Index: trunk/tests/test_StatAccumulator.cc =================================================================== --- trunk/tests/test_StatAccumulator.cc (revision 603) +++ trunk/tests/test_StatAccumulator.cc (revision 604) @@ -1,321 +1,347 @@ #include #include #include "UnitTest++.h" #include "test_utils.hh" #include "TestAccumulator.hh" #include "npstat/stat/StatAccumulator.hh" #include "npstat/stat/SampleAccumulator.hh" #include "npstat/stat/BinSummary.hh" #include "npstat/stat/arrayStats.hh" using namespace std; using namespace npstat; namespace { + TEST(arrayCumulants) + { + const long double eps = 1.0e-15L; + const unsigned maxpoints = 33; + + SampleAccumulator acc; + for (unsigned i=0; i acc; for (unsigned i=0; i acc; for (unsigned i=0; i acc; for (unsigned i=0; i acc; for (unsigned i=0; i acc; for (unsigned i=0; i #include #include "UnitTest++.h" #include "test_utils.hh" #include "npstat/stat/Distributions1D.hh" #include "npstat/stat/GaussianMixture1D.hh" #include "npstat/stat/JohnsonCurves.hh" #include "npstat/stat/TruncatedDistribution1D.hh" #include "npstat/stat/LeftCensoredDistribution.hh" #include "npstat/stat/RightCensoredDistribution.hh" #include "npstat/stat/QuantileTable1D.hh" #include "npstat/stat/DistributionMix1D.hh" #include "npstat/stat/VerticallyInterpolatedDistribution1D.hh" #include "npstat/stat/UGaussConvolution1D.hh" #include "npstat/stat/RatioOfNormals.hh" #include "npstat/stat/InterpolatedDistro1D1P.hh" #include "npstat/stat/TransformedDistribution1D.hh" #include "npstat/stat/EdgeworthSeries1D.hh" #include "npstat/stat/DeltaMixture1D.hh" #include "npstat/stat/distro1DStats.hh" +#include "npstat/stat/cumulantConversion.hh" #include "npstat/stat/IdentityTransform1D.hh" #include "npstat/stat/AsinhTransform1D.hh" #include "npstat/stat/LogRatioTransform1D.hh" #include "npstat/stat/LocationScaleTransform1.hh" #include "npstat/stat/Distribution1DReader.hh" #include "npstat/stat/DistributionTransform1DReader.hh" #include "npstat/stat/arrayStats.hh" #include "npstat/nm/EquidistantSequence.hh" #include "npstat/nm/LinearMapper1d.hh" #include "npstat/nm/ClassicalOrthoPolys1D.hh" #include "npstat/nm/MathUtils.hh" #include "npstat/nm/GaussHermiteQuadrature.hh" #include "npstat/rng/MersenneTwister.hh" #include "LogLogQuadratic1D.hh" #include "geners/pseudoIO.hh" #define LSQR2 1.41421356237309504880169L #define SQRTWOPIL 2.50662827463100050241577L using namespace npstat; using namespace std; struct Two : public npstat::ConstValue1 { inline Two() : npstat::ConstValue1(2.0) {} }; gs_enable_pseudo_io(Two) struct Three : public npstat::ConstValue1 { inline Three() : npstat::ConstValue1(3.0) {} }; gs_enable_pseudo_io(Three) struct Xsq { inline double operator()(const double x) const {return x*x;} inline bool operator==(const Xsq&) const {return true;} }; gs_enable_pseudo_io(Xsq) struct Xp1 { inline double operator()(const double x) const {return x + 1.0;} inline bool operator==(const Xp1&) const {return true;} }; gs_enable_pseudo_io(Xp1) static long double ldgexceedance(const long double x) { return erfcl(x/LSQR2)/2.0L; } static long double ldgcdf(const long double x) { return erfcl(-x/LSQR2)/2.0L; } namespace { double he0(const double x) { return 1.0; } double he1(const double x) { return x; } double he2(const double x) { return x*x - 1.0; } double he3(const double x) { return x*(x*x - 3.0); } double he4(const long double x) { const long double xsq = x*x; return 3 - 6*xsq + xsq*xsq; } double he5(const long double x) { const long double xsq = x*x; return x*(xsq*xsq - 10*xsq + 15); } double he6(const long double x) { const long double xsq = x*x; return -15 + 45*xsq - 15*xsq*xsq + xsq*xsq*xsq; } double he7(const long double x) { const long double xsq = x*x; return x*(-105 + 105*xsq - 21*xsq*xsq + xsq*xsq*xsq); } double he8(const long double x) { const long double xsq = x*x; const long double x4 = xsq*xsq; return 105 - 420*xsq + 210*x4 - 28*x4*xsq + x4*x4; } double he9(const long double x) { const long double xsq = x*x; const long double x4 = xsq*xsq; return x*(945 - 1260*xsq + 378*x4 - 36*xsq*x4 + x4*x4); } double he10(const long double x) { const long double xsq = x*x; const long double x4 = xsq*xsq; const long double x6 = x4*xsq; const long double x8 = x6*xsq; const long double x10 = x8*xsq; return -945 + 4725*xsq - 3150*x4 + 630*x6 - 45*x8 + x10; } double he11(const long double x) { const long double xsq = x*x; const long double x4 = xsq*xsq; const long double x6 = x4*xsq; const long double x8 = x6*xsq; const long double x10 = x8*xsq; return x*(-10395 + 17325*xsq - 6930*x4 + 990*x6 - 55*x8 + x10); } double he12(const long double x) { const long double xsq = x*x; const long double x4 = xsq*xsq; const long double x6 = x4*xsq; const long double x8 = x6*xsq; const long double x10 = x8*xsq; const long double x12 = x10*xsq; return 10395 - 62370*xsq + 51975*x4 - 13860*x6 + 1485*x8 - 66*x10 + x12; } + /* void cumulants_from_moments(const double m[10], double cumulants[10]) { - for (unsigned i=0; i<4; ++i) + cumulants[0] = 0.0; + for (unsigned i=1; i<4; ++i) cumulants[i] = m[i]; const double m2sq = m[2]*m[2]; const double m3sq = m[3]*m[3]; cumulants[4] = m[4] - 3*m2sq; cumulants[5] = m[5] - 10*m[2]*m[3]; cumulants[6] = m[6] - 15*m[2]*m[4] - 10*m[3]*m[3] + 30*m2sq*m[2]; cumulants[7] = m[7] + 210*m2sq*m[3] - 35*m[3]*m[4] - 21*m[2]*m[5]; cumulants[8] = -630*m2sq*m2sq + 420*m2sq*m[4] - 35*m[4]*m[4] - 56*m[3]*m[5] + 28*m[2]*(20*m3sq - m[6]) + m[8]; cumulants[9] = -7560*m2sq*m[2]*m[3] + 560*m[3]*m3sq + 756*m2sq*m[5] - 126*m[4]*m[5] - 84*m[3]*m[6] + 36*m[2]*(70*m[3]*m[4] - m[7]) + m[9]; } + */ - void get_cumulants_severini(const EdgeworthSeries1D& s, double cumulants[10]) + void get_edgeworth_cumulants(const EdgeworthSeries1D& s, double cumulants[10]) { - assert(s.method() == EDGEWORTH_SEVERINI); double m[10]; - GaussHermiteQuadrature quad(128); for (unsigned i=0; i<10; ++i) - { - EdgeworthSeriesMomentFcn fcn(s, i); - m[i] = quad.integrateProb(0.0, 1.0, fcn); - } - cumulants_from_moments(m, cumulants); - } - - void get_cumulants_classical(const EdgeworthSeries1D& s, double cumulants[10]) - { - assert(s.method() == EDGEWORTH_CLASSICAL); - double m[10]; - GaussHermiteQuadrature quad(128); - for (unsigned i=0; i<10; ++i) - { - EdgeworthSeriesMomentFcn fcn(s, i); - m[i] = quad.integrateProb(s.mean(), s.stdev(), fcn); - } - cumulants_from_moments(m, cumulants); + m[i] = s.empiricalCentralMoment(i); + if (s.order()) + m[1] = s.cum(0); + npstat::convertCentralMomentsToCumulants(m, 9, cumulants); } void io_test(const AbsDistribution1D& d) { std::ostringstream os; CHECK(d.classId().write(os)); CHECK(d.write(os)); std::istringstream is(os.str()); gs::ClassId id(is, 1); AbsDistribution1D* phoenix = AbsDistribution1D::read(id, is); CHECK(*phoenix == d); delete phoenix; } void standard_test(const AbsDistribution1D& d, const double range, const double eps, const bool do_io = true) { const double cdf0 = d.cdf(0.0); for (unsigned i=0; i<100; ++i) { const double r = 2*range*(test_rng() - 0.5); const double cdfr = d.cdf(r); if (cdfr > 0.0 && cdfr < 1.0) { CHECK_CLOSE(cdfr, 1.0 - d.exceedance(r), eps); CHECK_CLOSE(r, d.quantile(cdfr), eps); const double integ = simpson_integral( DensityFunctor1D(d), 0.0, r); CHECK_CLOSE(integ, cdfr-cdf0, eps); } } if (do_io) io_test(d); } void invcdf_test(const AbsDistribution1D& d, const double eps) { for (unsigned i=0; i<1000; ++i) { const double r = test_rng(); const double x = d.quantile(r); const double cdf = d.cdf(x); CHECK_CLOSE(cdf, r, eps); CHECK_CLOSE(cdf, 1.0 - d.exceedance(x), eps); } } void invexceedance_test(const EdgeworthSeries1D& d, const double eps) { for (unsigned i=0; i<1000; ++i) { const double r = test_rng(); const double x = d.inverseExceedance(r); const double exc = d.exceedance(x); CHECK_CLOSE(exc, r, eps); CHECK_CLOSE(exc, 1.0 - d.cdf(x), eps); } } TEST(Distributions1D_Gauss) { Gauss1D g(0., 1.); double value = simpson_integral(DensityFunctor1D(g), -6, 6); CHECK_CLOSE(1.0, value, 1.e-8); standard_test(g, 6, 1.e-7); CHECK_CLOSE(7.61985302416e-24, g.cdf(-10.0), 1.e-34); CHECK_CLOSE(7.61985302416e-24, g.exceedance(10.0), 1.e-34); CHECK_CLOSE(2.75362411861e-89, g.cdf(-20.0), 1.e-99); CHECK_CLOSE(2.75362411861e-89, g.exceedance(20.0), 1.e-99); } TEST(Distributions1D_Bifgauss_0) { const double lfrac = 0.3; const double lsigma = lfrac*2.0; const double rsigma = 2.0 - lsigma; BifurcatedGauss1D g(0.0, 1.0, lfrac, 2.0, 1.5); double value = simpson_integral(DensityFunctor1D(g), -lsigma*g.nSigmasLeft(), rsigma*g.nSigmasRight()); CHECK_CLOSE(1.0, value, 1.e-8); standard_test(g, lsigma*g.nSigmasLeft(), 1.e-7); } TEST(Distributions1D_Bifgauss_1) { const double eps = 1.0e-12; BifurcatedGauss1D g1(0.0, 2.0, 0.5, 2.0, 2.0); TruncatedGauss1D g2(0.0, 2.0, 2.0); for (unsigned i=0; i<100; ++i) { const double r = test_rng(); const double q1 = g1.quantile(r); const double q2 = g2.quantile(r); CHECK_CLOSE(q1, q2, eps); CHECK_CLOSE(g1.density(q1), g2.density(q1), eps); CHECK_CLOSE(g1.cdf(q1), g2.cdf(q1), eps); CHECK_CLOSE(g1.exceedance(q1), g2.exceedance(q1), eps); } } TEST(Distributions1D_Bifgauss_2) { BifurcatedGauss1D g(0.0, 1.0, 0.0, 2.0, 2.0); double value = simpson_integral(DensityFunctor1D(g), 0.0, 4.0); CHECK_CLOSE(1.0, value, 1.e-8); standard_test(g, 4.0, 1.e-7); } TEST(Distributions1D_Bifgauss_3) { BifurcatedGauss1D g(0.0, 1.0, 1.0, 2.0, 2.0); double value = simpson_integral(DensityFunctor1D(g), -4.0, 0.0); CHECK_CLOSE(1.0, value, 1.e-8); standard_test(g, 4.0, 1.e-7); IdentityTransform1D it(5.0); TransformedDistribution1D td(it, g); value = simpson_integral(DensityFunctor1D(td), -4.0, 0.0); CHECK_CLOSE(1.0, value, 1.e-8); standard_test(td, 4.0, 1.e-7); } TEST(Distributions1D_uniform) { Uniform1D g(0., 1.); double value = simpson_integral(DensityFunctor1D(g), -0.1, 1.1); CHECK_CLOSE(1.0, value, 1.e-3); standard_test(g, 1, 1.e-7); } TEST(Distributions1D_exp) { Exponential1D g(0., 1.); standard_test(g, 20.0, 1.e-7); g.setScale(3.); standard_test(g, 60.0, 1.e-7); } TEST(Distributions1D_Pareto) { Pareto1D p1(0., 1., 1.5); double value = simpson_integral(DensityFunctor1D(p1), 1, 6); CHECK_CLOSE(0.93195861825602283, value, 1.e-8); invcdf_test(p1, 1.e-10); io_test(p1); } TEST(Distributions1D_MirroredGauss) { { MirroredGauss1D g(0., 1., 0.3, 0.1); const double value = simpson_integral(DensityFunctor1D(g), 0, 1); CHECK_CLOSE(1.0, value, 1.e-12); invcdf_test(g, 1.e-10); io_test(g); for (unsigned i=0; i<100; ++i) { const double y = test_rng(); const double cdfy = simpson_integral(DensityFunctor1D(g), 0, y); CHECK_CLOSE(cdfy, g.cdf(y), 1.0e-10); } } { MirroredGauss1D g(0., 2., 0.7, 0.1); const double value = simpson_integral(DensityFunctor1D(g), 0, 2); CHECK_CLOSE(1.0, value, 1.e-12); invcdf_test(g, 1.e-10); io_test(g); for (unsigned i=0; i<100; ++i) { const double y = 2.0*test_rng(); const double cdfy = simpson_integral(DensityFunctor1D(g), 0, y); CHECK_CLOSE(cdfy, g.cdf(y), 1.0e-10); } } } TEST(Distributions1D_Huber) { Huber1D h1(0., 1., 0.0); double value = simpson_integral(DensityFunctor1D(h1), -6, 6); CHECK_CLOSE(1.0, value, 1.e-8); standard_test(h1, 6, 1.e-7); double tailW = 0.2; double sigma = 0.8; Huber1D h2(0., sigma, tailW); CHECK_EQUAL(tailW, h2.tailWeight()); value = simpson_integral(DensityFunctor1D(h2), -20, 20, 10000); CHECK_CLOSE(1.0, value, 1.e-8); standard_test(h2, 6, 1.e-7); const double a = sigma*h2.tailStart(); value = simpson_integral(DensityFunctor1D(h2), -a, a, 10000); CHECK_CLOSE(1.0-tailW, value, 1.e-8); for (unsigned i=0; i<1000; ++i) { const double rndx = 6*a*(test_rng() - 0.5); const double cdf = h2.cdf(rndx); value = simpson_integral(DensityFunctor1D(h2), -20, rndx, 10000); CHECK_CLOSE(cdf, value, 1.e-8); CHECK_CLOSE(h2.quantile(cdf), rndx, 1.e-8); } } TEST(Distributions1D_Symbeta) { SymmetricBeta1D sb(0.0, 1.0, 3); double value = simpson_integral(DensityFunctor1D(sb), -1, 1); CHECK_CLOSE(1.0, value, 1.e-8); for (unsigned i=0; i<10; ++i) { SymmetricBeta1D sb(0.0, 2.0, i); standard_test(sb, 1.8, 1.e-8); } } TEST(Distributions1D_Moyal) { Moyal1D mo(0.0, 1.0); double value = simpson_integral(DensityFunctor1D(mo), -7, 1000, 100000); CHECK_CLOSE(1.0, value, 1.e-9); CHECK_CLOSE(0.24197072451914335, mo.density(0.0), 1.0e-14); CHECK_CLOSE(0.20131624406488799, mo.density(1.0), 1.0e-14); CHECK_CLOSE(0.31731050786291410, mo.cdf(0.0), 1.0e-12); CHECK_CLOSE(0.54416242936230305, mo.cdf(1.0), 1.0e-12); invcdf_test(mo, 1.e-8); io_test(mo); } TEST(Distributions1D_StudentsT1D) { for (unsigned i=1; i<10; ++i) { StudentsT1D t(0.0, 1.0, i); invcdf_test(t, 1.e-8); } } TEST(Distributions1D_beta) { Beta1D b(0.0, 1.0, 3.0, 4.0); double value = simpson_integral(DensityFunctor1D(b), 0, 1); CHECK_CLOSE(1.0, value, 1.e-8); for (unsigned i=1; i<5; ++i) for (unsigned j=1; j<5; ++j) { Beta1D sb(0.5, 2.0, i, j); standard_test(sb, 0.9, 1.e-3); } } TEST(Distributions1D_gamma) { Gamma1D g1(0., 0.8, 1.0); standard_test(g1, 20.0, 5.e-3); Gamma1D g2(0., 0.9, 2.0); standard_test(g2, 20.0, 2.e-5); Gamma1D g3(0., 1.1, 3.0); standard_test(g3, 20.0, 2.e-5); } TEST(UGaussConvolution1D) { UGaussConvolution1D ug(0, 1, -1, 1); standard_test(ug, 6.0, 1.0e-6); } TEST(Distributions1D_Transformed) { StaticDistributionTransform1DReader::registerClass< LocationScaleTransform1 >(); const double teps = 1.0e-12; Two two; Three three; LocationScaleTransform1 tr(two, three); Gauss1D g(0.0, 1.0); TransformedDistribution1D d1(tr, g); io_test(d1); Gauss1D g1(2.0, 3.0); for (unsigned i=0; i<100; ++i) { const double x = 10.0*(test_rng() - 0.5); CHECK_CLOSE(g1.density(x), d1.density(x), teps); CHECK_CLOSE(g1.cdf(x), d1.cdf(x), teps); CHECK_CLOSE(g1.exceedance(x), d1.exceedance(x), teps); const double y = test_rng(); CHECK_CLOSE(g1.quantile(y), d1.quantile(y), teps); } } TEST(Distributions1D_JohnsonSu) { const double teps = 1.0e-12; JohnsonSu jsu1(0.0, 1.0, 1.0, 10.0); standard_test(jsu1, 6, 1.e-8); AsinhTransform1D tr1(jsu1.getDelta(), jsu1.getLambda(), jsu1.getGamma(), jsu1.getXi()); Gauss1D g(0.0, 1.0); TransformedDistribution1D d1(tr1, g); standard_test(d1, 6, 1.e-8); for (unsigned i=0; i<100; ++i) { const double x = 10.0*(test_rng() - 0.5); CHECK_CLOSE(jsu1.density(x), d1.density(x), teps); CHECK_CLOSE(jsu1.cdf(x), d1.cdf(x), teps); CHECK_CLOSE(jsu1.exceedance(x), d1.exceedance(x), teps); const double y = test_rng(); CHECK_CLOSE(jsu1.quantile(y), d1.quantile(y), teps); } JohnsonSu jsu2(0.1, 1.0, -1.0, 10.0); standard_test(jsu2, 6, 1.e-8); AsinhTransform1D tr2(jsu2.getDelta(), jsu2.getLambda(), jsu2.getGamma(), jsu2.getXi()); TransformedDistribution1D d2(tr2, g); standard_test(d2, 6, 1.e-8); double mean, sigma, skew, kurt; distro1DStats(jsu2, -30.0, 20.0, 500000, &mean, &sigma, &skew, &kurt); CHECK_CLOSE(0.1, mean, 1.0e-5); CHECK_CLOSE(1.0, sigma, 1.0e-4); CHECK_CLOSE(-1.0, skew, 0.01); CHECK_CLOSE(10.0, kurt, 0.2); } TEST(Distributions1D_JohnsonSb) { const double teps = 1.0e-12; JohnsonSb jsb1(0.0, 1.0, 1.0, 2.9); LogRatioTransform1D tr1(jsb1.getDelta(), jsb1.getLambda(), jsb1.getGamma(), jsb1.getXi()); Gauss1D g(0.0, 1.0); TransformedDistribution1D d1(tr1, g); const double lolim = jsb1.getXi(); const double range = jsb1.getLambda(); for (unsigned i=0; i<100; ++i) { const double x = lolim + range*test_rng(); CHECK_CLOSE(jsb1.density(x), d1.density(x), teps); CHECK_CLOSE(jsb1.cdf(x), d1.cdf(x), teps); CHECK_CLOSE(jsb1.exceedance(x), d1.exceedance(x), teps); const double y = test_rng(); CHECK_CLOSE(jsb1.quantile(y), d1.quantile(y), teps); } } TEST(Distributions1D_LogNormal0) { LogNormal g(0., 1., 0.); double value = simpson_integral(DensityFunctor1D(g), -6, 6); CHECK_CLOSE(1.0, value, 1.e-8); standard_test(g, 6, 1.e-6); } TEST(Distributions1D_LogNormal1) { LogNormal ln1(0., 1., 2.0); double value = simpson_integral(DensityFunctor1D(ln1), -6, 20); CHECK_CLOSE(1.0, value, 1.e-6); standard_test(ln1, 7, 2.e-4); } TEST(Distributions1D_LogNormal2) { LogNormal ln2(0., 1., -2.0); double value = simpson_integral(DensityFunctor1D(ln2), -20, 6); CHECK_CLOSE(1.0, value, 1.e-6); standard_test(ln2, 7, 4.e-4); } TEST(Distributions1D_LogNormal3) { LogNormal ln3(-0.5, 1., 2.0); standard_test(ln3, 7, 1.e-3); } TEST(Distributions1D_LogNormal4) { LogNormal ln4(-0.5, 1., -2.0); standard_test(ln4, 7, 1.e-3); } TEST(Distributions1D_LogNormal5) { LogNormal ln5(0.5, 2., 2.0); standard_test(ln5, 7, 1.e-3); } TEST(Distributions1D_LogNormal6) { LogNormal ln6(0.5, 2., -2.0); standard_test(ln6, 7, 1.e-3); } TEST(Distributions1D_LogNormal7) { LogNormal ln7(1., 2., 10.0); standard_test(ln7, 7, 1.e-3); } TEST(Distributions1D_LogNormal8) { LogNormal ln8(1., 2., -10.0); standard_test(ln8, 7, 1.e-3); } TEST(Distributions1D_misc) { Cauchy1D ch(0.0, 0.5); standard_test(ch, 5, 1.e-8); TruncatedGauss1D tg(0.0, 2.0, 3.0); standard_test(tg, 6.0, 1.e-8); Gauss1D gauss(0.0, 2.0); TruncatedDistribution1D td(gauss, -6.0, 6.0); standard_test(td, 6.0, 1.e-8); CHECK_CLOSE(td.density(0.5), tg.density(0.5), 1.0e-14); CHECK_CLOSE(td.cdf(0.5), tg.cdf(0.5), 1.0e-14); CHECK_CLOSE(td.quantile(0.3), tg.quantile(0.3), 1.0e-14); CHECK_CLOSE(td.exceedance(0.3), tg.exceedance(0.3), 1.0e-14); } TEST(EdgeworthSeries1D_io) { const unsigned order = 2; std::vector cumulants(4); for (unsigned i=0; i dummy; double empCum[10]; EdgeworthSeries1D es1(dummy, EDGEWORTH_SEVERINI, order, false); CHECK_CLOSE(0.241970724519143, es1.density(1.0), 1.e-14); CHECK_CLOSE(7.61985302416e-24, es1.cdf(-10.0), 1.e-34); CHECK_CLOSE(7.61985302416e-24, es1.exceedance(10.0), 1.e-34); standard_test(es1, 6, 1.e-8); invexceedance_test(es1, 1.e-8); - get_cumulants_severini(es1, empCum); - CHECK_CLOSE(1.0, empCum[0], 1.e-14); + get_edgeworth_cumulants(es1, empCum); + CHECK_CLOSE(0.0, empCum[0], 1.e-14); CHECK_CLOSE(0.0, empCum[1], 1.e-14); CHECK_CLOSE(1.0, empCum[2], 1.e-14); CHECK_CLOSE(0.0, empCum[3], 1.e-14); CHECK_CLOSE(0.0, empCum[4], 1.e-14); EdgeworthSeries1D es2(dummy, EDGEWORTH_SEVERINI, order, true); CHECK_CLOSE(0.241970724519143, es2.density(1.0), 1.e-14); CHECK_CLOSE(7.61985302416e-24, es2.cdf(-10.0), 1.e-34); CHECK_CLOSE(7.61985302416e-24, es2.exceedance(10.0), 1.e-34); standard_test(es2, 6, 1.e-8); invexceedance_test(es2, 1.e-8); - get_cumulants_severini(es2, empCum); - CHECK_CLOSE(1.0, empCum[0], 1.e-14); + get_edgeworth_cumulants(es2, empCum); + CHECK_CLOSE(0.0, empCum[0], 1.e-14); CHECK_CLOSE(0.0, empCum[1], 1.e-14); CHECK_CLOSE(1.0, empCum[2], 1.e-14); CHECK_CLOSE(0.0, empCum[3], 1.e-14); CHECK_CLOSE(0.0, empCum[4], 1.e-14); EdgeworthSeries1D es3(dummy, EDGEWORTH_CLASSICAL, order, false); CHECK_CLOSE(0.241970724519143, es3.density(1.0), 1.e-14); CHECK_CLOSE(7.61985302416e-24, es3.cdf(-10.0), 1.e-34); CHECK_CLOSE(7.61985302416e-24, es3.exceedance(10.0), 1.e-34); standard_test(es3, 6, 1.e-8); invexceedance_test(es3, 1.e-8); - get_cumulants_classical(es3, empCum); - CHECK_CLOSE(1.0, empCum[0], 1.e-14); + get_edgeworth_cumulants(es3, empCum); + CHECK_CLOSE(0.0, empCum[0], 1.e-14); CHECK_CLOSE(0.0, empCum[1], 1.e-14); CHECK_CLOSE(1.0, empCum[2], 1.e-14); CHECK_CLOSE(0.0, empCum[3], 1.e-14); CHECK_CLOSE(0.0, empCum[4], 1.e-14); EdgeworthSeries1D es4(dummy, EDGEWORTH_CLASSICAL, order, true); CHECK_CLOSE(0.241970724519143, es4.density(1.0), 1.e-14); CHECK_CLOSE(7.61985302416e-24, es4.cdf(-10.0), 1.e-34); CHECK_CLOSE(7.61985302416e-24, es4.exceedance(10.0), 1.e-34); standard_test(es4, 6, 1.e-8); invexceedance_test(es4, 1.e-8); - get_cumulants_classical(es4, empCum); - CHECK_CLOSE(1.0, empCum[0], 1.e-14); + get_edgeworth_cumulants(es4, empCum); + CHECK_CLOSE(0.0, empCum[0], 