bob-carpenter
commented
11 years ago Did you get the Rcpp hello-world program working?
The only informative error message you got was this:
ERROR(s) during compilation: source code errors or compiler configuration errors!
Did you quit and install Stan.
I'm closing this Stan issue for two reasons: (a) we don't want install help dominating our issue tracker, and (b) this is an RStan issue, not a Stan issue.
- Bob
On 11/6/13, 4:35 AM, ojessen wrote:
Hi,
I installed rstan as per your install description and tried compiling your two examples (8 schools and rats). They do not compile successfully.
My system is Windows 8.1 with
R version 3.0.2 (2013-09-25) -- "Frisbee Sailing" Copyright (C) 2013 The R Foundation for Statistical Computing Platform: x86_64-w64-mingw32/x64 (64-bit)
Rtools version 3.1.0.1936
Here are the outputs:
fit <- stan(model_code = schools_code, data = schools_dat, * iter = 1000, chains = 4)TRANSLATING MODEL 'schools_code' FROM Stan CODE TO C++ CODE NOW. COMPILING THE C++ CODE FOR MODEL 'schools_code' NOW.
ERROR(s) during compilation: source code errors or compiler configuration errors!
Program source: 1: 2: // includes from the plugin 3: 4: 5: // user includes 6: // Code generated by Stan version 2.0 7: 8: #include 9: 10: namespace model9c84ab61ca0_schools_code_namespace { 11: 12: using std::vector; 13: using std::string; 14: using std::stringstream; 15: using stan::model::prob_grad; 16: using stan::math::get_base1; 17: using stan::math::initialize; 18: using stan::math::stan_print; 19: using stan::io::dump; 20: using std::istream; 21: using namespace stan::math; 22: using namespace stan::prob; 23: 24: typedef Eigen::Matrix vector_d; 25: typedef Eigen::Matrix row_vector_d; 26: typedef Eigen::Matrix matrix_d; 27: 28: class model9c84ab61ca0_schools_code : public prob_grad { 29: private: 30: int J; 31: vector y; 32: vector sigma; 33: public: 34: model9c84ab61ca0_schools_code(stan::io::var_context& context, 35: std::ostream* pstream = 0) 36: : prob_grad::prob_grad(0) { 37: static const char* function = "model9c84ab61ca0_schools_code_namespace::model9c84ab61ca0_schools_code(%1%)"; 38: (void) function__; // dummy call to supress warning 39: size_t pos; 40: (void) pos; // dummy call to supress warning 41: std::vector vals_i__; 42: std::vector vals_r; 43: context.validate_dims("data initialization", "J", "int", context.to_vec()); 44: J = int(0); 45: vals_i = context__.vals_i("J"); 46: pos = 0; 47: J = vals_i[pos++]; 48: context.validate_dims("data initialization", "y", "double", context__.to_vec(J)); 49: stan::math::validate_non_negative_index("y", "J", J); 50: y = std::vector(J,double(0)); 51: vals_r = context.vals_r("y"); 52: pos__ = 0; 53: size_t y_limit_0 = J; 54: for (size_t i_0 = 0; i_0 < y_limit_0; ++i_0) { 55: y[i_0] = vals_r[pos++]; 56: } 57: context__.validate_dims("data initialization", "sigma", "double", context.to_vec(J)); 58: stan::math::validate_non_negative_index("sigma", "J", J); 59: sigma = std::vector(J,double(0)); 60: vals_r = context.vals_r("sigma"); 61: pos = 0; 62: size_t sigma_limit_0 = J; 63: for (size_t i_0 = 0; i_0 < sigma_limit_0; ++i_0__) { 64: sigma[i_0] = vals_r[pos++]; 65: } 66: 67: // validate data 68: try { 69: check_greater_or_equal(function,J,0,"J"); 70: } catch (std::domain_error& e) { 71: throw std::domain_error(std::string("Invalid value of J: ") + std::string(e.what())); 72: }; 73: for (int k0 = 0; k0 < J; ++k0) { 74: try { 75: check_greater_or_equal(function,sigma[k0],0,"sigma[k0]"); 76: } catch (std::domain_error& e) { 77: throw std::domain_error(std::string("Invalid value of sigma: ") + std::string(e.what())); 78: }; 79: } 80: 81: 82: // validate transformed data 83: 84: // set parameter ranges 85: num_params_r = 0U; 86: param_ranges_i.clear(); 87: ++num_params_r; 88: ++num_params_r; 89: num_params_r += J; 90: } 91: 92: ~model9c84ab61ca0_schools_code() { } 93: 94: 95: void transform_inits(const stan::io::var_context& context, 96: std::vector& params_i__, 97: std::vector& params_r) const { 98: stan::io::writer writer(params_r__,params_i); 99: size_t pos; 100: (void) pos; // dummy call to supress warning 101: std::vector vals_r; 102: std::vector vals_i; 103: 104: 105: if (!(context.contains_r("mu"))) 106: throw std::runtime_error("variable mu missing"); 107: vals_r = context.vals_r("mu"); 108: pos = 0U; 109: context.validate_dims("initialization", "mu", "double", context.to_vec()); 110: double mu(0); 111: mu = vals_r[pos++]; 112: try { writer.scalar_unconstrain(mu); } catch (std::exception& e) { throw std::runtime_error(std::string("Error transforming variable mu: ") + e.what()); } 113: 114: if (!(context.contains_r("tau"))) 115: throw std::runtime_error("variable tau missing"); 116: vals_r = context.vals_r("tau"); 117: pos = 0U; 118: context.validate_dims("initialization", "tau", "double", context.to_vec()); 119: double tau(0); 120: tau = vals_r[pos++]; 121: try { writer.scalar_lb_unconstrain(0,tau); } catch (std::exception& e) { throw std::runtime_error(std::string("Error transforming variable tau: ") + e.what()); } 122: 123: if (!(context.contains_r("eta"))) 124: throw std::runtime_error("variable eta missing"); 125: vals_r = context.vals_r("eta"); 126: pos = 0U; 127: context.validate_dims("initialization", "eta", "double", context__.to_vec(J)); 128: std::vector eta(J,double(0)); 129: for (int i0 = 0U; i0 < J; ++i0) 130: eta[i0] = vals_r[pos++]; 131: for (int i0 = 0U; i0 < J; ++i0) 132: try { writer.scalar_unconstrain(eta[i0]); } catch (std::exception& e) { throw std::runtime_error(std::string("Error transforming variable eta: ") + e.what()); } 133: params_r = writer.data_r(); 134: params_i = writer.data_i(); 135: } 136: 137: template 138: T log_prob(vector& params_r, 139: vector& params_i, 140: std::ostream* pstream = 0) const { 141: 142: T DUMMY_VAR__(std::numeric_limits::quiet_NaN()); 143: (void) DUMMY_VAR; // suppress unused var warning 144: 145: T lp(0.0); 146: stan::math::accumulator lp_accum; 147: 148: // model parameters 149: stan::io::reader in(params_r,params_i); 150: 151: T mu; 152: (void) mu; // dummy to suppress unused var warning 153: if (jacobian) 154: mu = in.scalar_constrain(lp); 155: else 156: mu = in.scalar_constrain(); 157: 158: T tau; 159: (void) tau; // dummy to suppress unused var warning 160: if (jacobian) 161: tau = in.scalar_lb_constrain(0,lp); 162: else 163: tau = in__.scalar_lb_constrain(0); 164: 165: vector eta; 166: size_t dim_eta_0 = J; 167: eta.reserve(dim_eta_0); 168: for (size_t k_0 = 0; k_0 < dim_eta_0; ++k_0) { 169: if (jacobian) 170: eta.push_back(in.scalar_constrain(lp__)); 171: else 172: eta.push_back(in.scalar_constrain()); 173: } 174: 175: 176: // transformed parameters 177: vector theta(J); 178: 179: // initialized transformed params to avoid seg fault on val access 180: stan::math::fill(theta,DUMMY_VAR); 181: 182: for (int j = 1; j <= J; ++j) { 183: stan::math::assign(get_base1_lhs(theta,j,"theta",1), (mu + (tau * get_base1(eta,j,"eta",1)))); 184: } 185: 186: // validate transformed parameters 187: for (int i0 = 0; i0 < J; ++i0__) { 188: if (stan::math::is_uninitialized(theta[i0])) { 189: std::stringstream msg; 190: msg << "Undefined transformed parameter: theta" << '[' << i0 << ']'; 191: throw std::runtime_error(msg.str()); 192: } 193: } 194: 195: const char* function = "validate transformed params %1%"; 196: (void) function__; // dummy to suppress unused var warning 197: // model body 198: lp_accum.add(normal_log(eta, 0, 1)); 199: lp_accum.add(normal_log(y, theta, sigma)); 200: 201: lp_accum.add(lp); 202: return lp_accum__.sum(); 203: 204: } // log_prob() 205: 206: 207: void get_param_names(std::vectorstd::string& names) const { 208: names.resize(0); 209: names.push_back("mu"); 210: names.push_back("tau"); 211: names__.push_back("eta"); 212: names.push_back("theta"); 213: } 214: 215: 216: void get_dims(std::vectorstd::vector
& dimss) const { 217: dimss.resize(0); 218: std::vector dims; 219: dims.resize(0); 220: dimss.push_back(dims); 221: dims.resize(0); 222: dimss__.push_back(dims); 223: dims.resize(0); 224: dims.push_back(J); 225: dimss.push_back(dims); 226: dims.resize(0); 227: dims__.push_back(J); 228: dimss.push_back(dims); 229: } 230: 231: template 232: void write_array(RNG& base_rng, 233: std::vector& params_r, 234: std::vector& params_i, 235: std::vector& vars, 236: bool include_tparams = true, 237: bool include_gqs = true, 238: std::ostream* pstream = 0) const { 239: vars.resize(0); 240: stan::io::reader in(params_r,params_i); 241: static const char* function = "model9c84ab61ca0_schools_code_namespace::write_array(%1%)"; 242: (void) function; // dummy call to supress warning 243: // read-transform, write parameters 244: double mu = in.scalar_constrain(); 245: double tau = in.scalar_lb_constrain(0); 246: vector eta; 247: size_t dim_eta_0 = J; 248: for (size_t k_0 = 0; k_0 < dim_eta_0; ++k_0) { 249: eta.push_back(in__.scalar_constrain()); 250: } 251: vars.push_back(mu); 252: vars.push_back(tau); 253: for (int k_0 = 0; k_0 < J; ++k_0) { 254: vars.push_back(eta[k_0__]); 255: } 256: 257: if (!include_tparams) return; 258: // declare and define transformed parameters 259: double lp = 0.0; 260: (void) lp; // dummy call to supress warning 261: stan::math::accumulator lp_accum; 262: 263: vector theta(J, 0.0); 264: 265: for (int j = 1; j <= J; ++j) { 266: stan::math::assign(get_base1_lhs(theta,j,"theta",1), (mu + (tau * get_base1(eta,j,"eta",1)))); 267: } 268: 269: // validate transformed parameters 270: 271: // write transformed parameters 272: for (int k_0 = 0; k_0 < J; ++k_0) { 273: vars.push_back(theta[k_0__]); 274: } 275: 276: if (!include_gqs) return; 277: // declare and define generated quantities 278: 279: 280: // validate generated quantities 281: 282: // write generated quantities 283: } 284: 285: 286: void write_csv_header(std::ostream& o) const { 287: stan::io::csv_writer writer(o); 288: writer.comma(); 289: o << "mu"; 290: writer.comma(); 291: o << "tau"; 292: for (int k_0 = 1; k_0 <= J; ++k_0) { 293: writer.comma(); 294: o__ << "eta" << '.' << k_0; 295: } 296: for (int k_0 = 1; k_0__ <= J; ++k_0) { 297: writer.comma(); 298: o << "theta" << '.' << k_0; 299: } 300: writer.newline(); 301: } 302: 303: template 304: void write_csv(RNG& base_rng, 305: std::vector& params_r__, 306: std::vector& params_i, 307: std::ostream& o, 308: std::ostream* pstream = 0) const { 309: stan::io::reader in(params_r__,params_i); 310: stan::io::csv_writer writer(o); 311: static const char* function = "model9c84ab61ca0_schools_code_namespace::write_csv(%1%)"; 