| /dports/math/stan/stan-2.28.2/src/test/unit/variational/ |
| H A D | advi_multivar_with_constraint_test.cpp | 34 Eigen::VectorXd cont_params = Eigen::VectorXd::Zero(2); in TEST() local
35 cont_params(0) = 0.75; in TEST()
36 cont_params(1) = 0.75; in TEST()
40 test_advi(my_model, cont_params, base_rng, n_monte_carlo_grad, in TEST()
91 Eigen::VectorXd cont_params = Eigen::VectorXd::Zero(2); in TEST() local
92 cont_params(0) = 0.75; in TEST()
93 cont_params(1) = 0.75; in TEST()
97 test_advi(my_model, cont_params, base_rng, n_monte_carlo_grad, in TEST()
177 EXPECT_THROW_MSG(musigmatilde.calc_grad(elbo_grad, my_model, cont_params, in TEST()
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| H A D | advi_multivar_no_constraint_test.cpp | 34 Eigen::VectorXd cont_params = Eigen::VectorXd::Zero(2); in TEST() local
35 cont_params(0) = 0.75; in TEST()
36 cont_params(1) = 0.75; in TEST()
40 test_advi(my_model, cont_params, base_rng, n_monte_carlo_grad, in TEST()
127 EXPECT_THROW_MSG(muL.calc_grad(elbo_grad, my_model, cont_params, in TEST()
151 Eigen::VectorXd cont_params = Eigen::VectorXd::Zero(2); in TEST() local
152 cont_params(0) = 0.75; in TEST()
153 cont_params(1) = 0.75; in TEST()
157 test_advi(my_model, cont_params, base_rng, n_monte_carlo_grad, in TEST()
236 EXPECT_THROW_MSG(musigmatilde.calc_grad(elbo_grad, my_model, cont_params, in TEST()
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| H A D | eta_adapt_mock_models_test.cpp | 204 cont_params = Eigen::VectorXd::Zero(3); in SetUp()
211 Eigen::VectorXd cont_params; member in eta_adapt_test
226 model, cont_params, rng, 1, 100, 100, 1); in TEST_F()
232 model, cont_params, rng, 1, 100, 100, 1); in TEST_F()
235 = stan::variational::normal_meanfield(cont_params); in TEST_F()
237 = stan::variational::normal_fullrank(cont_params); in TEST_F()
264 throwing_model, cont_params, rng, 1, 100, 100, 1); in TEST_F()
271 throwing_model, cont_params, rng, 1, 100, 100, 1); in TEST_F()
274 = stan::variational::normal_meanfield(cont_params); in TEST_F()
276 = stan::variational::normal_fullrank(cont_params); in TEST_F()
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| H A D | stochastic_gradient_ascent_test.cpp | 206 cont_params = Eigen::VectorXd::Zero(3); in SetUp()
214 Eigen::VectorXd cont_params; member in stochastic_gradient_ascent_test
231 model, cont_params, rng, 1, 100, 100, 1); in TEST_F()
237 model, cont_params, rng, 1, 100, 100, 1); in TEST_F()
240 = stan::variational::normal_meanfield(cont_params); in TEST_F()
242 = stan::variational::normal_fullrank(cont_params); in TEST_F()
271 throwing_model, cont_params, rng, 1, 100, 100, 1); in TEST_F()
278 throwing_model, cont_params, rng, 1, 100, 100, 1); in TEST_F()
281 = stan::variational::normal_meanfield(cont_params); in TEST_F()
283 = stan::variational::normal_fullrank(cont_params); in TEST_F()
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| H A D | advi_univar_with_constraint_test.cpp | 33 Eigen::VectorXd cont_params = Eigen::VectorXd::Zero(1); in TEST() local
34 cont_params(0) = -0.75; in TEST()
38 test_advi(my_model, cont_params, base_rng, n_monte_carlo_grad, in TEST()
138 EXPECT_THROW_MSG(muL.calc_grad(elbo_grad, my_model, cont_params, in TEST()
162 Eigen::VectorXd cont_params = Eigen::VectorXd::Zero(1); in TEST() local
163 cont_params(0) = -0.75; in TEST()
167 test_advi(my_model, cont_params, base_rng, n_monte_carlo_grad, in TEST()
258 EXPECT_THROW_MSG(musigmatilde.calc_grad(elbo_grad, my_model, cont_params, in TEST()
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| H A D | advi_univar_no_constraint_test.cpp | 33 Eigen::VectorXd cont_params = Eigen::VectorXd::Zero(1); in TEST() local
34 cont_params(0) = -0.75; in TEST()
38 test_advi(my_model, cont_params, base_rng, n_monte_carlo_grad, in TEST()
132 EXPECT_THROW_MSG(muL.calc_grad(elbo_grad, my_model, cont_params, in TEST()
156 Eigen::VectorXd cont_params = Eigen::VectorXd::Zero(1); in TEST() local
157 cont_params(0) = -0.75; in TEST()
161 test_advi(my_model, cont_params, base_rng, n_monte_carlo_grad, in TEST()
246 EXPECT_THROW_MSG(musigmatilde.calc_grad(elbo_grad, my_model, cont_params, in TEST()
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| H A D | hier_logistic_cp_test.cpp | 33 Eigen::VectorXd cont_params = Eigen::VectorXd::Zero(my_model.num_params_r()); in TEST() local