1.e-14); CHECK_CLOSE(0.0, empCum[1], 1.e-14); CHECK_CLOSE(1.0, empCum[2], 1.e-14); CHECK_CLOSE(0.0, empCum[3], 1.e-14); CHECK_CLOSE(0.0, empCum[4], 1.e-14); } TEST(EdgeworthSeries1D_1) { const double range = 5.0; const unsigned ntries = 10; const unsigned order = 1; const double k1 = 3, k2 = 2, k3 = 0.5; double empCum[10]; std::vector c_slr(1); c_slr[0] = k1; std::vector c_gen(3); c_gen[0] = k1; c_gen[1] = k2; c_gen[2] = k3; EdgeworthSeries1D es1(c_slr, EDGEWORTH_SEVERINI, order, true); standard_test(es1, 6, 1.e-8); invexceedance_test(es1, 1.e-8); for (unsigned i=0; i c_slr(2); c_slr[0] = k1; c_slr[1] = k2; std::vector c_gen(4); c_gen[0] = k1; c_gen[1] = k2; c_gen[2] = k3; c_gen[3] = k4; EdgeworthSeries1D es1(c_slr, EDGEWORTH_SEVERINI, order, true); standard_test(es1, 6, 1.e-8); for (unsigned i=0; i c_slr(3); c_slr[0] = k1; c_slr[1] = k2; c_slr[2] = k3; std::vector c_gen(5); c_gen[0] = k1; c_gen[1] = k2; c_gen[2] = k3; c_gen[3] = k4; c_gen[4] = k5; EdgeworthSeries1D es1(c_slr, EDGEWORTH_SEVERINI, order, true); standard_test(es1, 3, 1.e-8); for (unsigned i=0; i c_slr(4); c_slr[0] = k1; c_slr[1] = k2; c_slr[2] = k3; c_slr[3] = k4; std::vector c_gen(6); c_gen[0] = k1; c_gen[1] = k2; c_gen[2] = k3; c_gen[3] = k4; c_gen[4] = k5; c_gen[5] = k6; EdgeworthSeries1D es1(c_slr, EDGEWORTH_SEVERINI, order, true); standard_test(es1, 3, 1.e-8); invexceedance_test(es1, 1.e-8); for (unsigned i=0; i quantiles(nquant); arrayQuantiles1D(data, sizeof(data)/sizeof(data[0]), 0.0, 1.0, &qs[0], &quantiles[0], nquant); BinnedDensity1D t1(location, width, data, sizeof(data)/sizeof(data[0]), 0); for (unsigned i=0; i(); LogLogQuadratic1D q1(1.0, 10.0, 0.5, 1.0); standard_test(q1, 1.0, 1.e-9); invcdf_test(q1, 1.e-14); } TEST(GaussianMixture1D_1) { std::vector entries; entries.push_back(GaussianMixtureEntry(3, 0, 1)); GaussianMixture1D g(0, 1, &entries[0], entries.size()); double value = simpson_integral(DensityFunctor1D(g), -6, 6); CHECK_CLOSE(1.0, value, 1.e-8); standard_test(g, 6, 1.e-7); Gauss1D g2(0, 1); DistributionMix1D mix; mix.add(g2, 3.0); value = simpson_integral(DensityFunctor1D(mix), -6, 6); CHECK_CLOSE(1.0, value, 1.e-8); standard_test(mix, 6, 1.e-7); VerticallyInterpolatedDistribution1D shmix(1U); shmix.add(g2, 3.0); value = simpson_integral(DensityFunctor1D(shmix), -6, 6); CHECK_CLOSE(1.0, value, 1.e-8); standard_test(shmix, 6, 1.e-7, false); for (unsigned i=0; i<100; ++i) { const double r = test_rng(); CHECK_CLOSE(shmix.quantile(r), mix.quantile(r), 1.e-15); } } TEST(GaussianMixture1D_2) { for (unsigned i=0; i<100; ++i) { Gauss1D g(test_rng(), 0.1+test_rng()); GaussianMixture1D mix(g); for (unsigned j=0; j<100; ++j) { const double x = -3 + 6*test_rng(); CHECK_CLOSE(g.density(x), mix.density(x), 1.0e-15); CHECK_CLOSE(g.cdf(x), mix.cdf(x), 1.0e-15); } } } TEST(DistributionMix1D_2) { for (unsigned i=0; i<100; ++i) { Gauss1D g(test_rng(), 0.1+test_rng()); DistributionMix1D mix; VerticallyInterpolatedDistribution1D shmix; mix.add(g, 1); shmix.add(g, 1); for (unsigned j=0; j<100; ++j) { const double x = -3 + 6*test_rng(); CHECK_CLOSE(g.density(x), mix.density(x), 1.0e-15); CHECK_CLOSE(g.cdf(x), mix.cdf(x), 1.0e-15); CHECK_CLOSE(g.density(x), shmix.density(x), 1.0e-15); CHECK_CLOSE(g.cdf(x), shmix.cdf(x), 1.0e-15); } } } TEST(GaussianMixture1D_3) { std::vector entries; entries.push_back(GaussianMixtureEntry(3, 0, 1)); entries.push_back(GaussianMixtureEntry(2, -0.5, 1.5)); entries.push_back(GaussianMixtureEntry(1, 0.5, 0.5)); GaussianMixture1D g(0, 1, &entries[0], entries.size()); double value = simpson_integral(DensityFunctor1D(g), -8, 8); CHECK_CLOSE(1.0, value, 1.e-7); standard_test(g, 4, 1.e-7); } TEST(DistributionMix1D_3) { DistributionMix1D mix; VerticallyInterpolatedDistribution1D shmix(3); Gauss1D g1(0, 1), g2(-0.5, 1.5), g3(0.5, 0.5); mix.add(g1, 3); mix.add(g2, 2); mix.add(g3, 1); shmix.add(g1, 3); shmix.add(g2, 2); shmix.add(g3, 1); double value = simpson_integral(DensityFunctor1D(mix), -8, 8); CHECK_CLOSE(1.0, value, 1.e-7); value = simpson_integral(DensityFunctor1D(shmix), -8, 8); CHECK_CLOSE(1.0, value, 1.e-7); standard_test(mix, 4, 1.e-7); standard_test(shmix, 4, 1.e-7, false); } TEST(GaussianMixture1D_4) { const double m0 = 1.3; const double s0 = 3/2.0; std::vector entries; entries.push_back(GaussianMixtureEntry(3, 0, 1)); entries.push_back(GaussianMixtureEntry(2, -0.5, 1.5)); entries.push_back(GaussianMixtureEntry(1, 0.5, 0.5)); GaussianMixture1D g(m0, s0, &entries[0], entries.size()); // G[x_, m_, s_] := 1/Sqrt[2 Pi]/s Exp[-(x - m)^2/s^2/2] // w1 = 3/6; m1 = 0; s1 = 1 // w2 = 2/6; m2 = -1/2; s2 = 3/2 // w3 = 1/6; m3 = 1/2; s3 = 1/2 // m0 = 1 + 3/10 // s0 = 3/2 // f = (w1*G[(x-m0)/s0,m1,s1]+w2*G[(x-m0)/s0,m2,s2]+w3*G[(x-m0)/s0,m3,s3])/s0 // mean = Integrate[x f, {x, -Infinity, Infinity}] // stdev = Sqrt[Integrate[(x - mean)^2 f, {x, -Infinity, Infinity}]] // q0 = Integrate[f, {x, -Infinity, 5/2}] // N[q0, 20] const double expmean = 47.0/40; const double expstdev = sqrt(203.0)/8.0; const double expcdf = 0.78400933536932041748; CHECK_CLOSE(expmean, g.mean(), 1.0e-15); CHECK_CLOSE(expstdev, g.stdev(), 1.0e-15); CHECK_CLOSE(expcdf, g.cdf(2.5), 1.0e-15); CHECK_CLOSE(2.5, g.quantile(expcdf), 1.0e-12); } TEST(LeftCensoredDistribution) { const double cutoff = 0.1234; const double eps = 1.0e-9; const double infty = -100.0; Gauss1D gauss(0.0, 1.0); TruncatedDistribution1D td(gauss, cutoff, 100.0); const double frac = gauss.exceedance(cutoff); LeftCensoredDistribution lc(td, frac, infty); CHECK_CLOSE(lc.cdf(cutoff-1.0), 1.0-frac, eps); CHECK_CLOSE(lc.exceedance(cutoff-1.0), frac, eps); CHECK_EQUAL(lc.cdf(infty-10.0), 0.0); CHECK_EQUAL(lc.exceedance(infty-10.0), 1.0); for (unsigned i=0; i<1000; ++i) { const double r = cutoff + test_rng()*5.0; CHECK_CLOSE(gauss.density(r), lc.density(r), eps); CHECK_CLOSE(gauss.exceedance(r), lc.exceedance(r), eps); CHECK_CLOSE(gauss.cdf(r), lc.cdf(r), eps); CHECK_CLOSE(lc.quantile(lc.cdf(r)), r, eps); } io_test(lc); } TEST(RightCensoredDistribution) { const double cutoff = 0.1234; const double eps = 1.0e-10; const double infty = 100.0; Gauss1D gauss(0.0, 1.0); TruncatedDistribution1D td(gauss, -100.0, cutoff); const double frac = gauss.cdf(cutoff); RightCensoredDistribution rc(td, frac, infty); CHECK_CLOSE(rc.cdf(cutoff+1.0), frac, eps); CHECK_CLOSE(rc.exceedance(cutoff+1.0), 1.0-frac, eps); CHECK_EQUAL(rc.cdf(infty+10.0), 1.0); CHECK_EQUAL(rc.exceedance(infty+10.0), 0.0); for (unsigned i=0; i<1000; ++i) { const double r = cutoff - test_rng()*5.0; CHECK_CLOSE(gauss.density(r), rc.density(r), eps); CHECK_CLOSE(gauss.exceedance(r), rc.exceedance(r), eps); CHECK_CLOSE(gauss.cdf(r), rc.cdf(r), eps); CHECK_CLOSE(rc.quantile(rc.cdf(r)), r, eps); } io_test(rc); } TEST(RatioOfNormals) { RatioOfNormals r1(-2.0, 1.0, 0.5, 1.0, 0.7); standard_test(r1, 10, 1.e-8); RatioOfNormals r2(1.0, 3.0, 2.0, 1.0, 0.5); standard_test(r2, 10, 1.e-7); const double x = 1.0; const double cdf = r2.cdf(x); const double quantile = r2.quantile(cdf); CHECK_CLOSE(x, quantile, 1.0e-8); } TEST(InterpolatedDistro1D1P) { const double eps = 1.0e-8; const double gridPoints[] = {1.0, 2.0}; double param = 1.3; const unsigned nGridPoints = sizeof(gridPoints)/sizeof(gridPoints[0]); GridAxis ax(std::vector(gridPoints, gridPoints+nGridPoints)); std::vector > distros; distros.push_back(CPP11_shared_ptr(new Gauss1D(1.0, 2.0))); distros.push_back(CPP11_shared_ptr(new Gauss1D(-1.0, 1.0))); InterpolatedDistro1D1P idist(ax, distros, param); standard_test(idist, 10.0, 1.e-7); LinearMapper1d meanmap(gridPoints[0], 1.0, gridPoints[1], -1.0); LinearMapper1d sigmap(gridPoints[0], 2.0, gridPoints[1], 1.0); for (unsigned i=0; i<100; ++i) { param = 1.0 + test_rng(); idist.setParameter(param); Gauss1D g(meanmap(param), sigmap(param)); const double r = test_rng(); const double x = g.quantile(r); CHECK_CLOSE(x, idist.quantile(r), eps); CHECK_CLOSE(g.density(x), idist.density(x), eps); CHECK_CLOSE(g.cdf(x), idist.cdf(x), eps); } } TEST(distro1DStats_1) { const double eps = 1.0e-7; for (unsigned i=0; i<100; ++i) { const double mean = test_rng(); const double sigma = 0.5 + test_rng(); double m, s, skew, kurt; distro1DStats(Gauss1D(mean, sigma), -10., 11., 100000, &m, &s, &skew, &kurt); CHECK_CLOSE(mean, m, eps); CHECK_CLOSE(sigma, s, eps); CHECK_CLOSE(0.0, skew, eps); CHECK_CLOSE(3.0, kurt, eps); } } TEST(DeltaMixture1D_1) { const double eps = 1.0e-12; const unsigned nPoints = 3; double coords[nPoints] = {0., 1., 2.}; double weights[nPoints] = {1., 3., 2.}; DeltaMixture1D dmix(5.0, 1.0, coords, weights, nPoints); io_test(dmix); CHECK_CLOSE(0.6666666666666666, dmix.cdf(6.0), eps); CHECK_CLOSE(0.3333333333333333, dmix.exceedance(6.0), eps); MersenneTwister rng; int counts[nPoints] = {0}; for (unsigned i=0; i<6000; ++i) { double rnd; dmix.random(rng, &rnd); CHECK(rnd == 5.0 || rnd == 6.0 || rnd == 7.0); if (rnd == 5.0) ++counts[0]; if (rnd == 6.0) ++counts[1]; if (rnd == 7.0) ++counts[2]; } CHECK(std::abs(counts[0] - 1000) < 200); CHECK(std::abs(counts[2] - 2000) < 300); CHECK_CLOSE(0.5, dmix.integral(6.0, true, 6.0, true), eps); CHECK_CLOSE(0.0, dmix.integral(6.0, false, 6.0, false), eps); CHECK_CLOSE(0.0, dmix.integral(6.0, false, 6.0, true), eps); CHECK_CLOSE(0.0, dmix.integral(6.0, true, 6.0, false), eps); CHECK_CLOSE(1.0, dmix.integral(5.0, true, 7.0, true), eps); CHECK_CLOSE(0.5, dmix.integral(5.0, false, 7.0, false), eps); CHECK_CLOSE(0.8333333333333334, dmix.integral(5.0, false, 7.0, true), eps); CHECK_CLOSE(0.6666666666666667, dmix.integral(5.0, true, 7.0, false), eps); const double expectedMoments[4] = {1.0, 37/6.0, 77/2.0, 1459/6.0}; long double moments[4]; dmix.moments(0, 3, moments); for (unsigned i=0; i<=3; ++i) CHECK_CLOSE(expectedMoments[i], moments[i], eps); const double expectedCMoments[4] = {1.0, 37/6.0, 17/36.0, -2/27.0}; dmix.centralMoments(3, moments); for (unsigned i=0; i<=3; ++i) CHECK_CLOSE(expectedCMoments[i], moments[i], eps); } TEST(DeltaMixture1D_2) { const double eps = 1.0e-12; const unsigned nPoints = 3; double coords[nPoints] = {0., 1., 2.}; double weights[nPoints] = {1., 3., 2.}; DeltaMixture1D dmix(5.0, 2.0, coords, weights, nPoints); io_test(dmix); CHECK_CLOSE(0.6666666666666666, dmix.cdf(7.0), eps); CHECK_CLOSE(0.3333333333333333, dmix.exceedance(7.0), eps); MersenneTwister rng; int counts[nPoints] = {0}; for (unsigned i=0; i<6000; ++i) { double rnd; dmix.random(rng, &rnd); CHECK(rnd == 5.0 || rnd == 7.0 || rnd == 9.0); if (rnd == 5.0) ++counts[0]; if (rnd == 7.0) ++counts[1]; if (rnd == 9.0) ++counts[2]; } CHECK(std::abs(counts[0] - 1000) < 200); CHECK(std::abs(counts[2] - 2000) < 300); CHECK_CLOSE(0.5, dmix.integral(7.0, true, 7.0, true), eps); CHECK_CLOSE(0.0, dmix.integral(7.0, false, 7.0, false), eps); CHECK_CLOSE(0.0, dmix.integral(7.0, false, 7.0, true), eps); CHECK_CLOSE(0.0, dmix.integral(7.0, true, 7.0, false), eps); CHECK_CLOSE(1.0, dmix.integral(5.0, true, 9.0, true), eps); CHECK_CLOSE(0.5, dmix.integral(5.0, false, 9.0, false), eps); CHECK_CLOSE(0.8333333333333334, dmix.integral(5.0, false, 9.0, true), eps); CHECK_CLOSE(0.6666666666666667, dmix.integral(5.0, true, 9.0, false), eps); const double expectedMoments[4] = {1.0, 22/3.0, 167/3.0, 1306/3.0}; long double moments[4]; dmix.moments(0, 3, moments); for (unsigned i=0; i<=3; ++i) CHECK_CLOSE(expectedMoments[i], moments[i], eps); const double expectedCMoments[4] = {1.0, 22/3.0, 17/9.0, -16/27.0}; dmix.centralMoments(3, moments); for (unsigned i=0; i<=3; ++i) CHECK_CLOSE(expectedCMoments[i], moments[i], eps); } } Index: trunk/autom4te.cache/requests =================================================================== --- trunk/autom4te.cache/requests (revision 603) +++ trunk/autom4te.cache/requests (revision 604) @@ -1,509 +1,509 @@ # This file was generated by Autom4te Sun Aug 20 23:09:08 UTC 2017. # It contains the lists of macros which have been traced. # It can be safely removed. @request = ( bless( [ '0', 1, [ '/usr/share/autoconf' ], [ '/usr/share/autoconf/autoconf/autoconf.m4f', '-', '/usr/share/aclocal-1.15/internal/ac-config-macro-dirs.m4', '/usr/share/aclocal/pkg.m4', '/usr/share/aclocal-1.15/amversion.m4', '/usr/share/aclocal-1.15/auxdir.m4', '/usr/share/aclocal-1.15/cond.m4', '/usr/share/aclocal-1.15/depend.m4', '/usr/share/aclocal-1.15/depout.m4', '/usr/share/aclocal-1.15/init.m4', '/usr/share/aclocal-1.15/install-sh.m4', '/usr/share/aclocal-1.15/lead-dot.m4', 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'_LT_AC_LOCK' => 1, + 'PKG_CHECK_EXISTS' => 1 } ], 'Autom4te::Request' ) ); Index: trunk/npstat/stat/arrayStats.hh =================================================================== --- trunk/npstat/stat/arrayStats.hh (revision 603) +++ trunk/npstat/stat/arrayStats.hh (revision 604) @@ -1,144 +1,156 @@ #ifndef NPSTAT_ARRAYSTATS_HH_ #define NPSTAT_ARRAYSTATS_HH_ /*! // \file arrayStats.hh // // \brief Various descriptive statistics for 1-d and multidimensional arrays // // Author: I. Volobouev // // July 2010 */ #include "npstat/nm/BoxND.hh" #include "npstat/nm/Matrix.hh" namespace npstat { /** // This function estimates population mean, standard // deviation, skewness, and kurtosis. The array must have at least // one element. A numerically sound two-pass algorithm is used. // // Any of the output pointers can be specified as NULL if the // corresponding quantity is not needed (this might speed the code up). */ template void arrayStats(const Numeric* arr, unsigned long arrLen, double* mean, double* stdev, double* skewness=0, double* kurtosis=0); /** Function for calculating sample moments w.r.t. some point */ template long double arrayMoment(const Numeric* arr, unsigned long arrLen, long double center, unsigned order); /** // Function for calculating multiple sample moments w.r.t. some // point. The array "moments" should have at least "maxOrder+1" // elements. Upon exit, moments[k] will be set to moment of order k. */ template void arrayMoments(const Numeric* arr, unsigned long arrLen, long double center, unsigned maxOrder, long double* moments); /** + // Function for calculating multiple sample cumulants (k-statistics). + // The array "cumulants" should have at least "maxOrder+1" elements. + // Upon exit, cumulants[k] will be set to the sample cumulant of order k. + // Currently, "maxOrder" argument can not exceed 6. Formulae for these + // can be found, for example, in "Kendall's Advanced Theory of Statistics" + // by Stuart and Ord. + */ + template + void arrayCumulants(const Numeric* arr, unsigned long arrLen, + unsigned maxOrder, long double* cumulants); + + /** // Function for calculating multiple sample central moments and // estimating their uncertainties (if requested). The array "moments" // should have at least "maxOrder+1" elements. If provided, the // array "momentUncertainties" should also have at least "maxOrder+1" // elements. Upon exit, moments[0] will be set to 1 and moments[1] // will be set to the sample mean. For k > 1, moments[k] will be set // to the central moment of order k. The corresponding uncertainties // will be estimated approximately, to O(1/n), by substituting the // sample moments for the population moments in the asymptotic // formulae. The relevant formulae can be found, for example, in the // monograph "Mathematical Methods of Statistics" by Harald Cramer. */ template void arrayCentralMoments(const Numeric* arr, unsigned long arrLen, unsigned maxOrder, long double* moments, long double* momentUncertainties = 0); /** // Calculate the mean along each coordinate using array values as // weights. The coordinate ranges are defined by the given box, // and the array points are assumed to be in the centers of the bins, // like in a histogram. The results are stored in the "mean" array // whose length (given by lengthMean) must not be smaller than // the rank of the array. // // For this function, the array dimensionality can not exceed // CHAR_BIT*sizeof(unsigned long) which is normally 64 on 64-bit machines. */ template void arrayCoordMean(const Array& a, const BoxND& limits, double* mean, unsigned lengthMean); /** // Calculate the array covariance matrix. The "limits" argument has // the same meaning as in the arrayCoordMean function. */ template void arrayCoordCovariance(const Array& a, const BoxND& limits, Matrix* covarianceMatrix); /** // One-dimensional mean, variance, skewness, and kurtosis // using array values as weights. Any of the argument pointers // can be NULL in which case the corresponding quantity is not // calculated. The code estimates population shape quantities // rather than sample quantities (so that it can be best used // with equidistantly binned histograms and such). */ template void arrayShape1D(const Array& a, double xmin, double xmax, double* mean, double* stdev, double* skewness, double* kurtosis); /** // Quantiles for 1-d arrays in which array values are used as weights. // Essentially, the values are treated as histogram bin contents. // All input "qvalues" should be between 0 and 1. The results are // returned in the corresponding elements of the "quantiles" array. // The function will work faster if "qvalues" are sorted in the // increasing order. // // If you expect to call this function more than once using the same // data, it is likely that you can obtain the same information more // efficiently by creating the "BinnedDensity1D" object with its // interpolationDegree argument set to 0 and then using its "quantile" // method. */ template void arrayQuantiles1D(const Numeric* data, unsigned long len, double xmin, double xmax, const double* qvalues, double* quantiles, unsigned nqvalues); /** // This function returns negative sum of p_i ln(p_i) over array // elements p_i, divided by the total number of array elements. // All elements must be non-negative, and there must be at least // one positive element present. Useful for calculating entropies // of distributions represented on a grid. For example, mutual // information of two variables is just the entropy of their copula. */ template double arrayEntropy(const Numeric* p, unsigned long len, bool normalize = false); /** // This function assumes that Poisson distribution parameters are // given in the "means" array while the array "counts" contains // corresponding observations. "len" is the length of both "means" // and "counts" arrays. */ template double poissonLogLikelihood(const Real* means, const Numeric* counts, unsigned long len); } #include "npstat/stat/arrayStats.icc" #endif // NPSTAT_ARRAYSTATS_HH_ Index: trunk/npstat/stat/cumulantConversion.icc =================================================================== --- trunk/npstat/stat/cumulantConversion.icc (revision 0) +++ trunk/npstat/stat/cumulantConversion.icc (revision 604) @@ -0,0 +1,168 @@ +#include +#include + +namespace npstat { + template + void convertCumulantsToCentralMoments(const Real* c, + const unsigned maxOrder, + Real* m) + { + if (maxOrder > 12) throw std::invalid_argument( + "In npstat::convertCumulantsToCentralMoments: " + "maximum order outside of supported range"); + m[0] = static_cast(1); + + for (unsigned k=1U; k<=3U && k<=maxOrder; ++k) + m[k] = c[k]; + + if (maxOrder >= 4U) + { + const Real c2_2 = c[2]*c[2]; + m[4] = 3*c2_2 + c[4]; + + if (maxOrder >= 5U) + { + m[5] = 10*c[2]*c[3] + c[5]; + + if (maxOrder >= 6U) + { + const Real c2_3 = c2_2*c[2]; + const Real c3_2 = c[3]*c[3]; + m[6] = 15*c2_3 + 10*c3_2 + 15*c[2]*c[4] + c[6]; + + if (maxOrder >= 7U) + { + m[7] = 105*c2_2*c[3] + 35*c[3]*c[4] + 21*c[2]*c[5] + c[7]; + + if (maxOrder >= 8U) + { + const Real c2_4 = c2_2*c2_2; + const Real c4_2 = c[4]*c[4]; + m[8] = 105*c2_4 + 210*c2_2*c[4] + 35*c4_2 + 56*c[3]*c[5] + + 28*c[2]*(10*c3_2 + c[6]) + c[8]; + + if (maxOrder >= 9U) + { + const Real c3_3 = c3_2*c[3]; + m[9] = 1260*c2_3*c[3] + 280*c3_3 + 378*c2_2*c[5] + 126*c[4]*c[5] + + 84*c[3]*c[6] + 36*c[2]*(35*c[3]*c[4] + c[7]) + c[9]; + + if (maxOrder >= 10U) + { + const Real c2_5 = c2_4*c[2]; + const Real c5_2 = c[5]*c[5]; + m[10] = 945*c2_5 + 3150*c2_3*c[4] + 2100*c3_2*c[4] + 126*c5_2 + 210*c[4]*c[6] + + 630*c2_2*(10*c3_2 + c[6]) + 120*c[3]*c[7] + + 45*c[2]*(35*c4_2 + 56*c[3]*c[5] + c[8]) + c[10]; + + if (maxOrder >= 11U) + { + m[11] = 17325*c2_4*c[3] + 6930*c2_3*c[5] + 4620*c3_2*c[5] + 462*c[5]*c[6] + + 330*c[4]*c[7] + 990*c2_2*(35*c[3]*c[4] + c[7]) + + 165*c[3]*(35*c4_2 + c[8]) + 55*c[2]*(280*c3_3 + 126*c[4]*c[5] + + 84*c[3]*c[6] + c[9]) + c[11]; + + if (maxOrder >= 12U) + { + const Real c3_4 = c3_2*c3_2; + const Real c4_3 = c4_2*c[4]; + const Real c2_6 = c2_3*c2_3; + const Real c6_2 = c[6]*c[6]; + m[12] = 10395*c2_6 + 15400*c3_4 + 51975*c2_4*c[4] + 5775*c4_3 + + 9240*c3_2*c[6] + 462*c6_2 + 13860*c2_3*(10*c3_2 + c[6]) + + 792*c[5]*c[7] + 495*c[4]*c[8] + 1485*c2_2*(35*c4_2 + 56*c[3]*c[5] + + c[8]) + 220*c[3]*(126*c[4]*c[5] + c[9]) + + 66*c[2]*(2100*c3_2*c[4] + 126*c5_2 + 210*c[4]*c[6] + 120*c[3]*c[7] + c[10]) + c[12]; + } + } + } + } + } + } + } + } + } + } + + template + void convertCentralMomentsToCumulants(const Real* m, + const unsigned maxOrder, + Real* cumulants) + { + if (maxOrder > 12) throw std::invalid_argument( + "In npstat::convertCentralMomentsToCumulants: " + "maximum order outside of supported range"); + cumulants[0] = static_cast(0); + + for (unsigned k=1U; k<=3U && k<=maxOrder; ++k) + cumulants[k] = m[k]; + + if (maxOrder >= 4) + { + const Real m2_2 = m[2]*m[2]; + cumulants[4] = m[4] - 3*m2_2; + + if (maxOrder >= 5) + { + cumulants[5] = m[5] - 10*m[2]*m[3]; + + if (maxOrder >= 6) + { + const Real m2_3 = m2_2*m[2]; + const Real m3_2 = m[3]*m[3]; + cumulants[6] = 30*m2_3 - 10*m3_2 - 15*m[2]*m[4] + m[6]; + + if (maxOrder >= 7) + { + cumulants[7] = 210*m2_2*m[3] - 35*m[3]*m[4] - 21*m[2]*m[5] + m[7]; + + if (maxOrder >= 8) + { + const Real m2_4 = m2_2*m2_2; + const Real m4_2 = m[4]*m[4]; + cumulants[8] = -630*m2_4 + 420*m2_2*m[4] - 35*m4_2 + - 56*m[3]*m[5] + 28*m[2]*(20*m3_2 - m[6]) + m[8]; + + if (maxOrder >= 9) + { + const Real m3_3 = m3_2*m[3]; + cumulants[9] = -7560*m2_3*m[3] + 560*m3_3 + 756*m2_2*m[5] - 126*m[4]*m[5] + - 84*m[3]*m[6] + 36*m[2]*(70*m[3]*m[4] - m[7]) + m[9]; + + if (maxOrder >= 10) + { + const Real m2_5 = m2_4*m[2]; + const Real m5_2 = m[5]*m[5]; + cumulants[10] = 22680*m2_5 - 18900*m2_3*m[4] + 4200*m3_2*m[4] - 126*m5_2 - + 1260*m2_2*(30*m3_2 - m[6]) - 210*m[4]*m[6] - 120*m[3]*m[7] + + 45*m[2]*(70*m4_2 + 112*m[3]*m[5] - m[8]) + m[10]; + + if (maxOrder >= 11) + { + cumulants[11] = 415800*m2_4*m[3] - 41580*m2_3*m[5] + 9240*m3_2*m[5] - 462*m[5]*m[6] - + 1980*m2_2*(105*m[3]*m[4] - m[7]) - 330*m[4]*m[7] + + 165*m[3]*(70*m4_2 - m[8]) - 55*m[2]*(1680*m3_3 - 252*m[4]*m[5] - + 168*m[3]*m[6] + m[9]) + m[11]; + + if (maxOrder >= 12) + { + const Real m3_4 = m3_2*m3_2; + const Real m2_6 = m2_3*m2_3; + const Real m4_3 = m4_2*m[4]; + const Real m6_2 = m[6]*m[6]; + cumulants[12] = -1247400*m2_6 - 92400*m3_4 + 1247400*m2_4*m[4] + 11550*m4_3 + + 83160*m2_3*(40*m3_2 - m[6]) + 18480*m3_2*m[6] - 462*m6_2 - + 792*m[5]*m[7] - 2970*m2_2*(105*m4_2 + 168*m[3]*m[5] - m[8]) - + 495*m[4]*m[8] + 220*m[3]*(252*m[4]*m[5] - m[9]) - + 66*m[2]*(12600*m3_2*m[4] - 252*m5_2 - 420*m[4]*m[6] - 240*m[3]*m[7] + m[10]) + m[12]; + } + } + } + } + } + } + } + } + } + } +} Index: trunk/npstat/stat/Makefile.in =================================================================== --- trunk/npstat/stat/Makefile.in (revision 603) +++ trunk/npstat/stat/Makefile.in (revision 604) @@ -1,1181 +1,1183 @@ # Makefile.in generated by automake 1.15.1 from Makefile.am. # @configure_input@ # Copyright (C) 1994-2017 Free Software Foundation, Inc. # This Makefile.in is free software; the Free Software Foundation # gives unlimited permission to copy and/or distribute it, # with or without modifications, as long as this notice is preserved. # This program is distributed in the hope that it will be useful, # but WITHOUT ANY WARRANTY, to the extent permitted by law; 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BandwidthGCVLeastSquares1D.hh \ BandwidthGCVLeastSquares1D.icc \ BandwidthGCVLeastSquaresND.hh \ BandwidthGCVLeastSquaresND.icc \ BandwidthGCVPseudoLogli1D.hh \ BandwidthGCVPseudoLogli1D.icc \ BandwidthGCVPseudoLogliND.hh \ BandwidthGCVPseudoLogliND.icc \ BernsteinCopulaSmoother.hh \ BernsteinFilter1DBuilder.hh \ betaKernelsBandwidth.hh \ betaKernelsBandwidth.icc \ BetaFilter1DBuilder.hh \ BinnedADTest1D.hh \ BinnedKSTest1D.hh \ BinSummary.hh \ BinSummary.icc \ BoundaryHandling.hh \ BoundaryMethod.hh \ buildInterpolatedCompositeDistroND.hh \ buildInterpolatedCompositeDistroND.icc \ buildInterpolatedDistro1DNP.hh \ buildInterpolatedDistro1DNP.icc \ buildInterpolatedHelpers.hh \ CensoredQuantileRegression.hh \ CensoredQuantileRegression.icc \ CircularBuffer.hh \ CircularBuffer.icc \ Column.hh \ Column.icc \ CompositeDistribution1D.hh \ CompositeDistributionND.hh \ CompositeDistributionND.icc \ CompositeDistros1D.hh \ ConstantBandwidthSmoother1D.hh \ ConstantBandwidthSmootherND.hh \ ConstantBandwidthSmootherND.icc \ continuousDegreeTaper.hh \ convertAxis.hh \ CopulaInterpolationND.hh \ Copulas.hh \ CrossCovarianceAccumulator.hh \ CrossCovarianceAccumulator.icc \ + cumulantConversion.hh \ + cumulantConversion.icc \ CVCopulaSmoother.hh \ CVCopulaSmoother.icc \ DeltaMixture1D.hh \ DeltaMixture1D.icc \ DensityAveScanND.hh \ DensityScan1D.hh \ DensityScanND.hh \ DiscreteDistribution1DReader.hh \ DiscreteDistributions1D.hh \ discretizationErrorND.hh \ Distribution1DFactory.hh \ Distribution1DReader.hh \ DistributionTransform1DReader.hh \ DistributionMix1D.hh \ DistributionNDReader.hh \ Distributions1D.hh \ Distributions1D.icc \ DistributionsND.hh \ DistributionsND.icc \ distributionReadError.hh \ distro1DStats.hh \ DualHistoAxis.hh \ DummyCompositeDistroBuilder.hh \ DummyDistro1DBuilder.hh \ DummyResponseBoxBuilder.hh \ DummyResponseIntervalBuilder.hh \ EdgeworthSeries1D.hh \ EdgeworthSeriesMethod.hh \ empiricalCopula.hh \ empiricalCopulaHisto.hh \ empiricalCopulaHisto.icc \ empiricalCopula.icc \ fillHistoFromText.hh \ fillHistoFromText.icc \ Filter1DBuilders.hh \ FitUtils.hh \ FitUtils.icc \ GaussianMixture1D.hh \ gaussianResponseMatrix.hh \ GCVCopulaSmoother.hh \ GCVCopulaSmoother.icc \ griddedRobustRegression.hh \ griddedRobustRegression.icc \ GriddedRobustRegressionStop.hh \ GridInterpolatedDistribution.hh \ GridRandomizer.hh \ HistoAxis.hh \ HistoND.hh \ HistoND.icc \ HistoNDCdf.hh \ HistoNDFunctorInstances.hh \ histoStats.hh \ histoStats.icc \ histoUtils.hh \ histoUtils.icc \ IdentityTransform1D.hh \ InMemoryNtuple.hh \ InMemoryNtuple.icc \ InterpolatedDistribution1D.hh \ InterpolatedDistro1D1P.hh \ InterpolatedDistro1DNP.hh \ interpolateHistoND.hh \ interpolateHistoND.icc \ InterpolationFunctorInstances.hh \ JohnsonCurves.hh \ JohnsonKDESmoother.hh \ KDE1D.hh \ KDE1DCV.hh \ KDE1DHOSymbetaKernel.hh \ KDECopulaSmoother.hh \ KDECopulaSmoother.icc \ KDEGroupedCopulaSmoother.hh \ KDEGroupedCopulaSmoother.icc \ KDEFilterND.hh \ KDEFilterND.icc \ kendallsTau.hh \ kendallsTau.icc \ LeftCensoredDistribution.hh \ likelihoodStatisticCumulants.hh \ LikelihoodStatisticType.hh \ LocalLogisticRegression.hh \ LocalLogisticRegression.icc \ LocalMultiFilter1D.hh \ LocalMultiFilter1D.icc \ LocalPolyFilter1D.hh \ LocalPolyFilter1D.icc \ LocalPolyFilter1DReader.hh \ LocalPolyFilterND.hh \ LocalPolyFilterND.icc \ LocalQuadraticLeastSquaresND.hh \ LocalQuadraticLeastSquaresND.icc \ LocalQuantileRegression.hh \ LocalQuantileRegression.icc \ LocationScaleFamily1D.hh \ LocationScaleTransform1.hh \ LocationScaleTransform1.icc \ logLikelihoodPeak.hh \ LogRatioTransform1D.hh \ LogTransform1D.hh \ LOrPECopulaSmoother.hh \ LOrPECopulaSmoother.icc \ LOrPEGroupedCopulaSmoother.hh \ LOrPEGroupedCopulaSmoother.icc \ LOrPEMarginalSmoother.hh \ lorpeBackgroundCVDensity1D.hh \ lorpeBackgroundCVDensity1D.icc \ lorpeBackground1D.hh \ lorpeBackground1D.icc \ lorpeMise1D.hh \ lorpeSmooth1D.hh \ lorpeSmooth1D.icc \ MemoizingSymbetaFilterProvider.hh \ MemoizingSymbetaFilterProvider.icc \ mergeTwoHistos.hh \ mergeTwoHistos.icc \ mirrorWeight.hh \ MultiscaleEMUnfold1D.hh \ multinomialCovariance1D.hh \ MultivariateSumAccumulator.hh \ MultivariateSumsqAccumulator.hh \ MultivariateSumsqAccumulator.icc \ MultivariateWeightedSumAccumulator.hh \ MultivariateWeightedSumsqAccumulator.hh \ MultivariateWeightedSumsqAccumulator.icc \ neymanPearsonWindow1D.hh \ NMCombinationSequencer.hh \ NonparametricCompositeBuilder.hh \ NonparametricCompositeBuilder.icc \ NonparametricDistro1DBuilder.hh \ NonparametricDistro1DBuilder.icc \ NtHistoFill.hh \ NtNtupleFill.hh \ NtRectangularCut.hh \ NtRectangularCut.icc \ NtupleBuffer.hh \ NtupleBuffer.icc \ NtupleRecordTypes.hh \ NtupleRecordTypesFwd.hh \ NtupleReference.hh \ NUHistoAxis.hh \ OrderedPointND.hh \ OrderedPointND.icc \ orthoPoly1DVProducts.hh \ orthoPoly1DVProducts.icc \ OSDE1D.hh \ OSDE1D.icc \ PearsonsChiSquared.hh \ PolyFilterCollection1D.hh \ productResponseMatrix.hh \ productResponseMatrix.icc \ ProductSymmetricBetaNDCdf.hh \ QuadraticOrthoPolyND.hh \ QuadraticOrthoPolyND.icc \ QuantileRegression1D.hh \ QuantileRegression1D.icc \ QuantileTable1D.hh \ RatioOfNormals.hh \ RatioResponseBoxBuilder.hh \ RatioResponseBoxBuilder.icc \ RatioResponseIntervalBuilder.hh \ RatioResponseIntervalBuilder.icc \ ResponseMatrix.hh \ RightCensoredDistribution.hh \ SampleAccumulator.hh \ SampleAccumulator.icc \ SbMomentsCalculator.hh \ ScalableGaussND.hh \ scanDensityAsWeight.hh \ SequentialCopulaSmoother.hh \ SequentialGroupedCopulaSmoother.hh \ SequentialPolyFilterND.hh \ SequentialPolyFilterND.icc \ SinhAsinhTransform1D.hh \ SmoothedEMUnfold1D.hh \ SmoothedEMUnfoldND.hh \ spearmansRho.hh \ spearmansRho.icc \ StatAccumulator.hh \ StatAccumulatorArr.hh \ StatAccumulatorPair.hh \ statUncertainties.hh \ StatUtils.hh \ StatUtils.icc \ StorableHistoNDFunctor.hh \ StorableHistoNDFunctor.icc \ StorableInterpolationFunctor.hh \ 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install-dvi install-dvi-am install-exec \ install-exec-am install-html install-html-am \ install-includeHEADERS install-info install-info-am \ install-man install-pdf install-pdf-am install-ps \ install-ps-am install-strip installcheck installcheck-am \ installdirs maintainer-clean maintainer-clean-generic \ mostlyclean mostlyclean-compile mostlyclean-generic \ mostlyclean-libtool pdf pdf-am ps ps-am tags tags-am uninstall \ uninstall-am uninstall-includeHEADERS .PRECIOUS: Makefile # Tell versions [3.59,3.63) of GNU make to not export all variables. # Otherwise a system limit (for SysV at least) may be exceeded. .NOEXPORT: Index: trunk/npstat/stat/cumulantConversion.hh =================================================================== --- trunk/npstat/stat/cumulantConversion.hh (revision 0) +++ trunk/npstat/stat/cumulantConversion.hh (revision 604) @@ -0,0 +1,40 @@ +#ifndef NPSTAT_CUMULANTCONVERSION_HH_ +#define NPSTAT_CUMULANTCONVERSION_HH_ + +/*! +// \file cumulantConversion.hh +// +// \brief Conversions between cumulants and central moments +// +// Author: I. Volobouev +// +// July 2019 +*/ + +namespace npstat { + /** + // Arrays "cumulants" and "centralMoments" should have at least + // maxOrder+1 elements, with cumulants[2] set to the variance. + // On exit, centralMoments[0] will be set to 1, and centralMoments[1] + // to cumulants[1]. + */ + template + void convertCumulantsToCentralMoments(const Real* cumulants, + unsigned maxOrder, + Real* centralMoments); + + /** + // Arrays "cumulants" and "centralMoments" should have at least + // maxOrder+1 elements, with centralMoments[2] set to the variance. + // On exit, cumulants[0] will be set to 0, and cumulants[1] + // to centralMoments[1]. + */ + template + void convertCentralMomentsToCumulants(const Real* centralMoments, + unsigned maxOrder, + Real* cumulants); +} + +#include "npstat/stat/cumulantConversion.icc" + +#endif // NPSTAT_CUMULANTCONVERSION_HH_ Index: trunk/npstat/stat/EdgeworthSeries1D.cc =================================================================== --- trunk/npstat/stat/EdgeworthSeries1D.cc (revision 603) +++ trunk/npstat/stat/EdgeworthSeries1D.cc (revision 604) @@ -1,373 +1,392 @@ #include #include "npstat/nm/MathUtils.hh" #include "npstat/nm/SpecialFunctions.hh" #include "npstat/nm/findRootUsingBisections.hh" +#include "npstat/nm/GaussHermiteQuadrature.hh" #include "npstat/stat/EdgeworthSeries1D.hh" #include "npstat/stat/distributionReadError.hh" #include "geners/binaryIO.hh" #include "geners/vectorIO.hh" #define MAXCOEFFS 12 #define LSQR2 1.41421356237309504880169L #define SQRTWOPIL 2.50662827463100050241577L static long double ldgexceedance(const long double x) { return erfcl(x/LSQR2)/2.0L; } static long double ldgcdf(const long double x) { return erfcl(-x/LSQR2)/2.0L; } namespace npstat { EdgeworthSeries1D::EdgeworthSeries1D( const std::vector& cumulants, const EdgeworthSeriesMethod m, const unsigned i_order, const bool i_slrMode) : cumulants_(cumulants), m_(m), order_(i_order), slrMode_(i_slrMode) { if (order_ > 4) throw std::invalid_argument( "In npstat::EdgeworthSeries1D constructor: " "order parameter out of range"); if (order_) { const unsigned nMin = minNCumulants(); if (cumulants_.size() < nMin) throw std::invalid_argument( "In npstat::EdgeworthSeries1D constructor: " "not enough cumulants provided"); if (nMin > 1U) if (cumulants_[1] <= 0.0) throw std::invalid_argument( "In npstat::EdgeworthSeries1D constructor: " "variance must be positive"); } - else - cumulants_.clear(); } - double EdgeworthSeries1D::mean() const + double EdgeworthSeries1D::edgMean() const { - if (minNCumulants()) - return cumulants_[0]; + if (minNCumulants() && m_ == EDGEWORTH_CLASSICAL) + return cumulants_.at(0); else return 0.0; } - double EdgeworthSeries1D::stdev() const + double EdgeworthSeries1D::edgStdev() const { if (minNCumulants() > 1) return normalizedSigma(); else return 1.0; } unsigned EdgeworthSeries1D::minNCumulants() const { if (slrMode_) return order_; else return order_ ? order_ + 2U : 0U; } bool EdgeworthSeries1D::isEqual(const AbsDistribution1D& o) const { const EdgeworthSeries1D& r = static_cast(o); return cumulants_ == r.cumulants_ && m_ == r.m_ && order_ == r.order_ && slrMode_ == r.slrMode_; } bool EdgeworthSeries1D::write(std::ostream& os) const { const unsigned m = static_cast(m_); const unsigned char slr = slrMode_; gs::write_pod(os, m); gs::write_pod(os, order_); gs::write_pod(os, slr); return gs::write_item(os, cumulants_, false) && !os.fail(); } EdgeworthSeries1D* EdgeworthSeries1D::read( const gs::ClassId& id, std::istream& in) { static const gs::ClassId myClassId( gs::ClassId::makeId()); myClassId.ensureSameId(id); unsigned m, order; unsigned char slr; gs::read_pod(in, &m); gs::read_pod(in, &order); gs::read_pod(in, &slr); std::vector cumulants; gs::restore_item(in, &cumulants, false); if (in.fail()) { distributionReadError(in, classname()); return 0; } else return new EdgeworthSeries1D( cumulants, static_cast(m), order, slr); } double EdgeworthSeries1D::densityFactor(const double xin) const { long double coeffs[MAXCOEFFS+1]; unsigned maxdeg = 0; if (order_) { if (slrMode_) hermiteCoeffsSLR(coeffs+1, &maxdeg); else hermiteCoeffsNormal(coeffs+1, &maxdeg); ++maxdeg; } coeffs[0] = 0.0L; return 1.0 + hermiteSeriesSumProb(coeffs, maxdeg, normalizedCoord(xin))/normalizedSigma(); } double EdgeworthSeries1D::normalizedSigma() const { double sigma = 1.0; if (order_ > 1U && m_ == EDGEWORTH_CLASSICAL) sigma = sqrt(cumulants_.at(1)); return sigma; } double EdgeworthSeries1D::density(const double xin) const { const double x = normalizedCoord(xin); return exp(-x*x/2)/SQRTWOPIL/normalizedSigma()*densityFactor(xin); } double EdgeworthSeries1D::cdf(const double xin) const { const double z = normalizedCoord(xin); return ldgcdf(z) - expl(-z*z/2.0)/SQRTWOPIL/normalizedSigma()*cdfFactor(xin); } double EdgeworthSeries1D::exceedance(const double xin) const { const double z = normalizedCoord(xin); return ldgexceedance(z) + expl(-z*z/2.0)/SQRTWOPIL/normalizedSigma()*cdfFactor(xin); } double EdgeworthSeries1D::quantile(const double r1) const { if (!(r1 >= 0.0 && r1 <= 1.0)) throw std::domain_error( "In npstat::EdgeworthSeries1D::quantile: " "cdf argument outside of [0, 1] interval"); if (r1 == 0.0 || r1 == 1.0) return inverseGaussCdf(r1); const double x0 = inverseGaussCdf(0.0); const double x1 = inverseGaussCdf(1.0); CdfFunctor1D fcn(*this); double q = 0.0; if (!findRootUsingBisections(fcn, r1, x0, x1, 1.0e-15, &q)) throw std::runtime_error("In npstat::EdgeworthSeries1D::quantile: " "root finding failed"); return q; } double EdgeworthSeries1D::inverseExceedance(const double r1) const { if (!