.minimizeOptimumStorage(x);
EIGEN_UNUSED_VARIABLE(info)
// check return values
VERIFY_IS_EQUAL(info, 1);
// VERIFY_IS_EQUAL(info, 1);
LM_CHECK_N_ITERS(lm, 6, 5);
// check norm
@@ -570,10 +574,11 @@ void testLmdif1()
lmdif_functor functor;
DenseIndex nfev = -1; // initialize to avoid maybe-uninitialized warning
info = LevenbergMarquardt<lmdif_functor>::lmdif1(functor, x, &nfev);
EIGEN_UNUSED_VARIABLE(info)
// check return value
VERIFY_IS_EQUAL(info, 1);
VERIFY_IS_EQUAL(nfev, 26);
// VERIFY_IS_EQUAL(info, 1);
VERIFY( nfev <= 26*LM_EVAL_COUNT_TOL);
// check norm
functor(x, fvec);
@@ -601,10 +606,11 @@ void testLmdif()
NumericalDiff<lmdif_functor> numDiff(functor);
LevenbergMarquardt<NumericalDiff<lmdif_functor> > lm(numDiff);
info = lm.minimize(x);
EIGEN_UNUSED_VARIABLE(info)
// check return values
VERIFY_IS_EQUAL(info, 1);
VERIFY_IS_EQUAL(lm.nfev, 26);
// VERIFY_IS_EQUAL(info, 1);
VERIFY(lm.nfev <= 26*LM_EVAL_COUNT_TOL);
// check norm
fnorm = lm.fvec.blueNorm();
@@ -686,9 +692,10 @@ void testNistChwirut2(void)
chwirut2_functor functor;
LevenbergMarquardt<chwirut2_functor> lm(functor);
info = lm.minimize(x);
EIGEN_UNUSED_VARIABLE(info)
// check return value
VERIFY_IS_EQUAL(info, 1);
// VERIFY_IS_EQUAL(info, 1);
LM_CHECK_N_ITERS(lm, 10, 8);
// check norm^2
VERIFY_IS_APPROX(lm.fvec.squaredNorm(), 5.1304802941E+02);
@@ -706,9 +713,10 @@ void testNistChwirut2(void)
lm.parameters.ftol = 1.E6*NumTraits<double>::epsilon();
lm.parameters.xtol = 1.E6*NumTraits<double>::epsilon();
info = lm.minimize(x);
EIGEN_UNUSED_VARIABLE(info)
// check return value
VERIFY_IS_EQUAL(info, 1);
// VERIFY_IS_EQUAL(info, 1);
LM_CHECK_N_ITERS(lm, 7, 6);
// check norm^2
VERIFY_IS_APPROX(lm.fvec.squaredNorm(), 5.1304802941E+02);
@@ -764,9 +772,10 @@ void testNistMisra1a(void)
misra1a_functor functor;
LevenbergMarquardt<misra1a_functor> lm(functor);
info = lm.minimize(x);
EIGEN_UNUSED_VARIABLE(info)
// check return value
VERIFY_IS_EQUAL(info, 1);
// VERIFY_IS_EQUAL(info, 1);
LM_CHECK_N_ITERS(lm, 19, 15);
// check norm^2
VERIFY_IS_APPROX(lm.fvec.squaredNorm(), 1.2455138894E-01);
@@ -780,9 +789,10 @@ void testNistMisra1a(void)
x<< 250., 0.0005;
// do the computation
info = lm.minimize(x);
EIGEN_UNUSED_VARIABLE(info)
// check return value
VERIFY_IS_EQUAL(info, 1);
// VERIFY_IS_EQUAL(info, 1);
LM_CHECK_N_ITERS(lm, 5, 4);
// check norm^2
VERIFY_IS_APPROX(lm.fvec.squaredNorm(), 1.2455138894E-01);
@@ -852,9 +862,10 @@ void testNistHahn1(void)
hahn1_functor functor;
LevenbergMarquardt<hahn1_functor> lm(functor);
info = lm.minimize(x);
EIGEN_UNUSED_VARIABLE(info)
// check return value
VERIFY_IS_EQUAL(info, 1);
// VERIFY_IS_EQUAL(info, 1);
LM_CHECK_N_ITERS(lm, 11, 10);
// check norm^2
VERIFY_IS_APPROX(lm.fvec.squaredNorm(), 1.5324382854E+00);
@@ -873,9 +884,10 @@ void testNistHahn1(void)
