|
| auto | A = hydra::Parameter::Create().Name("A").Value(-5.0) |
| |
| char ** | argc |
| |
| auto | B = hydra::Parameter::Create().Name("B").Value(-1.5) |
| |
| auto | bigauss = hydra::BifurcatedGaussian<xvar>(mean, sigma_left, sigma_rigt) |
| |
| auto | bw = hydra::BreitWignerNR<xvar>(mass, width ) |
| |
| auto | C = hydra::Parameter::Create().Name("C").Value( 1.5) |
| |
| auto | chi2 = hydra::ChiSquare<xvar>(ndof) |
| |
| auto | D = hydra::Parameter::Create().Name("D").Value( 5.0) |
| |
| auto | data = hydra::device::vector< double>(10, .0) |
| |
| auto | delta = hydra::Parameter::Create().Name("delta" ).Value(2.0) |
| |
| hydra_thrust::default_random_engine | engine |
| |
| auto | exp = hydra::Exponential<xvar>(tau) |
| |
| auto | gamma = hydra::Parameter::Create().Name("gamma" ).Value(3.0) |
| |
| auto | gauss = hydra::Gaussian<xvar>(mean, sigma) |
| |
| auto | johnson_su = hydra::JohnsonSU<xvar>(gamma, delta, xi, lambda) |
| |
| auto | lambda = hydra::Parameter::Create().Name("lambda").Value(1.5) |
| |
| auto | lognormal = hydra::LogNormal<xvar>(mean, sigma) |
| |
| auto | mass = hydra::Parameter::Create().Name("mass" ).Value(5.0) |
| |
| auto | mean = hydra::Parameter::Create("mean" ).Value(0.0) |
| |
| auto | ndof = hydra::Parameter::Create().Name("ndof" ).Value(2.0) |
| |
| | nentries = EArg.getValue() |
| |
| | return |
| |
| auto | sigma = hydra::Parameter::Create("sigma").Value(0.25) |
| |
| auto | sigma_left = hydra::Parameter::Create("sigma left").Value(2.0) |
| |
| auto | sigma_rigt = hydra::Parameter::Create("sigma rigt").Value(1.0) |
| |
| auto | tau = hydra::Parameter::Create("mean" ).Value(1.0) |
| |
| auto | trapezoid = hydra::TrapezoidalShape<xvar>(A,B,C,D) |
| |
| auto | triangle = hydra::TriangularShape<xvar>(A,B,D) |
| |
| | try |
| |
| auto | uniform = hydra::UniformShape<xvar>(A,D) |
| |
| auto | width = hydra::Parameter::Create().Name("width").Value(0.5) |
| |
| auto | xi = hydra::Parameter::Create().Name("xi").Value(1.1) |
| |