Move stan::rng_t decl to Math library for consistency

stan-dev · May 17, 2024 · 9da4dc8 · 9da4dc8
1 parent 0379951
commit 9da4dc8
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diff --git a/stan/math/prim/meta/rng_t.hpp b/stan/math/prim/meta/rng_t.hpp
@@ -0,0 +1,12 @@
+#ifndef STAN_MATH_PRIM_META_RNG_T_HPP
+#define STAN_MATH_PRIM_META_RNG_T_HPP
+
+#include <boost/random/mixmax.hpp>
+
+namespace stan {
+
+using rng_t = boost::random::mixmax;
+
+}  // namespace stan
+
+#endif
diff --git a/test/unit/math/fwd/prob/lkj_corr_test.cpp b/test/unit/math/fwd/prob/lkj_corr_test.cpp
@@ -5,7 +5,7 @@
 
 TEST(ProbDistributionsLkjCorr, fvar_double) {
   using stan::math::fvar;
-  boost::random::mixmax rng;
+  stan::rng_t rng;
   int K = 4;
   Eigen::Matrix<fvar<double>, Eigen::Dynamic, Eigen::Dynamic> Sigma(K, K);
   Sigma.setZero();
@@ -24,7 +24,7 @@ TEST(ProbDistributionsLkjCorr, fvar_double) {
 
 TEST(ProbDistributionsLkjCorrCholesky, fvar_double) {
   using stan::math::fvar;
-  boost::random::mixmax rng;
+  stan::rng_t rng;
   int K = 4;
   Eigen::Matrix<fvar<double>, Eigen::Dynamic, Eigen::Dynamic> Sigma(K, K);
   Sigma.setZero();
@@ -43,7 +43,7 @@ TEST(ProbDistributionsLkjCorrCholesky, fvar_double) {
 
 TEST(ProbDistributionsLkjCorr, fvar_fvar_double) {
   using stan::math::fvar;
-  boost::random::mixmax rng;
+  stan::rng_t rng;
   int K = 4;
   Eigen::Matrix<fvar<fvar<double> >, Eigen::Dynamic, Eigen::Dynamic> Sigma(K,
                                                                            K);
@@ -63,7 +63,7 @@ TEST(ProbDistributionsLkjCorr, fvar_fvar_double) {
 
 TEST(ProbDistributionsLkjCorrCholesky, fvar_fvar_double) {
   using stan::math::fvar;
-  boost::random::mixmax rng;
+  stan::rng_t rng;
   int K = 4;
   Eigen::Matrix<fvar<fvar<double> >, Eigen::Dynamic, Eigen::Dynamic> Sigma(K,
                                                                            K);

diff --git a/test/unit/math/mix/prob/lkj_corr_test.cpp b/test/unit/math/mix/prob/lkj_corr_test.cpp
@@ -9,7 +9,7 @@
 TEST(ProbDistributionsLkjCorr, fvar_var) {
   using stan::math::fvar;
   using stan::math::var;
-  boost::random::mixmax rng;
+  stan::rng_t rng;
   int K = 4;
   Eigen::Matrix<fvar<var>, Eigen::Dynamic, Eigen::Dynamic> Sigma(K, K);
   Sigma.setZero();
@@ -31,7 +31,7 @@ TEST(ProbDistributionsLkjCorr, fvar_var) {
 TEST(ProbDistributionsLkjCorrCholesky, fvar_var) {
   using stan::math::fvar;
   using stan::math::var;
-  boost::random::mixmax rng;
+  stan::rng_t rng;
   int K = 4;
   Eigen::Matrix<fvar<var>, Eigen::Dynamic, Eigen::Dynamic> Sigma(K, K);
   Sigma.setZero();
@@ -54,7 +54,7 @@ TEST(ProbDistributionsLkjCorrCholesky, fvar_var) {
 TEST(ProbDistributionsLkjCorr, fvar_fvar_var) {
   using stan::math::fvar;
   using stan::math::var;
-  boost::random::mixmax rng;
+  stan::rng_t rng;
   int K = 4;
   Eigen::Matrix<fvar<fvar<var> >, Eigen::Dynamic, Eigen::Dynamic> Sigma(K, K);
   Sigma.setZero();
@@ -78,7 +78,7 @@ TEST(ProbDistributionsLkjCorr, fvar_fvar_var) {
 TEST(ProbDistributionsLkjCorrCholesky, fvar_fvar_var) {
   using stan::math::fvar;
   using stan::math::var;
-  boost::random::mixmax rng;
+  stan::rng_t rng;
   int K = 4;
   Eigen::Matrix<fvar<fvar<var> >, Eigen::Dynamic, Eigen::Dynamic> Sigma(K, K);
   Sigma.setZero();