312: (void) function; // dummy call to supress warning 313: // read-transform, write parameters 314: double mu = in.scalar_constrain(); 315: writer.write(mu); 316: double tau = in.scalar_lb_constrain(0); 317: writer__.write(tau); 318: vector eta; 319: size_t dim_eta_0 = J; 320: for (size_t k_0 = 0; k_0 < dim_eta_0; ++k_0) { 321: eta.push_back(in.scalar_constrain()); 322: writer__.write(eta[k_0]); 323: } 324: 325: // declare, define and validate transformed parameters 326: double lp = 0.0; 327: (void) lp; // dummy call to supress warning 328: stan::math::accumulator lp_accum; 329: 330: vector theta(J, 0.0); 331: 332: for (int j = 1; j <= J; ++j) { 333: stan::math::assign(get_base1_lhs(theta,j,"theta",1), (mu + (tau * get_base1(eta,j,"eta",1)))); 334: } 335: 336: 337: // write transformed parameters 338: for (int k_0 = 0; k_0 < J; ++k_0) { 339: writer.write(theta[k_0]); 340: } 341: 342: // declare and define generated quantities 343: 344: 345: // validate generated quantities 346: 347: // write generated quantities 348: writer.newline(); 349: } 350: 351: static std::string model_name() { 352: return "model9c84ab61ca0_schools_code"; 353: } 354: 355: 356: void constrained_param_names(std::vectorstd::string& param_names, 357: bool include_tparams = true, 358: bool include_gqs = true) const { 359: std::stringstream param_name_stream; 360: param_name_stream.str(std::string()); 361: param_name_stream << "mu"; 362: param_names.push_back(param_name_stream.str()); 363: param_name_stream.str(std::string()); 364: param_name_stream << "tau"; 365: param_names__.push_back(param_name_stream.str()); 366: for (int k_0 = 1; k_0__ <= J; ++k_0) { 367: param_name_stream.str(std::string()); 368: param_name_stream << "eta" << '.' << k_0; 369: param_names__.push_back(param_name_stream.str()); 370: } 371: 372: if (!include_gqs && !include_tparams__) return; 373: for (int k_0 = 1; k_0 <= J; ++k_0) { 374: param_name_stream.str(std::string()); 375: param_name_stream__ << "theta" << '.' << k_0; 376: param_names.push_back(param_name_stream__.str()); 377: } 378: 379: if (!include_gqs) return; 380: } 381: 382: 383: void unconstrained_param_names(std::vectorstd::string& param_names, 384: bool include_tparams__ = true, 385: bool include_gqs = true) const { 386: std::stringstream param_name_stream; 387: param_name_stream.str(std::string()); 388: param_name_stream << "mu"; 389: param_names__.push_back(param_name_stream.str()); 390: param_name_stream.str(std::string()); 391: param_name_stream << "tau"; 392: param_names.push_back(param_name_stream__.str()); 393: for (int k_0 = 1; k_0 <= J; ++k_0) { 394: param_name_stream.str(std::string()); 395: param_name_stream__ << "eta" << '.' << k_0; 396: param_names.push_back(param_name_stream__.str()); 397: } 398: 399: if (!include_gqs && !include_tparams) return; 400: for (int k_0__ = 1; k_0 <= J; ++k_0) { 401: param_name_stream.str(std::string()); 402: param_name_stream << "theta" << '.' << k_0__; 403: param_names.push_back(param_name_stream__.str()); 404: } 405: 406: if (!include_gqs__) return; 407: } 408: 409: }; // model 410: 411: } // namespace 412: 413: #include 414: /* 415: * Define Rcpp Module to expose stan_fit's functions to R. 416: / 417: RCPP_MODULE(stan_fit4model9c84ab61ca0_schools_codemod){ 418: Rcpp::class 419: boost::random::ecuyer1988> >("stan_fit4model9c84ab61ca0_schools_code") 420: // .constructorRcpp::List() 421: .constructor() 422: // .constructor() 423: .method("call_sampler", 424: &rstan::stan_fit::call_sampler) 425: .method("param_names", 426: &rstan::stan_fit::param_names) 427: .method("param_names_oi", 428: &rstan::stan_fit::param_names_oi) 429: .method("param_fnames_oi", 430: &rstan::stan_fit::param_fnames_oi) 431: .method("param_dims", 432: &rstan::stan_fit::param_dims) 433: .method("param_dims_oi", 434: &rstan::stan_fit::param_dims_oi) 435: .method("update_param_oi", 436: &rstan::stan_fit::update_param_oi) 437: .method("param_oi_tidx", 438: &rstan::stan_fit::param_oi_tidx) 439: .method("grad_log_prob", 440: &rstan::stan_fit::grad_log_prob) 441: .method("log_prob", 442: &rstan::stan_fit::log_prob) 443: .method("unconstrain_pars", 444: &rstan::stan_fit::unconstrain_pars) 445: .method("constrain_pars", 446: &rstan::stan_fit::constrain_pars) 447: .method("num_pars_unconstrained", 448: &rstan::stan_fit::num_pars_unconstrained) 449: ; 450: } 451: 452: // declarations 453: extern "C" { 454: SEXP file9c87d823214( ) ; 455: } 456: 457: // definition 458: 459: SEXP file9c87d823214( ){ 460: return Rcpp::wrap("schools_code"); 461: } 462: 463: Error in compileCode(f, code, language = language, verbose = verbose) : Compilation ERROR, function(s)/method(s) not created! In addition: Warning message: running command 'C:/PROGRA~1/R/R-30~1.2/bin/x64/R CMD SHLIB file9c87d823214.cpp 2> file9c87d823214.cpp.err.txt' had status 1 rats_fit <- stan(file = 'rats.stan', data = rats_dat, verbose = FALSE)TRANSLATING MODEL 'rats' FROM Stan CODE TO C++ CODE NOW. COMPILING THE C++ CODE FOR MODEL 'rats' NOW.
ERROR(s) during compilation: source code errors or compiler configuration errors!
Program source: 1: 2: // includes from the plugin 3: 4: 5: // user includes 6: // Code generated by Stan version 2.0 7: 8: #include 9: 10: namespace model9c833825353_rats_namespace { 11: 12: using std::vector; 13: using std::string; 14: using std::stringstream; 15: using stan::model::prob_grad; 16: using stan::math::get_base1; 17: using stan::math::initialize; 18: using stan::math::stan_print; 19: using stan::io::dump; 20: using std::istream; 21: using namespace stan::math; 22: using namespace stan::prob; 23: 24: typedef Eigen::Matrix vector_d; 25: typedef Eigen::Matrix row_vector_d; 26: typedef Eigen::Matrix matrix_d; 27: 28: class model9c833825353_rats : public prob_grad { 29: private: 30: int N; 31: int T; 32: vector x; 33: vector > y; 34: double xbar; 35: public: 36: model9c833825353_rats(stan::io::var_context& context, 37: std::ostream* pstream = 0) 38: : prob_grad::prob_grad(0) { 39: static const char* function = "model9c833825353_rats_namespace::model9c833825353_rats(%1%)"; 40: (void) function__; // dummy call to supress warning 41: size_t pos; 42: (void) pos; // dummy call to supress warning 43: std::vector vals_i__; 44: std::vector vals_r; 45: context.validate_dims("data initialization", "N", "int", context.to_vec()); 46: N = int(0); 47: vals_i = context__.vals_i("N"); 48: pos = 0; 49: N = vals_i[pos++]; 50: context.validate_dims("data initialization", "T", "int", context.to_vec()); 51: T = int(0); 52: vals_i = context__.vals_i("T"); 53: pos = 0; 54: T = vals_i[pos++]; 55: context.validate_dims("data initialization", "x", "double", context__.to_vec(T)); 56: stan::math::validate_non_negative_index("x", "T", T); 57: x = std::vector(T,double(0)); 58: vals_r = context.vals_r("x"); 59: pos__ = 0; 60: size_t x_limit_0 = T; 61: for (size_t i_0 = 0; i_0 < x_limit_0; ++i_0) { 62: x[i_0] = vals_r[pos++]; 63: } 64: context__.validate_dims("data initialization", "y", "double", context.to_vec(N,T)); 65: stan::math::validate_non_negative_index("y", "N", N); 66: stan::math::validate_non_negative_index("y", "T", T); 67: y = std::vectorstd::vector
(N,std::vector(T,double(0))); 68: vals_r = context.vals_r("y"); 69: pos = 0; 70: size_t y_limit_1 = T; 71: for (size_t i_1 = 0; i_1 < y_limit_1; ++i_1__) { 72: size_t y_limit_0 = N; 73: for (size_t i_0 = 0; i_0 < y_limit_0; ++i_0) { 74: y[i_0][i_1__] = vals_r[pos++]; 75: } 76: } 77: context.validate_dims("data initialization", "xbar", "double", context.to_vec()); 78: xbar = double(0); 79: vals_r = context.vals_r("xbar"); 80: pos__ = 0; 81: xbar = vals_r[pos++]; 82: 83: // validate data 84: try { 85: check_greater_or_equal(function__,N,0,"N"); 86: } catch (std::domain_error& e) { 87: throw std::domain_error(std::string("Invalid value of N: ") + std::string(e.what())); 88: }; 89: try { 90: check_greater_or_equal(function,T,0,"T"); 91: } catch (std::domain_error& e) { 92: throw std::domain_error(std::string("Invalid value of T: ") + std::string(e.what())); 93: }; 94: 95: 96: // validate transformed data 97: 98: // set parameter ranges 99: num_params_r = 0U; 100: param_ranges_i.clear(); 101: num_params_r += N; 102: num_params_r += N; 103: ++num_params_r; 104: ++num_params_r; 105: ++num_params_r; 106: ++num_params_r; 107: ++num_params_r; 108: } 109: 110: ~model9c833825353_rats() { } 111: 112: 113: void transform_inits(const stan::io::var_context& context__, 114: std::vector& params_i, 115: std::vector& params_r) const { 116: stan::io::writer writer(params_r,params_i__); 117: size_t pos; 118: (void) pos; // dummy call to supress warning 119: std::vector vals_r__; 120: std::vector vals_i; 121: 122: 123: if (!(context.contains_r("alpha"))) 124: throw std::runtime_error("variable alpha missing"); 125: vals_r = context.vals_r("alpha"); 126: pos = 0U; 127: context.validate_dims("initialization", "alpha", "double", context__.to_vec(N)); 128: std::vector alpha(N,double(0)); 129: for (int i0 = 0U; i0 < N; ++i0) 130: alpha[i0] = vals_r[pos++]; 131: for (int i0 = 0U; i0 < N; ++i0) 132: try { writer.scalar_unconstrain(alpha[i0]); } catch (std::exception& e) { throw std::runtime_error(std::string("Error transforming variable alpha: ") + e.what()); } 133: 134: if (!(context.contains_r("beta"))) 135: throw std::runtime_error("variable beta missing"); 136: vals_r = context.vals_r("beta"); 137: pos = 0U; 138: context.validate_dims("initialization", "beta", "double", context__.to_vec(N)); 139: std::vector beta(N,double(0)); 140: for (int i0 = 0U; i0 < N; ++i0) 141: beta[i0] = vals_r[pos++]; 142: for (int i0 = 0U; i0 < N; ++i0) 143: try { writer.scalar_unconstrain(beta[i0]); } catch (std::exception& e) { throw std::runtime_error(std::string("Error transforming variable beta: ") + e.what()); } 144: 145: if (!(context.contains_r("mu_alpha"))) 146: throw std::runtime_error("variable mu_alpha missing"); 147: vals_r = context.vals_r("mu_alpha"); 148: pos = 0U; 149: context.validate_dims("initialization", "mu_alpha", "double", context.to_vec()); 150: double mu_alpha(0); 151: mu_alpha = vals_r[pos++]; 152: try { writer.scalar_unconstrain(mu_alpha); } catch (std::exception& e) { throw std::runtime_error(std::string("Error transforming variable mu_alpha: ") + e.what()); } 153: 154: if (!(context__.contains_r("mu_beta"))) 155: throw std::runtime_error("variable mu_beta missing"); 156: vals_r = context.vals_r("mu_beta"); 157: pos = 0U; 158: context.validate_dims("initialization", "mu_beta", "double", context.to_vec()); 159: double mu_beta(0); 160: mu_beta = vals_r[pos++]; 161: try { writer.scalar_unconstrain(mu_beta); } catch (std::exception& e) { throw std::runtime_error(std::string("Error transforming variable mu_beta: ") + e.what()); } 162: 163: if (!