/dports/math/openturns/openturns-1.18/lib/src/Base/Func/ |
H A D | ExpertMixture.cxx | 141 Scalar bestGrade = SpecFunc::LowestScalar; in evaluateSupervised() 168 Scalar bestGrade = SpecFunc::LowestScalar; in evaluateNonSupervised() 202 Point bestGrades(size, SpecFunc::LowestScalar); in evaluateSupervised() 230 Point bestGrades(size, SpecFunc::LowestScalar); in evaluateNonSupervised()
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/dports/math/openturns/openturns-1.18/lib/src/Uncertainty/Distribution/ |
H A D | ExtremeValueCopula.cxx | 148 return SpecFunc::LowestScalar; in computeLogPDF() 155 if (!SpecFunc::IsNormal(A)) return SpecFunc::LowestScalar; in computeLogPDF() 157 if (!SpecFunc::IsNormal(dA)) return SpecFunc::LowestScalar; in computeLogPDF() 159 if (!SpecFunc::IsNormal(d2A)) return SpecFunc::LowestScalar; in computeLogPDF()
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H A D | KPermutationsDistribution.cxx | 135 if ((k < -supportEpsilon_) || (k > n_ + supportEpsilon_)) return SpecFunc::LowestScalar; in computeLogPDF() 137 if (std::abs(k - ik) > supportEpsilon_) return SpecFunc::LowestScalar; in computeLogPDF() 140 if (!x.check(n_)) return SpecFunc::LowestScalar; in computeLogPDF() 147 if (logPDF == SpecFunc::LowestScalar) return 0.0; in computePDF()
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H A D | NormalGamma.cxx | 141 if (logPDF == SpecFunc::LowestScalar) return 0.0; in computePDF() 153 if ((y <= a) || (y >= b)) return SpecFunc::LowestScalar; in computeLogPDF() 270 …const Function integrand(NormalGammaFunctions::KernelProbability(SpecFunc::LowestScalar, x, kappa_… in computeCDF()
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H A D | MaximumLikelihoodFactory.cxx | 168 return Point(1, SpecFunc::LowestScalar); in operator ()() 174 result = SpecFunc::IsNormal(logPdf) ? logPdf : SpecFunc::LowestScalar; in operator ()()
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H A D | StudentFactory.cxx | 89 if (factor <= 0.0) return Point(1, SpecFunc::LowestScalar); in computeLogLikelihood()
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H A D | GeneralizedPareto.cxx | 173 if (z < 0.0) return SpecFunc::LowestScalar; in computeLogPDF() 174 if ((xi_ < 0.0) && (z >= -1.0 / xi_)) return SpecFunc::LowestScalar; in computeLogPDF()
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H A D | TruncatedNormalFactory.cxx | 126 Point parametersLowerBound(dimension, SpecFunc::LowestScalar); in buildMethodOfLikelihoodMaximization()
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H A D | VonMises.cxx | 213 if (std::abs(x - mu_) > M_PI) return SpecFunc::LowestScalar; in computeLogPDF()
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H A D | Poisson.cxx | 117 …k < -supportEpsilon_) || (std::abs(k - round(k)) > supportEpsilon_)) return SpecFunc::LowestScalar; in computeLogPDF()
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/dports/math/openturns/openturns-1.18/lib/src/Uncertainty/Algorithm/MetaModel/Kriging/ |
H A D | GeneralLinearModelAlgorithm.cxx | 71 , lastReducedLogLikelihood_(SpecFunc::LowestScalar) in GeneralLinearModelAlgorithm() 102 , lastReducedLogLikelihood_(SpecFunc::LowestScalar) in GeneralLinearModelAlgorithm() 141 , lastReducedLogLikelihood_(SpecFunc::LowestScalar) in GeneralLinearModelAlgorithm() 192 , lastReducedLogLikelihood_(SpecFunc::LowestScalar) in GeneralLinearModelAlgorithm() 641 if (epsilon <= 0) lastReducedLogLikelihood_ = SpecFunc::LowestScalar; in computeReducedLogLikelihood() 730 if (lii <= 0.0) return SpecFunc::LowestScalar; in computeLapackLogDeterminantCholesky() 782 if (lii <= 0.0) return SpecFunc::LowestScalar; in computeHMatLogDeterminantCholesky() 922 lastReducedLogLikelihood_ = SpecFunc::LowestScalar; in reset()
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/dports/math/openturns/openturns-1.18/lib/src/Uncertainty/Algorithm/Simulation/openturns/ |
H A D | SimulationSensitivityAnalysis.hxx | 79 const Scalar lower = SpecFunc::LowestScalar,
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/dports/math/openturns/openturns-1.18/lib/src/Uncertainty/Model/ |