diff --git a/test/unit/math/opencl/multiply_transpose_test.cpp b/test/unit/math/opencl/multiply_transpose_test.cpp
@@ -7,7 +7,7 @@
 #include <boost/random/mersenne_twister.hpp>
 #include <gtest/gtest.h>
 #include <algorithm>
-boost::random::mixmax rng;
+stan::rng_t rng;
 
 TEST(MathMatrixOpenCL, multiply_transpose_exception_fail_zero) {
   stan::math::row_vector_d rv(0);

diff --git a/test/unit/math/opencl/prim/mdivide_left_tri_low_test.cpp b/test/unit/math/opencl/prim/mdivide_left_tri_low_test.cpp
@@ -29,7 +29,7 @@ TEST(MathMatrixCL, mdivide_left_tri_low_cl_exception) {
 }
 
 void mdivide_left_tri_low_Ab_test(int size) {
-  boost::random::mixmax rng;
+  stan::rng_t rng;
   auto m1 = stan::math::matrix_d(size, size);
   for (int i = 0; i < size; i++) {
     for (int j = 0; j < i; j++) {
@@ -57,7 +57,7 @@ void mdivide_left_tri_low_Ab_test(int size) {
 }
 
 void mdivide_left_tri_low_A_test(int size) {
-  boost::random::mixmax rng;
+  stan::rng_t rng;
   auto m1 = stan::math::matrix_d(size, size);
   for (int i = 0; i < size; i++) {
     for (int j = 0; j < i; j++) {

diff --git a/test/unit/math/opencl/prim/mdivide_right_tri_low_test.cpp b/test/unit/math/opencl/prim/mdivide_right_tri_low_test.cpp
@@ -29,7 +29,7 @@ TEST(MathMatrixCL, mdivide_right_tri_low_cl_exception) {
 }
 
 void mdivide_right_tri_low_Ab_test(int size) {
-  boost::random::mixmax rng;
+  stan::rng_t rng;
   auto m1 = stan::math::matrix_d(size, size);
   for (int i = 0; i < size; i++) {
     for (int j = 0; j < i; j++) {

diff --git a/test/unit/math/opencl/tri_inverse_test.cpp b/test/unit/math/opencl/tri_inverse_test.cpp
@@ -25,7 +25,7 @@ TEST(MathMatrixCL, inverse_cl_exception) {
 }
 
 void lower_inverse_test(int size) {
-  boost::random::mixmax rng;
+  stan::rng_t rng;
   auto m1 = stan::math::matrix_d(size, size);
   for (int i = 0; i < size; i++) {
     for (int j = 0; j < i; j++) {
@@ -56,7 +56,7 @@ void lower_inverse_test(int size) {
 }
 
 void upper_inverse_test(int size) {
-  boost::random::mixmax rng;
+  stan::rng_t rng;
   auto m1 = stan::math::matrix_d(size, size);
   for (int i = 0; i < size; i++) {
     for (int j = 0; j < i; j++) {

diff --git a/test/unit/math/prim/fun/chol2inv_test.cpp b/test/unit/math/prim/fun/chol2inv_test.cpp
@@ -25,7 +25,7 @@ TEST(MathMatrixPrimMat, chol2inv) {
   using stan::math::matrix_d;
   using stan::math::wishart_rng;
 
-  boost::random::mixmax rng;
+  stan::rng_t rng;
   matrix_d I(3, 3);
   I.setZero();
   I.diagonal().setOnes();

diff --git a/test/unit/math/prim/prob/bernoulli_logit_glm_rng_test.cpp b/test/unit/math/prim/prob/bernoulli_logit_glm_rng_test.cpp
@@ -9,7 +9,7 @@
 TEST(ProbDistributionsBernoulliLogitGlm, vectorized) {
   using stan::math::bernoulli_logit_glm_rng;
   //  Test scalar/vector combinations.
-  boost::random::mixmax rng;
+  stan::rng_t rng;
 