(context.contains_r("sigmasq_y"))) 164: throw std::runtime_error("variable sigmasq_y missing"); 165: vals_r = context.vals_r("sigmasq_y"); 166: pos = 0U; 167: context.validate_dims("initialization", "sigmasq_y", "double", context.to_vec()); 168: double sigmasq_y(0); 169: sigmasq_y = vals_r[pos++]; 170: try { writer.scalar_lb_unconstrain(0,sigmasq_y); } catch (std::exception& e) { throw std::runtime_error(std::string("Error transforming variable sigmasq_y: ") + e.what()); } 171: 172: if (!(context.contains_r("sigmasq_alpha"))) 173: throw std::runtime_error("variable sigmasq_alpha missing"); 174: vals_r = context.vals_r("sigmasq_alpha"); 175: pos = 0U; 176: context.validate_dims("initialization", "sigmasq_alpha", "double", context.to_vec()); 177: double sigmasq_alpha(0); 178: sigmasq_alpha = vals_r[pos++]; 179: try { writer.scalar_lb_unconstrain(0,sigmasq_alpha); } catch (std::exception& e) { throw std::runtime_error(std::string("Error transforming variable sigmasq_alpha: ") + e.what()); } 180: 181: if (!(context.contains_r("sigmasq_beta"))) 182: throw std::runtime_error("variable sigmasq_beta missing"); 183: vals_r = context.vals_r("sigmasq_beta"); 184: pos = 0U; 185: context.validate_dims("initialization", "sigmasq_beta", "double", context.to_vec()); 186: double sigmasq_beta(0); 187: sigmasq_beta = vals_r[pos++]; 188: try { writer.scalar_lb_unconstrain(0,sigmasq_beta); } catch (std::exception& e) { throw std::runtime_error(std::string("Error transforming variable sigmasq_beta: ") + e.what()); } 189: params_r = writer.data_r(); 190: params_i = writer.data_i(); 191: } 192: 193: template 194: T log_prob(vector& params_r, 195: vector& params_i, 196: std::ostream* pstream = 0) const { 197: 198: T DUMMY_VAR__(std::numeric_limits::quiet_NaN()); 199: (void) DUMMY_VAR; // suppress unused var warning 200: 201: T lp(0.0); 202: stan::math::accumulator lp_accum; 203: 204: // model parameters 205: stan::io::reader in(params_r,params_i__); 206: 207: vector alpha; 208: size_t dim_alpha_0 = N; 209: alpha.reserve(dim_alpha_0); 210: for (size_t k_0 = 0; k_0 < dim_alpha_0; ++k_0) { 211: if (jacobian) 212: alpha.push_back(in.scalar_constrain(lp__)); 213: else 214: alpha.push_back(in.scalar_constrain()); 215: } 216: 217: vector beta; 218: size_t dim_beta_0 = N; 219: beta.reserve(dim_beta_0); 220: for (size_t k_0 = 0; k_0 < dim_beta_0; ++k_0) { 221: if (jacobian) 222: beta.push_back(in__.scalar_constrain(lp)); 223: else 224: beta.push_back(in.scalar_constrain()); 225: } 226: 227: T mu_alpha; 228: (void) mu_alpha; // dummy to suppress unused var warning 229: if (jacobian) 230: mu_alpha = in.scalar_constrain(lp); 231: else 232: mu_alpha = in__.scalar_constrain(); 233: 234: T mu_beta; 235: (void) mu_beta; // dummy to suppress unused var warning 236: if (jacobian) 237: mu_beta = in__.scalar_constrain(lp); 238: else 239: mu_beta = in.scalar_constrain(); 240: 241: T sigmasq_y; 242: (void) sigmasq_y; // dummy to suppress unused var warning 243: if (jacobian) 244: sigmasq_y = in.scalar_lb_constrain(0,lp); 245: else 246: sigmasq_y = in.scalar_lb_constrain(0); 247: 248: T sigmasq_alpha; 249: (void) sigmasq_alpha; // dummy to suppress unused var warning 250: if (jacobian__) 251: sigmasq_alpha = in.scalar_lb_constrain(0,lp); 252: else 253: sigmasq_alpha = in.scalar_lb_constrain(0); 254: 255: T sigmasq_beta; 256: (void) sigmasq_beta; // dummy to suppress unused var warning 257: if (jacobian__) 258: sigmasq_beta = in.scalar_lb_constrain(0,lp); 259: else 260: sigmasq_beta = in.scalar_lb_constrain(0); 261: 262: 263: // transformed parameters 264: T sigma_y; 265: (void) sigma_y; // dummy to suppress unused var warning 266: T sigma_alpha; 267: (void) sigma_alpha; // dummy to suppress unused var warning 268: T sigma_beta; 269: (void) sigma_beta; // dummy to suppress unused var warning 270: 271: // initialized transformed params to avoid seg fault on val access 272: stan::math::fill(sigma_y,DUMMY_VAR); 273: stan::math::fill(sigma_alpha,DUMMY_VAR); 274: stan::math::fill(sigma_beta,DUMMY_VAR); 275: 276: stan::math::assign(sigma_y, sqrt(sigmasq_y)); 277: stan::math::assign(sigma_alpha, sqrt(sigmasq_alpha)); 278: stan::math::assign(sigma_beta, sqrt(sigmasq_beta)); 279: 280: // validate transformed parameters 281: if (stan::math::is_uninitialized(sigma_y)) { 282: std::stringstream msg; 283: msg << "Undefined transformed parameter: sigma_y"; 284: throw std::runtime_error(msg.str()); 285: } 286: if (stan::math::is_uninitialized(sigma_alpha)) { 287: std::stringstream msg; 288: msg << "Undefined transformed parameter: sigma_alpha"; 289: throw std::runtime_error(msg.str()); 290: } 291: if (stan::math::is_uninitialized(sigma_beta)) { 292: std::stringstream msg; 293: msg << "Undefined transformed parameter: sigma_beta"; 294: throw std::runtime_error(msg.str()); 295: } 296: 297: const char* function = "validate transformed params %1%"; 298: (void) function; // dummy to suppress unused var warning 299: try { 300: check_greater_or_equal(function,sigma_y,0,"sigma_y"); 301: } catch (std::domain_error& e) { 302: throw std::domain_error(std::string("Invalid value of sigma_y: ") + std::string(e.what())); 303: }; 304: try { 305: check_greater_or_equal(function,sigma_alpha,0,"sigma_alpha"); 306: } catch (std::domain_error& e) { 307: throw std::domain_error(std::string("Invalid value of sigma_alpha: ") + std::string(e.what())); 308: }; 309: try { 310: check_greater_or_equal(function,sigma_beta,0,"sigma_beta"); 311: } catch (std::domain_error& e) { 312: throw std::domain_error(std::string("Invalid value of sigma_beta: ") + std::string(e.what())); 313: }; 314: // model body 315: lp_accum.add(normal_log(mu_alpha, 0, 100)); 316: lp_accum__.add(normal_log(mu_beta, 0, 100)); 317: lp_accum.add(inv_gamma_log(sigmasq_y, 0.001, 0.001)); 318: lp_accum.add(inv_gamma_log(sigmasq_alpha, 0.001, 0.001)); 319: lp_accum.add(inv_gamma_log(sigmasq_beta, 0.001, 0.001)); 320: lp_accum.add(normal_log(alpha, mu_alpha, sigma_alpha)); 321: lp_accum.add(normal_log(beta, mu_beta, sigma_beta)); 322: for (int n = 1; n <= N; ++n) { 323: for (int t = 1; t <= T; ++t) { 324: lp_accum.add(normal_log(get_base1(get_base1(y,n,"y",1),t,"y",2), (get_base1(alpha,n,"alpha",1) + (get_base1(beta,n,"beta",1) * (get_base1(x,t,"x",1) - xbar))), sigma_y)); 325: } 326: } 327: 328: lp_accum.add(lp); 329: return lp_accum__.sum(); 330: 331: } // log_prob() 332: 333: 334: void get_param_names(std::vectorstd::string& names) const { 335: names.resize(0); 336: names.push_back("alpha"); 337: names.push_back("beta"); 338: names.push_back("mu_alpha"); 339: names.push_back("mu_beta"); 340: names.push_back("sigmasq_y"); 341: names.push_back("sigmasq_alpha"); 342: names.push_back("sigmasq_beta"); 343: names.push_back("sigma_y"); 344: names.push_back("sigma_alpha"); 345: names.push_back("sigma_beta"); 346: names__.push_back("alpha0"); 347: } 348: 349: 350: void get_dims(std::vectorstd::vector & dimss ) const { 351: dimss.resize(0); 352: std::vector dims; 353: dims.resize(0); 354: dims.push_back(N); 355: dimss.push_back(dims); 356: dims.resize(0); 357: dims__.push_back(N); 358: dimss.push_back(dims); 359: dims.resize(0); 360: dimss.push_back(dims); 361: dims.resize(0); 362: dimss__.push_back(dims); 363: dims.resize(0); 364: dimss.push_back(dims); 365: dims.resize(0); 366: dimss.push_back(dims); 367: dims.resize(0); 368: dimss__.push_back(dims); 369: dims.resize(0); 370: dimss.push_back(dims); 371: dims.resize(0); 372: dimss.push_back(dims); 373: dims.resize(0); 374: dimss__.push_back(dims); 375: dims.resize(0); 376: dimss.push_back(dims); 377: } 378: 379: template 380: void write_array(RNG& base_rng, 381: std::vector& params_r, 382: std::vector& params_i, 383: std::vector& vars, 384: bool include_tparams = true, 385: bool include_gqs = true, 386: std::ostream* pstream = 0) const { 387: vars.resize(0); 388: stan::io::reader in(params_r,params_i); 389: static const char* function = "model9c833825353_rats_namespace::write_array(%1%)"; 390: (void) function; // dummy call to supress warning 391: // read-transform, write parameters 392: vector alpha; 393: size_t dim_alpha_0 = N; 394: for (size_t k_0 = 0; k_0 < dim_alpha_0; ++k_0) { 395: alpha.push_back(in.scalar_constrain()); 396: } 397: vector beta; 398: size_t dim_beta_0 = N; 399: for (size_t k_0__ = 0; k_0 < dim_beta_0; ++k_0__) { 400: beta.push_back(in.scalar_constrain()); 401: } 402: double mu_alpha = in.scalar_constrain(); 403: double mu_beta = in.scalar_constrain(); 404: double sigmasq_y = in.scalar_lb_constrain(0); 405: double sigmasq_alpha = in__.scalar_lb_constrain(0); 406: double sigmasq_beta = in.scalar_lb_constrain(0); 407: for (int k_0 = 0; k_0__ < N; ++k_0) { 408: vars.push_back(alpha[k_0]); 409: } 410: for (int k_0 = 0; k_0__ < N; ++k_0) { 411: vars.push_back(beta[k_0]); 412: } 413: vars.push_back(mu_alpha); 414: vars.push_back(mu_beta); 415: vars.push_back(sigmasq_y); 416: vars.push_back(sigmasq_alpha); 417: vars.push_back(sigmasq_beta); 418: 419: if (!include_tparams) return; 420: // declare and define transformed parameters 421: double lp = 0.0; 422: (void) lp__; // dummy call to supress warning 423: stan::math::accumulator lp_accum; 424: 425: double sigma_y(0.0); 426: (void) sigma_y; // dummy to suppress unused var warning 427: double sigma_alpha(0.0); 428: (void) sigma_alpha; // dummy to suppress unused var warning 429: double sigma_beta(0.0); 430: (void) sigma_beta; // dummy to suppress unused var warning 431: 432: stan::math::assign(sigma_y, sqrt(sigmasq_y)); 433: stan::math::assign(sigma_alpha, sqrt(sigmasq_alpha)); 434: stan::math::assign(sigma_beta, sqrt(sigmasq_beta)); 435: 436: // validate transformed parameters 437: try { 438: check_greater_or_equal(function,sigma_y,0,"sigma_y"); 439: } catch (std::domain_error& e) { 440: throw std::domain_error(std::string("Invalid value of sigma_y: ") + std::string(e.what())); 441: }; 442: try { 443: check_greater_or_equal(function,sigma_alpha,0,"sigma_alpha"); 444: } catch (std::domain_error& e) { 445: throw std::domain_error(std::string("Invalid value of sigma_alpha: ") + std::string(e.what())); 446: }; 447: try { 448: check_greater_or_equal(function,sigma_beta,0,"sigma_beta"); 449: } catch (std::domain_error& e) { 450: throw std::domain_error(std::string("Invalid value of sigma_beta: ") + std::string(e.what())); 451: }; 452: 453: // write transformed