37 test_advi(my_model, cont_params, base_rng, 10, 100, 100, 1); in TEST()
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| /dports/math/stan/stan-2.28.2/src/test/unit/services/util/ |
| H A D | generate_transitions_test.cpp | 41 Eigen::VectorXd cont_params(cont_vector.size()); in TEST_F() local
43 cont_params[i] = cont_vector[i]; in TEST_F()
44 stan::mcmc::sample s(cont_params, 0, 0); in TEST_F()
97 Eigen::VectorXd cont_params(cont_vector.size()); in TEST_F() local
99 cont_params[i] = cont_vector[i]; in TEST_F()
100 stan::mcmc::sample s(cont_params, 0, 0); in TEST_F()
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| /dports/math/stan/stan-2.28.2/src/stan/mcmc/ |
| H A D | sample.hpp | 32 double cont_params(int k) const { return cont_params_(k); } in cont_params() function in stan::mcmc::sample
34 void cont_params(Eigen::VectorXd& x) const { x = cont_params_; } in cont_params() function in stan::mcmc::sample
36 const Eigen::VectorXd& cont_params() const { return cont_params_; } in cont_params() function in stan::mcmc::sample
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| /dports/math/py-pystan/pystan-2.19.0.0/pystan/stan/src/stan/mcmc/ |
| H A D | sample.hpp | 36 double cont_params(int k) const { in cont_params() function in stan::mcmc::sample
40 void cont_params(Eigen::VectorXd& x) const { in cont_params() function in stan::mcmc::sample
44 const Eigen::VectorXd& cont_params() const { in cont_params() function in stan::mcmc::sample
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| /dports/math/stan/stan-2.28.2/src/stan/variational/families/ |
| H A D | normal_fullrank.hpp | 96 explicit normal_fullrank(const Eigen::VectorXd& cont_params) in normal_fullrank() argument
97 : mu_(cont_params), in normal_fullrank()
99 Eigen::MatrixXd::Identity(cont_params.size(), cont_params.size())), in normal_fullrank()
100 dimension_(cont_params.size()) {} in normal_fullrank()
401 void calc_grad(normal_fullrank& elbo_grad, M& m, Eigen::VectorXd& cont_params, in calc_grad() argument
411 cont_params.size()); in calc_grad()
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| H A D | normal_meanfield.hpp | 57 explicit normal_meanfield(const Eigen::VectorXd& cont_params) in normal_meanfield() argument
58 : mu_(cont_params), in normal_meanfield()
59 omega_(Eigen::VectorXd::Zero(cont_params.size())), in normal_meanfield()
60 dimension_(cont_params.size()) {} in normal_meanfield()
337 Eigen::VectorXd& cont_params, int n_monte_carlo_grad, in calc_grad() argument
347 cont_params.size()); in calc_grad()
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| /dports/math/py-pystan/pystan-2.19.0.0/pystan/stan/src/stan/variational/families/ |
| H A D | normal_fullrank.hpp | 101 explicit normal_fullrank(const Eigen::VectorXd& cont_params) in normal_fullrank() argument
102 : mu_(cont_params), in normal_fullrank()
103 L_chol_(Eigen::MatrixXd::Identity(cont_params.size(), in normal_fullrank()
104 cont_params.size())), in normal_fullrank()
105 dimension_(cont_params.size()) { in normal_fullrank()
417 Eigen::VectorXd& cont_params, in calc_grad() argument
429 "Dimension of variables in model", cont_params.size()); in calc_grad()
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| H A D | normal_meanfield.hpp | 58 explicit normal_meanfield(const Eigen::VectorXd& cont_params) in normal_meanfield() argument
59 : mu_(cont_params), in normal_meanfield()
60 omega_(Eigen::VectorXd::Zero(cont_params.size())), in normal_meanfield()
61 dimension_(cont_params.size()) { in normal_meanfield()
348 Eigen::VectorXd& cont_params, in calc_grad() argument
361 "Dimension of variables in model", cont_params.size()); in calc_grad()
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| /dports/math/stan/stan-2.28.2/src/stan/services/util/ |
| H A D | mcmc_writer.hpp | 108 std::vector<double> cont_params( in write_sample_params() local
109 sample.cont_params().data(), in write_sample_params()
110 sample.cont_params().data() + sample.cont_params().size()); in write_sample_params()
111 model.write_array(rng, cont_params, params_i, model_values, true, true, in write_sample_params()
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| H A D | run_adaptive_sampler.hpp | 51 Eigen::Map<Eigen::VectorXd> cont_params(cont_vector.data(), in run_adaptive_sampler() local
56 sampler.z().q = cont_params; in run_adaptive_sampler()