x<< .1, -.1, .005, -.000001, -.005, .0001, -.0000001;
// do the computation
info = lm.minimize(x);
EIGEN_UNUSED_VARIABLE(info)
// check return value
VERIFY_IS_EQUAL(info, 1);
// VERIFY_IS_EQUAL(info, 1);
LM_CHECK_N_ITERS(lm, 11, 10);
// check norm^2
VERIFY_IS_APPROX(lm.fvec.squaredNorm(), 1.5324382854E+00);
@@ -936,9 +948,10 @@ void testNistMisra1d(void)
misra1d_functor functor;
LevenbergMarquardt<misra1d_functor> lm(functor);
info = lm.minimize(x);
EIGEN_UNUSED_VARIABLE(info)
// check return value
VERIFY_IS_EQUAL(info, 3);
// VERIFY_IS_EQUAL(info, 3);
LM_CHECK_N_ITERS(lm, 9, 7);
// check norm^2
VERIFY_IS_APPROX(lm.fvec.squaredNorm(), 5.6419295283E-02);
@@ -952,9 +965,10 @@ void testNistMisra1d(void)
x<< 450., 0.0003;
// do the computation
info = lm.minimize(x);
EIGEN_UNUSED_VARIABLE(info)
// check return value
VERIFY_IS_EQUAL(info, 1);
// VERIFY_IS_EQUAL(info, 1);
LM_CHECK_N_ITERS(lm, 4, 3);
// check norm^2
VERIFY_IS_APPROX(lm.fvec.squaredNorm(), 5.6419295283E-02);
@@ -1012,13 +1026,14 @@ void testNistLanczos1(void)
lanczos1_functor functor;
LevenbergMarquardt<lanczos1_functor> lm(functor);
info = lm.minimize(x);
EIGEN_UNUSED_VARIABLE(info)
// check return value
VERIFY_IS_EQUAL(info, 2);
// VERIFY_IS_EQUAL(info, 2);
LM_CHECK_N_ITERS(lm, 79, 72);
// check norm^2
std::cout.precision(30);
std::cout << lm.fvec.squaredNorm() << "\n";
// std::cout.precision(30);
// std::cout << lm.fvec.squaredNorm() << "\n";
VERIFY(lm.fvec.squaredNorm() <= 1.4307867721E-25);
// check x
VERIFY_IS_APPROX(x[0], 9.5100000027E-02);
@@ -1034,9 +1049,10 @@ void testNistLanczos1(void)
x<< 0.5, 0.7, 3.6, 4.2, 4., 6.3;
// do the computation
info = lm.minimize(x);
EIGEN_UNUSED_VARIABLE(info)
// check return value
VERIFY_IS_EQUAL(info, 2);
// VERIFY_IS_EQUAL(info, 2);
LM_CHECK_N_ITERS(lm, 9, 8);
// check norm^2
VERIFY(lm.fvec.squaredNorm() <= 1.4307867721E-25);
@@ -1098,9 +1114,10 @@ void testNistRat42(void)
rat42_functor functor;
LevenbergMarquardt<rat42_functor> lm(functor);
info = lm.minimize(x);
EIGEN_UNUSED_VARIABLE(info)
// check return value
VERIFY_IS_EQUAL(info, 1);
// VERIFY_IS_EQUAL(info, 1);
LM_CHECK_N_ITERS(lm, 10, 8);
// check norm^2
VERIFY_IS_APPROX(lm.fvec.squaredNorm(), 8.0565229338E+00);
@@ -1115,9 +1132,10 @@ void testNistRat42(void)
x<< 75., 2.5, 0.07;
// do the computation
info = lm.minimize(x);
EIGEN_UNUSED_VARIABLE(info)
// check return value
VERIFY_IS_EQUAL(info, 1);
// VERIFY_IS_EQUAL(info, 1);
LM_CHECK_N_ITERS(lm, 6, 5);
// check norm^2
VERIFY_IS_APPROX(lm.fvec.squaredNorm(), 8.0565229338E+00);
@@ -1174,9 +1192,10 @@ void testNistMGH10(void)
MGH10_functor functor;
LevenbergMarquardt<MGH10_functor> lm(functor);
info = lm.minimize(x);
EIGEN_UNUSED_VARIABLE(info)
// check return value
VERIFY_IS_EQUAL(info, 2);
// VERIFY_IS_EQUAL(info, 2);
LM_CHECK_N_ITERS(lm, 284, 249);