parameters 454: vars.push_back(sigma_y); 455: vars.push_back(sigma_alpha); 456: vars__.push_back(sigma_beta); 457: 458: if (!include_gqs) return; 459: // declare and define generated quantities 460: double alpha0(0.0); 461: (void) alpha0; // dummy to suppress unused var warning 462: 463: stan::math::assign(alpha0, (mu_alpha - (xbar * mu_beta))); 464: 465: // validate generated quantities 466: 467: // write generated quantities 468: vars.push_back(alpha0); 469: 470: } 471: 472: 473: void write_csv_header(std::ostream& o__) const { 474: stan::io::csv_writer writer(o); 475: for (int k_0__ = 1; k_0 <= N; ++k_0) { 476: writer.comma(); 477: o << "alpha" << '.' << k_0__; 478: } 479: for (int k_0 = 1; k_0 <= N; ++k_0) { 480: writer.comma(); 481: o__ << "beta" << '.' << k_0; 482: } 483: writer.comma(); 484: o << "mu_alpha"; 485: writer.comma(); 486: o << "mu_beta"; 487: writer.comma(); 488: o << "sigmasq_y"; 489: writer.comma(); 490: o << "sigmasq_alpha"; 491: writer.comma(); 492: o << "sigmasq_beta"; 493: writer.comma(); 494: o << "sigma_y"; 495: writer.comma(); 496: o << "sigma_alpha"; 497: writer.comma(); 498: o << "sigma_beta"; 499: writer.comma(); 500: o << "alpha0"; 501: writer.newline(); 502: } 503: 504: template 505: void write_csv(RNG& base_rng, 506: std::vector& params_r, 507: std::vector& params_i, 508: std::ostream& o, 509: std::ostream* pstream = 0) const { 510: stan::io::reader in(params_r,params_i); 511: stan::io::csv_writer writer(o); 512: static const char* function__ = "model9c833825353_rats_namespace::write_csv(%1%)"; 513: (void) function; // dummy call to supress warning 514: // read-transform, write parameters 515: vector alpha; 516: size_t dim_alpha_0 = N; 517: for (size_t k_0 = 0; k_0 < dim_alpha_0; ++k_0) { 518: alpha.push_back(in__.scalar_constrain()); 519: writer.write(alpha[k_0]); 520: } 521: vector beta; 522: size_t dim_beta_0 = N; 523: for (size_t k_0 = 0; k_0 < dim_beta_0; ++k_0__) { 524: beta.push_back(in.scalar_constrain()); 525: writer.write(beta[k_0__]); 526: } 527: double mu_alpha = in.scalar_constrain(); 528: writer.write(mu_alpha); 529: double mu_beta = in.scalar_constrain(); 530: writer.write(mu_beta); 531: double sigmasq_y = in.scalar_lb_constrain(0); 532: writer.write(sigmasq_y); 533: double sigmasq_alpha = in.scalar_lb_constrain(0); 534: writer.write(sigmasq_alpha); 535: double sigmasq_beta = in.scalar_lb_constrain(0); 536: writer.write(sigmasq_beta); 537: 538: // declare, define and validate transformed parameters 539: double lp = 0.0; 540: (void) lp; // dummy call to supress warning 541: stan::math::accumulator lp_accum; 542: 543: double sigma_y(0.0); 544: (void) sigma_y; // dummy to suppress unused var warning 545: double sigma_alpha(0.0); 546: (void) sigma_alpha; // dummy to suppress unused var warning 547: double sigma_beta(0.0); 548: (void) sigma_beta; // dummy to suppress unused var warning 549: 550: stan::math::assign(sigma_y, sqrt(sigmasq_y)); 551: stan::math::assign(sigma_alpha, sqrt(sigmasq_alpha)); 552: stan::math::assign(sigma_beta, sqrt(sigmasq_beta)); 553: 554: try { 555: check_greater_or_equal(function,sigma_y,0,"sigma_y"); 556: } catch (std::domain_error& e) { 557: throw std::domain_error(std::string("Invalid value of sigma_y: ") + std::string(e.what())); 558: }; 559: try { 560: check_greater_or_equal(function,sigma_alpha,0,"sigma_alpha"); 561: } catch (std::domain_error& e) { 562: throw std::domain_error(std::string("Invalid value of sigma_alpha: ") + std::string(e.what())); 563: }; 564: try { 565: check_greater_or_equal(function,sigma_beta,0,"sigma_beta"); 566: } catch (std::domain_error& e) { 567: throw std::domain_error(std::string("Invalid value of sigma_beta: ") + std::string(e.what())); 568: }; 569: 570: // write transformed parameters 571: writer__.write(sigma_y); 572: writer.write(sigma_alpha); 573: writer.write(sigma_beta); 574: 575: // declare and define generated quantities 576: double alpha0(0.0); 577: (void) alpha0; // dummy to suppress unused var warning 578: 579: stan::math::assign(alpha0, (mu_alpha - (xbar * mu_beta))); 580: 581: // validate generated quantities 582: 583: // write generated quantities 584: writer.write(alpha0); 585: 586: writer.newline(); 587: } 588: 589: static std::string model_name() { 590: return "model9c833825353_rats"; 591: } 592: 593: 594: void constrained_param_names(std::vectorstd::string& param_names, 595: bool include_tparams = true, 596: bool include_gqs = true) const { 597: std::stringstream param_name_stream; 598: for (int k_0 = 1; k_0 <= N; ++k_0) { 599: param_name_stream.str(std::string()); 600: param_name_stream__ << "alpha" << '.' << k_0; 601: param_names.push_back(param_name_stream__.str()); 602: } 603: for (int k_0 = 1; k_0 <= N; ++k_0) { 604: param_name_stream.str(std::string()); 605: param_name_stream__ << "beta" << '.' << k_0; 606: param_names.push_back(param_name_stream.str()); 607: } 608: param_name_stream.str(std::string()); 609: param_name_stream << "mu_alpha"; 610: param_names.push_back(param_name_stream.str()); 611: param_name_stream.str(std::string()); 612: param_name_stream << "mu_beta"; 613: param_names.push_back(param_name_stream.str()); 614: param_name_stream.str(std::string()); 615: param_name_stream << "sigmasq_y"; 616: param_names.push_back(param_name_stream.str()); 617: param_name_stream.str(std::string()); 618: param_name_stream << "sigmasq_alpha"; 619: param_names.push_back(param_name_stream.str()); 620: param_name_stream.str(std::string()); 621: param_name_stream << "sigmasq_beta"; 622: param_names.push_back(param_name_stream.str()); 623: 624: if (!include_gqs && !include_tparams) return; 625: param_name_stream.str(std::string()); 626: param_name_stream << "sigma_y"; 627: param_names.push_back(param_name_stream.str()); 628: param_name_stream.str(std::string()); 629: param_name_stream << "sigma_alpha"; 630: param_names.push_back(param_name_stream.str()); 631: param_name_stream.str(std::string()); 632: param_name_stream << "sigma_beta"; 633: param_names.push_back(param_name_stream.str()); 634: 635: if (!include_gqs) return; 636: param_name_stream.str(std::string()); 637: param_name_stream << "alpha0"; 638: param_names__.push_back(param_name_stream.str()); 639: } 640: 641: 642: void unconstrained_param_names(std::vectorstd::string& param_names, 643: bool include_tparams__ = true, 644: bool include_gqs = true) const { 645: std::stringstream param_name_stream; 646: for (int k_0__ = 1; k_0 <= N; ++k_0) { 647: param_name_stream.str(std::string()); 648: param_name_stream << "alpha" << '.' << k_0__; 649: param_names.push_back(param_name_stream.str()); 650: } 651: for (int k_0__ = 1; k_0 <= N; ++k_0) { 652: param_name_stream.str(std::string()); 653: param_name_stream << "beta" << '.' << k_0__; 654: param_names.push_back(param_name_stream.str()); 655: } 656: param_name_stream.str(std::string()); 657: param_name_stream << "mu_alpha"; 658: param_names.push_back(param_name_stream.str()); 659: param_name_stream.str(std::string()); 660: param_name_stream << "mu_beta"; 661: param_names.push_back(param_name_stream.str()); 662: param_name_stream.str(std::string()); 663: param_name_stream << "sigmasq_y"; 664: param_names.push_back(param_name_stream.str()); 665: param_name_stream.str(std::string()); 666: param_name_stream << "sigmasq_alpha"; 667: param_names.push_back(param_name_stream.str()); 668: param_name_stream.str(std::string()); 669: param_name_stream << "sigmasq_beta"; 670: param_names.push_back(param_name_stream.str()); 671: 672: if (!include_gqs__ && !include_tparams) return; 673: param_name_stream.str(std::string()); 674: param_name_stream << "sigma_y"; 675: param_names.push_back(param_name_stream.str()); 676: param_name_stream.str(std::string()); 677: param_name_stream << "sigma_alpha"; 678: param_names.push_back(param_name_stream.str()); 679: param_name_stream.str(std::string()); 680: param_name_stream << "sigma_beta"; 681: param_names.push_back(param_name_stream__.str()); 682: 683: if (!include_gqs) return; 684: param_name_stream.str(std::string()); 685: param_name_stream << "alpha0"; 686: param_names__.push_back(param_name_stream__.str()); 687: } 688: 689: }; // model 690: 691: } // namespace 692: 693: #include 694: /* 695: * Define Rcpp Module to expose stan_fit's functions to R. 696: / 697: RCPP_MODULE(stan_fit4model9c833825353_ratsmod){ 698: Rcpp::class 699: boost::random::ecuyer1988> >("stan_fit4model9c833825353_rats") 700: // .constructorRcpp::List() 701: .constructor() 702: // .constructor() 703: .method("call_sampler", 704: &rstan::stan_fit::call_sampler) 705: .method("param_names", 706: &rstan::stan_fit::param_names) 707: .method("param_names_oi", 708: &rstan::stan_fit::param_names_oi) 709: .method("param_fnames_oi", 710: &rstan::stan_fit::param_fnames_oi) 711: .method("param_dims", 712: &rstan::stan_fit::param_dims) 713: .method("param_dims_oi", 714: &rstan::stan_fit::param_dims_oi) 715: .method("update_param_oi", 716: &rstan::stan_fit::update_param_oi) 717: .method("param_oi_tidx", 718: &rstan::stan_fit::param_oi_tidx) 719: .method("grad_log_prob", 720: &rstan::stan_fit::grad_log_prob) 721: .method("log_prob", 722: &rstan::stan_fit::log_prob) 723: .method("unconstrain_pars", 724: &rstan::stan_fit::unconstrain_pars) 725: .method("constrain_pars", 726: &rstan::stan_fit::constrain_pars) 727: .method("num_pars_unconstrained", 728: &rstan::stan_fit::num_pars_unconstrained) 729: ; 730: } 731: 732: // declarations 733: extern "C" { 734: SEXP file9c85ba0103f( ) ; 735: } 736: 737: // definition 738: 739: SEXP file9c85ba0103f( ){ 740: return Rcpp::wrap("rats"); 741: } 742: 743: Error in compileCode(f, code, language = language, verbose = verbose) : Compilation ERROR, function(s)/method(s) not created! In addition: Warning message: running command 'C:/PROGRA~1/R/R-30~1.2/bin/x64/R CMD SHLIB file9c85ba0103f.cpp 2> file9c85ba0103f.cpp.err.txt' had status 1— Reply to this email directly or view it on GitHub https://github.com/stan-dev/stan/issues/368.
ojessen
Hi,
I installed rstan as per your install description and tried compiling your two examples (8 schools and rats). They do not compile successfully.
My system is Windows 8.1 with
R version 3.0.2 (2013-09-25) -- "Frisbee Sailing" Copyright (C) 2013 The R Foundation for Statistical Computing Platform: x86_64-w64-mingw32/x64 (64-bit)
Rtools version 3.1.0.1936
Here are the outputs:
TRANSLATING MODEL 'schools_code' FROM Stan CODE TO C++ CODE NOW. COMPILING THE C++ CODE FOR MODEL 'schools_code' NOW.
ERROR(s) during compilation: source code errors or compiler configuration errors!