(r1 >= 0.0 && r1 <= 1.0)) throw std::domain_error( "In npstat::EdgeworthSeries1D::inverseExceedance: " "exceedance argument outside of [0, 1] interval"); if (r1 == 0.0 || r1 == 1.0) return inverseGaussCdf(1.0 - r1); const double x0 = inverseGaussCdf(0.0); const double x1 = inverseGaussCdf(1.0); ExceedanceFunctor1D fcn(*this); double q = 0.0; if (!findRootUsingBisections(fcn, r1, x0, x1, 1.0e-15, &q)) throw std::runtime_error("In npstat::EdgeworthSeries1D::inverseExceedance: " "root finding failed"); return q; } double EdgeworthSeries1D::normalizedCoord(const double xin) const { double x = xin; if (order_) { switch (m_) { case EDGEWORTH_SEVERINI: break; case EDGEWORTH_CLASSICAL: { double sigma = 1.0; if (order_ > 1U) sigma = sqrt(cumulants_.at(1)); x = (xin - cumulants_.at(0))/sigma; } break; default: assert(!"Incomplete swich statement. This is a bug. Please report."); } } return x; } double EdgeworthSeries1D::cdfFactor(const double xin) const { if (order_) { long double coeffs[MAXCOEFFS]; unsigned maxdeg; if (slrMode_) hermiteCoeffsSLR(coeffs, &maxdeg); else hermiteCoeffsNormal(coeffs, &maxdeg); return hermiteSeriesSumProb(coeffs, maxdeg, normalizedCoord(xin)); } else return 0.0; } + double EdgeworthSeries1D::empiricalCentralMoment(const unsigned k) const + { + switch (k) + { + case 0U: + return 1.0; + + case 1U: + return 0.0; + + default: + if (k > 200U) + throw std::invalid_argument("In npstat::EdgeworthSeries1D::empiricalCentralMoment: " + "moment order is too high"); + GaussHermiteQuadrature quad(128); + EdgeworthSeriesMomentFcn fcn(*this, k); + return quad.integrateProb(edgMean(), edgStdev(), fcn); + } + } + void EdgeworthSeries1D::hermiteCoeffsSLR(long double* coeffs, unsigned* maxdeg) const { for (unsigned i=0; i= order_); *maxdeg = order_ - 1U; assert(MAXCOEFFS > *maxdeg); const double k1 = m_ == EDGEWORTH_SEVERINI ? cumulants_[0] : 0.0; coeffs[0] = k1; if (order_ > 1U) { const double k2 = m_ == EDGEWORTH_SEVERINI ? cumulants_[1] : 1.0; const double k2m1 = k2 - 1.0; coeffs[1] = (k1*k1 + k2m1)/2.0; if (order_ > 2U) { const double k3 = cumulants_[2]; coeffs[2] = (k1*(k1*k1 + 3*k2m1) + k3)/6; if (order_ > 3U) { const double k4 = cumulants_[3]; const double k1sq = k1*k1; coeffs[3] = (k1sq*k1sq + 6*k1sq*k2m1 + 3*k2m1*k2m1 + 4*k1*k3 + k4)/24; if (order_ > 4U) // We should not be here assert(0); } if (m_ == EDGEWORTH_CLASSICAL) { const double sigma = sqrt(cumulants_[1]); for (unsigned i=2; i<=*maxdeg; ++i) coeffs[i] /= powl(sigma, i); } } } } void EdgeworthSeries1D::hermiteCoeffsNormal(long double* coeffs, unsigned* maxdeg) const { for (unsigned i=0; i 2U); const double k1 = m_ == EDGEWORTH_SEVERINI ? cumulants_[0] : 0.0; const double k2 = m_ == EDGEWORTH_SEVERINI ? cumulants_[1] : 1.0; const double k3 = cumulants_[2]; *maxdeg = 2U; assert(MAXCOEFFS > *maxdeg); coeffs[0] = k1; coeffs[2] = k3/6.0; if (order_ > 1U) { assert(nk > 3U); const double k4 = cumulants_[3]; const double k2m1 = k2 - 1.0; *maxdeg = 5; assert(MAXCOEFFS > *maxdeg); coeffs[1] += (k1*k1 + k2m1)/2.0; coeffs[3] += (4*k1*k3 + k4)/24.0; coeffs[5] += k3*k3/72.0; if (order_ > 2U) { assert(nk > 4U); const double k5 = cumulants_[4]; *maxdeg = 8; assert(MAXCOEFFS > *maxdeg); coeffs[2] += k1*(k1*k1 + 3*k2m1)/6; coeffs[4] += (10*k1*k1*k3 + 10*k2m1*k3 + 5*k1*k4 + k5)/120; coeffs[6] += (k3*(2*k1*k3 + k4))/144; coeffs[8] += k3*k3*k3/1296; if (order_ > 3U) { assert(nk > 5U); const double k6 = cumulants_[5]; const double k1sq = k1*k1; const double k3sq = k3*k3; *maxdeg = 11; assert(MAXCOEFFS > *maxdeg); coeffs[3] += (k1sq*k1sq + 6*k1sq*k2m1 + 3*k2m1*k2m1)/24; coeffs[5] += (20*k1*k1sq*k3 + 60*k1*k2m1*k3 + 15*k1sq*k4 + 15*k2m1*k4 + 6*k1*k5 + k6)/720; coeffs[7] += (40*k1sq*k3sq + 40*k2m1*k3sq + 40*k1*k3*k4 + 5*k4*k4 + 8*k3*k5)/5760; coeffs[9] += (k3sq*(4*k1*k3 + 3*k4))/5184; coeffs[11] += k3sq*k3sq/31104; if (order_ > 4U) assert(0); } } if (m_ == EDGEWORTH_CLASSICAL) { const double sigma = sqrt(cumulants_[1]); for (unsigned i=2; i<=*maxdeg; ++i) coeffs[i] /= powl(sigma, i); } } } double EdgeworthSeriesMomentFcn::operator()(const double& x) const { const double fact = series_.densityFactor(x); switch (degree_) { case 0: return fact; case 1: return x*fact; default: - return pow(x - series_.mean(), degree_)*fact; + return pow(x - mean_, degree_)*fact; } } } Index: trunk/npstat/stat/arrayStats.icc =================================================================== --- trunk/npstat/stat/arrayStats.icc (revision 603) +++ trunk/npstat/stat/arrayStats.icc (revision 604) @@ -1,652 +1,705 @@ #include #include #include #include #include #include #include "npstat/nm/BoxNDScanner.hh" #include "npstat/rng/permutation.hh" namespace npstat { template void arrayCentralMoments(const Numeric* arr, const unsigned long sz, const unsigned maxOrder, long double* moments, long double* momentUncertainties) { if (!sz) throw std::invalid_argument("In npstat::arrayCentralMoments: " "can not process arrays with zero elements"); assert(arr); assert(moments); moments[0] = 1.0L; if (momentUncertainties) momentUncertainties[0] = 0.0L; if (maxOrder) { long double mean = 0.0L; for (unsigned long i=0; i(arr[i]); mean /= sz; if (momentUncertainties) { std::vector mu(2*maxOrder+1); arrayMoments(arr, sz, mean, 2*maxOrder, &mu[0]); for (unsigned k=2; k<=maxOrder; ++k) { const long double mm1 = k > 2U ? mu[k-1] : 0.0L; const long double tmp = k*mm1; const long double v = mu[2*k] - 2*k*mm1*mu[k+1] - mu[k]*mu[k] + tmp*tmp*mu[2]; assert(v >= 0.0L); moments[k] = mu[k]; momentUncertainties[k] = sqrtl(v/sz); } momentUncertainties[1] = sqrtl(mu[2]/sz); } else if (maxOrder > 1U) arrayMoments(arr, sz, mean, maxOrder, moments); moments[1] = mean; } } template void arrayMoments(const Numeric* arr, const unsigned long sz, const long double center, const unsigned maxOrder, long double* moments) { if (!sz) throw std::invalid_argument("In npstat::arrayMoments: " "can not process arrays with zero elements"); assert(arr); assert(moments); moments[0] = 1.0L; for (unsigned k=1; k<=maxOrder; ++k) moments[k] = 0.0L; if (maxOrder) { for (unsigned long i=0; i= 1U) + const long double delta = static_cast(arr[i]) - center; + long double dk = 1.0L; + for (unsigned k=1; k<=maxOrder; ++k) + { + dk *= delta; + moments[k] += dk; + } + } + } + for (unsigned k=1; k<=maxOrder; ++k) + moments[k] /= sz; + } + + template + void arrayCumulants(const Numeric* arr, const unsigned long sz, + const unsigned maxOrder, long double* cumulants) + { + const unsigned orderSupported = 6U; + long double s[orderSupported+1U] = {0.0L}; + + if (maxOrder > orderSupported) + throw std::invalid_argument("In npstat::arrayCumulants: order argument " + "outside of supported range"); + if (!sz || sz < maxOrder) throw std::invalid_argument("In npstat::arrayCumulants: " + "insufficient array length"); + assert(arr); + assert(cumulants); + cumulants[0] = 0.0L; + + if (maxOrder) + { + long double mean = 0.0L; + for (unsigned long i=0; i(arr[i]); + mean /= sz; + cumulants[1] = mean; + + if (maxOrder > 1U) + { + for (unsigned long i=0; i(arr[i]) - center; - moments[1] += delta; - if (maxOrder >= 2U) - { - const long double deltasq = delta*delta; - moments[2] += deltasq; - if (maxOrder >= 3U) + const long double delta = static_cast(arr[i]) - mean; + long double dk = delta; + for (unsigned k=2U; k<=maxOrder; ++k) + { + dk *= delta; + s[k] += dk; + } + } + cumulants[2] = s[2]/(sz - 1U); + + if (maxOrder > 2U) + cumulants[3] = sz*s[3]/(sz-1U)/(sz-2U); + + if (maxOrder > 3U) + { + const long double n = sz; + const long double n2 = n*n; + cumulants[4] = ((n2 + n)*s[4] - s[2]*s[2]*3*(sz - 1U))/(sz-1U)/(sz-2U)/(sz-3U); + + if (maxOrder > 4U) + { + const long double n3 = n2*n; + cumulants[5] = ((n3 + 5*n2)*s[5] - s[3]*s[2]*10*(n2 - n))/(sz-1U)/(sz-2U)/(sz-3U)/(sz-4U); + + if (maxOrder > 5U) { - moments[3] += delta*deltasq; - if (maxOrder >= 4U) - { - moments[4] += deltasq*deltasq; - for (unsigned k=5; k<=maxOrder; ++k) - moments[k] += powl(delta, k); - } + const long double n4 = n2*n2; + cumulants[6] = ((n4 + 16*n3 + 11*n2 - 4*n)*s[6] + - 15*(n-1)*(n-1)*(n+4)*s[4]*s[2] + - 10*(n3 - 2*n2 + 5*n - 4)*s[3]*s[3] + + 30*(n2 - 3*n + 2)*s[2]*s[2]*s[2])/(sz-1U)/(sz-2U)/(sz-3U)/(sz-4U)/(sz-5U); } } } } } - for (unsigned k=1; k<=maxOrder; ++k) - moments[k] /= sz; } template long double arrayMoment(const Numeric* arr, const unsigned long sz, const long double center, const unsigned order) { if (!sz) throw std::invalid_argument("In npstat::arrayMoment: " "can not process arrays with zero elements"); assert(arr); long double sum = 0.0L; switch (order) { case 0U: return 1.0L; case 1U: for (unsigned long i=0; i(arr[i]) - center); break; case 2U: for (unsigned long i=0; i(arr[i]) - center; sum += delta*delta; } break; case 3U: for (unsigned long i=0; i(arr[i]) - center; sum += delta*delta*delta; } break; case 4U: for (unsigned long i=0; i(arr[i]) - center; const long double tmp = delta*delta; sum += tmp*tmp; } break; default: for (unsigned long i=0; i(arr[i]) - center; sum += powl(delta, order); } } return sum/sz; } template inline void arrayStats(const Data* arr, const unsigned long sz, double* pmean, double* pstdev, double* pskew, double* pkurt) { if (pmean || pstdev || pskew || pkurt) { if (!sz) throw std::invalid_argument("In npstat::arrayStats: " "can not process arrays with zero elements"); assert(arr); if (pstdev) *pstdev = 0.0; if (pskew) *pskew = 0.0; if (pkurt) *pkurt = 3.0; if (sz == 1UL) { if (pmean) *pmean = static_cast(arr[0]); } else { long double sm = 0.0L; for (unsigned long i=0; i(mean); const bool b = (pskew && sz > 2UL) || (pkurt && sz > 3UL); if (pstdev || b) { long double sumsq = 0.0L, skewsum = 0.0L, kursum = 0.0L; for (unsigned long i=0; i 0.0L) { if (pstdev) *pstdev = static_cast(sqrtl(K2)); if (pskew && sz > 2UL) { const long double K3 = sz/NM1/(sz - 2UL)*skewsum; *pskew = static_cast(K3/powl(K2,1.5L)); } if (pkurt && sz > 3UL) { const long double g2 = kursum*sz/sumsq/sumsq-3.0L; *pkurt = static_cast(3.0L + NM1/(sz-2UL)/(sz-3UL)*((sz+1UL)*g2 + 6.0L)); } } } } } } template inline void arrayCoordMean(const Array& a, const BoxND& limits, double* mean, const unsigned storageLength) { const unsigned lenMean = a.rank(); if (lenMean) { long double meanAcc[CHAR_BIT*sizeof(unsigned long)] = {0.0L,}; if (lenMean > CHAR_BIT*sizeof(unsigned long)) throw std::out_of_range("In npstat::arrayCoordMean: " "array dimensionality is too large"); assert(mean); if (storageLength < lenMean) throw std::invalid_argument("In npstat::arrayCoordMean: " "result buffer is too small"); long double weightSum = 0.0L; for (BoxNDScanner scanner(limits, a.shape()); scanner.isValid(); ++scanner) { scanner.getCoords(mean, lenMean); const long double v = a.linearValue(scanner.state()); weightSum += v; for (unsigned i=0; i(meanAcc[i]/weightSum); } } template inline void arrayCoordCovariance(const Array& a, const BoxND& limits, Matrix* covmat) { const unsigned aRank = a.rank(); if (aRank) { assert(covmat); if (covmat->nRows() != aRank) throw std::invalid_argument("In npstat::arrayCoordCovariance: " "incompatible number of rows in the result matrix"); if (covmat->nColumns() != aRank) throw std::invalid_argument("In npstat::arrayCoordCovariance: " "incompatible number of columns in the result matrix"); double mean[CHAR_BIT*sizeof(unsigned long)]; arrayCoordMean(a, limits, mean, aRank); long double weightSum = 0.0L, weightSumSq = 0.0L; const unsigned matLen = aRank*(aRank+1U)/2; std::vector ldbuf(matLen, 0.0L); long double* acc = &ldbuf[0]; double coords[CHAR_BIT*sizeof(unsigned long)]; for (BoxNDScanner scanner(limits, a.shape()); scanner.isValid(); ++scanner) { scanner.getCoords(coords, aRank); const long double v = a.linearValue(scanner.state()); weightSum += v; weightSumSq += v*v; unsigned ilin = 0; for (unsigned i=0; i(covmat->data()); const unsigned len = covmat->length(); for (unsigned i=0; i( acc[ilin]/weightSum*(effM1 + 1.0L)/effM1); (*covmat)[i][j] = cov; (*covmat)[j][i] = cov; } } } } // The formulae used below assume that the effective number // of events is given by the ratio of squared sum of weights // to sum of weights squared. Once the effective number of events // is known, it is used with the standard population estimates // consistent with SAS (see, for example, the article "Comparing // measures of sample skewness and kurtosis", by D.N. Joanes // and C.A. Gill, The Statistician, Vol 47, pp 183-189 (1998). template inline void arrayShape1D(const Array& a, const double xmin, const double xmax, double* pmean, double* pstdev, double* pskewness, double* pkurtosis) { typedef typename Array::value_type Numeric; if (a.rank() != 1U) throw std::invalid_argument( "In npstat::arrayShape1D: array dimensionality must be 1"); if (xmin >= xmax) throw std::invalid_argument( "In npstat::arrayShape1D: invalid interval specification"); if (pmean || pstdev || pskewness || pkurtosis) { const Numeric* data = a.data(); const Numeric zero = static_cast(0); const unsigned long nbins = a.length(); const double binWidth = (xmax - xmin)/nbins; long double wsum = 0.0L, xsum = 0.0L; for (unsigned long i=0; i(xsum/wsum); if (pmean) *pmean = mean; if (pstdev || pskewness || pkurtosis) { long double wsumsq = 0.0L, varsum = 0.0L; const double shiftedMin = xmin - mean; for (unsigned long i=0; i(sqrtl(K2)); if (pskewness || pkurtosis) { long double skewsum = 0.0L, kursum = 0.0L; for (unsigned long i=0; i 0.0L) { const long double m3 = skewsum/wsum; const long double K3 = effN*effN/effM1/effM2*m3; *pskewness = static_cast(K3/powl(K2,1.5L)); } else *pskewness = 0.0; } if (pkurtosis) { const long double effM3 = effM2 - 1.0L; if (effM3 > 0.0L) { const long double m4 = kursum/wsum; const long double g2 = m4/m2/m2 - 3.0L; *pkurtosis = static_cast(3.0L + effM1/effM2/effM3*((effN+1.0L)*g2 + 6.0L)); } else *pkurtosis = 3.0; } } } } } template inline void arrayQuantiles1D(const Numeric* data, const unsigned long len, const double xmin, const double xmax, const double* qvalues, double* quantiles, const unsigned nqvalues) { if (nqvalues == 0U) return; if (!len) throw std::invalid_argument("In npstat::arrayQuantiles1D: " "can not process arrays with zero elements"); assert(data); if (xmin > xmax) throw std::invalid_argument("In npstat::arrayQuantiles1D: " "invalid interval specification"); assert(qvalues); assert(quantiles); for (unsigned i=0; i 1.0) throw std::domain_error("In npstat::arrayQuantiles1D: " "cdf argument outside of [0, 1] interval"); if (xmin == xmax) { for (unsigned i=0; i zero) { if (!positiveElementFound) { positiveElementFound = true; idlo = id; } sum += value; idhi = id; } } if (!positiveElementFound) throw std::invalid_argument( "In npstat::arrayQuantiles1D: all weights are zero"); const double xlo = xmin + idlo*step; const double xhi = idhi == len - 1UL ? xmax : xmin + (idhi+1UL)*step; const unsigned long lenm1 = len - 1UL; unsigned long scanbin = idlo; long double sumbelow = 0.0L; long double sumabove = data[idlo]; for (unsigned i=0; i= sumabove && scanbin < lenm1) { sumbelow = sumabove; sumabove += data[++scanbin]; } const double dbin = (sumneeded - sumbelow)/data[scanbin]; double qval = xmin + (scanbin + dbin)*step; if (qval > xmax) qval = xmax; quantiles[i] = qval; } } } template inline double arrayEntropy(const Numeric* p, const unsigned long len, const bool normalize) { const Numeric zero = Numeric(); bool havePositive = false; long double entropy = 0.0L; long double sum = 1.0L; if (normalize) { sum = std::accumulate(p, p+len, 0.0L); if (sum <= 0.0L) throw std::invalid_argument("In npstat::arrayEntropy: sum of" " array elements is not positive"); } for (unsigned long i=0; i zero) { havePositive = true; const long double prob = p[i]; entropy -= prob*std::log(prob/sum); } } if (!havePositive) throw std::invalid_argument("In npstat::arrayEntropy: there are no" " positive array elements"); entropy /= sum; return entropy/len; } // C++ does not support partial template specialization for // functions, only for classes namespace Private { template struct PoissonLogLikelihood { inline static double calculate(const Real* means, const Numeric* counts, const unsigned long len) { long double sum = 0.0L; for (unsigned long i=0; i(counts[i])); if (dc < 0.0) throw std::invalid_argument( "In npstat::poissonLogLikelihood: " "this function can not handle negative counts"); if (dc > static_cast(ULONG_MAX)) throw std::invalid_argument( "In npstat::poissonLogLikelihood: " "count is too large"); const unsigned long cnt = static_cast(dc); const double m = means[i]; if (cnt) { if (m <= 0.0) throw std::invalid_argument( "In npstat::poissonLogLikelihood: " "non-positive mean encountered with counts present"); sum += (cnt*log(m) - logfactorial(cnt) - m); } else sum -= m; } return sum; } }; template struct PoissonLogLikelihood { inline static double calculate(const Real* means, const unsigned* counts, const unsigned long len) { long double sum = 0.0L; for (unsigned long i=0; i struct PoissonLogLikelihood { inline static double calculate(const Real* means, const unsigned long* counts, const unsigned long len) { long double sum = 0.0L; for (unsigned long i=0; i inline double poissonLogLikelihood(const Real* means, const Numeric* counts, const unsigned long len) { double logli = 0.0; if (len) { assert(means); assert(counts); logli = Private::PoissonLogLikelihood::calculate( means, counts, len); } return logli; } } Index: trunk/npstat/stat/Makefile.am =================================================================== --- trunk/npstat/stat/Makefile.am (revision 603) +++ trunk/npstat/stat/Makefile.am (revision 604) @@ -1,360 +1,362 @@ AM_CPPFLAGS = -I@top_srcdir@/ $(DEPS_CFLAGS) noinst_LTLIBRARIES = libstat.la libstat_la_SOURCES = AbsDistribution1D.cc AbsUnfoldND.cc \ AbsDistributionND.cc amiseOptimalBandwidth.cc CompositeDistribution1D.cc \ CompositeDistributionND.cc CopulaInterpolationND.cc SymbetaParams1D.cc \ Distribution1DFactory.cc Distribution1DReader.cc DistributionNDReader.cc \ Distributions1D.cc DistributionsND.cc CrossCovarianceAccumulator.cc \ fitSbParameters.cc StatAccumulatorArr.cc HistoAxis.cc ResponseMatrix.cc \ InterpolatedDistribution1D.cc JohnsonCurves.cc JohnsonKDESmoother.cc \ LocalPolyFilter1D.cc logLikelihoodPeak.cc PolyFilterCollection1D.cc \ SbMomentsBigGamma.cc SbMomentsCalculator.cc gaussianResponseMatrix.cc \ SequentialCopulaSmoother.cc SequentialPolyFilterND.cc StatAccumulator.cc \ UnitMapInterpolationND.cc WeightedStatAccumulator.cc AbsNtuple.cc \ QuadraticOrthoPolyND.cc NMCombinationSequencer.cc Filter1DBuilders.cc \ StatAccumulatorPair.cc GridRandomizer.cc ConstantBandwidthSmoother1D.cc \ GaussianMixture1D.cc HistoNDCdf.cc scanDensityAsWeight.cc NUHistoAxis.cc \ distributionReadError.cc WeightedStatAccumulatorPair.cc AbsUnfold1D.cc \ ProductSymmetricBetaNDCdf.cc DualHistoAxis.cc multinomialCovariance1D.cc \ StorableMultivariateFunctor.cc StorableMultivariateFunctorReader.cc \ TruncatedDistribution1D.cc neymanPearsonWindow1D.cc AsinhTransform1D.cc \ LOrPEMarginalSmoother.cc LeftCensoredDistribution.cc QuantileTable1D.cc \ RightCensoredDistribution.cc AbsDiscreteDistribution1D.cc convertAxis.cc \ DiscreteDistribution1DReader.cc DiscreteDistributions1D.cc lorpeMise1D.cc \ BernsteinFilter1DBuilder.cc BetaFilter1DBuilder.cc AbsFilter1DBuilder.cc \ continuousDegreeTaper.cc RatioOfNormals.cc AbsCVCopulaSmoother.cc \ DensityScan1D.cc BoundaryHandling.cc SmoothedEMUnfold1D.cc Copulas.cc \ PearsonsChiSquared.cc BinnedKSTest1D.cc MultiscaleEMUnfold1D.cc \ AbsBinnedComparison1D.cc BinnedADTest1D.cc LocalPolyFilter1DReader.cc \ MemoizingSymbetaFilterProvider.cc UGaussConvolution1D.cc BinSummary.cc \ SmoothedEMUnfoldND.cc UnfoldingFilterNDReader.cc AbsUnfoldingFilterND.cc \ UnfoldingBandwidthScannerND.cc DistributionMix1D.cc ScalableGaussND.cc \ InterpolatedDistro1D1P.cc AbsDistributionTransform1D.cc LogTransform1D.cc \ DistributionTransform1DReader.cc TransformedDistribution1D.cc \ WeightTableFilter1DBuilder.cc VerticallyInterpolatedDistribution1D.cc \ LocalMultiFilter1D.cc LogRatioTransform1D.cc IdentityTransform1D.cc \ VariableBandwidthSmoother1D.cc AbsMarginalSmootherBase.cc OSDE1D.cc \ buildInterpolatedHelpers.cc GridInterpolatedDistribution.cc \ AbsCopulaSmootherBase.cc BernsteinCopulaSmoother.cc distro1DStats.cc \ SequentialGroupedCopulaSmoother.cc UnfoldingBandwidthScanner1D.cc \ InterpolatedDistro1DNP.cc volumeDensityFromBinnedRadial.cc \ statUncertainties.cc LocationScaleFamily1D.cc SinhAsinhTransform1D.cc \ AbsKDE1DKernel.cc KDE1DHOSymbetaKernel.cc EdgeworthSeriesMethod.cc \ EdgeworthSeries1D.cc DeltaMixture1D.cc LikelihoodStatisticType.cc \ likelihoodStatisticCumulants.cc includedir = ${prefix}/include/npstat/stat include_HEADERS = AbsBandwidthCV.hh \ AbsBandwidthGCV.hh \ AbsBinnedComparison1D.hh \ AbsBinnedComparison1D.icc \ AbsCompositeDistroBuilder.hh \ AbsCompositeDistroBuilder.icc \ AbsCopulaSmootherBase.hh \ AbsCopulaSmootherBase.icc \ AbsCVCopulaSmoother.hh \ AbsDiscreteDistribution1D.hh \ AbsDistribution1D.hh \ AbsDistributionND.hh \ AbsDistributionND.icc \ AbsDistributionTransform1D.hh \ AbsDistro1DBuilder.hh \ AbsDistro1DBuilder.icc \ AbsFilter1DBuilder.hh \ AbsGridInterpolatedDistribution.hh \ AbsInterpolatedDistribution1D.hh \ AbsInterpolationAlgoND.hh \ AbsKDE1DKernel.hh \ AbsKDE1DKernel.icc \ AbsLossCalculator.hh \ AbsMarginalSmootherBase.hh \ AbsMarginalSmootherBase.icc \ AbsNtuple.hh \ AbsNtuple.icc \ AbsPolyFilter1D.hh \ AbsPolyFilterND.hh \ AbsResponseBoxBuilder.hh \ AbsResponseIntervalBuilder.hh \ AbsSymbetaFilterProvider.hh \ AbsUnfold1D.hh \ AbsUnfoldingFilterND.hh \ AbsUnfoldND.hh \ amiseOptimalBandwidth.hh \ amiseOptimalBandwidth.icc \ ArchivedNtuple.hh \ ArchivedNtuple.icc \ ArrayProjectors.hh \ ArrayProjectors.icc \ arrayStats.hh \ arrayStats.icc \ AsinhTransform1D.hh \ BandwidthCVLeastSquares1D.hh \ BandwidthCVLeastSquares1D.icc \ BandwidthCVLeastSquaresND.hh \ BandwidthCVLeastSquaresND.icc \ BandwidthCVPseudoLogli1D.hh \ BandwidthCVPseudoLogli1D.icc \ BandwidthCVPseudoLogliND.hh \ BandwidthCVPseudoLogliND.icc \ BandwidthGCVLeastSquares1D.hh \ BandwidthGCVLeastSquares1D.icc \ BandwidthGCVLeastSquaresND.hh \ BandwidthGCVLeastSquaresND.icc \ BandwidthGCVPseudoLogli1D.hh \ BandwidthGCVPseudoLogli1D.icc \ BandwidthGCVPseudoLogliND.hh \ BandwidthGCVPseudoLogliND.icc \ BernsteinCopulaSmoother.hh \ BernsteinFilter1DBuilder.hh \ betaKernelsBandwidth.hh \ betaKernelsBandwidth.icc \ BetaFilter1DBuilder.hh \ BinnedADTest1D.hh \ BinnedKSTest1D.hh \ BinSummary.hh \ BinSummary.icc \ BoundaryHandling.hh \ BoundaryMethod.hh \ buildInterpolatedCompositeDistroND.hh \ buildInterpolatedCompositeDistroND.icc \ buildInterpolatedDistro1DNP.hh \ buildInterpolatedDistro1DNP.icc \ buildInterpolatedHelpers.hh \ CensoredQuantileRegression.hh \ CensoredQuantileRegression.icc \ CircularBuffer.hh \ CircularBuffer.icc \ Column.hh \ Column.icc \ CompositeDistribution1D.hh \ CompositeDistributionND.hh \ CompositeDistributionND.icc \ CompositeDistros1D.hh \ ConstantBandwidthSmoother1D.hh \ ConstantBandwidthSmootherND.hh \ ConstantBandwidthSmootherND.icc \ continuousDegreeTaper.hh \ convertAxis.hh \ CopulaInterpolationND.hh \ Copulas.hh \ CrossCovarianceAccumulator.hh \ CrossCovarianceAccumulator.icc \ + cumulantConversion.hh \ + cumulantConversion.icc \ CVCopulaSmoother.hh \ CVCopulaSmoother.icc \ DeltaMixture1D.hh \ DeltaMixture1D.icc \ DensityAveScanND.hh \ DensityScan1D.hh \ DensityScanND.hh \ DiscreteDistribution1DReader.hh \ DiscreteDistributions1D.hh \ discretizationErrorND.hh \ Distribution1DFactory.hh \ Distribution1DReader.hh \ DistributionTransform1DReader.hh \ DistributionMix1D.hh \ DistributionNDReader.hh \ Distributions1D.hh \ Distributions1D.icc \ DistributionsND.hh \ DistributionsND.icc \ distributionReadError.hh \ distro1DStats.hh \ DualHistoAxis.hh \ DummyCompositeDistroBuilder.hh \ DummyDistro1DBuilder.hh \ DummyResponseBoxBuilder.hh \ DummyResponseIntervalBuilder.hh \ EdgeworthSeries1D.hh \ EdgeworthSeriesMethod.hh \ empiricalCopula.hh \ empiricalCopulaHisto.hh \ empiricalCopulaHisto.icc \ empiricalCopula.icc \ fillHistoFromText.hh \ fillHistoFromText.icc \ Filter1DBuilders.hh \ FitUtils.hh \ FitUtils.icc \ GaussianMixture1D.hh \ gaussianResponseMatrix.hh \ GCVCopulaSmoother.hh \ GCVCopulaSmoother.icc \ griddedRobustRegression.hh \ griddedRobustRegression.icc \ GriddedRobustRegressionStop.hh \ GridInterpolatedDistribution.hh \ GridRandomizer.hh \ HistoAxis.hh \ HistoND.hh \ HistoND.icc \ HistoNDCdf.hh \ HistoNDFunctorInstances.hh \ histoStats.hh \ histoStats.icc \ histoUtils.hh \ histoUtils.icc \ IdentityTransform1D.hh \ InMemoryNtuple.hh \ InMemoryNtuple.icc \ InterpolatedDistribution1D.hh \ InterpolatedDistro1D1P.hh \ InterpolatedDistro1DNP.hh \ interpolateHistoND.hh \ interpolateHistoND.icc \ InterpolationFunctorInstances.hh \ JohnsonCurves.hh \ JohnsonKDESmoother.hh \ KDE1D.hh \ KDE1DCV.hh \ KDE1DHOSymbetaKernel.hh \ KDECopulaSmoother.hh \ KDECopulaSmoother.icc \ KDEGroupedCopulaSmoother.hh \ KDEGroupedCopulaSmoother.icc \ KDEFilterND.hh \ KDEFilterND.icc \ kendallsTau.hh \ kendallsTau.icc \ LeftCensoredDistribution.hh \ likelihoodStatisticCumulants.hh \ LikelihoodStatisticType.hh \ LocalLogisticRegression.hh \ LocalLogisticRegression.icc \ LocalMultiFilter1D.hh \ LocalMultiFilter1D.icc \ LocalPolyFilter1D.hh \ LocalPolyFilter1D.icc \ LocalPolyFilter1DReader.hh \ LocalPolyFilterND.hh \ LocalPolyFilterND.icc \ LocalQuadraticLeastSquaresND.hh \ LocalQuadraticLeastSquaresND.icc \ LocalQuantileRegression.hh \ LocalQuantileRegression.icc \ LocationScaleFamily1D.hh \ LocationScaleTransform1.hh \ LocationScaleTransform1.icc \ logLikelihoodPeak.hh \ LogRatioTransform1D.hh \ LogTransform1D.hh \ LOrPECopulaSmoother.hh \ LOrPECopulaSmoother.icc \ LOrPEGroupedCopulaSmoother.hh \ LOrPEGroupedCopulaSmoother.icc \ LOrPEMarginalSmoother.hh \ lorpeBackgroundCVDensity1D.hh \ lorpeBackgroundCVDensity1D.icc \ lorpeBackground1D.hh \ lorpeBackground1D.icc \ lorpeMise1D.hh \ lorpeSmooth1D.hh \ lorpeSmooth1D.icc \ MemoizingSymbetaFilterProvider.hh \ MemoizingSymbetaFilterProvider.icc \ mergeTwoHistos.hh \ mergeTwoHistos.icc \ mirrorWeight.hh \ MultiscaleEMUnfold1D.hh \ multinomialCovariance1D.hh \ MultivariateSumAccumulator.hh \ MultivariateSumsqAccumulator.hh \ MultivariateSumsqAccumulator.icc \ MultivariateWeightedSumAccumulator.hh \ MultivariateWeightedSumsqAccumulator.hh \ MultivariateWeightedSumsqAccumulator.icc \ neymanPearsonWindow1D.hh \ NMCombinationSequencer.hh \ NonparametricCompositeBuilder.hh \ NonparametricCompositeBuilder.icc \ NonparametricDistro1DBuilder.hh \ NonparametricDistro1DBuilder.icc \ NtHistoFill.hh \ NtNtupleFill.hh \ NtRectangularCut.hh \ NtRectangularCut.icc \ NtupleBuffer.hh \ NtupleBuffer.icc \ NtupleRecordTypes.hh \ NtupleRecordTypesFwd.hh \ NtupleReference.hh \ NUHistoAxis.hh \ OrderedPointND.hh \ OrderedPointND.icc \ orthoPoly1DVProducts.hh \ orthoPoly1DVProducts.icc \ OSDE1D.hh \ OSDE1D.icc \ PearsonsChiSquared.hh \ PolyFilterCollection1D.hh \ productResponseMatrix.hh \ productResponseMatrix.icc \ ProductSymmetricBetaNDCdf.hh \ QuadraticOrthoPolyND.hh \ QuadraticOrthoPolyND.icc \ QuantileRegression1D.hh \ QuantileRegression1D.icc \ QuantileTable1D.hh \ RatioOfNormals.hh \ RatioResponseBoxBuilder.hh \ RatioResponseBoxBuilder.icc \ RatioResponseIntervalBuilder.hh \ RatioResponseIntervalBuilder.icc \ ResponseMatrix.hh \ RightCensoredDistribution.hh \ SampleAccumulator.hh \ SampleAccumulator.icc \ SbMomentsCalculator.hh \ ScalableGaussND.hh \ scanDensityAsWeight.hh \ SequentialCopulaSmoother.hh \ SequentialGroupedCopulaSmoother.hh \ SequentialPolyFilterND.hh \ SequentialPolyFilterND.icc \ SinhAsinhTransform1D.hh \ SmoothedEMUnfold1D.hh \ SmoothedEMUnfoldND.hh \ spearmansRho.hh \ spearmansRho.icc \ StatAccumulator.hh \ StatAccumulatorArr.hh \ StatAccumulatorPair.hh \ statUncertainties.hh \ StatUtils.hh \ StatUtils.icc \ StorableHistoNDFunctor.hh \ StorableHistoNDFunctor.icc \ StorableInterpolationFunctor.hh \ StorableInterpolationFunctor.icc \ StorableMultivariateFunctor.hh \ StorableMultivariateFunctorReader.hh \ SymbetaParams1D.hh \ TransformedDistribution1D.hh \ TruncatedDistribution1D.hh \ TwoPointsLTSLoss.hh \ TwoPointsLTSLoss.icc \ UGaussConvolution1D.hh \ UnfoldingBandwidthScanner1D.hh \ UnfoldingBandwidthScannerND.hh \ UnfoldingFilterNDReader.hh \ UnitMapInterpolationND.hh \ variableBandwidthSmooth1D.hh \ variableBandwidthSmooth1D.icc \ VariableBandwidthSmoother1D.hh \ VerticallyInterpolatedDistribution1D.hh \ volumeDensityFromBinnedRadial.hh \ weightedCopulaHisto.hh \ weightedCopulaHisto.icc \ WeightedDistro1DPtr.hh \ WeightedLTSLoss.hh \ WeightedLTSLoss.icc \ WeightedSampleAccumulator.hh \ WeightedSampleAccumulator.icc \ WeightedStatAccumulator.hh \ WeightedStatAccumulatorPair.hh \ WeightTableFilter1DBuilder.hh EXTRA_DIST = 00README.txt npstat_doxy.hh Index: trunk/npstat/stat/EdgeworthSeries1D.hh =================================================================== --- trunk/npstat/stat/EdgeworthSeries1D.hh (revision 603) +++ trunk/npstat/stat/EdgeworthSeries1D.hh (revision 604) @@ -1,124 +1,148 @@ #ifndef NPSTAT_EDGEWORTHSERIES1D_HH_ #define NPSTAT_EDGEWORTHSERIES1D_HH_ /*! // \file EdgeworthSeries1D.hh // // \brief Distribution defined by Edgeworth series w.r.t. normal // // Author: I. Volobouev // // June 2019 */ #include #include "npstat/nm/SimpleFunctors.hh" #include "npstat/stat/AbsDistribution1D.hh" #include "npstat/stat/EdgeworthSeriesMethod.hh" namespace npstat { class EdgeworthSeries1D : public AbsDistribution1D { public: /** // Constructor arguments are as follows: // // cumulants -- The vector of cumulants. The first element // of the vector (with index 0) is the first // cumulant, the second element is the second, etc. // // m -- The method used to construct the distribition. // See EdgeworthSeriesMethod.hh header for further // explanations // // order -- The expansion order in powers of 1/sqrt(n). // O(1/sqrt(n)) is the 0th order, O(1/n) is the first // order, O(1/(n sqrt(n)) is the second order, etc. // Currently, the highest supported order is 4. // // slrMode -- If true, we will assume that the kth cumulant // vanishes (for k > 2) to O(n^{-k/2}) instead of // the usual O(n^{-(k-2)/2}). This is the case for // the SLR statistic. */ EdgeworthSeries1D(const std::vector& cumulants, EdgeworthSeriesMethod m, unsigned order, bool slrMode = false); inline virtual EdgeworthSeries1D* clone() const {return new EdgeworthSeries1D(*this);} inline virtual ~EdgeworthSeries1D() {} virtual double density(double x) const; virtual double cdf(double x) const; virtual double exceedance(double x) const; virtual double quantile(double x) const; /** // Inverse exceedance function. More precise than "quantile(1 - x)" // for small x. */ double inverseExceedance(double x) const; //@{ /** Inspector */ inline EdgeworthSeriesMethod method() const {return m_;} inline bool slrMode() const {return slrMode_;} inline unsigned order() const {return order_;} - double mean() const; - double stdev() const; //@} + /** + // This function returns the constructor argument, not the + // real cumulant which depends on the expansion order used. + // Use the "empiricalCentralMoment" function and then convert + // central moments to cumulants if you need real cumulants. + // The real mean is 0 if order == 0 and cum(0) if order > 0. + */ + inline double cum(const unsigned k) const {return cumulants_.at(k);}; + + /** Mean of the function used to build the expansion */ + double edgMean() const; + + /** Standard deviation of the function used to build the expansion */ + double edgStdev() const; + + /** Edgeworth expansion factor for the density */ double densityFactor(double x) const; + + /** Edgeworth expansion factor for the CDF */ double cdfFactor(double x) const; + /** + // Actual central moment of the density + // (evaluated numerically for degree > 1) + */ + double empiricalCentralMoment(unsigned degree) const; + //@{ /** Prototype needed for I/O */ inline virtual gs::ClassId classId() const {return gs::ClassId(*this);} virtual bool write(std::ostream&) const; //@} static inline const char* classname() {return "npstat::EdgeworthSeries1D";} static inline unsigned version() {return 1;} static EdgeworthSeries1D* read( const gs::ClassId& id, std::istream& is); protected: virtual bool isEqual(const AbsDistribution1D&) const; private: void hermiteCoeffsNormal(long double* buf, unsigned* maxdeg) const; void hermiteCoeffsSLR(long double* buf, unsigned* maxdeg) const; double normalizedCoord(double x) const; double normalizedSigma() const; unsigned minNCumulants() const; std::vector cumulants_; EdgeworthSeriesMethod m_; unsigned order_; bool slrMode_; }; /** This class is mostly useful for testing purposes */ class EdgeworthSeriesMomentFcn : public Functor1 { public: inline EdgeworthSeriesMomentFcn(const EdgeworthSeries1D& series, const unsigned degree) - : series_(series), degree_(degree) {} + : series_(series), mean_(0.0), degree_(degree) + {if (series_.order()) {mean_ = series_.cum(0);}} inline virtual ~EdgeworthSeriesMomentFcn() {} virtual double operator()(const double&) const; private: const EdgeworthSeries1D& series_; + double mean_; unsigned degree_; }; } #endif // NPSTAT_EDGEWORTHSERIES1D_HH_ Index: trunk/NEWS =================================================================== --- trunk/NEWS (revision 603) +++ trunk/NEWS (revision 604) @@ -1,724 +1,727 @@ Version 4.11.0 - development * Supported cumulant calculations for the Wald statistic in the Poisson process model. +* Added functions convertCumulantsToCentralMoments and + convertCentralMomentsToCumulants (header file cumulantConversion.hh). + Version 4.10.0 - July 11 2019, by I. Volobouev * Added SemiInfGaussianQuadrature class. * Added functions arrayMoment, arrayMoments, and arrayCentralMoments. * Added enum EdgeworthSeriesMethod and class EdgeworthSeries1D. * Added DeltaMixture1D class. * Added enum LikelihoodStatisticType. * Added functions "mixtureModelCumulants" and "poissonProcessCumulants" in the header likelihoodStatisticCumulants.hh. Version 4.9.0 - Dec 18 2018, by I. Volobouev * Added "integratePoly" and "jointIntegral" methods to the AbsClassicalOrthoPoly1D class. * Added utility functions "truncatedInverseSqrt" and "matrixIndexPairs". * Added a number of functions to "orthoPoly1DVProducts.hh". * Added classes ChebyshevOrthoPoly1st and ChebyshevOrthoPoly2nd inheriting from AbsClassicalOrthoPoly1D. * Added class HermiteProbOrthoPoly1D. * Added FejerQuadrature class. * Added classe IsoscelesTriangle1D and Logistic1D. * Added classes AbsKDE1DKernel and KDE1DHOSymbetaKernel. * Added static function "optimalDegreeHart" to OSDE1D class. Version 4.8.0 - Jul 9 2018, by I. Volobouev * Added ShiftedLegendreOrthoPoly1D class. * Added Lanczos method to generate recurrence coefficients for the ContOrthoPoly1D class. * Added npstat/stat/orthoPoly1DVProducts.hh file with various utilities for statistical analyis of chaos polynomials. Version 4.7.0 - Jan 13 2018, by I. Volobouev * Added "UniPareto1D" distribution (uniform with Pareto tail to the right). * More coordinate/weight cases for the GaussLegendreQuadrature class. * Added ContOrthoPoly1D class -- continuous orthogonal polynomials with discrete measure. * Added functions "linearLeastSquares" and "tdSymEigen" to the Matrix class. * Added OSDE1D class. * Added classes LocationScaleFamily1D and SinhAsinhTransform1D. * Added new functors (CdfFunctor1D, etc) as AbsDistribution1D helpers. * Small fix in StatAccumulatorArr.cc. Version 4.6.0 - Jan 23 2017, by I. Volobouev * Updated 1-d LOrPE cross validation code (classes AbsBandwidthCV, BandwidthCVLeastSquares1D, BandwidthCVPseudoLogli1D) for use with weighted samples in the case the sample itself is available at the point cross validation is run. Version 4.5.0 - Aug 01 2016, by I. Volobouev * A small fix in OrthoPolyND.icc (switched from cycling over unsigned to unsigned long in the scalar product function). * Implemented Gauss-Hermite quadrature with Gaussian density weight. * Changed the meaning of Quadratic1D and LogQuadratic1D parameters to be consistent with Legendre polynomial coefficients on [-1, 1] (new parameters are 1/2 of old). * Added class MinuitUnbinnedFitFcn1D (to interfaces). * Added function "findRootNewtonRaphson". * Added "statUncertainties" header with various functions. Version 4.4.0 - May 9 2016, by I. Volobouev * Added "timestamp" function. * Improved implementation of BinnedDensity1D::unscaledQuantile function. Certain problems caused by round-off errors are now fixed. * Added the capability to use the single closest parameter cells (thus disabling actual interpolation between parameter values, for speed) to "GridInterpolatedDistribution". Version 4.3.0 - March 19 2016, by I. Volobouev * Put additional assert statements inside OrthoPolyND.icc to prevent phony "array subscript is above array bounds" messages in g++ 4.9.2. * Improved CmdLine.hh. * Additional methods in CopulaInterpolationND and GridInterpolatedDistribution. * Added function "volumeDensityFromBinnedRadial". * Added convenience method "globalFilter" to the OrthoPoly1D class. * Initiated the transition of the Python API from Python 2 to Python 3. Version 4.2.0 - October 29 2015, by I. Volobouev * Added interpolation methods for the marginals to classes "CopulaInterpolationND" and "GridInterpolatedDistribution". * Removed assert on underflow in the "igamc" function. Now in such cases this function simply returns 0.0. Version 4.1.0 - July 27 2015, by I. Volobouev * Made a few additional methods virtual in AbsNtuple. * Declared methods "columnIndices" of AbsNtuple const (as they should be). * Added function "weightedCopulaHisto" to build copulas for samples of weighted points. * Added function "weightedVariableBandwidthSmooth1D" to use variable bandwidth smoothing with weighted histograms. * Added "AbsWeightedMarginalSmoother" interface class for smoothing samples of weighted points. Modified classes ConstantBandwidthSmoother1D, JohnsonKDESmoother, and LOrPEMarginalSmoother to support this interface. * Added class "VariableBandwidthSmoother1D" which implements both AbsMarginalSmoother and AbsWeightedMarginalSmoother interfaces. * Implemented cross-validation for weighted samples. * Implemented "buildInterpolatedCompositeDistroND" for generic construction of multivariate transfer functions. * Implemented "buildInterpolatedDistro1DNP" for generic construction of univariate transfer functions. Version 4.0.1 - June 17 2015, by I. Volobouev * Added "dump_qmc" example executable. Version 4.0.0 - June 10 2015, by I. Volobouev * Complete overhaul of 1-d filter-building code. Addition of new boundary methods is a lot easier now. The user API for choosing a LOrPE boundary method is encapsulated in the new "BoundaryHandling" class. * Implemented a number of new filter builders with different boundary treatments. * Updated the "LocalPolyFilter1D" class so that it holds the local bandwidth factors derived by the filter builders. Version 3.8.0 - June 1 2015, by I. Volobouev * Implemented class ConstSqFilter1DBuilder (declared in the header file npstat/stat/Filter1DBuilders.hh). The "BoundaryMethod" enum has been extended accordingly. Other files using this enum have been updated. * Implemented class FoldingSqFilter1DBuilder. Similar to ConstSqFilter1DBuilder but it also folds the kernel in addition to stretching it. * Added virtual destructors to a number of classes. * Added "externalMemArrayND" with various signatures to allow the use of ArrayND with memory not managed by ArrayND. * Added move constructors and move assignment operators to ArrayND and Matrix classes. Version 3.7.0 - May 10 2015, by I. Volobouev * Better numerical derivative calculation in InterpolatedDistribution1D.cc. * Added class "LocalMultiFilter1D" for fast generation of filters which correspond to each orthogonal polynomial separately. * Added a function calculating the area of n-dimensional sphere. * Added I/O capabilities to the RadialProfileND class. * Added class "LogRatioTransform1D". * Added utility function "multiFill1DHistoWithCDFWeights" (header file histoUtils.hh). * Avoiding underflow of the incomplete gamma in "convertToSphericalRandom". Version 3.6.0 - April 6 2015, by I. Volobouev * Fixed Marsaglia's code calculating the Anderson-Darling statistics (it was breaking down for large values of z). * Added high-level driver function "simpleVariableBandwidthSmooth1D" to automatically build the pilot estimate for "variableBandwidthSmooth1D". * Swithched to log of sigma as Minuit parameter in "minuitFitJohnsonCurves" instead of sigma (linear sigma would sometimes break the fit when Minuit would come up with 0 or negative trial value for it). * Extended "MinuitDensityFitFcn1D" class so that it could be used to fit non-uniformly binned histograms. * Adapted "minuitFitJohnsonCurves" function so that it could be used with histograms templated upon DualHistoAxis. * Added functions "fillArrayCentersPreservingAreas" and "canFillArrayCentersPreservingAreas". * Implemented an interface to monotonous coordinate transformations with the intent of using them in constructing densities. Implemented a number of transforms. * Implemented