// check norm^2
VERIFY_IS_APPROX(lm.fvec.squaredNorm(), 8.7945855171E+01);
@@ -1191,9 +1210,10 @@ void testNistMGH10(void)
x<< 0.02, 4000., 250.;
// do the computation
info = lm.minimize(x);
EIGEN_UNUSED_VARIABLE(info)
// check return value
VERIFY_IS_EQUAL(info, 3);
// VERIFY_IS_EQUAL(info, 3);
LM_CHECK_N_ITERS(lm, 126, 116);
// check norm^2
VERIFY_IS_APPROX(lm.fvec.squaredNorm(), 8.7945855171E+01);
@@ -1251,9 +1271,10 @@ void testNistBoxBOD(void)
lm.parameters.xtol = 1.E6*NumTraits<double>::epsilon();
lm.parameters.factor = 10.;
info = lm.minimize(x);
EIGEN_UNUSED_VARIABLE(info)
// check return value
VERIFY_IS_EQUAL(info, 1);
// VERIFY_IS_EQUAL(info, 1);
LM_CHECK_N_ITERS(lm, 31, 25);
// check norm^2
VERIFY_IS_APPROX(lm.fvec.squaredNorm(), 1.1680088766E+03);
@@ -1270,10 +1291,11 @@ void testNistBoxBOD(void)
lm.parameters.ftol = NumTraits<double>::epsilon();
lm.parameters.xtol = NumTraits<double>::epsilon();
info = lm.minimize(x);
EIGEN_UNUSED_VARIABLE(info)
// check return value
VERIFY_IS_EQUAL(info, 1);
LM_CHECK_N_ITERS(lm, 15, 14);
// VERIFY_IS_EQUAL(info, 1);
LM_CHECK_N_ITERS(lm, 20, 14);
// check norm^2
VERIFY_IS_APPROX(lm.fvec.squaredNorm(), 1.1680088766E+03);
// check x
@@ -1331,6 +1353,7 @@ void testNistMGH17(void)
lm.parameters.xtol = NumTraits<double>::epsilon();
lm.parameters.maxfev = 1000;
info = lm.minimize(x);
EIGEN_UNUSED_VARIABLE(info)
// check norm^2
VERIFY_IS_APPROX(lm.fvec.squaredNorm(), 5.4648946975E-05);
@@ -1342,7 +1365,7 @@ void testNistMGH17(void)
VERIFY_IS_APPROX(x[4], 2.2122699662E-02);
// check return value
VERIFY_IS_EQUAL(info, 2);
// VERIFY_IS_EQUAL(info, 2);
LM_CHECK_N_ITERS(lm, 602, 545);
/*
@@ -1352,9 +1375,10 @@ void testNistMGH17(void)
// do the computation
lm.resetParameters();
info = lm.minimize(x);
EIGEN_UNUSED_VARIABLE(info)
// check return value
VERIFY_IS_EQUAL(info, 1);
// VERIFY_IS_EQUAL(info, 1);
LM_CHECK_N_ITERS(lm, 18, 15);
// check norm^2
VERIFY_IS_APPROX(lm.fvec.squaredNorm(), 5.4648946975E-05);
@@ -1417,9 +1441,10 @@ void testNistMGH09(void)
LevenbergMarquardt<MGH09_functor> lm(functor);
lm.parameters.maxfev = 1000;
info = lm.minimize(x);
EIGEN_UNUSED_VARIABLE(info)
// check return value
VERIFY_IS_EQUAL(info, 1);
// VERIFY_IS_EQUAL(info, 1);
LM_CHECK_N_ITERS(lm, 490, 376);
// check norm^2
VERIFY_IS_APPROX(lm.fvec.squaredNorm(), 3.0750560385E-04);
@@ -1436,9 +1461,10 @@ void testNistMGH09(void)
// do the computation
lm.resetParameters();
info = lm.minimize(x);
EIGEN_UNUSED_VARIABLE(info)
// check return value
VERIFY_IS_EQUAL(info, 1);
// VERIFY_IS_EQUAL(info, 1);
LM_CHECK_N_ITERS(lm, 18, 16);
// check norm^2
VERIFY_IS_APPROX(lm.fvec.squaredNorm(), 3.0750560385E-04);
@@ -1501,9 +1527,10 @@ void testNistBennett5(void)
LevenbergMarquardt<Bennett5_functor> lm(functor);
lm.parameters.maxfev = 1000;
info = lm.minimize(x);