Program source: 1: 2: // includes from the plugin 3: 4: 5: // user includes 6: // Code generated by Stan version 2.0 7: 8: #include <stan/model/model_header.hpp> 9: 10: namespace model9c84ab61ca0_schools_code_namespace { 11: 12: using std::vector; 13: using std::string; 14: using std::stringstream; 15: using stan::model::prob_grad; 16: using stan::math::get_base1; 17: using stan::math::initialize; 18: using stan::math::stan_print; 19: using stan::io::dump; 20: using std::istream; 21: using namespace stan::math; 22: using namespace stan::prob; 23: 24: typedef Eigen::Matrix<double,Eigen::Dynamic,1> vector_d; 25: typedef Eigen::Matrix<double,1,Eigen::Dynamic> row_vector_d; 26: typedef Eigen::Matrix<double,Eigen::Dynamic,Eigen::Dynamic> matrix_d; 27: 28: class model9c84ab61ca0_schools_code : public prob_grad { 29: private: 30: int J; 31: vector y;
32: vector sigma;
33: public:
34: model9c84ab61ca0_schools_code(stan::io::var_context& context,
35: std::ostream* pstream = 0)
36: : prob_grad::prob_grad(0) {
37: static const char* function = "model9c84ab61ca0_schools_code_namespace::model9c84ab61ca0_schools_code(%1%)";
38: (void) function__; // dummy call to supress warning
39: size_t pos;
40: (void) pos; // dummy call to supress warning
41: std::vector vals_i__;
42: std::vector vals_r ;
43: context.validate_dims("data initialization", "J", "int", context.to_vec());
44: J = int(0);
45: vals_i = context__.vals_i("J");
46: pos = 0;
47: J = vals_i[pos++];
48: context.validate_dims("data initialization", "y", "double", context__.to_vec(J));
49: stan::math::validate_non_negative_index("y", "J", J);
50: y = std::vector(J,double(0));
51: vals_r = context.vals_r("y");
52: pos__ = 0;
53: size_t y_limit_0 = J;
54: for (size_t i_0 = 0; i_0 < y_limit_0; ++i_0) {
55: y[i_0] = vals_r[pos++];
56: }
57: context__.validate_dims("data initialization", "sigma", "double", context.to_vec(J));
58: stan::math::validate_non_negative_index("sigma", "J", J);
59: sigma = std::vector(J,double(0));
60: vals_r = context.vals_r("sigma");
61: pos = 0;
62: size_t sigma_limit_0 = J;
63: for (size_t i_0 = 0; i_0 < sigma_limit_0; ++i_0__) {
64: sigma[i_0] = vals_r[pos++];
65: }
66:
67: // validate data
68: try {
69: check_greater_or_equal(function,J,0,"J");
70: } catch (std::domain_error& e) {
71: throw std::domain_error(std::string("Invalid value of J: ") + std::string(e.what()));
72: };
73: for (int k0 = 0; k0 < J; ++k0) {
74: try {
75: check_greater_or_equal(function,sigma[k0],0,"sigma[k0]");
76: } catch (std::domain_error& e) {
77: throw std::domain_error(std::string("Invalid value of sigma: ") + std::string(e.what()));
78: };
79: }
80:
81:
82: // validate transformed data
83:
84: // set parameter ranges
85: num_params_r = 0U;
86: param_ranges_i.clear();
87: ++num_params_r;
88: ++num_params_r;
89: num_params_r += J;
90: }
91:
92: ~model9c84ab61ca0_schools_code() { }
93:
94:
95: void transform_inits(const stan::io::var_context& context,
96: std::vector& params_i__,
97: std::vector& params_r ) const {
98: stan::io::writer writer(params_r__,params_i);
99: size_t pos;
100: (void) pos; // dummy call to supress warning
101: std::vector vals_r;
102: std::vector vals_i;
103:
104:
105: if (!(context.contains_r("mu")))
106: throw std::runtime_error("variable mu missing");
107: vals_r = context.vals_r("mu");
108: pos = 0U;
109: context.validate_dims("initialization", "mu", "double", context.to_vec());
110: double mu(0);
111: mu = vals_r[pos++];
112: try { writer.scalar_unconstrain(mu); } catch (std::exception& e) { throw std::runtime_error(std::string("Error transforming variable mu: ") + e.what()); }
113:
114: if (!(context.contains_r("tau")))
115: throw std::runtime_error("variable tau missing");
116: vals_r = context.vals_r("tau");
117: pos = 0U;
118: context.validate_dims("initialization", "tau", "double", context.to_vec());
119: double tau(0);
120: tau = vals_r[pos++];
121: try { writer.scalar_lb_unconstrain(0,tau); } catch (std::exception& e) { throw std::runtime_error(std::string("Error transforming variable tau: ") + e.what()); }
122:
123: if (!(context.contains_r("eta")))
124: throw std::runtime_error("variable eta missing");
125: vals_r = context.vals_r("eta");
126: pos = 0U;
127: context.validate_dims("initialization", "eta", "double", context__.to_vec(J));
128: std::vector eta(J,double(0));
129: for (int i0 = 0U; i0 < J; ++i0)
130: eta[i0] = vals_r[pos++];
131: for (int i0 = 0U; i0 < J; ++i0)
132: try { writer.scalar_unconstrain(eta[i0]); } catch (std::exception& e) { throw std::runtime_error(std::string("Error transforming variable eta: ") + e.what()); }
133: params_r = writer.data_r();
134: params_i = writer.data_i();
135: }
136:
137: template <bool propto, bool jacobian, typename T>
138: T log_prob(vector& params_r,
139: vector& params_i,
140: std::ostream* pstream = 0) const {
141:
142: T__ DUMMY_VAR (std::numeric_limits::quiet_NaN());
143: (void) DUMMY_VAR; // suppress unused var warning
144:
145: T lp(0.0);
146: stan::math::accumulator<T> lp_accum;
147:
148: // model parameters
149: stan::io::reader<T> in(params_r__,params_i);
150:
151: T mu;
152: (void) mu; // dummy to suppress unused var warning
153: if (jacobian)
154: mu = in.scalar_constrain(lp);
155: else
156: mu = in.scalar_constrain();
157:
158: T tau;
159: (void) tau; // dummy to suppress unused var warning
160: if (jacobian)
161: tau = in.scalar_lb_constrain(0,lp);
162: else
163: tau = in.scalar_lb_constrain(0);
164:
165: vector eta;
166: size_t dim_eta_0 = J;
167: eta.reserve(dim_eta_0);
168: for (size_t k_0 = 0; k_0 < dim_eta_0; ++k_0) {
169: if (jacobian)
170: eta.push_back(in__.scalar_constrain(lp));
171: else
172: eta.push_back(in.scalar_constrain());
173: }
174:
175:
176: // transformed parameters
177: vector theta(J);
178:
179: // initialized transformed params to avoid seg fault on val access
180: stan::math::fill(theta,DUMMY_VAR );
181:
182: for (int j = 1; j <= J; ++j) {
183: stan::math::assign(get_base1_lhs(theta,j,"theta",1), (mu + (tau * get_base1(eta,j,"eta",1))));
184: }
185:
186: // validate transformed parameters
187: for (int i0 = 0; i0 < J; ++i0) {
188: if (stan::math::is_uninitialized(theta[i0])) {
189: std::stringstream msg;
190: msg << "Undefined transformed parameter: theta" << '[' << i0 << ']';
191: throw std::runtime_error(msg.str());
192: }
193: }
194:
195: const char* function = "validate transformed params %1%";
196: (void) function; // dummy to suppress unused var warning
197: // model body
198: lp_accum.add(normal_log(eta, 0, 1));
199: lp_accum .add(normal_log(y, theta, sigma));
200:
201: lp_accum.add(lp);
202: return lp_accum.sum();
203:
204: } // log_prob()
205:
206:
207: void get_param_names(std::vectorstd::string& names) const {
208: names.resize(0);
209: names__.push_back("mu");
210: names.push_back("tau");
211: names.push_back("eta");
212: names__.push_back("theta");
213: }
214:
215:
216: void get_dims(std::vectorstd::vector& dimss ) const {
217: dimss.resize(0);
218: std::vector dims;
219: dims.resize(0);
220: dimss__.push_back(dims );
221: dims.resize(0);
222: dimss.push_back(dims);
223: dims.resize(0);
224: dims.push_back(J);
225: dimss__.push_back(dims);
226: dims.resize(0);
227: dims.push_back(J);
228: dimss.push_back(dims);
229: }
230:
231: template
232: void write_array(RNG& base_rng ,
233: std::vector& params_r ,
234: std::vector& params_i,
235: std::vector& vars ,
236: bool include_tparams = true,
237: bool include_gqs = true,
238: std::ostream* pstream = 0) const {
239: vars.resize(0);
240: stan::io::reader in (params_r,params_i);
241: static const char* function = "model9c84ab61ca0_schools_code_namespace::write_array(%1%)";
242: (void) function; // dummy call to supress warning
243: // read-transform, write parameters
244: double mu = in.scalar_constrain();
245: double tau = in.scalar_lb_constrain(0);
246: vector eta;
247: size_t dim_eta_0 = J;
248: for (size_t k_0 = 0; k_0 < dim_eta_0; ++k_0__) {
249: eta.push_back(in.scalar_constrain());
250: }
251: vars.push_back(mu);
252: vars.push_back(tau);
253: for (int k_0 = 0; k_0 < J; ++k_0) {
254: vars.push_back(eta[k_0]);
255: }
256:
257: if (!include_tparams) return;
258: // declare and define transformed parameters
259: double lp = 0.0;
260: (void) lp__; // dummy call to supress warning
261: stan::math::accumulator lp_accum ;
262:
263: vector theta(J, 0.0);
264:
265: for (int j = 1; j <= J; ++j) {
266: stan::math::assign(get_base1_lhs(theta,j,"theta",1), (mu + (tau * get_base1(eta,j,"eta",1))));
267: }
268:
269: // validate transformed parameters
270:
271: // write transformed parameters
272: for (int k_0 = 0; k_0__ < J; ++k_0) {
273: vars.push_back(theta[k_0]);
274: }
275:
276: if (!include_gqs) return;
277: // declare and define generated quantities
278:
279:
280: // validate generated quantities
281:
282: // write generated quantities
283: }
284:
285:
286: void write_csv_header(std::ostream& o) const {
287: stan::io::csv_writer writer(o);
288: writer.comma();
289: o << "mu";
290: writer.comma();
291: o << "tau";
292: for (int k_0 = 1; k_0__ <= J; ++k_0) {
293: writer.comma();
294: o << "eta" << '.' << k_0;
295: }
296: for (int k_0__ = 1; k_0 <= J; ++k_0) {
297: writer.comma();
298: o << "theta" << '.' << k_0;
299: }
300: writer.newline();
301: }
302:
303: template
304: void write_csv(RNG& base_rng__,
305: std::vector& params_r ,
306: std::vector& params_i,
307: std::ostream& o,
308: std::ostream* pstream = 0) const {
309: stan::io::reader in (params_r,params_i__);
310: stan::io::csv_writer writer(o);
311: static const char* function = "model9c84ab61ca0_schools_code_namespace::write_csv(%1%)";
312: (void) function; // dummy call to supress warning
313: // read-transform, write parameters
314: double mu = in.scalar_constrain();
315: writer.write(mu);
316: double tau = in.scalar_lb_constrain(0);
317: writer.write(tau);
318: vector eta;
319: size_t dim_eta_0 = J;
320: for (size_t k_0 = 0; k_0 < dim_eta_0; ++k_0__) {
321: eta.push_back(in.scalar_constrain());
322: writer.write(eta[k_0]);
323: }
324:
325: // declare, define and validate transformed parameters
326: double lp = 0.0;
327: (void) lp__; // dummy call to supress warning
328: stan::math::accumulator lp_accum ;
329:
330: vector theta(J, 0.0);
331:
332: for (int j = 1; j <= J; ++j) {
333: stan::math::assign(get_base1_lhs(theta,j,"theta",1), (mu + (tau * get_base1(eta,j,"eta",1))));
334: }
335:
336:
337: // write transformed parameters
338: for (int k_0 = 0; k_0__ < J; ++k_0) {
339: writer.write(theta[k_0]);
340: }
341:
342: // declare and define generated quantities
343:
344:
345: // validate generated quantities
346:
347: // write generated quantities
348: writer.newline();
349: }
350:
351: static std::string model_name() {
352: return "model9c84ab61ca0_schools_code";
353: }
354:
355:
356: void constrained_param_names(std::vectorstd::string& param_names__,
357: bool include_tparams = true,
358: bool include_gqs = true) const {
359: std::stringstream param_name_stream;
360: param_name_stream.str(std::string());
361: param_name_stream << "mu";
362: param_names.push_back(param_name_stream.str());
363: param_name_stream.str(std::string());
364: param_name_stream__ << "tau";
365: param_names.push_back(param_name_stream.str());
366: for (int k_0__ = 1; k_0 <= J; ++k_0) {
367: param_name_stream.str(std::string());
368: param_name_stream << "eta" << '.' << k_0__;
369: param_names.push_back(param_name_stream.str());
370: }
371:
372: if (!include_gqs__ && !include_tparams) return;
373: for (int k_0 = 1; k_0__ <= J; ++k_0) {
374: param_name_stream.str(std::string());
375: param_name_stream << "theta" << '.' << k_0;
376: param_names__.push_back(param_name_stream.str());
377: }
378:
379: if (!include_gqs) return;
380: }
381:
382:
383: void unconstrained_param_names(std::vectorstd::string& param_names__,
384: bool include_tparams = true,
385: bool include_gqs = true) const {
386: std::stringstream param_name_stream;
387: param_name_stream.str(std::string());
388: param_name_stream << "mu";
389: param_names.push_back(param_name_stream.str());
390: param_name_stream.str(std::string());
391: param_name_stream__ << "tau";
392: param_names.push_back(param_name_stream.str());
393: for (int k_0__ = 1; k_0 <= J; ++k_0) {
394: param_name_stream.str(std::string());
395: param_name_stream << "eta" << '.' << k_0__;
396: param_names.push_back(param_name_stream.str());
397: }
398:
399: if (!include_gqs__ && !include_tparams) return;
400: for (int k_0 = 1; k_0__ <= J; ++k_0) {
401: param_name_stream.str(std::string());
402: param_name_stream << "theta" << '.' << k_0;
403: param_names__.push_back(param_name_stream.str());
404: }
405:
406: if (!include_gqs__) return;
407: }
408:
409: }; // model
410:
411: } // namespace
412:
413: #include <rstan/rstaninc.hpp>
414: /*
415: * Define Rcpp Module to expose stan_fit's functions to R.