class "TransformedDistribution1D". * Added class "VerticallyInterpolatedDistro1D1P". * Added utility function "fill1DHistoWithCDFWeights". Version 3.5.0 - February 21 2015, by I. Volobouev * Added "symPDEigenInv" method to the Matrix class. * Added "variableCount" method to unfolding bandwidth scanner classes. * Increased the tolerance parameters in JohnsonSu::initialize and in JohnsonFit constructor. * Bug fix in function "fillHistoFromText". Version 3.4.4 - January 13 2015, by I. Volobouev * Corrected handling of some "assert" statements so that the code compiles correctly with the -DNDEBUG option. Version 3.4.3 - January 5 2015, by I. Volobouev * Implemented class MirroredGauss1D. * Added method "getOracleData" to class UnfoldingBandwidthScanner1D. * Bug fix in FoldingFilter1DBuilder::makeOrthoPoly. Version 3.4.2 - December 15 2014, by I. Volobouev * Implemented InterpolatedDistro1D1P class. Version 3.4.1 - November 07 2014, by I. Volobouev * Implemented "divideTransforms" function for deconvolutions. * Implemented the Moyal distribution. * Added "fillHistoFromText" utility function. * Added "apply_lorpe_1d" example. Version 3.4.0 - October 01 2014, by I. Volobouev * Implemented Hadamard product and Hadamard ratio for matrices. * Bug fix in the "solve_linear_system" lapack interface function. Version 3.3.1 - August 08 2014, by I. Volobouev * Terminate iterative refinement of the unfolding error propagation matrix early in case the solution does not seem to improve. Version 3.3.0 - August 05 2014, by I. Volobouev * Added correction factors to the determination of the number of fitted parameters in various unfolding procedures. Version 3.2.0 - July 25 2014, by I. Volobouev * Added "gaussianResponseMatrix" function for non-uniform binning. * Added Pareto distribution. * Implemented EMS unfolding with sparse matrices. * Added methods "getObservedShape" and "getUnfoldedShape" to the AbsUnfoldND class. * Bug fix in the assignment operator of ProductDistributionND class. Made class ProductDistributionND persistent. * Bug fix in the error propagation for unfolding, in the code which takes into account the extra normalization constant. * Added "productResponseMatrix" function to assist in making sparse response matrices. * Bug fix in the factory constructor of the Cauchy1D class. * Completed implementation of the "RatioOfNormals" class. Version 3.1.0 - June 29 2014, by I. Volobouev * Improved (again) random number generator for the 1-d Gaussian distribution. Something about expectation values of normalized Hermite polynomials over random numbers made by this generator is still not fully understood. The standard deviation of these expectations decreases with the polynomial order (while it should stay constant). It is possible that the numbers of points used are simply insufficient to sample the tails correctly. * Implemented smoothed expectation-maximization (a.k.a. D'Agostini) unfolding for 1-d distributions in classes SmoothedEMUnfold1D and MultiscaleEMUnfold1D. In certain usage scenarios, MultiscaleEMUnfold1D can be more efficient than SmoothedEMUnfold1D. * Implemented smoothed expectation-maximization unfolding for multivariate distributions in a class SmoothedEMUnfoldND. * Added class "UnfoldingBandwidthScanner1D" to study 1-d unfolding behavior as a function of filter bandwidth. * Added class "UnfoldingBandwidthScannerND" to study multivariate unfolding behavior as a function of provided bandwidth values. * Added DummyLocalPolyFilter1D class useful when a filter is needed which does not smooth anything. * Added function "poissonLogLikelihood" (header file npstat/stat/arrayStats.hh). * Added function "pooledDiscreteTabulated1D" (header file npstat/stat/DiscreteDistributions1D.hh). * Implemented class UGaussConvolution1D (convolution of uniform distribution with a Gaussian). * Implemented gamma distribution (class Gamma1D). * Defined interface for comparing binned distributions, AbsBinnedComparison1D. * Implemented several comparison classes for comparing binned distributions: PearsonsChiSquared, BinnedKSTest1D, BinnedADTest1D. Class BinnedKSTest1D pulled in dependence on the "kstest" package. * Made classes LocalPolyFilter1D, LocalPolyFilterND, and SequentialPolyFilterND persistent. * Added code generating dense filter matrices to LocalPolyFilterND and SequentialPolyFilterND (as needed for unfolding). * Made class MemoizingSymbetaFilterProvider persistent. * Implemented function goldenSectionSearchOnAGrid (header file npstat/nm/goldenSectionSearch.hh). * Implemented function parabolicExtremum (header npstat/nm/MathUtils.hh). * Added class DistributionMix1D (header npstat/stat/DistributionMix1D.hh). * Added interface to solving A*X = B, with matrices X and B, to the Matrix class (method "solveLinearSystems"). * Added "reshape" methods to the ArrayND class. * Added "gaussianResponseMatrix" function. * Added a section on unfolding to the documentation. * Added "ems_unfold_1d" example program. Version 3.0.0 - March 14 2014, by I. Volobouev * Added interface to the LAPACK SVD routines. * Added function "lorpeMise1D" to calculate MISE for arbitrary distributions. * Added FoldingFilter1DBuilder class. * Changed interfaces for several high-level functions to use FoldingFilter1DBuilder. The major version number got bumped up. * Split DensityScan1D.hh away from AbsDistribution1D.hh. Version 2.7.0 - March 10 2014, by I. Volobouev * Added code to optimize operations with diagonal matrices. * Added discretizedDistance.hh file for simple L1 and L2 distance calculations with numeric arrays. * Added base class for future unfolding code. * The "reset" method of the Matrix class was renamed into "uninitialize" in order to be consistent with ArrayND. * Added function "multinomialCovariance1D". * Added "polyTimesWeight" method to the OrthoPoly1D class. * Added methods "TtimesThis" and "timesT" to the Matrix class. These methods are more efficient than transpose followed by multiplication. Version 2.6.0 - January 30 2014, by I. Volobouev * Added function "lorpeBackgroundCVDensity1D" which linearizes calculation of the cross validation likelihood in semiparametric fits. Argument "linearizeCrossValidation" was added to MinuitSemiparametricFitFcn1D constructor, "lorpeBackground1D" function, etc. * Added the ability to build filters with center point removed to classes WeightTableFilter1DBuilder and StretchingFilter1DBuilder. The function "symbetaLOrPEFilter1D" now has an appropriate switch. * Added "removeRowAndColumn" method to the Matrix class. * Added CircularBuffer class. * Added various plugin bandwidth functions which work with non-integer polynomial degrees. * Switched to the Legendre polynomial basis for calculating all 1-d orthogonal polynomials (instead of monomial basis). * Added MemoizingSymbetaFilterProvider class. * Added "operator+=" method to the MultivariateSumAccumulator class. * Simplified implementation of the PolyFilterCollection1D class. File PolyFilterCollection1D.icc is removed. * Added "RatioOfNormals" 1-d distribution function. Only the density is currently implemented but not the CDF. * Added ExpMapper1d class. Version 2.5.0 - October 15 2013, by I. Volobouev * Added "getFilterMatrix" method to the LocalPolyFilter1D class. * Added "genEigen" method to the Matrix class (for determination of eigenvalues and eigenvectors of general real matrices). * Refactored the LAPACK interface so that interface functions to floats are automatically generated from interface functions to doubles. See the comment at the end of the "lapack_interface.icc" file for the shell commands to do this. Version 2.4.0 - October 6 2013, by I. Volobouev * Added functions "lorpeBackground1D", "lorpeBgCVPseudoLogli1D", and "lorpeBgLogli1D". * Added minuit interface classes "MinuitLOrPEBgCVFcn1D" and "MinuitSemiparametricFitFcn1D". * Added "ScalableDensityConstructor1D" class for use with Minuit interface functions. * Added classes AbsSymbetaFilterProvider and SymbetaPolyCollection1D. Version 2.3.0 - October 1 2013, by I. Volobouev * Allowed point dimensionality to be larger than the histogram dimensionality in the "empiricalCopulaHisto" function. * Added "keepAllFilters" method to AbsFilter1DBuilder and all derived classes. * Implemented exclusion regions for WeightTableFilter1DBuilder and StretchingFilter1DBuilder. * "symbetaLOrPEFilter1D" function (in the header LocalPolyFilter1D.hh) is updated to take the exclusion mask argument. * Added "continuousDegreeTaper" function which can do something meaningful with the continuous LOrPE degree parameter. Version 2.2.0 - June 30 2013, by I. Volobouev * Added classes DiscreteBernsteinPoly1D and BernsteinFilter1DBuilder. * Added classes DiscreteBeta1D and BetaFilter1DBuilder. * Added BifurcatedGauss1D class to model Gaussian-like distributions with different sigmas on the left and right sides. * Added virtual destructors to the classes declared in the Filter1DBuilders.hh header. * Added a method to the Matrix template to calculate Frobenius norm. * Added methods to the Matrix template to calculate row and column sums. * Added "directSum" method to the Matrix template. * Added constructor from a subrange of another matrix to the Matrix template. * Added code to the LocalPolyFilter1D class that generates a doubly stochastic filter out of an arbitrary filter. * Added "npstat/nm/definiteIntegrals.hh" header and corresponding .cc file for various infrequently used integrals. * Added "betaKernelsBandwidth" function. Version 2.1.0 - June 20 2013, by I. Volobouev * Fixed couple problems which showed up in the robust regression code due to compiler update. * Fixed CensoredQuantileRegressionOnKDTree::process method (needed this-> dereference for some member). Version 2.0.0 - June 15 2013, by I. Volobouev * Updated to use "Geners" version 1.3.0. A few interfaces were changed (API for the string archives was removed because Geners own string archive facilities are now adequate) so the major version number was bumped up. Version 1.6.0 - June 12 2013, by I. Volobouev * Updated some documentation. * Updated fitCompositeJohnson.icc to use simplified histogram constructors. * Bug fix in the "minuitLocalQuantileRegression1D" function. * Changed the "quantileBinFromCdf" function to use unsigned long type for array indices. * Added "weightedLocalQuantileRegression1D" function (namespace npsi) for local regression with single predictor on weighted points. Version 1.5.0 - May 23 2013, by I. Volobouev * Added interfaces to LAPACK routines DSYEVD, DSYEVR, and corresponding single precision versions. * Added the "symPSDefEffectiveRank" method to the Matrix class for calculating effective ranks of symmetric positive semidefinite matrices. * Added converting constructor and assignment operator to the Matrix class. * Run the Gram-Schmidt procedure twice when orthogonal polynomials are derived in order to improve orthogonality. Version 1.4.0 - May 20 2013, by I. Volobouev * Added the "append" method to the AbsNtuple class. Version 1.3.0 - May 10 2013, by I. Volobouev * Added the code for Hermite polynomial series. * Improved random number generator for the 1-d Gaussian distribution. * Added a framework for discrete 1-d distributions as well as two concrete distribution classes (Poisson1D, DiscreteTabulated1D). * Added functions "readCompressedStringArchiveExt" and "writeCompressedStringArchiveExt" which can read/write either compressed or uncompressed string archives, distinguished by file extension. Version 1.2.1 - March 22 2013, by I. Volobouev * Improved CmdLine.hh in the "examples/C++" directory. * Added class QuantileTable1D. * Added classes LeftCensoredDistribution and RightCensoredDistribution. Version 1.2.0 - March 13 2013, by I. Volobouev * Added convenience "fill" methods to work with the ntuples which have small number of columns (up to 10). * Fixed a bug in AbsRandomGenerator for univariate generators making multivariate points. * Added LOrPEMarginalSmoother class. Version 1.1.1 - March 11 2013, by I. Volobouev * Added utility function "symbetaLOrPEFilter1D" which creates 1-d LOrPE filters using kernels from the symmetric beta family (and the Gaussian). * Added high level driver function "lorpeSmooth1D". * Allowed variables with zero variances for calculation of correlation coefficients in "MultivariateSumsqAccumulator". Such variables will have zero correlation coefficients with all other variables. * Added rebinning constructor to the HistoND class. Version 1.1.0 - March 8 2013, by I. Volobouev * Changed NUHistoAxis::fltBinNumber method to produce correct results with interpolation degree 0. It is not yet obvious which method would work best for higher interpolation degrees. * Added functions for converting between StringArchive and python bytearray. They have been placed in a new header: wrap/stringArchiveToBinary.hh. * Added methods "exportMemSlice" and "importMemSlice" to ArrayND. These methods allow for filling array slices from unstructured memory buffers and for exporting array slices to such memory buffers. * Added "simpleColumnNames" function (header file AbsNtuple.hh) to generate trivial column names when ntuple column names are not important. * Added functions "neymanPearsonWindow1D" and "signalToBgMaximum1D". They are declared in a new header npstat/neymanPearsonWindow1D.hh. Version 1.0.5 - December 17 2012, by I. Volobouev * Flush string archives before writing them out in stringArchiveIO.cc. * Added class TruncatedDistribution1D. Version 1.0.4 - November 14 2012, by I. Volobouev * Added utilities for reading/writing Geners string archives to files. * Added BinSummary class. * Doxygen documentation improved. Every header file in stat, nm, rng, and interfaces now has a brief description. Version 1.0.3 - September 27 2012, by I. Volobouev * Fixed some bugs related to moving StorableMultivariateFunctor code from "nm" to "stat". Version 1.0.2 - August 6 2012, by I. Volobouev * Added converting copy constructor to the "LinInterpolatedTableND" class. * Added StorableMultivariateFunctor class (together with the corresponding reader class). * Added StorableInterpolationFunctor class which inherits from the above and can be used with interpolation tables. * Added StorableHistoNDFunctor class which inherits from StorableMultivariateFunctor and can be used to interpolate histogram bins. * Added "transpose" method to HistoND class. * Created DualAxis class. * Created DualHistoAxis class. * Added conversion functions between histogram and grid axes. * Added "mergeTwoHistos" function for smooth merging of two histograms. * Added "ProductSymmetricBetaNDCdf" functor to be used as weight in merging histograms. * Added CoordinateSelector class. Version 1.0.1 - June 29 2012, by I. Volobouev * Implemented class LinInterpolatedTableND with related supporting code. Index: trunk/config.log =================================================================== --- trunk/config.log (revision 603) +++ trunk/config.log (revision 604) @@ -1,942 +1,942 @@ This file contains any messages produced by compilers while running configure, to aid debugging if configure makes a mistake. It was created by npstat configure 4.11.0, which was generated by GNU Autoconf 2.69. Invocation command line was $ ./configure --with-pic ## --------- ## ## Platform. ## ## --------- ## hostname = dawn uname -m = x86_64 uname -r = 4.15.0-54-generic uname -s = Linux uname -v = #58-Ubuntu SMP Mon Jun 24 10:55:24 UTC 2019 /usr/bin/uname -p = unknown /bin/uname -X = unknown /bin/arch = unknown /usr/bin/arch -k = unknown /usr/convex/getsysinfo = unknown /usr/bin/hostinfo = unknown /bin/machine = unknown /usr/bin/oslevel = unknown /bin/universe = unknown PATH: /home/igv/bin PATH: /home/igv/local/bin PATH: /usr/local/anaconda3/bin PATH: /usr/local/bin PATH: /usr/local/root/bin PATH: /usr/local/bin PATH: /bin PATH: /usr/bin PATH: /sbin PATH: /usr/sbin PATH: . ## ----------- ## ## Core tests. ## ## ----------- ## configure:2421: checking for a BSD-compatible install configure:2489: result: /usr/bin/install -c configure:2500: checking whether build environment is sane configure:2555: result: yes configure:2706: checking for a thread-safe mkdir -p configure:2745: result: /bin/mkdir -p configure:2752: checking for gawk configure:2768: found /usr/bin/gawk configure:2779: result: gawk configure:2790: checking whether make sets $(MAKE) configure:2812: result: yes configure:2841: checking whether make supports nested variables configure:2858: result: yes configure:3041: checking for pkg-config configure:3059: found /usr/bin/pkg-config configure:3071: result: /usr/bin/pkg-config configure:3096: checking pkg-config is at least version 0.9.0 configure:3099: result: yes configure:3109: checking for DEPS configure:3116: $PKG_CONFIG --exists --print-errors "fftw3 >= 3.1.2 geners >= 1.3.0 kstest >= 2.0.0" configure:3119: $? = 0 configure:3133: $PKG_CONFIG --exists --print-errors "fftw3 >= 3.1.2 geners >= 1.3.0 kstest >= 2.0.0" configure:3136: $? = 0 configure:3194: result: yes configure:3257: checking for g++ configure:3273: found /usr/bin/g++ configure:3284: result: g++ configure:3311: checking for C++ compiler version configure:3320: g++ --version >&5 g++ (Ubuntu 7.4.0-1ubuntu1~18.04.1) 7.4.0 Copyright (C) 2017 Free Software Foundation, Inc. This is free software; see the source for copying conditions. There is NO warranty; not even for MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. configure:3331: $? = 0 configure:3320: g++ -v >&5 Using built-in specs. COLLECT_GCC=g++ COLLECT_LTO_WRAPPER=/usr/lib/gcc/x86_64-linux-gnu/7/lto-wrapper OFFLOAD_TARGET_NAMES=nvptx-none OFFLOAD_TARGET_DEFAULT=1 Target: x86_64-linux-gnu Configured with: ../src/configure -v --with-pkgversion='Ubuntu 7.4.0-1ubuntu1~18.04.1' --with-bugurl=file:///usr/share/doc/gcc-7/README.Bugs --enable-languages=c,ada,c++,go,brig,d,fortran,objc,obj-c++ --prefix=/usr --with-gcc-major-version-only --program-suffix=-7 --program-prefix=x86_64-linux-gnu- --enable-shared --enable-linker-build-id --libexecdir=/usr/lib --without-included-gettext --enable-threads=posix --libdir=/usr/lib --enable-nls --with-sysroot=/ --enable-clocale=gnu --enable-libstdcxx-debug --enable-libstdcxx-time=yes --with-default-libstdcxx-abi=new --enable-gnu-unique-object --disable-vtable-verify --enable-libmpx --enable-plugin --enable-default-pie --with-system-zlib --with-target-system-zlib --enable-objc-gc=auto --enable-multiarch --disable-werror --with-arch-32=i686 --with-abi=m64 --with-multilib-list=m32,m64,mx32 --enable-multilib --with-tune=generic --enable-offload-targets=nvptx-none --without-cuda-driver --enable-checking=release --build=x86_64-linux-gnu --host=x86_64-linux-gnu --target=x86_64-linux-gnu Thread model: posix gcc version 7.4.0 (Ubuntu 7.4.0-1ubuntu1~18.04.1) configure:3331: $? = 0 configure:3320: g++ -V >&5 g++: error: unrecognized command line option '-V' g++: fatal error: no input files compilation terminated. configure:3331: $? = 1 configure:3320: g++ -qversion >&5 g++: error: unrecognized command line option '-qversion'; did you mean '--version'? g++: fatal error: no input files compilation terminated. configure:3331: $? = 1 configure:3351: checking whether the C++ compiler works configure:3373: g++ -std=c++11 -O3 -Wall -W -Werror conftest.cpp >&5 configure:3377: $? = 0 configure:3425: result: yes configure:3428: checking for C++ compiler