   Eigen::MatrixXd x(2, 3);
   x << 3.5, -1.5, 0.0, 2.0, 1.0, 3.0;
@@ -70,7 +70,7 @@ TEST(ProbDistributionsBernoulliLogitGlm, vectorized) {
 TEST(ProbDistributionsBernoulliLogitGlm, errorCheck) {
   using stan::math::bernoulli_logit_glm_rng;
   // Check errors for nonfinite and wrong sizes.
-  boost::random::mixmax rng;
+  stan::rng_t rng;
 
   int N = 3;
   int M = 2;
@@ -107,7 +107,7 @@ TEST(ProbDistributionsBernoulliLogitGlm, errorCheck) {
 TEST(ProbDistributionsBernoulliLogitGlm, marginalChiSquareGoodnessFitTest) {
   using stan::math::bernoulli_logit_glm_rng;
   // Check distribution of result.
-  boost::random::mixmax rng;
+  stan::rng_t rng;
   Eigen::MatrixXd x(2, 2);
   x << 3.5, -1.5, 2.0, -1.2;
   std::vector<double> alpha{2.0, 1.0};

diff --git a/test/unit/math/prim/prob/bernoulli_logit_test.cpp b/test/unit/math/prim/prob/bernoulli_logit_test.cpp
@@ -35,7 +35,7 @@ TEST(ProbDistributionsBernoulliLogit, distributionCheck) {
 }
 
 TEST(ProbDistributionsBernoulliLogit, error_check) {
-  boost::random::mixmax rng;
+  stan::rng_t rng;
 
   EXPECT_NO_THROW(stan::math::bernoulli_logit_rng(-3.5, rng));
   EXPECT_THROW(
@@ -44,7 +44,7 @@ TEST(ProbDistributionsBernoulliLogit, error_check) {
 }
 
 TEST(ProbDistributionsBernoulliLogit, logitChiSquareGoodnessFitTest) {
-  boost::random::mixmax rng;
+  stan::rng_t rng;
   // number of samples
   int N = 10000;
 

diff --git a/test/unit/math/prim/prob/bernoulli_test.cpp b/test/unit/math/prim/prob/bernoulli_test.cpp
@@ -35,7 +35,7 @@ TEST(ProbDistributionsBernoulli, distributionCheck) {
 }
 
 TEST(ProbDistributionsBernoulli, error_check) {
-  boost::random::mixmax rng;
+  stan::rng_t rng;
   EXPECT_NO_THROW(stan::math::bernoulli_rng(0.6, rng));
 
   EXPECT_THROW(stan::math::bernoulli_rng(1.6, rng), std::domain_error);
@@ -45,7 +45,7 @@ TEST(ProbDistributionsBernoulli, error_check) {
 }
 
 TEST(ProbDistributionsBernoulli, chiSquareGoodnessFitTest) {
-  boost::random::mixmax rng;
+  stan::rng_t rng;
   int N = 10000;
 
   std::vector<double> expected;

diff --git a/test/unit/math/prim/prob/beta_binomial_test.cpp b/test/unit/math/prim/prob/beta_binomial_test.cpp
@@ -40,7 +40,7 @@ TEST(ProbDistributionsBetaBinomial, distributionCheck) {
 }
 
 TEST(ProbDistributionBetaBinomial, error_check) {
-  boost::random::mixmax rng;
+  stan::rng_t rng;
   EXPECT_NO_THROW(stan::math::beta_binomial_rng(4, 0.6, 2.0, rng));
 
   EXPECT_THROW(stan::math::beta_binomial_rng(-4, 0.6, 2, rng),

diff --git a/test/unit/math/prim/prob/beta_proportion_test.cpp b/test/unit/math/prim/prob/beta_proportion_test.cpp
@@ -50,7 +50,7 @@ TEST(ProbDistributionsBetaProportion, distributionTest) {
 }
 
 TEST(ProbDistributionsBetaProportion, error_check) {
-  boost::random::mixmax rng;
+  stan::rng_t rng;
   EXPECT_NO_THROW(stan::math::beta_proportion_rng(0.5, 3.0, rng));
   EXPECT_NO_THROW(stan::math::beta_proportion_rng(1e-10, 1e-10, rng));
   EXPECT_THROW(stan::math::beta_proportion_rng(2.0, -1.0, rng),
@@ -68,7 +68,7 @@ TEST(ProbDistributionsBetaProportion, error_check) {
 }
 