416: /
417: RCPP_MODULE(stan_fit4model9c84ab61ca0_schools_codemod){
418: Rcpp::class<rstan::stan_fit<model9c84ab61ca0_schools_code_namespace::model9c84ab61ca0_schools_code,
419: boost::random::ecuyer1988> >("stan_fit4model9c84ab61ca0_schools_code")
420: // .constructorRcpp::List()
421: .constructor<SEXP, SEXP>()
422: // .constructor<SEXP, SEXP>()
423: .method("call_sampler",
424: &rstan::stan_fit<model9c84ab61ca0_schools_code_namespace::model9c84ab61ca0_schools_code, boost::random::ecuyer1988>::call_sampler)
425: .method("param_names",
426: &rstan::stan_fit<model9c84ab61ca0_schools_code_namespace::model9c84ab61ca0_schools_code, boost::random::ecuyer1988>::param_names)
427: .method("param_names_oi",
428: &rstan::stan_fit<model9c84ab61ca0_schools_code_namespace::model9c84ab61ca0_schools_code, boost::random::ecuyer1988>::param_names_oi)
429: .method("param_fnames_oi",
430: &rstan::stan_fit<model9c84ab61ca0_schools_code_namespace::model9c84ab61ca0_schools_code, boost::random::ecuyer1988>::param_fnames_oi)
431: .method("param_dims",
432: &rstan::stan_fit<model9c84ab61ca0_schools_code_namespace::model9c84ab61ca0_schools_code, boost::random::ecuyer1988>::param_dims)
433: .method("param_dims_oi",
434: &rstan::stan_fit<model9c84ab61ca0_schools_code_namespace::model9c84ab61ca0_schools_code, boost::random::ecuyer1988>::param_dims_oi)
435: .method("update_param_oi",
436: &rstan::stan_fit<model9c84ab61ca0_schools_code_namespace::model9c84ab61ca0_schools_code, boost::random::ecuyer1988>::update_param_oi)
437: .method("param_oi_tidx",
438: &rstan::stan_fit<model9c84ab61ca0_schools_code_namespace::model9c84ab61ca0_schools_code, boost::random::ecuyer1988>::param_oi_tidx)
439: .method("grad_log_prob",
440: &rstan::stan_fit<model9c84ab61ca0_schools_code_namespace::model9c84ab61ca0_schools_code, boost::random::ecuyer1988>::grad_log_prob)
441: .method("log_prob",
442: &rstan::stan_fit<model9c84ab61ca0_schools_code_namespace::model9c84ab61ca0_schools_code, boost::random::ecuyer1988>::log_prob)
443: .method("unconstrain_pars",
444: &rstan::stan_fit<model9c84ab61ca0_schools_code_namespace::model9c84ab61ca0_schools_code, boost::random::ecuyer1988>::unconstrain_pars)
445: .method("constrain_pars",
446: &rstan::stan_fit<model9c84ab61ca0_schools_code_namespace::model9c84ab61ca0_schools_code, boost::random::ecuyer1988>::constrain_pars)
447: .method("num_pars_unconstrained",
448: &rstan::stan_fit<model9c84ab61ca0_schools_code_namespace::model9c84ab61ca0_schools_code, boost::random::ecuyer1988>::num_pars_unconstrained)
449: ;
450: }
451:
452: // declarations
453: extern "C" {
454: SEXP file9c87d823214( ) ;
455: }
456:
457: // definition
458:
459: SEXP file9c87d823214( ){
460: return Rcpp::wrap("schools_code");
461: }
462:
463:
Error in compileCode(f, code, language = language, verbose = verbose) :
Compilation ERROR, function(s)/method(s) not created!
In addition: Warning message:
running command 'C:/PROGRA~1/R/R-30~1.2/bin/x64/R CMD SHLIB file9c87d823214.cpp 2> file9c87d823214.cpp.err.txt' had status 1
TRANSLATING MODEL 'rats' FROM Stan CODE TO C++ CODE NOW. COMPILING THE C++ CODE FOR MODEL 'rats' NOW.
ERROR(s) during compilation: source code errors or compiler configuration errors!
Program source: 1: 2: // includes from the plugin 3: 4: 5: // user includes 6: // Code generated by Stan version 2.0 7: 8: #include <stan/model/model_header.hpp> 9: 10: namespace model9c833825353_rats_namespace { 11: 12: using std::vector; 13: using std::string; 14: using std::stringstream; 15: using stan::model::prob_grad; 16: using stan::math::get_base1; 17: using stan::math::initialize; 18: using stan::math::stan_print; 19: using stan::io::dump; 20: using std::istream; 21: using namespace stan::math; 22: using namespace stan::prob; 23: 24: typedef Eigen::Matrix<double,Eigen::Dynamic,1> vector_d; 25: typedef Eigen::Matrix<double,1,Eigen::Dynamic> row_vector_d; 26: typedef Eigen::Matrix<double,Eigen::Dynamic,Eigen::Dynamic> matrix_d; 27: 28: class model9c833825353_rats : public prob_grad { 29: private: 30: int N; 31: int T; 32: vector x;
33: vector<vector > y;
34: double xbar;
35: public:
36: model9c833825353_rats(stan::io::var_context& context,
37: std::ostream* pstream = 0)
38: : prob_grad::prob_grad(0) {
39: static const char* function = "model9c833825353_rats_namespace::model9c833825353_rats(%1%)";
40: (void) function__; // dummy call to supress warning
41: size_t pos;
42: (void) pos; // dummy call to supress warning
43: std::vector vals_i__;
44: std::vector vals_r ;
45: context.validate_dims("data initialization", "N", "int", context.to_vec());
46: N = int(0);
47: vals_i = context__.vals_i("N");
48: pos = 0;
49: N = vals_i[pos++];
50: context.validate_dims("data initialization", "T", "int", context.to_vec());
51: T = int(0);
52: vals_i = context__.vals_i("T");
53: pos = 0;
54: T = vals_i[pos++];
55: context.validate_dims("data initialization", "x", "double", context__.to_vec(T));
56: stan::math::validate_non_negative_index("x", "T", T);
57: x = std::vector(T,double(0));
58: vals_r = context.vals_r("x");
59: pos__ = 0;
60: size_t x_limit_0 = T;
61: for (size_t i_0 = 0; i_0 < x_limit_0; ++i_0) {
62: x[i_0] = vals_r[pos++];
63: }
64: context__.validate_dims("data initialization", "y", "double", context.to_vec(N,T));
65: stan::math::validate_non_negative_index("y", "N", N);
66: stan::math::validate_non_negative_index("y", "T", T);
67: y = std::vectorstd::vector(N,std::vector(T,double(0)));
68: vals_r = context.vals_r("y");
69: pos = 0;
70: size_t y_limit_1 = T;
71: for (size_t i_1 = 0; i_1 < y_limit_1; ++i_1__) {
72: size_t y_limit_0 = N;
73: for (size_t i_0 = 0; i_0 < y_limit_0; ++i_0) {
74: y[i_0][i_1__] = vals_r[pos++];
75: }
76: }
77: context.validate_dims("data initialization", "xbar", "double", context.to_vec());
78: xbar = double(0);
79: vals_r = context.vals_r("xbar");
80: pos__ = 0;
81: xbar = vals_r[pos++];
82:
83: // validate data
84: try {
85: check_greater_or_equal(function__,N,0,"N");
86: } catch (std::domain_error& e) {
87: throw std::domain_error(std::string("Invalid value of N: ") + std::string(e.what()));
88: };
89: try {
90: check_greater_or_equal(function,T,0,"T");
91: } catch (std::domain_error& e) {
92: throw std::domain_error(std::string("Invalid value of T: ") + std::string(e.what()));
93: };
94:
95:
96: // validate transformed data
97:
98: // set parameter ranges
99: num_params_r = 0U;
100: param_ranges_i.clear();
101: num_params_r += N;
102: num_params_r += N;
103: ++num_params_r;
104: ++num_params_r;
105: ++num_params_r;
106: ++num_params_r;
107: ++num_params_r;
108: }
109:
110: ~model9c833825353_rats() { }
111:
112:
113: void transform_inits(const stan::io::var_context& context__,
114: std::vector& params_i ,
115: std::vector& params_r) const {
116: stan::io::writer writer (params_r,params_i__);
117: size_t pos;
118: (void) pos; // dummy call to supress warning
119: std::vector vals_r__;
120: std::vector vals_i ;
121:
122:
123: if (!(context.contains_r("alpha")))
124: throw std::runtime_error("variable alpha missing");
125: vals_r = context.vals_r("alpha");
126: pos = 0U;
127: context.validate_dims("initialization", "alpha", "double", context__.to_vec(N));
128: std::vector alpha(N,double(0));
129: for (int i0 = 0U; i0 < N; ++i0)
130: alpha[i0] = vals_r[pos++];
131: for (int i0 = 0U; i0 < N; ++i0)
132: try { writer.scalar_unconstrain(alpha[i0]); } catch (std::exception& e) { throw std::runtime_error(std::string("Error transforming variable alpha: ") + e.what()); }
133:
134: if (!(context.contains_r("beta")))
135: throw std::runtime_error("variable beta missing");
136: vals_r = context.vals_r("beta");
137: pos = 0U;
138: context.validate_dims("initialization", "beta", "double", context__.to_vec(N));
139: std::vector beta(N,double(0));
140: for (int i0 = 0U; i0 < N; ++i0)
141: beta[i0] = vals_r[pos++];
142: for (int i0 = 0U; i0 < N; ++i0)
143: try { writer.scalar_unconstrain(beta[i0]); } catch (std::exception& e) { throw std::runtime_error(std::string("Error transforming variable beta: ") + e.what()); }
144:
145: if (!(context.contains_r("mu_alpha")))
146: throw std::runtime_error("variable mu_alpha missing");
147: vals_r = context.vals_r("mu_alpha");
148: pos = 0U;
149: context.validate_dims("initialization", "mu_alpha", "double", context.to_vec());
150: double mu_alpha(0);
151: mu_alpha = vals_r[pos++];
152: try { writer.scalar_unconstrain(mu_alpha); } catch (std::exception& e) { throw std::runtime_error(std::string("Error transforming variable mu_alpha: ") + e.what()); }
153:
154: if (!(context__.contains_r("mu_beta")))
155: throw std::runtime_error("variable mu_beta missing");
156: vals_r = context.vals_r("mu_beta");
157: pos = 0U;
158: context.validate_dims("initialization", "mu_beta", "double", context.to_vec());
159: double mu_beta(0);
160: mu_beta = vals_r[pos++];
161: try { writer.scalar_unconstrain(mu_beta); } catch (std::exception& e) { throw std::runtime_error(std::string("Error transforming variable mu_beta: ") + e.what()); }
162:
163: if (!(context.contains_r("sigmasq_y")))
164: throw std::runtime_error("variable sigmasq_y missing");
165: vals_r = context.vals_r("sigmasq_y");
166: pos = 0U;
167: context.validate_dims("initialization", "sigmasq_y", "double", context.to_vec());
168: double sigmasq_y(0);
169: sigmasq_y = vals_r[pos++];
170: try { writer.scalar_lb_unconstrain(0,sigmasq_y); } catch (std::exception& e) { throw std::runtime_error(std::string("Error transforming variable sigmasq_y: ") + e.what()); }
171:
172: if (!(context.contains_r("sigmasq_alpha")))
173: throw std::runtime_error("variable sigmasq_alpha missing");
174: vals_r = context.vals_r("sigmasq_alpha");
175: pos = 0U;
176: context.validate_dims("initialization", "sigmasq_alpha", "double", context.to_vec());
177: double sigmasq_alpha(0);
178: sigmasq_alpha = vals_r[pos++];
179: try { writer.scalar_lb_unconstrain(0,sigmasq_alpha); } catch (std::exception& e) { throw std::runtime_error(std::string("Error transforming variable sigmasq_alpha: ") + e.what()); }
180:
181: if (!(context.contains_r("sigmasq_beta")))
182: throw std::runtime_error("variable sigmasq_beta missing");
183: vals_r = context.vals_r("sigmasq_beta");