default output file name configure:3430: result: a.out configure:3436: checking for suffix of executables configure:3443: g++ -o conftest -std=c++11 -O3 -Wall -W -Werror conftest.cpp >&5 configure:3447: $? = 0 configure:3469: result: configure:3491: checking whether we are cross compiling configure:3499: g++ -o conftest -std=c++11 -O3 -Wall -W -Werror conftest.cpp >&5 configure:3503: $? = 0 configure:3510: ./conftest configure:3514: $? = 0 configure:3529: result: no configure:3534: checking for suffix of object files configure:3556: g++ -c -std=c++11 -O3 -Wall -W -Werror conftest.cpp >&5 configure:3560: $? = 0 configure:3581: result: o configure:3585: checking whether we are using the GNU C++ compiler configure:3604: g++ -c -std=c++11 -O3 -Wall -W -Werror conftest.cpp >&5 configure:3604: $? = 0 configure:3613: result: yes configure:3622: checking whether g++ accepts -g configure:3642: g++ -c -g conftest.cpp >&5 configure:3642: $? = 0 configure:3683: result: yes configure:3717: checking for style of include used by make configure:3745: result: GNU configure:3771: checking dependency style of g++ configure:3882: result: gcc3 configure:3951: checking for g77 configure:3967: found /home/igv/bin/g77 configure:3978: result: g77 configure:4004: checking for Fortran 77 compiler version configure:4013: g77 --version >&5 GNU Fortran (Ubuntu 7.4.0-1ubuntu1~18.04.1) 7.4.0 Copyright (C) 2017 Free Software Foundation, Inc. This is free software; see the source for copying conditions. There is NO warranty; not even for MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. configure:4024: $? = 0 configure:4013: g77 -v >&5 Using built-in specs. COLLECT_GCC=g77 COLLECT_LTO_WRAPPER=/usr/lib/gcc/x86_64-linux-gnu/7/lto-wrapper OFFLOAD_TARGET_NAMES=nvptx-none OFFLOAD_TARGET_DEFAULT=1 Target: x86_64-linux-gnu Configured with: ../src/configure -v --with-pkgversion='Ubuntu 7.4.0-1ubuntu1~18.04.1' --with-bugurl=file:///usr/share/doc/gcc-7/README.Bugs --enable-languages=c,ada,c++,go,brig,d,fortran,objc,obj-c++ --prefix=/usr --with-gcc-major-version-only --program-suffix=-7 --program-prefix=x86_64-linux-gnu- --enable-shared --enable-linker-build-id --libexecdir=/usr/lib --without-included-gettext --enable-threads=posix --libdir=/usr/lib --enable-nls --with-sysroot=/ --enable-clocale=gnu --enable-libstdcxx-debug --enable-libstdcxx-time=yes --with-default-libstdcxx-abi=new --enable-gnu-unique-object --disable-vtable-verify --enable-libmpx --enable-plugin --enable-default-pie --with-system-zlib --with-target-system-zlib --enable-objc-gc=auto --enable-multiarch --disable-werror --with-arch-32=i686 --with-abi=m64 --with-multilib-list=m32,m64,mx32 --enable-multilib --with-tune=generic --enable-offload-targets=nvptx-none --without-cuda-driver --enable-checking=release --build=x86_64-linux-gnu --host=x86_64-linux-gnu --target=x86_64-linux-gnu Thread model: posix gcc version 7.4.0 (Ubuntu 7.4.0-1ubuntu1~18.04.1) configure:4024: $? = 0 configure:4013: g77 -V >&5 g77: error: unrecognized command line option '-V' g77: fatal error: no input files compilation terminated. configure:4024: $? = 1 configure:4013: g77 -qversion >&5 g77: error: unrecognized command line option '-qversion'; did you mean '--version'? g77: fatal error: no input files compilation terminated. configure:4024: $? = 1 configure:4033: checking whether we are using the GNU Fortran 77 compiler configure:4046: g77 -c conftest.F >&5 configure:4046: $? = 0 configure:4055: result: yes configure:4061: checking whether g77 accepts -g configure:4072: g77 -c -g conftest.f >&5 configure:4072: $? = 0 configure:4080: result: yes configure:4113: checking build system type configure:4127: result: x86_64-pc-linux-gnu configure:4147: checking host system type configure:4160: result: x86_64-pc-linux-gnu configure:4185: checking how to get verbose linking output from g77 configure:4195: g77 -c -g -O2 conftest.f >&5 configure:4195: $? = 0 configure:4213: g77 -o conftest -g -O2 -v conftest.f Using built-in specs. Target: x86_64-linux-gnu Thread model: posix gcc version 7.4.0 (Ubuntu 7.4.0-1ubuntu1~18.04.1) - /usr/lib/gcc/x86_64-linux-gnu/7/f951 conftest.f -ffixed-form -quiet -dumpbase conftest.f -mtune=generic -march=x86-64 -auxbase conftest -g -O2 -version -fintrinsic-modules-path /usr/lib/gcc/x86_64-linux-gnu/7/finclude -o /tmp/cc57IGvN.s + /usr/lib/gcc/x86_64-linux-gnu/7/f951 conftest.f -ffixed-form -quiet -dumpbase conftest.f -mtune=generic -march=x86-64 -auxbase conftest -g -O2 -version -fintrinsic-modules-path /usr/lib/gcc/x86_64-linux-gnu/7/finclude -o /tmp/ccd2irj4.s GNU Fortran (Ubuntu 7.4.0-1ubuntu1~18.04.1) version 7.4.0 (x86_64-linux-gnu) compiled by GNU C version 7.4.0, GMP version 6.1.2, MPFR version 4.0.1, MPC version 1.1.0, isl version isl-0.19-GMP GGC heuristics: --param ggc-min-expand=100 --param ggc-min-heapsize=131072 GNU Fortran2008 (Ubuntu 7.4.0-1ubuntu1~18.04.1) version 7.4.0 (x86_64-linux-gnu) compiled by GNU C version 7.4.0, GMP version 6.1.2, MPFR version 4.0.1, MPC version 1.1.0, isl version isl-0.19-GMP GGC heuristics: --param ggc-min-expand=100 --param ggc-min-heapsize=131072 - as -v --64 -o /tmp/ccW26QG0.o /tmp/cc57IGvN.s + as -v --64 -o /tmp/ccwvZqgs.o /tmp/ccd2irj4.s GNU assembler version 2.30 (x86_64-linux-gnu) using BFD version (GNU Binutils for Ubuntu) 2.30 Reading specs from /usr/lib/gcc/x86_64-linux-gnu/7/libgfortran.spec rename spec lib to liborig - /usr/lib/gcc/x86_64-linux-gnu/7/collect2 -plugin /usr/lib/gcc/x86_64-linux-gnu/7/liblto_plugin.so -plugin-opt=/usr/lib/gcc/x86_64-linux-gnu/7/lto-wrapper -plugin-opt=-fresolution=/tmp/ccrY2OSd.res -plugin-opt=-pass-through=-lgcc_s -plugin-opt=-pass-through=-lgcc -plugin-opt=-pass-through=-lquadmath -plugin-opt=-pass-through=-lm -plugin-opt=-pass-through=-lgcc_s -plugin-opt=-pass-through=-lgcc -plugin-opt=-pass-through=-lc -plugin-opt=-pass-through=-lgcc_s -plugin-opt=-pass-through=-lgcc --sysroot=/ --build-id --eh-frame-hdr -m elf_x86_64 --hash-style=gnu --as-needed -dynamic-linker /lib64/ld-linux-x86-64.so.2 -pie -z now -z relro -o conftest /usr/lib/gcc/x86_64-linux-gnu/7/../../../x86_64-linux-gnu/Scrt1.o /usr/lib/gcc/x86_64-linux-gnu/7/../../../x86_64-linux-gnu/crti.o /usr/lib/gcc/x86_64-linux-gnu/7/crtbeginS.o -L/usr/lib/gcc/x86_64-linux-gnu/7 -L/usr/lib/gcc/x86_64-linux-gnu/7/../../../x86_64-linux-gnu -L/usr/lib/gcc/x86_64-linux-gnu/7/../../../../lib -L/lib/x86_64-linux-gnu -L/lib/../lib -L/usr/lib/x86_64-linux-gnu -L/usr/lib/../lib -L/usr/lib/gcc/x86_64-linux-gnu/7/../../.. /tmp/ccW26QG0.o -lgfortran -lm -lgcc_s -lgcc -lquadmath -lm -lgcc_s -lgcc -lc -lgcc_s -lgcc /usr/lib/gcc/x86_64-linux-gnu/7/crtendS.o /usr/lib/gcc/x86_64-linux-gnu/7/../../../x86_64-linux-gnu/crtn.o + /usr/lib/gcc/x86_64-linux-gnu/7/collect2 -plugin /usr/lib/gcc/x86_64-linux-gnu/7/liblto_plugin.so -plugin-opt=/usr/lib/gcc/x86_64-linux-gnu/7/lto-wrapper -plugin-opt=-fresolution=/tmp/ccL2hdeQ.res -plugin-opt=-pass-through=-lgcc_s -plugin-opt=-pass-through=-lgcc -plugin-opt=-pass-through=-lquadmath -plugin-opt=-pass-through=-lm -plugin-opt=-pass-through=-lgcc_s -plugin-opt=-pass-through=-lgcc -plugin-opt=-pass-through=-lc -plugin-opt=-pass-through=-lgcc_s -plugin-opt=-pass-through=-lgcc --sysroot=/ --build-id --eh-frame-hdr -m elf_x86_64 --hash-style=gnu --as-needed -dynamic-linker /lib64/ld-linux-x86-64.so.2 -pie -z now -z relro -o conftest /usr/lib/gcc/x86_64-linux-gnu/7/../../../x86_64-linux-gnu/Scrt1.o /usr/lib/gcc/x86_64-linux-gnu/7/../../../x86_64-linux-gnu/crti.o /usr/lib/gcc/x86_64-linux-gnu/7/crtbeginS.o -L/usr/lib/gcc/x86_64-linux-gnu/7 -L/usr/lib/gcc/x86_64-linux-gnu/7/../../../x86_64-linux-gnu -L/usr/lib/gcc/x86_64-linux-gnu/7/../../../../lib -L/lib/x86_64-linux-gnu -L/lib/../lib -L/usr/lib/x86_64-linux-gnu -L/usr/lib/../lib -L/usr/lib/gcc/x86_64-linux-gnu/7/../../.. /tmp/ccwvZqgs.o -lgfortran -lm -lgcc_s -lgcc -lquadmath -lm -lgcc_s -lgcc -lc -lgcc_s -lgcc /usr/lib/gcc/x86_64-linux-gnu/7/crtendS.o /usr/lib/gcc/x86_64-linux-gnu/7/../../../x86_64-linux-gnu/crtn.o configure:4296: result: -v configure:4298: checking for Fortran 77 libraries of g77 configure:4321: g77 -o conftest -g -O2 -v conftest.f Using built-in specs. Target: x86_64-linux-gnu Thread model: posix gcc version 7.4.0 (Ubuntu 7.4.0-1ubuntu1~18.04.1) - /usr/lib/gcc/x86_64-linux-gnu/7/f951 conftest.f -ffixed-form -quiet -dumpbase conftest.f -mtune=generic -march=x86-64 -auxbase conftest -g -O2 -version -fintrinsic-modules-path /usr/lib/gcc/x86_64-linux-gnu/7/finclude -o /tmp/ccexDKkQ.s + /usr/lib/gcc/x86_64-linux-gnu/7/f951 conftest.f -ffixed-form -quiet -dumpbase conftest.f -mtune=generic -march=x86-64 -auxbase conftest -g -O2 -version -fintrinsic-modules-path /usr/lib/gcc/x86_64-linux-gnu/7/finclude -o /tmp/cc5HRqb6.s GNU Fortran (Ubuntu 7.4.0-1ubuntu1~18.04.1) version 7.4.0 (x86_64-linux-gnu) compiled by GNU C version 7.4.0, GMP version 6.1.2, MPFR version 4.0.1, MPC version 1.1.0, isl version isl-0.19-GMP GGC heuristics: --param ggc-min-expand=100 --param ggc-min-heapsize=131072 GNU Fortran2008 (Ubuntu 7.4.0-1ubuntu1~18.04.1) version 7.4.0 (x86_64-linux-gnu) compiled by GNU C version 7.4.0, GMP version 6.1.2, MPFR version 4.0.1, MPC version 1.1.0, isl version isl-0.19-GMP GGC heuristics: --param ggc-min-expand=100 --param ggc-min-heapsize=131072 - as -v --64 -o /tmp/ccHlDEE3.o /tmp/ccexDKkQ.s + as -v --64 -o /tmp/cct0HYgu.o /tmp/cc5HRqb6.s GNU assembler version 2.30 (x86_64-linux-gnu) using BFD version (GNU Binutils for Ubuntu) 2.30 Reading specs from /usr/lib/gcc/x86_64-linux-gnu/7/libgfortran.spec rename spec lib to liborig - /usr/lib/gcc/x86_64-linux-gnu/7/collect2 -plugin /usr/lib/gcc/x86_64-linux-gnu/7/liblto_plugin.so -plugin-opt=/usr/lib/gcc/x86_64-linux-gnu/7/lto-wrapper -plugin-opt=-fresolution=/tmp/ccWEnkZg.res -plugin-opt=-pass-through=-lgcc_s -plugin-opt=-pass-through=-lgcc -plugin-opt=-pass-through=-lquadmath -plugin-opt=-pass-through=-lm -plugin-opt=-pass-through=-lgcc_s -plugin-opt=-pass-through=-lgcc -plugin-opt=-pass-through=-lc -plugin-opt=-pass-through=-lgcc_s -plugin-opt=-pass-through=-lgcc --sysroot=/ --build-id --eh-frame-hdr -m elf_x86_64 --hash-style=gnu --as-needed -dynamic-linker /lib64/ld-linux-x86-64.so.2 -pie -z now -z relro -o conftest /usr/lib/gcc/x86_64-linux-gnu/7/../../../x86_64-linux-gnu/Scrt1.o /usr/lib/gcc/x86_64-linux-gnu/7/../../../x86_64-linux-gnu/crti.o /usr/lib/gcc/x86_64-linux-gnu/7/crtbeginS.o -L/usr/lib/gcc/x86_64-linux-gnu/7 -L/usr/lib/gcc/x86_64-linux-gnu/7/../../../x86_64-linux-gnu -L/usr/lib/gcc/x86_64-linux-gnu/7/../../../../lib -L/lib/x86_64-linux-gnu -L/lib/../lib -L/usr/lib/x86_64-linux-gnu -L/usr/lib/../lib -L/usr/lib/gcc/x86_64-linux-gnu/7/../../.. /tmp/ccHlDEE3.o -lgfortran -lm -lgcc_s -lgcc -lquadmath -lm -lgcc_s -lgcc -lc -lgcc_s -lgcc /usr/lib/gcc/x86_64-linux-gnu/7/crtendS.o /usr/lib/gcc/x86_64-linux-gnu/7/../../../x86_64-linux-gnu/crtn.o + /usr/lib/gcc/x86_64-linux-gnu/7/collect2 -plugin /usr/lib/gcc/x86_64-linux-gnu/7/liblto_plugin.so -plugin-opt=/usr/lib/gcc/x86_64-linux-gnu/7/lto-wrapper -plugin-opt=-fresolution=/tmp/cc5WtfnS.res -plugin-opt=-pass-through=-lgcc_s -plugin-opt=-pass-through=-lgcc -plugin-opt=-pass-through=-lquadmath -plugin-opt=-pass-through=-lm -plugin-opt=-pass-through=-lgcc_s -plugin-opt=-pass-through=-lgcc -plugin-opt=-pass-through=-lc -plugin-opt=-pass-through=-lgcc_s -plugin-opt=-pass-through=-lgcc --sysroot=/ --build-id --eh-frame-hdr -m elf_x86_64 --hash-style=gnu --as-needed -dynamic-linker /lib64/ld-linux-x86-64.so.2 -pie -z now -z relro -o conftest /usr/lib/gcc/x86_64-linux-gnu/7/../../../x86_64-linux-gnu/Scrt1.o /usr/lib/gcc/x86_64-linux-gnu/7/../../../x86_64-linux-gnu/crti.o /usr/lib/gcc/x86_64-linux-gnu/7/crtbeginS.o -L/usr/lib/gcc/x86_64-linux-gnu/7 -L/usr/lib/gcc/x86_64-linux-gnu/7/../../../x86_64-linux-gnu -L/usr/lib/gcc/x86_64-linux-gnu/7/../../../../lib -L/lib/x86_64-linux-gnu -L/lib/../lib -L/usr/lib/x86_64-linux-gnu -L/usr/lib/../lib -L/usr/lib/gcc/x86_64-linux-gnu/7/../../.. /tmp/cct0HYgu.o -lgfortran -lm -lgcc_s -lgcc -lquadmath -lm -lgcc_s -lgcc -lc -lgcc_s -lgcc /usr/lib/gcc/x86_64-linux-gnu/7/crtendS.o /usr/lib/gcc/x86_64-linux-gnu/7/../../../x86_64-linux-gnu/crtn.o configure:4517: result: -L/usr/lib/gcc/x86_64-linux-gnu/7 -L/usr/lib/gcc/x86_64-linux-gnu/7/../../../x86_64-linux-gnu -L/usr/lib/gcc/x86_64-linux-gnu/7/../../../../lib -L/lib/x86_64-linux-gnu -L/lib/../lib -L/usr/lib/x86_64-linux-gnu -L/usr/lib/../lib -L/usr/lib/gcc/x86_64-linux-gnu/7/../../.. -lgfortran -lm -lquadmath configure:4579: checking how to print strings configure:4606: result: printf configure:4675: checking for gcc configure:4691: found /usr/bin/gcc configure:4702: result: gcc configure:4931: checking for C compiler version configure:4940: gcc --version >&5 gcc (Ubuntu 7.4.0-1ubuntu1~18.04.1) 7.4.0 Copyright (C) 2017 Free Software Foundation, Inc. This is free software; see the source for copying conditions. There is NO warranty; not even for MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. configure:4951: $? = 0 configure:4940: gcc -v >&5 Using built-in specs. COLLECT_GCC=gcc COLLECT_LTO_WRAPPER=/usr/lib/gcc/x86_64-linux-gnu/7/lto-wrapper OFFLOAD_TARGET_NAMES=nvptx-none OFFLOAD_TARGET_DEFAULT=1 Target: x86_64-linux-gnu Configured with: ../src/configure -v --with-pkgversion='Ubuntu 7.4.0-1ubuntu1~18.04.1' --with-bugurl=file:///usr/share/doc/gcc-7/README.Bugs --enable-languages=c,ada,c++,go,brig,d,fortran,objc,obj-c++ --prefix=/usr --with-gcc-major-version-only --program-suffix=-7 --program-prefix=x86_64-linux-gnu- --enable-shared --enable-linker-build-id --libexecdir=/usr/lib --without-included-gettext --enable-threads=posix --libdir=/usr/lib --enable-nls --with-sysroot=/ --enable-clocale=gnu --enable-libstdcxx-debug --enable-libstdcxx-time=yes --with-default-libstdcxx-abi=new --enable-gnu-unique-object --disable-vtable-verify --enable-libmpx --enable-plugin --enable-default-pie --with-system-zlib --with-target-system-zlib --enable-objc-gc=auto --enable-multiarch --disable-werror --with-arch-32=i686 --with-abi=m64 --with-multilib-list=m32,m64,mx32 --enable-multilib --with-tune=generic --enable-offload-targets=nvptx-none --without-cuda-driver --enable-checking=release --build=x86_64-linux-gnu --host=x86_64-linux-gnu --target=x86_64-linux-gnu Thread model: posix gcc version 7.4.0 (Ubuntu 7.4.0-1ubuntu1~18.04.1) configure:4951: $? = 0 configure:4940: gcc -V >&5 gcc: error: unrecognized command line option '-V' gcc: fatal error: no input files compilation terminated. configure:4951: $? = 1 configure:4940: gcc -qversion >&5 gcc: error: unrecognized command line option '-qversion'; did you mean '--version'? gcc: fatal error: no input files compilation terminated. configure:4951: $? = 1 configure:4955: checking whether we are using the GNU C compiler configure:4974: gcc -c conftest.c >&5 configure:4974: $? = 0 configure:4983: result: yes configure:4992: checking whether gcc accepts -g configure:5012: gcc -c -g conftest.c >&5 configure:5012: $? = 0 configure:5053: result: yes configure:5070: checking for gcc option to accept ISO C89 configure:5133: gcc -c -g -O2 conftest.c >&5 configure:5133: $? = 0 configure:5146: result: none needed configure:5171: checking whether gcc understands -c and -o together configure:5193: gcc -c conftest.c -o conftest2.o configure:5196: $? = 0 configure:5193: gcc -c conftest.c -o conftest2.o configure:5196: $? = 0 configure:5208: result: yes configure:5227: checking dependency style of gcc configure:5338: result: gcc3 configure:5353: checking for a sed that does not truncate output configure:5417: result: /bin/sed configure:5435: checking for grep that handles long lines and -e configure:5493: result: /bin/grep configure:5498: checking for egrep configure:5560: result: /bin/grep -E configure:5565: checking for fgrep configure:5627: result: /bin/grep -F configure:5662: checking for ld used by gcc configure:5729: result: /usr/bin/ld configure:5736: checking if the linker (/usr/bin/ld) is GNU ld configure:5751: result: yes configure:5763: checking for BSD- or MS-compatible name lister (nm) configure:5817: result: /usr/bin/nm -B configure:5947: checking the name lister (/usr/bin/nm -B) interface configure:5954: gcc -c -g -O2 conftest.c >&5 configure:5957: /usr/bin/nm -B "conftest.o" configure:5960: output 0000000000000000 B some_variable configure:5967: result: BSD nm configure:5970: checking whether ln -s works configure:5974: result: yes configure:5982: checking the maximum length of command line arguments configure:6113: result: 1572864 configure:6161: checking how to convert x86_64-pc-linux-gnu file names to x86_64-pc-linux-gnu format configure:6201: result: func_convert_file_noop configure:6208: checking how to convert x86_64-pc-linux-gnu file names to toolchain format configure:6228: result: func_convert_file_noop configure:6235: checking for /usr/bin/ld option to reload object files configure:6242: result: -r configure:6316: checking for objdump configure:6332: found /usr/bin/objdump configure:6343: result: objdump configure:6375: checking how to recognize dependent libraries configure:6575: result: pass_all configure:6660: checking for dlltool configure:6690: result: no configure:6720: checking how to associate runtime and link libraries configure:6747: result: printf %s\n configure:6808: checking for ar configure:6824: found /usr/bin/ar configure:6835: result: ar configure:6872: checking for archiver @FILE support configure:6889: gcc -c -g -O2 conftest.c >&5 configure:6889: $? = 0 configure:6892: ar cru libconftest.a @conftest.lst >&5 ar: `u' modifier ignored since `D' is the default (see `U') configure:6895: $? = 0 configure:6900: ar cru libconftest.a @conftest.lst >&5 ar: `u' modifier ignored since `D' is the default (see `U') ar: conftest.o: No such file or directory configure:6903: $? = 1 configure:6915: result: @ configure:6973: checking for strip configure:6989: found /usr/bin/strip configure:7000: result: strip configure:7072: checking for ranlib configure:7088: found /usr/bin/ranlib configure:7099: result: ranlib configure:7201: checking command to parse /usr/bin/nm -B output from gcc object configure:7354: gcc -c -g -O2 conftest.c >&5 configure:7357: $? = 0 configure:7361: /usr/bin/nm -B conftest.o \| sed -n -e 's/^.