65 stan::mcmc::sample s(cont_params, 0, 0); in run_adaptive_sampler()
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| /dports/math/py-pystan/pystan-2.19.0.0/pystan/stan/src/stan/services/util/ |
| H A D | mcmc_writer.hpp | 114 std::vector<double> cont_params(sample.cont_params().data(), in write_sample_params() local
115 sample.cont_params().data() in write_sample_params()
116 + sample.cont_params().size()); in write_sample_params()
118 cont_params, in write_sample_params()
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| H A D | run_adaptive_sampler.hpp | 47 Eigen::Map<Eigen::VectorXd> cont_params(cont_vector.data(), in run_adaptive_sampler() local
52 sampler.z().q = cont_params; in run_adaptive_sampler()
62 stan::mcmc::sample s(cont_params, 0, 0); in run_adaptive_sampler()
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| /dports/math/py-pystan/pystan-2.19.0.0/pystan/stan/src/stan/services/sample/ |
| H A D | fixed_param.hpp | 63 Eigen::VectorXd cont_params(cont_vector.size()); in fixed_param() local
65 cont_params[i] = cont_vector[i]; in fixed_param()
66 stan::mcmc::sample s(cont_params, 0, 0); in fixed_param()
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| /dports/math/stan/stan-2.28.2/src/stan/services/sample/ |
| H A D | fixed_param.hpp | 60 Eigen::VectorXd cont_params(cont_vector.size()); in fixed_param() local
62 cont_params[i] = cont_vector[i]; in fixed_param()
63 stan::mcmc::sample s(cont_params, 0, 0); in fixed_param()
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| /dports/math/stan/stan-2.28.2/src/test/unit/mcmc/hmc/static_uniform/ |
| H A D | derived_static_uniform_test.cpp | 46 EXPECT_FLOAT_EQ(0.27224374, s.cont_params()(0)); in TEST()
83 EXPECT_FLOAT_EQ(0.27224374, s.cont_params()(0)); in TEST()
120 EXPECT_FLOAT_EQ(0.27224374, s.cont_params()(0)); in TEST()
157 EXPECT_FLOAT_EQ(0.37006485, s.cont_params()(0)); in TEST()
195 EXPECT_FLOAT_EQ(0.27224374, s.cont_params()(0)); in TEST()
233 EXPECT_FLOAT_EQ(0.27224374, s.cont_params()(0)); in TEST()
271 EXPECT_FLOAT_EQ(0.27224374, s.cont_params()(0)); in TEST()
309 EXPECT_FLOAT_EQ(0.37006485, s.cont_params()(0)); in TEST()
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| /dports/net/py-libcloud/apache-libcloud-3.4.1/libcloud/container/drivers/ |
| H A D | lxd.py | 551 cont_params = \
561 cont_params=cont_params,
1671 cont_params, argument
1691 if cont_params is None:
1708 data.update(cont_params)
1826 cont_params = {}
1833 cont_params["profiles"] = profiles
1838 cont_params["ephemeral"] = ephemeral
1843 cont_params["config"] = config
1846 cont_params["devices"] = devices
[all …]
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| /dports/graphics/rawtherapee/rawtherapee-5.8/rtengine/ |
| H A D | improcfun.h | 181 …void EPDToneMapResid(float * WavCoeffs_L0, unsigned int Iterates, int skip, struct cont_params& c…
183 …void ContrastResid(float * WavCoeffs_L0, struct cont_params &cp, int W_L, int H_L, float max0, flo…
199 …struct cont_params &cp, int skip, float *mean, float *sigma, float *MaxP, float *MaxN, const WavC…
200 …void WaveletcontAllLfinal(wavelet_decomposition &WaveletCoeffs_L, struct cont_params &cp, float *m…
202 struct cont_params &cp, const bool useChannelA);
204 struct cont_params &cp, FlatCurve* hhcurve, bool hhutili);
205 …**varchrom, float ** WavCoeffs_L, float * WavCoeffs_L0, int level, int dir, struct cont_params &cp,
207 …nalContAllL(float ** WavCoeffs_L, float * WavCoeffs_L0, int level, int dir, struct cont_params &cp,
209 …WavCoeffs_a0, int level, int dir, const WavOpacityCurveW & waOpacityCurveW, struct cont_params &cp,
218 …void calckoe(float ** WavCoeffs_LL, const struct cont_params& cp, float ** koeLi, int level, int d…
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| /dports/math/stan/stan-2.28.2/src/test/unit/mcmc/hmc/xhmc/ |
| H A D | softabs_xhmc_test.cpp | 115 EXPECT_FLOAT_EQ(1, s.cont_params()(0)); in TEST()
116 EXPECT_FLOAT_EQ(-1, s.cont_params()(1)); in TEST()
117 EXPECT_FLOAT_EQ(1, s.cont_params()(2)); in TEST()
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| H A D | unit_e_xhmc_test.cpp | 115 EXPECT_FLOAT_EQ(1, s.cont_params()(0)); in TEST()
116 EXPECT_FLOAT_EQ(-1, s.cont_params()(1)); in TEST()
117 EXPECT_FLOAT_EQ(1, s.cont_params()(2)); in TEST()
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