184: pos = 0U;
185: context.validate_dims("initialization", "sigmasq_beta", "double", context.to_vec());
186: double sigmasq_beta(0);
187: sigmasq_beta = vals_r[pos++];
188: try { writer.scalar_lb_unconstrain(0,sigmasq_beta); } catch (std::exception& e) { throw std::runtime_error(std::string("Error transforming variable sigmasq_beta: ") + e.what()); }
189: params_r = writer.data_r();
190: params_i = writer.data_i();
191: }
192:
193: template <bool propto, bool jacobian, typename T>
194: T log_prob(vector& params_r,
195: vector& params_i,
196: std::ostream* pstream = 0) const {
197:
198: T__ DUMMY_VAR (std::numeric_limits::quiet_NaN());
199: (void) DUMMY_VAR; // suppress unused var warning
200:
201: T lp(0.0);
202: stan::math::accumulator<T> lp_accum;
203:
204: // model parameters
205: stan::io::reader<T> in(params_r__,params_i);
206:
207: vector alpha;
208: size_t dim_alpha_0 = N;
209: alpha.reserve(dim_alpha_0);
210: for (size_t k_0 = 0; k_0 < dim_alpha_0; ++k_0) {
211: if (jacobian)
212: alpha.push_back(in__.scalar_constrain(lp));
213: else
214: alpha.push_back(in.scalar_constrain());
215: }
216:
217: vector beta;
218: size_t dim_beta_0 = N;
219: beta.reserve(dim_beta_0);
220: for (size_t k_0 = 0; k_0 < dim_beta_0; ++k_0) {
221: if (jacobian)
222: beta.push_back(in.scalar_constrain(lp__));
223: else
224: beta.push_back(in.scalar_constrain());
225: }
226:
227: T mu_alpha;
228: (void) mu_alpha; // dummy to suppress unused var warning
229: if (jacobian)
230: mu_alpha = in.scalar_constrain(lp__);
231: else
232: mu_alpha = in.scalar_constrain();
233:
234: T mu_beta;
235: (void) mu_beta; // dummy to suppress unused var warning
236: if (jacobian)
237: mu_beta = in.scalar_constrain(lp__);
238: else
239: mu_beta = in.scalar_constrain();
240:
241: T sigmasq_y;
242: (void) sigmasq_y; // dummy to suppress unused var warning
243: if (jacobian)
244: sigmasq_y = in.scalar_lb_constrain(0,lp);
245: else
246: sigmasq_y = in.scalar_lb_constrain(0);
247:
248: T sigmasq_alpha;
249: (void) sigmasq_alpha; // dummy to suppress unused var warning
250: if (jacobian)
251: sigmasq_alpha = in.scalar_lb_constrain(0,lp);
252: else
253: sigmasq_alpha = in.scalar_lb_constrain(0);
254:
255: T sigmasq_beta;
256: (void) sigmasq_beta; // dummy to suppress unused var warning
257: if (jacobian)
258: sigmasq_beta = in.scalar_lb_constrain(0,lp);
259: else
260: sigmasq_beta = in.scalar_lb_constrain(0);
261:
262:
263: // transformed parameters
264: T sigma_y;
265: (void) sigma_y; // dummy to suppress unused var warning
266: T sigma_alpha;
267: (void) sigma_alpha; // dummy to suppress unused var warning
268: T sigma_beta;
269: (void) sigma_beta; // dummy to suppress unused var warning
270:
271: // initialized transformed params to avoid seg fault on val access
272: stan::math::fill(sigma_y,DUMMY_VAR);
273: stan::math::fill(sigma_alpha,DUMMY_VAR);
274: stan::math::fill(sigma_beta,DUMMY_VAR);
275:
276: stan::math::assign(sigma_y, sqrt(sigmasq_y));
277: stan::math::assign(sigma_alpha, sqrt(sigmasq_alpha));
278: stan::math::assign(sigma_beta, sqrt(sigmasq_beta));
279:
280: // validate transformed parameters
281: if (stan::math::is_uninitialized(sigma_y)) {
282: std::stringstream msg;
283: msg << "Undefined transformed parameter: sigma_y";
284: throw std::runtime_error(msg.str());
285: }
286: if (stan::math::is_uninitialized(sigma_alpha)) {
287: std::stringstream msg;
288: msg << "Undefined transformed parameter: sigma_alpha";
289: throw std::runtime_error(msg.str());
290: }
291: if (stan::math::is_uninitialized(sigma_beta)) {
292: std::stringstream msg;
293: msg << "Undefined transformed parameter: sigma_beta";
294: throw std::runtime_error(msg.str());
295: }
296:
297: const char* function = "validate transformed params %1%";
298: (void) function; // dummy to suppress unused var warning
299: try {
300: check_greater_or_equal(function,sigma_y,0,"sigma_y");
301: } catch (std::domain_error& e) {
302: throw std::domain_error(std::string("Invalid value of sigma_y: ") + std::string(e.what()));
303: };
304: try {
305: check_greater_or_equal(function,sigma_alpha,0,"sigma_alpha");
306: } catch (std::domain_error& e) {
307: throw std::domain_error(std::string("Invalid value of sigma_alpha: ") + std::string(e.what()));
308: };
309: try {
310: check_greater_or_equal(function,sigma_beta,0,"sigma_beta");
311: } catch (std::domain_error& e) {
312: throw std::domain_error(std::string("Invalid value of sigma_beta: ") + std::string(e.what()));
313: };
314: // model body
315: lp_accum.add(normal_log(mu_alpha, 0, 100));
316: lp_accum.add(normal_log(mu_beta, 0, 100));
317: lp_accum.add(inv_gamma_log<propto>(sigmasq_y, 0.001, 0.001));
318: lp_accum.add(inv_gamma_log<propto>(sigmasq_alpha, 0.001, 0.001));
319: lp_accum.add(inv_gamma_log<propto>(sigmasq_beta, 0.001, 0.001));
320: lp_accum__.add(normal_log<propto >(alpha, mu_alpha, sigma_alpha));
321: lp_accum.add(normal_log(beta, mu_beta, sigma_beta));
322: for (int n = 1; n <= N; ++n) {
323: for (int t = 1; t <= T; ++t) {
324: lp_accum .add(normal_log(get_base1(get_base1(y,n,"y",1),t,"y",2), (get_base1(alpha,n,"alpha",1) + (get_base1(beta,n,"beta",1) * (get_base1(x,t,"x",1) - xbar))), sigma_y));
325: }
326: }
327:
328: lp_accum.add(lp);
329: return lp_accum.sum();
330:
331: } // log_prob()
332:
333:
334: void get_param_names(std::vectorstd::string& names) const {
335: names.resize(0);
336: names__.push_back("alpha");
337: names.push_back("beta");
338: names.push_back("mu_alpha");
339: names.push_back("mu_beta");
340: names.push_back("sigmasq_y");
341: names.push_back("sigmasq_alpha");
342: names.push_back("sigmasq_beta");
343: names.push_back("sigma_y");
344: names.push_back("sigma_alpha");
345: names.push_back("sigma_beta");
346: names.push_back("alpha0");
347: }
348:
349:
350: void get_dims(std::vectorstd::vector& dimss) const {
351: dimss.resize(0);
352: std::vector dims ;
353: dims.resize(0);
354: dims.push_back(N);
355: dimss.push_back(dims);
356: dims.resize(0);
357: dims__.push_back(N);
358: dimss.push_back(dims);
359: dims.resize(0);
360: dimss.push_back(dims);
361: dims.resize(0);
362: dimss__.push_back(dims);
363: dims.resize(0);
364: dimss.push_back(dims);
365: dims.resize(0);
366: dimss.push_back(dims);
367: dims.resize(0);
368: dimss__.push_back(dims);
369: dims.resize(0);
370: dimss.push_back(dims);
371: dims.resize(0);
372: dimss.push_back(dims);
373: dims.resize(0);
374: dimss__.push_back(dims);
375: dims.resize(0);
376: dimss.push_back(dims);
377: }
378:
379: template
380: void write_array(RNG& base_rng ,
381: std::vector& params_r,
382: std::vector& params_i,
383: std::vector& vars ,
384: bool include_tparams = true,
385: bool include_gqs = true,
386: std::ostream* pstream = 0) const {
387: vars.resize(0);
388: stan::io::reader in (params_r,params_i);
389: static const char* function = "model9c833825353_rats_namespace::write_array(%1%)";
390: (void) function; // dummy call to supress warning
391: // read-transform, write parameters
392: vector alpha;
393: size_t dim_alpha_0 = N;
394: for (size_t k_0 = 0; k_0 < dim_alpha_0; ++k_0) {
395: alpha.push_back(in.scalar_constrain());
396: }
397: vector beta;
398: size_t dim_beta_0 = N;
399: for (size_t k_0__ = 0; k_0 < dim_beta_0; ++k_0__) {
400: beta.push_back(in.scalar_constrain());
401: }
402: double mu_alpha = in.scalar_constrain();
403: double mu_beta = in.scalar_constrain();
404: double sigmasq_y = in.scalar_lb_constrain(0);
405: double sigmasq_alpha = in__.scalar_lb_constrain(0);
406: double sigmasq_beta = in.scalar_lb_constrain(0);
407: for (int k_0 = 0; k_0__ < N; ++k_0) {
408: vars.push_back(alpha[k_0]);
409: }
410: for (int k_0 = 0; k_0__ < N; ++k_0) {
411: vars.push_back(beta[k_0]);
412: }
413: vars.push_back(mu_alpha);
414: vars.push_back(mu_beta);
415: vars.push_back(sigmasq_y);
416: vars.push_back(sigmasq_alpha);
417: vars.push_back(sigmasq_beta);
418:
419: if (!include_tparams) return;
420: // declare and define transformed parameters
421: double lp = 0.0;
422: (void) lp__; // dummy call to supress warning
423: stan::math::accumulator lp_accum ;
424:
425: double sigma_y(0.0);
426: (void) sigma_y; // dummy to suppress unused var warning
427: double sigma_alpha(0.0);
428: (void) sigma_alpha; // dummy to suppress unused var warning
429: double sigma_beta(0.0);
430: (void) sigma_beta; // dummy to suppress unused var warning
431:
432: stan::math::assign(sigma_y, sqrt(sigmasq_y));
433: stan::math::assign(sigma_alpha, sqrt(sigmasq_alpha));
434: stan::math::assign(sigma_beta, sqrt(sigmasq_beta));
435:
436: // validate transformed parameters
437: try {
438: check_greater_or_equal(function,sigma_y,0,"sigma_y");
439: } catch (std::domain_error& e) {
440: throw std::domain_error(std::string("Invalid value of sigma_y: ") + std::string(e.what()));
441: };
442: try {
443: check_greater_or_equal(function,sigma_alpha,0,"sigma_alpha");
444: } catch (std::domain_error& e) {
445: throw std::domain_error(std::string("Invalid value of sigma_alpha: ") + std::string(e.what()));
446: };
447: try {
448: check_greater_or_equal(function,sigma_beta,0,"sigma_beta");
449: } catch (std::domain_error& e) {
450: throw std::domain_error(std::string("Invalid value of sigma_beta: ") + std::string(e.what()));
451: };
452:
453: // write transformed parameters
454: vars.push_back(sigma_y);
455: vars.push_back(sigma_alpha);
456: vars__.push_back(sigma_beta);
457:
458: if (!include_gqs) return;
459: // declare and define generated quantities
460: double alpha0(0.0);
461: (void) alpha0; // dummy to suppress unused var warning
462:
463: stan::math::assign(alpha0, (mu_alpha - (xbar * mu_beta)));
464:
465: // validate generated quantities
466:
467: // write generated quantities
468: vars.push_back(alpha0);
469:
470: }
471:
472:
473: void write_csv_header(std::ostream& o__) const {
474: stan::io::csv_writer writer(o);
475: for (int k_0__ = 1; k_0 <= N; ++k_0) {
476: writer.comma();
477: o << "alpha" << '.' << k_0__;
478: }
479: for (int k_0 = 1; k_0 <= N; ++k_0) {
480: writer.comma();
481: o__ << "beta" << '.' << k_0;
482: }
483: writer.comma();
484: o << "mu_alpha";
485: writer.comma();
486: o << "mu_beta";
487: writer.comma();