 TEST(ProbDistributionsBetaProportion, chiSquareGoodnessFitTest) {
-  boost::random::mixmax rng;
+  stan::rng_t rng;
   int N = 10000;
   int K = stan::math::round(2 * std::pow(N, 0.4));
 
@@ -99,7 +99,7 @@ TEST(ProbDistributionsBetaProportion, chiSquareGoodnessFitTest) {
 }
 
 TEST(ProbDistributionsBetaProportion, chiSquareGoodnessFitTest2) {
-  boost::random::mixmax rng;
+  stan::rng_t rng;
   int N = 10000;
   int K = stan::math::round(2 * std::pow(N, 0.4));
 

diff --git a/test/unit/math/prim/prob/beta_test.cpp b/test/unit/math/prim/prob/beta_test.cpp
@@ -46,7 +46,7 @@ TEST(ProbDistributionsBeta, distributionTest) {
 }
 
 TEST(ProbDistributionsBeta, error_check) {
-  boost::random::mixmax rng;
+  stan::rng_t rng;
   EXPECT_NO_THROW(stan::math::beta_rng(2.0, 1.0, rng));
   EXPECT_NO_THROW(stan::math::beta_rng(1e-10, 1e-10, rng));
 
@@ -60,7 +60,7 @@ TEST(ProbDistributionsBeta, error_check) {
 }
 
 TEST(ProbDistributionsBeta, chiSquareGoodnessFitTest) {
-  boost::random::mixmax rng;
+  stan::rng_t rng;
   int N = 10000;
   int K = stan::math::round(2 * std::pow(N, 0.4));
 
@@ -83,7 +83,7 @@ TEST(ProbDistributionsBeta, chiSquareGoodnessFitTest) {
 }
 
 TEST(ProbDistributionsBeta, chiSquareGoodnessFitTestSmallParameters) {
-  boost::random::mixmax rng;
+  stan::rng_t rng;
   int N = 10000;
   int K = stan::math::round(2 * std::pow(N, 0.4));
 

diff --git a/test/unit/math/prim/prob/binomial_test.cpp b/test/unit/math/prim/prob/binomial_test.cpp
@@ -39,7 +39,7 @@ TEST(ProbDistributionsBinomial, distributionCheck) {
 }
 
 TEST(ProbDistributionBinomiali, error_check) {
-  boost::random::mixmax rng;
+  stan::rng_t rng;
   EXPECT_NO_THROW(stan::math::binomial_rng(4, 0.6, rng));
   EXPECT_THROW(stan::math::binomial_rng(-4, 0.6, rng), std::domain_error);
   EXPECT_THROW(stan::math::binomial_rng(4, -0.6, rng), std::domain_error);
@@ -50,7 +50,7 @@ TEST(ProbDistributionBinomiali, error_check) {
 }
 
 TEST(ProbDistributionsBinomial, chiSquareGoodnessFitTest) {
-  boost::random::mixmax rng;
+  stan::rng_t rng;
   int N = 10000;
   int K = stan::math::round(2 * std::pow(N, 0.4));
   boost::math::binomial_distribution<> dist(100, 0.6);

diff --git a/test/unit/math/prim/prob/categorical_logit_rng_test.cpp b/test/unit/math/prim/prob/categorical_logit_rng_test.cpp
@@ -7,7 +7,7 @@
 TEST(ProbDistributionsCategoricalLogit, error_check) {
   using Eigen::VectorXd;
   using stan::math::categorical_logit_rng;
-  boost::random::mixmax rng;
+  stan::rng_t rng;
 
   VectorXd beta(3);
 
@@ -27,7 +27,7 @@ TEST(ProbDistributionsCategoricalLogit, error_check) {
 TEST(ProbDistributionsCategoricalLogit, chiSquareGoodnessFitTest) {
   using Eigen::VectorXd;
   using stan::math::softmax;
-  boost::random::mixmax rng;
+  stan::rng_t rng;
   int N = 10000;
   int K = 3;
   VectorXd beta(K);

diff --git a/test/unit/math/prim/prob/categorical_test.cpp b/test/unit/math/prim/prob/categorical_test.cpp
@@ -88,7 +88,7 @@ TEST(ProbDistributionsCategorical, error_check) {
   using Eigen::Dynamic;
   using Eigen::Matrix;
   using stan::math::categorical_log;
-  boost::random::mixmax rng;
+  stan::rng_t rng;
 