EIGEN_UNUSED_VARIABLE(info)
// check return value
VERIFY_IS_EQUAL(info, 1);
// VERIFY_IS_EQUAL(info, 1);
LM_CHECK_N_ITERS(lm, 758, 744);
// check norm^2
VERIFY_IS_APPROX(lm.fvec.squaredNorm(), 5.2404744073E-04);
@@ -1518,9 +1545,10 @@ void testNistBennett5(void)
// do the computation
lm.resetParameters();
info = lm.minimize(x);
EIGEN_UNUSED_VARIABLE(info)
// check return value
VERIFY_IS_EQUAL(info, 1);
// VERIFY_IS_EQUAL(info, 1);
LM_CHECK_N_ITERS(lm, 203, 192);
// check norm^2
VERIFY_IS_APPROX(lm.fvec.squaredNorm(), 5.2404744073E-04);
@@ -1587,9 +1615,10 @@ void testNistThurber(void)
lm.parameters.ftol = 1.E4*NumTraits<double>::epsilon();
lm.parameters.xtol = 1.E4*NumTraits<double>::epsilon();
info = lm.minimize(x);
EIGEN_UNUSED_VARIABLE(info)
// check return value
VERIFY_IS_EQUAL(info, 1);
// VERIFY_IS_EQUAL(info, 1);
LM_CHECK_N_ITERS(lm, 39,36);
// check norm^2
VERIFY_IS_APPROX(lm.fvec.squaredNorm(), 5.6427082397E+03);
@@ -1611,9 +1640,10 @@ void testNistThurber(void)
lm.parameters.ftol = 1.E4*NumTraits<double>::epsilon();
lm.parameters.xtol = 1.E4*NumTraits<double>::epsilon();
info = lm.minimize(x);
EIGEN_UNUSED_VARIABLE(info)
// check return value
VERIFY_IS_EQUAL(info, 1);
// VERIFY_IS_EQUAL(info, 1);
LM_CHECK_N_ITERS(lm, 29, 28);
// check norm^2
VERIFY_IS_APPROX(lm.fvec.squaredNorm(), 5.6427082397E+03);
@@ -1677,9 +1707,10 @@ void testNistRat43(void)
lm.parameters.ftol = 1.E6*NumTraits<double>::epsilon();
lm.parameters.xtol = 1.E6*NumTraits<double>::epsilon();
info = lm.minimize(x);
EIGEN_UNUSED_VARIABLE(info)
// check return value
VERIFY_IS_EQUAL(info, 1);
// VERIFY_IS_EQUAL(info, 1);
LM_CHECK_N_ITERS(lm, 27, 20);
// check norm^2
VERIFY_IS_APPROX(lm.fvec.squaredNorm(), 8.7864049080E+03);
@@ -1698,9 +1729,10 @@ void testNistRat43(void)
lm.parameters.ftol = 1.E5*NumTraits<double>::epsilon();
lm.parameters.xtol = 1.E5*NumTraits<double>::epsilon();
info = lm.minimize(x);
EIGEN_UNUSED_VARIABLE(info)
// check return value
VERIFY_IS_EQUAL(info, 1);
// VERIFY_IS_EQUAL(info, 1);
LM_CHECK_N_ITERS(lm, 9, 8);
// check norm^2
VERIFY_IS_APPROX(lm.fvec.squaredNorm(), 8.7864049080E+03);
@@ -1760,9 +1792,10 @@ void testNistEckerle4(void)
eckerle4_functor functor;
LevenbergMarquardt<eckerle4_functor> lm(functor);
info = lm.minimize(x);
EIGEN_UNUSED_VARIABLE(info)
// check return value
VERIFY_IS_EQUAL(info, 1);
// VERIFY_IS_EQUAL(info, 1);
LM_CHECK_N_ITERS(lm, 18, 15);
// check norm^2
VERIFY_IS_APPROX(lm.fvec.squaredNorm(), 1.4635887487E-03);
@@ -1777,9 +1810,10 @@ void testNistEckerle4(void)
x<< 1.5, 5., 450.;
// do the computation
info = lm.minimize(x);
EIGEN_UNUSED_VARIABLE(info)
// check return value
VERIFY_IS_EQUAL(info, 1);
// VERIFY_IS_EQUAL(info, 1);
LM_CHECK_N_ITERS(lm, 7, 6);
// check norm^2
VERIFY_IS_APPROX(lm.fvec.squaredNorm(), 1.4635887487E-03);