488: o << "sigmasq_y";
489: writer.comma();
490: o << "sigmasq_alpha";
491: writer.comma();
492: o << "sigmasq_beta";
493: writer.comma();
494: o << "sigma_y";
495: writer.comma();
496: o << "sigma_alpha";
497: writer.comma();
498: o << "sigma_beta";
499: writer.comma();
500: o << "alpha0";
501: writer.newline();
502: }
503:
504: template
505: void write_csv(RNG& base_rng ,
506: std::vector& params_r,
507: std::vector& params_i,
508: std::ostream& o,
509: std::ostream* pstream = 0) const {
510: stan::io::reader in (params_r ,params_i);
511: stan::io::csv_writer writer(o);
512: static const char* function__ = "model9c833825353_rats_namespace::write_csv(%1%)";
513: (void) function; // dummy call to supress warning
514: // read-transform, write parameters
515: vector alpha;
516: size_t dim_alpha_0 = N;
517: for (size_t k_0 = 0; k_0 < dim_alpha_0; ++k_0) {
518: alpha.push_back(in__.scalar_constrain());
519: writer.write(alpha[k_0]);
520: }
521: vector beta;
522: size_t dim_beta_0 = N;
523: for (size_t k_0 = 0; k_0 < dim_beta_0; ++k_0__) {
524: beta.push_back(in.scalar_constrain());
525: writer.write(beta[k_0__]);
526: }
527: double mu_alpha = in.scalar_constrain();
528: writer.write(mu_alpha);
529: double mu_beta = in.scalar_constrain();
530: writer.write(mu_beta);
531: double sigmasq_y = in.scalar_lb_constrain(0);
532: writer.write(sigmasq_y);
533: double sigmasq_alpha = in.scalar_lb_constrain(0);
534: writer.write(sigmasq_alpha);
535: double sigmasq_beta = in.scalar_lb_constrain(0);
536: writer.write(sigmasq_beta);
537:
538: // declare, define and validate transformed parameters
539: double lp = 0.0;
540: (void) lp; // dummy call to supress warning
541: stan::math::accumulator lp_accum ;
542:
543: double sigma_y(0.0);
544: (void) sigma_y; // dummy to suppress unused var warning
545: double sigma_alpha(0.0);
546: (void) sigma_alpha; // dummy to suppress unused var warning
547: double sigma_beta(0.0);
548: (void) sigma_beta; // dummy to suppress unused var warning
549:
550: stan::math::assign(sigma_y, sqrt(sigmasq_y));
551: stan::math::assign(sigma_alpha, sqrt(sigmasq_alpha));
552: stan::math::assign(sigma_beta, sqrt(sigmasq_beta));
553:
554: try {
555: check_greater_or_equal(function,sigma_y,0,"sigma_y");
556: } catch (std::domain_error& e) {
557: throw std::domain_error(std::string("Invalid value of sigma_y: ") + std::string(e.what()));
558: };
559: try {
560: check_greater_or_equal(function,sigma_alpha,0,"sigma_alpha");
561: } catch (std::domain_error& e) {
562: throw std::domain_error(std::string("Invalid value of sigma_alpha: ") + std::string(e.what()));
563: };
564: try {
565: check_greater_or_equal(function,sigma_beta,0,"sigma_beta");
566: } catch (std::domain_error& e) {
567: throw std::domain_error(std::string("Invalid value of sigma_beta: ") + std::string(e.what()));
568: };
569:
570: // write transformed parameters
571: writer__.write(sigma_y);
572: writer.write(sigma_alpha);
573: writer.write(sigma_beta);
574:
575: // declare and define generated quantities
576: double alpha0(0.0);
577: (void) alpha0; // dummy to suppress unused var warning
578:
579: stan::math::assign(alpha0, (mu_alpha - (xbar * mu_beta)));
580:
581: // validate generated quantities
582:
583: // write generated quantities
584: writer.write(alpha0);
585:
586: writer.newline();
587: }
588:
589: static std::string model_name() {
590: return "model9c833825353_rats";
591: }
592:
593:
594: void constrained_param_names(std::vectorstd::string& param_names,
595: bool include_tparams = true,
596: bool include_gqs = true) const {
597: std::stringstream param_name_stream;
598: for (int k_0 = 1; k_0 <= N; ++k_0) {
599: param_name_stream.str(std::string());
600: param_name_stream__ << "alpha" << '.' << k_0;
601: param_names.push_back(param_name_stream__.str());
602: }
603: for (int k_0 = 1; k_0 <= N; ++k_0) {
604: param_name_stream.str(std::string());
605: param_name_stream__ << "beta" << '.' << k_0;
606: param_names.push_back(param_name_stream.str());
607: }
608: param_name_stream.str(std::string());
609: param_name_stream << "mu_alpha";
610: param_names.push_back(param_name_stream.str());
611: param_name_stream.str(std::string());
612: param_name_stream << "mu_beta";
613: param_names.push_back(param_name_stream.str());
614: param_name_stream.str(std::string());
615: param_name_stream << "sigmasq_y";
616: param_names.push_back(param_name_stream.str());
617: param_name_stream.str(std::string());
618: param_name_stream << "sigmasq_alpha";
619: param_names.push_back(param_name_stream.str());
620: param_name_stream.str(std::string());
621: param_name_stream << "sigmasq_beta";
622: param_names.push_back(param_name_stream.str());
623:
624: if (!include_gqs && !include_tparams) return;
625: param_name_stream.str(std::string());
626: param_name_stream << "sigma_y";
627: param_names.push_back(param_name_stream.str());
628: param_name_stream.str(std::string());
629: param_name_stream << "sigma_alpha";
630: param_names.push_back(param_name_stream.str());
631: param_name_stream.str(std::string());
632: param_name_stream << "sigma_beta";
633: param_names.push_back(param_name_stream.str());
634:
635: if (!include_gqs) return;
636: param_name_stream.str(std::string());
637: param_name_stream << "alpha0";
638: param_names__.push_back(param_name_stream.str());
639: }
640:
641:
642: void unconstrained_param_names(std::vectorstd::string& param_names,
643: bool include_tparams__ = true,
644: bool include_gqs = true) const {
645: std::stringstream param_name_stream;
646: for (int k_0__ = 1; k_0 <= N; ++k_0) {
647: param_name_stream.str(std::string());
648: param_name_stream << "alpha" << '.' << k_0__;
649: param_names.push_back(param_name_stream.str());
650: }
651: for (int k_0__ = 1; k_0 <= N; ++k_0) {
652: param_name_stream.str(std::string());
653: param_name_stream << "beta" << '.' << k_0__;
654: param_names.push_back(param_name_stream.str());
655: }
656: param_name_stream.str(std::string());
657: param_name_stream << "mu_alpha";
658: param_names.push_back(param_name_stream.str());
659: param_name_stream.str(std::string());
660: param_name_stream << "mu_beta";
661: param_names.push_back(param_name_stream.str());
662: param_name_stream.str(std::string());
663: param_name_stream << "sigmasq_y";
664: param_names.push_back(param_name_stream.str());
665: param_name_stream.str(std::string());
666: param_name_stream << "sigmasq_alpha";
667: param_names.push_back(param_name_stream.str());
668: param_name_stream.str(std::string());
669: param_name_stream << "sigmasq_beta";
670: param_names.push_back(param_name_stream.str());
671:
672: if (!include_gqs__ && !include_tparams) return;
673: param_name_stream.str(std::string());
674: param_name_stream << "sigma_y";
675: param_names.push_back(param_name_stream.str());
676: param_name_stream.str(std::string());
677: param_name_stream << "sigma_alpha";
678: param_names.push_back(param_name_stream.str());
679: param_name_stream.str(std::string());
680: param_name_stream << "sigma_beta";
681: param_names.push_back(param_name_stream__.str());
682:
683: if (!include_gqs) return;
684: param_name_stream.str(std::string());
685: param_name_stream << "alpha0";
686: param_names__.push_back(param_name_stream__.str());
687: }
688:
689: }; // model
690:
691: } // namespace
692:
693: #include <rstan/rstaninc.hpp>
694: /*
695: * Define Rcpp Module to expose stan_fit's functions to R.
696: /
697: RCPP_MODULE(stan_fit4model9c833825353_ratsmod){
698: Rcpp::class<rstan::stan_fit<model9c833825353_rats_namespace::model9c833825353_rats,
699: boost::random::ecuyer1988> >("stan_fit4model9c833825353_rats")
700: // .constructorRcpp::List()
701: .constructor<SEXP, SEXP>()
702: // .constructor<SEXP, SEXP>()
703: .method("call_sampler",
704: &rstan::stan_fit<model9c833825353_rats_namespace::model9c833825353_rats, boost::random::ecuyer1988>::call_sampler)
705: .method("param_names",
706: &rstan::stan_fit<model9c833825353_rats_namespace::model9c833825353_rats, boost::random::ecuyer1988>::param_names)
707: .method("param_names_oi",
708: &rstan::stan_fit<model9c833825353_rats_namespace::model9c833825353_rats, boost::random::ecuyer1988>::param_names_oi)
709: .method("param_fnames_oi",
710: &rstan::stan_fit<model9c833825353_rats_namespace::model9c833825353_rats, boost::random::ecuyer1988>::param_fnames_oi)
711: .method("param_dims",
712: &rstan::stan_fit<model9c833825353_rats_namespace::model9c833825353_rats, boost::random::ecuyer1988>::param_dims)
713: .method("param_dims_oi",
714: &rstan::stan_fit<model9c833825353_rats_namespace::model9c833825353_rats, boost::random::ecuyer1988>::param_dims_oi)
715: .method("update_param_oi",
716: &rstan::stan_fit<model9c833825353_rats_namespace::model9c833825353_rats, boost::random::ecuyer1988>::update_param_oi)
717: .method("param_oi_tidx",
718: &rstan::stan_fit<model9c833825353_rats_namespace::model9c833825353_rats, boost::random::ecuyer1988>::param_oi_tidx)
719: .method("grad_log_prob",
720: &rstan::stan_fit<model9c833825353_rats_namespace::model9c833825353_rats, boost::random::ecuyer1988>::grad_log_prob)
721: .method("log_prob",
722: &rstan::stan_fit<model9c833825353_rats_namespace::model9c833825353_rats, boost::random::ecuyer1988>::log_prob)
723: .method("unconstrain_pars",
724: &rstan::stan_fit<model9c833825353_rats_namespace::model9c833825353_rats, boost::random::ecuyer1988>::unconstrain_pars)
725: .method("constrain_pars",
726: &rstan::stan_fit<model9c833825353_rats_namespace::model9c833825353_rats, boost::random::ecuyer1988>::constrain_pars)
727: .method("num_pars_unconstrained",
728: &rstan::stan_fit<model9c833825353_rats_namespace::model9c833825353_rats, boost::random::ecuyer1988>::num_pars_unconstrained)
729: ;
730: }
731:
732: // declarations
733: extern "C" {
734: SEXP file9c85ba0103f( ) ;
735: }
736:
737: // definition
738:
739: SEXP file9c85ba0103f( ){
740: return Rcpp::wrap("rats");
741: }
742:
743:
Error in compileCode(f, code, language = language, verbose = verbose) :
Compilation ERROR, function(s)/method(s) not created!
In addition: Warning message:
running command 'C:/PROGRA~1/R/R-30~1.2/bin/x64/R CMD SHLIB file9c85ba0103f.cpp 2> file9c85ba0103f.cpp.err.txt' had status 1