H A D | EllipticalDistribution.cxx | 153 if (densityGenerator == 0.0) return SpecFunc::LowestScalar; in computeLogDensityGenerator() 328 if (!SpecFunc::IsNormal(logDensityGenerator)) return SpecFunc::LowestScalar; in computeLogPDF() 349 if (!SpecFunc::IsNormal(logDensityGenerator)) return SpecFunc::LowestScalar; in computeLogPDF() 373 if (!SpecFunc::IsNormal(logDensityGenerator)) return SpecFunc::LowestScalar; in computeLogPDF() 381 if (!SpecFunc::IsNormal(logDensityGenerator)) return SpecFunc::LowestScalar; in computeLogPDF()
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/dports/math/openturns/openturns-1.18/lib/src/Uncertainty/Algorithm/Optimization/ |
H A D | EfficientGlobalOptimization.cxx | 94 if (!SpecFunc::IsNormal(sk)) return Point(1, SpecFunc::LowestScalar); in operator ()() 173 Scalar optimalValue = problem.isMinimization() ? SpecFunc::MaxScalar : SpecFunc::LowestScalar; in run() 241 … optimalValueSubstitute = problem.isMinimization() ? SpecFunc::MaxScalar : SpecFunc::LowestScalar; in run()
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/dports/math/openturns/openturns-1.18/lib/src/Uncertainty/Algorithm/WeightedExperiments/ |
H A D | LHSResult.cxx | 45 …lCriterion_ = spaceFilling_.isMinimizationProblem() ? SpecFunc::MaxScalar : SpecFunc::LowestScalar; in CLASSNAMEINIT() 56 …lCriterion_ = spaceFilling_.isMinimizationProblem() ? SpecFunc::MaxScalar : SpecFunc::LowestScalar; in LHSResult()
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H A D | MonteCarloLHS.cxx | 68 …ptimalValue = spaceFilling_.isMinimizationProblem() ? SpecFunc::MaxScalar : SpecFunc::LowestScalar; in generateWithWeights()
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/dports/math/openturns/openturns-1.18/lib/src/Base/Optim/ |
H A D | Dlib.cxx | 590 if (!finiteLowerBound[i]) lb(i) = SpecFunc::LowestScalar; in run() 598 lb(i) = SpecFunc::LowestScalar; in run() 655 SpecFunc::LowestScalar ); in run()
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H A D | IpoptProblem.cxx | 176 x_l[i] = SpecFunc::LowestScalar; in get_bounds_info() 190 x_l[i] = SpecFunc::LowestScalar; in get_bounds_info()
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H A D | BonminProblem.cxx | 211 x_l[i] = SpecFunc::LowestScalar; in get_bounds_info() 225 x_l[i] = SpecFunc::LowestScalar; in get_bounds_info()
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H A D | MultiStart.cxx | 96 Scalar bestValue = getProblem().isMinimization() ? SpecFunc::MaxScalar : SpecFunc::LowestScalar; in run()
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/dports/math/openturns/openturns-1.18/lib/src/Uncertainty/Algorithm/Classification/ |
H A D | MixtureClassifier.cxx | 104 Point bestGrades(size, SpecFunc::LowestScalar); in classify()
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/dports/math/openturns/openturns-1.18/lib/src/Base/Func/SpecFunc/ |
H A D | SpecFunc.cxx | 96 const Scalar SpecFunc::LowestScalar = -MaxScalar; member in SpecFunc 262 if (x <= 0.0) return LowestScalar; in LogBesselI1() 305 if (!(x > 0.0)) return LowestScalar; in DeltaLogBesselI10() 387 if (!IsNormal(integral) || (integral == 0.0)) return LowestScalar; in LogBesselK() 424 if (x == 0.0) return LowestScalar; in BesselKDerivative()
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/dports/math/openturns/openturns-1.18/lib/src/Base/Geom/ |
H A D | Interval.cxx | 419 lowerBound_[i] = (lowerBound[i] > 0.0 ? SpecFunc::MaxScalar : SpecFunc::LowestScalar); in setLowerBound() 437 upperBound_[i] = (upperBound[i] > 0.0 ? SpecFunc::MaxScalar : SpecFunc::LowestScalar); in setUpperBound()
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/dports/math/openturns/openturns-1.18/lib/src/Base/Stat/ |
H A D | GeneralizedExponential.cxx | 133 gradient(i, 0) = SpecFunc::LowestScalar; in partialGradient()
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/dports/math/openturns/openturns-1.18/lib/src/Uncertainty/Bayesian/ |
H A D | RandomWalkMetropolisHastings.cxx | 120 if (currentPenalizedLogLikelihood_ <= SpecFunc::LowestScalar) in getRealization()
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