*[ ]\([ABCDGIRSTW][ABCDGIRSTW]*\)[ ][ ]*\([_A-Za-z][_A-Za-z0-9]*\)$/\1 \2 \2/p' | sed '/ __gnu_lto/d' \> conftest.nm configure:7364: $? = 0 configure:7430: gcc -o conftest -g -O2 conftest.c conftstm.o >&5 configure:7433: $? = 0 configure:7471: result: ok configure:7518: checking for sysroot configure:7548: result: no configure:7555: checking for a working dd configure:7593: result: /bin/dd configure:7597: checking how to truncate binary pipes configure:7612: result: /bin/dd bs=4096 count=1 configure:7748: gcc -c -g -O2 conftest.c >&5 configure:7751: $? = 0 configure:7941: checking for mt configure:7957: found /bin/mt configure:7968: result: mt configure:7991: checking if mt is a manifest tool configure:7997: mt '-?' configure:8005: result: no configure:8682: checking how to run the C preprocessor configure:8713: gcc -E conftest.c configure:8713: $? = 0 configure:8727: gcc -E conftest.c conftest.c:11:10: fatal error: ac_nonexistent.h: No such file or directory #include ^~~~~~~~~~~~~~~~~~ compilation terminated. configure:8727: $? = 1 configure: failed program was: | /* confdefs.h */ | #define PACKAGE_NAME "npstat" | #define PACKAGE_TARNAME "npstat" | #define PACKAGE_VERSION "4.11.0" | #define PACKAGE_STRING "npstat 4.11.0" | #define PACKAGE_BUGREPORT "" | #define PACKAGE_URL "" | #define PACKAGE "npstat" | #define VERSION "4.11.0" | /* end confdefs.h. */ | #include configure:8752: result: gcc -E configure:8772: gcc -E conftest.c configure:8772: $? = 0 configure:8786: gcc -E conftest.c conftest.c:11:10: fatal error: ac_nonexistent.h: No such file or directory #include ^~~~~~~~~~~~~~~~~~ compilation terminated. configure:8786: $? = 1 configure: failed program was: | /* confdefs.h */ | #define PACKAGE_NAME "npstat" | #define PACKAGE_TARNAME "npstat" | #define PACKAGE_VERSION "4.11.0" | #define PACKAGE_STRING "npstat 4.11.0" | #define PACKAGE_BUGREPORT "" | #define PACKAGE_URL "" | #define PACKAGE "npstat" | #define VERSION "4.11.0" | /* end confdefs.h. */ | #include configure:8815: checking for ANSI C header files configure:8835: gcc -c -g -O2 conftest.c >&5 configure:8835: $? = 0 configure:8908: gcc -o conftest -g -O2 conftest.c >&5 configure:8908: $? = 0 configure:8908: ./conftest configure:8908: $? = 0 configure:8919: result: yes configure:8932: checking for sys/types.h configure:8932: gcc -c -g -O2 conftest.c >&5 configure:8932: $? = 0 configure:8932: result: yes configure:8932: checking for sys/stat.h configure:8932: gcc -c -g -O2 conftest.c >&5 configure:8932: $? = 0 configure:8932: result: yes configure:8932: checking for stdlib.h configure:8932: gcc -c -g -O2 conftest.c >&5 configure:8932: $? = 0 configure:8932: result: yes configure:8932: checking for string.h configure:8932: gcc -c -g -O2 conftest.c >&5 configure:8932: $? = 0 configure:8932: result: yes configure:8932: checking for memory.h configure:8932: gcc -c -g -O2 conftest.c >&5 configure:8932: $? = 0 configure:8932: result: yes configure:8932: checking for strings.h configure:8932: gcc -c -g -O2 conftest.c >&5 configure:8932: $? = 0 configure:8932: result: yes configure:8932: checking for inttypes.h configure:8932: gcc -c -g -O2 conftest.c >&5 configure:8932: $? = 0 configure:8932: result: yes configure:8932: checking for stdint.h configure:8932: gcc -c -g -O2 conftest.c >&5 configure:8932: $? = 0 configure:8932: result: yes configure:8932: checking for unistd.h configure:8932: gcc -c -g -O2 conftest.c >&5 configure:8932: $? = 0 configure:8932: result: yes configure:8946: checking for dlfcn.h configure:8946: gcc -c -g -O2 conftest.c >&5 configure:8946: $? = 0 configure:8946: result: yes configure:9213: checking for objdir configure:9228: result: .libs configure:9492: checking if gcc supports -fno-rtti -fno-exceptions configure:9510: gcc -c -g -O2 -fno-rtti -fno-exceptions conftest.c >&5 cc1: warning: command line option '-fno-rtti' is valid for C++/ObjC++ but not for C configure:9514: $? = 0 configure:9527: result: no configure:9885: checking for gcc option to produce PIC configure:9892: result: -fPIC -DPIC configure:9900: checking if gcc PIC flag -fPIC -DPIC works configure:9918: gcc -c -g -O2 -fPIC -DPIC -DPIC conftest.c >&5 configure:9922: $? = 0 configure:9935: result: yes configure:9964: checking if gcc static flag -static works configure:9992: result: yes configure:10007: checking if gcc supports -c -o file.o configure:10028: gcc -c -g -O2 -o out/conftest2.o conftest.c >&5 configure:10032: $? = 0 configure:10054: result: yes configure:10062: checking if gcc supports -c -o file.o configure:10109: result: yes configure:10142: checking whether the gcc linker (/usr/bin/ld -m elf_x86_64) supports shared libraries configure:11401: result: yes configure:11438: checking whether -lc should be explicitly linked in configure:11446: gcc -c -g -O2 conftest.c >&5 configure:11449: $? = 0 configure:11464: gcc -shared -fPIC -DPIC conftest.o -v -Wl,-soname -Wl,conftest -o conftest 2\>\&1 \| /bin/grep -lc \>/dev/null 2\>\&1 configure:11467: $? = 0 configure:11481: result: no configure:11641: checking dynamic linker characteristics configure:12222: gcc -o conftest -g -O2 -Wl,-rpath -Wl,/foo conftest.c >&5 configure:12222: $? = 0 configure:12459: result: GNU/Linux ld.so configure:12581: checking how to hardcode library paths into programs configure:12606: result: immediate configure:13154: checking whether stripping libraries is possible configure:13159: result: yes configure:13194: checking if libtool supports shared libraries configure:13196: result: yes configure:13199: checking whether to build shared libraries configure:13224: result: yes configure:13227: checking whether to build static libraries configure:13231: result: yes configure:13254: checking how to run the C++ preprocessor configure:13281: g++ -E conftest.cpp configure:13281: $? = 0 configure:13295: g++ -E conftest.cpp conftest.cpp:23:10: fatal error: ac_nonexistent.h: No such file or directory #include ^~~~~~~~~~~~~~~~~~ compilation terminated. configure:13295: $? = 1 configure: failed program was: | /* confdefs.h */ | #define PACKAGE_NAME "npstat" | #define PACKAGE_TARNAME "npstat" | #define PACKAGE_VERSION "4.11.0" | #define PACKAGE_STRING "npstat 4.11.0" | #define PACKAGE_BUGREPORT "" | #define PACKAGE_URL "" | #define PACKAGE "npstat" | #define VERSION "4.11.0" | #define STDC_HEADERS 1 | #define HAVE_SYS_TYPES_H 1 | #define HAVE_SYS_STAT_H 1 | #define HAVE_STDLIB_H 1 | #define HAVE_STRING_H 1 | #define HAVE_MEMORY_H 1 | #define HAVE_STRINGS_H 1 | #define HAVE_INTTYPES_H 1 | #define HAVE_STDINT_H 1 | #define HAVE_UNISTD_H 1 | #define HAVE_DLFCN_H 1 | #define LT_OBJDIR ".libs/" | /* end confdefs.h. */ | #include configure:13320: result: g++ -E configure:13340: g++ -E conftest.cpp configure:13340: $? = 0 configure:13354: g++ -E conftest.cpp conftest.cpp:23:10: fatal error: ac_nonexistent.h: No such file or directory #include ^~~~~~~~~~~~~~~~~~ compilation terminated. configure:13354: $? = 1 configure: failed program was: | /* confdefs.h */ | #define PACKAGE_NAME "npstat" | #define PACKAGE_TARNAME "npstat" | #define PACKAGE_VERSION "4.11.0" | #define PACKAGE_STRING "npstat 4.11.0" | #define PACKAGE_BUGREPORT "" | #define PACKAGE_URL "" | #define PACKAGE "npstat" | #define VERSION "4.11.0" | #define STDC_HEADERS 1 | #define HAVE_SYS_TYPES_H 1 | #define HAVE_SYS_STAT_H 1 | #define HAVE_STDLIB_H 1 | #define HAVE_STRING_H 1 | #define HAVE_MEMORY_H 1 | #define HAVE_STRINGS_H 1 | #define HAVE_INTTYPES_H 1 | #define HAVE_STDINT_H 1 | #define HAVE_UNISTD_H 1 | #define HAVE_DLFCN_H 1 | #define LT_OBJDIR ".libs/" | /* end confdefs.h. */ | #include configure:13516: checking for ld used by g++ configure:13583: result: /usr/bin/ld -m elf_x86_64 configure:13590: checking if the linker (/usr/bin/ld -m elf_x86_64) is GNU ld configure:13605: result: yes configure:13660: checking whether the g++ linker (/usr/bin/ld -m elf_x86_64) supports shared libraries configure:14733: result: yes configure:14769: g++ -c -std=c++11 -O3 -Wall -W -Werror conftest.cpp >&5 configure:14772: $? = 0 configure:15253: checking for g++ option to produce PIC configure:15260: result: -fPIC -DPIC configure:15268: checking if g++ PIC flag -fPIC -DPIC works configure:15286: g++ -c -std=c++11 -O3 -Wall -W -Werror -fPIC -DPIC -DPIC conftest.cpp >&5 configure:15290: $? = 0 configure:15303: result: yes configure:15326: checking if g++ static flag -static works configure:15354: result: yes configure:15366: checking if g++ supports -c -o file.o configure:15387: g++ -c -std=c++11 -O3 -Wall -W -Werror -o out/conftest2.o conftest.cpp >&5 configure:15391: $? = 0 configure:15413: result: yes configure:15418: checking if g++ supports -c -o file.o configure:15465: result: yes configure:15495: checking whether the g++ linker (/usr/bin/ld -m elf_x86_64) supports shared libraries configure:15535: result: yes configure:15676: checking dynamic linker characteristics configure:16421: result: GNU/Linux ld.so configure:16486: checking how to hardcode library paths into programs configure:16511: result: immediate configure:16652: checking if libtool supports shared libraries configure:16654: result: yes configure:16657: checking whether to build shared libraries configure:16681: result: yes configure:16684: checking whether to build static libraries configure:16688: result: yes configure:17040: checking for g77 option to produce PIC configure:17047: result: -fPIC configure:17055: checking if g77 PIC flag -fPIC works configure:17073: g77 -c -g -O2 -fPIC conftest.f >&5 configure:17077: $? = 0 configure:17090: result: yes configure:17113: checking if g77 static flag -static works configure:17141: result: yes configure:17153: checking if g77 supports -c -o file.o configure:17174: g77 -c -g -O2 -o out/conftest2.o conftest.f >&5 configure:17178: $? = 0 configure:17200: result: yes configure:17205: checking if g77 supports -c -o file.o configure:17252: result: yes configure:17282: checking whether the g77 linker (/usr/bin/ld -m elf_x86_64) supports shared libraries configure:18491: result: yes configure:18632: checking dynamic linker characteristics configure:19371: result: GNU/Linux ld.so configure:19436: checking how to hardcode library paths into programs configure:19461: result: immediate configure:19661: checking that generated files are newer than configure configure:19667: result: done configure:19694: creating ./config.status ## ---------------------- ## ## Running config.status. ## ## ---------------------- ## This file was extended by npstat config.status 4.11.0, which was generated by GNU Autoconf 2.69. Invocation command line was CONFIG_FILES = CONFIG_HEADERS = CONFIG_LINKS = CONFIG_COMMANDS = $ ./config.status on dawn config.status:1142: creating Makefile config.status:1142: creating npstat/nm/Makefile config.status:1142: creating npstat/rng/Makefile config.status:1142: creating npstat/stat/Makefile config.status:1142: creating npstat/wrap/Makefile config.status:1142: creating npstat/interfaces/Makefile config.status:1142: creating npstat/emsunfold/Makefile config.status:1142: creating npstat/Makefile config.status:1142: creating examples/C++/Makefile config.status:1142: creating npstat.pc config.status:1314: executing depfiles commands config.status:1314: executing libtool commands ## ---------------- ## ## Cache variables. ## ## ---------------- ## ac_cv_build=x86_64-pc-linux-gnu ac_cv_c_compiler_gnu=yes ac_cv_cxx_compiler_gnu=yes ac_cv_env_CCC_set= ac_cv_env_CCC_value= ac_cv_env_CC_set= ac_cv_env_CC_value= ac_cv_env_CFLAGS_set= ac_cv_env_CFLAGS_value= ac_cv_env_CPPFLAGS_set= ac_cv_env_CPPFLAGS_value= ac_cv_env_CPP_set= ac_cv_env_CPP_value= ac_cv_env_CXXCPP_set= ac_cv_env_CXXCPP_value= ac_cv_env_CXXFLAGS_set=set ac_cv_env_CXXFLAGS_value='-std=c++11 -O3 -Wall -W -Werror' ac_cv_env_CXX_set= ac_cv_env_CXX_value= ac_cv_env_DEPS_CFLAGS_set= ac_cv_env_DEPS_CFLAGS_value= ac_cv_env_DEPS_LIBS_set= ac_cv_env_DEPS_LIBS_value= ac_cv_env_F77_set= ac_cv_env_F77_value= ac_cv_env_FFLAGS_set= ac_cv_env_FFLAGS_value= ac_cv_env_LDFLAGS_set= ac_cv_env_LDFLAGS_value= ac_cv_env_LIBS_set= ac_cv_env_LIBS_value= ac_cv_env_LT_SYS_LIBRARY_PATH_set= ac_cv_env_LT_SYS_LIBRARY_PATH_value= ac_cv_env_PKG_CONFIG_LIBDIR_set= ac_cv_env_PKG_CONFIG_LIBDIR_value= ac_cv_env_PKG_CONFIG_PATH_set=set ac_cv_env_PKG_CONFIG_PATH_value=/usr/local/lib/pkgconfig ac_cv_env_PKG_CONFIG_set= ac_cv_env_PKG_CONFIG_value= ac_cv_env_build_alias_set= ac_cv_env_build_alias_value= ac_cv_env_host_alias_set= ac_cv_env_host_alias_value= ac_cv_env_target_alias_set= ac_cv_env_target_alias_value= ac_cv_f77_compiler_gnu=yes ac_cv_f77_libs=' -L/usr/lib/gcc/x86_64-linux-gnu/7 -L/usr/lib/gcc/x86_64-linux-gnu/7/../../../x86_64-linux-gnu -L/usr/lib/gcc/x86_64-linux-gnu/7/../../../../lib -L/lib/x86_64-linux-gnu -L/lib/../lib -L/usr/lib/x86_64-linux-gnu -L/usr/lib/../lib -L/usr/lib/gcc/x86_64-linux-gnu/7/../../.. -lgfortran -lm -lquadmath' ac_cv_header_dlfcn_h=yes ac_cv_header_inttypes_h=yes ac_cv_header_memory_h=yes ac_cv_header_stdc=yes ac_cv_header_stdint_h=yes ac_cv_header_stdlib_h=yes ac_cv_header_string_h=yes ac_cv_header_strings_h=yes ac_cv_header_sys_stat_h=yes ac_cv_header_sys_types_h=yes ac_cv_header_unistd_h=yes ac_cv_host=x86_64-pc-linux-gnu ac_cv_objext=o ac_cv_path_EGREP='/bin/grep -E' ac_cv_path_FGREP='/bin/grep -F' ac_cv_path_GREP=/bin/grep ac_cv_path_SED=/bin/sed ac_cv_path_ac_pt_PKG_CONFIG=/usr/bin/pkg-config ac_cv_path_install='/usr/bin/install -c' ac_cv_path_lt_DD=/bin/dd ac_cv_path_mkdir=/bin/mkdir ac_cv_prog_AWK=gawk ac_cv_prog_CPP='gcc -E' ac_cv_prog_CXXCPP='g++ -E' ac_cv_prog_ac_ct_AR=ar ac_cv_prog_ac_ct_CC=gcc ac_cv_prog_ac_ct_CXX=g++ ac_cv_prog_ac_ct_F77=g77 ac_cv_prog_ac_ct_MANIFEST_TOOL=mt ac_cv_prog_ac_ct_OBJDUMP=objdump ac_cv_prog_ac_ct_RANLIB=ranlib ac_cv_prog_ac_ct_STRIP=strip ac_cv_prog_cc_c89= ac_cv_prog_cc_g=yes ac_cv_prog_cxx_g=yes ac_cv_prog_f77_g=yes ac_cv_prog_f77_v=-v ac_cv_prog_make_make_set=yes am_cv_CC_dependencies_compiler_type=gcc3 am_cv_CXX_dependencies_compiler_type=gcc3 am_cv_make_support_nested_variables=yes am_cv_prog_cc_c_o=yes lt_cv_ar_at_file=@ lt_cv_archive_cmds_need_lc=no lt_cv_deplibs_check_method=pass_all lt_cv_file_magic_cmd='$MAGIC_CMD' lt_cv_file_magic_test_file= lt_cv_ld_reload_flag=-r lt_cv_nm_interface='BSD nm' lt_cv_objdir=.libs lt_cv_path_LD=/usr/bin/ld lt_cv_path_LDCXX='/usr/bin/ld -m elf_x86_64' lt_cv_path_NM='/usr/bin/nm -B' lt_cv_path_mainfest_tool=no lt_cv_prog_compiler_c_o=yes lt_cv_prog_compiler_c_o_CXX=yes lt_cv_prog_compiler_c_o_F77=yes lt_cv_prog_compiler_pic='-fPIC -DPIC' lt_cv_prog_compiler_pic_CXX='-fPIC -DPIC' lt_cv_prog_compiler_pic_F77=-fPIC lt_cv_prog_compiler_pic_works=yes lt_cv_prog_compiler_pic_works_CXX=yes lt_cv_prog_compiler_pic_works_F77=yes lt_cv_prog_compiler_rtti_exceptions=no lt_cv_prog_compiler_static_works=yes lt_cv_prog_compiler_static_works_CXX=yes lt_cv_prog_compiler_static_works_F77=yes lt_cv_prog_gnu_ld=yes lt_cv_prog_gnu_ldcxx=yes lt_cv_sharedlib_from_linklib_cmd='printf %s\n' lt_cv_shlibpath_overrides_runpath=yes lt_cv_sys_global_symbol_pipe='sed -n -e '\''s/^.*[ ]\([ABCDGIRSTW][ABCDGIRSTW]*\)[ ][ ]*\([_A-Za-z][_A-Za-z0-9]*\)$/\1 \2 \2/p'\'' | sed '\''/ __gnu_lto/d'\''' lt_cv_sys_global_symbol_to_c_name_address='sed -n -e '\''s/^: \(.*\) .*$/ {"\1", (void *) 0},/p'\'' -e '\''s/^[ABCDGIRSTW][ABCDGIRSTW]* .* \(.*\)$/ {"\1", (void *) \&\1},/p'\''' lt_cv_sys_global_symbol_to_c_name_address_lib_prefix='sed -n -e '\''s/^: \(.*\) .*$/ {"\1", (void *) 0},/p'\'' -e '\''s/^[ABCDGIRSTW][ABCDGIRSTW]* .* \(lib.*\)$/ {"\1", (void *) \&\1},/p'\'' -e '\''s/^[ABCDGIRSTW][ABCDGIRSTW]* .* \(.*\)$/ {"lib\1", (void *) \&\1},/p'\''' lt_cv_sys_global_symbol_to_cdecl='sed -n -e '\''s/^T .* \(.*\)$/extern int \1();/p'\'' -e '\''s/^[ABCDGIRSTW][ABCDGIRSTW]* .* \(.*\)$/extern char \1;/p'\''' lt_cv_sys_global_symbol_to_import= lt_cv_sys_max_cmd_len=1572864 lt_cv_to_host_file_cmd=func_convert_file_noop lt_cv_to_tool_file_cmd=func_convert_file_noop lt_cv_truncate_bin='/bin/dd bs=4096 count=1' pkg_cv_DEPS_CFLAGS=-I/usr/local/include pkg_cv_DEPS_LIBS='-L/usr/local/lib -lfftw3 -lgeners -lkstest' ## ----------------- ## ## Output variables. ## ## ----------------- ## ACLOCAL='${SHELL} /home/igv/Hepforge/npstat/trunk/missing aclocal-1.15' AMDEPBACKSLASH='\' AMDEP_FALSE='#' AMDEP_TRUE='' AMTAR='$${TAR-tar}' AM_BACKSLASH='\' AM_DEFAULT_V='$(AM_DEFAULT_VERBOSITY)' AM_DEFAULT_VERBOSITY='1' AM_V='$(V)' AR='ar' AUTOCONF='${SHELL} /home/igv/Hepforge/npstat/trunk/missing autoconf' AUTOHEADER='${SHELL} /home/igv/Hepforge/npstat/trunk/missing autoheader' AUTOMAKE='${SHELL} /home/igv/Hepforge/npstat/trunk/missing automake-1.15' AWK='gawk' CC='gcc' CCDEPMODE='depmode=gcc3' CFLAGS='-g -O2' CPP='gcc -E' CPPFLAGS='' CXX='g++' CXXCPP='g++ -E' CXXDEPMODE='depmode=gcc3' CXXFLAGS='-std=c++11 -O3 -Wall -W -Werror' CYGPATH_W='echo' DEFS='-DPACKAGE_NAME=\"npstat\" -DPACKAGE_TARNAME=\"npstat\" -DPACKAGE_VERSION=\"4.11.0\" -DPACKAGE_STRING=\"npstat\ 4.11.0\" -DPACKAGE_BUGREPORT=\"\" -DPACKAGE_URL=\"\" -DPACKAGE=\"npstat\" -DVERSION=\"4.11.0\" -DSTDC_HEADERS=1 -DHAVE_SYS_TYPES_H=1 -DHAVE_SYS_STAT_H=1 -DHAVE_STDLIB_H=1 -DHAVE_STRING_H=1 -DHAVE_MEMORY_H=1 -DHAVE_STRINGS_H=1 -DHAVE_INTTYPES_H=1 -DHAVE_STDINT_H=1 -DHAVE_UNISTD_H=1 -DHAVE_DLFCN_H=1 -DLT_OBJDIR=\".libs/\"' DEPDIR='.deps' DEPS_CFLAGS='-I/usr/local/include' DEPS_LIBS='-L/usr/local/lib -lfftw3 -lgeners -lkstest' DLLTOOL='false' DSYMUTIL='' DUMPBIN='' ECHO_C='' ECHO_N='-n' ECHO_T='' EGREP='/bin/grep -E' EXEEXT='' F77='g77' FFLAGS='-g -O2' FGREP='/bin/grep -F' FLIBS=' -L/usr/lib/gcc/x86_64-linux-gnu/7 -L/usr/lib/gcc/x86_64-linux-gnu/7/../../../x86_64-linux-gnu -L/usr/lib/gcc/x86_64-linux-gnu/7/../../../../lib -L/lib/x86_64-linux-gnu -L/lib/../lib -L/usr/lib/x86_64-linux-gnu -L/usr/lib/../lib -L/usr/lib/gcc/x86_64-linux-gnu/7/../../.. -lgfortran -lm -lquadmath' GREP='/bin/grep' INSTALL_DATA='${INSTALL} -m 644' INSTALL_PROGRAM='${INSTALL}' INSTALL_SCRIPT='${INSTALL}' INSTALL_STRIP_PROGRAM='$(install_sh) -c -s' LD='/usr/bin/ld -m elf_x86_64' LDFLAGS='' LIBOBJS='' LIBS='' LIBTOOL='$(SHELL) $(top_builddir)/libtool' LIPO='' LN_S='ln -s' LTLIBOBJS='' LT_SYS_LIBRARY_PATH='' MAKEINFO='${SHELL} /home/igv/Hepforge/npstat/trunk/missing makeinfo' MANIFEST_TOOL=':' MKDIR_P='/bin/mkdir -p' NM='/usr/bin/nm -B' NMEDIT='' OBJDUMP='objdump' OBJEXT='o' OTOOL64='' OTOOL='' PACKAGE='npstat' PACKAGE_BUGREPORT='' PACKAGE_NAME='npstat' PACKAGE_STRING='npstat 4.11.0' PACKAGE_TARNAME='npstat' PACKAGE_URL='' PACKAGE_VERSION='4.11.0' PATH_SEPARATOR=':' PKG_CONFIG='/usr/bin/pkg-config' PKG_CONFIG_LIBDIR='' PKG_CONFIG_PATH='/usr/local/lib/pkgconfig' RANLIB='ranlib' SED='/bin/sed' SET_MAKE='' SHELL='/bin/bash' STRIP='strip' VERSION='4.11.0' ac_ct_AR='ar' ac_ct_CC='gcc' ac_ct_CXX='g++' ac_ct_DUMPBIN='' ac_ct_F77='g77' am__EXEEXT_FALSE='' am__EXEEXT_TRUE='#' am__fastdepCC_FALSE='#' am__fastdepCC_TRUE='' am__fastdepCXX_FALSE='#' am__fastdepCXX_TRUE='' am__include='include' am__isrc='' am__leading_dot='.' am__nodep='_no' am__quote='' am__tar='$${TAR-tar} chof - "$$tardir"' am__untar='$${TAR-tar} xf -' bindir='${exec_prefix}/bin' build='x86_64-pc-linux-gnu' build_alias='' build_cpu='x86_64' build_os='linux-gnu' build_vendor='pc' datadir='${datarootdir}' datarootdir='${prefix}/share' docdir='${datarootdir}/doc/${PACKAGE_TARNAME}' dvidir='${docdir}' exec_prefix='${prefix}' host='x86_64-pc-linux-gnu' host_alias='' host_cpu='x86_64' host_os='linux-gnu' host_vendor='pc' htmldir='${docdir}' includedir='${prefix}/include' infodir='${datarootdir}/info' install_sh='${SHELL} /home/igv/Hepforge/npstat/trunk/install-sh' libdir='${exec_prefix}/lib' libexecdir='${exec_prefix}/libexec' localedir='${datarootdir}/locale' localstatedir='${prefix}/var' mandir='${datarootdir}/man' mkdir_p='$(MKDIR_P)' oldincludedir='/usr/include' pdfdir='${docdir}' prefix='/usr/local' program_transform_name='s,x,x,' psdir='${docdir}' runstatedir='${localstatedir}/run' sbindir='${exec_prefix}/sbin' sharedstatedir='${prefix}/com' sysconfdir='${prefix}/etc' target_alias='' ## ----------- ## ## confdefs.h. ## ## ----------- ## /* confdefs.h */ #define PACKAGE_NAME "npstat" #define PACKAGE_TARNAME "npstat" #define PACKAGE_VERSION "4.11.0" #define PACKAGE_STRING "npstat 4.11.0" #define PACKAGE_BUGREPORT "" #define PACKAGE_URL "" #define PACKAGE "npstat" #define VERSION "4.11.0" #define STDC_HEADERS 1 #define HAVE_SYS_TYPES_H 1 #define HAVE_SYS_STAT_H 1 #define HAVE_STDLIB_H 1 #define HAVE_STRING_H 1 #define HAVE_MEMORY_H 1 #define HAVE_STRINGS_H 1 #define HAVE_INTTYPES_H 1 #define HAVE_STDINT_H 1 #define HAVE_UNISTD_H 1 #define HAVE_DLFCN_H 1 #define LT_OBJDIR ".libs/" configure: exit 0