   Matrix<double, Dynamic, Dynamic> theta(3, 1);
   theta << 0.15, 0.45, 0.50;
@@ -100,7 +100,7 @@ TEST(ProbDistributionsCategorical, chiSquareGoodnessFitTest) {
   using Eigen::Dynamic;
   using Eigen::Matrix;
   using stan::math::categorical_log;
-  boost::random::mixmax rng;
+  stan::rng_t rng;
 
   int N = 10000;
   Matrix<double, Dynamic, Dynamic> theta(3, 1);

diff --git a/test/unit/math/prim/prob/cauchy_test.cpp b/test/unit/math/prim/prob/cauchy_test.cpp
@@ -46,7 +46,7 @@ TEST(ProbDistributionsCauchy, distributionTest) {
 }
 
 TEST(ProbDistributionsCauchy, error_check) {
-  boost::random::mixmax rng;
+  stan::rng_t rng;
   EXPECT_NO_THROW(stan::math::cauchy_rng(2.0, 1.0, rng));
 
   EXPECT_THROW(stan::math::cauchy_rng(2.0, -1.0, rng), std::domain_error);
@@ -59,7 +59,7 @@ TEST(ProbDistributionsCauchy, error_check) {
 }
 
 TEST(ProbDistributionsCauchy, chiSquareGoodnessFitTest) {
-  boost::random::mixmax rng;
+  stan::rng_t rng;
   int N = 10000;
   int K = stan::math::round(2 * std::pow(N, 0.4));
 

diff --git a/test/unit/math/prim/prob/chi_square_test.cpp b/test/unit/math/prim/prob/chi_square_test.cpp
@@ -42,7 +42,7 @@ TEST(ProbDistributionsChiSquare, distributionTest) {
 }
 
 TEST(ProbDistributionsChiSquare, error_check) {
-  boost::random::mixmax rng;
+  stan::rng_t rng;
   EXPECT_NO_THROW(stan::math::chi_square_rng(2.0, rng));
 
   EXPECT_THROW(stan::math::chi_square_rng(-2.0, rng), std::domain_error);
@@ -51,7 +51,7 @@ TEST(ProbDistributionsChiSquare, error_check) {
 }
 
 TEST(ProbDistributionsChiSquare, chiSquareGoodnessFitTest) {
-  boost::random::mixmax rng;
+  stan::rng_t rng;
   int N = 10000;
   int K = stan::math::round(2 * std::pow(N, 0.4));
 

diff --git a/test/unit/math/prim/prob/dirichlet_multinomial_test.cpp b/test/unit/math/prim/prob/dirichlet_multinomial_test.cpp
@@ -90,7 +90,7 @@ TEST(ProbDistributionsDirichletMultinomial, zeros) {
 TEST(ProbDistributionsDirichletMultinomial, rng) {
   using Eigen::Dynamic;
   using Eigen::Matrix;
-  boost::random::mixmax rng;
+  stan::rng_t rng;
 
   Matrix<double, Dynamic, 1> theta(3);
   theta << 0.5, 5.5, 12.0;
@@ -113,7 +113,7 @@ TEST(ProbDistributionsDirichletMultinomial, rng) {
 TEST(ProbDistributionsDirichletMultinomial, rngError) {
   using Eigen::Dynamic;
   using Eigen::Matrix;
-  boost::random::mixmax rng;
+  stan::rng_t rng;
 
   Matrix<double, Dynamic, 1> theta(3);
   theta << 0.5, 1.5, 4.0;
@@ -135,7 +135,7 @@ TEST(ProbDistributionsDirichletMultinomial, rngError) {
 TEST(ProbDistributionsDirichletMultinomial, chiSquareGoodnessFitTest) {
   using Eigen::Dynamic;
   using Eigen::Matrix;
-  boost::random::mixmax rng;
+  stan::rng_t rng;
   int M = 100;
   int trials = 100;
   int N = M * trials;
@@ -171,7 +171,7 @@ TEST(ProbDistributionsDirichletMultinomial, equivBetaBinomial) {
   using Eigen::Matrix;
   using stan::math::beta_binomial_lpmf;
 
-  boost::random::mixmax rng;
+  stan::rng_t rng;
   std::vector<int> ns;
   Matrix<double, Dynamic, 1> theta(2, 1);
   double alpha = 4.0;